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==General foundations of high-order immersed interface methods   to solve interface problems==
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'''Heidy Escamilla Puc<sup>a</sup>, Reymundo Itzá Balam<sup>b,c</sup>, Miguel Uh Zapataangeluh@cimat.mx<sup>b,c</sup>'''
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==Abstract==
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This work forms the foundation for addressing high-order immersed interface methods to solve interface problems and enables us to conduct in-depth examination of this theory. Here, we focus on the introduction a fourth-order finite-difference formulation to approximate the second-order derivative of discontinuous functions. The approach is based on the combination of a high-order implicit formulation and the immersed interface method. The idea is to modify the standard schemes by introducing additional contribution terms based on jump conditions. These contributions are calculated only at grid points where the stencil intersects with the interface. Here, we discuss the issues of implementing the one-dimensional Poisson equation and the heat conduction equation with discontinuous solutions as a three-point stencil for each grid point on the computational domain. In both cases, the resulting discretization approach yields a tridiagonal linear system with matrix coefficients identical to those employed for smooth solutions. We present several numerical experiments to verify the feasibility and accuracy of the method. Thus, this high-order method provides an attractive numerical framework that can efficiently lead to the solution to more complex problems.
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''Keywords:'' Immersed interface method; Implicit finite difference; Fourth-order accuracy; Poisson equation; Heat conduction equation
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==1 Introduction==
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High-order numerical solutions to differential equations arising from discontinuous solutions find extensive utility across various research domains <span id='citeF-1'></span><span id='citeF-2'></span><span id='citeF-3'></span><span id='citeF-4'></span><span id='citeF-5'></span><span id='citeF-6'></span>[[#cite-1|[1,2,3,4,5,6]]]. In the case of smooth solutions, the standard central finite-difference method requires a significant number of grid points to achieve a high level of accuracy in its numerical results. As a result, over the past few decades, several schemes have been developed to obtain fourth- and sixth-order finite-difference methods <span id='citeF-7'></span><span id='citeF-8'></span><span id='citeF-9'></span><span id='citeF-10'></span><span id='citeF-11'></span>[[#cite-7|[7,8,9,10,11]]], including those one based on the implicit finite-difference (IFD) formulation <span id='citeF-12'></span><span id='citeF-13'></span><span id='citeF-14'></span><span id='citeF-15'></span>[[#cite-12|[12,13,14,15]]].
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On the other hand, although several methods have been proposed to address discontinuous problems <span id='citeF-2'></span><span id='citeF-16'></span><span id='citeF-17'></span><span id='citeF-18'></span><span id='citeF-19'></span><span id='citeF-20'></span><span id='citeF-21'></span>[[#cite-2|[2,16,17,18,19,20,21]]], the immersed interface method (IIM) <span id='citeF-22'></span><span id='citeF-23'></span><span id='citeF-24'></span><span id='citeF-25'></span>[[#cite-22|[22,23,24,25]]] stands out as a highly accurate option that requires minimal adjustments to the standard finite-difference formulation. However, these methods typically achieve second-order accuracy. For instance, there are limited implementations of a few third-, fourth- and sixth-order IIMs available for solving Poisson equations with discontinuous solutions <span id='citeF-26'></span><span id='citeF-27'></span><span id='citeF-28'></span><span id='citeF-29'></span><span id='citeF-30'></span><span id='citeF-31'></span><span id='citeF-32'></span><span id='citeF-33'></span>[[#cite-26|[26,27,28,29,30,31,32,33]]].
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This paper focuses on the basic ideas of combining the IFD and IIM to achieve high-order approximations for second-order derivatives of both continuous and discontinuous real-valued functions. The IFD scheme offers a highly accurate numerical method <span id='citeF-34'></span><span id='citeF-35'></span>[[#cite-34|[34,35]]], while the IIM handles discontinuities through minimal adjustments made exclusively at grid points where the stencil intersects the interface <span id='citeF-36'></span><span id='citeF-37'></span>[[#cite-36|[36,37]]], yielding additional terms known as jump contributions. The resulting method will be named as implicit finite-difference immersed interface method (IFD-IIM).
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We illustrate the implementation of a global fourth-order IFD-IIM approach with two examples: the one-dimensional Poisson equation for static cases and the heat conduction equation with a fixed interface for time-evolving scenarios. Our proposed method offers several advantages. Notably, the resulting tridiagonal matrix coefficient of the finite-difference scheme remains the same as those for smooth solutions, with the additional terms arising from the jumps located in the right-hand side vector. Consequently, our algorithm is straightforward to implement, employing the efficient Thomas' algorithm.
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We have organized our study as follows. In Section 2, we introduce a fourth-order IFD method capable of handling second-order derivatives, both in smooth and discontinuous scenarios. Section 3 demonstrates the application of this implicit scheme in approximating solutions to the one-dimensional Poisson equation. Section 4 shows the combination of the IFD-IIM with the Crank-Nicolson method to solve the heat conduction equation. Sections 5 and 6 provide a series of numerical examples to illustrate the algorithm's accuracy for both equations. Lastly, Section 7 offers our conclusions and outlines directions for future research.
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==2 IFD formulation with discontinuities==
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In this section, we outline the key attributes of the IFD formulation to achieve a global fourth-order method, demonstrating how the scheme can be adapted for addressing discontinuous problems through the utilization of the IIM.
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We approximate the numerical solution on the domain <math display="inline">[\mathfrak{a},\,\mathfrak{b}]</math> that is divided into <math display="inline">N</math> sub-intervals using the points <math display="inline">x_i</math>, as follows
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<span id="eq-1"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>x_i = \mathfrak{a} + (i-1)h, \qquad i=1, 2, \dots , N,N+1,   </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (1)
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where the grid size is given by <math display="inline">h=(\mathfrak{b}-\mathfrak{a})/N</math>. We employ <math display="inline">U_i</math> and <math display="inline">u_i = u(x_i)</math> to denote the approximate and exact solution at the <math display="inline">i</math>th-point of the grid, respectively. Here, the interface is at <math display="inline">x=x_\alpha </math> located between grid points <math display="inline">x_I</math> and <math display="inline">x_{I+1}</math> as <math display="inline">x_I\leq x_\alpha{<}x_{I+1}</math>, see Fig.&nbsp;[[#img-1|1]]. The distances of the closest grid points to the interface are defined as <math display="inline">h_{L} = x_{I}-x_\alpha </math> and <math display="inline">h_{R} = x_{I+1}-x_\alpha </math>. Note that <math display="inline">h_{R}</math> and <math display="inline">h_{L}</math> are positive and negative values, respectively.
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<div id='img-1'></div>
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{| class="floating_imageSCP" style="text-align: center; border: 1px solid #BBB; margin: 1em auto; width: 100%;max-width: 100%;"
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|-
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|[[Image:Review_499745022132-Fig01_Scheme.png|600px|Example of a discontinuous function u with an interface located between the points x<sub>I</sub> and x<sub>I+1</sub>.]]
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|- style="text-align: center; font-size: 75%;"
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| colspan="1" | '''Figure 1:''' Example of a discontinuous function <math>u</math> with an interface located between the points <math>x_{I}</math> and <math>x_{I+1}</math>.
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On the other hand, the jump for <math display="inline">u</math> at <math display="inline">x_\alpha </math> is defined as
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<span id="eq-2"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>\left[u \right]= u^{+} - u^{-}, \quad \mathrm{where} \quad u^{+} = u(x_\alpha ^{+} )= \lim _{x\to x_\alpha ^+}u(x),\quad \mathrm{and} \quad  u^{-} = u(x_\alpha ^{-}) = \lim _{x\to x_\alpha ^-}u(x).  </math>
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We employ a similar definition for the jumps such as the ones of the right-hand side and the derivatives of <math display="inline">u</math>.
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In this paper, we designate <math display="inline">x_I</math> and <math display="inline">x_{I+1}</math> as ''irregular points'', while considering the rest as ''regular points''. This classification holds significant importance as distinct schemes are applied to each category, as presented in the following theorems.
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===2.1 Second-order derivative approximation for regular and irregular grid points===
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The following two Theorems state the main results to approximate the second-order derivative using high-order schemes for regular and irregular points.
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<span id='theorem-teo:regular'></span> '''Theorem 1: Regular points''' <span id='citeF-34'></span><span id='citeF-35'></span>[[#cite-34|[34,35]]]. Let us consider a real-valued function <math display="inline">u</math> with an interface <math display="inline">x_\alpha </math> such that <math display="inline">x_I\leq x_\alpha{<}x_{I+1}</math>. Then <math display="inline">u_{xx}</math> can be approximated by a fourth-order IFD scheme
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<span id="eq-2"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>\left.\mathfrak{D}^2 u_{xx}\right|_i = \left.\delta ^2 u\right|_i + O(h^4), \quad i \neq I, I+1,    </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (2)
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where
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<span id="eq-3"></span>
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|-
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>\mathfrak{D}^2(\cdot )  :=  (\cdot )  + bh^2 (\cdot )_{xx},   </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (3)
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<math display="inline">b=1/12</math>, and the central finite-difference formula <math display="inline">\delta ^2</math> is given by
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<span id="eq-4"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>\left.\delta ^2 u\right|_i := \frac{1}{h^2} \left\{u_{i-1}-2u_i+u_{i+1}\right\}.  </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (4)
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'''Proof.'''
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From Taylor series expansions and under some simplifications, the second-order derivative at any regular point <math display="inline">x_i</math> can be written in terms of the centered finite-difference operator, as follows
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<span id="eq-5"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>\left.u_{xx}\right|_i = \frac{1}{h^2} \left\{u_{i-1}-2u_i+u_{i+1}\right\}- \frac{1}{12}h^2\left.u_{xxxx}\right|_i +O(h^4),   </math>
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Previous equation holds due to the solution is smooth on a neighborhood around <math display="inline">x_{i}</math>. Thus, we obtain a fourth-order IFD using a stencil of three nodes by moving the fourth-order term to the left-hand side. We get
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>\left.u_{xx}\right|_i +  \frac{1}{12}h^2 \left(\left.u_{xx} \right)_{xx}\right|_i = \frac{1}{h^2} \left\{u_{i-1}-2u_i+u_{i+1}\right\}+ O(h^4).  </math>
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Finally, the proof is completed by using the definition of operator <math display="inline">\mathfrak{D}^2</math>, <math display="inline">\delta ^2</math>, and <math display="inline">b</math>. This completes the proof. ♦
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It is important to remark that formula [[#eq-2|(2)]] is applicable exclusively for regular points. In order to address this limitation for the two irregular points near the interface, we introduce a modified IFD scheme using the IIM, specifically tailored to handle discontinuous solutions. Furthermore, instead of having a fourth-order local truncation error for the irregular points, we proceed as other IIMs <span id='citeF-22'></span><span id='citeF-23'></span><span id='citeF-24'></span><span id='citeF-29'></span><span id='citeF-33'></span><span id='citeF-32'></span>[[#cite-22|[22,23,24,29,33,32]]] by taking one order lower at these points. We will numerically show that the global order of convergence can be still <math display="inline">O(h^4)</math> even if the local truncation error at <math display="inline">i=I</math> and <math display="inline">i=I+1</math> is <math display="inline">O(h^{3})</math>.
