4 papers
Anchor: Reducing Temporal and Spatial Output Performance Variability on Quantum Computers
Yuqian Huo, Daniel Leeds, Jason Ludmir +2
Quantum computing, which has the power to accelerate many computing applications, is currently a technology under development. As a result, the existing noisy intermediate-scale qu…
Layerwise Federated Learning for Heterogeneous Quantum Clients using Quorus
Jason Han, Nicholas S. DiBrita, Daniel Leeds +3
Quantum machine learning (QML) holds the promise to solve classically intractable problems, but, as critical data can be fragmented across private clients, there is a need for dist…
Quorum: Zero-Training Unsupervised Anomaly Detection using Quantum Autoencoders
Jason Zev Ludmir, Sophia Rebello, Jacob Ruiz +1
Detecting mission-critical anomalous events and data is a crucial challenge across various industries, including finance, healthcare, and energy. Quantum computing has recently eme…
Modeling and Simulating Rydberg Atom Quantum Computers for Hardware-Software Co-design with PachinQo
Jason Zev Ludmir, Yuqian Huo, Nicholas S. DiBrita +1
Quantum computing has the potential to accelerate various domains: scientific computation, machine learning, and optimization. Recently, Rydberg atom quantum computing has emerged…