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Food insecurity is widespread among college students in the United States. Food benefits delivered through the CalFresh program, California's version of the federal Supplemental Nutrition Assistance Program (SNAP), can reduce hunger by helping students pay for groceries, but may not reach all eligible students. To date, higher education systems have lacked good estimates of the share of their students who are eligible for CalFresh and the share who actually receive benefits. To address this information gap, the California Policy Lab (CPL) partnered with the California Community College (CCC) Chancellor's Office, the University of California Office of the President (UCOP), the California Department of Social Services (CDSS), and the California Student Aid Commission (CSAC) to build a linked database of student-level administrative data on college enrollment, financial aid, and CalFresh participation. This database covers all students enrolled at CCC or UC campuses from academic years 2010-11 through 2021-22, along with corresponding FAFSA submissions and CalFresh participation. Using these data, researchers are able to measure how many college students are likely eligible for CalFresh, and of those how many participate. This report was updated in August 2024 with updated eligibility statistics that reflect results from a refined simulation of student eligibility for CalFresh. Using the improved simulation, the researchers found that among California Community College students, 20% of students were eligible for CalFresh (an increase from the 16% estimate in the June version of this report), among University of California (UC) undergraduates, 33% were eligible (an increase from 31% in the June report), and among UC graduate students, 7% were eligible (an increase from 6%).

Brown dwarfs are the bridge between low-mass stars and giant planets. One way of shedding light on their dominant formation mechanism is to study them at the earliest stages of their evolution, when they are deeply embedded in their parental clouds. Several works have identified pre- and proto-brown dwarfs candidates using different observational approaches. The aim of this work is to create a database with all the objects classified as very young substellar candidates in the litearature in order to study them in an homogeneous way. We have gathered all the information about very young substellar candidates available in the literature until 2020. We have retrieved their published photometry from the optical to the centimeter regime, and we have written our own codes to derive their bolometric temperatures and luminosities, and their internal luminosities. We have also populated the database with other parameters extracted from the literature, like e.g. the envelope masses, their detection in some molecular species, and presence of outflows. The result of our search is the SUCANES database, containing 174 objects classified as potential very young substellar candidates in the literature. We present an analysis of the main properties of the retrieved objects. Since we have updated the distances to several star forming regions, this has allowed us to reject some candidates based on their internal luminosities. We have also discussed the derived physical parameters and envelope masses for the best substellar candidates isolated in SUCANES. As an example of a scientific exploitation of this database, we present a feasibility study for the detection of radiojets with upcoming facilities: the ngVLA and the SKA interferometers. The SUCANES database is accessible through a Graphical User Interface and it is open to any potential user., Comment: 17 pages, 7 figures

The rapid evolution of digital image manipulation techniques poses significant challenges for content verification, with models such as stable diffusion and mid-journey producing highly realistic, yet synthetic, images that can deceive human perception. This research develops and evaluates convolutional neural networks (CNNs) specifically tailored for the detection of these manipulated images. The study implements a comparative analysis of three progressively complex CNN architectures, assessing their ability to classify and localize manipulations across various facial image modifications. Regularization and optimization techniques were systematically incorporated to improve feature extraction and performance. The results indicate that the proposed models achieve an accuracy of up to 76\% in distinguishing manipulated images from genuine ones, surpassing traditional approaches. This research not only highlights the potential of CNNs in enhancing the robustness of digital media verification tools, but also provides insights into effective architectural adaptations and training strategies for low-computation environments. Future work will build on these findings by extending the architectures to handle more diverse manipulation techniques and integrating multi-modal data for improved detection capabilities.

