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We introduce rainbow codes, a novel class of quantum error correcting codes generalising colour codes and pin codes. Rainbow codes can be defined on any $D$-dimensional simplicial complex that admits a valid $(D+1)$-colouring of its $0$-simplices. We study in detail the case where these simplicial complexes are derived from chain complexes obtained via the hypergraph product and, by reinterpreting these codes as collections of colour codes joined at domain walls, show that we can obtain code families with growing distance and number of encoded qubits as well as logical non-Clifford gates implemented by transversal application of $T$ and $T^\dag$. By combining these techniques with the quasi-hyperbolic colour codes of Zhu et al. (arXiv:2310.16982) we obtain families of codes with transversal non-Clifford gates and parameters $[\![n,O(n),O(log(n))]\!]$ which allow the magic-state yield parameter $\gamma = \log_d(n/k)$ to be made arbitrarily small. In contrast to other recent constructions that achieve $\gamma \rightarrow 0$ our codes are natively defined on qubits, are LDPC, and have logical non-Clifford gates implementable by single-qubit (rather than entangling) physical operations, but are not asymptotically good., Comment: 19 pages (+ 13 page appendices); 12 (+ 7) figures

We use the First Light And Reionisation Epoch Simulations (FLARES) to study the evolution of the rest-frame ultraviolet (UV) and far-infrared (FIR) sizes for a statistical sample of massive ($\gtrsim10^{9}$M$_{\odot}$) high redshift galaxies (z $\in$ [5,10]). Galaxies are post-processed using the SKIRT radiative transfer code, to self-consistently obtain the full spectral energy distribution and surface brightness distribution. We create mock observations of the galaxies for the Near Infrared Camera (NIRCam) to study the rest-frame UV 1500 $\unicode{xC5}$ morphology. We also generate mock rest-frame FIR (50 $\mu$m) photometry and mock ALMA (158 $\mu$m) (0.01"-0.03" and $\approx$0.3" angular resolution) observations to study the dust-continuum. We find the effect of dust on observed sizes reduces with increasing wavelength from the UV to optical ($\sim$0.6 times the UV at 0.4$\mu$m), with no evolution in FIR sizes. Observed sizes vary within 0.4-1.2 times the intrinsic sizes at different signal to noise ratios (SNR = 5-20) across redshifts. The effect of PSF and noise makes bright structures prominent, whereas fainter regions blend with noise, leading to an underestimation (factor of 0.4-0.8) of sizes at SNR=5. At SNR=15-20, the underestimation reduces (factor of 0.6-0.9) at z=5-8 but due to PSF, at z=9-10, bright cores are dominant, resulting in an overestimation (factor of 1.0-1.2). For ALMA, low resolution sizes are effected by noise which acts as extended emission. The size evolution in UV broadly agrees with current observational samples and other simulations. This work is one of the first to analyse the panchromatic sizes of a statistically significant sample of simulated high-redshift galaxies, complementing a growing body of research highlighting the importance of conducting an equivalent comparison between observed galaxies and their simulated counterparts in the early Universe., Comment: 22 pages, 28 figures, data along with code to reproduce figures will be available on GitHub after publication

We use a sample of 73 simulated satellite and central dwarf galaxies spanning a stellar mass range of $10^{5.3}-10^{9.1} M_\odot$ to investigate the origin of their stellar age gradients. We find that dwarf galaxies often form their stars "inside-out," i.e., the stars form at successively larger radii over time. However, the oldest stars get reshuffled beyond the star forming radius by fluctuations in the gravitational potential well caused by stellar feedback (the same mechanisms that cause dwarfs to form dark matter cores). The result is that many dwarfs appear to have an "outside-in" age gradient at $z=0$, with younger stellar populations more centrally concentrated. However, for the reshuffled galaxies with the most extended star formation, young stars can form out to the large radii to which the old stars have been reshuffled, erasing the age gradient. We find that major mergers do not play a significant role in setting the age gradients of dwarfs. We find similar age gradient trends in satellites and field dwarfs, suggesting environment plays only a minor role, if any. Finally, we find that the age gradient trends are imprinted on the galaxies at later times, suggesting that the stellar reshuffling dominates after the galaxies have formed 50% of their stellar mass. The later reshuffling is at odds with results from the FIRE-2 simulations. Hence, age gradients offer a test of current star formation and feedback models that can be probed via observations of resolved stellar populations., Comment: 25 pages, 9 figures

Understanding human attention is crucial for vision science and AI. While many models exist for free-viewing, less is known about task-driven image exploration. To address this, we introduce CapMIT1003, a dataset with captions and click-contingent image explorations, to study human attention during the captioning task. We also present NevaClip, a zero-shot method for predicting visual scanpaths by combining CLIP models with NeVA algorithms. NevaClip generates fixations to align the representations of foveated visual stimuli and captions. The simulated scanpaths outperform existing human attention models in plausibility for captioning and free-viewing tasks. This research enhances the understanding of human attention and advances scanpath prediction models., Comment: arXiv admin note: substantial text overlap with arXiv:2305.12380

Plastic deformation behavior is most conveniently assessed by characterization on a surface, but whether such observations are representative of bulk properties is uncertain. Motivated by reported inconsistencies in slip resistance probed at different depths, we investigated (i) whether the average slip family activity is affected by the presence of a surface and (ii) how the kinematic nature of available slip families influences a potential surface effect. The slip family activity as a function of distance from the surface was extracted from full-field crystal plasticity simulations of random polycrystalline hexagonal close-packed (HCP) and body-centered cubic (BCC) metals as examples of mixed in contrast to universally-high numbers of slip systems per family. Under certain conditions, a deviation from bulk slip activity is observed up to about two grains from the surface. For the easiest (least slip-resistant) family, a surface effect of decreasing activity with depth emerges if the number of slip systems falls below about six. For harder families, slip activity always increases with depth. These phenomena are explained on the basis of varying constraints with depth in connection with the kinematic properties of slip families in the material.

