Mellin transform
The Mellin transform is an integral transform in mathematics that maps a function f(t) defined on the positive real line to a function \phi(z) in the complex plane, defined by the formula \phi(z) = \int_0^\infty t^{z-1} f(t) \, dt for appropriate complex values z where the integral converges.[1] Its inverse is given by the contour integral f(t) = \frac{1}{2\pi i} \int_{c-i\infty}^{c+i\infty} t^{-z} \phi(z) \, dz, where c is chosen in the strip of analyticity.[1] This transform is particularly suited for analyzing functions with multiplicative or scaling properties, as it diagonalizes dilations unlike the shift-invariant Fourier transform.[2] Named after the Finnish mathematician Hjalmar Mellin (1854–1933), who systematically developed it in the late 19th century, the transform builds on earlier work in integral representations and has since become a cornerstone in complex analysis.[2] It is closely related to the two-sided Laplace transform, obtained by the substitution t = e^{-u}, which converts the Mellin transform of f(t) into the Laplace transform of f(e^{-u}).[2] Similarly, it connects to the Fourier transform through exponential changes of variables, making it a "multiplicative version" of these classical transforms.[3] Key properties include linearity, scaling (M\{f(at); z\} = a^{-z} \phi(z)), and differentiation rules involving the gamma function, such as M\{f'(t); z\} = -\frac{\Gamma(z)}{\Gamma(z-1)} \phi(z-1).[2] The transform's convergence typically requires f(t) to decay appropriately at both t \to 0^+ and t \to \infty, often analyzed via the strip of holomorphy in the complex plane.[1] Notable applications span multiple fields: in number theory, it facilitates proofs of the prime number theorem by relating arithmetic functions like the Riemann zeta function to its Mellin transform.[1] In statistics, it simplifies the study of distributions for products and quotients of independent positive random variables, yielding closed forms for densities like the Student's t- and F-distributions.[4] For partial differential equations, such as Laplace's equation in wedge domains, the Mellin transform reduces problems to ordinary differential equations via separation of variables in logarithmic coordinates.[5] In computer science, its scale invariance makes it essential for asymptotic analysis of algorithms, including divide-and-conquer recurrences and harmonic sums in probabilistic models.[3]Definition and Convergence
Definition
The Mellin transform of a function f(x) is defined as \mathcal{M}\{f\}(s) = \int_{0}^{\infty} f(x) \, x^{s-1} \, dx, where s \in \mathbb{C} is a complex variable.[1] This integral transform generalizes certain aspects of the Laplace and Fourier transforms by incorporating a multiplicative kernel x^{s-1}, making it particularly suited for problems involving scaling or homogeneity.[6] The inverse Mellin transform recovers the original function via the contour integral f(x) = \frac{1}{2\pi i} \int_{c - i\infty}^{c + i\infty} \mathcal{M}\{f\}(s) \, x^{-s} \, ds, where the path of integration is a vertical line \operatorname{Re}(s) = c in the complex plane.[6] This inversion formula relies on the residue theorem and analytic properties of the transform, ensuring uniqueness under appropriate conditions.[1] Common notation for the Mellin transform includes \mathcal{M}\{f\}(s) or M_f(s), with the inverse often denoted similarly.[1] In related contexts, such as the theory of special functions, the transform connects directly to the gamma function \Gamma(s); for instance, the Mellin transform of e^{-x} yields \Gamma(s) for \operatorname{Re}(s) > 0, highlighting its role in representing factorial-like generalizations.[7] The Mellin transform was introduced by the Finnish mathematician Robert Hjalmar Mellin in 1897, initially as a tool for analyzing integral equations and the theories of the gamma and hypergeometric functions.[8]Fundamental Strip and Analytic Continuation
The convergence of the Mellin transform M\{f\}(s) = \int_0^\infty f(x) x^{s-1} \, dx is analyzed in the complex s-plane, where s = \sigma + i \tau with \sigma = \operatorname{Re}(s) and \tau = \operatorname{Im}(s). The integral converges absolutely in a vertical strip defined by a < \sigma < b, known as the fundamental strip \langle a, b \rangle, which is the maximal such open strip. This strip is determined by the asymptotic behavior of f(x) at the endpoints of the integration interval. Specifically, near x \to 0^+, if f(x) = O(x^{-\alpha}) for some \alpha \in \mathbb{R}, the condition for convergence of the integral over (0,1] requires \sigma > \alpha, setting the left boundary a = \alpha. Similarly, as x \to \infty, if f(x) = O(x^{-\beta}) for \beta > 0, convergence over [1, \infty) holds for \sigma < \beta, establishing the right boundary b = \beta. Provided a < b, the Mellin transform exists and is analytic throughout this fundamental strip.