Search

As modern AI models become integral to everyday tasks, concerns about their inherent biases and their potential impact on human decision-making have emerged. While bias in models are well-documented, less is known about how these biases influence human decisions. This paper presents two interactive experiments investigating the effects of partisan bias in AI language models on political decision-making. Participants interacted freely with either a biased liberal, conservative, or unbiased control model while completing political decision-making tasks. We found that participants exposed to politically biased models were significantly more likely to adopt opinions and make decisions aligning with the AI's bias, regardless of their personal political partisanship. However, we also discovered that prior knowledge about AI could lessen the impact of the bias, highlighting the possible importance of AI education for robust bias mitigation. Our findings not only highlight the critical effects of interacting with biased AI and its ability to impact public discourse and political conduct, but also highlights potential techniques for mitigating these risks in the future.

We give a description of the Linnell division ring of a countable residually (poly-$\mathbb Z$ virtually nilpotent) (RPVN) group in terms of a generalised Novikov ring, and show that vanishing top-degree cohomology of a finite type group $G$ with coefficients in this Novikov ring implies the existence of a normal subgroup $N \leqslant G$ such that $\mathrm{cd}_{\mathbb Q}(N) < \mathrm{cd}_{\mathbb Q}(G)$ and $G/N$ is poly-$\mathbb Z$ virtually nilpotent. As a consequence, we show that if $G$ is an RPVN group of finite type, then its top-degree $\ell^2$-Betti number vanishes if and only if there is a poly-$\mathbb Z$ virtually nilpotent quotient $G/N$ such that $\mathrm{cd}_{\mathbb Q}(N) < \mathrm{cd}_{\mathbb Q}(G)$. In particular, finitely generated RPVN groups of cohomological dimension $2$ are virtually free-by-nilpotent if and only if their second $\ell^2$-Betti number vanishes, and therefore $2$-dimensional RPVN groups with vanishing second $\ell^2$-Betti number are coherent. As another application, we show that if $G$ is a finitely generated parafree group with $\mathrm{cd}(G) = 2$, then $G$ satisfies the Parafree Conjecture if and only if the terms of its lower central series are eventually free. Note that the class of RPVN groups contains all finitely generated RFRS groups and all finitely generated residually torsion-free nilpotent groups., Comment: 27 pages

We present a transmission spectrum of the misaligned hot Jupiter WASP-15b from 2.8--5.2 microns observed with JWST's NIRSpec/G395H grating. Our high signal to noise data, which has negligible red noise, reveals significant absorption by H$_2$O ($4.2\sigma$) and CO$_2$ ($8.9\sigma$). From independent data reduction and atmospheric retrieval approaches, we infer that WASP-15b's atmospheric metallicity is super-solar ($\gtrsim 15\times$ solar) and its C/O is consistent with solar, that together imply planetesimal accretion. Our GCM simulations for WASP-15b suggest that the C/O we measure at the limb is likely representative of the entire photosphere due to the mostly uniform spatial distribution of H$_2$O, CO$_2$ and CO. We additionally see evidence for absorption by SO$_2$ and absorption at 4.9$\mu$m, for which the current leading candidate is OCS, albeit with several caveats. If confirmed, this would be the first detection of OCS in an exoplanet atmosphere and point towards complex photochemistry of sulphur-bearing species in the upper atmosphere. These are the first observations from the BOWIE-ALIGN survey which is using JWST's NIRSpec/G395H instrument to compare the atmospheric compositions of aligned/low-obliquity and misaligned/high-obliquity hot Jupiters around F stars above the Kraft break. The goal of our survey is to determine whether the atmospheric composition differs across two populations of planets that have likely undergone different migration histories (disc versus disc-free) as evidenced by their obliquities (aligned versus misaligned)., Comment: 24 pages, 23 figures, 6 tables. Submitted to MNRAS

In this paper we study the (co)homology of Tanabe algebras, which are a family of subalgebras of the partition algebras exhibiting a Schur-Weyl duality with certain complex reflection groups. The homology of the partition algebras has been shown to be related to the homology of the symmetric groups by Boyd-Hepworth-Patzt and the results they obtain depend on a parameter. In all known results, the homology of a diagram algebra is dependent on one of two things: the invertibility of a parameter in the ground ring or the parity of the positive integer indexing the number of pairs of vertices. We show that the (co)homology of Tanabe algebras is isomorphic to the (co)homology of the symmetric groups and that this is independent of both the parameter and the parity of the index. To the best of our knowledge, this is the first example of a result of this sort. Along the way we will also study the (co)homology of the uniform block permutation algebra and the totally propagating partition algebra as well collecting cohomological analogues of known results for the homology of partition algebras and Jones annular algebras., Comment: 14 pages

