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Digital holographic microscopy (DHM) applied to quantitative phase imaging (QPI) has been successfully demonstrated as a powerful label-free method to analyse the optical properties of cells. Spatially multiplexed interferometric microscopy (SMIM) is a DHM technique that implements a common-path interferometric layout in the embodiment of a standard microscope to achieve QPI. More concretely, SMIM introduces three minimal modifications: 1) replaces the broadband illumination of the microscope by a coherent or partially coherent light source, 2) divides the input plane into two or three regions for transmission in parallel of both imaging and reference beams, and 3) includes a one-dimensional diffraction grating or a beam splitter cube for holographic recording. Hence, SMIM is a cost-effective, extremely simple, and highly stable manner of converting a standard bright field microscope into a holographic one. The goal of this contribution is to provide a review of the SMIM approaches implemented using a one-dimensional (1D) diffraction grating, and highlight vast range of capabilities including super-resolved, reflective, transflective, noise-reduced and single-shot slightly off-axis amplitude and phase imaging.

The combination of different imaging modalities into single imaging platforms has a strong potential in biomedical sciences since it permits the analysis of complementary properties of the target sample. Here, we report on an extremely simple, cost-effective, and compact microscope platform for achieving simultaneous fluorescence and quantitative phase imaging modes with the capability of working in a single snapshot. It is based on the use of a single illumination wavelength to both excite the sample fluorescence and provide coherent illumination for phase imaging. After passing the microscope layout, the two imaging paths are separated by using a bandpass filter and the two imaging modes are simultaneously obtained by using two digital cameras. We first present calibration and analysis of both fluorescence and phase imaging modalities working independently and, later on, experimental validation for the proposed common-path dual-mode imaging platform considering static (resolution test targets, fluorescent micro-beads and water-suspended lab-made cultures) as well as dynamic (flowing fluorescent beads, human sperm cells and live specimens from lab-made cultures) samples.

We report on a novel layout providing variable zoom in digital in-line holographic microscopy (VZ-DIHM). The implementation is in virtue of an electrically tunable lens (ETL) which enables to slightly shift the illumination source axial position without mechanical movement of any system component. Magnifications ranging from 15X to 35X are easily achievable using the same layout and resulting in a substantial variation of the total field of view (FOV). The performance of the proposed setup is, first, validated using a resolution test target where the main parameters are analyzed (theoretically and experimentally) and, second, corroborated analyzing biological sample (prostate cancer cells) showing its application to biomedical imaging.

Quantitative phase microscopy (QPM), a technique combining phase imaging and microscopy, enables visualization of the 3D topography in reflective samples, as well as the inner structure or refractive index distribution of transparent and translucent samples. Similar to other imaging modalities, QPM is constrained by the conflict between numerical aperture (NA) and field of view (FOV): an imaging system with a low NA has to be employed to maintain a large FOV. This fact severely limits the resolution in QPM up to being the illumination wavelength. Consequently, finer structures of samples cannot be resolved by using modest NA objectives in QPM. Aimed to that, many approaches, such as oblique illumination, structured illumination, and speckle illumination (just to cite a few), have been proposed to improve the spatial resolution (or the space bandwidth product) in phase microscopy by restricting other degrees of freedom (mostly time). This paper aims to provide an up to date review on the resolution enhancement approaches in QPM, discussing the pros and cons of each technique as well as the confusion on resolution definition claims on QPM and other coherent microscopy methods. Through this survey, we will review the most appealing and useful techniques for superresolution in coherent microscopy, working with and without lenses and with special attention to QPM.

Following the discovery of dimethyl sulfide (CH$_3$SCH$_3$, DMS) signatures in comet 67P/Churyumov-Gerasimenko, we report the first detection of this organosulfur species in the interstellar medium, during the exploration of an ultradeep molecular line survey performed toward the Galactic Center molecular cloud G+0.693-0.027 with the Yebes 40$\,$m and IRAM 30$\,$m telescopes. We derive a molecular column density of $N$ = (2.6 $\pm$ 0.3)$\times$10$^{13}$ cm$^{-2}$, yielding a fractional abundance relative to H$_2$ of $\sim$1.9$\times$10$^{-10}$. This implies that DMS is a factor of $\sim$1.6 times less abundant than its structural isomer CH$_3$CH$_2$SH and $\sim$30 times less abundant than its O-analogue dimethyl ether (CH$_3$OCH$_3$) toward this cloud, in excellent agreement with previous results on various O/S pairs. Furthermore, we find a remarkable resemblance between the relative abundance of DMS/CH$_3$OH in G+0.693-0.027 ($\sim$1.7$\times$10$^{-3}$) and in the comet ($\sim$1.3$\times$10$^{-3}$), further strengthening the connection between the chemical inventory of the interstellar medium and that of the minor bodies of the Solar System. Although the chemistry of DMS beyond Earth is yet to be fully disclosed, this discovery provides conclusive observational evidence on its efficient abiotic production in the interstellar medium, casting doubts about using DMS as a reliable biomarker in exoplanet science., Comment: 15 pages, 4 Figures and 5 Tables, re-submitted to ApJL after addressing the reviewers' comments. The initial submission was on November 26, 2024

We present the point-spread function (PSF) modeling for weak lensing shear measurement using the full six years of the Dark Energy Survey (DES Y6) data. We review the PSF estimation procedure using the PIFF (PSFs In the Full FOV) software package and describe the key improvements made to PIFF and modeling diagnostics since the DES year three (Y3) analysis: (i) use of external Gaia and infrared photometry catalogs to ensure higher purity of the stellar sample used for model fitting, (ii) addition of color-dependent PSF modeling, the first for any weak lensing analysis, and (iii) inclusion of model diagnostics inspecting fourth-order moments, which can bias weak lensing measurements to a similar degree as second-order modeling errors. Through a comprehensive set of diagnostic tests, we demonstrate the improved accuracy of the Y6 models evident in significantly smaller systematic errors than those of the Y3 analysis, in which all $g$ band data were excluded due to insufficiently accurate PSF models. For the Y6 weak lensing analysis, we include $g$ band photometry data in addition to the $riz$ bands, providing a fourth band for photometric redshift estimation. Looking forward to the next generation of wide-field surveys, we describe several ongoing improvements to PIFF, which will be the default PSF modeling software for weak lensing analyses for the Vera C. Rubin Observatory's Legacy Survey of Space and Time., Comment: 33 pages, 24 figures

