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Open educational resources (OER) are teaching, learning, or research resources that are offered freely to users in at least one form and that either reside in the public domain or have been released under an open copyright license that allows for its free use, reuse, modification, and sharing with attribution. Course marking (also called attributes, designations, tags, flags, labels) are specific, searchable attributes or designations that are applied to courses, allowing students to quickly identify important information to aid in their decision making and allow them to efficiently plan their academic careers. In 2022, the report, "Toward Convergence: Creating Clarity to Drive More Consistency in Understanding the Benefits and Costs of OER," introduced a set of principles and frameworks that provide guidance for states, systems, and institutions wanting to better understand the benefits of open educational resources (OER). MHEC led the national effort to produce the report, which details recommendations for consistently estimating the cost savings realized by students when a course uses OER compared to traditional course material. Realizing such analyses are not possible without accurate data on course materials, MHEC then led a national effort to create this report to highlight five steps critical for the development of an effective course marking process, providing committed stakeholders with a roadmap and set of recommendations to improve consistency and reliability for marking courses in college registration materials, so students know the costs and nature of such materials at the time they choose their classes. Consistency of course marking efforts across the United States contributes to the ability to aggregate data from many institutions and conduct studies of how OER saves students money and contributes to enhanced student outcomes.

Student records, and specifically academic transcripts, are the traditional record of a student's completed coursework and their earned credential at an educational institution. Transcripts can serve as proof and a signal to potential employers and other educational institutions that a student has engaged in certain learning activities and obtained knowledge in given areas. Early in 2021, staff members from the Higher Learning Commission (HLC), the U.S. Department of Education and the regional compacts -- the Midwestern Higher Education Compact (MHEC), the New England Board of Higher Education (NEBHE), and the Western Interstate Commission for Higher Education (WICHE) -- met to discuss students' access to their records as a matter of student success. Three concerns were identified: student access to transcripts when there are financial or administrative holds placed on student accounts at institutions; access to student records when an institution closes; and the future of student records access. HLC and the regional compacts have continued to discuss and study the topic of transcript holds and closed school records. The issues surrounding transcript holds and closed school records have received ever greater attention in light of supporting student success since the pandemic. Because of the many ways the pandemic caused a re-thinking of business as usual, changes to transcript holds became a policy and process initiative at the federal, state, and institutional levels. The definition of student success for this paper includes enrolling in and completing a postsecondary education, transferring between institutions, earning licensure, securing employment, qualifying for military service, and other scenarios that vary by student. This paper provides an overview of student records issues, from an accreditor and regional compacts perspective. It includes recent legislative and policy actions at the federal and state levels as well as practitioner solutions and tools for institutions created by regional compacts, institutions, and other organizations. Resources are provided for those working at the institutional level as well as at the state or federal policy level to help students succeed.

The EdResearch for Action "Overview Series" summarizes the research on key topics to provide K-12 education decision makers and advocates with an evidence base to ground discussions about how to best serve students. This overview brief discusses the central question: What is the evidence on strategies to build a sense of school connectedness and engagement among all students? Key insights are arranged in the following sections: (1) breaking down the issue; (2) evidence-based practices; and (3) practices to avoid. [The BARR Center and Network for College Success are additional collaborators for this report.]

We present a systematic search for radio active galactic nuclei (AGNs) in dwarf galaxies using recent observations taken by the Very Large Array Sky Survey (VLASS). To select these objects, we first establish a criterion to identify radio-excess AGNs using the infrared-radio correlation (IRRC) parameter, $q$, that describes the tight relation between radio and IR emission in star forming (SF) galaxies. We find a $2\sigma$ threshold of $q < 1.94$ to select radio-excess AGNs, which is derived from a sample of $\sim 7,000$ galaxies across the full mass range in the NASA-Sloan Atlas (NSA) that have radio and IR detections from VLASS and the Wide-Field Infrared Survey Explorer, respectively. We create catalogs of radio-excess AGNs and SF galaxies and make these available to the community. Applying our criterion to dwarf galaxies with stellar masses $M_\star \lesssim 3 \times 10^9 M_\odot$ and redshifts $z \le 0.15$, and carefully removing interlopers, we find 10 radio-excess AGNs with radio-optical positional offsets between $\sim$ 0 and 2.3 arcseconds (0 - 2.7 kpc). Based on statistical arguments and emission line diagnostics, we expect the majority of these radio-excess AGNs to be associated with the dwarf host galaxies rather than background AGNs. Five of the objects have evidence for hosting AGNs at other wavelengths, and 5 objects are identified as AGNs in dwarf galaxies for the first time. We also identify 8 variable radio sources in dwarf galaxies by comparing the VLASS epoch 1 and epoch 2 observations to FIRST detections presented in arXiv:1909.04670., Comment: 27 pages, 21 figures, 3 tables, accepted for publication in The Astrophysical Journal

The Hybrid Asymmetric Linear Higgs Factory (HALHF) proposes a shorter and cheaper design for a future Higgs factory. It reaches a $\sqrt{s} = 250$ GeV using a 500 GeV electron beam accelerated by an electron-driven plasma wake-field, and a conventionally-accelerated 31 GeV positron beam. Assuming plasma acceleration R&D challenges are solved in a timely manner, the asymmetry of the collisions brings additional challenges regarding the detector and the physics analyses, from forward boosted topologies and beam backgrounds. This contribution will detail the impact of beam parameters on beam-induced backgrounds, and provide a first look at what modification compared to e.g. the ILD can improve the physics performance at such a facility. The studies will be benchmarked against some flagship Higgs Factory analyses for comparison., Comment: To be published in PoS

In the attention economy, online platforms are incentivized to maximize user engagement through extended-use designs (EUDs), even when such practices conflict with users' best interests. We conducted a structured content analysis of all Very Large Online Platforms (VLOPs) to identify the EUDs these influential apps and sites use. We conducted this analysis posing as a teenager to understand the EUDs that young people are exposed to. We find that VLOPs use four strategies to promote extended use: pressuring, enticing, trapping, and lulling users. We report on a hierarchical taxonomy organizing the 63 designs that fall under these categories. Applying this taxonomy to all 17 VLOPs, we identify 583 instances of EUDs, with social media platforms using twice as many EUDs as other VLOPs. We present three vignettes illustrating how these designs reinforce one another in practice. We further contribute a graphical dataset of videos illustrating these features in the wild., Comment: 29 pages, 23 figures, open source Github page: https://extendedusedesign.github.io/ExtendedUseDesign/

