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<title>Quantum Monte Carlo</title>
@ -329,151 +329,151 @@ for the JavaScript code in this tag.
<h2>Table of Contents</h2>
<div id="text-table-of-contents">
<ul>
<li><a href="#org49d04ba">1. Introduction</a></li>
<li><a href="#org829df65">2. Numerical evaluation of the energy</a>
<li><a href="#org8dcaa4e">1. Introduction</a></li>
<li><a href="#orgf2d601e">2. Numerical evaluation of the energy</a>
<ul>
<li><a href="#org05487b8">2.1. Local energy</a>
<li><a href="#org0b86853">2.1. Local energy</a>
<ul>
<li><a href="#org0a1896f">2.1.1. Exercise 1</a>
<li><a href="#orgb4f1dcb">2.1.1. Exercise 1</a>
<ul>
<li><a href="#orgeac8364">2.1.1.1. Solution</a></li>
<li><a href="#orge1171f3">2.1.1.1. Solution</a></li>
</ul>
</li>
<li><a href="#org54f52bf">2.1.2. Exercise 2</a>
<li><a href="#org805f102">2.1.2. Exercise 2</a>
<ul>
<li><a href="#orgec4496f">2.1.2.1. Solution</a></li>
<li><a href="#orge839f82">2.1.2.1. Solution</a></li>
</ul>
</li>
<li><a href="#orgb2b2470">2.1.3. Exercise 3</a>
<li><a href="#org30a89b7">2.1.3. Exercise 3</a>
<ul>
<li><a href="#orgc9384b2">2.1.3.1. Solution</a></li>
<li><a href="#org37f3a90">2.1.3.1. Solution</a></li>
</ul>
</li>
<li><a href="#org27c82a8">2.1.4. Exercise 4</a>
<li><a href="#org8a71cb9">2.1.4. Exercise 4</a>
<ul>
<li><a href="#org3488e51">2.1.4.1. Solution</a></li>
<li><a href="#org3127c46">2.1.4.1. Solution</a></li>
</ul>
</li>
<li><a href="#orgb470382">2.1.5. Exercise 5</a>
<li><a href="#org5ae05ca">2.1.5. Exercise 5</a>
<ul>
<li><a href="#org95fe0ba">2.1.5.1. Solution</a></li>
<li><a href="#orgde68619">2.1.5.1. Solution</a></li>
</ul>
</li>
</ul>
</li>
<li><a href="#org3c5c95d">2.2. Plot of the local energy along the \(x\) axis</a>
<li><a href="#org6b6a61c">2.2. Plot of the local energy along the \(x\) axis</a>
<ul>
<li><a href="#orga2b9bcf">2.2.1. Exercise</a>
<li><a href="#orga530380">2.2.1. Exercise</a>
<ul>
<li><a href="#org93945d1">2.2.1.1. Solution</a></li>
<li><a href="#orgcd9f1bf">2.2.1.1. Solution</a></li>
</ul>
</li>
</ul>
</li>
<li><a href="#org2555573">2.3. Numerical estimation of the energy</a>
<li><a href="#org2387d29">2.3. Numerical estimation of the energy</a>
<ul>
<li><a href="#org102c578">2.3.1. Exercise</a>
<li><a href="#orgde278da">2.3.1. Exercise</a>
<ul>
<li><a href="#org4da0f5c">2.3.1.1. Solution</a></li>
<li><a href="#org73954f7">2.3.1.1. Solution</a></li>
</ul>
</li>
</ul>
</li>
<li><a href="#org74ce38e">2.4. Variance of the local energy</a>
<li><a href="#orgd0c5f25">2.4. Variance of the local energy</a>
<ul>
<li><a href="#org0510da2">2.4.1. Exercise (optional)</a>
<li><a href="#orgdd8878b">2.4.1. Exercise (optional)</a>
<ul>
<li><a href="#org1c5cb68">2.4.1.1. Solution</a></li>
<li><a href="#org874aece">2.4.1.1. Solution</a></li>
</ul>
</li>
<li><a href="#org499a5a7">2.4.2. Exercise</a>
<li><a href="#org55c03ac">2.4.2. Exercise</a>
<ul>
<li><a href="#org93fe370">2.4.2.1. Solution</a></li>
<li><a href="#orgff8da50">2.4.2.1. Solution</a></li>
</ul>
</li>
</ul>
</li>
</ul>
</li>
<li><a href="#org6a0028a">3. Variational Monte Carlo</a>
<li><a href="#org500fc9e">3. Variational Monte Carlo</a>
<ul>
<li><a href="#org8b03841">3.1. Computation of the statistical error</a>
<li><a href="#org1395f72">3.1. Computation of the statistical error</a>
<ul>
<li><a href="#org5bcb81b">3.1.1. Exercise</a>
<li><a href="#orgbf3b7c1">3.1.1. Exercise</a>
<ul>
<li><a href="#orgc97d0a8">3.1.1.1. Solution</a></li>
<li><a href="#org96a3dcd">3.1.1.1. Solution</a></li>
</ul>
</li>
</ul>
</li>
<li><a href="#org1d4a893">3.2. Uniform sampling in the box</a>
<li><a href="#org6f903d5">3.2. Uniform sampling in the box</a>
