Theory of Barnes Beta Distributions

A new family of probability distributions $\beta_{M, N},$ $M=0\cdots N,$ $N\in\mathbb{N}$ on the unit interval $(0, 1]$ is defined by the Mellin transform. The Mellin transform of $\beta_{M, N}$ is characterized in terms of products of ratios of Barnes multiple gamma functions, shown to satisfy a functional equation, and a Shintani-type infinite product factorization. The distribution $\log\beta_{M, N}$ is infinitely divisible. If $M<N,$ $-\log\beta_{M, N}$ is compound Poisson, if $M=N,$ $\log\beta_{M, N}$ is absolutely continuous. The integral moments of $\beta_{M, N}$ are expressed as Selberg-type products of multiple gamma functions. The asymptotic behavior of the Mellin transform is derived and used to prove an inequality involving multiple gamma functions and establish positivity of a class of alternating power series. For application, the Selberg integral is interpreted probabilistically as a transformation of $\beta_{1, 1}$ into a product of $\beta^{-1}_{2, 2}s.$Comment: 15 pages, published version (removed Th. 4.5 and Section 5, updated references

Structure-Blind Signal Recovery

We consider the problem of recovering a signal observed in Gaussian noise. If the set of signals is convex and compact, and can be specified beforehand, one can use classical linear estimators that achieve a risk within a constant factor of the minimax risk. However, when the set is unspecified, designing an estimator that is blind to the hidden structure of the signal remains a challenging problem. We propose a new family of estimators to recover signals observed in Gaussian noise. Instead of specifying the set where the signal lives, we assume the existence of a well-performing linear estimator. Proposed estimators enjoy exact oracle inequalities and can be efficiently computed through convex optimization. We present several numerical illustrations that show the potential of the approach

Instanton-induced Azimuthal Spin Asymmetry in Deep Inelastic Scattering

It is by now well understood that spin asymmetry in deep inelastic scattering (DIS) can appear if two things are both present: (i) a chirality flip of the struck quark; (ii) a nonzero T-odd phase due to its final state interaction. So far (i) was attributed to a new structure/wave function of the nucleon and (ii) to some gluon exchanges. We propose a new mechanism utilizing strong vacuum fluctuations of the gluon field described semiclasically by instantons, and show that both (i) and (ii) are present. The magnitude of the effect is estimated using known parameters of the instanton ensemble in the QCD vacuum and known structure and fragmentation functions, without any new free parameters. The result agrees in sign and (roughly) in magnitude with the available data on single particle inclusive DIS. Furthermore, our predictions uniquely relate effects for longitudinally and transversely polarized targets.Comment: version 2 includes few refs and new fig.5 which contains comparison to recent dat

Adaptive Recovery of Signals by Convex Optimization

International audienceWe present a theoretical framework for adaptive estimation and prediction of signals of unknown structure in the presence of noise. The framework allows to address two intertwined challenges: (i) designing optimal statistical estimators; (ii) designing efficient numerical algorithms. In particular, we establish oracle inequalities for the performance of adaptive procedures, which rely upon convex optimization and thus can be efficiently implemented. As an application of the proposed approach, we consider denoising of harmonic oscillations

Adaptive Recovery of Signals by Convex Optimization

International audienceWe present a theoretical framework for adaptive estimation and prediction of signals of unknown structure in the presence of noise. The framework allows to address two intertwined challenges: (i) designing optimal statistical estimators; (ii) designing efficient numerical algorithms. In particular, we establish oracle inequalities for the performance of adaptive procedures, which rely upon convex optimization and thus can be efficiently implemented. As an application of the proposed approach, we consider denoising of harmonic oscillations

Azimuthal asymmetry in transverse energy flow in nuclear collisions at high energies

The azimuthal pattern of transverse energy flow in nuclear collisions at RHIC and LHC energies is considered. We show that the probability distribution of the event-by-event azimuthal disbalance in transverse energy flow is essentially sensitive to the presence of the semihard minijet component.Comment: 6 pages, 2 figure

Subcritical multiplicative chaos for regularized counting statistics from random matrix theory

For an N×N random unitary matrix U_N, we consider the random field defined by counting the number of eigenvalues of U_N in a mesoscopic arc of the unit circle, regularized at an N-dependent scale Ɛ_N>0. We prove that the renormalized exponential of this field converges as N → ∞ to a Gaussian multiplicative chaos measure in the whole subcritical phase. In addition, we show that the moments of the total mass converge to a Selberg-like integral and by taking a further limit as the size of the arc diverges, we establish part of the conjectures in [55]. By an analogous construction, we prove that the multiplicative chaos measure coming from the sine process has the same distribution, which strongly suggests that this limiting object should be universal. The proofs are based on the asymptotic analysis of certain Toeplitz or Fredholm determinants using the Borodin-Okounkov formula or a Riemann-Hilbert problem for integrable operators. Our approach to the L¹-phase is based on a generalization of the construction in Berestycki [5] to random fields which are only asymptotically Gaussian. In particular, our method could have applications to other random fields coming from either random matrix theory or a different context