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20242026
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quant-ph2026

Pushing the Classical Frontier of 1D Fermi-Hubbard Quench Dynamics Beyond Current Quantum Simulations

Roman Rausch, Sukhbinder Singh, Saeed S. Jahromi +2

Establishing quantum advantage requires comparison against the best achievable classical simulation. The Q-CTRL team recently simulated quench dynamics of the one-dimensional Fermi…

quant-ph2026

Quantum-enhanced Large Language Models on Quantum Hardware via Cayley Unitary Adapters

Borja Aizpurua, Sukhbinder Singh, Augustine Kshetrimayum +2

Large language models (LLMs) have transformed artificial intelligence, yet classical architectures impose a fundamental constraint: every trainable parameter demands classical memo…

quant-ph2026

Classical Neural Networks on Quantum Devices via Tensor Network Disentanglers: A Case Study in Image Classification

Borja Aizpurua, Sukhbinder Singh, Román Orús

We address the problem of implementing bottleneck layers from classical pre-trained neural networks on a quantum computer, with the goal of exploring intrinsically quantum ansatz f…

quant-ph2026

Quantum Advantage: a Tensor Network Perspective

Augustine Kshetrimayum, Saeed S. Jahromi, Sukhbinder Singh +1

We review the recent quantum advantage experiments by IBM, D-Wave, and Google, focusing on cases where efficient classical simulations of the experiment were demonstrated or attemp…

quant-ph2024

Quantum Large Language Models via Tensor Network Disentanglers

Borja Aizpurua, Saeed S. Jahromi, Fernando Loren +2

We introduce a framework for seamlessly integrating quantum computing into pretrained large language models (LLMs). The key idea is to construct a hybrid quantum-classical represen…