Presentation
Effective Quantum Resource Optimization via Circuit Resizing in BQSKit
DescriptionIn the noisy intermediate-scale quantum era, mid-circuit measurement and reset operations facilitate novel circuit optimization strategies by reducing a circuit's qubit count in a method called resizing. This paper introduces two such algorithms. The first one leverages gate-dependency rules to reduce qubit count by 61.6% or 45.3% when optimizing depth as well. Based on numerical instantiation and synthesis, the second algorithm finds resizing opportunities in previously unresizable circuits via dependency rules and other state-of-the-art tools. This resizing algorithm, implemented in BQSKit, reduces qubit count by 20.7% on average for these previously impossible-to-resize circuits.
Event Type
Research Manuscript
TimeWednesday, June 262:30pm - 2:45pm PDT
Location3002, 3rd Floor
Design
Quantum Computing