JWST has enabled detecting and spatially resolving the heavily dust-attenuated stellar populations of sub-millimeter galaxies, revealing detail that was previously inaccessible. In this work we construct a sample of 289 sub-millimeter galaxies with detailed joint ALMA and JWST constraints in the COSMOS field. Sources are originally selected using the SCUBA-2 instrument and have archival ALMA observations from various programs. Their JWST NIRCam imaging is from COSMOS-Web and PRIMER. We extract multi-wavelength photometry in a manner that leverages the unprecedented near-infrared spatial resolution of JWST, and fit the data with spectral energy distribution models to derive photometric redshifts, stellar masses, star-formation rates and optical attenuation. The sample has an average z=2.6, A_V=2.5, SFR=270 and log(M*)=11.1. There are 81 (30%) galaxies that have no previous optical/near-infrared detections, including 75% of the z>4 sub-sample (n=28). The faintest observed near-infrared sources have the highest redshifts and largest A_V=4. In a preliminary morphology analysis we find that ~10% of our sample exhibit spiral arms and 5% host stellar bars, with one candidate bar found at z>3. Finally, we find that the clustering of JWST galaxies within 10 arcseconds of a sub-mm galaxy is a factor of 2 greater than what is expected based on either random clustering or the distribution of sources around any red galaxy irrespective of a sub-mm detection., Comment: 37 pages (15 for RGBs + references), 14 figures, submitted to ApJ

High-redshift radio(-loud) galaxies (H$z$RGs) are massive galaxies with powerful radio-loud active galactic nuclei (AGNs) and serve as beacons for protocluster identification. However, the interplay between H$z$RGs and the large-scale environment remains unclear. To understand the connection between H$z$RGs and the surrounding obscured star formation, we investigated the overdensity and spatial distribution of submillimeter-bright galaxies (SMGs) in the field of 4C\,23.56, a well-known H$z$RG at $z=2.48$. We used SCUBA-2 data ($\sigma\,{\sim}\,0.6$\,mJy) to estimate the $850\,{\rm \mu m}$ source number counts and examine the radial and azimuthal overdensities of the $850\,{\rm \mu m}$ sources in the vicinity of the H$z$RG. The angular distribution of SMGs is inhomogeneous around the H$z$RG 4C\,23.56, with fewer sources oriented along the radio jet. We also find a significant overdensity of bright SMGs (${\rm S}_{850\rm\,\mu m}\geq5\,$mJy). Faint and bright SMGs exhibit different spatial distributions. The former are concentrated in the core region, while the latter prefer the outskirts of the H$z$RG field. High-resolution observations show that the seven brightest SMGs in our sample are intrinsically bright, suggesting that the overdensity of bright SMGs is less likely due to the source multiplicity., Comment: 19 pages, 17 figures, 5 tables, accepted to A&A

The AGORA Cosmorun (arXiv:2106.09738) is a set of hydrodynamical cosmological zoom-in simulations carried out within the AGORA High-resolution Galaxy Simulations Comparison Project (arXiv:1308.2669,arXiv:1610.03066). These simulations show the formation and evolution of a Milky Way-sized galaxy using eight of the most widely used numerical codes in the community (Art-I, Enzo, Ramses, Changa, Gadget-3, Gear, Gizmo, and Arepo). In this short report, we describe the public release of the raw output data from all of these simulations at z = 8, 7, 6, 5, 4, 3, 2 (plus at z=1, 0 when available), and several metadata files containing the halo centers, virial quantities, and merger trees. The data from even thinner timesteps will be released as soon as the upcoming collaboration papers (VII-IX) are submitted and accepted., Comment: ArXiv Data Release from the AGORA Collaboration. arXiv admin note: text overlap with arXiv:2001.04354

This paper investigates the frequency of transiting planetary systems around metal-polluted white dwarfs using high-cadence photometry from ULTRACAM and ULTRASPEC on the ground, and space-based observations with TESS. Within a sample of 313 metal-polluted white dwarfs with available TESS light curves, two systems known to have irregular transits are blindly recovered by box-least-squares and Lomb-Scargle analyses, with no new detections, yielding a transit fraction of 0.8 (-0.4, +0.6) per cent. Planet detection sensitivities are determined using simulated transit injection and recovery for all light curves, producing upper limit occurrences over radii from dwarf to Kronian planets, with periods from 1 h to 27 d. The dearth of short-period, transiting planets orbiting polluted white dwarfs is consistent with engulfment during the giant phases of stellar evolution, and modestly constrains dynamical re-injection of planets to the shortest orbital periods. Based on simple predictions of transit probability, where (R + Rp)/a ~ 0.01, the findings here are nominally consistent with a model where 100 per cent of polluted white dwarfs have circumstellar debris near the Roche limit; however, the small sample size precludes statistical confidence in this result. Single transits are also ruled out in all light curves using a search for correlated outliers, providing weak constraints on the role of Oort-like comet clouds in white dwarf pollution., Comment: 10 pages, 5 figures and 1 table. Accepted for publication in MNRAS

Measuring the environments of massive galaxies at high redshift is crucial to understanding galaxy evolution and the conditions that gave rise to the distribution of matter we see in the Universe today. While high-$z$ radio galaxies (H$z$RGs) and quasars tend to reside in protocluster-like systems, the environments of their radio-quiet counterparts are relatively unexplored, particularly in the submillimetre, which traces dust-obscured star formation. In this study we search for 850 $\mu$m-selected submillimetre galaxies in the environments of massive ($M_{\star} > 10^{11} M_{\odot}$), radio-quiet ($L_{500 {\rm MHz}} \lesssim 10^{25}$ W Hz$^{-1}$) galaxies at $z \sim 1\text{--}3$ using S2COSMOS data. By constructing number counts in circular regions of radius 1--6 arcmin and comparing with blank-field measurements, we find no significant overdensities of SMGs around massive radio-quiet galaxies at any of these scales, despite being sensitive down to overdensities of $\delta \sim 0.4$. To probe deeper than the catalogue we also examine the distribution of peaks in the SCUBA-2 SNR map, which reveals only tentative signs of any difference in the SMG densities of the radio-quiet galaxy environments compared to the blank field, and only on smaller scales (1$^{\prime}$ radii, corresponding to $\sim0.5$ Mpc) and higher SNR thresholds. We conclude that massive, radio-quiet galaxies at cosmic noon are typically in environments with $\delta\lesssim0.4$, which are either consistent with the blank field or contain only weak overdensities spanning sub-Mpc scales. The contrast between our results and studies of H$z$RGs with similar stellar masses and redshifts implies an intrinsic link between the wide-field environment and radio AGN luminosity at high redshift., Comment: 13 pages, 5 figures. Accepted for publication in MNRAS. Typos corrected, acknowledgements added

