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QUADRATIC EIGENVALUE-PROBLEM

  • Quadratic eigenvalue problem
  • In mathematics, the quadratic eigenvalue problem (QEP), is to find scalar eigenvalues λ {\displaystyle \lambda } , left eigenvectors y {\displaystyle

    Quadratic eigenvalue problem

    Quadratic_eigenvalue_problem

  • Eigenvalues and eigenvectors
  • Concepts from linear algebra

    {\displaystyle m{\ddot {x}}+c{\dot {x}}+kx=0} leads to a so-called quadratic eigenvalue problem, ( ω 2 m + ω c + k ) x = 0. {\displaystyle \left(\omega ^{2}m+\omega

    Eigenvalues and eigenvectors

    Eigenvalues_and_eigenvectors

  • Nonlinear eigenproblem
  • Type of equation involving matrix-valued functions

    nonlinear eigenvalue problem, is a generalization of the (ordinary) eigenvalue problem to equations that depend nonlinearly on the eigenvalue. Specifically

    Nonlinear eigenproblem

    Nonlinear_eigenproblem

  • Quadratic programming
  • Solving an optimization problem with a quadratic objective function

    Quadratic programming (QP) is the process of solving certain mathematical optimization problems involving quadratic functions. Specifically, one seeks

    Quadratic programming

    Quadratic_programming

  • Matrix pencil
  • Concept in linear algebra

    matrix. Generalized eigenvalue problem Generalized pencil-of-function method Nonlinear eigenproblem Quadratic eigenvalue problem Generalized Rayleigh

    Matrix pencil

    Matrix_pencil

  • Quadratic form
  • Polynomial with all terms of degree two

    whether all other non-zero eigenvalues are of the same sign: If they are, then it is elliptic; otherwise, it is hyperbolic. Quadratic forms over the ring of

    Quadratic form

    Quadratic_form

  • Modal analysis using FEM
  • Computational analysis of vibrations

    {\displaystyle [F]} is the force vector. The general problem, with nonzero damping, is a quadratic eigenvalue problem. However, for vibrational modal analysis, the

    Modal analysis using FEM

    Modal_analysis_using_FEM

  • SLEPc
  • PEP is intended for polynomial eigenproblems, including the quadratic eigenvalue problem. Solvers based on explicit linearization, that rely on EPS solvers

    SLEPc

    SLEPc

  • Inverse problem
  • Process of calculating the causal factors that produced a set of observations

    notion of eigenvalue does not make sense any longer. A mathematical analysis is required to make it a bounded operator and design a well-posed problem: an illustration

    Inverse problem

    Inverse_problem

  • Eigenvalue algorithm
  • Numerical methods for matrix eigenvalue calculation

    the most important problems is designing efficient and stable algorithms for finding the eigenvalues of a matrix. These eigenvalue algorithms may also

    Eigenvalue algorithm

    Eigenvalue_algorithm

  • Grover's algorithm
  • Quantum search algorithm

    algorithms for NP-complete problems require exponentially many steps, and Grover's algorithm provides at most a quadratic speedup over the classical solution

    Grover's algorithm

    Grover's_algorithm

  • QEP
  • Topics referred to by the same term

    plan or query execution plan, in a database software system Quadratic eigenvalue problem, a special case of nonlinear eigenproblem in mathematics QEP

    QEP

    QEP

  • Riemann hypothesis
  • Conjecture on zeros of the zeta function

    this is important open problem itself and part of Langlands program. Artin (1924) introduced global zeta functions of (quadratic) function fields and conjectured

    Riemann hypothesis

    Riemann hypothesis

    Riemann_hypothesis

  • Convex optimization
  • Subfield of mathematical optimization

    can be seen as reducing a general unconstrained convex problem, to a sequence of quadratic problems.Newton's method can be combined with line search for

    Convex optimization

    Convex_optimization

  • Jacobi eigenvalue algorithm
  • Numerical linear algebra algorithm

    following result of Schönhage yields locally quadratic convergence. To this end let S have m distinct eigenvalues λ 1 , . . . , λ m {\displaystyle \lambda

