Updates for compatibility with TensorKit v0.15 (#270)

* CompatHelper: bump compat for TensorKit to 0.15, (keep existing compat)

* Rename `TruncationScheme` to `TruncationStrategy`

* Lower SVD broadening test tolerance

* Replace TensorKit's SDD and SVD

* Update all occurences of `tsvd`, `eigh`, `leftorth` and `rightorth` to new interface

* Use `svd_vals` instead of `svd_compact`

Co-authored-by: Lukas Devos <ldevos98@gmail.com>

* Use some more `svd_vals`

* Remove old TensorKit (internal) functions from src/utility/svd.jl and update with new MAK functions

* Remove some more old TensorKit

* Fix TruncationSpace problems

* Readd TensorKit internal functions for IterSVD computation

* Fix SVD running issues

* Fix CTMRG flavors test

* Formatting

* Fix `truncerror` errors

* Fix `_svd_trunc!` for `FixedSVD`

* Enforce non-dualness of truncspaces

* Make clust bond truncation tests runnable again and fix more dual truncspaces

* Remove accidental TensorKitSectors

* Formatting

* Remove asserts no longer necessary

* Fix `qr/lq_through`

* Replace `dual(V)` by `flip(V)` in SU FixedSpaceTruncation

* Use `flip` to flip spaces

* Forbid dual environment spaces

* Drop TensorKit v0.14

* Remove dual env spaces from tests

* Fix LAPACK algorithm call error

* Fix typos

* Add hacky computation for truncation error in _svd_trunc!

* Fix small typo

* Apply truncation error suggestion

* (Temporary?) workaround for duality check

* Ignore crashing `svd_vals` derivatives

* Improve duality checking for environment virtual spaces

* Use wts as initialization for 3-site SU env

* Replace all occurences of `trscheme` by `trunc`

* Fix VUMPS test

* Remove explicit `truncrank` and `trunctol` import

* Remove the rest as well

* Return r, l only from `qr/lq_through`

* Restore parametrized inner `CTMRGEnv` constructor, move version with spacechecks to outer constructor

---------

Co-authored-by: CompatHelper Julia <compathelper_noreply@julialang.org>
Co-authored-by: Paul Brehmer <paul.brehmer@univie.ac.at>
Co-authored-by: Paul Brehmer <paulbrehmer8@googlemail.com>
Co-authored-by: Lukas Devos <ldevos98@gmail.com>
Co-authored-by: Yue Zhengyuan <yuezy1997@icloud.com>
Co-authored-by: leburgel <lander.burgelman@gmail.com>

Author: 6 people

Project.toml

@@ -14,6 +14,7 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LoggingExtras = "e6f89c97-d47a-5376-807f-9c37f3926c36"
 MPSKit = "bb1c41ca-d63c-52ed-829e-0820dda26502"
 MPSKitModels = "ca635005-6f8c-4cd1-b51d-8491250ef2ab"
+MatrixAlgebraKit = "6c742aac-3347-4629-af66-fc926824e5e4"
 OhMyThreads = "67456a42-1dca-4109-a031-0a68de7e3ad5"
 OptimKit = "77e91f04-9b3b-57a6-a776-40b61faaebe0"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
@@ -35,13 +36,14 @@ LinearAlgebra = "1"
 LoggingExtras = "1"
 MPSKit = "0.13.7"
 MPSKitModels = "0.4"
+MatrixAlgebraKit = "0.5.0"
 OhMyThreads = "0.7, 0.8"
 OptimKit = "0.3, 0.4"
 Printf = "1"
 QuadGK = "2.11.1"
 Random = "1"
 Statistics = "1"
-TensorKit = "0.14.9"
+TensorKit = "0.15"
 TensorOperations = "5"
 TestExtras = "0.3"
 VectorInterface = "0.4, 0.5"

docs/src/examples/bose_hubbard/index.md

@@ -77,7 +77,7 @@ When running PEPS simulations with explicit internal symmetries, specifying the
 the virtual spaces of the PEPS and its environment becomes a bit more involved. For the
 environment, one could in principle allow the virtual space to be chosen dynamically during
 the boundary contraction using CTMRG by using a truncation scheme that allows for this
-(e.g. using `alg=:truncdim` or `alg=:truncbelow` to truncate to a fixed total bond dimension
+(e.g. using `alg=:truncrank` or `alg=:trunctol` to truncate to a fixed total bond dimension
 or singular value cutoff respectively). For the PEPS virtual space however, the structure
 has to be specified before the optimization.
 