We describe the photometric data set assembled from the full six years of observations by the Dark Energy Survey (DES) in support of static-sky cosmology analyses. DES Y6 Gold is a curated data set derived from DES Data Release 2 (DR2) that incorporates improved measurement, photometric calibration, object classification and value added information. Y6 Gold comprises nearly $5000~{\rm deg}^2$ of $grizY$ imaging in the south Galactic cap and includes 669 million objects with a depth of $i_{AB} \sim 23.4$ mag at S/N $\sim 10$ for extended objects and a top-of-the-atmosphere photometric uniformity $< 2~{\rm mmag}$. Y6 Gold augments DES DR2 with simultaneous fits to multi-epoch photometry for more robust galaxy shapes, colors, and photometric redshift estimates. Y6 Gold features improved morphological star-galaxy classification with efficiency $98.6\%$ and contamination $0.8\%$ for galaxies with $17.5 < i_{AB} < 22.5$. Additionally, it includes per-object quality information, and accompanying maps of the footprint coverage, masked regions, imaging depth, survey conditions, and astrophysical foregrounds that are used for cosmology analyses. After quality selections, benchmark samples contain 448 million galaxies and 120 million stars. This paper will be complemented by online data access and documentation., Comment: Data products and documentation are publicly available at https://des.ncsa.illinois.edu/releases

In recent years the chemistry of sulfur in the interstellar medium has experienced a renewed interest due to the detection of a large variety of molecules containing sulfur. Here we report the first identification in space of a new S-bearing molecule, thioacetaldehyde (CH3CHS), which is the sulfur counterpart of acetaldehyde (CH3CHO). The astronomical observations are part of QUIJOTE, a Yebes 40m Q band line survey of the cold dense cloud TMC-1. We detected seven individual lines corresponding to A and E components of the four most favorable rotational transitions of CH3CHS covered in the Q band (31.0-50.3 GHz). Assuming a rotational temperature of 9 K, we derive a column density of 9.8e10 cm-2 for CH3CHS, which implies that it is 36 times less abundant than its oxygen counterpart CH3CHO. By comparing the column densities of the O- and S-bearing molecules detected in TMC-1, we find that as molecules increase their degree of hydrogenation, sulfur-bearing molecules become less abundant compared to their oxygen analog. That is, hydrogenation seems to be less favored for S-bearing molecules than for O-bearing ones in cold sources like TMC-1. We explored potential formation pathways to CH3CHS and implemented them into a chemical model, which however underestimates by several orders of magnitude the observed abundance of thioacetaldehyde. Quantum chemical calculations carried out for one of the potential formation pathways, the S + C2H5 reaction, indicate that formation of CH3CHS is only a minor channel in this reaction., Comment: Accepted for publication in A&A Letters

Synthetic source injection (SSI), the insertion of sources into pixel-level on-sky images, is a powerful method for characterizing object detection and measurement in wide-field, astronomical imaging surveys. Within the Dark Energy Survey (DES), SSI plays a critical role in characterizing all necessary algorithms used in converting images to catalogs, and in deriving quantities needed for the cosmology analysis, such as object detection rates, galaxy redshift estimation, galaxy magnification, star-galaxy classification, and photometric performance. We present here a source injection catalog of $146$ million injections spanning the entire 5000 deg$^2$ DES footprint, generated using the Balrog SSI pipeline. Through this sample, we demonstrate that the DES Year 6 (Y6) image processing pipeline provides accurate estimates of the object properties, for both galaxies and stars, at the percent-level, and we highlight specific regimes where the accuracy is reduced. We then show the consistency between SSI and data catalogs, for all galaxy samples developed within the weak lensing and galaxy clustering analyses of DES Y6. The consistency between the two catalogs also extends to their correlations with survey observing properties (seeing, airmass, depth, extinction, etc.). Finally, we highlight a number of applications of this catalog to the DES Y6 cosmology analysis. This dataset is the largest SSI catalog produced at this fidelity and will serve as a key testing ground for exploring the utility of SSI catalogs in upcoming surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time.

We present the Metadetection weak lensing galaxy shape catalogue from the six-year Dark Energy Survey (DES Y6) imaging data. This dataset is the final release from DES, spanning 4422 deg$^2$ of the southern sky. We describe how the catalogue was constructed, including the two new major processing steps, cell-based image coaddition and shear measurements with Metadetection. The DES Y6 Metadetection weak lensing shape catalogue consists of 151,922,791 galaxies detected over riz bands, with an effective number density of $n_{\rm eff}$ =8.22 galaxies per arcmin$^2$ and shape noise of $\sigma_e$ = 0.29. We carry out a suite of validation tests on the catalogue, including testing for PSF leakage, testing for the impact of PSF modeling errors, and testing the correlation of the shear measurements with galaxy, PSF, and survey properties. In addition to demonstrating that our catalogue is robust for weak lensing science, we use the DES Y6 image simulation suite (Mau, Becker et al. 2025) to estimate the overall multiplicative shear bias of our shear measurement pipeline. We find no detectable multiplicative bias at the roughly half-percent level, with m = (3.4 $\pm$ 6.1) x $10^{-3}$, at 3$\sigma$ uncertainty. This is the first time both cell-based coaddition and Metadetection algorithms are applied to observational data, paving the way to the Stage-IV weak lensing surveys., Comment: 30 pages, 22 figures

