Using reinforcement learning to optimize pulse sequences to improve quantum computing stability
Transforming quantum research through advanced modeling and experimental validation techniques.
Innovating Quantum Research Solutions
We specialize in quantum noise simulation, hybrid reward algorithms, and experimental validation to enhance quantum computing performance and reliability.
Our Research Approach
Our three-phase approach includes simulation modeling, RL algorithm development, and experimental validation for optimized quantum pulse sequences and enhanced performance.
Quantum Simulation Services
We provide advanced quantum simulation modeling and reinforcement learning algorithm development for optimal performance.
Pulse Optimization Solutions
Optimize pulse sequences for superconducting quantum chips using advanced simulation and validation techniques.
Reinforcement Learning
Develop hybrid reward functions and integrate hardware constraints for enhanced quantum performance.
Automate experiment logging and error analysis for efficient quantum research and development.
Experiment Automation
Quantum Optimization
Innovative solutions for quantum noise simulation and pulse optimization.
Simulation Modeling
Building quantum noise simulation environments for optimized performance.
RL Development
Designing hybrid reward functions for enhanced algorithm performance.
Experimental Validation
Deploying optimized sequences on quantum chips for comparison.
Automated Logging
Streamlining experiment logging and error analysis processes.