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<span id='theorem-teo:irregular'></span> '''Theorem 2: Irregular points''' <span id='citeF-14'></span>[[#cite-14|[14]]]. Let us consider the known jump conditions
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<span id="eq-5"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>\left[u \right],\quad  \left[u_{x} \right],\quad  \left[u_{xx} \right],\quad  \left[u_{xxx} \right],\quad  \left[u_{xxxx} \right],\quad   </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (5)
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at <math display="inline">x_\alpha </math> such that <math display="inline">x_I\leq x_\alpha{<}x_{I+1}</math>. Then <math display="inline">u_{xx}</math> can be approximated at <math display="inline">x_I</math> and <math display="inline">x_{I+1}</math> by the IFD-IIM given by
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<span id="eq-6"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>\mathfrak{D}^2 u_{xx}\left.\right|_i = \left.\delta ^2 u\right|_i + C_i + O(h^3), \quad i= I, I+1,    </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (6)
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where <math display="inline">\mathfrak{D}^2</math> and <math display="inline">\delta ^2</math> are defined in [[#eq-3|(3)]] and [[#eq-4|(4)]], respectively, and
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<span id="eq-7"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>C_i =  \begin{cases}- \dfrac{1}{h^2}\left\{[u]+h_R\left[u_{x}\right]+\dfrac{h_R^2}{2}\left[u_{xx} \right]+b\left(2h_R^3\left[u_{xxx} \right]+\dfrac{h_R^4}{2}\left[u_{xxxx} \right]\right)\right\}, & i=I, \\[3mm]    \dfrac{1}{h^2}\left\{[u]+h_L\left[u_{x} \right]+\dfrac{h_L^2}{2}\left[u_{xx} \right]+ b \left(2h_L^3\left[u_{xxx} \right]+\dfrac{h_L^4}{2}\left[u_{xxxx} \right]\right)\right\}, & i=I+1, \end{cases}  </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (7)
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and where <math display="inline">b=1/12</math>.
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'''Proof.'''
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We obtain a third-order scheme for at <math display="inline">x_I</math> and <math display="inline">x_{I+1}</math> following similar ideas as the ones developed for the generalized Taylor expansion proposed by Xu & Wang <span id="citeF-36"></span>[[#cite-36|[36]]] and the IIM for elliptic interface problems with straight interfaces proposed by Feng & Li <span id="citeF-37"></span>[[#cite-37|[37]]]. The idea is to consider extended smooth solutions of <math display="inline">u</math> such that we can apply the standard central scheme to <math display="inline">x_I</math> and <math display="inline">x_{I+1}</math>. For instance, a function based on the original left solution is defined as
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<span id="eq-8"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>u_\ell (x) = \begin{cases}u(x), & x\leq x_\alpha ,\\ \displaystyle u^-+h_R u_{x}^{-}+\frac{h_R^2}{2}u_{xx}^{-} +\dfrac{h_R^3}{6}u_{xxx}^{-}+\dfrac{h_R^4}{24}u_{xxxx}^{-} , & x_\alpha{<}x,\\ \end{cases}  </math>
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Using Taylor series expansions of <math display="inline">u_{I+1}</math> around <math display="inline">x_\alpha </math>, the definition of jumps [[#eq-5|(5)]], and some simplification yield
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>\left.\delta ^2 u\right|_I = \left.\delta ^2 u_{\ell }\right|_I + \dfrac{1}{h^2}\left([u]+h_R\left[u_{x} \right]+\dfrac{h_R^2}{2}\left[u_{xx} \right]+\dfrac{h_R^3}{6}\left[u_{xxx} \right]+\dfrac{h_R^4}{24}\left[u_{xxxx} \right]\right)+O(h^3). </math>
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Thus,
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>\left.\delta ^2 u\right|_I =  \left.(u_\ell )_{xx} \right|_I + bh^2 \left.(u_\ell )_{xxxx} \right|_I </math>
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| style="text-align: center;" | <math>  +\dfrac{1}{h^2}\left([u]+h_R\left[u_{x} \right]+\dfrac{h_R^2}{2}\left[u_{xx} \right]+\dfrac{h_R^3}{6}\left[u_{xxx} \right]+\dfrac{h_R^4}{24}\left[u_{xxxx} \right]\right)+O(h^3). </math>
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Finally, we get [[#eq-6|(6)]] which complete the proof. The same procedure can be applied for the proof at <math display="inline">x_{I+1}</math>. We refer to the reader to the work of Itza Balam and Uh Zapata <span id='citeF-14'></span>[[#cite-14|[14]]] for more details. ♦
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<span id='theorem-EFD'></span>'''Remark 1:''' If <math display="inline">b=0</math>, then Theorem [[#theorem-teo:regular|1]] yields the standard second-order finite-difference method for regular points given by
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>\left.u_{xx}\right|_i = \left.\delta ^2 u\right|_i + O(h^2), \quad i \neq I, I+1,  </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (8)
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and Theorem [[#theorem-teo:regular|1]] results in an IIM of first-order for irregular points <math display="inline"> i= I, I+1</math> as follows
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<span id="eq-9"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>\left.u_{xx}\right|_i = \left.\delta ^2 u\right|_i + c_i+ O(h), \quad i=I,I+1,   </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (9)
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where
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<span id="eq-10"></span>
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>c_i =  \begin{cases}- \dfrac{1}{h^2}\left([u]+h_R\left[u_{x} \right]+\dfrac{h_R^2}{2}\left[u_{xx} \right]\right), & i=I, \\[3mm]    \dfrac{1}{h^2}\left([u]+h_L\left[u_{x} \right]+\dfrac{h_L^2}{2}\left[u_{xx} \right]\right), & i=I+1. \end{cases}  </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (10)
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Note that, in this case, we only require to explicitly know jump conditions <math display="inline">[u]</math>, <math display="inline">\left[u_{x} \right]</math> and <math display="inline">\left[u_{xx} \right]</math>.
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===2.2 Implicit approximation for a real-valued function===
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Before applying previous results to approximate differential equations, it would be useful to express the operator <math display="inline">\mathfrak{D}^2u</math> using finite differences  for a real-valued function <math display="inline">u</math> rather than its second-order derivative <math display="inline">u_{xx}</math>. The finite-difference formula is obtained by approximating <math display="inline">\left.u_{xx}\right|</math> with the central finite differences, as presented in [[#theorem-EFD|(1)]]-[[#eq-10|(10)]] for regular and irregular points, respectively.
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For regular points (<math display="inline">i\neq I,I+1</math>), it follows from equation [[#theorem-EFD|(1)]]:
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| style="text-align: center;" | <math>\left.\mathfrak{D}^2u\right|_i    =   u_i+\left.bh^2 u_{xx}\right|_i    =   u_i + bh^2\left\{\left.\delta ^2 u \right|_i  + O(h^2)\right\}   =   b u_{i-1}+\,(1-2b) u_i+\,b u_{i+1}  + O(h^4). </math>
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Thus, if we define as <math display="inline">\mathfrak{d}^2</math> the resulting finite-difference
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<span id="eq-11"></span>
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>\left.\mathfrak{d}^2 u \right|_i  : =  b u_{i-1}+\,(1-2b) u_i+\,b u_{i+1},  </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (11)
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then, we have that
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<span id="eq-12"></span>
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{| style="text-align: left; margin:auto;width: 100%;" 
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| style="text-align: center;" | <math>\left.\mathfrak{D}^2 u \right|_i = \left.\mathfrak{d}^2 u \right|_i + O(h^4), \quad i\neq I,I+1.  </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (12)
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However, we still have the same issue to overcome for a discontinuous function <math display="inline">u</math>. We remark that this second-order derivative of <math display="inline">u</math> is already multiplied for <math display="inline">h^2</math>. Consequently, we can use the IIM technique where the contribution term is only first-order accurate to <math display="inline">u</math>; thus, we still have a local <math display="inline">O(h^3)</math> to keep a global fourth-order accurate method. Then for irregular points, the IIM applied for this term follows
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<span id="eq-13"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>\left.\mathfrak{D}^2 u \right|_i = \left.\mathfrak{d}^2 u \right|_i + (c_u)_i + O(h^3), \quad i=I,I+1,  </math>
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|}
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| style="width: 5px;text-align: right;white-space: nowrap;" | (13)
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|}
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where <math display="inline">\mathfrak{d}^2</math> is given by finite difference [[#eq-11|(11)]] and
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<span id="eq-14"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>(c_u)_i  = \begin{cases}- b\left([u]+h_R\left[u_x\right]+\dfrac{h_R^2}{2}\left[u_{xx} \right]\right), & i=I, \\[3mm]    b\left([u]+h_L\left[u_x \right]+\dfrac{h_L^2}{2}\left[u_{xx} \right]\right), & i=I+1. \end{cases}  </math>
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|}
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| style="width: 5px;text-align: right;white-space: nowrap;" | (14)
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|}
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Finally, for regular and irregular points, we have high-order finite-difference approximations of the implicit operator <math display="inline">\mathfrak{D}^2</math> applied to a real-valued function <math display="inline">u</math> as in [[#eq-12|(12)]] and [[#eq-13|(13)]], and to its second-order derivative <math display="inline">u_{xx}</math> as in [[#eq-2|(2)]] and [[#eq-6|(6)]]. Now, we proceed to implement them to the solution of differential equations, as presented in the following two sections.
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==3 Poisson equation==
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In this section, we develop a fourth-order finite difference scheme for the Poisson equation. Let us consider <math display="inline">u</math> and <math display="inline">f</math> as the solution of the problem and known right-hand side function, respectively. Thus the interface problem is given by
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<span id="eq-15"></span>
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<span id="eq-15"></span>
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<span id="eq-15"></span>
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<span id="eq-15"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>\Delta u(\boldsymbol{x}) = f(\boldsymbol{x}), \quad \boldsymbol{x}\in \Omega \setminus \Gamma , \quad \Omega = \Omega ^{+} \cup \Omega ^{-}, </math>
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|-
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| style="text-align: center;" | <math> u(\boldsymbol{x}) = g(\boldsymbol{x}),  \quad \boldsymbol{x}\in \partial \Omega , </math>
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|-
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| style="text-align: center;" | <math> \left[u\right]_\Gamma   = \mathfrak{p}(\boldsymbol{x}),  \quad \boldsymbol{x}\in \Gamma , </math>
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|-
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| style="text-align: center;" | <math> \left[u_{\boldsymbol{n}} \right]_\Gamma = \mathfrak{q}(\boldsymbol{x}) , \quad \boldsymbol{x}\in \Gamma{.}  </math>
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|}
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|}
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We divide <math display="inline">\Omega </math> in two regions, <math display="inline">\Omega ^{+}</math> and <math display="inline">\Omega ^{-}</math>, separated by an immersed interface <math display="inline">\Gamma </math>. Dirichlet boundary conditions are defined on <math display="inline">\partial \Omega </math> through function <math display="inline">g</math>. We assume that <math display="inline">u</math> and <math display="inline">f</math> may have discontinuities at the interface <math display="inline">\Gamma </math>. Thus, we require additional conditions <math display="inline">\left[u\right]_\Gamma </math> and <math display="inline">\left[u_{\boldsymbol{n}} \right]_\Gamma </math> known as principal jump conditions. Here, <math display="inline">u_{\boldsymbol{n}}</math> is the derivative in the normal direction. Note that the principal jump conditions, <math display="inline">\mathfrak{p}</math> and <math display="inline">\mathfrak{q}</math>, are known functions defined on <math display="inline">\Gamma </math>.