    Jacobi eigenvalue algorithm

    Jacobi_eigenvalue_algorithm

  • List of unsolved problems in mathematics
  • scissors-congruent? Babai's problem: which groups are Babai invariant groups? Brouwer's conjecture on upper bounds for sums of eigenvalues of Laplacians of graphs

    List of unsolved problems in mathematics

    List_of_unsolved_problems_in_mathematics

  • Newton's method
  • Algorithm for finding zeros of functions

    ^{2}-22.12728346\lambda +34.49868830=0} . Applying the quadratic formula gives the two eigenvalues as λ 1 = 22.12728346 + 351.62192 2 ≈ 20.43943 {\displaystyle

    Newton's method

    Newton's method

    Newton's_method

  • Quaternion estimator algorithm
  • Algorithm to solve Wahba's problem

    Wahba's problem as a quadratic form, using the Cayley–Hamilton theorem and the Newton–Raphson method to efficiently solve the eigenvalue problem and construct

    Quaternion estimator algorithm

    Quaternion_estimator_algorithm

  • Definite quadratic form
  • Type of homogeneous polynomial of degree 2

    indefiniteness, of this quadratic form is equivalent to the same property of A, which can be checked by considering all eigenvalues of A or by checking the

    Definite quadratic form

    Definite_quadratic_form

  • Stark effect
  • Spectral line splitting in electrical field

    effect is either linear (proportional to the applied electric field) or quadratic with a high accuracy. The Stark effect can be observed both for emission

    Stark effect

    Stark effect

    Stark_effect

  • Orthogonal diagonalization
  • Method in linear algebra

    3000 Solved Problems in Linear Algebra. Maxime Bôcher (with E.P.R. DuVal) (1907) Introduction to Higher Algebra, § 45 Reduction of a quadratic form to a

    Orthogonal diagonalization

    Orthogonal_diagonalization

  • Longest increasing subsequence
  • Computer science problem

    longest increasing subsequence problem is closely related to the longest common subsequence problem, which has a quadratic time dynamic programming solution:

    Longest increasing subsequence

    Longest_increasing_subsequence

  • Preconditioner
  • Transforms equations for numerical solution

    the shift, the original eigenvalue problem A x = λ x {\displaystyle Ax=\lambda x} is replaced with the shift-and-invert problem ( A − α I ) − 1 x = μ x

    Preconditioner

    Preconditioner

  • Slepian function
  • Mathematical function

    approximation and in linear inverse problems, and as apodization tapers or window functions in quadratic problems of spectral density estimation. Slepian

    Slepian function

    Slepian_function

  • Rayleigh–Ritz method
  • Method for approximating eigenvalues

    numerical method of approximating eigenvalues, which originated in the context of solving physical boundary-value problems. It is named after Lord Rayleigh

    Rayleigh–Ritz method

    Rayleigh–Ritz_method

  • Terence Tao
  • Australian and American mathematician (born 1975)

    sets into the setting of restriction to quadratic hypersurfaces.[T03] The multilinear setting for these problems was further developed by Tao in collaboration

    Terence Tao

    Terence Tao

    Terence_Tao

  • Linear algebra
  • Branch of mathematics

    electric power. Linear algebraic concepts such as matrix operations and eigenvalue problems are employed to enhance the efficiency, reliability, and economic

    Linear algebra

    Linear algebra

    Linear_algebra

  • QR algorithm
  • Algorithm to calculate eigenvalues

    the QR algorithm or QR iteration is an eigenvalue algorithm: that is, a procedure to calculate the eigenvalues and eigenvectors of a matrix. The QR algorithm

    QR algorithm

    QR_algorithm

  • Definite matrix
  • Property of a mathematical matrix

    min-max theorem, the kth largest eigenvalue of M {\displaystyle M} is greater than or equal to the kth largest eigenvalue of N . {\displaystyle N.} If M

    Definite matrix

    Definite_matrix

  • Calculus of variations
  • Differential calculus on function spaces

    multi-dimensional eigenvalue problems can be formulated as variational problems. The Sturm–Liouville eigenvalue problem involves a general quadratic form Q [ y

    Calculus of variations

    Calculus_of_variations

  • Linear discriminant analysis
  • Method used in statistics, pattern recognition, and other fields

    covariance matrix. These projections can be found by solving a generalized eigenvalue problem, where the numerator is the covariance matrix formed by treating the

