Machine Learning Prediction of Quantum Field Statistics
Predicting quantum field statistics from atomic population dynamics using advanced neural architectures.
Where I bend light, chase photons, and explore the frontiers of quantum mechanics.
Predicting quantum field statistics from atomic population dynamics using advanced neural architectures.
Investigating collapse and revival features in quantum optics and light-matter interactions.
A hybrid pipeline for photonic design using JAX and discrete optimization for high performance optics.
Modeling the up-quark parton distribution function using parametric circuits and experimental data analysis.
Using a 29-qubit processor to drive true random walk simulations with genuine quantum randomness.
Demonstrating efficiency differences between matrix and tensor operations in complex quantum simulations.
Built with PennyLane and Flask to simulate quantum circuits from custom user-defined gate sequences.
Implemented Tachikoma algorithm in JAX for high Quantum Fisher Information search and state engineering.