118 citations · 179 across the 6 of their papers we have counts for
6 papers
Overcoming the Coherence Time Barrier in Quantum Machine Learning on Temporal Data
Fangjun Hu, Saeed A. Khan, Nicholas T. Bronn +4
Practical implementation of many quantum algorithms known today is limited by the coherence time of the executing quantum hardware and quantum sampling noise. Here we present a mac…
Tackling Sampling Noise in Physical Systems for Machine Learning Applications: Fundamental Limits and Eigentasks
Fangjun Hu, Gerasimos Angelatos, Saeed A. Khan +6
The expressive capacity of physical systems employed for learning is limited by the unavoidable presence of noise in their extracted outputs. Though present in physical systems acr…
Quantifying the Expressive Capacity of Quantum Systems: Fundamental Limits and Eigentasks
Fangjun Hu, Gerasimos Angelatos, Saeed A. Khan +6
The expressive capacity of quantum systems for machine learning is limited by quantum sampling noise incurred during measurement. Although it is generally believed that noise limit…
Nonlinear input transformations are ubiquitous in quantum reservoir computing
L. C. G. Govia, G. J. Ribeill, G. E. Rowlands +1
The nascent computational paradigm of quantum reservoir computing presents an attractive use of near-term, noisy-intermediate-scale quantum processors. To understand the potential…
Quantum reservoir computing with a single nonlinear oscillator
L. C. G. Govia, G. J. Ribeill, G. E. Rowlands +2
Realizing the promise of quantum information processing remains a daunting task, given the omnipresence of noise and error. Adapting noise-resilient classical computing modalities…
Sub-nanosecond switching in a cryogenic spin-torque spin-valve memory element with a dilute permalloy free layer
Laura Rehm, Volker Sluka, Graham E. Rowlands +3
We present a study of the pulsed current switching characteristics of spin-valve nanopillars with in-plane magnetized dilute permalloy and undiluted permalloy free layers in the ba…