Late gadolinium enhancement MRI (LGE MRI) is the gold standard for the detection of myocardial scars for post myocardial infarction (MI). LGE MRI requires the injection of a contrast agent, which carries potential side effects and increases scanning time and patient discomfort. To address these issues, we propose a novel framework that combines cardiac motion observed in cine MRI with image texture information to segment the myocardium and scar tissue in the left ventricle. Cardiac motion tracking can be formulated as a full cardiac image cycle registration problem, which can be solved via deep neural networks. Experimental results prove that the proposed method can achieve scar segmentation based on non-contrasted cine images with comparable accuracy to LGE MRI. This demonstrates its potential as an alternative to contrast-enhanced techniques for scar detection., Comment: 5 pages, 2figs, 2tables

The chapter supports educators and postgraduate students in understanding the role of simulation in software engineering research based on the authors' experience. This way, it includes a background positioning simulation-based studies in software engineering research, the proposition of learning objectives for teaching simulation as a research method, and presents our experience when teaching simulation concepts and practice. For educators, it further provides learning objectives when teaching simulation, considering the current state of the art in software engineering research and the necessary guidance and recommended learning activities to achieve these objectives. For students, it drives the learning path for those interested in learning this method but had no opportunity to engage in an entire course on simulation in the context of empirical research.

We consider projective, irreducible, non-singular curves over an algebraically closed field $\k$. A cover $Y \to X$ of such curves corresponds to an extension $\Omega/\Sigma$ of their function fields and yields an isomorphism $\A_{Y} \simeq \A_{X} \otimes_{\Sigma} \Omega$ of their geometric adele rings. The primitive element theorem shows that $\A_{Y}$ is a quotient of $\A_{X}[T]$ by a polynomial. In general, we may look at quotient algebras $\AXp{\p} = \A_{X}[T]/(\p(T))$ where $\p(T) \in \A_{X}[T]$ is monic and separable over $\A_{X}$, and try to characterize the field extensions $\Omega/\Sigma$ lying in $\AXp{\p}$ which arise from covers as above. We achieve this topologically, namely, as those $\Omega$ which embed discretely in $\AXp{\p}$, and in terms of an additive analog of the product formula for global fields, a result which is reminiscent of classical work of Artin-Whaples and Iwasawa. The technical machinery requires studying which topology on $\AXp{\p}$ is natural for this problem. Local compactness no longer holds, but instead we have linear topologies defined by commensurability of $\k$-subspaces which coincide with the restricted direct product topology with respect to integral closures. The content function is given as an index measuring the discrepancy in commensurable subspaces.

We propose an algebraic method for the classification of branched Galois covers of a curve $X$ focused on studying Galois ring extensions of its geometric adele ring $\A_{X}$. As an application, we deal with cyclic covers; namely, we determine when a given cyclic ring extension of $\A_{X}$ comes from a corresponding cover of curves $Y \to X$, which is reminiscent of a Grunwald-Wang problem, and also determine when two covers yield isomorphic ring extensions, which is known in the literature as an equivalence problem. This completely algebraic method permits us to recover ramification, certain analytic data such as rotation numbers, and enumeration formulas for covers.

Let E be a transitive Courant algebroid with scalar product of neutral signature. A generalized almost complex structure \mathcal J on E is a skew-symmetric smooth field of endomorphisms of E which squares to minus the identity. We say that \mathcal J is integrable (or is a generalized complex structure) if the space of sections of its (1,0) bundle is closed under the Dorfman bracket of E. In this paper we determine, under certain natural conditions, the local form of \mathcal J around regular points. This result is analogous to Gualtieri's Darboux theorem for generalized complex structures on manifolds and extends Wang's description of skew-symmetric left-invariant complex structures on compact semisimple Lie groups., Comment: 58 pages

Increasing HPC cluster sizes and large-scale simulations that produce petabytes of data per run, create massive IO and storage challenges for analysis. Deep learning-based techniques, in particular, make use of these amounts of domain data to extract patterns that help build scientific understanding. Here, we demonstrate a streaming workflow in which simulation data is streamed directly to a machine-learning (ML) framework, circumventing the file system bottleneck. Data is transformed in transit, asynchronously to the simulation and the training of the model. With the presented workflow, data operations can be performed in common and easy-to-use programming languages, freeing the application user from adapting the application output routines. As a proof-of-concept we consider a GPU accelerated particle-in-cell (PIConGPU) simulation of the Kelvin- Helmholtz instability (KHI). We employ experience replay to avoid catastrophic forgetting in learning from this non-steady process in a continual manner. We detail challenges addressed while porting and scaling to Frontier exascale system., Comment: 12 pages, 9 figures

We report the first detection in interstellar medium of the 1-cyano propargyl radical, HC$_3$HCN. This species is an isomer of the 3-cyano propargyl radical (CH$_2$C$_3$N), which was recently discovered in TMC-1. The 1-cyano propargyl radical was observed in the cold dark cloud TMC-1 using data from the ongoing QUIJOTE line survey, which is being carried out with the Yebes 40m telescope. A total of seven rotational transitions with multiple hyperfine components were detected in the 31.0-50.4 GHz range. We derived a column density of (2.2$\pm$0.2)$\times$10$^{11}$ cm$^{-2}$ and a rotational temperature of 7$\pm$1\,K. The abundance ratio between HC$_3$HCN and CH$_2$C$_3$N is 1.4. The almost equal abundance of these isomers indicates that the two species may be produced in the same reaction with a similar efficiency, probably in the reaction C + CH$_2$CHCN and perhaps also in the reaction C$_2$ + CH$_3$CN and the dissociative recombination with electrons of CH$_2$C$_3$NH$^+$, Comment: Accepted as a Letter to the Editor in Astronomy & Astrophysics on December 29th 2024

