Built site for gh-pages

.nojekyll

@@ -1 +1 @@
-17ecdf5e
+f553c2de

examples/problem_decomposition/ifci_mifno.html

@@ -449,7 +449,7 @@ <h1 class="title">Exploring the Method of Increments with QEMIST Cloud and Tange
 
 </header>
 
-<p>In this notebook, we illustrate how users can leverage QEMIST Cloud and Tangelo to explore the impact of quantum computing on problems tackled with the method of increments (MI) problem decomposition technique. We demonstrate workflows using the Frozen Natural Orbital Based Method of Increments (MI-FNO), as well as the incremental Full Configuration Interaction (iFCI).</p>
+<p>In this notebook, we illustrate how users can leverage QEMIST Cloud and Tangelo to explore the impact of quantum computing on problems tackled with the method of increments (MI) problem decomposition technique. We demonstrate workflows using the Frozen Natural Orbital Based Method of Increments (MI-FNO), as well as the incremental Full Configuration Interaction (iFCI) approach.</p>
 <p>You do not need to have the <code>qemist-client</code> python package installed to run this notebook: only <code>tangelo</code> is required. For more information about <a href="https://goodchemistry.com/qemist-cloud/">QEMIST Cloud</a> (installation, features, issues, <code>qemist_client</code> API…), please refer to the QEMIST Cloud documentation or contact the development team.</p>
 <p>The first section provides a high-level description of the MI approach. The second one briefly shows how QEMIST Cloud can apply this approach to a usecase, and provide reference results computed with high-accuracy classical solvers. We then focus on the API provided in Tangelo allowing users to combine the MI performed by QEMIST Cloud and any quantum workflow written with Tangelo.</p>
 <p>The cell below installs the required dependencies for this notebook in case Tangelo is not found in your current environment.</p>
@@ -485,8 +485,8 @@ <h2 class="anchored" data-anchor-id="use-case">Use case</h2>
 </section>
 <section id="what-are-ifci-and-mi-fno" class="level2">
 <h2 class="anchored" data-anchor-id="what-are-ifci-and-mi-fno">What are iFCI and MI-FNO ?</h2>
-<p>The method of increment (MI) expresses the electron correlation energy of a molecular system as a truncated many-body expansion in terms of orbitals, atoms, molecules, or fragments. The electron correlation of the system is expanded in terms of occupied orbitals, and MI is employed to systematically reduce the occupied orbital space. Simultaneously, the virtual orbital space is reduced based on orbital localization and the one-particle density matrix from the second-order many-body perturbation theory. Following this approach, the methods referred to as <a href="https://doi.org/10.1063/1.4977727">iFCI</a> and <a href="https://doi.org/10.1063/5.0054647">MI-FNO</a> are available for the systematic reduction of both the occupied space and the virtual space in quantum chemistry simulations. Although the two methods share similarities, they exhibit a few key differences, including the approach used to truncate the virtual orbital space (Frozen Natural Orbitals (FNOs) vs Summation Natural Orbitals (SNOs)) and the inclusion of a correction factor for each MI-FNO fragment (which is not required for iFCI fragments).</p>
-<p>MI was first introduced in quantum chemistry by Nesbet (<a href="https://doi.org/10.1103/PhysRev.155.51">Phys. Rev.&nbsp;1967, 155, 51</a>, <a href="https://doi.org/10.1103/PhysRev.155.56">Phys. Rev.&nbsp;1967, 155, 56</a> and <a href="https://doi.org/10.1103/PhysRev.175.2">Phys. Rev.&nbsp;1968, 175, 2</a>), is based upon the n-body Bethe–Goldstone expansion (<a href="https://doi.org/10.1098/rspa.1957.0017">Proc. R. Soc. A, 1957, 238, 551</a>) of the correlation energy of a molecule. The correlation energy (<span class="math inline">\(E_c\)</span>), defined as the difference between the exact (<span class="math inline">\(E_{\text{exact}}\)</span>) and the Hartree–Fock (mean-field) energy (<span class="math inline">\(E_{\text{HF}}\)</span>), can be expanded as</p>
