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Let $X$ be an integral scheme of finite type over a complete DVR of mixed characteristic. We provide a definition of a test ideal which agrees with the multiplier ideal after inverting $p$, can be computed from a sufficiently large alteration, agrees with previous mixed characteristic BCM test ideals after localizing and completing at any point of residue characteristic $p$ (up to small perturbation), and which satisfies the full suite of expected properties of a multiplier or test ideal. This object is obtained via the $p$-adic Riemann-Hilbert functor., Comment: 99 pages, comments welcome

Synthetic data has made tremendous strides in various commercial settings including finance, healthcare, and virtual reality. We present a broad overview of prototypical applications of synthetic data in the financial sector and in particular provide richer details for a few select ones. These cover a wide variety of data modalities including tabular, time-series, event-series, and unstructured arising from both markets and retail financial applications. Since finance is a highly regulated industry, synthetic data is a potential approach for dealing with issues related to privacy, fairness, and explainability. Various metrics are utilized in evaluating the quality and effectiveness of our approaches in these applications. We conclude with open directions in synthetic data in the context of the financial domain., Comment: 50 pages, journal submission; updated 6 privacy levels

Addressing the uncertainty and variability in the quality of 3D printed metals can further the wide spread use of this technology. Process mapping for new alloys is crucial for determining optimal process parameters that consistently produce acceptable printing quality. Process mapping is typically performed by conventional methods and is used for the design of experiments and ex situ characterization of printed parts. On the other hand, in situ approaches are limited because their observable features are limited and they require complex high-cost setups to obtain temperature measurements to boost accuracy. Our method relaxes these limitations by incorporating the temporal features of molten metal dynamics during laser-metal interactions using video vision transformers and high-speed imaging. Our approach can be used in existing commercial machines and can provide in situ process maps for efficient defect and variability quantification. The generalizability of the approach is demonstrated by performing cross-dataset evaluations on alloys with different compositions and intrinsic thermofluid properties.

We study how experience with asset price bubbles changes the trading strategies of reinforcement learning (RL) traders and ask whether the change in trading strategies helps to prevent future bubbles. We train the RL traders in a multi-agent market simulation platform, ABIDES, and compare the strategies of traders trained with and without bubble experience. We find that RL traders without bubble experience behave like short-term momentum traders, whereas traders with bubble experience behave like value traders. Therefore, RL traders without bubble experience amplify bubbles, whereas RL traders with bubble experience tend to suppress and sometimes prevent them. This finding suggests that learning from experience is a mechanism for a boom and bust cycle where the experience of a collapsing bubble makes future bubbles less likely for a period of time until the memory fades and bubbles become more likely to form again.

A previously unremarkable star near the Canis Major OB1/R1 association underwent an episode of multiple deep brightness minima. Light curves based on archival Gaia, ZTF, NEOWISE data and additional observations from LCO and UKIRT show that the star was not variable prior to 2019 Aug 18 (MJD 58700), and on that date started showing brightness dips of up to 3 magnitudes in the Gaia G and ZTF r bandpasses. After MJD 59500, ~800 days after the onset of these dipping events, the star returned to its previous brightness, and no significant dipping events have been recorded since. Compared to the stable phase, NEOWISE infrared photometry in the W1 and W2 bands indicates a generally redder color, and both decreases and increases in brightness at different times during the dipping episode. The spectrum of Gaia21bcv taken after the end of the dipping episode shows several neutral and ionized metal absorption lines, including Li, indicating a spectral type of ~ K5. Variable emission from [OI] was observed. The H alpha absorption in Gaia21bcv is too faint and irregular for this spectral type, indicating that the line is partly filled in by variable emission, a signature of weak episodic accretion. Gaia21bcv lies above the zero-age main sequence, but is much fainter than typical R CrB stars. We interpret the light curve of Gaia21bcv as being similar to the occultation events in Epsilon Aurigae, i.e., occultation by a disk around a companion object orbiting the primary star., Comment: 16 pages, 6 figures, accepted for publication in The Astronomical Journal

We have measured the absolute doubly differential angular sputtering yield for 20 keV Kr+ impacting a polycrystalline Cu slab at an incidence angle of {\theta}i = 45{\deg} relative to the surface normal. Sputtered Cu atoms were captured using collectors mounted on a half dome above the sample, and the sputtering distribution was measured as a function of the sputtering polar, {\theta}s, and azimuthal, phi, angles. Absolute results of the sputtering yield were determined from the mass gain of each collector, the ion dose, and the solid angle subtended, after irradiation to a total fluence of ~ 1 x 10^18 ions/cm^2. Our approach overcomes shortcomings of commonly used methods that only provide relative yields as a function of {\theta}s in the incidence plane (defined by the ion velocity and the surface normal). Our experimental results display an azimuthal variation that increases with increasing {\theta}s and is clearly discrepant with simulations using binary collision theory. We attribute the observed azimuthal anisotropy to ion-induced formation of micro- and nano-scale surface features that suppress the sputtering yield through shadowing and redeposition effects, neither of which are accounted for in the simulations. Our experimental results demonstrate the importance of doubly differential angular sputtering studies to probe ion sputtering processes at a fundamental level and to explore the effect of ion-beam-generated surface roughness., Comment: 29 pages, 9 figures

