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arXiv:2610.03884

The ALPS project release 3.0: open source software for strongly correlated systems

F. Alet, T. Chen, A. Feiguin, E. Gull, S. Iskakov, J. P. F. LeBlanc, F. Lin, A. Mirmira, G. Möller, L. Pollet, M. Rosales, V. W. Scarola, H. Shinaoka, H. Terletska, S. Todo, M. Troyer, M. Wallerberger, P. Werner, T. M. R. Wolf

cond-mat.str-elcond-mat.quant-gasphysics.comp-phquant-phSubmitted Oct 2, 2026• Announced Oct 6, 2026• 0 citations
v1 · Oct 2, 2026v2 · Oct 6, 2026
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Abstract

We present release 3.0 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. As in previous releases, development is centered on common data formats, on libraries to simplify and speed up code development, and on full-featured simulation programs that let non-experts carry out serial or parallel numerical simulations using 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), and continuous-time QMC solvers for dynamical mean-field theory (DMFT). Major changes in release 3.0 include distribution of the pyalps binary through the Python Package Index (pip install pyalps) and through Spack for HPC systems; migration of development to GitHub with continuous integration and automated testing; relicensing of the package under the permissive MIT license; a rebuilt documentation and tutorial website, including a set of Jupyter-notebook tutorials and localized content; a broad modernization of the C++ codebase (C++17 compliance, Boost and NumPy 2.0 compatibility, and warning and dead-code cleanup) together with a major DMRG update and associated reliability and build-compatibility fixes; the removal of legacy components (the VisTrails provenance integration and the TEBD, MPS, and directed-worm-algorithm application codes); archival of release 3.0.0 with a Zenodo DOI (10.5281/zenodo.22775899); and a formal governance and sustainability model developed under the US National Science Foundation (NSF) POSE program. The software is available at https://alps.comp-phys.org.

