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Today's most popular techniques for accurately calculating the dynamics ofthe reduced density operator in an open quantum system, either require, or gaingreat computational benefits, from representing the bath response function a(t)in the form a(t)={\Sigma}_k^K p_k e^{O_k t} . For some of these techniques, thenumber of terms in the series K plays the lead role in the computational costof the calculation, and is therefore often a limiting factor in simulating openquantum system dynamics. We present an open source MATLAB program calledBATHFIT 1, whose input is any spectral distribution functions J(w) or bathresponse function, and whose output attempts to be the set of parameters{p_k,w_k}_k=1^K such that for a given value of K, the series {\Sigma}_k^k p_ke^{O_k t} is as close as possible to a(t). This should allow the user torepresent a(t) as accurately as possible with as few parameters as possible.The program executes non-linear least squares fitting, and for a very widevariety of spectral distribution functions, competent starting parameters areused for these fits. For most forms of J(w), these starting parameters, and theexact a(t) corresponding to the given J(w), are calculated using the recentPade decomposition technique - therefore this program can also be used tomerely implement the Pade decomposition for these spectral distributionfunctions; and it can also be used just to efficiently and accurately calculatea(t) for any given J(w) . The program also gives the J(w) corresponding to agiven a(t), which may allow one to assess the quality (in the w-domain) of arepresentation of a(t) being used. Finally, the program can calculate thediscretized influence functional coefficients for any J(w), and this iscomputed very efficiently for most forms of J(w) by implementing the recenttechnique published in [Quantum Physics Letters (2012) 1 (1) pg. 35].

Optimal representation of the bath response function & fast calculation of influence functional coefficients in open quantum systems with BATHFIT 1