Search

We present photometric and spectroscopic observations of SN 2023fyq, a type Ibn supernova in the nearby galaxy NGC 4388 (D$\simeq$18~Mpc). In addition, we trace long-standing precursor emission at the position of SN 2023fyq using data from DLT40, ATLAS, ZTF, ASAS-SN, Swift, and amateur astronomer Koichi Itagaki. Precursor activity is observed up to nearly three years before the supernova explosion, with a relatively rapid rise in the final 100 days. The double-peaked post-explosion light curve reaches a luminosity of $\sim10^{43}~\rm erg\,s^{-1}$. The strong intermediate-width He lines observed in the nebular spectrum of SN 2023fyq imply the interaction is still active at late phases. We found that the precursor activity in SN 2023fyq is best explained by the mass transfer in a binary system involving a low-mass He star and a compact companion. An equatorial disk is likely formed in this process ($\sim$0.6$\rm M_{\odot}$), and the interaction of SN ejecta with this disk powers the main peak of the supernova. The early SN light curve reveals the presence of dense extended material ($\sim$0.3$\rm M_{\odot}$) at $\sim$3000$\rm R_{\odot}$ ejected weeks before the SN explosion, likely due to final-stage core silicon burning or runaway mass transfer resulting from binary orbital shrinking, leading to rapid rising precursor emission within $\sim$30 days prior to explosion. The final explosion could be triggered either by the core-collapse of the He star or by the merger of the He star with a compact object. SN 2023fyq, along with SN 2018gjx and SN 2015G, forms a unique class of Type Ibn SNe which originate in binary systems and are likely to exhibit detectable long-lasting pre-explosion outbursts with magnitudes ranging from $-$10 to $-$13., Comment: submitted to ApJ

Major European Union-funded research infrastructure and open science projects have traditionally included dissemination work, for mostly one-way communication of the research activities. Here we present and review our radical re-envisioning of this work, by directly engaging citizen science volunteers into the research. We summarise the citizen science in the Horizon-funded projects ASTERICS (Astronomy ESFRI and Research Infrastructure Clusters) and ESCAPE (European Science Cluster of Astronomy and Particle Physics ESFRI Research Infrastructures), engaging hundreds of thousands of volunteers in providing millions of data mining classifications. Not only does this have enormously more scientific and societal impact than conventional dissemination, but it facilitates the direct research involvement of what is often arguably the most neglected stakeholder group in Horizon projects, the science-inclined public. We conclude with recommendations and opportunities for deploying crowdsourced data mining in the physical sciences, noting that the primary goal is always the fundamental research question; if public engagement is the primary goal to optimise, then other, more targeted approaches may be more effective., Comment: Accepted by European Physical Journal Plus. Invited review. 26 pages, 1 figure

The study of small ($<$300 m) near-Earth objects (NEOs) is important because they are more closely related than larger objects to the precursors of meteorites that fall on Earth. Collisions of these bodies with Earth are also more frequent. Although such collisions cannot produce massive extinction events, they can still produce significant local damage. Here we present the results of a photometric and spectroscopic survey of small NEOs, which include near-infrared (NIR) spectra of 84 objects with a mean diameter of 126 m and photometric data of 59 objects with a mean diameter of 87 m. We found that S-complex asteroids are the most abundant among the NEOs, comprising $\sim$66\% of the sample. Most asteroids in the S-complex were found to have compositions consistent with LL-chondrites. Our study revealed the existence of NEOs with spectral characteristics similar to those in the S-complex, but that could be hidden within the C- or X-complex due to their weak absorption bands. We suggest that the presence of metal or shock-darkening could be responsible for the attenuation of the absorption bands. These objects have been grouped into a new subclass within the S-complex called Sx-types. The dynamical modeling showed that 83\% of the NEOs escaped from the $\nu_{6}$ resonance, 16\% from the 3:1 and just 1\% from the 5:2 resonance. Lightcurves and rotational periods were derived from the photometric data. No clear trend between the axis ratio and the absolute magnitude or rotational period of the NEOs was found., Comment: 61 pages, 43 figures, 5 tables. Accepted for publication in the Planetary Science Journal