<ul>
<li><a href="#orgc78cc2c">3.2.1. Exercise</a>
<li><a href="#orgd5d2e4f">3.2.1. Exercise</a>
<ul>
<li><a href="#orgf1caad9">3.2.1.1. Solution</a></li>
<li><a href="#orge0a3bca">3.2.1.1. Solution</a></li>
</ul>
</li>
</ul>
</li>
<li><a href="#org9ac37db">3.3. Metropolis sampling with \(\Psi^2\)</a>
<li><a href="#org31acf84">3.3. Metropolis sampling with \(\Psi^2\)</a>
<ul>
<li><a href="#org5ca4e2c">3.3.1. Exercise</a>
<li><a href="#org6d54039">3.3.1. Exercise</a>
<ul>
<li><a href="#orgde750dd">3.3.1.1. Solution</a></li>
<li><a href="#org8084209">3.3.1.1. Solution</a></li>
</ul>
</li>
</ul>
</li>
<li><a href="#org9cb319e">3.4. Gaussian random number generator</a></li>
<li><a href="#orgc52c7d5">3.5. Generalized Metropolis algorithm</a>
<li><a href="#org92d024f">3.4. Gaussian random number generator</a></li>
<li><a href="#org1a64e1d">3.5. Generalized Metropolis algorithm</a>
<ul>
<li><a href="#org4689b7c">3.5.1. Exercise 1</a>
<li><a href="#org97c1b29">3.5.1. Exercise 1</a>
<ul>
<li><a href="#org26c9d33">3.5.1.1. Solution</a></li>
<li><a href="#org19e85c9">3.5.1.1. Solution</a></li>
</ul>
</li>
<li><a href="#org3e39526">3.5.2. Exercise 2</a>
<li><a href="#orgaef93b5">3.5.2. Exercise 2</a>
<ul>
<li><a href="#orga3cf826">3.5.2.1. Solution</a></li>
<li><a href="#org17fe7c6">3.5.2.1. Solution</a></li>
</ul>
</li>
</ul>
</li>
</ul>
</li>
<li><a href="#orgebb7fc1">4. Diffusion Monte Carlo</a>
<li><a href="#org9f51d1e">4. Diffusion Monte Carlo</a>
<ul>
<li><a href="#org8cf0ab0">4.1. Schrödinger equation in imaginary time</a></li>
<li><a href="#org78a65a5">4.2. Diffusion and branching</a></li>
<li><a href="#org00d8981">4.3. Importance sampling</a>
<li><a href="#org344d9de">4.1. Schrödinger equation in imaginary time</a></li>
<li><a href="#org06862e7">4.2. Diffusion and branching</a></li>
<li><a href="#orgdf62087">4.3. Importance sampling</a>
<ul>
<li><a href="#org024b07c">4.3.1. Appendix : Details of the Derivation</a></li>
<li><a href="#org855e049">4.3.1. Appendix : Details of the Derivation</a></li>
</ul>
</li>
<li><a href="#orgce840bc">4.4. Fixed-node DMC energy</a></li>
<li><a href="#orga97437f">4.5. Pure Diffusion Monte Carlo (PDMC)</a></li>
<li><a href="#org54d9e47">4.6. Hydrogen atom</a>
<li><a href="#org6fbf6b7">4.4. Fixed-node DMC energy</a></li>
<li><a href="#org4379250">4.5. Pure Diffusion Monte Carlo (PDMC)</a></li>
<li><a href="#org3a30f06">4.6. Hydrogen atom</a>
<ul>
<li><a href="#org77c2d07">4.6.1. Exercise</a>
<li><a href="#orgba6aa2f">4.6.1. Exercise</a>
<ul>
<li><a href="#orgc3fb998">4.6.1.1. Solution</a></li>
<li><a href="#org2311033">4.6.1.1. Solution</a></li>
</ul>
</li>
</ul>
</li>
<li><a href="#orgb88b04d">4.7. <span class="todo TODO">TODO</span> H<sub>2</sub></a></li>
<li><a href="#org81121c2">4.7. <span class="todo TODO">TODO</span> H<sub>2</sub></a></li>
</ul>
</li>
<li><a href="#org622ff55">5. <span class="todo TODO">TODO</span> <code>[0/3]</code> Last things to do</a></li>
<li><a href="#orgf5ad8c9">5. <span class="todo TODO">TODO</span> <code>[0/3]</code> Last things to do</a></li>
</ul>
</div>
</div>
<div id="outline-container-org49d04ba" class="outline-2">
<h2 id="org49d04ba"><span class="section-number-2">1</span> Introduction</h2>
<div id="outline-container-org8dcaa4e" class="outline-2">
<h2 id="org8dcaa4e"><span class="section-number-2">1</span> Introduction</h2>
<div class="outline-text-2" id="text-1">
<p>
This web site contains the QMC tutorial of the 2021 LTTC winter school
This website contains the QMC tutorial of the 2021 LTTC winter school
<a href="https://www.irsamc.ups-tlse.fr/lttc/Luchon">Tutorials in Theoretical Chemistry</a>.
