Showing quant-phShow all
3 papers · 1 filter
quant-ph2025
Combining quantum noise reduction resources: a practical approach
Sohitri Ghosh, Matthew A. Feldman, Seongjin Hong +4
Optomechanical sensors are capable of transducing external perturbations to resolvable optical signals. A particular regime of interest is that of high-bandwidth force detection, w…
quant-ph2025
Variational optical phase learning on a continuous-variable quantum compiler
Matthew A. Feldman, Tyler Volkoff, Seongjin Hong +5
Quantum process learning is a fundamental primitive that draws inspiration from machine learning with the goal of better studying the dynamics of quantum systems. One approach to q…
quant-ph2024
Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions
Yuri Alexeev, Maximilian Amsler, Paul Baity +124
Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of e…