Method Of Steepest Descent
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In mathematics, the method of steepest descent or saddle-point method is an extension of
Laplace's method In mathematics, Laplace's method, named after Pierre-Simon Laplace, is a technique used to approximate integrals of the form :\int_a^b e^ \, dx, where f(x) is a twice-differentiable function, ''M'' is a large number, and the endpoints ''a'' an ...
for approximating an integral, where one deforms a contour integral in the complex plane to pass near a stationary point (
saddle point In mathematics, a saddle point or minimax point is a point on the surface of the graph of a function where the slopes (derivatives) in orthogonal directions are all zero (a critical point), but which is not a local extremum of the function ...
), 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 :\int_Cf(z)e^\,dz, 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: # ''C′'' passes through one or more zeros of the derivative ''g''′(''z''), # 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 Bessel functions, first defined by the mathematician Daniel Bernoulli and then generalized by Friedrich Bessel, are canonical solutions of Bessel's differential equation x^2 \frac + x \frac + \left(x^2 - \alpha^2 \right)y = 0 for an arbitrary ...
and pointed out that it occurred in the unpublished note by about hypergeometric functions.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 described some other unpublished notes of Riemann, where he used this method to derive the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 In mathematics, the Riemann–Siegel formula is an asymptotic formula for the error of the approximate functional equation of the Riemann zeta function, an approximation of the zeta function by a sum of two finite Dirichlet series. It was found by ...
.


Basic idea

The method of steepest descent is a method to approximate a complex integral of the formI(\lambda) = \int_Cf(z)e^\,\mathrmzfor large \lambda \rightarrow \infty, where f(z) and g(z) are
analytic function In mathematics, an analytic function is a function that is locally given by a convergent power series. There exist both real analytic functions and complex analytic functions. Functions of each type are infinitely differentiable, but complex an ...
s of z. Because the integrand is analytic, the contour C can be deformed into a new contour C' without changing the integral. In particular, one seeks a new contour on which the imaginary part of g(z) = \text (z)+ i \, \text (z)/math> is constant. Then I(\lambda) = e^ \int_f(z)e^\,\mathrmz,and the remaining integral can be approximated with other methods like
Laplace's method In mathematics, Laplace's method, named after Pierre-Simon Laplace, is a technique used to approximate integrals of the form :\int_a^b e^ \, dx, where f(x) is a twice-differentiable function, ''M'' is a large number, and the endpoints ''a'' an ...
.


Etymology

The method is called the method of steepest descent because for analytic g(z), constant phase contours are equivalent to steepest descent contours. If g(z) = X(z) + i Y(z) is an
analytic function In mathematics, an analytic function is a function that is locally given by a convergent power series. There exist both real analytic functions and complex analytic functions. Functions of each type are infinitely differentiable, but complex an ...
of z = x + i y, it satisfies the
Cauchy–Riemann equations In the field of complex analysis in mathematics, the Cauchy–Riemann equations, named after Augustin Cauchy and Bernhard Riemann, consist of a system of two partial differential equations which, together with certain continuity and differ ...
\frac = \frac \qquad \text \qquad \frac = - \frac .Then \frac \frac + \frac \frac = \nabla X \cdot \nabla Y = 0,so contours of constant phase are also contours of steepest descent.


A simple estimate

Let and . If : M = \sup_ \Re (S(x)) < \infty, where \Re (\cdot) denotes the real part, and there exists a positive real number such that :\int_ \left, f(x) e^ \ dx < \infty, then the following estimate holds: :\left, \int_ f(x) e^ dx \ \leqslant \text\cdot e^, \qquad \forall \lambda \in \mathbb, \quad \lambda \geqslant \lambda_0. Proof of the simple estimate: :\begin \left, \int_ f(x) e^ dx \ &\leqslant \int_C , f(x), \left, e^ \ dx \\ &\equiv \int_ , f(x), e^ \left , e^ e^ \ dx \\ &\leqslant \int_C , f(x), e^ \left, e^ \ dx && \left, e^ \ \leqslant 1 \\ &= \underbrace_ \cdot e^. \end


The case of a single non-degenerate saddle point


Basic notions and notation

Let be a complex -dimensional vector, and :S''_(x) \equiv \left( \frac \right), \qquad 1\leqslant i,\, j\leqslant n, denote the
Hessian matrix In mathematics, the Hessian matrix or Hessian is a square matrix of second-order partial derivatives of a scalar-valued function, or scalar field. It describes the local curvature of a function of many variables. The Hessian matrix was developed ...
for a function . If :\boldsymbol(x) = (\varphi_1(x), \varphi_2(x), \ldots, \varphi_k(x)) is a vector function, then its
Jacobian matrix In vector calculus, the Jacobian matrix (, ) of a vector-valued function of several variables is the matrix of all its first-order partial derivatives. When this matrix is square, that is, when the function takes the same number of variables as ...
is defined as :\boldsymbol_x' (x) \equiv \left( \frac \right), \qquad 1 \leqslant i \leqslant k, \quad 1 \leqslant j \leqslant n. A non-degenerate saddle point, , of a holomorphic function is a critical point of the function (i.e., ) where the function's Hessian matrix has a non-vanishing determinant (i.e., \det S''_(z^0) \neq 0). The following is the main tool for constructing the asymptotics of integrals in the case of a non-degenerate saddle point:


