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The central regions of the Milky Way constitute a unique laboratory for a wide swath of astrophysical studies, consequently the inner $\sim$400 pc has been the target of numerous large surveys at all accessible wavelengths. In this paper we present a catalog of sources at 25 and 37 $\mu$m located within all of the regions observed with the SOFIA/FORCAST instrument in the inner $\sim$200 pc of the Galaxy. The majority of the observations were obtained as part of the SOFIA Cycle 7 Galactic Center Legacy program survey, which was designed to complement the Spitzer/MIPS 24 $\mu$m catalog in regions saturated in the MIPS observations. Due to the wide variety of source types captured by our observations at 25 and 37 $\mu$m, we do not limit the FORCAST source catalog to unresolved point sources, or treat all sources as if they are point-like sources. The catalog includes all detectable sources in the regions, resulting in a catalog of 950 sources, including point sources, compact sources, and extended sources. We also provide the user with metrics to discriminate between the source types., Comment: 29 pages, 13 figures, Accepted to ApJ

In this study, we report a tetragonal perovskite structure of SrIrO$_3$ (P4/mmm, a = 3.9362(9) \r{A}, c = 7.880(3) \r{A}) synthesized at 6 GPa and 1400 $\deg$C, employing the ambient pressure monoclinic SrIrO$_3$ with distorted 6H structure as a precursor. The crystal structure of tetragonal SrIrO3 was evaluated on the basis of single crystal and powder X-ray diffraction. A cubic indexing was observed attributed to overlooked superlattice reflections. Weak fractional peaks in the H and K dimensions suggest possible structure modulation by oxygen defects. Magnetization study reveals weak paramagnetic behavior down to 2 K, indicative of the interplay between spin-orbit coupling, electron correlations, and crystal electric field. Additionally, measurements of electrical resistivity display metallic behavior with an upturn at about 54 K, ascribed to weak electron localization and possible structural defects., Comment: 31 pages, 12 figures

We observed the Seyfert 1 galaxy Mrk817 during an intensive multi-wavelength reverberation mapping campaign for 16 months. Here, we examine the behavior of narrow UV absorption lines seen in HST/COS spectra, both during the campaign and in other epochs extending over 14 years. We conclude that while the narrow absorption outflow system (at -3750 km/s with FWHM=177 km/s) responds to the variations of the UV continuum as modified by the X-ray obscurer, its total column density (logNH =19.5 cm-2) did not change across all epochs. The adjusted ionization parameter (scaled with respect to the variations in the Hydrogen ionizing continuum flux) is log UH =-1.0. The outflow is located at a distance smaller than 38 parsecs from the central source, which implies a hydrogen density of nH > 3000 cm-3. The absorption outflow system only covers the continuum emission source and not the broad emission line region, which suggests that its transverse size is small (< 1e16 cm), with potential cloud geometries ranging from spherical to elongated along the line of sight., Comment: 18 pages, 12 Figures, Accepted for publication in ApJ

Well-posedness of certain semilinear parabolic problems with nonlocal initial conditions is shown in time-weighted spaces. The result is applied to recover the initial states in semilinear parabolic problems with nonlinearities of superlinear behavior near zero from small time-averages over arbitrary time periods., Comment: 19 pages

Advances in Artificial Intelligence (AI) are helping tackle a growing number of societal challenges, demonstrating technology's increasing capability to address complex issues, including those outlined in the United Nations (UN) Sustainable Development Goals (SDGs). Despite global efforts, 80 percent of SDG targets have deviated, stalled, or regressed, and only 15 percent are on track as of 2023, illustrating the urgency of accelerating efforts to meet the goals by 2030. We draw on Google's internal and collaborative research, technical work, and social impact initiatives to show AI's potential to accelerate action on the SDGs and make substantive progress to help address humanity's most pressing challenges. The paper highlights AI capabilities (including computer vision, generative AI, natural language processing, and multimodal AI) and showcases how AI is altering how we approach problem-solving across all 17 SDGs through use cases, with a spotlight on AI-powered innovation in health, education, and climate. We then offer insights on AI development and deployment to drive bold and responsible innovation, enhance impact, close the accessibility gap, and ensure that everyone, everywhere, can benefit from AI., Comment: 12 pages

We consider the momentum formulation of the two-dimensional surface quasi-geostrophic equations forced by random noise, of both additive and linear multiplicative types. For any prescribed deterministic function under some conditions, we construct solutions to each system whose energy is the fixed function. Consequently, we prove non-uniqueness of almost sure Markov selections of suitable class of weak solutions associated to the momentum surface quasi-geostrophic equations in both cases of noise.

