We show, using covariant Lyapunov vectors, that the tangent space of spatially extended dissipative systems is split into two hyperbolically decoupled subspaces: one comprising a finite number of frequently entangled "physical" modes, which carry the physically relevant information of the trajectory, and a residual set of strongly decaying "spurious" modes. The decoupling of the physical and spurious subspaces is defined by the absence of tangencies between them and found to take place generally; we find evidence in partial differential equations in one and two spatial dimensions and even in lattices of coupled maps or oscillators. We conjecture that the physical modes may constitute a local linear description of the inertial manifold at any point in the global attractor.
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http://dx.doi.org/10.1103/PhysRevE.84.046214 | DOI Listing |
bioRxiv
December 2024
Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA.
RNA velocities and generalizations emerge as powerful approaches for exacting dynamical information from high-throughput snapshot single-cell data. Several inherent limitations restrict applying the approaches to genes not suitable for RNA velocity inference due to complex transcriptional dynamics, low expression, or lacking splicing dynamics, and data of non-transcriptomic modality. Here, we present GraphVelo, a graph-based machine learning procedure that uses RNA velocities inferred from existing methods as input and infer velocity vectors lie in the tangent space of the low-dimensional manifold formed by the single cell data.
View Article and Find Full Text PDFElectron J Stat
November 2024
Department of Biostatistics and Medical Informatics, 207A WARF Office Building, 610 Walnut St., University of Wisconsin-Madison.
The marginal inference of an outcome variable can be improved by closely related covariates with a structured distribution. This differs from standard covariate adjustment in randomized trials, which exploits covariate-treatment independence rather than knowledge on the covariate distribution. Yet it can also be done robustly against misspecification of the outcome-covariate relationship.
View Article and Find Full Text PDFArq Bras Oftalmol
December 2024
Department of Ophthalmology, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brazil.
The paper starts discussing the teleological concept that eye motions - rotations and translations - serve to vision (which supports the notion that torsions are not voluntarily driven, since they do not contribute to expand the visual exploration of space). It proposes that the primary position of the eye (not "of gaze") , the standard condition to measure them, must be defined as the coincidence of the orbital (fixed) and the ocular (movable) system of coordinates. However this becomes only a theoretic concept, since practical operations to obtain it are almost unfeasible.
View Article and Find Full Text PDFChaos
December 2024
Universidade Estadual Paulista (UNESP), Câmpus de São João da Boa Vista, Av. Profa. Isette Corrêa Fontão, 505, 13876-750 São João da Boa Vista, SP, Brazil.
A family of dissipative two-dimensional nonlinear mappings is considered. The mapping is described by the angle and action variables and parameterized by ε controlling nonlinearity, δ controlling the amount of dissipation, and an exponent γ is a dynamic free parameter that enables a connection with various distinct dynamic systems. The Lyapunov exponents are obtained for different values of the control parameters to characterize the chaotic attractors.
View Article and Find Full Text PDFSensors (Basel)
November 2024
National Key Laboratory of Electromagnetic Space Security, Jiaxing 314000, China.
To tackle the issue of poor accuracy in single-snapshot data processing for Direction of Arrival (DOA) estimation in passive radar systems, this paper introduces a method for judiciously leveraging multi-snapshot data. This approach effectively enhances the accuracy of DOA estimation and spatial angle resolution in passive radar systems. Additionally, in response to the non-convex nature of the mixed norm, we propose a hyperbolic tangent model as a replacement, transforming the problem into a directly solvable convex optimization problem.
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