build based on 66d346e

dev/.documenter-siteinfo.json

@@ -1 +1 @@
-{"documenter":{"julia_version":"1.11.1","generation_timestamp":"2024-11-19T01:09:36","documenter_version":"1.8.0"}}
+{"documenter":{"julia_version":"1.11.1","generation_timestamp":"2024-11-22T12:37:07","documenter_version":"1.8.0"}}

dev/examples/classic2d/1.hard-hexagon/main.ipynb

@@ -145,11 +145,11 @@
    "file_extension": ".jl",
    "mimetype": "application/julia",
    "name": "julia",
-   "version": "1.10.4"
+   "version": "1.11.1"
   },
   "kernelspec": {
-   "name": "julia-1.10",
-   "display_name": "Julia 1.10.4",
+   "name": "julia-1.11",
+   "display_name": "Julia 1.11.1",
    "language": "julia"
   }
  },

dev/examples/quantum1d/1.ising-cft/main.ipynb

@@ -69,9 +69,10 @@
   {
    "cell_type": "markdown",
    "source": [
-    "!!! note \"Krylov dimension\"\n",
-    "    Note that we have specified a large Krylov dimension as degenerate eigenvalues are\n",
-    "    notoriously difficult for iterative methods."
+    "> **Krylov dimension**\n",
+    ">\n",
+    "> Note that we have specified a large Krylov dimension as degenerate eigenvalues are\n",
+    "> notoriously difficult for iterative methods."
    ],
    "metadata": {}
   },
@@ -231,11 +232,11 @@
    "file_extension": ".jl",
    "mimetype": "application/julia",
    "name": "julia",
-   "version": "1.10.4"
+   "version": "1.11.1"
   },
   "kernelspec": {
-   "name": "julia-1.10",
-   "display_name": "Julia 1.10.4",
+   "name": "julia-1.11",
+   "display_name": "Julia 1.11.1",
    "language": "julia"
   }
  },

dev/examples/quantum1d/2.haldane/main.ipynb

@@ -179,11 +179,11 @@
    "file_extension": ".jl",
    "mimetype": "application/julia",
    "name": "julia",
-   "version": "1.10.4"
+   "version": "1.11.1"
   },
   "kernelspec": {
-   "name": "julia-1.10",
-   "display_name": "Julia 1.10.4",
+   "name": "julia-1.11",
+   "display_name": "Julia 1.11.1",
    "language": "julia"
   }
  },

dev/examples/quantum1d/3.ising-dqpt/index.html

@@ -3,13 +3,14 @@
 
 L = 20
 ψ₀ = FiniteMPS(rand, ComplexF64, L, ℂ^2, ℂ^10)
-ψ₀, _ = find_groundstate(ψ₀, H₀, DMRG());</code></pre><pre><code class="nohighlight hljs">[ Info: DMRG init:	obj = +9.833992820341e+00	err = 1.5162e-01
-[ Info: DMRG   1:	obj = -2.040021714792e+01	err = 1.0482607701e-02	time = 0.07 sec
-[ Info: DMRG   2:	obj = -2.040021715176e+01	err = 2.9301055999e-07	time = 0.02 sec
-[ Info: DMRG   3:	obj = -2.040021783353e+01	err = 2.1923563339e-05	time = 0.14 sec
-[ Info: DMRG   4:	obj = -2.040021786702e+01	err = 1.8539117704e-06	time = 0.21 sec
-[ Info: DMRG   5:	obj = -2.040021786703e+01	err = 7.8191209682e-08	time = 0.04 sec
-[ Info: DMRG conv 6:	obj = -2.040021786703e+01	err = 6.4920277294e-11	time = 0.49 sec
+ψ₀, _ = find_groundstate(ψ₀, H₀, DMRG());</code></pre><pre><code class="nohighlight hljs">[ Info: DMRG init:	obj = +9.799964091770e+00	err = 1.5223e-01
+[ Info: DMRG   1:	obj = -2.040021714743e+01	err = 2.4038839149e-02	time = 0.09 sec
+[ Info: DMRG   2:	obj = -2.040021715170e+01	err = 6.0313575856e-07	time = 0.07 sec
+[ Info: DMRG   3:	obj = -2.040021773534e+01	err = 1.6799456960e-05	time = 0.14 sec
+[ Info: DMRG   4:	obj = -2.040021786694e+01	err = 1.9058246307e-06	time = 0.09 sec
+[ Info: DMRG   5:	obj = -2.040021786703e+01	err = 1.1474711603e-06	time = 0.05 sec
+[ Info: DMRG   6:	obj = -2.040021786703e+01	err = 4.3837579221e-10	time = 0.02 sec
+[ Info: DMRG conv 7:	obj = -2.040021786703e+01	err = 1.9834477158e-11	time = 0.50 sec
 </code></pre><h2 id="Finite-MPS-quenching"><a class="docs-heading-anchor" href="#Finite-MPS-quenching">Finite MPS quenching</a><a id="Finite-MPS-quenching-1"></a><a class="docs-heading-anchor-permalink" href="#Finite-MPS-quenching" title="Permalink"></a></h2><p>We can define a helper function that measures the loschmith echo</p><pre><code class="language-julia hljs">echo(ψ₀::FiniteMPS, ψₜ::FiniteMPS) = -2 * log(abs(dot(ψ₀, ψₜ))) / length(ψ₀)
 @assert isapprox(echo(ψ₀, ψ₀), 0, atol=1e-10)</code></pre><p>We will initially use a two-site TDVP scheme to dynamically increase the bond dimension while time evolving, and later on switch to a faster one-site scheme. A single timestep can be done using</p><pre><code class="language-julia hljs">H₁ = transverse_field_ising(; g=-2.0)
 ψₜ = deepcopy(ψ₀)
@@ -32,14 +33,24 @@
 
