quantum-control
quantum-control-repo
Meta-Reinforcement Learning for Adaptive Quantum Control
Author: Nima Leclerc (nleclerc@mitre.org) -- PI for Adaptive Quantum Sensing and Quantum Research Scientist at MITRE
© 2025 The MITRE Corporation, All Rights Reserved
Approved for Public Release; Distribution Unlimited. Public Release Case Number 25-2936.
A research implementation of first-order Model-Agnostic Meta-Learning (MAML) for quantum state control under noise. This framework trains a meta-learned policy… See the full description on the dataset page: https://huggingface.co/datasets/Sor0ush/quantum-control-repo.quantum-control-pulse-instability-v0.1
quantum-control-pulse-instability-v0.1
What this dataset does
This dataset evaluates whether models can detect instability in quantum control pulse regimes.
Each row represents a simplified control scenario where quantum gates are implemented through microwave or optical pulse sequences.
The task is to determine whether the pulse regime remains stable or becomes unstable due to drift, noise, or synchronization failures.
Core stability idea
Quantum control… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/quantum-control-pulse-instability-v0.1.quantum-bridge-teamleader-employee-access-control
nit1607/quantum-bridge-teamleader-employee-access-control
Dataset for QuantumBridge Networks. highest_access_level: department_head
quantum-bridge-dh-teamleader-access-control
nit1607/quantum-bridge-dh-teamleader-access-control
Dataset for QuantumBridge Networks. highest_access_level: department_head
quantum-bridge-dh-employee-access-control
nit1607/quantum-bridge-dh-employee-access-control
Dataset for QuantumBridge Networks. highest_access_level: department_head