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In the context of the general problem, the computational domain can be considered into multiple dimensions. Nevertheless, since the primary objective of this paper is to illustrate the fundamental attributes of the proposed implicit high-order method, we concentrate on investigating the one-dimensional (1D) interface problem as defined by
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<span id="eq-15"></span>
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<span id="eq-16"></span>
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<span id="eq-17"></span>
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<span id="eq-18"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>u_{xx}(x) = f(x),\quad x\in (\mathfrak{a},x_\alpha ) \cup (x_\alpha , \mathfrak{b}), </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (15)
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|-
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| style="text-align: center;" | <math> u(x) = g(x),  \quad x\in \{ \mathfrak{a},\mathfrak{b}\} , </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (16)
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|-
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| style="text-align: center;" | <math> \left[u\right] = \mathfrak{p}, </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (17)
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| style="text-align: center;" | <math> \left[u_{x}\right] = \mathfrak{q},  </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (18)
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|}
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|}
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Here, <math display="inline">u</math> and <math display="inline">f</math> can be discontinuous functions at a given fixed point <math display="inline">x=x_\alpha </math>, and principal jump conditions <math display="inline">\left[u\right]=\left[u\right]_{x_\alpha }</math> and <math display="inline">\left[u_{x}\right]=\left[u_{x}\right]_{x_\alpha }</math> are known values at <math display="inline">x_\alpha </math>.
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===3.1 IFD-IIM for the 1D Poisson problem===
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Let us consider that <math display="inline">x_\alpha </math> is located between the adjacent grid points <math display="inline">x_I</math> and <math display="inline">x_{I+1}</math> as <math display="inline">x_I \leq x_\alpha < x_{I+1}</math>. If we apply operator <math display="inline">\mathfrak{D}^2(\cdot ) = (\cdot ) +bh^2 (\cdot )_{xx}</math> at both sides of [[#eq-15|(15)]], then we get
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<span id="eq-19"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>\left.\mathfrak{D}^2 u_{xx}\right|_{i} = \left.\mathfrak{D}^2 f\right|_{i}, \qquad i=2,\dots , N.  </math>
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|}
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| style="width: 5px;text-align: right;white-space: nowrap;" | (19)
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|}
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For <math display="inline">i=1</math> and <math display="inline">i=N+1</math>, the grid points are at the boundary, thus the Dirichlet boundary condition can be directly applied. Thus, using the IFD scheme [[#eq-2|(2)]] and approximation [[#eq-12|(12)]] in [[#eq-19|(19)]] at <math display="inline">x_i</math>, we have that the finite-difference scheme for regular points is given by
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<span id="eq-20"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>\left.\delta ^2u\right|_{i} = \left.\mathfrak{d}^2f\right|_{i} + O(h^4), \qquad i\neq I,I+1.  </math>
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|}
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| style="width: 5px;text-align: right;white-space: nowrap;" | (20)
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|}
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Similarly, using formulas [[#eq-6|(6)]] and [[#eq-13|(13)]], the scheme for irregular points is given by
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<span id="eq-21"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>\left.\delta ^2u\right|_{i} + C_i = \left.\mathfrak{d}^2f\right|_{i} + (c_f)_i + O(h^3), \qquad i=I,I+1,  </math>
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|}
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| style="width: 5px;text-align: right;white-space: nowrap;" | (21)
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|}
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where <math display="inline">C_i</math> and <math display="inline">(c_f)_i</math> are given by [[#eq-7|(7)]] and [[#eq-14|(14)]], respectively. Thus, combining the results for all grid points, the IFD-IIM for the 1D Poisson equation [[#eq-15|(15)]] at <math display="inline">x_i</math> is given by
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<span id="eq-22"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>\frac{1}{h^2}U_{i-1}\,\,-\frac{2}{h^2}U_{i}\,+\,\frac{1}{h^2}U_{i+1}  =  bf_{i-1}+\,(1-2b)f_i+\,bf_{i+1} + \mathfrak{C}_i, \quad i=2, \dots , N,  </math>
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|}
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| style="width: 5px;text-align: right;white-space: nowrap;" | (22)
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|}
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where total contribution is <math display="inline">\mathfrak{C}_i = (c_f)_i - C_i</math> with
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<span id="eq-23"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>C_i =  \begin{cases}- \dfrac{1}{h^2}\left([u]+h_R\left[u_{x}\right]+\dfrac{h_R^2}{2} \left[u_{xx}\right] + b \left(2 h_R^3\left[u_{xxx}\right]+\dfrac{h_R^4}{2}\left[u_{xxxx}\right]\right)\right), & i=I,\\[4mm]   \dfrac{1}{h^2} \left([u]+h_L\left[u_{x}\right]+\dfrac{h_L^2}{2}\left[u_{xx}\right] + b \left(2h_L^3\left[u_{xxx}\right]+\dfrac{h_L^4}{2}\left[u_{xxxx}\right]\right)\right), & i=I+1,\\[2mm]    0, & \textrm{else where,}  \end{cases}  </math>
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|}
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| style="width: 5px;text-align: right;white-space: nowrap;" | (23)
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|}
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and
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<span id="eq-24"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>(c_f)_i  = \begin{cases}- b\left([f]+h_R\left[f_x\right]+\dfrac{h_R^2}{2}\left[f_{xx} \right]\right), & i=I, \\[3mm]    b\left([f]+h_L\left[f_x \right]+\dfrac{h_L^2}{2}\left[f_{xx} \right]\right), & i=I+1,\\[2mm]     0, & \textrm{else where.} \end{cases}  </math>
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|}
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| style="width: 5px;text-align: right;white-space: nowrap;" | (24)
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|}
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We remark that scheme [[#eq-22|(22)]]-[[#eq-24|(24)]] results in an approximation with local truncation error of fourth- and third-order for regular and irregular grid points, respectively. Thus, a global <math display="inline">O(h^4)</math> method is expected.
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===3.2 IFD-IIM and principal jump conditions===
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Note that <math display="inline">\left[u\right]</math>, <math display="inline">\left[u_{x}\right]</math>, <math display="inline">\left[u_{xx}\right]</math>, <math display="inline">\left[u_{xxx}\right]</math>, and <math display="inline">\left[u_{xxxx}\right]</math> must be known to apply the proposal fourth-order IFD-IIM. Thus, it seems that more jump conditions of <math display="inline">u</math> rather than the principal jump conditions [[#eq-17|(17)]] and [[#eq-18|(18)]] are required to have a fourth-order accurate method. However, we can use the Poisson equation [[#eq-15|(15)]] to obtain them as follows
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>\left[u_{xx}\right]=[f], \qquad  \left[u_{xxx}\right]=\left[f_{x}\right], \qquad  \left[u_{xxxx}\right]=\left[f_{xx}\right].  </math>
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|}
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| style="width: 5px;text-align: right;white-space: nowrap;" | (25)
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|}
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Thus, the total jump contribution for the one-dimensional Poisson problem is given by
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<span id="eq-26"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>\mathfrak{C}_i =  \begin{cases}  \dfrac{1}{h^2}\left([u]+h_R\left[u_{x}\right]+\dfrac{h_R^2}{2}\left[f\right] \right)& \\ \qquad  - b \left\{[f] + h_R\left(- \dfrac{2h_R^2}{h^2}+1\right)\left[f_x\right]+\dfrac{h_R^2}{2} \left(-\dfrac{h_R^2}{h^2}+1\right)\left[f_{xx}\right]\right\}, & i=I, \\[2mm] - \dfrac{1}{h^2} \left([u]+h_L\left[u_{x}\right]+\dfrac{h_L^2}{2}\left[f\right] \right)& \\ \qquad  + b \left\{[f] + h_L\left(- \dfrac{2h_L^2}{h^2} +1\right)\left[f_x\right]+ \dfrac{h_L^2}{2} \left(-\dfrac{h_L^2}{h^2}+1\right)\left[f_{xx}\right]\right\}, & i=I+1,\\[4mm]    0, & \textrm{else where}. \end{cases}  </math>
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|}
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| style="width: 5px;text-align: right;white-space: nowrap;" | (26)
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|}
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Thus contribution <math display="inline">\mathfrak{C}_i</math> depends only on the principal jump conditions, <math display="inline">[u]</math> and <math display="inline">[u_x]</math>, and right-hand side jumps: <math display="inline">[f]</math>, <math display="inline">\left[f_{x}\right]</math>, and <math display="inline">\left[f_{xx} \right]</math>. The additional jumps derivatives from the right-hand side can be approximated using the current values of <math display="inline">f</math>. In this paper, we will assume that we know them.
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'''Remark 2:''' For the 1D Poisson problem, a global second-order IIM (<math display="inline">b=0</math>) only requires to know the principal jump conditions <math display="inline">[u]</math>, <math display="inline">\left[u_{x}\right]</math> and <math display="inline">\left[f\right]</math>.
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'''Remark 3:''' If <math display="inline">h_R/h=1</math>, then <math display="inline">h_L=0</math> and both weight terms next to second-order derivative jump of <math display="inline">f</math> are equal to zero in [[#eq-26|(26)]]. Thus, we do not require to know jump condition <math display="inline">\left[f_{xx}\right]</math> to obtain a fourth-order method when the interface is located at a grid point.
