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We demonstrate that a deep learning emulator for chaotic systems can forecast phenomena absent from training data. Using the Kuramoto-Sivashinsky and beta-plane turbulence models, we evaluate the emulator through scenarios probing the fundamental phenomena of both systems: forecasting spontaneous relaminarisation, capturing initialisation of arbitrary chaotic states, zero-shot prediction of dynamics with parameter values outside of the training range, and characterisation of dynamical statistics from artificially restricted training datasets. Our results show that deep learning emulators can uncover emergent behaviours and rare events in complex systems by learning underlying mathematical rules, rather than merely mimicking observed patterns.

We present the luminosity function and volumetric rate of a sample of Type IIP supernovae (SNe) from the Zwicky Transient Facility Census of the Local Universe survey (CLU). This is the largest sample of Type IIP SNe from a systematic volume-limited survey to-date. The final sample includes 330 Type IIP SNe and 36 low-luminosity Type II (LLIIP) SNe with $M_{\textrm{r,peak}}>-16$ mag, which triples the literature sample of LLIIP SNe. The fraction of LLIIP SNe is $19^{+3}_{-4}\%$ of the total CLU Type IIP SNe population ($8^{+1}_{-2}\%$ of all core-collapse SNe). This implies that while LLIIP SNe likely represent the fate of core-collapse SNe of $8-12$ \Msun\ progenitors, they alone cannot account for the fate of all massive stars in this mass range. To derive an absolute rate, we estimate the ZTF pipeline efficiency as a function of the apparent magnitude and the local surface brightness. We derive a volumetric rate of $(3.9_{-0.4}^{+0.4}) \times 10^{4}\ \textrm{Gpc}^{-3}\ \textrm{yr}^{-1}$ for Type IIP SNe and $(7.3_{-0.6}^{+0.6}) \times 10^{3}\ \textrm{Gpc}^{-3}\ \textrm{yr}^{-1}$ for LLIIP SNe. Now that the rate of LLIIP SNe is robustly derived, the unresolved discrepancy between core-collapse SN rates and star-formation rates cannot be explained by LLIIP SNe alone., Comment: Submitted to PASP

Social online games like Minecraft and Roblox have become increasingly integral to children's daily lives. Our study explores how children aged 8 to 13 create and customize avatars in these virtual environments. Through semi-structured interviews and gameplay observations with 48 participants, we investigate the motivations behind children's avatar-making. Our findings show that children's avatar creation is motivated by self-representation, experimenting with alter ego identities, fulfilling social needs, and improving in-game performance. In addition, designed monetization strategies play a role in shaping children's avatars. We identify the ''wardrobe effect,'' where children create multiple avatars but typically use only one favorite consistently. We discuss the impact of cultural consumerism and how social games can support children's identity exploration while balancing self-expression and social conformity. This work contributes to understanding how avatar shapes children's identity growth in social online games.

An important step in understanding the formation and evolution of the Nuclear Star Cluster (NSC) is to investigate its chemistry and chemical evolution. Additionally, exploring the relationship of the NSC to the other structures in the Galactic Center and the Milky Way disks is of great interest. Extreme optical extinction has previously prevented optical studies, but near-IR high-resolution spectroscopy is now possible. Here, we present a detailed chemical abundance analysis of 19 elements - more than four times as many as previously published - for 9 stars in the NSC of the Milky Way, observed with the IGRINS spectrometer on the Gemini South telescope. This study provides new, crucial observational evidence to shed light on the origin of the NSC. We demonstrate that it is possible to probe a variety of nucleosynthetic channels, reflecting different chemical evolution timescales. Our findings reveal that the NSC trends for the elements F, Mg, Al, Si, S, K, Ca, Ti, Cr, Mn, Co, Ni, Cu, and Zn, as well as the s-process elements Ba, Ce, Nd, and Yb, generally follow the inner bulge trends within uncertainties. This suggests a likely shared evolutionary history and our results indicate that the NSC population is consistent with the chemical sequence observed in the inner Galaxy (the inner-disk sequence). However, we identify a significant and unexplained difference in the form of higher Na abundances in the NSC compared to the inner-bulge. This is also observed in few Galactic globular clusters, and may suggest a common enrichment process at work in all these systems., Comment: 10 pages, 4 figures, Accepted for publication in The Astrophysical Journal Letters