In the early Universe, neutrinos decouple quickly from the primordial plasma and propagate without further interactions. The impact of free-streaming neutrinos is to create a temporal shift in the gravitational potential that impacts the acoustic waves known as baryon acoustic oscillations (BAOs), resulting in a non-linear spatial shift in the Fourier-space BAO signal. In this work, we make use of and extend upon an existing methodology to measure the phase shift amplitude $\beta_{\phi}$ and apply it to the DESI Data Release 1 (DR1) BAOs with an anisotropic BAO fitting pipeline. We validate the fitting methodology by testing the pipeline with two publicly available fitting codes applied to highly precise cubic box simulations and realistic simulations representative of the DESI DR1 data. We find further study towards the methods used in fitting the BAO signal will be necessary to ensure accurate constraints on $\beta_{\phi}$ in future DESI data releases. Using DESI DR1, we present individual measurements of the anisotropic BAO distortion parameters and the $\beta_{\phi}$ for the different tracers, and additionally a combined fit to $\beta_{\phi}$ resulting in $\beta_{\phi} = 2.7 \pm 1.7$. After including a prior on the distortion parameters from constraints using \textit{Planck} we find $\beta_{\phi} = 2.7^{+0.60}_{-0.67} $ suggesting $\beta_{\phi} > 0$ at 4.3$\sigma$ significance. This result may hint at a phase shift that is not purely sourced from the standard model expectation for $N_{\rm{eff}}$ or could be a upwards statistical fluctuation in the measured $\beta_{\phi}$; this result relaxes in models with additional freedom beyond $\Lambda$CDM.

Challenging neutron-capture cross-section measurements of small cross sections and samples with a very limited number of atoms require high-flux time-of-flight facilities. In turn, such facilities need innovative detection setups that are fast, have low sensitivity to neutrons, can quickly recover from the so-called $\gamma$-flash, and offer the highest possible detection sensitivity. In this paper, we present several steps toward such advanced systems. Specifically, we describe the performance of a high-sensitivity experimental setup at CERN n\_TOF EAR2. It consists of nine sTED detector modules in a compact cylindrical configuration, two conventional used large-volume C$_{6}$D$_{6}$ detectors, and one LaCl$_{3}$(Ce) detector. The performance of these detection systems is compared using $^{93}$Nb($n$,$\gamma$) data. We also developed a detailed \textsc{Geant4} Monte Carlo model of the experimental EAR2 setup, which allows for a better understanding of the detector features, including their efficiency determination. This Monte Carlo model has been used for further optimization, thus leading to a new conceptual design of a $\gamma$ detector array, STAR, based on a deuterated-stilbene crystal array. Finally, the suitability of deuterated-stilbene crystals for the future STAR array is investigaged experimentally utilizing a small stilbene-d12 prototype. The results suggest a similar or superior performance of STAR with respect to other setups based on liquid-scintillators, and allow for additional features such as neutron-gamma discrimination and a higher level of customization capability.

The chemical enrichment in low-ionization nuclear emission-line regions (LINERs) is still an issue with spatial resolution spectroscopic data due to the lack of studies and the uncertainties in the nature of their ionizing source, despite being the most abundant type of active galaxies in the nearby Universe. Considering different scenarios for the ionizing source (hot old stellar populations, active galactic nuclei (AGN) or inefficient accretion disks), we analyze the implications of these assumptions to constrain the chemical content of the gas-phase interstellar medium (ISM). We used a sample of 105 galaxies from Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, whose nuclear central spaxels show LINER-like emission. For each scenario considered, we built a grid of photoionization models (4928 models for each considered ionizing source) which are later used in the open-source code HII-CHI-Mistry, allowing us to estimate chemical abundance ratios such as 12+log(O/H) or log(N/O) and constrain the ionization parameter that characterize the ionized ISM in those galaxies. We obtain that oxygen abundances in the nuclear region of LINER-like galaxies spread over a wide range 8.08 < 12+log(O/H) < 8.89, with a median solar value (in agreement with previous studies) if AGN models are considered. Nevertheless, the derived nitrogen-to-oxygen ratio is much less affected by the assumptions on the ionizing source, and point towards suprasolar values (log(N/O) = -0.69). By comparing the different analyzed scenarios, we show that if hot old stellar populations were responsible of the ionization of the ISM a complex picture (such as outflows and/or inflows scaling with galaxy chemical abundance) would be needed to explain the chemical enrichment history, whereas the assumption of AGN activity is compatible with the standard scenario found in most galaxies., Comment: Revised version after language edition. 24 pages, 13 figures, 9 tables (5 as supplemented material). Accepted for publication in A&A