Let $F$ be an arbitrary totally real field. Under weak conditions we prove the existence of certain Eisenstein congruences between parallel weight $k \geq 3$ Hilbert eigenforms of level $\mathfrak{mp}$ and Hilbert Eisenstein series of level $\mathfrak{m}$, for arbitrary ideal $\mathfrak{m}$ and prime ideal $\mathfrak{p}\nmid \mathfrak{m}$ of $\mathcal{O}_F$. Such congruences have their moduli coming from special values of Hecke $L$-functions and their Euler factors, and our results allow for the eigenforms to have non-trivial Hecke character. After this, we consider the question of when such congruences can be satisfied by newforms, proving a general result about this., Comment: 23 pages

We present the Early Data Release of the Multi-Cycle JWST-NEXUS Treasury program (2024-2028), which includes NIRCam imaging and WFSS observations from the first (partial) NEXUS-Wide epoch covering the central 100 ${\rm arcmin^2}$ of the NEXUS field, located near the North Ecliptic Pole and within the Euclid Ultra-Deep Field. We release reduced NIRCam mosaics (F090W, F115W, F150W, F200W, F356W, F444W), photometric source catalogs, as well as preliminary WFSS spectra (in F322W2 and F444W) for the subset of bright sources (F356W$<$21 mag or F444W$<$21 mag). These observations fully cover the NEXUS-Deep area, and anchor the long-term baseline of the program. These data will be used for initial target selection for the NIRSpec/MSA spectroscopy starting from June 2025. The NIRCam imaging reaches depths of 27.4--28.2 (AB) mags in F090W--F444W. Upcoming NEXUS-Wide epochs will expand the area to the full $\sim 400\,{\rm arcmin^2}$, and improve the NIRCam exposure depths in the Wide tier by a factor of three. In addition, this central region will be repeatedly covered by the NEXUS-Deep observations (NIRCam imaging and NIRSpec/MSA PRISM spectroscopy) over 18 epochs with a $\sim 2$-month cadence. We demonstrate the data quality of the first NEXUS observations, and showcase some example science cases enabled by these data., Comment: 14 pages, 9 figures, 2 tables. Data products are publicly accessible at https://ariel.astro.illinois.edu/nexus/edr/ Online interactive map for quick visualization of released images and WFSS spectra can be found at https://ariel.astro.illinois.edu/nexus/map/

Among the most puzzling early discoveries of JWST are "Little Red Dots" -- compact red sources that host broad Balmer emission lines and, in many cases, exhibit a "V shaped" change in slope in the rest-optical. The physical properties of Little Red Dots currently have order-of-magnitude uncertainties, because models to explain the continuum of these sources differ immensely. Here, we leverage the complete selection of red sources in the RUBIES program, supplemented with public PRISM spectra, to study the origin of this "V shape". By fitting a broken power law with a flexible inflection point, we find that a large fraction (20/44, nearly all spatially unresolved) of extremely red H$\alpha$ emitters at $2

Digital technologies have long been explored as a complement to standard procedure in mental health research and practice, ranging from the management of electronic health records to app-based interventions. The recent emergence of large language models (LLMs), both proprietary and open-source ones, represents a major new opportunity on that front. Yet there is still a divide between the community developing LLMs and the one which may benefit from them, thus hindering the beneficial translation of the technology into clinical use. This divide largely stems from the lack of a common language and understanding regarding the technology's inner workings, capabilities, and risks. Our narrative review attempts to bridge this gap by providing intuitive explanations behind the basic concepts related to contemporary LLMs.

Dispersion measures (DM) of fast radio bursts (FRBs) probe the density of electrons in the intergalactic medium (IGM) along their lines-of-sight, including the average density versus distance to the source and its variations in direction. While previous study focused on low-redshift, FRBs are potentially detectable out to high redshift, where their DMs can, in principle, probe the epoch of reionization (EOR) and its patchiness. We present the first predictions from large-scale, radiation-hydrodynamical simulation of fully-coupled galaxy formation and reionization, using Cosmic Dawn (``CoDa")~II to model the density and ionization fields of the universe down to redshifts through the end of the EOR at $z_{re}\approx6.1$. Combining this with an N-body simulation CoDa~II--Dark Matter of the fully-ionized epoch from the EOR to the present, we calculate the mean and standard deviation of FRB DMs as functions of their source redshift. The mean and standard deviation of DM increase with redshift, reaching a plateau by $z(x_{HII}\lesssim0.25)\gtrsim8$, i.e. well above $z_{re}$. The mean-DM asymptote $\mathcal{DM}_{max} \approx 5900~\mathrm{pc\, cm^{-3}}$ reflects the end of the EOR and its duration. The standard deviation there is $\sigma_{DM, max}\approx497 ~\mathrm{pc\, cm^{-3}}$, reflecting inhomogeneities of both patchy reionization and density. Inhomogeneities in ionization during the EOR contribute $\mathcal{O}(1$ per cent) of this value of $\sigma_{DM,max}$ from FRBs at redshifts $z\gtrsim 8$. Current estimates of FRB rates suggest this may be detectable within a few years of observation., Comment: 14 pages, 10 figures, 2 tables, 2 appendices

The determination of the Higgs self-coupling is a key target for future colliders, in particular through di-Higgs production at $e^+e^-$ Linear Colliders with $\sqrt{s} > 450$\,GeV, e.g.\ ILC, C3 or CLIC. This contribution will discuss the roles and the interplay of di-Higgs production processes at various collider energies, including the case of non-SM values of the self-coupling. Previous studies, already based on Geant4-based detector simulation, established that the Higgs self-coupling can be extracted with $10-27\%$ precision and provided a solid understanding of the limiting factors. This provides a robust starting point to explore the potential of more modern and sophisticated reconstruction and analysis techniques. We summarize the impact of advanced, often machine-learning-based algorithms, including e.g.\ jet clustering, kinematic fitting and matrix element-inferred likelihoods on the reconstruction of $ZHH$ events and before discussing the dependence of the projected precision on the center-of-mass energy and on the actual value of the self-coupling., Comment: 6 pages, contribution to proceedings of ICHEP 2024

