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20242026
most citedSynthesis of discrete-continuous quantum circuits with multimodal diffusion models

3 citations · 4 across the 3 of their papers we have counts for

collaborators

8 papers

quant-ph2026

Benchmarking the computational power of quantum computers

Timothy Proctor, Oliver Hart, Oliver Widzowski Maupin +27

Quantum computing hardware is advancing rapidly toward utility-scale machines that will enable scientific breakthroughs. Many teams are pursuing distinct and difficult-to-compare r…

quant-ph2026

Photonic Quantum-Enhanced Knowledge Distillation

Kuan-Cheng Chen, Shang Yu, Chen-Yu Liu +10

Photonic quantum processors naturally produce intrinsically stochastic measurement outcomes, offering a hardware-native source of structured randomness that can be exploited during…

quant-ph2025

Hybrid Classical-Quantum Supercomputing: A demonstration of a multi-user, multi-QPU and multi-GPU environment

Mateusz Slysz, Piotr Rydlichowski, Krzysztof Kurowski +7

Achieving a practical quantum advantage for near-term applications is widely expected to rely on hybrid classical-quantum algorithms. To deliver this practical advantage to users,…

quant-ph20251 cited

Quantum-Classical Auxiliary Field Quantum Monte Carlo with Matchgate Shadows on Trapped Ion Quantum Computers

Luning Zhao, Joshua J. Goings, Willie Aboumrad +38

We demonstrate an end-to-end workflow to model chemical reaction barriers with the quantum-classical auxiliary field quantum Monte Carlo (QC-AFQMC) algorithm with quantum tomograph…

quant-ph20253 cited

Synthesis of discrete-continuous quantum circuits with multimodal diffusion models

Florian Fürrutter, Zohim Chandani, Ikko Hamamura +2

Efficiently compiling quantum operations remains a major bottleneck in scaling quantum computing. Today's state-of-the-art methods achieve low compilation error by combining search…

quant-ph2025

A Hybrid Transformer Architecture with a Quantized Self-Attention Mechanism Applied to Molecular Generation

Anthony M. Smaldone, Yu Shee, Gregory W. Kyro +4

The success of the self-attention mechanism in classical machine learning models has inspired the development of quantum analogs aimed at reducing computational overhead. Self-atte…