Improving application performance with biased distributions of quantum states
We consider the properties of a specific distribution of mixed quantum states of arbitrary
dimension that can be biased towards a specific mean purity. In particular, we analyze …
dimension that can be biased towards a specific mean purity. In particular, we analyze …
Demonstration of machine-learning-enhanced Bayesian quantum state estimation
Abstract Machine learning (ML) has found broad applicability in quantum information
science in topics as diverse as experimental design, state classification, and even studies on …
science in topics as diverse as experimental design, state classification, and even studies on …
Dimension-adaptive machine learning-based quantum state reconstruction
We introduce an approach for performing quantum state reconstruction on systems of n
qubits using a machine learning-based reconstruction system trained exclusively on m …
qubits using a machine learning-based reconstruction system trained exclusively on m …
On how neural networks enhance quantum state tomography with constrained measurements
Quantum state tomography aiming at reconstructing the density matrix of a quantum state
plays an important role in various emerging quantum technologies. Inspired by the intuition …
plays an important role in various emerging quantum technologies. Inspired by the intuition …
Learning-based quantum state reconstruction using biased quantum state distributions
We derive the Dirichlet concentration parameters for mixtures of Haar-random pure states
that recover mean purities equal to standard measures, demonstrating how tailored …
that recover mean purities equal to standard measures, demonstrating how tailored …