Temporary fix for docs

Author: lkdvos

docs/Project.toml

@@ -2,7 +2,6 @@
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 KrylovKit = "0b1a1467-8014-51b9-945f-bf0ae24f4b77"
 MPSKit = "bb1c41ca-d63c-52ed-829e-0820dda26502"
-MPSKitModels = "ca635005-6f8c-4cd1-b51d-8491250ef2ab"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 Polynomials = "f27b6e38-b328-58d1-80ce-0feddd5e7a45"
 Symbolics = "0c5d862f-8b57-4792-8d23-62f2024744c7"

docs/src/index.md

@@ -37,7 +37,6 @@ operators and models.
 using TensorOperations
 using TensorKit
 using MPSKit
-using MPSKitModels
 using LinearAlgebra: norm
 ```
 
@@ -48,7 +47,6 @@ using LinearAlgebra
 using TensorOperations
 using TensorKit
 using MPSKit
-using MPSKitModels
 ```
 
 Finite MPS are characterised by a set of tensors, one for each site, which each have 3 legs.
@@ -106,10 +104,16 @@ Using the pre-defined models in `MPSKitModels`, we can construct the groundstate
 transverse field Ising model:
 
 ```@example finitemps
-H = transverse_field_ising(; J=1.0, g=0.5)
+J = 1.0
+g = 0.5
+lattice = fill(ComplexSpace(2), 10)
+X = TensorMap(ComplexF64[0 1; 1 0], ComplexSpace(2), ComplexSpace(2))
+Z = TensorMap(ComplexF64[1 0; 0 -1], space(X))
+H = FiniteMPOHamiltonian(lattice, (i, i+1) => -J * X ⊗ X for i in 1:length(lattice)-1) +
+    FiniteMPOHamiltonian(lattice, (i,) => - g * Z for i in 1:length(lattice))
 find_groundstate!(mps, H, DMRG(; maxiter=10))
 E0 = expectation_value(mps, H)
-println("<mps|H|mps> = $(sum(real(E0)) / length(mps))")
+println("<mps|H|mps> = $real(E0)")
 ```
 
 ### Infinite Matrix Product States
@@ -119,7 +123,6 @@ using LinearAlgebra
 using TensorOperations
 using TensorKit
 using MPSKit
-using MPSKitModels
 ```
 
 Similarly, an infinite MPS can be constructed by specifying the tensors for the unit cell,
@@ -173,11 +176,16 @@ println("<mps|𝕀₁|mps> = $N2")
     observable computed from the MPS would either blow up to infinity or vanish to zero.
 
 Finally, the MPS can be optimized in order to determine groundstates of given Hamiltonians.
-Using the pre-defined models in `MPSKitModels`, we can construct the groundstate for the
-transverse field Ising model:
+There are plenty of pre-defined models in `MPSKitModels`, but we can also manually construct
+the groundstate for the transverse field Ising model:
 
 ```@example infinitemps
-H = transverse_field_ising(; J=1.0, g=0.5)
+J = 1.0
+g = 0.5
+lattice = PeriodicVector([ComplexSpace(2)])
+X = TensorMap(ComplexF64[0 1; 1 0], ComplexSpace(2), ComplexSpace(2))
+Z = TensorMap(ComplexF64[1 0; 0 -1], space(X))
+H = InfiniteMPOHamiltonian(lattice, (1, 2) => -J * X ⊗ X, (1,) => - g * Z)
 mps, = find_groundstate(mps, H, VUMPS(; maxiter=10))
 E0 = expectation_value(mps, H)
 println("<mps|H|mps> = $(sum(real(E0)) / length(mps))")
@@ -212,4 +220,4 @@ request or an issue on the [GitHub repository](https://github.com/QuantumKitHub/
 - Gertian Roose, Laurens Vanderstraeten, Jutho Haegeman, and Nick Bultinck. Anomalous domain wall condensation in a modified ising chain. Phys. Rev. B, 99: 195132, May 2019. 10.1103/​PhysRevB.99.195132.
 https:/​/​doi.org/​10.1103/​PhysRevB.99.195132
 - Roose, G., Bultinck, N., Vanderstraeten, L. et al. Lattice regularisation and entanglement structure of the Gross-Neveu model. J. High Energ. Phys. 2021, 207 (2021). https://doi.org/10.1007/JHEP07(2021)207
-- Roose, G., Haegeman, J., Van Acoleyen, K. et al. The chiral Gross-Neveu model on the lattice via a Landau-forbidden phase transition. J. High Energ. Phys. 2022, 19 (2022). https://doi.org/10.1007/JHEP06(2022)019
+- Roose, G., Haegeman, J., Van Acoleyen, K. et al. The chiral Gross-Neveu model on the lattice via a Landau-forbidden phase transition. J. High Energ. Phys. 2022, 19 (2022). https://doi.org/10.1007/JHEP06(2022)019

