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Using physics to solve the hardest problems.

At Entropica, we use the power of quantum and statistical physics to solve the hardest problems in optimisation, machine learning and applied mathematics.

Entropica Optimisation Suite

The Entropica Optimisation Suite (EOS) provides a unified framework to run, test, deploy and benchmark classical and quantum optimisation algorithms. EOS offers the simplicity of parameter-free solvers and the power to fully customise your algorithms. 


EQAOA is a python library to do research in quantum computing and optimisation with the Quantum Approximate Optimisation Algorithm (QAOA). EQAOA offers complete freedom in the parametrisation of your QAOA circuit and an extensive choice of classical optimisation routines. EQAOA runs on IBM Q, AWS Braket and a selected pool of simulators.


The Entropica Physics-based Optimisation Suite (EPOS) is our proprietary collection of physics-based solvers for optimisation. EPOS is a unique instrument to quickly benchmark the performances of quantum algorithms versus highly customisable classical techniques.

Contact us for an early access to EOS

To interact with EOS, we designed the client library as a superposition of Scikit-learn and Qiskit to make your experience as unfrustrating as possible. We believe you will spend less time swearing at the computer and more time doing the most with quantum.

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