[9][10] The boundaries of the fundamental strip arise directly from the integrability conditions split across the near-origin and far-origin behaviors of f. For the portion near zero, the integral \int_0^1 |f(x)| x^{\sigma - 1} \, dx converges when the exponent ensures the power-law decay dominates, yielding the lower limit on \sigma. At infinity, \int_1^\infty |f(x)| x^{\sigma - 1} \, dx imposes an upper limit on \sigma to counteract the growth or decay of f(x). If f is piecewise continuous and of bounded variation in finite intervals, or satisfies milder local integrability conditions, the strip remains well-defined as long as the global asymptotics permit a < b. Outside this strip, the integral may diverge, but the transform can still be meaningfully extended.[9][10] Within the fundamental strip, M\{f\}(s) is holomorphic, reflecting the analytic dependence of the integral on the parameter s. Beyond the strip, analytic continuation extends the domain of definition, typically resulting in a meromorphic function in larger regions of the complex plane. This continuation is achieved through methods such as functional equations relating values at different points or contour deformations via the residue theorem, allowing evaluation in strips where the original integral diverges. The meromorphic nature implies that singularities are isolated poles, with the transform analytic elsewhere except at these points.[10][11] Singularities in the continued Mellin transform often manifest as poles whose locations and orders correspond to the asymptotic expansions of f(x) at $0^+ or \infty. For instance, a term x^c (\log x)^k in the expansion of f(x) near zero induces a pole of order k+1 at s = -c, with the residue capturing the coefficient of that term. Such poles frequently arise from factors involving the gamma function in explicit representations, where simple poles occur at non-positive integers due to \Gamma(s). These residues play a key role in inversion formulas and asymptotic approximations, enabling the recovery of f(x) via contour integrals that encircle the poles.[9][10][11]Relations to Other Transforms
Connection to Laplace and Fourier Transforms
The Mellin transform is closely related to the two-sided Laplace transform through a logarithmic change of variables. Specifically, substituting t = -\log x (so x = e^{-t} and dx = -e^{-t} dt) into the Mellin transform integral M\{f\}(s) = \int_0^\infty f(x) x^{s-1} \, dx yields M\{f\}(s) = \int_{-\infty}^\infty f(e^{-t}) e^{-s t} \, dt, which is the two-sided Laplace transform \mathcal{L}\{g\}(s) of the function g(t) = f(e^{-t}).[9] This equivalence holds in the fundamental strip where both transforms converge, determined by the asymptotic behavior of f(x) as x \to 0^+ and x \to \infty.[9] The relation extends to the Fourier transform by viewing the Mellin transform as the Fourier transform on the multiplicative group of positive real numbers under the Haar measure dx/x. With the substitution x = e^u (so u = \log x and dx = e^u du), the Mellin transform becomes M\{f\}(s) = \int_{-\infty}^\infty f(e^u) e^{s u} \, du, which corresponds to the Fourier transform of h(u) = f(e^u) evaluated at frequency -s/i (depending on the Fourier convention).[12] This perspective highlights the Mellin transform's role in analyzing scale-invariant problems, analogous to the Fourier transform's treatment of translation-invariant ones.[12] Extensions to two-sided transforms further link these: the bilateral Mellin transform for functions supported on (0, \infty) maps directly to the bilateral Laplace transform via the same logarithmic substitution, facilitating analysis on the full real line.[9]Mellin-Barnes Integral Representation
The Mellin-Barnes integral representation expresses certain special functions as contour integrals in the complex plane, where the integrand consists of a product or ratio of Gamma functions multiplied by a power of the variable. This form arises naturally as the inverse Mellin transform of the Mellin transform of a function, providing a powerful tool for analytic continuation and representation of functions beyond their power series domains. Specifically, for functions like the generalized hypergeometric series, the representation takes the form f(z) = \frac{1}{2\pi i} \int_{\gamma - i\infty}^{\gamma + i\infty} M(s) z^{-s} \, ds, where M(s) is a meromorphic function typically expressed as a ratio of products of Gamma functions, such as \prod \Gamma(a_j + A_j s) / \prod \Gamma(b_k + B_k s), with positive coefficients A_j, B_k ensuring convergence properties.