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Reference

Methods

QFiND.AAAfittedSD — Method
(specdens::AAAfittedSD)(ω::Float64; scale::Float64=1.0) -> Float64

Compute the spectral density fitted by the AAA algorithm.

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QFiND.BrownianSD — Method
(specdens::BrownianSD)(ω::Float64; scale::Float64=1.0) -> Float64

Compute the spectral density for the Brownian oscillator model.

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QFiND.DrudeSD — Method
(specdens::DrudeSD)(ω::Float64; scale::Float64=1.0) -> Float64

Compute the spectral density for the Drude-Lorentz model.

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QFiND.PowerLawExpSD — Method
(specdens::PowerLawExpSD)(ω::Float64; scale::Float64=1.0) -> Float64

Compute the spectral density for the Power-law with exponential cutoff model.

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QFiND.SemicircleSD — Method
(specdens::SemicircleSD)(ω::Float64; scale::Float64=1.0) -> Float64

Compute the spectral density for the Semicircle model.

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QFiND.TannorMeyerSD — Method
(specdens::TannorMeyerSD)(ω::Float64; scale::Float64=1.0) -> Float64

Compute the spectral density for the Tannor-Meyer model.

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QFiND.balanced_truncation — Method
balanced_truncation(a::AbstractVector{<:Number}, c::AbstractVector{<:Number}, eps::Float64) :: Exponentials

Given the exponents a and coefficients c of a sum of exponentials, compute a new sum of exponentials with a reduced number of terms for a given tolerance eps. The initial exponents must have positive real part.

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QFiND.balanced_truncation — Method
balanced_truncation(a::AbstractVector{<:Number}, c::AbstractVector{<:Number}, M::Int) :: Exponentials

Given the exponents a and coefficients c of a sum of exponentials, compute a new sum of exponentials with a given number of terms M. The initial exponents must have positive real part.

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QFiND.bsdo_discr — Method
bsdo(sbeta, ω::AbstractVector{Float64}, M_sp::Int)

Compute the discretization of the QNSD using the BSDO method.

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QFiND.chebyshev_bcf — Method
chebyshev_bcf(cheb::ChebyshevExpansion)

Create a bath correlation function using Chebyshev expansion.

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QFiND.chebyshev_bcf — Method
chebyshev_bcf(sd::SpectralDensity, Temp::Real, ω_min::Real, ω_max::Real, 
              n_terms::Int; kwargs...)

Create a bath correlation function using Chebyshev expansion.

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QFiND.chebyshev_expansion — Method
chebyshev_expansion(sd::SpectralDensity, Temp::Real, ω_min::Real, ω_max::Real, n_terms::Int; 
                   scale::Float64=1.0, rtol::Real=1e-8, atol::Real=1e-12)

Compute Chebyshev expansion coefficients for a bath correlation function using QuadGK.

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QFiND.evaluate_correlation — Method
evaluate_correlation(cheb::ChebyshevExpansion, t::Real)

Evaluate the correlation function at time t using Chebyshev expansion.

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QFiND.id_freq — Method
id_freq_rank(f::AbstractMatrix{ComplexF64}, frank::Int, rnd::Bool)

Perform interpolative decomposition on matrix f with a specified rank frank.

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QFiND.id_freq — Method
id_freq_eps(f::AbstractMatrix{Float64}, eps::Real, rnd::Bool)

Perform interpolative decomposition on matrix f with error tolerance eps.

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QFiND.id_freq — Method
id_freq_rank(f::AbstractMatrix{Float64}, frank::Int, rnd::Bool)

Perform interpolative decomposition on matrix f with a specified rank frank.

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QFiND.id_freq — Method
id_freq_eps(f::AbstractMatrix{Float64}, eps::Real, rnd::Bool)

Perform interpolative decomposition on matrix f with error tolerance eps.

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QFiND.id_time — Method
id_time(f::AbstractMatrix{ComplexF64}, frank::Int, rnd::Bool)

Perform interpolative decomposition on matrix f with a specified rank frank.

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QFiND.nnls_weight — Method
nnls_weight(t, B)

Estimate the coefficients (amplitudes) by solving a nonnegative least‐squares (NNLS) problem.

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