Tidal disruption events (TDEs) that are spatially offset from the nucleus of their host galaxies offer a new probe of massive black hole (MBH) wanderers, binaries, triples, and recoiling MBHs. Here we present AT2024tvd, the first off-nuclear TDE identified through optical sky surveys. High-resolution imaging with the Hubble Space Telescope shows that AT2024tvd is $0.914\pm 0.010$ arcsec offset from the apparent center of its host galaxy, corresponding to a projected distance of $0.808\pm 0.009$ kpc at $z=0.045$. AT2024tvd exhibits typical properties of nuclear TDEs, including a persistent hot UV/optical component that peaks at $L_{ bb}\sim 6\times 10^{43}\,erg\,s^{-1}$, broad hydrogen lines in its optical spectra, and delayed brightening of luminous ($L_{ X,peak}\sim 3\times 10^{43}\,erg\,s^{-1}$), highly variable soft X-ray emission. The MBH mass of AT2024tvd is $10^{6\pm1}\,M_\odot$, at least 10 times lower than its host galaxy's central black hole mass ($\gtrsim 10^8\,M_\odot$). The MBH in AT2024tvd has two possible origins: a wandering MBH from the lower-mass galaxy in a minor merger during the dynamical friction phase or a recoiling MBH ejected by triple interactions. Combining AT2024tvd with two previously known off-nuclear TDEs discovered in X-rays (3XMM\,J2150 and EP240222a), which likely involve intermediate-mass black holes in satellite galaxies, we find that the parent galaxies of all three events are very massive ($\sim 10^{10.9}\,M_\odot$). This result aligns with expectations from cosmological simulations that the number of offset MBHs scales linearly with the host halo mass., Comment: 26 pages, 16 figures, 4 tables. Submitted to journal on 24 Feb 2025. Comments welcome

Ads recommendation is a prominent service of online advertising systems and has been actively studied. Recent studies indicate that scaling-up and advanced design of the recommendation model can bring significant performance improvement. However, with a larger model scale, such prior studies have a significantly increasing gap from industry as they often neglect two fundamental challenges in industrial-scale applications. First, training and inference budgets are restricted for the model to be served, exceeding which may incur latency and impair user experience. Second, large-volume data arrive in a streaming mode with data distributions dynamically shifting, as new users/ads join and existing users/ads leave the system. We propose the External Large Foundation Model (ExFM) framework to address the overlooked challenges. Specifically, we develop external distillation and a data augmentation system (DAS) to control the computational cost of training/inference while maintaining high performance. We design the teacher in a way like a foundation model (FM) that can serve multiple students as vertical models (VMs) to amortize its building cost. We propose Auxiliary Head and Student Adapter to mitigate the data distribution gap between FM and VMs caused by the streaming data issue. Comprehensive experiments on internal industrial-scale applications and public datasets demonstrate significant performance gain by ExFM., Comment: Accepted by the ACM Web Conference (WWW) 2025 Industrial Track as Oral Presentation

Sharing diverse genomic and other biomedical datasets is critical to advance scientific discoveries and their equitable translation to improve human health. However, data sharing remains challenging in the context of legacy datasets, evolving policies, multi-institutional consortium science, and international stakeholders. The NIH-funded Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium was established to improve the performance of polygenic risk estimates for a broad range of health and disease outcomes with global impacts. Improving polygenic risk score performance across genetically diverse populations requires access to large, diverse cohorts. We report on the design and implementation of data sharing policies and procedures developed in PRIMED to aggregate and analyze data from multiple, heterogeneous sources while adhering to existing data sharing policies for each integrated dataset. We describe two primary data sharing mechanisms: coordinated dbGaP applications and a Consortium Data Sharing Agreement, as well as provide alternatives when individual-level data cannot be shared within the Consortium (e.g., federated analyses). We also describe technical implementation of Consortium data sharing in the NHGRI Analysis Visualization and Informatics Lab-space (AnVIL) cloud platform, to share derived individual-level data, genomic summary results, and methods workflows with appropriate permissions. As a Consortium making secondary use of pre-existing data sources, we also discuss challenges and propose solutions for release of individual- and summary-level data products to the broader scientific community. We make recommendations for ongoing and future policymaking with the goal of informing future consortia and other research activities.