[13] The contour of integration is chosen as a vertical line \operatorname{Re}(s) = \gamma in the fundamental strip of analyticity, where \gamma is selected to lie between the leftmost and rightmost poles of M(s), ensuring the integral converges absolutely for | \arg z | < \pi/2. In cases where poles lie on the line, the contour may be indented with small semicircles to avoid them, forming a Hankel-type path that separates poles of the numerator Gammas (typically to the left) from those of the denominator (to the right). This setup allows the integral to enclose residues corresponding to series expansions when deformed appropriately.[14] These representations are particularly valuable for asymptotic analysis, as the Mellin-Barnes form facilitates the application of the saddle-point method to evaluate the integral for large |z|. By deforming the contour to pass through saddle points of the phase function \log M(s) - s \log z, one obtains uniform asymptotic expansions that capture the leading behavior and higher-order terms, often superior to direct methods for functions with branch points or Stokes lines.[15] The Mellin-Barnes integral is synonymous with the Barnes integral, introduced by E. W. Barnes in his work on multiple Gamma functions, and extends to the general Barnes integral with multiple complex parameters. In its most general form, involving products of multiple Gamma factors, it defines the Meijer G-function, a unifying framework for many transcendental functions, where the integral G_{p,q}^{m,n} \left( z \,\middle|\, \begin{matrix} a_1, \dots, a_p \\ b_1, \dots, b_q \end{matrix} \right) = \frac{1}{2\pi i} \int_L \frac{\prod_{j=1}^m \Gamma(b_j + s) \prod_{j=1}^n \Gamma(1 - a_j - s)}{\prod_{j=m+1}^q \Gamma(1 - b_j - s) \prod_{j=n+1}^p \Gamma(a_j + s)} z^{-s} \, ds encodes the structure with a suitable contour L separating pole clusters.[14]Examples of Mellin Transforms
Transforms of Basic Functions
The Mellin transforms of elementary functions often yield closed-form expressions involving the gamma function or other special functions, valid within specific vertical strips in the complex plane where the defining integral converges absolutely. These transforms are fundamental for understanding the analytic continuation and properties of the Mellin transform, as the location and nature of singularities in the transform reveal asymptotic behaviors of the original function near zero and infinity.[6] For the power function f(x) = x^{\alpha}, the integral \int_0^\infty x^{s-1} x^{\alpha} \, dx diverges in the classical sense, but in the distributional framework, its Mellin transform is given by \delta(s + \alpha), where \delta denotes the Dirac delta distribution. This holds over the entire complex plane, reflecting the homogeneous nature of power functions under scaling.[5] The exponential function f(x) = e^{-x} has the Mellin transform \Gamma(s), where \Gamma is the gamma function, converging for \operatorname{Re}(s) > 0. This is a direct consequence of the integral representation of the gamma function itself. For the generalized Gaussian f(x) = e^{-x^{\beta}} with \beta > 0, the Mellin transform is \frac{1}{\beta} \Gamma\left(\frac{s}{\beta}\right), valid for \operatorname{Re}(s) > 0. The case \beta = 2 simplifies to \frac{1}{2} \Gamma\left(\frac{s}{2}\right), obtained via the substitution u = x^{\beta}. Polynomials, being finite linear combinations of power functions, have Mellin transforms that are sums of Dirac delta distributions; for the monomial f(x) = x^{k} with nonnegative integer k, it is \delta(s + k) in the distributional sense. Alternatively, for regularized versions like moments of exponentials, such as M\{x^{k} e^{-x}\}(s) = \frac{\Gamma(s + k)}{\Gamma(s)} for \operatorname{Re}(s) > 0, these can be derived by repeated differentiation of the gamma function transform, since differentiation under the integral corresponds to multiplication by powers in the transform domain.[5] A representative rational function, f(x) = \frac{1}{1 + x}, has Mellin transform \pi \csc(\pi s), converging in the strip $0 < \operatorname{Re}(s) < 1. This result follows from the beta function representation after substitution t = x/(1+x).| Function f(x) | Mellin Transform M\{f\}(s) | Convergence Strip |
|---|---|---|
| x^{\alpha} | \delta(s + \alpha) | Entire plane (distributional) |
| e^{-x} | \Gamma(s) | \operatorname{Re}(s) > 0 |
| e^{-x^{\beta}} (\beta > 0) | \frac{1}{\beta} \Gamma\left(\frac{s}{\beta}\right) | \operatorname{Re}(s) > 0 |
| x^{k} (k \in \mathbb{N}_0) | \delta(s + k) | Entire plane (distributional) |
| \frac{1}{1 + x} | \pi \csc(\pi s) | $0 < \operatorname{Re}(s) < 1 |
Transforms Involving Special Functions