</p>
@ -487,7 +487,8 @@ computes a statistical estimate of the expectation value of the energy
associated with a given wave function, and apply this approach to the
hydrogen atom.
Finally, we present the diffusion Monte Carlo (DMC) method which
we use here to estimate the exact energy of the hydrogen atom and of the H<sub>2</sub> molecule.
we use here to estimate the exact energy of the hydrogen atom and of the H<sub>2</sub> molecule,
starting from an approximate wave function.
</p>
<p>
@ -510,11 +511,11 @@ coordinates, etc).
</div>
</div>
<div id="outline-container-org829df65" class="outline-2">
<h2 id="org829df65"><span class="section-number-2">2</span> Numerical evaluation of the energy</h2>
<div id="outline-container-orgf2d601e" class="outline-2">
<h2 id="orgf2d601e"><span class="section-number-2">2</span> Numerical evaluation of the energy</h2>
<div class="outline-text-2" id="text-2">
<p>
In this section we consider the Hydrogen atom with the following
In this section, we consider the hydrogen atom with the following
wave function:
</p>
@ -525,7 +526,7 @@ wave function:
</p>
<p>
We will first verify that, for a given value of \(a\), \(\Psi\) is an
We will first verify that, for a particular value of \(a\), \(\Psi\) is an
eigenfunction of the Hamiltonian
</p>
@ -536,7 +537,7 @@ eigenfunction of the Hamiltonian
</p>
<p>
To do that, we will check if the local energy, defined as
To do that, we will compute the local energy, defined as
</p>
<p>
@ -546,31 +547,11 @@ To do that, we will check if the local energy, defined as
</p>
<p>
is constant.
</p>
<p>
The probabilistic <i>expected value</i> of an arbitrary function \(f(x)\)
with respect to a probability density function \(p(x)\) is given by
and check whether it is constant.
</p>
<p>
\[ \langle f \rangle_p = \int_{-\infty}^\infty p(x)\, f(x)\,dx. \]
</p>
<p>
Recall that a probability density function \(p(x)\) is non-negative
and integrates to one:
</p>
<p>
\[ \int_{-\infty}^\infty p(x)\,dx = 1. \]
</p>
<p>
The electronic energy of a system is the expectation value of the
In general, the electronic energy of a system, \(E\), can be rewritten as the expectation value of the
local energy \(E(\mathbf{r})\) with respect to the 3N-dimensional
electron density given by the square of the wave function:
</p>
@ -580,12 +561,40 @@ E & = & \frac{\langle \Psi| \hat{H} | \Psi\rangle}{\langle \Psi |\Psi \rangle}
= \frac{\int \Psi(\mathbf{r})\, \hat{H} \Psi(\mathbf{r})\, d\mathbf{r}}{\int \left[\Psi(\mathbf{r}) \right]^2 d\mathbf{r}} \\
& = & \frac{\int \left[\Psi(\mathbf{r})\right]^2\, \frac{\hat{H} \Psi(\mathbf{r})}{\Psi(\mathbf{r})}\,d\mathbf{r}}{\int \left[\Psi(\mathbf{r}) \right]^2 d\mathbf{r}}
= \frac{\int \left[\Psi(\mathbf{r})\right]^2\, E_L(\mathbf{r})\,d\mathbf{r}}{\int \left[\Psi(\mathbf{r}) \right]^2 d\mathbf{r}}
= \langle E_L \rangle_{\Psi^2}
= \langle E_L \rangle_{\Psi^2}\,,
\end{eqnarray*}
<p>
where \(\mathbf{r}\) is the vector of the 3N-dimensional electronic coordinates (\(N=1\) for the hydrogen atom).
</p>
<p>
For a small number of dimensions, one can compute \(E\) by evaluating the integrals on a grid. However,
</p>
<p>
The probabilistic <i>expected value</i> of an arbitrary function \(f(x)\)
with respect to a probability density function \(p(x)\) is given by
</p>
<p>
\[ \langle f \rangle_p = \int_{-\infty}^\infty p(x)\, f(x)\,dx, \]
</p>
<p>
where probability density function \(p(x)\) is non-negative
and integrates to one:
</p>
<p>
\[ \int_{-\infty}^\infty p(x)\,dx = 1. \]
</p>
</div>
<div id="outline-container-org05487b8" class="outline-3">
<h3 id="org05487b8"><span class="section-number-3">2.1</span> Local energy</h3>
<div id="outline-container-org0b86853" class="outline-3">
<h3 id="org0b86853"><span class="section-number-3">2.1</span> Local energy</h3>
<div class="outline-text-3" id="text-2-1">
<p>
Write all the functions of this section in a single file :
@ -608,8 +617,8 @@ to catch the error.
</div>
</div>
<div id="outline-container-org0a1896f" class="outline-4">
<h4 id="org0a1896f"><span class="section-number-4">2.1.1</span> Exercise 1</h4>
<div id="outline-container-orgb4f1dcb" class="outline-4">
<h4 id="orgb4f1dcb"><span class="section-number-4">2.1.1</span> Exercise 1</h4>
<div class="outline-text-4" id="text-2-1-1">
<div class="exercise">
<p>
@ -653,8 +662,8 @@ and returns the potential.