Cost Adaptive Multi-queue eviction Policy (CAMP) is an algorithm for a general purpose key-value store (KVS) that manages key-value pairs computed by applications with different access patterns, key-value sizes, and varying costs for each key-value pair. CAMP is an approximation of the Greedy Dual Size (GDS) algorithm that can be implemented as efficiently as LRU. In particular, CAMP's eviction policies are as effective as those of GDS but require only a small fraction of the updates to an internal data structure in order to make those decisions. Similar to an implementation of LRU using queues, it adapts to changing workload patterns based on the history of requests for different key-value pairs. It is superior to LRU because it considers both the size and cost of key-value pairs to maximize the utility of the available memory across competing applications. We compare CAMP with both LRU and an alternative that requires human intervention to partition memory into pools and assign grouping of key-value pairs to different pools. The results demonstrate CAMP is as fast as LRU while outperforming both LRU and the pooled alternative. We also present results from an implementation of CAMP using Twitter's version of memcached., Comment: A shorter version of CAMP appeared in the Proceedings of the ACM/IFIP/USENIX Middleware Conference, Bordeaux, France, December 2014. See https://github.com/scdblab/CAMP for an implementation

An unresolved question in studies of active galactic nuclei (AGN) is whether their different classes probe different evolutionary stages of black hole--host galaxy interaction. We present the projected two-point cross-correlation function between a sample of Dark Energy Spectroscopic Instrument (DESI)-matched AGN selected from Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) optical + Wide-field Infrared Survey Explorer ($WISE$) mid-IR photometry, and DESI-designated luminous red galaxies, for $z\in 0.5-1.0$. The total overlap area is 43.4 deg$^2$, including $\sim27,000$ spectroscopic LRGs in our redshift range. We visually classified 1,991 matched HSC-DESI objects in our redshift range, spectroscopically confirming that 1,517 ($76\%$) of them are AGN. Of these 1,517 objects, $73\%$ are broad-line AGN, $27\%$ are obscured AGN. We infer that the parent HSC+$WISE$ AGN catalog has a number density of at least $\sim 240$ deg$^{-2}$, confirming it is one of the most complete optical/infrared AGN catalog to date. We investigate the AGN clustering as a function of the spectroscopic classification and infer the halo mass for each sample. The inferred average mass of the halos $\langle M_h\rangle$ that host unobscured broad-line AGN ($M_h \approx 10^{13.4}h^{-1}M_\odot$) is $\sim 5.5\times$ larger than the halos that host obscured AGN ($M_h \approx 10^{12.6}\, h^{-1}M_\odot$), at $2.8\sigma$ significance, in the same sense as our prior work based on photometric redshifts. This suggests that we may relax our concerns about systematic shifts in the inferred redshift distribution producing this halo mass difference. While we do not yet find statistically significant spectroscopic evidence that unobscured AGN reside in more massive halos than their obscured counterparts, further analyses are necessary to distinguish if more complex evolutionary histories are needed to model these AGN populations., Comment: 27 pages, 12 figures, submitted to ApJ

Stellar streams retain a memory of their gravitational interactions with small-scale perturbations. While perturbative models for streams have been formulated in action-angle coordinates, a direct transformation to these coordinates is only available for static and typically axisymmetric models for the galaxy. The real Milky Way potential is in a state of disequilibrium, complicating the application of perturbative methods around an equilibrium system. Here, we utilize a combination of differentiable simulations and Hamiltonian perturbation theory to model the leading-order effect of dark matter subhalos on stream observables. To obtain a perturbative description of streams, we develop a direct and efficient forward mode differentiation of Hamilton's equations of motion. Our model operates in observable coordinates, allowing us to treat the effects of arbitrary subhalo potentials on streams perturbatively, while simultaneously capturing non-linear effects due to other substructures like the infalling LMC or the rotating bar. The model predicts the velocity dispersion of streams as a function of subhalo statistics, allowing us to constrain the low-mass range of subhalos down to $\sim 10^5~M_\odot$. We forecast the velocity dispersion of the GD-1 stream, and find that observations are in agreement with a CDM subhalo population, with a slight preference for more dense subhalos. The method provides a new approach to characterize streams in the presence of substructure, with significantly more modeling flexibility compared to previous works., Comment: 31 pages (+5 appendix), 17 figures (+4 appendix). Submitted to ApJ. Comments welcome. Code release will accompany publication

We present a new empirical framework modeling the metallicity and star-formation history (SFH) dependence of X-ray luminous ($L > 10^{36}$ ergs s$^{-1}$) point-source population luminosity functions (XLFs) in normal galaxies. We expect the X-ray point-source populations are dominated by X-ray binaries (XRBs), with contributions from supernova remnants near the low luminosity end of our observations. Our framework is calibrated using the collective statistical power of 3,731 X-ray detected point-sources within 88 Chandra-observed galaxies at $D <$ 40 Mpc that span broad ranges of metallicity ($Z \approx$ 0.03-2 $Z_\odot$), SFH, and morphology (dwarf irregulars, late-types, and early-types). Our best-fitting models indicate that the XLF normalization per unit stellar mass declines by $\approx$2-3 dex from 10 Myr to 10 Gyr, with a slower age decline for low-metallicity populations. The shape of the XLF for luminous X-ray sources ($L < 10^{38}$ ergs s$^{-1}$) significantly steepens with increasing age and metallicity, while the lower-luminosity XLF appears to flatten with increasing age. Integration of our models provide predictions for X-ray scaling relations that agree very well with past results presented in the literature, including, e.g., the $L_{\rm X}$-SFR-$Z$ relation for high-mass XRBs (HMXBs) in young stellar populations as well as the $L_{\rm X}/M_\star$ ratio observed in early-type galaxies that harbor old populations of low-mass XRBs (LMXBs). The model framework and data sets presented in this paper further provide unique benchmarks that can be used for calibrating binary population synthesis models., Comment: Accepted for publication in ApJS; extended figures/materials available at https://lehmer.uark.edu/downloads/ ; python SED fitting code Lightning available at https://github.com/ebmonson/lightningpy

It has been proposed, and confirmed by multiple observations, that disks around low mass stars display a molecule-rich emission and carbon-rich disk chemistry as compared to their hotter, more massive solar counterparts. In this work, we present JWST Disk Infrared Spectral Chemistry Survey (JDISCS) MIRI-MRS observations of the solar-mass star DoAr 33, a low-accretion rate T Tauri star showing an exceptional carbon-rich inner disk. We report detections of H$_2$O, OH, and CO$_2$, as well as the more complex hydrocarbons, C$_2$H$_2$ and C$_4$H$_2$. Through the use of thermochemical models, we explore different spatial distributions of carbon and oxygen across the inner disk and compare the column densities and temperatures obtained from LTE slab model retrievals. We find a best match to the observed column densities with models that have carbon enrichment, and the retrieved emitting temperature and area of C$_2$H$_2$ with models that have C/O $=$ 2$-$4 inside the 500 K carbon-rich dust sublimation line. This suggests that the origin of the carbon-rich chemistry is likely due to the sublimation of carbon rich grains near the soot line. This would be consistent with the presence of dust processing as indicated by the detection of crystalline silicates. We propose that this long-lived hydrocarbon rich chemistry observed around a solar-mass star is a consequence of the unusually low M-star-like accretion rate of the central star, which lengthens the radial mixing timescale of the inner disk allowing the chemistry powered by carbon grain destruction to linger., Comment: 17 pages, 12 figures, 5 tables, 5 appendices (9 additional pages, 10 additional figures). Accepted for publication in ApJ

