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Update print statements DMRG
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@lkdvos
lkdvos committed Oct 19, 2023
1 parent 3032a57 commit 488a28e
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134 changes: 73 additions & 61 deletions src/algorithms/groundstate/dmrg.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -20,30 +20,33 @@ Single site DMRG algorithm for finding groundstates.
end

function find_groundstate!(Ψ::AbstractFiniteMPS, H, alg::DMRG, envs=environments(Ψ, H))
tol = alg.tol
maxiter = alg.maxiter
iter = 0
delta::Float64 = 2 * tol

while iter < maxiter && delta > tol
delta = 0.0

for pos in [1:(length(Ψ) - 1); length(Ψ):-1:2]
h = ∂∂AC(pos, Ψ, H, envs)
_, vecs = eigsolve(h, Ψ.AC[pos], 1, :SR, alg.eigalg)
delta = max(delta, calc_galerkin(Ψ, pos, envs))
Ψ.AC[pos] = vecs[1]
t₀ = Base.time_ns()
ϵ::Float64 = 2 * alg.tol

for iter in 1:(alg.maxiter)
global ϵ = 0.0
Δt = @elapsed begin
for pos in [1:(length(Ψ) - 1); length(Ψ):-1:2]
h = ∂∂AC(pos, Ψ, H, envs)
_, vecs = eigsolve(h, Ψ.AC[pos], 1, :SR, alg.eigalg)
ϵ = max(ϵ, calc_galerkin(Ψ, pos, envs))
Ψ.AC[pos] = vecs[1]
end

Ψ, envs = alg.finalize(iter, Ψ, H, envs)::Tuple{typeof(Ψ),typeof(envs)}
end

alg.verbose && @info "Iteraton $(iter) error $(delta)"
flush(stdout)
alg.verbose &&
@info "DMRG iteration:" iter ϵ λ = sum(expectation_value(Ψ, H, envs)) Δt

iter += 1

Ψ, envs = alg.finalize(iter, Ψ, H, envs)::Tuple{typeof(Ψ),typeof(envs)}
ϵ <= alg.tol && break
iter == alg.maxiter &&
@warn "DMRG maximum iterations" iter ϵ λ = sum(expectation_value(Ψ, H, envs))
end

return Ψ, envs, delta
Δt = (Base.time_ns() - t₀) / 1.0e9
alg.verbose && @info "DMRG summary:" ϵ λ = sum(expectation_value(Ψ, H, envs)) Δt
return Ψ, envs, ϵ
end

"""
Expand All @@ -70,53 +73,62 @@ end
end

function find_groundstate!(Ψ::AbstractFiniteMPS, H, alg::DMRG2, envs=environments(Ψ, H))
tol = alg.tol
maxiter = alg.maxiter
iter = 0
delta::Float64 = 2 * tol

while iter < maxiter && delta > tol
delta = 0.0

#left to right sweep
for pos in 1:(length(Ψ) - 1)
@plansor ac2[-1 -2; -3 -4] := Ψ.AC[pos][-1 -2; 1] * Ψ.AR[pos + 1][1 -4; -3]

_, vecs = eigsolve(∂∂AC2(pos, Ψ, H, envs), ac2, 1, :SR, alg.eigalg)
newA2center = first(vecs)

al, c, ar, ϵ = tsvd(newA2center; trunc=alg.trscheme, alg=TensorKit.SVD())
normalize!(c)
v = @plansor ac2[1 2; 3 4] * conj(al[1 2; 5]) * conj(c[5; 6]) * conj(ar[6; 3 4])
delta = max(delta, abs(1 - abs(v)))

Ψ.AC[pos] = (al, complex(c))
Ψ.AC[pos + 1] = (complex(c), _transpose_front(ar))
t₀ = Base.time_ns()
ϵ::Float64 = 2 * alg.tol

for iter in 1:(alg.maxiter)
ϵ = 0.0
Δt = @elapsed begin
#left to right sweep
for pos in 1:(length(Ψ) - 1)
@plansor ac2[-1 -2; -3 -4] := Ψ.AC[pos][-1 -2; 1] * Ψ.AR[pos + 1][1 -4; -3]

_, vecs = eigsolve(∂∂AC2(pos, Ψ, H, envs), ac2, 1, :SR, alg.eigalg)
newA2center = first(vecs)

al, c, ar, = tsvd!(newA2center; trunc=alg.trscheme, alg=TensorKit.SVD())
normalize!(c)
v = @plansor ac2[1 2; 3 4] *
conj(al[1 2; 5]) *
conj(c[5; 6]) *
conj(ar[6; 3 4])
ϵ = max(ϵ, abs(1 - abs(v)))

Ψ.AC[pos] = (al, complex(c))
Ψ.AC[pos + 1] = (complex(c), _transpose_front(ar))
end

for pos in (length(Ψ) - 2):-1:1
@plansor ac2[-1 -2; -3 -4] := Ψ.AL[pos][-1 -2; 1] * Ψ.AC[pos + 1][1 -4; -3]

_, vecs = eigsolve(∂∂AC2(pos, Ψ, H, envs), ac2, 1, :SR, alg.eigalg)
newA2center = first(vecs)

al, c, ar, = tsvd!(newA2center; trunc=alg.trscheme, alg=TensorKit.SVD())
normalize!(c)
v = @plansor ac2[1 2; 3 4] *
conj(al[1 2; 5]) *
conj(c[5; 6]) *
conj(ar[6; 3 4])
ϵ = max(ϵ, abs(1 - abs(v)))

