215 research outputs found

    Spectral Analysis of Jet Substructure with Neural Networks: Boosted Higgs Case

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    Jets from boosted heavy particles have a typical angular scale which can be used to distinguish them from QCD jets. We introduce a machine learning strategy for jet substructure analysis using a spectral function on the angular scale. The angular spectrum allows us to scan energy deposits over the angle between a pair of particles in a highly visual way. We set up an artificial neural network (ANN) to find out characteristic shapes of the spectra of the jets from heavy particle decays. By taking the Higgs jets and QCD jets as examples, we show that the ANN of the angular spectrum input has similar performance to existing taggers. In addition, some improvement is seen when additional extra radiations occur. Notably, the new algorithm automatically combines the information of the multi-point correlations in the jet.Comment: 18 pages, 12 figures, published in JHEP. A cut-based analysis is adde

    Mapping Dark Matter in the Milky Way using Normalizing Flows and Gaia DR3

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    We present a novel, data-driven analysis of Galactic dynamics, using unsupervised machine learning -- in the form of density estimation with normalizing flows -- to learn the underlying phase space distribution of 6 million nearby stars from the Gaia DR3 catalog. Solving the collisionless Boltzmann equation with the assumption of approximate equilibrium, we calculate -- for the first time ever -- a model-free, unbinned, fully 3D map of the local acceleration and mass density fields within a 3 kpc sphere around the Sun. As our approach makes no assumptions about symmetries, we can test for signs of disequilibrium in our results. We find our results are consistent with equilibrium at the 10% level, limited by the current precision of the normalizing flows. After subtracting the known contribution of stars and gas from the calculated mass density, we find clear evidence for dark matter throughout the analyzed volume. Assuming spherical symmetry and averaging mass density measurements, we find a local dark matter density of 0.47±0.05  GeV/cm30.47\pm 0.05\;\mathrm{GeV/cm}^3. We fit our results to a generalized NFW, and find a profile broadly consistent with other recent analyses.Comment: 19 pages, 13 figures, 3 table

    Monojet signatures from heavy colored particles: future collider sensitivities and theoretical uncertainties

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    In models with colored particle Q that can decay into a dark matter candidate X, the relevant collider process pp → QQ¯ → X X¯ + jets gives rise to events with significant transverse momentum imbalance. When the masses of Q and X are very close, the relevant signature becomes monojetlike, and Large Hadron Collider (LHC) search limits become much less constraining. In this paper, we study the current and anticipated experimental sensitivity to such particles at the High-Luminosity LHC at √s = 14 TeV with L = 3 ab−1 of data and the proposed High-Energy LHC at √s = 27 TeV with L = 15 ab−1 of data. We estimate the reach for various Lorentz and QCD color representations of Q. Identifying the nature of Q is very important to understanding the physics behind the monojet signature. Therefore, we also study the dependence of the observables built from the pp → QQ¯ + j process on Q itself. Using the state-of-theart Monte Carlo suites MadGraph5_aMC@NLO+Pythia8 and Sherpa, we find that when these observables are calculated at NLO in QCD with parton shower matching and multijet merging, the residual theoretical uncertainties are comparable to differences observed when varying the quantum numbers of Q itself. We find, however, that the precision achievable with NNLO calculations, where available, can resolve this dilemma

    OPTIMASS: A Package for the Minimization of Kinematic Mass Functions with Constraints

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    Reconstructed mass variables, such as M2M_2, M2CM_{2C}, MTM_T^\star, and MT2WM_{T2}^W, play an essential role in searches for new physics at hadron colliders. The calculation of these variables generally involves constrained minimization in a large parameter space, which is numerically challenging. We provide a C++ code, OPTIMASS, which interfaces with the MINUIT library to perform this constrained minimization using the Augmented Lagrangian Method. The code can be applied to arbitrarily general event topologies and thus allows the user to significantly extend the existing set of kinematic variables. We describe this code and its physics motivation, and demonstrate its use in the analysis of the fully leptonic decay of pair-produced top quarks using the M2M_2 variables.Comment: 39 pages, 12 figures, (1) minor revision in section 3, (2) figure added in section 4.3, (3) reference added and (4) matched with published versio

    Insulin Secretion and Incretin Hormone Concentration in Women with Previous Gestational Diabetes Mellitus

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    BackgroundWe examined the change in the levels of incretin hormone and effects of glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide 1 (GLP-1) on insulin secretion in women with previous gestational diabetes (pGDM).MethodsA 75-g oral glucose tolerance test (OGTT) was conducted on 34 women with pGDM. In addition, 11 women with normal glucose tolerance, matched for age, height and weight, were also tested. The insulin, GIP, GLP-1, and glucagon concentrations were measured, and their anthropometric and biochemical markers were also measured.ResultsAmong 34 women with pGDM, 18 had normal glucose tolerance, 13 had impaired glucose tolerance (IGT) and 1 had diabetes. No significant differences were found in GLP-1 concentration between the pGDM and control group. However, a significantly high level of glucagon was present in the pGDM group at 30 minutes into the OGTT. The GIP concentration was elevated at 30 minutes and 60 minutes in the pGDM group. With the exception of the 30-minute timepoint, women with IGT had significantly high blood glucose from 0 to 120 minutes. However, there was no significant difference in insulin or GLP-1 concentration. The GIP level was significantly high from 0 to 90 minutes in patients diagnosed with IGT.ConclusionGLP-1 secretion does not differ between pGDM patients and normal women. GIP was elevated, but that does not seem to induce in increase in insulin secretion. Therefore, we conclude that other factors such as heredity and environment play important roles in the development of type 2 diabetes

    Whole Genome Analysis of the Red-Crowned Crane Provides Insight into Avian Longevity

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    The red-crowned crane (Grus japonensis) is an endangered, large-bodied crane native to East Asia. It is a traditional symbol of longevity and its long lifespan has been confirmed both in captivity and in the wild. Lifespan in birds is known to be positively correlated with body size and negatively correlated with metabolic rate, though the genetic mechanisms for the red-crowned crane's long lifespan have not previously been investigated. Using whole genome sequencing and comparative evolutionary analyses against the grey-crowned crane and other avian genomes, including the long-lived common ostrich, we identified red-crowned crane candidate genes with known associations with longevity. Among these are positively selected genes in metabolism and immunity pathways (NDUFA5, NDUFA8, NUDT12, SOD3, CTH, RPA1, PHAX, HNMT, HS2ST1, PPCDC, PSTK CD8B, GP9, IL-9R, and PTPRC). Our analyses provide genetic evidence for low metabolic rate and longevity, accompanied by possible convergent adaptation signatures among distantly related large and long-lived birds. Finally, we identified low genetic diversity in the red-crowned crane, consistent with its listing as an endangered species, and this genome should provide a useful genetic resource for future conservation studies of this rare and iconic species