Non-negative Matrix Factorization (NMF) is an effective algorithm for multivariate data analysis, including applications to feature selection, pattern recognition, and computer vision. Its variant, Semi-Nonnegative Matrix Factorization (SNF), extends the ability of NMF to render parts-based data representations to include mixed-sign data. Graph Regularized SNF builds upon this paradigm by adding a graph regularization term to preserve the local geometrical structure of the data space. Despite their successes, SNF-related algorithms to date still suffer from instability caused by the Frobenius norm due to the effects of outliers and noise. In this paper, we present a new $L_{2,1}$ SNF algorithm that utilizes the noise-insensitive $L_{2,1}$ norm. We provide monotonic convergence analysis of the $L_{2,1}$ SNF algorithm. In addition, we conduct numerical experiments on three benchmark mixed-sign datasets as well as several randomized mixed-sign matrices to demonstrate the performance superiority of $L_{2,1}$ SNF over conventional SNF algorithms under the influence of Gaussian noise at different levels.

In a compound AI system, components such as an LLM call, a retriever, a code interpreter, or tools are interconnected. The system's behavior is primarily driven by parameters such as instructions or tool definitions. Recent advancements enable end-to-end optimization of these parameters using an LLM. Notably, leveraging an LLM as an optimizer is particularly efficient because it avoids gradient computation and can generate complex code and instructions. This paper presents a survey of the principles and emerging trends in LLM-based optimization of compound AI systems. It covers archetypes of compound AI systems, approaches to LLM-based end-to-end optimization, and insights into future directions and broader impacts. Importantly, this survey uses concepts from program analysis to provide a unified view of how an LLM optimizer is prompted to optimize a compound AI system. The exhaustive list of paper is provided at https://github.com/linyuhongg/LLM-based-Optimization-of-Compound-AI-Systems.

Some highlights of the physics case for running an $e^+e^-$ collider at 500 GeV and above are discussed with a particular emphasis on the experimental access to the Higgs potential via di-Higgs and (at sufficiently high energy) triple Higgs production. The information obtainable from Higgs pair production at about 500 GeV is compared with the prospects for the HL-LHC and with the indirect information that can be obtained from a Higgs factory running at lower energies., Comment: 9 pages, contribution to the proceedings of LCWS2024, Tokyo, July 2024

The double Higgs-strahlungs process $e^+e^- \rightarrow ZHH$ allows to access the Higgs self-coupling at center-of-mass energies above $450$ GeV. Its cross-section exhibits a very different behavior as a function of the value of the self-coupling than fusion-type processes like gluon-gluon fusion at LHC (and future hadron colliders) and $WW$ / $ZZ$ fusion at higher energy lepton colliders. Therefore it adds unique information to the picture, in particular should the value of the Higgs self-coupling differ from its Standard Model prediction. The last full evaluation of the potential of the ILC to measure this process is more than ten years old, and since then many of the reconstruction tools have received very significant improvements. This contribution presents the ongoing work in the ILD collaboration to update the ZHH projections for the next European Particle Physics Strategy Update., Comment: contribution to proceedings of LCWS2024, 10 pages

Pair-production and single-production of $W$ bosons provide many opportunities to look for new physics via precision measurements, for instance via scrutinising the involved triple-gauge vertices or by measuring CKM matrix elements in an environment very complementary to $B$ hadron decays. This contribution presents the ongoing work based on full simulation of the ILD concept, exploiting the O($10^8$) $W$ bosons produced during the $250$\,GeV stage of the ILC, as well as the CLD concept proposed for the FCC-ee. The projections, which also contribute to two focus topics of the current ECFA study on future Higgs/Top/Electroweak factories, promise improvements of the measurement precision of TGCs and the CKM matrix, respectively, of one to two orders of magnitude with respects to LEP., Comment: Contribution to proceedings of LCWS 2024, 6 pages

In this Letter, we investigate the turbulence and energy injection in the extended nebulae surrounding two luminous obscured quasars, WISEA J100211.29$+$013706.7 ($z=1.5933$) and SDSS J165202.64$+$172852.3 ($z=2.9489$). Utilizing high-resolution data from the NIRSpec IFU onboard the James Webb Space Telescope, we analyze the velocity fields of line-emitting gas in and around these quasars and construct the second-order velocity structure functions (VSFs) to quantify turbulent motions across different spatial scales. Our findings reveal a notable flattening in the VSFs from $\approx\!3$ kpc up to a scale of 10--20 kpc, suggesting that energy injection predominantly occurs at a scale $\lesssim$10 kpc, likely powered by quasar outflows and jet-driven bubbles. The extended spatial range of flat VSFs may also indicate the presence of multiple energy injection sources at these scales. For J1652, the turbulent energy in the host interstellar medium (ISM) is significantly higher than in tidally stripped gas, consistent with the expectation of active galactic nucleus (AGN) activities stirring up the host ISM. Compared to the VSFs observed on spatial scales of 10--50 kpc around lower-redshift UV-bright quasars, these obscured quasars exhibit higher turbulent energies in their immediate surroundings, implying different turbulence drivers between the ISM and halo-scale gas. Future studies with an expanded sample are essential to elucidate further the extent and the pivotal role of AGNs in shaping the gas kinematics of host galaxies and beyond., Comment: 10 pages, 4 figures; submitted; comments welcome!