Ψ.AC[pos + 1] = (complex(c), _transpose_front(ar))
Ψ.AC[pos] = (al, complex(c))
end

Ψ, envs = alg.finalize(iter, Ψ, H, envs)::Tuple{typeof(Ψ),typeof(envs)}
end

for pos in (length(Ψ) - 2):-1:1
@plansor ac2[-1 -2; -3 -4] := Ψ.AL[pos][-1 -2; 1] * Ψ.AC[pos + 1][1 -4; -3]

_, vecs = eigsolve(∂∂AC2(pos, Ψ, H, envs), ac2, 1, :SR, alg.eigalg)
newA2center = first(vecs)

al, c, ar, ϵ = tsvd(newA2center; trunc=alg.trscheme, alg=TensorKit.SVD())
normalize!(c)
v = @plansor ac2[1 2; 3 4] * conj(al[1 2; 5]) * conj(c[5; 6]) * conj(ar[6; 3 4])
delta = max(delta, abs(1 - abs(v)))

Ψ.AC[pos + 1] = (complex(c), _transpose_front(ar))
Ψ.AC[pos] = (al, complex(c))
end
alg.verbose && @info "DMRG iteration:" iter ϵ λ = expectation_value(Ψ, H, envs) Δt

alg.verbose && @info "Iteraton $(iter) error $(delta)"
flush(stdout)
#finalize
Ψ, envs = alg.finalize(iter, Ψ, H, envs)::Tuple{typeof(Ψ),typeof(envs)}
iter += 1
ϵ <= alg.tol && break
iter == alg.maxiter &&
@warn "DMRG maximum iterations" iter ϵ λ = expectation_value(Ψ, H, envs)
end

return Ψ, envs, delta
Δt = (Base.time_ns() - t₀) / 1.0e9
alg.verbose && @info "DMRG summary:" ϵ λ = sum(expectation_value(Ψ, H, envs)) Δt
return Ψ, envs, ϵ
end

function find_groundstate(Ψ, H, alg::Union{DMRG,DMRG2}, envs...)
Expand Down
27 changes: 13 additions & 14 deletions src/algorithms/groundstate/vumps.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -35,11 +35,11 @@ https://arxiv.org/abs/1701.07035.
gauge_tolfactor::Float64 = Defaults.gauge_tolfactor
end

function updatetols(alg::VUMPS, iter, ε)
function updatetols(alg::VUMPS, iter, ϵ)
if alg.dynamical_tols
tol_eigs = between(alg.tol_min, ε * alg.eigs_tolfactor / sqrt(iter), alg.tol_max)
tol_envs = between(alg.tol_min, ε * alg.envs_tolfactor / sqrt(iter), alg.tol_max)
tol_gauge = between(alg.tol_min, ε * alg.gauge_tolfactor / sqrt(iter), alg.tol_max)
tol_eigs = between(alg.tol_min, ϵ * alg.eigs_tolfactor / sqrt(iter), alg.tol_max)
tol_envs = between(alg.tol_min, ϵ * alg.envs_tolfactor / sqrt(iter), alg.tol_max)
tol_gauge = between(alg.tol_min, ϵ * alg.gauge_tolfactor / sqrt(iter), alg.tol_max)
else # preserve legacy behavior
tol_eigs = alg.tol_galerkin / 10
tol_envs = Defaults.tol
Expand All @@ -56,11 +56,11 @@ end

function find_groundstate(Ψ::InfiniteMPS, H, alg::VUMPS, envs=environments(Ψ, H))
t₀ = Base.time_ns()
ε::Float64 = calc_galerkin(Ψ, envs)
ϵ::Float64 = calc_galerkin(Ψ, envs)
temp_ACs = similar.(Ψ.AC)

for iter in 1:(alg.maxiter)
tol_eigs, tol_envs, tol_gauge = updatetols(alg, iter, ε)
tol_eigs, tol_envs, tol_gauge = updatetols(alg, iter, ϵ)
Δt = @elapsed begin
eigalg = Arnoldi(; tol=tol_eigs)

Expand All @@ -83,21 +83,20 @@ function find_groundstate(Ψ::InfiniteMPS, H, alg::VUMPS, envs=environments(Ψ,

Ψ, envs = alg.finalize(iter, Ψ, H, envs)::Tuple{typeof(Ψ),typeof(envs)}

ε = calc_galerkin(Ψ, envs)
ϵ = calc_galerkin(Ψ, envs)
end

alg.verbose &&
@info "VUMPS iteration:" iter ε λ = sum(expectation_value(Ψ, H, envs)) Δt
@info "VUMPS iteration:" iter ϵ λ = sum(expectation_value(Ψ, H, envs)) Δt

ε <= alg.tol_galerkin && break
ϵ <= alg.tol_galerkin && break
iter == alg.maxiter &&
@warn "VUMPS maximum iterations" iter ε λ = sum(expectation_value(Ψ, H, envs)) Δt
@warn "VUMPS maximum iterations" iter ϵ λ = sum(expectation_value(Ψ, H, envs))
end

alg.verbose && @info "VUMPS summary:" ε λ = sum(expectation_value(Ψ, H, envs)) Δt = (
(Base.time_ns() - t₀) / 1.0e9
)
return Ψ, envs, ε
Δt = (Base.time_ns() - t₀) / 1.0e9
alg.verbose && @info "VUMPS summary:" ϵ λ = sum(expectation_value(Ψ, H, envs)) Δt
return Ψ, envs, ϵ
end

function _vumps_localupdate!(AC′, loc, Ψ, H, envs, eigalg, factalg=QRpos())
Expand Down

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