We introduce and study the pinnacle sets of a simple graph $G$ with $n$ vertices. Given a bijective vertex labeling $\lambda\,:\,V(G)\rightarrow [n]$, the label $\lambda(v)$ of vertex $v$ is a pinnacle of $(G, \lambda)$ if $\lambda(v)>\lambda(w)$ for all vertices $w$ in the neighborhood of $v$. The pinnacle set of $(G, \lambda)$ contains all the pinnacles of the labeled graph. A subset $S\subseteq[n]$ is a pinnacle set of $G$ if there exists a labeling $\lambda$ such that $S$ is the pinnacle set of $(G,\lambda)$. Of interest to us is the question: Which subsets of $[n]$ are the pinnacle sets of $G$? Our main results are as follows. We show that when $G$ is connected, $G$ has a size-$k$ pinnacle set if and only if $G$ has an independent set of the same size. Consequently, determining if $G$ has a size-$k$ pinnacle set and determining if $G$ has a particular subset $S$ as a pinnacle set are NP-complete problems. Nonetheless, we completely identify all the pinnacle sets of complete graphs, complete bipartite graphs, cycles and paths. We also present two techniques for deriving new pinnacle sets from old ones that imply a typical graph has many pinnacle sets. Finally, we define a poset on all the size-$k$ pinnacle sets of $G$ and show that it is a join semilattice. If, additionally, the poset has a minimum element, then it is a distributive lattice. We conclude with some open problems for further study.

We present our findings from the new deep Chandra observations ($256$ ks) of the merging galaxy cluster SPT-CL J2031-4037 at $z = 0.34$. Our observations reveal intricate structures seen in a major merger akin to the Bullet Cluster. The X-ray data confirm the existence of two shock fronts, one to the northwest and one to the southeast by directly measuring the temperature jump of gas across the surface brightness edges. The stronger shock front in the northwest has a density jump of $3.16 \pm 0.34$ across the sharp surface brightness edge and Mach number $M = 3.36^{+0.87}_{-0.48}$, which makes this cluster one of the rare merging systems with a Mach number $M > 2$. We use the northwestern shock to compare two models for shock heating - the instant heating model and the Coulomb collisional heating model, and we determine that the temperatures across the shock front agree with the Coulomb collisional model of heating. For the shock front in the southeastern region, we find a density jump of $1.53 \pm 0.14$ and a Mach number of $M = 1.36 ^{+0.09}_{-0.08}$., Comment: Accepted for publication in ApJ

Cosmological parameters such as $\Omega_{\rm{M}}$ and $\sigma_{8}$ can be measured indirectly using various methods, including galaxy cluster abundance and cosmic shear. These measurements constrain the composite parameter $S_{8}$, leading to degeneracy between $\Omega_{\rm{M}}$ and $\sigma_{8}$. However, some structural properties of galaxy clusters also correlate with cosmological parameters, due to their dependence on a cluster's accretion history. In this work, we focus on the splashback radius, an observable cluster feature that represents a boundary between a cluster and the surrounding Universe. Using a suite of cosmological simulations with a range of values for $\Omega_{\rm{M}}$ and $\sigma_{8}$, we show that the position of the splashback radius around cluster-mass halos is greater in cosmologies with smaller values of $\Omega_{\rm{M}}$ or larger values of $\sigma_{8}$. This variation breaks the degeneracy between $\Omega_{\rm{M}}$ and $\sigma_{8}$ that comes from measurements of the $S_{8}$ parameter. We also show that this variation is, in principle, measurable in observations. As the splashback radius can be determined from the same weak lensing analysis already used to estimate $S_{8}$, this new approach can tighten low-redshift constraints on cosmological parameters, either using existing data, or using upcoming data such as that from Euclid and LSST., Comment: 12 pages, 7 figures, 1 table, accepted for publication in ApJ