Aims. This work aims to reproduce the time before or after a merger event of merging galaxies from the IllustrisTNG cosmological simulation using machine learning. Methods. Images of merging galaxies were created in the u, g, r, and i bands from IllustrisTNG. The merger times were determined using the time difference between the last simulation snapshot where the merging galaxies were tracked as two galaxies and the first snapshot where the merging galaxies were tracked as a single galaxy. This time was then further refined using simple gravity simulations. These data were then used to train a residual network (ResNet50), a Swin Transformer (Swin), a convolutional neural network (CNN), and an autoencoder (using a single latent neuron) to reproduce the merger time. The full latent space of the autoencoder was also studied to see if it reproduces the merger time better than the other methods. This was done by reducing the latent space dimensions using Isomap, linear discriminant analysis (LDA), neighbourhood components analysis, sparse random projection, truncated singular value decomposition and uniform manifold approximation and projection. Results. The CNN is the best of all the neural networks. The performance of the autoencoder was close to the CNN, with Swin close behind the autoencoder. ResNet50 performed the worst. The LDA dimensionality reduction performed the best of the six methods used. The exploration of the full latent space produced worse results than the single latent neuron of the autoencoder. For the test data set, we found a median error of 190 Myr, comparable to the time separation between snapshots in IllustrisTNG. Galaxies more than $\approx$ 625 Myr before a merger have poorly recovered merger times, as well as galaxies more than $\approx$ 125 Myr after a merger event., Comment: 16 pages, 20 figures, 1 appendix, Accepted for publication in Astronomy & Astrophysics

We present the first degree-scale tomography map of the dusty magnetized interstellar medium (ISM) from stellar polarimetry and distance measurements. We used the RoboPol polarimeter at Skinakas Observatory to conduct a survey of starlight polarization in a region of the sky of 4 square degrees. We propose a Bayesian method to decompose the stellar-polarization source field along the distance to invert the 3D volume occupied by the observed stars. We used it to obtain the first 3D map of the dusty magnetized ISM. Specifically, we produced a tomography map of the orientation of the plane-of-sky (POS) component of the magnetic field threading the diffuse, dusty regions responsible for the stellar polarization. For the targeted region centered on Galactic coordinates $(l,b) \approx (103.3^\circ, 22.3^\circ)$, we identified several ISM clouds. Most of the lines of sight intersect more than one cloud. A very nearby component was detected in the foreground of a dominant component from which most of the polarization signal comes. Farther clouds, with a distance of up to 2~kpc, were similarly detected. Some of them likely correspond to intermediate-velocity clouds seen in HI spectra in this region of the sky. We found that the orientation of the POS component of the magnetic field changes along distance for most of the lines of sight. Our study demonstrates that starlight polarization data coupled to distance measures have the power to reveal the great complexity of the dusty magnetized ISM in 3D and, in particular, to provide local measurements of the POS component of the magnetic field. This demonstrates that the inversion of large data volumes, as expected from the PASIPHAE survey, will provide the necessary means to move forward in the modeling of the Galactic magnetic field and of the dusty magnetized ISM as a contaminant in observations of the cosmic microwave background polarization., Comment: Preprint of the accepted version at Astronomy & Astrophysics. The 3D map obtained in this paper can be visualized online at https://pasiphae.science/visualization and a video featuring it is accessible at https://www.youtube.com/watch?v=dB_6J1zhmPI

This editorial outlines an expanded scope for the next (fifth) generation of integrated marketing communication. It identifies key market forces that gave rise to this evolution and describes a trajectory of where Integrated Marketing Communication (IMC) has been and where it is going. The central shift is moving from primarily focusing on one stakeholder to multiple ones, including people (employees and society), the planet (environment), and profits. It identifies examples from industry that exemplify multi-stakeholder decision-making and uses the examples to suggest research questions that academics and practitioners should address. Examples and research directions are organized around marketing strategy, communication media and messages, and measurement systems.