We present JWST NIRCam imaging targeting 13 $z\sim3$ infrared-luminous ($L_{\rm IR}\sim5\times10^{12}L_{\odot}$) galaxies from the ALESS survey with uniquely deep, high-resolution (0.08$''$$-$0.16$''$) ALMA 870$\mu$m imaging. The 2.0$-$4.4$\mu$m (observed frame) NIRCam imaging reveals the rest-frame near-infrared stellar emission in these submillimeter-selected galaxies (SMGs) at the same (sub-)kpc resolution as the 870$\mu$m dust continuum. The newly revealed stellar morphologies show striking similarities with the dust continuum morphologies at 870$\mu$m, with the centers and position angles agreeing for most sources, clearly illustrating that the spatial offsets reported previously between the 870$\mu$m and HST morphologies were due to strong differential dust obscuration. The F444W sizes are 78$\pm$21% larger than those measured at 870$\mu$m, in contrast to recent results from hydrodynamical simulations that predict larger 870$\mu$m sizes. We report evidence for significant dust obscuration in F444W for the highest-redshift sources, emphasizing the importance of longer-wavelength MIRI imaging. The majority of the sources show evidence that they are undergoing mergers/interactions, including tidal tails/plumes -- some of which are also detected at 870$\mu$m. We find a clear correlation between NIRCam colors and 870$\mu$m surface brightness on $\sim$1 kpc scales, indicating that the galaxies are primarily red due to dust -- not stellar age -- and we show that the dust structure on $\sim$kpc-scales is broadly similar to that in nearby galaxies. Finally, we find no strong stellar bars in the rest-frame near-infrared, suggesting the extended bar-like features seen at 870$\mu$m are highly obscured and/or gas-dominated structures that are likely early precursors to significant bulge growth., Comment: 26 pages, 10 figures. Submitted to ApJ. Comments welcome

Model parameter inference is a universal problem across science. This challenge is particularly pronounced in developmental biology, where faithful mechanistic descriptions require spatial-stochastic models with numerous parameters, yet quantitative empirical data often lack sufficient granularity due to experimental limitations. Parameterizing such complex models thus necessitates methods that elaborate on classical Bayesian inference by incorporating notions of optimality and goal-orientation through low-dimensional objective functions that quantitatively capture the target behavior of the underlying system. In this study, we contrast two such inference workflows and apply them to biophysics-inspired spatial-stochastic models. Technically, both workflows are simulation-based inference (SBI) methods. The first method leverages a modern deep-learning technique known as sequential neural posterior estimation (SNPE), while the second is based on a classical optimization technique called simulated annealing (SA). We evaluate these workflows by inferring the parameters of two complementary models for the inner cell mass (ICM) lineage differentiation in the blastocyst-stage mouse embryo. This developmental biology system serves as a paradigmatic example of a highly robust and reproducible cell-fate proportioning process that self-organizes under strongly stochastic conditions, such as intrinsic biochemical noise and cell-cell signaling delays. Our results indicate that while both methods largely agree in their predictions, the modern SBI workflow provides substantially richer inferred distributions at an equivalent computational cost. We identify the computational scenarios that favor the modern SBI method over its classical counterpart. Finally, we propose a plausible approach to integrate these two methods, thereby synergistically exploiting their parameter space exploration capabilities., Comment: 48 pages, 17 figures, 1 table

Clinicians spend a significant amount of time reviewing medical images and transcribing their findings regarding patient diagnosis, referral and treatment in text form. Vision-language models (VLMs), which automatically interpret images and summarize their findings as text, have enormous potential to alleviate clinical workloads and increase patient access to high-quality medical care. While foundational models have stirred considerable interest in the medical community, it is unclear whether their general capabilities translate to real-world clinical utility. In this work, we show that foundation VLMs markedly underperform compared to practicing ophthalmologists on specialist tasks crucial to the care of patients with age-related macular degeneration (AMD). To address this, we initially identified the essential capabilities required for image-based clinical decision-making, and then developed a curriculum to selectively train VLMs in these skills. The resulting model, RetinaVLM, can be instructed to write reports that significantly outperform those written by leading foundation medical VLMs in disease staging (F1 score of 0.63 vs. 0.11) and patient referral (0.67 vs. 0.39), and approaches the diagnostic performance of junior ophthalmologists (who achieve 0.77 and 0.78 on the respective tasks). Furthermore, in a reader study involving two senior ophthalmologists with up to 32 years of experience, RetinaVLM's reports were found to be similarly correct (78.6% vs. 82.1%) and complete (both 78.6%) as reports written by junior ophthalmologists with up to 10 years of experience. These results demonstrate that our curriculum-based approach provides a blueprint for specializing generalist foundation medical VLMs to handle real-world clinical tasks., Comment: Submitted to Nature Medicine

Radiation therapy (RT) is one of the most effective treatments for cancer, and its success relies on the accurate delineation of targets. However, target delineation is a comprehensive medical decision that currently relies purely on manual processes by human experts. Manual delineation is time-consuming, laborious, and subject to interobserver variations. Although the advancements in artificial intelligence (AI) techniques have significantly enhanced the auto-contouring of normal tissues, accurate delineation of RT target volumes remains a challenge. In this study, we propose a visual language model-based RT target volume auto-delineation network termed Radformer. The Radformer utilizes a hierarichal vision transformer as the backbone and incorporates large language models to extract text-rich features from clinical data. We introduce a visual language attention module (VLAM) for integrating visual and linguistic features for language-aware visual encoding (LAVE). The Radformer has been evaluated on a dataset comprising 2985 patients with head-and-neck cancer who underwent RT. Metrics, including the Dice similarity coefficient (DSC), intersection over union (IOU), and 95th percentile Hausdorff distance (HD95), were used to evaluate the performance of the model quantitatively. Our results demonstrate that the Radformer has superior segmentation performance compared to other state-of-the-art models, validating its potential for adoption in RT practice.

