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Methods from learning theory are used in the state space of linear dynamical and control systems in order to estimate the system matrices. An application to stabilization via algebraic Riccati equations is included. The approach is…

Dynamical Systems · Mathematics 2015-08-12 Fritz Colonius , Boumediene Hamzi

In this paper, using Riemann-Lagrange geometrical methods, we construct a geometrical model on 1-jet spaces for the study of multi-time relativistic magnetized non-viscous plasma, characterized by a given energy-stress-momentum…

Differential Geometry · Mathematics 2017-07-17 Mircea Neagu

We prove that many aspects of the differential geometry of embedded Riemannian manifolds can be formulated in terms of multi linear algebraic structures on the space of smooth functions. In particular, we find algebraic expressions for…

Differential Geometry · Mathematics 2010-09-27 Joakim Arnlind , Jens Hoppe , Gerhard Huisken

In this work, we consider the bilevel optimization problem on Riemannian manifolds. We inspect the calculation of the hypergradient of such problems on general manifolds and thus enable the utilization of gradient-based algorithms to solve…

Optimization and Control · Mathematics 2024-02-09 Jiaxiang Li , Shiqian Ma

We use a Riemannian (or pseudo-Riemannian) geometric framework to formulate the theory of the classical r-matrix for integrable systems. In this picture the r-matrix is related to a fourth rank tensor, named the r-tensor, on the…

solv-int · Physics 2009-10-31 Kjell Rosquist

We describe TensoriaCalc, a tensor calculus package written to be smoothly consistent with the Wolfram Language, so as to ensure ease of usage. It allows multiple metrics to be defined in a given session; and, once a metric is computed,…

General Relativity and Quantum Cosmology · Physics 2025-12-23 Wei-Hao Chen , Yi-Zen Chu , Vaidehi Varma

We consider the question: what is the abstraction that should be implemented by the computational engine of a machine learning system? Current machine learning systems typically push whole tensors through a series of compute kernels such as…

Databases · Computer Science 2021-08-10 Binhang Yuan , Dimitrije Jankov , Jia Zou , Yuxin Tang , Daniel Bourgeois , Chris Jermaine

A 4-dimensional Riemannian manifold M, equipped with an additional tensor structure S, whose fourth power is minus identity, is considered. The structure S has a skew-circulant matrix with respect to some basis of the tangent space at a…

Differential Geometry · Mathematics 2020-07-08 Dimitar Razpopov , Iva Dokuzova

This paper is concerned with solving some structured multi-linear systems, which are called tensor absolute value equations. This kind of absolute value equations is closely related to tensor complementarity problems and is a generalization…

Numerical Analysis · Mathematics 2017-05-19 Shouqiang Du , Liping Zhang , Chiyu Chen , Liqun Qi

We introduce a new theoretical framework for deriving lower bounds on data movement in bilinear algorithms. Bilinear algorithms are a general representation of fast algorithms for bilinear functions, which include computation of matrix…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-06-23 Edgar Solomonik , James Demmel , Torsten Hoefler

A novel efficient method to calculate the scattering matrix (SM) of arbitrary tight-binding Hamiltonians is proposed, including cases with multiterminal structures. In particular, the SM of two kind of fundamental structures are given,…

Mesoscale and Nanoscale Physics · Physics 2020-03-11 Carlos Ramirez , Luis A. Medina-Amayo

Kjolstad et. al. proposed a tensor algebra compiler. It takes expressions that define a tensor element-wise, such as $f_{ij}(a,b,c,d) = \exp\left[-\sum_{k=0}^4 \left((a_{ik}+b_{jk})^2\, c_{ii} + d_{i+k}^3 \right) \right]$, and generates the…

Symbolic Computation · Computer Science 2017-11-07 Sebastian Urban , Patrick van der Smagt

Prediction for high dimensional time series is a challenging task due to the curse of dimensionality problem. Classical parametric models like ARIMA or VAR require strong modeling assumptions and time stationarity and are often…

Statistics Theory · Mathematics 2020-12-16 Nikita Puchkin , Aleksandr Timofeev , Vladimir Spokoiny

We derive a formula for the curvature tensor of the natural Riemannian metric on the space of two-dimensional conformal field theories and also a formula for the curvature tensor of the space of boundary conformal field theories.

High Energy Physics - Theory · Physics 2015-06-05 Daniel Friedan , Anatoly Konechny

The statistics of meanders is studied in connection with the Temperley-Lieb algebra. Each (multi-component) meander corresponds to a pair of reduced elements of the algebra. The assignment of a weight $q$ per connected component of meander…

High Energy Physics - Theory · Physics 2015-06-26 P. Di Francesco , O. Golinelli , E. Guitter

The numerical simulation of structural mechanics applications via finite elements usually requires the solution of large-size and ill-conditioned linear systems, especially when accurate results are sought for derived variables interpolated…

Numerical Analysis · Mathematics 2019-06-26 Andrea Franceschini , Victor A. Paludetto Magri , Gianluca Mazzucco , Nicolò Spiezia , Carlo Janna

In biological and engineering systems, structure, function and dynamics are highly coupled. Such interactions can be naturally and compactly captured via tensor based state space dynamic representations. However, such representations are…

Optimization and Control · Mathematics 2019-12-30 Can Chen , Amit Surana , Anthony Bloch , Indika Rajapakse

Being inspired by phasor analysis in linear circuit theory, and its algebraic counterpart - the AC-(operational)-calculus for sinusoids developed by W. Marten and W. Mathis - we define a complex structure on several spaces of real-valued…

Classical Analysis and ODEs · Mathematics 2007-09-20 Eberhard H. -A. Gerbracht

The computation of the Mittag-Leffler (ML) function with matrix arguments, and some applications in fractional calculus, are discussed. In general the evaluation of a scalar function in matrix arguments may require the computation of…

Numerical Analysis · Mathematics 2019-12-03 Roberto Garrappa , Marina Popolizio

The development of a metric for structural data is a long-term problem in pattern recognition and machine learning. In this paper, we develop a general metric for comparing nonlinear dynamical systems that is defined with Perron-Frobenius…

Machine Learning · Statistics 2018-11-01 Isao Ishikawa , Keisuke Fujii , Masahiro Ikeda , Yuka Hashimoto , Yoshinobu Kawahara