Results 31 to 40 of about 1,826,426 (368)
SPIN: SE(3)-Invariant Physics Informed Network for Binding Affinity Prediction [PDF]
European Conference on Artificial IntelligenceAccurate prediction of protein-ligand binding affinity is crucial for rapid and efficient drug development. Recently, the importance of predicting binding affinity has led to increased attention on research that models the three-dimensional structure of ...
Seungyeon Choi +2 more
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Experimental Identification of the Second‐Order Non‐Hermitian Skin Effect with Physics‐Graph‐Informed Machine Learning [PDF]
Advancement of science, 2022 Topological phases of matter are conventionally characterized by the bulk‐boundary correspondence in Hermitian systems. The topological invariant of the bulk in d dimensions corresponds to the number of (d − 1)‐dimensional boundary states.
Ce Shang +13 more
semanticscholar +1 more source
Notes on topological insulators [PDF]
, 2016 This paper is a survey of the $\mathbb{Z}_2$-valued invariant of topological insulators used in condensed matter physics. The $\mathbb{Z}$-valued topological invariant, which was originally called the TKNN invariant in physics, has now been fully ...
Kaufmann, Ralph M. +2 more
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The Physics of spectral invariants [PDF]
2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2010 To make full use of the increased possibilities of imaging spectroscopy (compared with the traditional multispectral instruments) for remote sensing of vegetation canopies, physically-based models should be used. The problem of retrieving the large number of model parameters from remotely sensed reflectance data is an ill-posed and underdetermined one.
openaire +2 more sources
Scientific Reports, 2022 A signature invariant geometric algebra framework for spacetime physics is formulated. By following the original idea of David Hestenes in the spacetime algebra of signature $$(+,-,-,-)$$ ( + , - , - , - ) , the techniques related to relative vector and ...
Bofeng Wu
doaj +1 more source
NeuPhysics: Editable Neural Geometry and Physics from Monocular Videos [PDF]
Neural Information Processing Systems, 2022 We present a method for learning 3D geometry and physics parameters of a dynamic scene from only a monocular RGB video input. To decouple the learning of underlying scene geometry from dynamic motion, we represent the scene as a time-invariant signed ...
Yi-Ling Qiao +2 more
semanticscholar +1 more source
Searches for new physics in collision events using a statistical technique for anomaly detection
SciPost Physics Proceedings, 2022 This paper discusses a statistical anomaly-detection method for model-independent searches for new physics in collision events produced at the Large Hadron Collider (LHC).
S. V. Chekanov
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Gauge Symmetries, Symmetry Breaking, and Gauge-Invariant Approaches [PDF]
, 2021 Gauge symmetries play a central role, both in the mathematical foundations as well as the conceptual construction of modern (particle) physics theories.
Philipp Berghofer +6 more
semanticscholar +1 more source
Neural Network-Based Intuitive Physics for Non-Inertial Reference Frames
IEEE Access, 2021 Classical mechanics offers us reliable means to predict various physical quantities, but it is difficult to derive the precise dynamic equations underlying most phenomena and obtain physical quantities in real-world situations.
Jongwoo Seo, Sang Wan Lee
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Predictions from Heavy New Physics Interpretation of the Top Forward-Backward Asymmetry [PDF]
, 2012 We derive generic predictions at hadron colliders from the large forward-backward asymmetry observed at the Tevatron, assuming the latter arises from heavy new physics beyond the Standard Model.
A Martin +31 more
core +2 more sources