update first week

mhjensen · mhjensen · commit 4b5a52998576 · 2024-12-25T13:29:08.000+01:00
diff --git a/doc/pub/week1/html/._week1-bs006.html b/doc/pub/week1/html/._week1-bs006.html
@@ -255,11 +255,11 @@ <h2 id="course-format" class="anchor">Course Format </h2>
 <div class="panel panel-default">
 <div class="panel-body">
 <!-- subsequent paragraphs come in larger fonts, so start with a paragraph -->
-<ul>
-  <li> Two  compulsory projects. Electronic reports only. You are free to choose your format. We use canvas.uio.no to hand in the projects.</li>
-  <li> Evaluation and grading: The two  projects count 1/2 each of the final mark.</li> 
-  <li> The computer lab (room F&#216;434 in the Physics building) has no PCs, so please bring your own laptops. C/C++ and Python are the default programming language, but programming languages like Fortran2008, Rust, Julia and other can  also be used. All source codes discussed during the lectures can be found at the webpage of the course.</li> 
-</ul>
+<ol>
+<li> Two  compulsory projects. Electronic reports only. You are free to choose your format. We use canvas.uio.no to hand in the projects.</li>
+<li> Evaluation and grading: The two  projects count 1/2 each of the final mark.</li> 
+<li> The computer lab (room F&#216;434 in the Physics building) has no PCs, so please bring your own laptops. C/C++ and Python are the default programming language, but programming languages like Fortran2008, Rust, Julia and other can  also be used. All source codes discussed during the lectures can be found at the webpage of the course.</li> 
+</ol>
 </div>
 </div>
 
diff --git a/doc/pub/week1/html/._week1-bs007.html b/doc/pub/week1/html/._week1-bs007.html
@@ -254,12 +254,12 @@ <h2 id="aims" class="anchor">Aims </h2>
 <div class="panel panel-default">
 <div class="panel-body">
 <!-- subsequent paragraphs come in larger fonts, so start with a paragraph -->
-<ul>
+<ol>
 <li> Be able to apply central many-particle methods like the Variational Monte Carlo method to properties of many-fermion systems and many-boson systems.</li>
 <li> Understand how to simulate quantum mechanical systems with many interacting particles. The methods are relevant for atomic, molecular, condensed matter physics, materials science, nanotechnology, quantum chemistry  and nuclear physics.</li> 
 <li> Learn to manage and structure larger projects, with unit tests, object orientation and writing clean code</li>
 <li> Learn about a proper statistical analysis of large data sets</li>
-</ul>
+</ol>
 </div>
 </div>
 
diff --git a/doc/pub/week1/html/._week1-bs008.html b/doc/pub/week1/html/._week1-bs008.html
@@ -254,11 +254,11 @@ <h2 id="more-aims" class="anchor">More aims </h2>
 <div class="panel panel-default">
 <div class="panel-body">
 <!-- subsequent paragraphs come in larger fonts, so start with a paragraph -->
-<ul>
+<ol>
 <li> Learn to optimize with convex optimization methods functions that depend on many variables.</li>
 <li> Parallelization and code optimizations</li>
 <li> Depending on interests, the second project can focus on different topics. These can be <b>quantum computing for studies of quantum mechanical problems</b>, machine learning for solving quantum-mechanical problems, quantum machine learning and many-body methods like coupled cluster theory, Hartree-Fock theory and other.</li> 
-</ul>
+</ol>
 </div>
 </div>
 
diff --git a/doc/pub/week1/html/._week1-bs009.html b/doc/pub/week1/html/._week1-bs009.html
@@ -255,12 +255,12 @@ <h2 id="topics-covered-in-this-course" class="anchor">Topics covered in this cou
 <div class="panel panel-default">
 <div class="panel-body">
 <!-- subsequent paragraphs come in larger fonts, so start with a paragraph -->
-<ul>
-  <li> Parallelization (MPI and OpenMP), high-performance computing topics. Choose between Python, Fortran2008 and/or C++ as programming languages.</li> 
-  <li> Algorithms for Monte Carlo Simulations (multidimensional integrals), Metropolis-Hastings and importance sampling algorithms.  Improved Monte Carlo methods.</li>
-  <li> Statistical analysis of data  from Monte Carlo calculations, bootstrapping, jackknife and blocking methods.</li> 
-  <li> Eigenvalue solvers</li>
-</ul>
+<ol>
+<li> Parallelization (MPI and OpenMP), high-performance computing topics. Choose between Python, Fortran2008 and/or C++ as programming languages.</li> 
+<li> Algorithms for Monte Carlo Simulations (multidimensional integrals), Metropolis-Hastings and importance sampling algorithms.  Improved Monte Carlo methods. Stochastic reconfiguration.</li>
+<li> Statistical analysis of data  from Monte Carlo calculations, bootstrapping, jackknife and blocking methods.</li> 
+<li> Eigenvalue solvers</li>
+</ol>
 </div>
 </div>
 
