Rylan Conway

The PHENIX detector is designed to perform a broad study of A–A, p–A, and p–p collisions to investigate nuclear matter under extreme conditions. A wide variety of probes, sensitive to all timescales, are used to study systematic variations with species and energy as well as to measure the spin structure of the nucleon. Designing for the needs of the heavy-ion and polarized-proton programs has produced a detector with unparalleled capabilities. PHENIX measures electron and muon pairs, photons, and hadrons with excellent energy and momentum resolution. The detector consists of a large number of subsystems that are discussed in other papers in this volume. The overall design parameters of the detector are presented.

The timing, location and particle multiplicity of a PHENIX collision are determined by the Beam–Beam Counters (BBC), the Multiplicity/Vertex Detector (MVD) and the Zero-Degree Calorimeters (ZDC). The BBCs provide both the time of interaction and position of a collision from the flight time of prompt particles. The MVD provides a measure of event particle multiplicity, collision vertex position and fluctuations in charged particle distributions. The ZDCs provide information on the most grazing collisions. A Normalization Trigger Counter (NTC) is used to obtain absolute cross-section measurements for p–p collisions. The BBC, MVD and NTC are described below.

The physics emphases of the PHENIX collaboration and the design and current status of the PHENIX detector are discussed. The plan of the collaboration for making the most effective use of the available luminosity in the first years of RHIC operation is also presented.

River catchments are dynamic networks that contain multiple levels of spatial and temporal complexity. Benthic macroinvertebrates are key indicator taxa throughout catchments, and beta diversity has been used as a metric to explore determinants of community composition at the catchment scale. Although factors influencing spatial beta diversity have been explored, the determinants of temporal beta diversity have been understudied. In this study, we aimed to understand how shifts in benthic macroinvertebrate community composition over multiple years are related to local and regional variables. We used beta regression with a large, publicly available biomonitoring dataset from river networks in California, USA, to model the effects of local environmental variables, flow variability, and spatial network context on benthic macroinvertebrate temporal beta diversity. The spatial variables channel slope, drainage density, and upstream catchment area had the strongest relationships with macroinvertebrate beta diversity. Channel slope was negatively related to temporal beta diversity, whereas drainage density and upstream catchment area were positively related to temporal beta diversity. Temporal beta diversity was also higher when the rate and magnitude of rises and falls in flow were higher in the hydrograph, as well as when the number of zero-flow days and the duration of flow rises and falls were higher. Overall, our results indicate that temporal beta diversity of freshwater benthic macroinvertebrates is shaped by both long-term hydrological context and spatial context and that these factors may serve as better predictors of long-term community variability than variability in point estimates of environmental measurements. Our study supports the need for biomonitoring efforts at long spatial and temporal timescales and highlights the need to consider metacommunity change in the management of freshwater systems.

Gesture typing is a method of text entry that is ergonomically well-suited to the form factor of touchscreen devices and allows for much faster input than tapping each letter individually. The QWERTY keyboard was, however, not designed with gesture input in mind and its particular layout results in a high frequency of gesture recognition errors. In this paper, we describe a new approach to quantifying the frequency of gesture input recognition errors through the use of modeling and simulating realistically imperfect user input. We introduce new methodologies for modeling randomized gesture inputs, efficiently reconstructing words from gestures on arbitrary keyboard layouts, and using these in conjunction with a frequency weighted lexicon to perform Monte Carlo evaluations of keyboard error rates or any other arbitrary metric. An open source framework, Dodona, is also provided that allows for these techniques to be easily employed and customized in the evaluation of a wide spectrum of possible keyboards and input methods. Finally, we perform an optimization procedure over permutations of the QWERTY keyboard to demonstrate the effectiveness of this approach and describe ways that future analyses can build upon these results.