We identify 182 flares on 158 stars within 100 pc of the Sun in both the near-ultraviolet (NUV: 1750-2750 \r{A}) and far-ultraviolet (FUV: 1350-1750 \r{A}) using high-cadence light curves from the Galaxy Evolution Explorer (GALEX). Ultraviolet (UV) emission from stellar flares plays a crucial role in determining the habitability of exoplanetary systems. However, whether such UV emission promotes or threatens such life depends strongly on the energetics of these flares. Most studies assessing the effect of flares on planetary habitability assume a 9000 K blackbody spectral energy distribution that produces more NUV flux than FUV flux ($R \equiv F_{\rm FUV} / F_{\rm NUV} \approx \frac{1}{6}$). Instead, we observe the opposite with the excess FUV reaching $R \approx \frac{1}{2} - 2$, roughly $3-12$ times the expectation of a 9000 K blackbody. The ratio of FUV to NUV time-integrated flare energies is 3.0 times higher on average than would be predicted by a constant 9000 K blackbody during the flare. Finally, we find that the FUV/NUV ratio at peak tentatively correlates ($\sim 2 \sigma$ significance) both with total UV flare energy and with the G - RP color of the host star. On average, we observe higher FUV/NUV ratios at peak in $E_{\text{UV}}>10^{32}$ erg flares and in flares on fully convective stars., Comment: Submitted to MNRAS, comments welcome

This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks - notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of the Gemini family in cross-modal reasoning and language understanding will enable a wide variety of use cases. We discuss our approach toward post-training and deploying Gemini models responsibly to users through services including Gemini, Gemini Advanced, Google AI Studio, and Cloud Vertex AI.

We survey applications of pretrained foundation models in robotics. Traditional deep learning models in robotics are trained on small datasets tailored for specific tasks, which limits their adaptability across diverse applications. In contrast, foundation models pretrained on internet-scale data appear to have superior generalization capabilities, and in some instances display an emergent ability to find zero-shot solutions to problems that are not present in the training data. Foundation models may hold the potential to enhance various components of the robot autonomy stack, from perception to decision-making and control. For example, large language models can generate code or provide common sense reasoning, while vision-language models enable open-vocabulary visual recognition. However, significant open research challenges remain, particularly around the scarcity of robot-relevant training data, safety guarantees and uncertainty quantification, and real-time execution. In this survey, we study recent papers that have used or built foundation models to solve robotics problems. We explore how foundation models contribute to improving robot capabilities in the domains of perception, decision-making, and control. We discuss the challenges hindering the adoption of foundation models in robot autonomy and provide opportunities and potential pathways for future advancements. The GitHub project corresponding to this paper (Preliminary release. We are committed to further enhancing and updating this work to ensure its quality and relevance) can be found here: https://github.com/robotics-survey/Awesome-Robotics-Foundation-Models

We describe a testbed to characterize the optical response of compact superconducting on-chip spectrometers in development for the Experiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM) mission. EXCLAIM is a balloonborne far-infrared experiment to probe the CO and CII emission lines in galaxies from redshift 3.5 to the present. The spectrometer, called u-Spec, comprises a diffraction grating on a silicon chip coupled to kinetic inductance detectors (KIDs) read out via a single microwave feedline. We use a prototype spectrometer for EXCLAIM to demonstrate our ability to characterize the spectrometers spectral response using a photomixer source. We utilize an on-chip reference detector to normalize relative to spectral structure from the off-chip optics and a silicon etalon to calibrate the absolute frequency.

The detections of Lyman-$\alpha$ ($\rm Ly\alpha$) emission in galaxies with redshifts above 5 are of utmost importance for constraining the cosmic reionization timeline, yet such detections are usually based on slit spectroscopy. Here we investigate the significant bias induced by slit placement on the estimate of $\rm Ly\alpha$ escape fraction ( $f_{\rm esc}^{\mathrm{Ly\alpha}}$), by presenting a galaxy (dubbed A2744-z6Lya) at $z=5.66$ where its deep JWST NIRSpec prism spectroscopy completely misses the strong $\rm Ly\alpha$ emission detected in the MUSE data. A2744-z6Lya exhibits a pronounced UV continuum with an extremely steep spectral slope of $\beta=-2.574_{-0.008}^{+0.008}$, and it has a stellar mass of $\mathrm{\sim10^{8.82}~M_\odot}$, a star-formation rate of $\mathrm{\sim8.35~M_\odot yr^{-1}}$ and gas-phase metallicity of $\mathrm{12+log\,(O/H)\sim7.88}$. The observed flux and rest-frame equivalent width of its Ly$\alpha$ from MUSE spectroscopy are $1.2\times \rm 10^{-16} erg~s^{-1}cm^{-2}$ and 75\r{A}, equivalent to $f_{\rm esc}^{\mathrm{Ly\alpha}}=78\pm4 \%$. However, its Ly$\alpha$ non-detection from JWST NIRSpec gives a 5-$\sigma$ upper limit of $<13 \%$, in stark contrast to that derived from MUSE. To explore the reasons for this bias, we perform spatially resolved stellar population analysis of A2744-z6Lya using the JWST NIRCam imaging data to construct 2-dimensional maps of SFR, dust extinction and neutral hydrogen column density. We find that the absence of Ly$\alpha$ in the slit regions probably stems from both the resonance scattering effect of neutral hydrogen and dust extinction. Through analyzing an extreme case in detail, this work highlights the important caveat of inferring $f_{\rm esc}^{\mathrm{Ly\alpha}}$ from slit spectroscopy, particularly when using the JWST multiplexed NIRSpec microshutter assembly., Comment: 10 pages, 4 figures, 1 table

