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In geosciences, the use of classical Euclidean methods is unsuitable for treating and analyzing some types of data, as this may not belong to a vector space. This is the case for correlation matrices, belonging to a subfamily of symmetric…

Applications · Statistics 2021-10-04 Alvaro Riquelme

Geometrical properties of holonomic and non holonomic varieties defined by the Pfaff equations connected with a first order systems of differential equations are studied. The Riemann extensions of affine connected spaces for investigation…

Differential Geometry · Mathematics 2007-05-23 Valerii Dryuma

When a reductive group $G$ acts linearly on a complex projective scheme $X$ there is a stratification of $X$ into $G$-invariant locally closed subschemes, with an open stratum $X^{ss}$ formed by the semistable points in the sense of…

Algebraic Geometry · Mathematics 2014-02-26 Victoria Hoskins , Frances Kirwan

In this paper we study the holomorphic Euler characteristics of determinant line bundles on moduli spaces of rank 2 semistable sheaves on an algebraic surface X, which can be viewed as $K$-theoretic versions of the Donaldson invariants. In…

Algebraic Geometry · Mathematics 2007-05-23 Lothar Göttsche , Hiraku Nakajima , Kota Yoshioka

For the study of highly nonlinear, conservative dynamic systems, finding special periodic solutions which can be seen as generalization of the well-known normal modes of linear systems is very attractive. However, the study of…

Systems and Control · Electrical Eng. & Systems 2019-11-06 Alin Albu-Schaeffer , Dominic Lakatos , Stefano Stramigioli

Differential calculus on the space of asymptotically linear curves is developed. The calculus is applied to the vortex filament equation in its Hamiltonian description. The recursion operator generating the infinite sequence of commuting…

High Energy Physics - Theory · Physics 2015-06-26 Yukinori Yasui , Norihito Sasaki

The first part of this paper considers higher order CR invariants of three dimensional hypersurfaces of finite type. Using a full normal form we give a complete characterization of hypersurfaces with trivial local automorphism group, and…

Complex Variables · Mathematics 2008-04-21 Martin Kolar

Nonlinear extensions of the Kalman filter (KF), such as the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), are indispensable for state estimation in complex dynamical systems, yet the conditions for a nonlinear KF to…

Systems and Control · Electrical Eng. & Systems 2026-03-25 Shida Jiang , Jaewoong Lee , Shengyu Tao , Scott Moura

Let L be an ample line bundle on a (geometrically reduced) projective variety X over any complete valued field. Our main result describes the leading asymptotics of the determinant of cohomology of large powers of L, with respect to the…

Algebraic Geometry · Mathematics 2021-01-11 Sébastien Boucksom , Dennis Eriksson

Unitary and dissipative models of quantum dynamics are linear maps on the space of states or density matrices. This linearity encodes the superposition principle, a key feature of quantum theory. However, this principle can break down in…

Quantum Physics · Physics 2025-10-31 Orion Lee , Qian Cao , Yogesh N. Joglekar , Kater Murch

We consider generic degenerate subvarieties $X_i\subset\mathbb{P}^n$. We determine an integer $N$, depending on the varieties, and for $n\geq N$ we compute dimension and degree formulas for the Hadamard product of the varieties $X_i$.…

Algebraic Geometry · Mathematics 2019-08-06 G. Calussi , E. Carlini , G. Fatabbi , A. Lorenzini

We introduce in this paper a hypercohomology version of the resonance varieties and obtain some relations to the characteristic varieties of rank one local systems on a smooth quasi-projective complex variety $M$, see Theorem (3.1) and…

Algebraic Geometry · Mathematics 2019-02-20 Alexandru Dimca

For nonrelativistic Hamiltonians which are shape invariant, analytic expressions for the eigenvalues and eigenvectors can be derived using the well known method of supersymmetric quantum mechanics. Most of these Hamiltonians also possess…

High Energy Physics - Theory · Physics 2009-10-31 A. Gangopadhyaya , J. V. Mallow , C. Rasinariu , U. P. Sukhatme

Quantum computers have the potential to efficiently solve a system of nonlinear ordinary differential equations (ODEs), which play a crucial role in various industries and scientific fields. However, it remains unclear which system of…

Quantum Physics · Physics 2025-04-07 Yu Tanaka , Keisuke Fujii

We evidence a family $\mathcal{X}$ of square matrices over a field $\mathbb{K}$, whose elements will be called X-matrices. We show that this family is shape invariant under multiplication as well as transposition. We show that $\mathcal{X}$…

Rings and Algebras · Mathematics 2024-03-28 Emanuele Borgonovo , Marco Artusa , Elmar Plischke , Francesco Viganò

Adaptive stochastic gradient algorithms in the Euclidean space have attracted much attention lately. Such explorations on Riemannian manifolds, on the other hand, are relatively new, limited, and challenging. This is because of the…

Machine Learning · Computer Science 2019-07-01 Hiroyuki Kasai , Pratik Jawanpuria , Bamdev Mishra

The field of machine have seen rising applications of equivariance criterion. However, there is no systematic way to justify its usage, including why it works, whether there is an optimal solution and if so, what form it carries. In this…

Statistics Theory · Mathematics 2025-09-23 Daowei Wang , Mian Wu , Haojin Zhou

We present hybrid quantum-classical pipelines for solving the Duffing equation that leverage Carleman linearization and the Variational Quantum Linear Solver (VQLS). First, we demonstrate that Carleman linearization accurately approximates…

Quantum Physics · Physics 2026-05-18 Yunya Liu , Pai Wang

Variational analysis provides the theoretical foundations and practical tools for constructing optimization algorithms without being restricted to smooth or convex problems. We survey the central concepts in the context of a concrete but…

Optimization and Control · Mathematics 2025-04-08 Johannes O. Royset

Square-root Kalman filters propagate state covariances in Cholesky-factor form for numerical stability, and are a natural target for gradient-based parameter learning in state-space models. Their core operation, triangularization of a…

Machine Learning · Statistics 2026-03-17 Adrien Corenflos
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