Physics of An Ultrahigh-Statistics Charm Experiment

We review the physics goals of an ultrahigh-statistics charm experiment and place them in the broader context of the community's efforts to study the Standard Model and to search for physics beyond the Standard Model, and we point out some of the experimental difficulties which must be overcome if these goals are to be met.Comment: 9 pages, no figure

Model-independent partial wave analysis using a massively-parallel fitting framework

The functionality of GooFit, a GPU-friendly framework for doing maximum-likelihood fits, has been extended to extract model-independent S-wave amplitudes in three-body decays such as $D^+ \to h^+h^+h^-$. A full amplitude analysis is done where the magnitudes and phases of the S-wave amplitudes are anchored at a finite number of $m^2(h^+h^-)$ control points, and a cubic spline is used to interpolate between these points. The amplitudes for P-wave and D-wave intermediate states are modeled as spin-dependent Breit-Wigner resonances. GooFit uses the Thrust library, with a CUDA backend for NVIDIA GPUs and an OpenMP backend for threads with conventional CPUs. Performance on a variety of platforms is compared. Executing on systems with GPUs is typically a few hundred times faster than executing the same algorithm on a single CPU.Comment: 5 pages, 3 figures, 2 tables, submitted to the proceedings of the 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 201

Hnrnph1 Is A Quantitative Trait Gene for Methamphetamine Sensitivity.

Psychostimulant addiction is a heritable substance use disorder; however its genetic basis is almost entirely unknown. Quantitative trait locus (QTL) mapping in mice offers a complementary approach to human genome-wide association studies and can facilitate environment control, statistical power, novel gene discovery, and neurobiological mechanisms. We used interval-specific congenic mouse lines carrying various segments of chromosome 11 from the DBA/2J strain on an isogenic C57BL/6J background to positionally clone a 206 kb QTL (50,185,512-50,391,845 bp) that was causally associated with a reduction in the locomotor stimulant response to methamphetamine (2 mg/kg, i.p.; DBA/2J < C57BL/6J)-a non-contingent, drug-induced behavior that is associated with stimulation of the dopaminergic reward circuitry. This chromosomal region contained only two protein coding genes-heterogeneous nuclear ribonucleoprotein, H1 (Hnrnph1) and RUN and FYVE domain-containing 1 (Rufy1). Transcriptome analysis via mRNA sequencing in the striatum implicated a neurobiological mechanism involving a reduction in mesolimbic innervation and striatal neurotransmission. For instance, Nr4a2 (nuclear receptor subfamily 4, group A, member 2), a transcription factor crucial for midbrain dopaminergic neuron development, exhibited a 2.1-fold decrease in expression (DBA/2J < C57BL/6J; p 4.2 x 10-15). Transcription activator-like effector nucleases (TALENs)-mediated introduction of frameshift deletions in the first coding exon of Hnrnph1, but not Rufy1, recapitulated the reduced methamphetamine behavioral response, thus identifying Hnrnph1 as a quantitative trait gene for methamphetamine sensitivity. These results define a novel contribution of Hnrnph1 to neurobehavioral dysfunction associated with dopaminergic neurotransmission. These findings could have implications for understanding the genetic basis of methamphetamine addiction in humans and the development of novel therapeutics for prevention and treatment of substance abuse and possibly other psychiatric disorders

Demultiplexing of OTDM-DPSK signals based on a single semiconductor optical amplifier and optical filtering

We propose and demonstrate the use of a single semiconductor optical amplifier (SOA) and optical filtering to time demultiplex tributaries from an optical time division multiplexing-differential phase shift keying (OTDM-DPSK) signal. The scheme takes advantage of the fact that phase variations added to the target channel by cross-phase modulation from the control signal are effectively subtracted in the differential demodulation scheme employed for DPSK signals. Demultiplexing from 80 to 40 Gbit/s is demonstrated with moderate power penalty using an SOA with recovery time twice as long as the bit period at 80 Gbit/s. Large dynamic ranges for the input power and SOA current are experimentally demonstrated. The scheme is expected to be scalable toward higher bit rates.</p

BACE1 activity impairs neuronal glucose oxidation:rescue by beta-hydroxybutyrate and lipoic acid

Glucose hypometabolism and impaired mitochondrial function in neurons have been suggested to play early and perhaps causative roles in Alzheimer's disease (AD) pathogenesis. Activity of the aspartic acid protease, beta-site amyloid precursor protein (APP) cleaving enzyme 1 (BACE1), responsible for beta amyloid peptide generation, has recently been demonstrated to modify glucose metabolism. We therefore examined, using a human neuroblastoma (SH-SY5Y) cell line, whether increased BACE1 activity is responsible for a reduction in cellular glucose metabolism. Overexpression of active BACE1, but not a protease-dead mutant BACE1, protein in SH-SY5Y cells reduced glucose oxidation and the basal oxygen consumption rate, which was associated with a compensatory increase in glycolysis. Increased BACE1 activity had no effect on the mitochondrial electron transfer process but was found to diminish substrate delivery to the mitochondria by inhibition of key mitochondrial decarboxylation reaction enzymes. This BACE1 activity-dependent deficit in glucose oxidation was alleviated by the presence of beta hydroxybutyrate or &alpha;-lipoic acid. Consequently our data indicate that raised cellular BACE1 activity drives reduced glucose oxidation in a human neuronal cell line through impairments in the activity of specific tricarboxylic acid cycle enzymes. Because this bioenergetic deficit is recoverable by neutraceutical compounds we suggest that such agents, perhaps in conjunction with BACE1 inhibitors, may be an effective therapeutic strategy in the early-stage management or treatment of AD

HEP Community White Paper on Software trigger and event reconstruction

Realizing the physics programs of the planned and upgraded high-energy physics (HEP) experiments over the next 10 years will require the HEP community to address a number of challenges in the area of software and computing. For this reason, the HEP software community has engaged in a planning process over the past two years, with the objective of identifying and prioritizing the research and development required to enable the next generation of HEP detectors to fulfill their full physics potential. The aim is to produce a Community White Paper which will describe the community strategy and a roadmap for software and computing research and development in HEP for the 2020s. The topics of event reconstruction and software triggers were considered by a joint working group and are summarized together in this document.Comment: Editors Vladimir Vava Gligorov and David Lang

Comparing and improving hybrid deep learning algorithms for identifying and locating primary vertices

Using deep neural networks to identify and locate proton-proton collision points, or primary vertices, in LHCb has been studied for several years. Preliminary results demonstrated the ability for a hybrid deep learning algorithm to achieve similar or better physics performances compared to standard heuristic approaches. The previously studied architectures relied directly on hand-calculated Kernel Density Estimators (KDEs) as input features. Calculating these KDEs was slow, making use of the DNN inference engines in the experiment's real-time analysis (trigger) system problematic. Here we present recent results from a high-performance hybrid deep learning algorithm that uses track parameters as input features rather than KDEs, opening the path to deployment in the real-time trigger system.Comment: Proceedings for the ACAT 2022 conferenc