For the 696 trans-Neptunian objects (TNOs) with absolute magnitudes $5.5 < H_r < 8.2$ detected in the Dark Energy Survey (DES), we characterize the relationships between their dynamical state and physical properties -- namely $H_r$, indicating size; colors, indicating surface composition; and flux variation semi-amplitude $A$, indicating asphericity and surface inhomogeneity. We seek ``birth'' physical distributions that can recreate these parameters in every dynamical class. We show that the observed colors of these TNOs are consistent with 2 Gaussian distributions in $griz$ space, ``near-IR bright'' (NIRB) and ``near-IR faint'' (NIRF), presumably an inner and outer birth population, respectively. We find a model in which both the NIRB and NIRF $H_r$ and $A$ distributions are independent of current dynamical states, supporting their assignment as birth populations. All objects are consistent with a common rolling $p(H_r)$, but NIRF objects are significantly more variable. Cold classicals (CCs) are purely NIRF, while hot classical (HC), scattered, and detached TNOs are consistent with $\approx70\%$ NIRB, and resonances' NIRB fractions show significant variation. The NIRB component of the HCs and of some resonances have broader inclination distributions than the NIRFs, i.e. their current dynamics retains information about birth location. We find evidence for radial stratification within the birth NIRB population, in that HC NIRBs are on average redder than detached or scattered NIRBs; a similar effect distinguishes CCs from other NIRFs. We estimate total object counts and masses of each class within our $H_r$ range. These results will strongly constrain models of the outer solar system., Comment: 52 pages, 13 figures, 4 appendices. Abstract abridged. Associated repository: https://github.com/bernardinelli/des_tno_likelihood

Using the Event Horizon Telescope (EHT), the gravitationally lensed rings around the supermassive black holes (SMBHs) in Messier 87 (M87) and Sagittarius A* (Sgr A*) have now been successfully imaged at a resolution under 10 gravitational radii (R$_{\rm g}$ $ = \rm{GM/c^2}$). To expand studies beyond M87 and Sgr A*, we have constructed the Event Horizon and Environs (ETHER) sample, a comprehensive database encompassing approximately 3.15 million SMBH mass estimates, $\sim$ 20,000 Very-Long Baseline Interferometry (VLBI) radio flux densities, and $\sim$ 36,000 hard X-ray flux densities. This database is designed to identify and optimize target selection for the EHT and its upgrades on the ground and in space. We have identified a Gold Sample (GS) of nearby low-luminosity Active Galactic Nuclei (AGNs) within it that are ideal for studying jet bases and potentially imaging black hole shadows. We observed 27 of these AGNs using the EHT from 2022 to 2024, providing an opportunity to resolve and image accretion flows and jets at resolutions of $\leq$ 100 R$_{\rm g}$. Only a few SMBHs have sufficiently high enough flux density to be imaged at scales of $\leq$ 50 R$_{\rm g}$ with the present EHT. Among these are M87, Sgr A*, NGC4594 (Sombrero/M104), NGC4261, and NGC4374 (Messier 84/M84). Of these, NGC4261, Sombrero, and M84 have been observed and/or are scheduled for deep imaging with EHT+ALMA from 2023 to 2025. Sombrero, NGC4261, M84, NGC4278, and NGC5232 are clearly detected in our EHT+ALMA observations in 2022, indicating that the 230 GHz flux density from the accretion flows is significantly high. Ongoing imaging of the ETHER GS will enable measurements of black hole mass and spin, help constrain General Relativity, and enrich our understanding of jet launching and accretion inflows across a broad multi-parameter space, including black hole mass, spin, accretion rate, and orientation., Comment: 9 pages, 6 figures, 1 table, published in Proceedings of the 16th EVN Symposium, Ed. E. Ros, P. Benke, S.A. Dzib, I. Rottmann, & J.A. Zensus, Bonn: Max-Planck-Institut f\"ur Radioastronomie, 2024, pages 75-84, https://cloud.mpifr-bonn.mpg.de/index.php/s/BkX2CC2Xjn2aKR4

Turbulence cascade has been modeled using various methods; the one we have used applies to a more exact representation of turbulence where people use the multifractal representation. The nature of the energy dissipation is usually governed by partial differential equations that have been described, such as Navier-Stokes Equations, although usually in climate modeling, the Kolmogorov turbulence cascading approximation leads towards an isotropic representation. In recent years, Meneveau et al. have proposed to go away from Kolmogorov assumptions and propose multifractal models where we can account for a new anisotropic representation. Our research aims to use Direct Numerical Simulations (DNS) from the JHU Turbulence Database and Large Eddy Simulations (LES) we simulated using OpenFOAM to predict how accurate these simulations are in replicating Meneveau experimental procedures with numerical simulations using the same rigorous mathematical approaches. Modeling turbulence cascading using higher fidelity data will advance the field and produce faster and better remote sensing metrics. We have written computer code to analyze DNS and LES data and study the multifractal nature of energy dissipation. The box-counting method is used to identify the multifractal dimension spectrum of the DNS and LES data in every direction to follow Meneveau work to represent turbulence-cascading effects in the atmosphere better., Comment: 12 pages

Building trust between humans and robots has long interested the robotics community. Various studies have aimed to clarify the factors that influence the development of user trust. In Human-Robot Interaction (HRI) environments, a critical aspect of trust development is the robot's ability to make its behavior understandable. The concept of an eXplainable Autonomous Robot (XAR) addresses this requirement. However, giving a robot self-explanatory abilities is a complex task. Robot behavior includes multiple skills and diverse subsystems. This complexity led to research into a wide range of methods for generating explanations about robot behavior. This paper presents a systematic literature review that analyzes existing strategies for generating explanations in robots and studies the current XAR trends. Results indicate promising advancements in explainability systems. However, these systems are still unable to fully cover the complex behavior of autonomous robots. Furthermore, we also identify a lack of consensus on the theoretical concept of explainability, and the need for a robust methodology to assess explainability methods and tools has been identified., Comment: 14 pages, 12 figures, 10 tables. This paper is a preprint of an article submitted to IEEE Access

Combining gaseous detectors with a high-granularity pixelated charge readout enables experimental applications which otherwise could not be achieved. This includes high-resolution tracking of low-energetic particles, requiring ultra-low material budget, X-ray polarimetry at low energies ($\lessapprox$ 2 keV) or rare-event searches which profit from event selection based on geometrical parameters. In this article, the idea of embedding a pixel ASIC - specifically the Timepix4 - into a micro-pattern gaseous amplification stage is illustrated. Furthermore, the first results of reading out a triple-GEM detector with the Timepix4 (GEMPix4) are shown, including the first X-ray images taken with a Timepix4 utilising Through Silicon Vias (TSVs). Lastly, a new readout concept is presented, called the 'Silicon Readout Board', extending the use of pixel ASICs to read out gaseous detectors to a wider range of HEP applications.