+<p>The method of increments (MI) expresses the electron correlation energy of a molecular system as a truncated many-body expansion in terms of orbitals, atoms, molecules, or fragments. The electron correlation energy of the system is expanded in terms of occupied orbitals, and MI is employed to systematically reduce the occupied orbital space. Simultaneously, the virtual orbital space of each increment is reduced by spanning it by a truncated set of natural orbitals obtained from diagonalization of a one-particle density matrix. Following this approach, the methods referred to as <a href="https://doi.org/10.1063/1.4977727">iFCI</a> and <a href="https://doi.org/10.1063/5.0054647">MI-FNO</a> are available for the systematic reduction of both the occupied space and the virtual space in quantum chemistry simulations. Although the two methods share similarities, they exhibit a few key differences, including the approach used to truncate the virtual orbital space (Frozen Natural Orbitals (FNOs) vs Summation Natural Orbitals (SNOs)) and the inclusion of a correction factor for each MI-FNO fragment (which is not required for iFCI fragments).</p>
+<p>MI was first introduced in quantum chemistry by Nesbet (<a href="https://doi.org/10.1103/PhysRev.155.51">Phys. Rev.&nbsp;1967, 155, 51</a>, <a href="https://doi.org/10.1103/PhysRev.155.56">Phys. Rev.&nbsp;1967, 155, 56</a> and <a href="https://doi.org/10.1103/PhysRev.175.2">Phys. Rev.&nbsp;1968, 175, 2</a>) and is based upon the n-body Bethe–Goldstone expansion (<a href="https://doi.org/10.1098/rspa.1957.0017">Proc. R. Soc. A, 1957, 238, 551</a>) of the correlation energy of a molecule. The correlation energy (<span class="math inline">\(E_c\)</span>), defined as the difference between the exact (<span class="math inline">\(E_{\text{exact}}\)</span>) and the Hartree–Fock (mean-field) energy (<span class="math inline">\(E_{\text{HF}}\)</span>), can be expanded as</p>
 <p><span class="math display">\[
 \begin{align*}
 E_c &amp;= E_{\text{exact}} - E_{\text{HF}} \\
@@ -503,7 +503,7 @@ <h2 class="anchored" data-anchor-id="what-are-ifci-and-mi-fno">What are iFCI and
 &amp;\vdots
 \end{align*}
 \]</span></p>
-<p>The following figure, taken from <a href="https://doi.org/10.1063/5.0054647">J. Chem. Phys. 2021, 155, 034110</a>, illustrates this problem decomposition scheme in terms of 1-body and many-body interactions. On each subproblem, a truncation is applied to reduce their virtual space. The subproblems resulting from the iFCI and MI-FNO reduction can then be solved by any algorithm, including quantum algorithms such as the phase estimation algorithm and the variational quantum eigensolver (VQE), to predict the correlation energies of a molecular system.</p>
+<p>The following figure, taken from <a href="https://doi.org/10.1063/5.0054647">J. Chem. Phys. 2021, 155, 034110</a>, illustrates this problem decomposition scheme in terms of 1-body and many-body interactions. On each subproblem, a truncation is applied to reduce their virtual space. The subproblems resulting from the iFCI and MI-FNO reduction can then be solved by any algorithm, including quantum algorithms such as the phase estimation algorithm and the variational quantum eigensolver (VQE), to approximate the correlation energies of a molecular system.</p>
 <div>
 <p><img src="../img/mi.png" width="800"></p>
 </div>

