AIMC Topic: Quantum Theory

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Learning the Exciton Properties of Azo-dyes.

The journal of physical chemistry letters
The determination of electronic excited state (ES) properties is the cornerstone of theoretical photochemistry. Yet, traditional ES methods become impractical when applied to fairly large molecules, or when used on thousands of systems. Machine lear...

Machine Learning in QM/MM Molecular Dynamics Simulations of Condensed-Phase Systems.

Journal of chemical theory and computation
Quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations have been developed to simulate molecular systems, where an explicit description of changes in the electronic structure is necessary. However, QM/MM MD simulations are ...

Life as a self-referential deep learning system: A quantum-like Boltzmann machine model.

Bio Systems
It has been empirically found that the income structure of market-economy societies obeys a Boltzmann-like income distribution. The empirical evidence has covered more than 66 countries. In this paper, we show that when a human society obeys a Boltzm...

Creating and concentrating quantum resource states in noisy environments using a quantum neural network.

Neural networks : the official journal of the International Neural Network Society
Quantum information processing tasks require exotic quantum states as a prerequisite. They are usually prepared with many different methods tailored to the specific resource state. Here we provide a versatile unified state preparation scheme based on...

Doping-Induced Charge Localization Suppresses Electron-Hole Recombination in Copper Zinc Tin Sulfide: Quantum Dynamics Combined with Deep Neural Networks Analysis.

The journal of physical chemistry letters
Nonradiative electron-hole recombination constitutes a major route for charge and energy losses in copper zinc tin sulfide (CZTS) solar cells. Using a combination of nonadiabatic (NA) molecular dynamics and deep neural networks (DNN), we demonstrated...

Statistical field theory of the transmission of nerve impulses.

Theoretical biology & medical modelling
BACKGROUND: Stochastic processes leading voltage-gated ion channel dynamics on the nerve cell membrane are a sufficient condition to describe membrane conductance through statistical mechanics of disordered and complex systems.

A Machine Learning Protocol for Predicting Protein Infrared Spectra.

Journal of the American Chemical Society
Infrared (IR) absorption provides important chemical fingerprints of biomolecules. Protein secondary structure determination from IR spectra is tedious since its theoretical interpretation requires repeated expensive quantum-mechanical calculations i...

COSMO-RS-Based Descriptors for the Machine Learning-Enabled Screening of Nucleotide Analogue Drugs against SARS-CoV-2.

The journal of physical chemistry letters
Chemical similarity-based approaches employed to repurpose or develop new treatments for emerging diseases, such as COVID-19, correlates molecular structure-based descriptors of drugs with those of a physiological counterpart or clinical phenotype. W...

Site-Level Bioactivity of Small-Molecules from Deep-Learned Representations of Quantum Chemistry.

The journal of physical chemistry. A
Atom- or bond-level chemical properties of interest in medicinal chemistry, such as drug metabolism and electrophilic reactivity, are important to understand and predict across arbitrary new molecules. Deep learning can be used to map molecular struc...

Machine learning-accelerated quantum mechanics-based atomistic simulations for industrial applications.

Journal of computer-aided molecular design
Atomistic simulations have become an invaluable tool for industrial applications ranging from the optimization of protein-ligand interactions for drug discovery to the design of new materials for energy applications. Here we review recent advances in...