@@ -99,7 +99,7 @@ optimization framework in the usual way to find the ground state. So, we first s
 algorithms and their tolerances:
 
 ````julia
-boundary_alg = (; tol = 1.0e-8, alg = :simultaneous, trscheme = (; alg = :fixedspace))
+boundary_alg = (; tol = 1.0e-8, alg = :simultaneous, trunc = (; alg = :fixedspace))
 gradient_alg = (; tol = 1.0e-6, maxiter = 10, alg = :eigsolver, iterscheme = :diffgauge)
 optimizer_alg = (; tol = 1.0e-4, alg = :lbfgs, maxiter = 150, ls_maxiter = 2, ls_maxfg = 2);
 ````

docs/src/examples/bose_hubbard/main.ipynb

@@ -1,16 +1,17 @@
 {
  "cells": [
   {
-   "outputs": [],
    "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "using Markdown #hide"
-   ],
-   "metadata": {},
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "# Optimizing the $U(1)$-symmetric Bose-Hubbard model\n",
     "\n",
@@ -21,23 +22,23 @@
     "environment - made possible through TensorKit.\n",
     "\n",
     "But first let's seed the RNG and import the required modules:"
-   ],
-   "metadata": {}
+   ]
   },
   {
-   "outputs": [],
    "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "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",
@@ -48,62 +49,62 @@
     "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": {}
+   ]
   },
   {
-   "outputs": [],
    "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "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": {}
+   ]
   },
   {
-   "outputs": [],
    "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "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": {}
+   ]
   },
   {
-   "outputs": [],
    "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "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",
@@ -117,7 +118,7 @@
     "the virtual spaces of the PEPS and its environment becomes a bit more involved. For the\n",
     "environment, one could in principle allow the virtual space to be chosen dynamically during\n",
     "the boundary contraction using CTMRG by using a truncation scheme that allows for this\n",
-    "(e.g. using `alg=:truncdim` or `alg=:truncbelow` to truncate to a fixed total bond dimension\n",
+    "(e.g. using `alg=:truncrank` or `alg=:trunctol` to truncate to a fixed total bond dimension\n",
     "or singular value cutoff respectively). For the PEPS virtual space however, the structure\n",
     "has to be specified before the optimization.\n",
     "\n",
@@ -126,43 +127,43 @@
     "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": {}
+   ]
   },
   {
-   "outputs": [],
    "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "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": {}
+   ]
   },
   {
-   "outputs": [],
    "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
-    "boundary_alg = (; tol = 1.0e-8, alg = :simultaneous, trscheme = (; alg = :fixedspace))\n",
+    "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",
@@ -179,81 +180,80 @@
     "\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": {}
+   ]
   },
   {
-   "outputs": [],
    "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "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": {}
+   ]
   },
   {
-   "outputs": [],
    "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "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": {}
+   ]
   },
   {
-   "outputs": [],
    "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "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"
-  },
-  "kernelspec": {
-   "name": "julia-1.11",
-   "display_name": "Julia 1.11.5",
-   "language": "julia"
   }
  },
- "nbformat": 4
+ "nbformat": 4,
+ "nbformat_minor": 3
 }

docs/src/examples/fermi_hubbard/index.md

@@ -81,7 +81,7 @@ Again, the procedure of ground state optimization is very similar to before. Fir
 define all algorithmic parameters:
 
 ````julia
-boundary_alg = (; tol = 1.0e-8, alg = :simultaneous, trscheme = (; alg = :fixedspace))
+boundary_alg = (; tol = 1.0e-8, alg = :simultaneous, trunc = (; alg = :fixedspace))
 gradient_alg = (; tol = 1.0e-6, alg = :eigsolver, maxiter = 10, iterscheme = :diffgauge)
 optimizer_alg = (; tol = 1.0e-4, alg = :lbfgs, maxiter = 80, ls_maxiter = 3, ls_maxfg = 3)
 ````