We present a measurement of the mass-metallicity relation (MZR) at cosmic noon, using the JWST near-infrared wide-field slitless spectroscopy obtained by the GLASS-JWST Early Release Science program. By combining the power of JWST and the lensing magnification by the foreground cluster A2744, we extend the measurements of the MZR to the dwarf mass regime at high redshifts. A sample of 50 galaxies with several emission lines is identified across two wide redshift ranges of $z=1.8-2.3$ and $2.6-3.4$ in the stellar mass range of $\log{(M_*/M_\odot)}\in [6.9, 10.0]$. The observed slope of MZR is $0.223 \pm 0.017$ and $0.294 \pm 0.010$ at these two redshift ranges, respectively, consistent with the slopes measured in field galaxies with higher masses. In addition, we assess the impact of the morphological broadening on emission line measurement by comparing two methods of using 2D forward modeling and line profile fitting to 1D extracted spectra. We show that ignoring the morphological broadening effect when deriving line fluxes from grism spectra results in a systematic reduction of flux by $\sim30\%$ on average. This discrepancy appears to affect all the lines and thus does not lead to significant changes in flux ratio and metallicity measurements. This assessment of the morphological broadening effect using JWST data presents, for the first time, an important guideline for future work deriving galaxy line fluxes from wide-field slitless spectroscopy, such as Euclid, Roman, and the Chinese Space Station Telescope., Comment: 19 pages, 6 figures, accepted for publication in ApJL

We treat the problem of finding transitive subgroups G of S_n containing normal subgroups N_1 and N_2, with N_1 transitive and N_2 not transitive, such that G/N_1 is isomorphic G/N_2. We show that such G exist whenever n has a prime factor that also divides the Euler-phi function of n. We show that no such G exist when n = pq for p < q with p not dividing q-1.

We present a catalog of 689 galaxy cluster candidates detected at significance $\xi>4$ via their thermal Sunyaev-Zel'dovich (SZ) effect signature in 95 and 150 GHz data from the 500-square-degree SPTpol survey. We use optical and infrared data from the Dark Energy Camera and the Wide-field Infrared Survey Explorer (WISE) and \spitzer \ satellites, to confirm 544 of these candidates as clusters with $\sim94\%$ purity. The sample has an approximately redshift-independent mass threshold at redshift $z>0.25$ and spans $1.5 \times 10^{14} < M_{500c} < 9.1 \times 10^{14}$ $M_\odot/h_{70}$ \ and $0.031$. We use external radio data from the Sydney University Molonglo Sky Survey (SUMSS) to estimate contamination to the SZ signal from synchrotron sources. The contamination reduces the recovered $\xi$ by a median value of 0.032, or $\sim0.8\%$ of the $\xi=4$ threshold value, and $\sim7\%$ of candidates have a predicted contamination greater than $\Delta \xi = 1$. With the exception of a small number of systems $(<1\%)$, an analysis of clusters detected in single-frequency 95 and 150 GHz data shows no significant contamination of the SZ signal by emission from dusty or synchrotron sources. This cluster sample will be a key component in upcoming astrophysical and cosmological analyses of clusters. The SPTpol millimeter-wave maps and associated data products used to produce this sample are available at https://pole.uchicago.edu/public/data/sptpol_500d_clusters/index.html, and the NASA LAMBDA website. An interactive sky server with the SPTpol maps and Dark Energy Survey data release 2 images is also available at NCSA https://skyviewer.ncsa.illinois.edu., Comment: Matches version accepted by OJA. 19 pages + references, 14 figures, cluster candidate table provided in Appendix. Data products available at https://pole.uchicago.edu/public/data/sptpol_500d_clusters/index.html and an interactive sky server at https://skyviewer.ncsa.illinois.edu

We seek to accelerate research in developing rich, multimodal scene models trained from egocentric data, based on differentiable volumetric ray-tracing inspired by Neural Radiance Fields (NeRFs). The construction of a NeRF-like model from an egocentric image sequence plays a pivotal role in understanding human behavior and holds diverse applications within the realms of VR/AR. Such egocentric NeRF-like models may be used as realistic simulations, contributing significantly to the advancement of intelligent agents capable of executing tasks in the real-world. The future of egocentric view synthesis may lead to novel environment representations going beyond today's NeRFs by augmenting visual data with multimodal sensors such as IMU for egomotion tracking, audio sensors to capture surface texture and human language context, and eye-gaze trackers to infer human attention patterns in the scene. To support and facilitate the development and evaluation of egocentric multimodal scene modeling, we present a comprehensive multimodal egocentric video dataset. This dataset offers a comprehensive collection of sensory data, featuring RGB images, eye-tracking camera footage, audio recordings from a microphone, atmospheric pressure readings from a barometer, positional coordinates from GPS, connectivity details from Wi-Fi and Bluetooth, and information from dual-frequency IMU datasets (1kHz and 800Hz) paired with a magnetometer. The dataset was collected with the Meta Aria Glasses wearable device platform. The diverse data modalities and the real-world context captured within this dataset serve as a robust foundation for furthering our understanding of human behavior and enabling more immersive and intelligent experiences in the realms of VR, AR, and robotics.