docs/src/lib/lib.md

@@ -12,13 +12,7 @@ MPSMultiline
 ```@docs
 AbstractMPO
 MPO
-FiniteMPO
-InfiniteMPO
 MPOHamiltonian
-FiniteMPOHamiltonian
-InfiniteMPOHamiltonian
-SparseMPO
-DenseMPO
 ```
 
 ## Environments
@@ -31,23 +25,6 @@ MPSKit.FiniteEnvironments
 MPSKit.IDMRGEnvironments
 ```
 
-## Generic actions
-```@docs
-∂C
-∂∂C
-∂AC
-∂∂AC
-∂AC2
-∂∂AC2
-
-c_proj
-ac_proj
-ac2_proj
-
-transfer_left
-transfer_right
-```
-
 ## Algorithms
 ```@docs
 find_groundstate

docs/src/man/algorithms.md

@@ -1,7 +1,5 @@
 ```@meta
-DocTestSetup = quote
-    using MPSKit, MPSKitModels, TensorKit
-end
+DocTestSetup = :( using MPSKit, TensorKit)
 ```
 
 # [Algorithms](@id um_algorithms)
@@ -168,7 +166,9 @@ in the transverse field Ising model, we calculate the first excited state as sho
 provided code snippet, amd check the accuracy against theoretical values. Some deviations
 are expected, both due to finite-bond-dimension and finite-size effects.
 
-```jldoctest; output = false
+<!-- TODO: reenable doctest -->
+
+```julia
 # Model parameters
 g = 10.0
 L = 16
@@ -194,7 +194,9 @@ in the unit cell in a plane-wave superposition, requiring momentum specification
 [Haldane gap](https://iopscience.iop.org/article/10.1088/0953-8984/1/19/001) computation in
 the Heisenberg model illustrates this approach.
 
-```jldoctest; output = false
+<!-- TODO: reenable doctest -->
+
+```julia
 # Setting up the model and momentum
 momentum = π
 H = heisenberg_XXX()
@@ -219,7 +221,9 @@ trivial total charge. However, quasiparticles with different charges can be obta
 the sector keyword. For instance, in the transverse field Ising model, we consider an
 excitation built up of flipping a single spin, aligning with `Z2Irrep(1)`.
 
-```jldoctest; output = false
+<!-- TODO: reenable doctest -->
+
+```julia
 g = 10.0
 L = 16
 H = transverse_field_ising(Z2Irrep; g)
@@ -260,7 +264,9 @@ often referred to as the 'Chepiga ansatz', named after one of the authors of thi
 
 This is supported via the following syntax:
 
-```jldoctest
+<!-- TODO: reenable doctest -->
+
+```julia
 g = 1.0
 L = 16
 H = transverse_field_ising(; g)
@@ -278,7 +284,9 @@ true
 In order to improve the accuracy, a two-site version also exists, which varies two
 neighbouring sites:
 
