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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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10213141 · May 202619922001200920172026
48 results for rational spectra

Researchers describe a new method to compute Seiberg-Witten-Floer spectra for a specific class of manifolds.

problem Computing Seiberg-Witten-Floer spectra for a specific class of manifolds.
method Using lattice homology, they provide an explicit combinatorial description of the spectra.
result They calculate Manolescu's κ-invariant for certain connected sums of the spaces.

Generalizing Cusick's theorem on the closedness of the classical Lagrange spectrum for the approximation of real numbers by rational ones, we prove that various approximation spectra are closed, using penetration properties of the geodesic flow in cusp neighbourhoods in negatively curved manifolds and a result of Mauco…

2008-06-02abs ↗pdf ↗

The paper extends the Manhattan curve concept to complex dynamics and studies its relation to multiplier spectra.

problem Understanding the growth rate of lengths of closed geodesics in complex dynamics.
method Defining and studying the Manhattan curve for holomorphic endomorphisms of CPk\mathbb{C}\mathbb{P}^k and relating it to multiplier spectra.
result The Manhattan curve for two holomorphic endomorphisms is related to the correlation number of their multiplier spectra.

In this paper, we show that one can naturally associate a limiting dynamical system F:TTF: T\longrightarrow T on an R\R-tree to any degenerating sequence of rational maps $f_n: \hat\C \longrightarrow \hat\C$ of fixed degree. The construction of FF is in 22 steps: first we use barycentric extension to get $\E f_n : \Hy…

2019-05-02abs ↗pdf ↗

The settings for homotopical algebra---categories such as simplicial groups, simplicial rings, AA_\infty spaces, EE_\infty ring spectra, etc.---are often equivalent to categories of algebras over some monad or triple TT. In such cases, TT is acting on a nice simplicial model category in such a way that TT descends…

2013-01-08abs ↗pdf ↗

This paper studies torsion obstructions to complex sections on manifolds.

problem Torsion obstructions to finding complex sections on almost complex manifolds.
method Calculations using the Adams-Novikov spectral sequence for Thom spectra.
result Torsion obstructions for finding rr complex sections of order pp vanish for r<p2pr < p^2 - p.

We give a simple sufficient condition for Quinn's "bordism-type spectra" to be weakly equivalent to strictly associative ring spectra. We also show that Poincare bordism and symmetric L-theory are naturally weakly equivalent to monoidal functors. Part of the proof of these statements involves showing that Quinn's funct…

2009-07-14abs ↗pdf ↗

Tomova, along with results of Bachman and Schleimer, showed that any high distance knot has a stair-step bridge spectrum. In this paper, we compute the bridge spectra and distance of generalized Montesinos knots. In particular, we produce the first example of a class of knots which attain the stair-step bridge spectra …

2015-10-28abs ↗pdf ↗

New ICA method for sources with mixed spectra.

problem Inaccurate separation of sources with temporal autocorrelations and mixed spectra.
method Estimates spectral density functions and line spectra using cubic splines and indicator functions, then maximizes the Whittle likelihood function.
result Outperforms existing ICA methods in simulations and EEG data applications.

Jones-Wenzl projectors lifted to Khovanov spectra, proving knot conjectures.

problem Understanding Jones-Wenzl projectors in Khovanov spectra.
method Constructing and studying lifted projectors via maps and polynomial actions.
result Complete computation of 3-colored Khovanov spectrum of the unknot, proving conjectures.

We give a method to calculate spectra of the square of the Rarita-Schwinger operator on compact symmetric spaces. According to Weitzenböck formulas, the operator can be written by the Laplace operator, which is the Casimir operator on compact symmetric spaces. Then we can obtain the spectra by using the Freudenthal's f…

2020-01-17abs ↗pdf ↗

We introduce a framework, twisted parametrized stable homotopy theory, for describing semi-infinite homotopy types. A twisted parametrized spectrum is a section of a bundle whose fibre is the category of spectra. We define these bundles in terms of modules over a stack of parametrized spectra and in terms of diagrams o…

2005-08-03abs ↗pdf ↗

We prove explicit upper and lower bounds for the L1L^1-moment spectra for the Brownian motion exit time from extrinsic metric balls of submanifolds PmP^m in ambient Riemannian spaces NnN^{n}. We assume that PP and NN both have controlled radial curvatures (mean curvature and sectional curvature, respectively) as view…

2010-09-07abs ↗pdf ↗

The paper describes correlations of spectra for higher rank Anosov representations.

problem Understanding correlations of spectra for Anosov representations of higher rank groups.
method Relates correlation problem to counting projections in truncated hypertubes.
result Extends previous work on rank one representations to higher rank.

We view strict ring spectra as generalized rings. The study of their algebraic K-theory is motivated by its applications to the automorphism groups of compact manifolds. Partial calculations of algebraic K-theory for the sphere spectrum are available at regular primes, but we seek more conceptual answers in terms of lo…

2014-03-24abs ↗pdf ↗

Wavelet scattering spectra model non-Gaussian time-series, proving scale invariance for self-similar processes.

problem Modeling non-Gaussian time-series with stationary increments.
method Complex wavelet transform for scale variations, joint correlation matrix for scale dependencies, second wavelet transform for diagonalization, maximum entropy models conditioned by scattering spectra coefficients.
result Scattering spectra of self-similar processes are scale invariant, allowing statistical testing and generation of new time-series.

Manifold methods improve amino acid classification in LIBS spectra.

problem Improving classification accuracy of amino acids in LIBS spectra.
method Developed an information theoretic method for measuring LIBS energy spectra, implemented manifold methods for nonlinear dimensionality reduction.
result Nonlinear methods lead to increased classification accuracy in amino acid classification.

Length spectra for Riemannian metrics are well studied, while sub-Riemannian length spectra have been largely unexplored. Here we give the length spectrum for a canonical sub-Riemannian structure attached to any compact Lie group by restricting its Killing form to the sum of the root spaces. Surprisingly, the shortest …

2017-04-16abs ↗pdf ↗

We introduce a new quasi-isometry invariant, called the divergence spectrum, to study finitely generated groups. We compare the concept of divergence spectrum with the other classical notions of divergence and we examine the divergence spectra of relatively hyperbolic groups. We show the existence of an infinite collec…

2016-11-15abs ↗pdf ↗

Bayesian framework integrates spectral deconvolution with expert reasoning for robust peak estimation.

problem Challenges in extracting meaningful peaks from noisy or complex spectra.
method Bayesian spectral deconvolution coupled with a physical-property regression layer.
result Recovery of weak peaks in poly(lactic acid) IR spectra related to degradation rates.

For mass spectra acquired from cancer patients by MALDI or SELDI techniques, automated discrimination between cancer types or stages has often been implemented by machine learnings. These techniques typically generate "black-box" classifiers, which are difficult to interpret biologically. We develop new and efficient s…

2014-10-13abs ↗pdf ↗

Cycle-StarNet bridges theory and data by adapting synthetic spectra to observational data.

problem Lack of consistency between theoretical stellar models and observational data.
method Hybrid generative domain adaptation using unsupervised learning on large spectroscopic surveys.
result Improved spectral fitting and reduced gap between synthetic and observational data.