8 papers
Quantum-Enhanced Inference of Conditional Future Probabilities with Reduced Memory Cost
Jianjun Chen, Akshat Gupta, Chengran Yang +4
Many potential future events have devastating consequences, from the onset of earthquakes to financial black swan events. Accurate predictions of their probability of occurrence ar…
Spatiotemporal quantum advantages for rare-event sampling
Akshat Gupta, Jianjun Chen, Chengran Yang +4
In a world fraught with uncertainty, it behooves us to consider the most disastrous possible outcomes, in order that we can best mitigate against them. Often these are extreme risk…
Versatile Quantum Machine Learning with an Ultra-low Power Photonic Quantum Reservoir Computer
Wei Wang, Zan Tang, Menglong Fang +7
Integrated photonic microprocessors provide high-bandwidth, massively parallel linear computation, but realizing nonlinear feature maps and temporal memory remain key challenges fo…
Single-shot online sequence classification with unbounded quantum memory advantage
Keith K. Ng, Haochen Jay Li, Mile Gu +1
An agent monitors a complex environment, receiving one observation at each time step and eventually deciding how to label the resulting sequence. Does the sequence indicate an anom…
An Irreducible Quantum Advantage in Aligning World Models with Reality
Josep Lumbreras, Hailan Ma, Jayne Thompson +1
World models provide digital simulacra of the true world, allowing agents to be trained and tested before costly real-world deployment. At each time step, they receive an action an…
Quantum enhanced rare event discovery and sampling
Naixu Guo, Po-Wei Huang, Qisheng Wang +4
Financial crashes, cascading failures in infrastructure, and critical errors in AI systems are frequently triggered by events that occur with extremely small probability. Efficient…
Photonic-Implemented Efficient Deep Quantum Neural Network via Virtual-Driven Hilbert Space Expansion
Haoran Ma, Huihui Zhu, Zichao Zhao +10
The growing computational demands of classical neural networks have intensified the search for energy-efficient and powerful computational alternatives. Quantum neural networks (QN…
Learning Quantum-Samplers for Stochastic Processes with Quantum Sequence Models
Ximing Wang, Chengran Yang, Chidambaram Aditya Somasundaram +2
Quantum circuits that generate coherent superpositions of stochastic processes are key to many downstream quantum-accelerated tasks, such as risk analysis, importance sampling, and…