</div>
</div>
<div id="outline-container-orgeac8364" class="outline-5">
<h5 id="orgeac8364"><span class="section-number-5">2.1.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div id="outline-container-orge1171f3" class="outline-5">
<h5 id="orge1171f3"><span class="section-number-5">2.1.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div class="outline-text-5" id="text-2-1-1-1">
<p>
<b>Python</b>
@ -694,8 +703,8 @@ and returns the potential.
</div>
</div>
<div id="outline-container-org54f52bf" class="outline-4">
<h4 id="org54f52bf"><span class="section-number-4">2.1.2</span> Exercise 2</h4>
<div id="outline-container-org805f102" class="outline-4">
<h4 id="org805f102"><span class="section-number-4">2.1.2</span> Exercise 2</h4>
<div class="outline-text-4" id="text-2-1-2">
<div class="exercise">
<p>
@ -730,8 +739,8 @@ input arguments, and returns a scalar.
</div>
</div>
<div id="outline-container-orgec4496f" class="outline-5">
<h5 id="orgec4496f"><span class="section-number-5">2.1.2.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div id="outline-container-orge839f82" class="outline-5">
<h5 id="orge839f82"><span class="section-number-5">2.1.2.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div class="outline-text-5" id="text-2-1-2-1">
<p>
<b>Python</b>
@ -758,8 +767,8 @@ input arguments, and returns a scalar.
</div>
</div>
<div id="outline-container-orgb2b2470" class="outline-4">
<h4 id="orgb2b2470"><span class="section-number-4">2.1.3</span> Exercise 3</h4>
<div id="outline-container-org30a89b7" class="outline-4">
<h4 id="org30a89b7"><span class="section-number-4">2.1.3</span> Exercise 3</h4>
<div class="outline-text-4" id="text-2-1-3">
<div class="exercise">
<p>
@ -840,8 +849,8 @@ So the local kinetic energy is
</div>
</div>
<div id="outline-container-orgc9384b2" class="outline-5">
<h5 id="orgc9384b2"><span class="section-number-5">2.1.3.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div id="outline-container-org37f3a90" class="outline-5">
<h5 id="org37f3a90"><span class="section-number-5">2.1.3.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div class="outline-text-5" id="text-2-1-3-1">
<p>
<b>Python</b>
@ -882,8 +891,8 @@ So the local kinetic energy is
</div>
</div>
<div id="outline-container-org27c82a8" class="outline-4">
<h4 id="org27c82a8"><span class="section-number-4">2.1.4</span> Exercise 4</h4>
<div id="outline-container-org8a71cb9" class="outline-4">
<h4 id="org8a71cb9"><span class="section-number-4">2.1.4</span> Exercise 4</h4>
<div class="outline-text-4" id="text-2-1-4">
<div class="exercise">
<p>
@ -926,8 +935,8 @@ local kinetic energy.
</div>
</div>
<div id="outline-container-org3488e51" class="outline-5">
<h5 id="org3488e51"><span class="section-number-5">2.1.4.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div id="outline-container-org3127c46" class="outline-5">
<h5 id="org3127c46"><span class="section-number-5">2.1.4.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div class="outline-text-5" id="text-2-1-4-1">
<p>
<b>Python</b>
@ -957,8 +966,8 @@ local kinetic energy.
</div>
</div>
<div id="outline-container-orgb470382" class="outline-4">
<h4 id="orgb470382"><span class="section-number-4">2.1.5</span> Exercise 5</h4>
<div id="outline-container-org5ae05ca" class="outline-4">
<h4 id="org5ae05ca"><span class="section-number-4">2.1.5</span> Exercise 5</h4>
<div class="outline-text-4" id="text-2-1-5">
<div class="exercise">
<p>
@ -968,8 +977,8 @@ Find the theoretical value of \(a\) for which \(\Psi\) is an eigenfunction of \(
</div>
</div>
<div id="outline-container-org95fe0ba" class="outline-5">
<h5 id="org95fe0ba"><span class="section-number-5">2.1.5.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div id="outline-container-orgde68619" class="outline-5">
<h5 id="orgde68619"><span class="section-number-5">2.1.5.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div class="outline-text-5" id="text-2-1-5-1">
\begin{eqnarray*}
E &=& \frac{\hat{H} \Psi}{\Psi} = - \frac{1}{2} \frac{\Delta \Psi}{\Psi} -
@ -989,8 +998,8 @@ equal to -0.5 atomic units.
</div>
</div>
<div id="outline-container-org3c5c95d" class="outline-3">
<h3 id="org3c5c95d"><span class="section-number-3">2.2</span> Plot of the local energy along the \(x\) axis</h3>
<div id="outline-container-org6b6a61c" class="outline-3">
<h3 id="org6b6a61c"><span class="section-number-3">2.2</span> Plot of the local energy along the \(x\) axis</h3>
<div class="outline-text-3" id="text-2-2">
<div class="note">
<p>
@ -1001,8 +1010,8 @@ choose a grid which does not contain the origin.
