| http://dbpedia.org/ontology/abstract
|
Metoda najszybszego spadku – algorytm numeryczny mający na celu znalezienie minimum zadanej funkcji celu. Metoda najszybszego spadku jest modyfikacją metody gradientu prostego.
, En mathématiques, la méthode du point col … En mathématiques, la méthode du point col (aussi appelée méthode du col, méthode de la plus grande pente ou méthode de la descente rapide ; en anglais, saddle point approximation ou SPA) permet d'évaluer le comportement asymptotique d'une intégrale complexe du type : lorsque . Les fonctions et sont analytiques et est un chemin d'intégration du plan complexe. Bien que reposant sur des concepts différents, la méthode du point col est généralement considérée comme l'extension de la méthode de la phase stationnaire aux intégrales complexes. Cette méthode est notamment utilisée en combinatoire analytique et en mécanique statistique.re analytique et en mécanique statistique.
, Метод перевала — метод, использующийся для аппроксимации интегралов вида где — некоторые мероморфные функции, — некоторое большое число, а контур может быть бесконечным. Этот метод часто называется обобщением метода Лапласа.
, In mathematics, the method of steepest des … In mathematics, the method of steepest descent or saddle-point method is an extension of Laplace's method for approximating an integral, where one deforms a contour integral in the complex plane to pass near a stationary point (saddle point), in roughly the direction of steepest descent or stationary phase. The saddle-point approximation is used with integrals in the complex plane, whereas Laplace’s method is used with real integrals. The integral to be estimated is often of the form where C is a contour, and λ is large. One version of the method of steepest descent deforms the contour of integration C into a new path integration C′ so that the following conditions hold: 1.
* C′ passes through one or more zeros of the derivative g′(z), 2.
* the imaginary part of g(z) is constant on C′. The method of steepest descent was first published by , who used it to estimate Bessel functions and pointed out that it occurred in the unpublished note by about hypergeometric functions. The contour of steepest descent has a minimax property, see . described some other unpublished notes of Riemann, where he used this method to derive the Riemann–Siegel formula.thod to derive the Riemann–Siegel formula.
|
| http://dbpedia.org/ontology/wikiPageExternalLink
|
https://zenodo.org/record/2397260 +
|
| http://dbpedia.org/ontology/wikiPageID
|
27082137
|
| http://dbpedia.org/ontology/wikiPageLength
|
31290
|
| http://dbpedia.org/ontology/wikiPageRevisionID
|
1107236129
|
| http://dbpedia.org/ontology/wikiPageWikiLink
|
http://dbpedia.org/resource/Partition_of_unity +
, http://dbpedia.org/resource/Connected_space +
, http://dbpedia.org/resource/Chain_rule +
, http://dbpedia.org/resource/Combinatorics +
, http://dbpedia.org/resource/One-to-one_function +
, http://dbpedia.org/resource/Riemann%E2%80%93Hilbert_factorization +
, http://dbpedia.org/resource/Pearcey_integral +
, http://dbpedia.org/resource/File:Illustration_To_Derivation_Of_Asymptotic_For_Saddle_Point_Integration.pdf +
, http://dbpedia.org/resource/Hypergeometric_functions +
, http://dbpedia.org/resource/Simply_connected_space +
, http://dbpedia.org/resource/File:Complex_Morse_Lemma_Illustration.pdf +
, http://dbpedia.org/resource/Morse_theory +
, http://dbpedia.org/resource/Jacobian_matrix_and_determinant +
, http://dbpedia.org/resource/Catastrophe_theory +
, http://dbpedia.org/resource/Caustic_%28optics%29 +
, http://dbpedia.org/resource/Integrable_model +
