Bikramaditya Mandal

collaborators

3 papers

physics.chem-ph2025

Neural network ensemble for computing cross sections for rotational transitions in H $_{2}$ O + H $_{2}$ O collisions

Bikramaditya Mandal, Dmitri Babikov, Phillip C. Stancil +3

Water (H $_{2}$ O) is one of the most abundant molecules in the universe and is found in a wide variety of astrophysical environments. Rotational transitions in H $_{2}$ O + H $_{2}$ O collisi…

physics.chem-ph2024

On Mixed Quantum/Classical Theory for Rotationally Inelastic Scattering of Identical Collision Partners

Dulat Bostan, Bikramaditya Mandal, Dmitri Babikov

Mixed quantum/classical theory (MQCT) for the treatment of rotationally inelastic transitions during collisions of two identical molecules, described either as indistinguishable or…

quant-ph2024

Rate Coefficients for Rotational State-to-State Transitions in H $_{2}$ O + H $_{2}$ Collisions as Predicted by Mixed Quantum/Classical Theory (MQCT)

Carolin Joy, Dulat Bostan, Bikramaditya Mandal +1

A new database of collisional rate coefficients for transitions between the rotational states of H $_{2}$ O collided with H $_{2}$ background gas is developed. The goal is to expand over…

Neural network ensemble for computing cross sections for rotational transitions in H2​O + H2​O collisions

On Mixed Quantum/Classical Theory for Rotationally Inelastic Scattering of Identical Collision Partners

Rate Coefficients for Rotational State-to-State Transitions in H2​O + H2​ Collisions as Predicted by Mixed Quantum/Classical Theory (MQCT)

Neural network ensemble for computing cross sections for rotational transitions in H $_{2}$ O + H $_{2}$ O collisions

Rate Coefficients for Rotational State-to-State Transitions in H $_{2}$ O + H $_{2}$ Collisions as Predicted by Mixed Quantum/Classical Theory (MQCT)