BabyIAXO is the intermediate stage of the International Axion Observatory (IAXO) to be hosted at DESY. Its primary goal is the detection of solar axions following the axion helioscope technique. Axions are converted into photons in a large magnet that is pointing to the sun. The resulting X-rays are focused by appropriate X-ray optics and detected by sensitive low-background detectors placed at the focal spot. The aim of this article is to provide an accurate quantitative description of the different components (such as the magnet, optics, and X-ray detectors) involved in the detection of axions. Our efforts have focused on developing robust and integrated software tools to model these helioscope components, enabling future assessments of modifications or upgrades to any part of the IAXO axion helioscope and evaluating the potential impact on the experiment's sensitivity. In this manuscript, we demonstrate the application of these tools by presenting a precise signal calculation and response analysis of BabyIAXO's sensitivity to the axion-photon coupling. Though focusing on the Primakoff solar flux component, our virtual helioscope model can be used to test different production mechanisms, allowing for direct comparisons within a unified framework., Comment: 36 pages, 18 figures, 4 tables, Submitted to JHEP

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

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

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

We investigate nontrigonometric forms of Riesz transforms in the context of Schur multipliers. This refines Grothendieck-Haagerup's endpoint criterion with a new condition for the Schatten p-boundedness of Schur multipliers and strengthens Potapov/Sukochev's solution of Arazy's conjecture. We recover as well dimension-free estimates for trigonometric Riesz transforms. Our discrete approach is much simpler than previous harmonic analysis and probabilistic approaches. As an application, we find a very simple proof of recent criteria for Schur multipliers of H\"ormander-Mikhlin and Marcinkiewicz type., Comment: Minor improvements

Context. Small bodies in Earth-like orbits, the Arjunas, are good targets for scientific exploration and mining studies as they enable low-cost missions. The subset of such objects that experience recurrent temporarily captured flyby or orbiter events, also called mini-moon episodes, are among the best ranked in terms of accessibility. Only a handful of objects are known to have engaged in such a dynamical behavior. Finding and characterizing more of them may help to expand scientific and commercial research activities in space over the next few decades. Asteroid 2024 PT5 was found recently and belongs to this group of interesting objects. Aims. Here, we investigate the orbital context of 2024 PT5, and its spectral and rotational properties. Methods. We studied the short-term orbital evolution of 2024 PT5 using direct N-body simulations. We identified its spectral class from the visible reflectance spectrum and used photometric observations to derive its rotational properties. Observational data were obtained with the OSIRIS camera spectrograph at the 10.4 m Gran Telescopio Canarias and the Two-meter Twin Telescope. Results. Asteroid 2024 PT5 experiences recurrent co-orbital engagements and mini-moon events of the temporarily captured flyby type. Its visible spectrum is consistent with that of an Sv-type asteroid or perhaps lunar ejecta. Its rotational period could be less than or close to 1 h. Conclusions. The discovery of 2024 PT5 confirms that temporarily captured flybys are relatively frequent and involve objects larger than a few meters, suitable as accessible targets for scientific research activities and commercial mining ventures in space., Comment: 10 pages, 11 figures, 3 tables, 4 appendices, submitted to A&A Letters on 23 October 2024, currently under review (corrected label in Fig. 3 and caption of Fig. D.1)

Radiology report generation (RRG) aims to create free-text radiology reports from clinical imaging. Grounded radiology report generation (GRRG) extends RRG by including the localisation of individual findings on the image. Currently, there are no manually annotated chest X-ray (CXR) datasets to train GRRG models. In this work, we present a dataset called PadChest-GR (Grounded-Reporting) derived from PadChest aimed at training GRRG models for CXR images. We curate a public bi-lingual dataset of 4,555 CXR studies with grounded reports (3,099 abnormal and 1,456 normal), each containing complete lists of sentences describing individual present (positive) and absent (negative) findings in English and Spanish. In total, PadChest-GR contains 7,037 positive and 3,422 negative finding sentences. Every positive finding sentence is associated with up to two independent sets of bounding boxes labelled by different readers and has categorical labels for finding type, locations, and progression. To the best of our knowledge, PadChest-GR is the first manually curated dataset designed to train GRRG models for understanding and interpreting radiological images and generated text. By including detailed localization and comprehensive annotations of all clinically relevant findings, it provides a valuable resource for developing and evaluating GRRG models from CXR images. PadChest-GR can be downloaded under request from https://bimcv.cipf.es/bimcv-projects/padchest-gr/

