8 papers
Three Birds with One Stone: Improving Performance, Convergence, and System Throughput with Nest
Yuqian Huo, David Quiroga, Anastasios Kyrillidis +1
Variational quantum algorithms (VQAs) have the potential to demonstrate quantum utility on near-term quantum computers. However, these algorithms often get executed on the highest-…
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…
Revisiting Noise-adaptive Transpilation in Quantum Computing: How Much Impact Does it Have?
Yuqian Huo, Jinbiao Wei, Christopher Kverne +3
Transpilation, particularly noise-aware optimization, is widely regarded as essential for maximizing the performance of quantum circuits on superconducting quantum computers. The c…
ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers
Nicholas S. DiBrita, Jason Han, Tirthak Patel
Research in quantum machine learning has recently proliferated due to the potential of quantum computing to accelerate machine learning. An area of machine learning that has not ye…
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…