arXiv subjects

Alice Cai

Publications and source records attributed to Alice Cai.

9 recordsLinked to original sources

arXiv2026

Evidence of Supernova Between Formation of Stellar Populations in a Globular Cluster

Globular clusters do not undergo conventional chemical evolution driven by supernova enrichment. Instead, they exhibit unique abundance patterns of the light elements, which cannot be fully explained by any of the proposed enrichment mechanisms. "Normal" stars of low sodium abundances comprise the first population of cluster stars, and "enriched" stars of high sodium abundances, which are found only in globular clusters, comprise the second population. Here we show from a differential line-by-line analysis of stars that span a small range of effective temperature that the globular cluster M92 has higher Fe abundances in second-population (sodium-enhanced) stars than first-population stars. The two populations are well separated in Na, Al, and Fe abundances. The rise in Fe abundance between the first and second stellar populations suggests that M92 was able to retain at least some supernova ejecta, all of which exploded after the first population finished forming. This result provides a lower limit for the time delay between populations.

astro-ph.SR↗

arXiv2026

Discovery of 30 Repeating Fast Radio Burst Sources and Uniform Population Statistics of 80 Repeating Sources from CHIME/FRB

We present 30 newly discovered repeating fast radio burst (FRB) sources from the second catalog of bursts detected by the FRB backend on the Canadian Hydrogen Intensity Mapping Experiment (CHIME/FRB). These repeaters have extragalactic dispersion measures (DMs) spanning $99.4-1446.0\ \text{pc cm}^{-3}$ and burst rates between $10^{-5.7}$ and $10^{-0.5}$ hr$^{-1}$ scaled to a fluence threshold of 5 Jy ms. We report evidence of monotonic, linear DM variations in four repeaters on years-long timescales. The newly discovered sources bring CHIME/FRB's total number of observed repeating FRBs to 80, 79 of which were discovered by CHIME/FRB, between 2018 July 25 and 2023 September 15. In the full CHIME/FRB sample, only 2.4$\pm 0.4\%$ of sources have been observed to repeat, and we do not find evidence for significant evolution of this value over the duration of the experiment. We find no substantial evidence for bimodal populations of one-off and repeating FRBs in their burst rate distributions; the distribution of upper limits on repeat rates implied from observations of as-yet one-offs is entirely contained within the observed range of repeater burst rates and the distributions do not appear inconsistent. Similarly, using the population analysis framework of C. W. James (2023), we find that our observations of repeating and yet-one-off FRBs are equally well fit assuming a power-law distribution of repeat rates with 50$-$100% of the population repeating.

astro-ph.HE↗

arXiv2026

Where can AI be used? Insights from a deep ontology of work activities

Artificial intelligence (AI) is poised to profoundly reshape how work is executed and organized, but we do not yet have deep frameworks for understanding where AI can be used. Here we provide a comprehensive ontology of work activities that can help systematically analyze and predict uses of AI. To do this, we disaggregate and then substantially reorganize the approximately 20K activities in the US Department of Labor's widely used O*NET occupational database. Next, we use this framework to classify descriptions of 13,275 AI software applications and a worldwide tally of 20.8 million robotic systems. Finally, we use the data about both these kinds of AI to generate graphical displays of how the estimated units and market values of all worldwide AI systems used today are distributed across the work activities that these systems help perform. We find a highly uneven distribution of AI market value across activities, with the top 1.6% of activities accounting for over 60% of AI market value. Most of the market value is used in information-based activities (72%), especially creating information (36%), and only 12% is used in physical activities. Interactive activities include both information-based and physical activities and account for 48% of AI market value, much of which (26%) involves transferring information. These results can be viewed as rough predictions of the AI applicability for all the different work activities down to very low levels of detail. Thus, we believe this systematic framework can help predict at a detailed level where today's AI systems can and cannot be used and how future AI capabilities may change this.

cs.AI↗

arXiv2025

$r$-process Abundance Dispersion in the Globular Cluster M5 using Keck Archival Data