We previously studied the inner crust and the pasta mantle of a neutron star within the 4th-order extended Thomas-Fermi (ETF) approach with consistent proton shell corrections added perturbatively via the Strutinsky integral (SI) theorem together with the contribution due to pairing. To speed up the computations and avoid numerical problems, we adopted parametrized nucleon density distributions. However, the errors incurred by the choice of the parametrization are expected to become more significant as the mean baryon number density is increased, especially in the pasta mantle where the differences in the energy per nucleon of the different phases are very small, typically a few keV. To improve the description of these exotic structures, we discuss the important features that a nuclear profile should fulfill and introduce two new parametrizations. Performing calculations using the BSk24 functional, we find that these parametrizations lead to lower ETF energy solutions for all pasta phases than the parametrization we adopted before and more accurately reproduce the exact equilibrium nucleon density distributions obtained from unconstrained variational calculations. Within the ETFSI method, all parametrizations predict the same composition in the region with quasi-spherical clusters. However, the two new parametrizations lead to a different mantle structure at mean baryon densities above about 0.07 fm^-3, at which point lasagna is energetically favored. Interestingly, spherical clusters reappear in the pasta region. The inverted pasta phases such as bucatini and Swiss cheese are still found in the densest region above the core in all cases., Comment: 12 pages, 9 figures, published in Phys. Rev. C

We present the first systematic investigation of supervised scaling laws outside of an ImageNet-like context - on images of galaxies. We use 840k galaxy images and over 100M annotations by Galaxy Zoo volunteers, comparable in scale to Imagenet-1K. We find that adding annotated galaxy images provides a power law improvement in performance across all architectures and all tasks, while adding trainable parameters is effective only for some (typically more subjectively challenging) tasks. We then compare the downstream performance of finetuned models pretrained on either ImageNet-12k alone vs. additionally pretrained on our galaxy images. We achieve an average relative error rate reduction of 31% across 5 downstream tasks of scientific interest. Our finetuned models are more label-efficient and, unlike their ImageNet-12k-pretrained equivalents, often achieve linear transfer performance equal to that of end-to-end finetuning. We find relatively modest additional downstream benefits from scaling model size, implying that scaling alone is not sufficient to address our domain gap, and suggest that practitioners with qualitatively different images might benefit more from in-domain adaption followed by targeted downstream labelling., Comment: 10+6 pages, 12 figures. Appendix C2 based on arxiv:2206.11927. Code, demos, documentation at https://github.com/mwalmsley/zoobot

Various galaxy merger detection methods have been applied to diverse datasets. However, it is difficult to understand how they compare. We aim to benchmark the relative performance of machine learning (ML) merger detection methods. We explore six leading ML methods using three main datasets. The first one (the training data) consists of mock observations from the IllustrisTNG simulations and allows us to quantify the performance metrics of the detection methods. The second one consists of mock observations from the Horizon-AGN simulations, introduced to evaluate the performance of classifiers trained on different, but comparable data. The third one consists of real observations from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) survey. For the binary classification task (mergers vs. non-mergers), all methods perform reasonably well in the domain of the training data. At $0.1

COVID-19 appeared abruptly in early 2020, requiring a rapid response amid a context of great uncertainty. Good quality data and knowledge was initially lacking, and many early models had to be developed with causal assumptions and estimations built in to supplement limited data, often with no reliable approach for identifying, validating and documenting these causal assumptions. Our team embarked on a knowledge engineering process to develop a causal knowledge base consisting of several causal BNs for diverse aspects of COVID-19. The unique challenges of the setting lead to experiments with the elicitation approach, and what emerged was a knowledge engineering method we call Causal Knowledge Engineering (CKE). The CKE provides a structured approach for building a causal knowledge base that can support the development of a variety of application-specific models. Here we describe the CKE method, and use our COVID-19 work as a case study to provide a detailed discussion and analysis of the method., Comment: 22 pages (plus 19 pages in appendices), 9 figures, submitted for review

