The Fermionic Quantum Emulator

Nicholas C. Rubin¹, Klaas Gunst², Alec White², Leon Freitag², Kyle Throssell², Garnet Kin-Lic Chan³, Ryan Babbush¹, and Toru Shiozaki²

¹Google Quantum AI, Mountain View, CA, 94043
²Quantum Simulation Technologies, Inc., Cambridge, MA 02139
³Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena CA 91125

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Abstract

The fermionic quantum emulator (FQE) is a collection of protocols for emulating quantum dynamics of fermions efficiently taking advantage of common symmetries present in chemical, materials, and condensed-matter systems. The library is fully integrated with the OpenFermion software package and serves as the simulation backend. The FQE reduces memory footprint by exploiting number and spin symmetry along with custom evolution routines for sparse and dense Hamiltonians, allowing us to study significantly larger quantum circuits at modest computational cost when compared against qubit state vector simulators. This release paper outlines the technical details of the simulation methods and key advantages.

► BibTeX data

@article{Rubin2021fermionicquantum, doi = {10.22331/q-2021-10-27-568}, url = {https://doi.org/10.22331/q-2021-10-27-568}, title = {The {F}ermionic {Q}uantum {E}mulator}, author = {Rubin, Nicholas C. and Gunst, Klaas and White, Alec and Freitag, Leon and Throssell, Kyle and Chan, Garnet Kin-Lic and Babbush, Ryan and Shiozaki, Toru}, journal = {{Quantum}}, issn = {2521-327X}, publisher = {{Verein zur F{“{o}}rderung des Open Access Publizierens in den Quantenwissenschaften}}, volume = {5}, pages = {568}, month = oct, year = {2021}<br /> }

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Cited by

[1] William J. Huggins, Bryan A. O’Gorman, Nicholas C. Rubin, David R. Reichman, Ryan Babbush, and Joonho Lee, “Unbiasing Fermionic Quantum Monte Carlo with a Quantum Computer”, arXiv:2106.16235.

[2] Nicholas C. Rubin, Joonho Lee, and Ryan Babbush, “Compressing Many-Body Fermion Operators Under Unitary Constraints”, arXiv:2109.05010.

[3] Nicholas H. Stair and Francesco A. Evangelista, “QForte: an efficient state simulator and quantum algorithms library for molecular electronic structure”, arXiv:2108.04413.

[4] Qingchun Wang, Huan-Yu Liu, Qing-Song Li, Ye Li, Yahui Chai, Qiankun Gong, Haotian Wang, Yu-Chun Wu, Yong-Jian Han, Guang-Can Guo, and Guo-Ping Guo, “ChemiQ: A Chemistry Simulator for Quantum Computer”, arXiv:2106.10162.

[5] Gaurav Gyawali and Michael J. Lawler, “Insights from an adaptive variational wave function study of the Fermi-Hubbard Model”, arXiv:2109.12126.

The above citations are from SAO/NASA ADS (last updated successfully 2021-10-28 03:49:42). The list may be incomplete as not all publishers provide suitable and complete citation data.

On Crossref’s cited-by service no data on citing works was found (last attempt 2021-10-28 03:49:40).

This Paper is published in Quantum under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Copyright remains with the original copyright holders such as the authors or their institutions.

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