</div>
</div>
<div id="outline-container-orga2b9bcf" class="outline-4">
<h4 id="orga2b9bcf"><span class="section-number-4">2.2.1</span> Exercise</h4>
<div id="outline-container-orga530380" class="outline-4">
<h4 id="orga530380"><span class="section-number-4">2.2.1</span> Exercise</h4>
<div class="outline-text-4" id="text-2-2-1">
<div class="exercise">
<p>
@ -1085,8 +1094,8 @@ plot './data' index 0 using 1:2 with lines title 'a=0.1', \
</div>
</div>
<div id="outline-container-org93945d1" class="outline-5">
<h5 id="org93945d1"><span class="section-number-5">2.2.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div id="outline-container-orgcd9f1bf" class="outline-5">
<h5 id="orgcd9f1bf"><span class="section-number-5">2.2.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div class="outline-text-5" id="text-2-2-1-1">
<p>
<b>Python</b>
@ -1161,8 +1170,8 @@ plt.savefig(<span style="color: #8b2252;">"plot_py.png"</span>)
</div>
</div>
<div id="outline-container-org2555573" class="outline-3">
<h3 id="org2555573"><span class="section-number-3">2.3</span> Numerical estimation of the energy</h3>
<div id="outline-container-org2387d29" class="outline-3">
<h3 id="org2387d29"><span class="section-number-3">2.3</span> Numerical estimation of the energy</h3>
<div class="outline-text-3" id="text-2-3">
<p>
If the space is discretized in small volume elements \(\mathbf{r}_i\)
@ -1192,8 +1201,8 @@ The energy is biased because:
</div>
<div id="outline-container-org102c578" class="outline-4">
<h4 id="org102c578"><span class="section-number-4">2.3.1</span> Exercise</h4>
<div id="outline-container-orgde278da" class="outline-4">
<h4 id="orgde278da"><span class="section-number-4">2.3.1</span> Exercise</h4>
<div class="outline-text-4" id="text-2-3-1">
<div class="exercise">
<p>
@ -1262,8 +1271,8 @@ To compile the Fortran and run it:
</div>
</div>
<div id="outline-container-org4da0f5c" class="outline-5">
<h5 id="org4da0f5c"><span class="section-number-5">2.3.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div id="outline-container-org73954f7" class="outline-5">
<h5 id="org73954f7"><span class="section-number-5">2.3.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div class="outline-text-5" id="text-2-3-1-1">
<p>
<b>Python</b>
@ -1378,8 +1387,8 @@ a = 2.0000000000000000 E = -8.0869806678448772E-002
</div>
</div>
<div id="outline-container-org74ce38e" class="outline-3">
<h3 id="org74ce38e"><span class="section-number-3">2.4</span> Variance of the local energy</h3>
<div id="outline-container-orgd0c5f25" class="outline-3">
<h3 id="orgd0c5f25"><span class="section-number-3">2.4</span> Variance of the local energy</h3>
<div class="outline-text-3" id="text-2-4">
<p>
The variance of the local energy is a functional of \(\Psi\)
@ -1406,8 +1415,8 @@ energy can be used as a measure of the quality of a wave function.
</p>
</div>
<div id="outline-container-org0510da2" class="outline-4">
<h4 id="org0510da2"><span class="section-number-4">2.4.1</span> Exercise (optional)</h4>
<div id="outline-container-orgdd8878b" class="outline-4">
<h4 id="orgdd8878b"><span class="section-number-4">2.4.1</span> Exercise (optional)</h4>
<div class="outline-text-4" id="text-2-4-1">
<div class="exercise">
<p>
@ -1418,8 +1427,8 @@ Prove that :
</div>
</div>
<div id="outline-container-org1c5cb68" class="outline-5">
<h5 id="org1c5cb68"><span class="section-number-5">2.4.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div id="outline-container-org874aece" class="outline-5">
<h5 id="org874aece"><span class="section-number-5">2.4.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div class="outline-text-5" id="text-2-4-1-1">
<p>
\(\bar{E} = \langle E \rangle\) is a constant, so \(\langle \bar{E}
@ -1438,8 +1447,8 @@ Prove that :
</div>
</div>
</div>
<div id="outline-container-org499a5a7" class="outline-4">
<h4 id="org499a5a7"><span class="section-number-4">2.4.2</span> Exercise</h4>
<div id="outline-container-org55c03ac" class="outline-4">
<h4 id="org55c03ac"><span class="section-number-4">2.4.2</span> Exercise</h4>
<div class="outline-text-4" id="text-2-4-2">
<div class="exercise">
<p>
@ -1513,8 +1522,8 @@ To compile and run:
</div>
</div>
<div id="outline-container-org93fe370" class="outline-5">
<h5 id="org93fe370"><span class="section-number-5">2.4.2.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div id="outline-container-orgff8da50" class="outline-5">
<h5 id="orgff8da50"><span class="section-number-5">2.4.2.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div class="outline-text-5" id="text-2-4-2-1">
<p>
<b>Python</b>
@ -1651,8 +1660,8 @@ a = 2.0000000000000000 E = -8.0869806678448772E-002 s2 = 1.8068814
</div>
</div>
<div id="outline-container-org6a0028a" class="outline-2">
<h2 id="org6a0028a"><span class="section-number-2">3</span> Variational Monte Carlo</h2>
<div id="outline-container-org500fc9e" class="outline-2">
<h2 id="org500fc9e"><span class="section-number-2">3</span> Variational Monte Carlo</h2>
<div class="outline-text-2" id="text-3">
<p>
Numerical integration with deterministic methods is very efficient
@ -1668,8 +1677,8 @@ interval.
