Fractal platform
As part of my work with eXact lab I contribute to developing Fractal, "a framework to process high content imaging data at scale and prepare it for interactive visualization".Links to code: All components of the Fractal framework (including server/client components, a set of computational tasks, and a set of examples) are available as repositories of the fractal-analytics-platform organization. Several of them are also released as packages on PyPI: fractal-server, fractal-client, fractal-tasks-core.
BoseHubbardGutzwiller
This code implements the homogeneous Gutzwiller variational wave function for the Bose-Hubbard model. The search for the optimal wave-function parameters is performed through Simulated Annealing, a Monte Carlo method for stochastic optimization.Links to code: Zenodo, GitHub
Author: Tommaso Comparin
DOI identifier: 10.5281/zenodo.846904
Used in: Chaviguri et al. [Phys. Rev. A 97, 023614 (2018)], Huembeli et al. [Phys. Rev. B 97, 134109 (2018)].
GutzwillerDynamics
This code implements the Gutzwiller variational wave function for the Bose-Hubbard model. The Gutzwiller coefficients are site-dependent (so that one can add an external confinement potential) and complex-valued (so that one can use this code both for imaginary- and real-time dynamics).Link to code: https://github.com/tcompa/GutzwillerDynamics
Author: Tommaso Comparin
Note: This code is relatively recent, please open a github issue or contact me if you notice any unexpected behavior.
Laughlin-Metropolis
This code implements the Metropolis Monte Carlo algorithm to sample configurations from the Laughlin wave function with an arbitrary number of quasiholes (see for instance Morf&Halperin, 1986).Links to code: Zenodo, GitHub
Authors: Tommaso Comparin, Elia Macaluso
DOI identifier: 10.5281/zenodo.1161969
Used in: Umucalilar et al. [Phys. Rev. Lett. 120, 230403 (2018)].