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Replace Gram-Schmidt method by QR for random Chain initialization #175

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merged 6 commits into from
Aug 1, 2024
Merged

Replace Gram-Schmidt method by QR for random Chain initialization #175

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ef1edb0
Replace Gram-Schmidt method by QR for random Chain initialization
jofrevalles Jul 31, 2024
c668b00
Fix typo
jofrevalles Jul 31, 2024
adada43
Format code
jofrevalles Jul 31, 2024
49d6ec9
Fix function for odd numbered chain
jofrevalles Jul 31, 2024
8a49286
Change for-loop back into map
jofrevalles Aug 1, 2024
e5de892
Apply suggestions from code review
mofeing Aug 1, 2024
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38 changes: 10 additions & 28 deletions src/Ansatz/Chain.jl
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Original file line number Diff line number Diff line change
@@ -1,6 +1,5 @@
using LinearAlgebra
using Random
using Muscle: gramschmidt!

struct Chain <: Ansatz
super::Quantum
Expand Down Expand Up @@ -223,6 +222,7 @@ function Base.rand(rng::AbstractRNG, ::Type{A}, ::Type{B}, ::Type{S}; kwargs...)
return rand(rng, ChainSampler{B,S}(; kwargs...), B, S)
end

# TODO let choose the orthogonality center
function Base.rand(rng::Random.AbstractRNG, sampler::ChainSampler, ::Type{Open}, ::Type{State})
n = sampler.parameters.n
χ = sampler.parameters.χ
Expand All @@ -238,27 +238,19 @@ function Base.rand(rng::Random.AbstractRNG, sampler::ChainSampler, ::Type{Open},
(isodd(n) && i == n ÷ 2 + 1) ? (χl, χl) : (after_mid ? (χr, χl) : (χl, χr))
end

# fix for first site
i == 1 && ((χl, χr) = (χr, 1))

# orthogonalize by Gram-Schmidt algorithm
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A = gramschmidt!(rand(rng, T, χl, χr * p))
F = lq!(rand(rng, T, χl, p * χr))

A = reshape(A, χl, χr, p)
permutedims(A, (3, 1, 2))
reshape(Matrix(F.Q), χl, p, χr)
end

# reshape boundary sites
arrays[1] = reshape(arrays[1], p, p)
arrays[n] = reshape(arrays[n], p, p)

# normalize state
arrays[1] ./= sqrt(p)

return Chain(State(), Open(), arrays)
return Chain(State(), Open(), arrays; order=(:l, :o, :r))
end

# TODO let choose the orthogonality center
# TODO different input/output physical dims
function Base.rand(rng::Random.AbstractRNG, sampler::ChainSampler, ::Type{Open}, ::Type{Operator})
n = sampler.parameters.n
Expand All @@ -277,26 +269,16 @@ function Base.rand(rng::Random.AbstractRNG, sampler::ChainSampler, ::Type{Open},
(isodd(n) && i == n ÷ 2 + 1) ? (χl, χl) : (after_mid ? (χr, χl) : (χl, χr))
end

shape = if i == 1
(χr, ip, op)
elseif i == n
(χl, ip, op)
else
(χl, χr, ip, op)
end

# orthogonalize by Gram-Schmidt algorithm
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A = gramschmidt!(rand(rng, T, shape[1], prod(shape[2:end])))
A = reshape(A, shape)

(i == 1 || i == n) ? permutedims(A, (2, 3, 1)) : permutedims(A, (3, 4, 1, 2))
F = lq!(rand(rng, T, χl, ip * op * χr))
reshape(Matrix(F.Q), χl, ip, op, χr)
end

# normalize
ζ = min(χ, ip * op)
arrays[1] ./= sqrt(ζ)
# reshape boundary sites
arrays[1] = reshape(arrays[1], p, p, min(χ, ip * op))
arrays[n] = reshape(arrays[n], min(χ, ip * op), p, p)

return Chain(Operator(), Open(), arrays)
return Chain(Operator(), Open(), arrays; order=(:l, :i, :o, :r))
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end

Tenet.contract(tn::Chain, query::Symbol, args...; kwargs...) = contract!(copy(tn), Val(query), args...; kwargs...)
Expand Down
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