The Mellin transform provides integral representations for several special functions, particularly through connections to theta functions, Dirichlet series, and generating functions for hypergeometric series. One prominent example is the relation to the Riemann zeta function via the Jacobi theta function, defined as \theta(x) = \sum_{n=-\infty}^{\infty} e^{-\pi n^2 x} for x > 0. The Mellin transform of \theta(x) - 1 yields \int_0^\infty (\theta(x) - 1) x^{s/2 - 1} \, dx = 2 \pi^{-s/2} \Gamma(s/2) \zeta(s), valid for \Re(s) > 1, where the subtraction of 1 ensures convergence at the lower limit. This formula links the oscillatory behavior of the theta function to the analytic properties of the zeta function, facilitating its meromorphic continuation via the functional equation derived from the Poisson summation formula applied to \theta(x). The strip of convergence \Re(s) > 1 corresponds to the absolute convergence of the zeta function's Dirichlet series representation.[16][17] Dirichlet series arise naturally as Mellin transforms of power series generating functions. Consider f(x) = \sum_{n=0}^\infty a_n x^n for $0 < x < 1, where the coefficients a_n grow sufficiently slowly to ensure convergence. The Mellin transform is M\{f\}(s) = \int_0^1 f(x) x^{s-1} \, dx = \sum_{n=0}^\infty a_n \int_0^1 x^{n + s - 1} \, dx = \sum_{n=0}^\infty \frac{a_n}{n + s}, converging in half-planes determined by the asymptotic growth of a_n, typically \Re(s) > -\sigma_0 for some \sigma_0 \geq 0 depending on the series. This representation interchanges summation and integration under suitable conditions, such as uniform convergence on compact subsets of the unit disk, and extends to more general Dirichlet series \sum a_n n^{-s} via logarithmic substitution x = e^{-t}.[10] Power series generating functions for special functions, such as those appearing in hypergeometric series, have Mellin transforms expressible in terms of gamma functions. For instance, the binomial expansion (1 - x)^{-a} = \sum_{n=0}^\infty \binom{n + a - 1}{n} x^n for $0 < x < 1 and \Re(a) > 0 has Mellin transform \int_0^1 (1 - x)^{-a} x^{s - 1} \, dx = B(s, a) = \frac{\Gamma(s) \Gamma(a)}{\Gamma(s + a)}, valid for \Re(s) > 0 and \Re(a) > 0. This beta function integral serves as a building block for hypergeometric functions, as the hypergeometric {}_2F_1(a, b; c; x) admits a Mellin-Barnes contour integral representation involving products of gamma functions, linking power series expansions to meromorphic continuations in the complex plane.[5] A specific application of the Mellin transform to alternating series is the Cahen-Mellin integral, which provides representations for sums like \sum_{n=0}^\infty \frac{(-1)^n}{n + s}. This sum equals \int_0^1 \frac{x^{s-1}}{1 + x} \, dx for \Re(s) > 0, obtained by term-by-term integration of the geometric series $1/(1 + x) = \sum_{n=0}^\infty (-1)^n x^n. Extending to the full positive real line gives the key identity \int_0^\infty \frac{x^{s-1}}{1 + x} \, dx = \frac{\pi}{\sin(\pi s)}, for $0 < \Re(s) < 1, derived via contour integration or residue theorem. The original alternating sum relates to this via the decomposition of the integral over (0,1) and (1,\infty), with convergence in half-planes \Re(s) > 0 adjusted for the pole structure. For zeta-related contexts, such representations hold in strips like \Re(s) > 1.[17]Properties
Linearity and Differentiation Under the Integral
The Mellin transform is a linear operator. For complex constants \alpha and \beta, and functions f(x) and g(x) for which the respective transforms exist in a common vertical strip of the complex plane, the following holds: \mathcal{M}\{\alpha f + \beta g\}(s) = \alpha \mathcal{M}\{f\}(s) + \beta \mathcal{M}\{g\}(s). This property arises directly from the linearity of the defining integral \mathcal{M}\{f\}(s) = \int_0^\infty f(x) x^{s-1} \, dx.[18] Under suitable regularity conditions on f(x) that permit differentiation under the integral sign—such as absolute integrability of f(x) x^{s-1} \log x in the fundamental strip—the derivative of the Mellin transform with respect to the complex parameter s satisfies \frac{d}{ds} \mathcal{M}\{f\}(s) = \int_0^\infty f(x) x^{s-1} \log x \, dx = \mathcal{M}\{f(x) \log x\}(s). This relation links the Mellin transform to functions modified by a logarithmic factor and is often applied in asymptotic analysis and the evaluation of integrals involving parameters.[19] The Mellin transform also accommodates differentiation of the original function via integration by parts. Assuming boundary conditions where the relevant boundary terms vanish (e.g., f(x) \to 0 sufficiently rapidly as x \to 0^+ and x \to \infty), the transform of the derivative is \mathcal{M}\left\{\frac{d}{dx} f(x)\right\}(s) = -(s-1) \mathcal{M}\{f\}(s-1), provided the transforms exist in the appropriate shifted strips. This property, derived from partial integration on the defining integral, facilitates the solution of differential equations in Mellin space.[18] A key feature related to scaling is the transform's response to argument dilation: for a > 0, \mathcal{M}\{f(ax)\}(s) = a^{-s} \mathcal{M}\{f\}(s). This follows from the substitution u = ax in the integral, highlighting the transform's utility in problems with multiplicative structure and scale invariance.Multiplication and Convolution Theorems