    Linear discriminant analysis

    Linear discriminant analysis

    Linear_discriminant_analysis

  • Sylvester's theorem
  • Topics referred to by the same term

    function in terms of eigenvalues. Sylvester's law of inertia, also called Sylvester's rigidity theorem, about the signature of a quadratic form. Sylvester's

    Sylvester's theorem

    Sylvester's_theorem

  • Courant minimax principle
  • maximized — i.e., the length of the quadratic form q(x) is maximized — this is the eigenvector, and its length is the eigenvalue. All other eigenvectors will

    Courant minimax principle

    Courant_minimax_principle

  • Low-rank matrix approximations
  • Approximations used in machine learning

    is at least quadratic in the number of training data points, but most kernel methods include computation of matrix inversion or eigenvalue decomposition

    Low-rank matrix approximations

    Low-rank_matrix_approximations

  • Euler's three-body problem
  • Problem in physics and astronomy

    the eigenvalues (energies) have been obtained: these are a generalization of the Lambert W function. Various generalizations of Euler's problem are known;

    Euler's three-body problem

    Euler's_three-body_problem

  • List of numerical analysis topics
  • Types of problems: Linear-quadratic regulator — system dynamics is a linear differential equation, objective is quadratic Linear-quadratic-Gaussian control

    List of numerical analysis topics

    List_of_numerical_analysis_topics

  • Principal axis theorem
  • Principle in geometry and linear algebra

    {1}{\sqrt {2}}}\end{bmatrix}}.} This applies to the present problem of "diagonalizing" the quadratic form through the observation that 5 x 2 + 8 x y + 5 y 2

    Principal axis theorem

    Principal_axis_theorem

  • Shor's algorithm
  • Quantum algorithm for integer factorization

    factoring problem to the problem of order-finding. This reduction is similar to that used for other factoring algorithms, such as the quadratic sieve. A

    Shor's algorithm

    Shor's_algorithm

  • Conic section
  • Curve from a cone intersecting a plane

    A conic section, conic or a quadratic curve is a curve obtained from a cone's surface intersecting a plane. The three types of conic section are the hyperbola

    Conic section

    Conic section

    Conic_section

  • Matrix (mathematics)
  • Array of numbers

    sprang from several sources. Number-theoretical problems led Gauss to relate coefficients of quadratic forms, that is, expressions such as x2 + xy − 2y2

    Matrix (mathematics)

    Matrix (mathematics)

    Matrix_(mathematics)

  • John E. Osborn (mathematician)
  • American mathematician

    David; Elman, Howard; Osborn, John E. (2009), "A non-self-adjoint quadratic eigenvalue problem describing a fluid-solid interaction. {II}. {A}nalysis of convergence"

    John E. Osborn (mathematician)

    John E. Osborn (mathematician)

    John_E._Osborn_(mathematician)

  • Standard deviation
  • Measure of variation in statistics

    \mathbf {1} )} is the multivariate standard normal. The eigenvectors and eigenvalues of S {\displaystyle \mathbf {S} } correspond to the axes of the 1 sd

    Standard deviation

    Standard deviation

    Standard_deviation

  • Quantum algorithm
  • Algorithm to be run on quantum computers

    general number field sieve. Likewise, Grover's algorithm would run quadratically faster than the best possible classical algorithm for the same task

    Quantum algorithm

    Quantum_algorithm

  • Silver ratio
  • Number, approximately 2.41421

    is the positive solution of quadratic equation σ 2 − 2 σ − 1 = 0. {\displaystyle \sigma ^{2}-2\sigma -1=0.} The quadratic formula gives the two solutions

    Silver ratio

    Silver ratio

    Silver_ratio

  • Gradient descent
  • Optimization algorithm

    \mathbf {A} \mathbf {x} -\mathbf {b} =0} reformulated as a quadratic minimization problem. If the system matrix A {\displaystyle \mathbf {A} } is real

    Gradient descent

    Gradient descent

    Gradient_descent

  • Polynomial root-finding
  • roots exist only when the degree of the polynomial is less than 5. The quadratic formula has been known since antiquity, and the cubic and quartic formulas