search.json

@@ -431,7 +431,7 @@
     "href": "examples/problem_decomposition/ifci_mifno.html",
     "title": "Exploring the Method of Increments with QEMIST Cloud and Tangelo",
     "section": "",
-    "text": "In this notebook, we illustrate how users can leverage QEMIST Cloud and Tangelo to explore the impact of quantum computing on problems tackled with the method of increments (MI) problem decomposition technique. We demonstrate workflows using the Frozen Natural Orbital Based Method of Increments (MI-FNO), as well as the incremental Full Configuration Interaction (iFCI).\nYou do not need to have the qemist-client python package installed to run this notebook: only tangelo is required. For more information about QEMIST Cloud (installation, features, issues, qemist_client API…), please refer to the QEMIST Cloud documentation or contact the development team.\nThe first section provides a high-level description of the MI approach. The second one briefly shows how QEMIST Cloud can apply this approach to a usecase, and provide reference results computed with high-accuracy classical solvers. We then focus on the API provided in Tangelo allowing users to combine the MI performed by QEMIST Cloud and any quantum workflow written with Tangelo.\nThe cell below installs the required dependencies for this notebook in case Tangelo is not found in your current environment.\n# Installation of tangelo if not already installed.\ntry:\n    import tangelo\nexcept ModuleNotFoundError:\n    !pip install pyscf\n    !pip install git+https://github.com/goodchemistryco/Tangelo.git@develop --quiet\n\n# Download the data folder at https://github.com/goodchemistryco/Tangelo/branches/develop/tangelo/problem_decomposition/tests/incremental/data/BeH2_CCPVDZ_MIFNO_HBCI\nimport os\ndata_folder = \"BeH2_CCPVDZ_MIFNO_HBCI\"\n\nif not os.path.isdir(data_folder):\n    !curl https://codeload.github.com/goodchemistryco/Tangelo/tar.gz/develop | \\\n    tar -xz --strip=6 Tangelo-develop/tangelo/problem_decomposition/tests/incremental/data/{data_folder}"
+    "text": "In this notebook, we illustrate how users can leverage QEMIST Cloud and Tangelo to explore the impact of quantum computing on problems tackled with the method of increments (MI) problem decomposition technique. We demonstrate workflows using the Frozen Natural Orbital Based Method of Increments (MI-FNO), as well as the incremental Full Configuration Interaction (iFCI) approach.\nYou do not need to have the qemist-client python package installed to run this notebook: only tangelo is required. For more information about QEMIST Cloud (installation, features, issues, qemist_client API…), please refer to the QEMIST Cloud documentation or contact the development team.\nThe first section provides a high-level description of the MI approach. The second one briefly shows how QEMIST Cloud can apply this approach to a usecase, and provide reference results computed with high-accuracy classical solvers. We then focus on the API provided in Tangelo allowing users to combine the MI performed by QEMIST Cloud and any quantum workflow written with Tangelo.\nThe cell below installs the required dependencies for this notebook in case Tangelo is not found in your current environment.\n# Installation of tangelo if not already installed.\ntry:\n    import tangelo\nexcept ModuleNotFoundError:\n    !pip install pyscf\n    !pip install git+https://github.com/goodchemistryco/Tangelo.git@develop --quiet\n\n# Download the data folder at https://github.com/goodchemistryco/Tangelo/branches/develop/tangelo/problem_decomposition/tests/incremental/data/BeH2_CCPVDZ_MIFNO_HBCI\nimport os\ndata_folder = \"BeH2_CCPVDZ_MIFNO_HBCI\"\n\nif not os.path.isdir(data_folder):\n    !curl https://codeload.github.com/goodchemistryco/Tangelo/tar.gz/develop | \\\n    tar -xz --strip=6 Tangelo-develop/tangelo/problem_decomposition/tests/incremental/data/{data_folder}"
   },
   {
     "objectID": "examples/problem_decomposition/ifci_mifno.html#use-case",
@@ -445,7 +445,7 @@
     "href": "examples/problem_decomposition/ifci_mifno.html#what-are-ifci-and-mi-fno",
     "title": "Exploring the Method of Increments with QEMIST Cloud and Tangelo",
     "section": "What are iFCI and MI-FNO ?",
-    "text": "What are iFCI and MI-FNO ?\nThe method of increment (MI) expresses the electron correlation energy of a molecular system as a truncated many-body expansion in terms of orbitals, atoms, molecules, or fragments. The electron correlation of the system is expanded in terms of occupied orbitals, and MI is employed to systematically reduce the occupied orbital space. Simultaneously, the virtual orbital space is reduced based on orbital localization and the one-particle density matrix from the second-order many-body perturbation theory. Following this approach, the methods referred to as iFCI and MI-FNO are available for the systematic reduction of both the occupied space and the virtual space in quantum chemistry simulations. Although the two methods share similarities, they exhibit a few key differences, including the approach used to truncate the virtual orbital space (Frozen Natural Orbitals (FNOs) vs Summation Natural Orbitals (SNOs)) and the inclusion of a correction factor for each MI-FNO fragment (which is not required for iFCI fragments).