The Mellin transform exhibits a convolution theorem analogous to those in Fourier and Laplace analysis, but adapted to the multiplicative structure of the positive real line. Specifically, the Mellin convolution of two functions f and g is defined as (f \ast g)(x) = \int_0^\infty f(t) \, g\left(\frac{x}{t}\right) \frac{dt}{t}, provided the integral converges appropriately in the fundamental strips of f and g. The Mellin transform of this convolution is the pointwise product of the individual transforms: \mathcal{M}\{f \ast g\}(s) = \mathcal{M}\{f\}(s) \, \mathcal{M}\{g\}(s), where the convergence holds for \operatorname{Re}(s) in the intersection of the respective fundamental strips.[20][5] This property follows from the integral representation and Fubini's theorem under suitable analyticity conditions.[21] The dual property, known as the multiplication theorem, addresses the transform of a product of functions. For functions f and g, the Mellin transform of their product f(x) g(x) (adjusted for the kernel's homogeneity) yields a convolution in the transform domain: \mathcal{M}\{f \cdot g\}(s) = \frac{1}{2\pi i} \int_{c - i\infty}^{c + i\infty} \mathcal{M}\{f\}(s - w) \, \mathcal{M}\{g\}(w) \, dw, where the vertical contour \operatorname{Re}(w) = c is chosen within the intersection of the strips where both transforms are analytic, ensuring absolute convergence.[5] This integral arises from substituting the inverse Mellin formula for one function into the direct transform of the product and interchanging orders via the residue theorem or analytic continuation.[21] These theorems reflect the Mellin transform's role in diagonalizing operations on the multiplicative group (\mathbb{R}_+, \times). The transform effectively Fourier-analyzes dilations on this group, converting the Mellin convolution—invariant under group multiplication—into multiplication in the s-domain, thereby simplifying problems involving scale-invariant structures.[21] In practice, the convolution theorem facilitates solving Mellin-type integral equations of the form (f \ast k)(x) = h(x), where k is a known kernel. Taking Mellin transforms yields \mathcal{M}\{f\}(s) \, \mathcal{M}\{k\}(s) = \mathcal{M}\{h\}(s), so \mathcal{M}\{f\}(s) = \mathcal{M}\{h\}(s) / \mathcal{M}\{k\}(s) (assuming \mathcal{M}\{k\}(s) \neq 0 and analytic continuation where needed), followed by inversion to recover f. This approach is particularly effective for equations arising in scaling problems, such as those in asymptotic analysis or singular integrals.[5][22]Advanced Theorems
Parseval's and Plancherel's Theorems
Parseval's theorem for the Mellin transform relates the integral of the product of two functions over the positive real line to an integral involving their Mellin transforms along a vertical contour in the complex plane. For suitable functions f and g analytic in a common strip of convergence, the theorem asserts that \int_0^\infty f(x) g(x) \, dx = \frac{1}{2\pi i} \int_{c-i\infty}^{c+i\infty} \hat{f}(s) \hat{g}(1-s) \, ds, where \hat{f}(s) and \hat{g}(s) denote the Mellin transforms of f and g, respectively (assuming real-valued functions), and c lies in the intersection of the fundamental strips. [23] This relation holds under conditions ensuring absolute integrability or square-integrability in the respective domains, often requiring f, g \in L^2(\mathbb{R}^+, dx) with appropriate decay at the boundaries. [23] Plancherel's theorem extends this to the preservation of norms for square-integrable functions, establishing that the Mellin transform acts as an isometry up to a constant factor on suitable L^2 spaces. Specifically, for f \in L^2(\mathbb{R}^+, dx) with Mellin transform analytic in a vertical strip containing \sigma, \|f\|_2^2 = \int_0^\infty |f(x)|^2 \, dx = \frac{1}{2\pi} \int_{-\infty}^\infty |\hat{f}(\sigma + i\tau)|^2 \, d\tau, where the line \operatorname{Re}(s) = \sigma is fixed within the strip of convergence. [24] This formula confirms the unitarity of the Mellin transform (up to the $1/(2\pi) factor) when mapping between L^2(\mathbb{R}^+, dx) and the corresponding L^2 space along the imaginary axis shifted by \sigma, via the logarithmic substitution x = e^u with normalization h(u) = f(e^u) e^{u/2}. [25] For the weighted space L^2(\mathbb{R}^+, dx/x), see the unitary structure below. The inner product preservation implied by these theorems underscores the Mellin transform's role as a unitary operator (modulo scaling) on appropriate Hilbert spaces, facilitating energy conservation in applications like signal processing and harmonic analysis. A sketch of the proof relies on the logarithmic change of variables x = e^u, which maps the Mellin transform to a Fourier transform of the rescaled function h(u) = f(e^u) e^{u/2}; applying the standard Plancherel theorem for the Fourier transform on L^2(\mathbb{R}, du) then yields the result after substitution back to the original variables. [25]Unitary Structure on L2 Spaces