    Polynomial root-finding

    Polynomial_root-finding

  • Semidefinite programming
  • Subfield of convex optimization

    of edges crossing from one side to the other. This problem can be expressed as an integer quadratic program: Maximize ∑ ( i , j ) ∈ E 1 − v i v j 2 , {\displaystyle

    Semidefinite programming

    Semidefinite_programming

  • Rotation matrix
  • Matrix representing a Euclidean rotation

    odd, there will be a "dangling" eigenvalue of 1; and for any dimension the rest of the polynomial factors into quadratic terms like the one here (with the

    Rotation matrix

    Rotation_matrix

  • Newton's method in optimization
  • Method for finding stationary points of a function

    iterate x k + 1 {\displaystyle x_{k+1}} is defined so as to minimize this quadratic approximation in t {\displaystyle t} , and setting x k + 1 = x k + t {\displaystyle

    Newton's method in optimization

    Newton's method in optimization

    Newton's_method_in_optimization

  • Partial differential equation
  • Type of differential equation

    there is more than one positive eigenvalue and more than one negative eigenvalue, and there are no zero eigenvalues. The theory of elliptic, parabolic

    Partial differential equation

    Partial differential equation

    Partial_differential_equation

  • Least mean squares filter
  • Statistical algorithm

    the error. The mean-square error as a function of filter weights is a quadratic function which means it has only one extremum, that minimizes the mean-square

    Least mean squares filter

    Least_mean_squares_filter

  • Isospectral
  • Linear operators with a common spectrum

    spectrum. Roughly speaking, they are supposed to have the same sets of eigenvalues, when those are counted with multiplicity. The theory of isospectral

    Isospectral

    Isospectral

  • Quadric
  • Locus of the zeros of a polynomial of degree two

    {radius}^{2}={\frac {C}{eigenvalue\;of{\mathbf {A}}}}} where the radial axes and along the eigenvectors of the corresponding eigenvalues, and C = p T A p −

    Quadric

    Quadric

  • Conjugate gradient method
  • Mathematical optimization algorithm

    optimization, and variation of the Arnoldi/Lanczos iteration for eigenvalue problems. Despite differences in their approaches, these derivations share

    Conjugate gradient method

    Conjugate gradient method

    Conjugate_gradient_method

  • Hermitian matrix
  • Matrix equal to its conjugate-transpose

    Ritz and Lord Rayleigh. Parlett, Beresford N. (1998). The symmetric eigenvalue problem. Classics in applied mathematics. Philadelphia, Pa: Society for Industrial

    Hermitian matrix

    Hermitian_matrix

  • Multiplier
  • Topics referred to by the same term

    value or values; see Periodic points of complex quadratic mappings Characteristic multiplier, an eigenvalue of a monodromy matrix Multiplier algebra, a construction

    Multiplier

    Multiplier

  • Random matrix
  • Matrix-valued random variable

    in the state equation and the problem is known as one of stochastic control. A key result in the case of linear-quadratic control with stochastic matrices

    Random matrix

    Random_matrix

  • Configuration interaction
  • Concept in computational chemistry

    some eigenvalues E j {\displaystyle \mathbf {E} ^{j}} and their corresponding eigenvectors c I j {\displaystyle \mathbf {c} _{I}^{j}} . The eigenvalues are

    Configuration interaction

    Configuration_interaction

  • Quantum harmonic oscillator
  • Quantum mechanical model

    eigenstate. Then solve the differential equation representing this eigenvalue problem in the coordinate basis, for the wave function ⟨ x | ψ ⟩ = ψ ( x )

    Quantum harmonic oscillator

    Quantum harmonic oscillator

    Quantum_harmonic_oscillator

  • Quartic function
  • Polynomial function of degree 4

    that the depressed equation is bi-quadratic, and may be solved by an easier method (see above). This was not a problem at the time of Ferrari, when one

    Quartic function

    Quartic function

    Quartic_function

  • Symmetric matrix
  • Matrix equal to its transpose

    symmetric matrix A {\displaystyle A} is equal to the number of non-zero eigenvalues of A {\displaystyle A} . Any square matrix can uniquely be written as