We studied $28$ RGB stars in the mildly metal-rich globular cluster M5 ([Fe/H] $= -1.29$) using archival high-resolution spectra from the Keck Observatory archive (KOA) to better understand the $r$-process in globular clusters. Previous studies (M15, M92, and NGC 2298) have shown $r$-process dispersion in varying amounts, hinting at the source of the $r$-process in those clusters. We extend these dispersion studies to the more metal-rich cluster M5 by studying the rare-earth peak, specifically the elements Ba, Nd, and Eu. We separately analyze the different stellar generations, as traced by the abundance of Na and O. Based on the Nd and Eu abundances, we report a tenuous detection of $r$-process dispersion that is dependent on the generation and element. Based on a log-likelihood dispersion study accounting for measurement errors, Nd has an intrinsic first generation abundance spread of $\sigma_{1G}(\text{Nd}) = 0.15_{-0.07}^{+0.10}$ and an $2\sigma$ upper limit on the second generation spread of $\sigma_{2G}(\text{Nd}) < 0.28$. The upper limits on the Eu intrinsic spread are $\sigma_{1G}(\text{Eu}) < 0.34$ and $\sigma_{2G}(\text{Eu}) < 0.16$. A potential dispersion implies the cluster gas was inhomogeneously polluted, either due to an event concurrent with the formation of the cluster or due to clouds of disparate composition that coalesced to form the cluster.

astro-ph.GA↗

arXiv2025

FRB 20250316A: A Brilliant and Nearby One-Off Fast Radio Burst Localized to 13 parsec Precision

Precise localizations of a small number of repeating fast radio bursts (FRBs) using very long baseline interferometry (VLBI) have enabled multiwavelength follow-up observations revealing diverse local environments. However, the 2--3\% of FRB sources that are observed to repeat may not be representative of the full population. Here we use the VLBI capabilities of the full CHIME Outriggers array for the first time to localize a nearby (40 Mpc), bright (kJy), and apparently one-off FRB source, FRB 20250316A, to its environment on 13-pc scales. We use optical and radio observations to place deep constraints on associated transient emission and the properties of its local environment. We place a $5\sigma$ upper limit of $L_{\mathrm{9.9~\mathrm{GHz}}} < 2.1\times10^{25}~\mathrm{erg~s^{-1}~Hz^{-1}}$ on spatially coincident radio emission, a factor of 100 lower than any known compact persistent radio source associated with an FRB. Our KCWI observations allow us to characterize the gas density, metallicity, nature of gas ionization, dust extinction and star-formation rate through emission line fluxes. We leverage the exceptional brightness and proximity of this source to place deep constraints on the repetition of FRB 20250316A, and find it is inconsistent with all well-studied repeaters given the non-detection of bursts at lower spectral energies. We explore the implications of a measured offset of 190$\pm20$ pc from the center of the nearest star-formation region, in the context of progenitor channels. FRB 20250316A marks the beginning of an era of routine localizations for one-off FRBs on tens of mas-scales, enabling large-scale studies of their local environments.

astro-ph.HE↗

arXiv2025

Discovery and Localization of the Swift-Observed FRB 20241228A in a Star-forming Host Galaxy

On 2024 December 28, CHIME/FRB detected the thus-far non-repeating FRB 20241228A with a real-time signal-to-noise ratio of $>50$. Approximately 112~s later, the X-ray Telescope onboard the Neil Gehrels Swift Observatory was on source, the fastest follow-up to-date of a non-repeating FRB (Tohuvavohu et al. in prep.). Using CHIME/FRB and two of the three CHIME/FRB Outriggers, we obtained a Very Long Baseline Interferometry localization for FRB 20241228A with a 1$\sigma$ confidence ellipse of 11$^{\prime\prime}$ by 0.2$^{\prime\prime}$. This represents the first published localization using both the CHIME-KKO and CHIME-GBO Outriggers. We associate FRB 20241228A with a star-forming galaxy at a redshift of $z = 0.1614\pm0.0002$. The persistent X-ray luminosity limit at this source's location and distance is $<1.2 \times 10^{43}$ erg s$^{-1}$ in the $0.3-10$ keV band, the most stringent limit of any non-repeating FRB to-date (Tohuvavohu et al. in prep.). The stellar mass ($\sim 2.6 \times 10^{10}\,M_{\odot}$) and star formation rate ($\sim 2.9\,M_{\odot}$~yr$^{-1}$) of the host galaxy of FRB 20241228A are consistent with the broader FRB host galaxy population. We measure significant scattering ($\sim$1ms) and scintillation ($\sim$20 kHz at 600 MHz) along the line of sight to this source, and suggest the scintillation screen is Galactic while the scattering screen is extragalactic. FRB 20241228A represents an exciting example of a new era in which we can harness VLBI-localizations and rapid high-energy follow-up to probe FRB progenitors.