The Hilbert space L^2((0, \infty), dx/x) consists of measurable functions f: (0, \infty) \to \mathbb{C} such that \int_0^\infty |f(x)|^2 \, dx/x < \infty, equipped with the inner product \langle f, g \rangle = \int_0^\infty f(x) \overline{g(x)} \, dx/x.[26] This space is invariant under multiplication by positive constants, reflecting the structure of the multiplicative group (0, \infty) under which the measure dx/x is the unique (up to scalar) Haar measure, ensuring left-invariance: for a > 0, \int_0^\infty f(ax) \, dx/x = \int_0^\infty f(x) \, dx/x.[26] The weight dx/x thus endows the space with a group-theoretic foundation, analogous to Lebesgue measure dx for the additive group \mathbb{R}.[5] The Mellin transform \mathcal{M} f(s) = \int_0^\infty f(x) x^{s-1} \, dx (often normalized with the measure incorporated as \int_0^\infty f(x) x^{s-1} \, dx/x) acts as an isometry from L^2((0, \infty), dx/x) to L^2(\mathbb{R}, d\tau/(2\pi)), where the codomain is identified with functions on the vertical line \operatorname{Re}(s) = 1/2 via s = 1/2 + i\tau with \tau \in \mathbb{R}.[5] Specifically, for f \in L^2((0, \infty), dx/x), \int_0^\infty |f(x)|^2 \, \frac{dx}{x} = \frac{1}{2\pi} \int_{-\infty}^\infty |\mathcal{M} f(1/2 + i\tau)|^2 \, d\tau, establishing the L^2-preservation.[27] This mapping is unitary, meaning it is a bijective isometry with a bounded inverse given by the inverse Mellin transform f(x) = \frac{1}{2\pi i} \int_{1/2 - i\infty}^{1/2 + i\infty} \mathcal{M} f(s) x^{-s} \, ds, which recovers f almost everywhere.[5] The unitarity follows from the substitution x = e^u, which conjugates the Mellin transform to the Fourier transform on L^2(\mathbb{R}, du), a known unitary operator.[26] The role of the measure dx/x is pivotal in preserving the multiplicative group structure, where the characters x^{it} (for t \in \mathbb{R}) diagonalize the dilation operators D_a f(x) = a^{-1/2} f(ax) (unitarily normalized), leading to the spectral decomposition via the Mellin transform.[5] This framework highlights the Mellin transform as the Fourier analysis tool for scale-invariant problems on the positive reals. Extensions of this unitary structure include mappings to Hardy spaces H^2 in vertical strips of the complex plane, where the Mellin transform of functions in weighted L^2 subspaces on (0, \infty) yields analytic functions bounded in the half-plane \operatorname{Re}(s) > 1/2, with boundary values in L^2 on the critical line.[28] Additionally, the Mellin-Fourier isomorphism explicitly links the structure to the standard Fourier transform via the logarithmic change of variables, facilitating extensions to broader function classes like tempered distributions on the multiplicative group.[26]Applications
In Number Theory and Zeta Functions
The Mellin transform plays a pivotal role in deriving the functional equation of the Riemann zeta function through the inversion formula for the theta function. The Jacobi theta function \theta(t) = \sum_{n \in \mathbb{Z}} e^{-\pi n^2 t} for \operatorname{Re}(t) > 0 satisfies the transformation law \theta(1/t) = \sqrt{t} \, \theta(t), obtained via Poisson summation. Applying the Mellin transform to \theta(t), specifically \phi(s) = \int_1^\infty (\theta(t) - 1) t^{s/2 - 1} \, dt + \int_0^1 (\theta(t) - t^{-1/2}) t^{s/2 - 1} \, dt, yields an entire function that satisfies \phi(s) = \phi(1 - s). This symmetry, combined with the relation \pi^{-s/2} \Gamma(s/2) \zeta(s) = \frac{1}{s-1} + \frac{1}{1-s} + \phi(s)/2, provides the analytic continuation of \zeta(s) to the complex plane (except for a simple pole at s=1) and establishes the functional equation \Lambda(s) = \pi^{-s/2} \Gamma(s/2) \zeta(s) = \Lambda(1 - s).[29][30] In analytic number theory, the Mellin transform connects the pole of \zeta(s) at s=1 to asymptotic estimates in the prime number theorem. The logarithmic derivative \zeta'(s)/\zeta(s) admits a Mellin transform representation as \zeta'(s)/\zeta(s) = -\sum_p \log p \sum_{k=1}^\infty p^{-k s} / (1 - p^{-k s}), which relates to the Chebyshev function \psi(x) = \sum_{p^k \leq x} \log p. By expressing \log \zeta(s) as the Mellin transform s \int_1^\infty J(x) x^{-s-1} \, dx where J(x) = \sum_{k=1}^\infty \pi(x^{1/k})/k, the residue at the pole s=1 (of order 1 with residue 1) implies \psi(x) \sim x via Tauberian theorems like Ikehara's. This yields the prime number theorem \pi(x) \sim x / \log x, with error terms refined by zero-free regions near \operatorname{Re}(s)=1.