RT Journal Article
T1 Simulating key properties of lithium-ion batteries with a fault-tolerant quantum computer
A1 Delgado, Alain
A1 Casares, Pablo A. M.
A1 dos Reis, Roberto
A1 Zini, Modjtaba Shokrian
A1 Campos, Roberto
A1 Cruz Hernández, Norge
A1 Voigt, Arne Christian
A1 Lowe, Angus
A1 Jahangiri, Soran
A1 Martín-Delgado Alcántara, Miguel Ángel
A1 Mueller, Jonathan
A1 Arrazola, Juan Miguel
AB There is a pressing need to develop new rechargeable battery technologies that can offer higher energy storage, faster charging, and lower costs. Despite the success of existing methods for the simulation of battery materials, they can sometimes fall short of delivering accurate and reliable results. Quantum computing has been discussed as an avenue to overcome these issues, but only limited work has been done to outline how it may impact battery simulations. In this work, we provide a detailed answer to the following question: how can a quantum computer be used to simulate key properties of a lithium-ion battery? Based on recently introduced first-quantization tech-niques, we lay out an end-to-end quantum algorithm for calculating equilibrium cell voltages, ionic mobility, and thermal stability. These can be obtained from ground-state energies of materials, which are the core calculations executed by the quantum computer using qubitization-based quantum phase estimation. The algorithm includes explicit methods for preparing approximate ground states of periodic materials in first quantization. We bring these insights together to estimate the resources required to implement a quantum algorithm for simulating a realistic cathode material, dilithium iron silicate.
PB Amer Physical Soc
SN 2469-9926
YR 2022
FD 2022-09-26
LK https://hdl.handle.net/20.500.14352/72602
UL https://hdl.handle.net/20.500.14352/72602
LA eng
NO © 2022 Amer Physical Soc.The authors thank Tobias J. Osborne, Yuval Sanders, Dominic Berry, Michael Kaicher, Craig Gidney, and Maria Schuld for valuable discussions. P.A.M.C., R.C., and M.A.M.-D. acknowledge financial support from the Spanish MINECO grants, MINECO/FEDER Projects FIS 2017- 91460-EXP and PGC2018-099169-B-I00 FIS-2018, and from CAM/FEDER Project No. S2018/TCS-4342 (QUITEMAD- CM) . The research of M.A.M.-D. has been partially supported by the U.S. Army Research Office through Grant No. W911NF-14-1-0103. P.A.M.C. acknowledges the support of a MECD Grant No. FPU17/03620, and R.C. the support of a CAM Grant No. IND2019/TIC17146.
NO Ministerio de Economía y Competitividad (MINECO)/ FEDER
NO Ministerio de Educación, Cultura y Deporte (MECD)
NO Comunidad de Madrid/FEDER
NO Comunidad de Madrid
NO U.S. Army Research Office
DS Docta Complutense
RD 8 abr 2025