115 citations · 185 across the 17 of their papers we have counts for
5 papers · 1 filter
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…
Practical Trainable Temporal Postprocessor for Multistate Quantum Measurement
Saeed A. Khan, Ryan Kaufman, Boris Mesits +2
We develop and demonstrate a trainable temporal post-processor (TPP) harnessing a simple but versatile machine learning algorithm to provide optimal processing of quantum measureme…
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…
Efficient computation of coherent multimode instabilities in lasers using a spectral approach
Sara Kacmoli, Saeed A. Khan, Claire F. Gmachl +1
Coherent multimode instabilities are responsible for several phenomena of recent interest in semiconductor lasers, such as the generation of frequency combs and ultrashort pulses.…
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…