[31] The approach extends to Dirichlet L-functions L(s, \chi) = \sum_{n=1}^\infty \chi(n) n^{-s} for a primitive Dirichlet character \chi modulo q, using Mellin transforms of associated theta functions. Define \theta_\chi(x) = \sum_{n=1}^\infty \chi(n) e^{-\pi n^2 x} (adjusted for parity), whose Mellin transform gives \pi^{-(s+a)/2} \Gamma((s+a)/2) L(s, \chi) = \int_0^\infty \theta_\chi(x) x^{(s+a)/2 - 1} \, dx, where a = 0 or 1 depending on \chi. Splitting the integral and applying Poisson summation to the part from 0 to 1, leveraging the character's Gauss sum, produces the functional equation q^{s/2} (2\pi)^{-s} \Gamma(s) L(s, \chi) = \epsilon(\chi) q^{(1-s)/2} (2\pi)^{s-1} \Gamma(1-s) L(1-s, \overline{\chi}) (up to parity adjustments), enabling meromorphic continuation and revealing non-vanishing properties at s=1 for non-principal \chi. This generalizes the zeta case and underpins class number formulas and Artin reciprocity.[32] The Selberg trace formula further illustrates the Mellin transform's utility in linking spectral theory to number-theoretic sums over arithmetic groups like \mathrm{PSL}_2(\mathbb{Z}). On the hyperbolic plane, the trace formula equates the spectral side \sum_j h(1/2 + i r_j) + \frac{1}{4\pi} \int_{-\infty}^\infty h(1/2 + i t) \frac{t \tanh(\pi t)}{2} \, dt (summing over Laplacian eigenvalues \lambda_j = 1/4 + r_j^2) to the geometric side involving lengths of closed geodesics. Here, h(s) is the Mellin transform of a test function g(y) = \int K(x,y) \, dx on the upper half-plane, facilitating the inversion and Plancherel measure \frac{t \tanh(\pi t)}{2\pi} dt for the continuous spectrum. This framework connects eigenvalue distributions to prime-like sums in the fundamental domain, with applications to subconvexity bounds for L-functions via spectral gaps.[33]In Probability and Moment-Generating Functions
In probability theory, the Mellin transform serves as a moment-generating tool for positive random variables, capturing their power moments through evaluation at integer points. For a non-negative random variable X with probability density function f(x) supported on (0, \infty), the Mellin transform is given by M(s) = \int_0^\infty x^{s-1} f(x) \, dx = \mathbb{E}[X^{s-1}], where the integral converges for s in a suitable strip of the complex plane depending on the distribution's tail behavior.[34] Specifically, for positive integers k, M(k+1) = \mathbb{E}[X^k] yields the raw moments, providing a multiplicative analog to the classical moment-generating function M_X(t) = \mathbb{E}[e^{tX}] but adapted to the positive reals and power laws rather than exponentials. This property facilitates the study of distributions with heavy tails, where ordinary moments may diverge, by analytically continuing M(s) beyond integers.[35] The Mellin transform also connects deeply with log-stable distributions, where \log X follows a stable law. In such cases, the transform links directly to the characteristic function of \log X via the substitution u = \log x, recasting the Mellin integral as a Fourier transform over the logarithmic scale. Precisely, M(1 + it) = \mathbb{E}[X^{it}] = \phi_{\log X}(t), where \phi_{\log X}(t) denotes the characteristic function of \log X. This relationship is particularly valuable for deriving densities and stability parameters in multiplicative processes, such as those in financial modeling or physics, where log-stable laws model phenomena like turbulence or income distributions.[36] Regarding cumulants, the logarithm of the Mellin transform generates the cumulants of \log X. The function \log M(1 + z) admits a series expansion whose coefficients are the cumulants \kappa_n of \log X, via \log M(1 + z) = \sum_{n=1}^\infty \kappa_n \frac{z^n}{n!}, offering insights into independence, additivity, and asymptotic behavior under convolution. This logarithmic cumulant approach, rooted in the Mellin framework, enhances robustness against outliers compared to direct moment methods, as it emphasizes relative scales and is widely applied in robust estimation for skewed or heavy-tailed data.[37] Representative examples illustrate these concepts for common distributions. The Pareto distribution, with shape \alpha > 0 and scale 1 (density f(x) = \alpha x^{-\alpha-1} for x \geq 1), has Mellin transform M(s) = \frac{\alpha}{\alpha - s + 1}, \quad \Re(s) < \alpha + 1, directly implying moments \mathbb{E}[X^k] = \alpha / (\alpha - k) for k < \alpha, which highlights the distribution's power-law tails and finite moments only below the shape parameter.[38] Similarly, the lognormal distribution, where \log X \sim \mathcal{N}(\mu, \sigma^2), yields M(s) = \exp\left( (s-1)\mu + \frac{(s-1)^2 \sigma^2}{2} \right), mirroring the moment-generating function of the underlying normal and enabling exact computation of all moments while underscoring the distribution's log-convexity and applications in modeling multiplicative noise.[39]In Solving Differential Equations
