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Bhubhanjyoti Bhattacharya
Department of Natural Sciences
Lawrence Technological University
Puzzles in B-meson Decays
Heavy meson decays provide optimal testing grounds for theories
beyond the Standard Model of particle physics. In this talk, I
will discuss a handful of recently uncovered puzzles in decays of
heavy B mesons that may shed greater light on the “flavor
tail” of new physics.
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Likun Zhang and Cecille Labuda
Department of Physics and Astronomy
University of Mississippi;
Physical Acoustics and Fluid Dynamics
Likun Zhang and Cecille Labuda will give a general overview of
their research in physical acoustics and fluid dynamics. The talk
will cover complex fluids, biomedical applications of
ultrasonics, ocean, physics, fluid physics and “
acoustofluidics”.
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Xiaoyan Huang
Department of Physics and Astronomy
University of Mississippi
TMS Charge ID in the DUNE Experiment
An introduction to the DUNE experiment, TMS of the near detector
system, its role in the reconstruction of muon track and charge
identification.
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Joshua Moore
Department of Physics and Astronomy
University of Mississippi
Entanglement in the Fredkin Spin Chain
Quantum entanglement has emerged as a useful tool for studying the ground states of many-body systems. It has been proven that the entanglement entropy for gapped systems in one-dimension does not grow with the system size, obeying an “area law”. We investigate the entanglement properties of a gapless one-dimensional spin chain — the Fredkin spin chain — where the entanglement entropy is found to grow logarithmically with the system size.
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Aniket Khairnar
Department of Physics and Astronomy
University of Mississippi
Approximate Helical Symmetry in Compact Binaries
The inspiral of a circular, non-precessing binary exhibits an
approximate helical symmetry. The effects of eccentricity,
precession, and radiation reaction break the exact symmetry. We
estimate the failure of this symmetry using the flux of the BMS
charge corresponding to helical symmetry carried away by
gravitational waves. We compare the analytical computation of
helical flux with 113 NR waveforms of quasi-circular
non-precessing binaries from the SXS catalog. The helical
symmetry is numerically satisfied to at least a relative 5PN
order.
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Sunghwan Jung
Department of Biological and Environmental Engineering
Cornell University
Drinking, Diving, and Shaking
Biological organisms have presumably adapted their behaviors or
features in response to surrounding mechanical forces or
instabilities to achieve better performance. In this talk, I will
discuss three problems in which the dynamical system approach
elucidates the physics behind animal behaviors. First, we
investigated how cats and dogs transport water into the mouth using
an inertia-driven (lapping) mechanism. We found that to maximize
water intake per lap, both cats and dogs close the jaw at the column
break-up time governed by unsteady inertia. This break-up (or
pinch-off) time can be predicted using the stability analysis of the
water column in which surface tension balances with inertia.
Second, we studied how animals plunge-dive and survive from impact.
Physical experiments using an elastic beam as a model for the body
attached to different shapes revealed limits for the stability of
the injuries during plunge-dive. The body response can be simplified
as the Euler beam buckling problem with unsteady impact force on the
diving front. Third, I will discuss the mechanism of releasing water
lodged in the ear canal. For example, people often shake their head
sideways to remove water out of ear canal after swimming or s
howering. This removal process involves high acceleration to push
water out of a canal, which is analogous to the Rayleigh-Taylor
instability. If time permits, I will briefly talk about how humans
produce sound by clapping their hands, a process that can be modeled
using classical Helmholtz resonance.
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Bhupal Dev
Department of Physics
Washington University in Saint Louis
Seeing the Invisible: Neutrino-Dark Matter Interactions
Neutrinos and dark matter remain two of the least known sectors
of fundamental physics. Although both are “invisible”
particles, we argue that a sizable interaction between them can
leave footprints in several experimental observables. We
implement the full catalog of constraints coming from
cosmological and astrophysical datasets, as well as derive new
laboratory constraints from meson and Z-boson decays. We then
study the prospects of detecting neutrino-dark matter
interactions in future galactic supernovaneutrino events at
large-volume neutrino experiments, such as DUNE. |
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James Bonifacio
Department of Physics and Astronomy
University of Mississippi
Bounding the Unknown: Hyperbolic Manifolds and the Conformal Bootstrap
The conformal bootstrap has emerged as a powerful tool in
theoretical physics, enabling us to find precise constraints on
conformal field theories using only fundamental consistency
conditions. In this talk, I will introduce a version of the
conformal bootstrap that can be applied to hyperbolic manifolds
and show how it can be used to find bounds on the eigenvalues of
the Laplacian operator that are in remarkable agreement with
numerically computed spectra.