</p>
</div>
<div id="outline-container-org8b03841" class="outline-3">
<h3 id="org8b03841"><span class="section-number-3">3.1</span> Computation of the statistical error</h3>
<div id="outline-container-org1395f72" class="outline-3">
<h3 id="org1395f72"><span class="section-number-3">3.1</span> Computation of the statistical error</h3>
<div class="outline-text-3" id="text-3-1">
<p>
To compute the statistical error, you need to perform \(M\)
@ -1709,8 +1718,8 @@ And the confidence interval is given by
</p>
</div>
<div id="outline-container-org5bcb81b" class="outline-4">
<h4 id="org5bcb81b"><span class="section-number-4">3.1.1</span> Exercise</h4>
<div id="outline-container-orgbf3b7c1" class="outline-4">
<h4 id="orgbf3b7c1"><span class="section-number-4">3.1.1</span> Exercise</h4>
<div class="outline-text-4" id="text-3-1-1">
<div class="exercise">
<p>
@ -1748,8 +1757,8 @@ input array.
</div>
</div>
<div id="outline-container-orgc97d0a8" class="outline-5">
<h5 id="orgc97d0a8"><span class="section-number-5">3.1.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div id="outline-container-org96a3dcd" class="outline-5">
<h5 id="org96a3dcd"><span class="section-number-5">3.1.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div class="outline-text-5" id="text-3-1-1-1">
<p>
<b>Python</b>
@ -1808,8 +1817,8 @@ input array.
</div>
</div>
<div id="outline-container-org1d4a893" class="outline-3">
<h3 id="org1d4a893"><span class="section-number-3">3.2</span> Uniform sampling in the box</h3>
<div id="outline-container-org6f903d5" class="outline-3">
<h3 id="org6f903d5"><span class="section-number-3">3.2</span> Uniform sampling in the box</h3>
<div class="outline-text-3" id="text-3-2">
<p>
We will now do our first Monte Carlo calculation to compute the
@ -1843,8 +1852,8 @@ compute the statistical error.
</p>
</div>
<div id="outline-container-orgc78cc2c" class="outline-4">
<h4 id="orgc78cc2c"><span class="section-number-4">3.2.1</span> Exercise</h4>
<div id="outline-container-orgd5d2e4f" class="outline-4">
<h4 id="orgd5d2e4f"><span class="section-number-4">3.2.1</span> Exercise</h4>
<div class="outline-text-4" id="text-3-2-1">
<div class="exercise">
<p>
@ -1944,8 +1953,8 @@ well as the index of the current step.
</div>
</div>
<div id="outline-container-orgf1caad9" class="outline-5">
<h5 id="orgf1caad9"><span class="section-number-5">3.2.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div id="outline-container-orge0a3bca" class="outline-5">
<h5 id="orge0a3bca"><span class="section-number-5">3.2.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div class="outline-text-5" id="text-3-2-1-1">
<p>
<b>Python</b>
@ -2059,8 +2068,8 @@ E = -0.49518773675598715 +/- 5.2391494923686175E-004
</div>
</div>
<div id="outline-container-org9ac37db" class="outline-3">
<h3 id="org9ac37db"><span class="section-number-3">3.3</span> Metropolis sampling with \(\Psi^2\)</h3>
<div id="outline-container-org31acf84" class="outline-3">
<h3 id="org31acf84"><span class="section-number-3">3.3</span> Metropolis sampling with \(\Psi^2\)</h3>
<div class="outline-text-3" id="text-3-3">
<p>
We will now use the square of the wave function to sample random
@ -2148,8 +2157,8 @@ step such that the acceptance rate is close to 0.5 is a good compromise.
</div>
<div id="outline-container-org5ca4e2c" class="outline-4">
<h4 id="org5ca4e2c"><span class="section-number-4">3.3.1</span> Exercise</h4>
<div id="outline-container-org6d54039" class="outline-4">
<h4 id="org6d54039"><span class="section-number-4">3.3.1</span> Exercise</h4>
<div class="outline-text-4" id="text-3-3-1">
<div class="exercise">
<p>
@ -2256,8 +2265,8 @@ Can you observe a reduction in the statistical error?