The direct pair-production of the superpartner of the $\tau$-lepton, the $\widetilde{\tau}$, is one of the most interesting channels to search for SUSY in: the $\widetilde{\tau}$ is likely to be the lightest of the scalar leptons, and is one of the most experimentally chalanging ones. The current model-independent $\widetilde{\tau}$ limits come from LEP, while limits obtained at the LHC do extend to higher masses, but are model-dependent. The future Higgs factories will be powerful facilities for SUSY searches, offering advantages with respect to previous electron-positron colliders as well as to hadron machines. In order to quantify the capabilities of these future $e^+e^-$ colliders, the "worst-case" scenario for $\widetilde{\tau}$ exclusion/discovery has been studied, taking into account the effect of the $\widetilde{\tau}$ mixing on $\widetilde{\tau}$ production cross-section and detection efficiency. To evaluate the latter, the ILD concept, originally developed for the International Linear Collider (ILC), and the ILC beam conditions at a centre-of-mass energy of 500 GeV have been used for detailed simulations. The obtained exclusion and discovery reaches extend to only a few GeV below the kinematic limit even in the worst-case scenario. The results of the detailed simulation study are then discussed in view of the experimental environment of other proposed Higgs factory projects., Comment: Contributed to The International Workshop on Future Linear Colliders (LCWS2024), 8-11 July 2024,Tokyo, Japan

Contaminated and polluted water poses significant threats to human health, necessitating vigilant monitoring of water sources for potential contamination. This paper introduces a low-cost Internet of Things (IoT)-based water quality monitoring system designed to address water quality challenges in rural communities, as demonstrated through a case study conducted in the Philippines. The system consists of two core components. The hardware component of the system, built on Arduino technology and featuring real-time data transmission, focuses on monitoring pH levels, turbidity, and temperature via sensors. The system is equipped to transmit data to a cloud database and send informative messages to mobile numbers, updating users on the status of water supplies. The application component acts as a user interface for accessing and managing data collected by the sensors. The successful deployment of this Water Quality Monitoring (WQM) system not only helps community leaders and health workers monitor water sources but also underscores its potential to empower communities in safeguarding their water sources, thereby contributing to the advancement of clean and safe water access., Comment: Proceedings of the 2024 9th International Conference on Business and Industrial Research, May 2024, Bangkok, Thailand

In this work, we aim to deepen the understanding of inertial clustering and the role of sling events in high-Reynolds number ($Re$) particle-laden turbulence. To this end, we perform one-way coupled particle tracking in flow fields obtained from direct numerical simulations (DNS) of forced homogeneous isotropic turbulence. Additionally, we examine the impact of filtering utilized in large eddy simulations (LES) by applying a sharp spectral filter to the DNS fields. Our analysis reveals that while instantaneous clustering through the centrifuge mechanism explains clustering at early times, the path history effect--the sampling of fluid flow along particle trajectories--becomes important later on. The filtered fields expose small-scale fractal clustering that cannot be predicted by the instantaneous flow field. We show that there exists a filter-effective Stokes number that governs the degree of fractal clustering and preferential sampling, revealing scale-similarity in the spatial distributions and fractal dimensions. Sling events are prevalent throughout our simulations and impose prominent patterns on the particle fields. In pursuit of investigating the sling dynamics, we compute the relative velocity, ensemble-averaged over proximal neighboring particles, to identify particles undergoing caustics. As postulated in recent theories, we find that in fully resolved, high-$Re$ turbulence, sling events occur in thin sheets of high strain, situated between turbulent vortices. This behavior is driven by rare, extreme events of compressive straining, manifested by fluctuations of the flow velocity gradients that propagate back and forth the positive branch of the Vieillefosse line.

Quasar feedback may play a key role in the evolution of massive galaxies. The dust-reddened quasar, F2M110648.35$+$480712 at $z = 0.4352$ is one of the few cases at its redshift that exhibits powerful quasar feedback through bipolar outflows. Our new observation with the integral field unit mode of Near-infrared Spectrograph onboard JWST opens a new window to examine this spectacular outflow through Pa$\alpha$ emission line with $\sim$3$\times$ better spatial resolution than previous work. The morphology and kinematics of the Pa$\alpha$ nebula confirm the existence of a bipolar outflow extending on a scale of $\sim$17$\times$14 kpc and with a velocity reaching $\sim$1100 km s$^{-1}$. The higher spatial resolution of our new observation leads to more reliable measurements of outflow kinematics. Considering only the spatially resolved outflow and assuming an electron density of 100 cm$^{-2}$, the mass, momentum and kinetic energy outflow rates are $\sim$50-210 M$_{\odot}$ yr$^{-1}$, $\sim$0.3-1.7$\times$10$^{36}$ dynes ($\sim$14-78\% of the quasar photon momentum flux) and $\sim$0.16-1.27$\times$10$^{44}$ erg s$^{-1}$ ($\sim$0.02-0.20\% of the quasar bolometric luminosity), respectively. The local instantaneous outflow rates generally decrease radially. We infer that the quasar is powerful enough to drive the outflow, while stellar processes cannot be overlooked as a contributing energy source. The mass outflow rate is $\sim$0.4-1.5 times the star formation rate, and the ratio of kinetic energy outflow rate to the quasar bolometric luminosity is comparable to the minimum value required for negative quasar feedback in simulations. This outflow may help regulate the star formation activity within the system to some extent., Comment: 14 pages, 6 figures, 1 table, ApJ in review

Understanding uncertainty plays a critical role in achieving common ground (Clark et al.,1983). This is especially important for multimodal AI systems that collaborate with users to solve a problem or guide the user through a challenging concept. In this work, for the first time, we present a dataset annotated in collaboration with developmental and cognitive psychologists for the purpose of studying nonverbal cues of uncertainty. We then present an analysis of the data, studying different roles of uncertainty and its relationship with task difficulty and performance. Lastly, we present a multimodal machine learning model that can predict uncertainty given a real-time video clip of a participant, which we find improves upon a baseline multimodal transformer model. This work informs research on cognitive coordination between human-human and human-AI and has broad implications for gesture understanding and generation. The anonymized version of our data and code will be publicly available upon the completion of the required consent forms and data sheets., Comment: SIGDIAL 2023

