4 papers
Quantum Dimension Reduction of Hidden Markov Models
Rishi Sundar, Thomas J. Elliott
Hidden Markov models (HMMs) are ubiquitous in time-series modelling, with applications ranging from chemical reaction modelling to speech recognition. These HMMs are often large, w…
BOA Constrictor: A Mamba-based lossless compressor for High Energy Physics data
Akshat Gupta, Caterina Doglioni, Thomas Joseph Elliott
The petabyte-scale data generated annually by High Energy Physics (HEP) experiments like those at the Large Hadron Collider present a significant data storage challenge. Whilst tra…
Identifiability and minimality bounds of quantum and post-quantum models of classical stochastic processes
Paul M. Riechers, Thomas J. Elliott
To make sense of the world around us, we develop models, constructed to enable us to replicate, describe, and explain the behaviours we see. Focusing on the broad case of sequences…
Neural networks leverage nominally quantum and post-quantum representations
Paul M. Riechers, Thomas J. Elliott, Adam S. Shai
We show that deep neural networks, including transformers and RNNs, pretrained as usual on next-token prediction, intrinsically discover and represent beliefs over 'quantum' and 'p…