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Mengfei Ran

dblp:165/8827 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none

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

Artificial intelligence and machine learning · 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 · 65% Coding theory · 22% Mathematical optimization · 13%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory › error-correcting codes › error detection
parity check
0.812024
Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz · NeurIPS 2024
Quantum computing and quantum information
quantum error mitigation
0.812024
Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz · NeurIPS 2024
Quantum computing and quantum information › quantum algorithms
variational quantum algorithms
0.812024
Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz · NeurIPS 2024
Mathematical optimization
combinatorial optimization
0.212024
Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz · NeurIPS 2024
Mathematical optimization › combinatorial optimization › assignment problem
quadratic assignment problem
0.212024
Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz · NeurIPS 2024

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

variational quantum algorithm · 0.8parity check · 0.8hamming weight preserving ansatz · 0.8
YearPublicationVenuePosition
2024 Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz
abstract
With the arrival of the Noisy Intermediate-Scale Quantum (NISQ) era, Variational Quantum Algorithms (VQAs) have emerged to obtain possible quantum advantage. In particular, how to effectively incorporate hard constraints in VQAs remains a critical and open question. In this paper, we manage to combine the Hamming Weight Preserving ansatz with a topological-aware parity check on physical qubits to enforce error mitigation and further hard constraints. We demonstrate the combination significantly outperforms peer VQA methods on both quantum chemistry problems and constrained combinatorial optimization problems e.g. Quadratic Assignment Problem. Intensive experimental results on both simulators and superconducting quantum processors are provided to verify that the combination of HWP ansatz with parity check is among the most promising candidates to demonstrate quantum advantages in the NISQ era to solve more realistic problems.
Ge Yan 0001, Mengfei Ran, Ruocheng Wang, Kaisen Pan, Junchi Yan
NeurIPS2