Inclusive Diffraction at HERA

New precision measurements of inclusive diffractive deep-inelastic ep scattering interactions, performed by the H1 and ZEUS collaborations at the HERA collider, are discussed. A new set of diffractive parton distributions, determined from recent high precision H1 data, is presented.Comment: 5 pages, to appear in the proceedings of the 31st Intl. Conference on High Energy Physics ICHEP 2002, Amsterdam, July 200

Relative distributions of W's and Z's at low transverse momenta

Despite large uncertainties in the $W^\pm$ and $Z^0$ transverse momentum ($q_T$) distributions for q_T\lsim 10 GeV, the ratio of the distributions varys little. The uncertainty in the ratio of $W$ to $Z$ $q_T$ distributions is on the order of a few percent, independent of the details of the nonperturbative parameterization.Comment: 13 pages in revtex, 5 postscript figures available upon request, UIOWA-94-0

Design of prototype charged particle fog dispersal unit

The unit was designed to be easily modified so that certain features that influence the output current and particle size distribution could be examined. An experimental program was designed to measure the performance of the unit. The program described includes measurements in a fog chamber and in the field. Features of the nozzle and estimated nozzle characteristics are presented

Resolving the plasma profile via differential single inclusive suppression

The ability of experimental signatures to resolve the spatio-temporal profile of an expanding quark gluon plasma is studied. In particular, the single inclusive suppression of high momentum hadrons versus the centrality of a heavy-ion collision and with respect to the reaction plane in non-central collisions is critically examined. Calculations are performed in the higher twist formalism for the modification of the fragmentation functions. Radically different nuclear geometries are used. The influence of different initial gluon distributions as well as different temporal evolution scenarios on the single inclusive suppression of high momentum pions are outlined. It is demonstrated that the modification versus the reaction plane is quite sensitive to the initial spatial density. Such sensitivity remains even in the presence of a strong elliptic flow.Comment: 5 pages, 4 figures, RevTex

Single spin asymmetries in hadron-hadron collisions

We study weighted azimuthal single spin asymmetries in hadron-hadron scattering using the diagrammatic approach at leading order and assuming factorization. The effects of the intrinsic transverse momenta of the partons are taken into account. We show that the way in which $T$-odd functions, such as the Sivers function, appear in these processes does not merely involve a sign flip when compared with semi-inclusive deep inelastic scattering, such as in the case of the Drell-Yan process. Expressions for the weighted scattering cross sections in terms of distribution and fragmentation functions folded with hard cross sections are obtained by introducing modified hard cross sections, referred to as gluonic pole cross sections.Comment: 22 pages, 4 figures; minor text modifications and some additional reference

An evaluation of the suitability of ERTS data for the purposes of petroleum exploration

This experiment was designed to determine the types and amounts of information valuable to petroleum exploration extractable from ERTS data and the cost of obtaining the information using traditional or conventional means. It was desired that an evaluation of this new petroleum exploration tool be made in a geologically well known area in order to assess its usefulness in an unknown area. The Anadarko Basin lies in western Oklahoma and the panhandle of Texas. It was chosen as a test site because there is a great deal of published information available on the surface and subsurface geology of the area, and there are many known structures that act as traps for hydrocarbons. This basin is similar to several other large epicontinental sedimentary basins. It was found that ERTS imagery is an excellent tool for reconnaissance exploration of large sedimentary basins or new exploration provinces. For the first time, small and medium size oil companies can rapidly and effectively analyze exploration provinces as a whole

Hard-scattering factorization with heavy quarks: A general treatment

A detailed proof of hard scattering factorization is given with the inclusion of heavy quark masses. Although the proof is explicitly given for deep-inelastic scattering, the methods apply more generally The power-suppressed corrections to the factorization formula are uniformly suppressed by a power of \Lambda/Q, independently of the size of heavy quark masses, M, relative to Q.Comment: 52 pages. Version as published plus correction of misprint in Eq. (45

Nonstationary Stochastic Resonance in a Single Neuron-Like System

Stochastic resonance holds much promise for the detection of weak signals in the presence of relatively loud noise. Following the discovery of nondynamical and of aperiodic stochastic resonance, it was recently shown that the phenomenon can manifest itself even in the presence of nonstationary signals. This was found in a composite system of differentiated trigger mechanisms mounted in parallel, which suggests that it could be realized in some elementary neural networks or nonlinear electronic circuits. Here, we find that even an individual trigger system may be able to detect weak nonstationary signals using stochastic resonance. The very simple modification to the trigger mechanism that makes this possible is reminiscent of some aspects of actual neuron physics. Stochastic resonance may thus become relevant to more types of biological or electronic systems injected with an ever broader class of realistic signals.Comment: Plain Latex, 7 figure

Applying machine learning to the problem of choosing a heuristic to select the variable ordering for cylindrical algebraic decomposition

Cylindrical algebraic decomposition(CAD) is a key tool in computational algebraic geometry, particularly for quantifier elimination over real-closed fields. When using CAD, there is often a choice for the ordering placed on the variables. This can be important, with some problems infeasible with one variable ordering but easy with another. Machine learning is the process of fitting a computer model to a complex function based on properties learned from measured data. In this paper we use machine learning (specifically a support vector machine) to select between heuristics for choosing a variable ordering, outperforming each of the separate heuristics.Comment: 16 page