Robust quantum gates using smooth pulses and physics-informed neural networks

Thumbnail Image

Files

2011.02512.pdf (422.97 KB)

Links to Files

https://arxiv.org/abs/2011.02512

Permanent Link

http://hdl.handle.net/11603/20215

Collections

UMBC Physics Department
UMBC Faculty Collection

Author/Creator

Author/Creator ORCID

Date

2020-11-04

Type of Work

journal articles preprints
Text

Department

Program

Citation of Original Publication

Utkan Güngördü and J. P. Kestner, Robust quantum gates using smooth pulses and physics-informed neural networks, https://arxiv.org/abs/2011.02512

Rights

This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.

Subjects

Abstract

The presence of decoherence in quantum computers necessitates the suppression of noise. Dynamically corrected gates via specially designed control pulses offer a path forward, but hardware-specific experimental constraints can cause complications. Here, we present a widely applicable method for obtaining smooth pulses which is not based on a sampling approach and does not need any assumptions with regards to the underlying statistics of the experimental noise. We demonstrate the capability of our approach by finding smooth shapes which suppress the effects of noise within the logical subspace as well as leakage out of that subspace.