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Monte Carlo framework that provides MPI parallelization, checkpointing and statistical postprocessing in an algorithm-agnostic way.

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Carlo.jl

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Carlo is a framework for developing high-performance, distributed (quantum) Monte Carlo simultations. Its aim is to take care of model-independent tasks such as

  • autocorrelation and error analysis,
  • Monte-Carlo-aware MPI scheduling, and
  • checkpointing

while leaving all the flexibility of implementating Monte Carlo updates and estimators to you.

Getting started

To install the package, type

using Pkg; Pkg.add("Carlo")

The package itself does not include Monte Carlo algorithms. The quickest way to see how to implement one yourself is to check out the reference implementation for the Ising model.

If you are a practitioner, stay tuned for a (not yet released) stochastic series expansion or auxiliary field quantum Monte Carlo packages–or let me know if you are interested in testing it pre-release!

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Monte Carlo framework that provides MPI parallelization, checkpointing and statistical postprocessing in an algorithm-agnostic way.

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