Ranges of the real-valued parameters $\alpha$, $a$, $b$, and $m$ are identified for which the operator $$\mathcal{A}_{\alpha}(a,b)f(x):=x^\alpha\left(f''(x)+\frac{a}{x}f'(x)+\frac{b}{x^2}f(x)\right), \quad x>0,$$ generates an analytic semigroup in $L_1((0,\infty),x^m\mathrm{d}x)$.

The Fred Young Submillimeter Telescope (FYST), on Cerro Chajnantor in the Atacama desert of Chile, will conduct wide-field and small deep-field surveys of the sky with more than 100,000 detectors on the Prime-Cam instrument. Kinetic inductance detectors (KIDs) were chosen as the primary sensor technology for their high density focal plane packing. Additionally, they benefit from low cost, ease of fabrication, and simplified cryogenic readout, which are all beneficial for successful deployment at scale. The cryogenic multiplexing complexity is pulled out of the cryostat and is instead pushed into the digital signal processing of the room temperature electronics. Using the Xilinx Radio Frequency System on a Chip (RFSoC), a highly multiplexed KID readout was developed for the first light Prime-Cam and commissioning Mod-Cam instruments. We report on the performance of the RFSoC-based readout with multiple detector arrays in various cryogenic setups. Specifically we demonstrate detector noise limited performance of the RFSoC-based readout under the expected optical loading conditions., Comment: draft submitted to SPIE

Revealing the quantum properties of matter requires a high degree of experimental control accompanied by a profound theoretical understanding. At ultracold temperatures, quantities that appear continuous in everyday life, such as the motional angular momentum of two colliding particles, become quantized, leaving a measurable imprint on experimental results. Embedding a single particle within a larger quantum bath at lowest temperatures can result in resonant partial-wave dependent interaction, whose strength near zero energy is dictated by universal threshold scaling laws. Hybrid atom-ion systems have emerged as a novel platform in which a single charged atom in an ultracold bath serves as a well-controlled impurity of variable energy. However, entering the low-energy s-wave regime and exploring the role of higher-partial-wave scattering within has remained an open challenge. Here, we immerse a Barium ion in a cloud of ultracold spin-polarized Lithium atoms, realize tunable collision energies below the s-wave limit and explore resonant higher-partial-wave scattering by studying the energy dependence of Feshbach resonances. Utilizing precise electric field control, we tune the collision energy over four orders of magnitude, reaching from the many-parital-wave to the s-wave regime. At the lowest energies, we probe the energy dependence of an isolated s-wave Feshbach resonance and introduce a theoretical model that allows to distinguish it from higher-partial-wave resonances. Additionally, at energies around the p-wave barrier, we find and identify an open-channel f-wave resonance, consistent with threshold laws. Our findings highlight and benchmark the importance of higher-partial-wave scattering well within the s-wave regime and offer control over chemical reactions and complex many-body dynamics in atom-ion ensembles - on the level of individual angular momentum quanta.

Several sources of repeating coherent bursts of radio emission with periods of many minutes have now been reported in the literature. These "ultra-long period" (ULP) sources have no clear multi-wavelength counterparts and challenge canonical pulsar emission models, leading to debate regarding their nature. In this work we report the discovery of a bright, highly-polarised burst of radio emission at low Galactic latitude as part of a wide-field survey for transient and variable radio sources. ASKAP\,J175534.9$-$252749.1 does not appear to repeat, with only a single intense two-minute $\sim$200-mJy burst detected from 60~hours of observations. The burst morphology and polarisation properties are comparable to those of classical pulsars but the duration is more than one hundred times longer, analogous to ULPs. Combined with the existing ULP population, this suggests that these sources have a strong Galactic latitude dependence and hints at an unexplored population of transient and variable radio sources in the thin disk of the Milky Way. The resemblance of this burst with both ULPs and pulsars calls for a unified coherent emission model for objects with spin periods from milliseconds to tens of minutes. However, whether or not these are all neutron stars or have the same underlying power source remains open for debate.