Aims. In this work, we intend to examine how environment influences the merger fraction, from the low density field environment to higher density groups and clusters. We also aim to study how the properties of a group or cluster, as well as the position of a galaxy in the group or cluster, influences the merger fraction. Methods. We identified galaxy groups and clusters in the North Ecliptic Pole using a friends-of-friends algorithm and the local density. Once identified, we determined the central galaxies, group radii, velocity dispersions, and group masses of these groups and clusters. Merging systems were identified with a neural network as well as visually. With these, we examined how the merger fraction changes as the local density changes for all galaxies as well as how the merger fraction changes as the properties of the groups or clusters change. Results. We find that the merger fraction increases as local density increases and decreases as the velocity dispersion increases, as is often found in literature. A decrease in merger fraction as the group mass increases is also found. We also find groups with larger radii have higher merger fractions. The number of galaxies in a group does not influence the merger fraction. Conclusions. The decrease in merger fraction as group mass increases is a result of the link between group mass and velocity dispersion. Hence, this decrease of merger fraction with increasing mass is a result of the decrease of merger fraction with velocity dispersion. The increasing relation between group radii and merger fraction may be a result of larger groups having smaller velocity dispersion at a larger distance from the centre or larger groups hosting smaller, infalling groups with more mergers. However, we do not find evidence of smaller groups having higher merger fractions., Comment: 15 pages, 10 figures, 8 tables, 2 appendices, accepted for publication in Astronomy & Astrophysics

Galaxy mergers play a crucial role in galaxy evolution. However, the correlation between mergers and the local environment of galaxies is not fully understood. We aim to address the question of whether galaxy mergers prefer denser or less dense environments by quantifying the spatial clustering of mergers and non-mergers. We use two different indicators to classify mergers and non-mergers - classification based on a deep learning technique ($f$) and non-parametric measures of galaxy morphology, Gini-$M_{20}$ ($g$). We used a set of galaxy samples in the redshift range 0.1 < z < 0.15 from the Galaxy and Mass Assembly (GAMA) survey with a stellar mass cut of log (M*/Msun) > 9.5. We measured and compared the two-point correlation function (2pCF) of mergers and non-mergers classified using the two merger indicators $f$ and $g$. We measured the marked correlation function (MCF), in which the galaxies are weighted by $f$ to probe the environmental dependence of galaxy mergers. We do not observe a statistically significant difference between the clustering strengths of mergers and non-mergers obtained using 2pCF. However, using the MCF measurements with $f$ as a mark, we observe an anti-correlation between the likelihood of a galaxy being a merger and its environment. Our results emphasise the advantage of MCF over 2pCF in probing the environmental correlations. Based on the MCF measurements, we conclude that the galaxy mergers prefer to occur in the under-dense environments on scales greater than 50 kpc/h of the large-scale structure (LSS). We attribute this observation to the high relative velocities of galaxies in the densest environments that prevent them from merging., Comment: 13 pages, 9 figures, accepted for publication in A&A

Neutral atom quantum processors provide a viable route to scalable quantum computing, with recent demonstrations of high-fidelity and parallel gate operations and initial implementation of quantum algorithms using both physical and logical qubit encodings. In this work we present a characterization of the algorithmic performance of near term Rydberg atom quantum computers through device simulation to enable comparison against competing architectures. We consider three different quantum algorithm related tests, exploiting the ability to dynamically update qubit connectivity and multi-qubit gates. We calculate a quantum volume of $\mathbf{\mathit{V_{Q}}=2^{9}}$ for 9 qubit devices with realistic parameters, which is the maximum achievable value for this device size and establishes a lower bound for larger systems. We also simulate highly efficient implementations of both the Bernstein-Vazirani algorithm with >0.95 success probability for 9 data qubits and 1 ancilla qubit without loss correction, and Grover's search algorithm with a loss-corrected success probability of 0.97 for an implementation of the algorithm using 6 data qubits and 3 ancilla qubits using native multi-qubit $\mathbf{CCZ}$ gates. Our results indicate Rydberg atom processors are a highly competitive near-term platform which, bolstered by the potential for further scalability, can pave the way toward useful quantum computation., Comment: 14 pages, 7 figures