Neutral sodium (Na I) is an alkali metal with a favorable absorption cross section such that tenuous gases are easily illuminated at select transiting exoplanet systems. We examine both the time-averaged and time-series alkali spectral flux individually, over 4 nights at a hot Saturn system on a $\sim$ 2.8 day orbit about a Sun-like star WASP-49 A. Very Large Telescope/ESPRESSO observations are analyzed, providing new constraints. We recover the previously confirmed residual sodium flux uniquely when averaged, whereas night-to-night Na I varies by more than an order of magnitude. On HARPS/3.6-m Epoch II, we report a Doppler redshift at $v_{ \Gamma, \mathrm{NaD}} =$ +9.7 $\pm$ 1.6 km/s with respect to the planet's rest frame. Upon examining the lightcurves, we confirm night-to-night variability, on the order of $\sim$ 1-4 % in NaD rarely coinciding with exoplanet transit, not readily explained by stellar activity, starspots, tellurics, or the interstellar medium. Coincident with the $\sim$+10 km/s Doppler redshift, we detect a transient sodium absorption event dF$_{\mathrm{NaD}}$/F$_{\star}$ = 3.6 $\pm$ 1 % at a relative difference of $\Delta F_{\mathrm{NaD}} (t) \sim$ 4.4 $\pm$ 1 %, enduring $\Delta t_{\mathrm{NaD}} \gtrsim$ 40 minutes. Since exoplanetary alkali signatures are blueshifted due to the natural vector of radiation pressure, estimated here at roughly $\sim$ -5.7 km/s, the radial velocity is rather at +15.4 km/s, far larger than any known exoplanet system. Given that the redshift magnitude v$_{\Gamma}$ is in between the Roche limit and dynamically stable satellite orbits, the transient sodium may be a putative indication of a natural satellite orbiting WASP-49 A b., Comment: Accepted to ApJ Letters (2024 August 2)

We revisit the problem explored in [1] of guaranteeing satisfaction of multiple simultaneous state constraints applied to a single-input, single-output plant consisting of a chain of n integrators subject to input limitations. For this problem setting, we derive an analytic, easy-to-implement safety filter which respects input limitations and ensures forward-invariance of all state constraints simultaneously. Additionally, we provide a straightforward extension to the multi-input, multi-output chained integrator setting, and provide an analytic safety filter guaranteeing satisfaction of arbitrarily many simultaneous hyperplane constraints on the output vector. Whereas the approach in [1] obtains maximal invariant sets, our approach trades off some degree of conservatism in exchange for a recursive safety filter which is analytic for any arbitrary n >= 1., Comment: To be submitted to the 2025 American Control Conference

We present a boundary data-driven magneto-hydrodynamic (MHD) simulation of the 2011-02-15 coronal mass ejection (CME) event of Active Region (AR) NOAA 11158. The simulation is driven at the lower boundary with an electric field derived from the normal magnetic field and the vertical electric current measured from the Solar Dynamics Observatory (SDO) Helioseismic Magnetic Imager (HMI) vector magnetograms. The simulation shows the build up of a pre-eruption coronal magnetic field that is close to the nonlinear force-free field (NLFFF) extrapolation, and it subsequently develops multiple eruptions. The sheared/twisted field lines of the pre-eruption magnetic field show qualitative agreement with the brightening loops in the SDO Atmospheric Imaging Assembly (AIA) hot passband images. We find that the eruption is initiated by the tether-cutting reconnection in a highly sheared field above the central polarity inversion line (PIL) and a magnetic flux rope with dipped field lines forms during the eruption. The modeled erupting magnetic field evolves to develop a complex structure containing two distinct flux ropes and produces an outgoing double-shell feature consistent with the Solar TErrestrial RElations Observatory B / Extreme UltraViolet Imager (STEREO-B/EUVI) observation of the CME. The foot points of the erupting field lines are found to correspond well with the dimming regions seen in the SDO/AIA observation of the event. These agreements suggest that the derived electric field is a promising way to drive MHD simulations to establish the realistic pre-eruption coronal field based on the observed vertical electric current and model its subsequent dynamic eruption., Comment: 17 pages, 13 figures, accepted for publication in the Astrophysical Journal

The supervision of state-of-the-art multiple object tracking (MOT) methods requires enormous annotation efforts to provide bounding boxes for all frames of all videos, and instance IDs to associate them through time. To this end, we introduce Walker, the first self-supervised tracker that learns from videos with sparse bounding box annotations, and no tracking labels. First, we design a quasi-dense temporal object appearance graph, and propose a novel multi-positive contrastive objective to optimize random walks on the graph and learn instance similarities. Then, we introduce an algorithm to enforce mutually-exclusive connective properties across instances in the graph, optimizing the learned topology for MOT. At inference time, we propose to associate detected instances to tracklets based on the max-likelihood transition state under motion-constrained bi-directional walks. Walker is the first self-supervised tracker to achieve competitive performance on MOT17, DanceTrack, and BDD100K. Remarkably, our proposal outperforms the previous self-supervised trackers even when drastically reducing the annotation requirements by up to 400x., Comment: ECCV 2024

