Tupendra Oli, Wilkie Olin-Ammentorp, Xingfu Wu
et al.
As particle physics experiments evolve to achieve higher energies and resolutions, handling the massive data volumes produced by silicon pixel detectors, which are used for charged particle tracking, poses a significant challenge. To address the challenge of data transport from high resolution tracking systems, we investigate a support vector machine (SVM)-based data classification system designed to reject low-momentum particles in real-time. This SVM system achieves high accuracy through the use of a customized mixed kernel function, which is specifically adapted to the data recorded by a silicon tracker. Moreover, this custom kernel can be implemented using highly efficient, novel van der Waals heterojunction devices. This study demonstrates the co-design of circuits with applications that may be adapted to meet future device and processing needs in high-energy physics (HEP) collider experiments.
Leptoquark (LQ) models are well motivated solutions to the $(g-2)_μ$ anomaly. In the minimal LQ models, only specific representations can lead to the chiral enhancements. For the scalar LQs, the $R_2$ and $S_1$ can lead to the top quark chiral enhancement. For the vector LQs, the $V_2$ and $U_1$ can lead to the bottom quark chiral enhancement. When we consider the LQ and vector-like quark (VLQ) simultaneously, there can be more scenarios. In our previous work, we considered the scalar LQ and VLQ extended models with up-type quark chiral enhancement. Here, we study the scalar LQ and VLQ extended models with down-type quark chiral enhancement. We find two new models with $B$ quark chiral enhancement, which originate from the bottom and bottom partner mixing. Then, we propose new LQ and VLQ search channels under the constraints of $(g-2)_μ$.
High energy physics experiments essentially rely on simulated data for physics analyses. However, running detailed simulation models requires a tremendous amount of computation resources. New approaches to speed up detector simulation are therefore needed. The generation of calorimeter responses is often the most expensive component of the simulation chain for HEP experiments. It was shown that deep learning techniques, especially Generative Adversarial Networks, may be used to reproduce the calorimeter response. However, those applications are challenging, as the generated responses need evaluation not only in terms of image consistency: different physics-based quality metrics should be also taken into consideration. In our work, we develop a multitask GAN-based framework with the goal to speed up the response generation of the Electromagnetic Calorimeter (ECAL) of the LHCb detector at LHC. We introduce the Auxiliary Regressor as a second task to evaluate a proxy metric of the given input that is used by the Discriminator of the GAN. We show that this approach improves the stability of GAN and the model produces samples with better physics distributions.
Precision measurements of jet substructure are used as a probe of fundamental QCD processes. The primary Lund jet plane density is a two-dimensional visual representation of the radiation off the primary emitter within the jet that can be used to isolate different regions of the QCD phase space. A new measurement of the primary Lund plane density for inclusive charged-particle jets in the transverse momentum range of 20 and 120 GeV/$c$ in pp collisions at $\sqrt{s} = $ 13 TeV with the ALICE detector will be presented. This is the first measurement of the Lund plane density in an intermediate jet $p_{\rm T}$ range where hadronization and underlying event effects play a dominant role. The projections of the Lund plane density onto the splitting scale $k_{\rm T}$ and splitting angle $Δ{R}$ axis are shown, highlighting the perturbative/non-perturbative and wide/narrow angle regions of the splitting phase space. Through a 3D unfolding procedure, the Lund plane density is corrected for detector effects which allows for quantitative comparisons to MC generators to provide insight into how well generators describe different features of the parton shower and hadronization.
Grids allow users flexible on-demand usage of computing resources through remote communication networks. A remarkable example of a Grid in High Energy Physics (HEP) research is used in the ALICE experiment at European Organization for Nuclear Research CERN. Physicists can submit jobs used to process the huge amount of particle collision data produced by the Large Hadron Collider (LHC). Grids face complex security challenges. They are interesting targets for attackers seeking for huge computational resources. Since users can execute arbitrary code in the worker nodes on the Grid sites, special care should be put in this environment. Automatic tools to harden and monitor this scenario are required. Currently, there is no integrated solution for such requirement. This paper describes a new security framework to allow execution of job payloads in a sandboxed context. It also allows process behavior monitoring to detect intrusions, even when new attack methods or zero day vulnerabilities are exploited, by a Machine Learning approach. We plan to implement the proposed framework as a software prototype that will be tested as a component of the ALICE Grid middleware.