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==4 Heat equation with a fixed interface==
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For the second differential equation, we consider the heat conduction equation with initial, boundary, and principal jump conditions, as follows
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<span id="eq-27"></span>
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<span id="eq-27"></span>
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<span id="eq-27"></span>
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<span id="eq-27"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>u_t(\boldsymbol{x},t) = \Delta u(\boldsymbol{x},t)- f(\boldsymbol{x},t), \quad \boldsymbol{x}\in \Omega \setminus \Gamma \times (0,T], \quad \Omega = \Omega ^{+} \cup \Omega ^{-}, </math>
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|-
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| style="text-align: center;" | <math> u(\boldsymbol{x},0) = u_0(\boldsymbol{x}),  \quad \boldsymbol{x} \in \Omega ,</math>
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| style="text-align: center;" | <math> u(\boldsymbol{x},t) = g(\boldsymbol{x},t),  \quad (\boldsymbol{x},t) \in \partial \Omega \times [0,T], </math>
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|-
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| style="text-align: center;" | <math> \left[u\right]_\Gamma   = \mathfrak{p}(\boldsymbol{x},t),  \quad \boldsymbol{x}\in \Gamma \times [0,T], </math>
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| style="text-align: center;" | <math> \left[u_{\boldsymbol{n}} \right]_\Gamma = \mathfrak{q}(\boldsymbol{x},t) , \quad \boldsymbol{x}\in \Gamma \times [0,T],  </math>
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|}
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|}
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where the source <math display="inline">f</math> and initial value <math display="inline">u_0</math> may be discontinuous or singular across a fixed interface <math display="inline">\Gamma </math>. The interface <math display="inline">\Gamma </math> is immersed in the domain <math display="inline">\Omega </math> and divides into two parts, <math display="inline">\Omega ^{+}</math> and <math display="inline">\Omega ^{-}</math>. As the Poisson equation, <math display="inline">g</math>, <math display="inline">\mathfrak{p}</math> and <math display="inline">\mathfrak{q}</math> are known functions. This paper only focuses on the one-dimensional problem given by
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<span id="eq-27"></span>
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<span id="eq-28"></span>
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<span id="eq-29"></span>
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<span id="eq-30"></span>
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<span id="eq-31"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>u_t = u_{xx}-f, \quad (x,t) \in (\mathfrak{a},x_\alpha ) \cup (x_\alpha , \mathfrak{b}) \times (0,T],  </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (27)
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|-
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| style="text-align: center;" | <math> u(x,0) = u_0(x), \quad x \in (\mathfrak{a},\mathfrak{b}), </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (28)
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|-
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| style="text-align: center;" | <math> u(x,t) = g(x,t),  \quad (x,t) \in \{ \mathfrak{a},\mathfrak{b}\} \times [0,T], </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (29)
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|-
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| style="text-align: center;" | <math> \left[u\right] =  \mathfrak{p}(t),\quad t\in [0,T], </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (30)
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|-
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| style="text-align: center;" | <math> \left[u_{x}\right] = \mathfrak{q}(t), \quad t\in [0,T].  </math>
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| style="width: 5px;text-align: right;white-space: nowrap;" | (31)
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|}
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|}
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where the source <math display="inline">f</math> and initial value <math display="inline">u_0</math> may be discontinuous or singular across a fixed interface located at <math display="inline">x_\alpha </math>.
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===4.1 IFD-IIM for the 1D heat conduction problem===
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Since the interface is fixed and all the quantities are continuous with time, we can approximate the time derivative using the Crank-Nicolson method, as follows
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<span id="eq-32"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>u^{n+1} = u^{n} + \dfrac{\Delta t}{2} \left\{\left(u_{xx}-f\right)^{n+1} + \left(u_{xx}-f\right)^{n}\right\}+ O(\Delta t^2).  </math>
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|}
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| style="width: 5px;text-align: right;white-space: nowrap;" | (32)
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|}
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Applying the fourth-order operator [[#eq-3|(3)]] to equation [[#eq-32|(32)]] for <math display="inline">i=2, \dots , N</math>, yields
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<span id="eq-33"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>\left.\mathfrak{D}^2u\right|_{i}^{n+1}  = \left.\mathfrak{D}^2u\right|_{i}^{n}   + \dfrac{\Delta t}{2}\left\{ \left.\mathfrak{D}^2u_{xx}\right|_{i}^{n+1}  +\left.\mathfrak{D}^2u_{xx}\right|_{i}^{n} -\left.\mathfrak{D}^2f\right|_{i}^{n+1}  -\left.\mathfrak{D}^2f\right|_{i}^{n} \right\} + O(\Delta t^2).  </math>
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|}
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| style="width: 5px;text-align: right;white-space: nowrap;" | (33)
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|}
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By employing the IFD method [[#eq-2|(2)]] and approximation [[#eq-12|(12)]], equation [[#eq-33|(33)]] can be approximated for regular points as follows
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<span id="eq-34"></span>
584
{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
587
{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>\left.\mathfrak{d}^2u\right|_{i}^{n+1}  = \left.\mathfrak{d}^2u\right|_{i}^{n}   + \dfrac{\Delta t}{2}\left\{ \left.\delta ^2u\right|_{i}^{n+1}  +\left.\delta ^2u\right|_{i}^{n} -\left.\mathfrak{d}^2f\right|_{i}^{n+1}  -\left.\mathfrak{d}^2f\right|_{i}^{n} \right\}</math>
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|-
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| style="text-align: center;" | <math>  +  O(\Delta t^2) + O(h^4), \qquad i\neq I,I+1.   </math>
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|}
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| style="width: 5px;text-align: right;white-space: nowrap;" | (34)
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|}
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By using the IFD-IIM [[#eq-6|(6)]] and approximation [[#eq-13|(13)]], the implicit scheme for irregular points is given by
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<span id="eq-35"></span>
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{| class="formulaSCP" style="width: 100%; text-align: left;" 
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|-
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| 
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{| style="text-align: left; margin:auto;width: 100%;" 
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|-
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| style="text-align: center;" | <math>\left.\mathfrak{d}^2u\right|_{i}^{n+1}  = \left.\mathfrak{d}^2u\right|_{i}^{n}  + \dfrac{\Delta t}{2}\left\{ \left.\delta ^2u\right|_{i}^{n+1} +\left.\delta ^2u\right|_{i}^{n} -\left.\mathfrak{d}^2f\right|_{i}^{n+1} -\left.\mathfrak{d}^2f\right|_{i}^{n} \right\}+ \mathfrak{C}_i </math>
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|-
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| style="text-align: center;" | <math>  +  O(\Delta t^2) + O(h^3), \qquad i= I,I+1,  </math>
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|}
608
| style="width: 5px;text-align: right;white-space: nowrap;" | (35)
609
|}
610
611
where
612
613
<span id="eq-36"></span>
614
{| class="formulaSCP" style="width: 100%; text-align: left;" 
615
|-
616
| 
617
{| style="text-align: left; margin:auto;width: 100%;" 
618
|-
619
| style="text-align: center;" | <math>\mathfrak{C}_i = - (c_u)_{i}^{n+1} + (c_u)_{i}^{n} + \dfrac{\Delta t}{2}\left\{ C_{i}^{n+1} + C_{i}^{n} - (c_f)_{i}^{n+1} - (c_f)_{i}^{n} \right\}.  </math>
620
|}
621
| style="width: 5px;text-align: right;white-space: nowrap;" | (36)
622
|}
623
624
Here, <math display="inline">(c_u)_i</math> and <math display="inline">(c_f)_i</math> are defined as [[#eq-14|(14)]], and <math display="inline">C_i</math> is given by [[#eq-7|(7)]]. Thus, for 1D heat conduction equation [[#eq-27|(27)]], the IFD-IIM reads
625
626
<span id="eq-37"></span>
627
{| class="formulaSCP" style="width: 100%; text-align: left;" 
628
|-
629
| 
630
{| style="text-align: left; margin:auto;width: 100%;" 
631
|-
632
| style="text-align: center;" | <math>(b-r)U_{i-1}^{n+1}+(1-2b+2r)U_i^{n+1}+(b-r)U_{i+1}^{n+1} </math>
633
|-
634
| style="text-align: center;" | <math> = (b+r)U_{i-1}^{n}+(1-2b-2r)U_i^{n}+(b+r)U_{i+1}^{n} </math>
635
|-
636
| style="text-align: center;" | <math>  - \dfrac{\Delta t}{2}\left\{bf_{i-1}^{n+1}+(1-2b)f_i^{n+1}+bf_{i+1}^{n+1} \right\} </math>
637
| style="width: 5px;text-align: right;white-space: nowrap;" | (37)
638
|-
639
| style="text-align: center;" | <math>  - \dfrac{\Delta t}{2}\left\{bf_{i-1}^{n}+(1-2b)f_i^{n}+bf_{i+1}^{n} \right\}+ \mathfrak{C}_i, </math>
640
|}
641
|}
642
643
where <math display="inline">r=\frac{1}{2}\Delta t/h^2</math> and <math display="inline">\mathfrak{C}_i</math> is given by [[#eq-36|(36)]]. Here, we have that <math display="inline">\mathfrak{C}_i=0</math>  for regular points.
644
645
'''Remark 4:''' The IFD-IIM [[#eq-37|(37)]] is unconditionally stable and the local truncation error is of <math display="inline">O(\Delta t^2 + h^4)</math> and <math display="inline">O(\Delta t^2 + h^3)</math> for regular and irregular grid points, respectively. Thus a global fourth-order method is expected by taking <math display="inline">\Delta t = O(h^2)</math>.
646
647
'''Remark 5:''' As the Crank-Nicolson method is implicit in time, the IFD-IIM solves a linear system at each time step. To address this efficiently, we employed Thomas' algorithm, given that the resulting matrix is tridiagonal. Furthermore, the implicit method in space preserves the original structure of this system of equations, thus yielding a higher-order method without compromising the efficiency of the standard scheme.
648
649
'''Remark 6:''' In addition to accounting for the contributions of the source term <math display="inline">f</math> and its derivatives, the finite-difference scheme presented in equation [[#eq-37|(37)]] requires additional knowledge of the jump conditions for the solution given by <math display="inline">\left[u_{xx}\right]</math>, <math display="inline">\left[u_{xxx}\right]</math>, and <math display="inline">\left[u_{xxxx}\right]</math>. It is worth noting that, although not presented here, there are techniques available for deriving all the necessary jump conditions from the principal jump conditions <span id='citeF-14'></span>[[#cite-14|[14]]].
650
651
==5 Numerical results for the Poisson equation==
652
653
In this section, we test the IFD-IIM for different examples of the Poisson equation. In the following simulations, we numerically solve the equation for a given right-hand side function and compare it with its analytic solution. In all cases the resulting linear system is solved using the Thomas' algorithm.
654
655
The numerical method is tested using three different examples. Example 1 considers a smooth solution to verify the fourth-order implicit method for smooth solutions. Example 2 studies a Poisson equation with a discontinuous solution in a single interface point. Finally, Example 3 presents a discontinuous problem with multiple interface points. A Matlab code of these examples can be download at https://github.com/CIMATMerida/IFD-IIM
656
657
For the all these examples, the computational domain is the interval <math display="inline">[0,1]</math>, and the grid spacing is <math display="inline">h=1/N</math> for different <math display="inline">N</math> sub-intervals. The errors are reported using the <math display="inline">L_\infty </math>-norm and the discrete <math display="inline">L_2</math>-norm calculated as
658
659
<span id="eq-38"></span>
660
{| class="formulaSCP" style="width: 100%; text-align: left;" 
661
|-
662
| 
663
{| style="text-align: left; margin:auto;width: 100%;" 
664
|-
665
| style="text-align: center;" | <math>\left\|e \right\|_\infty = \max _{1\leq i\leq N+1} \left|u_{i}-U_{i} \right|,   \quad \mathrm{and} \quad  \left\|e\right\|_2 = \left(\sum _{i=1}^{N+1} (u_{i}-U_{i})^2\Delta x\right)^{1/2}, </math>
666
|}
667
| style="width: 5px;text-align: right;white-space: nowrap;" | (38)
668
|}
669
670
respectively, where <math display="inline">U_{i}</math> and <math display="inline">u_{i}</math> corresponds to the numerical and exact solution at <math display="inline">x_i</math>, respectively. The estimated order of accuracy is computed as
671
672
<span id="eq-39"></span>
673
{| class="formulaSCP" style="width: 100%; text-align: left;" 
674
|-
675
| 
676
{| style="text-align: left; margin:auto;width: 100%;" 
677
|-
678
| style="text-align: center;" | <math>\textrm{Order} := \dfrac{\log \left(\left\|e \right\|_{N_1}/ \left\|e \right\|_{N_2}\right)}{\log \left(N_1/N_2 \right)}, </math>
679
|}
680
| style="width: 5px;text-align: right;white-space: nowrap;" | (39)
681
|}
682
683
where <math display="inline">N_1</math> and <math display="inline">N_2</math> indicates the different number of sub-intervals of the corresponding norm.
