From 5304edb7a9f7574d375654aaf4fa4c5a7f48a600 Mon Sep 17 00:00:00 2001 From: wexlergroup Date: Wed, 9 Oct 2024 00:32:23 -0500 Subject: [PATCH] Update documentation --- _sources/lecture-14-metropolis.md | 2 +- genindex.html | 2 +- intro.html | 4 ++-- lecture-14-metropolis.html | 10 +++++----- objects.inv | Bin 750 -> 745 bytes search.html | 2 +- searchindex.js | 2 +- 7 files changed, 11 insertions(+), 11 deletions(-) diff --git a/_sources/lecture-14-metropolis.md b/_sources/lecture-14-metropolis.md index 3e3bf52..9dc1ccf 100644 --- a/_sources/lecture-14-metropolis.md +++ b/_sources/lecture-14-metropolis.md @@ -11,7 +11,7 @@ kernelspec: name: python3 --- -# Lecture 14: The Metropolis Algorithm and Monte Carlo Simulations +# Lecture 14: A Basic Monte Carlo Algorithm ## Learning Objectives diff --git a/genindex.html b/genindex.html index df4c4ee..81325c5 100644 --- a/genindex.html +++ b/genindex.html @@ -193,7 +193,7 @@
  • Lecture 11: Ensembles and Ergodicity
  • Lecture 12: The Monte Carlo Method
  • Lecture 13: Monte Carlo Integration
    • -
  • Lecture 14: The Metropolis Algorithm and Monte Carlo Simulations
    • +
  • Lecture 14: A Basic Monte Carlo Algorithm
    • diff --git a/intro.html b/intro.html index 84b764e..b957525 100644 --- a/intro.html +++ b/intro.html @@ -197,7 +197,7 @@
  • Lecture 11: Ensembles and Ergodicity
  • Lecture 12: The Monte Carlo Method
  • Lecture 13: Monte Carlo Integration
    • -
  • Lecture 14: The Metropolis Algorithm and Monte Carlo Simulations
    • +
  • Lecture 14: A Basic Monte Carlo Algorithm
    • @@ -412,7 +412,7 @@

    Welcome to Computational Problem Solving in the Chemical SciencesLecture 11: Ensembles and Ergodicity
  • Lecture 12: The Monte Carlo Method
  • Lecture 13: Monte Carlo Integration
    • -
  • Lecture 14: The Metropolis Algorithm and Monte Carlo Simulations
    • +
  • Lecture 14: A Basic Monte Carlo Algorithm
    • diff --git a/lecture-14-metropolis.html b/lecture-14-metropolis.html index 5c93596..74f75af 100644 --- a/lecture-14-metropolis.html +++ b/lecture-14-metropolis.html @@ -8,7 +8,7 @@ - Lecture 14: The Metropolis Algorithm and Monte Carlo Simulations — Computational Problem Solving in the Chemical Sciences + Lecture 14: A Basic Monte Carlo Algorithm — Computational Problem Solving in the Chemical Sciences @@ -195,7 +195,7 @@
  • Lecture 11: Ensembles and Ergodicity
  • Lecture 12: The Monte Carlo Method
  • Lecture 13: Monte Carlo Integration
    • -
  • Lecture 14: The Metropolis Algorithm and Monte Carlo Simulations
    • +
  • Lecture 14: A Basic Monte Carlo Algorithm
    • @@ -381,7 +381,7 @@
    -

