Noise-Aware Circuit Compilations for a Continuously Parameterized Two-Qubit Gateset
Christopher G. Yale, Rich Rines, Victory Omole, Bharath Thotakura, Ashlyn D. Burch, Matthew N. H. Chow, Megan Ivory, Daniel Lobser, Brian K. McFarland, Melissa C. Revelle, Susan M. Clark, and Pranav Gokhale

TL;DR
This paper presents noise-aware circuit compilation techniques for continuously parameterized two-qubit gates on trapped-ion quantum processors, improving performance and quantum volume through hardware-specific optimizations.
Contribution
It introduces novel compilation strategies tailored for continuously parameterized two-qubit gates on trapped-ion hardware, enhancing noise resilience and circuit efficiency.
Findings
Improved quantum volume achieved with noise-aware compilation.
Optimizations reduce total entangling angle and circuit depth.
Distinct error channel impacts analyzed for different compilation methods.
Abstract
State-of-the-art noisy-intermediate-scale quantum (NISQ) processors are currently implemented across a variety of hardware platforms, each with their own distinct gatesets. As such, circuit compilation should not only be aware of, but also deeply connect to, the native gateset and noise properties of each. Trapped-ion processors are one such platform that provides a gateset that can be continuously parameterized across both one- and two-qubit gates. Here we use the Quantum Scientific Computing Open User Testbed (QSCOUT) to study noise-aware compilations focused on continuously parameterized two-qubit gates (based on the M{\o}lmer-S{\o}rensen interaction) using , a quantum software platform for hardware-aware circuit compiler optimizations. We discuss the realization of gates with arbitrary angle on the all-to-all connected trapped-ion…
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