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Register a new user$texttt{TRIQS}/texttt{SOM}$: Implementation of the Stochastic Optimization Method for Analytic Continuation
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We present the $texttt{TRIQS}/texttt{SOM}$ analytic continuation package, an efficient implementation of the Stochastic Optimization Method proposed by A. Mishchenko et al [Phys. Rev. B $textbf{62}$, 6317 (2000)]. $texttt{TRIQS}/texttt{SOM}$ strives to provide a high quality open source (distributed under the GNU General Public License version 3) alternative to the more widely adopted Maximum Entropy continuation programs. It supports a variety of analytic continuation problems encountered in the field of computational condensed matter physics. Those problems can be formulated in terms of response functions of imaginary time, Matsubara frequencies or in the Legendre polynomial basis representation. The application is based on the $texttt{TRIQS}$ C++/Python framework, which allows for easy interoperability with $texttt{TRIQS}$-based quantum impurity solvers, electronic band structure codes and visualization tools. Similar to other $texttt{TRIQS}$ packages, it comes with a convenient Python interface.
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We present $texttt{Maxent}$, a tool for performing analytic continuation of spectral functions using the maximum entropy method. The code operates on discrete imaginary axis datasets (values with uncertainties) and transforms this input to the real axis. The code works for imaginary time and Matsubara frequency data and implements the Legendre representation of finite temperature Greens functions. It implements a variety of kernels, default models, and grids for continuing bosonic, fermionic, anomalous, and other data. Our implementation is licensed under GPLv2 and extensively documented. This paper shows the use of the programs in detail.
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Asteroseismology is well-established in astronomy as the gold standard for determining precise and accurate fundamental stellar properties like masses, radii, and ages. Several tools have been developed for asteroseismic analyses but many of them are closed-source and therefore not accessible to the general astronomy community. Here we present $texttt{pySYD}$, a Python package for detecting solar-like oscillations and measuring global asteroseismic parameters. $texttt{pySYD}$ was adapted from the IDL-based $texttt{SYD}$ pipeline, which was extensively used to measure asteroseismic parameters for $textit{Kepler}$ stars. $texttt{pySYD}$ was developed using the same well-tested methodology and comes with several new improvements to provide accessible and reproducible results. Well-documented, open-source asteroseismology software that has been benchmarked against closed-source tools are critical to ensure the reproducibility of legacy results from the $textit{Kepler}$ mission. Moreover, $texttt{pySYD}$ will also be a promising tool for the broader astronomy community to analyze current and forthcoming data from the NASA TESS mission.
We present a Fourier Continuation-based parallel pseudospectral method for incompressible fluids in cuboid non-periodic domains. The method produces dispersionless and dissipationless derivatives with fast spectral convergence inside the domain, and with very high order convergence at the boundaries. Incompressibility is imposed by solving a Poisson equation for the pressure. Being Fourier-based, the method allows for fast computation of spectral transforms. It is compatible with uniform grids (although refined or nested meshes can also be implemented), which in turn allows for explicit time integration at sufficiently high Reynolds numbers. Using a new parallel code named SPECTER we illustrate the method with two problems: channel flow, and plane Rayleigh-Benard convection under the Boussinesq approximation. In both cases the method yields results compatible with previous studies using other high-order numerical methods, with mild requirements on the time step for stability.
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