The paper analyzes the performance of delay-based reservoir computing using eigenvalue analysis.
problem Quantifying the performance of delay-based reservoir computing.
method Eigenvalue analysis of the dynamical system to predict reservoir computing performance.
result The performance of a reservoir computing system can be predicted by analyzing the small signal response and eigenvalue spectrum.
We propose a method to clean covariance matrices of nonstationary systems by using time-independent eigenvalues.
problem Noise in covariance matrices of nonstationary systems with time-independent eigenvalues.
method Data-driven approach to use independent eigenvalues encoding long-term influence of future on present.
result Our method outperforms optimal stationary methods for filtering covariance matrix and its inverse.
Complex frequency generalizes eigenvalues in LTI systems.
problem Characterizing dynamics of signals with complex values.
method Geometric frequency interpretation and transformation analysis.
result Complex frequencies in LTI systems match eigenvalues.
Eigenvalue analogy explains item-based recommender system accuracy.
problem Lack of theoretical explanation for item-based recommender system success.
method Formalized as an eigenvalue problem, estimating ratings as true ratings multiplied by user-specific eigenvalues.
result Eigenvalue magnitude correlates with user's recommendation accuracy and can measure confidence.
Let $\om $ be a bounded domain in an n-dimensional Euclidean space Rn. We study eigenvalues of an eigenvalue problem of a system of elliptic equations: $$ \{\aligned &Δ{\mathbf u}+ α{\rm grad}(\text{div}{\mathbf u})=-σ{\mathbf u}, \ \text{in $Ω$}, &{\mathbf u}|_{\partial Ω}={\mathbf 0}. \aligned . $$ Estimate…
The paper studies eigenvalues of a special Laplacian system on compact manifolds.
problem Investigating the first eigenvalue of the (p,q)-Laplacian system on compact manifolds. method Analyzing the (p,q)-Laplacian system on compact Riemannian manifolds without boundary. result For large eigenvalues, there exists a conformal metric to the standard metric of Sm. The paper studies eigenvalue problems on manifolds and recovers known inequalities.
problem Eigenvalue problems on complete compact Riemannian manifolds with Dirichlet boundary conditions.
method Cheng comparison estimates, Faber-Krahn inequality, Cheeger estimates.
result Eigenvalue bounds and convergence to Cheeger's constant as p,qo1,1. Physics-informed GP regression solves eigenvalue problems by identifying non-trivial eigenspaces.
problem Solving eigenvalue problems of linear operators with trivial solutions.
method Constructing a transfer function-type indicator using physics-informed Gaussian Process posterior.
result The posterior covariance is non-trivial only for eigenvalues of the operator, indicating non-trivial eigenspaces.
This work identifies eigenvalues of unknown linear dynamics without full system identification.
problem Identifying parameters of a linear dynamical system is challenging.
method Developed a computationally efficient algorithm to estimate eigenvalues of the state-transition matrix.
result The algorithm can efficiently cluster multi-dimensional time series with temporal offsets and varying lengths.
In this paper we deal with the classical question of existence of polynomial in momenta integrals for geodesic flows on the 2-torus. For the quasi-linear system on coefficients of the polynomial integral we consider the region (so called elliptic regions) where there are complex-conjugate eigenvalues. We show that for …
The paper provides estimates for eigenvalues of elliptic differential problems.
problem Computing eigenvalue estimates for elliptic differential problems.
method Analytical computation of eigenvalues for specific types of elliptic differential equations.
result Universal estimates of eigenvalues and gaps between consecutive eigenvalues are derived.
Sharp eigenvalue bounds and splitting for modified Ricci flow.
problem Eigenvalue bounds and splitting in modified Ricci flow.
method Sharp lower bounds for eigenvalues of the drift Laplacian for a modified Ricci flow.
result Splitting theorem in the case of equality.
The eigenvalue problem for the Sen--Witten operator on closed spacelike hypersurfaces is investigated. The (square of its) eigenvalues are shown to be given exactly by the 3-surface integral appearing in the expression of the total energy-momentum of the matter+gravity systems in Witten's energy positivity proof. A sha…
Motivated by a sharp eigenvalue estimate for the Kohn Laplacian, we prove a theorem that characterizes the CR sphere in terms of the existence of a non-trivial complex-valued function satisfying a certain overdetermined system.
Solves numerical computation of Killing and conformal Killing vector fields on compact Riemannian manifolds.
problem Overdetermined systems of PDE make numerical computation difficult.
method Reduces to symmetric eigenvalue problem solved by finite element techniques.
result Valid in any dimension and for arbitrary compact Riemannian manifolds.