     return times, echos
 end</code></pre><pre><code class="nohighlight hljs">finite_sim (generic function with 1 method)</code></pre><p><img src="finite_timeev.png" alt/></p><h2 id="Infinite-MPS-quenching"><a class="docs-heading-anchor" href="#Infinite-MPS-quenching">Infinite MPS quenching</a><a id="Infinite-MPS-quenching-1"></a><a class="docs-heading-anchor-permalink" href="#Infinite-MPS-quenching" title="Permalink"></a></h2><p>Similarly we could start with an initial infinite state and find the pre-quench groundstate:</p><pre><code class="language-julia hljs">ψ₀ = InfiniteMPS([ℂ^2], [ℂ^10])
-ψ₀, _ = find_groundstate(ψ₀, H₀, VUMPS());</code></pre><pre><code class="nohighlight hljs">[ Info: VUMPS init:	obj = +5.083504996507e-01	err = 3.8682e-01
-[ Info: VUMPS   1:	obj = -1.060586960116e+00	err = 4.7773289906e-02	time = 1.51 sec
-[ Info: VUMPS   2:	obj = -1.063544400328e+00	err = 8.6203478863e-05	time = 0.01 sec
-[ Info: VUMPS   3:	obj = -1.063544409973e+00	err = 2.6470717828e-07	time = 0.01 sec
-[ Info: VUMPS   4:	obj = -1.063544409973e+00	err = 8.9760940163e-09	time = 0.00 sec
-[ Info: VUMPS   5:	obj = -1.063544409973e+00	err = 4.1698951454e-10	time = 0.00 sec
-[ Info: VUMPS conv 6:	obj = -1.063544409973e+00	err = 3.7060383050e-11	time = 1.53 sec
-</code></pre><p>The dot product of two infinite matrix product states scales as  <span>$\alpha ^N$</span> where <span>$α$</span> is the dominant eigenvalue of the transfer matrix. It is this <span>$α$</span> that is returned when calling</p><pre><code class="language-julia hljs">dot(ψ₀, ψ₀)</code></pre><pre><code class="nohighlight hljs">0.9999999999999964 - 7.217459182439675e-17im</code></pre><p>so the loschmidth echo takes on the pleasant form</p><pre><code class="language-julia hljs">echo(ψ₀::InfiniteMPS, ψₜ::InfiniteMPS) = -2 * log(abs(dot(ψ₀, ψₜ)))
+ψ₀, _ = find_groundstate(ψ₀, H₀, VUMPS());</code></pre><pre><code class="nohighlight hljs">[ Info: VUMPS init:	obj = +5.000419382862e-01	err = 3.8507e-01
+[ Info: VUMPS   1:	obj = -1.062780898337e+00	err = 2.4151374798e-02	time = 1.31 sec
+┌ Warning: ignoring imaginary component -3.817802691569172e-6 from total weight 2.4343214394239743: operator might not be hermitian?
+│   α = 1.7081089443203243 - 3.817802691569172e-6im
+│   β₁ = 0.14004438155194618
+│   β₂ = 1.7287776826281838
+└ @ KrylovKit ~/.julia/packages/KrylovKit/xccMN/src/factorizations/lanczos.jl:170
+┌ Warning: ignoring imaginary component -4.33258309393697e-6 from total weight 3.290563788912538: operator might not be hermitian?
+│   α = 2.784222669687663 - 4.33258309393697e-6im
+│   β₁ = 0.13141322180957496
+│   β₂ = 1.7488981501547187
+└ @ KrylovKit ~/.julia/packages/KrylovKit/xccMN/src/factorizations/lanczos.jl:170
+[ Info: VUMPS   2:	obj = -1.063544409753e+00	err = 1.4337063091e-05	time = 0.08 sec
+[ Info: VUMPS   3:	obj = -1.063544409973e+00	err = 1.7048015038e-07	time = 0.01 sec
+[ Info: VUMPS   4:	obj = -1.063544409973e+00	err = 1.7183182449e-08	time = 0.01 sec
+[ Info: VUMPS   5:	obj = -1.063544409973e+00	err = 5.8865202016e-10	time = 0.01 sec
+[ Info: VUMPS conv 6:	obj = -1.063544409973e+00	err = 6.8020365686e-11	time = 1.42 sec
+</code></pre><p>The dot product of two infinite matrix product states scales as  <span>$\alpha ^N$</span> where <span>$α$</span> is the dominant eigenvalue of the transfer matrix. It is this <span>$α$</span> that is returned when calling</p><pre><code class="language-julia hljs">dot(ψ₀, ψ₀)</code></pre><pre><code class="nohighlight hljs">1.0000000000000018 - 7.06078012856404e-16im</code></pre><p>so the loschmidth echo takes on the pleasant form</p><pre><code class="language-julia hljs">echo(ψ₀::InfiniteMPS, ψₜ::InfiniteMPS) = -2 * log(abs(dot(ψ₀, ψₜ)))
 @assert isapprox(echo(ψ₀, ψ₀), 0, atol=1e-10)</code></pre><p>This time we cannot use a two-site scheme to grow the bond dimension, as this isn&#39;t implemented (yet). Instead, we have to make use of the changebonds machinery. Multiple algorithms are available, but we will only focus on <code>OptimalEpand()</code>. Growing the bond dimension by <span>$5$</span> can be done by calling:</p><pre><code class="language-julia hljs">ψₜ = deepcopy(ψ₀)
 ψₜ, envs = changebonds(ψₜ, H₁, OptimalExpand(; trscheme=truncdim(5)));</code></pre><p>a single timestep is easy</p><pre><code class="language-julia hljs">dt = 0.01
 ψₜ, envs = timestep(ψₜ, H₁, 0, dt, TDVP(), envs);</code></pre><p>With performance in mind we should once again try to re-use these &quot;envs&quot; cache objects. The final code is</p><pre><code class="language-julia hljs">function infinite_sim(dt=0.05, finaltime=5.0)
@@ -61,4 +72,4 @@
     end
 
