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Bochner's theorem

Bochner's theorem is a fundamental result in and that characterizes continuous positive definite functions on . Specifically, it states that a \phi: \mathbb{R}^n \to \mathbb{C} is continuous and positive definite—meaning that for any finite set of points x_1, \dots, x_m \in \mathbb{R}^n and complex coefficients c_1, \dots, c_m \in \mathbb{C}, the inequality \sum_{j=1}^m \sum_{k=1}^m \overline{c_j} \phi(x_j - x_k) c_k \geq 0 holds— there exists a unique finite nonnegative \mu on \mathbb{R}^n such that \phi(x) = \int_{\mathbb{R}^n} e^{i \langle x, \xi \rangle} \, d\mu(\xi) for all x \in \mathbb{R}^n. Named after the mathematician (1899–1982), the theorem appeared in his 1932 Vorlesungen über Fouriersche e, where it provided a key representation linking to Fourier-Stieltjes transforms. This work built on earlier developments in representations and marked a significant advancement in understanding the structure of positive definite functions beyond finite-dimensional settings. The theorem has broad implications across mathematics, particularly in probability theory, where it implies that the characteristic function of any random variable—defined as \phi(t) = \mathbb{E}[e^{i \langle t, X \rangle}]—is continuous and positive definite, and conversely, every continuous positive definite function with \phi(0) = 1 arises as the characteristic function of a unique probability measure on \mathbb{R}^n. In harmonic analysis, it extends to more general locally compact abelian groups via Pontryagin duality and has connections to the spectral theorem for self-adjoint operators on Hilbert spaces. Applications also appear in approximation theory, kernel methods in machine learning, and the study of stationary processes, where positive definite functions serve as valid covariance kernels.

Mathematical Foundations

Positive-definite functions

In the context of , a f: G \to \mathbb{C} on a G is defined as positive-definite if, for every finite collection of points g_1, \dots, g_n \in G and complex coefficients c_1, \dots, c_n \in \mathbb{C}, \sum_{j=1}^n \sum_{k=1}^n c_j \overline{c_k} f(g_j^{-1} g_k) \geq 0. This condition ensures that the matrix (f(g_j^{-1} g_k)) is positive semi-definite for any such finite set. Positive-definite functions are often normalized by requiring f(e) = 1, where e denotes the of G, which aligns with their role in representing expectations or inner products in associated Hilbert spaces. Examples of positive-definite functions include the constant function f(g) = 1 for all g \in G, which trivially satisfies the inequality. On abelian groups, continuous characters \xi: G \to \mathbb{C} (homomorphisms into the unit circle) are positive-definite, since the quadratic form is \left| \sum_{j=1}^n c_j \xi(g_j) \right|^2 \geq 0. More generally, diagonal matrix coefficients \langle \pi(g) \xi, \xi \rangle arising from irreducible unitary representations \pi of G on a , for unit vectors \xi, yield positive-definite functions. Key properties of continuous positive-definite functions include boundedness, with |f(g)| \leq f(e) = 1 for all g \in G, and hermiticity, satisfying f(g^{-1}) = \overline{f(g)} (which holds automatically on abelian groups). These ensure that f behaves like a , maintaining non-negativity in quadratic forms. The term "positive-definite function" was introduced by I. J. Schoenberg in 1938, extending concepts from earlier work by G. Herglotz in 1911 on sequences over the integers.

