Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2024 IEEE International Conference on Quantum Computing and Engineering (QCE) |
| Herausgeber/-innen | Candace Culhane, Greg T. Byrd, Hausi Muller, Yuri Alexeev, Yuri Alexeev, Sarah Sheldon |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
| Seiten | 150-160 |
| Seitenumfang | 11 |
| ISBN (elektronisch) | 979-8-3315-4137-8 |
| ISBN (Print) | 979-8-3315-4138-5 |
| Publikationsstatus | Veröffentlicht - 15 Sept. 2024 |
| Veranstaltung | 5th IEEE International Conference on Quantum Computing and Engineering, QCE 2024 - Montreal, Kanada Dauer: 15 Sept. 2024 → 20 Sept. 2024 |
Abstract
Quantum signal processing (QSP) and its extensions are increasingly popular frameworks for developing quantum algorithms. Yet QSP implementations still struggle to complete a classical pre-processing step ('QSP-processing') that determines the set of SU (2) rotation matrices defining the QSP circuit. We introduce a method of QSP-processing for complex polynomials that identifies a solution without optimization or root-finding and verify the success of our methods with polynomials characterized by floating point precision coefficients. We demonstrate the success of our technique for relevant target polynomials and precision regimes, including the Jacobi-Anger expansion used in QSP Hamiltonian Simulation. For popular choices of sign and inverse function approximations, we characterize regimes where all known QSP-processing methods should be expected to struggle without arbitrary precision arithmetic.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Theoretische Informatik und Mathematik
- Informatik (insg.)
- Computernetzwerke und -kommunikation
- Informatik (insg.)
- Hardware und Architektur
- Informatik (insg.)
- Signalverarbeitung
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
- Ingenieurwesen (insg.)
- Sicherheit, Risiko, Zuverlässigkeit und Qualität
- Mathematik (insg.)
- Computational Mathematics
- Physik und Astronomie (insg.)
- Statistische und nichtlineare Physik
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2024 IEEE International Conference on Quantum Computing and Engineering (QCE). Hrsg. / Candace Culhane; Greg T. Byrd; Hausi Muller; Yuri Alexeev; Yuri Alexeev; Sarah Sheldon. Institute of Electrical and Electronics Engineers Inc., 2024. S. 150-160.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Mostly Harmless Methods for QSP-Processing with Laurent Polynomials
AU - Skelton, S. E.
N1 - Publisher Copyright: © 2024 IEEE.
PY - 2024/9/15
Y1 - 2024/9/15
N2 - Quantum signal processing (QSP) and its extensions are increasingly popular frameworks for developing quantum algorithms. Yet QSP implementations still struggle to complete a classical pre-processing step ('QSP-processing') that determines the set of SU (2) rotation matrices defining the QSP circuit. We introduce a method of QSP-processing for complex polynomials that identifies a solution without optimization or root-finding and verify the success of our methods with polynomials characterized by floating point precision coefficients. We demonstrate the success of our technique for relevant target polynomials and precision regimes, including the Jacobi-Anger expansion used in QSP Hamiltonian Simulation. For popular choices of sign and inverse function approximations, we characterize regimes where all known QSP-processing methods should be expected to struggle without arbitrary precision arithmetic.
AB - Quantum signal processing (QSP) and its extensions are increasingly popular frameworks for developing quantum algorithms. Yet QSP implementations still struggle to complete a classical pre-processing step ('QSP-processing') that determines the set of SU (2) rotation matrices defining the QSP circuit. We introduce a method of QSP-processing for complex polynomials that identifies a solution without optimization or root-finding and verify the success of our methods with polynomials characterized by floating point precision coefficients. We demonstrate the success of our technique for relevant target polynomials and precision regimes, including the Jacobi-Anger expansion used in QSP Hamiltonian Simulation. For popular choices of sign and inverse function approximations, we characterize regimes where all known QSP-processing methods should be expected to struggle without arbitrary precision arithmetic.
KW - laurent polynomials
KW - quantum signal processing
KW - quantum singular value transformations
UR - http://www.scopus.com/inward/record.url?scp=85217419652&partnerID=8YFLogxK
U2 - 10.1109/QCE60285.2024.00027
DO - 10.1109/QCE60285.2024.00027
M3 - Conference contribution
AN - SCOPUS:85217419652
SN - 979-8-3315-4138-5
SP - 150
EP - 160
BT - 2024 IEEE International Conference on Quantum Computing and Engineering (QCE)
A2 - Culhane, Candace
A2 - Byrd, Greg T.
A2 - Muller, Hausi
A2 - Alexeev, Yuri
A2 - Alexeev, Yuri
A2 - Sheldon, Sarah
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th IEEE International Conference on Quantum Computing and Engineering, QCE 2024
Y2 - 15 September 2024 through 20 September 2024
ER -