684
685
===5.1 Example 1. Poison equation with smooth solution===
686
687
Example 1 considers the one-dimensional Poisson problem
688
689
<span id="eq-40"></span>
690
{| class="formulaSCP" style="width: 100%; text-align: left;" 
691
|-
692
| 
693
{| style="text-align: left; margin:auto;width: 100%;" 
694
|-
695
| style="text-align: center;" | <math>\begin{array}{rcl}u_{xx}(x) &=& f(x),\quad x\in (0, 1), \\[1mm] u(0) &=& e^{-\pi /4}, \\  u(1) &=& e^{-9\pi /4}, \end{array}  </math>
696
|}
697
| style="width: 5px;text-align: right;white-space: nowrap;" | (40)
698
|}
699
700
where the right-hand side in [[#eq-40|(40)]] is given by
701
702
<span id="eq-41"></span>
703
{| class="formulaSCP" style="width: 100%; text-align: left;" 
704
|-
705
| 
706
{| style="text-align: left; margin:auto;width: 100%;" 
707
|-
708
| style="text-align: center;" | <math>f(x)= 4\pi (16\pi x^2-8\pi x+\pi{-2)}e^{-4\pi (x-1/4)^2}.  </math>
709
|}
710
|}
711
712
The exact solution of problem [[#eq-40|(40)]] is an infinitely smooth and differentiable function given by the following expression
713
714
<span id="eq-41"></span>
715
{| class="formulaSCP" style="width: 100%; text-align: left;" 
716
|-
717
| 
718
{| style="text-align: left; margin:auto;width: 100%;" 
719
|-
720
| style="text-align: center;" | <math>u(x) = e^{-4\pi (x-1/4)^2}.  </math>
721
|}
722
| style="width: 5px;text-align: right;white-space: nowrap;" | (41)
723
|}
724
725
Note that the function <math display="inline">f</math> and Dirichlet boundary conditions are obtained directly from [[#eq-41|(41)]]. Due to the regularity of the solution, the jump contributions <math display="inline">\mathcal{C}_I</math> and <math display="inline">\mathcal{C}_{I+1}</math> are equal to zero.
726
727
Table [[#table-1|1]] presents the convergence analysis of Example 1 for different grid resolutions. If <math display="inline">b = 0</math>, then we recover the standard central finite-difference method of second-order accuracy. On the other hand, the fourth-order implicit scheme is recovered when <math display="inline">b=1/12</math>. Last row of table [[#table-1|1]] shows the numerical order calculated by the regression-line slope based on a least squares method (LSM) of the <math display="inline">L_{\infty }</math>- and <math display="inline">L_2</math>-norm error. A complete analysis of the IFD method for smooth solutions can be found in <span id='citeF-12'></span>[[#cite-12|[12]]].
728
729
730
{|  class="floating_tableSCP" style="text-align: left; margin: 1em auto;border-top: 2px solid;border-bottom: 2px solid;min-width:99%;"
731
|+ style="font-size: 75%;" |<span id='table-1'></span>'''Table. 1''' Convergence analysis of Example 1 testing a Poisson equation with smooth solution.     
732
!
733
! colspan="4" |<math display="inline">b=0</math>
734
! colspan="4" |<math display="inline">b=1/12</math>
735
|-
736
! <math display="inline">N</math>  
737
! <math display="inline">L_\infty </math>-norm 
738
!  Order 
739
! <math display="inline">L_2</math>-norm 
740
!  Order
741
! <math display="inline">L_\infty </math>-norm 
742
!  Order 
743
! <math display="inline">L_2</math>-norm 
744
!  Order
745
|-
746
| 10 
747
|  7.52e-02 
748
|  &#8211;-   
749
|   2.84e-02 
750
|  &#8211;-  
751
|  9.30e-03 
752
|  &#8211;-   
753
|   3.56e-03 
754
|  &#8211;-   
755
|-
756
| 20 
757
|  1.70e-02 
758
|  2.15  
759
|   6.52e-03 
760
|  2.12 
761
|  5.05e-04 
762
|  4.20  
763
|   1.93e-04 
764
|  4.21  
765
|-
766
| 40 
767
|  4.15e-03 
768
|  2.03  
769
|   1.60e-03 
770
|  2.03 
771
|  3.06e-05 
772
|  4.04  
773
|   1.17e-05 
774
|  4.04  
775
|-
776
| 80 
777
|  1.03e-03 
778
|  2.01  
779
|   3.98e-04 
780
|  2.01 
781
|  1.90e-06 
782
|  4.01  
783
|   7.27e-07 
784
|  4.01  
785
|-
786
| 160 
787
|  2.57e-04 
788
|  2.00  
789
|   9.95e-05 
790
|  2.00 
791
|  1.18e-07 
792
|  4.00  
793
|   4.54e-08 
794
|  4.00  
795
|-
796
| LSM 
797
|    
798
| '''2.04''' 
799
| 
800
|  '''2.04''' 
801
| 
802
|  '''4.06''' 
803
| 
804
|  '''4.06'''
805
|-
806
|}
807
808
===5.2 Example 2. Poison equation with a single interface===
809
810
For Example 2, we show the method's capability by solving a single interface problem located at <math display="inline">x = x_\alpha </math>. Here, we consider the one-dimensional Poisson problem
811
812
<span id="eq-42"></span>
813
{| class="formulaSCP" style="width: 100%; text-align: left;" 
814
|-
815
| 
816
{| style="text-align: left; margin:auto;width: 100%;" 
817
|-
818
| style="text-align: center;" | <math>\begin{array}{rcl}u_{xx}(x) &=& f(x),\quad x\in (0,x_\alpha ) \cup (x_\alpha , 1), \\[1mm] u(0) &=& 0 \\[1mm] u(1) &=& -1, \\[1mm] \left[u\right]  & = & \cos (\pi x_\alpha ) - \sin (\pi x_\alpha ),\\[1mm] \left[u_x\right]& = &-\pi (\sin (\pi x_\alpha ) + \cos (\pi x_\alpha )),  \end{array}  </math>
819
|}
820
| style="width: 5px;text-align: right;white-space: nowrap;" | (42)
821
|}
822
823
where the right-hand side in [[#eq-42|(42)]] is
824
825
{| class="formulaSCP" style="width: 100%; text-align: left;" 
826
|-
827
| 
828
{| style="text-align: left; margin:auto;width: 100%;" 
829
|-
830
| style="text-align: center;" | <math>f(x) = \begin{cases}-\pi ^2\sin (\pi x), & x < x_\alpha ,\\ -\pi ^2\cos (\pi x), & x > x_\alpha{.} \end{cases} </math>
831
|}
832
|}
833
834
The exact solution of problem [[#eq-42|(42)]] is a discontinuous function given by the expression
835
836
<span id="eq-43"></span>
837
{| class="formulaSCP" style="width: 100%; text-align: left;" 
838
|-
839
| 
840
{| style="text-align: left; margin:auto;width: 100%;" 
841
|-
842
| style="text-align: center;" | <math>u(x) = \begin{cases}\sin (\pi x), & x < x_\alpha ,\\ \cos (\pi x), & x > x_\alpha{.} \end{cases}  </math>
843
|}
844
| style="width: 5px;text-align: right;white-space: nowrap;" | (43)
845
|}
846
847
Note that the right-hand side, Dirichlet boundary conditions, and principal jump conditions are obtained directly from equation [[#eq-43|(43)]].
848
849
We test two different points: <math display="inline">x_\alpha=0.4</math> and <math display="inline">x_\alpha=0.63</math>.  For the case <math display="inline">x_\alpha=0.4</math>, we always have <math display="inline">h_R/h=1</math> for <math display="inline">N=10\times{2}^{n}</math> (<math display="inline">n=0,1,2,\dots </math>); thus the interface is always located at one grid point of that resolution. In general, for <math display="inline">x_\alpha=0.63</math>, we have different <math display="inline">h_R/h</math> values for different <math display="inline">N</math> numbers. Fig.&nbsp;[[#img-2|2]] shows the numerical and exact solution when the interface is located at these two values using <math display="inline">N = 40</math>. As expected, the exact solution is accurately recovered for both cases.
850
851
<div id='img-2'></div>
852
{| class="floating_imageSCP" style="text-align: center; border: 1px solid #BBB; margin: 1em auto; width: 100%;max-width: 100%;"
853
|-
854
|[[Image:Review_499745022132-Fig02_Poisson_Ex2_Sol.png|594px|Numerical and exact solution of Example 2 using N = 40 using (a) x_α= 0.4, and (b) x_α= 0.63. Here, the interface is located at one grid point using N=40 and x_α=0.4.]]
855
|- style="text-align: center; font-size: 75%;"
856
| colspan="1" | '''Figure 2:''' Numerical and exact solution of Example 2 using <math>N = 40</math> using (a) <math>x_\alpha = 0.4</math>, and (b) <math>x_\alpha = 0.63</math>. Here, the interface is located at one grid point using <math>N=40</math> and <math>x_\alpha=0.4</math>.
857
|}
858
Table [[#table-2|2]] shows the convergence analysis for Example 2 for the two <math display="inline">x_\alpha </math> values. Observe that a second-order method is recovered for <math display="inline">b = 0</math> and a fourth-order method for <math display="inline">b=1/12</math>. As expected, the IFD-IIM numerical order does not depend on the location of the interface. However, the magnitude of the error may present minor variations due to the interface position. Fig.&nbsp;[[#img-3|3]] shows the error analysis corresponding to interface locations <math display="inline">x_\alpha = 0.40</math> and <math display="inline">x_\alpha = 0.63</math> for <math display="inline">N = 10,11,12, \dots ,320</math>. The solid black line for this and the following figures shows the numerical order calculated by the regression-line slope based on a least squares method of the <math display="inline">L_{\infty }</math>-norm.
859
860
861
{|  class="floating_tableSCP" style="text-align: left; margin: 1em auto;border-top: 2px solid;border-bottom: 2px solid;min-width:99%;"
862
|+ style="font-size: 75%;" |<span id='table-2'></span>'''Table. 2''' Convergence analysis of Example 2 using the IFD-IIM.
863
!