Assembly theory (AT) quantifies selection using the assembly equation and identifies complex objects that occur in abundance based on two measurements, assembly index and copy number, where the assembly index is the minimum number of joining operations necessary to construct an object from basic parts, and the copy number is how many instances of the given object(s) are observed. Together these define a quantity, called Assembly, which captures the amount of causation required to produce objects in abundance in an observed sample. This contrasts with the random generation of objects. Herein we describe how AT's focus on selection as the mechanism for generating complexity offers a distinct approach, and answers different questions, than computational complexity theory with its focus on minimum descriptions via compressibility. To explore formal differences between the two approaches, we show several simple and explicit mathematical examples demonstrating that the assembly index, itself only one piece of the theoretical framework of AT, is formally not equivalent to other commonly used complexity measures from computer science and information theory including Shannon entropy, Huffman encoding, and Lempel-Ziv-Welch compression. We also include proofs that assembly index is not in the same computational complexity class as these compression algorithms and discuss fundamental differences in the ontological basis of AT, and assembly index as a physical observable, which distinguish it from theoretical approaches to formalizing life that are unmoored from measurement., Comment: 38 pages, 4 figures, 1 table, and 91 references

We present an analysis of high-resolution optical spectra recorded for 30 stars of the split extended main-sequence turnoff (eMSTO) of the young ($\sim$ 40 Myr) Small Magellanic Cloud (SMC) globular cluster NGC 330. Spectra were obtained with the M2FS and MIKE spectrographs located on the Magellan-Clay 6.5m telescope. These spectra revealed the presence of Be stars, occupying primarily the cool side of the split main sequence (MS). Rotational velocity ($v\sin{i}$) measurements for most of the targets are consistent with the presence of two populations of stars in the cluster: one made up of rapidly rotating Be stars ($ \approx 200$ $\rm km\,s^{-1}$), and {the other} consisting of warmer stars with slower rotation ($<\!v\sin{i}\!>\approx50$ $\rm km\,s^{-1}$). Core emission in the H$\delta$ photospheric lines was observed for most of the H$\alpha$ emitters. The shell parameter computed for the targets in our sample indicate that most of the observed stars should have inclinations below 75$^{\circ}$. These results confirm the detection of Be stars obtained through photometry, but also reveal the presence of narrow H$\alpha$ and H$\delta$ features for some targets that cannot be detected with low-resolution spectroscopy or photometry. Asymmetry variability of H$\alpha$ line profiles on the timescales of a few years is also observed, and could provide information on the geometry of the decretion disks. Observations revealed the presence of nebular H$\alpha$ emission, strong enough in faint targets to compromise the extraction of spectra and to impact narrow band photometry used to assess the presence of H$\alpha$ emission., Comment: 15 pages, 13 figures, accepted for publication in The Astrophysical Journal

Due to the uncontrolled and complex real-life radio propagation environments, Claude Shannon's information theory of communications describes fundamental limits to state-of-the-art 5G radio access network (RAN) capacity, with respect to fixed radio resource usage. Fortunately, recent research has found that a holographic metasurface-based new physical layer architecture may hold the key to overcome these fundamental limits of current mobile networks under a new paradigm, smart wireless environment (SWE), where the long-standing challenge of mobile communications, fading channel hostility, may be solved, leading to a step-change boost in network performance and user experience. Despite recent research activities in SWE, the best way to implement it as a network operator remains an open challenge. In this industrial review, we adopt a novel yet realistic mobile channel stabilisation perspective for network operators to understand this paradigm shift. More specifically, we provide a technical analysis of the synergy between key next-gen mobile network enablers, e.g., holographic metasurface, wireless sensing, and machine intelligence, as well as of how this synergy leads to a robust future RAN architecture. Against the as yet unclear theoretical boundaries and low technology readiness level (TRL) of SWE enhanced telecommunications, we conclude by identifying critical challenges in future commercial deployments., Comment: This work has been submitted to the IEEE for possible publication

