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We develop new solvability methods for divergence form second order, real and complex, elliptic systems above Lipschitz graphs, with $L_2$ boundary data. The coefficients $A$ may depend on all variables, but are assumed to be close to…

Analysis of PDEs · Mathematics 2010-09-16 Pascal Auscher , Andreas Axelsson

Probabilistic prediction of stochastic dynamical systems (SDSs) aims to accurately predict the conditional probability distributions of future states. However, accurate probabilistic predictions tightly hinge on accurate distributional…

Optimization and Control · Mathematics 2026-04-21 Tao Xu , Jianping He

In this paper, we introduce the online and streaming MAP inference and learning problems for Non-symmetric Determinantal Point Processes (NDPPs) where data points arrive in an arbitrary order and the algorithms are constrained to use a…

Machine Learning · Computer Science 2021-11-30 Aravind Reddy , Ryan A. Rossi , Zhao Song , Anup Rao , Tung Mai , Nedim Lipka , Gang Wu , Eunyee Koh , Nesreen Ahmed

We introduce the notion of "\delta-complete decision procedures" for solving SMT problems over the real numbers, with the aim of handling a wide range of nonlinear functions including transcendental functions and solutions of…

Logic in Computer Science · Computer Science 2012-09-18 Sicun Gao , Jeremy Avigad , Edmund Clarke

Positively (resp. negatively) associated point processes are a class of point processes that induce attraction (resp. inhibition) between the points. As an important example, determinantal point processes (DPPs) are negatively associated.…

Statistics Theory · Mathematics 2018-02-20 Arnaud Poinas , Bernard Delyon , Frédéric Lavancier

Classical (maximal) superintegrable systems in $n$ dimensions are Hamiltonian systems with $2n-1$ independent constants of the motion, globally defined, the maximum number possible. They are very special because they can be solved…

Mathematical Physics · Physics 2015-11-04 Yuxuan Chen , Ernie G. Kalnins , Qiushi Li , Willard Miller

Despite many applications, dimensionality reduction in the $\ell_1$-norm is much less understood than in the Euclidean norm. We give two new oblivious dimensionality reduction techniques for the $\ell_1$-norm which improve exponentially…

Data Structures and Algorithms · Computer Science 2021-08-09 Yi Li , David P. Woodruff , Taisuke Yasuda

Let $X$ be the family of hypersurfaces in the odd-dimensional torus ${\mathbb T}^{2n+1}$ defined by a Laurent polynomial $f$ with fixed exponents and variable coefficients. We show that if $n\Delta$, the dilation of the Newton polytope…

Algebraic Geometry · Mathematics 2018-06-28 Alan Adolphson , Steven Sperber

As well as arising naturally in the study of non-intersecting random paths, random spanning trees, and eigenvalues of random matrices, determinantal point processes (sometimes also called fermionic point processes) are relatively easy to…

Probability · Mathematics 2008-04-04 Steven N. Evans , Alex Gottlieb

For the system of semilinear elliptic equations \[ \Delta V_i = V_i \sum_{j \neq i} V_j^2, \qquad V_i > 0 \qquad \text{in $\mathbb{R}^N$} \] we devise a new method to construct entire solutions. The method extends the existence results…

Analysis of PDEs · Mathematics 2016-10-26 Nicola Soave , Alessandro Zilio

2nd-order conformal superintegrable systems in $n$ dimensions are Laplace equations on a manifold with an added scalar potential and $2n - 1$ independent 2nd order conformal symmetry operators. They encode all the information about…

Mathematical Physics · Physics 2016-06-29 M. A. Escobar-Ruiz , Willard Miller

In this paper, we discuss duality about components of invariant variety of periodic points(IVPP) and fundamental domain of recurrence equation, and present an algorithm for the derivation of all components of IVPPs of any rational maps. It…

Mathematical Physics · Physics 2015-11-17 Tsukasa Yumibayashi

We investigate and characterize the emergence of finite-component dissipative phase transitions (DPTs) in nonlinear photon resonators subject to $n$-photon driving and dissipation. Exploiting a semiclassical approach, we derive general…

Quantum Physics · Physics 2023-11-08 Fabrizio Minganti , Vincenzo Savona , Alberto Biella

We investigate the product of $n$ complex non-Hermitian, independent random matrices, each of size $N\times N$ in the class of elliptic matrices, with independent identically distributed entries. The joint probability distribution of the…

Probability · Mathematics 2016-01-28 Mohamed Bouali

The analogy between determinantal point processes (DPPs) and free fermionic calculi is well-known. We point out that, from the perspective of free fermionic algebras, Pfaffian point processes (PfPPs) naturally emerge, and show that a…

Probability · Mathematics 2021-01-27 Shinji Koshida

Numerical solutions to high-dimensional partial differential equations (PDEs) based on neural networks have seen exciting developments. This paper derives complexity estimates of the solutions of $d$-dimensional second-order elliptic PDEs…

Numerical Analysis · Mathematics 2021-11-09 Ziang Chen , Jianfeng Lu , Yulong Lu

We consider determinantal Coulomb gas ensembles with a class of discrete rotational symmetric potentials whose droplets consist of several disconnected components. Under the insertion of a point charge at the origin, we derive the…

Mathematical Physics · Physics 2022-10-11 Sung-Soo Byun , Meng Yang

We prove the existence of entire solutions with exponential growth for the semilinear elliptic system [\begin{cases} -\Delta u = -u v^2 & \text{in $\R^N$} -\Delta v= -u^2 v & \text{in $\R^N$} u,v>0, \end{cases}] for every $N \ge 2$. Our…

Analysis of PDEs · Mathematics 2014-02-18 Nicola Soave , Alessandro Zilio

We present limit theorems for a sequence of Piecewise Deterministic Markov Processes (PDMPs) taking values in a separable Hilbert space. This class of processes provides a rigorous framework for stochastic spatial models in which discrete…

Probability · Mathematics 2012-04-13 Martin G. Riedler , Michèle Thieullen , Gilles Wainrib

Subset selection problems ask for a small, diverse yet representative subset of the given data. When pairwise similarities are captured by a kernel, the determinants of submatrices provide a measure of diversity or independence of items…

Data Structures and Algorithms · Computer Science 2016-07-07 Tarun Kathuria , Amit Deshpande