The Mellin transform is particularly effective for solving partial differential equations (PDEs) and ordinary differential equations (ODEs) that exhibit scale invariance or multiplicative structure, such as those arising in radial or cylindrical coordinates. By transforming the radial variable r into the complex parameter s, the transform converts differentiation with respect to r into algebraic operations involving s, simplifying equations like the Euler-Cauchy type that commonly appear in separated variables solutions.[5] In cylindrical coordinates, the Mellin transform facilitates the solution of the radial Laplace equation, \nabla^2 u = 0, especially for problems with azimuthal dependence handled via Fourier series. Assuming separation of variables u(r, \theta) = R(r) \Theta(\theta), the angular part yields \Theta'' + m^2 \Theta = 0 for integer m, leading to the radial Euler equation r^2 R'' + r R' - m^2 R = 0. Applying the Mellin transform \mathcal{M}\{R(r)\}(s) = \int_0^\infty r^{s-1} R(r) \, dr reduces this to the algebraic relation s^2 \hat{R}(s) - m^2 \hat{R}(s) = 0, with solutions \hat{R}(s) \propto s^2 - m^2 = 0, corresponding to power-law behaviors R(r) \propto r^{\pm m} upon inversion. For full cylindrical problems without axial dependence (effectively 2D polar), the transform in r combined with Fourier in \theta yields Bessel functions through the inverse, as the Mellin contour integral evaluates to modified Bessel functions for certain boundary geometries.[40] For Sturm-Liouville problems, particularly those with Euler-Cauchy operators, the Mellin transform maps the differential operator L = \sum_{k=0}^n a_k (r \frac{d}{dr})^k to a polynomial in s: \hat{L}(s) = \sum_{k=0}^n a_k (-s)^k \hat{u}(s) = \hat{g}(s). This algebraic form allows solving for \hat{u}(s) = \hat{g}(s) / \hat{L}(s), with the inverse Mellin transform providing the solution in the spatial domain, provided the poles of $1/\hat{L}(s) are analyzed within the fundamental strip of analyticity. Such reductions are standard for self-adjoint problems on (0, \infty) with weight r^{\alpha}, where boundary conditions at r=0 and r=\infty determine the contour shift.[5] A representative example is the radial heat equation in cylindrical coordinates, u_t = k (u_{rr} + \frac{1}{r} u_r), assuming azimuthal symmetry for simplicity. Applying the Mellin transform in r, \hat{u}(s, t) = \int_0^\infty r^{s-1} u(r, t) \, dr, transforms the spatial operator to k s^2 \hat{u}(s, t), yielding the ODE \partial_t \hat{u} = -k s^2 \hat{u}, whose solution is \hat{u}(s, t) = \hat{u}(s, 0) e^{-k s^2 t}. Inverting via the Mellin contour gives u(r, t), effectively solving a diffusion equation in the logarithmic variable \log r, where the transform acts as a Fourier representation on the multiplicative group. For wedge domains, this approach extends to Robin boundary conditions by parameterizing angular modes and using weighted Sobolev spaces defined via Mellin symbols for regularity analysis.[41] In boundary value problems, the Mellin transform enables matching conditions across domains by exploiting the strip of convergence in the complex s-plane, where initial or boundary data are incorporated via residue calculus or contour deformation. For instance, in a wedge with Dirichlet data on the rays, the transform of the boundary function determines the coefficients, and the inverse along a suitable Bromwich contour resolves discontinuities at interfaces like r = a, producing series solutions convergent in subdomains. This method avoids singularities at the origin inherent in radial coordinates and aligns with convolution theorems for composite problems.[40]Selected Mellin Transforms
Table of Common Transforms
The Mellin transform, defined as M\{f\}(s) = \int_0^\infty x^{s-1} f(x) \, dx, is typically unilateral for functions supported on (0, \infty). The table below summarizes common examples, with convergence strips indicated. These are drawn from standard integral representations in mathematical analysis.| f(x) | M\{f\}(s) | Convergence Strip |
|---|---|---|
| e^{-x} | \Gamma(s) | \Re(s) > 0 |
| x^{a-1} (1 + x)^{-b} | \frac{\Gamma(s + a - 1) \Gamma(b - s - a + 1)}{\Gamma(b)} | $1 - a < \Re(s) < b - a + 1, \Re(a) > 0, \Re(b - a) > 0 |
| e^{-x^2} | \frac{1}{2} \Gamma\left(\frac{s}{2}\right) | \Re(s) > 0 |
| \frac{1}{1 + x} | \frac{\pi}{\sin(\pi s)} | $0 < \Re(s) < 1 |
| x^{a-1} e^{-x} | \Gamma(a + s) | \Re(a + s) > 0 |