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.doctrees/3_numerical.doctree

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3_numerical.html

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First, compute the intermediate stage vectors:</p>
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<div class="math notranslate nohighlight">
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\[\mathbf{k}_i =
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\mathbf{u} \Bigl( \mathbf{x}_n + \Delta t \sum_{j=1}^{i-1} a_{ij}\,\mathbf{k}_j,\,
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\mathbf{u} \Bigl( \mathbf{x}_n + \sigma\,\Delta t \sum_{j=1}^{i-1} a_{ij}\,\mathbf{k}_j,\,
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t_n + c_i \Delta t \Bigr),
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\qquad i = 1, 2, \dots, s,\]</div>
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<p>and then update the solution:</p>
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<div class="math notranslate nohighlight">
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\[\mathbf{x}_{n+1} =
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\mathbf{x}_n + \Delta t \sum_{i=1}^s b_i\,\mathbf{k}_i.\]</div>
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\mathbf{x}_n + \sigma\,\Delta t \sum_{i=1}^s b_i\,\mathbf{k}_i.\]</div>
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<p>Here, the boldface stage variables <span class="math notranslate nohighlight">\(\mathbf{k}_i\)</span> represent intermediate slope estimates.</p>
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<p><strong>Second-Order Runge-Kutta (RK2, Heun’s)</strong></p>
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<p>Heun’s <code class="docutils literal notranslate"><span class="pre">RK2</span></code> method attains second-order accuracy by combining predictor and corrector slopes:</p>

_sources/3_numerical.rst.txt

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@@ -51,7 +51,7 @@ First, compute the intermediate stage vectors:
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.. math::
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\mathbf{k}_i =
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\mathbf{u} \Bigl( \mathbf{x}_n + \Delta t \sum_{j=1}^{i-1} a_{ij}\,\mathbf{k}_j,\,
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\mathbf{u} \Bigl( \mathbf{x}_n + \sigma\,\Delta t \sum_{j=1}^{i-1} a_{ij}\,\mathbf{k}_j,\,
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t_n + c_i \Delta t \Bigr),
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\qquad i = 1, 2, \dots, s,
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.. math::
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\mathbf{x}_{n+1} =
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\mathbf{x}_n + \Delta t \sum_{i=1}^s b_i\,\mathbf{k}_i.
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\mathbf{x}_n + \sigma\,\Delta t \sum_{i=1}^s b_i\,\mathbf{k}_i.
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Here, the boldface stage variables :math:`\mathbf{k}_i` represent intermediate slope estimates.
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