We present the optical discovery and multiwavelength follow-up observations of AT2024kmq, a likely tidal disruption event (TDE) associated with a supermassive ($M_{\rm BH}\sim 10^{8} M_\odot$) black hole in a massive galaxy at $z=0.192$. The optical light curve of AT2024kmq exhibits two distinct peaks: an early fast (timescale 1 d) and luminous ($M\approx-20$ mag) red peak, then a slower (timescale 1 month) blue peak with a higher optical luminosity ($M\approx-22$ mag) and featureless optical spectra. The second component is similar to the spectroscopic class of "featureless TDEs" in the literature, and during this second component we detect highly variable, luminous ($L_X\approx 10^{44}$ erg s$^{-1}$), and hard ($f_\nu \propto \nu^{-1.5}$) X-ray emission. Luminous ($10^{29} $erg s$^{-1}$ Hz$^{-1}$ at 10 GHz) but unchanging radio emission likely arises from an underlying active galactic nucleus. The luminosity, timescale, and color of the early red optical peak can be explained by synchrotron emission, or alternatively by thermal emission from material at a large radius ($R\approx\mathrm{few}\times10^{15}$ cm). Possible physical origins for this early red component include an off-axis relativistic jet, and shocks from self-intersecting debris leading to the formation of the accretion disk. Late-time radio observations will help distinguish between the two possibilities., Comment: 23 pages, 7 figures, 6 tables. Submitted to journal on 11 Feb 2025. Comments welcome

From $>1000$ orbits of HST imaging, we present deep homogeneous resolved star color-magnitude diagrams that reach the oldest main sequence turnoff and uniformly measured star formation histories (SFHs) of 36 dwarf galaxies ($-6 \ge M_V \ge -17$) associated with the M31 halo, and for 10 additional fields in M31, M33, and the Giant Stellar Stream. From our SFHs we find: i) the median stellar age and quenching epoch of M31 satellites correlate with galaxy luminosity and galactocentric distance. Satellite luminosity and present-day distance from M31 predict the satellite quenching epoch to within $1.8$ Gyr at all epochs. This tight relationship highlights the fundamental connection between satellite halo mass, environmental history, and star formation duration. ii) There is no difference between the median SFH of galaxies on and off the great plane of Andromeda satellites. iii) $\sim50$\% of our M31 satellites show prominent ancient star formation ($>12$ Gyr ago) followed by delayed quenching ($8-10$ Gyr ago), which is not commonly observed among the MW satellites. iv) A comparison with TNG50 and FIRE-2 simulated satellite dwarfs around M31-like hosts show that some of these trends (dependence of SFH on satellite luminosity) are reproduced in the simulations while others (dependence of SFH on galactocentric distance, presence of the delayed-quenching population) are weaker or absent. We provide all photometric catalogs and SFHs as High-Level Science Products on MAST., Comment: Accepted for publication on ApJ. 47 pages, 24 figures, 12 tables. Corresponding HLSP data can be retrieved at: https://archive.stsci.edu/hlsp/m31-satellites

We created new reddening maps and derived new extinction laws from visual to near-infrared passbands using improved RR~Lyrae period-absolute magnitude-metallicity relations, thus enabling distance estimates for individual bulge RR~Lyrae variables. The extinction law is most uniform in RIK and RJK and the distances to individual RR~Lyrae based on these colors are determined with an accuracy six and four percent, respectively. Using only the near-infrared passbands for distance estimation we inferred the distance to the Galactic center equal to djk = 8.2 +- 0.001(stat) +- 0.53(sys)pc after geometrical correction. We show that variations in the extinction law toward the Galactic bulge can mimic a barred spatial distribution in the bulge RR~Lyrae star population in visual passbands. This arises from a gradient in extinction differences along Galactic longitudes and latitudes, which can create the perception of the Galactic bar, particularly when using visual passband-based distances. A barred angle in the RR~Lyrae spatial distribution disappears when near-infrared passband-based distances are used, as well as when reddening law variations are incorporated in visual passband-based distances. The prominence of the bar, as traced by RR~Lyrae stars, depends on their metallicity, with metal-poor RR~Lyrae stars ([Fe/H]<-1.0dex) showing little to no tilt with respect to the bar. Metal-rich ([Fe/H]>-1.0dex) RR~Lyrae stars do show a barred/bulge signature in spatial properties derived using near-infrared distances, with an angle {\iota} = 18 +- 5deg, consistent with previous bar measurements from the literature. The 5D kinematic analysis, primarily based on transverse velocities, indicates a rotational lag in RR~Lyrae stars compared to red clump giants. Despite variations in the extinction law, our kinematic conclusions are robust across different distance estimation methods., Comment: Accepted for publication in A&A