We present deep Subaru/FOCAS spectra for two extreme emission line galaxies (EELGs) at $z\sim 1$ with strong {\sc[Oiii]}$\lambda$5007 emission lines, exhibiting equivalent widths (EWs) of $2905^{+946}_{-578}$ \AA\ and $2000^{+188}_{-159}$ \AA, comparable to those of EELGs at high redshifts that are now routinely identified with JWST spectroscopy. Adding a similarly large {\sc [Oiii]} EW ($2508^{+1487}_{-689}$ \AA) EELG found at $z\sim 2$ in the JWST CEERS survey to our sample, we explore for the physical origins of the large {\sc [Oiii]} EWs of these three galaxies with the Subaru spectra and various public data including JWST/NIRSpec, NIRCam, and MIRI data. While there are no clear signatures of AGN identified by the optical line diagnostics, we find that two out of two galaxies covered by the MIRI data show strong near-infrared excess in the spectral energy distributions (SEDs) indicating obscured AGN. Because none of the three galaxies show clear broad H$\beta$ lines, the upper limits on the flux ratios of broad-H$\beta$ to {\sc [Oiii]} lines are small, $\lesssim 0.15$ that are comparable with Seyfert $1.8-2.0$ galaxies. We conduct \texttt{Cloudy} modeling with the stellar and AGN incident spectra, allowing a wide range of parameters including metallicities and ionization parameters. We find that the large {\sc [Oiii]} EWs are not self-consistently reproduced by the spectra of stars or unobscured AGN, but obscured AGN that efficiently produces O$^{++}$ ionizing photons with weak nuclear and stellar continua that are consistent with the SED shapes., Comment: submitted to ApJ

Modern cryptographic methods for implementing privacy-preserving LLMs such as Homomorphic Encryption (HE) require the LLMs to have a polynomial form. Forming such a representation is challenging because Transformers include non-polynomial components, such as Softmax and layer normalization. Previous approaches have either directly approximated pre-trained models with large-degree polynomials, which are less efficient over HE, or replaced non-polynomial components with easier-to-approximate primitives before training, e.g., Softmax with pointwise attention. The latter approach might introduce scalability challenges. We present a new HE-friendly variant of self-attention that offers a stable form for training and is easy to approximate with polynomials for secure inference. Our work introduces the first polynomial LLMs with 32 layers and over a billion parameters, exceeding the size of previous models by more than tenfold. The resulting models demonstrate reasoning and in-context learning (ICL) capabilities comparable to standard transformers of the same size, representing a breakthrough in the field. Finally, we provide a detailed latency breakdown for each computation over encrypted data, paving the way for further optimization, and explore the differences in inductive bias between transformers relying on our HE-friendly variant and standard transformers. Our code is attached as a supplement.

Understanding protein motion within the cell is crucial for predicting reaction rates and macromolecular transport in the cytoplasm. A key question is how crowded environments affect protein dynamics through hydrodynamic and direct interactions at molecular length scales. Using megahertz X-ray Photon Correlation Spectroscopy (MHz-XPCS) at the European X-ray Free Electron Laser (EuXFEL), we investigate ferritin diffusion at microsecond time scales. Our results reveal anomalous diffusion, indicated by the non-exponential decay of the intensity autocorrelation function $g_2(q,t)$ at high concentrations. This behavior is consistent with the presence of cage-trapping in between the short- and long-time protein diffusion regimes. Modeling with the $\delta\gamma$-theory of hydrodynamically interacting colloidal spheres successfully reproduces the experimental data by including a scaling factor linked to the protein direct interactions. These findings offer new insights into the complex molecular motion in crowded protein solutions, with potential applications for optimizing ferritin-based drug delivery, where protein diffusion is the rate-limiting step.

The dearth of high quality spectroscopy of dusty star-forming galaxies (DSFGs) -- the main drivers of the assembly of dust and stellar mass at the peak of activity in the Universe -- greatly hinders our ability to interpret their physical processes and evolutionary pathways. We present JWST/NIRSpec observations from RUBIES of four submillimeter-selected, ALMA-detected DSFGs at cosmic noon, $z\sim2.3-2.7$. While photometry uniformly suggests vigorous ongoing star formation for the entire sample in line with canonical DSFGs, the spectra differ: one source has spectroscopic evidence of an evolved stellar population, indicating a recent transition to a post-starburst phase, while the remainder show strong spectroscopic signatures of ongoing starbursts. All four galaxies are infrared-luminous (log$_{10}$$L_{\rm{IR}}$/L$_{\rm \odot}$ $>12.4$), massive (log$_{10}\,M_\star$/M$_{\rm \odot}$ $>11$), and very dust-obscured ($A_V\sim3-4$ ABmag). Leveraging detections of multiple Balmer and Paschen lines, we derive an optical attenuation curve consistent with Calzetti overall, yet an optical extinction ratio $R_V\sim2.5$, potentially indicating smaller dust grains or differences in star-dust geometry. This case study provides some of the first detailed spectroscopic evidence that the DSFGs encompass a heterogeneous sample spanning a range of star formation properties and evolutionary stages, and illustrates the advantages of synergistic JWST and ALMA analysis of DSFGs., Comment: 20 pages, 4 figures; submitted to ApJ

High-spin states in molecular systems hold significant interest for a wide range of applications ranging from optoelectronics to quantum information and singlet fission (SF). Quintet and triplet states play crucial roles, particularly in SF systems, necessitating a precise monitoring and control of their spin dynamics. Spin states in intramolecular SF (iSF) are of particular interest, but tuning these systems to control triplet multiplication pathways has not been extensively studied. Additionally, whilst studies in this context focus on participation of triplet pathways leading to photoluminescence, emission pathways via quintet states remain largely unexplored. Here, we employ a set of unique spin-sensitive techniques to investigate high-spin state formation and emission in dimers and trimers comprising multiple diphenylhexatriene (DPH) units. We demonstrate the formation of pure quintet states in all these oligomers, with optical emission via quintet states dominating delayed fluorescence up to room temperature. For triplet formation, we distinguish between SF and ISC pathways, identifying the trimer Me-(DPH)$_3$ as the only oligomer exhibiting exclusively the desired SF pathways. Conversely, linear (DPH)$_3$ and (DPH)$_2$ show additional or exclusive triplet pathways via ISC. Our comprehensive analysis provides a detailed investigation into high-spin state formation, control, and emission in intramolecular singlet fission systems.

