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20232026
most citedArtificial Intelligence for Quantum Computing

40 citations · 154 across the 14 of their papers we have counts for

collaborators

14 papers

quant-ph2026

DQAOA-GPT: AI-Accelerated Distributed Quantum Optimization for Combinatorial Problems

Seongmin Kim, Abhinav Rijal, Yuri Alexeev +5

While combinatorial optimization problems are central to many scientific and engineering applications, their solution remains challenging due to exponentially large search spaces.…

quant-ph2026

SCALAR: A Neurosymbolic Framework for Automated Conjecture and Reasoning in Quantum Circuit Analysis

Sean Feeney, Pooja Rao, Andreas Klappenecker +5

In this paper, we present SCALAR (Symbolic Conjecture and LLM-Assisted Reasoning), a neurosymbolic framework for automated conjecture generation in quantum circuit analysis built o…

quant-ph2025★ 3 cited

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits

Ilya Tyagin, Marwa H. Farag, Kyle Sherbert +3

Quantum computing has the potential to improve our ability to solve certain optimization problems that are computationally difficult for classical computers, by offering new algori…

quant-ph2025★ 33 cited

Certified randomness using a trapped-ion quantum processor

Minzhao Liu, Ruslan Shaydulin, Pradeep Niroula +29

While quantum computers have the potential to perform a wide range of practically important tasks beyond the capabilities of classical computers, realizing this potential remains a…

astro-ph.IM2025★ 1 cited

Lossy Compression of Scientific Data: Applications Constrains and Requirements

Franck Cappello, Allison Baker, Ebru Bozda +22

Increasing data volumes from scientific simulations and instruments (supercomputers, accelerators, telescopes) often exceed network, storage, and analysis capabilities. The scienti…

quant-ph2025

The Art of Avoiding Constraints: A Penalty-free Approach to Constrained Combinatorial Optimization with QAOA

Prashanti Priya Angara, Danylo Lykov, Ulrike Stege +2

The quantum approximate optimization algorithm (QAOA) is designed to determine optimum and near optimum solutions of quadratic (and higher order) unconstrained binary optimization…

quant-ph2025★ 19 cited

Tensor networks for quantum computing

Aleksandr Berezutskii, Minzhao Liu, Atithi Acharya +25

In the rapidly evolving field of quantum computing, tensor networks serve as an important tool due to their multifaceted utility. In this paper, we review the diverse applications…

quant-ph2025★ 1 cited

Improved Quantum Computation using Operator Backpropagation

Bryce Fuller, Minh C. Tran, Danylo Lykov +10

Decoherence of quantum hardware is currently limiting its practical applications. At the same time, classical algorithms for simulating quantum circuits have progressed substantial…

quant-ph2024★ 40 cited

Artificial Intelligence for Quantum Computing

Yuri Alexeev, Marwa H. Farag, Taylor L. Patti +25

Artificial intelligence (AI) advancements over the past few years have had an unprecedented and revolutionary impact across everyday application areas. Its significance also extend…

quant-ph2024★ 32 cited

The computational power of random quantum circuits in arbitrary geometries

Matthew DeCross, Reza Haghshenas, Minzhao Liu +49

Empirical evidence for a gap between the computational powers of classical and quantum computers has been provided by experiments that sample the output distributions of two-dimens…

quant-ph2024

Equivariant QAOA and the Duel of the Mixers

Boris Tsvelikhovskiy, Ilya Safro, Yuri Alexeev

Constructing an optimal mixer for Quantum Approximate Optimization Algorithm (QAOA) Hamiltonian is crucial for enhancing the performance of QAOA in solving combinatorial optimizati…

quant-ph2024★ 1 cited

Graph Representation Learning for Parameter Transferability in Quantum Approximate Optimization Algorithm

Jose Falla, Quinn Langfitt, Yuri Alexeev +1

The quantum approximate optimization algorithm (QAOA) is one of the most promising candidates for achieving quantum advantage through quantum-enhanced combinatorial optimization. O…

quant-ph2023

QArchSearch: A Scalable Quantum Architecture Search Package

Ankit Kulshrestha, Danylo Lykov, Ilya Safro +1

The current era of quantum computing has yielded several algorithms that promise high computational efficiency. While the algorithms are sound in theory and can provide potentially…

quant-ph2023★ 24 cited

Fast Simulation of High-Depth QAOA Circuits

Danylo Lykov, Ruslan Shaydulin, Yue Sun +2

Until high-fidelity quantum computers with a large number of qubits become widely available, classical simulation remains a vital tool for algorithm design, tuning, and validation.…