Locally compact abelian groups and Pontryagin duality

A locally compact (LCAG) is defined as a G that is abelian (i.e., commutative under the group operation), Hausdorff (to ensure separation of points), and locally compact (meaning every point has a compact neighborhood). This structure generalizes familiar groups like the under to more abstract settings, enabling the extension of classical analysis tools such as integration and transforms. Prominent examples of LCAGs include the Euclidean space \mathbb{R}^n with the standard topology, the integers \mathbb{Z} equipped with the discrete topology, the circle group \mathbb{T} = \mathbb{R}/\mathbb{Z} (which is compact), and the p-adic integers \mathbb{Z}_p for a prime p (which are compact and totally disconnected). These examples illustrate the diversity of LCAGs, ranging from connected and non-compact to discrete and compact topologies. Central to the theory of LCAGs is , which associates to every LCAG G its Pontryagin dual group \hat{G}, defined as the set of all continuous group homomorphisms (known as characters) from G to the circle group \mathbb{T}. The dual group \hat{G} is equipped with the , making it another LCAG, and the Pontryagin duality theorem asserts that there is a topological G \cong \hat{\hat{G}} between G and its double dual, preserving the group structure and topology. This duality provides a profound that underpins on non-Euclidean groups, allowing the transfer of analytic properties between a group and its dual. To perform analysis on LCAGs, one employs the , which is a unique (up to positive scalar multiples) non-trivial regular \mu on G that is left-invariant under the , satisfying \mu(gE) = \mu(E) for all g \in G and measurable sets E \subseteq G. This measure extends the on \mathbb{R}^n and enables the definition of integrable functions L^1(G) via the integral \int_G f(g) \, d\mu(g), providing a foundation for and other operations invariant under group translations. The on an LCAG G is defined for functions f \in L^1(G) by \hat{f}(\xi) = \int_G f(g) \overline{\xi(g)} \, d\mu(g), \quad \xi \in \hat{G}, where \overline{\xi(g)} is the of the character value and \mu is a on G. This transform diagonalizes convolutions, much like in the classical case, and extends by density to an isometric isomorphism on L^2(G) via the , which equates the L^2-norms on G and \hat{G} (with an appropriate dual Haar measure on \hat{G}) and identifies L^2(G) with L^2(\hat{G}). A key algebraic consequence is the Gelfand-Fourier isomorphism, which establishes that the group C^*(G)—the completion of L^1(G) under the from the left on L^2(G)—is isometrically *-isomorphic to C_0(\hat{G}), the of continuous complex-valued functions on \hat{G} that vanish at infinity, via the . This isomorphism highlights the commutative nature of C^*(G) for abelian G and bridges with classical function spaces on the group.

Statement of the Theorem

General version for locally compact abelian groups

Bochner's theorem in its general form characterizes continuous positive-definite functions on a locally compact G as the Fourier transforms of positive measures on the Pontryagin dual group \hat{G}. Specifically, let G be a \sigma-compact locally compact equipped with its . A function f: G \to \mathbb{C} is positive-definite if for every n \in \mathbb{N}, g_1, \dots, g_n \in G, and c_1, \dots, c_n \in \mathbb{C}, the \sum_{j,k=1}^n \overline{c_j} c_k f(g_j g_k^{-1}) \geq 0 holds. The theorem states that if f is continuous and positive-definite on G, then there exists a unique \mu on \hat{G} such that f(g) = \int_{\hat{G}} \xi(g) \, d\mu(\xi) for all g \in G, where \xi \in \hat{G} denotes the continuous homomorphisms from G to the circle group \mathbb{T}, often written as characters \chi(g). This integral is the Fourier-Stieltjes transform of \mu, and \mu is nonnegative with finite \|\mu\| = f(e), where e is the in G. For the normalized case, assume f(e) = 1, which implies that \mu is a probability measure on \hat{G}, i.e., \mu(\hat{G}) = 1. The continuity of f ensures that \mu is tight, meaning for every \epsilon > 0, there exists a compact subset K \subset \hat{G} such that \mu(\hat{G} \setminus K) < \epsilon. This tightness follows from the uniform continuity properties in the context of \sigma-compact groups, guaranteeing the measure's regularity. Intuitively, the positive-definiteness of f induces a positive linear functional on the space of continuous functions vanishing at infinity on \hat{G}, C_0(\hat{G}), via the , which represents it as integration against a positive \mu. In terms of unitary representations, since G is abelian, the irreducible representations are precisely the characters in \hat{G}; thus, f arises as the integral of matrix coefficients (here, simply \xi(g)) of the one-dimensional over \mu.

