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Keep track of S #98

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2a12135
Keeptrack_S
dartsushi Sep 28, 2025
8130a01
ef_change
dartsushi Sep 28, 2025
ade86cb
format
dartsushi Sep 28, 2025
0ed2a73
Update src/schemes/symmetric_looptnr.jl
VictorVanthilt Oct 13, 2025
fa45a5d
Update src/schemes/symmetric_looptnr.jl
VictorVanthilt Oct 13, 2025
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90 changes: 52 additions & 38 deletions src/schemes/symmetric_looptnr.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -23,15 +23,16 @@ $(TYPEDFIELDS)
"""
mutable struct SLoopTNR <: TNRScheme
T::TensorMap
S::TensorMap

gradalg::OptimKit.LBFGS
finalize!::Function
function SLoopTNR(
T::TensorMap;
gradalg = LBFGS(10; verbosity = 0, gradtol = 6.0e-7, maxiter = 40000),
finalize = (finalize!)
)
return new(T, gradalg, finalize)
T::TensorMap;
gradalg = LBFGS(10; verbosity = 0, gradtol = 6.0e-7, maxiter = 40000),
finalize = (finalize!),
)
return new(T, T, gradalg, finalize)
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@VictorVanthilt VictorVanthilt Sep 29, 2025

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If S is a three-leg tensor, why is it instantiated as a four-leg one?

end
end

Expand All @@ -42,8 +43,8 @@ function classical_ising_inv(β)

S = ℤ₂Space(0 => 1, 1 => 1)
T = zeros(Float64, S ⊗ S ← S' ⊗ S')
block(T, Irrep[ℤ₂](0)) .= [2x^2 2x * y; 2x * y 2y^2]
block(T, Irrep[ℤ₂](1)) .= [2x * y 2x * y; 2x * y 2x * y]
block(T, Irrep[ℤ₂](0)) .= [2x^2 2x*y; 2x*y 2y^2]
block(T, Irrep[ℤ₂](1)) .= [2x*y 2x*y; 2x*y 2x*y]

return permute(T, (1, 2, 3, 4))
end
Expand Down Expand Up @@ -77,14 +78,17 @@ function TTtoNorm(TT)
return tr(T8 * b)
end

function cost_looptnr(S, T)
function to_const_TT(T)
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@VictorVanthilt VictorVanthilt Sep 29, 2025

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What does this function do?

@tensor TT[-1 -2; -3 -4] := T[1 -1 2 -3] * conj(T[1 -2 2 -4])
return TTtoNorm(TT)
end

function cost_looptnr(S, T, const_TT)
@assert eltype(S) == Float64 "Modification is needed for complex numbers!"
SS = StoSS(S)
@tensor TT[-1 -2; -3 -4] := T[1 -1 2 -3] * conj(T[1 -2 2 -4])
@tensor TSS[-1 -2; -3 -4] := T[1 -1 2 -3] * conj(SS[1 -2 2 -4])
@tensor S4[-1 -2; -3 -4] := SS[1 -1 2 -3] * conj(SS[1 -2 2 -4])
# T
return TTtoNorm(TT) + TTtoNorm(S4) - 2 * TTtoNorm(TSS)
return (const_TT + TTtoNorm(S4) - 2 * TTtoNorm(TSS)) / const_TT
end

########## Gradient Optimization ##########
Expand All @@ -95,12 +99,10 @@ function fg(f, A)
end

function optimize_S(scheme, S)
opt_fun(x) = cost_looptnr(x, scheme.T)
const_TT = to_const_TT(scheme.T)
opt_fun(x) = cost_looptnr(x, scheme.T, const_TT)
opt_fg(x) = fg(opt_fun, x)
Sopt, fx, gx, numfg, normgradhistory = optimize(
opt_fg, S,
scheme.gradalg
)
Sopt, fx, gx, numfg, normgradhistory = optimize(opt_fg, S, scheme.gradalg)
return Sopt
end

Expand All @@ -127,30 +129,35 @@ function Ψ_corner(T)
return psi
end

function entanglement_filtering(T; trunc = truncbelow(1.0e-12))
function entanglement_filtering(T; ef_trunc = truncbelow(1.0e-14))
entanglement_function(steps, data) = abs(data[end])
entanglement_criterion = maxiter(100) & convcrit(1.0e-12, entanglement_function)

psi_center = Ψ_center(T)
psi_corner = Ψ_corner(T)

