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Abstract In an effort to search for faint sources of emission over arbitrary timescales, we present a novel method for analyzing forced photometry light curves in difference imaging from optical surveys. Our method “ATLAS Clean,” or ATClean, utilizes the reported fluxes, uncertainties, and fits to the point-spread function (PSF) from difference images to quantify the statistical significance of individual measurements. We apply this method to control light curves across the image to determine whether any source of flux is present in the data for a range of specific timescales. From ATLASo-band imaging at the site of the Type II supernova (SN) 2023ixf in M101 from 2015–2023, we show that this method accurately reproduces the 3σflux limits produced from other, more computationally expensive methods. We derive limits for emission on timescales of 5 days and 80–300 days at the site of SN 2023ixf, which are 19.8 and 21.3 mag, respectively. The latter limits rule out variability for unextinguished red supergiants with initial masses >22M_⊙, comparable to the most luminous predictions for the SN 2023ixf progenitor system. We also compare our limits to short-timescale outbursts, similar to those expected for Type IIn SN progenitor stars or the Type II SN 2020tlf, and rule out outburst ejecta masses of >0.021M_⊙, much lower than the inferred mass of circumstellar matter around SN 2023ixf in the literature. In the future, these methods can be applied to any forced photometry on difference imaging from other surveys, such as Rubin optical imaging. 

Abstract The generation of broadband wave energy frequency spectra from narrowband wave forcing in geophysical flows remains a conundrum. In contrast to the long-standing view that nonlinear wave–wave interactions drive the spreading of wave energy in frequency space, recent work suggests that Doppler-shifting by geostrophic flows may be the primary agent. We investigate this possibility by ray tracing a large number of inertia–gravity wave packets through three-dimensional, geostrophically turbulent flows generated either by a quasigeostrophic (QG) simulation or by synthetic random processes. We find that, in all cases investigated, a broadband quasi-stationary inertia–gravity wave frequency spectrum forms, irrespective of the initial frequencies and wave vectors of the packets. The frequency spectrum is well represented by a power law. A possible theoretical explanation relies on the analogy between the kinematic stretching of passive tracer gradients and the refraction of wave vectors. Consistent with this hypothesis, the spectrum of eigenvalues of the background flow velocity gradients predicts a frequency spectrum that is nearly identical to that found by integration of the ray tracing equations. 

Transfer students, who are disproportionately URM and first-generation, are a target population for boosting engineering representation. Transfer students in mechanical, aerospace and civil engineering at [the institution] take thermodynamics, a required gateway course, in their first or second term. This paper outlines the results from an observational study to determine how students interact in a peer-led learning environment. The PEERSIST (Peer-led, Student Instructed, Study group) model promotes academic competence through peer dialogue, in which disciplinary knowledge is socially co-constructed and refined over successive sessions. In order to help demonstrate that student interactions are the main source of learning in Peer-Led Study Groups (PLSGs), interactions between students were recorded and compared to those in traditional TA-led recitations using the observation protocol. Results show that students in PLSGs interact with their peers significantly more than students in the TA-led control group. The study also compares peer interactions by incoming course preparedness and finds a non-significant relationship between incoming GPA and peer-to-peer interactions. In contrast, the study finds a negative relationship between the rate at which students ask for and receive help and incoming GPA. 

Abstract The discovery and localization of FRB 20240209A by the Canadian Hydrogen Intensity Mapping Fast Radio Burst (CHIME/FRB) experiment marks the first repeating FRB localized with the CHIME/FRB Outriggers and adds to the small sample of repeating FRBs with associated host galaxies. Here we present Keck and Gemini observations of the host that reveal a redshiftz = 0.1384 ± 0.0004. We perform stellar population modeling to jointly fit the optical through mid-IR data of the host and infer a median stellar mass log(M_*/M_⊙) = 11.35 ± 0.01 and a mass-weighted stellar population age  ~11 Gyr, corresponding to the most massive and oldest FRB host discovered to date. Coupled with a star formation rate  <0.31M_⊙yr⁻¹, the specific star formation rate  <10^−11.9yr⁻¹classifies the host as quiescent. Through surface brightness profile modeling, we determine an elliptical galaxy morphology, marking the host as the first confirmed elliptical FRB host. The discovery of a quiescent early-type host galaxy within a transient class predominantly characterized by late-type star-forming hosts is reminiscent of short-duration gamma-ray bursts, Type Ia supernovae, and ultraluminous X-ray sources. Based on these shared host demographics, coupled with a large offset as demonstrated in our companion Letter, we conclude that preferred sources for FRB 20240209A include magnetars formed through merging binary neutron stars/white dwarfs or the accretion-induced collapse of a white dwarf, or a luminous X-ray binary. Together with FRB 20200120E localized to a globular cluster in M81, our findings provide strong evidence that some fraction of FRBs may arise from a process distinct from the core collapse of massive stars. 

In this report, we characterize seven of twenty-five students’ responses to a single written homework assignment from the Spring 2021 academic semester. The homework was designed to incorporate the Vector Unknown 2D digital game to investigate how students answered questions about span and linear independence after playing various levels of the game. We present our modification of the roles and characteristics framework of Zandieh et al. (2019), our identification of students’ grammatical use of game language and math language, as well as the results of analyzing students’ homework responses using our framework.