Hello everyone!
I want to use ITensorTDVP.jl to achieve global subspace expansion (GSE) TDVP algorithm to do real time evolution.
But errors occured when I use function ITensorTDVP.extend(psi,[psi,phi1,phi2]) to exptend basis.
ERROR: LoadError: `perutedims!(output_tensor::Tensor, tensor::Tensor, perm, f::Function=(r, t) -> t)` not implemented for `typeof(output_tensor) = NDTensors.DiagBlockSparseTensor{Float64, 2, Tuple{Index{Vector{Pair{QN, Int64}}}, Index{Vector{Pair{QN, Int64}}}}, NDTensors.DiagBlockSparse{Float64, Float64, 2}}`, `typeof(tensor) = NDTensors.BlockSparseTensor{Float64, 2, Tuple{Index{Vector{Pair{QN, Int64}}}, Index{Vector{Pair{QN, Int64}}}}, NDTensors.BlockSparse{Float64, Vector{Float64}, 2}}`, `perm = (1, 2)`, and `f = #283`.
Stacktrace:
[1] error(s::String)
@ Base .\error.jl:35
[2] permutedims!(output_tensor::NDTensors.DiagBlockSparseTensor{Float64, 2, Tuple{Index{Vector{Pair{QN, Int64}}}, Index{Vector{Pair{QN, Int64}}}}, NDTensors.DiagBlockSparse{Float64, Float64, 2}}, tensor::NDTensors.BlockSparseTensor{Float64, 2, Tuple{Index{Vector{Pair{QN, Int64}}}, Index{Vector{Pair{QN, Int64}}}}, NDTensors.BlockSparse{Float64, Vector{Float64}, 2}}, perm::Tuple{Int64, Int64}, f::Function)
@ NDTensors C:\Users\Wang\.julia\packages\NDTensors\tAAFJ\src\generic_tensor_operations.jl:20
[3] permutedims!!(output_tensor::NDTensors.DiagBlockSparseTensor{Float64, 2, Tuple{Index{Vector{Pair{QN, Int64}}}, Index{Vector{Pair{QN, Int64}}}}, NDTensors.DiagBlockSparse{Float64, Float64, 2}}, tensor::NDTensors.BlockSparseTensor{Float64, 2, Tuple{Index{Vector{Pair{QN, Int64}}}, Index{Vector{Pair{QN, Int64}}}}, NDTensors.BlockSparse{Float64, Vector{Float64}, 2}}, perm::Tuple{Int64, Int64}, f::Function)
@ NDTensors C:\Users\Wang\.julia\packages\NDTensors\tAAFJ\src\generic_tensor_operations.jl:14
[4] _map!!(f::Function, R::NDTensors.DiagBlockSparseTensor{Float64, 2, Tuple{Index{Vector{Pair{QN, Int64}}}, Index{Vector{Pair{QN, Int64}}}}, NDTensors.DiagBlockSparse{Float64, Float64, 2}}, T1::NDTensors.DiagBlockSparseTensor{Float64, 2, Tuple{Index{Vector{Pair{QN, Int64}}}, Index{Vector{Pair{QN, Int64}}}}, NDTensors.DiagBlockSparse{Float64, Float64, 2}}, T2::NDTensors.BlockSparseTensor{Float64, 2, Tuple{Index{Vector{Pair{QN, Int64}}}, Index{Vector{Pair{QN, Int64}}}}, NDTensors.BlockSparse{Float64, Vector{Float64}, 2}})
@ ITensors C:\Users\Wang\.julia\packages\ITensors\4aoLl\src\itensor.jl:1921
[5] map!(f::Function, R::ITensor, T1::ITensor, T2::ITensor)
@ ITensors C:\Users\Wang\.julia\packages\ITensors\4aoLl\src\itensor.jl:1926
[6] copyto!
@ C:\Users\Wang\.julia\packages\ITensors\4aoLl\src\broadcast.jl:321 [inlined]
[7] materialize!
@ .\broadcast.jl:871 [inlined]
[8] materialize!
@ .\broadcast.jl:868 [inlined]
[9] -(A::ITensor, B::ITensor)
@ ITensors C:\Users\Wang\.julia\packages\ITensors\4aoLl\src\itensor.jl:1843
[10] extend(psi::MPS, phis::Vector{MPS}; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ ITensorTDVP C:\Users\Wang\.julia\packages\ITensorTDVP\xjpcf\src\basis_extend.jl:47
[11] extend(psi::MPS, phis::Vector{MPS})
@ ITensorTDVP C:\Users\Wang\.julia\packages\ITensorTDVP\xjpcf\src\basis_extend.jl:21
[12] top-level scope
@ F:\data\superlattice\julia_example\GSE_TDVP\sl_gse_tdvp.jl:216
in expression starting at F:\data\superlattice\julia_example\GSE_TDVP\sl_gse_tdvp.jl:6
The following script shows the detail.
tstep=0.01
ttotal=100
sites=siteinds("Boson",L;conserve_qns = true,conserve_number = true,dim = 5)
#initial state
state=[]
for n=1:L
if isodd(n)
push!(state,"1")
elseif iseven(n)
push!(state,"0")
end
end
psi=productMPS(sites,state)
#MPO of hamiltonian
hal=OpSum()
for i=1:L-1
if isodd(i)
hal += -j1,"Adag",i,"A",i+1
hal += -j1,"Adag",i+1,"A",i
elseif iseven(i)
hal += -j2,"Adag",i,"A",i+1
hal += -j2,"Adag",i+1,"A",i
end
hal += U/2,"N",i,"N",i
hal += -U/2,"N",i
end
hal += U/2,"N",L,"N",L
hal += -U/2,"N",L
H = toMPO(hal,sites)
#the first-order expansion of the time evolution operator,
Id=MPO(sites,"Id")
Krylov_MPO=Id-im*tstep*H
#time evolution
for i in 0:1:div(ttotal,tstep)
tsofar=i*tstep
@show tsofar
noise=1e-14
psi=normalize!(psi)
phi1=apply(Krylov_MPO,psi)
normalize!(phi1)
phi2=apply(Krylov_MPO,phi1)
normalize!(phi2)
#subspace expansion
psi=ITensorTDVP.extend(psi,[psi,phi1,phi2])
phi1=0
phi2=0
phi3=0
#one-site TDVP
psi = tdvp(
solver_backend="applyexp",
H,
-im*tstep,
psi;
nsweeps=1,
maxdim=300,
cutoff=1E-14,
noise,
reverse_step=true,
nsite=1,
order=1,
outputlevel=1,
normalize=true,
solver_tol=1e-12,
solver_maxiter=300,
solver_krylovdim=50
)
end
Are there some mistakes in my script or did I misunderstand the way to achieve GSE-TDVP algorithm in ITensor?
Also, how could I set the “linkdim” larger than 1 when I want to use “MPS(sites,state)” or “productMPS(sites,state)” like randomMPS(sites,state;linkdims=50) to specify a certain initial state for the purpose of one-site TDVP real time evolution?
It seems like when “linkdim=1”, the initial MPS cannot totally evolved when use one-site TDVP.
Any help will be appreciate!