RT @BatesCollege: Come on a visit to the historic Stephens Telescope. “It’s such a great place,” said Bates Astronomy Club co-president E….

PLEASE SHARE! My department (Physics & Astronomy at Bates College) is hiring two tenure-track positions (one in solar physics / geospace science, one in any subfield of physics or astronomy), and we start reviewing applications in 10 days!

RT @NathanLundblad: We're hiring for two tenure-track positions in Physics & Astronomy at Bates. One in any subfield of physics or astronom….

That's a wrap for #SimonsNSBP @SimonsFdn @NSBPInc

Ishika Gobin: Investigating the Impact of Astrophysical Parameters on Cosmological Constants using Galaxy Clustering. Uses CAMELS-SAM models run through Santa Cruz Semi Analytic Model, varies 2 cosmological parameters and 9 astrophysical parameters (previous work only varied 3).

Isabelle Jones: Variable Accretion in Low Mass Star Formation. Creates models in MESA with different initial masses and different accretion models: constant cold accretion, constant hot accretion, variable accretion. Impacts path in pre-main sequence region of HR diagram.

Jasmine Freeman presents results for TOI-3362 b discovered by TESS. Shows PyMC modeling of posterior probability distributions for eccentricity, orbital period, radius relative to host star. A “warm” Jupiter with high eccentricity 0.8 #SimonsNSBP.

Nia Suitt presents Omega GPT: Cosmology with Transformers. Shows previous work based on 700,000 simulated galaxies in universes with different values for Omega_matter (CAMELS simulations: Could Omega_matter be constrained with individual galaxy data?.

Hidalgo Mudonhi on Normalizing Flows and Data Efficient Architecture. Analogy: budgets allow a human to get the most out of their money, flow architecture allows machine learning to get the most out of the data. Goal: train a good model with the least amount of data possible.

J’Avani Stinson from Georgia Tech describes a cellular automaton model of the transition from an egg to a cleaved embryo with distinct cell lineages, emphasizing the dynamics of cytoplasmic determinants. Looking at polarization, asymmetry, redistribution #SimonsNSBP.

@BatesCollege Preston Ohanuka: Understanding Cell Division Using Simulation-Based Inference. Testing the effectiveness at inferring parameter values from experimental data for a model of cell division. Compares polynomial fit (broad posterior) vs cosine transform (narrow posterior, so better).

Spencer Obiero from @BatesCollege: Diagnostics for the Laughlin Wave Function through the Metropolis Hastings Algorithml. Explains fractional quantum Hall effect, conducts simulations of electron gas in 2D, finds transition between fluid and crystalline structure #SimonsNSBP.

Mirnelle Mathurin on Symmetry breaking in Drosophila. Looking at mRNA localization and accumulation in the oocytes of fruit flies. Imaged Stage 12 egg cells with laser scanning confocal microscope. Did 3D particle tracking, compared to simulations of particles in Brownian motion.

@SimonsObs Cameren Whitaker from U Virginia working with Mathew Madhavacheril: Detecting Sunyaev Zeldovich Galaxy Clusters Through Supervised Machine Learning. Using Mask Region-based Convolutional Neural Network features and WebSky Simulations. Next: add noise and beam convolution.

@SimonsObs Rachel McQueen from Haverford College also working on transition edge sensors for @SimonsObs. Simulates how complex impedance should behave, compares to actual data for one channel and finds good agreement. Looks at superconducting, overbiased, and transition regions #SimonsNSBP.

@SimonsObs Julia Ahing Brockland on noise in transition edge sensors as a function of frequency for @SimonsObs. Looking at noise at different frequencies, using what is consistent and calculable (Johnson noise, readout noise) to find what is unexpected. Possible noise from Bias Line.

Donovan Flagg: Improving the Thermal Conductivity of Copper Straps for use in the Large Aperture Telescope Receiver @SimonsObs. Stages at 40 K/4K/100 mK. How to reduce temperature gradient between 100 mK stage, thermal BUS, optical tubes? #SimonsNSBP.

Ayanna Bearden shows work to characterize the detectors used by the Simons Observatory. Wants to understand detector efficiency, looking at outliers based on signal as a function of precipitable water vapor. #SimonsNSBP.

Jasmine Verette from Howard University: Hunting galaxies in the early universe, with Laura Sommovigo. Uses suite of dark matter simulations (100 Mpc box with 10^6 solar mass resolution) to calculate stellar mass function at z=6-10 (using power-law function) compares to JWST data.

Kiara Ruffin on simulations of dark matter halo substructures: finds more mass loss from tidal stripping of subhalos (dwarf galaxies 10x less massive than the Milky Way) for self-interacting dark matter (w/ cored density profiles) than cold dark matter (w/ cuspy density profiles).