Uniqueness, existence, and corollaries

The existence of the representing measure \mu in Bochner's theorem follows from the Riesz–Markov–Kakutani representation theorem applied to the dual group \hat{G}. Specifically, the positive-definiteness of the continuous function f: G \to \mathbb{C} induces a positive linear functional \Lambda on C_0(\hat{G}), the space of continuous functions on \hat{G} vanishing at infinity. This functional is defined initially on trigonometric polynomials \sum_{g \in F} c_g \gamma_g, where F \subset G is finite, \gamma_g \in \hat{G}^\wedge = G acts as \gamma_g(\xi) = \xi(g), by \Lambda\left( \sum_{g \in F} c_g \gamma_g \right) = \sum_{g,h \in F} c_g \overline{c_h} f(g h^{-1}), and extended by continuity to all of C_0(\hat{G}). This functional is positive because f is positive-definite, ensuring \Lambda(\phi) \geq 0 for \phi \geq 0. The Riesz–Markov theorem then yields a unique regular positive Borel measure \mu \in M_+(\hat{G}) such that \Lambda(\phi) = \int_{\hat{G}} \phi \, d\mu for all \phi \in C_0(\hat{G}), and the Fourier inversion formula implies f(x) = \int_{\hat{G}} \langle x, \xi \rangle \, d\mu(\xi), where \langle x, \xi \rangle denotes the pairing. Uniqueness of \mu is a consequence of the injectivity of the –Stieltjes transform on the space of finite measures M(\hat{G}). Suppose \mu_1, \mu_2 \in M_+(\hat{G}) both satisfy f(x) = \int_{\hat{G}} \langle x, \xi \rangle \, d\mu_1(\xi) = \int_{\hat{G}} \langle x, \xi \rangle \, d\mu_2(\xi) for all x \in G. Then the difference \nu = \mu_1 - \mu_2 has \hat{\nu} = 0 on G. Since the is injective on M(\hat{G}) for locally compact abelian groups (as established by the uniqueness of and density arguments on compactly supported functions), it follows that \nu = 0, so \mu_1 = \mu_2. A key is the between the set of continuous positive-definite functions f: G \to \mathbb{C} with f(e) = 1 (where e is the ) and the set of probability measures on \hat{G}. In this normalized case, the total mass \mu(\hat{G}) = f(e) = 1, establishing the correspondence via the . More generally, without normalization, continuous positive-definite functions correspond bijectively to finite positive measures on \hat{G}, with \mu(\hat{G}) = f(e) < \infty. Another immediate corollary concerns convolution: if f = \hat{\mu} and g = \hat{\nu} are positive-definite functions corresponding to finite positive measures \mu, \nu \in M_+(\hat{G}), then the pointwise product f \cdot g is also positive-definite and equals \widehat{\mu * \nu}, where * denotes of measures on \hat{G}. This follows from the property that the converts pointwise multiplication to convolution: \widehat{\mu * \nu}(\gamma) = \hat{\mu}(\gamma) \hat{\nu}(\gamma) for \gamma \in G, and the product of positive-definite functions inherits positive-definiteness from the original inequalities.

Special Cases

Herglotz's theorem on the integers

Herglotz's theorem provides the characterization of positive-definite functions on the integers \mathbb{Z}, which form a discrete locally compact abelian group G. The Pontryagin dual \hat{G} of \mathbb{Z} is the circle group \mathbb{T}, identified with the interval [0,1) under addition modulo 1, equipped with the Haar measure normalized to total mass 1. A f: \mathbb{[Z](/page/Z)} \to \mathbb{C} is if, for every integer n \geq 1, points k_1, \dots, k_n \in \mathbb{[Z](/page/Z)}, and coefficients c_1, \dots, c_n \in \mathbb{C}, the inequality \sum_{j,k=1}^n \overline{c_j} f(k_j - k_k) c_k \geq 0 holds. The states that a normalized f: \mathbb{[Z](/page/Z)} \to \mathbb{C} (with f(0) = 1) admits a unique representation as the of a \mu on \mathbb{T}, given by f(k) = \int_{\mathbb{T}} e^{2\pi i k x} \, d\mu(x) for all k \in \mathbb{[Z](/page/Z)}. This is a special case of the general Bochner for locally compact abelian groups. Originally formulated by Gustav Herglotz in 1911, the theorem predates and inspired Salomon Bochner's 1932 generalization to arbitrary locally compact abelian groups, serving as a foundational result in the of stationary sequences. A representative example is the function f(k) = r^{|k|} for |r| \leq 1, which is normalized positive-definite on \mathbb{Z}. It corresponds to the \mu on \mathbb{T} with density \frac{1 - r^2}{2\pi (1 - 2r \cos(2\pi x) + r^2)} with respect to , known as the on the circle.

