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Update tensorOps.jl
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@tfmlaX
tfmlaX authored Jan 30, 2024
1 parent c3f0397 commit b393c3e
Showing 1 changed file with 27 additions and 27 deletions.
54 changes: 27 additions & 27 deletions src/tensorOps.jl
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
function ACOAC(AC::Array{T1, 3}, O::Array{T2, 2}) where {T1,T2}
@tensor v = scalar(conj(AC[a,b,s']) * O[s',s] * AC[a,b,s])
@tensor v = tensorscalar(conj(AC[a,b,s']) * O[s',s] * AC[a,b,s])
end

function contractC!(A::Array{T1,2}, C::Array{T2,2}, dir::Int) where {T1,T2}
Expand Down Expand Up @@ -33,10 +33,10 @@ function contractC!(A::Array{T1,6}, C::Array{T2,2}, dir::Int) where {T1,T2}
end

function rhoAAstar(ρ::Array{T1,2}, A::Array{T2,2}, indir::Int) where {T1,T2}
@tensoropt ρO = scalar(ρ[a0,b0] * conj(A[a0,s]) * A[b0,s])
@tensoropt ρO = tensorscalar(ρ[a0,b0] * conj(A[a0,s]) * A[b0,s])
end
function rhoAAstar(ρ::Array{T1,2}, A::Array{T2,2}) where {T1,T2}
@tensoropt ρO = scalar(ρ[a0,b0] * conj(A[a0,s]) * A[b0,s])
@tensoropt ρO = tensorscalar(ρ[a0,b0] * conj(A[a0,s]) * A[b0,s])
end
function rhoAAstar(ρ::Array{T1,2}, A::Array{T2,3}, indir::Int, outdir::Int) where {T1,T2}
indir==1 && return @tensoropt ρO[a,b] := ρ[a0,b0] * conj(A[a0,a,s]) * A[b0,b,s]
Expand Down Expand Up @@ -78,29 +78,29 @@ function rhoAAstar(ρ::Array{T1,2}, A::Array{T2,5}, indir::Int, outdir::Int) whe
end

function rhoAOAstar(ρ::Array{T1,2}, A::Array{T2,2}, O::Array{T3,2}, indir::Int, ::Nothing) where {T1,T2,T3}
@tensoropt ρO = scalar(ρ[a0,b0] * conj(A[a0,s']) * O[s',s] * A[b0,s])
@tensoropt ρO = tensorscalar(ρ[a0,b0] * conj(A[a0,s']) * O[s',s] * A[b0,s])
end
function rhoAOAstar(ρ::Array{T1,2}, A::Array{T2,2}, O::Array{T3,2}, ::Nothing) where {T1,T2,T3}
@tensoropt ρO = scalar(ρ[a0,b0] * conj(A[a0,s']) * O[s',s] * A[b0,s])
@tensoropt ρO = tensorscalar(ρ[a0,b0] * conj(A[a0,s']) * O[s',s] * A[b0,s])
end
function rhoAOAstar(ρ::Array{T1,2}, A::Array{T2,3}, O::Array{T3,2}, indir::Int, ::Nothing) where {T1,T2,T3}
indir==1 && return @tensoropt ρO = scalar(ρ[a0,b0] * conj(A[a0,c0,s']) * O[s',s] * A[b0,c0,s])
indir==2 && return @tensoropt ρO = scalar(ρ[a0,b0] * conj(A[c0,a0,s']) * O[s',s] * A[c0,b0,s])
indir==1 && return @tensoropt ρO = tensorscalar(ρ[a0,b0] * conj(A[a0,c0,s']) * O[s',s] * A[b0,c0,s])
indir==2 && return @tensoropt ρO = tensorscalar(ρ[a0,b0] * conj(A[c0,a0,s']) * O[s',s] * A[c0,b0,s])
end
function rhoAOAstar(ρ::Array{T1,2}, A::Array{T2,3}, O::Array{T3,2}, ::Nothing) where {T1,T2,T3}
return @tensoropt ρO = scalar(ρ[a0,b0] * conj(A[a0,c0,s']) * O[s',s] * A[b0,c0,s])
return @tensoropt ρO = tensorscalar(ρ[a0,b0] * conj(A[a0,c0,s']) * O[s',s] * A[b0,c0,s])
end

