Bulletin of the American Physical Society
APS April Meeting 2023
Volume 68, Number 6
Minneapolis, Minnesota (Apr 15-18)
Virtual (Apr 24-26); Time Zone: Central Time
Session GG03: V: Computational Modeling |
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Sponsoring Units: DCOMP Chair: Elena D'Onghia Room: Virtual Room 3 |
Monday, April 24, 2023 3:30PM - 3:42PM |
GG03.00001: Computational Study of Structural, Elastic, Electronic, Phonon Dispersion relation and Thermodynamic Properties of Orthorhombic CaZrS3 for Optoelectronic Application Mulugetta Duressa Kassa, Menberu Mengesha Woldemariam, Nebiyu Gemechu Debelo Chalcogenide perovskites offer superior thermal and aqueous stability as well as a benign elemental composition compared to organic halide comparts for optoelectronic applications. In this study, the structural, electrical, elastic, phonon dispersion, and thermodynamic features of the orthorhombic phase of chalcogenide perovskite CaZrS3 (space group pnma) were examined by first principles calculations utilizing the plane wave pseudopotentials (PW-PPs) approach in generalized gradient approximations (GGA). The ground state properties such as lattice parameter, unit cell volume, bulk modulus, and its derivative were calculated and are in a good agreement with existing findings. The mechanical properties such as bulk modulus, shear modulus, Young's modulus and elastic anisotropy were calculated from the obtained elastic constants. The ratio of bulk modulus to shear modulus confirms that the orthorhombic phase of CaZrS3 is a ductile material. The absence of imaginary frequencies (negative frequencies) in phonon dispersion curve and the phonon density of states give an indication that the structure is dynamically stable. Finally, thermodynamic parameters such as free energy, entropy, and heat capacity were calculated with variation in temperature. The estimated findings follow the same pattern as previous efforts. |
Monday, April 24, 2023 3:42PM - 3:54PM |
GG03.00002: Structural and thermodynamic evolution of rutile and amorphous TiO2- nano-lamellae in the range from 0 to 4THz in polar and apolar environments: A Classical simulation Saravana Prakash Thirumuruganandham, Eduardo Patricio Estévez Ruiz, Joaquín Cayetano López Lago Eduardo Patricio Estévez Ruiz1, Joaquín Cayetano López Lago1, Saravana Prakash Thirumuruganandham 2 |
Monday, April 24, 2023 3:54PM - 4:06PM |
GG03.00003: Electronic structure of semiconductor nanoparticles from stochastic evaluation of imaginary-time path integral Andrei B Kryjevski The fermion sign problem, when severe, prevents the computation of physical quantities of a system of interacting fermions via stochastic evaluation of its path integral defined on discretized space-time due to the oscillatory nature of the integrand exp(-S), where S is the imaginary-time action. However, in the Kohn-Sham orbital basis, which is the output of a Density Functional Theory simulation, the path integral lattice field theory aproach for electrons in a semiconductor nanoparticle may have only a mild fermion sign problem and is amenable to evaluation by the standard stochastic methods. This is evidenced by our simulations of silicon hydrogen-passivated nanocrystals, such as Si35H36, Si87H76, Si147H100 and Si293H172, which range in size 1.0 - 2.4 nm and contain 176 to 1344 valence electrons, and to a 1.8 nm hetero-structured (Janus-type) NC Cd37Pb31Se68 with 1582 valence electrons. We find that approximating the fermion action by its leading order polarization term results in a positive-definite integrand, and is a very good approximation of the full action. We compute imaginary-time electron propagators and extract the energies of low-lying electron and hole levels. Our quasiparticle gap predictions agree with the results of previous G0W0 calculations. This formalism naturally allows calculations of more complex excited states, such as excitons and trions, for which we present some results. |
Monday, April 24, 2023 4:06PM - 4:18PM |
GG03.00004: High-order finite element method for atomic structure calculations Rohit Goswami, Ondrej Certik, John E Pask, Isuru Fernando, Lee A Collins, Gianmarco Manzini, N. Sukumar, Jirí Vackár
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Monday, April 24, 2023 4:18PM - 4:30PM |
GG03.00005: Exploring the Capabilities of Gibbs Sampling in Searches for Gravitational Waves in Pulsar Timing Arrays Nima Laal, Stephen R Taylor, Xavier Siemens, William Lamb The sensitivity of pulsar timing arrays (PTAs) to nano-hertz stochastic gravitational waves (SGWs) relies heavily on two factors: the number of pulsars timed and the number of years each timed pulsar is observed for. Currently, the most sensitive PTA experiments observe close to 80 millisecond pulsars with about a dozen of such pulsars observed for twelve to seventeen years. However, alongside the increase in sensitivity to detection of SGWs, the computational cost of noise modeling and parameter estimation also grows significantly as more pulsars are timed. This poses a significant challenge for Bayesian inference as a typical search for a SGW involves a large number of parameters: at the very least twice the number pulsars in the array plus the number of parameters necessary to model the GW signal. As a result, fast and reliable sampling methods such as Gibbs sampling could be of great use in searches for SGWs in PTAs. |
Monday, April 24, 2023 4:30PM - 4:42PM |
GG03.00006: Solar cells (as Silicon-based life) have consciousness perform a wireless remote order of tester to change their photo-voltages over physical principle in our experiments Dayong Cao According to our experimental phenomena, solar cells (as Silicon-based life) have actions to show that they have consciousness. They can perform a wireless remote order of the tester (Carbon-based life) to change their photo-voltages over the physical principle. |
Monday, April 24, 2023 4:42PM - 4:54PM |
GG03.00007: Machine learning for the surrogate modeling of radiofrequency quadrupole accelerators Joshua Villarreal The IsoDAR (Isotope Decay-At-Rest) experiment is a novel antielectron-neutrino source proposed to operate with an unprecedented primary proton beam current of 10 mA. Chief among the technical innovations that make this possible is the inclusion of a Radiofrequency Quadrupole (RFQ) that accelerates and pre-bunches the beam during its axial injection into the cyclotron. The accurate start-to-end simulation of through-going beams in this and similar experimental setups is computationally expensive, particularly because the high beam current leads to nonlinear space charge effects which must be accounted for. In this contribution, we demonstrate that machine learning-based surrogate models can approximate, to high predictive accuracy, the output beam parameters when passed through a virtual representation of the IsoDAR RFQ, significantly more computationally efficient than traditional high-fidelity simulations. This is the basis for a toolkit with the potential to transform traditional particle accelerator engineering by incorporating insights from artificial intelligence. We discuss pros and cons of such surrogate models, particularly when it comes to predicting quantities based on the second moments of the beam particle distribution such as transverse beam emittance, and discuss opportunities for the use of such surrogate models as a much faster accelerator design optimization tool. |
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