Study on equilibrium points of dynamical systems with multiple integrals.
problem Understanding the equilibrium points of dynamical systems with multiple independent first integrals.
method Analyzes the equilibrium locus as a smooth manifold and fiber bundle with a natural connection.
result Parallel transport exists for the connection and can measure eigenvalue variations.
Kernel method approximates Koopman operator eigenfunctions.
problem Complexity of computing Koopman operator spectra.
method Kernel-based approach to construct principal eigenfunctions.
result Principal eigenfunctions match linearization eigenvalues.
Let G/K be a simply connected spin compact inner irreducible symmetric space, endowed with the metric induced by the Killing form of G sign-changed. We give a formula for the square of the first eigenvalue of the Dirac operator in terms of a root system of G. As an example of application, we give the list of the …
A new metric compares dynamical systems using operator eigenvalues.
problem Comparing and interpolating nonlinear dynamical systems from trajectory data.
method Representing systems as distributions of operator eigenvalues and projectors, defining a spectral-Grassmann Wasserstein metric.
result The proposed metric outperforms standard operator-based distances in machine learning applications.
Proves local bi-integrability of bi-Hamiltonian systems via bi-Poisson reduction.
problem Local bi-integrability of bi-Hamiltonian systems.
method Bi-Poisson reduction to prove local bi-integrability.
result Constructs a complete set of functions in bi-involution for bi-Hamiltonian systems.
Paper connects Painlevé VI equation to irregular systems, solving monodromy data.
problem Solving monodromy data for irregular systems related to Painlevé VI.
method Expressed Frobenius integrability in terms of PVI, computed monodromy data for coalescing eigenvalues.
result Computed monodromy data for transcendentals holomorphic at critical points of PVI.
Solves parameter non-identifiability in Bayesian LTI system identification.
problem Parameter non-identifiability in standard Bayesian approaches for LTI system identification.
method Embedding canonical forms of LTI systems within the Bayesian framework.
result Unlocking the use of meaningful priors and robust uncertainty estimates.
Method detects phase transitions in financial markets using eigenvalue decomposition.
problem Detecting tipping points and fluctuation patterns in financial markets.
method Eigenvalue decomposition and eigen-entropy from cross-correlation matrix.
result Market events undergo phase separation and order-disorder transitions.
Study non-asymptotic bounds on correlation in high-dimensional linear systems, revealing invariant subspaces and bottlenecks.
problem Understanding correlation and mixing in high-dimensional linear systems with Gaussian noise.
method Sampling from sub-trajectories, using Talagrand's inequality, and analyzing invariant subspaces.
result Large discrepancy between algebraic and geometric multiplicity leads to bottlenecks between invariant subspaces.
The paper analyzes global inflation's systemic nature and its impact on equity markets.
problem Understanding the systemic nature of global inflation and its financial market implications.
method Data-driven study using eigenvalue analysis, inner-product optimization, and time-varying portfolio optimization.
result Countries with high centrality in global inflation are identified, and the robustness of equity indices and sectors during inflationary periods are explored.
New insights into spectral statistics of sample covariance matrix for stable linear systems.
problem Estimating high-dimensional stable state transition matrices from noisy data.
method Combining spectral theorem for non-Hermitian operators, concentration of measure, and perturbation theory.
result The spectral radius of the sample covariance matrix exhibits phase transitions in high dimensions.
Measures collectivity in financial covariances and correlations to reveal trends and precursors.
problem Capturing collective motion in financial markets to predict trends and precursors.
method Measures collectivity using the largest eigenvalue and average sector collectivity.
result Identifies collective signals around major financial events and captures trends in covariances and correlations.
Improved eigenvalue distribution method for financial data.
problem Noise and complexity in financial markets.
method Matrix H theory, hierarchical structure, informational cascade.
result Captures a larger fraction of data variance in financial markets.
Paper uses autoencoders for efficient reduced-order modeling of eigenvalue problems.
problem Efficiently modeling eigenvalue problems in high dimensions.
method Autoencoder-based reduced-order modeling for eigenvalue problems.
result Autoencoder-based models outperform standard POD-Galerkin methods in neutron diffusion applications.
Researchers found new spectral coordinates for the Calogero-Moser system.
problem The Rational Calogero-Moser system.
method Bi-Hamiltonian geometry and canonical spectral coordinates.
result Explicit construction of spectral canonical coordinates.
The paper bounds Cheeger ratios of eigenfunctions and their level sets.
problem Understanding geometric features of Riemannian manifolds through eigenfunctions.
method Constructive upper bounds on Cheeger constants using eigenvalues and eigenfunctions.
result Upper bounds on Cheeger ratios of eigenfunction level sets and their superlevel sets.