</div>
</div>
<div id="outline-container-orgde750dd" class="outline-5">
<h5 id="orgde750dd"><span class="section-number-5">3.3.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div id="outline-container-org8084209" class="outline-5">
<h5 id="org8084209"><span class="section-number-5">3.3.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div class="outline-text-5" id="text-3-3-1-1">
<p>
<b>Python</b>
@ -2402,8 +2411,8 @@ A = 0.51695266666666673 +/- 4.0445505648997396E-004
</div>
</div>
<div id="outline-container-org9cb319e" class="outline-3">
<h3 id="org9cb319e"><span class="section-number-3">3.4</span> Gaussian random number generator</h3>
<div id="outline-container-org92d024f" class="outline-3">
<h3 id="org92d024f"><span class="section-number-3">3.4</span> Gaussian random number generator</h3>
<div class="outline-text-3" id="text-3-4">
<p>
To obtain Gaussian-distributed random numbers, you can apply the
@ -2465,8 +2474,8 @@ In Python, you can use the <a href="https://numpy.org/doc/stable/reference/rando
</p>
</div>
</div>
<div id="outline-container-orgc52c7d5" class="outline-3">
<h3 id="orgc52c7d5"><span class="section-number-3">3.5</span> Generalized Metropolis algorithm</h3>
<div id="outline-container-org1a64e1d" class="outline-3">
<h3 id="org1a64e1d"><span class="section-number-3">3.5</span> Generalized Metropolis algorithm</h3>
<div class="outline-text-3" id="text-3-5">
<p>
One can use more efficient numerical schemes to move the electrons,
@ -2565,8 +2574,8 @@ The transition probability becomes:
</div>
<div id="outline-container-org4689b7c" class="outline-4">
<h4 id="org4689b7c"><span class="section-number-4">3.5.1</span> Exercise 1</h4>
<div id="outline-container-org97c1b29" class="outline-4">
<h4 id="org97c1b29"><span class="section-number-4">3.5.1</span> Exercise 1</h4>
<div class="outline-text-4" id="text-3-5-1">
<div class="exercise">
<p>
@ -2600,8 +2609,8 @@ Write a function to compute the drift vector \(\frac{\nabla \Psi(\mathbf{r})}{\P
</div>
</div>
<div id="outline-container-org26c9d33" class="outline-5">
<h5 id="org26c9d33"><span class="section-number-5">3.5.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div id="outline-container-org19e85c9" class="outline-5">
<h5 id="org19e85c9"><span class="section-number-5">3.5.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div class="outline-text-5" id="text-3-5-1-1">
<p>
<b>Python</b>
@ -2634,8 +2643,8 @@ Write a function to compute the drift vector \(\frac{\nabla \Psi(\mathbf{r})}{\P
</div>
</div>
<div id="outline-container-org3e39526" class="outline-4">
<h4 id="org3e39526"><span class="section-number-4">3.5.2</span> Exercise 2</h4>
<div id="outline-container-orgaef93b5" class="outline-4">
<h4 id="orgaef93b5"><span class="section-number-4">3.5.2</span> Exercise 2</h4>
<div class="outline-text-4" id="text-3-5-2">
<div class="exercise">
<p>
@ -2729,8 +2738,8 @@ Modify the previous program to introduce the drifted diffusion scheme.
</div>
</div>
<div id="outline-container-orga3cf826" class="outline-5">
<h5 id="orga3cf826"><span class="section-number-5">3.5.2.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div id="outline-container-org17fe7c6" class="outline-5">
<h5 id="org17fe7c6"><span class="section-number-5">3.5.2.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div class="outline-text-5" id="text-3-5-2-1">
<p>
<b>Python</b>
@ -2916,12 +2925,12 @@ A = 0.78839866666666658 +/- 3.2503783452043152E-004
</div>
</div>
<div id="outline-container-orgebb7fc1" class="outline-2">
<h2 id="orgebb7fc1"><span class="section-number-2">4</span> Diffusion Monte Carlo&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h2>
<div id="outline-container-org9f51d1e" class="outline-2">
<h2 id="org9f51d1e"><span class="section-number-2">4</span> Diffusion Monte Carlo&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h2>
<div class="outline-text-2" id="text-4">
</div>
<div id="outline-container-org8cf0ab0" class="outline-3">
<h3 id="org8cf0ab0"><span class="section-number-3">4.1</span> Schrödinger equation in imaginary time</h3>
<div id="outline-container-org344d9de" class="outline-3">
<h3 id="org344d9de"><span class="section-number-3">4.1</span> Schrödinger equation in imaginary time</h3>
<div class="outline-text-3" id="text-4-1">
<p>
Consider the time-dependent Schrödinger equation:
@ -2980,8 +2989,8 @@ system.
</div>
</div>
<div id="outline-container-org78a65a5" class="outline-3">
<h3 id="org78a65a5"><span class="section-number-3">4.2</span> Diffusion and branching</h3>
<div id="outline-container-org06862e7" class="outline-3">
<h3 id="org06862e7"><span class="section-number-3">4.2</span> Diffusion and branching</h3>
<div class="outline-text-3" id="text-4-2">
<p>
The <a href="https://en.wikipedia.org/wiki/Diffusion_equation">diffusion equation</a> of particles is given by
@ -3035,8 +3044,8 @@ the combination of a diffusion process and a branching process.
</div>
</div>
<div id="outline-container-org00d8981" class="outline-3">
<h3 id="org00d8981"><span class="section-number-3">4.3</span> Importance sampling</h3>
<div id="outline-container-orgdf62087" class="outline-3">
<h3 id="orgdf62087"><span class="section-number-3">4.3</span> Importance sampling</h3>
<div class="outline-text-3" id="text-4-3">
<p>
In a molecular system, the potential is far from being constant,
@ -3093,8 +3102,8 @@ error known as the <i>fixed node error</i>.
