63 citations · 84 across the 14 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
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…
Quantum Large Language Models via Tensor Network Disentanglers
Borja Aizpurua, Fernando Loren, Saeed S. Jahromi +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…
Efficient tensor network simulation of IBM's largest quantum processors
Siddhartha Patra, Saeed S. Jahromi, Sukhbinder Singh +1
We show how quantum-inspired 2d tensor networks can be used to efficiently and accurately simulate the largest quantum processors from IBM, namely Eagle (127 qubits), Osprey (433 q…