    Lecture 14: The Metropolis Algorithm and Monte Carlo Simulations

    +

    Lecture 14: A Basic Monte Carlo Algorithm

    @@ -434,8 +434,8 @@

    Contents

    -
    -

    Lecture 14: The Metropolis Algorithm and Monte Carlo Simulations#

    +
    +

    Lecture 14: A Basic Monte Carlo Algorithm#

    Learning Objectives#

    By the end of this lecture, you should be able to

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  • Lecture 12: The Monte Carlo Method
  • Lecture 13: Monte Carlo Integration
    • -
  • Lecture 14: The Metropolis Algorithm and Monte Carlo Simulations
    • +
  • Lecture 14: A Basic Monte Carlo Algorithm
    • diff --git a/searchindex.js b/searchindex.js index 6d007b9..b4e79fc 100644 --- a/searchindex.js +++ b/searchindex.js @@ -1 +1 @@ -Search.setIndex({"alltitles": {"": [[1, null], [1, null], [2, null], [2, null], [2, null], [3, null], [3, null], [5, null], [8, null], [9, null], [9, null], [9, null], [9, null], [9, null], [9, null], [10, null], [11, null], [12, null], [13, null], [14, null]], "1.1 Download and Install Python": [[1, "download-and-install-python"]], "1.1 Key Features of NumPy": [[2, "key-features-of-numpy"]], "1.1 The if Statement": [[3, "the-if-statement"]], "1.2 Check if Python is Already Installed": [[1, "check-if-python-is-already-installed"]], "1.2 The if-else Statement": [[3, "the-if-else-statement"]], "1.2 Working with NumPy Arrays": [[2, "working-with-numpy-arrays"]], "1.3 Practice Exercises": [[2, "practice-exercises"]], "1.3 The if-elif-else Statement": [[3, "the-if-elif-else-statement"]], "1.3 Windows-Specific Note": [[1, "windows-specific-note"]], "2.1 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"exercise-3-factorial-of-a-number"]], "Exercise 4": [[3, null]], "Exercise 4: Check if a String is a Palindrome": [[3, "exercise-4-check-if-a-string-is-a-palindrome"]], "Exercise 5": [[3, null]], "Exercise 5: Find the Maximum and Minimum Elements in a List": [[3, "exercise-5-find-the-maximum-and-minimum-elements-in-a-list"]], "Explanation of the Code": [[14, "explanation-of-the-code"]], "Free Energy and Entropy": [[10, "free-energy-and-entropy"]], "Fundamental Thermodynamic Relation": [[9, "fundamental-thermodynamic-relation"]], "General Case for Hydrocarbon Combustion": [[6, null]], "Generating Arrays with Specific Properties": [[2, "generating-arrays-with-specific-properties"]], "Grand Canonical Ensemble": [[11, "grand-canonical-ensemble"]], "Grand Canonical Ensemble: Example": [[11, "grand-canonical-ensemble-example"]], "Hands-On Activity": [[4, "hands-on-activity"], [7, "hands-on-activity"], [8, "hands-on-activity"]], "Hands-On Activity: Overlap of Two He 1s Orbitals": [[5, 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Carlo Method": [[12, null]], "Lecture 13: Monte Carlo Integration": [[13, null]], "Lecture 14: The Metropolis Algorithm and Monte Carlo Simulations": [[14, null]], "Lecture 1: Introduction to Python for the Chemical Sciences": [[1, null]], "Lecture 2: Essential Python Packages for the Chemical Sciences": [[2, null]], "Lecture 3: Control Structures in Python": [[3, null]], "Lecture 4: Chemical Reaction Equilibria and Roots of Equations": [[4, null]], "Lecture 5: Chemical Bonding and Numerical Integration": [[5, null]], "Lecture 6: Balancing Chemical Equations and Systems of Linear Algebraic Equations": [[6, null]], "Lecture 7: Orders of Reaction and Linear Regression Analysis": [[7, null]], "Lecture 8: Calibration Data, Confidence Intervals, and Correlation Analysis": [[8, null]], "Lecture 9: Classical Thermodynamics": [[9, null]], "Line Plots": [[2, "line-plots"]], "Linear Regression Analysis": [[7, "linear-regression-analysis"]], "List Comprehensions": [[3, "list-comprehensions"]], 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"motivation-for-importance-sampling"]], "Non-Ergodic Systems": [[11, "non-ergodic-systems"]], "Note": [[3, null], [4, null], [5, null]], "Numerical Integration": [[5, "numerical-integration"]], "Numerical Integration Using a Riemann Sum": [[5, "numerical-integration-using-a-riemann-sum"]], "Numerical Integration Using the Trapezoidal Rule": [[5, "numerical-integration-using-the-trapezoidal-rule"]], "Numerical Methods for Finding Roots of Equations": [[4, "numerical-methods-for-finding-roots-of-equations"]], "Orders of Reaction": [[7, "orders-of-reaction"]], "Ordinary Least Squares": [[7, "ordinary-least-squares"]], "Phase Equilibria": [[9, "phase-equilibria"]], "Plotting Thermal Expansion": [[14, "plotting-thermal-expansion"]], "Plotting the Results": [[14, "plotting-the-results"]], "Python Implementation": [[12, "python-implementation"]], "Python Lists": [[2, null]], "Random Sampling": [[13, "random-sampling"]], "Recap": [[6, "recap"]], "References": [[14, "references"]], "Relating 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"Section 4: Pandas - Powerful Data Manipulation in Python": [[2, "section-4-pandas-powerful-data-manipulation-in-python"]], "Simulation Over a Range of Temperatures": [[14, "simulation-over-a-range-of-temperatures"]], "Solving for Equilibrium": [[4, "solving-for-equilibrium"]], "Solving the Equation Using Python": [[6, "solving-the-equation-using-python"]], "Solving the System of Equations": [[6, "solving-the-system-of-equations"]], "Statement of the First Law": [[9, "statement-of-the-first-law"]], "Step 1: Formulating the Equilibrium Equation": [[4, "step-1-formulating-the-equilibrium-equation"]], "Step 1: Getting Python Installed": [[1, "step-1-getting-python-installed"]], "Step 1: Import the Necessary Libraries": [[6, "step-1-import-the-necessary-libraries"]], "Step 2: Define the Coefficient Matrix, \\mathbf{A}": [[6, "step-2-define-the-coefficient-matrix-mathbf-a"]], "Step 2: Installing Jupyter Notebook": [[1, "step-2-installing-jupyter-notebook"]], "Step 2: Minimizing the 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