Parallelized and Vectorized Tracking Using Kalman Filters with CMS Detector Geometry and Events

The High-Luminosity Large Hadron Collider at CERN will be characterized by greater pileup of events and higher occupancy, making the track reconstruction even more computationally demanding. Existing algorithms at the LHC are based on Kalman filter techniques with proven excellent physics performance under a variety of conditions. Starting in 2014, we have been developing Kalman-filter-based methods for track finding and fitting adapted for many-core SIMD processors that are becoming dominant in high-performance systems. This paper summarizes the latest extensions to our software that allow it to run on the realistic CMS-2017 tracker geometry using CMSSW-generated events, including pileup. The reconstructed tracks can be validated against either the CMSSW simulation that generated the hits, or the CMSSW reconstruction of the tracks. In general, the code's computational performance has continued to improve while the above capabilities were being added. We demonstrate that the present Kalman filter implementation is able to reconstruct events with comparable physics performance to CMSSW, while providing generally better computational performance. Further plans for advancing the software are discussed

AtDelfi: Automatically Designing Legible, Full Instructions For Games

This paper introduces a fully automatic method for generating video game tutorials. The AtDELFI system (AuTomatically DEsigning Legible, Full Instructions for games) was created to investigate procedural generation of instructions that teach players how to play video games. We present a representation of game rules and mechanics using a graph system as well as a tutorial generation method that uses said graph representation. We demonstrate the concept by testing it on games within the General Video Game Artificial Intelligence (GVG-AI) framework; the paper discusses tutorials generated for eight different games. Our findings suggest that a graph representation scheme works well for simple arcade style games such as Space Invaders and Pacman, but it appears that tutorials for more complex games might require higher-level understanding of the game than just single mechanics.Comment: 10 pages, 11 figures, published at Foundations of Digital Games Conference 201

Reconstruction of Charged Particle Tracks in Realistic Detector Geometry Using a Vectorized and Parallelized Kalman Filter Algorithm

One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is finding and fitting particle tracks during event reconstruction. Algorithms used at the LHC today rely on Kalman filtering, which builds physical trajectories incrementally while incorporating material effects and error estimation. Recognizing the need for faster computational throughput, we have adapted Kalman-filter-based methods for highly parallel, many-core SIMD and SIMT architectures that are now prevalent in high-performance hardware. Previously we observed significant parallel speedups, with physics performance comparable to CMS standard tracking, on Intel Xeon, Intel Xeon Phi, and (to a limited extent) NVIDIA GPUs. While early tests were based on artificial events occurring inside an idealized barrel detector, we showed subsequently that our mkFit software builds tracks successfully from complex simulated events (including detector pileup) occurring inside a geometrically accurate representation of the CMS-2017 tracker. Here, we report on advances in both the computational and physics performance of mkFit, as well as progress toward integration with CMS production software. Recently we have improved the overall efficiency of the algorithm by preserving short track candidates at a relatively early stage rather than attempting to extend them over many layers. Moreover, mkFit formerly produced an excess of duplicate tracks; these are now explicitly removed in an additional processing step. We demonstrate that with these enhancements, mkFit becomes a suitable choice for the first iteration of CMS tracking, and eventually for later iterations as well. We plan to test this capability in the CMS High Level Trigger during Run 3 of the LHC, with an ultimate goal of using it in both the CMS HLT and offline reconstruction for the HL-LHC CMS tracker

Transport and binding of tumor necrosis factor-α in articular cartilage depend on its quaternary structure

The effect of tumor necrosis factor-α (TNFα) on cartilage matrix degradation is mediated by its transport and binding within the extracellular matrix (ECM) of the tissue, which mediates availability to cell receptors. Since the bioactive form of TNFα is a homotrimer of monomeric subunits, conversion between trimeric and monomeric forms during intratissue transport may affect binding to ECM and, thereby, bioactivity within cartilage. We studied the transport and binding of TNFα in cartilage, considering the quaternary structure of this cytokine. Competitive binding assays showed significant binding of TNFα in cartilage tissue, leading to an enhanced uptake. However, studies in which TNFα was cross-linked to remain in the trimeric form revealed that the binding of trimeric TNFα was negligible. Thus, binding of TNFα to ECM was associated with the monomeric form. Binding of TNFα was not disrupted by pre-treating cartilage tissue with trypsin, which removes proteoglycans and glycoproteins but leaves the collagen network intact. Therefore, proteoglycan loss during osteoarthritis should only alter the passive diffusion of TNFα but not its binding interaction with the remaining matrix. Our results suggest that matrix binding and trimer–monomer conversion of TNFα both play crucial roles in regulating the accessibility of bioactive TNFα within cartilage.National Institute of Arthritis and Musculoskeletal and Skin Diseases (U.S.) (Grant AR45779)National Institute of Arthritis and Musculoskeletal and Skin Diseases (U.S.) (Grant AR60331