864
! colspan="4" |<math display="inline">b=0</math>
865
! colspan="4" |<math display="inline">b=1/12</math>
866
|-
867
! <math display="inline">N</math>  
868
! <math display="inline">L_\infty </math>-norm 
869
!  Order 
870
! <math display="inline">L_2</math>-norm 
871
!  Order
872
! <math display="inline">L_\infty </math>-norm 
873
!  Order 
874
! <math display="inline">L_2</math>-norm 
875
!  Order
876
|-
877
| 10 
878
|  1.69e-02 
879
|  &#8211;-  
880
|  5.19e-03 
881
|  &#8211;-  
882
|  5.75e-05 
883
|  &#8211;-  
884
|  3.42e-05 
885
|  &#8211;-  
886
|-
887
| 20 
888
|  4.21e-03 
889
|  2.00 
890
|  1.18e-03 
891
|  2.13 
892
|  3.58e-06 
893
|  4.00 
894
|  1.97e-06 
895
|  4.12 
896
|-
897
| 40 
898
|  1.05e-03 
899
|  2.00 
900
|  3.07e-04 
901
|  1.95 
902
|  2.24e-07 
903
|  4.00 
904
|  1.39e-07 
905
|  3.82 
906
|-
907
| 80 
908
|  2.63e-04 
909
|  2.00 
910
|  7.53e-05 
911
|  2.03 
912
|  1.40e-08 
913
|  4.00 
914
|  7.75e-09 
915
|  4.16 
916
|-
917
| 160 
918
|  6.57e-05 
919
|  2.00 
920
|  1.86e-05 
921
|  2.01 
922
|  8.74e-10 
923
|  4.00 
924
|  5.37e-10 
925
|  3.85 
926
|-
927
| LSM  
928
| 
929
| '''2.04''' 
930
| 
931
|  '''2.02''' 
932
| 
933
|  '''4.00''' 
934
| 
935
|  '''3.99'''
936
|-
937
|}
938
<div id='img-3'></div>
939
{| class="floating_imageSCP" style="text-align: center; border: 1px solid #BBB; margin: 1em auto; width: 100%;max-width: 100%;"
940
|-
941
|[[Image:Review_499745022132-Fig03_Poisson_Ex2_Order4th.png|594px|Convergence analysis of Example 2 for N = 10,\dots ,320 using (a) x_α= 0.40, and (b) x_α= 0.63. The solid black line shows the numerical order 4.00 calculated by the regression-line slope based on a least squares method of the L<sub>∞</sub>-norm.]]
942
|- style="text-align: center; font-size: 75%;"
943
| colspan="1" | '''Figure 3:''' Convergence analysis of Example 2 for <math>N = 10,\dots ,320</math> using (a) <math>x_\alpha = 0.40</math>, and (b) <math>x_\alpha = 0.63</math>. The solid black line shows the numerical order <math>4.00</math> calculated by the regression-line slope based on a least squares method of the <math>L_{\infty }</math>-norm.
944
|}
945
The contribution formula includes jumps <math display="inline">[u]</math>, <math display="inline">[u_x]</math>, <math display="inline">[u_{xx}]</math>, <math display="inline">[u_{xxx}]</math>, and <math display="inline">[u_{xxxx}]</math> to obtain a fourth-order accurate method. Fig.&nbsp;[[#img-4|4]] shows that if we add additional jumps of high-order derivatives into <math display="inline">\mathcal{C}</math>, such as <math display="inline">[u_{xxxxx}]=[f_{xxx}]</math>, we observe that the error oscillation decreases in comparison with Fig.&nbsp;[[#img-3|3]] results. It is expected because the method is <math display="inline">O(h^4)</math> for the whole computational domain, including the irregular points. Thus, we can mitigate error oscillations due to interface position by adding high-order jumps.
946
947
<div id='img-4'></div>
948
{| class="floating_imageSCP" style="text-align: center; border: 1px solid #BBB; margin: 1em auto; width: 100%;max-width: 100%;"
949
|-
950
|[[Image:Review_499745022132-Fig04_Poisson_Ex2_Order5th.png|594px|Convergence analysis of Example 2 for N = 10,\dots ,320 using (a) α= 0.40, and (b) α= 0.63. The contribution includes jumps up to fifth-order ([uₓₓₓₓₓ]=[fₓₓₓ]).]]
951
|- style="text-align: center; font-size: 75%;"
952
| colspan="1" | '''Figure 4:''' Convergence analysis of Example 2 for <math>N = 10,\dots ,320</math> using (a) <math>\alpha = 0.40</math>, and (b) <math>\alpha = 0.63</math>. The contribution includes jumps up to fifth-order (<math>[u_{xxxxx}]=[f_{xxx}]</math>).
953
|}
954
Now we study the effect of removing jumps in <math display="inline">\mathcal{C}</math>. Let us consider a contribution term up to the third derivative jump by dropping <math display="inline">[u_{xxxx}]=[f_{xx}]</math>. Thus, the numerical approximation is only third-order accurate, as shown in Fig.&nbsp;[[#img-5|5]] for different interface values.  Note that error oscillations may have a clear pattern or a scattered distribution depending on the interface location. In general, the error magnitude perturbations are related to the variations coming from <math display="inline">h_R/h</math> and <math display="inline">h_L/h</math> values in the <math display="inline">\mathcal{C}</math> formula [[#eq-26|(26)]].
955
956
<div id='img-5'></div>
957
{| class="floating_imageSCP" style="text-align: center; border: 1px solid #BBB; margin: 1em auto; width: 100%;max-width: 100%;"
958
|-
959
|[[Image:Review_499745022132-Fig05_Poisson_Ex2_Order3rd.png|594px|Convergence analysis of Example 2 for N = 10,\dots ,320 using (a) α= 0.40, and (b) α= 0.63. The contribution includes jumps up to third-order ([uₓₓₓ]=[fₓ]).]]
960
|- style="text-align: center; font-size: 75%;"
961
| colspan="1" | '''Figure 5:''' Convergence analysis of Example 2 for <math>N = 10,\dots ,320</math> using (a) <math>\alpha = 0.40</math>, and (b) <math>\alpha = 0.63</math>. The contribution includes jumps up to third-order (<math>[u_{xxx}]=[f_{x}]</math>).
962
|}
963
Note that there are some points in Fig.&nbsp;[[#img-5|5]], marked with circles, that are close to the fourth-order line. Those circled markers correspond to the values with <math display="inline">h_R/h=1</math>: (a) <math display="inline">N = 5,10,15,\dots ,315</math> for <math display="inline">x_\alpha=0.40</math>, and (b) <math display="inline">N = 100, 200, 300</math> for <math display="inline">x_\alpha=0.63</math>.  Both set of points satisfy that the interface <math display="inline">x_\alpha </math> is located at a grid point <math display="inline">x_I</math>. In the case of <math display="inline">x_\alpha=0.4</math>, we observe that the global order (black points) is close to <math display="inline">3.21</math>; meanwhile, the circled points order is four. Similar behavior is obtained for <math display="inline">x_\alpha=0.63</math>. Thus, for a given mesh resolution <math display="inline">N</math>, the IFD-IIM is still fourth-order accurate for <math display="inline">h_R/h = 1</math>, as  proven theoretically in Section [[#4.2 IFD-IIM and principal jump conditions|4.2]].
964
965
===5.3 Example 3. Poison equation with multiple interface points===
966
967
Example 3 investigates the numerical scheme capability to solve a multiple interface problem. We only focus on two interface points located at <math display="inline">x = x_{\alpha _1}</math> and <math display="inline">x = x_{\alpha _2}</math>. However, the methodology could be applied for multiple interfaces by doing minor modifications in the implementation. For this problem, the exact solution of the Poisson problem is given by
968
969
<span id="eq-44"></span>
970
{| class="formulaSCP" style="width: 100%; text-align: left;" 
971
|-
972
| 
973
{| style="text-align: left; margin:auto;width: 100%;" 
974
|-
975
| style="text-align: center;" | <math>u(x) = \begin{cases}\sin (2\pi x), & x < x_{\alpha _1},\\ \cos (2\pi x), & x_{\alpha _1}< x < x_{\alpha _2}, \\ \sin (2\pi x), & x_{\alpha _2} < x. \end{cases}  </math>
976
|}
977
| style="width: 5px;text-align: right;white-space: nowrap;" | (44)
978
|}
979
980
The right-hand function, Dirichlet boundary conditions, and principal jump conditions are obtained directly from the exact solution [[#eq-44|(44)]].  We consider the same computational domain and grid resolution as previous 1D examples. Fig.&nbsp;[[#img-6|6]] presents the analytical and numerical solution when the interface is located at <math display="inline">x_{\alpha _1}= 0.3</math> and <math display="inline">x_{\alpha _2} = 0.7</math> using <math display="inline">N=40</math>. This figure also shows the error analysis. As expected, the IFD-IIM is a fourth-order accurate method.
981
982
<div id='img-6'></div>
983
{| class="floating_imageSCP" style="text-align: center; border: 1px solid #BBB; margin: 1em auto; width: 100%;max-width: 100%;"
984
|-
985
|[[Image:Review_499745022132-Fig06_Poisson_Ex3.png|594px|(a) Numerical and exact solution of Example 3 with multiple interfaces using N = 40, and (b) convergence error analysis using  grid resolutions of N = 10, 20, 40, 80 and 160.]]
986
|- style="text-align: center; font-size: 75%;"
987
| colspan="1" | '''Figure 6:''' (a) Numerical and exact solution of Example 3 with multiple interfaces using <math>N = 40</math>, and (b) convergence error analysis using  grid resolutions of <math>N = 10</math>, 20, 40, 80 and 160.
988
|}
989
990
==6 Numerical results for the Heat equation==
991
992
This section tests the IFD-IIM for the Heat conduction equation in different scenarios. Example 4 verifies the fourth-order implicit method for smooth solutions in space. Example 5 studies a Heat equation with a discontinuous solution in a single interface point and no source term. Finally, Example 6 presents a general discontinuous problem. For the all these examples, the computational domain is the same interval <math display="inline">[0,1]</math> and space step, <math display="inline">h</math>, used for the Poisson examples. Here, the final time is at <math display="inline">T=0.5</math> and the time step is <math display="inline">\Delta t = \frac{1}{4}h^2</math>. The error and estimated order of accuracy are reported using  [[#eq-38|(38)]] and [[#eq-39|(39)]], respectively, at the final step approximation.
993
994
===6.1 Example 4. Heat equation with smooth solution===
995
996
This example considers the heat conduction problem
997
998
<span id="eq-45"></span>
999
{| class="formulaSCP" style="width: 100%; text-align: left;" 
1000
|-
1001
| 
1002
{| style="text-align: left; margin:auto;width: 100%;" 
1003
|-
1004
| style="text-align: center;" | <math>\begin{array}{rcll}u_t(x,t) &=& u_{xx}(x,t)-f(x,t), & (x,t)\in (0, 1)\times (0,\frac{1}{2}], \\[2mm] u(x,0) &=& \sin \left(\frac{3}{2}\pi x\right),&  x \in (0, 1), \\[2mm] u(0,t) &=& 0, &  t\in [0,\frac{1}{2}],\\[2mm] u(1,t) &=& -e^{-t}, &  t\in [0,\frac{1}{2}], \end{array}  </math>
1005
|}
1006
| style="width: 5px;text-align: right;white-space: nowrap;" | (45)
1007
|}
1008
1009
where <math display="inline">f</math> in [[#eq-45|(45)]] is given by
1010
1011
{| class="formulaSCP" style="width: 100%; text-align: left;" 
1012
|-
1013
| 
1014
{| style="text-align: left; margin:auto;width: 100%;" 
1015
|-
1016
| style="text-align: center;" | <math>f(x,t)= \left(1-\frac{9}{4}\pi ^2\right)\sin \left(\frac{3}{2}\pi x\right)e^{-t}. </math>
1017
|}
1018
|}
1019
1020
This example is constructed so that the exact solution is
1021
1022
<span id="eq-46"></span>
1023
{| class="formulaSCP" style="width: 100%; text-align: left;" 
1024
|-
1025
| 
1026
{| style="text-align: left; margin:auto;width: 100%;" 
1027
|-
1028
| style="text-align: center;" | <math>u(x,t) = \sin \left(\frac{3}{2}\pi x\right)e^{-t}.  </math>
1029
|}
1030
| style="width: 5px;text-align: right;white-space: nowrap;" | (46)
1031
|}
1032
1033
Note that the source term, <math display="inline">f</math>, initial condition and boundary conditions are obtained from the exact solution [[#eq-46|(46)]]. The convergence analysis of this example is presented in Table [[#table-3|3]] with the final time being <math display="inline">T = 0.5</math>. As expected, the high-order methods reach their corresponding order of accuracy.