Recently, NIRSpec PRISM/CLEAR observations by JWST have begun providing rest-frame UV continuum measurements of galaxies at $z\gtrsim7$, revealing signatures of Ly$\alpha$ damping-wing (DW) absorption by the intergalactic medium (IGM). We develop a methodology to constrain the global ionization fraction of the IGM $(Q_{\rm HII})$ using low-resolution spectra, employing the random forest classification (RFC) method. We construct mock spectra using the simulated galaxies and the IGM from the Cosmic Dawn II simulation and train RFC models to estimate $Q_{\rm HII}$ at the redshift of the source and to detect the presence of a damped Ly$\alpha$ absorber (DLA). We find that individual galaxy spectra with spectral bins between 1220 and 1270 {\AA} and with signal-to-noise ratios greater than 20 can place tight constraints on $Q_{\rm HII}$, provided the UV continuum is accurately modeled. This method is particularly effective for the early phase of reionization ($Q_{\rm HII}<50\%$), when the IGM opacity is high in the DW. As a demonstration, we apply our model to existing NIRSpec PRISM/CLEAR spectra, placing upper bounds of $Q_{\rm HII}=59.6\%$, $5.6\%$, and $18.5\%$ at $z=7.7,~9.4,$ and $10.6$, respectively, with $68\%$ confidence, though several modeling uncertainties remain to be discussed. These constraints favor late-starting reionization models, where $\gtrsim 80\%$ of the IGM is ionized after $z=8$. We conclude that high SNR observations of carefully selected targets around $z\sim7-9$ can effectively constrain reionization models., Comment: 20 pages, 11 figures, submitted to ApJ

JWST has revealed an abundance of compact, red objects at $z\approx5-8$ dubbed "little red dots" (LRDs), whose SEDs display a faint blue UV continuum followed by a steep rise in the optical. Despite extensive study of their characteristic V-shaped SEDs, the nature of LRDs remains unknown. We present a new analysis of the NIRSpec/PRISM spectrum of A2744-QSO1, a triply imaged LRD at $z=7.04$ from the UNCOVER survey. The spectrum shows a strong Balmer break and broad Balmer emission lines, both of which are difficult to explain with models invoking exclusively AGN or stellar contributions. Our fiducial model decomposes the spectrum into a post-starburst galaxy dominating the UV-optical continuum and a reddened AGN being sub-dominant at all wavelength and contributing at $\sim20\%$ level. However, our most credible model infers a stellar mass of $M_\star\approx 4\times10^9\,\mathrm{M_\odot}$ within a radius of $r_\mathrm{e}<30\,$pc, driving its central density to the highest among observations to date. This high central density could be explained if A2744-QSO-1 is the early-forming core of a modern-day massive elliptical galaxy that later puffed up via the inside-out growth channel. The models also necessitate an unusually steep dust law to preserve the strong break strength, though this steepness may be explained by a deficit of large dust grains. It is also probable that these challenges reflect our ignorance of A2744-QSO1's true nature. Future variability and reverberation mapping studies could help disentangle the galaxy and AGN contribution to the continuum, and deeper redder observations could also unveil the dust properties in LRDs., Comment: 19 pages, 7 figures, 2 tables. Submitted to ApJ. Comments are welcome

Analyses of major group mergers are key to understanding the evolution of large-scale structure in the Universe and the microphysical properties of the hot gas in these systems. We present imaging and spectral analyses of deep Chandra observations of hot gas structures formed in the major merger of the NGC 7618 and UGC 12491 galaxy groups and compare the observed hot gas morphology, temperatures, and abundances with recent simulations. The morphology of the observed multiple cold front edges and boxy wings are consistent with those expected to be formed by Kelvin-Helmholtz instabilities and gas sloshing in inviscid gas. The arc-shaped slingshot tail morphologies seen in each galaxy suggest that the dominant galaxies are near their orbital apogee after having experienced at least one core passage at a large impact parameter., Comment: 30 pages, 8 figures

We present a detailed analysis of JWST/NIRSpec and NIRCam observations of ZF-UDS-7329, a massive, quiescent galaxy at redshift $z=3.2$, which has been put forward to challenge cosmology and galaxy formation physics. Our study extends previous works by focusing on the impact of different star formation history (SFH) priors, stellar libraries, metallicity, and initial mass function assumptions. Our results show that ZF-UDS-7329, with a formed stellar mass of $M_{\star} \approx 10^{11.4}~M_{\odot}$ and a specific star formation rate of $\mathrm{sSFR} \approx 0.03$ Gyr$^{-1}$, formed efficiently in the first billion years of the Universe. In agreement with previous work, we find that the spectrum is consistent with mass-weighted stellar ages of $1.3-1.8$ Gyr, depending on the SFH prior used. A physically motivated rising SFH prior makes the formation history of ZF-UDS-7329 compatible with stellar mass and star-formation rate estimates of high-redshift ($z>6$) galaxies. Using NIRCam imaging, we identify a colour gradient indicative of an old, quiescent bulge and a younger disc component, as expected from a complex formation history. The inferred SFH is consistent a high stellar fraction of $f_{\star}=M_{\star}/(f_b \cdot M_{\rm h}) \approx 100\%$ at $z=7-12$, implying an extremely high integrated star-formation efficiency. However, when considering cosmic variance and possible mergers as expected in over-dense environments - as traced by ZF-UDS-7329 - the stellar fractions could be reduced to $f_{\star} \approx 50\%$, which is more consistent with galaxy formation models and the stellar-to-halo mass relation at lower redshifts. We conclude that ZF-UDS-7329 forms extremely efficient in the early universe, but does not necessitate unseen galaxies at higher redshifts since the inferred SFR of ancestors are consistent with those seen in $z>6$ galaxies., Comment: 15 pages and 8 figures (+appendix), submitted to MNRAS

Everyone aspires to achieve personal goals. However, getting started is often complex and daunting, especially for large projects. AI has the potential to create plans and help jumpstart progress, but it often lacks sufficient personal context to be useful. We introduce JumpStarter, a system that uses AI-powered context curation to create action plans and draft personalized working solutions. JumpStarter assists users by posing questions to elicit relevant context, breaking down goals into manageable steps, and selecting appropriate context to draft working solutions for each step. A technical evaluation indicates that context curation results in plans and working solutions of higher quality. A user study demonstrates that compared to ChatGPT, JumpStarter significantly reduces users' mental load and increases their efficiency in kickstarting personal projects. We discuss the design implications of AI-powered context curation to facilitate the use of generative AI in complex problem-solving.

