Ursinus College Alumni Journal, Winter 1950

A good investment • Locally speaking • To the ladies • President\u27s page • Alumni Association appoints committees • Dr. Lentz attends church unification conference • Nine Ursinus hockey stars in national tourney • York County alumni only slightly winded after vigorous square dance opener • Ursinus Women\u27s Club holds yuletide luncheon • Woman dead, returns to life as result of Dr. Valloti\u27s diagnosis • College establishes new placement bureau • So Much to Be Done filmed on Ursinus campus • Dr. John Mauchly invents new computing machine • McClure elected president of St. Andrew\u27s Society • Bailey elected officer of athletic conference • Art catalogue prepared for Lachman paintings • Chandler reelected to museum board • Necrology • News about town: Coed wins magazine post; Francis heads school board; Hartzell wins DeMolay honor; Sewage plant in service • Sports review: Bruin wrestlers take eighth straight meet; Basketball team compiles 2-4 record at midseason; Pattison to captain girls\u27 swimming team; Jayvee hockey team\u27s 3-year record broken; JV courtmen rack up six wins in eight tilts; Lone victory closes poor grid season; Hockeyites win five, tie one, lose one; College hockey star to play in Europe; Soccermen beat alumni for season\u27s only win • News about ourselveshttps://digitalcommons.ursinus.edu/alumnijournal/1037/thumbnail.jp

Ursinus College Alumni Journal, Spring 1950

Constitutional amendments proposed extending terms of office to two years • President\u27s page • Alumni Day set for June third • Ursinus Woman\u27s Club entertains senior girls • Lloyd Wood, candidate for lieutenant-governor • Kenneth Fink directs opinion survey service • Frank Tornetta named assistant anesthesiologist • Dr. Charles Dotterer heads hospital staff • Alpha Sigma Nu alumnae will meet June third • Woman\u27s Club will hear Captain John Graf • Salinger hits movies • 15 at Glenwood reunion • Phi Psi alumnae meet • Ray Gurzynski appointed head coach of football • Viewbook becomes new Ursinus agent • 246 to receive degrees at 80th commencement • Dean Stahr and alumnae meet at convention • Eugene Miller lectures on world affairs • Church synod to meet at Ursinus in June • Necrology • Coeds trip the light fantastic on Ursinus greensward since 1905 • Whence Ursinus? • Sports review: Baseball team opens with 3 straight wins; Men\u27s tennis team wins, 8-1; loses, 9-0; 1950 football schedule includes Adelphi College; Cumpstone opens season with record javelin toss; Bronson, Young named cage co-captains; Helfferich wins title as matmen close season; Freshman Joan Compton wins breaststroke title • News about ourselveshttps://digitalcommons.ursinus.edu/alumnijournal/1038/thumbnail.jp

Modeling scale-dependent bias on the baryonic acoustic scale with the statistics of peaks of Gaussian random fields

Models of galaxy and halo clustering commonly assume that the tracers can be treated as a continuous field locally biased with respect to the underlying mass distribution. In the peak model pioneered by BBKS, one considers instead density maxima of the initial, Gaussian mass density field as an approximation to the formation site of virialized objects. In this paper, the peak model is extended in two ways to improve its predictive accuracy. Firstly, we derive the two-point correlation function of initial density peaks up to second order and demonstrate that a peak-background split approach can be applied to obtain the k-independent and k-dependent peak bias factors at all orders. Secondly, we explore the gravitational evolution of the peak correlation function within the Zel'dovich approximation. We show that the local (Lagrangian) bias approach emerges as a special case of the peak model, in which all bias parameters are scale-independent and there is no statistical velocity bias. We apply our formulae to study how the Lagrangian peak biasing, the diffusion due to large scale flows and the mode-coupling due to nonlocal interactions affect the scale dependence of bias from small separations up to the baryon acoustic oscillation (BAO) scale. For 2-sigma density peaks collapsing at z=0.3, our model predicts a ~ 5% residual scale-dependent bias around the acoustic scale that arises mostly from first-order Lagrangian peak biasing (as opposed to second-order gravity mode-coupling). We also search for a scale dependence of bias in the large scale auto-correlation of massive halos extracted from a very large N-body simulation provided by the MICE collaboration. For halos with mass M>10^{14}Msun/h, our measurements demonstrate a scale-dependent bias across the BAO feature which is very well reproduced by a prediction based on the peak model.Comment: (v1): 23 pages text, 8 figures + appendix (v2): typos fixed, references added, accepted for publication in PR

The Physical Models and Statistical Procedures Used in the RACER Monte Carlo Code