</p>
</div>
<div id="outline-container-org024b07c" class="outline-4">
<h4 id="org024b07c"><span class="section-number-4">4.3.1</span> Appendix : Details of the Derivation</h4>
<div id="outline-container-org855e049" class="outline-4">
<h4 id="org855e049"><span class="section-number-4">4.3.1</span> Appendix : Details of the Derivation</h4>
<div class="outline-text-4" id="text-4-3-1">
<p>
\[
@ -3156,8 +3165,8 @@ Defining \(\Pi(\mathbf{r},t) = \psi(\mathbf{r},\tau)
</div>
<div id="outline-container-orgce840bc" class="outline-3">
<h3 id="orgce840bc"><span class="section-number-3">4.4</span> Fixed-node DMC energy</h3>
<div id="outline-container-org6fbf6b7" class="outline-3">
<h3 id="org6fbf6b7"><span class="section-number-3">4.4</span> Fixed-node DMC energy</h3>
<div class="outline-text-3" id="text-4-4">
<p>
Now that we have a process to sample \(\Pi(\mathbf{r},\tau) =
@ -3209,8 +3218,8 @@ energies computed with the trial wave function.
</div>
</div>
<div id="outline-container-orga97437f" class="outline-3">
<h3 id="orga97437f"><span class="section-number-3">4.5</span> Pure Diffusion Monte Carlo (PDMC)</h3>
<div id="outline-container-org4379250" class="outline-3">
<h3 id="org4379250"><span class="section-number-3">4.5</span> Pure Diffusion Monte Carlo (PDMC)</h3>
<div class="outline-text-3" id="text-4-5">
<p>
Instead of having a variable number of particles to simulate the
@ -3262,13 +3271,13 @@ code, so this is what we will do in the next section.
</div>
</div>
<div id="outline-container-org54d9e47" class="outline-3">
<h3 id="org54d9e47"><span class="section-number-3">4.6</span> Hydrogen atom</h3>
<div id="outline-container-org3a30f06" class="outline-3">
<h3 id="org3a30f06"><span class="section-number-3">4.6</span> Hydrogen atom</h3>
<div class="outline-text-3" id="text-4-6">
</div>
<div id="outline-container-org77c2d07" class="outline-4">
<h4 id="org77c2d07"><span class="section-number-4">4.6.1</span> Exercise</h4>
<div id="outline-container-orgba6aa2f" class="outline-4">
<h4 id="orgba6aa2f"><span class="section-number-4">4.6.1</span> Exercise</h4>
<div class="outline-text-4" id="text-4-6-1">
<div class="exercise">
<p>
@ -3367,8 +3376,8 @@ energy of H for any value of \(a\).
</div>
</div>
<div id="outline-container-orgc3fb998" class="outline-5">
<h5 id="orgc3fb998"><span class="section-number-5">4.6.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div id="outline-container-org2311033" class="outline-5">
<h5 id="org2311033"><span class="section-number-5">4.6.1.1</span> Solution&#xa0;&#xa0;&#xa0;<span class="tag"><span class="solution">solution</span></span></h5>
<div class="outline-text-5" id="text-4-6-1-1">
<p>
<b>Python</b>
@ -3584,8 +3593,8 @@ A = 0.98788066666666663 +/- 7.2889356133441110E-005
</div>
<div id="outline-container-orgb88b04d" class="outline-3">
<h3 id="orgb88b04d"><span class="section-number-3">4.7</span> <span class="todo TODO">TODO</span> H<sub>2</sub></h3>
<div id="outline-container-org81121c2" class="outline-3">
<h3 id="org81121c2"><span class="section-number-3">4.7</span> <span class="todo TODO">TODO</span> H<sub>2</sub></h3>
<div class="outline-text-3" id="text-4-7">
<p>
We will now consider the H<sub>2</sub> molecule in a minimal basis composed of the
@ -3606,8 +3615,8 @@ the nuclei.
</div>
<div id="outline-container-org622ff55" class="outline-2">
<h2 id="org622ff55"><span class="section-number-2">5</span> <span class="todo TODO">TODO</span> <code>[0/3]</code> Last things to do</h2>
<div id="outline-container-orgf5ad8c9" class="outline-2">
<h2 id="orgf5ad8c9"><span class="section-number-2">5</span> <span class="todo TODO">TODO</span> <code>[0/3]</code> Last things to do</h2>
<div class="outline-text-2" id="text-5">
<ul class="org-ul">
<li class="off"><code>[&#xa0;]</code> Give some hints of how much time is required for each section</li>
@ -3623,7 +3632,7 @@ the H\(_2\) molecule at $R$=1.4010 bohr. Answer: 0.17406 a.u.</li>
</div>
<div id="postamble" class="status">
<p class="author">Author: Anthony Scemama, Claudia Filippi</p>
<p class="date">Created: 2021-01-30 Sat 08:25</p>
<p class="date">Created: 2021-01-30 Sat 12:21</p>
<p class="validation"><a href="http://validator.w3.org/check?uri=referer">Validate</a></p>
</div>
</body>