Data distillation and coresets have emerged as popular approaches to generate a smaller representative set of samples for downstream learning tasks to handle large-scale datasets. At the same time, machine learning is being increasingly applied to decision-making processes at a societal level, making it imperative for modelers to address inherent biases towards subgroups present in the data. While current approaches focus on creating fair synthetic representative samples by optimizing local properties relative to the original samples, their impact on downstream learning processes has yet to be explored. In this work, we present fair Wasserstein coresets (FWC), a novel coreset approach which generates fair synthetic representative samples along with sample-level weights to be used in downstream learning tasks. FWC uses an efficient majority minimization algorithm to minimize the Wasserstein distance between the original dataset and the weighted synthetic samples while enforcing demographic parity. We show that an unconstrained version of FWC is equivalent to Lloyd's algorithm for k-medians and k-means clustering. Experiments conducted on both synthetic and real datasets show that FWC: (i) achieves a competitive fairness-utility tradeoff in downstream models compared to existing approaches, (ii) improves downstream fairness when added to the existing training data and (iii) can be used to reduce biases in predictions from large language models (GPT-3.5 and GPT-4)., Comment: Accepted at NeurIPS 2024, 30 pages, 7 figures, 8 tables

CONCERTO (CarbON CII line in post-rEionization and ReionizaTiOn) is a low-resolution Fourier transform spectrometer dedicated to the study of star-forming galaxies and clusters of galaxies in the transparent millimeter windows from the ground. It is characterized by a wide instantaneous 18.6 arcmin field of view, operates at 130-310 GHz, and was installed on the 12-meter Atacama Pathfinder Experiment (APEX) telescope at 5100 m above sea level. CONCERTO's double focal planes host two arrays of 2152 kinetic inductance detectors and represent a pioneering instrument to meet a state-of-the-art scientific challenge. This paper introduces the CONCERTO instrument and explains its status, shows the first CONCERTO spectral maps of Orion, and describes the perspectives of the project., Comment: 6 pages, 2 figures, to appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Sciences

The Ornstein-Uhlenbeck (OU) process, a mean-reverting stochastic process, has been widely applied as a time series model in various domains. This paper describes the design and implementation of a model-based synthetic time series model based on a multivariate OU process and the Arbitrage Pricing Theory (APT) for generating synthetic pricing data for a complex market of interacting stocks. The objective is to create a group of synthetic stock price time series that reflects the correlation between individual stocks and clusters of stocks in how a real market behaves. We demonstrate the method using the Standard and Poor's (S&P) 500 universe of stocks as an example.

Mobile money services in Sub-Saharan Africa (SSA) have increased access to financial services. To ensure proper identification of users, countries have put in place Know-Your-Customer (KYC) measures such as SIM registration using an official identification. However, half of the 850 million people without IDs globally live in SSA, and the use of SIM cards registered in another person's name (third-party SIM) is prevalent. In this study, we explore challenges that contribute to and arise from the use of third-party SIM cards. We interviewed 36 participants in Kenya and Tanzania. Our results highlight great strides in ID accessibility, but also highlight numerous institutional and social factors that contribute to the use of third-party SIM cards. While privacy concerns contribute to the use of third-party SIM cards, third-party SIM card users are exposed to significant security and privacy risks, including scams, financial loss, and wrongful arrest.

Recent years have seen a surge of machine learning approaches aimed at reducing disparities in model outputs across different subgroups. In many settings, training data may be used in multiple downstream applications by different users, which means it may be most effective to intervene on the training data itself. In this work, we present FairWASP, a novel pre-processing approach designed to reduce disparities in classification datasets without modifying the original data. FairWASP returns sample-level weights such that the reweighted dataset minimizes the Wasserstein distance to the original dataset while satisfying (an empirical version of) demographic parity, a popular fairness criterion. We show theoretically that integer weights are optimal, which means our method can be equivalently understood as duplicating or eliminating samples. FairWASP can therefore be used to construct datasets which can be fed into any classification method, not just methods which accept sample weights. Our work is based on reformulating the pre-processing task as a large-scale mixed-integer program (MIP), for which we propose a highly efficient algorithm based on the cutting plane method. Experiments demonstrate that our proposed optimization algorithm significantly outperforms state-of-the-art commercial solvers in solving both the MIP and its linear program relaxation. Further experiments highlight the competitive performance of FairWASP in reducing disparities while preserving accuracy in downstream classification settings., Comment: AAAI 2024, 15 pages, 4 figures, 1 table

Neural networks often learn task-specific latent representations that fail to generalize to novel settings or tasks. Conversely, humans learn discrete representations (i.e., concepts or words) at a variety of abstraction levels (e.g., "bird" vs. "sparrow") and deploy the appropriate abstraction based on task. Inspired by this, we train neural models to generate a spectrum of discrete representations, and control the complexity of the representations (roughly, how many bits are allocated for encoding inputs) by tuning the entropy of the distribution over representations. In finetuning experiments, using only a small number of labeled examples for a new task, we show that (1) tuning the representation to a task-appropriate complexity level supports the highest finetuning performance, and (2) in a human-participant study, users were able to identify the appropriate complexity level for a downstream task using visualizations of discrete representations. Our results indicate a promising direction for rapid model finetuning by leveraging human insight., Comment: NeurIPS 2023