Three-orifice baffles equally spaced along a circular tube are investigated as a means for heat transfer enhancement under net, oscillatory and compound flows. An unprecedented, systematic analysis of the relative orientation of consecutive baffles -- aligned or opposed -- is accomplished to assess the changes induced on the flow structure and their impact on the thermal-hydraulic performance. The results cover the Nusselt number, the net and oscillatory friction factors and the instantaneous velocity fields using PIV in an experimental campaign with a 32 mm tube diameter. The study is conducted in the range of net Reynolds numbers $50 < Re_n < 1000$ and oscillatory Reynolds numbers $0 < Re_{osc}< 750$, for a dimensionless amplitude $x_0/D = 0.5$ and $Pr=65$. In absence of oscillatory flow, opposed baffles advance the transition to turbulence from $Re_n = 100$ to $50$, increasing the net friction factor (40 %) for $Re_n > 50$ and the Nusselt number (maximum of 27 %) for $Re_n < 150$. When an oscillatory flow is applied, augmentations caused by opposed baffles are only observed for $Re_n < 150$ and $Re_{osc} < 150$. Above $Re_n$, $Re_{osc}>150$, opposed baffles are not recommended for the promotion of heat transfer, owing to friction penalties. However, the chaotic mixing and lack of short-circuiting between baffles observed with flow velocimetry over a wide range of operational conditions point out the interest of this configuration to achieve plug flow., Comment: 20 pages, 16 figures

We propose AV-Link, a unified framework for Video-to-Audio and Audio-to-Video generation that leverages the activations of frozen video and audio diffusion models for temporally-aligned cross-modal conditioning. The key to our framework is a Fusion Block that enables bidirectional information exchange between our backbone video and audio diffusion models through a temporally-aligned self attention operation. Unlike prior work that uses feature extractors pretrained for other tasks for the conditioning signal, AV-Link can directly leverage features obtained by the complementary modality in a single framework i.e. video features to generate audio, or audio features to generate video. We extensively evaluate our design choices and demonstrate the ability of our method to achieve synchronized and high-quality audiovisual content, showcasing its potential for applications in immersive media generation. Project Page: snap-research.github.io/AVLink/, Comment: Project Page: snap-research.github.io/AVLink/

Although a good portion of elementary linear algebra concerns itself with matrices over a field such as $\mathbb{R}$ or $\mathbb{C}$, many combinatorial problems naturally surface when we instead work with matrices over a finite field. As some recent work has been done in these areas, we turn our attention to the problem of enumerating the square matrices with entries in $\mathbb{Z}_{p^k}$ that are diagonalizable over $\mathbb{Z}_{p^k}$. This turns out to be significantly more nontrivial than its finite field counterpart due to the presence of zero divisors in $\mathbb{Z}_{p^k}$., Comment: 17 pages, 4 figures, 3 tables, published in Involve, a Journal of Mathematics

A monolithic silicon pixel ASIC prototype, produced in 2024 as part of the Horizon 2020 MONOLITH ERC Advanced project, was tested with a 120 GeV/c pion beam. The ASIC features a matrix of hexagonal pixels with a 100 \mu m pitch, read by low-noise, high-speed front-end electronics built using 130 nm SiGe BiCMOS technology. It includes the PicoAD sensor, which employs a continuous, deep PN junction to generate avalanche gain. Data were taken across power densities from 0.05 to 2.6 W/cm2 and sensor bias voltages from 90 to 180 V. At the highest bias voltage, corresponding to an electron gain of 50, and maximum power density, an efficiency of (99.99 \pm 0.01)% was achieved. The time resolution at this working point was (24.3 \pm 0.2) ps before time-walk correction, improving to (12.1 \pm 0.3) ps after correction.

The James Webb Space Telescope (JWST) has recently discovered a new population of objects at high redshift referred to as `Little Red Dots' (LRDs). Their nature currently remains elusive, despite their surprisingly high inferred number densities. This emerging population of red point-like sources is reshaping our view of the early Universe and may shed light on the formation of high-redshift supermassive black holes. Here we present a spectroscopically confirmed LRD CANUCS-LRD-z8.6 at $z_{\rm spec}=8.6319\pm 0.0005$ hosting an Active Galactic Nucleus (AGN), using JWST data. This source shows the typical spectral shape of an LRD (blue UV and red optical continuum, unresolved in JWST imaging), along with broad H$\beta$ line emission, detection of high-ionization emission lines (CIV, NIV]) and very high electron temperature indicative of the presence of AGN. This is also combined with a very low metallicity ($Z<0.1 Z_\odot$). The presence of all these diverse features in one source makes CANUCS-LRD-z8.6 unique. We show that the inferred black hole mass of CANUCS-LRD-z8.6 ($M_{\rm BH}=1.0^{+0.6}_{-0.4}\times 10^{8}\rm ~M_\odot$) strongly challenges current standard theoretical models and simulations of black hole formation, and forces us to adopt `ad hoc' prescriptions. Indeed if massive seeds, or light seeds with super-Eddington accretion, are considered, the observed BH mass of CANUCS-LRD-z8.6 at $z=8.6$ can be reproduced. Moreover, the black hole is over-massive compared to its host, relative to the local $M_{\rm BH}-M_*$ relations, pointing towards an earlier and faster evolution of the black hole compared to its host galaxy., Comment: 4 main figures; 8 supplementary figures; 5 supplementary tables

