EDBT 2026 Demo / reviewers in the wild / expert
Jessica Pointing
dblp:307/2765
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Software 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.
| Theoretical computer science
1 paper |
Quantum computing and quantum information · 77% Automated reasoning and model checking · 23% | |
| Software engineering, system software, and programming languages
1 paper |
Compilers and program optimization · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Compilers and program optimization › compiler optimization
superoptimization |
0.6 | 1 | 2022 | Quartz: superoptimization of Quantum circuits · PLDI 2022 |
Quantum computing and quantum information
quantum circuit optimization |
0.6 | 1 | 2022 | Quartz: superoptimization of Quantum circuits · PLDI 2022 |
Automated reasoning and model checking
automated theorem proving |
0.2 | 1 | 2022 | Quartz: superoptimization of Quantum circuits · PLDI 2022 |
Methods — techniques the papers use, named apart from their topics
cost-based backtracking search · 1.1automated theorem proving · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Quartz: superoptimization of Quantum circuitsabstractExisting quantum compilers optimize quantum circuits by applying circuit transformations designed by experts. This approach requires significant manual effort to design and implement circuit transformations for different quantum devices, which use different gate sets, and can miss optimizations that are hard to find manually. We propose Quartz, a quantum circuit superoptimizer that automatically generates and verifies circuit transformations for arbitrary quantum gate sets. For a given gate set, Quartz generates candidate circuit transformations by systematically exploring small circuits and verifies the discovered transformations using an automated theorem prover. To optimize a quantum circuit, Quartz uses a cost-based backtracking search that applies the verified transformations to the circuit. Our evaluation on three popular gate sets shows that Quartz can effectively generate and verify transformations for different gate sets. The generated transformations cover manually designed transformations used by existing optimizers and also include new transformations. Quartz is therefore able to optimize a broad range of circuits for diverse gate sets, outperforming or matching the performance of hand-tuned circuit optimizers. Mingkuan Xu, Zikun Li, Oded Padon, Sina Lin, Jessica Pointing, Auguste Hirth, Henry Ma, Jens Palsberg, Alex Aiken, Umut A. Acar |
PLDI | 5 |