As we begin to reach the limits of classical computing, quantum computing has emerged as
a technology that has captured the imagination of the scientific world. While for many years …

Optically active molecular materials, such as organic conjugated polymers and biological
systems, are characterized by strong coupling between electronic and vibrational degrees of …

Nonadiabatic mixed quantum–classical (NA-MQC) dynamics methods form a class of
computational theoretical approaches in quantum chemistry tailored to investigate the time …

The Born–Oppenheimer approximation underlies much of chemical simulation and provides
the framework defining the potential energy surfaces that are used for much of our pictorial …

Machine learning (ML) methods are being used in almost every conceivable area of
electronic structure theory and molecular simulation. In particular, ML has become firmly …

We review the Surface Hopping including ARbitrary Couplings (SHARC) approach for
excited‐state nonadiabatic dynamics simulations. As a generalization of the popular surface …

Machine learning has emerged as an invaluable tool in many research areas. In the present
work, we harness this power to predict highly accurate molecular infrared spectra with …

The ultrafast dynamics of photoexcited charge carriers in condensed matter systems play an
important role in optoelectronics and solar energy conversion. Yet it is challenging to …

Ultrafast processes in light-absorbing proteins have been implicated in the primary step in
the light-to-energy conversion and the initialization of photoresponsive biological functions …

A new versatile code based on Python scripts was developed to calculate spin–orbit
coupling (SOC) elements between singlet and triplet states. The code, named PySOC, is …