6 papers
WSBD: Freezing-Based Optimizer for Quantum Neural Networks
Christopher Kverne, Mayur Akewar, Yuqian Huo +2
The training of Quantum Neural Networks (QNNs) is hindered by the high computational cost of gradient estimation and the barren plateau problem, where optimization landscapes becom…
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…
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…
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…
ReCon: Reconfiguring Analog Rydberg Atom Quantum Computers for Quantum Generative Adversarial Networks
Nicholas S. DiBrita, Daniel Leeds, Yuqian Huo +2
Quantum computing has shown theoretical promise of speedup in several machine learning tasks, including generative tasks using generative adversarial networks (GANs). While quantum…