Research
On-device research index

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.

169,051 papers · 148 categories

Trend · papers per month

86173259345 · Jun 202019922001200920182026
48 results for oscillator representation

Study finds the spectrum of a cubic Dirac operator on specific oscillator group manifolds.

problem Determining the spectrum of a cubic Dirac operator on oscillator group manifolds.
method Explicit decomposition of the regular representation and calculation of eigenspaces.
result Explicit eigenspaces and spectrum of the cubic Dirac operator determined.

Researchers compute determinants and torsions of Rumin complex in specific Lie group representations.

problem Computing determinants and torsions of Rumin complex in specific Lie group representations.
method Analyzing Schrodinger and generic representations of the (2,3,5) nilpotent Lie group.
result Computed the spectrum and zeta regularized determinant of Rumin differentials in Schrodinger representations and evaluated their alternating product in generic representations.

Study examines boundedness of oscillating singular integrals on specific Lie groups.

problem Investigating boundedness of oscillating singular integrals on Lie groups of polynomial growth.
method Presented kernel criteria in terms of sub-Riemannian structure and Fourier analysis.
result Extended classical oscillating conditions for boundedness of oscillating convolution operators.

Log-periodic oscillations have been used to predict price trends and crashes on financial markets. So far two types of log-periodic oscillations have been associated with the real markets. The first type are oscillations which accompany a rising market and which ends in a crash. The second type oscillations, called "an…

2003-07-14abs ↗pdf ↗

Study theta series and special cycles on Hermitian spaces, linking them to automorphic forms.

problem Understanding special cycles and theta series on Hermitian spaces.
method Using oscillator representation and theta series, link cycles to automorphic forms.
result Poincaré duals of special cycles are Fourier coefficients of theta series.

Estimates box dimension of fractal interpolation surfaces using oscillation vectors.

problem Estimating the complexity of fractal interpolation surfaces.
method Defined vertical scaling matrices and used them to relate oscillation vectors of different levels.
result Obtained the box dimension of generalized affine fractal interpolation surfaces.

Recently, studies on deep Reservoir Computing (RC) highlighted the role of layering in deep recurrent neural networks (RNNs). In this paper, the use of linear recurrent units allows us to bring more evidence on the intrinsic hierarchical temporal representation in deep RNNs through frequency analysis applied to the sta…

2017-05-16abs ↗pdf ↗

The Duffing oscillator's parameters are identified online using variational message passing.

problem Estimating parameters of a nonlinear Duffing oscillator in real-time.
method Variational message passing on a factor graph of the Duffing oscillator's generative model.
result The online inference procedure performs as well as offline methods.

The present paper introduces a majority orienting model in which the dealers' behavior changes based on the influence of the price to show the oscillation of stock price in the stock market. We show the oscillation of the price for the model by applying the van der Pol equation which is a deterministic approximation of…

2004-03-31abs ↗pdf ↗

The study derives generalization bounds for neural oscillators, improving their performance with regularization.

problem Quantifying the generalization capacities of neural oscillators.
method Using Rademacher complexity and squared Wasserstein-1 distances, the study derives theoretical upper PAC generalization bounds for neural oscillators.
result Theoretical bounds show polynomial growth in estimation errors with MLP size and time length, and regularization improves performance.

Study on black hole interiors with matter fields, showing oscillation condition impacts blow-up.

problem Examining Strong Cosmic Censorship in the presence of matter fields.
method Einstein equations coupled with charged/massive scalar fields, spherically symmetric data, relaxation rate analysis.
result Oscillation condition on event horizon determines whether matter fields blow up or not.

Using geometric quantization procedure, the quantization of algebra of observables for physical system with Ricci-flat phase space is obtained. In the classical case the appointed physical system is reduced to harmonic oscillator when the one real parameter is vanished.

1999-02-18abs ↗pdf ↗

New non-separable covariance kernels for spatiotemporal data derived from harmonic oscillator physics.

problem Capturing complex spatiotemporal dependencies in Gaussian processes.
method Hybrid spectral method based on the harmonic oscillator, deriving explicit covariance kernels.
result Explicit non-separable covariance kernels with space-time interactions.