We present JWST spectral and photometric observations of the Type IIP supernova (SN) 2022acko at ~50 days past explosion. These data are the first JWST spectral observations of a core-collapse SN. We identify ~30 different H I features, other features associated with products produced from the CNO cycle, and s-process elements such as Sc II and Ba II. By combining the JWST spectra with ground-based optical and NIR spectra, we construct a full Spectral Energy Distribution from 0.4 to 25 microns and find that the JWST spectra are fully consistent with the simultaneous JWST photometry. The data lack signatures of CO formation and we estimate a limit on the CO mass of < 10^{-8} solar mass. We demonstrate how the CO fundamental band limits can be used to probe underlying physics during stellar evolution, explosion, and the environment. The observations indicate little mixing between the H envelope and C/O core in the ejecta and show no evidence of dust. The data presented here set a critical baseline for future JWST observations, where possible molecular and dust formation may be seen.

Large future sky surveys, such as the LSST, will provide optical photometry for billions of objects. This paper aims to construct a proxy for the far ultraviolet attenuation (AFUVp) from the optical data alone, enabling the rapid estimation of the star formation rate (SFR) for galaxies that lack UV or IR data. To mimic LSST observations, we use the deep panchromatic optical coverage of the SDSS Photometric Catalogue DR~12, complemented by the estimated physical properties for the SDSS galaxies from the GALEX-SDSS-WISE Legacy Catalog (GSWLC) and inclination information obtained from the SDSS DR7. We restricted our sample to the 0.025-0.1 z-spec range and investigated relations among surface brightness, colours, and dust attenuation in the far UV range for star-forming galaxies obtained from the spectral energy distribution (SED). {Dust attenuation is best correlated with (u-r) colour and the surface brightness in the u band ($\rm \mu_{u}$). We provide a dust attenuation proxy for galaxies on the star-forming main sequence, which can be used for the LSST or any other type of broadband optical survey. The mean ratio between the catalogue values of SFR and those estimated using optical-only SDSS data with the AFUVp prior calculated as $\Delta$SFR=log(SFR$_{\tiny{\mbox{this work}}}$/SFR$_{\tiny{}\texttt{GSWLC}}$) is found to be less than 0.1~dex, while runs without priors result in an SFR overestimation larger than 0.3~dex. The presence or absence of theAFUVp has a negligible influence on the stellar mass estimation (with $\Delta$M$_{star}$ in the range from 0 to $-0.15$ dex). Forthcoming deep optical observations of the LSST Deep Drilling Fields, which also have multi-wavelength data, will enable one to calibrate the obtained relation for higher redshift galaxies and, possibly, extend the study towards other types of galaxies, such as early-type galaxies off the main sequence., Comment: 18 pages, accepted for publication in Astronomy and Astrophysics

Carbonaceous chondrites are among the most important meteorite types and have played a vital role in deciphering the origin and evolution of our solar system. They have been linked to low-albedo C-type asteroids, but due to subdued absorption bands, definitive asteroid-meteorite linkages remain elusive. A majority of these existing linkages rely on fine-grained (typically < 45 micron) powders across a limited wavelength range in the visible to near-infrared (0.35-2.5 microns). While this is useful in interpreting the fine-grained regolith of larger main-belt objects like Ceres, recent spacecraft missions to smaller near-Earth asteroids (NEAs), such as Bennu and Ryugu, have shown that their surfaces are dominated by larger grain size material. To better interpret the surfaces of these smaller, carbonaceous NEAs, we obtained laboratory reflectance spectra of seven carbonaceous chondrite meteorite groups (CI, CM, CO, CV, CR, CK, C2-ungrouped) over the ultraviolet to mid-infrared range (0.2-14 microns). Each meteorite contained five grain size bins (45-1000 microns) to help constrain spectral grain size effects. We find a correlation between grain size and absolute reflectance, spectral slope, band depth, and the Christiansen feature band center. Principal component analysis of grain size variation illustrates a similar trend to lunar-style space weathering. We also show that the Bus-DeMeo asteroid taxonomic classification of our samples is affected by grain size, specifically shifting CM2 Aguas Zarcas from a Ch-type to B-type with increasing grain size. This has implications for the parent body of the OSIRIS-REx target, Bennu. With Aguas Zarcas, we present results from Hapke modeling., Comment: 40 pages, 15 figures, published in the Planetary Science Journal

