GPAS Conference Talks
Hosted by GPAS Professional Development Committee
Modeling Non-Kekulé Molecules With Quantum Corrals
Dr. Anthony Francisco
Non-Kekulé molecules possess interesting magnetic properties but are difficult or impossible to synthesize and are challenging to model with conventional computational methods. However, artificial molecules present a unique tool to study molecular properties. Their lack of ''real'' bonds and the low temperature at which they are constructed makes them highly stable in any configuration they can be assembled. We have used artificial molecules to model and study the molecular properties of such systems. Here CO molecules are adsorbed onto a Cu surface and arranged in quantum corrals to shape the wavefunction of the surface electrons. We present studies of a synthetic molecule that closely reproduces the electronic features of phenalenyl radical as predicted by density functional theory calculations.
Link and node communities of the macaque neural network
Jorge Martinez Armas
Analyzing weighted and directed anatomical neural networks is fundamental for understanding how brains operate efficiently. The vast repertoire of functional processing indicates the existence of carefully organized connectivity structures within the brain. Retrograde tract-tracing experiments in the macaque monkey generate a dense, directed, and heterogeneous network that proves to be challenging for the current state-of-the-art community detection algorithms. In order to perform a community structure analysis in such networks, we need novel algorithms that can separate the communities from within a dense and heterogeneous environment. In this paper, we have extended a previously introduced link community algorithm to handle directed, dense, and heterogeneous networks and apply it to the aforementioned tract-tracing macaque dataset. Moreover, we have developed an algorithm that projects link hierarchies into node hierarchies and the corresponding node communities, validating those on benchmark networks. Using this algorithm, we show that the heterogenous cortical circuitry in the brain is organized into a hierarchical structure in which areal communities emerge from the similarity of their directed neighborhoods. We also show that the obtained structures are statistically significant compared to appropriate null models. The introduced method reveals a network's complex organization through a link and node hierarchical structure.
Beta-neutrino angular correlation measurements of mirror transitions with St. Benedict
Precise measurements of nuclear beta decays provide a unique insight into the Standard Model due to their connection to electroweak interactions. These decays can provide constraints on the unitarity or non-unitarity of the Cabbibo-Kobayashi-Maskawa (CKM) quark mixing matrix, where non-unitarity would signal potential physics Beyond the Standard Model. The most precise of these tests involves the matrix element Vud as determined from superallowed pure Fermi beta decays, and indicates a deviation from unitarity on the order of ~2.4σ. As such, cross-checks from additional methods, including superallowed mixed mirror beta decays, are necessary. Vud precision from mirror decays is currently limited by the absence of precise Fermi-to-Gamow Teller mixing ratios, which are most sensitively determined via the angular correlation of the neutrino and beta particle emitted during the decay. At the Nuclear Science Laboratory (NSL) at the University of Notre Dame, the Superallowed Transition Beta-Neutrino Decay Ion Coincidence Trap (St. Benedict) is being constructed to determine the beta-neutrino angular correlation parameter of various mirror decays. We plan on measuring this correlation parameter for the beta decays of nuclei ranging from 11C to 41Sc using radioactive ion beams from the NSL’s TwinSol separator, which will result in significantly improved precision of the Vud element of the CKM matrix from superallowed mirror transitions. The status of the development of St. Benedict, including its beam preparation and measurement stages, will be presented.
Measuring and Comparing the Masses of Five Uniformly Sized Planets in the Kepler-323 and Kepler-104 Systems
C. Alexander Thomas
Of the approximately 4,000 stars that host exoplanets, almost half of them were discovered by the NASA Kepler mission, and at least 25% of the Kepler stars host more than one planet. While the Kepler mission was successful in discovering planets of a wide range of sizes via the transit method, this technique does not, in most cases, relay information about the masses of the planets. We measured the masses of five planets in two planetary systems by detecting Doppler shifts in stellar spectra as the gravity of the planets accelerates their host stars. Our spectra come from the HIRES instrument at the W.M. Keck Observatory and the HARPS-N instrument on the Telescopio Nazionale Galileo. For Kepler-323 and Kepler-104, we analyzed 129 and 44 radial velocity measurements, respectively. The two Kepler-323 planets have masses of 2.5pm1.4 and 6.6pm1.8 Earth masses and the three Kepler-104 planets are 10.1pm2.8, 7.1(-3.6+3.9), and 5.5(-3.6+4.7) Earth masses. The Kepler-104 system has remarkably uniform masses and spacing, illustrated by a low value for gap complexity and mass partition. Meanwhile, the Kepler-323 planets have a mass partition similar to that of the rocky Solar System. The discovery and characterization of multi-planet systems, especially those containing sub-Neptune sized planets orbiting close to their star, like Kepler-323 and Kepler-104, is relatively new and important as it illuminates, not only on the current structure of exoplanet systems, but also on potential formation mechanisms.