7 papers
Perspective on a challenge: predicting the photochemistry of cyclobutanone
JiÅà JanoÅ¡, Nanna Holmgaard List, Andrew J. Orr-Ewing +37
This Perspective is part of a Special Topic that explored the maturity of nonadiabatic molecular dynamics for predicting photochemical processes. In 2023, a prediction challenge wa…
milearn: A Python Package for Multi-Instance Machine Learning
Dmitry Zankov, Pavlo Polishchuk, Michal Sobieraj +1
We introduce milearn, a Python package for multi-instance learning (MIL) that follows the familiar scikit-learn fit/predict interface while providing a unified framework for both c…
The Quantum Measurement Problem: A Review of Recent Trends
Anderson A. Tomaz, Rafael S. Mattos, Mario Barbatti
Left on its own, a quantum state evolves deterministically under the Schrödinger Equation, forming superpositions. Upon measurement, however, a stochastic process governed by the…
Ehrenfest Dynamics with Spontaneous Localization
Anderson A. Tomaz, Rafael S. Mattos, Saikat Mukherjee +1
We propose Ehrenfest Dynamics with Spontaneous Localization (SLED), a decoherence-corrected extension of Ehrenfest dynamics based on the Gisin-Percival quantum-state diffusion (QSD…
A simple approach to rotationally invariant machine learning of avector quantity
Jakub Martinka, Marek Pederzoli, Mario Barbatti +2
Unlike with the energy, which is a scalar property, machine learning (ML) predictions of vector or tensor properties poses the additional challenge of achieving proper invariance (…
Roadmap for Molecular Benchmarks in Nonadiabatic Dynamics
Léon E. Cigrang, Basile F. E. Curchod, Rebecca A. Ingle +42
Simulating the coupled electronic and nuclear response of a molecule to light excitation requires the application of nonadiabatic molecular dynamics. However, when faced with a spe…