Precomputed derivatives IV

Revert "Precomputed derivatives III"

This reverts commit d704ccf.

Precomputed derivatives IV

Precomputed derivatives V

reduce test terminal clutter

update plots script

playing around with more kernels

remove piracy

rework jordanmpo

small fix

Author: lkdvos

benchmark/Project.toml

@@ -4,7 +4,9 @@ BlockTensorKit = "5f87ffc2-9cf1-4a46-8172-465d160bd8cd"
 CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
+MKL = "33e6dc65-8f57-5167-99aa-e5a354878fb2"
 MPSKit = "bb1c41ca-d63c-52ed-829e-0820dda26502"
 MPSKitModels = "ca635005-6f8c-4cd1-b51d-8491250ef2ab"
 TOML = "fa267f1f-6049-4f14-aa54-33bafae1ed76"
 TensorKit = "07d1fe3e-3e46-537d-9eac-e9e13d0d4cec"
+TensorKitManifolds = "11fa318c-39cb-4a83-b1ed-cdc7ba1e3684"

benchmark/plot_results.jl

@@ -8,12 +8,14 @@ using Statistics
 resultdir = joinpath(@__DIR__, "results")
 resultfile(i) = "results_MPSKit@bench$i.json"
 
+versions = [0, 1, 2, 3, 5]
+
 df_contract = let df = DataFrame(
         :version => Int[], :model => String[], :symmetry => String[],
         :D => Int[], :V => Int[], :memory => Int[], :allocs => Int[], :times => Vector{Int}[]
     )
 
-    for version in 0:3
+    for version in versions
         result = JSON.parsefile(joinpath(resultdir, resultfile(version)))
         for (model, model_res) in result.data.derivatives.data.AC2_contraction.data
             for (symmetry, sym_res) in model_res.data
@@ -35,7 +37,7 @@ df_prep = let df = DataFrame(
         :D => Int[], :V => Int[], :memory => Int[], :allocs => Int[], :times => Vector{Int}[]
     )
 
-    for version in 0:3
+    for version in versions
         result = JSON.parsefile(joinpath(resultdir, resultfile(version)))
         for (model, model_res) in result.data.derivatives.data.AC2_preparation.data
             for (symmetry, sym_res) in model_res.data

src/MPSKit.jl

@@ -60,6 +60,7 @@ using Compat: @compat
 # -------
 using TensorKit
 using TensorKit: BraidingTensor
+using TensorKit: TupleTools as TT
 using MatrixAlgebraKit
 using MatrixAlgebraKit: TruncationStrategy, PolarViaSVD, LAPACK_SVDAlgorithm
 using BlockTensorKit
@@ -141,6 +142,7 @@ include("environments/lazylincocache.jl")
 include("algorithms/fixedpoint.jl")
 include("algorithms/derivatives/derivatives.jl")
 include("algorithms/derivatives/mpo_derivatives.jl")
+include("algorithms/derivatives/hamiltonian_derivatives.jl")
 include("algorithms/derivatives/projection_derivatives.jl")
 include("algorithms/expval.jl")
 include("algorithms/toolbox.jl")

src/algorithms/derivatives/derivatives.jl

@@ -217,27 +217,15 @@ Base.:*(h::LazySum{<:Union{DerivativeOrMultiplied}}, v) = h(v)
 # Operator preparation
 # --------------------
 """
-    prepare_operator!!(O, x, [backend], [allocator]) -> O′, x′
+    prepare_operator!!(O, [backend], [allocator]) -> O′
 
 Given an operator and vector, try to construct a more efficient representation of that operator for repeated application.
 This should always be used in conjunction with [`unprepare_operator!!`](@ref).
 """
-function prepare_operator!!(
-        O, x,
-        backend::AbstractBackend = DefaultBackend(), allocator = DefaultAllocator()
-    )
-    return O, x
-end
-
-"""
-    unprepare_operator!!(y, O, x, [backend], [allocator]) -> y′
+prepare_operator!!(O, backend::AbstractBackend = DefaultBackend(), allocator = DefaultAllocator()) = O
 
-Given the result `y` of applying a prepared operator `O` on vectors like `x`, undo the preparation work on the vector, and clean up the operator.
-This should always be used in conjunction with [`prepare_operator!!`](@ref).
-"""
-function unprepare_operator!!(
-        y, O, x,
-        backend::AbstractBackend = DefaultBackend(), allocator = DefaultAllocator()
-    )
-    return y
-end
+# to make benchmark scripts run
+prepare_operator!!(O, x::AbstractTensorMap, backend::AbstractBackend = DefaultBackend(), allocator = DefaultAllocator()) =
+    prepare_operator!!(O, backend, allocator), x
+unprepare_operator!!(y, O, x, backend::AbstractBackend = DefaultBackend(), allocator = DefaultAllocator()) =
+    y