# Problem using DMRG-X **URL:** \ **Category:** DMRG and Numerical Methods\ **Created:** [November 8, 2022, 7:12pm UTC](https://itensor.discourse.group/t/problem-using-dmrg-x/506 "2022-11-08T19:12:09Z")\ **Posts on this page:** 3\ **Page:** 1
**Author:** ![ray-l](https://yyz2.discourse-cdn.com/free1/user_avatar/itensor.discourse.group/ray-l/32/76_2.png) [@ray-l](https://itensor.discourse.group/u/ray-l)\ **Post date:** [November 8, 2022, 7:12pm UTC](https://itensor.discourse.group/t/problem-using-dmrg-x/506/1 "2022-11-08T19:12:09Z")
Hi there, I’m following the test example of DMRG-X in the TDVP code. As of now the following minimal example does not work: (Btw by reading the original paper, I’m not sure if this method is completely general as it seems to rely heavily on MBL LIOM properties, but I’d assume your algorithms are not restrictive in terms of physics) ```julia @testset "DMRG-X" begin function HB(L) ampo = OpSum() hop = 1.0 t = 1.0 for j=1 :L-1 #println(hop) # Hopping ampo += -t * hop, "C",j,"Cdag",j+1 ampo += -t * hop, "C",j+1,"Cdag",j end return ampo end L = 12 N = 6 s = siteinds("Fermion", L, conserve_qns=true) H = MPO(HB(L), s) initstate = append!(["Occ" for n=1:N] , ["Emp" for n=1:L -N]) ψ = randomMPS(s, initstate) dmrg_x_kwargs = ( nsweeps=20, reverse_step=false, normalize=true, maxdim=20, cutoff=1e-10, outputlevel=0 ) ϕ = dmrg_x(ProjMPO(H), ψ; nsite=2, dmrg_x_kwargs...) end ``` And I get the following errors ```julia DMRG-X: Error During Test at /path/behavior_test.jl:8 Got exception outside of a @test Attempting to contract IndexSet: ((dim=2|id=346|"Fermion,Site,n=1") 1: QN("Nf",0,-1) => 1 2: QN("Nf",1,-1) => 1, (dim=2|id=823|"Fermion,Site,n=2") 1: QN("Nf",0,-1) => 1 2: QN("Nf",1,-1) => 1, (dim=1|id=859|"Link,l=2") 1: QN("Nf",4,-1) => 1) with IndexSet: ((dim=1|id=859|"Link,l=2") 1: QN("Nf",4,-1) => 1, (dim=2|id=823|"Fermion,Site,n=2") 1: QN("Nf",0,-1) => 1 2: QN("Nf",1,-1) => 1, (dim=2|id=346|"Fermion,Site,n=1") 1: QN("Nf",0,-1) => 1 2: QN("Nf",1,-1) => 1, (dim=2|id=780|"Link,eigen") 1: QN("Nf",5,-1) => 2) QN indices must have opposite direction to contract, but indices: (dim=2|id=346|"Fermion,Site,n=1") 1: QN("Nf",0,-1) => 1 2: QN("Nf",1,-1) => 1 and: (dim=2|id=346|"Fermion,Site,n=1") 1: QN("Nf",0,-1) => 1 2: QN("Nf",1,-1) => 1 do not have opposite directions. Stacktrace: [1] error(s::String) @ Base ./error.jl:33 [2] compute_contraction_labels(Ais::Tuple{Index{Vector{Pair{QN, Int64}}}, Index{Vector{Pair{QN, Int64}}}, Index{Vector{Pair{QN, Int64}}}}, Bis::NTuple{4, Index{Vector{Pair{QN, Int64}}}}) @ ITensors ~/.julia/packages/ITensors/OjQuG/src/indexset.jl:648 [3] _contract(A::NDTensors.BlockSparseTensor{Float64, 3, Tuple{Index{Vector{Pair{QN, Int64}}}, Index{Vector{Pair{QN, Int64}}}, Index{Vector{Pair{QN, Int64}}}}, NDTensors.BlockSparse{Float64, Vector{Float64}, 3}}, B::NDTensors.BlockSparseTensor{Float64, 