Complex Morse lemma

The
Morse lemma In mathematics, specifically in differential topology, Morse theory enables one to analyze the topology of a manifold by studying differentiable functions on that manifold. According to the basic insights of Marston Morse, a typical differenti ...
for real-valued functions generalizes as follows for
holomorphic function In mathematics, a holomorphic function is a complex-valued function of one or more complex variables that is complex differentiable in a neighbourhood of each point in a domain in complex coordinate space . The existence of a complex derivativ ...
s: near a non-degenerate saddle point of a holomorphic function , there exist coordinates in terms of which is exactly quadratic. To make this precise, let be a holomorphic function with domain , and let in be a non-degenerate saddle point of , that is, and \det S''_(z^0) \neq 0. Then there exist neighborhoods of and of , and a
bijective In mathematics, a bijection, also known as a bijective function, one-to-one correspondence, or invertible function, is a function between the elements of two sets, where each element of one set is paired with exactly one element of the other ...
holomorphic function with such that :\forall w \in V: \qquad S(\boldsymbol(w)) = S(z^0) + \frac \sum_^n \mu_j w_j^2, \quad \det\boldsymbol_w'(0) = 1, Here, the are the
eigenvalues In linear algebra, an eigenvector () or characteristic vector of a linear transformation is a nonzero vector that changes at most by a scalar factor when that linear transformation is applied to it. The corresponding eigenvalue, often denoted b ...
of the matrix S_''(z^0).


The asymptotic expansion in the case of a single non-degenerate saddle point

Assume # and are
holomorphic In mathematics, a holomorphic function is a complex-valued function of one or more complex variables that is complex differentiable in a neighbourhood of each point in a domain in complex coordinate space . The existence of a complex derivati ...
functions in an
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, bounded, and simply connected set such that the is
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; # \Re(S(z)) has a single maximum: \max_ \Re(S(z)) = \Re(S(x^0)) for exactly one point ; # is a non-degenerate saddle point (i.e., and \det S''_(x^0) \neq 0). Then, the following asymptotic holds e^ \left(f(x^0)+ O\left(\lambda^\right) \right) \prod_^n (-\mu_j)^, \qquad \lambda \to \infty,, where are eigenvalues of the Hessian S''_(x^0) and (-\mu_j)^ are defined with arguments This statement is a special case of more general results presented in Fedoryuk (1987). \int_0^ e^ d\xi = \sqrt (-\mu_j)^. Equation (8) can also be written as e^ \left ( \det (-S_''(x^0)) \right )^ \left (f(x^0) + O\left(\lambda^\right) \right),, where the branch of :\sqrt is selected as follows :\begin \left (\det \left (-S_''(x^0) \right ) \right)^ &= \exp\left( -i \text \left (- S_''(x^0) \right ) \right) \prod_^n \left, \mu_j \^, \\ \text \left (-S_''(x^0) \right) &= \tfrac \sum_^n \arg (-\mu_j), && , \arg(-\mu_j), < \tfrac. \end Consider important special cases: * If is real valued for real and in (aka, the multidimensional Laplace method), then \text \left(-S_''(x^0) \right ) = 0. * If is purely imaginary for real (i.e., \Re(S(x)) = 0 for all in ) and in (aka, the multidimensional stationary phase method), thenSee equation (2.2.6') on page 186 in \text \left (-S_''(x^0) \right ) = \frac \textS_''(x_0), where \textS_''(x_0) denotes the signature of matrix S_''(x_0), which equals to the number of negative eigenvalues minus the number of positive ones. It is noteworthy that in applications of the stationary phase method to the multidimensional WKB approximation in quantum mechanics (as well as in optics), is related to the
Maslov index In mathematics, the Lagrangian Grassmannian is the smooth manifold of Lagrangian subspaces of a real symplectic vector space ''V''. Its dimension is ''n''(''n'' + 1) (where the dimension of ''V'' is ''2n''). It may be identified with the homogeneous ...
see, e.g., and .


