8 citations · 10 across the 12 of their papers we have counts for
5 papers · 1 filter
Benchmarking Simulacra AI's Quantum Accurate Synthetic Data Generation for Chemical Sciences
Fabio Falcioni, Elena Orlova, Timothy Heightman +2
In this work, we benchmark \simulacra's synthetic data generation pipeline against a state-of-the-art Microsoft pipeline on a dataset of small to large systems. By analyzing the en…
Deep Learning in Classical and Quantum Physics
Timothy Heightman, Marcin Płodzień
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…
Heisenberg-Limited Quantum Hamiltonian Learning via Randomly Spread Product-States
Bora Baran, Timothy Heightman
We show how the Heisenberg-limited quadratic Fisher-information regime of short-time quantum evolution can be made practically accessible for quantum Hamiltonian learning, using on…
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…
Mapping Phase Diagrams of Quantum Spin Systems through Semidefinite-Programming Relaxations
David Jansen, Donato Farina, Luke Mortimer +5
Identifying quantum phase transitions poses a significant challenge in condensed matter physics, as this requires methods that both provide accurate results and scale well with sys…