yapanuwan
/
BergEC-jl
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Missed one

This commit is contained in:
Nuwan Yapa 2025-01-13 18:22:38 -05:00
parent 29bbceac03
commit 9215bcad05
1 changed files with 8 additions and 55 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

63
calculations/3body_Berggren_B2R_EC.jl
View File

@ -1,17 +1,17 @@
using Plots include("../EC.jl")
training_c = [2.6, 2.4, 2.2, 2.0, 1.8] training_c = [2.6, 2.4, 2.2, 2.0, 1.8]
extrapolating_c = 0.0 : 0.2 : 1.2 extrapolating_c = 0.0 : 0.2 : 1.2
training_ref = -2.22 # complete list not needed because identification is simple training_ref = -2.22 # complete list not needed because identification is simple
exact_ref = reverse([4.076662025307587-0.012709842443350328im, extrapolating_ref = [4.076662025307587-0.012709842443350328im,
3.613318119833891-0.007335804709990623im, 3.613318119833891-0.007335804709990623im,
3.1453431847006783-0.004030580410326795im, 3.1453431847006783-0.004030580410326795im,
2.672967129943755-0.00211498327461944im, 2.672967129943755-0.00211498327461944im,
2.196542557810288-0.0010719835443437104im, 2.196542557810288-0.0010719835443437104im,
1.7164583929199813-0.0005455212208182736im, 1.7164583929199813-0.0005455212208182736im,
1.233088227541505-0.0003070320106485624im]) 1.233088227541505-0.0003070320106485624im]
include("../p_space_3body_resonance.jl") include("../p_space_3body_resonance.jl")
H0 = H H0 = H
@ -29,58 +29,11 @@ end
@time "Vp2" Vp2 = W_left * Vp2_HO * transpose(W_right) @time "Vp2" Vp2 = W_left * Vp2_HO * transpose(W_right)
@time "Vp" Vp = Vpb + Vp2 @time "Vp" Vp = Vpb + Vp2
# free memory
basis = Hb_blocks = Hb = basis_ho = V2_HO = W_right = W_left = V2 = nothing
GC.gc()
exact = ComplexF64[]
training = ComplexF64[]
extrapolated = ComplexF64[]
training_vecs = Vector{ComplexF64}[]
current_E = training_ref
for c in training_c
println("Training for c = $c")
local H = H0 + c .* Vp
local evals, evecs = eigs(H, sigma=current_E, maxiter=5000, tol=1e-5, ritzvec=true, check=1)
global current_E = nearest(evals, current_E)
push!(training, current_E)
push!(training_vecs, evecs[:, nearestIndex(evals, current_E)])
end
weights = repeat(kron(ws, ws), jmax + 1) weights = repeat(kron(ws, ws), jmax + 1)
weights_mat = spdiagm(weights)
training_vecs = vcat(training_vecs, conj(training_vecs)) # CA-EC EC = affine_EC(H0, Vp, weights)
println("Original EC dimensionality = $(length(training_vecs))") train!(EC, training_c; ref_eval=training_ref, CAEC=true)
@time "Gram-Schmidt" training_vecs = gram_schmidt!(training_vecs, weights; verbose=true) # orthonormalization extrapolate!(EC, extrapolating_c; ref_eval=extrapolating_ref)
EC_basis = hcat(training_vecs...) exportCSV(EC, "temp/Berggren_B2R.csv")
H0_EC = transpose(EC_basis) * weights_mat * H0 * EC_basis plot(EC, "temp/Berggren_B2R.pdf")
Vp_EC = transpose(EC_basis) * weights_mat * Vp * EC_basis
for c in extrapolating_c
println("Extrapolating for c = $c")
global current_E = pop!(exact_ref)
local H = H0 + c .* Vp
local evals, _ = eigs(H, sigma=current_E, maxiter=5000, tol=1e-5, ritzvec=false, check=1)
global current_E = nearest(evals, current_E)
push!(exact, current_E)
# extrapolation
H_EC = H0_EC + c .* Vp_EC
evals = eigvals(H_EC)
push!(extrapolated, nearest(evals, current_E))
end
exportCSV("temp/Berggren_B2R.csv", (training, exact, extrapolated), ("training", "exact", "extrapolated"))
scatter(real.(training),imag.(training), label="training")
scatter!(real.(exact),imag.(exact), label="exact")
scatter!(real.(extrapolated),imag.(extrapolated), label="extrapolated")
savefig("temp/Berggren_B2R.pdf")