233 citations · 241 across the 4 of their papers we have counts for
4 papers
Generating Approximate Ground States of Molecules Using Quantum Machine Learning
Jack Ceroni, Torin F. Stetina, Maria Kieferova +3
The potential energy surface (PES) of molecules with respect to their nuclear positions is a primary tool in understanding chemical reactions from first principles. However, obtain…
Tailgating quantum circuits for high-order energy derivatives
Jack Ceroni, Alain Delgado, Soran Jahangiri +1
To understand the chemical properties of molecules, it is often important to study derivatives of energies with respect to nuclear coordinates or external fields. Quantum algorithm…
Differentiable quantum computational chemistry with PennyLane
Juan Miguel Arrazola, Soran Jahangiri, Alain Delgado +15
This work describes the theoretical foundation for all quantum chemistry functionality in PennyLane, a quantum computing software library specializing in quantum differentiable pro…
PennyLane: Automatic differentiation of hybrid quantum-classical computations
Ville Bergholm, Josh Izaac, Maria Schuld +65
PennyLane is a Python 3 software framework for differentiable programming of quantum computers. The library provides a unified architecture for near-term quantum computing devices,…