We present comprehensive optical observations of SN~2021gmj, a type II supernova (SN~II) discovered within a day of explosion by the Distance Less Than 40~Mpc (DLT40) survey. Follow up observations show that SN~2021gmj is a low luminosity SN~II (LL~SN~II), with a peak magnitude $M_V = -15.45$ and Fe II velocity of $\sim 1800 \ \mathrm{km} \ \mathrm{s}^{-1}$ at 50 days past explosion. Using the expanding photosphere method we derive a distance of $17.8^{+0.6}_{-0.4}$~Mpc. From the tail of the light-curve we obtain a radioactive nickel mass of $0.014 \pm 0.001$ $\mathrm{M}_{\odot}$. The presence of circumstellar material (CSM) is suggested by the early light curve, early spectra and the presence of high velocity H$\alpha$ in absorption. Analytical shock-cooling models of the early light curve cannot reproduce the fast rise, also supporting the idea that the early emission is partially powered by the interaction of the SN ejecta and CSM. The inferred low CSM mass of 0.025 $\mathrm{M}_{\odot}$ in our hydrodynamic-modeling light curve analysis is also consistent with our spectroscopic observations. We observe a broad feature near 4600 A, which may be high ionization lines of C, N or/and He II. This feature is reproduced by radiation hydrodynamic simulations of red supergiants with extended atmospheres. Several LL~SNe~II show similar spectral features implying that high density material around the progenitor may be common among them., Comment: Submitted to ApJ

We used 5487 star-forming galaxies at redshift z~0.63 extracted from the VIPERS and 143774 comparison galaxies in the local Universe from the GSWLC catalog. We employed two families of methods: parametric and non-parametric. In the former approaches, we compared the FMR projections plagued by observational biases on differently constructed control samples at various redshifts. Then, the metallicity difference between different redshifts in M*-SFR bins. In the latter approach, we related the metallicity and the normalized sSFR. The methodologies implemented to construct fair, complete samples for studying the MZR and the FMR produced consistent results showing a small, but still statistically significant evolution of both relations up to z~0.63. In particular, we observed a systematic trend where the median metallicity of the sample at z=0.63 is lower than that of the local sample at the same M* and SFR. The average difference in the metallicity of the low and intermediate redshifts is approximately 1.8 times the metallicity standard deviation of the median, of the intermediate redshift sample, in M*-SFR bins. We confirmed this result using the Kolmogorov-Smirnov test. When we applied the M*-completeness criterion to catalogs, the metallicity difference in redshifts decreased to approximately 0.96 times the metallicity standard deviation of the median, thus not statistically significant. This result may be dominated by the limited parameter space, being the lower M* galaxies where the difference is larger out from the analysis. A careful reading of the results, and their underlying selection criteria, are crucial in studies of the mass-metallicity and FMRs., Comment: Accepted for publication in A&A, 22 pages, 20 figures

In this paper we consider the numerical solution to the soft-margin support vector machine optimization problem. This problem is typically solved using the SMO algorithm, given the high computational complexity of traditional optimization algorithms when dealing with large-scale kernel matrices. In this work, we propose employing an NFFT-accelerated matrix-vector product using an ANOVA decomposition for the feature space that is used within an interior point method for the overall optimization problem. As this method requires the solution of a linear system of saddle point form we suggest a preconditioning approach that is based on low-rank approximations of the kernel matrix together with a Krylov subspace solver. We compare the accuracy of the ANOVA-based kernel with the default LIBSVM implementation. We investigate the performance of the different preconditioners as well as the accuracy of the ANOVA kernel on several large-scale datasets., Comment: Official Code https://github.com/wagnertheresa/NFFTSVMipm

The National Assessment Governing Board (the Board) contracted with Pearson to design and implement a review of the achievement level descriptions (ALDs) for National Assessment of Educational Progress (NAEP) Grade 8 assessments in Science, U.S. History, and Civics. This document describes the procedural and technical aspects and outcomes of the operational ALD Review study. This study commenced after Pearson had completed an ALD Review study for Mathematics and Reading in 2022, which itself was undertaken on behalf of the Board for the reasons noted in the Background section of this report. In particular, this report addresses the Board's updated achievement levels policy that called for the development of Reporting ALDs, which state what student performance associated with each NAEP achievement level likely can demonstrate related to the assessment content, and how these align with the existing content ALDs included in the frameworks and achievement level policy definitions. [For the 2022 report, "Achievement Level Description Review for the National Assessment of Educational Progress Mathematics and Reading Assessments. Final Process Documentation and Technical Report," see ED627620.]

