6 papers · 1 filter
Continuous-time quantum walk-based ansätze on neutral atom hardware
Edric Matwiejew, Jonathan Wurtz, Jing Chen +3
Continuous-time quantum walks offer provable speedups for certain computational problems, yet translating these advantages to near-term hardware remains challenging. We realize var…
Quantum Reservoir Computing with Neutral Atoms on a Small, Complex, Medical Dataset
Luke Antoncich, Yuben Moodley, Ugo Varetto +5
Biomarker-based prediction of clinical outcomes is challenging due to nonlinear relationships, correlated features, and the limited size of many medical datasets. Classical machine…
Quantum circuits as a game: A reinforcement learning agent for quantum compilation and its application to reconfigurable neutral atom arrays
Kouhei Nakaji, Jonathan Wurtz, Haozhe Huang +4
We introduce the "quantum circuit daemon" (QC-Daemon), a reinforcement learning agent for compiling quantum device operations aimed at efficient quantum hardware execution. We appl…
Experimental Demonstration of Logical Magic State Distillation
Pedro Sales Rodriguez, John M. Robinson, Paul Niklas Jepsen +70
Realizing universal fault-tolerant quantum computation is a key goal in quantum information science. By encoding quantum information into logical qubits utilizing quantum error cor…
Non-native Quantum Generative Optimization with Adversarial Autoencoders
Blake A. Wilson, Jonathan Wurtz, Vahagn Mkhitaryan +5
Large-scale optimization problems are prevalent in several fields, including engineering, finance, and logistics. However, most optimization problems cannot be efficiently encoded…
Large-scale quantum reservoir learning with an analog quantum computer
Milan KornjaÄa, Hong-Ye Hu, Chen Zhao +50
Quantum machine learning has gained considerable attention as quantum technology advances, presenting a promising approach for efficiently learning complex data patterns. Despite t…