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Eunou Lee

dblp:272/6059 · DBLP profile ↗
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5ranked-venue papers
2as first author
4since 2021 · last 2026
—ORCID · none

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

Theory of computation · 5 · 2 first-author · 4 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 · 33% Approximation and online algorithms · 33% Mathematical optimization · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Approximation and online algorithms
approximation algorithms
0.812024
An Improved Quantum Max Cut Approximation via Maximum Matching · ICALP 2024
Quantum computing and quantum information
quantum algorithms
0.812024
An Improved Quantum Max Cut Approximation via Maximum Matching · ICALP 2024
Mathematical optimization › semidefinite programming
semidefinite programming approximation
0.812024
An Improved Quantum Max Cut Approximation via Maximum Matching · ICALP 2024

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

semidefinite programming · 0.8maximum matching · 0.8
YearPublicationVenuePosition
2026 A 0.8395-Approximation Algorithm for the EPR Problem
abstract
We give an efficient 0.8395-approximation algorithm for the EPR Hamiltonian. Our improvement comes from a new nonlinear monogamy-of-entanglement bound on star graphs and a refined parameterization of a shallow quantum circuit from previous works. We also prove limitations showing that current methods cannot achieve substantially better approximation ratios, indicating that further progress will require fundamentally new techniques.
Anuj Apte, Eunou Lee, Kunal Marwaha, Ojas Parekh, Lennart Sinjorgo, James Sud
ESA2
2025 Improved Algorithms for Quantum MaxCut via Partially Entangled Matchings
Anuj Apte, Eunou Lee, Kunal Marwaha, Ojas Parekh, James Sud
ESA2
2024 An Improved Quantum Max Cut Approximation via Maximum Matching
abstract
Finding a high (or low) energy state of a given quantum Hamiltonian is a potential area to gain a provable and practical quantum advantage. A line of recent studies focuses on Quantum Max Cut, where one is asked to find a high energy state of a given antiferromagnetic Heisenberg Hamiltonian. In this work, we present a classical approximation algorithm for Quantum Max Cut that achieves an approximation ratio of 0.595, outperforming the previous best algorithms of Lee [Eunou Lee, 2022] (0.562, generic input graph) and King [King, 2023] (0.582, triangle-free input graph). The algorithm is based on finding the maximum weighted matching of an input graph and outputs a product of at most 2-qubit states, which is simpler than the fully entangled output states of the previous best algorithms.
Eunou Lee, Ojas Parekh
ICALP1
2022 Optimizing Quantum Circuit Parameters via SDP
Eunou Lee
ISAAC1
2020 An Approximation Algorithm for the MAX-2-Local Hamiltonian Problem
abstract
The EPR Hamiltonian is a family of 2-local quantum Hamiltonians introduced by King [King, 2023]. We introduce a polynomial time (1+√5)/4≈0.809-approximation algorithm for the problem of computing the ground energy of the EPR Hamiltonian, improving upon the previous state of the art of 0.72 [Jorquera et al., 2024].
Sean Hallgren, Eunou Lee, Ojas Parekh
APPROX-RANDOM2