Session J05: Nuclear and Particle Physics

Progress on a cryoprobe spectroscopy system for barium tagging in nEXO

The nEXO experiment is a planned search for 0$\nu \beta \beta $ decay using a liquid xenon time projection chamber. In order to reduce background, several methods for identifying (or ``tagging'') the daughter barium are being developed. One potential method of barium tagging being investigated involves freezing the potential barium in solid xenon and then extracting the frozen sample by using a cryoprobe system. Matrix isolation spectroscopic techniques would then be used to identify the single barium within the frozen sample. Progress is presented here on developing a cryoprobe spectroscopy system at CSU for freezing solid xenon (SXe) from liquid xenon, creation of Ba$^{\mathrm{+}}$ ions by laser ablation of Ba metal and capturing them in SXe on a window on the cryoprobe and spectroscopy of the Ba atoms and ions in the SXe.   

Path Integral Quantum Monte Carlo Calculations of $^4$He with Argonne $v_6'$ Interaction

Quantum Monte Carlo(QMC) methods, which are based on ab-initio principle and featured by their accuracy and efficiency, have been successfully used in various nuclear physics calculations. Among them, Path Integral Monte Carlo(PIMC) method, in particular, by nature, has the advantage of its capability of directly and accurately calculating expectation values of important operators which do not commute with Hamiltonian. In this work, based on Argonne $v_6'$ two-body nucleon-nucleon interaction, we show the first nuclear PIMC calculations of Helium 4, which might be served as a benchmark test for larger nuclei PIMC calculations. For operator commutes with Hamiltonian, eg, Hamiltonian itself, our PIMC $^4$He ground state binding energy agrees with Green's Function Monte Carlo(GFMC) result which is -26.15(2) MeV. For operators which are important but do not commute with Hamiltonians (and therefore cannot be directly and accurately calculated by other QMC methods without tradeoff), we will show particle number density distribution and Euclidean response functions for single-nucleon couplings. We will also discuss the PIMC algorithms used in this work.   

Applying a Model to Describe the Radiation-induced Leakage Current in the ATLAS Silicon Detector

Silicon pixel detectors, which are located at the heart of the ATLAS detector, are exposed to high radiation. This damages the sensors, making it necessary to regularly adjust their operating conditions to maintain efficient detection for as long as possible. Sensor leakage current data are used to quantify the radiation damage. The Hamburg Model was developed to describe the leakage current as a function of fluence, temperature, and time. This model is important for predicting the operation of the detector under future conditions. In its present form, computer code for the model requires lengthy runs in order to acquire statistics relevant to LHC scenarios. A project is underway to parallelize this code in order to reduce the run time for producing large statistical data sets.   

Search for Long Lived Particles in the Muon Spectrometer of the ATLAS Experiment at CERN

A search for highly displaced vertices resulting from the decay of neutral long-lived particles (LLP) produced by proton-proton collisions and collected by the ATLAS experiment at the CERN Large Hadron Collider is in progress. These particles have a relatively long decay time and decay in the Muon Spectrometer. Such long-lived particles are predicted by several Beyond-the-Standard Model (BSM) theories including those with hidden sectors and those with heavy new neutrinos, which will be discussed. Results from an earlier analysis using 36.1 fb-1 of data will be summarized. Possible improvements in the analysis of 140 fb-1 of data will be discussed. Several variables used in the selection of signal events will be analyzed and presented.   

Tagging Quark and Gluon Jets with Machine Learning

Jets are collimated showers of particles that are produced in the hadronization of quarks and gluons. For many physics processes, it is interesting to be able to tag whether a jet arises from the hadronization of a quark or gluon. Our approach was to use a Bayesian neural network implemented using the TFLearn library in TensorFlow to tag quark and gluon jets. Seven relevant jet variables (LesHouches multiplicity, mass, PtD, rapidity, width, pt, and number of constituents) were used as input to the neural network. The main jet observable used in this study was the LesHouches multiplicity. The LesHouches is a jet variable that relates the energy of jet constituents to the angle of the jet constituents. This was compared to the other variables to find what gave the neural network the most power to discriminate between jets.   

Mirror Symmetry for Multi-Parameter K3 Surfaces

For a superstring theory to be consistent with observations, its space-time must be four-dimensional at the relevant distance scales, so one must look for ways to restrict the necessary extra dimensions to smaller scales. This is accomplished by a process called compactification, in which the extra dimensions are curled-up and assumed to "close up" on themselves to form a compact Calabi-Yau manifold. As an intermediate step one obtains for this Calabi-Yau manifold a four-dimensional K3 manifold. A duality between two different superstring theories presents itself through the compactification of the respective theories on two different K3 manifolds; more precisely, the duality relates a compactification on a symplectic K3 manifold to a family of complex K3 manifolds. In this case, the relationship between the two theories is known as K3-mirror symmetry. The Greene-Plesser orbifolding method allows for the construction of a mirror of the symplectic K3 manifold from a special one-parameter family of K3 manifolds known as the Dwork pencil. We develop a natural extension of the Greene-Plesser mechanism from the one-dimensional to a three-parameter family. Moreover, for this three-parameter family we compute the (arithmetic) mirror map governing the string duality.   

Front-end Electronics for the New Small Wheel of the ATLAS Muon Spectrometer

The HL-LHC (high luminosity Large Hadron Collider) will increase the LHC luminosity by a factor of 5-7. This will extend the discovery reach for beyond-the-Standard Model physics and allow precision measurements of Higgs boson properties. However the higher luminosity will also stress the trigger and performance of the ATLAS experiment. An upgrade to the ATLAS Muon Spectrometer is the New Small Wheel (NSW), which will significantly improve muon triggering capabilities and preserve the performance of the muon measurements at increased luminosity in the forward region. Two new detector technologies, Micromegas detectors and small-strip Thin Gap Chambers will be used in the NSW.~ Front end electronics for the Micromegas detectors, which use several custom ASIC's in order to survive the high radiation environment, are being developed and tested. ~The physics motivation for the NSW will be discussed.~ A short technical description of the front-end boards will be given.~ Tests and results on the production design front end boards will be presented.