4 papers
Revisiting Thermal Scalability for Large-Scale Superconducting Quantum Systems
Shaswot Shresthamali, Ilkwon Byun, Teruo Tanimoto +4
The readout amplification chain imposes a critical thermal scalability bottleneck in large-scale superconducting quantum systems. This happens through three mechanisms: amplifier d…
Scalable Quantum Reinforcement Learning on NISQ Devices with Dynamic-Circuit Qubit Reuse and Grover Optimization
Thet Htar Su, Shaswot Shresthamali, Masaaki Kondo
A scalable and resource-efficient quantum reinforcement learning framework is presented that eliminates the linear qubit-scaling barrier in multi-step quantum Markov decision proce…
Quantum framework for Reinforcement Learning: Integrating Markov decision process, quantum arithmetic, and trajectory search
Thet Htar Su, Shaswot Shresthamali, Masaaki Kondo
This paper introduces a quantum framework for addressing reinforcement learning (RL) tasks, grounded in the quantum principles and leveraging a fully quantum model of the classical…
Q-gen: A Parameterized Quantum Circuit Generator
Yikai Mao, Shaswot Shresthamali, Masaaki Kondo
Unlike most classical algorithms that take an input and give the solution directly as an output, quantum algorithms produce a quantum circuit that works as an indirect solution to…