The paper proposes a method to improve Koopman operator estimation using indicator functions.
problem Difficulty in identifying good observables for Koopman operator expansion.
method Clustering procedure based on Hidden Markov Model (HMM) to infer surrogate observables.
result Inferred indicator functions significantly improve estimation of Koopman operator eigenvalues and transition timescales.
Through simple analytical calculations and numerical simulations, we demonstrate the generic existence of a self-organized macroscopic state in any large multivariate system possessing non-vanishing average correlations between a finite fraction of all pairs of elements. The coexistence of an eigenvalue spectrum predic…
Study reveals signatures of market crashes through eigenvalue analysis of stock return matrices.
problem Understanding the complexity and dynamics of market crashes.
method Cross-correlation structures and eigenspectra of stock return matrices were analyzed over different epochs.
result The smallest eigenvalue can distinguish between internal and external market instabilities.
The paper analyzes Nordic stock markets' correlation structures and regime shifts.
problem Understanding and exploiting regime shifts in Nordic stock markets.
method Examined two decades of daily data for OMXS30, OMXC20, and OMXH25 universes; proposed an adaptive portfolio allocation framework.
result Documented pronounced regime dependence in rolling correlation matrices; proposed an adaptive portfolio allocation framework.
Reverse stress testing reveals key triggers of financial contagion.
problem Identifying the smallest exogenous shock leading to systemic loss.
method Reconstructing interbank network dynamics and analyzing shocks.
result Ranking banks by systemic importance based on smallest shocks.
Study elliptic operators on glued manifolds, reducing to finite-dimensional systems.
problem Mapping properties of elliptic operators in gluing problems.
method Reduction to finite-dimensional linear systems in the limit Tightarrow∞. result Construction of Fredholm inverses with controlled norms.
We analyze the spectral properties of correlation matrices between distinct statistical systems. Such matrices are intrinsically non symmetric, and lend themselves to extend the spectral analyses usually performed on standard Pearson correlation matrices to the realm of complex eigenvalues. We employ some recent random…
Investigates financial portfolios using quantum system analogies and clustering properties.
problem Understanding the behavior and clustering of correlated financial assets.
method Analogy with quantum systems, development of eigenportfolios, and use of metrics for participation matrix.
result Shows localized states in the correlation matrix of digital currencies, indicating clustering behavior.
Numerous methods for computing conformal mesh paramterizations has been developed due to the vast applications in the field of geometry processing. Spectral conformal parameterization (SCP) is one of these methods to computing a quality conformal parameterization based on the spectral technique. SCP focus on a generali…
Quantum vacuum energy (Casimir energy) is reviewed for a mathematical audience as a topic in spectral theory. Then some one-dimensional systems are solved exactly, in terms of closed classical paths and periodic orbits. The relations among local spectral densities, energy densities, global eigenvalue densities, and tot…
A new method for ML classification without using norms.
problem Machine Learning classification problems without norm criteria.
method Quantum mechanics-like probability states and eigenvalues for classification.
result Avoids norm usage for classification, estimating y distribution. Enhances Koopman operator estimation with intrinsic observables in RKHS.
problem Accurate estimation of Koopman operator and its spectrum.
method Jet Extended Dynamic Mode Decomposition (JetEDMD) leveraging RKHS jets.
result Proves JetEDMD's superiority with error bounds and convergence rate.
A positive path in the linear symplectic group $\Sp(2n)$ is a smooth path which is everywhere tangent to the positive cone. These paths are generated by negative definite (time-dependent) quadratic Hamiltonian functions on Euclidean space. A special case are autonomous positive paths, which are generated by time-indepe…
Explains eigenvalue and generalized eigenvalue problems with examples.
problem Eigenvalue and generalized eigenvalue problems.
method Introduction and examples from machine learning.
result Solutions to eigenvalue and generalized eigenvalue problems.
We compare correlations and coherent structures in nuclei and financial markets. In the nuclear physics part we review giant resonances which can be interpreted as a coherent structure embedded in chaos. With similar methods we investigate the financial empirical correlation matrix of the DAX and Dow Jones. We will sho…
The paper compares Steklov and Laplacian eigenvalues on graphs.
problem Understanding the relationship between Steklov and Laplacian eigenvalues on graphs.
method Analyzing eigenvalues and discussing rigidity.
result Obtained Lichnerowicz-type estimates and combinatorial estimates for Steklov eigenvalues.
Paper finds bounds for Steklov eigenvalues on manifolds.
problem Eigenvalue bounds for Steklov eigenvalues on manifolds.
method Eigenvalue comparison theorems and bounds for the first non-zero eigenvalue of the Wentzell eigenvalue problem.
result Established bounds for Steklov eigenvalues and Wentzell eigenvalues.