Star-forming clumps have been found to significantly influence the star formation of gas-rich $z>1$ galaxies. Using public data from JWST/NIRCam (COSMOS-Web) and ALMA (FMOS-COSMOS), we study a sample of 32 massive ($>10^{10.5}\,\rm M_{\odot}$) main-sequence galaxies at $z_{\rm spec}\sim1.5$ with $\sim0.3\,\rm kpc$ resolution. We create composite morphological models consisting of bulge, disk, and clumps to fully 'deconstruct' the galaxy images. With the resulting measurements of the flux and size of these components, we find the following: (I)The combined contribution of clumps is $1-30\%$ towards the net star formation rate (SFR) of the host while contributing $1-20\%$ to its stellar mass. The clumps show a correlation between their stellar mass and SFR, but have an increased specific-SFR (sSFR) relative to the star-forming main sequence, with offsets ranging from $0\lesssim\Delta\log\rm sSFR\lesssim 0.4$. They feature star formation surface densities of $10^{-2}-10^{2}\,\rm M_{\odot}/yr/kpc^{2}$, consistent with values observed in local star-forming and starburst galaxies. (II)The clumps span a large range of characteristic sizes ($r_{e}\sim0.1-1\,\rm kpc$) and stellar masses ($\sim 10^{8.0-9.5}\,\rm M_{\odot}$). We estimate a mass-size relation ($r_{e}\propto\rm M_{\star}^{\,0.52\pm0.07}$) along with a stellar mass function (slope, $\alpha=-1.85\pm 0.19$), both suggesting a hierarchical nature similar to that expected in star-forming regions in local galaxies. (III)Our measurements agree with the properties of stellar clumps in $z\gtrsim1$ lensed systems, bridging the gap between lensed and unlensed studies by detecting structures at sub-kpc scales.(IV)Clumps are found to be preferentially located along spiral features visible primarily in the residual rest-frame near-IR images. In conclusion, we present an observation-based, coherent picture of star-forming clumps at $z>1$., Comment: Published in MNRAS; 22 pages, 24 figures

Understanding factors contributing to premature mortality is critical for public health planning. This study examines the relationships between premature death rates and multiple risk factors across several Texas counties, utilizing EPA air quality data, Census information, and county health records from recent years. We analyze the impact of air quality (PM2.5 levels), socioeconomic factors (median household income), and health conditions (COPD prevalence) through statistical analysis and modeling techniques. Results reveal COPD prevalence as a strong predictor of premature death rates, with higher prevalence associated with a substantial increase in years of potential life lost. While socioeconomic factors show a significant negative correlation, air quality demonstrates more complex indirect relationships. These findings emphasize the need for integrated public health interventions that prioritize key health conditions while addressing underlying socioeconomic disparities., Comment: 5 pages

Detection and study of the intracluster light in rich clusters of galaxies has been a problem of long standing challenge and interest. Using the lowest surface brightness images of the Coma cluster of galaxies in the g and r bands, from the Halos and Environment of Nearby Galaxies (HERON) Coma Cluster Project, we obtained the most extensive image of intracluster light (ICL) in a single cluster to date, spreading over 1.5 Mpc from the cluster core. The unprecedented wealth of spectroscopic data made publicly available by the Dark Energy Spectroscopic Instrument (DESI) Early Data Release, complemented with a compilation from the NASA/IPAC Extragalactic Database and the literature, enabled the identification of 2,157 galaxy members within Coma, from which 42 distinct groups were identified. The synergy between these high-quality data allowed us to: 1) calculate ICL fractions of $19.9\pm0.5$\% and $19.6\pm0.6$\% in the g and r bands, respectively, consistent with a dynamically active cluster, 2) unveil Coma's faintest tidal features, and 3) provide a comprehensive picture of the dynamics and interactions within this complex system. Our findings indicate that the ICL connects several of these groups in a filamentous network, from which we infer the ongoing dynamical processes. In particular, we identified a faint stellar bridge linking the core of Coma with the galaxy NGC 4839, providing compelling evidence that this galaxy has already traversed the central region of the cluster., Comment: 16 pages, 8 figures, 4 tables; accepted for publication in A&A

