Design and construction of CMS central hadron calorimeter

The hadron calorimeter ( HCAL) for the Compact Muon Solenoid Detector ( CMS) covers the central pseudorapidity region ( eta <3.0). It is a sampling calorimeter with brass absorber plates interspersed with scintillator readout plates. In this note, we discuss test beam results used in the optimization of the final design of the calorimeter and report on the status of the construction of the absorber and scintillator packages of HCAL

Satellite Relative Motion Control for MIT\u27s SPHERES Program

Autonomous formation flight concepts and algorithms have great potential to revolutionize spacecraft operations enabling missions to perform autonomous docking, in-space refueling, in-space robotic assembly, and space debris removal. Such tasks require the implementation of speed and path control algorithms to maneuver satellites along relative paths with specified rates along those paths. This thesis uses MATLAB® and SIMULINK® to design and simulate a control algorithm capable of providing relative speed and path control between satellites with a pointing error of less than two degrees, a position error of less than two millimeters, and a millimeter per second of velocity error. The enclosed research provides enhancements to Massachusetts Institute of Technology\u27s SPHERES (Synchronized Position Hold Engage Reorient Experimental Satellites) program, a testbed for multi-object rendezvous and docking research. This control algorithm is to be used on-board the International Space Station to allow MIT\u27s SPHERES program to continue to provide a practical intermediate step to develop, test, and validate autonomous formation spaceflight algorithms. Furthermore, the simulation tool used to develop the control algorithm allows a greater community of control engineers to interact with SPHERES purely in the MATLAB® development environment

Are there hadronic bound states above the QCD transition temperature?

Recent lattice QCD calculations, at physical pion masses and small lattice spacings that approach the continuum limit, have revealed that non-diagonal quark correlators above the critical temperature are finite up to about 2 $T_c$. Since the transition from hadronic to free partonic degrees of freedom is merely an analytic cross-over, it is likely that, in the temperature regime between 1-2 $T_c$, quark and gluon quasiparticles and pre-hadronic bound states can coexist. The correlator values, in comparison to PNJL model calculations beyond mean-field, indicate that at least part of the mixed phase resides in color-neutral bound states. A similar effect was postulated for the in-medium fragmentation process, i.e. for partons which do not thermalize with the system and thus constitute the non-equilibrium component of the particle emission spectrum from a deconfined plasma phase. Here, for the first time we investigate the likelihood of forming bound states also in the equilibrated, parton dominated phase above $T_c$ which is described by lattice QCD.Comment: 15 pages, 4 Figure

Fiber R and D for the CMS HCAL

This paper documents the fiber R and D for the CMS hadron barrel calorimeter (HCAL). The R and D includes measurements of fiber flexibility, splicing, mirror reflectivity, relative light yield, attenuation length, radiation effects, absolute light yield, and transverse tile uniformity. Schematics of the hardware for each measurement are shown. These studies are done for different diameters and kinds of multiclad fiber.Comment: 23 pages, 30 Figures 89 pages, 41 figures, corresponding author: H. Budd, [email protected]

An Integrated Picture of Star Formation, Metallicity Evolution, and Galactic Stellar Mass Assembly

We present an integrated study of star formation and galactic stellar mass assembly from z=0.05-1.5 and galactic metallicity evolution from z=0.05-0.9 using a very large and highly spectroscopically complete sample selected by rest-frame NIR bolometric flux in the GOODS-N. We assume a Salpeter IMF and fit Bruzual & Charlot (2003) models to compute the galactic stellar masses and extinctions. We determine the expected formed stellar mass density growth rates produced by star formation and compare them with the growth rates measured from the formed stellar mass functions by mass interval. We show that the growth rates match if the IMF is slightly increased from the Salpeter IMF at intermediate masses (~10 solar masses). We investigate the evolution of galaxy color, spectral type, and morphology with mass and redshift and the evolution of mass with environment. We find that applying extinction corrections is critical when analyzing galaxy colors; e.g., nearly all of the galaxies in the green valley are 24um sources, but after correcting for extinction, the bulk of the 24um sources lie in the blue cloud. We find an evolution of the metallicity-mass relation corresponding to a decrease of 0.21+/-0.03 dex between the local value and the value at z=0.77 in the 1e10-1e11 solar mass range. We use the metallicity evolution to estimate the gas mass of the galaxies, which we compare with the galactic stellar mass assembly and star formation histories. Overall, our measurements are consistent with a galaxy evolution process dominated by episodic bursts of star formation and where star formation in the most massive galaxies (>1e11 solar masses) ceases at z<1.5 because of gas starvation. (Abstract abridged)Comment: 48 pages, Accepted by the Astrophysical Journa

