An Algebraic Quantum Circuit Compression Algorithm for Hamiltonian Simulation

Quantum computing is a promising technology that harnesses the peculiarities of quantum mechanics to deliver computational speedups for some problems that are intractable to solve on a classical computer. Current generation noisy intermediate-scale quantum (NISQ) computers are severely limited in te...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:SIAM journal on matrix analysis and applications Ročník 43; číslo 3; s. 1084 - 1108
Hlavní autoři: Camps, Daan, Kökcü, Efekan, Bassman Oftelie, Lindsay, de Jong, Wibe A., Kemper, Alexander F., Van Beeumen, Roel
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Society for Industrial and Applied Mathematics (SIAM) 01.01.2022
Témata:
algebraic circuit compression
free fermions
Hamiltonian simulation
MATHEMATICS AND COMPUTING
NISQ
quantum circuit synthesis
quantum computing
ISSN:0895-4798, 1095-7162
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Quantum computing is a promising technology that harnesses the peculiarities of quantum mechanics to deliver computational speedups for some problems that are intractable to solve on a classical computer. Current generation noisy intermediate-scale quantum (NISQ) computers are severely limited in terms of chip size and error rates. Shallow quantum circuits with uncomplicated topologies are essential for successful applications in the NISQ era. In this work, based on matrix analysis, we derive localized circuit transformations to efficiently compress quantum circuits for simulation of certain spin Hamiltonians known as free fermions. The depth of the compressed circuits is independent of simulation time and grows linearly with the number of spins. The proposed numerical circuit compression algorithm behaves backward stable and scales cubically in the number of spins enabling circuit synthesis beyond O(103) spins. The resulting quantum circuits have a simple nearest-neighbor topology, which makes them ideally suited for NISQ devices.
Bibliografie:USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
AC02-05CH11231; SC0019469
USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division
USDOE Laboratory Directed Research and Development (LDRD) Program
ISSN:0895-4798
1095-7162
DOI:10.1137/21M1439298