Introduces fractional length and nonlocal curvature for smooth curves.
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Introduces fractional k-dimensional measure bridging fractional length and area.
Paper approximates fractional harmonic maps with numerical methods.
The paper solves fractional combinatorial flows for prescribed hyperbolic bordered surfaces.
First variation of fractional -dimensional measure for submanifolds
Deep learning improves Hurst parameter estimation for fractional processes.
We compute the asymptotic growth rate of the number N(C, R) of closed geodesics of length less than R in a connected component C of a stratum of quadratic differentials. We prove that for any 0 < θ< 1, the number of closed geodesics of length at most R that spend at least θ-fraction of time outside of a compact subset …
The purpose of this article is to find a family of curves parametrized by arc length and that depend on an angular function and an intrinsic fraction function, which is defined as the quotient between torsion and curvature. We find for this family of curves explicit formulas of curvature, torsion and geodetic curvature…
Study on stable commutator length in RAAGs and Coxeter groups, proving spectral gaps and hardness results.
Python package for estimating Hurst exponent in fBm.
The paper introduces combinatorial Calabi flows to find hyperbolic metrics on surfaces with boundary.
Study shows volumes of knot complements are bounded by linear functions of geodesic periods.
We show that, for any given 3-manifold M, there are at most finitely many hyperbolic knots K in the 3-sphere and fractions p/q (with q > 22), such that M is obtained by p/q surgery along K. This is a corollary of the following result. If M is obtained by Dehn filling the cusps of a hyperbolic 3-manifold X, where each f…
The study bounds the number of closed geodesics in a specific orbit closure of surfaces.
DL/FBF improves GPSR solutions by selecting compact, generalising expressions.
The paper develops adaptive confidence intervals for Efron's Gaussian two-groups model with unknown contamination.
We consider the problem of clustering noisy finite-length observations of stationary ergodic random processes according to their generative models without prior knowledge of the model statistics and the number of generative models. Two algorithms, both using the -distance between estimated power spectral densities…
We show that a Kleinian surface group, or hyperbolic 3-manifold with a cusp-preserving homotopy-equivalence to a surface, has bounded geometry if and only if there is an upper bound on an associated collection of coefficients that depend only on its end invariants. Bounded geometry is a positive lower bound on the leng…
RNA structures show that a significant portion of bases do not form hydrogen bonds.
Large trades in a financial market are usually split into smaller parts and traded incrementally over extended periods of time. We address these large trades as hidden orders. In order to identify and characterize hidden orders we fit hidden Markov models to the time series of the sign of the tick by tick inventory var…
The paper proves a Fenchel theorem for Gauss maps and shows circles and disks minimize certain energies.
This paper provides an algorithm for simulating improper (or noncircular) complex-valued stationary Gaussian processes. The technique utilizes recently developed methods for multivariate Gaussian processes from the circulant embedding literature. The method can be performed in operations, where…
Discrete forms of the scalar, sectional and Ricci curvatures are constructed on simplicial piecewise flat triangulations of smooth manifolds, depending directly on the simplicial structure and a choice of dual tessellation. This is done by integrating over volumes which include appropriate samplings of hinges for each …
In this work we present a new approach on studying dynamical systems. Combining the two ways of expressing the uncertainty, using probabilistic theory and credibility theory, we have research the generalized fractional hybrid equations. We have introduced the concepts of generalized fractional Wiener process, generaliz…
Methods from the geometry of nonholonomic manifolds and Lagrange-Finsler spaces are applied in fractional calculus with Caputo derivatives and for elaborating models of fractional gravity and fractional Lagrange mechanics. The geometric data for such models are encoded into (fractional) bi-Hamiltonian structures and as…
The theory of derivative of noninteger order goes back to Leibniz, Liouville and Riemann. Derivatives of fractional order have found many applications in recent studies in mechanics, physics, economics. In this paper we define the fractional tangent bundle on a manifold, using a method of Radu Miron. The fractional Lei…
Study on fractional curvature flow on unit sphere, extending previous work.
Let be a closed orientable surface of genus and a simple closed nonseparating curve in . Let denote a left handed Dehn twist about . A \textit{fractional power} of of \textit{exponent} $\fraction{\ell}{n}$ is an $h \in \Mod(S_g)$ such that . Unlike a root of a $t…
We formulate the fractional Ricci flow theory for (pseudo) Riemannian geometries enabled with nonholonomic distributions defining fractional integro-differential structures, for non-integer dimensions. There are constructed fractional analogs of Perelman's functionals and derived the corresponding fractional evolution …
Using Caputo fractional derivative of order we build the fractional jet bundle of order and its main geometrical structures. Defined on that bundle, some fractional dynamical systems with applications to economics are studied.
Volatility roughness studied using fractional noise-driven models.
Using the reviewed Riemann-Liouville fractional derivative we introduce the fractional osculator Lagrange space of k order and the main structures on it. The results are applied at the k order fractional prolongation of Lagrange, Finsler and Riemann fractional structures.
Develops fractional de Rham theory for Maxwell equations.
Modeling financial markets with memory using fractional calculus and Brownian motion.
Long and short memory in economic processes is usually described by the so-called discrete fractional differencing and fractional integration. We prove that the discrete fractional differencing and integration are the Grunwald-Letnikov fractional differences of non-integer order d. Equations of ARIMA(p,d,q) and ARFIMA(…
We study the fractional gravity for spacetimes with non-integer dimensions. Our constructions are based on a geometric formalism with the fractional Caputo derivative and integral calculus adapted to nonolonomic distributions. This allows us to define a fractional spacetime geometry with fundamental geometric/physical …
In this paper we established the condition for a curve to satisfy stochas- tic fractional HP (Hamilton-Pontryagin) equations. These equations are described using It^o integral. We have also considered the case of stochastic fractional Hamiltonian equa- tions, for a hyperregular Lagrange function. From the stochastic fr…
Extends fractional uncertainty principles with extremizers and stability results.
Approximates derivative pricing under fractional stochastic volatility.
Enhances graph neural networks with random walks to improve performance.
New method uses fractional posteriors for semiparametric inference with improved uncertainty quantification.
pySigLib speeds up signature-based computations on CPUs and GPUs.
In this paper we introduce a link between geometry of ordinary continued fractions and trajectories of points that moves according to the second Kepler law. We expand geometric interpretation of ordinary continued fractions to the case of continued fractions with arbitrary elements.
The paper studies inequalities for fractional GJMS operators on conformal infinity.
Using the fractional integration and differentiation on R we build the fractional jet fibre bundle on a differentiable manifold and we emphasize some important geometrical objects. Euler-Lagrange fractional equations are described. Some significant examples from mechanics and economics are presented.
New linear models improve time series classification efficiency and interpretability.
New model uses generalized fractional Brownian motion for stock price prediction.
New framework for ranking distributions using variable fractional parameters.