The Hubble Space Telescope has been a pioneering instrument for studying the atmospheres of exoplanets, specifically its WFC3 and STIS instruments. With the launch of JWST, we are able to observe larger spectral ranges at higher precision. NIRISS/SOSS covers the range 0.6--2.8 microns, and thus can serve as a direct comparison to WFC3 (0.8--1.7 microns). We perform atmospheric retrievals of WFC3 and NIRISS transmission spectra of WASP-39 b in order to compare their constraining power. We find that NIRISS is able to retrieve precise H2O abundances that do not suffer a degeneracy with the continuum level, due to the coverage of multiple spectral features. We also combine these datasets with spectra from STIS, and find that challenges associated with fitting the steep optical slope can bias the retrieval results. In an effort to diagnose the differences between the WFC3 and NIRISS retrievals, we perform the analysis again on the NIRISS data cut to the same wavelength range as WFC3. We find that the water abundance is in strong disagreement with both the WFC3 and full NIRISS retrievals, highlighting the importance of wide wavelength coverage. Finally, we carry out mock retrievals on the different instruments, which shows further evidence of the challenges in constraining water abundance from the WFC3 data alone. Our study demonstrates the vast information gain of JWST's NIRISS instrument over WFC3, highlighting the insights to be obtained from our new era of space-based instruments., Comment: 21 pages, 17 figures; Accepted for publication in MNRAS

Predicting the emergence of multiple chronic conditions (MCC) is crucial for early intervention and personalized healthcare, as MCC significantly impacts patient outcomes and healthcare costs. Graph neural networks (GNNs) are effective methods for modeling complex graph data, such as those found in MCC. However, a significant challenge with GNNs is their reliance on an existing graph structure, which is not readily available for MCC. To address this challenge, we propose a novel generative framework for GNNs that constructs a representative underlying graph structure by utilizing the distribution of the data to enhance predictive analytics for MCC. Our framework employs a graph variational autoencoder (GVAE) to capture the complex relationships in patient data. This allows for a comprehensive understanding of individual health trajectories and facilitates the creation of diverse patient stochastic similarity graphs while preserving the original feature set. These variations of patient stochastic similarity graphs, generated from the GVAE decoder, are then processed by a GNN using a novel Laplacian regularization technique to refine the graph structure over time and improves the prediction accuracy of MCC. A contextual Bandit is designed to evaluate the stochastically generated graphs and identify the best-performing graph for the GNN model iteratively until model convergence. We validate the performance of the proposed contextual Bandit algorithm against $\varepsilon$-Greedy and multi-armed Bandit algorithms on a large cohort (n = 1,592) of patients with MCC. These advancements highlight the potential of the proposed approach to transform predictive healthcare analytics, enabling a more personalized and proactive approach to MCC management.

Using a combination of HST, JWST, and ALMA data, we perform spatially resolved spectral energy distributions (SED) fitting of fourteen 4

We present a spatially resolved analysis of four star-forming galaxies at $z = 4.44-5.64$ using data from the JWST PRIMER and ALMA-CRISTAL surveys to probe the stellar and inter-stellar medium properties on the sub-kpc scale. In the $1-5\,\mu{\rm m}$ JWST NIRCam imaging we find that the galaxies are composed of multiple clumps (between $2$ and $\sim 8$) separated by $\simeq 5\,{\rm kpc}$, with comparable morphologies and sizes in the rest-frame UV and optical. Using BAGPIPES to perform pixel-by-pixel SED fitting to the JWST data we show that the SFR ($\simeq 25\,{\rm M}_{\odot}/{\rm yr}$) and stellar mass (${\rm log}_{10}(M_{\star}/{\rm M}_{\odot}) \simeq 9.5$) derived from the resolved analysis are in close ($ \lesssim 0.3\,{\rm dex}$) agreement with those obtained by fitting the integrated photometry. In contrast to studies of lower-mass sources, we thus find a reduced impact of outshining of the older (more massive) stellar populations in these normal $z \simeq 5$ galaxies. Our JWST analysis recovers bluer rest-frame UV slopes ($\beta \simeq -2.1$) and younger ages ($\simeq 100\,{\rm Myr}$) than archival values. We find that the dust continuum from ALMA-CRISTAL seen in two of these galaxies correlates, as expected, with regions of redder rest-frame UV slopes and the SED-derived $A_{\rm V}$, as well as the peak in the stellar mass map. We compute the resolved IRX-$\beta$ relation, showing that the IRX is consistent with the local starburst attenuation curve and further demonstrating the presence of an inhomogeneous dust distribution within the galaxies. A comparison of the CRISTAL sources to those from the FirstLight zoom-in simulation of galaxies with the same $M_{\star}$ and SFR reveals similar age and colour gradients, suggesting that major mergers may be important in the formation of clumpy galaxies at this epoch., Comment: 16 pages, 8 figures, 3 tables, plus 4 page appendix. Submitted to MNRAS

Scientists increasingly recognize the importance of providing rich, standards-adherent metadata to describe their experimental results. Despite the availability of sophisticated tools to assist in the process of data annotation, investigators generally seem to prefer to use spreadsheets when supplying metadata, despite the limitations of spreadsheets in ensuring metadata consistency and compliance with formal specifications. In this paper, we describe an end-to-end approach that supports spreadsheet-based entry of metadata, while ensuring rigorous adherence to community-based metadata standards and providing quality control. Our methods employ several key components, including customizable templates that capture metadata standards and that can inform the spreadsheets that investigators use to author metadata, controlled terminologies and ontologies for defining metadata values that can be accessed directly from a spreadsheet, and an interactive Web-based tool that allows users to rapidly identify and fix errors in their spreadsheet-based metadata. We demonstrate how this approach is being deployed in a biomedical consortium known as HuBMAP to define and collect metadata about a wide range of biological assays.