     return times, echos
-end</code></pre><pre><code class="nohighlight hljs">infinite_sim (generic function with 3 methods)</code></pre><p><img src="infinite_timeev.png" alt/></p><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.8.0 on <span class="colophon-date" title="Tuesday 19 November 2024 01:09">Tuesday 19 November 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>
+end</code></pre><pre><code class="nohighlight hljs">infinite_sim (generic function with 3 methods)</code></pre><p><img src="infinite_timeev.png" alt/></p><hr/><p><em>This page was generated using <a href="https://github.com/fredrikekre/Literate.jl">Literate.jl</a>.</em></p></article><nav class="docs-footer"><p class="footer-message">Powered by <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> and the <a href="https://julialang.org/">Julia Programming Language</a>.</p></nav></div><div class="modal" id="documenter-settings"><div class="modal-background"></div><div class="modal-card"><header class="modal-card-head"><p class="modal-card-title">Settings</p><button class="delete"></button></header><section class="modal-card-body"><p><label class="label">Theme</label><div class="select"><select id="documenter-themepicker"><option value="auto">Automatic (OS)</option><option value="documenter-light">documenter-light</option><option value="documenter-dark">documenter-dark</option><option value="catppuccin-latte">catppuccin-latte</option><option value="catppuccin-frappe">catppuccin-frappe</option><option value="catppuccin-macchiato">catppuccin-macchiato</option><option value="catppuccin-mocha">catppuccin-mocha</option></select></div></p><hr/><p>This document was generated with <a href="https://github.com/JuliaDocs/Documenter.jl">Documenter.jl</a> version 1.8.0 on <span class="colophon-date" title="Friday 22 November 2024 12:37">Friday 22 November 2024</span>. Using Julia version 1.11.1.</p></section><footer class="modal-card-foot"></footer></div></div></div></body></html>

dev/examples/quantum1d/3.ising-dqpt/main.ipynb

@@ -282,11 +282,11 @@
    "file_extension": ".jl",
    "mimetype": "application/julia",
    "name": "julia",
-   "version": "1.10.4"
+   "version": "1.11.1"
   },
   "kernelspec": {
-   "name": "julia-1.10",
-   "display_name": "Julia 1.10.4",
+   "name": "julia-1.11",
+   "display_name": "Julia 1.11.1",
    "language": "julia"
   }
  },