Neoantigen targeting therapies including personalized vaccines have shown promise in the treatment of cancers. Accurate identification/prioritization of neoantigens is highly relevant to designing clinical trials, predicting treatment response, and understanding mechanisms of resistance. With the advent of massively parallel sequencing technologies, it is now possible to predict neoantigens based on patient-specific variant information. However, numerous factors must be considered when prioritizing neoantigens for use in personalized therapies. Complexities such as alternative transcript annotations, various binding, presentation and immunogenicity prediction algorithms, and variable peptide lengths/registers all potentially impact the neoantigen selection process. While computational tools generate numerous algorithmic predictions for neoantigen characterization, results from these pipelines are difficult to navigate and require extensive knowledge of the underlying tools for accurate interpretation. Due to the intricate nature and number of salient neoantigen features, presenting all relevant information to facilitate candidate selection for downstream applications is a difficult challenge that current tools fail to address. We have created pVACview, the first interactive tool designed to aid in the prioritization and selection of neoantigen candidates for personalized neoantigen therapies. pVACview has a user-friendly and intuitive interface where users can upload, explore, select and export their neoantigen candidates. The tool allows users to visualize candidates using variant, transcript and peptide information. pVACview will allow researchers to analyze and prioritize neoantigen candidates with greater efficiency and accuracy in basic and translational settings. The application is available as part of the pVACtools pipeline at pvactools.org and as an online server at pvacview.org., Comment: Supplemental tables available at 10.5281/zenodo.11534338

Artificial intelligence methods are being increasingly applied across various domains, but their often opaque nature has raised concerns about accountability and trust. In response, the field of explainable AI (XAI) has emerged to address the need for human-understandable AI systems. Evolutionary computation (EC), a family of powerful optimization and learning algorithms, offers significant potential to contribute to XAI, and vice versa. This paper provides an introduction to XAI and reviews current techniques for explaining machine learning models. We then explore how EC can be leveraged in XAI and examine existing XAI approaches that incorporate EC techniques. Furthermore, we discuss the application of XAI principles within EC itself, investigating how these principles can illuminate the behavior and outcomes of EC algorithms, their (automatic) configuration, and the underlying problem landscapes they optimize. Finally, we discuss open challenges in XAI and highlight opportunities for future research at the intersection of XAI and EC. Our goal is to demonstrate EC's suitability for addressing current explainability challenges and to encourage further exploration of these methods, ultimately contributing to the development of more understandable and trustworthy ML models and EC algorithms., Comment: 24 pages, 4 figures. arXiv admin note: substantial text overlap with arXiv:2306.14786

In health, most large language model (LLM) research has focused on clinical tasks. However, mobile and wearable devices, which are rarely integrated into such tasks, provide rich, longitudinal data for personal health monitoring. Here we present Personal Health Large Language Model (PH-LLM), fine-tuned from Gemini for understanding and reasoning over numerical time-series personal health data. We created and curated three datasets that test 1) production of personalized insights and recommendations from sleep patterns, physical activity, and physiological responses, 2) expert domain knowledge, and 3) prediction of self-reported sleep outcomes. For the first task we designed 857 case studies in collaboration with domain experts to assess real-world scenarios in sleep and fitness. Through comprehensive evaluation of domain-specific rubrics, we observed that Gemini Ultra 1.0 and PH-LLM are not statistically different from expert performance in fitness and, while experts remain superior for sleep, fine-tuning PH-LLM provided significant improvements in using relevant domain knowledge and personalizing information for sleep insights. We evaluated PH-LLM domain knowledge using multiple choice sleep medicine and fitness examinations. PH-LLM achieved 79% on sleep and 88% on fitness, exceeding average scores from a sample of human experts. Finally, we trained PH-LLM to predict self-reported sleep quality outcomes from textual and multimodal encoding representations of wearable data, and demonstrate that multimodal encoding is required to match performance of specialized discriminative models. Although further development and evaluation are necessary in the safety-critical personal health domain, these results demonstrate both the broad knowledge and capabilities of Gemini models and the benefit of contextualizing physiological data for personal health applications as done with PH-LLM., Comment: 72 pages

