AIMC Topic: Quantum Theory

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Integration of Quantum Chemistry, Statistical Mechanics, and Artificial Intelligence for Computational Spectroscopy: The UV-Vis Spectrum of TEMPO Radical in Different Solvents.

Journal of chemical theory and computation Sep 27, 2022
The ongoing integration of quantum chemistry, statistical mechanics, and artificial intelligence is paving the route toward more effective and accurate strategies for the investigation of the spectroscopic properties of medium-to-large size chromopho...
Artificial Intelligence Reproducibility of Results Molecular Dynamics Simulation Quantum Theory Solvents Spectrum Analysis Cyclic N-Oxides
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Orbital Mixer: Using Atomic Orbital Features for Basis-Dependent Prediction of Molecular Wavefunctions.

Journal of chemical theory and computation Sep 19, 2022
Leveraging ab initio data at scale has enabled the development of machine learning models capable of extremely accurate and fast molecular property prediction. A central paradigm of many previous studies focuses on generating predictions for only a f...
Neural Networks, Computer Molecular Structure Quantum Theory
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Quantum Neural Networks and Topological Quantum Field Theories.

Neural networks : the official journal of the International Neural Network Society Jun 7, 2022
Our work intends to show that: (1) Quantum Neural Networks (QNNs) can be mapped onto spin-networks, with the consequence that the level of analysis of their operation can be carried out on the side of Topological Quantum Field Theory (TQFT); (2) A nu...
Neural Networks, Computer Machine Learning Quantum Theory
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Quantum Perturbation Theory Using Tensor Cores and a Deep Neural Network.

Journal of chemical theory and computation Jun 7, 2022
Time-independent quantum response calculations are performed using Tensor cores. This is achieved by mapping density matrix perturbation theory onto the computational structure of a deep neural network. The main computational cost of each deep layer ...
Neural Networks, Computer Computers Quantum Theory
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Deep learning study of tyrosine reveals that roaming can lead to photodamage.

Nature chemistry Jun 2, 2022
Amino acids are among the building blocks of life, forming peptides and proteins, and have been carefully 'selected' to prevent harmful reactions caused by light. To prevent photodamage, molecules relax from electronic excited states to the ground st...
Deep Learning Amino Acids Quantum Theory Tyrosine Photochemistry
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Reconstruction of Nuclear Ensemble Approach Electronic Spectra Using Probabilistic Machine Learning.

Journal of chemical theory and computation Apr 28, 2022
The theoretical prediction of molecular electronic spectra by means of quantum mechanical (QM) computations is fundamental to gain a deep insight into many photophysical and photochemical processes. A computational strategy that is attracting signifi...
Machine Learning Quantum Theory Electronics Solvents
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Brain-inspired computing needs a master plan.

Nature Apr 13, 2022
New computing technologies inspired by the brain promise fundamentally different ways to process information with extreme energy efficiency and the ability to handle the avalanche of unstructured and noisy data that we are generating at an ever-incre...
Neural Networks, Computer Brain Quantum Theory Biomimetics
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Predicting the future of excitation energy transfer in light-harvesting complex with artificial intelligence-based quantum dynamics.

Nature communications Apr 11, 2022
Exploring excitation energy transfer (EET) in light-harvesting complexes (LHCs) is essential for understanding the natural processes and design of highly-efficient photovoltaic devices. LHCs are open systems, where quantum effects may play a crucial ...
Artificial Intelligence Bacterial Proteins Quantum Theory Energy Transfer Light-Harvesting Protein Complexes
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CIDER: An Expressive, Nonlocal Feature Set for Machine Learning Density Functionals with Exact Constraints.

Journal of chemical theory and computation Mar 2, 2022
Machine learning (ML) has recently gained attention as a means to develop more accurate exchange-correlation (XC) functionals for density functional theory, but functionals developed thus far need to be improved on several metrics, including accuracy...
Machine Learning Quantum Theory
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Disruptive innovation in psychiatry.

Annals of the New York Academy of Sciences Mar 1, 2022
Disruptive innovation is a cornerstone of various disciplines, particularly in the business world, where paradigm-altering approaches are often lauded. As a construct, disruptive psychiatry can be considered to embody such an approach by the pursuit ...
Humans Artificial Intelligence Machine Learning Psychiatry Quantum Theory Computing Methodologies
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