We present a theoretical framework for temperature imaging from long-wavelength infrared thermal radiation (e.g. 8-12 $\mu$m) through the end-to-end design of a metasurface-optics frontend and a computational-reconstruction backend. We introduce a new nonlinear reconstruction algorithm, ``Planck regression," that reconstructs the temperature map from a grayscale sensor image, even in the presence of severe chromatic aberration, by exploiting blackbody and optical physics particular to thermal imaging. We combine this algorithm with an end-to-end approach that optimizes a manufacturable, single-layer metasurface to yield the most accurate reconstruction. Our designs demonstrate high-quality, noise-robust reconstructions of arbitrary temperature maps (including completely random images) in simulations of an ultra-compact thermal-imaging device. We also show that Planck regression is much more generalizable to arbitrary images than a straightforward neural-network reconstruction, which requires a large training set of domain-specific images., Comment: 17 pages, 4 figures

The adiabatic elastocaloric effect relates changes in the strain that a material experiences to resulting changes in its temperature. While elastocaloric materials have been utilized for cooling in room temperature applications, the use of such materials for cryogenic cooling remains relatively unexplored. Here, we use a strain load/unload technique at low temperatures, similar to those employed at room-temperature, to demonstrate a large cooling effect in TmVO$_4$. For strain changes of $1.8 \cdot 10^{-3}$, the inferred cooling reaches approximately 50% of the material's starting temperature at 5 K, justifying the moniker "giant". Beyond establishing the suitability of this class of material for cryogenic elastocaloric cooling, these measurements also provide additional insight to the entropy landscape in the material as a function of strain and temperature, including the behavior proximate to the quadrupolar phase transition.

The distribution of different types of atmospheres and surfaces on rocky planets is one of the major questions in exoplanet astronomy, but there are currently no published unambiguous detections of atmospheres on any rocky exoplanets. The MIRI instrument on JWST can measure thermal emission from tidally locked rocky exoplanets orbiting small, cool stars. This emission is a function of their surface and atmospheric properties, potentially allowing the detection of atmospheres. One technique is to measure day-side emission to search for lower thermal emission than expected for a black-body planet due to atmospheric absorption features. Another technique is to measure phase curves of thermal emission to search for night-side emission due to atmospheric heat redistribution. In this work we compare strategies for detecting atmospheres on rocky exoplanets using these techniques. We simulate secondary eclipse and phase curve observations in the MIRI F1500W and F1280W filters, for a range of surfaces and atmospheres on thirty exoplanets selected for their F1500W signal-to-noise ratio. Our results show that secondary eclipse observations are highly degenerate between surfaces and atmospheres, given the wide range of potential surface albedos. We also show that thick atmospheres can support emission consistent with a black-body planet in these filters. These two results make it difficult to unambiguously detect or rule out atmospheres using their photometric day-side emission, except in a subset of CO$_{2}$-dominated atmospheres. We suggest that an F1500W phase curve could instead be observed for a similar sample of planets, allowing the unambiguous detection of atmospheres by night-side emission.

Interest in the study and analysis of dynamic processes in the social, behavioral, and health sciences has burgeoned in recent years due to the increased availability of intensive longitudinal data. However, how best to model and account for the persistent heterogeneity characterizing such processes remains an open question. The multi-VAR framework, a recent methodological development built on the vector autoregressive model, accommodates heterogeneous dynamics in multiple-subject time series through structured penalization. In the original multi-VAR proposal, individual-level transition matrices are decomposed into common and unique dynamics, allowing for generalizable and person-specific features. The current project extends this framework to allow additionally for the identification and penalized estimation of subgroup-specific dynamics; that is, patterns of dynamics that are shared across subsets of individuals. The performance of the proposed subgrouping extension is evaluated in the context of both a simulation study and empirical application, and results are compared to alternative methods for subgrouping multiple-subject, multivariate time series.

Insects excel in trajectory and attitude handling during flight, yet the specific kinematic behaviours they use for maintaining stability in air disturbances are not fully understood. This study investigates the adaptive strategies of bumblebees when exposed to gust disturbances directed from three different angles within a plane cross-sectional to their flight path. By analyzing characteristic wing motions during gust traversal, we aim to uncover the mechanisms that enable bumblebees to maintain control in unsteady environments. We utilised high-speed cameras to capture detailed flight paths, allowing us to extract dynamic information. Our results reveal that bees make differential bilateral kinematic adjustments based on gust direction: sideward gusts elicit posterior shifts in the wing closest to the gust, while upward gusts trigger coordinated posterior shifts in both wings. Downward gusts prompted broader flapping and increased flapping frequencies, along with variations in flap timing and sweep angle. Stroke sweep angle was a primary factor influencing recovery responses, coupled with motion around the flap axis. The adaptive behaviours strategically position the wings to optimize gust reception and enhance wing-generated forces. These strategies can be distilled into specific behavioural patterns for analytical modelling to inform the design of robotic flyers. We observed a characteristic posterior shift of wings when particular counteractive manoeuvres were required. This adjustment reduced the portion of the stroke during which the wing receiving gust forces was positioned in front of the centre of gravity, potentially enhancing manoeuvrability and enabling more effective recovery manoeuvres. These findings deepen our understanding of insect flight dynamics and offer promising strategies for enhancing the stability and manoeuvrability of MAVs in turbulent environments., Comment: 8 pages, 6 figures