One of the main objectives of the Mars Exploration Program is to search for evidence of past or current life on the planet. To achieve this, Mars exploration has been focusing on regions that may have liquid or frozen water. A set of critical areas may have seen cycles of ice thawing in the relatively recent past in response to periodic changes in the obliquity of Mars. In this work, we use convolutional neural networks to detect surface regions containing "Brain Coral" terrain, a landform on Mars whose similarity in morphology and scale to sorted stone circles on Earth suggests that it may have formed as a consequence of freeze/thaw cycles. We use large images (~100-1000 megapixels) from the Mars Reconnaissance Orbiter to search for these landforms at resolutions close to a few tens of centimeters per pixel (~25--50 cm). Over 52,000 images (~28 TB) were searched (~5% of the Martian surface) where we found detections in over 200 images. To expedite the processing we leverage a classifier network (prior to segmentation) in the Fourier domain that can take advantage of JPEG compression by leveraging blocks of coefficients from a discrete cosine transform in lieu of decoding the entire image at the full spatial resolution. The hybrid pipeline approach maintains ~93% accuracy while cutting down on ~95% of the total processing time compared to running the segmentation network at the full resolution on every image. The timely processing of big data sets helps inform mission operations, geologic surveys to prioritize candidate landing sites, avoid hazardous areas, or map the spatial extent of certain terrain. The segmentation masks and source code are available on Github for the community to explore and build upon., Comment: Submitted for publication, seeking comments from the community. Code available: https://github.com/pearsonkyle/Mars-Brain-Coral-Network

Cells are the fundamental unit of biological organization, and identifying them in imaging data - cell segmentation - is a critical task for various cellular imaging experiments. While deep learning methods have led to substantial progress on this problem, models that have seen wide use are specialist models that work well for specific domains. Methods that have learned the general notion of "what is a cell" and can identify them across different domains of cellular imaging data have proven elusive. In this work, we present CellSAM, a foundation model for cell segmentation that generalizes across diverse cellular imaging data. CellSAM builds on top of the Segment Anything Model (SAM) by developing a prompt engineering approach to mask generation. We train an object detector, CellFinder, to automatically detect cells and prompt SAM to generate segmentations. We show that this approach allows a single model to achieve state-of-the-art performance for segmenting images of mammalian cells (in tissues and cell culture), yeast, and bacteria collected with various imaging modalities. To enable accessibility, we integrate CellSAM into DeepCell Label to further accelerate human-in-the-loop labeling strategies for cellular imaging data. A deployed version of CellSAM is available at https://label-dev.deepcell.org/.

We present high cadence optical and ultraviolet observations of the Type II supernova (SN), SN 2022jox which exhibits early spectroscopic high ionization flash features of \ion{H}{1}, \ion{He}{2}, \ion{C}{4}, and \ion{N}{4} that disappear within the first few days after explosion. SN 2022jox was discovered by the Distance Less than 40 Mpc (DLT40) survey $\sim$0.75 days after explosion with followup spectra and UV photometry obtained within minutes of discovery. The SN reached a peak brightness of M$_V \sim$ $-$17.3 mag, and has an estimated $^{56}$Ni mass of 0.04 M$_{\odot}$, typical values for normal Type II SNe. The modeling of the early lightcurve and the strong flash signatures present in the optical spectra indicate interaction with circumstellar material (CSM) created from a progenitor with a mass loss rate of $\dot{M} \sim 10^{-3}-10^{-2}\ M_\odot\ \mathrm{yr}^{-1}$. There may also be some indication of late-time CSM interaction in the form of an emission line blueward of H$\alpha$ seen in spectra around 200 days. The mass-loss rate is much higher than the values typically associated with quiescent mass loss from red supergiants, the known progenitors of Type II SNe, but is comparable to inferred values from similar core collapse SNe with flash features, suggesting an eruptive event or a superwind in the progenitor in the months or years before explosion., Comment: ApJ, accepted 2024 Feb 14