PR_list, PL_list = TNRKit.find_projectors(
psi_center, [1, 1, 1, 1], [3, 3, 3, 3],
entanglement_criterion, trunc
PR_list, PL_list = find_projectors(
psi_center,
[1, 1, 1, 1],
[3, 3, 3, 3],
entanglement_criterion,
ef_trunc,
)
P_bottom = PL_list[1]
P_right = PL_list[1]

PR_list, PL_list = TNRKit.find_projectors(
PR_list, PL_list = find_projectors(
psi_corner,
[1, 1, 1, 1], [3, 3, 3, 3],
entanglement_criterion, trunc
[1, 1, 1, 1],
[3, 3, 3, 3],
entanglement_criterion,
ef_trunc,
)
P_top = PL_list[3]
P_left = PL_list[3]

@tensor T_new[-1 -2 -3 -4] := T[1 2 3 4] * P_left[-1; 1] * P_bottom[-2; 2] *
P_top[-3; 3] * P_right[-4; 4]
@tensor T_new[-1 -2 -3 -4] :=
T[1 2 3 4] * P_left[-1; 1] * P_bottom[-2; 2] * P_top[-3; 3] * P_right[-4; 4]
return T_new
end

Expand All @@ -164,7 +171,7 @@ function ef_oneloop(T, trunc::TensorKit.TruncationScheme)
ΨA = Ψ_center(T)
ΨB = []

for i in 1:4
for i = 1:4
s1, s2 = SVD12(ΨA[i], truncdim(trunc.dim * 2))
push!(ΨB, s1)
push!(ΨB, s2)
Expand All @@ -173,14 +180,16 @@ function ef_oneloop(T, trunc::TensorKit.TruncationScheme)
ΨB_function(steps, data) = abs(data[end])
criterion = maxiter(100) & convcrit(1.0e-12, ΨB_function)
PR_list, _ = find_projectors(
ΨB, [1, 1, 1, 1, 1, 1, 1, 1], [2, 2, 2, 2, 2, 2, 2, 2],
criterion, trunc
ΨB,
[1, 1, 1, 1, 1, 1, 1, 1],
[2, 2, 2, 2, 2, 2, 2, 2],
criterion,
trunc,
)

ΨB_disentangled = []
for i in 1:1
@tensor B1[-2 -1; -3] := ΨB[i][-1; -2 2] *
PR_list[mod(i, 8) + 1][2; -3]
for i = 1:1
@tensor B1[-2 -1; -3] := ΨB[i][-1; -2 2] * PR_list[mod(i, 8)+1][2; -3]
push!(ΨB_disentangled, B1)
end
S = ΨB_disentangled[1]
Expand All @@ -195,23 +204,28 @@ function combine_4S(S)
end

########## Main funcitons ##########
function step!(scheme, trunc, oneloop)
scheme.T = entanglement_filtering(scheme.T)
function step!(scheme, trunc, oneloop; ef_trunc = truncbelow(1.0e-14))
scheme.T = entanglement_filtering(scheme.T; ef_trunc)
if oneloop == true
S = ef_oneloop(scheme.T, trunc)
else
S = decompose_T(scheme.T, trunc)
end
S = optimize_S(scheme, S)
scheme.T = combine_4S(S)
scheme.S = S
return scheme
end

function run!(
scheme::SLoopTNR, trscheme::TensorKit.TruncationScheme,
criterion::TNRKit.stopcrit; finalize_beginning = true, oneloop = true,
verbosity = 1
)
scheme::SLoopTNR,
trscheme::TensorKit.TruncationScheme,
criterion::TNRKit.stopcrit;
finalize_beginning = true,
oneloop = true,
verbosity = 1,
ef_trunc = truncbelow(1.0e-14),
)
data = []

LoggingExtras.withlevel(; verbosity) do
Expand All @@ -225,7 +239,7 @@ function run!(

t = @elapsed while crit
@infov 2 "Step $(steps + 1), data[end]: $(!isempty(data) ? data[end] : "empty")"
step!(scheme, trscheme, oneloop)
step!(scheme, trscheme, oneloop; ef_trunc)
push!(data, scheme.finalize!(scheme))
steps += 1
crit = criterion(steps, data)
Expand Down
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