-```jldoctest
+<!-- TODO: reenable doctest -->
+
+```julia
 g = 1.0
 L = 16
 H = transverse_field_ising(; g)

docs/src/man/operators.md

@@ -103,7 +103,7 @@ h = 0.5
 chain = fill(ℂ^2, 3) # a finite chain of 4 sites, each with a 2-dimensional Hilbert space
 single_site_operators = [1 => -h * S_z, 2 => -h * S_z, 3 => -h * S_z]
 two_site_operators = [(1, 2) => -J * S_x ⊗ S_x, (2, 3) => -J * S_x ⊗ S_x]
-H_ising = FIniteMPOHamiltonian(chain, single_site_operators..., two_site_operators...);
+H_ising = FiniteMPOHamiltonian(chain, single_site_operators..., two_site_operators...);
 ```
 
 Various alternative constructions are possible, such as using a `Dict` with key-value pairs
@@ -229,9 +229,11 @@ general form, by supplying a 3-dimensional array $W$ to the constructor. Here, t
 dimension specifies the site in the unit cell, the second dimension specifies the row of the
 matrix, and the third dimension specifies the column of the matrix.
 
-```@example operators
+<!-- TODO: reenable doctest -->
+
+```julia
 data = Array{Any,3}(missing, 1, 3, 3) # missing is interpreted as zero
-data[1, 1, 1] = id(Matrix{ComplexF64}, ℂ^2)
+data[1, 1, 1] = id(ComplexF64, ℂ^2)
 data[1, 3, 3] = 1 # regular numbers are interpreted as identity operators
 data[1, 1, 2] = -J * S_x
 data[1, 2, 3] = S_x
@@ -263,34 +265,3 @@ a collection (direct sum) of spaces, one for each row/column.
 
 <!-- TODO: add examples virtualspace once blocktensors are in place -->
 
-## DenseMPO
-
-This operator is used for statistical physics problems. It is simply a periodic array of mpo tensors.
-
-Can be created using
-```julia
-DenseMPO(t::AbstractArray{T,1}) where T<:MPOTensor
-```
-
-## SparseMPO
-
-`SparseMPO` is similar to a `DenseMPO`, in that it again represents an mpo tensor, periodically repeated. However this type keeps track of all internal zero blocks, allowing for a more efficient representation of certain operators (such as time evolution operators and quantum hamiltonians). You can convert a sparse mpo to a densempo, but the converse does not hold.
-
-
-Indexing a `SparseMPO` returns a `SparseMPOSlice` object, which has 3 fields
-
-```@docs
-MPSKit.SparseMPOSlice
-```
-
-When indexing a `SparseMPOSlice` at index `[j, k]` (or equivalently `SparseMPO[i][j, k]`), the code looks up the corresponding field in `Os[j, k]`. Either that element is a tensormap, in which case it gets returned. If it equals `zero(E)`, then we return a tensormap
-```julia
-domspaces[j] * pspace ← pspace * imspaces[k]
-```
-with norm zero. If the element is a nonzero number, then implicitly we have the identity operator there (multiplied by that element).
-
-The idea here is that you don't have to worry about the underlying structure, you can just index into a sparsempo as if it is a vector of matrices. Behind the scenes we then optimize certain contractions by using the sparsity structure.
-
-SparseMPO are always assumed to be periodic in the first index (position).
-In this way, we can both represent periodic infinite mpos and place dependent finite mpos.
-

src/algorithms/expval.jl

@@ -19,7 +19,7 @@ acts, while the operator is either a `AbstractTensorMap` or a `FiniteMPO`.
 
 # Examples
 ```jldoctest
-julia> ψ = FiniteMPS(ones, Float64, 4, ℂ^2, ℂ^3);
+julia> ψ = FiniteMPS(ones(Float64, (ℂ^2)^4));
 
 julia> S_x = TensorMap(Float64[0 1; 1 0], ℂ^2, ℂ^2);
 
@@ -28,9 +28,6 @@ julia> round(expectation_value(ψ, 2 => S_x))
 
 julia> round(expectation_value(ψ, (2, 3) => S_x ⊗ S_x))
 1.0
-
-julia> round(expectation_value(ψ, MPOHamiltonian(S_x)))
-4.0
 ```
 """
 function expectation_value end