Besides direct molecular interactions, proteins and nanoparticles embedded in or adsorbed to membranes experience indirect interactions that are mediated by the membranes. These membrane-mediated interactions arise from the membrane curvature induced by the particles and can lead to assemblies of particles that generate highly curved spherical or tubular membranes shapes, but have mainly been quantified for planar or weakly curved membranes. In this article, we systematically investigate the membrane-mediated interactions of arc-shaped particles adsorbed to a variety of tubular and spherical membrane shapes with coarse-grained modelling and simulations. We determine both the pairwise interaction free energy, with includes entropic contributions due to rotational entropy loss at close particle distances, and the pairwise interaction energy without entropic components from particle distributions observed in the simulations. For membrane shapes with small curvature, the membrane-mediated interaction free energies of particle pairs exceed the thermal energy kT and can lead to particle ordering and aggregation. The interactions strongly decrease with increasing curvature of the membrane shape and are minimal for tubular shapes with membrane curvatures close to the particle curvature., Comment: 12 pages, 6 figures

We present a novel forecasting framework for lake water temperature profiles, crucial for managing lake ecosystems and drinking water resources. The General Lake Model (GLM), a one-dimensional process-based model, has been widely used for this purpose, but, similar to many process-based simulation models, it: requires a large number of input variables, many of which are stochastic; presents challenges for uncertainty quantification (UQ); and can exhibit model bias. To address these issues, we propose a Gaussian process (GP) surrogate-based forecasting approach that efficiently handles large, high-dimensional data and accounts for input-dependent variability and systematic GLM bias. We validate the proposed approach and compare it with other forecasting methods, including a climatological model and raw GLM simulations. Our results demonstrate that our bias-corrected GP surrogate (GPBC) can outperform competing approaches in terms of forecast accuracy and UQ up to two weeks into the future., Comment: 34 pages, 17 figures

We present Virgil, a MIRI extremely red object (MERO) detected with the F1000W filter as part of the MIRI Deep Imaging Survey (MIDIS) observations of the Hubble Ultra Deep Field (HUDF). Virgil is a Lyman-$\alpha$ emitter (LAE) at $z_{spec} = 6.6312\pm 0.0019$ (from VLT/MUSE) with a rest-frame UV-to-optical spectral energy distribution (SED) typical of LAEs at similar redshifts. However, MIRI observations reveal an unexpected extremely red color at rest-frame near-infrared wavelengths, $\rm F444W - F1000W = 2.33 \pm 0.06$. Such steep rise in the near-infrared, completely missed without MIRI imaging, is poorly reproduced by models including only stellar populations and hints towards the presence of an Active Galactic Nucleus (AGN). Interestingly, the overall SED shape of Virgil resembles that of the recently discovered population of Little Red Dots (LRDs) but does not meet their compactness criterion: at rest-frame UV-optical wavelengths Virgil's morphology follows a 2D-S\'ersic profile with average index $n = 0.93^{+0.85}_{-0.31}$ and $r_e = 0.43$~pkpc. Only at MIRI wavelengths Virgil is unresolved due to the coarser PSF. We also estimate a bolometric luminosity $L_{\rm bol} = (8.4-11.1)\times 10^{44}\rm~erg~s^{-1}$ and a supermassive black hole mass $M_{\rm BH} = (4-7)\times 10^7\rm ~ M_\odot$ in agreement with recently reported values for LRDs. This discovery demonstrates the crucial importance of deep MIRI surveys to find AGN amongst high-$z$ galaxies that otherwise would be completely missed and raises the question of how common Virgil-like objects could be in the early Universe., Comment: 17 pages, 10 figures, 3 tables. Submitted to ApJ

We present a new family of quantum low-density parity-check codes, which we call radial codes, obtained from the lifted product of a specific subset of classical quasi-cyclic codes. The codes are defined using a pair of integers $(r,s)$ and have parameters $[\![2r^2s,2(r-1)^2,\leq2s]\!]$, with numerical studies suggesting average-case distance linear in $s$. In simulations of circuit-level noise, we observe comparable error suppression to surface codes of similar distance while using approximately five times fewer physical qubits. This is true even when radial codes are decoded using a single-shot approach, which can allow for faster logical clock speeds and reduced decoding complexity. We describe an intuitive visual representation, canonical basis of logical operators and optimal-length stabiliser measurement circuits for these codes, and argue that their error correction capabilities, tunable parameters and small size make them promising candidates for implementation on near-term quantum devices., Comment: 16 pages, 10 figures

A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transverse and longitudinal granularity. The active media are silicon sensors and scintillator tiles readout by SiPMs and the absorbers are a combination of lead and Cu/CuW in the electromagnetic section, and steel in the hadronic section. The shower reconstruction method is based on graph neural networks and it makes use of a dynamic reduction network architecture. It is shown that the algorithm is able to capture and mitigate the main effects that normally hinder the reconstruction of hadronic showers using classical reconstruction methods, by compensating for fluctuations in the multiplicity, energy, and spatial distributions of the shower's constituents. The performance of the algorithm is evaluated using test beam data collected in 2018 prototype of the CMS HGCAL accompanied by a section of the CALICE AHCAL prototype. The capability of the method to mitigate the impact of energy leakage from the calorimeter is also demonstrated., Comment: Prepared for submission to JINST