T2K is a long-baseline neutrino oscillation experiment taking data since 2010. A neutrino beam is produced at the J-PARC accelerator in Japan and is sampled at a Near Detector complex 280 m from the neutrino production point and at the far detector, Super-Kamiokande, located 295 km from the source. Beams predominantly composed of muon neutrinos or muon anti-neutrinos have been produced by changing the currents in the magnetic focusing horns. This presentation will show the most recent T2K oscillation results obtained from a combined analysis of the entire available data set in the muon neutrino and muon anti-neutrino disappearance channels, and in the electron neutrino and electron anti-neutrino appearance channels. The data cover runs 1 to 8 (2010 to 2017) and consist of $7.252 \cdot 10^{20}$ POT in neutrino mode and $7.531 \cdot 10^{20}$ POT in antineutrino mode. Using these data, we measure four oscillations parameters: $\sin^2 θ_{23}$, $\sin^2 θ_{13}$, $Δm_{32}^2$ and $δ_{CP}$. The analysis excludes CP-conservation in the neutrino sector at 90\% C.L.
Bright gamma-ray Galactic Center excess and dark dwarfs: Strong tension for dark matter annihilation despite Milky Way halo profile Kevork N. Abazajian ∗ and Ryan E. Keeley † arXiv:1510.06424v4 [hep-ph] 8 Apr 2016 Center for Cosmology, Department of Physics and Astronomy, University of California, Irvine, Irvine, California 92697 USA We incorporate Milky Way dark matter halo profile uncertainties, as well as an accounting of diffuse gamma-ray emission uncertainties in dark matter annihilation models for the Galactic Center Extended gamma-ray excess (GCE) detected by the Fermi Gamma Ray Space Telescope. The range of particle annihilation rate and masses expand when including these unknowns. However, two of the most precise empirical determinations of the Milky Way halo’s local density and density profile leave the signal region to be in considerable tension with dark matter annihilation searches from combined dwarf galaxy analyses for single-channel dark matter annihilation models. The GCE and dwarf tension can be alleviated if: one, the halo is very highly concentrated or strongly contracted; two, the dark matter annihilation signal differentiates between dwarfs and the GC; or, three, local stellar density measures are found to be significantly lower, like that from recent stellar counts, increasing the local dark matter density. PACS numbers: 95.35.+d,95.55.Ka,95.85.Pw,97.60.Gb I. INTRODUCTION The Milky Way’s Galactic Center (GC) is an exceed- ingly crowded region with numerous gamma-ray point sources and several sources of diffuse emission. It is also expected to contain a high density of dark matter, which makes it a promising place to search for signals of dark matter annihilation or decay. Weakly Interact- ing Massive Particles (WIMPs) are among the leading candidates for dark matter, due to a natural mechanism for their thermal production at the proper density in the early Universe. Supersymmetric extensions to the stan- dard model of particle physics can easily accommodate a WIMP [1]. In previous work, several known sources of gamma-ray emission toward the GC have been detected and mod- eled. There are 18 gamma-ray sources within the the 7 ◦ × 7 ◦ region about the GC within the Second Fermi Gamma-ray LAT Source Catalog (2FGL). For example, the gamma-ray point source associated with Sgr A ∗ is one of the brightest sources in the region and its emission in this band can be modeled as originating from hadronic cosmic rays transitioning from diffuse to rectilinear prop- agation [2]. There is an abundance of gamma rays associ- ated with bremsstrahlung emission from e ± , as mapped by the 20 cm radio map of the GC [3]. There is also Inverse Compton (IC) emission that is consistent with coming from the same e ± source as the bremsstrahlung emission [4] After considering known sources of gamma-ray emis- sion, there remains an extended excess [5–13]. This Galactic Center Extended (GCE) excess signal gained significant interest since it may be consistent with a kevork@uci.edu rkeeley@uci.edu