Measurements of dihadron correlations triggered by very high-pT particles in 2.76 TeV PbPb collisions are presented. The analysis explores the full 2011 PbPb data set corresponding to an integrated luminosity of 150μb−1 collected by CMS. Long-range correlations driven by single-particle azimuthal anisotropies (characterized by the Fourier harmonics, vn) are measured up to pT∼50 GeV/c. After subtracting the v2 – v4 harmonic components, the associated particle yields on the near and away side of the residual jet-like dihadron correlations are studied over a wide kinematic range in trigger and associated particle pT, as a function of collision centrality. By comparing to pp data at the same energy, a suppression of about 50% in the away-side associated yield is observed for pTassoc>3GeV/c. The yield is found to be significantly enhanced up to a factor of 3–4 on the away side at pTassoc∼0.5GeV/c. A moderate enhancement is suggested on the near side.

In a spoken dialogue system, dialogue state tracker (DST) components track the state of the conversation by updating a distribution of values associated with each of the slots being tracked for the current user turn, using the interactions until then. Much of the previous work has relied on modeling the natural order of the conversation, using distance based offsets as an approximation of time. In this work, we hypothesize that leveraging the wall-clock temporal difference between turns is crucial for finer-grained control of dialogue scenarios. We develop a novel approach that applies a time mask, based on the wall-clock time difference, to the associated slot embeddings and empirically demonstrate that our proposed approach outperforms existing approaches that leverage distance offsets, on both an internal benchmark dataset as well as DSTC2.

We describe the design and expected performance of the PHENIX Multiplicity and Vertex Detector (MVD) sub-system of the PHENIX detector at the Relativistic Heavy Ion Collider (RHIC).

Swiping is a technique used for text entry on touchscreen devices which involves sliding a finger between each successive letter in a word. The word is then probabilistically reconstructed from this ambiguous input. This method of text input is ergonomically suited for the form factor of touchscreen devices and results in a much faster input method than tapping each letter individually. Unfortunately, there are many cases where different words have extremely similar swipe patterns which results in a high frequency of errors. In this paper, we describe a method to determine a keyboard layout that minimizes swipe errors in order to further increase the speed of text input on a touchscreen device. Finally, we present the results of running this analysis on an English language corpus and standard keyboard geometry leading to a reduction in the frequency of swipe errors by over 50% relative to the standard QWERTY keyboard.

Abstract These proceedings present the results from azimuthal angle correlations of charged hadrons measured in s N N = 2.76 TeV PbPb collisions by the CMS experiment at the LHC. Two-particle correlation functions are shown in 2D for multiple centralities. The factorization assumption of the anisotropy parameters from two-particle correlations is directly tested for various centralities and p T trig ranges. Higher order azimuthal anisotropy coefficients are also extracted from two-particle correlations and presented as a function of N part for three separate p T trig ranges.

Measurements of dihadron correlations triggered by very high-pT particles in 2.76 TeV PbPb collisions are shown. The data set, which corresponds to an integrated luminosity of 150 μb−1, collected by the CMS detector is utilized. Long-range correlations are measured up to pT ~ 50 GeV/c. These correlations are driven by single-particle azimuthal anisotropies and characterized by the Fourier harmonics, vn. Once the V2 − v4 harmonic components are subtracted the associated particle yields on the near and away side of the jet-like correlations are studied. These measurements are done over a wide kinematic range in the associated and trigger particle pT and as a function of centrality. The data are compared to pp collisions at the same energy. A suppression of about 50% from the pp reference in the away-side associated yield is observed for passocT > 3 GeV/c. For lower momentums, passocT ~ 0.5 GeV/c, the yield is found to be enhanced significantly by up to a factor of 3–4 on the away-side. On the near side, there is some evidence of a moderate enhancement.

This proceeding reports the results from azimuthal angle correlations of charged hadrons measured in VsNN = 2.76 TeV PbPb collisions by the CMS experiment. The azimuthal distributions exhibit anisotropies that are correlated with the event-by-event orientation of the participant plane (the plane that contains the beam axis and the short direction of the lenticular overlap region). In general, the participant plane will not contain the reaction impact parameter vector because of fluctuations that arise from having a finite number of nucleons. The second Fourier coefficient of the charged hadron azimuthal distributions was measured as a function of transverse momentum, pseudorapidity, and centrality in a broad kinematic range. In addition, results on higher-order Fourier components are presented and their connection to the hydrodynamic medium will be discussed.