We present the discovery of 14 new (and recovery of 4 known) low accretion rate magnetic white dwarfs in post-common envelope binaries that emit strong cyclotron emission using the Zwicky Transient Facility (ZTF) light curves, doubling the known sample size. In addition, we discovered a candidate magnetic period bouncer and recovered three known ones. We confirmed the presence of cyclotron emission using low-resolution spectra in 19 objects. Using the ZTF light curves, follow-up spectra, and the spectral energy distribution, we measured the orbital period, magnetic field strength, and white dwarf temperature of each system. Although the phase-folded light curves have diverse shapes and show a much larger variability amplitude, we show that their intrinsic properties (e.g. period distribution, magnetic field strength) are similar to those of previously known systems. The diversity in light curve shapes can be explained by differences in the optical depth of the accretion spot and geometric differences, the inclination angle and the magnetic spot latitude. The evolutionary states of the longer period binaries are somewhat uncertain but are vary; we found systems consistent with being pre-polars, detached polars, or low-state polars. In addition, we discovered two new low-state polars that likely have brown dwarf companions and could be magnetic period bouncers.

Optically dark dusty star-forming galaxies (DSFGs) play an essential role in massive galaxy formation at early cosmic time, however their nature remains elusive. Here we present a detailed case study of all the baryonic components of a $z=4.821$ DSFG, XS55. Selected from the ultra-deep COSMOS-XS 3GHz map with a red SCUBA-2 450$\mu$m/850$\mu$m colour, XS55 was followed up with ALMA 3mm line scans and spectroscopically confirmed to be at $z=4.821$ via detections of the CO(5-4) and [CI](1-0) lines. JWST/NIRCam imaging reveals that XS55 is a F150W-dropout with red F277W/F444W colour, and a complex morphology: a compact central component embedded in an extended structure with a likely companion. XS55 is tentatively detected in X-rays with both Chandra and XMM-Newton, suggesting an active galactic nucleus (AGN) nature. By fitting a panchromatic SED spanning NIR to radio wavelengths, we revealed that XS55 is a massive main-sequence galaxy with a stellar mass of $M_\ast=(5\pm1)\times10^{10}\,{\rm M_\odot}$ and a star formation rate of ${\rm SFR}=540\pm177~{\rm M_\odot\,yr^{-1}}$. The dust of XS55 is optically thick in the far infrared (FIR) with a surprisingly cold dust temperature of $T_{\rm dust}=33\pm2\,{\rm K}$, making XS55 one of the coldest DSFGs at $z>4$ known to date. This work unveils the nature of a radio-selected F150W-dropout, suggesting the existence of a population of DSFGs hosting active black holes embedded in optically thick dust., Comment: 11 pages, 7 figures, accepted in Astronomy & Astrophysics

We report on the fault-tolerant operation of logical qubits on a neutral atom quantum computer, with logical performance surpassing physical performance for multiple circuits including Bell states (12x error reduction), random circuits (15x), and a prototype Anderson Impurity Model ground state solver for materials science applications (up to 6x, non-fault-tolerantly). The logical qubits are implemented via the [[4, 2, 2]] code (C4). Our work constitutes the first complete realization of the benchmarking protocol proposed by Gottesman 2016 [1] demonstrating results consistent with fault-tolerance. In light of recent advances on applying concatenated C4/C6 detection codes to achieve error correction with high code rates and thresholds, our work can be regarded as a building block towards a practical scheme for fault tolerant quantum computation. Our demonstration of a materials science application with logical qubits particularly demonstrates the immediate value of these techniques on current experiments.

