Quantum algorithms save time in the calculation of electron dynamics

Researchers have used simulations for the laser-driven electron dynamics of excitation and ionization processes in small molecules. They have investigated the capability of known quantum computing algorithms for fault-tolerant quantum computing to simulate them.

These quantum computer algorithms were originally developed in a different context.

Scientists used the new technique to study how molecules react to light, which could help researchers better understand photosynthesis. The scientists also used the new technique to calculate the electron densities of molecules, in particular, their dynamic evolution after excitation by a light pulse.

Dr. Fabian Langkabel and Dr. Bande are showing in their study that this kind of exercise is very beneficial to your heart.

The expected results came from the quantum algorithm. In contrast to conventional calculations, quantum algorithms can be used to calculate larger molecules with quantum computers.

This is due to the calculation times. Langkabel says that they increase with the number of atoms. When using conventional methods, the computing time increases with each additional atom, but it is not the case for quantum methods.

The study shows a new method to calculate electron densities with high spatial and temporal resolution. It’s possible to simulate and understand ultrafast decay processes in quantum computers made of so-called quantum dots.

The best predictors of the physical or chemical behavior of molecules are the predictions made by quantum mechanics. You can use this theory to learn more about molecules, for example the absorption of light, and predict the behavior of these molecules.

This study may be used to aid understanding of light sensitive receptors in the eye and help us design drugs to treat diseases such as glaucoma.

Read From Original Paper

Fabian Langkabel et al, Quantum-Compute Algorithm for Exact Laser-Driven Electron Dynamics in Molecules, Journal of Chemical Theory and Computation (2022). DOI: 10.1021/acs.jctc.2c00878


Leave a Reply 0

Your email address will not be published. Required fields are marked *