diff --git a/doc/pub/week1/html/._week1-bs010.html b/doc/pub/week1/html/._week1-bs010.html
@@ -255,14 +255,14 @@ <h2 id="more-on-topics-covered-in-this-course" class="anchor">More on topics cov
 <div class="panel-body">
 <!-- subsequent paragraphs come in larger fonts, so start with a paragraph -->
 <ul>
-  <li> For project 2 there are several possibilities
+<li> For project 2 there are several possibilities
 <ol type="a"></li>
-   <li> Variational Monte Carlo for fermions</li>
-   <li> Hartree-Fock theory for fermions with time dependence</li>
-   <li> Coupled cluster theory for fermions (iterative methods)</li>
-   <li> Neural networks and Machine Learning to solve the same problems as in project 1</li>
-   <li> Eigenvalue problems with deep learning methods</li>
-   <li> Possible project on quantum computing and quantum machine learning</li>
+ <li> Variational Monte Carlo for fermions</li>
+ <li> Hartree-Fock theory for fermions with time dependence</li>
+ <li> Coupled cluster theory for fermions (iterative methods)</li>
+ <li> Neural networks and Machine Learning to solve the same problems as in project 1</li>
+ <li> Eigenvalue problems with deep learning methods</li>
+ <li> Possible project on quantum computing and quantum machine learning</li>
 </ol>
 </ul>
 </div>
diff --git a/doc/pub/week1/html/week1-reveal.html b/doc/pub/week1/html/week1-reveal.html
@@ -280,14 +280,11 @@ <h2 id="course-format">Course Format </h2>
 <div class="alert alert-block alert-block alert-text-normal">
 <b></b>
 <p>
-<ul>
-
+<ol>
 <p><li> Two  compulsory projects. Electronic reports only. You are free to choose your format. We use canvas.uio.no to hand in the projects.</li>
-
-<p><li> Evaluation and grading: The two  projects count 1/2 each of the final mark.</li>
-
+<p><li> Evaluation and grading: The two  projects count 1/2 each of the final mark.</li> 
 <p><li> The computer lab (room F&#216;434 in the Physics building) has no PCs, so please bring your own laptops. C/C++ and Python are the default programming language, but programming languages like Fortran2008, Rust, Julia and other can  also be used. All source codes discussed during the lectures can be found at the webpage of the course.</li> 
-</ul>
+</ol>
 </div>
 </section>
 
@@ -296,12 +293,12 @@ <h2 id="aims">Aims </h2>
 <div class="alert alert-block alert-block alert-text-normal">
 <b></b>
 <p>
-<ul>
+<ol>
 <p><li> Be able to apply central many-particle methods like the Variational Monte Carlo method to properties of many-fermion systems and many-boson systems.</li>
 <p><li> Understand how to simulate quantum mechanical systems with many interacting particles. The methods are relevant for atomic, molecular, condensed matter physics, materials science, nanotechnology, quantum chemistry  and nuclear physics.</li> 
 <p><li> Learn to manage and structure larger projects, with unit tests, object orientation and writing clean code</li>
 <p><li> Learn about a proper statistical analysis of large data sets</li>
-</ul>
+</ol>
 </div>
 </section>
 
@@ -310,11 +307,11 @@ <h2 id="more-aims">More aims </h2>
 <div class="alert alert-block alert-block alert-text-normal">
 <b></b>
 <p>
-<ul>
+<ol>
 <p><li> Learn to optimize with convex optimization methods functions that depend on many variables.</li>
 <p><li> Parallelization and code optimizations</li>
 <p><li> Depending on interests, the second project can focus on different topics. These can be <b>quantum computing for studies of quantum mechanical problems</b>, machine learning for solving quantum-mechanical problems, quantum machine learning and many-body methods like coupled cluster theory, Hartree-Fock theory and other.</li> 
-</ul>
+</ol>
 </div>
 </section>
 