Bochner-Khinchin theorem on the reals

The Bochner-Khinchin theorem addresses the special case of Bochner's theorem for the locally compact abelian group G = \mathbb{R}^d equipped with vector addition, where the Pontryagin dual group \hat{G} is isomorphic to \mathbb{R}^d itself, with continuous characters given by \chi_\xi(t) = e^{i \xi \cdot t} for \xi, t \in \mathbb{R}^d. A function f: \mathbb{R}^d \to \mathbb{C} that is continuous, positive-definite, and normalized with f(0) = 1 admits a unique representation as the Fourier-Stieltjes transform of a \mu on \mathbb{R}^d: f(t) = \int_{\mathbb{R}^d} e^{i \xi \cdot t} \, d\mu(\xi), \quad t \in \mathbb{R}^d. Here, the integral is understood in the Stieltjes sense, accommodating singular measures that may not be absolutely continuous with respect to . This characterization establishes a between such functions and probability distributions on \mathbb{R}^d. In , the theorem identifies these positive-definite functions precisely as characteristic functions of random vectors in \mathbb{R}^d. Specifically, f(t) = \mathbb{E}[e^{i t \cdot X}], where X is a random vector with distribution \mu, and the expectation equals \int_{\mathbb{R}^d} e^{i t \cdot x} \, d\mu(x); the positive-definiteness of f arises directly from this integral representation via properties of the inner product in L^2(\mu). A example is the of the standard multivariate Gaussian distribution, f(t) = e^{-\|t\|^2 / 2}, which is continuous and positive-definite, corresponding to the unique probability measure \mu that is the standard normal distribution on \mathbb{R}^d with mean zero and identity covariance matrix. This illustrates how the theorem links explicit forms of characteristic functions to their underlying distributions. The nomenclature "Bochner-Khinchin theorem" is commonly employed in probability literature to underscore the theorem's integral representation and its implications for deriving moments, cumulants, and other distributional properties from characteristic functions.

Applications and Extensions

In and

Bochner's theorem plays a central role in abstract on locally compact abelian groups (LCAGs) by enabling the recovery of positive measures from positive-definite functions through Fourier inversion formulas. Specifically, if \phi: G \to \mathbb{C} is a continuous positive-definite function on an LCAG G, then Bochner's theorem asserts that \phi is the Fourier-Stieltjes transform of a unique bounded positive \mu on the Pontryagin dual \hat{G}, given by \phi(x) = \int_{\hat{G}} \chi_x(\xi) \, d\mu(\xi). The inversion formula then allows reconstruction of \mu from \phi under suitable conditions, such as when \phi is integrable, via standard Fourier inversion procedures. This extends the classical Fourier inversion to general LCAGs and underpins the Plancherel theorem's unitary isomorphism between L^2(G) and L^2(\hat{G}). In the context of unitary , positive-definite functions on LCAGs arise as matrix coefficients of cyclic vectors in unitary representations, and Bochner's facilitates the decomposition of representations into direct integrals of irreducibles. For the left \lambda on L^2(G), the implies that it decomposes as a direct integral \int_{\hat{G}}^{\oplus} \pi_\xi \, d\mu(\xi), where each \pi_\xi is the irreducible representation given by \pi_\xi(f) \psi(x) = \int_G f(y) \psi(y^{-1}x) \, dy twisted by the character \xi, and \mu is the Plancherel measure on \hat{G}; this multiplicity-free decomposition highlights the abelian structure and is derived from the applied to the convolution operators. More generally, any continuous positive-definite function \phi corresponds to the coefficient \phi(x) = \langle \pi(x) \xi, \xi \rangle for some cyclic vector \xi in a unitary representation \pi of G, with Bochner's ensuring \pi is a direct integral over \hat{G} weighted by the measure \mu. Bochner's theorem also informs the structure of group C*-algebras C^*(G), the completion of L^1(G) under the universal norm, by identifying the space K(G) of compactly supported continuous functions as a dense -subalgebra whose Gelfand spectrum relates to positive-definite functions. In particular, for abelian G, C^*(G) \cong C_0(\hat{G}), and positive-definite functions on G correspond to positive elements in this algebra via the Fourier transform, with the theorem implying that closed two-sided ideals in C^*(G) are of the form \{f \in C^*(G) : \hat{f} vanishes on a closed subset of \hat{G}\}; this has applications to amenability, as G is amenable if and only if C^*(G) has an approximate identity of idempotents bounded in the operator norm. Furthermore, the theorem aids in studying idempotents in C^*(G), which correspond to characteristic functions of open subgroups in \hat{G}, thereby characterizing the ideal structure and providing tools for analyzing the reduced C-algebra C^*_r(G). For compact abelian groups, Bochner's theorem specializes to yield finite atomic measures \mu on the discrete dual \hat{G}, refining the abelian Peter-Weyl theorem by expressing positive-definite functions as finite sums \phi(g) = \sum_{\chi \in \hat{G}} \mu(\{\chi\}) \chi(g), where \chi are the 1-dimensional characters; this decomposition underscores the finite-dimensionality of the and the orthogonality of characters in L^2(G). Extensions of Bochner's theorem to non-abelian locally compact groups employ the to obtain Choquet representations for as over extreme points, which are matrix coefficients of irreducible unitary representations. In this setting, a continuous \phi: G \to \mathbb{C} admits a representing measure \mu on the space of irreducibles such that \phi(g) = \int \langle \pi(g) \xi_\pi, \eta_\pi \rangle \, d\mu(\pi), where the is a direct Bochner-type theorem; this framework, relying on the convexity of the state space and Choquet's theorem for barycentric representations, generalizes the abelian case and applies to decomposition of the in type I groups.

