AUTHOR=Otten Matthew , Kang Byeol , Fedorov Dmitry , Lee Joo-Hyoung , Benali Anouar , Habib Salman , Gray Stephen K. , Alexeev Yuri TITLE=QREChem: quantum resource estimation software for chemistry applications JOURNAL=Frontiers in Quantum Science and Technology VOLUME=2 YEAR=2023 URL=https://www.frontiersin.org/journals/quantum-science-and-technology/articles/10.3389/frqst.2023.1232624 DOI=10.3389/frqst.2023.1232624 ISSN=2813-2181 ABSTRACT=

As quantum hardware continues to improve, more and more application scientists have entered the field of quantum computing. However, even with the rapid improvements in the last few years, quantum devices, especially for quantum chemistry applications, still struggle to perform calculations that classical computers could not calculate. In lieu of being able to perform specific calculations, it is important have a systematic way of estimating the resources necessary to tackle specific problems. Standard arguments about computational complexity provide hope that quantum computers will be useful for problems in quantum chemistry but obscure the true impact of many algorithmic overheads. These overheads will ultimately determine the precise point when quantum computers will perform better than classical computers. We have developed QREChem to provide logical resource estimates for ground state energy estimation in quantum chemistry through a Trotter-based quantum phase estimation approach. QREChem provides resource estimates which include the specific overheads inherent to problems in quantum chemistry by including heuristic estimates of the number of Trotter steps and number of necessary ancilla, allowing for more accurate estimates of the total number of gates. We utilize QREChem to provide logical resource estimates for a variety of small molecules in various basis sets, obtaining estimates in the range of 107–1015 for total number of T gates. We also determine estimates for the FeMoco molecule and compare all estimates to other resource estimation tools. Finally, we compare the total resources, including hardware and error correction overheads, demonstrating the need for fast error correction cycle times.