WIMP dark matter annihilation model. Primarily, the spatial profile of the excess is consistent with the ex- pected profile from dark matter halos in galaxy formation simulations. Secondly, the strength of the signal implies an interaction cross section that is consistent with the thermal relic cross section. And thirdly, the spectra of the excess signal is consistent with a WIMP with a mass between 10-50 GeV that decays through quark or lepton channels. This triple consistency of the WIMP paradigm as an explanation of the GCE has gained significant at- tention. Of course, there exist other candidates for the GCE gamma-ray emission. For instance, there is a large popu- lation of compact objects which can be bright gamma-ray sources. The GC Central Stellar Cluster can harbor a sig- nificant population of millisecond pulsars (MSPs). Since MSPs can have a spectra similar to low-particle-mass annihilating WIMPs, their presence can confuse a dark matter interpretation of the GC emission [14, 15]. Signif- icantly, flux probability distribution methods have found evidence that point sources are more consistent with the GCE flux map than a smooth halo source [16, 17]. If annihilating dark matter explains the GCE, then there should be annihilation signals in other places that have a high density of dark matter. Two such places are the “inner Galaxy” (within ∼20 ◦ of the GC) and the dwarf satellites of the Milky Way. Previous work has found that the inner galaxy signal is consistent with the mass and cross section supported by the galactic center [12, 13]. We will show the Milky Way dwarf galaxies’ lack of a signal [18, 19] significantly constrains the GCE parameter space. However, there is a reported excess from the newly discovered Reticulum 2 dwarf galaxy that may be consistent with the GC annihilation signal [20]. We will discuss below what would be required to have the GCE signal be consistent with the dwarf galaxy limits. Previous analyses have largely used fixed values for the parameters of the Milky Way’s dark matter halo when
This paper describes a novel system for automatic classification of images obtained from Anti-Nuclear Antibody (ANA) pathology tests on Human Epithelial type 2 (HEp-2) cells using the Indirect Immunofluorescence (IIF) protocol. The IIF protocol on HEp-2 cells has been the hallmark method to identify the presence of ANAs, due to its high sensitivity and the large range of antigens that can be detected. However, it suffers from numerous shortcomings, such as being subjective as well as time and labour intensive. Computer Aided Diagnostic (CAD) systems have been developed to address these problems, which automatically classify a HEp-2 cell image into one of its known patterns (eg. speckled, homogeneous). Most of the existing CAD systems use handpicked features to represent a HEp-2 cell image, which may only work in limited scenarios. We propose a novel automatic cell image classification method termed Cell Pyramid Matching (CPM), which is comprised of regional histograms of visual words coupled with the Multiple Kernel Learning framework. We present a study of several variations of generating histograms and show the efficacy of the system on two publicly available datasets: the ICPR HEp-2 cell classification contest dataset and the SNPHEp-2 dataset.
We cloned and characterized the Drosophila homolog of mammalian Jun-N-terminal kinases (DJNK). We show that DJNK is encoded by basket (bsk). Like hemipterous (hep), which encodes the Drosophila JNK kinase, bsk is required in the embryo for dorsal closure, a process involving coordinate cell shape changes of ectodermal cells. Dorsal closure can also be blocked by dominant negative Drosophila cdc42, which has been shown to act upstream of JNKK in vertebrates. Therefore it appears that the JNK pathway is conserved and that it is involved in controlling cell morphogenesis in Drosophila. Although DJNK efficiently phosphorylates DJun in vitro, bsk function is not required for the specification of cell fate in the developing eye, a process that requires MAP kinase and DJun function.