To understand the evolution of dust properties in molecular clouds in the course of the star formation process, we constrain the changes in the dust emissivity index from star-forming filaments to prestellar and protostellar cores to T Tauri stars. Using the NIKA2 continuum camera on the IRAM 30~m telescope, we observed the Taurus B211/B213 filament at 1.2\,mm and 2\,mm with unprecedented sensitivity and used the resulting maps to derive the dust emissivity index $\beta$. Our sample of 105 objects detected in the $\beta$ map of the B211/B213 filament indicates that, overall, $\beta$ decreases from filament and prestellar cores ($\beta \sim 2\pm0.5$) to protostellar cores ($\beta \sim 1.2 \pm 0.2$) to T-Tauri protoplanetary disk ($\beta < 1$). The averaged dust emissivity index $\beta$ across the B211/B213 filament exhibits a flat ($\beta \sim 2\pm0.3$) profile. This may imply that dust grain sizes are rather homogeneous in the filament, start to grow significantly in size only after the onset of the gravitational contraction/collapse of prestellar cores to protostars, reaching big sizes in T Tauri protoplanetary disks. This evolution from the parent filament to T-Tauri disks happens on a timescale of about 1-2~Myr., Comment: to appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Sciences

Forced alignment systems automatically determine boundaries between segments in speech data, given an orthographic transcription. These tools are commonplace in phonetics to facilitate the use of speech data that would be infeasible to manually transcribe and segment. In the present paper, we describe a new neural network-based forced alignment system, the Mason-Alberta Phonetic Segmenter (MAPS). The MAPS aligner serves as a testbed for two possible improvements we pursue for forced alignment systems. The first is treating the acoustic model in a forced aligner as a tagging task, rather than a classification task, motivated by the common understanding that segments in speech are not truly discrete and commonly overlap. The second is an interpolation technique to allow boundaries more precise than the common 10 ms limit in modern forced alignment systems. We compare configurations of our system to a state-of-the-art system, the Montreal Forced Aligner. The tagging approach did not generally yield improved results over the Montreal Forced Aligner. However, a system with the interpolation technique had a 27.92% increase relative to the Montreal Forced Aligner in the amount of boundaries within 10 ms of the target on the test set. We also reflect on the task and training process for acoustic modeling in forced alignment, highlighting how the output targets for these models do not match phoneticians' conception of similarity between phones and that reconciliation of this tension may require rethinking the task and output targets or how speech itself should be segmented., Comment: submitted for publication

We prove that a polynomial fraction of the set of $k$-component forests in the $m \times n$ grid graph have equal numbers of vertices in each component, for any constant $k$. This resolves a conjecture of Charikar, Liu, Liu, and Vuong, and establishes the first provably polynomial-time algorithm for (exactly or approximately) sampling balanced grid graph partitions according to the spanning tree distribution, which weights each $k$-partition according to the product, across its $k$ pieces, of the number of spanning trees of each piece. Our result follows from a careful analysis of the probability a uniformly random spanning tree of the grid can be cut into balanced pieces. Beyond grids, we show that for a broad family of lattice-like graphs, we achieve balance up to any multiplicative $(1 \pm \varepsilon)$ constant with constant probability, and up to an additive constant with polynomial probability. More generally, we show that, with constant probability, components derived from uniform spanning trees can approximate any given partition of a planar region specified by Jordan curves. These results imply polynomial time algorithms for sampling approximately balanced tree-weighted partitions for lattice-like graphs. Our results have applications to understanding political districtings, where there is an underlying graph of indivisible geographic units that must be partitioned into $k$ population-balanced connected subgraphs. In this setting, tree-weighted partitions have interesting geometric properties, and this has stimulated significant effort to develop methods to sample them.

Existing text scaling methods often require a large corpus, struggle with short texts, or require labeled data. We develop a text scaling method that leverages the pattern recognition capabilities of generative large language models (LLMs). Specifically, we propose concept-guided chain-of-thought (CGCoT), which uses prompts designed to summarize ideas and identify target parties in texts to generate concept-specific breakdowns, in many ways similar to guidance for human coder content analysis. CGCoT effectively shifts pairwise text comparisons from a reasoning problem to a pattern recognition problem. We then pairwise compare concept-specific breakdowns using an LLM. We use the results of these pairwise comparisons to estimate a scale using the Bradley-Terry model. We use this approach to scale affective speech on Twitter. Our measures correlate more strongly with human judgments than alternative approaches like Wordfish. Besides a small set of pilot data to develop the CGCoT prompts, our measures require no additional labeled data and produce binary predictions comparable to a RoBERTa-Large model fine-tuned on thousands of human-labeled tweets. We demonstrate how combining substantive knowledge with LLMs can create state-of-the-art measures of abstract concepts., Comment: 26 pages, 2 figures

Deep learning has significantly advanced the potential for automated contouring in radiotherapy planning. In this manuscript, guided by contemporary literature, we underscore three key insights: (1) High-quality training data is essential for auto-contouring algorithms; (2) Auto-contouring models demonstrate commendable performance even with limited medical image data; (3) The quantitative performance of auto-contouring is reaching a plateau. Given these insights, we emphasize the need for the radiotherapy research community to embrace data-centric approaches to further foster clinical adoption of auto-contouring technologies., Comment: 13 pages, 4 figures