The case of multiple non-degenerate saddle points

If the function has multiple isolated non-degenerate saddle points, i.e., :\nabla S \left (x^ \right ) = 0, \quad \det S''_ \left (x^ \right ) \neq 0, \quad x^ \in \Omega_x^, where :\left \_^K is an
open cover In mathematics, and more particularly in set theory, a cover (or covering) of a set X is a collection of subsets of X whose union is all of X. More formally, if C = \lbrace U_\alpha : \alpha \in A \rbrace is an indexed family of subsets U_\alph ...
of , then the calculation of the integral asymptotic is reduced to the case of a single saddle point by employing the
partition of unity In mathematics, a partition of unity of a topological space is a set of continuous functions from to the unit interval ,1such that for every point x\in X: * there is a neighbourhood of where all but a finite number of the functions of are 0, ...
. The
partition of unity In mathematics, a partition of unity of a topological space is a set of continuous functions from to the unit interval ,1such that for every point x\in X: * there is a neighbourhood of where all but a finite number of the functions of are 0, ...
allows us to construct a set of continuous functions such that :\begin \sum_^K \rho_k(x) &= 1, && \forall x \in \Omega_x, \\ \rho_k(x) &= 0 && \forall x \in \Omega_x\setminus \Omega_x^. \end Whence, :\int_ f(x) e^ dx \equiv \sum_^K \int_ \rho_k(x) f(x) e^ dx. Therefore as we have: :\sum_^K \int_ f(x) e^ dx = \left(\frac\right)^ \sum_^K e^ \left ( \det \left(-S_'' \left (x^ \right )\right) \right)^ f \left (x^ \right ), where equation (13) was utilized at the last stage, and the pre-exponential function at least must be continuous.


The other cases

When and \det S''_(z^0) = 0, the point is called a degenerate saddle point of a function . Calculating the asymptotic of : \int f(x) e^ dx, when is continuous, and has a degenerate saddle point, is a very rich problem, whose solution heavily relies on the catastrophe theory. Here, the catastrophe theory replaces the
Morse lemma In mathematics, specifically in differential topology, Morse theory enables one to analyze the topology of a manifold by studying differentiable functions on that manifold. According to the basic insights of Marston Morse, a typical differenti ...
, valid only in the non-degenerate case, to transform the function into one of the multitude of canonical representations. For further details see, e.g., and . Integrals with degenerate saddle points naturally appear in many applications including optical caustics and the multidimensional
WKB approximation In mathematical physics, the WKB approximation or WKB method is a method for finding approximate solutions to linear differential equations with spatially varying coefficients. It is typically used for a semiclassical calculation in quantum mecha ...
in quantum mechanics. The other cases such as, e.g., and/or are discontinuous or when an extremum of lies at the integration region's boundary, require special care (see, e.g., and ).


Extensions and generalizations

An extension of the steepest descent method is the so-called ''nonlinear stationary phase/steepest descent method''. Here, instead of integrals, one needs to evaluate asymptotically solutions of Riemann–Hilbert factorization problems. Given a contour ''C'' in the complex sphere, a function ''f'' defined on that contour and a special point, say infinity, one seeks a function ''M'' holomorphic away from the contour ''C'', with prescribed jump across ''C'', and with a given normalization at infinity. If ''f'' and hence ''M'' are matrices rather than scalars this is a problem that in general does not admit an explicit solution. An asymptotic evaluation is then possible along the lines of the linear stationary phase/steepest descent method. The idea is to reduce asymptotically the solution of the given Riemann–Hilbert problem to that of a simpler, explicitly solvable, Riemann–Hilbert problem. Cauchy's theorem is used to justify deformations of the jump contour. The nonlinear stationary phase was introduced by Deift and Zhou in 1993, based on earlier work of the Russian mathematician Alexander Its. A (properly speaking) nonlinear steepest descent method was introduced by Kamvissis, K. McLaughlin and P. Miller in 2003, based on previous work of Lax, Levermore, Deift, Venakides and Zhou. As in the linear case, steepest descent contours solve a min-max problem. In the nonlinear case they turn out to be "S-curves" (defined in a different context back in the 80s by Stahl, Gonchar and Rakhmanov). The nonlinear stationary phase/steepest descent method has applications to the theory of
soliton In mathematics and physics, a soliton or solitary wave is a self-reinforcing wave packet that maintains its shape while it propagates at a constant velocity. Solitons are caused by a cancellation of nonlinear and dispersive effects in the medium ...
equations and
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s,
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and
combinatorics Combinatorics is an area of mathematics primarily concerned with counting, both as a means and an end in obtaining results, and certain properties of finite structures. It is closely related to many other areas of mathematics and has many appl ...
.


See also

* Pearcey integral *
Stationary phase approximation In mathematics, the stationary phase approximation is a basic principle of asymptotic analysis, applying to the limit as k \to \infty . This method originates from the 19th century, and is due to George Gabriel Stokes and Lord Kelvin. It is closel ...
*
Laplace's method In mathematics, Laplace's method, named after Pierre-Simon Laplace, is a technique used to approximate integrals of the form :\int_a^b e^ \, dx, where f(x) is a twice-differentiable function, ''M'' is a large number, and the endpoints ''a'' an ...


Notes


References

* * English translation in *. *. *. * n Russian *. * (Unpublished note, reproduced in Riemann's collected papers.) * Reprinted in Gesammelte Abhandlungen, Vol. 1. Berlin: Springer-Verlag, 1966. **Translated in . *. * *{{Citation , last1=Wong , first1=R. , title=Asymptotic approximations of integrals , publisher=Academic Press , year=1989 . Asymptotic analysis Perturbation theory