1034
1035
1036
{|  class="floating_tableSCP" style="text-align: left; margin: 1em auto;border-top: 2px solid;border-bottom: 2px solid;min-width:99%;"
1037
|+ style="font-size: 75%;" |<span id='table-3'></span>'''Table. 3''' Convergence analysis of Example 4 testing a heat equation with smooth solution.
1038
!
1039
! colspan="4" |<math display="inline">b=0</math>
1040
! colspan="4" |<math display="inline">b=1/12</math>
1041
|-
1042
! <math display="inline">N</math>  
1043
! <math display="inline">L_\infty </math>-norm 
1044
!  Order 
1045
! <math display="inline">L_2</math>-norm 
1046
!  Order
1047
! <math display="inline">L_\infty </math>-norm 
1048
!  Order 
1049
! <math display="inline">L_2</math>-norm 
1050
!  Order
1051
|-
1052
| 10 
1053
|  1.66e-02 
1054
|  &#8211;-   
1055
|   1.07e-02 
1056
|  &#8211;-  
1057
|  1.84e-04 
1058
|  &#8211;-   
1059
|  1.18e-04 
1060
|  &#8211;-   
1061
|-
1062
| 20 
1063
|  4.12e-03 
1064
|  2.01  
1065
|   2.65e-03 
1066
|  2.01 
1067
|  1.14e-05 
1068
|  4.01  
1069
|  7.34e-06 
1070
|  4.01  
1071
|-
1072
| 40 
1073
|  1.03e-03 
1074
|  2.00  
1075
|   6.60e-04 
1076
|  2.00 
1077
|  7.15e-07 
1078
|  4.00  
1079
|  4.58e-07 
1080
|  4.00  
1081
|-
1082
| 80 
1083
|  2.58e-04 
1084
|  2.00  
1085
|   1.65e-04 
1086
|  2.00 
1087
|  4.47e-08 
1088
|  4.00  
1089
|  2.86e-08 
1090
|  4.00  
1091
|-
1092
| 160 
1093
|  6.44e-05 
1094
|  2.00  
1095
|   4.12e-05 
1096
|  2.00 
1097
|  2.79e-09 
1098
|  4.00  
1099
|  1.79e-09 
1100
|  4.00  
1101
|-
1102
| LSM 
1103
|    
1104
| '''2.00''' 
1105
| 
1106
|  '''2.00''' 
1107
| 
1108
|  '''4.00''' 
1109
| 
1110
|  '''4.00'''
1111
|-
1112
|}
1113
1114
===6.2 Example 5. Heat equation with discontinuous solution===
1115
1116
In this example, the heat equation with discontinuous solution is given by
1117
1118
<span id="eq-47"></span>
1119
{| class="formulaSCP" style="width: 100%; text-align: left;" 
1120
|-
1121
| 
1122
{| style="text-align: left; margin:auto;width: 100%;" 
1123
|-
1124
| style="text-align: center;" | <math>\begin{array}{rcll}u_t(x,t) &=& u_{xx}(x,t), & (x,t)\in (0,x_\alpha ) \cup (x_\alpha , 1) \times (0,\frac{1}{2}], \\[2mm] u(x,0) &=&\begin{cases}\sin (x), & x < x_\alpha ,\\ \cos (x), & x > x_\alpha ,\\ \end{cases}  & x \in (0,x_\alpha ) \cup (x_\alpha , 1), \\ \\[-3mm] u(0,t) &=& 0, & t\in [0,\frac{1}{2}],\\[2mm] u(1,t) &=& \cos (1)e^{-t}, & t\in [0,\frac{1}{2}],\\[2mm] \left[u\right](t)  &=&     \left(\cos (x_\alpha )-\sin (x_\alpha )\right)e^{-t}, &  t\in [0,\frac{1}{2}],\\[2mm] \left[u_{x}\right](t)  &=& -\left(\sin (x_\alpha )+\cos (x_\alpha )\right)e^{-t}, & t\in [0,\frac{1}{2}].  \end{array}  </math>
1125
|}
1126
| style="width: 5px;text-align: right;white-space: nowrap;" | (47)
1127
|}
1128
1129
The exact solution <math display="inline">u</math> is defined as
1130
1131
<span id="eq-48"></span>
1132
{| class="formulaSCP" style="width: 100%; text-align: left;" 
1133
|-
1134
| 
1135
{| style="text-align: left; margin:auto;width: 100%;" 
1136
|-
1137
| style="text-align: center;" | <math>u(x,t) = \begin{cases}\sin (x)e^{-t}, & x < x_\alpha ,\\ \cos (x)e^{-t}, & x > x_\alpha{.} \end{cases}  </math>
1138
|}
1139
| style="width: 5px;text-align: right;white-space: nowrap;" | (48)
1140
|}
1141
1142
Similar to previous examples, we use <math display="inline">x_\alpha=0.4</math> and <math display="inline">x_\alpha=0.63</math>. Note that the source term <math display="inline">f</math> of this problem is <math display="inline">f\equiv 0</math>. In this example, both the function <math display="inline">u</math> and their derivatives have jumps, and these jumps vary in time. The boundary condition, initial condition, and all jumps are specified by <math display="inline">u</math>.
1143
1144
The figure of numerical solution and absolute error plot using <math display="inline">N=40</math> for different time stages are shown in Fig.&nbsp;[[#img-7|7]]. On the other hand, the one-dimensional results at <math display="inline">T=0.5</math> are presented in Figs.&nbsp;[[#img-8|8]] and [[#img-9|9]]. As expected, we can accurately recover the exact solution using the proposed method for <math display="inline">N=40</math> and considering different interface values.  Additionally, we provide the absolute error for both cases, noting that the maximum error is found in close proximity to the point <math display="inline">x_\alpha </math>.  This behavior is also expected since the local truncation error for irregular points is less accurate than for regular points. Finally, the convergence analysis using <math display="inline">N=10</math>, 20, 40, 80 and 160 confirms the fourth-order global convergence of the proposed method.
1145
1146
More details of the grid refinement analysis at <math display="inline">T=0.5</math> is presented in Table [[#table-4|4]] for two different interface point locations. As expected, a fourth-order method is obtained for both interfaces. We remark that the variation of the errors using <math display="inline">x_\alpha=0.63</math> is because the different <math display="inline">h_R/h</math> values resulting from the discretization.
1147
1148
<div id='img-7'></div>
1149
{| class="floating_imageSCP" style="text-align: center; border: 1px solid #BBB; margin: 1em auto; width: 100%;max-width: 100%;"
1150
|-
1151
|[[Image:Review_499745022132-Fig07_Heat_Ex5_3D.png|594px|Numerical solution and absolute error of Example 5 using N = 40, x_α=0.4 for tퟄ[0,0.5].]]
1152
|- style="text-align: center; font-size: 75%;"
1153
| colspan="1" | '''Figure 7:''' Numerical solution and absolute error of Example 5 using <math>N = 40</math>, <math>x_\alpha=0.4</math> for <math>t\in [0,0.5]</math>.
1154
|}
1155
<div id='img-8'></div>
1156
{| class="floating_imageSCP" style="text-align: center; border: 1px solid #BBB; margin: 1em auto; width: 100%;max-width: 100%;"
1157
|-
1158
|[[Image:Review_499745022132-Fig08_Heat_Ex5_0p40.png|594px|Numerical results at final time simulation T=0.5 and x_α=0.4 of Example 5.]]
1159
|- style="text-align: center; font-size: 75%;"
1160
| colspan="1" | '''Figure 8:''' Numerical results at final time simulation <math>T=0.5</math> and <math>x_\alpha=0.4</math> of Example 5.
1161
|}
1162
<div id='img-9'></div>
1163
{| class="floating_imageSCP" style="text-align: center; border: 1px solid #BBB; margin: 1em auto; width: 100%;max-width: 100%;"
1164
|-
1165
|[[Image:Review_499745022132-Fig09_Heat_Ex5_0p63.png|594px|Numerical results at final time simulation T=0.5 and x_α=0.63 of Example 5.]]
1166
|- style="text-align: center; font-size: 75%;"
1167
| colspan="1" | '''Figure 9:''' Numerical results at final time simulation <math>T=0.5</math> and <math>x_\alpha=0.63</math> of Example 5.
1168
|}
1169
1170
{|  class="floating_tableSCP" style="text-align: left; margin: 1em auto;border-top: 2px solid;border-bottom: 2px solid;min-width:99%;"
1171
|+ style="font-size: 75%;" |<span id='table-4'></span>'''Table. 4''' Convergence analysis of Example 5 using the IFD-IIM for the heat equation with a discontinuous solution.
1172
!
1173
! colspan="4" |<math display="inline">x_\alpha=0.4</math>
1174
! colspan="4" |<math display="inline">x_\alpha=0.63</math>
1175
|-
1176
! <math display="inline">N</math>  
1177
! <math display="inline">L_\infty </math>-norm 
1178
!  Order 
1179
! <math display="inline">L_2</math>-norm 
1180
!  Order
1181
! <math display="inline">L_\infty </math>-norm 
1182
!  Order 
1183
! <math display="inline">L_2</math>-norm 
1184
!  Order
1185
|-
1186
| 10 
1187
|  1.11e-07 
1188
|  &#8211;-   
1189
|   6.52e-08 
1190
|  &#8211;-  
1191
|  7.57e-08 
1192
|  &#8211;-   
1193
|  4.49e-08 
1194
|  &#8211;-   
1195
|-
1196
| 20 
1197
|  6.90e-09 
1198
|  4.01  
1199
|   4.01e-09 
1200
|  4.02 
1201
|  3.75e-09 
1202
|  4.34  
1203
|  2.25e-09 
1204
|  4.32  
1205
|-
1206
| 40 
1207
|  4.29e-10 
1208
|  4.00  
1209
|   2.49e-10 
1210
|  4.01 
1211
|  3.58e-10 
1212
|  3.39  
1213
|  2.09e-10 
1214
|  4.43  
1215
|-
1216
| 80 
1217
|  2.68e-11 
1218
|  4.00  
1219
|   1.55e-11 
1220
|  4.00 
1221
|  1.53e-11 
1222
|  4.55  
1223
|  8.93e-12 
1224
|  4.55  
1225
|-
1226
| 160 
1227
|  1.63e-12 
1228
|  4.03  
1229
|   9.39e-13 
1230
|  4.04 
1231
|  1.35e-12 
1232
|  3.50  
1233
|  7.82e-13 
1234
|  3.51  
1235
|-
1236
| LSM 
1237
|    
1238
| '''4.01''' 
1239
| 
1240
|  '''4.02''' 
1241
| 
1242
|  '''3.95''' 
1243
| 
1244
|  '''3.96'''
1245
|-
1246
|}
1247
From Table&nbsp;[[#table-5|5]], we can find the results when the time step is chosen as <math display="inline">\Delta t = h</math>. As expected, the proposed IFD-IIM is stable and has two-order convergence either we take a second- or fourth-order approximation in space. We remark that this is a property of the selected time integration method. For instance, similar findings as Table&nbsp;[[#table-5|5]] can be obtained for smooth solutions.