In probability and stationary processes

Bochner's theorem plays a central role in through its application to functions. The Bochner–Khinchin theorem establishes that a continuous function \phi: \mathbb{R}^d \to \mathbb{C} satisfying \phi(0) = 1 is the of some on \mathbb{R}^d if and only if it is positive definite. This characterization, which follows directly from Bochner's general result on positive-definite functions as transforms of positive measures, provides a necessary and sufficient condition for the existence of a corresponding distribution. It is particularly useful in addressing moment problems, where one seeks to determine a from its moments, by ensuring the associated generating function admits a probabilistic interpretation. In the study of stationary processes, Bochner's theorem characterizes the autocovariance structure of weakly stationary time series. For a weakly stationary process \{X_t\}_{t \in \mathbb{Z}} with mean zero, the autocovariance function \gamma(k) = \mathbb{E}[X_{t+k} \overline{X_t}] is positive definite on \mathbb{Z}. By Bochner's theorem—applied via its special case on the integers, known as Herglotz's theorem—the autocovariance admits a spectral representation \gamma(k) = \int_{-\pi}^{\pi} e^{i \lambda k} \, F(d\lambda), where F is a non-decreasing spectral distribution function on [-\pi, \pi] with F(\pi) - F(-\pi) = \gamma(0). This representation, first derived by Khinchin using Bochner's framework, links the time-domain covariances to a frequency-domain measure, enabling the analysis of dependence structures through spectral properties. Representative examples illustrate the theorem's utility. For , where \gamma(k) = \delta_{0k} (the Kronecker delta), the F is uniform on [-\pi, \pi], corresponding to a flat spectrum. In periodic processes, such as a deterministic sinusoid, F is atomic, with point masses at the process's frequencies. For autoregressive (ARMA) models, the F is absolutely continuous with a rational function, reflecting the rational of the model. A key refinement is Cramér's theorem, which specifies conditions for the existence of a . If the autocovariances are absolutely summable, \sum_{k=-\infty}^{\infty} |\gamma(k)| < \infty, then F is absolutely continuous with respect to , possessing a density f(\lambda) = \frac{1}{2\pi} \sum_{k=-\infty}^{\infty} \gamma(k) e^{-i \lambda k} \geq 0. This result, established in Cramér's foundational work on processes, ensures the spectral measure has a density interpretable as the power . The representation facilitated by Bochner's theorem underpins advanced results in time series analysis, including the Wold decomposition. This decomposes a into a deterministic component (predictable from the infinite past) and a purely indeterministic innovation-driven part, which is representable as a of . Such decompositions are essential for theory, where optimal forecasts rely on inverting the measure to compute operators in the of the process.