This report describes the MCV (Monte Carlo - Vectorized)Monte Carlo neutron transport code [Brown, 1982, 1983; Brown and Mendelson, 1984a]. MCV is a module in the RACER system of codes that is used for Monte Carlo reactor physics analysis. The MCV module contains all of the neutron transport and statistical analysis functions of the system, while other modules perform various input-related functions such as geometry description, material assignment, output edit specification, etc. MCV is very closely related to the 05R neutron Monte Carlo code [Irving et al., 1965] developed at Oak Ridge National Laboratory. 05R evolved into the 05RR module of the STEMB system, which was the forerunner of the RACER system. Much of the overall logic and physics treatment of 05RR has been retained and, indeed, the original verification of MCV was achieved through comparison with STEMB results. MCV has been designed to be very computationally efficient [Brown, 1981, Brown and Martin, 1984b; Brown, 1986]. It was originally programmed to make use of vector-computing architectures such as those of the CDC Cyber- 205 and Cray X-MP. MCV was the first full-scale production Monte Carlo code to effectively utilize vector-processing capabilities. Subsequently, MCV was modified to utilize both distributed-memory [Sutton and Brown, 1994] and shared memory parallelism. The code has been compiled and run on platforms ranging from 32-bit UNIX workstations to clusters of 64-bit vector-parallel supercomputers. The computational efficiency of the code allows the analyst to perform calculations using many more neutron histories than is practical with most other Monte Carlo codes, thereby yielding results with smaller statistical uncertainties. MCV also utilizes variance reduction techniques such as survival biasing, splitting, and rouletting to permit additional reduction in uncertainties. While a general-purpose neutron Monte Carlo code, MCV is optimized for reactor physics calculations. It has the capability of performing iterated-source (criticality), multiplied-fixed-source, and fixed-source calculations. MCV uses a highly detailed continuous-energy (as opposed to multigroup) representation of neutron histories and cross section data. The spatial modeling is fully three-dimensional (3-D), and any geometrical region that can be described by quadric surfaces may be represented. The primary results are region-wise reaction rates, neutron production rates, slowing-down-densities, fluxes, leakages, and when appropriate the eigenvalue or multiplication factor. Region-wise nuclidic reaction rates are also computed, which may then be used by other modules in the system to determine time-dependent nuclide inventories so that RACER can perform depletion calculations. Furthermore, derived quantities such as ratios and sums of primary quantities and/or other derived quantities may also be calculated. MCV performs statistical analyses on output quantities, computing estimates of the 95% confidence intervals as well as indicators as to the reliability of these estimates. The remainder of this chapter provides an overview of the MCV algorithm. The following three chapters describe the MCV mathematical, physical, and statistical treatments in more detail. Specifically, Chapter 2 discusses topics related to tracking the histories including: geometry modeling, how histories are moved through the geometry, and variance reduction techniques related to the tracking process. Chapter 3 describes the nuclear data and physical models employed by MCV. Chapter 4 discusses the tallies, statistical analyses, and edits. Chapter 5 provides some guidance as to how to run the code, and Chapter 6 is a list of the code input options

Please mind the gap: students’ perspectives of the transition in academic skills between A-level and degree level geography

This paper explores first-year undergraduates’ perceptions of the transition from studying geography at pre-university level to studying for a degree. This move is the largest step students make in their education, and the debate about it in the UK has been reignited due to the government’s planned changes to A-level geography. However, missing from most of this debate is an appreciation of the way in which geography students themselves perceive their transition to university. This paper begins to rectify this absence. Using student insights, we show that their main concern is acquiring the higher level skills required for university learning

Resumming Cosmological Perturbations via the Lagrangian Picture: One-loop Results in Real Space and in Redshift Space

We develop a new approach to study the nonlinear evolution in the large-scale structure of the Universe both in real space and in redshift space, extending the standard perturbation theory of gravitational instability. Infinite series of terms in standard Eulerian perturbation theory are resummed as a result of our starting from a Lagrangian description of perturbations. Delicate nonlinear effects on scales of the baryon acoustic oscillations are more accurately described by our method than the standard one. Our approach differs from other resummation techniques recently proposed, such as the renormalized perturbation theory, etc., in that we use simple techniques and thus resulting equations are undemanding to evaluate, and in that our approach is capable of quantifying the nonlinear effects in redshift space. The power spectrum and correlation function of our approach are in good agreement with numerical simulations in literature on scales of baryon acoustic oscillations. Especially, nonlinear effects on the baryon acoustic peak of the correlation function are accurately described both in real space and in redshift space. Our approach provides a unique opportunity to analytically investigate the nonlinear effects on baryon acoustic scales in observable redshift space, which is requisite in constraining the nature of dark energy, the curvature of the Universe, etc., by redshift surveys.Comment: 18 pages, 12 figures, replaced to match the published versio

Search for Gravitational Waves from Compact Binary Coalescence in LIGO and Virgo Data from S5 and VSR1

We report the results of the first search for gravitational waves from compact binary coalescence using data from the Laser Interferometer Gravitational-wave Observatory (LIGO) and Virgo detectors. Five months of data were collected during the concurrent S5 (UGO) and VSRI (Virgo) science runs. The search focused on signals from binary mergers with a total mass between 2 and 35 Solar Mass. No gravitational waves are identified. The cumulative 90%-confidence upper limits on the rate of compact binary coalescence are calculated for non-spinning binary neutron stars, black hole-neutron star systems, and binary black holes to be 8.7 x 10(exp -3) / yr-1/L(sub 10) 2.2 x 10-3 yr-1L101, and 4.4 x 10(exp -4)3) / yr-1/L(sub 10) respectively, where L (sub 10) is 10(exp 10) times the blue solar luminosity. These upper limits are compared with astrophysical expectations