QSP-based pulse characterization

ORAL

Abstract

Exact pulse implementations for quantum systems are critical for tasks in analog quantum computing. However, calibrating composite pulse sequences exactly is challenging, oftentimes requiring iterative approaches which fail under realistic noise models. Using quantum signal processing, we produce an analytic form for composite pulse sequences, finding they can be expressed as Laurent polynomials. Via Fourier-based polynomial interpolation, we may learn these polynomials and the underlying rotations, enabling us to characterize pulse sequences. We test this learning scheme numerically and under open quantum dynamics.

*This work is funded in part by EPiQC, an NSF Expedition in Computing, under award CCF-1730449; in part by STAQ under award NSF Phy-1818914/232580; in part by the US Department of Energy Office of Advanced Scientific Computing Research, Accelerated Research for Quantum Computing Program; and in part by the NSF Quantum Leap Challenge Institute for Hybrid Quantum Architectures and Networks (NSF Award 2016136), in part based upon work supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, and in part by the Army Research Office under Grant Number W911NF-23-1-0077. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.

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Presenters

  • Christopher Kang

    • University of Chicago

Authors

  • Christopher Kang

    • University of Chicago

  • Yulong Dong

    • University of California, Berkeley

  • Murphy Yuezhen Niu

    • University of Maryland College Park
    • University of California, Santa Barbara