Authorship obfuscation, rewriting a text to intentionally obscure the identity of the author, is an important but challenging task. Current methods using large language models (LLMs) lack interpretability and controllability, often ignoring author-specific stylistic features, resulting in less robust performance overall. To address this, we develop StyleRemix, an adaptive and interpretable obfuscation method that perturbs specific, fine-grained style elements of the original input text. StyleRemix uses pre-trained Low Rank Adaptation (LoRA) modules to rewrite an input specifically along various stylistic axes (e.g., formality and length) while maintaining low computational cost. StyleRemix outperforms state-of-the-art baselines and much larger LLMs in a variety of domains as assessed by both automatic and human evaluation. Additionally, we release AuthorMix, a large set of 30K high-quality, long-form texts from a diverse set of 14 authors and 4 domains, and DiSC, a parallel corpus of 1,500 texts spanning seven style axes in 16 unique directions

Vision-based motion estimation methods show promise in accurately and unobtrusively estimating human body motion for healthcare purposes. However, these methods are not specifically designed for healthcare purposes and face challenges in real-world applications. Human pose estimation methods often lack the accuracy needed for detecting fine-grained, subtle body movements, while optical flow-based methods struggle with poor lighting conditions and unseen real-world data. These issues result in human body motion estimation errors, particularly during critical medical situations where the body is motionless, such as during unconsciousness. To address these challenges and improve the accuracy of human body motion estimation for healthcare purposes, we propose the OPPH operator designed to enhance current vision-based motion estimation methods. This operator, which considers human body movement and noise properties, functions as a multi-stage filter. Results tested on two real-world and one synthetic human motion dataset demonstrate that the operator effectively removes real-world noise, significantly enhances the detection of motionless states, maintains the accuracy of estimating active body movements, and maintains long-term body movement trends. This method could be beneficial for analyzing both critical medical events and chronic medical conditions.

Language models are known to absorb biases from their training data, leading to predictions driven by statistical regularities rather than semantic relevance. We investigate the impact of these biases on answer choice preferences in the Massive Multi-Task Language Understanding (MMLU) task. Our findings reveal that differences in learned regularities across answer options are predictive of model preferences and mirror human test-taking strategies. To address this issue, we introduce two novel methods: Counterfactual Prompting with Chain of Thought (CoT) and Counterfactual Prompting with Agnostically Primed CoT (APriCoT). We demonstrate that while Counterfactual Prompting with CoT alone is insufficient to mitigate bias, our novel Primed Counterfactual Prompting with CoT approach effectively reduces the influence of base-rate probabilities while improving overall accuracy. Our results suggest that mitigating bias requires a "System-2" like process and that CoT reasoning is susceptible to confirmation bias under some prompting methodologies. Our contributions offer practical solutions for developing more robust and fair language models.

Estimating varying treatment effects in randomized trials with noncompliance is inherently challenging since variation comes from two separate sources: variation in the impact itself and variation in the compliance rate. In this setting, existing flexible machine learning methods are highly sensitive to the weak instruments problem, in which the compliance rate is (locally) close to zero. Our main methodological contribution is to present a Bayesian Causal Forest model for binary response variables in scenarios with noncompliance. By repeatedly imputing individuals' compliance types, we can flexibly estimate heterogeneous treatment effects among compliers. Simulation studies demonstrate the usefulness of our approach when compliance and treatment effects are heterogeneous. We apply the method to detect and analyze heterogeneity in the treatment effects in the Illinois Workplace Wellness Study, which not only features heterogeneous and one-sided compliance but also several binary outcomes of interest. We demonstrate the methodology on three outcomes one year after intervention. We confirm a null effect on the presence of a chronic condition, discover meaningful heterogeneity impact of the intervention on metabolic parameters though the average effect is null in classical partial effect estimates, and find substantial heterogeneity in individuals' perception of management prioritization of health and safety., Comment: 24 pages, 8 figures

In this paper, we study characteristics of horofunction boundaries of Carnot groups. In particular, we show that for Carnot groups, i.e., stratified nilpotent Lie groups equipped with certain left-invariant homogeneous metrics, all horofunctions are piecewise-defined using Pansu derivatives. For higher Heisenberg groups and filiform Lie groups, two families which generalize the standard 3-dimensional real Heisenberg group, we study the dimensions and topologies of their horofunction boundaries. In doing so, we find that filiform Lie groups $L_n$ of dimension $n\geq 8$ provide the first-known examples of Carnot groups whose horofunction boundaries are not full-dimensional, i.e., of codimension 1., Comment: 29 pages, 4 figures

