Results 11 to 20 of about 16,000,889 (256)
Machine-learning number fields [PDF]
, 2022 We show that standard machine-learning algorithms may be trained to predict certain invariants of algebraic number fields to high accuracy. A random-forest classifier that is trained on finitely many Dedekind zeta coefficients is able to distinguish ...
Oliver, T., He, Y.-H., Lee, K.-H.
core +2 more sources
Levels and sublevels of composition algebras over p-adic function fields [PDF]
, 2008 In [O'S], the level and sublevel of composition algebras are studied, wherein these quantities are determined for those algebras defined over local fields.
Van Geel, Jan +3 more
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Classification of algebraic function fields with class number one [PDF]
, 2015 In this paper we prove that there are exactly eight function fields, up to isomorphism, over finite fields with class number one and positive genus. This classification was already suggested, although not completely proved, in a previous work about this ...
MERCURI, PIETRO, STIRPE, CLAUDIO
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The Chebotarev density theorem for function fields-Incomplete intervals
, 2021 We prove a Polya-Vinogradov type variation of the Chebotarev density theorem for function fields over finite fields valid for "incomplete intervals" I subset of F-p, provided (p(1/2) log p)/|I| = o(1). Applications include density results for irreducible
Rosenzweig, Lior,, Kurlberg, Pär,
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Preprint: Machine-learning number fields
, 2020 We show that standard machine-learning algorithms may be trained to predict certain invariants of algebraic number fields to high accuracy. A random-forest classifier that is trained on finitely many Dedekind zeta coefficients is able to distinguish ...
Oliver, T., He, Y.-H., Lee, K.-H.
core +1 more source
Scientific Reports, 2022 Based on physics-informed deep learning method, the deep learning model is proposed for thermal fluid fields reconstruction. This method applied fully-connected layers to establish the mapping function from design variables and space coordinates to ...
Yunzhu Li, Tianyuan Liu, Yonghui Xie
doaj +1 more source
DOUBLE NERF: REPRESENTING DYNAMIC SCENES AS NEURAL RADIANCE FIELDS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 Neural Radiance Fields (NeRFs) are non-convolutional neural models that learn 3D scene structure and color to produce novel images of a given scene from a new view point.
V. V. Kniaz +7 more
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Advances in High Energy Physics, 2013 The Klein-Gordon (KG) equation for the two-dimensional scalar-vector harmonic oscillator plus Cornell potentials in the presence of external magnetic and Aharonov-Bohm (AB) flux fields is solved using the wave function ansatz method.
Sameer M. Ikhdair, Ramazan Sever
doaj +1 more source
A string theory which isn’t about strings
Journal of High Energy Physics, 2017 Quantization of closed string proceeds with a suitable choice of worldsheet vacuum. A priori, the vacuum may be chosen independently for left-moving and right-moving sectors.
Kanghoon Lee +2 more
doaj +1 more source
Additive Cellular Automata and Volume Growth
Entropy, 2000 : A class of dynamical systems associated to rings of S-integers in rational function fields is described. General results about these systems give a rather complete description of the well-known dynamics in one-dimensional additive cellular automata ...
Thomas B. Ward
doaj +1 more source