    Symmetric matrix

    Symmetric matrix

    Symmetric_matrix

  • Algebraic Riccati equation
  • Nonlinear equation which arises on linear optimal control problems

    time-invariant Linear-Quadratic Regulator problem (LQR) as well as that of the infinite horizon time-invariant Linear-Quadratic-Gaussian control problem (LQG). These

    Algebraic Riccati equation

    Algebraic_Riccati_equation

  • Cubic equation
  • Polynomial equation of degree 3

    arithmetic operations, square roots, and cube roots. (This is also true of quadratic (second-degree) and quartic (fourth-degree) equations, but not for higher-degree

    Cubic equation

    Cubic equation

    Cubic_equation

  • M-matrix
  • Matrix in mathematics

    complementarity problem. Linear complementarity problems arise in linear and quadratic programming, computational mechanics, and in the problem of finding

    M-matrix

    M-matrix

  • Pi
  • Number, approximately 3.14

    of the Dirichlet eigenvalue problem in one dimension, the Poincaré inequality is the variational form of the Neumann eigenvalue problem, in any dimension

    Pi

    Pi

  • Dirichlet energy
  • Mathematical measure of a function's variability

    is a measure of how variable a function is. More abstractly, it is a quadratic functional on the Sobolev space H1. The Dirichlet energy is intimately

    Dirichlet energy

    Dirichlet_energy

  • Perturbation theory
  • Methods of mathematical approximation

    finding an approximate solution to a problem, by starting from the exact solution of a related, simpler problem. A critical feature of the technique is

    Perturbation theory

    Perturbation_theory

  • ΑΒΒ
  • Second-order deterministic global optimization algorithm

    relaxation for nonlinear functions of general form by superposing them with a quadratic of sufficient magnitude, called α, such that the resulting superposition

    ΑΒΒ

    ΑΒΒ

  • Hierarchical Risk Parity
  • Machine learning framework for portfolio construction

    portfolios have been proposed as a robust alternative to traditional quadratic optimization methods, including the Critical Line Algorithm (CLA) of Markowitz

    Hierarchical Risk Parity

    Hierarchical_Risk_Parity

  • Ridge regression
  • Regularization technique for ill-posed problems

    the inverse-problem, the inverse mapping operates as a high-pass filter that has the undesirable tendency of amplifying noise (eigenvalues / singular values

    Ridge regression

    Ridge_regression

  • Matrix differential equation
  • Type of mathematical equation

    +c_{n}e^{\lambda _{n}t}\mathbf {u} _{n}~,} where λ1, λ2, …, λn are the eigenvalues of A; u1, u2, …, un are the respective eigenvectors of A; and c1, c2

    Matrix differential equation

    Matrix_differential_equation

  • Quantum walk search
  • Quantum algorithm

    asymptotic quadratic speedup similar to that of Grover's algorithm. One of the first works on the application of quantum walk to search problems was proposed

    Quantum walk search

    Quantum_walk_search

  • Periodic points of complex quadratic mappings
  • some complex quadratic maps. A map is a formula for computing a value of a variable based on its own previous value or values; a quadratic map is one that

    Periodic points of complex quadratic mappings

    Periodic_points_of_complex_quadratic_mappings

  • Strongly regular graph
  • Concept in graph theory

    get a quadratic: p 2 + ( μ − λ ) p − ( k − μ ) = 0 {\displaystyle p^{2}+(\mu -\lambda )p-(k-\mu )=0} This gives the two additional eigenvalues 1 2 [ (

    Strongly regular graph

    Strongly regular graph

    Strongly_regular_graph

  • Phase plane
  • Visual representation used in non-linear control system analysis

    q=AD-BC=\det(\mathbf {A} )\,.} The explicit solution of the eigenvalues are then given by the quadratic formula: λ = 1 2 ( p ± Δ ) {\displaystyle \lambda ={\frac

    Phase plane

    Phase_plane

  • Littlewood conjecture
  • Mathematical problem

    Ad_{L}} -unipotent elements, i.e. elements g for which 1 is the only eigenvalue of A d L ( g ) {\displaystyle Ad_{L}(g)} . Borel showed in 1909 that the

    Littlewood conjecture

    Littlewood_conjecture

  • Orthogonal matrix
  • Real square matrix whose columns and rows are orthogonal unit vectors

    conjugate pairs of eigenvalues lying on the unit circle in the complex plane; so this decomposition confirms that all eigenvalues have absolute value