We present a near infrared (NIR) candidate star cluster catalog for the central kiloparsec of M82 based on new JWST NIRCam images. We identify star cluster candidates using the F250M filter, finding 1357 star cluster candidates with stellar masses $>10^4$ M$_\odot$. Compared to previous optical catalogs, nearly all (87%) of the candidates we identify are new. The star cluster candidates have a median intrinsic cluster radius of $\approx$1 pc and have stellar masses up to $10^6$ M$_\odot$. By comparing the color-color diagram to dust-free yggdrasil stellar population models, we estimate that the star cluster candidates have A$_{\rm V}\sim3-24$ mag, corresponding to A$_{\rm 2.5\mu m}\sim0.3-2.1$ mag. There is still appreciable dust extinction towards these clusters into the NIR. We measure the stellar masses of the star cluster candidates, assuming ages of 0 and 8 Myr. The slope of the resulting cluster mass function is $\beta=1.9\pm0.2$, in excellent agreement with studies of star clusters in other galaxies., Comment: Resubmitted to ApJL

We prove that a closed negatively curved analytic Riemannian manifold that contains infinitely many totally geodesic hypersurfaces is isometric to an arithmetic hyperbolic manifold. Equivalently, any closed analytic Riemannian manifold with negative sectional curvature has only finitely many totally geodesic hypersurfaces, unless it has constant curvature., Comment: 30 pages, minor revisions

We implement a variant of the quantum pigeonhole paradox thought experiment to study whether classical counting principles survive in the quantum domain. We observe strong measurements significantly violate the pigeonhole principle (that among three pigeons in two holes, at least one pair must be in the same hole) and the sum rule (that the number of pigeon pairs in the same hole is the sum of the number of pairs across each of the holes) in an ensemble that is pre and postselected into particular separable states. To investigate whether measurement disturbance is a viable explanation for these counter-intuitive phenomena, we employ the first ever variable-strength measurement of a non-local observable. As we decrease the measurement strength, we find the violation of the sum rule decreases, yet the pigeonhole principle remains violated. In the weak limit, the sum rule is restored due to the cancellation between two weak values with equal and opposite imaginary parts. We observe the same kind of cancellation at higher measurement strengths, thus raising the question: do strong measurements have imaginary parts?, Comment: 8 pages, 4 figures

In semiconductor-based quantum technologies, the capability to shuttle charges between components is profoundly enabling. We numerically simulated various "conveyor-belt" shuttling scenarios for simple Si/SiO2 devices, explicitly modelling the electron's wave function using grid-based split-operator methods and a time-dependent 2D potential (obtained from a Poisson solver). This allowed us to fully characterise the electron loss probability and excitation fraction. Remarkably, with as few as three independent electrodes the process can remain near-perfectly adiabatic even in the presence of pulse imperfection, nearby charge defects, and Johnson-Nyquist noise. Only a substantial density of charge defects, or defects at 'adversarial' locations, can catastrophically disrupt the charge shuttling. While we do not explicitly model the spin or valley degrees of freedom, our results from this charge propagation study support the conclusion that conveyor-belt shuttling is an excellent candidate for providing connectivity in semiconductor quantum devices., Comment: 32 pages, 34 figures

The gas-phase velocity dispersions in disk galaxies, which trace turbulence in the interstellar medium, are observed to increase with lookback time. However, the mechanisms that set this rise in turbulence are observationally poorly constrained. To address this, we combine kiloparsec-scale ALMA observations of CO(3-2) and CO(4-3) with HST observations of H$\alpha$ to characterize the molecular gas and star formation properties of seven local analogues of main sequence galaxies at $z \sim 1-2$, drawn from the DYNAMO sample. Investigating the ''molecular gas main sequence'' on kpc-scales, we find that galaxies in our sample are more gas-rich than local star-forming galaxies at all disk positions. We measure beam smearing corrected molecular gas velocity dispersions and relate them to the molecular gas and star formation rate surface densities. Despite being relatively nearby ($z \sim 0.1$), DYNAMO galaxies exhibit high velocity dispersions and gas and star formation rate surface densities throughout their disks, when compared to local star forming samples. Comparing these measurements to predictions from star formation theory, we find very good agreements with the latest feedback-regulated star formation models. However, we find that theories which combine gravitational energy dissipation from radial gas transport with feedback over-estimate the observed molecular gas velocity dispersions., Comment: 24 pages, 12 figures, 2 tables, accepted for publication in The Astrophysical Journal

Statistical analyses based on the spatial correlation between the sky maps of Gravitational Wave (GW) events and the positions of potential host environments are a powerful tool to infer the origin of the black hole binary mergers that have been detected by the LIGO, Virgo, and KAGRA instruments. In this paper, we tighten our previous constraints on the fraction of detected GW events that may have originated from Active Galactic Nuclei (AGN). We consider 159 mergers detected not later than June 1st, 2024, and the all-sky quasar catalogue Quaia. We increase by a factor of 5.3 and 114 the number of considered GW sources and AGN respectively, also extending our analysis from redshift 0.3 to 1.5. This is possible thanks to the uniformity of the AGN catalogue and its high level of completeness, which we estimate as a function of redshift and luminosity. We find at a 95 per cent credibility level that un-obscured AGN with a bolometric luminosity higher than $10^{44.5}{\rm erg\ s}^{-1}$ ($10^{45}{\rm erg\ s}^{-1}$) do not contribute to more than the 21 (11) per cent of the detected GW events., Comment: 10 pages, 6 figures, 3 tables

