ALPS documentation includes basic theory, code and data structure of various simulation models, as well as available libraries and API calls.

Introduction

How to run ALPS: installing the package, setting up input files, choosing lattices and models, and evaluating your simulation results.

Models

An overview of the quantum and classical lattice models supported by ALPS, from the Ising and Heisenberg models to the Hubbard and t-J models.

Methods

The simulation methods ALPS implements to solve these models, including exact diagonalization, classical and quantum Monte Carlo, and DMRG.

API

Reference documentation for the pyalps Python functions used to run applications, load measurement data, and evaluate results in the ALPS tutorials.

Libraries

Documentation for the underlying ALPS C++ libraries — general utilities, random numbers, parameter parsing, lattices, models, and more — that ALPS applications are built on.

Development

Tutorials on writing your own simulations with the ALPS libraries and scheduler, in both Python and C++.

Integrating Your Code with ALPS

A step-by-step guide to integrating your own C, C++, or Fortran application with ALPS parameters, measurements, and the parapack scheduler.

Publications

Guidance on which papers to cite — the original algorithm, the specific application, and the ALPS library itself — when publishing work that uses ALPS.