Despite extensive efforts to create fairer machine learning (ML) datasets, there remains a limited understanding of the practical aspects of dataset curation. Drawing from interviews with 30 ML dataset curators, we present a comprehensive taxonomy of the challenges and trade-offs encountered throughout the dataset curation lifecycle. Our findings underscore overarching issues within the broader fairness landscape that impact data curation. We conclude with recommendations aimed at fostering systemic changes to better facilitate fair dataset curation practices., Comment: NeurIPS Datasets & Benchmarks 2024 (Oral)

We present the second data release for the GaLactic and Extragalactic All-sky Murchison Widefield Array eXtended (GLEAM-X) survey. This data release is an area of 12,892-deg^2 around the South Galactic Pole region covering 20h 40m <= RA <= 6h 40m, -90deg <= Dec <= +30deg. Observations were taken in 2020 using the Phase-II configuration of the Murchison Widefield Array (MWA) and covering a frequency range of 72-231MHz with twenty frequency bands. We produce a wideband source-finding mosaic over 170-231MHz with a median root mean squared noise of 1.5 (+1.5/-0.5) mJy beam^(-1). We present a catalogue of 624,866 components, including 562,302 components which are spectrally fit. This catalogue is 98% complete at 50mJy, and a reliability of 98.7% at a 5sigma level, consistent with expectations for this survey. The catalogue is made available via Vizier and the PASA datastore and accompanying mosaics for this data release are made available via AAO Data Central and SkyView., Comment: Accepted for publication in PASA; 24 pages, 15 figures

The CCAT Collaboration's six-meter Fred Young Submillimeter Telescope is scheduled to begin observing in the Chilean Atacama in 2025, targeting a variety of science goals throughout cosmic history. Prime-Cam is a 1.8-meter diameter cryostat that will host up to seven independent instrument modules designed for simultaneous spectroscopic and broadband, polarimetric surveys at millimeter to submillimeter wavelengths. The first of these instrument modules, the 280 GHz module, will include ${\sim}$10,000 kinetic inductance detectors (KIDs) across three arrays. While the first array was fabricated out of tri-layer TiN/Ti/TiN, the other two arrays were fabricated out of a single layer of Al. This combination of materials within the same instrument provides a unique opportunity to directly compare the performance and noise properties of two different detector materials that are seeing increasing use within the field. We present preliminary comparisons here based on lab testing, along with a discussion of the potential impacts on operation when observing and translating raw data to science-grade maps., Comment: 6 pages, 3 figures, conference proceedings submitted to the Journal of Low Temperature Physics

Assembly Theory (AT) was developed to help distinguish living from non-living systems. The theory is simple as it posits that the amount of selection or Assembly is a function of the number of complex objects where their complexity can be objectively determined using assembly indices. The assembly index of a given object relates to the number of recursive joining operations required to build that object and can be not only rigorously defined mathematically but can be experimentally measured. In pervious work we outlined the theoretical basis, but also extensive experimental measurements that demonstrated the predictive power of AT. These measurements showed that is a threshold in assembly indices for organic molecules whereby abiotic chemical systems could not randomly produce molecules with an assembly index greater or equal than 15. In a recent paper by Hazen et al [1] the authors not only confused the concept of AT with the algorithms used to calculate assembly indices, but also attempted to falsify AT by calculating theoretical assembly indices for objects made from inorganic building blocks. A fundamental misunderstanding made by the authors is that the threshold is a requirement of the theory, rather than experimental observation. This means that exploration of inorganic assembly indices similarly requires an experimental observation, correlated with the theoretical calculations. Then and only then can the exploration of complex inorganic molecules be done using AT and the threshold for living systems, as expressed with such building blocks, be determined. Since Hazen et al.[1] present no experimental measurements of assembly theory, their analysis is not falsifiable., Comment: 6 pages, 11 references

