The ALPS project release 2.0: open source software for strongly correlated systems

By Bela Bauer, L. Carr, H. Evertz, A. Feiguin, J. Freire, S. Fuchs, L. Gamper, J. Gukelberger, Emanuel Gull, S. Guertler and 22 more. 2011

803 citations recorded by the source corpus.

We present release 2.0 of the ALPS (Algorithms and Libraries for Physics Simulations) project, an open source software project to develop libraries and application programs for the simulation of strongly correlated quantum lattice models such as quantum magnets, lattice bosons, and strongly correlated fermion systems. The code development is centered on common XML and HDF5 data formats, libraries to simplify and speed up code development, common evaluation and plotting tools, and simulation programs. The programs enable non-experts to start carrying out serial or parallel numerical simulations by providing basic implementations of the important algorithms for quantum lattice models: classical and quantum Monte Carlo (QMC) using non-local updates, extended ensemble simulations, exact and full diagonalization (ED), the density matrix renormalization group (DMRG) both in a static version and a dynamic time-evolving block decimation (TEBD) code, and quantum Monte Carlo solvers for dynamical mean field theory (DMFT). The ALPS libraries provide a powerful framework for programmers to develop their own applications, which, for instance, greatly simplify the steps of porting a serial code onto a parallel, distributed memory machine. Major changes in release 2.0 include the use of HDF5 for binary data, evaluation tools in Python, support for the Windows operating system, the use of CMake as build system and binary installation packages for Mac OS X and Windows, and integration with the VisTrails workflow provenance tool. The software is available from our web server at http://alps.comp-phys.org/.

Subfields: Condensed Matter Physics, Nuclear and High Energy Physics

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Citations in the corpus

A literature survey of low‐rank tensor approximation techniques (2013, neutral): “ALPS [18] provides C++ libraries for simulating strongly correlated quantum mechanical systems, including DMRG. Block [237] is a C++ implementation of the DMRG algorithms discussed in [236].”
Practical quantum advantage in quantum simulation (2022, background): “For example, although tremendous progress has been made possible by quantum Monte Carlo methods in recent decades 42–44 , path-integral Monte Carlo calculations face the challenge of the so-called sign problem in sampling.”
TRIQS: A toolbox for research on interacting quantum systems (2015, methodology): “s a jackknife procedure to remove the bias introduced by the nonlinearity. In TRIQS, all these operations are performed by the following code snippet, using a little library similar to e.g. ALPS/alea [7]: Listing 5 Statistics: error analysis //fillobservablewiththeseries observable <double> X,”
Cold and ultracold molecules: science, technology and applications (2009, background): “Exact diagonalization [469] is not very useful for molecules because the internal degrees of freedom take up most of the computationally accessible Hilbert space, and one is left with only a few sites and/or a few molecules, at best.”
Algorithm 941 (2014, neutral): “x = htenrandn([5, 4, 6, 3]); u = randn(4, 1); y = ttm(x, u.”
Solving the quantum many-body problem with artificial neural networks (2016, methodology): “The time-dependent MPS results have been obtained with the open-source ALPS implementation [30, 39].”
QuSpin: a Python Package for Dynamics and Exact Diagonalisation of Quantum Many Body Systems part I: spin chains (2016, background): “herehaveappearedfreelyaccessiblenumericalpackagesandlibraries whichcontributetowidespreadtheuseofsuchnumericaltechniquesamongthecondensedmattercommunity: theAlgorithmsandLibrariesforPhysicsSimulations[10,11,12,13](ALPS), C++ libraries for tensor networks:ITensor[14] andTensor Network Theory Library[”
Deep autoregressive models for the efficient variational simulation of many-body quantum systems (2019, methodology): “[27] B.”
Quantum trajectories and open many-body quantum systems (2014, methodology): “(47), such systems are of the order of 10 particles on 10 lattice sites for rapid computations, although recent calculations with the Bose-Hubbard model (without quantum trajectories) have extended to 14 particles on 14 sites [205, 206].”