Mosaic crystals, with their high integrated reflectivities, are widely-employed in spectrometers used to diagnose high energy density systems. X-ray Thomson scattering (XRTS) has emerged as a powerful diagnostic tool of these systems, providing in principle direct access to important properties such as the temperature via detailed balance. However, the measured XRTS spectrum is broadened by the spectrometer instrument function (IF), and without careful consideration of the IF one risks misdiagnosing system conditions. Here, we consider in detail the IF of 40 $\mu$m and 100 $\mu$m mosaic HAPG crystals, and how the broadening varies across the spectrometer in an energy range of 6.7-8.6 keV. Notably, we find a strong asymmetry in the shape of the IF towards higher energies. As an example, we consider the effect of the asymmetry in the IF on the temperature inferred via XRTS for simulated 80 eV CH plasmas, and find that the temperature can be overestimated if an approximate symmetric IF is used. We therefore expect a detailed consideration of the full IF will have an important impact on system properties inferred via XRTS in both forward modelling and model-free approaches., Comment: 19 pages, 13 figures

We present an analysis of the JWST NIRCam and MIRI morphological properties of 80 massive ($\log_{10}(M_\ast[M_{\odot}])$=11.2$\pm$0.1) dusty star-forming galaxies at $z$$=$2.7$^{+1.2}_{-0.7}$, identified as sub-millimetre galaxies (SMGs) by ALMA, that have been observed as part of the JWST PRIMER project. To compare the structure of these massive, active galaxies to more typical star-forming galaxies, we define a sample of 850 field galaxies with matched redshifts and specific star formation rates. We identify 20$\pm$5% of the SMGs as candidate late-stage major mergers, a further 40$\pm$10% as potential minor mergers and 40$\pm$10% which have comparatively undisturbed disk-like morphologies, with no obvious massive neighbours on $\lesssim$20-30kpc (projected) scales. These rates are comparable to those for the field sample and indicate that the majority of the sub-millimetre-detected galaxies are not late-stage major mergers, but have interaction rates similar to the less-active population at $z$$\sim$2-3. Through a multi-wavelength morphological analysis, we establish that SMGs have comparable near-infrared sizes to the less active population, but exhibit lower S\'ersic indices, consistent with bulge-less disks and have more structured morphologies at 2$\mu$m relative to 4$\mu$m. We find evidence for dust reddening as the origin of the morphological differences between the populations, identifying a strong correlation between the F200W$-$F444W pixel colour and the 870$\mu$m surface brightness. We conclude that SMGs and less active galaxies at the same epochs share a common disk-like structure, but the weaker bulge components of the SMGs results in a lower dynamical stability. Consequently, instabilities triggered either secularly or by minor external perturbations result in higher levels of activity (and dust content) in SMGs compared to typical star-forming galaxies. [Abridged], Comment: 29 pages, 13 figures including appendices. Submitted to A&A. Comments welcome

Image quality assessment (IQA) is standard practice in the development stage of novel machine learning algorithms that operate on images. The most commonly used IQA measures have been developed and tested for natural images, but not in the medical setting. Reported inconsistencies arising in medical images are not surprising, as they have different properties than natural images. In this study, we test the applicability of common IQA measures for medical image data by comparing their assessment to manually rated chest X-ray (5 experts) and photoacoustic image data (2 experts). Moreover, we include supplementary studies on grayscale natural images and accelerated brain MRI data. The results of all experiments show a similar outcome in line with previous findings for medical imaging: PSNR and SSIM in the default setting are in the lower range of the result list and HaarPSI outperforms the other tested measures in the overall performance. Also among the top performers in our medical experiments are the full reference measures FSIM, GMSD, LPIPS and MS-SSIM. Generally, the results on natural images yield considerably higher correlations, suggesting that the additional employment of tailored IQA measures for medical imaging algorithms is needed.

Discrete GPU accelerators, while providing massive computing power for supercomputers and data centers, have their separate memory domain. Explicit memory management across device and host domains in programming is tedious and error-prone. To improve programming portability and productivity, Unified Memory (UM) integrates GPU memory into the host virtual memory systems, and provides transparent data migration between them and GPU memory oversubscription. Nevertheless, current UM technologies cause significant performance loss for applications. With AMD GPUs increasingly being integrated into the world's leading supercomputers, it is necessary to understand their Shared Virtual Memory (SVM) and mitigate the performance impacts. In this work, we delve into the SVM design, examine its interactions with applications' data accesses at fine granularity, and quantitatively analyze its performance effects on various applications and identify the performance bottlenecks. Our research reveals that SVM employs an aggressive prefetching strategy for demand paging. This prefetching is efficient when GPU memory is not oversubscribed. However, in tandem with the eviction policy, it causes excessive thrashing and performance degradation for certain applications under oversubscription. We discuss SVM-aware algorithms and SVM design changes to mitigate the performance impacts. To the best of our knowledge, this work is the first in-depth and comprehensive study for SVM technologies., Comment: To be published in ICS '24

The exploration and understanding of Executable and Linkable Format (ELF) objects underpin various critical activities in computer systems, from debugging to reverse engineering. Traditional UNIX tooling like readelf, nm, and objdump have served the community reliably over the years. However, as the complexity and scale of software projects has grown, there arises a need for more intuitive, flexible, and powerful methods to investigate ELF objects. In this paper, we introduce sqlelf, an innovative tool that empowers users to probe ELF objects through the expressive power of SQL. By modeling ELF objects as relational databases, sqlelf offers the following advantages over conventional methods. Our evaluations demonstrate that sqlelf not only provides more nuanced and comprehensive insights into ELF objects but also significantly reduces the effort and time traditionally required for ELF exploration tasks

We present new exclusion bounds obtained at the European X-ray Free Electron Laser facility (EuXFEL) on axion-like particles (ALPs) in the mass range 10^{-3} eV < m_a < 10^{4} eV. Our experiment exploits the Primakoff effect via which photons can, in the presence of a strong external electric field, decay into axions, which then convert back into photons after passing through an opaque wall. While similar searches have been performed previously at a 3^rd generation synchrotron [1], our work demonstrates improved sensitivity, exploiting the higher brightness of X-rays at EuXFEL., Comment: 7 pages, 6 figures

Particle-in-Cell (PIC) method is a powerful plasma simulation tool for investigating high-intensity femtosecond laser-matter interaction. However, its simulation capability at high-density plasmas around the Fermi temperature is considered to be inadequate due, among others, to the necessity of implementing atomic-scale collisions. Here, we performed a one-dimensional with three-velocity space (1D3V) PIC simulation that features the realistic collision frequency around the Fermi temperature and atomic-scale cell size. The results are compared with state-of-the-art experimental results as well as with hydrodynamic simulation. We found that the PIC simulation is capable of simulating the nanoscale dynamics of solid-density plasmas around the Fermi temperature up to $\sim$2~ps driven by a laser pulse at the moderate intensity of $10^{14-15}$~$\mathrm{W/cm^{2}}$, by comparing with the state-of-the-art experimental results. The reliability of the simulation can be further improved in the future by implementing multi-dimensional kinetics and radiation transport.

