AIMC Topic: Quantum Theory

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Machine-Learning-Assisted Free Energy Simulation of Solution-Phase and Enzyme Reactions.

Journal of chemical theory and computation Sep 1, 2021
Despite recent advances in the development of machine learning potentials (MLPs) for biomolecular simulations, there has been limited effort on developing stable and accurate MLPs for enzymatic reactions. Here we report a protocol for performing mach...
Quantum Theory Thermodynamics Machine Learning
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Ab Initio Machine Learning in Chemical Compound Space.

Chemical reviews Aug 13, 2021
Chemical compound space (CCS), the set of all theoretically conceivable combinations of chemical elements and (meta-)stable geometries that make up matter, is colossal. The first-principles based virtual sampling of this space, for example, in search...
Organic Chemicals Quantum Theory Machine Learning Inorganic Chemicals
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Multitask machine learning models for predicting lipophilicity (logP) in the SAMPL7 challenge.

Journal of computer-aided molecular design Jul 17, 2021
Accurate prediction of lipophilicity-logP-based on molecular structures is a well-established field. Predictions of logP are often used to drive forward drug discovery projects. Driven by the SAMPL7 challenge, in this manuscript we describe the steps...
Drug Discovery Neural Networks, Computer Models, Statistical Machine Learning Solubility Thermodynamics Quantum Theory Solvents Models, Chemical
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Nuclear Quantum Effect and Its Temperature Dependence in Liquid Water from Random Phase Approximation via Artificial Neural Network.

The journal of physical chemistry letters Jul 7, 2021
We report structural and dynamical properties of liquid water described by the random phase approximation (RPA) correlation together with the exact exchange energy (EXX) within density functional theory. By utilizing thermostated ring polymer molecul...
Models, Molecular Water Molecular Conformation Neural Networks, Computer Quantum Theory Temperature
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Learning the Exciton Properties of Azo-dyes.

The journal of physical chemistry letters Jun 22, 2021
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...
Azo Compounds Molecular Conformation Quantum Theory Coloring Agents Models, Molecular Machine Learning
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Machine Learning in QM/MM Molecular Dynamics Simulations of Condensed-Phase Systems.

Journal of chemical theory and computation Apr 5, 2021
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 ...
Quantum Theory Molecular Dynamics Simulation Static Electricity Machine Learning
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Life as a self-referential deep learning system: A quantum-like Boltzmann machine model.

Bio Systems Feb 25, 2021
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...
Deep Learning Humans Quantum Theory Models, Theoretical Entropy Income
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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 Jan 12, 2021
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...
Machine Learning Neural Networks, Computer Quantum Theory
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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 Jan 8, 2021
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...
Electrons Neural Networks, Computer Sulfides Tin Compounds Quantum Theory Solar Energy Copper Zinc
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Statistical field theory of the transmission of nerve impulses.

Theoretical biology & medical modelling Jan 6, 2021
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.
Quantum Theory Computing Methodologies Action Potentials Artificial Intelligence Models, Neurological
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