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Gil Paz
Department of Physics and Astronomy
Wayne State University
How Big Is The Proton?
Current atomic and optical physics methods allow to search for
very weak new interactions. The main obstacle is often
controlling nuclear uncertainties. Such studies can yield
benefits for these areas of physics independent of the new
physics motivation.
In this talk I will discuss three such examples. The first is the
proton radius puzzle and looking for a new force that couples to
muons but not electrons. The second is looking for dark matter
via oscillations of nuclear radii. The third is using a
nuclearclock to look for time variation of fundamental constants.
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Meghna Bhattacharya
Scientific Computing Division
Fermi National Accelerator Laboratory
Probing the Unknown Through a Neutrino Lens
Neutrinos are some of the most fascinating fundamental particles
in nature, they are ubiquitous and enigmatic at the same time. As
misfits of the Standard Model, neutrinos have been observed to
change their flavor, or oscillate, providing evidence for
neutrino mass and Beyond the Standard Model (BSM) physics. There
are also hints that neutrinos could be the reason the universe is
made of matter rather than antimatter.
In this talk, I will outline some of the most fundamental
questions in physics and the quest for better understanding
through neutrino physics experiments. These fundamental questions
range from the origin of matter, to supernova bursts in the
universe, to the grand unification of forces. I will give an
overview of the field of neutrino measurements from past to
present and discuss how recent results from current neutrino
oscillation experiments such as NOνA and T2K have shaped our
understanding. Additionally, I will focus on how the next
generation of experiments such as the Deep Underground Neutrino
Experiment (DUNE) are being designed to enhance the precision
with which we can use neutrinos to probe these deep questions
about our universe. Finally, I will highlight recent results from
the MicroBooNE experiment, which has been a trailblazer in the
flagship liquid argon detector program and is paving the path
towards DUNE.
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Kumar Pandey
Department of Physics and Astronomy
University of Mississippi
Differential Decay Distributions in Semi-Leptonic B Mesons
This talk delves into the study of semi-leptonic decays of B
mesons, specifically focusing on the differential distributions
of decay products to probe potential signatures of New Physics
(NP) beyond the Standard Model (SM). Using an effective field
theory (EFT) framework, we model the
b → cℓ−ν transitions in
B mesons, incorporating NP effects through various four-quark
operators and coupling constants. A Monte Carlo simulation with
EvtGen is employed to examine distributions such as
q2, θ*,
χ and under both SM and NP assumptions. Results
indicate minor deviations in angular distributions between SM and
NP scenarios, though overall alignment with SM predictions
suggests limited sensitivity to NP within certain variables.
Concluding with insights into future observables, this study
emphasizes the importance of differential decay distributions in
refining our understanding of the SM and exploring potential NP
contributions.
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James Friend
Center for Medical Devices
University of California — San Diego
Acoustic Streaming
The analysis and use of acoustic streaming has taken on new
urgency in the past few years with the recognition that classical
analysis methods are unable to accurately quantify the flows
generated by passing acoustic waves beyond a few hundred kHz. This
issue, known since at least Lighthill’s namesake publication
in the 1970s, has not been addressed in the time since, with many
researchers—including the author—resorting to
computational analysis and approximations to overcome at least some
of the problems. Moreover, few researchers have been willing to
consider the dynamic behavior of acoustic streaming: the delayed
onset, the response to inharmonic excitation, and the delayed flows
after the acoustic wave ceases, though these aspects are important
in many experiments. Much of the reason is the challenge of the
analysis of such flows. After considerable work via an alternative
analysis path, we may finally have arrived at a method for
closed-form analysis of acoustic streaming at least in one
dimension, with transient behavior and both nonlinear
compressibility and viscous effects included. We present a coherent
and straightforward plan for analyzing simple acoustic streaming
cases where classic theories fall short.
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Shawn Dubey
Department of Physics
Brown University
Training Deep 3D Convolutional Neural Networks to Extract BSM Physics Parameters Directly from HEP Data: a Proof-of-Concept Study Using Monte Carlo Simulations
We report on a novel application of computer vision techniques to
extract beyond the Standard Model parameters directly from high
energy physics flavor data. We propose a simple but novel data
representation that transforms the angular and kinematic
distributions into “quasi-images”, which are used to
train a convolutional neural network to perform regression tasks,
similar to fitting. As a proof-of-concept, we train a 34-layer
Residual Neural Network to regress on these images and determine
information about the Wilson Coefficient C9
in Monte Carlo simulations of B0 →
K*0μ+μ−
decays. The method described here can be generalized and may find
applicability across a variety of experiments.
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