Femtosecond high-intensity laser pulses at intensities surpassing $10^{14} \,\text{W}/\text{cm}^2$ can generate a diverse range of functional surface nanostructures. Achieving precise control over the production of these functional structures necessitates a thorough understanding of the surface morphology dynamics with nanometer-scale spatial resolution and picosecond-scale temporal resolution. In this study, we show that individual XFEL pulses can elucidate structural changes on surfaces induced by laser-generated plasmas, employing grazing-incidence small-angle x-ray scattering (GISAXS). Using aluminum-coated multilayer samples we can differentiate between ultrafast surface morphology dynamics and subsequent subsurface density dynamics, achieving nanometer-depth sensitivity and subpicosecond temporal resolution. The observed subsurface density dynamics serve to validate advanced simulation models depicting matter under extreme conditions. Our findings promise to unveil novel avenues for laser material nanoprocessing and high-energy-density science., Comment: 11 pages, 5 figures. This is the version of the article before peer review

The formation and evolution of supermassive black holes (SMBHs) remains an open question in the field of modern cosmology. The detection of nanohertz (n-Hz) gravitational waves via pulsar timing arrays (PTAs) in the form of individual events and the stochastic gravitational wave background (SGWB) offers a promising avenue for studying SMBH evolution across cosmic time, with SGWB signal being the immediately detectable signal with the currently accessible telescope sensitivities. By connecting the galaxy properties in the large scale (Gpc scale) cosmological simulation such as \texttt{MICECAT} with the small scale ($\sim$ Mpc scale) galaxy simulations from \texttt{ROMULUS}, we show that different scenarios of galaxy-SMBH evolution with redshift leads to a frequency-dependent spatial anisotropy in the SGWB signal. The presence of slow evolution of the SMBHs in the Universe leads to a pronounced blue anisotropic spectrum of the SGWB. In contrast, if SMBHs grow faster in the Universe in lighter galaxies, the frequency-dependent spatial anisotropy exhibits a more flattened anisotropic spectrum. This additional aspect of the SGWB signal on top of the monopole SGWB signal, can give insight on how the SMBHs form in the high redshift Universe and its interplay with the galaxy formation from future measurements., Comment: 17 pages, 11 figures

We report measurements characterizing the performance of a kinetic inductance detector array designed for a wavelength of 25 microns and very low optical background level suitable for applications such as a far-infrared instrument on a cryogenically cooled space telescope. In a pulse counting mode of operation at low optical flux, the detectors can resolve individual 25-micron photons. In an integrating mode, the detectors remain photon noise limited over more than six orders of magnitude in absorbed power from 70 zW to 200 fW, with a limiting NEP of 4.6 x 10^-20 W/rtHz at 1 Hz. In addition, the detectors are highly stable with flat power spectra under optical load down to 1 mHz. Operational parameters of the detector are determined including the efficiency of conversion of the incident optical power into quasiparticles in the aluminum absorbing element and the quasiparticle self-recombination constant., Comment: 35 pages, 18 figures

In 2018, a fort of a graph was introduced as a non-empty subset of vertices in which no vertex outside of the set has exactly one neighbor in the set. Since then, forts have been used to characterize zero forcing sets, model the zero forcing number as an integer program, and generate lower bounds on the zero forcing number of a Cartesian product. In this article, we investigate the number of minimal forts of a graph, where a fort is minimal if every proper subset is not a fort. In particular, we show that the number of minimal forts of a graph of order at least six is strictly less than Sperner's bound, a famous bound due to Emanuel Sperner (1928) on the size of a collection of subsets where no subset contains another. Then, we derive an explicit formula for the number of minimal forts for several families of graphs, including the path, cycle, and spider graphs. Moreover, we show that the asymptotic growth rate of the number of minimal forts of the spider graph is bounded above by that of the path graph. We conjecture that the asymptotic growth rate of the path graph is extremal over all trees. Finally, we develop methods for constructing minimal forts of graph products using the minimal forts of the original graphs. In the process, we derive explicit formulas and lower bounds on the number of minimal forts for additional families of graphs, such as the wheel, sunlet, and windmill graphs. Most notably, we show that the family of windmill graphs has an exponential number of minimal forts with a maximum asymptotic growth rate of cube root of three, which is the largest asymptotic growth rate we have observed. We conjecture that there exist families of graphs with a larger asymptotic growth rate., Comment: 21 pages, 6 figures, 1 table

The combination of isochoric heating of solids by free electron lasers (FEL) and in situ diagnostics by X-ray Thomson scattering (XRTS) allows for measurements of material properties at warm dense matter (WDM) conditions relevant for astrophysics, inertial confinement fusion, and material science. In the case of metals, the FEL beam pumps energy directly into electrons with the lattice structure of ions being nearly unaffected. This leads to a unique transient state that gives rise to a set of interesting physical effects, which can serve as a reliable testing platform for WDM theories. In this work, we present extensive linear-response time-dependent density functional theory (TDDFT) results for the electronic dynamic structure factor of isochorically heated copper with a face-centered cubic lattice. At ambient conditions, the plasmon is heavily damped due to the presence of $d$-band excitations, and its position is independent of the wavenumber. In contrast, the plasmon feature starts to dominate the excitation spectrum and has a Bohm-Gross type plasmon dispersion for temperatures $T \geq 4~{\rm eV}$, where the quasi-free electrons in the interstitial region are in the WDM regime. In addition, we analyze the thermal changes in the $d$-band excitations and outline the possibility to use future XRTS measurements of isochorically heated copper as a controlled testbed for WDM theories.

