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ABSTRACT
Talk 1
Title: Viability of Local Dyson Sphere
Speaker: Michael Romero (Physics Dept., UAF)
Abstract
The purpose of this
research is to determine the viability of a Dyson
mega-structure (sphere) for the purposes of large-scale
energy accumulation and dispersal. The large amounts of
energy coming from the sun would allow for a massive
decrease in fossil fuel dependence and large-scale
advancements such as interplanetary and interstellar
travel. The simulation models the solar system with 8
planets and the Sun and uses the mass of Mars 6.410 x
10^23 kg as the reference material to build the sphere.
The sphere is simulated between 10 Earth years at radii
between 1.00 AU and 1.35 AU and it was found that the
energy necessary to maintain the structure's position,
relative to the Sun, is between 1.7077 x 10^34 J and
3.6297 x 10^34 J; energy demands increasing with a smaller
radius for the trade-off of needing much more compact and
efficient solar satellites. The net energy collected, with
a solar conversion efficiency of 30% for solar panels, is
between 3.6937 x 10^33 J and 1.2092 x 10^34 J between 1.20
and 1.35 AU. With our predicted outputs for energy
exceeding 10^8 times 2024's current global energy
production, the main factor in determining the viability
of the model lies in an efficient design of thrusters and
solar panels, as well as a reliable and compact method of
energy transfer from the sphere.
Talk 2
Title: Investigating Field Line Resonances in the Jovian
Plasma Sheet: Juno Mission and Simulation Data Analysis
with Continuous Wavelet and Hilbert-Huang Transforms
Speaker: Vivian Palmer (Physics Dept., UAF)
Abstract
Magnetometer observations from the
Galileo mission have provided evidence of standing Alfvén
waves, also known as Field Line Resonances (FLRs) in the
Jovian magnetosphere (e.g., Manners & Masters, 2019).
Using primarily Juno magnetometer observations, this
project expands on the Galilean findings to identify FLRs
in the Jovian current sheet. These waves are a common
feature of Earth’s magnetosphere and are thought to be
correlated with mono-energetic electron energization that
drives some terrestrial discrete auroral arcs. Periodic
auroral emissions at Jupiter have also been observed using
the Hubble Space Telescope (e.g., Nichols et al., 2017),
suggesting these waves participate in generating some
auroral emissions at Jupiter as well. We find and
characterize short-periodic waves within Jupiter’s
equatorial plasma sheet using Continuous Wavelet
Transformations (CWT) and Hilbert-Huang Transforms
(HHT). We analyze both the toroidal and poloidal
polarizations of the perturbed transverse magnetic field
where the Juno spacecraft crosses or skims Jupiter’s
equatorial plasma sheet. The same analysis tools are
applied to fluctuations of the observed density moments to
help distinguish Alfvénic modes from structure-driven
modes. We also analyze magnetic field perturbations
derived from FLR simulations to better elucidate the
harmonic structure found within the Juno data. Preliminary
results suggest the presence of FLRs with periods in the
range of some tens of minutes or less, comparable to
previous findings.
Talk 3
Title: Exploring the Efficacy of Unsupervised Feature
Extraction for the Identification of Mesoscale Auroral
Morphologies
Speaker: Aedan McKee (Physics Dept., UAF)
Abstract
THEMIS ASI database
contains an expanding collection of billions of images,
however it lacks efficient methods for retrieving specific
mesoscale phenomena, such as auroral beads. This research
explores the use of an unsupervised machine learning model
to vectorize images through a feature extraction process
enabling the use of distances between vectors for event
searching. By using FAISS and its FlatIP index method, we
ensure the identification of the closest feature vectors
by the inner product comparison. This approach allows for
statistical analysis on a wide range of events that would
not have been possible before. Setting the stage for
studying sub-storms and onset waves and geomagnetic
relationships with auroral morphologies such as auroral
beads. Preliminary performance of the algorithm has shown
great results in identifying events but with false
positives, with additional work and refinement this can be
a potent tool to auroral physics.
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