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Efforts toward a comprehensive description of behavior have indeed facilitated the development of representation-based approaches that utilize deep learning to capture behavioral information. As behavior complexity increases, the expressive…

Computational Engineering, Finance, and Science · Computer Science 2024-01-01 Cheng Wang , Hangyu Zhu , Yuhang Lin , Changjun Jiang

The automatic analysis of chemical literature has immense potential to accelerate the discovery of new materials and drugs. Much of the critical information in patent documents and scientific articles is contained in figures, depicting the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Lucas Morin , Martin Danelljan , Maria Isabel Agea , Ahmed Nassar , Valery Weber , Ingmar Meijer , Peter Staar , Fisher Yu

We use density functional theory to describe the phase behaviors of rigid molecules. The construction of kernel function G(x, P, x, P) is discussed. Excluded-volume potential is calculated for two types of molecules with C_{2v} symmetry.…

Mathematical Physics · Physics 2017-11-23 Jie Xu , Pingwen Zhang

Complexity metrics and machine learning (ML) models have been utilized to analyze the lengths of segmental genomic entities like: exons, introns, intergenic and repeat/unique DNA sequences, in each of the 22 human chromosomes. The purpose…

IR or near-infrared (NIR) spectroscopy is a method used to identify a compound or to analyze the composition of a material. Calibration of NIR spectra refers to the use of the spectra as multivariate descriptors to predict concentrations of…

Neural and Evolutionary Computing · Computer Science 2015-03-19 A. Ukil , J. Bernasconi , H. Braendle , H. Buijs , S. Bonenfant

The calculation of the optical properties of hot dense plasmas with a model that has self-consistent plasma physics is a grand challenge for high energy density science. Here we exploit a recently developed electronic structure model that…

Plasma Physics · Physics 2022-01-07 Nathaniel R. Shaffer , Charles E. Starrett

The application of molecular dynamics (MD) simulations to the interpretation of Raman scattering spectra is hindered by inability of atomistic simulations to account for the dynamic evolution of electronic polarizability, requiring the use…

Materials Science · Physics 2023-04-18 Atanu Paul , Anthony Ruffino , Stefan Masiuk , Jonathan Spanier , Ilya Grinberg

Spectral lines from interstellar molecules provide crucial insights into the physical and chemical conditions of the interstellar medium. Traditional spectral line analysis relies heavily on manual intervention, which becomes impractical…

Astrophysics of Galaxies · Physics 2026-01-14 Yisheng Qiu , Tianwei Zhang , Tie Liu , Fengyao Zhu , Dezhao Meng , Huaxi Chen , Thomas Möller , Peter Schilke , Donghui Quan

A multiscale QM/classical approach is presented, that is able to model the optical properties of complex nanostructures composed of a molecular system adsorbed on metal nanoparticles. The latter are described by a combined…

Chemical Physics · Physics 2024-10-29 Pablo Grobas Illobre , Piero Lafiosca , Luca Bonatti , Tommaso Giovannini , Chiara Cappelli

A measure of complexity based on a probabilistic description of physical systems is proposed. This measure incorporates the main features of the intuitive notion of such a magnitude. It can be applied to many physical situations and to…

Chaotic Dynamics · Physics 2009-11-07 Ricardo Lopez-Ruiz , Hector Mancini , Xavier Calbet

Second-harmonic scattering experiments of water and other bulk molecular liquids have long been assumed to be insensitive to interactions between the molecules. The measured intensity is generally thought to arise from incoherent scattering…

Soft Condensed Matter · Physics 2017-08-28 Gabriele Tocci , Chungwen Liang , David M. Wilkins , Sylvie Roke , Michele Ceriotti

Chemical space which encompasses all stable compounds is unfathomably large and its dimension scales linearly with the number of atoms considered. The success of machine learning methods suggests that many physical quantities exhibit…

Chemical Physics · Physics 2025-07-04 Ali Banjafar , Guido Falk von Rudorff

Preparing molecules at rest and in a highly pure quantum state is a long standing dream in chemistry and physics, so far achieved only for a select set of molecules in dedicated experimental setups. Here, a quantum-limited combination of…

Quantum Physics · Physics 2015-05-30 D. Leibfried

This paper addresses the problem of separating spectral sources which are linearly mixed with unknown proportions. The main difficulty of the problem is to ensure the full additivity (sum-to-one) of the mixing coefficients and…

Methodology · Statistics 2010-08-30 Nicolas Dobigeon , Said Moussaoui , Jean-Yves Tourneret , Cedric Carteret

We devise a theory of x-ray absorption by symmetric-top molecules which are aligned by an intense optical laser. Initially, the density matrix of the system is composed of the electronic ground state of the molecules and a thermal ensemble…

Chemical Physics · Physics 2008-02-23 Christian Buth , Robin Santra

The performance of organic optoelectronic devices is critically dependent on how molecules orient within organic thin films. Yet, standard characterization techniques only reveal the first and second moments of the molecular orientation…

Cumulant mapping employs a statistical reconstruction of the whole by sampling its parts. The theory developed in this work formalises and extends ad hoc methods of `multi-fold' or `multi-dimensional' covariance mapping. Explicit formulae…

Data Analysis, Statistics and Probability · Physics 2023-11-06 Leszek J. Frasinski

Progress on researches in the field of molecules at cold and ultracold temperatures is reported in this review. It covers extensively the experimental methods to produce, detect and characterize cold and ultracold molecules including…

Quantum Physics · Physics 2015-05-13 Olivier Dulieu , Carlo Gabbanini

Transmission electron microscopy (TEM) is a potent technique for the determination of three-dimensional atomic scale structure of samples in structural biology and materials science. In structural biology, three-dimensional structures of…

Machine learning has emerged as an invaluable tool in many research areas. In the present work, we harness this power to predict highly accurate molecular infrared spectra with unprecedented computational efficiency. To account for…

Chemical Physics · Physics 2021-03-16 Michael Gastegger , Jörg Behler , Philipp Marquetand