We present $griz$ photometric light curves for the full 5 years of the Dark Energy Survey Supernova program (DES-SN), obtained with both forced Point Spread Function (PSF) photometry on Difference Images (DIFFIMG) performed during survey operations, and Scene Modelling Photometry (SMP) on search images processed after the survey. This release contains $31,636$ DIFFIMG and $19,706$ high-quality SMP light curves, the latter of which contains $1635$ photometrically-classified supernovae that pass cosmology quality cuts. This sample spans the largest redshift ($z$) range ever covered by a single SN survey ($0.1

We report constraints on a variety of non-standard cosmological models using the full 5-year photometrically-classified type Ia supernova sample from the Dark Energy Survey (DES-SN5YR). Both Akaike Information Criterion (AIC) and Suspiciousness calculations find no strong evidence for or against any of the non-standard models we explore. When combined with external probes, the AIC and Suspiciousness agree that 11 of the 15 models are moderately preferred over Flat-$\Lambda$CDM suggesting additional flexibility in our cosmological models may be required beyond the cosmological constant. We also provide a detailed discussion of all cosmological assumptions that appear in the DES supernova cosmology analyses, evaluate their impact, and provide guidance on using the DES Hubble diagram to test non-standard models. An approximate cosmological model, used to perform bias corrections to the data holds the biggest potential for harbouring cosmological assumptions. We show that even if the approximate cosmological model is constructed with a matter density shifted by $\Delta\Omega_m\sim0.2$ from the true matter density of a simulated data set the bias that arises is sub-dominant to statistical uncertainties. Nevertheless, we present and validate a methodology to reduce this bias., Comment: Published to MNRAS on 20 August 2024; v2 updates to the accepted version

We present a precise measurement of cosmological time dilation using the light curves of 1504 type Ia supernovae from the Dark Energy Survey spanning a redshift range $0.1\lesssim z\lesssim 1.2$. We find that the width of supernova light curves is proportional to $(1+z)$, as expected for time dilation due to the expansion of the Universe. Assuming type Ia supernovae light curves are emitted with a consistent duration $\Delta t_{\rm em}$, and parameterising the observed duration as $\Delta t_{\rm obs}=\Delta t_{\rm em}(1+z)^b$, we fit for the form of time dilation using two methods. Firstly, we find that a power of $b \approx 1$ minimises the flux scatter in stacked subsamples of light curves across different redshifts. Secondly, we fit each target supernova to a stacked light curve (stacking all supernovae with observed bandpasses matching that of the target light curve) and find $b=1.003\pm0.005$ (stat) $\pm\,0.010$ (sys). Thanks to the large number of supernovae and large redshift-range of the sample, this analysis gives the most precise measurement of cosmological time dilation to date, ruling out any non-time-dilating cosmological models at very high significance., Comment: 14 pages, 13 figures. Updated in response to reviewer feedback. Accepted for publication in the Monthly Notices of the Royal Astronomical Society (MNRAS)

We measure the current expansion rate of the Universe, Hubble's constant $H_0$, by calibrating the absolute magnitudes of supernovae to distances measured by Baryon Acoustic Oscillations. This `inverse distance ladder' technique provides an alternative to calibrating supernovae using nearby absolute distance measurements, replacing the calibration with a high-redshift anchor. We use the recent release of 1829 supernovae from the Dark Energy Survey spanning $0.01\lt z \lt1.13$ anchored to the recent Baryon Acoustic Oscillation measurements from DESI spanning $0.30 \lt z_{\mathrm{eff}} \lt 2.33$. To trace cosmology to $z=0$, we use the third-, fourth- and fifth-order cosmographic models, which, by design, are agnostic about the energy content and expansion history of the universe. With the inclusion of the higher-redshift DESI-BAO data, the third-order model is a poor fit to both data sets, with the fourth-order model being preferred by the Akaike Information Criterion. Using the fourth-order cosmographic model, we find $H_0=67.19^{+0.66}_{-0.64}\mathrm{~km} \mathrm{~s}^{-1} \mathrm{~Mpc}^{-1}$, in agreement with the value found by Planck without the need to assume Flat-$\Lambda$CDM. However the best-fitting expansion history differs from that of Planck, providing continued motivation to investigate these tensions.