We consider a numerical framework tailored to identifying optimal parameters in the context of modelling disease propagation. Our focus is on understanding the behaviour of optimisation algorithms for such problems, where the dynamics are described by a system of ordinary differential equations associated with the epidemiological SIRD model. We examine properties of the solution operator and determine existence of optimal parameters for the problem considered. Further, first-order optimality conditions are derived, the solution of which provides a certificate of goodness of fit, which is not always guaranteed with parameter tuning techniques. We then propose strategies for the numerical solution of such problems, based on projected gradient descent, Fast Iterative Shrinkage-Thresholding Algorithm (FISTA), and limited memory BFGS trust region approaches. We carry out a thorough computational study for a range of problems of interest, determining the relative performance of these numerical methods. Our results provide insights into the efficacy of these strategies, contributing to ongoing research into optimising parameters for accurate and reliable disease spread modelling. Moreover, our approach paves the way for calibration of more intricate compartmental models., Comment: 26 pages, 7 figures, 3 tables

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

We introduce a design modification to conventional geometry of the cryogenic three-terminal switch, the nanocryotron (nTron). The conventional geometry of nTrons is modified by including parallel current-carrying channels, an approach aimed at enhancing the device's performance in magnetic field environments. The common challenge in nTron technology is to maintain efficient operation under varying magnetic field conditions. Here we show that the adaptation of parallel channel configurations leads to an enhanced gate signal sensitivity, an increase in operational gain, and a reduction in the impact of superconducting vortices on nTron operation within magnetic fields up to 1 Tesla. Contrary to traditional designs that are constrained by their effective channel width, the parallel nanowire channels permits larger nTron cross sections, further bolstering the device's magnetic field resilience while improving electro-thermal recovery times due to reduced local inductance. This advancement in nTron design not only augments its functionality in magnetic fields but also broadens its applicability in technological environments, offering a simple design alternative to existing nTron devices., Comment: 6 pages, 5 figures. Accepted by Applied Physics Letters. Supplemental information includes additional supporting figures and tables

We present a near-IR survey of the Trapezium Cluster and inner Orion Nebula using the NASA/ESA/CSA James Webb Space Telescope. The survey with the NIRCam instrument covers 10.9 x 7.5 arcminutes (~1.25 x 0.85 pc) in twelve wide-, medium-, and narrow-band filters from 1-5 microns and is diffraction-limited at all wavelengths, providing a maximum spatial resolution of 0.063 arcsec at 2 microns, corresponding to ~25 au at Orion. The suite of filters chosen was designed to address a number of scientific questions including the form of the extreme low-mass end of the IMF into the planetary-mass range to 1 Jupiter mass and below; the nature of ionised and non-ionised circumstellar disks and associated proplyds in the near-IR with a similar resolution to prior HST studies; to examine the large fragmented outflow from the embedded BN-KL region at very high resolution and fidelity; and to search for new jets and outflows from young stars in the Trapezium Cluster and the Orion Molecular Cloud 1 behind. In this paper, we present a description of the design of the observational programme, explaining the rationale for the filter set chosen and the telescope and detector modes used to make the survey; the reduction of the data using the JWST pipeline and other tools; the creation of large colour mosaics covering the region; and an overview of the discoveries made in the colour images and in the individual filter mosaics. Highlights include the discovery of large numbers of free-floating planetary-mass candidates as low as 0.6 Jupiter masses, a significant fraction of which are in wide binaries; new emission phenomena associated with the explosive outflow from the BN-KL region; and a mysterious "dark absorber" associated with a number of disparate features in the region, but which is seen exclusively in the F115W filter. Further papers will examine those discoveries and others in more detail., Comment: 39 pages, 18 figures, 1 table