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In this paper, the Riemannian gradient algorithm and the natural gradient algorithm are applied to solve descent direction problems on the manifold of positive definite Hermitian matrices, where the geodesic distance is considered as the…

Optimization and Control · Mathematics 2021-06-01 Xiaomin Duan , Huafei Sun , Linyu Peng

We apply the holonomic gradient method introduced by Nakayama et al.(2011) to the evaluation of the exact distribution function of the largest root of a Wishart matrix, which involves a hypergeometric function 1F1 of a matrix argument.…

Statistics Theory · Mathematics 2013-04-15 Hiroki Hashiguchi , Yasuhide Numata , Nobuki Takayama , Akimichi Takemura

In this paper we use the Riemann-Hilbert problem, with jumps supported on appropriate curves in the complex plane, for matrix biorthogonal polynomials and apply it to find Sylvester systems of differential equations for the orthogonal…

Classical Analysis and ODEs · Mathematics 2018-07-20 Amilcar Branquinho , Ana Foulquié Moreno , Manuel Mañas

In this paper we introduce discrete gradient methods to discretize irreversible port-Hamiltonian systems showing that the main qualitative properties of the continuous system are preserved using this kind discretizations methods.

Numerical Analysis · Mathematics 2023-03-15 Alexandre Anahory Simoes , David Martín de Diego , Bernhard Maschke

This work studies limits of Pfaffian systems, a class of first-order PDEs appearing in the Feynman integral calculus. Such limits appear naturally in the context of scattering amplitudes when there is a separation of scale in a given set of…

High Energy Physics - Theory · Physics 2023-05-17 Vsevolod Chestnov , Saiei J. Matsubara-Heo , Henrik J. Munch , Nobuki Takayama

We suggest an algorithm for derivation of the Picard--Fuchs system of Pfaffian equations for Abelian integrals corresponding to semiquasihomogeneous Hamiltonians. It is based on an effective decomposition of polynomial forms in the…

Dynamical Systems · Mathematics 2007-05-23 S. Yakovenko

A crucial task in system identification problems is the selection of the most appropriate model class, and is classically addressed resorting to cross-validation or using asymptotic arguments. As recently suggested in the literature, this…

Numerical Analysis · Mathematics 2015-06-09 Silvia Bonettini , Alessandro Chiuso , Marco Prato

In probabilistic modeling, parameter estimation is commonly formulated as a minimization problem on a parameter manifold. Optimization in such spaces requires geometry-aware methods that respect the underlying information structure. While…

Computation · Statistics 2025-11-17 Derun Zhou , Keisuke Yano , Mahito Sugiyama

We present a gradient-based calibration algorithm to identify a port-Hamiltonian system from given time-domain input-output data. The gradient is computed with the help of sensitivities and the algorithm is tailored such that the structure…

Numerical Analysis · Mathematics 2023-01-06 Michael Günther , Birgit Jacob , Claudia Totzeck

This paper presents enhancement strategies for the Hermitian and skew-Hermitian splitting method based on gradient iterations. The spectral properties are exploited for the parameter estimation, often resulting in a better convergence. In…

Numerical Analysis · Mathematics 2020-07-08 Qinmeng Zou , Frederic Magoules

We describe efficient differentiation methods for computing Jacobians and gradients of a large class of matrix functions including the matrix logarithm $\log(A)$ and $p$-th roots $A^{\frac{1}{p}}$. We exploit contour integrals and conformal…

Computational Physics · Physics 2025-01-06 Tina Torabi , Timon S Gutleb , Christoph Ortner

We prove an effective integrability criterion for differential-algebraic Pfaffian systems leading to a decision method of consistency with a triple exponential complexity bound. As a byproduct, we obtain an upper bound for the order of…

Commutative Algebra · Mathematics 2015-01-21 Lisi D'Alfonso , Gabriela Jeronimo , Pablo Solernó

Inspired by the connection between the Dodgson's condensation algorithm and Hirota's difference equation, we consider condensation algorithms for Pfaffians from the perspectives of discrete integrable systems. The discretisation of Pfaffian…

Mathematical Physics · Physics 2020-06-12 Shi-Hao Li

Bilevel optimization has gained prominence in various applications. In this study, we introduce a framework for solving bilevel optimization problems, where the variables in both the lower and upper levels are constrained on Riemannian…

Optimization and Control · Mathematics 2024-11-05 Andi Han , Bamdev Mishra , Pratik Jawanpuria , Akiko Takeda

In this paper, we derive the algorithm for calculating the normal form of the double Hopf bifurcation that appears in a memory-based diffusion system via taking memory-based diffusion coefficient and the memory delay as the perturbation…

Dynamical Systems · Mathematics 2022-02-10 Yongli Song , Yahong Peng , Tonghua Zhang

We derive a rigorous, quantum mechanical map of fermionic creation and annihilation operators to continuous Cartesian variables that exactly reproduces the matrix structure of the many-fermion problem. We show how our scheme can be used to…

Chemical Physics · Physics 2018-03-20 Andrés Montoya-Castillo , Thomas E. Markland

This article serves a two-fold purpose. On the one hand, it is a survey about the classification of finite-dimensional pointed Hopf algebras with abelian coradical, whose final step is the computation of the liftings or deformations of…

Quantum Algebra · Mathematics 2018-08-01 Iván Angiono , Agustín García Iglesias

We show how fermionic statistics can be naturally incorporated in tensor networks on arbitrary graphs through the use of graded Hilbert spaces. This formalism allows to use tensor network methods for fermionic lattice systems in a local…

The method of subquotients is developed and used to determine all finite dimensional rank 2 Nichols algebras of diagonal type over an arbitrary field of characteristic zero. Key Words: Hopf algebra, Nichols algebra

Quantum Algebra · Mathematics 2016-09-07 I. Heckenberger

In this paper, we study a strictly stationary Markov chain gradient descent algorithm operating in general Hilbert spaces. Our analysis focuses on the mixing coefficients of the underlying process, specifically the $\phi$- and…

Machine Learning · Statistics 2025-08-14 Priyanka Roy , Susanne Saminger-Platz