Results 51 to 60 of about 1,487,794 (276)
Exact Discrete Stochastic Simulation With Deep‐Learning‐Scale Gradient Optimization
A 203,796‐parameter gene regulatory network classifies handwritten digits with 98.4% accuracy using exact stochastic dynamics. The framework decouples forward simulation from backward differentiation, making continuous‐time Markov chain models compatible with deep‐learning optimization.
Jose M. G. Vilar, Leonor Saiz
wiley +1 more source
Gap‐Free Information Transfer in 4D‐STEM via Fusion of Complementary Scattering Channels
Fused Full‐Field STEM (FF‐STEM) is introduced as a 4D‐STEM imaging modality that combines direct ptychography with tilt‐corrected dark‐field reconstruction in a single acquisition. Fourier‐space fusion using Wiener‐type spectral weighting closes the low‐frequency contrast gap inherent to bright‐field methods, delivering gap‐free, dose‐efficient, near ...
Shengbo You +15 more
wiley +1 more source
Adjoint SU(5) GUT model with modular S 4 symmetry
We study the textures of SM fermion mass matrices and their mixings in a supersymmetric adjoint SU(5) Grand Unified Theory with modular S 4 being the horizontal symmetry.
Ya Zhao, Hong-Hao Zhang
doaj +1 more source
Effect of Approximations of the Discrete Adjoint on Gradient-Based Optimization [PDF]
An exact discrete adjoint of an unstructured nite-volume solver for the RANS equations has been developed. The adjoint is exact in the sense of being based on the full linearization of all terms in the solver, including all turbulence model ...
Brezillon, Joel, Dwight, Richard
core
Conceptual illustration of a Global Ecosystem Methane Observing System (GEM‐OS) integrating satellites, aircraft, atmospheric networks, and ecosystem measurements to quantify methane emissions from anthropogenic and natural sources. The multi‐scale observing framework improves source attribution, reduces uncertainty in regional methane budgets, and ...
P. Ciais +32 more
wiley +1 more source
Investigation on Adjoint Based Gradient Computations for Realistic 3d Aero-Optimization [PDF]
A discrete adjoint method for e ciently computing gradients for aerodynamic shape op- timizations is presented. The chain itself involves an unstructured mesh Reynolds-Averaged Navier-Stokes solver, and is suitable for the optimization of complex ...
Brezillon, Joel +3 more
core
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley +1 more source
Phases Of Adjoint QCD$_3$ And Dualities
We study 2+1 dimensional gauge theories with a Chern-Simons term and a fermion in the adjoint representation. We apply general considerations of symmetries, anomalies, and renormalization group flows to determine the possible phases of the theory as a
Jaume Gomis, Zohar Komargodski, Nathan Seiberg
doaj +1 more source
Lifting Automorphisms of Quotients of Adjoint Representations
Changes made following referee's suggestions.
openaire +3 more sources
Adjoint Map Representation for Shape Analysis and Matching [PDF]
AbstractIn this paper, we propose to consider the adjoint operators of functional maps, and demonstrate their utility in several tasks in geometry processing. Unlike a functional map, which represents a correspondence simply using the pull‐back of function values, the adjoint operator reflects both the map and its distortion with respect to given inner
Huang, Ruqi, Ovsjanikov, Maks
openaire +1 more source