Modern biological research is increasingly data-intensive, leading to a growing demand for effective training in biological data science. In this article, we provide an overview of key resources and best practices available within the Bioconductor project - an open-source software community focused on omics data analysis. This guide serves as a valuable reference for both learners and educators in the field., Comment: 16 pages, 2 figures, 1 table, 1 supplemental table

Using medium-band imaging from the newly released Merian Survey, we conduct a nonparametric morphological analysis of H$\alpha$ emission maps and stellar continua for a sample of galaxies with $8\lesssim\log (M_\star/M_\odot) < 10.3$ at $0.064

We present the Merian Survey, an optical imaging survey optimized for studying the physical properties of bright star-forming dwarf galaxies. Merian is carried out with two medium-band filters ($N708$ and $N540$, centered at $708$ and $540$ nm), custom-built for the Dark Energy Camera (DECam) on the Blanco telescope. Merian covers $\sim 750\,\mathrm{deg}^2$ of equatorial fields, overlapping with the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) wide, deep, and ultra-deep fields. When combined with the HSC-SSP imaging data ($grizy$), the new Merian DECam medium-band imaging allows for photometric redshift measurements via the detection of H$\rm\alpha$ and [OIII] line emission flux excess in the $N708$ and $N540$ filters, respectively, at $0.06

We present the PANORAMIC survey, a pure parallel extragalactic imaging program with NIRCam observed during JWST Cycle 1. The survey obtained $\sim$530 sq arcmin of NIRCam imaging from 1-5$\mu$m, totaling $\sim$192 hours of science integration time. This represents the largest on-sky time investment of any Cycle 1 GO extragalactic NIRCam imaging program by nearly a factor of 2. The survey includes $\sim$432 sq arcmin of novel sky area not yet observed with JWST using at least $6$ NIRCam broad-band filters, increasing the existing area covered by similar Cycle 1 data by $\sim$60%. 70 square arcmin was also covered by a 7th filter (F410M). A fraction of PANORAMIC data ($\sim$200 sq arcmin) was obtained in or around extragalactic deep-fields, enhancing their legacy value. Pure parallel observing naturally creates a wedding cake survey with both wide and ultra-deep tiers, with 5$\sigma$ point source depths at F444W ranging from 27.8-29.4 (ABmag), and with minimized cosmic variance. The 6+ filter observing setup yields remarkably good photometric redshift performance, achieving similar median scatter and outlier fraction as CANDELS ($\sigma_{\rm NMAD}\sim0.07$; $\eta\sim0.2$), which enables a wealth of science across redshift without the need for followup or ancillary data. We overview the proposed survey, the data obtained as part of this program, and document the science-ready data products in the first data release. PANORAMIC has delivered wide-area and deep imaging with excellent photometric performance, demonstrating that pure parallel observations with JWST are a highly efficient observing mode that is key to acquiring a complete picture of galaxy evolution from rare bright galaxies to fainter, more abundant sources at all redshifts., Comment: Submitted to AAS Journals; comments welcome. Initial data release available at https://panoramic-jwst.github.io/

Dwarf galaxies hold the key to crucial frontiers of astrophysics, however, their faintness renders spectroscopy challenging. Here we present the JWST Cycle 2 survey, All the Little Things (ALT, PID 3516), which is designed to seek late-forming Pop III stars and the drivers of reionization at $z\sim6-7$. ALT has acquired the deepest NIRCam grism spectroscopy yet (7-27 hr), at JWST's most sensitive wavelengths (3-4 $\mu$m), covering the powerful lensing cluster Abell 2744. Over the same 30 arcmin$^2$, ALT's ultra-deep F070W+F090W imaging ($\sim$30 mag) enables selection of very faint sources at $z>6$. We demonstrate the success of ALT's novel ``butterfly" mosaic to solve spectral confusion and contamination, and introduce the ``Allegro" method for emission line identification. By collecting spectra for every source in the field of view, ALT has measured precise ($R\sim1600$) redshifts for 1630 sources at $z=0.2-8.5$. This includes one of the largest samples of distant dwarf galaxies: [1015, 475, 50] sources less massive than the SMC, Fornax, and Sculptor with $\log(M_{*}/M_{\odot})<$[8.5, 7.5, 6.5]. We showcase ALT's discovery space with: (i) spatially resolved spectra of lensed clumps in galaxies as faint as $M_{\rm{UV}}\sim-15$; (ii) large-scale clustering -- overdensities at $z$=[2.50, 2.58, 3.97, 4.30, 5.66, 5.77, 6.33] hosting massive galaxies with striking Balmer breaks; (iii) small-scale clustering -- a system of satellites around a Milky Way analog at $z\sim6$; (iv) spectroscopically confirmed multiple images that help constrain the lensing model underlying all science in this legacy field; (v) sensitive star-formation maps based on dust-insensitive tracers such as Pa$\alpha$; (vi) direct spectroscopic discovery of rare sources such as AGN with ionized outflows. These results provide a powerful proof of concept for how grism surveys maximize the potential of strong lensing fields., Comment: Submitted to the Open Journal of Astrophysics. Figs. 6 and 10 illustrate the quality of the spectra and imaging, while Fig. 12 summarizes the yield of the survey. Comments warmly welcomed and greatly appreciated. The ALT DR1 catalog is available at https://zenodo.org/records/13871850

Recent advancements in large language models have significantly expedited the process of generating front-end code. This allows users to rapidly prototype user interfaces and ideate through code, a process known as exploratory programming. However, existing LLM code-generation tools focus more on technical implementation details rather than finding the right design given a particular problem. We present DynEx, an LLM-based method for design exploration in accelerated exploratory programming. DynEx uses LLMs to guide users through a structured Design Matrix to explore the design space before dynamic iterative implementation. It also introduces a technique to self-invoke generative AI, enabling the creation of a diverse suite of applications. A user study of 10 experts found that DynEx increased design exploration and enabled the creation of more complex and varied prototypes compared to a Claude Artifact baseline. We conclude with a discussion of the implications of design exploration for exploratory programming., Comment: 18 pages, 7 figures

The introduction of generative pre-trained models, like GPT-4, has introduced a phenomenon known as prompt engineering, whereby model users repeatedly write and revise prompts while trying to achieve a task. Using these AI models for intelligent features in software applications require using APIs that are controlled through developer-written prompts. These prompts have powered AI experiences in popular software products, potentially reaching millions of users. Despite the growing impact of prompt-powered software, little is known about its development process and its relationship to programming. In this work, we argue that some forms of prompts are programs, and that the development of prompts is a distinct phenomenon in programming. We refer to this phenomenon as prompt programming. To this end, we develop an understanding of prompt programming using Straussian grounded theory through interviews with 20 developers engaged in prompt development across a variety of contexts, models, domains, and prompt complexities. Through this study, we contribute 14 observations about prompt programming. For example, rather than building mental models of code, prompt programmers develop mental models of the FM's behavior on the prompt and its unique qualities by interacting with the model. While prior research has shown that experts have well-formed mental models, we find that prompt programmers who have developed dozens of prompts, each with many iterations, still struggle to develop reliable mental models. This contributes to a rapid and unsystematic development process. Taken together, our observations indicate that prompt programming is significantly different from traditional software development, motivating the creation of tools to support prompt programming. Our findings have implications for software engineering practitioners, educators, and researchers.