Holography in the EPRL Model

In this research announcement, we propose a new interpretation of the EPR quantization of the BC model using a functor we call the time functor, which is the first example of a CLa-ren functor. Under the hypothesis that the universe is in the Kodama state, we construct a holographic version of the model. Generalisations to other CLa-ren functors and connections to model category theory are considered.Comment: research announcement. Latex fil

Around the tangent cone theorem

A cornerstone of the theory of cohomology jump loci is the Tangent Cone theorem, which relates the behavior around the origin of the characteristic and resonance varieties of a space. We revisit this theorem, in both the algebraic setting provided by cdga models, and in the topological setting provided by fundamental groups and cohomology rings. The general theory is illustrated with several classes of examples from geometry and topology: smooth quasi-projective varieties, complex hyperplane arrangements and their Milnor fibers, configuration spaces, and elliptic arrangements.Comment: 39 pages; to appear in the proceedings of the Configurations Spaces Conference (Cortona 2014), Springer INdAM serie

Composite vertices that lead to soft form factors

The momentum-space cut-off parameter $\Lambda$ of hadronic vertex functions is studied in this paper. We use a composite model where we can measure the contributions of intermediate particle propagations to $\Lambda$. We show that in many cases a composite vertex function has a much smaller cut-off than its constituent vertices, particularly when light constituents such as pions are present in the intermediate state. This suggests that composite meson-baryon-baryon vertex functions are rather soft, i.e., they have \Lambda considerably less than 1 GeV. We discuss the origin of this softening of form factors as well as the implications of our findings on the modeling of nuclear reactions.Comment: REVTex, 19 pages, 5 figs(to be provided on request

The choice of tree prior and molecular clock does not substantially affect phylogenetic inferences of diversification rates

Comparative methods allow researchers to make inferences about evolutionary processes and patterns from phylogenetic trees. In Bayesian phylogenetics, estimating a phylogeny requires specifying priors on parameters characterizing the branching process and rates of substitution among lineages, in addition to others. Accordingly, characterizing the effect of prior selection on phylogenies is an active area of research. The choice of priors may systematically bias phylogenetic reconstruction and, subsequently, affect conclusions drawn from the resulting phylogeny. Here, we focus on the impact of priors in Bayesian phylogenetic inference and evaluate how they affect the estimation of parameters in macroevolutionary models of lineage diversification. Specifically, we simulate trees under combinations of tree priors and molecular clocks, simulate sequence data, estimate trees, and estimate diversification parameters (e.g., speciation and extinction rates) from these trees. When substitution rate heterogeneity is large, diversification rate estimates deviate substantially from those estimated under the simulation conditions when not captured by an appropriate choice of relaxed molecular clock. However, in general, we find that the choice of tree prior and molecular clock has relatively little impact on the estimation of diversification rates insofar as the sequence data are sufficiently informative and substitution rate heterogeneity among lineages is low-to-moderate

Measurements of 0.2 to 20 GeV/n cosmic-ray proton and helium spectra from 1997 through 2002 with the BESS spectrometer

We measured low energy cosmic-ray proton and helium spectra in the kinetic energy range 0.215 - 21.5 GeV/n at different solar activities during a period from 1997 to 2002. The observations were carried out with the BESS spectrometer launched on a balloon at Lynn Lake, Canada. A calculation for the correction of secondary particle backgrounds from the overlying atmosphere was improved by using the measured spectra at small atmospheric depths ranging from 5 through 37 g/cm^2. The uncertainties including statistical and systematic errors of the obtained spectra at the top of atmosphere are 5-7 % for protons and 6-9 % for helium nuclei in the energy range 0.5 - 5 GeV/n.Comment: 27 pages, 7 Tables, 9 figures, Submitted to Astroparticle Physic

Hadron Production in Heavy Ion Collisions

We review hadron production in heavy ion collisions with emphasis on pion and kaon production at energies below 2 AGeV and on partonic collectivity at RHIC energies.Comment: 31 pages, 26 figures, accepted for publication in Landolt-Boernstein Volume 1-23

Measurements of Proton, Helium and Muon Spectra at Small Atmospheric Depths with the BESS Spectrometer

The cosmic-ray proton, helium, and muon spectra at small atmospheric depths of 4.5 -- 28 g/cm^2 were precisely measured during the slow descending period of the BESS-2001 balloon flight. The variation of atmospheric secondary particle fluxes as a function of atmospheric depth provides fundamental information to study hadronic interactions of the primary cosmic rays with the atmosphere.Comment: 21 pages, 11 figures, 4 table

Measurement of cosmic-ray low-energy antiproton spectrum with the first BESS-Polar Antarctic flight

The BESS-Polar spectrometer had its first successful balloon flight over Antarctica in December 2004. During the 8.5-day long-duration flight, almost 0.9 billion events were recorded and 1,520 antiprotons were detected in the energy range 0.1-4.2 GeV. In this paper, we report the antiproton spectrum obtained, discuss the origin of cosmic-ray antiprotons, and use antiprotons to probe the effect of charge sign dependent drift in the solar modulation.Comment: 18 pages, 1 table, 5 figures, submitted to Physics Letters

Characterizing mood disorders in the AFFECT study: a large, longitudinal, and phenotypically rich genetic cohort in the US

There has recently been marked progress in identifying genetic risk factors for major depression (MD) and bipolar disorder (BD); however, few systematic efforts have been made to elucidate heterogeneity that exists within and across these diagnostic taxa. The Affective disorders, Environment, and Cognitive Trait (AFFECT) study presents an opportunity to identify and associate the structure of cognition and symptom-level domains across the mood disorder spectrum in a prospective study from a diverse US population. Participants were recruited from the 23andMe, Inc research participant database and through social media; self-reported diagnosis of MD or BD by a medical professional and medication status data were used to enrich for mood-disorder cases. Remote assessments were used to acquire an extensive range of phenotypes, including mood state, transdiagnostic symptom severity, task-based measures of cognition, environmental exposures, personality traits. In this paper we describe the study design, and the demographic and clinical characteristics of the cohort. In addition we report genetic ancestry, SNP heritability, and genetic correlations with other large cohorts of mood disorders. A total of 48,467 participants were enrolled: 14,768 with MD, 9864 with BD, and 23,835 controls. Upon enrollment, 47% of participants with MD and 27% with BD indicated being in an active mood episode. Cases reported early ages of onset (mean = 13.2 and 14.3 years for MD and BD, respectively), and high levels of recurrence (78.6% and 84.9% with >5 episodes), psychotherapy, and psychotropic medication use. SNP heritability on the liability scale for the ascertained MD participants (0.19–0.21) was consistent with the high level of disease severity in this cohort, while BD heritability estimates (0.16–0.22) were comparable to reports in other large scale genomic studies of mood disorders. Genetic correlations between the AFFECT cohort and other large-scale cohorts were high for MD but not for BD. By incorporating transdiagnostic symptom assessments, repeated measures, and genomic data, the AFFECT study represents a unique resource for dissecting the structure of mood disorders across multiple levels of analysis. In addition, the fully remote nature of the study provides valuable insights for future virtual and decentralized clinical trials within mood disorders