Release v0.7.0

Project.toml

@@ -1,7 +1,7 @@
 name = "PEPSKit"
 uuid = "52969e89-939e-4361-9b68-9bc7cde4bdeb"
 authors = ["Paul Brehmer", "Lander Burgelman", "Lukas Devos <ldevos98@gmail.com>"]
-version = "0.6.1"
+version = "0.7.0"
 
 [deps]
 Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"

docs/src/examples/bose_hubbard/main.ipynb

@@ -1,17 +1,16 @@
 {
  "cells": [
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
    "outputs": [],
+   "cell_type": "code",
    "source": [
     "using Markdown #hide"
-   ]
+   ],
+   "metadata": {},
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "# Optimizing the $U(1)$-symmetric Bose-Hubbard model\n",
     "\n",
@@ -22,23 +21,23 @@
     "environment - made possible through TensorKit.\n",
     "\n",
     "But first let's seed the RNG and import the required modules:"
-   ]
+   ],
+   "metadata": {}
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
    "outputs": [],
+   "cell_type": "code",
    "source": [
     "using Random\n",
     "using TensorKit, PEPSKit\n",
     "using MPSKit: add_physical_charge\n",
     "Random.seed!(2928528935);"
-   ]
+   ],
+   "metadata": {},
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "## Defining the model\n",
     "\n",
@@ -49,62 +48,62 @@
     "ground state to be well approximated by a PEPS with a manifest global $U(1)$ symmetry.\n",
     "Furthermore, we'll impose a cutoff at 2 bosons per site, set the chemical potential to zero\n",
     "and use a simple $1 \\times 1$ unit cell:"
-   ]
+   ],
+   "metadata": {}
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
    "outputs": [],
+   "cell_type": "code",
    "source": [
     "t = 1.0\n",
     "U = 30.0\n",
     "cutoff = 2\n",
     "mu = 0.0\n",
     "lattice = InfiniteSquare(1, 1);"
-   ]
+   ],
+   "metadata": {},
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "Next, we impose an explicit global $U(1)$ symmetry as well as a fixed particle number\n",
     "density in our simulations. We can do this by setting the `symmetry` argument of the\n",
     "Hamiltonian constructor to `U1Irrep` and passing one as the particle number density\n",
     "keyword argument `n`:"
-   ]
+   ],
+   "metadata": {}
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
    "outputs": [],
+   "cell_type": "code",
    "source": [
     "symmetry = U1Irrep\n",
     "n = 1\n",
     "H = bose_hubbard_model(ComplexF64, symmetry, lattice; cutoff, t, U, n);"
-   ]
+   ],
+   "metadata": {},
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "Before we continue, it might be interesting to inspect the corresponding lattice physical\n",
     "spaces (which is here just a $1 \\times 1$ matrix due to the single-site unit cell):"
-   ]
+   ],
+   "metadata": {}
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
    "outputs": [],
+   "cell_type": "code",
    "source": [
     "physical_spaces = physicalspace(H)"
-   ]
+   ],
+   "metadata": {},
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "Note that the physical space contains $U(1)$ charges -1, 0 and +1. Indeed, imposing a\n",
     "particle number density of +1 corresponds to shifting the physical charges by -1 to\n",
@@ -127,43 +126,43 @@
     "with a model at unit filling our physical space only contains integer $U(1)$ irreps.\n",
     "Therefore, we'll build our PEPS and environment spaces using integer $U(1)$ irreps centered\n",
     "around the zero charge:"
-   ]
+   ],
+   "metadata": {}
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
    "outputs": [],
+   "cell_type": "code",
    "source": [
     "V_peps = U1Space(0 => 2, 1 => 1, -1 => 1)\n",
     "V_env = U1Space(0 => 6, 1 => 4, -1 => 4, 2 => 2, -2 => 2);"
-   ]
+   ],
+   "metadata": {},
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "## Finding the ground state\n",
     "\n",
     "Having defined our Hamiltonian and spaces, it is just a matter of plugging this into the\n",
     "optimization framework in the usual way to find the ground state. So, we first specify all\n",
     "algorithms and their tolerances:"
-   ]
+   ],
+   "metadata": {}
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
    "outputs": [],
+   "cell_type": "code",
    "source": [
     "boundary_alg = (; tol = 1.0e-8, alg = :simultaneous, trunc = (; alg = :fixedspace))\n",
     "gradient_alg = (; tol = 1.0e-6, maxiter = 10, alg = :eigsolver, iterscheme = :diffgauge)\n",
     "optimizer_alg = (; tol = 1.0e-4, alg = :lbfgs, maxiter = 150, ls_maxiter = 2, ls_maxfg = 2);"
-   ]
+   ],
+   "metadata": {},
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "!!! note\n",
     "\tTaking CTMRG gradients and optimizing symmetric tensors tends to be more problematic\n",
@@ -180,80 +179,81 @@
     "\n",
     "Keep in mind that the PEPS is constructed from a unit cell of spaces, so we have to make a\n",
     "matrix of `V_peps` spaces:"
-   ]
+   ],
+   "metadata": {}
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
    "outputs": [],
+   "cell_type": "code",
    "source": [
     "virtual_spaces = fill(V_peps, size(lattice)...)\n",
     "peps₀ = InfinitePEPS(randn, ComplexF64, physical_spaces, virtual_spaces)\n",
     "env₀, = leading_boundary(CTMRGEnv(peps₀, V_env), peps₀; boundary_alg...);"
-   ]
+   ],
+   "metadata": {},
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "And at last, we optimize (which might take a bit):"
-   ]
+   ],
+   "metadata": {}
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
    "outputs": [],
+   "cell_type": "code",
    "source": [
     "peps, env, E, info = fixedpoint(\n",
     "    H, peps₀, env₀; boundary_alg, gradient_alg, optimizer_alg, verbosity = 3\n",
     ")\n",
     "@show E;"
-   ]
+   ],
+   "metadata": {},
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "We can compare our PEPS result to the energy obtained using a cylinder-MPS calculation\n",
     "using a cylinder circumference of $L_y = 7$ and a bond dimension of 446, which yields\n",
     "$E = -0.273284888$:"
-   ]
+   ],
+   "metadata": {}
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
    "outputs": [],
+   "cell_type": "code",
    "source": [
     "E_ref = -0.273284888\n",
     "@show (E - E_ref) / E_ref;"
-   ]
+   ],
+   "metadata": {},
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
     "---\n",
     "\n",
     "*This notebook was generated using [Literate.jl](https://github.com/fredrikekre/Literate.jl).*"
-   ]
+   ],
+   "metadata": {}
   }
  ],
+ "nbformat_minor": 3,
  "metadata": {
-  "kernelspec": {
-   "display_name": "Julia 1.11.5",
-   "language": "julia",
-   "name": "julia-1.11"
-  },
   "language_info": {
    "file_extension": ".jl",
    "mimetype": "application/julia",
    "name": "julia",
-   "version": "1.11.5"
+   "version": "1.11.7"
+  },
+  "kernelspec": {
+   "name": "julia-1.11",
+   "display_name": "Julia 1.11.7",
+   "language": "julia"
   }
  },
- "nbformat": 4,
- "nbformat_minor": 3
-}
+ "nbformat": 4
+}