TY - GEN
T1 - A Shuttle-Efficient Qubit Mapper for Trapped-Ion Quantum Computers
AU - Upadhyay, Suryansh
AU - Saki, Abdullah Ash
AU - Topaloglu, Rasit Onur
AU - Ghosh, Swaroop
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/6/6
Y1 - 2022/6/6
N2 - Trapped-ion (TI) quantum computer is one of the forerunner quantum technologies. Execution of a quantum gate in multiple trap TI system may frequently involve ions from two different traps, hence one of the ions needs to be shuttled (moved) between traps to be co-located, degrading fidelity, and increasing the program execution time. The choice of initial mapping influences the number of shuttles. The existing Greedy policy neglects the depth of the program at which a gate is present. Intuitively, the contribution of the late-stage gates to the initial mapping is less since the ions might have already shuttled to a different trap to satisfy other gate operations. In this paper, we target this gap and propose a new program adaptive policy especially for programs with considerable depth and high number of qubits (valid for practical-scale quantum programs). Our technique achieves an average reduction of 9% shuttles/program (with 21.3% at best) for 120 random circuits and enhances the program fidelity up to 3.3X (1.41X on average).
AB - Trapped-ion (TI) quantum computer is one of the forerunner quantum technologies. Execution of a quantum gate in multiple trap TI system may frequently involve ions from two different traps, hence one of the ions needs to be shuttled (moved) between traps to be co-located, degrading fidelity, and increasing the program execution time. The choice of initial mapping influences the number of shuttles. The existing Greedy policy neglects the depth of the program at which a gate is present. Intuitively, the contribution of the late-stage gates to the initial mapping is less since the ions might have already shuttled to a different trap to satisfy other gate operations. In this paper, we target this gap and propose a new program adaptive policy especially for programs with considerable depth and high number of qubits (valid for practical-scale quantum programs). Our technique achieves an average reduction of 9% shuttles/program (with 21.3% at best) for 120 random circuits and enhances the program fidelity up to 3.3X (1.41X on average).
UR - http://www.scopus.com/inward/record.url?scp=85131676351&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85131676351&partnerID=8YFLogxK
U2 - 10.1145/3526241.3530366
DO - 10.1145/3526241.3530366
M3 - Conference contribution
AN - SCOPUS:85131676351
T3 - Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI
SP - 305
EP - 308
BT - GLSVLSI 2022 - Proceedings of the Great Lakes Symposium on VLSI 2022
PB - Association for Computing Machinery
T2 - 32nd Great Lakes Symposium on VLSI, GLSVLSI 2022
Y2 - 6 June 2022 through 8 June 2022
ER -