Very-high-energy (0.1-100 TeV) gamma-ray emission was observed in HAWC data from the lobes of the microquasar SS 433, making them the first set of astrophysical jets that were resolved at TeV energies. In this work, we update the analysis of SS 433 using 2,565 days of data from the High Altitude Water Cherenkov (HAWC) observatory. Our analysis reports the detection of a point-like source in the east lobe at a significance of $6.6\,\sigma$ and in the west lobe at a significance of $8.2\,\sigma$. For each jet lobe, we localize the gamma-ray emission and identify a best-fit position. The locations are close to the X-ray emission sites "e1" and "w1" for the east and west lobes, respectively. We analyze the spectral energy distributions and find that the energy spectra of the lobes are consistent with a simple power-law $\text{d}N/\text{d}E\propto E^{\alpha}$ with $\alpha = -2.44^{+0.13+0.04}_{-0.12-0.04}$ and $\alpha = -2.35^{+0.12+0.03}_{-0.11-0.03}$ for the east and west lobes, respectively. The maximum energy of photons from the east and west lobes reaches 56 TeV and 123 TeV, respectively. We compare our observations to various models and conclude that the very-high-energy gamma-ray emission can be produced by a population of electrons that were efficiently accelerated.

The sequential execution of actions and their hierarchical structure consisting of different levels of abstraction, provide features that remain unexplored in the task of action recognition. In this study, we present a novel approach to improve action recognition by exploiting the hierarchical organization of actions and by incorporating contextualized textual information, including location and prior actions to reflect the sequential context. To achieve this goal, we introduce a novel transformer architecture tailored for action recognition that utilizes both visual and textual features. Visual features are obtained from RGB and optical flow data, while text embeddings represent contextual information. Furthermore, we define a joint loss function to simultaneously train the model for both coarse and fine-grained action recognition, thereby exploiting the hierarchical nature of actions. To demonstrate the effectiveness of our method, we extend the Toyota Smarthome Untrimmed (TSU) dataset to introduce action hierarchies, introducing the Hierarchical TSU dataset. We also conduct an ablation study to assess the impact of different methods for integrating contextual and hierarchical data on action recognition performance. Results show that the proposed approach outperforms pre-trained SOTA methods when trained with the same hyperparameters. Moreover, they also show a 17.12% improvement in top-1 accuracy over the equivalent fine-grained RGB version when using ground-truth contextual information, and a 5.33% improvement when contextual information is obtained from actual predictions.

We introduce MarDini, a new family of video diffusion models that integrate the advantages of masked auto-regression (MAR) into a unified diffusion model (DM) framework. Here, MAR handles temporal planning, while DM focuses on spatial generation in an asymmetric network design: i) a MAR-based planning model containing most of the parameters generates planning signals for each masked frame using low-resolution input; ii) a lightweight generation model uses these signals to produce high-resolution frames via diffusion de-noising. MarDini's MAR enables video generation conditioned on any number of masked frames at any frame positions: a single model can handle video interpolation (e.g., masking middle frames), image-to-video generation (e.g., masking from the second frame onward), and video expansion (e.g., masking half the frames). The efficient design allocates most of the computational resources to the low-resolution planning model, making computationally expensive but important spatio-temporal attention feasible at scale. MarDini sets a new state-of-the-art for video interpolation; meanwhile, within few inference steps, it efficiently generates videos on par with those of much more expensive advanced image-to-video models., Comment: Project Page: https://mardini-vidgen.github.io

Microquasars are laboratories for the study of jets of relativistic particles produced by accretion onto a spinning black hole. Microquasars are near enough to allow detailed imaging of spatial features across the multiwavelength spectrum. The recent extension of the spatial morphology of a microquasar, SS 433, to TeV gamma rays \cite{abeysekara2018very} localizes the acceleration of electrons at shocks in the jet far from the black hole \cite{hess2024ss433}. Here we report TeV gamma-ray emission from another microquasar, V4641~Sgr, which reveals particle acceleration at similar distances from the black hole as SS~433. Additionally, the gamma-ray spectrum of V4641 is among the hardest TeV spectra observed from any known gamma-ray source and is detected up to 200 TeV. Gamma rays are produced by particles, either electrons or hadrons, of higher energies. Because electrons lose energy more quickly the higher their energy, such a spectrum either very strongly constrains the electron production mechanism or points to the acceleration of high-energy hadrons. This observation suggests that large-scale jets from microquasars could be more common than previously expected and that microquasars could be a significant source of Galactic cosmic rays. high energy gamma-rays also provide unique constraints on the acceleration mechanisms of extra-Galactic cosmic rays postulated to be produced by the supermassive black holes and relativistic jets of quasars. The distance to quasars limits imaging studies due to insufficient angular resolution of gamma-rays and due to attenuation of the highest energy gamma-rays by the extragalactic background light.

