63 citations · 84 across the 14 of their papers we have counts for
5 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…
Fast Tensorization of Neural Networks via Slice-wise Feature Distillation
Safa Hamreras, Sukhbinder Singh, Román Orús
We propose a scalable tensorization framework for neural network compression based on slice-wise feature distillation. Unlike conventional tensor decomposition methods that rely on…
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…
Weight Clustering Reveals the Importance of Relative Rank in Large Language Models
Borja Aizpurua, Sukhbinder Singh, Román Orús
Large language models (LLMs) contain billions of parameters, but many exact weight values are not essential. We apply scalar -means clustering to pretrained models, replacing ea…