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We present release 3.0 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. As in previous releases, development is centered on common data formats, on libraries to simplify and speed up code development, and on full-featured simulation programs that let non-experts carry out serial or parallel numerical simulations using 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), and continuous-time QMC solvers for dynamical mean-field theory (DMFT). Major changes in release 3.0 include distribution of the pyalps binary through the Python Package Index (pip install pyalps) and through Spack for HPC systems; migration of development to GitHub with continuous integration and automated testing; relicensing of the package under the permissive MIT license; a rebuilt documentation and tutorial website, including a set of Jupyter-notebook tutorials and localized content; a broad modernization of the C++ codebase (C++17 compliance, Boost and NumPy 2.0 compatibility, and warning and dead-code cleanup) together with a major DMRG update and associated reliability and build-compatibility fixes; the removal of legacy components (the VisTrails provenance integration and the TEBD, MPS, and directed-worm-algorithm application codes); archival of release 3.0.0 with a Zenodo DOI (10.5281/zenodo.22775899); and a formal governance and sustainability model developed under the US National Science Foundation (NSF) POSE program. The software is available at https://alps.comp-phys.org.
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/ .
We present the ALPS (Algorithms and Libraries for Physics Simulations) project, an international 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. Development is centered on common XML and binary data formats, on libraries to simplify and speed up code development, and on full-featured simulation programs. The programs enable non-experts to start carrying out 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), as well as the density matrix renormalization group (DMRG). The software is available from our web server at http://alps.comp-phys.org.
The open source ALPS (Algorithms and Libraries for Physics Simulations) project provides a collection of physics libraries and applications, with a focus on simulations of lattice models and strongly correlated electron systems. The libraries provide a convenient set of well-documented and reusable components for developing condensed matter physics simulation codes, and the applications strive to make commonly used and proven computational algorithms available to a non-expert community. In this paper we present an update of the core ALPS libraries. We present in particular new Monte Carlo libraries and new Green's function libraries.
We introduce version 1.0 of the SmoQyElPhQMC.jl package, an open-source Julia code for performing scalable quantum Monte Carlo simulations of electron-phonon coupled model Hamiltonians. SmoQyElPhQMC.jl is built upon the SmoQyDQMC.jl codebase and implements improved versions of the algorithms presented in [B. Cohen-Stead \textit{et al}., Phys. Rev. E 105, 065302 (2022)] to enable (near-linear) scalable simulations of a broad class of uncorrelated eee-ph models both in system size and inverse temperature. By extending the functionality of the flexible scripting interface introduced in SmoQyDQMC.jl, the SmoQyElPhQMC.jl package continues to allow users to adapt it to different workflows and interface with other software packages in the Julia ecosystem. The code for this package can be downloaded from our GitHub repository at https://github.com/SmoQySuite/SmoQyElPhQMC.jl or installed using the Julia package manager. The online documentation, including examples, can be obtained from our documentation page at https://smoqysuite.github.io/SmoQyElPhQMC.jl/stable/.
We present qlbm , a Python software package designed to facilitate the development, simulation, and analysis of Quantum Lattice Boltzmann Methods (QBMs). qlbm is a modular framework that introduces a quantum component abstraction hierarchy tailored to the implementation of novel QBMs. The framework interfaces with state-of-the-art quantum software infrastructure to enable efficient simulation and validation pipelines, and leverages novel execution and pre-processing techniques that significantly reduce the computational resources required to develop quantum circuits. We demonstrate the versatility of the software by showcasing multiple QBMs in 2D and 3D with complex boundary conditions, integrated within automated benchmarking utilities. Accompanying the source code are extensive test suites, thorough online documentation resources, analysis tools, visualization methods, and demos that aim to increase the accessibility of QBMs while encouraging reproducibility and collaboration. Program summary Program Title: qlbm CPC Library link to program files: https://doi.org/10.17632/28hkvsg7p2.1 Developer's repository link: https://github.com/QCFD-Lab/qlbm Licensing provisions: MPL-2.0 Programming language: Python3 Supplementary material: The documentation of is available at https://qcfd-lab.github.io/qlbm/ . Nature of problem: The advent of quantum algorithms for computational fluid dynamics brings with it challenges that are new to the established field of computational physics. These challenges include the lack of standardized implementations of the still nascent quantum methods, the intense computational demands of developing and simulating quantum algorithms on hardware available today, and the absence of tools that integrate novel developments into established infrastructure. Because of these current limitations, physicists and mathematicians expend superfluous resources on tasks that more mature computational physics branches have surmounted long ago. Solution method: QLBM is a software package that provides an end-to-end development environment for quantum lattice Boltzmann methods. The modular design and flexible quantum circuit library provide a base for extending and generalizing quantum algorithms. Performance enhancements exploit the paradigm of quantum computing simulations to accelerate the speed at which researchers can verify the validity of their methods. Its integration with state-of-the-art quantum computing software and visualization tools increases the algorithms' accesibility. These features allow QLBM to effectively generate, simulate, and analyze quantum circuits for 2D and 3D computational fluid dynamics problems.
mVMC (many-variable Variational Monte Carlo) is an open-source software package based on the variational Monte Carlo method applicable for a wide range of Hamiltonians for interacting fermion systems. In mVMC, we introduce more than ten thousands variational parameters and simultaneously optimize them by using the stochastic reconfiguration (SR) method. In this paper, we explain basics and user interfaces of mVMC. By using mVMC, users can perform the calculation by preparing only one input file of about ten lines for widely studied quantum lattice models, and can also perform it for general Hamiltonians by preparing several additional input files. We show the benchmark results of mVMC for the Hubbard model, the Heisenberg model, and the Kondo-lattice model. These benchmark results demonstrate that mVMC provides ground-state and low-energy-excited-state wave functions for interacting fermion systems with high accuracy. Program title: mVMC Program Files doi: http://dx.doi.org/10.17632/xhgyp6ncvt.1 Licensing provisions: GNU General Public License version 3 Programming language: C External routines/libraries: MPI, BLAS, LAPACK, Pfapack, ScaLAPACK (optional) Nature of problem: Physical properties (such as the charge/spin structure factors) of strongly correlated electrons at zero temperature. Solution method: Application software based on the variational Monte Carlo method for quantum lattice model such as the Hubbard model, the Heisenberg model and the Kondo model. Unusual features: It is possible to perform the highly-accurate calculations for ground states in a wide range of theoretical Hamiltonians in quantum many-body systems. In addition to the conventional orders such as magnetic and/or charge orders, user can treat the anisotropic superconductivities within the same framework. This flexibility is the main advantage of mVMC.