The presence of dual active galactic nuclei (AGN) on scales of a few tens of kpc can be used to study merger-induced accretion on supermassive black holes (SMBHs) and offer insights about SMBH mergers, using dual AGNs as merger precursors. In this study, we use the Romulus25 cosmological simulation to investigate the properties and evolution of dual AGNs. We first analyze the properties of AGNs ($L_{bol} > 10^{43} \rm erg/s$) and their neighboring SMBHs (any SMBHs closer than 30 pkpc to an AGN) at $z \leq 2$. This is our underlying population. Subsequently, we applied the luminosity threshold of $L_{bol} > 10^{43} erg/s$ to the neighboring SMBHs thereby identifying dual and multiple AGNs in our simulation. We examined the properties and statistics of dual AGNs in comparison to single AGNs. Our findings indicate an increase in the number of both single and dual AGNs from lower to higher redshifts. All dual AGNs in our sample resulted from major mergers. Compared with the single AGN population, duals are characterized by a lower black hole to halo mass ratio. We found that the properties of dual AGN host halos, including halo mass, stellar mass, star formation rate (SFR), and gas mass, are generally consistent with those of single AGN halos, albeit tending towards the higher end of their respective property ranges. Our analysis uncovered a diverse array of evolutionary patterns among dual AGNs, including rapidly evolving systems, slower ones, and instances where SMBH mergers are ineffective.

Significance: Photoacoustic imaging (PAI) promises to measure spatially-resolved blood oxygen saturation, but suffers from a lack of accurate and robust spectral unmixing methods to deliver on this promise. Accurate blood oxygenation estimation could have important clinical applications, from cancer detection to quantifying inflammation. Aim: This study addresses the inflexibility of existing data-driven methods for estimating blood oxygenation in PAI by introducing a recurrent neural network architecture. Approach: We created 25 simulated training dataset variations to assess neural network performance. We used a long short-term memory network to implement a wavelength-flexible network architecture and proposed the Jensen-Shannon divergence to predict the most suitable training dataset. Results: The network architecture can handle arbitrary input wavelengths and outperforms linear unmixing and the previously proposed learned spectral decolouring method. Small changes in the training data significantly affect the accuracy of our method, but we find that the Jensen-Shannon divergence correlates with the estimation error and is thus suitable for predicting the most appropriate training datasets for any given application. Conclusions: A flexible data-driven network architecture combined with the Jensen-Shannon Divergence to predict the best training data set provides a promising direction that might enable robust data-driven photoacoustic oximetry for clinical use cases., Comment: 37 pages, 7 figures

We present an interpretation of the recent Daniel K. Inouye Solar Telescope (DKIST) observations of propagating wavefronts in the lower solar atmosphere. Using MPS/University of Chicago MHD (MURaM) radiative magnetohydrodynamic simulations spanning solar photosphere, overshoot region, and lower chromosphere, we identify three acoustic-wave source mechanisms, each occurring at a different atmospheric height. We synthesize the DKIST Visible Broadband Imager (VBI) G-band, blue-continuum, and CaIIK signatures of these waves at high spatial and temporal resolution, and conclude that the wavefronts observed by DKIST likely originate from acoustic sources at the top of the solar photosphere overshoot region and in the chromosphere proper. The overall importance of these local sources to the atmospheric energy and momentum budget of the solar atmosphere is unknown, but one of the excitation mechanism identified (upward propagating shock interaction with down-welling chromospheric plasma resulting in acoustic radiation) appears to be an important shock dissipation mechanism. Additionally, the observed wavefronts may prove useful for ultra-local helioseismological inversions and promise to play an important diagnostic role at multiple atmospheric heights., Comment: For associated video (mp4) files see https://drive.google.com/file/d/1vWrXVsaazyk--0WSaFXp_shNrZug0cu7/view?usp=drive_link, https://drive.google.com/file/d/12VL2O2O5QztxUVxyB0HqNeGdnKH-ti2Y/view?usp=drive_link, and https://drive.google.com/file/d/1ARmq-m7UTHofPAuQf-p4_9yooRFaJUe9/view?usp=drive_link

The study of protoplanetary disks has become increasingly important with the Kepler satellite finding that exoplanets are ubiquitous around stars in our galaxy and the discovery of enormous diversity in planetary system architectures and planet properties. High-resolution near-IR and ALMA images show strong evidence for ongoing planet formation in young disks. The JWST MIRI mid-INfrared Disk Survey (MINDS) aims to (1) investigate the chemical inventory in the terrestrial planet-forming zone across stellar spectral type, (2) follow the gas evolution into the disk dispersal stage, and (3) study the structure of protoplanetary and debris disks in the thermal mid-IR. The MINDS survey will thus build a bridge between the chemical inventory of disks and the properties of exoplanets. The survey comprises 52 targets (Herbig Ae stars, T Tauri stars, very low-mass stars and young debris disks). We primarily obtain MIRI/MRS spectra with high S/N (~100-500) covering the complete wavelength range from 4.9 to 27.9 {\mu}m. For a handful of selected targets we also obtain NIRSpec IFU high resolution spectroscopy (2.87-5.27 {\mu}m). We will search for signposts of planet formation in thermal emission of micron-sized dust - information complementary to near-IR scattered light emission from small dust grains and emission from large dust in the submillimeter wavelength domain. We will also study the spatial structure of disks in three key systems that have shown signposts for planet formation, TW Hya and HD 169142 using the MIRI coronagraph at 15.5 {\mu}m and 10.65 {\mu}m respectively and PDS70 using NIRCam imaging in the 1.87 {\mu}m narrow and the 4.8 {\mu}m medium band filter. ..., Comment: accepted for publication in PASP

