AIMC Topic: Quantum Theory

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Dicke simulators with emergent collective quantum computational abilities.

Physical review letters
Using an approach inspired from spin glasses, we show that the multimode disordered Dicke model is equivalent to a quantum Hopfield network. We propose variational ground states for the system at zero temperature, which we conjecture to be exact in t...

Machine learning in computational docking.

Artificial intelligence in medicine
OBJECTIVE: The objective of this paper is to highlight the state-of-the-art machine learning (ML) techniques in computational docking. The use of smart computational methods in the life cycle of drug design is relatively a recent development that has...

ChargeNet: E(3) Equivariant Graph Attention Network for Atomic Charge Prediction.

Journal of chemical information and modeling
Atomic charge is a fundamental quantum chemical property essential for advancing drug design and discovery. Although quantum mechanics (QM) methods offer the highest level of accuracy, their computational demands scale quadratically with the number o...

Transfer-Learning Deep Raman Models Using Semiempirical Quantum Chemistry.

Journal of chemical information and modeling
Biophotonic technologies such as Raman spectroscopy are powerful tools for obtaining highly specific molecular information. Due to its minimal sample preparation requirements, Raman spectroscopy is widely used across diverse scientific disciplines, o...

Quantum federated learning with pole-angle quantum local training and trainable measurement.

Neural networks : the official journal of the International Neural Network Society
Recently, quantum federated learning (QFL) has received significant attention as an innovative paradigm. QFL has remarkable features by employing quantum neural networks (QNNs) instead of conventional neural networks owing to quantum supremacy. In or...

NepoIP/MM: Toward Accurate Biomolecular Simulation with a Machine Learning/Molecular Mechanics Model Incorporating Polarization Effects.

Journal of chemical theory and computation
Machine learning force fields offer the ability to simulate biomolecules with quantum mechanical accuracy while significantly reducing computational costs, attracting a growing amount of attention in biophysics. Meanwhile, by leveraging the efficienc...

High-Performance Computing-Based Brain Tumor Detection Using Parallel Quantum Dilated Convolutional Neural Network.

NMR in biomedicine
In the healthcare field, brain tumor causes irregular development of cells in the brain. One of the popular ways to identify the brain tumor and its progression is magnetic resonance imaging (MRI). However, existing methods often suffer from high com...

Machine Learning Classification of Chirality and Optical Rotation Using a Simple One-Hot Encoded Cartesian Coordinate Molecular Representation.

Journal of chemical information and modeling
Absolute stereochemical configurations and optical rotations were computed for 121,416 molecular structures from the QM9 quantum chemistry data set using density functional theory. A representation for the molecules was developed using Cartesian coor...

The Quest for Cognition in Purposive Action: From Cybernetics to Quantum Computing.

Journal of integrative neuroscience
Norbert Wiener and Nikolai Bernstein set the stage for a worldwide multidisciplinary attempt to understand how purposive action is integrated with cognition in a circular, bidirectional manner, both in life sciences and engineering. Such a 'workshop'...

A deep transfer learning-based protocol accelerates full quantum mechanics calculation of protein.

Briefings in bioinformatics
Effective full quantum mechanics (FQM) calculation of protein remains a grand challenge and of great interest in computational biology with substantial applications in drug discovery, protein dynamic simulation and protein folding. However, the huge ...