\nMI was first introduced in quantum chemistry by Nesbet (Phys. Rev. 1967, 155, 51, Phys. Rev. 1967, 155, 56 and Phys. Rev. 1968, 175, 2), is based upon the n-body Bethe–Goldstone expansion (Proc. R. Soc. A, 1957, 238, 551) of the correlation energy of a molecule. The correlation energy (\\(E_c\\)), defined as the difference between the exact (\\(E_{\\text{exact}}\\)) and the Hartree–Fock (mean-field) energy (\\(E_{\\text{HF}}\\)), can be expanded as\n\\[\n\\begin{align*}\nE_c &= E_{\\text{exact}} - E_{\\text{HF}} \\\\\n&= \\sum_i \\epsilon_i + \\sum_{i>j} \\epsilon_{ij} + \\sum_{i>j>k} \\epsilon_{ijk} + \\sum_{i>j>k>l} \\epsilon_{ijkl} + \\dots\n\\end{align*}\n\\]\nwhere \\(\\epsilon_i\\), \\(\\epsilon_{ij}\\), \\(\\epsilon_{ijk}\\), and \\(\\epsilon_{ijkl}\\) are, respectively, the one-, two-, three-, and four-body increments (expansions) defined as\n\\[\n\\begin{align*}\n\\epsilon_i &= E_c(i) \\\\\n\\epsilon_{ij} &= E_c(ij) - \\epsilon_i - \\epsilon_j \\\\\n\\epsilon_{ijk} &= E_c(ijk) - \\epsilon_{ij} - \\epsilon_{ik} - \\epsilon_{jk} - \\epsilon_{i} - \\epsilon_{j} - \\epsilon_{k} \\\\\n\\epsilon_{ijkl} &= E_c(ijkl) - \\epsilon_{ijk} - \\epsilon_{ijl} - \\epsilon_{jkl} - \\dots \\\\\n&\\vdots\n\\end{align*}\n\\]\nThe following figure, taken from J. Chem. Phys. 2021, 155, 034110, illustrates this problem decomposition scheme in terms of 1-body and many-body interactions. On each subproblem, a truncation is applied to reduce their virtual space. The subproblems resulting from the iFCI and MI-FNO reduction can then be solved by any algorithm, including quantum algorithms such as the phase estimation algorithm and the variational quantum eigensolver (VQE), to predict the correlation energies of a molecular system.\n\n\n\nThe iFCI and MI-FNO problem decomposition pipelines are available in QEMIST Cloud. In this notebook, we illustrate how to export MI fragment data computed in QEMIST Cloud, and import it in Tangelo for further treatment, such as using quantum solvers."
+    "text": "What are iFCI and MI-FNO ?\nThe method of increments (MI) expresses the electron correlation energy of a molecular system as a truncated many-body expansion in terms of orbitals, atoms, molecules, or fragments. The electron correlation energy of the system is expanded in terms of occupied orbitals, and MI is employed to systematically reduce the occupied orbital space. Simultaneously, the virtual orbital space of each increment is reduced by spanning it by a truncated set of natural orbitals obtained from diagonalization of a one-particle density matrix. Following this approach, the methods referred to as iFCI and MI-FNO are available for the systematic reduction of both the occupied space and the virtual space in quantum chemistry simulations. Although the two methods share similarities, they exhibit a few key differences, including the approach used to truncate the virtual orbital space (Frozen Natural Orbitals (FNOs) vs Summation Natural Orbitals (SNOs)) and the inclusion of a correction factor for each MI-FNO fragment (which is not required for iFCI fragments).\nMI was first introduced in quantum chemistry by Nesbet (Phys. Rev. 1967, 155, 51, Phys. Rev. 1967, 155, 56 and Phys. Rev. 1968, 175, 2) and is based upon the n-body Bethe–Goldstone expansion (Proc. R. Soc. A, 1957, 238, 551) of the correlation energy of a molecule. The correlation energy (\\(E_c\\)), defined as the difference between the exact (\\(E_{\\text{exact}}\\)) and the Hartree–Fock (mean-field) energy (\\(E_{\\text{HF}}\\)), can be expanded as\n\\[\n\\begin{align*}\nE_c &= E_{\\text{exact}} - E_{\\text{HF}} \\\\\n&= \\sum_i \\epsilon_i + \\sum_{i>j} \\epsilon_{ij} + \\sum_{i>j>k} \\epsilon_{ijk} + \\sum_{i>j>k>l} \\epsilon_{ijkl} + \\dots\n\\end{align*}\n\\]\nwhere \\(\\epsilon_i\\), \\(\\epsilon_{ij}\\), \\(\\epsilon_{ijk}\\), and \\(\\epsilon_{ijkl}\\) are, respectively, the one-, two-, three-, and four-body increments (expansions) defined as\n\\[\n\\begin{align*}\n\\epsilon_i &= E_c(i) \\\\\n\\epsilon_{ij} &= E_c(ij) - \\epsilon_i - \\epsilon_j \\\\\n\\epsilon_{ijk} &= E_c(ijk) - \\epsilon_{ij} - \\epsilon_{ik} - \\epsilon_{jk} - \\epsilon_{i} - \\epsilon_{j} - \\epsilon_{k} \\\\\n\\epsilon_{ijkl} &= E_c(ijkl) - \\epsilon_{ijk} - \\epsilon_{ijl} - \\epsilon_{jkl} - \\dots \\\\\n&\\vdots\n\\end{align*}\n\\]\nThe following figure, taken from J. Chem. Phys. 2021, 155, 034110, illustrates this problem decomposition scheme in terms of 1-body and many-body interactions. On each subproblem, a truncation is applied to reduce their virtual space. The subproblems resulting from the iFCI and MI-FNO reduction can then be solved by any algorithm, including quantum algorithms such as the phase estimation algorithm and the variational quantum eigensolver (VQE), to approximate the correlation energies of a molecular system.\n\n\n\nThe iFCI and MI-FNO problem decomposition pipelines are available in QEMIST Cloud. In this notebook, we illustrate how to export MI fragment data computed in QEMIST Cloud, and import it in Tangelo for further treatment, such as using quantum solvers."
   },
   {
     "objectID": "examples/problem_decomposition/ifci_mifno.html#performing-mi-calculations-with-qemist-cloud",