This study examines the impact of lifelong learning on the professional lives of employed and unemployed individuals. Lifelong learning is a crucial factor in securing employment or enhancing one's existing career prospects. To achieve this objective, this study proposes the implementation of a multi-criteria decision support system for the evaluation of training courses in accordance with their capacity to enhance the employability of the students. The methodology is delineated in four stages. Firstly, a `working life curve' was defined to provide a quantitative description of an individual's working life. Secondly, an analysis based on K-medoids clustering defined a control group for each individual for comparison. Thirdly, the performance of a course according to each of the four predefined criteria was calculated using a t-test to determine the mean performance value of those who took the course. Ultimately, the unweighted TOPSIS method was used to evaluate the efficacy of the various training courses in relation to the four criteria. This approach effectively addresses the challenge of using extensive datasets within a system while facilitating the application of a multi-criteria unweighted TOPSIS method. The results of the multi-criteria TOPSIS method indicated that training courses related to the professional fields of administration and management, hostel and tourism and community and sociocultural services have positive impact on employability and improving the working conditions of citizens. However, courses that demonstrate the greatest effectiveness in ranking are the least demanded by citizens. The results will help policymakers evaluate the effectiveness of each training course offered by the regional government., Comment: 24 pages, 12 figures

In this study, we investigate the Klein-Gordon-Zakharov system with a focus on identifying multi-soliton solutions. Specifically, for a given number $N$ of solitons, we demonstrate the existence of a multi-soliton solution that asymptotically converges, in the energy space, to the sum of these solitons. Our proof extends and builds upon the previous results in \cite{cote, cotem, IA} concerning the nonlinear Schr\"{o}dinger equation and the generalized Klein-Gordon equation. In contrast to the method used in \cite{cotem} to establish the existence of multi-solitons for the Klein-Gordon equation, where the difficulty arises from the directions imposed by the coercivity property, requiring the identification of eigenfunctions of the coercivity operator to derive new control estimates, the structure of the present system allows for a more refined result. Specifically, the directional constraints can be eliminated by employing orthogonality arguments derived from localization and modulation techniques., Comment: arXiv admin note: text overlap with arXiv:2406.17498

A kinetic model for granular mixtures is considered to study three different non-equilibrium situations. The model is based on the equivalence between a gas of elastic hard spheres subjected to a drag force proportional to the particle velocity and a gas of inelastic hard spheres. As a first problem, the relaxation of the velocity moments to their forms in the homogeneous cooling state (HCS) is studied. Then, taking the HCS as the reference state, the kinetic model is solved by the Chapman-Enskog method, which is conveniently adapted to inelastic collisions. For small spatial gradients, the mass, momentum and heat fluxes of the mixture are determined and exact expressions for the Navier-Stokes transport coefficients are obtained. As a third nonequilibrium problem, the kinetic model is solved exactly in the uniform shear flow (USF) state, where the rheological properties of the mixture are computed in terms of the parameter space of the mixture. In addition to the transport properties, the velocity distribution functions of each species are also explicitly obtained. To assess the reliability of the model, its theoretical predictions are compared with both (approximate) analytical results and computer simulations of the original Boltzmann equation. In general, the comparison shows a reasonable agreement between the two kinetic equations. While the diffusion transport coefficients show excellent agreement with the Boltzmann results, more quantitative differences appear in the case of the shear viscosity coefficient and the heat flux transport coefficients. In the case of the USF, although the model qualitatively captures the shear rate dependence of the rheological properties well, the discrepancies increase with increasing inelasticity in collisions., Comment: 25 pages; 11 figures; to be published in Phys. Fluids

The standard quadratic optimization problem (StQP) consists of minimizing a quadratic form over the standard simplex. Without convexity or concavity of the quadratic form, the StQP is NP-hard. This problem has many relevant real-life applications ranging portfolio optimization to pairwise clustering and replicator dynamics. Sometimes, the data matrix is uncertain. We investigate models where the distribution of the data matrix is known but where both the StQP after realization of the data matrix and the here-and-now problem are indefinite. We test the performance of a chance-constrained epigraphic StQP to the uncertain StQP.

Quantum networks are promising venues for quantum information processing. This motivates the study of the entanglement properties of the particular multipartite quantum states that underpin these structures. In particular, it has been recently shown that when the links are noisy two drastically different behaviors can occur regarding the global entanglement properties of the network. While in certain configurations the network displays genuine multipartite entanglement (GME) for any system size provided the noise level is below a certain threshold, in others GME is washed out if the system size is big enough for any fixed non-zero level of noise. However, this difference has only been established considering the two extreme cases of maximally and minimally connected networks (i.e. complete graphs versus trees, respectively). In this article we investigate this question much more in depth and relate this behavior to the growth of several graph theoretic parameters that measure the connectivity of the graph sequence that codifies the structure of the network as the number of parties increases. The strongest conditions are obtained when considering the degree growth. Our main results are that a sufficiently fast degree growth (i.e. $\Omega(N)$, where $N$ is the size of the network) is sufficient for asymptotic robustness of GME, while if it is sufficiently slow (i.e. $o(\log N)$) then the network becomes asymptotically biseparable. We also present several explicit constructions related to the optimality of these results., Comment: 45 pages

The exponential growth of text-based data in domains such as healthcare, education, and social sciences has outpaced the capacity of traditional qualitative analysis methods, which are time-intensive and prone to subjectivity. Large Language Models (LLMs), powered by advanced generative AI, have emerged as transformative tools capable of automating and enhancing qualitative analysis. This study systematically maps the literature on the use of LLMs for qualitative research, exploring their application contexts, configurations, methodologies, and evaluation metrics. Findings reveal that LLMs are utilized across diverse fields, demonstrating the potential to automate processes traditionally requiring extensive human input. However, challenges such as reliance on prompt engineering, occasional inaccuracies, and contextual limitations remain significant barriers. This research highlights opportunities for integrating LLMs with human expertise, improving model robustness, and refining evaluation methodologies. By synthesizing trends and identifying research gaps, this study aims to guide future innovations in the application of LLMs for qualitative analysis., Comment: 8 pages, includes 1 figures and 3 tables. Submitted to the WSESE 2025 ICSE Workshop