Abstract River catchments are dynamic networks that contain multiple levels of spatial and temporal complexity. Benthic macroinvertebrates are key indicator taxa throughout catchments and beta diversity has been used as a metric to explore determinants of community composition at the catchment scale. Commonly explored drivers of beta diversity include environmental and spatial variables such as flow, temperature, and spatial distance. While factors influencing spatial beta diversity have been explored, factors explaining temporal beta diversity have been understudied. Temporal beta diversity is predicted to also be important since community assembly mechanisms are not stable over time, and more studies are needed to determine which factors most strongly determine temporal beta diversity patterns. We investigated the effects of local environmental variables, flow variability, and spatial context on temporal beta-diversity using a large, publicly available biomonitoring dataset from river networks in California. Data included benthic macroinvertebrate community composition and environmental data from multiple locations and years, allowing us to explore temporal changes in these communities as a function of site-specific environmental and spatial factors. Associated gage data were used to calculate hydrograph metrics and contextualize the flow regime at each location over long timescales. We then used beta regression to model the relationship between benthic macroinvertebrate temporal beta-diversity, environmental variables, flow regimes, and spatial network context. Flow and spatial catchment-related predictors were the strongest predictors of temporal beta diversity, while changes in environmental variables were much weaker. Channel slope, drainage density, and upstream catchment area were the most significant spatial factors. Channel slope showed a negative relationship with temporal beta diversity, while drainage density and upstream catchment area showed positive ones. Temporal beta diversity was also higher when the rate and magnitude of rises and falls in flow was higher in the hydrograph as well as when the number of zero-flow days and the duration of flow rises and falls was higher. Overall, our results indicate that temporal beta diversity of freshwater benthic macroinvertebrates is shaped by both long-term hydrological context and spatial context, and that these factors may serve as better predictors of long term community variability than variability in point estimates of environmental measurements. Flow regimes and spatial metrics may provide more environmental context than point-estimate environmental measurements, as the latter may not accurately capture the dynamic conditions that drive variability in metacommunity responses. Our study supports the need for biomonitoring efforts at long spatial and temporal timescales, and highlights the need to consider metacommunity change in the management of freshwater systems.

The PHENIX Multiplicity Vertex Detector (MVD) provides event characterization, a centrality trigger, collision vertex position, and measures fluctuations in charged particle multiplicities. The design criteria include a large rapidity coverage, good azimuthal coverage and granularity, minimizing material in the electron arm acceptance, and minimizing costs. The MVD contains two concentric barrels of Si strip detectors with two disk-shaped Si pad detector endcaps. Simulations show that the vertex position can be located to within a few hundred microns using hits in the barrels. A channel multiplicity signal is formed for use in the Level-1 trigger. The effect of the expected discriminator performance on this trigger signal will be shown. The pad and strip detectors are read-out with identical electronics. The influence of the performance of the electronics on the detector's performance are discussed.

In a spoken dialogue system, dialogue state tracker (DST) components track the state of the conversation by updating a distribution of values associated with each of the slots being tracked for the current user turn, using the interactions until then. Much of the previous work has relied on modeling the natural order of the conversation, using distance based offsets as an approximation of time. In this work, we hypothesize that leveraging the wall-clock temporal difference between turns is crucial for finer-grained control of dialogue scenarios. We develop a novel approach that applies a {\it time mask}, based on the wall-clock time difference, to the associated slot embeddings and empirically demonstrate that our proposed approach outperforms existing approaches that leverage distance offsets, on both an internal benchmark dataset as well as DSTC2.

In a spoken dialogue system, dialogue state tracker (DST) components track the state of the conversation by updating a distribution of values associated with each of the slots being tracked for the current user turn, using the interactions until then. Much of the previous work has relied on modeling the natural order of the conversation, using distance based offsets as an approximation of time. In this work, we hypothesize that leveraging the wall-clock temporal difference between turns is crucial for finer-grained control of dialogue scenarios. We develop a novel approach that applies a {\it time mask}, based on the wall-clock time difference, to the associated slot embeddings and empirically demonstrate that our proposed approach outperforms existing approaches that leverage distance offsets, on both an internal benchmark dataset as well as DSTC2.