4 papers · 1 filter
Lindbladian Learning with Neural Differential Equations
Timothy Heightman, Roman Aseguinolaza Gallo, Edward Jiang +3
Inferring the dynamical generator of a many-body quantum system from measurement data is essential for the verification, calibration, and control of quantum processors. When the sy…
Quantifying superluminal signalling in Schrödinger-Newton model
Julia OsÄka-Lenart, Marcin PÅodzieÅ, Maciej Lewenstein +1
The Schrödinger-Newton equation aims at describing the dynamics of massive quantum systems subject to the gravitational self-interaction. As a deterministic nonlinear quantum wave…
Quantum Machine Learning in Multi-Qubit Phase-Space Part I: Foundations
Timothy Heightman, Edward Jiang, Ruth Mora-Soto +2
Quantum machine learning (QML) seeks to exploit the intrinsic properties of quantum mechanical systems, including superposition, coherence, and quantum entanglement for classical d…
Deep Learning in Classical and Quantum Physics
Timothy Heightman, Marcin PÅodzieÅ
Scientific progress is tightly coupled to the emergence of new research tools. Today, machine learning (ML)-especially deep learning (DL)-has become a transformative instrument for…