Large learning rates cause oscillations in NN weights that improve generalization.

problem Improving generalization of neural networks trained with large learning rates.
method Theoretical analysis and feature-noise data generation model.
result Oscillating SGD with large learning rates benefits NN generalization by effectively learning weak features.

We show that there are minimal graphs in R^{n+1} whose intersection with the portion of the horizontal hyperplane contained in the unit ball has any prescribed geometry, up to a small deformation. The proof hinges on the construction of minimal graphs that are almost flat but have small oscillations whose geometry we c…

2016-02-16abs ↗pdf ↗

A new RNN model based on coupled oscillators mitigates gradient issues.

problem Gradient vanishing and exploding issues in RNNs.
method Time-discretization of a system of second-order ODEs modeling coupled oscillators.
result The model maintains bounded gradients, leading to stable learning of long-term dependencies.

A new method predicts dynamical systems better by using two different latent spaces.

problem Predicting the future of dynamical systems with optimal accuracy.
method Uses two different latent mappings for present and future states.
result Optimal 2-mapping method significantly outperforms single latent representation methods.

KuramotoGNN uses Kuramoto model to prevent over-smoothing in graph neural networks.

problem Over-smoothing in graph neural networks where node features become indistinguishable.
method Integrates Kuramoto model to prevent phase synchronization and instead achieve frequency synchronization.
result KuramotoGNN reduces over-smoothing on various graph deep learning tasks.

The Black-Scholes model anticipates rather well the observed prices for options in the case of a strike price that is not too far from the current price of the underlying asset. Some useful extensions can be obtained by an adequate modification of the coefficients in the Black-Scholes equation. We investigate from a ma…

2013-10-15abs ↗pdf ↗

The main result is a version of Morse inequalities for the minimum and maximum ideal boundary conditions of the de Rham complex on strata of compact Thom-Mather stratifications, endowed with adapted metrics. An adaptation of the analytic method of Witten is used in the proof, as well as certain perturbation of the harm…

2012-05-02abs ↗pdf ↗

This paper extends the earlier work on an oscillating error correction technique. Specifically, it extends the design to include further corrections, by adding new layers to the classifier through a branching method. This technique is still consistent with earlier work and also neural networks in general. With this ext…

2017-11-19abs ↗pdf ↗

Proposes a new method combining Reservoir Computing and Normalizing Flow for predicting stochastic dynamical systems.

problem Predicting and capturing long-term behaviors of stochastic dynamical systems.
method Data-driven framework combining Reservoir Computing and Normalizing Flow, integrating error modeling and both approaches virtues.
result Successfully predicts the long-term evolution of stochastic dynamical systems and replicates dynamical behaviors.

Study on compact Quasi-Einstein manifolds yields diameter estimates and Hitchin-Thorpe inequality conditions.

problem Estimating diameters and verifying Hitchin-Thorpe inequality for compact Quasi-Einstein manifolds.
method Derive geometric estimates relating potential function oscillation to manifold diameter; derive lower bounds for diameter.
result Diameter conditions ensure compact Quasi-Einstein manifolds satisfy Hitchin-Thorpe inequality in dimension four.

We consider the oscillator group equipped with a bi-invariant Lorentzian metric, and then some geometrical properties of this group i.e. homogeneous Ricci solitons and harmonicity properties of invariant vector fields are obtained. We also determine all vector fields which are critical points for the energy functional …

2016-04-15abs ↗pdf ↗

Three ways synchronization in financial markets can cause contagion, using models of decision-making and oscillators.

problem Contagion in financial markets caused by synchronization of decision-making.
method Agent-based modeling, integrate-and-fire oscillators, and communication models.
result Synchronization in financial markets can lead to turbulent periods and contagion.

We give, using an explicit expression obtained in [V. Jones, Ann. of Math. 126, 335 (1987)], a basic hypergeometric representation of the HOMFLY polynomial of (n,m)(n,m) torus knots, and present a number of equivalent expressions, all related by Heine's transformations. Using this result the (m,n)(n,m)(m,n)\leftrightarrow (n,m) s…

2014-01-31abs ↗pdf ↗