We introduce Temporal Residual Jacobians as a novel representation to enable data-driven motion transfer. Our approach does not assume access to any rigging or intermediate shape keyframes, produces geometrically and temporally consistent motions, and can be used to transfer long motion sequences. Central to our approach are two coupled neural networks that individually predict local geometric and temporal changes that are subsequently integrated, spatially and temporally, to produce the final animated meshes. The two networks are jointly trained, complement each other in producing spatial and temporal signals, and are supervised directly with 3D positional information. During inference, in the absence of keyframes, our method essentially solves a motion extrapolation problem. We test our setup on diverse meshes (synthetic and scanned shapes) to demonstrate its superiority in generating realistic and natural-looking animations on unseen body shapes against SoTA alternatives. Supplemental video and code are available at https://temporaljacobians.github.io/ ., Comment: 15 pages, 6 figures

The first generation of ELT instruments includes an optical-infrared high-resolution spectrograph, indicated as ELT-HIRES and recently christened ANDES (ArmazoNes high Dispersion Echelle Spectrograph). ANDES consists of three fibre-fed spectrographs ([U]BV, RIZ, YJH) providing a spectral resolution of $\sim$100,000 with a minimum simultaneous wavelength coverage of 0.4-1.8 $\mu$m with the goal of extending it to 0.35-2.4 $\mu$m with the addition of a U arm to the BV spectrograph and a separate K band spectrograph. It operates both in seeing- and diffraction-limited conditions and the fibre feeding allows several, interchangeable observing modes including a single conjugated adaptive optics module and a small diffraction-limited integral field unit in the NIR. Modularity and fibre-feeding allow ANDES to be placed partly on the ELT Nasmyth platform and partly in the Coud\'e room. ANDES has a wide range of groundbreaking science cases spanning nearly all areas of research in astrophysics and even fundamental physics. Among the top science cases, there are the detection of biosignatures from exoplanet atmospheres, finding the fingerprints of the first generation of stars, tests on the stability of Nature's fundamental couplings, and the direct detection of the cosmic acceleration. The ANDES project is carried forward by a large international consortium, composed of 35 Institutes from 13 countries, forming a team of almost 300 scientists and engineers which include the majority of the scientific and technical expertise in the field that can be found in ESO member states., Comment: SPIE astronomical telescope and instrumentation 2024, in press

We present new JWST/NIRSpec IFU observations of the J1000+0234 system at $z=4.54$, the dense core of a galaxy protocluster hosting a massive, dusty star forming galaxy (DSFG) with a low luminosity radio counterpart. The new data reveals two extended, high equivalent width (EW$_0 > 1000$ {\AA}) nebulae at each side of the DSFG disk along its minor axis (namely O3-N and O3-S). On one hand, O3-N's spectrum shows a prominent FWHM $\sim1300$ km s$^{-1}$ broad and blueshifted component, suggesting an outflow origin. On the other hand, O3-S stretches over parsec and has a velocity gradient that spans $800$ km s$^{-1}$ but no evidence of a broad component. Both sources, however, seem to be powered at least partially by an active galactic nucleus (AGN), so we classify them as extended emission-line regions (EELRs). The strongest evidence comes from the detection of the high-ionization [Ne V] $\lambda3427$ line toward O3-N, which paired with the non-detection of hard X-rays implies an obscuring column density above the Compton-thick regime. In O3-S, the [Ne V] line is not detected, but we measure a He II well above the expectation for star formation. We interpret this as O3-S being externally irradiated by the AGN, akin to the famous Hanny's Voorwerp object in the local Universe. In addition, more classical line ratio diagnostics (e.g. [O III]/H$\beta$ vs [N II]/H$\alpha$) put the DSFG itself in the AGN region of the diagrams, and hence the most probable host of the AGN. These results showcase the ability of JWST of unveiling highly obscured AGN at high redshifts., Comment: 5 pages, 4 figures plus 5 appendices (incl. 3 extra figures and one table). Submitted to A&A on July 17th 2024

Effective representation of 2D images is fundamental in digital image processing, where traditional methods like raster and vector graphics struggle with sharpness and textural complexity respectively. Current neural fields offer high-fidelity and resolution independence but require predefined meshes with known discontinuities, restricting their utility. We observe that by treating all mesh edges as potential discontinuities, we can represent the magnitude of discontinuities with continuous variables and optimize. Based on this observation, we introduce a novel discontinuous neural field model that jointly approximate the target image and recovers discontinuities. Through systematic evaluations, our neural field demonstrates superior performance in denoising and super-resolution tasks compared to InstantNGP, achieving improvements of over 5dB and 10dB, respectively. Our model also outperforms Mumford-Shah-based methods in accurately capturing discontinuities, with Chamfer distances 3.5x closer to the ground truth. Additionally, our approach shows remarkable capability in handling complex artistic drawings and natural images.