The electron-phonon interaction is one of the most fundamental mechanisms in condensed matter physics. Phonons can induce memory effects in solid-state platforms when localized electronic states interact with lattice vibrations in non-unitary dynamical maps. In this work, we demonstrate how single-mode and structured phonon environments can give rise to non-Markovian dynamics of an individual negatively charged silicon-vacancy center in diamond. Using trace distance as a quantifier via numerical simulations and theoretical calculations, we identify the physical conditions for emerging and understanding non-Markovian behavior in diverse scenarios. Most importantly, we investigate the influence of magnetic fields (longitudinal and transverse), phonon couplings, Fock states, and temperature to understand how these factors influence memory effects in this solid-state device., Comment: 14 pages, 7 figures, 1 table

Software bots, extensively adopted by Open Source Software (OSS) projects, support developers across several activities, from automating predefined tasks to generating code that aids software engineers. However, with the growing prominence of bots, questions have emerged regarding the extension to which they truly assist or hinder software engineers in their routine tasks. To address this, an exploratory survey was conducted with 37 software engineers to gather insights into their views on the use of bots within the software development process. The findings suggest that bots are present across multiple phases of the software development lifecycle, providing daily support to professionals by enhancing productivity and facilitating task automation. Respondents stated that current bots are not sufficiently intelligent and raised new challenges and enhancements to aid bot designers in developing additional functionalities and integrations., Comment: 6 pages, 6 figures, 3 tables

In this paper, we introduce a new technique to study the distribution in residue classes of sets of integers with digit and sum-of-digits restrictions. From our main theorem, we derive a necessary and sufficient condition for integers with missing digits to be uniformly distributed in arithmetic progressions, extending previous results going back to work of Erd\H{o}s, Mauduit and S\'ark\"ozy. Our approach utilizes Markov chains and does not rely on Fourier analysis as many results of this nature do. Our results apply more generally to the class of multiplicatively invariant sets of integers. This class, defined by Glasscock, Moreira and Richter using symbolic dynamics, is an integer analogue to fractal sets and includes all missing digits sets. We address uniform distribution in this setting, partially answering an open question posed by the same authors., Comment: 40 pages

The recent discovery of superconductivity in infinite-layer (IL, ABO$_2$) nickelates has opened a new avenue to deepen the understanding of high-temperature superconductivity. However, progress in this field is slowed by significant challenges in material synthesis and the scarcity of research groups capable of producing high quality superconducting samples. IL nickelates are obtained from a reduction of the perovskite ABO$_3$ phase, typically achieved by annealing using CaH$_2$ as a reducing agent. Here, we present a new method to synthesize superconducting infinite-layer nickelate Pr$_{0.8}$Sr$_{0.2}$NiO$_2$ thin films using an aluminum overlayer deposited by sputtering as a reducing agent. We systematically optimized the aluminum deposition parameters and obtained superconducting samples reduced either in situ or ex situ (after air exposure of the precursor ABO$_3$ films). A comparison of their crystalline quality and transport properties shows that in situ Al reduction enhances the quality of the superconducting Pr$_{0.8}$Sr$_{0.2}$NiO$_2$ thin films, achieving a maximum superconducting transition temperature $T_{c}^{onset}$ of 17 K, in agreement with the optimum value reported for this compound. This simple synthesis route, much more accessible than existing methods, offers better control and reproducibility over the topotactic transformation, opening new opportunities to gain insights into the physics of superconductivity in nickelates.

Examples of algebraic surfaces of general type with maximal Picard number are not abundant in the literature. Moreover, most known examples either possess low invariants, lie near the Noether line $K^2=2\chi-6$ or are somewhat scattered. A notable exception is Persson's sequence of double covers of the projective plane with maximal Picard number, whose invariants converge to the Severi line $K^2=4\chi$. This note is devoted to the construction of infinitely many new sequences of surfaces of general type with maximal Picard number whose invariants converge to the Severi line., Comment: 12 pages, comments are welcome. arXiv admin note: text overlap with arXiv:2306.15241

Methods of Machine and Deep Learning are gradually being integrated into industrial operations, albeit at different speeds for different types of industries. The aerospace and aeronautical industries have recently developed a roadmap for concepts of design assurance and integration of neural network-related technologies in the aeronautical sector. This paper aims to contribute to this paradigm of AI-based certification in the context of supervised learning, by outlining a complete validation pipeline that integrates deep learning, optimization and statistical methods. This pipeline is composed by a directed graphical model of ten steps. Each of these steps is addressed by a merging key concepts from different contributing disciplines (from machine learning or optimization to statistics) and adapting them to an industrial scenario, as well as by developing computationally efficient algorithmic solutions. We illustrate the application of this pipeline in a realistic supervised problem arising in aerostructural design: predicting the likelikood of different stress-related failure modes during different airflight maneuvers based on a (large) set of features characterising the aircraft internal loads and geometric parameters., Comment: 38 pages, 17 figures

We present and analyze two stabilized finite element methods for solving numerically the Poisson--Nernst--Planck equations. The stabilization we consider is carried out by using a shock detector and a discrete graph Laplacian operator for the ion equations, whereas the discrete equation for the electric potential need not be stabilized. Discrete solutions stemmed from the first algorithm preserve both maximum and minimum discrete principles. For the second algorithm, its discrete solutions are conceived so that they hold discrete principles and obey an entropy law provided that an acuteness condition is imposed for meshes. Remarkably the latter is found to be unconditionally stable. We validate our methodology through numerical experiments., Comment: 29 pages, 25 figures

