Demo Data from EDBT 2026 / reviewers in the wild / expert
Paige Frederick
dblp:349/5598
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Emerging computing paradigms › quantum computer architecture › quantum circuit simulation
circuit cutting |
0.7 | 1 | 2023 | Clifford-based Circuit Cutting for Quantum Simulation · ISCA 2023 |
Emerging computing paradigms › quantum computer architecture
quantum circuit simulation |
0.7 | 1 | 2023 | Clifford-based Circuit Cutting for Quantum Simulation · ISCA 2023 |
Emerging computing paradigms
quantum computing |
0.7 | 1 | 2023 | Clifford-based Circuit Cutting for Quantum Simulation · ISCA 2023 |
Performance modeling and evaluation
benchmarking |
0.2 | 1 | 2023 | Clifford-based Circuit Cutting for Quantum Simulation · ISCA 2023 |
Emerging computing paradigms
quantum computer architecture |
0.2 | 1 | 2023 | Clifford-based Circuit Cutting for Quantum Simulation · ISCA 2023 |
Methods — techniques the papers use, named apart from their topics
clifford-based simulation · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Clifford-based Circuit Cutting for Quantum SimulationabstractQuantum 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 |
ISCA | 4 |