Magnetic nanoparticles play a crucial role in different fields such as biomedicine or information and quantum technologies. These applications require nanoparticles with a single, well-defined energy minimum, free of metastable states, and characterized by narrow switching field distributions. Here, we demonstrate that high-transition-temperature nanoSQUIDs can be successfully applied to the characterization of individual nanodiscs hosting magnetic vortices. We present measurements performed under varying temperature and external magnetic field, revealing signatures of ubiquitous, multiple metastable configurations. We also demonstrate that metastability can be reduced by introducing an intended asymmetry. NanoSQUID measurements can be applied to optimize the fabrication of on-demand spin-texture states, such as degenerated vortices or particles with fixed circulation and deterministic and narrow switching probabilities.

We combine JWST/NIRCam and Subaru/MOIRCS dual Pa$\mathrm{\beta}$ + H$\mathrm{\alpha}$ narrow-band imaging to trace the dust attenuation and the star-formation activities of a sample of 43 H$\mathrm{\alpha}$ emitters at the core of one of the most massive and best-studied clusters in formation at the cosmic noon: the Spiderweb protocluster at $\mathrm{z=2.16}$. We find that most H$\mathrm{\alpha}$ emitters display Pa$\mathrm{\beta}$/H$\mathrm{\alpha}$ ratios compatible with Case B recombination conditions, which translates into nebular extinction values ranging at $\mathrm{A_V\approx0-3}$ magnitudes, and dust corrected $\mathrm{Pa\beta}$ star formation rates consistent with coeval main sequence field galaxies at fixed stellar mass ($\mathrm{9.4<\log M_*/M_\odot<11.0}$) during this cosmic epoch. Furthermore, we investigate possible environmental impacts on dust extinction across the protocluster large-scale structure and find no correlation between the dustiness of its members and environmental proxies such as phase-space position, clustercentric radius, or local density. These results support the scenario for which dust production within the main galaxy population of this protocluster is driven by secular star formation activities fueled by smooth gas accretion across its large-scale structure. This downplays the role of gravitational interactions in boosting star formation and dust production within the Spiderweb protocluster, in contrast with observations in higher redshift and less evolved protocluster cores., Comment: 21 pages, 8 figures. Accepted for publication in ApJ

We report the initial result of our Pa$\beta$ narrowband imaging on a protocluster with the JWST Near Infrared Camera (NIRCam). As NIRCam enables deep narrowband imaging of rest-frame NIR lines at $z>1$, we target one of the most studied protoclusters, the Spiderweb protocluster at $z=2.16$, in which previous studies have confirmed more than a hundred member galaxies. The NIRCam F405N narrowband filter covers in Pa$\beta$ line the protocluster redshift given by known protocluster members, allowing the search for new member candidates. The weight-corrected color-magnitude diagram obtained 57 sources showing narrowband excesses, 41 of which satisfy further color selection criteria for limiting the sample to Pa$\beta$ emitter candidates at $z\sim2.16$, and 24 of them do not have H$\alpha$ emitter counterparts. The Pa$\beta$ emitter candidates appear to follow the spatial distribution of known protocluster members; however, follow-up spectroscopic confirmation is required. Only 17 out of 58 known H$\alpha$-emitting cluster members are selected as Pa$\beta$ emitters in the current data, albeit the rest fall out of the narrowband selection owing to their small Pa$\beta$ equivalent widths. We derive Pa$\beta$ luminosity function in the Spiderweb protocluster, showing a normalization density of $\log{\phi^\ast}=-2.53\pm0.15$ at a characteristic Pa$\beta$ luminosity of $\log{L^\ast}=42.33\pm0.17$. Furthermore, we examine the possibility of detecting faint line emitters visible only in the narrow-band image, but find no promising candidates., Comment: 19 pages, 12 figures, 2 tables; Accepted for publication in ApJ