@@ -324,16 +321,12 @@ <h2 id="topics-covered-in-this-course">Topics covered in this course </h2>
 <div class="alert alert-block alert-block alert-text-normal">
 <b></b>
 <p>
-<ul>
-
-<p><li> Parallelization (MPI and OpenMP), high-performance computing topics. Choose between Python, Fortran2008 and/or C++ as programming languages.</li>
-
-<p><li> Algorithms for Monte Carlo Simulations (multidimensional integrals), Metropolis-Hastings and importance sampling algorithms.  Improved Monte Carlo methods.</li>
-
-<p><li> Statistical analysis of data  from Monte Carlo calculations, bootstrapping, jackknife and blocking methods.</li>
-
+<ol>
+<p><li> Parallelization (MPI and OpenMP), high-performance computing topics. Choose between Python, Fortran2008 and/or C++ as programming languages.</li> 
+<p><li> Algorithms for Monte Carlo Simulations (multidimensional integrals), Metropolis-Hastings and importance sampling algorithms.  Improved Monte Carlo methods. Stochastic reconfiguration.</li>
+<p><li> Statistical analysis of data  from Monte Carlo calculations, bootstrapping, jackknife and blocking methods.</li> 
 <p><li> Eigenvalue solvers</li>
-</ul>
+</ol>
 </div>
 </section>
 
@@ -343,21 +336,14 @@ <h2 id="more-on-topics-covered-in-this-course">More on topics covered in this co
 <b></b>
 <p>
 <ul>
-
 <p><li> For project 2 there are several possibilities
 <ol type="a"></li>
-
-<p><li> Variational Monte Carlo for fermions</li>
-
-<p><li> Hartree-Fock theory for fermions with time dependence</li>
-
-<p><li> Coupled cluster theory for fermions (iterative methods)</li>
-
-<p><li> Neural networks and Machine Learning to solve the same problems as in project 1</li>
-
-<p><li> Eigenvalue problems with deep learning methods</li>
-
-<p><li> Possible project on quantum computing and quantum machine learning</li>
+ <p><li> Variational Monte Carlo for fermions</li>
+ <p><li> Hartree-Fock theory for fermions with time dependence</li>
+ <p><li> Coupled cluster theory for fermions (iterative methods)</li>
+ <p><li> Neural networks and Machine Learning to solve the same problems as in project 1</li>
+ <p><li> Eigenvalue problems with deep learning methods</li>
+ <p><li> Possible project on quantum computing and quantum machine learning</li>
 </ol>
 <p>
 </ul>
diff --git a/doc/pub/week1/html/week1-solarized.html b/doc/pub/week1/html/week1-solarized.html
@@ -314,11 +314,11 @@ <h2 id="course-format">Course Format </h2>
 <div class="alert alert-block alert-block alert-text-normal">
 <b></b>
 <p>
-<ul>
-  <li> Two  compulsory projects. Electronic reports only. You are free to choose your format. We use canvas.uio.no to hand in the projects.</li>
-  <li> Evaluation and grading: The two  projects count 1/2 each of the final mark.</li> 
-  <li> The computer lab (room F&#216;434 in the Physics building) has no PCs, so please bring your own laptops. C/C++ and Python are the default programming language, but programming languages like Fortran2008, Rust, Julia and other can  also be used. All source codes discussed during the lectures can be found at the webpage of the course.</li> 
-</ul>
+<ol>
+<li> Two  compulsory projects. Electronic reports only. You are free to choose your format. We use canvas.uio.no to hand in the projects.</li>
+<li> Evaluation and grading: The two  projects count 1/2 each of the final mark.</li> 
+<li> The computer lab (room F&#216;434 in the Physics building) has no PCs, so please bring your own laptops. C/C++ and Python are the default programming language, but programming languages like Fortran2008, Rust, Julia and other can  also be used. All source codes discussed during the lectures can be found at the webpage of the course.</li> 
+</ol>
 </div>
 
 
@@ -327,12 +327,12 @@ <h2 id="aims">Aims </h2>
 <div class="alert alert-block alert-block alert-text-normal">
 <b></b>
 <p>
-<ul>
+<ol>
 <li> Be able to apply central many-particle methods like the Variational Monte Carlo method to properties of many-fermion systems and many-boson systems.</li>
 <li> Understand how to simulate quantum mechanical systems with many interacting particles. The methods are relevant for atomic, molecular, condensed matter physics, materials science, nanotechnology, quantum chemistry  and nuclear physics.</li> 
 <li> Learn to manage and structure larger projects, with unit tests, object orientation and writing clean code</li>
 <li> Learn about a proper statistical analysis of large data sets</li>
-</ul>
+</ol>
 </div>
 