User prompts for generative AI models are often underspecified, leading to sub-optimal responses. This problem is particularly evident in text-to-image (T2I) generation, where users commonly struggle to articulate their precise intent. This disconnect between the user's vision and the model's interpretation often forces users to painstakingly and repeatedly refine their prompts. To address this, we propose a design for proactive T2I agents equipped with an interface to (1) actively ask clarification questions when uncertain, and (2) present their understanding of user intent as an understandable belief graph that a user can edit. We build simple prototypes for such agents and verify their effectiveness through both human studies and automated evaluation. We observed that at least 90% of human subjects found these agents and their belief graphs helpful for their T2I workflow. Moreover, we develop a scalable automated evaluation approach using two agents, one with a ground truth image and the other tries to ask as few questions as possible to align with the ground truth. On DesignBench, a benchmark we created for artists and designers, the COCO dataset (Lin et al., 2014), and ImageInWords (Garg et al., 2024), we observed that these T2I agents were able to ask informative questions and elicit crucial information to achieve successful alignment with at least 2 times higher VQAScore (Lin et al., 2024) than the standard single-turn T2I generation. Demo: https://github.com/google-deepmind/proactive_t2i_agents.

The promise of unsupervised multi-view-stereo (MVS) is to leverage large unlabeled datasets, yet current methods underperform when training on difficult data, such as handheld smartphone videos of indoor scenes. Meanwhile, high-quality synthetic datasets are available but MVS networks trained on these datasets fail to generalize to real-world examples. To bridge this gap, we propose a semi-supervised learning framework that allows us to train on real and rendered images jointly, capturing structural priors from synthetic data while ensuring parity with the real-world domain. Central to our framework is a novel set of losses that leverages powerful existing monocular relative-depth estimators trained on the synthetic dataset, transferring the rich structure of this relative depth to the MVS predictions on unlabeled data. Inspired by perceptual image metrics, we compare the MVS and monocular predictions via a deep feature loss and a multi-scale statistical loss. Our full framework, which we call Prism, achieves large quantitative and qualitative improvements over current unsupervised and synthetic-supervised MVS networks. This is a best-case-scenario result, opening the door to using both unlabeled smartphone videos and photorealistic synthetic datasets for training MVS networks., Comment: 11 pages, 6 figures, 3 tables

A chemical characterization of the Galactic Center is essential for understanding its formation and structural evolution. Trends of alpha-elements, such as Mg, Si, and Ca, serve as powerful diagnostic tools, offering insights into star-formation rates and gas-infall history. However, high extinction has previously hindered such studies. In this study, we present a detailed chemical abundance analysis of M giants in the Milky Way's Nuclear Star Cluster (NSC), focusing on alpha-element trends with metallicity. High-resolution, near-infrared spectra were obtained using the IGRINS spectrograph on the Gemini South telescope for nine M giants. Careful selection of spectral lines, based on a solar-neighborhood control sample of 50 M giants, was implemented to minimize systematic uncertainties. Our findings show enhanced alpha-element abundances in the predominantly metal-rich NSC stars, consistent with trends in the inner bulge. The NSC stars follow the high-[alpha/Fe] envelope seen in the solar vicinity's metal-rich population, indicating a high star-formation rate. The alpha-element trends decrease with increasing metallicity, also at the highest metallicities. Our results suggest the NSC population likely shares a similar evolutionary history with the inner bulge, challenging the idea of a recent dominant star formation burst. This connection between the NSC and the inner-disk sequence suggests that the chemical properties of extragalactic NSCs of Milky Way type galaxies could serve as a proxy for understanding the host galaxies' evolutionary processes., Comment: Accepted for publication in ApJ

Column chromatography is an important process in downstream biopharmaceutical manufacturing that enables high-selectivity separation of proteins through various modalities, such as affinity, ion exchange, hydrophobic interactions, or a combination of the aforementioned modes. Current mechanistic models of column chromatography typically abstract particle-level phenomena, in particular adsorption kinetics. A mechanistic model capable of incorporating particle-level phenomena would increase the value derived from mechanistic models. To this end, we model column chromatography via sphere packing, formulating three versions, each with increasing complexity. The first, homogeneous circle packing, is recast as maximum independent set and solved by the Quantum Approximate Optimization Algorithm on a quantum computer. The second, heterogeneous circle packing, is formulated as a graphical optimization problem and solved via classical simulations, accompanied by a road map to a quantum solution. An extension to the third, heterogeneous sphere packing, is formulated mathematically in a manner suitable to a quantum solution. Finally, detailed resource scaling is conducted to estimate the quantum resources required to simulate the most realistic model, providing a pathway to quantum advantage.

