44 citations · 126 across the 11 of their papers we have counts for
8 papers · 1 filter
Quantum Observers: A NISQ Hardware Demonstration of Chaotic State Prediction Using Quantum Echo-state Networks
Erik L. Connerty, Ethan N. Evans, Gerasimos Angelatos +1
Recent advances in artificial intelligence have highlighted the remarkable capabilities of neural network (NN)-powered systems on classical computers. However, these systems face s…
Predicting Chaotic Systems with Quantum Echo-state Networks
Erik Connerty, Ethan Evans, Gerasimos Angelatos +1
Recent advancements in artificial neural networks have enabled impressive tasks on classical computers, but they demand significant computational resources. While quantum computing…
A neural processing approach to quantum state discrimination
Saeed A. Khan, Fangjun Hu, Gerasimos Angelatos +2
Although linear quantum amplification has proven essential to the processing of weak quantum signals, extracting higher-order quantum features such as correlations in principle dem…
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…
Physical reservoir computing using finitely-sampled quantum systems
Saeed Ahmed Khan, Fangjun Hu, Gerasimos Angelatos +1
The paradigm of reservoir computing exploits the nonlinear dynamics of a physical reservoir to perform complex time-series processing tasks such as speech recognition and forecasti…
Reservoir Computing Approach to Quantum State Measurement
Gerasimos Angelatos, Saeed Khan, Hakan E. Türeci
Efficient quantum state measurement is important for maximizing the extracted information from a quantum system. For multi-qubit quantum processors in particular, the development o…