Food insecurity is widespread among college students in the United States. CalFresh food benefits, known federally as the Supplemental Nutrition Assistance Program, or SNAP, can help students in California pay for food, but may not reach all eligible students. To better measure student participation in CalFresh, the California Policy Lab (CPL) partners with the California Community College system (CCC), the University of California Office of the President (UCOP), the California Department of Social Services (CDSS), and the California Student Aid Commission (CSAC). Through this partnership, CPL has created a linked database of student-level administrative data on college enrollment, financial aid, and CalFresh participation that makes this analysis possible. This data point provides estimates of CalFresh participation rates among community college and University of California (UC) students in California. In the academic year 2020-21 (June 2020-May 2021), the first year of the COVID-19 pandemic, 10.6% of CCC students, 12.3% of UC undergraduate students, and 6.3% of UC graduate students participated in CalFresh. While the share of community college students participating in CalFresh increased slightly since 2019-20, the total number of students participating in the program -- approximately 205,000 community college students -- represents a decrease of about 21,000 students from the 2019-20 school year due to overall enrollment declines in the community college system. CalFresh participation rates and counts increased for UC undergraduate and graduate students overall, with over 29,000 undergraduates and nearly 4,000 graduate students participating in CalFresh.

We use the angular cross-correlation between a Luminous Red Galaxy (LRG) sample from the DR9 DESI Legacy Survey and the $Planck$ PR4 CMB lensing maps to constrain the local primordial non-Gaussianity parameter $f_{\rm NL}$ using the scale-dependent galaxy bias effect. The galaxy sample covers $\sim$ 40% of the sky and contains galaxies up to $z \sim 1.4$, and is calibrated with the LRG spectra that have been observed for the DESI Survey Validation. We apply a nonlinear imaging systematics treatment based on neural networks to remove observational effects that could potentially bias the $f_{\rm NL}$ measurement. Our measurement is performed without blinding, but the full analysis pipeline is tested with simulations including systematics. Using the two-point angular cross-correlation between LRG and CMB lensing only ($C_\ell^{\kappa G}$) we find $f_{\rm NL} = 39_{-38}^{+40}$ at 68% confidence level, and our result is robust in terms of systematics and cosmology assumptions. If we combine this information with the autocorrelation of LRG ($C_\ell^{GG}$) applying a $\ell_{\rm min}$ scale cut to limit the impact of systematics, we find $f_{\rm NL} = 24_{-21}^{+20}$ at 68% confidence level. Our results motivate the use of CMB lensing cross-correlations for measuring $f_{\rm NL}$ with future datasets given its stability in terms of observational systematics compared to the angular auto-correlation., Comment: 13 pages, 11 figures, to be submitted to A&A

The main goal of this paper is to give a complete fractal analysis of piecewise smooth (PWS) slow-fast Li\'{e}nard equations. For the analysis, we use the notion of Minkowski dimension of one-dimensional orbits generated by slow relation functions. More precisely, we find all possible values for the Minkowski dimension near PWS slow-fast Hopf points and near bounded balanced crossing canard cycles. We study fractal properties of the unbounded canard cycles using PWS classical Li\'{e}nard equations. We also show how the trivial Minkowski dimension implies the non-existence of limit cycles of crossing type close to Hopf points. This is not true for crossing limit cycles produced by bounded balanced canard cycles, i.e. we find a system undergoing a saddle-node bifurcation of crossing limit cycles and a system without limit cycles (in both cases, the Minkowski dimension is trivial). We also connect the Minkowski dimension with upper bounds for the number of limit cycles produced by bounded canard cycles., Comment: 31 pages, 4 Figures

In this article, we claim that axion-like particles (ALPs) with MeV masses can be produced with semi-relativistic velocities in core-collapse supernovae (SNe), generating a diffuse galactic flux. We show that these ALPs can be detected in neutrino water Cherenkov detectors via $a \, p \rightarrow p \, \gamma$ interactions. Using Super-Kamiokande data, we derive new constraints on the ALP parameter space, excluding a region spanning more than one order of magnitude in the ALP-proton coupling above cooling bounds for ALP masses in the range of $1-80$ MeV and ALP-proton couplings between $6\times10^{-6}-2\times10^{-4}$. We show that the future Hyper-Kamiokande will be able to probe couplings as small as $2\times10^{-6}$, fully closing the allowed region above SN 1987A cooling bounds., Comment: 15 pages, 5 figures

