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Paige Frederick

dblp:349/5598 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0003-2500-8845ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Emerging computing paradigms · 92% Performance modeling and evaluation · 8%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Emerging computing paradigms › quantum computer architecture › quantum circuit simulation
circuit cutting
0.712023
Clifford-based Circuit Cutting for Quantum Simulation · ISCA 2023
Emerging computing paradigms › quantum computer architecture
quantum circuit simulation
0.712023
Clifford-based Circuit Cutting for Quantum Simulation · ISCA 2023
Emerging computing paradigms
quantum computing
0.712023
Clifford-based Circuit Cutting for Quantum Simulation · ISCA 2023
Performance modeling and evaluation
benchmarking
0.212023
Clifford-based Circuit Cutting for Quantum Simulation · ISCA 2023
Emerging computing paradigms
quantum computer architecture
0.212023
Clifford-based Circuit Cutting for Quantum Simulation · ISCA 2023

Methods — techniques the papers use, named apart from their topics

clifford-based simulation · 0.7
YearPublicationVenuePosition
2023 Clifford-based Circuit Cutting for Quantum Simulation
abstract
Quantum computing has potential to provide exponential speedups over classical computing for many important applications. However, today's quantum computers are in their early stages, and hardware quality issues hinder the scale of program execution. Benchmarking and simulation of quantum circuits on classical computers is therefore essential to advance the understanding of how quantum computers and programs operate, enabling both algorithm discovery that leads to high-impact quantum computation and engineering improvements that deliver to more powerful quantum systems. Unfortunately, the nature of quantum information causes simulation complexity to scale exponentially with problem size.
Kaitlin N. Smith, Michael A. Perlin, Pranav Gokhale, Paige Frederick, David Owusu-Antwi, Richard Rines, Victory Omole, Fred Chong
ISCA4