Machine learning based surrogate models offer researchers powerful tools for accelerating simulation-based workflows. However, as standard datasets in this space often cover small classes of physical behavior, it can be difficult to evaluate the efficacy of new approaches. To address this gap, we introduce the Well: a large-scale collection of datasets containing numerical simulations of a wide variety of spatiotemporal physical systems. The Well draws from domain experts and numerical software developers to provide 15TB of data across 16 datasets covering diverse domains such as biological systems, fluid dynamics, acoustic scattering, as well as magneto-hydrodynamic simulations of extra-galactic fluids or supernova explosions. These datasets can be used individually or as part of a broader benchmark suite. To facilitate usage of the Well, we provide a unified PyTorch interface for training and evaluating models. We demonstrate the function of this library by introducing example baselines that highlight the new challenges posed by the complex dynamics of the Well. The code and data is available at https://github.com/PolymathicAI/the_well., Comment: 38th Conference on Neural Information Processing Systems (NeurIPS 2024) Track on Datasets and Benchmarks

We present cosmological results from the measurement of clustering of galaxy, quasar and Lyman-$\alpha$ forest tracers from the first year of observations with the Dark Energy Spectroscopic Instrument (DESI Data Release 1). We adopt the full-shape (FS) modeling of the power spectrum, including the effects of redshift-space distortions, in an analysis which has been validated in a series of supporting papers. In the flat $\Lambda$CDM cosmological model, DESI (FS+BAO), combined with a baryon density prior from Big Bang Nucleosynthesis and a weak prior on the scalar spectral index, determines matter density to $\Omega_\mathrm{m}=0.2962\pm 0.0095$, and the amplitude of mass fluctuations to $\sigma_8=0.842\pm 0.034$. The addition of the cosmic microwave background (CMB) data tightens these constraints to $\Omega_\mathrm{m}=0.3056\pm 0.0049$ and $\sigma_8=0.8121\pm 0.0053$, while further addition of the the joint clustering and lensing analysis from the Dark Energy Survey Year-3 (DESY3) data leads to a 0.4% determination of the Hubble constant, $H_0 = (68.40\pm 0.27)\,{\rm km\,s^{-1}\,Mpc^{-1}}$. In models with a time-varying dark energy equation of state, combinations of DESI (FS+BAO) with CMB and type Ia supernovae continue to show the preference, previously found in the DESI DR1 BAO analysis, for $w_0>-1$ and $w_a<0$ with similar levels of significance. DESI data, in combination with the CMB, impose the upper limits on the sum of the neutrino masses of $\sum m_\nu < 0.071\,{\rm eV}$ at 95% confidence. DESI data alone measure the modified-gravity parameter that controls the clustering of massive particles, $\mu_0=0.11^{+0.45}_{-0.54}$, while the combination of DESI with the CMB and the clustering and lensing analysis from DESY3 constrains both modified-gravity parameters, giving $\mu_0 = 0.04\pm 0.22$ and $\Sigma_0 = 0.044\pm 0.047$, in agreement with general relativity. [Abridged.], Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers/). 55 pages, 10 figures

We present the samples of galaxies and quasars used for DESI 2024 cosmological analyses, drawn from the DESI Data Release 1 (DR1). We describe the construction of large-scale structure (LSS) catalogs from these samples, which include matched sets of synthetic reference `randoms' and weights that account for variations in the observed density of the samples due to experimental design and varying instrument performance. We detail how we correct for variations in observational completeness, the input `target' densities due to imaging systematics, and the ability to confidently measure redshifts from DESI spectra. We then summarize how remaining uncertainties in the corrections can be translated to systematic uncertainties for particular analyses. We describe the weights added to maximize the signal-to-noise of DESI DR1 2-point clustering measurements. We detail measurement pipelines applied to the LSS catalogs that obtain 2-point clustering measurements in configuration and Fourier space. The resulting 2-point measurements depend on window functions and normalization constraints particular to each sample, and we present the corrections required to match models to the data. We compare the configuration- and Fourier-space 2-point clustering of the data samples to that recovered from simulations of DESI DR1 and find they are, generally, in statistical agreement to within 2\% in the inferred real-space over-density field. The LSS catalogs, 2-point measurements, and their covariance matrices will be released publicly with DESI DR1., Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers/)

We present the measurements and cosmological implications of the galaxy two-point clustering using over 4.7 million unique galaxy and quasar redshifts in the range $0.1