 
@@ -341,11 +341,11 @@ <h2 id="more-aims">More aims </h2>
 <div class="alert alert-block alert-block alert-text-normal">
 <b></b>
 <p>
-<ul>
+<ol>
 <li> Learn to optimize with convex optimization methods functions that depend on many variables.</li>
 <li> Parallelization and code optimizations</li>
 <li> Depending on interests, the second project can focus on different topics. These can be <b>quantum computing for studies of quantum mechanical problems</b>, machine learning for solving quantum-mechanical problems, quantum machine learning and many-body methods like coupled cluster theory, Hartree-Fock theory and other.</li> 
-</ul>
+</ol>
 </div>
 
 
@@ -355,12 +355,12 @@ <h2 id="topics-covered-in-this-course">Topics covered in this course </h2>
 <div class="alert alert-block alert-block alert-text-normal">
 <b></b>
 <p>
-<ul>
-  <li> Parallelization (MPI and OpenMP), high-performance computing topics. Choose between Python, Fortran2008 and/or C++ as programming languages.</li> 
-  <li> Algorithms for Monte Carlo Simulations (multidimensional integrals), Metropolis-Hastings and importance sampling algorithms.  Improved Monte Carlo methods.</li>
-  <li> Statistical analysis of data  from Monte Carlo calculations, bootstrapping, jackknife and blocking methods.</li> 
-  <li> Eigenvalue solvers</li>
-</ul>
+<ol>
+<li> Parallelization (MPI and OpenMP), high-performance computing topics. Choose between Python, Fortran2008 and/or C++ as programming languages.</li> 
+<li> Algorithms for Monte Carlo Simulations (multidimensional integrals), Metropolis-Hastings and importance sampling algorithms.  Improved Monte Carlo methods. Stochastic reconfiguration.</li>
+<li> Statistical analysis of data  from Monte Carlo calculations, bootstrapping, jackknife and blocking methods.</li> 
+<li> Eigenvalue solvers</li>
+</ol>
 </div>
 
 
@@ -370,14 +370,14 @@ <h2 id="more-on-topics-covered-in-this-course">More on topics covered in this co
 <b></b>
 <p>
 <ul>
-  <li> For project 2 there are several possibilities
+<li> For project 2 there are several possibilities
 <ol type="a"></li>
-   <li> Variational Monte Carlo for fermions</li>
-   <li> Hartree-Fock theory for fermions with time dependence</li>
-   <li> Coupled cluster theory for fermions (iterative methods)</li>
-   <li> Neural networks and Machine Learning to solve the same problems as in project 1</li>
-   <li> Eigenvalue problems with deep learning methods</li>
-   <li> Possible project on quantum computing and quantum machine learning</li>
+ <li> Variational Monte Carlo for fermions</li>
+ <li> Hartree-Fock theory for fermions with time dependence</li>
+ <li> Coupled cluster theory for fermions (iterative methods)</li>
+ <li> Neural networks and Machine Learning to solve the same problems as in project 1</li>
+ <li> Eigenvalue problems with deep learning methods</li>
+ <li> Possible project on quantum computing and quantum machine learning</li>
 </ol>
 </ul>
 </div>
diff --git a/doc/pub/week1/html/week1.html b/doc/pub/week1/html/week1.html
@@ -391,11 +391,11 @@ <h2 id="course-format">Course Format </h2>
 <div class="alert alert-block alert-block alert-text-normal">
 <b></b>
 <p>
-<ul>
-  <li> Two  compulsory projects. Electronic reports only. You are free to choose your format. We use canvas.uio.no to hand in the projects.</li>
-  <li> Evaluation and grading: The two  projects count 1/2 each of the final mark.</li> 
-  <li> The computer lab (room F&#216;434 in the Physics building) has no PCs, so please bring your own laptops. C/C++ and Python are the default programming language, but programming languages like Fortran2008, Rust, Julia and other can  also be used. All source codes discussed during the lectures can be found at the webpage of the course.</li> 
-</ul>
+<ol>
+<li> Two  compulsory projects. Electronic reports only. You are free to choose your format. We use canvas.uio.no to hand in the projects.</li>
+<li> Evaluation and grading: The two  projects count 1/2 each of the final mark.</li> 
+<li> The computer lab (room F&#216;434 in the Physics building) has no PCs, so please bring your own laptops. C/C++ and Python are the default programming language, but programming languages like Fortran2008, Rust, Julia and other can  also be used. All source codes discussed during the lectures can be found at the webpage of the course.</li> 
+</ol>
 </div>
 
