Merge pull request #53 from QuantumKitHub/pb-ctmrg-allsides

Implement simultaneous CTMRG scheme and CTMRG gradients without gauge-fix differentiation

README.md

@@ -45,9 +45,8 @@ ctm_alg = CTMRG(; tol=1e-10, miniter=4, maxiter=100, verbosity=1, trscheme=trunc
 opt_alg = PEPSOptimize(;
     boundary_alg=ctm_alg,
     optimizer=LBFGS(4; maxiter=100, gradtol=1e-4, verbosity=2),
-    gradient_alg=GMRES(; tol=1e-6, maxiter=100),
+    gradient_alg=LinSolver(),
     reuse_env=true,
-    verbosity=2,
 )
 
 # ground state search

docs/src/index.md

@@ -30,9 +30,8 @@ ctm_alg = CTMRG(; tol=1e-10, miniter=4, maxiter=100, verbosity=1, trscheme=trunc
 opt_alg = PEPSOptimize(;
     boundary_alg=ctm_alg,
     optimizer=LBFGS(4; maxiter=100, gradtol=1e-4, verbosity=2),
-    gradient_alg=GMRES(; tol=1e-6, maxiter=100),
+    gradient_alg=LinSolver(),
     reuse_env=true,
-    verbosity=2,
 )
 
 # ground state search

examples/heisenberg.jl

@@ -11,13 +11,12 @@ H = square_lattice_heisenberg(; Jx=-1, Jy=1, Jz=-1)
 # Parameters
 χbond = 2
 χenv = 20
-ctm_alg = CTMRG(; tol=1e-10, miniter=4, maxiter=100, verbosity=1, trscheme=truncdim(χenv))
+ctm_alg = CTMRG(; tol=1e-10, miniter=4, maxiter=100, verbosity=2)
 opt_alg = PEPSOptimize(;
     boundary_alg=ctm_alg,
     optimizer=LBFGS(4; maxiter=100, gradtol=1e-4, verbosity=2),
-    gradient_alg=GMRES(; tol=1e-6, maxiter=100),
+    gradient_alg=LinSolver(; solver=GMRES(; tol=1e-6, maxiter=100)),
     reuse_env=true,
-    verbosity=2,
 )
 
 # Ground state search

src/PEPSKit.jl

@@ -13,6 +13,7 @@ using MPSKit: loginit!, logiter!, logfinish!, logcancel!
 include("utility/util.jl")
 include("utility/svd.jl")
 include("utility/rotations.jl")
+include("utility/diffset.jl")
 include("utility/hook_pullback.jl")
 include("utility/autoopt.jl")
 
@@ -31,7 +32,9 @@ include("environments/ctmrgenv.jl")
 include("operators/localoperator.jl")
 include("operators/models.jl")
 
+include("algorithms/ctmrg_gauge_fix.jl")
 include("algorithms/ctmrg.jl")
+include("algorithms/ctmrg_all_sides.jl")
 include("algorithms/peps_opt.jl")
 
 include("utility/symmetrization.jl")
@@ -54,19 +57,25 @@ Module containing default values that represent typical algorithm parameters.
 - `fpgrad_tol = 1e-6`: Convergence tolerance for the fixed-point gradient iteration
 """
 module Defaults
+    using TensorKit, KrylovKit, OptimKit
     const ctmrg_maxiter = 100
     const ctmrg_miniter = 4
-    const ctmrg_tol = 1e-12
-    const fpgrad_maxiter = 100
+    const ctmrg_tol = 1e-10
+    const fpgrad_maxiter = 20
     const fpgrad_tol = 1e-6
+    const ctmrgscheme = :simultaneous
+    const iterscheme = :fixed
+    const fwd_alg = TensorKit.SVD()
+    const rrule_alg = GMRES(; tol=ctmrg_tol)
+    const optimizer = LBFGS(10; maxiter=100, gradtol=1e-4, verbosity=2)
 end
 
 export SVDAdjoint, IterSVD, NonTruncSVDAdjoint
 export FixedSpaceTruncation, ProjectorAlg, CTMRG, CTMRGEnv
 export LocalOperator
 export expectation_value, costfun
 export leading_boundary
-export PEPSOptimize, GeomSum, ManualIter, LinSolve
+export PEPSOptimize, GeomSum, ManualIter, LinSolver
 export fixedpoint
 
 export InfinitePEPS, InfiniteTransferPEPS