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The mechanisms by which a protein's 3D structure can be determined based on its amino acid sequence have long been one of the key mysteries of biophysics. Often simplistic models, such as those derived from geometric constraints, capture…

Biological Physics · Physics 2023-01-02 Nora Molkenthin , J. J. Güven , Steffen Mühle , Antonia S. J. S. Mey

Single-molecule experimental techniques track the real-time dynamics of molecules by recording a small number of experimental observables. Following these observables provides a coarse-grained, low-dimensional representation of the…

Computational Physics · Physics 2021-02-03 Maximilian Topel , Andrew L. Ferguson

Unfolding is an important procedure in particle physics experiments which corrects for detector effects and provides differential cross section measurements that can be used for a number of downstream tasks, such as extracting fundamental…

High Energy Physics - Phenomenology · Physics 2023-07-19 Jay Chan , Benjamin Nachman

We establish that many fundamental concepts and techniques in quantum field theory and collider physics can be naturally understood and unified through a simple new geometric language. The idea is to equip the space of collider events with…

High Energy Physics - Phenomenology · Physics 2020-07-15 Patrick T. Komiske , Eric M. Metodiev , Jesse Thaler

Amorphous materials are solids that lack long-range atomic order but possess complex short- and medium-range order. Unlike crystalline materials that can be described by unit cells containing few up to hundreds of atoms, amorphous materials…

Machine Learning · Computer Science 2026-04-01 Yan Lin , Jonas A. Finkler , Tao Du , Jilin Hu , Morten M. Smedskjaer

Carbon is fundamental to science and technology due to its diverse bonding configurations, structural versatility, and essential role in defining the mechanical, chemical, electronic, and quantum properties of materials. However, direct…

Super-resolution imaging techniques have largely improved our capabilities to visualize nanometric structures in biological systems. Their application further enables one to potentially quantitate relevant parameters to determine the…

Biological Physics · Physics 2019-12-18 Tina Kosǔta , Marta Cullell-Dalmau , Francesca Cella Zanacchi , Carlo Manzo

Despite rapid progress in the development of quantum algorithms in quantum computing as well as numerical simulation methods in classical computing for atomic and molecular applications, no systematic and comprehensive electronic structure…

We are concerned with the inverse scattering problem of extracting the geometric structures of an unknown/inaccessible inhomogeneous medium by using the corresponding acoustic far-field measurement. Using the intrinsic geometric properties…

Analysis of PDEs · Mathematics 2017-06-15 Jingzhi Li , Xiaofei Li , Hongyu Liu

The mechanical unfolding of an engineered protein composed of eight domains of Ig27 is investigated by using atomic force microscopy. Exploiting a fluctuation relation, the equilibrium free energy as a function of the molecule elongation is…

Soft Condensed Matter · Physics 2008-05-29 A. Imparato , F. Sbrana , M. Vassalli

Distance metrics and their nonlinear variant play a crucial role in machine learning based real-world problem solving. We demonstrated how Euclidean and cosine distance measures differ not only theoretically but also in real-world medical…

Machine Learning · Computer Science 2021-02-25 Der-Chen Chang , Ophir Frieder , Chi-Feng Hung , Hao-Ren Yao

Unsupervised classification called clustering is a process of organizing objects into groups whose members are similar in some way. Clustering of uncertain data objects is a challenge in spatial data bases. In this paper we use Probability…

Databases · Computer Science 2013-12-10 Ramachandra Rao Kurada

This letter aims at resolving the issues raised in the recent short communication [1] and answered by [2] by proposing a systematic approximation scheme based on non-mapped shape functions, which both allows to fully exploit the unique…

Numerical Analysis · Computer Science 2011-07-20 Stephane PA Bordas , Sundararajan Natarajan

We propose a versatile, parameter-less approach for solving the shape matching problem, specifically in the context of atomic structures when atomic assignments are not known a priori. The algorithm Iteratively suggests Rotated…

Computational Physics · Physics 2021-11-02 Miha Gunde , Nicolas Salles , Anne Hémeryck , Layla Martin-Samos

The properties of polycrystalline materials are often dominated by the size of their grains and by the atomic structure of their grain boundaries. These effects should be especially pronounced in 2D materials, where even a line defect can…

We present a novel technique of sampling the configurations of helical proteins. Assuming knowledge of native secondary structure, we employ assembly rules gathered from a database of existing structures to enumerate the geometrically…

Soft Condensed Matter · Physics 2009-09-25 Boris Fain , Michael Levitt

A novel crystalline structure of hybrid monolayer hexagonal boron nitride (BN) and graphene is predicted by means of the first-principles calculations. This material can be derived via boron or nitrogen atoms substituted by carbon atoms…

Mesoscale and Nanoscale Physics · Physics 2013-10-25 Jinyun Li , Daqiang Gao , Xiaoning Niu , Mingsu Si , Desheng Xue

The current state of the art in structural biology is led by NMR, X-ray crystallography and TEM investigations. These powerful tools however all rely on averaging over a large ensemble of molecules. Here, we present an alternative concept…

Atomic and Molecular Clusters · Physics 2015-12-15 Tatiana Latychevskaia , Jean-Nicolas Longchamp , Conrad Escher , Hans-Werner Fink

The analysis of the three-dimensional structure of proteins is an important topic in molecular biochemistry. Structure plays a critical role in defining the function of proteins and is more strongly conserved than amino acid sequence over…

Applications · Statistics 2015-01-19 Abel Rodriguez , Scott C. Schmidler

A novel nonparametric clustering algorithm is proposed using the interpoint distances between the members of the data to reveal the inherent clustering structure existing in the given set of data, where we apply the classical nonparametric…

Methodology · Statistics 2024-09-02 Soumita Modak