    Orthogonal matrix

    Orthogonal_matrix

  • Kalman filter
  • Algorithm that estimates unknowns from a series of measurements over time

    statistics and control theory, Kalman filtering (also known as linear quadratic estimation) is an algorithm that uses a series of measurements observed

    Kalman filter

    Kalman filter

    Kalman_filter

  • Idempotent matrix
  • Matrix that, squared, equals itself

    matrix A {\displaystyle A} and λ {\displaystyle \lambda } its associated eigenvalue, then λ x = A x = A 2 x = A λ x = λ A x = λ 2 x , {\textstyle \lambda

    Idempotent matrix

    Idempotent_matrix

  • Multidisciplinary design optimization
  • Field of engineering

    developed a Rayleigh quotient approximation to improve the accuracy of eigenvalue approximations. Barthelemy and Haftka published a comprehensive review

    Multidisciplinary design optimization

    Multidisciplinary_design_optimization

  • Batch normalization
  • Method of improving artificial neural network

    iteration III: A short and sharp convergence estimate for generalized eigenvalue problems". Linear Algebra and Its Applications. 358 (1–3): 95–114. doi:10

    Batch normalization

    Batch_normalization

  • Stiff equation
  • Differential equation exhibiting high rate of dissipation

    the symmetric eigenvalue problem H e ( A ) v = μ v , {\displaystyle {\mathrm {He} }(A)v=\mu v\,,} whose d {\displaystyle d} real eigenvalues μ 1 ≥ μ 2 ≥

    Stiff equation

    Stiff_equation

  • Hale Trotter
  • Canadian-American mathematician (1931–2022)

    289–292. doi:10.1090/S0002-9904-1977-14310-3. Trotter, H. F. (1984). "Eigenvalue distributions of large Hermitian matrices; Wigner's semi-circle law and

    Hale Trotter

    Hale Trotter

    Hale_Trotter

  • Nonlinearity (disambiguation)
  • Topics referred to by the same term

    problem (NCP), finding a vector meeting certain conditions based on a given smooth mapping Nonlinear eigenproblem (AKA nonlinear eigenvalue problem)

    Nonlinearity (disambiguation)

    Nonlinearity_(disambiguation)

  • Schrödinger equation
  • Description of a quantum-mechanical system

    the result will be one of its eigenvalues with probability given by the Born rule: in the simplest case the eigenvalue λ {\displaystyle \lambda } is non-degenerate

    Schrödinger equation

    Schrödinger_equation

  • Variable (mathematics)
  • Symbol representing a mathematical object

    determined; in which case, it is called an unknown; for example, in the quadratic equation ax2 + bx + c = 0, the variables a, b, c are parameters, and x

    Variable (mathematics)

    Variable_(mathematics)

  • List of quantum-mechanical systems with analytical solutions
  • {\left(\mathbf {r} \right)}=E\psi {\left(\mathbf {r} \right)},} which is an eigenvalue equation. Very often, only numerical solutions to the Schrödinger equation

    List of quantum-mechanical systems with analytical solutions

    List_of_quantum-mechanical_systems_with_analytical_solutions

  • Separation principle
  • feedback controller designed to minimize a quadratic cost, is optimal for the stochastic control problem with output measurements. When process and observation

    Separation principle

    Separation_principle

  • Matrix representation of conic sections
  • Concept in mathematics

    A&B/2\\B/2&C\end{pmatrix}}{\begin{pmatrix}x\\y\end{pmatrix}},} is the quadratic form associated with the equation, and the matrix A 33 = ( A B / 2 B /

    Matrix representation of conic sections

    Matrix_representation_of_conic_sections

  • List of things named after James Joseph Sylvester
  • theorem, a.k.a. Sylvester's formula, for a matrix function in terms of eigenvalues. Sylvester's theorem on the product of k consecutive integers > k, that

    List of things named after James Joseph Sylvester

    List_of_things_named_after_James_Joseph_Sylvester

  • Hessian matrix
  • Matrix of second derivatives

    product of the eigenvalues. If it is positive, then the eigenvalues are both positive or both negative. If it is negative, then the two eigenvalues have different

