43 lines
778 B
Julia
43 lines
778 B
Julia
include("CPU.jl")
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T=Float32
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function V_test(r2)
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return -4 * exp(-r2 / 4)
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end
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d = 1
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n = 3
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N = 8
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L::T = 16
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n_imag = 0
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μ::T = 0.5
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H = HOperator{T}(V_test, d, n, N, L, μ, n_imag)
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dim = N ^ (d * (n - 1))
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H_mat = zeros(Complex{T}, dim, dim)
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iter = CartesianIndices(vectorDims(H))
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open("temp/mat_dump.csv", "w") do f
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# this can be heavily optimized by getting rid of 'bi' vector
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for i in 1 : dim
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bi = zeros(Complex{T}, vectorDims(H)...)
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bi[iter[i]] = 1
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for j in 1 : dim
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bj = zeros(Complex{T}, vectorDims(H)...)
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bj[iter[j]] = 1
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Hbj = similar(bj)
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Hbj = mul!(Hbj, H, bj)
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H_mat[i, j] = dot(bi, Hbj)
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end
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end
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end
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evals, _ = eigen(H_mat)
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evals = real.(evals)
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print(evals)
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