We present results from a search for X-ray/gamma-ray counterparts of gravitational-wave (GW) candidates from the third observing run (O3) of the LIGO-Virgo-KAGRA (LVK) network using the Swift Burst Alert Telescope (Swift-BAT). The search includes 636 GW candidates received in low latency, 86 of which have been confirmed by the offline analysis and included in the third cumulative Gravitational-Wave Transient Catalogs (GWTC-3). Targeted searches were carried out on the entire GW sample using the maximum--likelihood NITRATES pipeline on the BAT data made available via the GUANO infrastructure. We do not detect any significant electromagnetic emission that is temporally and spatially coincident with any of the GW candidates. We report flux upper limits in the 15-350 keV band as a function of sky position for all the catalog candidates. For GW candidates where the Swift-BAT false alarm rate is less than 10$^{-3}$ Hz, we compute the GW--BAT joint false alarm rate. Finally, the derived Swift-BAT upper limits are used to infer constraints on the putative electromagnetic emission associated with binary black hole mergers., Comment: 50 pages, 10 figures, 4 tables

Measurements can detect errors in a decohered quantum memory allowing active error correction to increase the memory time. Previous understanding of this mechanism has focused on evaluating the performance of error correction algorithms based on measurement results. In this work, we instead intrinsically characterize the information dynamics in a quantum memory under repeated measurements, using coherent information and relative entropy. We consider the dynamics of a $d$-dimensional stabilizer code subject to Pauli errors and noisy stabilizer measurements and develop a $(d+1)$-dimensional statistical mechanics model for the information-theoretic diagnostics. Our model is dual to the model previously obtained for the optimal decoding algorithm, and the potential decoding transition in the quantum memory again manifests as a thermal phase transition in the statistical mechanics model. We explicitly derive the model and study the phase transition in information encoding in three examples: surface codes, repetition codes, and the XZZX code., Comment: 27 pages, 9 figures

Transformers have exhibited promising performance in computer vision tasks including image super-resolution (SR). However, popular transformer-based SR methods often employ window self-attention with quadratic computational complexity to window sizes, resulting in fixed small windows with limited receptive fields. In this paper, we present a general strategy to convert transformer-based SR networks to hierarchical transformers (HiT-SR), boosting SR performance with multi-scale features while maintaining an efficient design. Specifically, we first replace the commonly used fixed small windows with expanding hierarchical windows to aggregate features at different scales and establish long-range dependencies. Considering the intensive computation required for large windows, we further design a spatial-channel correlation method with linear complexity to window sizes, efficiently gathering spatial and channel information from hierarchical windows. Extensive experiments verify the effectiveness and efficiency of our HiT-SR, and our improved versions of SwinIR-Light, SwinIR-NG, and SRFormer-Light yield state-of-the-art SR results with fewer parameters, FLOPs, and faster speeds ($\sim7\times$)., Comment: ECCV 2024

This paper evaluates whether large language models (LLMs) exhibit cognitive fan effects, similar to those discovered by Anderson in humans, after being pre-trained on human textual data. We conduct two sets of in-context recall experiments designed to elicit fan effects. Consistent with human results, we find that LLM recall uncertainty, measured via token probability, is influenced by the fan effect. Our results show that removing uncertainty disrupts the observed effect. The experiments suggest the fan effect is consistent whether the fan value is induced in-context or in the pre-training data. Finally, these findings provide in-silico evidence that fan effects and typicality are expressions of the same phenomena.

A primary objective of exoplanet atmosphere characterisation is to learn about planet formation and evolution, however, this is challenged by degeneracies. To determine whether differences in atmospheric composition can be reliably traced to differences in evolution, we are undertaking a new survey with JWST to compare the compositions of a sample of hot Jupiters that orbit F stars above the Kraft break with different orbital alignments. Under the assumption that aligned planets migrate through the inner disc, while misaligned planets migrate after disc dispersal, the act of migrating through the inner disc should lead to a measurable difference in the C/O between aligned and misaligned planets. We expect the amplitude and sign of this difference to depend on the amount of planetesimal accretion and whether silicates accreted from the inner disc release their oxygen. Here, we identify all known exoplanets that are suitable for testing this hypothesis, describe our JWST survey, and use noise simulations and atmospheric retrievals to estimate our survey's sensitivity. With the selected sample of four aligned and four misaligned hot Jupiters, we will be sensitive to the predicted differences in C/O between aligned and misaligned hot Jupiters for a wide range of model scenarios., Comment: 13 pages, 8 figures, submitted to RASTI

While existing alignment paradigms have been integral in developing large language models (LLMs), LLMs often learn an averaged human preference and struggle to model diverse preferences across cultures, demographics, and communities. We propose Modular Pluralism, a modular framework based on multi-LLM collaboration for pluralistic alignment: it "plugs into" a base LLM a pool of smaller but specialized community LMs, where models collaborate in distinct modes to flexibility support three modes of pluralism: Overton, steerable, and distributional. Modular Pluralism is uniquely compatible with black-box LLMs and offers the modular control of adding new community LMs for previously underrepresented communities. We evaluate Modular Pluralism with six tasks and four datasets featuring questions/instructions with value-laden and perspective-informed responses. Extensive experiments demonstrate that Modular Pluralism advances the three pluralism objectives across six black-box and open-source LLMs. Further analysis reveals that LLMs are generally faithful to the inputs from smaller community LLMs, allowing seamless patching by adding a new community LM to better cover previously underrepresented communities., Comment: EMNLP 2024