    Hessian matrix

    Hessian_matrix

  • Complete set of invariants
  • invariant for matrices over a field up to conjugation (similarity), but eigenvalues (with multiplicities) are not. The elementary divisors are a complete

    Complete set of invariants

    Complete_set_of_invariants

  • List of algorithms
  • quantum algorithms for optimization problems Quantum phase estimation algorithm: estimates the phase of an eigenvalue of a unitary operator Quantum singular

    List of algorithms

    List_of_algorithms

  • Fundamental theorem of algebra
  • Every polynomial has a real or complex root

    vector space of matrices. The eigenvalues of A are precisely the poles of R(z). Since, by assumption, A has no eigenvalues, the function R(z) is an entire

    Fundamental theorem of algebra

    Fundamental_theorem_of_algebra

  • Regularized least squares
  • Concept in regression analysis mathematics

    least squares (RLS) is a family of methods for solving the least-squares problem while using regularization to further constrain the resulting solution

    Regularized least squares

    Regularized_least_squares

  • Bogoliubov transformation
  • Mathematical operation in quantum optics, general relativity and other areas of physics

    with a corresponding transformation of the state function. Operator eigenvalues calculated with the diagonalized Hamiltonian on the transformed state

    Bogoliubov transformation

    Bogoliubov_transformation

  • Hilbert space
  • Type of vector space in math

    to study the behavior of eigenvalues and eigenfunctions of differential equations. For example, the Sturm–Liouville problem arises in the study of the

    Hilbert space

    Hilbert space

    Hilbert_space

  • Control theory
  • Branch of engineering and mathematics

    untouched in the closed-loop system. If such an eigenvalue is not stable, the dynamics of this eigenvalue will be present in the closed-loop system which

    Control theory

    Control_theory

  • Clebsch–Gordan coefficients for SU(3)
  • Representation of angular momentum tensor product states important to physics

    generalizes the mere two labels for SU(2) multiplets, namely the eigenvalues of its quadratic Casimir and of I3. Since [ I ^ 3 , Y ^ ] = 0 {\displaystyle [{\hat

    Clebsch–Gordan coefficients for SU(3)

    Clebsch–Gordan_coefficients_for_SU(3)

  • Marchenko–Pastur distribution
  • Distribution of singular values of large rectangular random matrices

    {\displaystyle \lambda _{1},\,\lambda _{2},\,\dots ,\,\lambda _{m}} be the eigenvalues of Y n {\displaystyle Y_{n}} (viewed as random variables). Finally, consider

    Marchenko–Pastur distribution

    Marchenko–Pastur distribution

    Marchenko–Pastur_distribution

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  • Biquadratic
  • n.

    A biquadrate.

  • -trices
  • pl.

    of Quadratrix

  • Quadrated
  • imp. & p. p.

    of Quadrate

  • Quad
  • n.

    A quadrat.

  • Quadrate
  • v. t.

    To adjust (a gun) on its carriage; also, to train (a gun) for horizontal firing.

  • Quadrate
  • a.

    To square; to agree; to suit; to correspond; -- followed by with.

  • Quadratrix
  • n.

    A curve made use of in the quadrature of other curves; as the quadratrix, of Dinostratus, or of Tschirnhausen.

  • Quarry
  • a.

    Quadrate; square.

  • Quadratic
  • a.

    Tetragonal.

  • Quadratic
  • a.

    Of or pertaining to a square, or to squares; resembling a quadrate, or square; square.

  • Biquadratic
  • a.

    Of or pertaining to the biquadrate, or fourth power.

  • Quadratojugal
  • a.

    Of or pertaining to the quadrate and jugal bones.

  • Quadrating
  • p. pr. & vb. n.

    of Quadrate

  • Quartile
  • n.

    Same as Quadrate.

  • -trixes
  • pl.

    of Quadratrix

  • Quadratic
  • a.

    Pertaining to terms of the second degree; as, a quadratic equation, in which the highest power of the unknown quantity is a square.

  • Quadrature
  • a.

    A quadrate; a square.

  • Quadratics
  • n.

    That branch of algebra which treats of quadratic equations.

  • Biquadratic
  • n.

    A biquadratic equation.

  • Quadrate
  • a.

    The quadrate bone.