function rhoAOAstar(ρ::Array{T1,2}, A::Array{T2,4}, O::Array{T3,2}, indir::Int, ::Nothing) where {T1,T2,T3}
indir==1 && return @tensoropt ρO = scalar(ρ[a0,b0] * conj(A[a0,c0,c1,s']) * O[s',s] * A[b0,c0,c1,s])
indir==2 && return @tensoropt ρO = scalar(ρ[a0,b0] * conj(A[c0,a0,c1,s']) * O[s',s] * A[c0,b0,c1,s])
indir==3 && return @tensoropt ρO = scalar(ρ[a0,b0] * conj(A[c0,c1,a0,s']) * O[s',s] * A[c0,c1,b0,s])
indir==1 && return @tensoropt ρO = tensorscalar(ρ[a0,b0] * conj(A[a0,c0,c1,s']) * O[s',s] * A[b0,c0,c1,s])
indir==2 && return @tensoropt ρO = tensorscalar(ρ[a0,b0] * conj(A[c0,a0,c1,s']) * O[s',s] * A[c0,b0,c1,s])
indir==3 && return @tensoropt ρO = tensorscalar(ρ[a0,b0] * conj(A[c0,c1,a0,s']) * O[s',s] * A[c0,c1,b0,s])
end
function rhoAOAstar(ρ::Array{T1,2}, A::Array{T2,5}, O::Array{T3,2}, indir::Int, ::Nothing) where {T1,T2,T3}
indir==1 && return @tensoropt ρO = scalar(ρ[a0,b0] * conj(A[a0,c0,c1,c2,s']) * O[s',s] * A[b0,c0,c1,c2,s])
indir==2 && return @tensoropt ρO = scalar(ρ[a0,b0] * conj(A[c0,a0,c1,c2,s']) * O[s',s] * A[c0,b0,c1,c2,s])
indir==3 && return @tensoropt ρO = scalar(ρ[a0,b0] * conj(A[c0,c1,a0,c2,s']) * O[s',s] * A[c0,c1,b0,c2,s])
indir==4 && return @tensoropt ρO = scalar(ρ[a0,b0] * conj(A[c0,c1,c2,a0,s']) * O[s',s] * A[c0,c1,c2,b0,s])
indir==1 && return @tensoropt ρO = tensorscalar(ρ[a0,b0] * conj(A[a0,c0,c1,c2,s']) * O[s',s] * A[b0,c0,c1,c2,s])
indir==2 && return @tensoropt ρO = tensorscalar(ρ[a0,b0] * conj(A[c0,a0,c1,c2,s']) * O[s',s] * A[c0,b0,c1,c2,s])
indir==3 && return @tensoropt ρO = tensorscalar(ρ[a0,b0] * conj(A[c0,c1,a0,c2,s']) * O[s',s] * A[c0,c1,b0,c2,s])
indir==4 && return @tensoropt ρO = tensorscalar(ρ[a0,b0] * conj(A[c0,c1,c2,a0,s']) * O[s',s] * A[c0,c1,c2,b0,s])
end

function rhoAOAstar(ρ::Array{T1,2}, A::Array{T2,3}, O::Array{T3,2}, indir::Int, outdir::Int) where {T1,T2,T3}
Expand Down Expand Up @@ -243,24 +243,24 @@ function updateenv4(A, M, F1, F2, F3)
@tensor F[a,b,c] := F1[a1,b1,c1]*F2[a2,b2,c2]*F3[a3,b3,c3]*conj(A[a1,a2,a3,a,s'])*M[b1,b2,b3,b,s',s]*A[c1,c2,c3,c,s]
end

@tensoropt function applyH2(AA, H1, H2, F1, F2)
HAA[a1,s1,a2,s2] := F1[a1,b1,c1]*AA[c1,s1',c2,s2']*H1[b1,b,s1,s1']*H2[b,b2,s2,s2']*F2[a2,b2,c2]
function applyH2(AA, H1, H2, F1, F2)
@tensoropt HAA[a1,s1,a2,s2] := F1[a1,b1,c1]*AA[c1,s1',c2,s2']*H1[b1,b,s1,s1']*H2[b,b2,s2,s2']*F2[a2,b2,c2]
# @tensoropt HAA[a1,s1,a2,s2] := F1[a1,b1,c1]*AA[c1,s1',c2,s2']*H1[b1,b,s1,s1']*H2[b,b2,s2,s2']*F2[a2,b2,c2]
end
@tensoropt function applyH1(AC, M, F)
HAC[a,s'] := F[a,b,c]*AC[c,s]*M[b,s',s]
function applyH1(AC, M, F)
@tensoropt HAC[a,s'] := F[a,b,c]*AC[c,s]*M[b,s',s]
end
@tensoropt function applyH1(AC, M, F0, F1)
HAC[a0,a1,s'] := F0[a0,b0,c0]*F1[a1,b1,c1]*AC[c0,c1,s]*M[b0,b1,s',s]
function applyH1(AC, M, F0, F1)
@tensoropt HAC[a0,a1,s'] := F0[a0,b0,c0]*F1[a1,b1,c1]*AC[c0,c1,s]*M[b0,b1,s',s]
end
@tensoropt function applyH1(AC, M, F0, F1, F2)
HAC[a0,a1,a2,s'] := F0[a0,b0,c0]*F1[a1,b1,c1]*F2[a2,b2,c2]*AC[c0,c1,c2,s]*M[b0,b1,b2,s',s]
function applyH1(AC, M, F0, F1, F2)
@tensoropt HAC[a0,a1,a2,s'] := F0[a0,b0,c0]*F1[a1,b1,c1]*F2[a2,b2,c2]*AC[c0,c1,c2,s]*M[b0,b1,b2,s',s]
end
@tensoropt function applyH1(AC, M, F0, F1, F2, F3)
HAC[a0,a1,a2,a3,s'] := F0[a0,b0,c0]*F1[a1,b1,c1]*F2[a2,b2,c2]*F3[a3,b3,c3]*AC[c0,c1,c2,c3,s]*M[b0,b1,b2,b3,s',s]
function applyH1(AC, M, F0, F1, F2, F3)
@tensoropt HAC[a0,a1,a2,a3,s'] := F0[a0,b0,c0]*F1[a1,b1,c1]*F2[a2,b2,c2]*F3[a3,b3,c3]*AC[c0,c1,c2,c3,s]*M[b0,b1,b2,b3,s',s]
end
@tensor function applyH0(C, F0, F1)
HC[α,β] := F0[α,a,α']*C[α',β']*F1[β,a,β']
function applyH0(C, F0, F1)
@tensor HC[α,β] := F0[α,a,α']*C[α',β']*F1[β,a,β']
end

#sets the right/left bond dimension of A, ie will truncate if Dnew is smaller than the current bond dimension and zero pad if it's larger
Expand Down

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