Diseases are currently managed by grading systems, where patients are stratified by grading systems into stages that indicate patient risk and guide clinical management. However, these broad categories typically lack prognostic value, and proposals for new biomarkers are currently limited to anecdotal observations. In this work, we introduce a deep-learning-based biomarker proposal system for the purpose of accelerating biomarker discovery in age-related macular degeneration (AMD). It works by first training a neural network using self-supervised contrastive learning to discover, without any clinical annotations, features relating to both known and unknown AMD biomarkers present in 46,496 retinal optical coherence tomography (OCT) images. To interpret the discovered biomarkers, we partition the images into 30 subsets, termed clusters, that contain similar features. We then conduct two parallel 1.5-hour semi-structured interviews with two independent teams of retinal specialists that describe each cluster in clinical language. Overall, both teams independently identified clearly distinct characteristics in 27 of 30 clusters, of which 23 were related to AMD. Seven were recognised as known biomarkers already used in established grading systems and 16 depicted biomarker combinations or subtypes that are either not yet used in grading systems, were only recently proposed, or were unknown. Clusters separated incomplete from complete retinal atrophy, intraretinal from subretinal fluid and thick from thin choroids, and in simulation outperformed clinically-used grading systems in prognostic value. Overall, contrastive learning enabled the automatic proposal of AMD biomarkers that go beyond the set used by clinically established grading systems. Ultimately, we envision that equipping clinicians with discovery-oriented deep-learning tools can accelerate discovery of novel prognostic biomarkers.

Membrane-induced interactions have been predicted to be important for the organization of membrane proteins. Measurements of the interactions between two and three membrane deforming objects have revealed their non-additive nature. They are thought to lead to complex many-body effects, however, experimental evidence is lacking to date. We here present an experimental method to measure many-body effects in membrane-mediated interactions using colloidal spheres placed between a deflated giant unilamellar vesicles and a planar substrate. The thus confined colloidal particles cause a large deformation of the membrane while not being physochemically attached to it and interact through it. Two particles are found to attract with a maximum force of 0.2~pN. For three particles, we observe a preference for forming compact equilateral triangles over a linear arrangement. We use numerical energy minimization to establish that the attraction stems from a reduction in the membrane-deformation energy caused by the particles. Confining up to 36 particles, we find a preference for hexagonally close packed clusters. However, with increasing number of particles the order of the confined particles decreases, while at the same time, diffusivity of the particles increases. Our experiments for the first time show that the non-additive nature of membrane-mediated interactions affects the interactions and arrangements and ultimately leads to spherical aggregates with liquid-like order of potential importance for cellular processes.

Using a novel ultrahigh resolution ($\Delta E \sim 0.1\,$eV) setup to measure electronic features in x-ray Thomson scattering (XRTS) experiments at the European XFEL in Germany, we have studied the collective plasmon excitation in aluminium at ambient conditions, which we can measure very accurately even at low momentum transfers. As a result, we can resolve previously reported discrepancies between ab initio time-dependent density functional theory simulations and experimental observations. The demonstrated capability for high-resolution XRTS measurements will be a game changer for the diagnosis of experiments with matter under extreme densities, temperatures, and pressures, and unlock the full potential of state-of-the-art x-ray free electron laser (XFEL) facilities to study planetary interior conditions, to understand inertial confinement fusion applications, and for material science and discovery.

Aluminum monofluoride (AlF) is a suitable molecule for laser cooling and trapping. Such experiments require an extensive spectroscopic characterization of the electronic structure. Two of the theoretically predicted higher lying triplet states of AlF, the counterparts of the well-characterized D$^1\Delta$ and E$^1\Pi$ states, had experimentally not been identified yet. We here report on the characterization of the d$^3\Pi$ ($v=0-6$) and e$^3\Delta$ ($v=0-2$) states, confirming the predicted energetic ordering of these states (J. Chem. Phys. 88 (1988) 5715-5725), as well as of the f$^3\Sigma^+$ ($v=0-2$) state. The transition intensity of the d$^3\Pi, v=3$ $-$ a$^3\Pi, v=3$ band is negligibly small. This band gets its weak, unexpected rotational structure via intensity borrowing from the nearby e$^3\Delta, v=2$ $-$ a$^3\Pi, v=3$ band, made possible via spin-orbit and spin-rotation interaction between the d$^3\Pi$ and e$^3\Delta$ states. This interaction affects the equilibrium rotational constants in both states; their deperturbed values yield equilibrium internuclear distances that are consistent with the observations. We determine the ionization potential of AlF to be 78492(1) cm$^{-1}$ by ionization from the d$^3\Pi$ state.

We report the discovery of Cerberus, an extremely red object detected with the MIRI Deep Imaging Survey (MIDIS) observations in the F1000W filter of the Hubble Ultra Deep Field. The object is detected at $S/N\sim6$, with $\mathrm{F1000W}\sim27$ mag, and undetected in the NIRCam data gathered by the JWST Advanced Deep Extragalactic Survey, JADES, fainter than the 30.0-30.5 mag $5\sigma$ detection limits in individual bands, as well as in the MIDIS F560W ultra-deep data ($\sim$29 mag, $5\sigma$). Analyzing the spectral energy distribution built with low-$S/N$ ($<5$) measurements in individual optical-to-mid-infrared filters and higher $S/N$ ($\gtrsim5$) in stacked NIRCam data, we discuss the possible nature of this red NIRCam-dark source using a battery of codes. We discard the possibility of Cerberus being a Solar System body based on the $<0.016$" proper motion in the 1-year apart JADES and MIDIS observations. A sub-stellar Galactic nature is deemed unlikely, given that the Cerberus' relatively flat NIRCam-to-NIRCam and very red NIRCam-to-MIRI flux ratios are not consistent with any brown dwarf model. The extragalactic nature of Cerberus offers 3 possibilities: (1) A $z\sim0.4$ galaxy with strong emission from polycyclic aromatic hydrocarbons; the very low inferred stellar mass, $\mathrm{M}_\star=10^{5-6}$ M$_\odot$, makes this possibility highly improbable. (2) A dusty galaxy at $z\sim4$ with an inferred stellar mass $\mathrm{M}_\star\sim10^{8}$ M$_\odot$. (3) A galaxy with observational properties similar to those of the reddest little red dots discovered around $z\sim7$, but Cerberus lying at $z\sim15$, with the rest-frame optical dominated by emission from a dusty torus or a dusty starburst., Comment: Accepted for publication in ApJL, results unchanged, manuscript shortened to publish as a letter