 
@@ -404,12 +404,12 @@ <h2 id="aims">Aims </h2>
 <div class="alert alert-block alert-block alert-text-normal">
 <b></b>
 <p>
-<ul>
+<ol>
 <li> Be able to apply central many-particle methods like the Variational Monte Carlo method to properties of many-fermion systems and many-boson systems.</li>
 <li> Understand how to simulate quantum mechanical systems with many interacting particles. The methods are relevant for atomic, molecular, condensed matter physics, materials science, nanotechnology, quantum chemistry  and nuclear physics.</li> 
 <li> Learn to manage and structure larger projects, with unit tests, object orientation and writing clean code</li>
 <li> Learn about a proper statistical analysis of large data sets</li>
-</ul>
+</ol>
 </div>
 
 
@@ -418,11 +418,11 @@ <h2 id="more-aims">More aims </h2>
 <div class="alert alert-block alert-block alert-text-normal">
 <b></b>
 <p>
-<ul>
+<ol>
 <li> Learn to optimize with convex optimization methods functions that depend on many variables.</li>
 <li> Parallelization and code optimizations</li>
 <li> Depending on interests, the second project can focus on different topics. These can be <b>quantum computing for studies of quantum mechanical problems</b>, machine learning for solving quantum-mechanical problems, quantum machine learning and many-body methods like coupled cluster theory, Hartree-Fock theory and other.</li> 
-</ul>
+</ol>
 </div>
 
 
@@ -432,12 +432,12 @@ <h2 id="topics-covered-in-this-course">Topics covered in this course </h2>
 <div class="alert alert-block alert-block alert-text-normal">
 <b></b>
 <p>
-<ul>
-  <li> Parallelization (MPI and OpenMP), high-performance computing topics. Choose between Python, Fortran2008 and/or C++ as programming languages.</li> 
-  <li> Algorithms for Monte Carlo Simulations (multidimensional integrals), Metropolis-Hastings and importance sampling algorithms.  Improved Monte Carlo methods.</li>
-  <li> Statistical analysis of data  from Monte Carlo calculations, bootstrapping, jackknife and blocking methods.</li> 
-  <li> Eigenvalue solvers</li>
-</ul>
+<ol>
+<li> Parallelization (MPI and OpenMP), high-performance computing topics. Choose between Python, Fortran2008 and/or C++ as programming languages.</li> 
+<li> Algorithms for Monte Carlo Simulations (multidimensional integrals), Metropolis-Hastings and importance sampling algorithms.  Improved Monte Carlo methods. Stochastic reconfiguration.</li>
+<li> Statistical analysis of data  from Monte Carlo calculations, bootstrapping, jackknife and blocking methods.</li> 
+<li> Eigenvalue solvers</li>
+</ol>
 </div>
 
 
@@ -447,14 +447,14 @@ <h2 id="more-on-topics-covered-in-this-course">More on topics covered in this co
 <b></b>
 <p>
 <ul>
-  <li> For project 2 there are several possibilities
+<li> For project 2 there are several possibilities
 <ol type="a"></li>
-   <li> Variational Monte Carlo for fermions</li>
-   <li> Hartree-Fock theory for fermions with time dependence</li>
-   <li> Coupled cluster theory for fermions (iterative methods)</li>
-   <li> Neural networks and Machine Learning to solve the same problems as in project 1</li>
-   <li> Eigenvalue problems with deep learning methods</li>
-   <li> Possible project on quantum computing and quantum machine learning</li>
+ <li> Variational Monte Carlo for fermions</li>
+ <li> Hartree-Fock theory for fermions with time dependence</li>
+ <li> Coupled cluster theory for fermions (iterative methods)</li>
+ <li> Neural networks and Machine Learning to solve the same problems as in project 1</li>
+ <li> Eigenvalue problems with deep learning methods</li>
+ <li> Possible project on quantum computing and quantum machine learning</li>
 </ol>
 </ul>
 </div>
diff --git a/doc/pub/week1/ipynb/ipynb-week1-src.tar.gz b/doc/pub/week1/ipynb/ipynb-week1-src.tar.gz
diff --git a/doc/pub/week1/ipynb/week1.ipynb b/doc/pub/week1/ipynb/week1.ipynb
diff --git a/doc/pub/week1/pdf/week1-beamer.pdf b/doc/pub/week1/pdf/week1-beamer.pdf
diff --git a/doc/pub/week1/pdf/week1.pdf b/doc/pub/week1/pdf/week1.pdf
