EDBT 2026 Demo / reviewers in the wild / expert
Julien Froustey
dblp:388/3674
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Quantum computing and quantum information
quantum circuit compilation |
0.9 | 1 | 2025 | HATT: Hamiltonian Adaptive Ternary Tree for Optimizing Fermion-to-Qubit Mapping · HPCA 2025 |
Quantum computing and quantum information
quantum simulation |
0.9 | 1 | 2025 | HATT: Hamiltonian Adaptive Ternary Tree for Optimizing Fermion-to-Qubit Mapping · HPCA 2025 |
Quantum computing and quantum information
quantum circuit optimization |
0.3 | 1 | 2025 | HATT: Hamiltonian Adaptive Ternary Tree for Optimizing Fermion-to-Qubit Mapping · HPCA 2025 |
Methods — techniques the papers use, named apart from their topics
ternary tree mapping · 0.9bottom-up construction · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | HATT: Hamiltonian Adaptive Ternary Tree for Optimizing Fermion-to-Qubit MappingabstractThis paper introduces the Hamiltonian-Adaptive Ternary Tree (HATT) framework to compile optimized Fermion-to-qubit mapping for specific Fermionic Hamiltonians. In the simulation of Fermionic quantum systems, efficient Fermion-toqubit mapping plays a critical role in transforming the Fermionic system into a qubit system. HATT utilizes ternary tree mapping and a bottom-up construction procedure to generate Hamiltonian aware Fermion-to-qubit mapping to reduce the Pauli weight of the qubit Hamiltonian, resulting in lower quantum simulation circuit overhead. Additionally, our optimizations retain the important vacuum state preservation property in our Fermion-toqubit mapping and reduce the complexity of our algorithm from $O\left(N^{4}\right)$ to $O\left(N^{3}\right)$. Evaluations on various Fermionic systems demonstrate $5 \sim 25 \%$ reduction in Pauli weight, gate count, and circuit depth, alongside excellent scalability to larger systems. Experiments on the Ionq device also show the advantages of HATT in noise resistance in quantum simulations. Yuhao Liu 0017, Kevin Yao, Jonathan Hong, Julien Froustey, Ermal Rrapaj, Costin Iancu, Gushu Li, Yunong Shi |
HPCA | 4 |