Time-Division Multiplexing is the readout architecture of choice for many ground and space experiments, as it is a very mature technology with proven outstanding low-frequency noise stability, which represents a central challenge in multiplexing. Once fully populated, each of the two BICEP Array high frequency receivers, observing at 150GHz and 220/270GHz, will have 7776 TES detectors tiled on the focal plane. The constraints set by these two receivers required a redesign of the warm readout electronics. The new version of the standard Multi Channel Electronics, developed and built at the University of British Columbia, is presented here for the first time. BICEP Array operates Time Division Multiplexing readout technology to the limits of its capabilities in terms of multiplexing rate, noise and crosstalk, and applies them in rigorously demanding scientific application requiring extreme noise performance and systematic error control. Future experiments like CMB-S4 plan to use TES bolometers with Time Division/SQUID-based readout for an even larger number of detectors., Comment: 10 pages, 7 figures, Submitted to Journal of Low Temperature Physics

Inventory matching is a standard mechanism/auction for trading financial stocks by which buyers and sellers can be paired. In the financial world, banks often undertake the task of finding such matches between their clients. The related stocks can be traded without adversely impacting the market price for either client. If matches between clients are found, the bank can offer the trade at advantageous rates. If no match is found, the parties have to buy or sell the stock in the public market, which introduces additional costs. A problem with the process as it is presently conducted is that the involved parties must share their order to buy or sell a particular stock, along with the intended quantity (number of shares), to the bank. Clients worry that if this information were to leak somehow, then other market participants would become aware of their intentions and thus cause the price to move adversely against them before their transaction finalizes. We provide a solution, Prime Match, that enables clients to match their orders efficiently with reduced market impact while maintaining privacy. In the case where there are no matches, no information is revealed. Our main cryptographic innovation is a two-round secure linear comparison protocol for computing the minimum between two quantities without preprocessing and with malicious security, which can be of independent interest. We report benchmarks of our Prime Match system, which runs in production and is adopted by J.P. Morgan. The system is designed utilizing a star topology network, which provides clients with a centralized node (the bank) as an alternative to the idealized assumption of point-to-point connections, which would be impractical and undesired for the clients to implement in reality. Prime Match is the first secure multiparty computation solution running live in the traditional financial world., Comment: 27 pages, 7 figures, USENIX Security 2023

We present a JWST mid-infrared spectrum of the under-luminous Type Ia Supernova (SN Ia) 2022xkq, obtained with the medium-resolution spectrometer on the Mid-Infrared Instrument (MIRI) $\sim130$ days post-explosion. We identify the first MIR lines beyond 14 $\mu$m in SN Ia observations. We find features unique to under-luminous SNe Ia, including: isolated emission of stable Ni, strong blends of [Ti II], and large ratios of singly ionized to doubly ionized species in both [Ar] and [Co]. Comparisons to normal-luminosity SNe Ia spectra at similar phases show a tentative trend between the width of the [Co III] 11.888 $\mu$m feature and the SN light curve shape. Using non-LTE-multi-dimensional radiation hydro simulations and the observed electron capture elements we constrain the mass of the exploding white dwarf. The best-fitting model shows that SN 2022xkq is consistent with an off-center delayed-detonation explosion of a near-Chandrasekhar mass WD (M$_{\rm ej}$ $\approx 1.37$ M$_{\odot}$) of high-central density ($\rho_c \geq 2.0\times10^{9}$ g cm$^{-3}$) seen equator on, which produced M($^{56}$Ni) $= 0.324$ M$_{\odot}$ and M($^{58}$Ni) $\geq 0.06$ M$_{\odot}$. The observed line widths are consistent with the overall abundance distribution; and the narrow stable Ni lines indicate little to no mixing in the central regions, favoring central ignition of sub-sonic carbon burning followed by an off-center DDT beginning at a single point. Additional observations may further constrain the physics revealing the presence of additional species including Cr and Mn. Our work demonstrates the power of using the full coverage of MIRI in combination with detailed modeling to elucidate the physics of SNe Ia at a level not previously possible., Comment: 31 pages, 18 figures, accepted to ApJ; updated to accepted version

Simulation is an essential tool to develop and benchmark autonomous vehicle planning software in a safe and cost-effective manner. However, realistic simulation requires accurate modeling of nuanced and complex multi-agent interactive behaviors. To address these challenges, we introduce Waymax, a new data-driven simulator for autonomous driving in multi-agent scenes, designed for large-scale simulation and testing. Waymax uses publicly-released, real-world driving data (e.g., the Waymo Open Motion Dataset) to initialize or play back a diverse set of multi-agent simulated scenarios. It runs entirely on hardware accelerators such as TPUs/GPUs and supports in-graph simulation for training, making it suitable for modern large-scale, distributed machine learning workflows. To support online training and evaluation, Waymax includes several learned and hard-coded behavior models that allow for realistic interaction within simulation. To supplement Waymax, we benchmark a suite of popular imitation and reinforcement learning algorithms with ablation studies on different design decisions, where we highlight the effectiveness of routes as guidance for planning agents and the ability of RL to overfit against simulated agents.