, http://dbpedia.org/resource/Holomorphic_function +
, http://dbpedia.org/resource/Method_of_steepest_descent +
, http://dbpedia.org/resource/Complex_sphere +
, http://dbpedia.org/resource/Definite_bilinear_form +
, http://dbpedia.org/resource/Eigenvalues_and_eigenvectors +
, http://dbpedia.org/resource/WKB_approximation +
, http://dbpedia.org/resource/Laplace%27s_method +
, http://dbpedia.org/resource/Jordan_normal_form +
, http://dbpedia.org/resource/Analytic_function +
, http://dbpedia.org/resource/Sylvester%27s_law_of_inertia +
, http://dbpedia.org/resource/Mathematical_induction +
, http://dbpedia.org/resource/Category:Perturbation_theory +
, http://dbpedia.org/resource/Bessel_functions +
, http://dbpedia.org/resource/Saddle_point +
, http://dbpedia.org/resource/Stationary_phase_approximation +
, http://dbpedia.org/resource/Random_matrices +
, http://dbpedia.org/resource/Open_cover +
, http://dbpedia.org/resource/Bounded_set_%28topological_vector_space%29 +
, http://dbpedia.org/resource/Open_set +
, http://dbpedia.org/resource/Soliton +
, http://dbpedia.org/resource/Cauchy%E2%80%93Riemann_equations +
, http://dbpedia.org/resource/Maslov_index +
, http://dbpedia.org/resource/Riemann%E2%80%93Siegel_formula +
, http://dbpedia.org/resource/Category:Asymptotic_analysis +
, http://dbpedia.org/resource/Hessian_matrix +
|
| http://dbpedia.org/property/first
|
M. V.
|
| http://dbpedia.org/property/last
|
Fedoryuk
|
| http://dbpedia.org/property/proof
|
The following proof is a straightforward g … The following proof is a straightforward generalization of the proof of the real Morse Lemma, which can be found in. We begin by demonstrating
:Auxiliary statement. Let be holomorphic in a neighborhood of the origin and . Then in some neighborhood, there exist functions such that where each is holomorphic and
From the identity
:
we conclude that
:
and
:
Without loss of generality, we translate the origin to , such that and . Using the Auxiliary Statement, we have
:
Since the origin is a saddle point,
:
we can also apply the Auxiliary Statement to the functions and obtain
Recall that an arbitrary matrix can be represented as a sum of symmetric and anti-symmetric matrices,
:
The contraction of any symmetric matrix B with an arbitrary matrix is
i.e., the anti-symmetric component of does not contribute because
:
Thus, in equation can be assumed to be symmetric with respect to the interchange of the indices and . Note that
:
hence, because the origin is a non-degenerate saddle point.
Let us show by induction that there are local coordinates , such that
First, assume that there exist local coordinates , such that
where is symmetric due to equation . By a linear change of the variables , we can assure that . From the chain rule, we have
:
Therefore:
:
whence,
:
The matrix can be recast in the Jordan normal form: , were gives the desired non-singular linear transformation and the diagonal of contains non-zero eigenvalues of . If then, due to continuity of , it must be also non-vanishing in some neighborhood of the origin. Having introduced , we write
:
Motivated by the last expression, we introduce new coordinates
:
The change of the variables is locally invertible since the corresponding Jacobian is non-zero,
:
Therefore,
Comparing equations and , we conclude that equation is verified. Denoting the eigenvalues of by , equation can be rewritten as
Therefore,
From equation , it follows that . The Jordan normal form of reads , where is an upper diagonal matrix containing the eigenvalues and ; hence, . We obtain from equation
:
If , then interchanging two variables assures that .interchanging two variables assures that .