A search for $D^0$ meson decays to the $\pi^+\pi^-e^+e^-$ and $K^+K^-e^+e^-$ final states is reported using a sample of proton-proton collisions collected by the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 6 fb$^{-1}$. The decay $D^0 \rightarrow \pi^+\pi^-e^+e^-$ is observed for the first time when requiring that the two electrons are consistent with coming from the decay of a $\phi$ or $\rho^0/\omega$ meson. The corresponding branching fractions are measured relative to the $D^0 \rightarrow K^-\pi^-[e^+e^-]_{\rho^0/\omega}$ decay, where the two electrons are consistent with coming from the decay of a $\rho^0$ or $\omega$ meson. No evidence is found for the $D^0 \rightarrow K^+K^-e^+e^-$ decay and world-best limits are set on its branching fraction. The results are compared to, and found to be consistent with, the branching fractions of the $D^0 \rightarrow \pi^+\pi^-\mu^+\mu^-$ and $D^0 \rightarrow K^+K^-\mu^+\mu^-$ decays recently measured by LHCb and confirm lepton universality at the current precision., Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://lbfence.cern.ch/alcm/public/analysis/full-details/1611/ (LHCb public pages)

Multiphase flows, characterized by the presence of particles, bubbles, or droplets dispersed within a fluid, are ubiquitous in natural and industrial processes. Studying densely dispersed flows in 4D (3D + time) at very small scales without introducing perturbations is challenging, but crucial to understand their macroscopic behavior. The penetration power of X-rays and the flux provided by advanced X-ray sources, such as synchrotron-radiation facilities, offer an opportunity to address this need. However, current X-ray methods at these facilities require the rotation of the sample to obtain 4D information, thus disturbing the flow. Here, we demonstrate the potential of using X-ray Multi-Projection Imaging (XMPI), a novel technique to temporally resolve any dense particle suspension flows in 4D, while eliminating the need of sample rotation. By acquiring images of a microparticle-seeded flow from multiple viewing directions simultaneously, we can determine their instantaneous three-dimensional positions, both when flowing in a simple liquid and a highly dense and opaque complex fluid (e.g. blood). Along with the recent progress in AI-supported 4D reconstruction from sparse projections, this approach creates new opportunities for high-speed rotation-free 4D microtomography, opening a new spatiotemporal frontier. With XMPI, it is now feasible to track the movement of individual microparticles within dense suspensions, extending even to the chaotic realms of turbulent flows.

We present the results of the second commissioning phase of the short-focal-length area of the Apollon laser facility (located in Saclay, France), which was performed with the main laser beam (F1), scaled to a peak power of 2 PetaWatt. Under the conditions that were tested, this beam delivered on-target pulses of maximum energy up to 45 J and 22 fs duration. Several diagnostics were fielded to assess the performance of the facility. The on-target focal spot and its spatial stability, as well as the secondary sources produced when irradiating solid targets, have all been characterized, with the goal of helping users design future experiments. The laser-target interaction was characterized, as well as emissions of energetic ions, X-ray and neutrons recorded, all showing good laser-to-target coupling efficiency. Moreover, we demonstrated the simultaneous fielding of F1 with the auxiliary 0.5 PW F2 beam of Apollon, enabling dual beam operation. The present commissioning will be followed in 2025 by a further commissioning stage of F1 at the 8 PW level, en route to the final 10 PW goal.

Decoding low-density parity-check codes is critical in many current technologies, such as fifth-generation (5G) wireless networks and satellite communications. The belief propagation algorithm allows for fast decoding due to the low density of these codes. However, there is scope for improvement to this algorithm both in terms of its computational cost when decoding large codes and its error-correcting abilities. Here, we introduce the quantum-enhanced belief propagation (QEBP) algorithm, in which the Quantum Approximate Optimization Algorithm (QAOA) acts as a pre-processing step to belief propagation. We perform exact simulations of syndrome decoding with QAOA, whose result guides the belief propagation algorithm, leading to faster convergence and a lower block error rate (BLER). In addition, through the repetition code, we study the possibility of having shared variational parameters between syndromes and, in this case, code lengths. We obtain a unique pair of variational parameters for level-1 QAOA by optimizing the probability of successful decoding through a transfer matrix method. Then, using these parameters, we compare the scaling of different QAOA post-processing techniques with code length.