1248
1249
1250
{|  class="floating_tableSCP" style="text-align: left; margin: 1em auto;border-top: 2px solid;border-bottom: 2px solid;min-width:99%;"
1251
|+ style="font-size: 75%;" |<span id='table-5'></span>'''Table. 5''' Convergence analysis of Example 5 testing the heat equation with <math>\Delta t=h</math>.
1252
!
1253
! colspan="4" |<math display="inline">b=0</math>
1254
! colspan="4" |<math display="inline">b=1/12</math>
1255
|-
1256
! <math display="inline">N</math>  
1257
! <math display="inline">L_\infty </math>-norm 
1258
!  Order 
1259
! <math display="inline">L_2</math>-norm 
1260
!  Order
1261
! <math display="inline">L_\infty </math>-norm 
1262
!  Order 
1263
! <math display="inline">L_2</math>-norm 
1264
!  Order
1265
|-
1266
| 10 
1267
|  2.94e-04 
1268
|  &#8211;-   
1269
|   1.87e-04 
1270
|  &#8211;-  
1271
|  3.78e-05 
1272
|  &#8211;-   
1273
|   2.67e-05 
1274
|  &#8211;-   
1275
|-
1276
| 20 
1277
|  8.53e-05 
1278
|  1.78  
1279
|   4.85e-05 
1280
|  1.95 
1281
|  1.03e-05 
1282
|  1.87  
1283
|   7.22e-06 
1284
|  1.89  
1285
|-
1286
| 40 
1287
|  2.11e-05 
1288
|  2.01  
1289
|   1.26e-05 
1290
|  1.94 
1291
|  2.74e-06 
1292
|  1.91  
1293
|   1.92e-06 
1294
|  1.91  
1295
|-
1296
| 80 
1297
|  5.31e-06 
1298
|  1.99  
1299
|   3.15e-06 
1300
|  2.00 
1301
|  6.91e-07 
1302
|  1.99  
1303
|   4.83e-07 
1304
|  1.99  
1305
|-
1306
| 160 
1307
|  1.34e-06 
1308
|  1.99  
1309
|   7.83e-07 
1310
|  2.00 
1311
|  1.72e-07 
1312
|  2.00  
1313
|   1.21e-07 
1314
|  2.00  
1315
|-
1316
| LSM 
1317
|    
1318
| '''1.96''' 
1319
| 
1320
|  '''1.97''' 
1321
| 
1322
|  '''1.95''' 
1323
| 
1324
|  '''1.95'''
1325
|-
1326
|}
1327
1328
===6.3 Example 6. Heat equation with a general discontinuous solution===
1329
1330
Finally, Example 6 investigates the capability to solve a heat interface problem with a general discontinuous solution. For this problem, we slightly modified the previous example such that the exact solution of the heat conduction problem is given by
1331
1332
<span id="eq-49"></span>
1333
{| class="formulaSCP" style="width: 100%; text-align: left;" 
1334
|-
1335
| 
1336
{| style="text-align: left; margin:auto;width: 100%;" 
1337
|-
1338
| style="text-align: center;" | <math>u(x) = \begin{cases}\sin (2\pi x)e^{-t}, & x < x_{\alpha },\\ \cos (2\pi x)e^{-t}, & x > x_{\alpha }. \end{cases}  </math>
1339
|}
1340
| style="width: 5px;text-align: right;white-space: nowrap;" | (49)
1341
|}
1342
1343
Here, the source term <math display="inline">f</math> is a general function that varies both in time and space. It is directly derived from equation [[#eq-27|(27)]] as well as the exact solution [[#eq-49|(49)]]. Furthermore, the exact solution is utilized to specify the boundary condition, initial condition, and all jumps contributions.
1344
1345
In Fig.&nbsp;[[#img-10|10]], we depict the temporal evolution of the numerical solution and absolute errors using parameters <math display="inline">N=40</math> and <math display="inline">x_\alpha=0.4</math>. It is noteworthy that the behavior of the solution differs from the previous example. More in-depth analysis of the results at <math display="inline">T = 0.5</math> are illustrated in Figs.&nbsp;[[#img-11|11]] and [[#img-12|12]], corresponding to values of <math display="inline">x_\alpha=0.4</math> and <math display="inline">x_\alpha=0.63</math>, respectively. First, the numerical solution is accurately approximated using the proposed implicit method for <math display="inline">N=40</math>, regardless of the interface locations. It is worth noting that the maximum error for <math display="inline">x_\alpha=0.63</math> is concentrated near to this point; however, this is not observed for <math display="inline">x_\alpha=0.4</math>. This difference in behavior can be attributed to the interplay between the interface location (<math display="inline">h_R/h=1</math> and <math display="inline">x_\alpha=0.4</math>) and the non-zero right-hand side values, which contribute to the local truncation errors. Grid refinement analyses are also provided in these figures using <math display="inline">N=10</math>, 20, 40, 80 and 160. As anticipated, the IFD-IIM method demonstrates fourth-order accuracy, a validation that is further detailed in Table [[#table-6|6]].
1346
1347
<div id='img-10'></div>
1348
{| class="floating_imageSCP" style="text-align: center; border: 1px solid #BBB; margin: 1em auto; width: 100%;max-width: 100%;"
1349
|-
1350
|[[Image:Review_499745022132-Fig10_Heat_Ex6_3D.png|594px|Numerical solution and absolute error of Example 6 using N = 40, x_α=0.4 for tퟄ[0,0.5].]]
1351
|- style="text-align: center; font-size: 75%;"
1352
| colspan="1" | '''Figure 10:''' Numerical solution and absolute error of Example 6 using <math>N = 40</math>, <math>x_\alpha=0.4</math> for <math>t\in [0,0.5]</math>.
1353
|}
1354
<div id='img-11'></div>
1355
{| class="floating_imageSCP" style="text-align: center; border: 1px solid #BBB; margin: 1em auto; width: 100%;max-width: 100%;"
1356
|-
1357
|[[Image:Review_499745022132-Fig11_Heat_Ex6_0p40.png|594px|Numerical results at final time simulation T=0.5 and x_α=0.4 of Example 6. ]]
1358
|- style="text-align: center; font-size: 75%;"
1359
| colspan="1" | '''Figure 11:''' Numerical results at final time simulation <math>T=0.5</math> and <math>x_\alpha=0.4</math> of Example 6. 
1360
|}
1361
<div id='img-12'></div>
1362
{| class="floating_imageSCP" style="text-align: center; border: 1px solid #BBB; margin: 1em auto; width: 100%;max-width: 100%;"
1363
|-
1364
|[[Image:Review_499745022132-Fig12_Heat_Ex6_0p63.png|594px|Numerical results at final time simulation T=0.5 and x_α=0.63 of Example 6.]]
1365
|- style="text-align: center; font-size: 75%;"
1366
| colspan="1" | '''Figure 12:''' Numerical results at final time simulation <math>T=0.5</math> and <math>x_\alpha=0.63</math> of Example 6.
1367
|}
1368
1369
{|  class="floating_tableSCP" style="text-align: left; margin: 1em auto;border-top: 2px solid;border-bottom: 2px solid;min-width:99%;"
1370
|+ style="font-size: 75%;" |<span id='table-6'></span>'''Table. 6''' Convergence analysis of Example 6 using the IFD-IIM for the heat equation with a general discontinuous solution.
1371
!
1372
! colspan="4" |<math display="inline">x_\alpha=0.4</math>
1373
! colspan="4" |<math display="inline">x_\alpha=0.63</math>
1374
|-
1375
! <math display="inline">N</math>  
1376
! <math display="inline">L_\infty </math>-norm 
1377
!  Order 
1378
! <math display="inline">L_2</math>-norm 
1379
!  Order
1380
! <math display="inline">L_\infty </math>-norm 
1381
!  Order 
1382
! <math display="inline">L_2</math>-norm 
1383
!  Order
1384
|-
1385
| 10 
1386
|  3.91e-04 
1387
|  &#8211;-   
1388
|   2.18e-04 
1389
|  &#8211;-  
1390
|  4.32e-04 
1391
|  &#8211;-   
1392
|  2.43e-04 
1393
|  &#8211;-   
1394
|-
1395
| 20 
1396
|  2.50e-05 
1397
|  3.97  
1398
|   1.34e-05 
1399
|  4.02 
1400
|  2.48e-05 
1401
|  4.12  
1402
|  1.45e-05 
1403
|  4.07  
1404
|-
1405
| 40 
1406
|  1.56e-06 
1407
|  4.00  
1408
|   8.37e-07 
1409
|  4.01 
1410
|  2.38e-06 
1411
|  3.38  
1412
|  1.12e-06 
1413
|  3.69  
1414
|-
1415
| 80 
1416
|  9.72e-08 
1417
|  4.00  
1418
|   5.22e-08 
1419
|  4.00 
1420
|  9.48e-08 
1421
|  4.65  
1422
|  5.56e-08 
1423
|  4.34  
1424
|-
1425
| 160 
1426
|  6.08e-09 
1427
|  4.03  
1428
|   3.26e-09 
1429
|  4.00 
1430
|  9.29e-09 
1431
|  3.35  
1432
|  4.37e-09 
1433
|  3.69  
1434
|-
1435
| LSM 
1436
|    
1437
| '''4.00''' 
1438
| 
1439
|  '''4.01''' 
1440
| 
1441
|  '''3.90''' 
1442
| 
1443
|  '''3.95'''
1444
|-
1445
|}
1446
1447
==7 Conclusions==
1448
1449
This work serves as the general foundation for addressing high-order IIMs to solve interface problems, facilitating comprehensive investigations into this theoretical framework. Here, we present a fourth-order finite-difference scheme for approximating the second-order derivative of real-valued continuous and discontinuous functions. This method combines an implicit formulation with the IIM. Our proposed scheme employs a three-point stencil, achieving different accuracy at regular and irregular points. To illustrate the effectiveness of the proposed IFD-IIM approach, we applied it to solve the one-dimensional Poisson equation and the heat conduction equation. The global accuracy of the fourth order was demonstrated using several numerical examples for both equations. Hence, this study establishes a general strategy for high-order IIMs, enabling their application to elliptic and time-evolving problems in several dimensions. Additionally, the implicit procedure lends itself to developing of higher-order numerical schemes based on the IIM, including sixth-order methods.
1450
1451
==Acknowledgments==
1452
1453
This work was partially supported by CONAHCYT under the program ''Investigadoras e Investigadores por México''. We also thanks the facilities provided by the ''Facultad de Matemáticas (UADY)'' for the development of this work.
1454
1455
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