ALPS
The ALPS project release 2.0: open source software for strongly correlated systems. 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/.
Keywords for this software
References in zbMATH (referenced in 8 articles )
Showing results 1 to 8 of 8.
Sorted by year (- Phillip Weinberg, Marin Bukov: QuSpin: a Python Package for Dynamics and Exact Diagonalisation of Quantum Many Body Systems. Part II: bosons, fermions and higher spins (2018) arXiv
- Dugave, Maxime; Göhmann, Frank; Kozlowski, Karol K.; Suzuki, Junji: Thermal form factor approach to the ground-state correlation functions of the XXZ chain in the antiferromagnetic massive regime (2016)
- Weiß, Andreas; Karastoyanova, Dimka: Enabling coupled multi-scale, multi-field experiments through choreographies of data-driven scientific simulations (2016) ioport
- Dolfi, Michele; Bauer, Bela; Keller, Sebastian; Kosenkov, Alexandr; Ewart, Timothée; Kantian, Adrian; Giamarchi, Thierry; Troyer, Matthias: Matrix product state applications for the ALPS project (2014)
- Kressner, Daniel; Tobler, Christine: Algorithm 941: htucker -- a Matlab toolbox for tensors in hierarchical Tucker format (2014)
- Grasedyck, Lars; Kressner, Daniel; Tobler, Christine: A literature survey of low-rank tensor approximation techniques (2013)
- Moran, Niall; Kells, Graham; Vala, Jiri: Diagonalisation of quantum observables on regular lattices and general graphs (2011)
- Fukui, Kouki; Todo, Synge: Order-$n$ cluster Monte Carlo method for spin systems with long-range interactions (2009)