, thumb|center|An illustration to the deriva … thumb|center|An illustration to the derivation of equation (8)
First, we deform the contour into a new contour passing through the saddle point and sharing the boundary with . This deformation does not change the value of the integral . We employ the Complex Morse Lemma to change the variables of integration. According to the lemma, the function maps a neighborhood onto a neighborhood containing the origin. The integral can be split into two: , where is the integral over , while is over . Since the latter region does not contain the saddle point , the value of is exponentially smaller than as ; thus, is ignored. Introducing the contour such that , we have
Recalling that as well as , we expand the pre-exponential function into a Taylor series and keep just the leading zero-order term
Here, we have substituted the integration region by because both contain the origin, which is a saddle point, hence they are equal up to an exponentially small term. The integrals in the r.h.s. of equation can be expressed as
From this representation, we conclude that condition must be satisfied in order for the r.h.s. and l.h.s. of equation to coincide. According to assumption 2, is a negatively defined quadratic form implying the existence of the integral , which is readily calculated
: integral , which is readily calculated
:
|
| http://dbpedia.org/property/title
|
Proof of complex Morse lemma
, Saddle point method
, Derivation of equation
|
| http://dbpedia.org/property/wikiPageUsesTemplate
|
http://dbpedia.org/resource/Template:Harvtxt +
, http://dbpedia.org/resource/Template:For +
, http://dbpedia.org/resource/Template:Mvar +
, http://dbpedia.org/resource/Template:Cite_arXiv +
, http://dbpedia.org/resource/Template:Eom +
, http://dbpedia.org/resource/Template:Math_proof +
, http://dbpedia.org/resource/Template:Reflist +
, http://dbpedia.org/resource/Template:Citation +
, http://dbpedia.org/resource/Template:= +
, http://dbpedia.org/resource/Template:NumBlk +
, http://dbpedia.org/resource/Template:Math +
, http://dbpedia.org/resource/Template:EquationRef +
|
| http://purl.org/dc/terms/subject
|
http://dbpedia.org/resource/Category:Asymptotic_analysis +
, http://dbpedia.org/resource/Category:Perturbation_theory +
|
| http://www.w3.org/ns/prov#wasDerivedFrom
|
http://en.wikipedia.org/wiki/Method_of_steepest_descent?oldid=1107236129&ns=0 +
|
| http://xmlns.com/foaf/0.1/isPrimaryTopicOf
|
http://en.wikipedia.org/wiki/Method_of_steepest_descent +
|
| owl:sameAs |
http://fr.dbpedia.org/resource/M%C3%A9thode_du_point_col +
, http://ru.dbpedia.org/resource/%D0%9C%D0%B5%D1%82%D0%BE%D0%B4_%D0%BF%D0%B5%D1%80%D0%B5%D0%B2%D0%B0%D0%BB%D0%B0 +
, http://www.wikidata.org/entity/Q1997812 +
, https://global.dbpedia.org/id/uSPf +
, http://pl.dbpedia.org/resource/Metoda_najszybszego_spadku +
, http://rdf.freebase.com/ns/m.02zr_k +
, http://dbpedia.org/resource/Method_of_steepest_descent +
|
| rdfs:comment |
Metoda najszybszego spadku – algorytm numeryczny mający na celu znalezienie minimum zadanej funkcji celu. Metoda najszybszego spadku jest modyfikacją metody gradientu prostego.
, En mathématiques, la méthode du point col … En mathématiques, la méthode du point col (aussi appelée méthode du col, méthode de la plus grande pente ou méthode de la descente rapide ; en anglais, saddle point approximation ou SPA) permet d'évaluer le comportement asymptotique d'une intégrale complexe du type : lorsque . Les fonctions et sont analytiques et est un chemin d'intégration du plan complexe. un chemin d'intégration du plan complexe.
, In mathematics, the method of steepest des … In mathematics, the method of steepest descent or saddle-point method is an extension of Laplace's method for approximating an integral, where one deforms a contour integral in the complex plane to pass near a stationary point (saddle point), in roughly the direction of steepest descent or stationary phase. The saddle-point approximation is used with integrals in the complex plane, whereas Laplace’s method is used with real integrals. The integral to be estimated is often of the formegral to be estimated is often of the form
, Метод перевала — метод, использующийся для аппроксимации интегралов вида где — некоторые мероморфные функции, — некоторое большое число, а контур может быть бесконечным. Этот метод часто называется обобщением метода Лапласа.
|
| rdfs:label |
Méthode du point col
, Метод перевала
, Method of steepest descent
, Metoda najszybszego spadku
|
