Bruteforce fix for the identification issue
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6d254480fe
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@ -9,6 +9,14 @@ println("No of threads = ", Threads.nthreads())
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atol = 10^-5
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maxevals = 10^5
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exact_ref = reverse([4.076662025307587-0.012709842443350328im,
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3.613318119833891-0.007335804709990623im,
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3.1453431847006783-0.004030580410326795im,
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2.672967129943755-0.00211498327461944im,
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2.196542557810288-0.0010719835443437104im,
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1.7164583929199813-0.0005455212208182736im,
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1.233088227541505-0.0003070320106485624im])
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Λ = 0
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m = 1.0
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Va_of_r(r) = 2 * exp(-(r-3)^2 / (1.5)^2)
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@ -19,7 +27,7 @@ Vb_of_r(r) = -exp(-(r/3)^2)
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μ2 = m * 2/3
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vertices = [0, 2 - 0.1im, 3, 4]
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subdivisions = [10, 10, 10]
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subdivisions = [16, 10, 10]
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ks, ws = get_mesh(vertices, subdivisions)
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jmax = 4
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@ -65,9 +73,9 @@ E_max = 40
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@time "Ha" Ha = T + Va1 + Va2
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@time "Vb" Vb = Vb1 + Vb2
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@time "Eigenvalues" target_evals, _ = eigs(Ha, nev=3, ncv=24, which=:LI, maxiter=5000, tol=1e-5, ritzvec=false, check=1)
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@time "Eigenvalues" test_evals, _ = eigs(Ha, sigma=exact_ref[end], maxiter=5000, tol=1e-5, ritzvec=false, check=1)
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display(target_evals)
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display(test_evals)
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# free memory
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Es = n1s = l1s = n2s = l2s = mask1 = mask2 = T1 = T2 = V1_cache = V_relative_cache = V1 = V_relative = U = V2 = nothing
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@ -86,7 +94,7 @@ training_vecs = Vector{ComplexF64}[]
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for c in training_c
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println("Training for c = $c")
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H = Ha + c .* Vb
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evals, evecs = eigs(H, nev=3, ncv=24, which=:LI, maxiter=5000, tol=1e-5, ritzvec=true, check=1)
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evals, evecs = eigs(H, sigma=current_E, maxiter=5000, tol=1e-5, ritzvec=true, check=1)
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global current_E = nearest(evals, current_E)
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push!(training, current_E)
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@ -101,12 +109,12 @@ N_EC = transpose(EC_basis) * weights_mat * EC_basis
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Ha_EC = transpose(EC_basis) * weights_mat * Ha * EC_basis
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Vb_EC = transpose(EC_basis) * weights_mat * Vb * EC_basis
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current_E = 4.0766890719636635 - 0.01275892774109674im
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for c in extrapolating_c
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println("Extrapolating for c = $c")
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global current_E = pop!(exact_ref)
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H = Ha + c .* Vb
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evals, evecs = eigs(H, nev=3, ncv=24, which=:LI, maxiter=5000, tol=1e-5, ritzvec=true, check=1)
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evals, _ = eigs(H, sigma=current_E, maxiter=5000, tol=1e-5, ritzvec=false, check=1)
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global current_E = nearest(evals, current_E)
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push!(exact, current_E)
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