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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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12.5%25.0%37.5%50.0% · May 199319922001200920172026
48 results for polynomial systems

New methods assess topological entanglement in periodic systems.

problem Assessing topological entanglement in systems with periodic boundary conditions.
method Introducing Periodic Jones polynomial and Cell Jones polynomial.
result Periodic Jones polynomial is a recurring factor of Jones polynomial of finite cutoffs.

The paper studies random dynamical systems of polynomial automorphisms on C^2 and finds mean stability.

problem Random dynamical systems of polynomial automorphisms on C^2.
method Generic random dynamical systems of polynomial automorphisms are shown to have mean stability.
result A generic random dynamical system of polynomial automorphisms on C^2 has mean stability.

Polynomial-time reachability for LTI systems with TLL NN controllers is achieved.

problem Bounding the reachable set of LTI systems controlled by TLL NN controllers.
method Polynomial-time computation of exact one-step reachable set and tight bounding box via two methods.
result Exact reachability computation in polynomial time for TLL NN controllers.

This paper presents a new method for solving systems with polynomial stiffness.

problem Finding analytical solutions to nonlinear differential equations with polynomial stiffness is challenging.
method The paper introduces a geometric/algebraic method using generating series and shuffle product.
result The method provides a recursive schematic that can be automated and applied to systems with polynomial stiffness.

Polynomial inequalities lie at the heart of many mathematical disciplines. In this paper, we consider the fundamental computational task of automatically searching for proofs of polynomial inequalities. We adopt the framework of semi-algebraic proof systems that manipulate polynomial inequalities via elementary inferen…

2019-06-04abs ↗pdf ↗

We discuss the relation between knot polynomials and the KP hierarchy. Mainly, we study the scaling 1-hook property of the coloured Alexander polynomial: ARK(q)=A[1]K(qR)\mathcal{A}^\mathcal{K}_R(q)=\mathcal{A}^\mathcal{K}_{[1]}(q^{\vert R\vert}) for all 1-hook Young diagrams RR. Via the Kontsevich construction, it is reformulated …

2018-05-07abs ↗pdf ↗

The paper addresses online prediction in marginally stable systems with bounded perturbations.

problem Online prediction in marginally stable linear dynamical systems with adversarial or stochastic perturbations.
method The online least-squares algorithm is used to achieve sublinear regret, with a refined regret analysis and a structural lemma.
result The online least-squares algorithm achieves sublinear regret, with polynomial dependence on the system's parameters.

Estimation is the computational task of recovering a hidden parameter xx associated with a distribution DxD_x, given a measurement yy sampled from the distribution. High dimensional estimation problems arise naturally in statistics, machine learning, and complexity theory. Many high dimensional estimation problems ca…

2018-07-30abs ↗pdf ↗

The study finds polynomial upper bounds for singularities in Einstein-scalar field system.

problem Understanding the strength of singularities in gravitational collapse.
method Analyzing geometric quantities, focusing on the Kretschmann scalar.
result Polynomial blow-up upper bounds O(1/rN)O(1/r^N) for the Kretschmann scalar, improving previous bounds.

Study integrable geodesic flows on 2-surfaces with high-degree polynomial first integrals.

problem Integrable geodesic flows on 2-surfaces with high-degree polynomial first integrals.
method Semi-Hamiltonian systems of PDEs and generalized hodograph method.
result Construction of many local explicit and implicit integrable examples with polynomial first integrals of degrees 3, 4, 5.

New method learns low-dimensional models for systems with non-polynomial terms.

problem Modeling systems with non-polynomial nonlinear terms that are spatially local and given in analytic form.
method Non-intrusive model reduction method that learns operators for linear and polynomially nonlinear dynamics via a least-squares problem incorporating given non-polynomial terms.
result Comparable accuracy to intrusive methods that require full knowledge of governing equations.

