The main components

For more details see our arxiv paper. The code is available on github with documentation and tutorials here.

Quantum Compiler

Quantum programs can be written in our high-level domain specific language in Python. The modular compiler then allows to compile these quantum algorithms for any back-end; be it a simulator or an actual quantum device. The compiler supports arbitrary gate sets. (Based on [1]).

Simulator and Emulator

The world's fastest high-performance quantum circuit simulator and emulator allows users to efficiently test and debug their quantum algorithms. The compiler enables the emulation at different levels of abstraction and using arbitrary gate sets.

Hardware Backends

Our high-level quantum programs written in Python can be compiled and mapped directly to quantum hardware. This allows users to run their algorithms on various devices such as, e.g., the IBM Quantum Experience chip without changing their implementation.

Version 0.1 is released on Github.

The Founders

Thomas Häner
Thomas Häner
Founder & Lead Developer
Damian Steiger
Damian Steiger
Founder & Lead Developer
Matthias Troyer
Matthias Troyer
Founder & Scientific Advisor

Acknowledgments

Special thanks go to the researchers from IBM, Lev S. Bishop, Fran Cabrera, Jorge Carballo, Jerry M. Chow, Andrew W. Cross, Ismael Faro, Stefan Filipp, Jay M. Gambetta, Paco Martin, Nikolaj Moll, Mark Ritter, and John Smolin for their help with interfacing to the IBM Quantum Experience chip.

We thank Jonathan Home, Matteo Marinelli, and Vlad Negnevitsky for working with us on an interface to their ion trap quantum computer.

Furthermore, we want to thank the following people for enlightening discussions: Jana Darulová, Michele Dolfi, Dominik Gresch, Andreas Hehn, Mario Könz, Natalie Pearson, Donjan Rodic, Slava Savenko, Andreas Wallraff, and Camillo Zapata Ocampo from ETH Zurich; Matthew Neeley, Daniel Sank, and Hartmut Neven from Google Quantum AI; Alan Geller, Martin Roetteler, Krysta Svore, Dave Wecker, and Nathan Wiebe from Microsoft Research; and Anne Matsuura and Mikhail Smelyanskiy from Intel.

We would also like to thank Ryan Babbush and Jarrod McClean for collaborating with us on fermilib.