Recent advances in artificial intelligence (AI) have underscored the need for explainable AI (XAI) to support human understanding of AI systems. Consideration of human factors that impact explanation efficacy, such as mental workload and human understanding, is central to effective XAI design. Existing work in XAI has demonstrated a tradeoff between understanding and workload induced by different types of explanations. Explaining complex concepts through abstractions (hand-crafted groupings of related problem features) has been shown to effectively address and balance this workload-understanding tradeoff. In this work, we characterize the workload-understanding balance via the Information Bottleneck method: an information-theoretic approach which automatically generates abstractions that maximize informativeness and minimize complexity. In particular, we establish empirical connections between workload and complexity and between understanding and informativeness through human-subject experiments. This empirical link between human factors and information-theoretic concepts provides an important mathematical characterization of the workload-understanding tradeoff which enables user-tailored XAI design.

High-resolution mapping of the hot gas in galaxy clusters is a key tool for cluster-based cosmological analyses. Taking advantage of the NIKA2 millimeter camera operated at the IRAM 30-m telescope, the NIKA2 SZ Large Program seeks to get a high-resolution follow-up of 38 galaxy clusters covering a wide mass range at intermediate to high redshift. The measured SZ fluxes will be essential to calibrate the SZ scaling relation and the galaxy clusters mean pressure profile, needed for the cosmological exploitation of SZ surveys. We present in this study a method to infer a mean pressure profile from cluster observations. We have designed a pipeline encompassing the map-making and the thermodynamical properties estimates from maps. We then combine all the individual fits, propagating the uncertainties on integrated quantities, such as $R_{500}$ or $P_{500}$, and the intrinsic scatter coming from the deviation to the standard self-similar model. We validate the proposed method on realistic LPSZ-like cluster simulations., Comment: to appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Sciences

We present the first preliminary results of the project \textit{ICED}, focusing on the face-on galaxy NGC4254. We use the millimetre maps observed with NIKA2 at IRAM-30m, as part of the IMEGIN Guaranteed Time Large Program, and of a wide collection of ancillary data (multi-wavelength photometry and gas phase spectral lines) that are publicly available. We derive the global and local properties of interstellar dust grains through infrared-to-radio spectral energy distribution fitting, using the hierarchical Bayesian code HerBIE, which includes the grain properties of the state-of-the-art dust model, THEMIS. Our method allows us to get the following dust parameters: dust mass, average interstellar radiation field, and fraction of small grains. Also, it is effective in retrieving the intrinsic correlations between dust parameters and interstellar medium properties. We find an evident anti-correlation between the interstellar radiation field and the fraction of small grains in the centre of NGC4254, meaning that, at strong radiation field intensities, very small amorphous carbon grains are efficiently destroyed by the ultra-violet photons coming from newly formed stars, through photo-desorption and sublimation. We observe a flattening of the anti-correlation at larger radial distances, which may be driven by the steep metallicity gradient measured in NGC4254., Comment: to appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Sciences

Three galaxy clusters selected from the XXL X-ray survey at high redshift and low mass ($z\sim1$ and $M_{500} \sim 1-2 \times 10^{14}$ M$_{\odot}$) were observed with NIKA2 to image their Sunyaev-Zel'dovich effect (SZ) signal. They all present an SZ morphology, together with the comparison with X-ray and optical data, that indicates dynamical activity related to merging events. Despite their disturbed intracluster medium, their high redshifts, and their low masses, the three clusters follow remarkably well the pressure profile and the SZ flux-mass relation expected from standard evolution. This suggests that the physics that drives cluster formation is already in place at $z \sim 1$ down to $M_{500} \sim 10^{14}$ M$_{\odot}$., Comment: to appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Sciences

Accelerated muon beams have been considered for next-generation studies of high-energy lepton-antilepton collisions and neutrino oscillations. However, high-brightness muon beams have not yet been produced. The main challenge for muon acceleration and storage stems from the large phase-space volume occupied by the beam, derived from the muon production mechanism through the decay of pions from proton collisions. Ionization cooling is the technique proposed to decrease the muon beam phase-space volume. Here we demonstrate a clear signal of ionization cooling through the observation of transverse emittance reduction in beams that traverse lithium hydride or liquid hydrogen absorbers in the Muon Ionization Cooling Experiment (MICE). The measurement is well reproduced by the simulation of the experiment and the theoretical model. The results shown here represent a substantial advance towards the realization of muon-based facilities that could operate at the energy and intensity frontiers., Comment: 23 pages and 5 figures

Successfully achieving bipedal locomotion remains challenging due to real-world factors such as model uncertainty, random disturbances, and imperfect state estimation. In this work, we propose a novel metric for locomotive robustness -- the estimated size of the hybrid forward invariant set associated with the step-to-step dynamics. Here, the forward invariant set can be loosely interpreted as the region of attraction for the discrete-time dynamics. We illustrate the use of this metric towards synthesizing nominal walking gaits using a simulation-in-the-loop learning approach. Further, we leverage discrete-time barrier functions and a sampling-based approach to approximate sets that are maximally forward invariant. Lastly, we experimentally demonstrate that this approach results in successful locomotion for both flat-foot walking and multi-contact walking on the Atalante lower-body exoskeleton.