Quantum state preparation and macroscopic entanglement in gravitational-wave detectors

Long-baseline laser-interferometer gravitational-wave detectors are operating at a factor of 10 (in amplitude) above the standard quantum limit (SQL) within a broad frequency band. Such a low classical noise budget has already allowed the creation of a controlled 2.7 kg macroscopic oscillator with an effective eigenfrequency of 150 Hz and an occupation number of 200. This result, along with the prospect for further improvements, heralds the new possibility of experimentally probing macroscopic quantum mechanics (MQM) - quantum mechanical behavior of objects in the realm of everyday experience - using gravitational-wave detectors. In this paper, we provide the mathematical foundation for the first step of a MQM experiment: the preparation of a macroscopic test mass into a nearly minimum-Heisenberg-limited Gaussian quantum state, which is possible if the interferometer's classical noise beats the SQL in a broad frequency band. Our formalism, based on Wiener filtering, allows a straightforward conversion from the classical noise budget of a laser interferometer, in terms of noise spectra, into the strategy for quantum state preparation, and the quality of the prepared state. Using this formalism, we consider how Gaussian entanglement can be built among two macroscopic test masses, and the performance of the planned Advanced LIGO interferometers in quantum-state preparation

Searching for a Stochastic Background of Gravitational Waves with LIGO

The Laser Interferometer Gravitational-wave Observatory (LIGO) has performed the fourth science run, S4, with significantly improved interferometer sensitivities with respect to previous runs. Using data acquired during this science run, we place a limit on the amplitude of a stochastic background of gravitational waves. For a frequency independent spectrum, the new limit is $\Omega_{\rm GW} < 6.5 \times 10^{-5}$. This is currently the most sensitive result in the frequency range 51-150 Hz, with a factor of 13 improvement over the previous LIGO result. We discuss complementarity of the new result with other constraints on a stochastic background of gravitational waves, and we investigate implications of the new result for different models of this background.Comment: 37 pages, 16 figure

The Role of Health Behaviours Across the Life Course in the Socioeconomic Patterning of All-Cause Mortality: The West of Scotland Twenty-07 Prospective Cohort Study

Background: Socioeconomic differentials in mortality are increasing in many industrialised countries. Purpose: This study aims to examine the role of behaviours (smoking, alcohol, exercise, and diet) in explaining socioeconomic differentials in mortality and whether this varies over the life course, between cohorts and by gender. Methods: Analysis of two representative population cohorts of men and women, born in the 1950s and 1930s, were performed. Health behaviours were assessed on five occasions over 20 years. Results: Health behaviours explained a substantial part of the socioeconomic differentials in mortality. Cumulative behaviours and those that were more strongly associated with socioeconomic status had the greatest impact. For example, in the 1950s cohort, the age-sex adjusted hazard ratio comparing respondents with manual versus non-manual occupational status was 1.80 (1.25, 2.58); adjustment for cumulative smoking over 20 years attenuated the association by 49 %, diet by 43 %, drinking by 13 % and inactivity by only 1%. Conclusions: Health behaviours have an important role in explaining socioeconomic differentials in mortality. © 2013 The Author(s)

Family Income Gradients in the Health and Health Care Access of US Children

This study sought to examine the shape and magnitude of family income gradients in US children’s health, access to care, and use of services. We analyzed cross-sectional data from the 2003 National Survey of Children’s Health, a telephone survey of 102,353 parents of children aged 0–17 years. Associations between family income [Below 100% Federal Poverty Level (FPL), 100–199% FPL, 200–299% FPL, 300–399% FPL, 400% FPL or Greater] and a set of 32 health and health care indicators were examined using linear polynomial testing and multivariate logistic regression. The percentage of children in better health increased with family income for 15 health outcomes. In multivariate logistic regression models that controlled for health insurance coverage and socio-demographic confounders, odds ratios >2 comparing the lowest to the highest income groups were noted for health conditions across both physical and developmental domains (diabetes, headaches, ear infections, learning disabilities, behavior/conduct problems, speech problems). Parent-reported global child health status, activity limitation, and oral health status showed steeper gradients than specific chronic and acute conditions. Ten measures of health care access and utilization were associated with family income in multivariate logistic regression models. Income gradients are pervasive across many health indicators at an early age. Social and health policy interventions are needed to address the multitude of factors that can affect children’s health and initiate disparities in development