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Early Stopping Criteria besides number of iterations #11

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Early Stopping Criteria besides number of iterations #11

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e01e9a4
Allow atol / rtol as stopping criteria
iagoleal Dec 18, 2024
e385792
Use isapprox for calculating convergence
iagoleal Dec 19, 2024
508e65d
Allow time limit stopping criterion
iagoleal Dec 26, 2024
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28 changes: 26 additions & 2 deletions src/solver.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@ import Combinatorics: multiset_permutations

using ITensorMPS, ITensors
import ITensorMPS: MPS, MPO, dmrg, OpSum, OpName, SiteType, StateName
import ITensorMPS: AbstractObserver


function issquare(A :: AbstractMatrix)
Expand All @@ -14,6 +15,24 @@ function maybe(f::Function, mx::Union{T, Nothing}; default=nothing) where T
return isnothing(mx) ? default : f(mx)
end

mutable struct ConvergenceObserver <: AbstractObserver
atol :: Float64
rtol :: Float64
time_limit :: Float64
init_time :: Float64
previous_energy :: Float64

ConvergenceObserver(atol, rtol, time_limit = +Inf) = new(atol, rtol, time_limit, time() , +Inf)
end

function ITensorMPS.checkdone!(o::ConvergenceObserver; energy, sweep, kwargs...)
converged = isapprox(energy, o.previous_energy; atol = o.atol, rtol = o.rtol)
o.previous_energy = energy

return converged || time() - o.init_time > o.time_limit
end


# Diagonal matrix whose eigenvalues are the ordered feasible values for an integer variable.
# For qubits, this is a projection on |1>. Or equivalently, (I - σ_z) / 2.
# This looks like type piracy,
Expand Down Expand Up @@ -130,8 +149,11 @@ minimize(Q; device = Metal.mtl)
function minimize( Q :: AbstractMatrix{T}
, l :: Union{AbstractVector{T}, Nothing} = nothing
, c :: T = zero(T)
; cutoff :: Float64 = 1e-8
, iterations :: Int = 10
; cutoff :: Float64 = 1e-8
, atol :: Float64 = cutoff
, rtol :: Float64 = atol
, iterations :: Int = 10
, time_limit :: Float64 = +Inf
, maxdim = [10, 20, 100, 100, 200]
, device :: Function = identity
, kwargs...
Expand All @@ -145,9 +167,11 @@ function minimize( Q :: AbstractMatrix{T}
# Initial product state
# Slight entanglement to help DMRG avoid local minima
psi0 = random_mps(T, sites; linkdims=2)
observer = ConvergenceObserver(atol, rtol, time_limit)

energy, tn = dmrg(device(H), device(psi0)
; nsweeps = iterations
, observer = observer
, maxdim, cutoff, kwargs...)

# The calculated energy has approximation errors compared to the true solution.
Expand Down
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