4, NTuple{4, Index{Vector{Pair{QN, Int64}}}}, NDTensors.BlockSparse{Float64, Vector{Float64}, 4}}) @ ITensors ~/.julia/packages/ITensors/OjQuG/src/itensor.jl:1863 [4] _contract(A::ITensor, B::ITensor) @ ITensors ~/.julia/packages/ITensors/OjQuG/src/itensor.jl:1870 [5] contract(A::ITensor, B::ITensor) @ ITensors ~/.julia/packages/ITensors/OjQuG/src/itensor.jl:1974 [6] * @ ~/.julia/packages/ITensors/OjQuG/src/itensor.jl:1961 [inlined] [7] dmrg_x_solver(PH::ProjMPO, t::Float64, psi0::ITensor; kwargs::Base.Pairs{Symbol, Real, Tuple{Symbol, Symbol}, NamedTuple{(:current_time, :outputlevel), Tuple{Float64, Int64}}}) @ ITensorTDVP ~/.julia/packages/ITensorTDVP/p6CK4/src/dmrg_x.jl:5 [8] tdvp_site_update!(nsite_val::Val{2}, reverse_step_val::Val{false}, solver::typeof(ITensorTDVP.dmrg_x_solver), PH::ProjMPO, psi::MPS, b::Int64; current_time::Float64, outputlevel::Int64, time_step::Float64, normalize::Bool, direction::Base.Order.ForwardOrdering, noise::Float64, which_decomp::Nothing, svd_alg::String, cutoff::Float64, maxdim::Int64, mindim::Int64, maxtruncerr::Float64) @ ITensorTDVP ~/.julia/packages/ITensorTDVP/p6CK4/src/tdvp_step.jl:302 [9] tdvp_site_update!(solver::typeof(ITensorTDVP.dmrg_x_solver), PH::ProjMPO, psi::MPS, b::Int64; nsite::Int64, reverse_step::Bool, current_time::Float64, outputlevel::Int64, time_step::Float64, normalize::Bool, direction::Base.Order.ForwardOrdering, noise::Float64, which_decomp::Nothing, svd_alg::String, cutoff::Float64, maxdim::Int64, mindim::Int64, maxtruncerr::Float64) @ ITensorTDVP ~/.julia/packages/ITensorTDVP/p6CK4/src/tdvp_step.jl:155 [10] tdvp_sweep(direction::Base.Order.ForwardOrdering, solver::Function, PH::ProjMPO, time_step::Float64, psi::MPS; kwargs::Base.Pairs{Symbol, Real, NTuple{11, Symbol}, NamedTuple{(:current_time, :reverse_step, :nsite, :nsweeps, :normalize, :maxdim, :cutoff, :outputlevel, :sweep, :mindim, :noise), Tuple{Float64, Bool, Int64, Int64, Bool, Int64, Float64, Int64, Int64, Int64, Float64}}}) @ ITensorTDVP ~/.julia/packages/ITensorTDVP/p6CK4/src/tdvp_step.jl:79 [11] tdvp_step(order::ITensorTDVP.TDVPOrder{2, Base.Order.ForwardOrdering()}, solver::Function, PH::ProjMPO, time_step::Float64, psi::MPS; current_time::Float64, kwargs::Base.Pairs{Symbol, Real, NTuple{10, Symbol}, NamedTuple{(:reverse_step, :nsite, :nsweeps, :normalize, :maxdim, :cutoff, :outputlevel, :sweep, :mindim, :noise), Tuple{Bool, Int64, Int64, Bool, Int64, Float64, Int64, Int64, Int64, Float64}}}) @ ITensorTDVP ~/.julia/packages/ITensorTDVP/p6CK4/src/tdvp_step.jl:9 [12] macro expansion @ ~/.julia/packages/ITensorTDVP/p6CK4/src/tdvp_generic.jl:84 [inlined] [13] macro expansion @ ./timing.jl:299 [inlined] [14] tdvp(solver::Function, PH::ProjMPO, t::Float64, psi0::MPS; kwargs::Base.Pairs{Symbol, Real, NTuple{7, Symbol}, NamedTuple{(:reverse_step, :nsite, :nsweeps, :normalize, :maxdim, :cutoff, :outputlevel), Tuple{Bool, Int64, Int64, Bool, Int64, Float64, Int64}}}) @ ITensorTDVP ~/.julia/packages/ITensorTDVP/p6CK4/src/tdvp_generic.jl:83 [15] #dmrg_x#50 @ ~/.julia/packages/ITensorTDVP/p6CK4/src/dmrg_x.jl:12 [inlined] [16] macro expansion @ ~/Desktop/Code/iTensor/mysrc/behavior_test.jl:39 [inlined] [17] macro expansion @ /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/Test/src/Test.jl:1283 [inlined] [18] top-level scope @ ~/Desktop/Code/iTensor/mysrc/behavior_test.jl:10 [19] eval @ ./boot.jl:373 [inlined] [20] include_string(mapexpr::typeof(identity), mod::Module, code::String, filename::String) @ Base ./loading.jl:1196 [21] include_string(m::Module, txt::String, fname::String) @ Base ./loading.jl:1206 [22] invokelatest(::Any, ::Any, ::Vararg{Any}; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}) @ Base ./essentials.jl:716 [23] invokelatest(::Any, ::Any, ::Vararg{Any}) @ Base ./essentials.jl:714 + further VSCode env errors Test Summary: | Error Total DMRG-X | 1 1 ERROR: Some tests did not pass: 0 passed, 0 failed, 1 errored, 0 broken. ``` ---
**Author:** ![mtfishman](https://yyz2.discourse-cdn.com/free1/user_avatar/itensor.discourse.group/mtfishman/32/11_2.png) [@mtfishman](https://itensor.discourse.group/u/mtfishman)\ **Post date:** [November 8, 2022, 10:19pm UTC](https://itensor.discourse.group/t/problem-using-dmrg-x/506/2 "2022-11-08T22:19:06Z")
It looks like we just hadn’t tested out the DMRG-X code for QN conserving tensors, could you raise an issue about it at [Issues · ITensor/ITensorTDVP.jl · GitHub](https://github.com/ITensor/ITensorTDVP.jl/issues)? The part that is particular to the physics in some more abstract way is that currently the solver works by diagonalizing the local Hamiltonian and picking the eigenstate that has the largest overlap with the previous state. This is inspired by the l-bit view of MBL, where you try to find an eigenstate that is close to a certain product state. The particular details of the solver may depend on the application (for example, it could be modified to target a particular eigenvalue, which I have done for other applications). The implementation is very simple: [ITensorTDVP.jl/dmrg\_x.jl at ae85e5e854559f59482b94ff5e762e634ca4a797 · ITensor/ITensorTDVP.jl · GitHub](https://github.com/ITensor/ITensorTDVP.jl/blob/ae85e5e854559f59482b94ff5e762e634ca4a797/src/dmrg_x.jl#L1-L14) so you could easily define your own solver for your application (though of course we should fix the bug that you’ve come across with QN conserving tensors)! ---
**Author:** ![ray-l](https://yyz2.discourse-cdn.com/free1/user_avatar/itensor.discourse.group/ray-l/32/76_2.png) [@ray-l](https://itensor.discourse.group/u/ray-l)\ **Post date:** [November 8, 2022, 10:36pm UTC](https://itensor.discourse.group/t/problem-using-dmrg-x/506/3 "2022-11-08T22:36:53Z")
Thank you! I have raised an issue and will look into specific applications.