Large scientific institutions, such as the Space Telescope Science Institute, track the usage of their facilities to understand the needs of the research community. Astrophysicists incorporate facility usage data into their scientific publications, embedding this information in plain-text. Traditional automatic search queries prove unreliable for accurate tracking due to the misidentification of facility names in plain-text. As automatic search queries fail, researchers are required to manually classify publications for facility usage, which consumes valuable research time. In this work, we introduce a machine learning classification framework for the automatic identification of facility usage of observation sections in astrophysics publications. Our framework identifies sentences containing telescope mission keywords (e.g., Kepler and TESS) in each publication. Subsequently, the identified sentences are transformed using Term Frequency-Inverse Document Frequency and classified with a Support Vector Machine. The classification framework leverages the context surrounding the identified telescope mission keywords to provide relevant information to the classifier. The framework successfully classifies usage of MAST hosted missions with a 92.9% accuracy. Furthermore, our framework demonstrates robustness when compared to other approaches, considering common metrics and computational complexity. The framework's interpretability makes it adaptable for use across observatories and other scientific facilities worldwide., Comment: 11 pages, 6 figures, 1 table

In the framework of data envelopment analysis (DEA), Tone (2001) introduced the slacks-based measure (SBM) of efficiency, which is a nonradial model that incorporates all the slacks of the evaluated decision-making units (DMUs) into their efficiency scores, unlike classical radial efficiency models. Next, Tone (2002) developed the SBM super-efficiency model in order to differentiate and rank efficient DMUs, whose SBM efficiency scores are always $1$. However, as pointed out by Chen (2013), some interpretation problems arise when the so-called super-efficiency projections are weakly efficient, leading to an overestimation of the SBM super-efficiency score. Moreover, this overestimation is closely related to discontinuity issues when implementing SBM super-efficiency in conjunction with SBM efficiency. Chen (2013) and Chen et al. (2019) treated these problems, but they did not arrive to a fully satisfactory solution. In this paper, we review these papers and propose a new complementary score, called composite SBM, that actually fixes the discontinuity problems by counteracting the overestimation of the SBM super-efficiency score. Moreover, we extend the composite SBM model to different orientations and variable returns to scale, and propose additive versions. Finally, we give examples and state some open problems., Comment: 25 pages, 3 figures

We construct a new family of chance constrained directional models in stochastic data envelopment analysis, generalizing the deterministic directional models and the chance constrained radial models. We prove that chance constrained directional models define the same concept of stochastic efficiency as the one given by chance constrained radial models and, as a particular case, we obtain a stochastic version of the generalized Farrell measure. Finally, we give some examples of application of chance constrained directional models with stochastic and deterministic directions, showing that inefficiency scores obtained with stochastic directions are less or equal than those obtained considering deterministic directions whose values are the means of the stochastic ones., Comment: 15 pages

Quantum Communications is a field that promises advances in cryptography, quantum computing and clock synchronisation, among other potential applications. However, communication based on quantum phenomena requires an extreme level of isolation from external disturbances, making the transmission of quantum signals together with classical ones difficult. A range of techniques has been tested to introduce quantum communications in already deployed optical networks which also carry legacy traffic. This comes with challenges, not only at the physical layer but also at the operations and management layer. To achieve a broad acceptance among network operators, the joint management and operation of quantum and classical resources, compliance with standards, and quality and legal assurance need to be addressed. This article presents a detailed account of solutions to the above issues, deployed and evaluated in the MadQCI (Madrid Quantum Communication Infrastructure) testbed. This network is designed to integrate quantum communications in the telecommunications ecosystem by installing quantum-key-distribution modules from multiple providers in production nodes of two different operators. The modules were connected through an optical-switched network with more than 130 km of deployed optical fibre. The tests were done in compliance with strict service level agreements that protected the legacy traffic of the pre-existing classical network. The goal was to achieve full quantum-classical compatibility at all levels, while limiting the modifications of optical transport and encryption and complying with as many standards as possible. This effort was intended to serve as a blueprint, which can be used as the foundation of large-scale quantum network deployments. To demonstrate the capabilities of MadQCI, end-to-end encryption services were deployed and a variety of use-cases were showcased., Comment: 18 pages

This study presents a comparative analysis between two scientific document classification systems. The first system employs the Scopus journal-based assignment method, adapted to a fractional model, while the second system uses an item-by-item system based on reclassified references according to the origin of the citers. The study's results are divided into three different sections: the first involves comparisons at the Scopus area level, the second examines comparisons at the category level, and the third tests various bibliometric indicators to identify the variations between the two systems. Highlighting the characteristics of the paper level system, it offers a reduction in the number of categories to which each document is assigned, achieving higher values of single-category assignment compared to the All Science Journal Classification (ASJC). When reclassifying areas and categories, the paper level system tends to accentuate differences at the extreme values, increasing the size of the largest categories and reducing that of the smallest ones. Moreover, the paper-by-paper system provides more homogeneous distributions in normalised impacts and adjusts values related to excellence more uniformly.

Modeling the intrinsic alignment (IA) of galaxies poses a challenge to weak lensing analyses. The Dark Energy Survey is expected to be less impacted by IA when limited to blue, star-forming galaxies. The cosmological parameter constraints from this blue cosmic shear sample are stable to IA model choice, unlike passive galaxies in the full DES Y3 sample, the goodness-of-fit is improved and the $\Omega_{m}$ and $S_8$ better agree with the cosmic microwave background. Mitigating IA with sample selection, instead of flexible model choices, can reduce uncertainty in $S_8$ by a factor of 1.5., Comment: Data access available at https://jamiemccullough.github.io/data/blueshear/

As machine learning models evolve, maintaining transparency demands more human-centric explainable AI techniques. Counterfactual explanations, with roots in human reasoning, identify the minimal input changes needed to obtain a given output and, hence, are crucial for supporting decision-making. Despite their importance, the evaluation of these explanations often lacks grounding in user studies and remains fragmented, with existing metrics not fully capturing human perspectives. To address this challenge, we developed a diverse set of 30 counterfactual scenarios and collected ratings across 8 evaluation metrics from 206 respondents. Subsequently, we fine-tuned different Large Language Models (LLMs) to predict average or individual human judgment across these metrics. Our methodology allowed LLMs to achieve an accuracy of up to 63% in zero-shot evaluations and 85% (over a 3-classes prediction) with fine-tuning across all metrics. The fine-tuned models predicting human ratings offer better comparability and scalability in evaluating different counterfactual explanation frameworks., Comment: This paper extends the AAAI-2025 version by including the Appendix