Historical Development

Origins and key contributions

The origins of Bochner's theorem lie in early 20th-century investigations into positive definite sequences and the representation of analytic functions with nonnegative real parts. In 1911, examined the domain of variability for Fourier coefficients of positive harmonic functions, providing insights into positive definite quadratic forms that foreshadowed integral representations in . Independently, in 1911 Gustav Herglotz established that a trigonometric sum on the integers is positive definite if and only if its Fourier coefficients correspond to a positive measure on the unit circle, a result central to the theory of stationary processes. These contributions built on Frigyes Riesz's 1909 representation theorem for functions analytic in the unit disk with positive real part, which utilized Stieltjes integrals to express such functions in terms of positive measures. Salomon Bochner advanced this framework significantly in the early 1930s by generalizing it to continuous functions on spaces. In his 1932 monograph Vorlesungen über sche Integrale, Bochner characterized continuous positive definite functions on \mathbb{R}^n as the transforms of finite positive Radon measures, synthesizing discrete and continuous cases through integral representations. He elaborated this in a 1933 paper, employing monotone functions and Stieltjes integrals to prove the theorem, which resolved key questions in and . Influenced by Wiener's tauberian theorems from the 1920s, which connected to measure theory, Bochner's work integrated these ideas into a unified perspective. Bochner further extended the theorem in subsequent work during to arbitrary locally compact abelian groups, leveraging Lev Pontryagin's duality theory published in to define Fourier transforms abstractly. This generalization appeared amid surge in abstract , coinciding with the development of theory by and others, which provided the operator-theoretic tools essential for . Bochner's contributions, initially published in Mathematische Annalen, gained widespread recognition through later expositions, such as Walter Rudin's 1962 Fourier Analysis on Groups and Katznelson's 1976 An Introduction to Harmonic Analysis. Modern generalizations of Bochner's theorem extend its scope beyond abelian groups and classical probability measures, incorporating non-commutative structures and operator-theoretic frameworks. One key direction involves non-abelian groups, where classical is replaced by matrix-valued or representation-theoretic analogs. For compact non-abelian groups, a Bochner-style characterizes positive definite functions as integrals over irreducible representations, building on earlier work by establishing uniqueness and multiplicity bounds in the . This approach addresses the limitations of the abelian case by accounting for the group's , as seen in extensions to semisimple Lie groups where spherical functions play a central role in the inversion formula. Further, the Bochner-Schwartz-Godement provides a complete for positive definite distributions in settings like generalized Gelfand pairs, refining existence and uniqueness for broader applications in non-abelian contexts. In , extensions leverage the Bochner integral to handle vector-valued functions, enabling the of random elements in Banach spaces. The Bochner integral generalizes the Lebesgue integral to functions taking values in separable Banach spaces, preserving measurability and integrability properties essential for processes. This framework is crucial for characterizing infinitely divisible distributions, where the Lévy-Khinchin formula serves as a refinement of Bochner's theorem by expressing the logarithm of the in terms of a Lévy measure, Gaussian , and drift, directly linking to the structure of . Specifically, for Lévy processes, Bochner's theorem ensures that the is positive definite, while the Lévy-Khinchin representation provides the explicit parametric form, facilitating applications in modeling beyond scalar cases. Related theorems connect Bochner's ideas to and . Bochner's positive definite functions underpin the reduction to Choi's theorem in finite-dimensional settings, establishing that completely positive maps correspond to block-positive matrices via a duality with . Similarly, Szegő's limit theorem for Toeplitz determinants links to Bochner through the positive definite symbol of Toeplitz operators in stationary processes; the theorem asymptotes the determinant to the exponential of the integral of the log-symbol, relying on Herglotz-Bochner representations for the to ensure the symbol's analyticity in the unit disk. Post-2000 developments in quantum probability integrate Bochner's theorem into operator , yielding versions for locally compact quantum groups where completely functions are integrated against Haar states on the dual . These quantum Bochner theorems characterize transforms of states on non-commutative spaces, extending classical inversion to von Neumann and enabling compatibility conditions for incompatible observables in . Connections to free probability, pioneered by Voiculescu in the , introduce non-commutative analogs where free cumulants replace classical ones, and is adapted to R-transforms; this framework generalizes Bochner's characterization to free infinitely divisible distributions, with applications to limits and operator-valued processes. Additionally, computational aspects in utilize Bochner's theorem for designing stationary kernels in Gaussian processes, approximating spectral densities via sampling of the positive measure to enhance efficiency in high-dimensional filtering and prediction tasks.

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