astro-ph.HE↗

arXiv2025

Simulating Cooperative Prosocial Behavior with Multi-Agent LLMs: Evidence and Mechanisms for AI Agents to Inform Policy Decisions

Human prosocial cooperation is essential for our collective health, education, and welfare. However, designing social systems to maintain or incentivize prosocial behavior is challenging because people can act selfishly to maximize personal gain. This complex and unpredictable aspect of human behavior makes it difficult for policymakers to foresee the implications of their designs. Recently, multi-agent LLM systems have shown remarkable capabilities in simulating human-like behavior, and replicating some human lab experiments. This paper studies how well multi-agent systems can simulate prosocial human behavior, such as that seen in the public goods game (PGG), and whether multi-agent systems can exhibit ``unbounded actions'' seen outside the lab in real world scenarios. We find that multi-agent LLM systems successfully replicate human behavior from lab experiments of the public goods game with three experimental treatments - priming, transparency, and varying endowments. Beyond replicating existing experiments, we find that multi-agent LLM systems can replicate the expected human behavior when combining experimental treatments, even if no previous study combined those specific treatments. Lastly, we find that multi-agent systems can exhibit a rich set of unbounded actions that people do in the real world outside of the lab -- such as collaborating and even cheating. In sum, these studies are steps towards a future where LLMs can be used to inform policy decisions that encourage people to act in a prosocial manner.

cs.HC↗

arXiv2024

Antagonistic AI

The vast majority of discourse around AI development assumes that subservient, "moral" models aligned with "human values" are universally beneficial -- in short, that good AI is sycophantic AI. We explore the shadow of the sycophantic paradigm, a design space we term antagonistic AI: AI systems that are disagreeable, rude, interrupting, confrontational, challenging, etc. -- embedding opposite behaviors or values. Far from being "bad" or "immoral," we consider whether antagonistic AI systems may sometimes have benefits to users, such as forcing users to confront their assumptions, build resilience, or develop healthier relational boundaries. Drawing from formative explorations and a speculative design workshop where participants designed fictional AI technologies that employ antagonism, we lay out a design space for antagonistic AI, articulating potential benefits, design techniques, and methods of embedding antagonistic elements into user experience. Finally, we discuss the many ethical challenges of this space and identify three dimensions for the responsible design of antagonistic AI -- consent, context, and framing.

cs.AI↗

arXiv2023

AtomXR: Streamlined XR Prototyping with Natural Language and Immersive Physical Interaction

As technological advancements in extended reality (XR) amplify the demand for more XR content, traditional development processes face several challenges: 1) a steep learning curve for inexperienced developers, 2) a disconnect between 2D development environments and 3D user experiences inside headsets, and 3) slow iteration cycles due to context switching between development and testing environments. To address these challenges, we introduce AtomXR, a streamlined, immersive, no-code XR prototyping tool designed to empower both experienced and inexperienced developers in creating applications using natural language, eye-gaze, and touch interactions. AtomXR consists of: 1) AtomScript, a high-level human-interpretable scripting language for rapid prototyping, 2) a natural language interface that integrates LLMs and multimodal inputs for AtomScript generation, and 3) an immersive in-headset authoring environment. Empirical evaluation through two user studies offers insights into natural language-based and immersive prototyping, and shows AtomXR provides significant improvements in speed and user experience compared to traditional systems.

cs.HC↗