Let $A \subset \mathbb{Z}^d$ be a finite set. It is known that the sumset $NA$ has predictable size ($\vert NA\vert = P_A(N)$ for some $P_A(X) \in \mathbb{Q}[X]$) and structure (all of the lattice points in some finite cone other than all of the lattice points in a finite collection of exceptional subcones), once $N$ is larger than some threshold. In previous work, joint with Shakan, the first and third named authors established the first effective bounds for both of these thresholds for an arbitrary set $A$. In this article we substantially improve each of these bounds, coming much closer to the corresponding lower bounds known., Comment: 15 pages

Empirical evidence for a gap between the computational powers of classical and quantum computers has been provided by experiments that sample the output distributions of two-dimensional quantum circuits. Many attempts to close this gap have utilized classical simulations based on tensor network techniques, and their limitations shed light on the improvements to quantum hardware required to frustrate classical simulability. In particular, quantum computers having in excess of $\sim 50$ qubits are primarily vulnerable to classical simulation due to restrictions on their gate fidelity and their connectivity, the latter determining how many gates are required (and therefore how much infidelity is suffered) in generating highly-entangled states. Here, we describe recent hardware upgrades to Quantinuum's H2 quantum computer enabling it to operate on up to $56$ qubits with arbitrary connectivity and $99.843(5)\%$ two-qubit gate fidelity. Utilizing the flexible connectivity of H2, we present data from random circuit sampling in highly connected geometries, doing so at unprecedented fidelities and a scale that appears to be beyond the capabilities of state-of-the-art classical algorithms. The considerable difficulty of classically simulating H2 is likely limited only by qubit number, demonstrating the promise and scalability of the QCCD architecture as continued progress is made towards building larger machines., Comment: Includes minor updates to the text and an updated author list to include researchers who made technical contributions in upgrading the machine to 56 qubits but were left off the original version by mistake

We outline the development of the readout software for the Prime-Cam and Mod-Cam instruments on the CCAT Fred Young Submillimeter Telescope (FYST), primecam_readout. The instruments feature lumped-element kinetic inductance detector (LEKID) arrays driven by Xilinx ZCU111 RFSoC boards. In the current configuration, each board can drive up to 4000 KIDs, and Prime-Cam is implementing approximately 25 boards. The software runs on a centralized control computer connected to the boards via dedicated ethernet, and facilitates such tasks as frequency-multiplexed tone comb driving, comb calibration and optimization, and detector timestream establishment. The control computer utilizes dynamically generated control channels for each board, allowing for simultaneous parallel control over all, while uniquely tracking diagnostics for each. This work demonstrates a scalable RFSoC readout architecture where computational demands increase linearly with the number of detectors, enabling control of tens-of-thousands of KIDs with modest hardware, and opening the door to the next generation of KID arrays housing millions of detectors., Comment: SPIE Astronomical Telescopes + Instrumentation conference proceedings

In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over fine-grained information from millions of tokens of context, including multiple long documents and hours of video and audio. The family includes two new models: (1) an updated Gemini 1.5 Pro, which exceeds the February version on the great majority of capabilities and benchmarks; (2) Gemini 1.5 Flash, a more lightweight variant designed for efficiency with minimal regression in quality. Gemini 1.5 models achieve near-perfect recall on long-context retrieval tasks across modalities, improve the state-of-the-art in long-document QA, long-video QA and long-context ASR, and match or surpass Gemini 1.0 Ultra's state-of-the-art performance across a broad set of benchmarks. Studying the limits of Gemini 1.5's long-context ability, we find continued improvement in next-token prediction and near-perfect retrieval (>99%) up to at least 10M tokens, a generational leap over existing models such as Claude 3.0 (200k) and GPT-4 Turbo (128k). Finally, we highlight real-world use cases, such as Gemini 1.5 collaborating with professionals on completing their tasks achieving 26 to 75% time savings across 10 different job categories, as well as surprising new capabilities of large language models at the frontier; when given a grammar manual for Kalamang, a language with fewer than 200 speakers worldwide, the model learns to translate English to Kalamang at a similar level to a person who learned from the same content.