We propose a method called ideal regression for approximating an arbitrary system of polynomial equations by a system of a particular type. Using techniques from approximate computational algebraic geometry, we show how we can solve ideal regression directly without resorting to numerical optimization. Ideal regression…

2011-10-20abs ↗pdf ↗

We prove that stochastic gradient descent efficiently converges to the global optimizer of the maximum likelihood objective of an unknown linear time-invariant dynamical system from a sequence of noisy observations generated by the system. Even though the objective function is non-convex, we provide polynomial running …

2016-09-16abs ↗pdf ↗

We show that the adjacency matrices of the intersection graphs of chord diagrams satisfy the 2-term relations of Bar-Natan and Garoufalides [bg], and hence give rise to weight systems. Among these weight systems are those associated with the Conway and HOMFLYPT polynomials. We extend these ideas to looking at a space o…

2000-04-12abs ↗pdf ↗

New method for accurately predicting linear dynamical systems.

problem Forecasting and estimating system matrices of linear dynamical systems.
method Non-convex polynomial optimization approach with global convergence guarantee.
result Global convergence of numerical solutions to a least-squares estimator.

Estimates hybrid dynamical systems with polynomial expansions and Markovian switching.

problem Identifying hybrid dynamical systems with nonlinear autoregressive exogenous (NARX) components and Markovian switching.
method Probabilistic framework using Expectation Maximization for parameter estimation, including submodel coefficients, hidden state values, and transition probabilities. Disentangles mode classification and NARX regression tasks. Uses soft-labels and coordinate descent approach for parameter fitting.
result Demonstrated on a SMNARX problem with three nonlinear sub-models, achieving parsimonious models through l1-norm bridge estimation and hard-thresholding.

We present formulae for computing the Yamada polynomial of spatial graphs obtained by replacing edges of plane graphs, such as cycle-graphs, theta-graphs, and bouquet-graphs, by spatial parts. As a corollary, it is shown that zeros of Yamada polynomials of some series of spatial graphs are dense in a certain region in …

2018-01-27abs ↗pdf ↗

Polynomial chaos expansions on Grassmannian submanifolds for high-dimensional stochastic systems.

problem Uncertainty quantification in high-dimensional stochastic systems.
method Principal Geodesic Analysis on the Grassmann manifold, adaptive algorithm for local submanifolds, polynomial chaos expansion.
result Efficient surrogate modeling of system behavior across different parameter spaces.

Novel symmetry found in colored HOMFLY polynomials from superalgebras.

problem Understanding symmetries in colored HOMFLY polynomials.
method Exploring the sl(NM)\mathfrak{sl}(N|M) superalgebra to find a symmetry.
result A symmetry relating polynomials colored by different representations.

Paper reduces sample complexity for bilinear systems identification to nearly constant.

problem Identifying discrete-time bilinear systems under bounded disturbances.
method Uses trajectory-dependent regressors and polynomial mean-square state growth analysis.
result Proves sample complexity of O~(1/ε)\widetilde{\mathcal O}(1/ε) for estimation error εε.

The paper equidistributes zeros of random polynomials and sections on manifolds.

problem Equidistribution of zeros of random polynomials and sections on manifolds.
method Weighted pluripotential theory, asymptotic Bernstein-Markov measures, variance estimation.
result Equidistribution holds for non-i.i.d. random coefficients and non-homogeneous manifolds.

Skew parallelogram nets factorize, encompassing discrete differential geometry.

problem Factorization of polynomials in discrete differential geometry.
method Lax representation, Bäcklund transformations, factorization of polynomials.
result Skew parallelogram nets encompass all systems with polynomial representations.

Machine learning identifies boundaries of real solutions in polynomial systems.

problem Locating boundaries in parameter space for real solutions of polynomial systems.
method Supervised machine learning approach using nearest neighbor and deep learning approximations.
result Efficiently approximates the real discriminant locus for multidimensional parameter spaces.

We introduce polynomial processes taking values in an arbitrary Banach space BB via their infinitesimal generator LL and the associated martingale problem. We obtain two representations of the (conditional) moments in terms of solutions of a system of ODEs on the truncated tensor algebra of dual respectively bidual s…

2019-11-06abs ↗pdf ↗