Incorporating Historical Models with Adaptive Bayesian Updates

This paper considers Bayesian approaches for incorporating information from a historical model into a current analysis when the historical model includes only a subset of covariates currently of interest. The statistical challenge is two-fold. First, the parameters in the nested historical model are not generally equal to their counterparts in the larger current model, neither in value nor interpretation. Second, because the historical information will not be equally informative for all parameters in the current analysis, additional regularization may be required beyond that provided by the historical information. We propose several novel extensions of the so-called power prior that adaptively combine a prior based upon the historical information with a variance-reducing prior that shrinks parameter values toward zero. The ideas are directly motivated by our work building mortality risk prediction models for pediatric patients receiving extracorporeal membrane oxygenation, or ECMO. We have developed a model on a registry-based cohort of ECMO patients and now seek to expand this model with additional biometric measurements, not available in the registry, collected on a small auxiliary cohort. Our adaptive priors are able to leverage the efficiency of the original model and identify novel mortality risk factors. We support this with a simulation study, which demonstrates the potential for efficiency gains in estimation under a variety of scenarios

Observational Characterization of the Downward Atmospheric Longwave Radiation at the Surface in the City of São Paulo

This work describes the seasonal and diurnal variations of downward longwave atmospheric irradiance (LW) at the surface in São Paulo, Brazil, using 5-min-averaged values of LW, air temperature, relative humidity, and solar radiation observed continuously and simultaneously from 1997 to 2006 on a micrometeorological platform, located at the top of a 4-story building. An objective procedure, including 2-step filtering and dome emission effect correction, was used to evaluate the quality of the 9-yr-long LW dataset. The comparison between LW values observed and yielded by the Surface Radiation Budget project shows spatial and temporal agreement, indicating that monthly and annual average values of LW observed in one point of São Paulo can be used as representative of the entire metropolitan region of São Paulo. The maximum monthly averaged value of the LW is observed during summer (389 ± 14 W m-2; January), and the minimum is observed during winter (332 ± 12 W m-2; July). The effective emissivity follows the LW and shows a maximum in summer (0.907 ± 0.032; January) and a minimum in winter (0.818 ± 0.029; June). The mean cloud effect, identified objectively by comparing the monthly averaged values of the LW during clear-sky days and all-sky conditions, intensified the monthly average LW by about 32.0 ± 3.5 W m-2 and the atmospheric effective emissivity by about 0.088 ± 0.024. In August, the driest month of the year in São Paulo, the diurnal evolution of the LW shows a minimum (325 ± 11 W m-2) at 0900 LT and a maximum (345 ± 12 W m-2) at 1800 LT, which lags behind (by 4 h) the maximum diurnal variation of the screen temperature. The diurnal evolution of effective emissivity shows a minimum (0.781 ± 0.027) during daytime and a maximum (0.842 ± 0.030) during nighttime. The diurnal evolution of all-sky condition and clear-sky day differences in the effective emissivity remain relatively constant (7% ± 1%), indicating that clouds do not change the emissivity diurnal pattern. The relationship between effective emissivity and screen air temperature and between effective emissivity and water vapor is complex. During the night, when the planetary boundary layer is shallower, the effective emissivity can be estimated by screen parameters. During the day, the relationship between effective emissivity and screen parameters varies from place to place and depends on the planetary boundary layer process. Because the empirical expressions do not contain enough information about the diurnal variation of the vertical stratification of air temperature and moisture in São Paulo, they are likely to fail in reproducing the diurnal variation of the surface emissivity. The most accurate way to estimate the LW for clear-sky conditions in São Paulo is to use an expression derived from a purely empirical approach

Default Priors for the Intercept Parameter in Logistic Regressions

In logistic regression, separation refers to the situation in which a linear combination of predictors perfectly discriminates the binary outcome. Because finite-valued maximum likelihood parameter estimates do not exist under separation, Bayesian regressions with informative shrinkage of the regression coefficients offer a suitable alternative. Little focus has been given on whether and how to shrink the intercept parameter. Based upon classical studies of separation, we argue that efficiency in estimating regression coefficients may vary with the intercept prior. We adapt alternative prior distributions for the intercept that downweight implausibly extreme regions of the parameter space rendering less sensitivity to separation. Through simulation and the analysis of exemplar datasets, we quantify differences across priors stratified by established statistics measuring the degree of separation. Relative to diffuse priors, our recommendations generally result in more efficient estimation of the regression coefficients themselves when the data are nearly separated. They are equally efficient in non-separated datasets, making them suitable for default use. Modest differences were observed with respect to out-of-sample discrimination. Our work also highlights the interplay between priors for the intercept and the regression coefficients: numerical results are more sensitive to the choice of intercept prior when using a weakly informative prior on the regression coefficients than an informative shrinkage prior