The thermodynamical properties of the intracluster medium (ICM) are driven by scale-free gravitational collapse, but they also reflect the rich astrophysical processes at play in galaxy clusters. At low masses ($\sim 10^{14}$ M$_{\odot}$) and high redshift ($z \gtrsim 1$), these properties remain poorly constrained observationally, due to the difficulty in obtaining resolved and sensitive data. This paper aims at investigating the inner structure of the ICM as seen through the Sunyaev-Zel'dovich (SZ) effect in this regime of mass and redshift. Focus is set on the thermal pressure profile and the scaling relation between SZ flux and mass, namely the $Y_{\rm SZ} - M$ scaling relation. The three galaxy clusters XLSSC~072 ($z=1.002$), XLSSC~100 ($z=0.915$), and XLSSC~102 ($z=0.969$), with $M_{500} \sim 2 \times 10^{14}$ M$_{\odot}$, were selected from the XXL X-ray survey and observed with the NIKA2 millimeter camera to image their SZ signal. XMM-Newton X-ray data were used in complement to the NIKA2 data to derive masses based on the $Y_X - M$ relation and the hydrostatic equilibrium. The SZ images of the three clusters, along with the X-ray and optical data, indicate dynamical activity related to merging events. The pressure profile is consistent with that expected for morphologically disturbed systems, with a relatively flat core and a shallow outer slope. Despite significant disturbances in the ICM, the three high-redshift low-mass clusters follow remarkably well the $Y_{\rm SZ}-M$ relation expected from standard evolution. These results indicate that the dominant physics that drives cluster evolution is already in place by $z \sim 1$, at least for systems with masses above $M_{500} \sim 10^{14}$ M$_{\odot}$., Comment: 24 pages, published in A&A. Note that the title number had to be changed. This version matches the one from A&A

The NIKA2 camera operating at the IRAM 30 m telescope excels in high-angular resolution mapping of the thermal Sunyaev-Zeldovich effect towards galaxy clusters at intermediate and high-redshift. As part of the NIKA2 guaranteed time, the SZ Large Program (LPSZ) aims at tSZ-mapping a representative sample of SZ-selected galaxy clusters in the catalogues of the Planck satellite and of the Atacama Cosmology Telescope, and also observed in X-ray with XMM Newton or Chandra. Having completed observations in January 2023, we present tSZ maps of 38 clusters spanning the targeted mass ($3 < M_{500}/10^{14} M_{\odot} < 10$) and redshift ($0.5 < z < 0.9$) ranges. The first in depth studies of individual clusters highlight the potential of combining tSZ and X-ray observations at similar angular resolution for accurate mass measurements. These were milestones for the development of a standard data analysis pipeline to go from NIKA2 raw data to the thermodynamic properties of galaxy clusters for the upcoming LPSZ data release. Final products will include unprecedented measurements of the mean pressure profile and mass observable scaling relation using a distinctive SZ-selected sample, which will be key for ultimately improving the accuracy of cluster based cosmology., Comment: to appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Sciences

In the framework of the IMEGIN Large Program, we used the NIKA2 camera on the IRAM 30-m telescope to observe the edge-on galaxy NGC 891 at 1.15 mm and 2 mm and at a FWHM of 11.1" and 17.6", respectively. Multiwavelength data enriched with the new NIKA2 observations fitted by the HerBIE SED code (coupled with the THEMIS dust model) were used to constrain the physical properties of the ISM. Emission originating from the diffuse dust disk is detected at all wavelengths from mid-IR to mm, while mid-IR observations reveal warm dust emission from compact HII regions. Indications of mm excess emission have also been found in the outer parts of the galactic disk. Furthermore, our SED fitting analysis constrained the mass fraction of the small (< 15 Angstrom) dust grains. We found that small grains constitute 9.5% of the total dust mass in the galactic plane, but this fraction increases up to ~ 20% at large distances (|z| > 3 kpc) from the galactic plane., Comment: To appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Sciences

This study presents the first millimeter continuum mapping observations of two nearby galaxies, the starburst spiral galaxy NGC2146 and the dwarf galaxy NGC2976, at 1.15 mm and 2 mm using the NIKA2 camera on the IRAM 30m telescope, as part of the Guaranteed Time Large Project IMEGIN. These observations provide robust resolved information about the physical properties of dust in nearby galaxies by constraining their FIR-radio SED in the millimeter domain. After subtracting the contribution from the CO line emission, the SEDs are modeled spatially using a Bayesian approach. Maps of dust mass surface density, temperature, emissivity index, and thermal radio component of the galaxies are presented, allowing for a study of the relations between the dust properties and star formation activity (using observations at 24$\mu$m as a tracer). We report that dust temperature is correlated with star formation rate in both galaxies. The effect of star formation activity on dust temperature is stronger in NGC2976, an indication of the thinner interstellar medium of dwarf galaxies. Moreover, an anti-correlation trend is reported between the dust emissivity index and temperature in both galaxies., Comment: To appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Sciences

In cluster cosmology, cluster masses are the main parameter of interest. They are needed to constrain cosmological parameters through the cluster number count. As the mass is not an observable, a scaling relation is needed to link cluster masses to the integrated Compton parameters Y, i.e. the Sunyaev-Zeldovich observable (SZ). Planck cosmological results obtained with cluster number counts are based on a scaling relation measured with clusters at low redshift ($z$<0.5) observed in SZ and X-ray. In the SZ Large Program (LPSZ) of the NIKA2 collaboration, the scaling relation will be obtained with a sample of 38 clusters at intermediate to high redshift ($0.5