Controllable person image generation aims to generate a person image conditioned on reference images, allowing precise control over the person's appearance or pose. However, prior methods often distort fine-grained textural details from the reference image, despite achieving high overall image quality. We attribute these distortions to inadequate attention to corresponding regions in the reference image. To address this, we thereby propose learning flow fields in attention (Leffa), which explicitly guides the target query to attend to the correct reference key in the attention layer during training. Specifically, it is realized via a regularization loss on top of the attention map within a diffusion-based baseline. Our extensive experiments show that Leffa achieves state-of-the-art performance in controlling appearance (virtual try-on) and pose (pose transfer), significantly reducing fine-grained detail distortion while maintaining high image quality. Additionally, we show that our loss is model-agnostic and can be used to improve the performance of other diffusion models., Comment: github: https://github.com/franciszzj/Leffa, demo: https://huggingface.co/spaces/franciszzj/Leffa, model: https://huggingface.co/franciszzj/Leffa

A large, faint nebula was unexpectedly discovered near M31 using narrowband [O III] images. Its apparent size and the lack of a clear counterpart at other wavelengths make it unique and challenging to explain. We aim to determine whether the nebula is extragalactic or located within the Milky Way. This will enable us to constrain its physical properties and assess its nature. To do so, we obtained deep narrowband [O II]3727 and H$\alpha$+[NII] observations with the JAST80 telescope at the Observatorio Astrof\'isico de Javalambre, as well as high-spectral-resolution spectroscopy at four locations within the region of interest using MEGARA at the Gran Telescopio Canarias. We found extended [O II] emission along two near-parallel strands to the [O III], offset by six arcmin. The nebular spectra reveals up to 6 emission lines from [O III]4959,5007, H$\beta$, [N II]6583, and [S II]6716,6731. Their receding velocities are above $-$40 km s$^{-1}$, far from the systemic velocity of M31 ($-$300 km s$^{-1}$). The fluxes and velocities are consistent for the same lines across different regions of the nebula. The nebular properties suggest a location within the Milky Way rather than being physically associated with M31. The most likely scenario is a resolved ionization structure in a Galactic nebula with a separation between [O II] and [O III] of a few parsecs. The observed receding velocities would be unprecedented for an object physically linked to M31 but are common for nearby gas filaments. Their consistency across the nebula would also be unusual if it were larger than a kiloparsec. The analysis of the emission-line ratios, line widths, and morphology suggests the possibility of it being an interstellar gas filament with an additional source of ionization to explain the [O III] emission. However, the complex properties of this object call for further observations to confirm its nature., Comment: 13 pages, 6 figures. Submitted to Astronomy & Astrophysics

While formal models of concurrency tend to focus on synchronous communication, asynchronous communication is relevant in practice. In this paper, we will discuss asynchronous communication in the context of session-based concurrency, the model of computation in which session types specify the structure of the two-party protocols implemented by the channels of a communicating process. We overview recent work on addressing the challenge of ensuring the deadlock-freedom property for message-passing processes that communicate asynchronously in cyclic process networks governed by session types. We offer a gradual presentation of three typed process frameworks and outline how they may be used to guarantee deadlock freedom for a concurrent functional language with sessions., Comment: In Proceedings ICE 2024, arXiv:2412.07570

The main focus of this paper is to show that the gluing of formal schemes is also a formal scheme. The algebraic approach established here also leads us to conclude when the gluing of $k$-formal schemes is a $k$-formal scheme. In addition, we derive that the gluing of formal schemes is always singular, regardless of whether we know the structure of the schemes involved.

Photon-subtracted two-mode squeezed vacuum states, a significant quantum resource, exhibit intricate correlations and unique quantum properties. In this work, we propose a theoretical yet experimentally feasible model to engineer these states using a waveguide trimer. Our study uncovers distinct characteristics of the photon-subtracted state depending on whether an even or odd number of photons is extracted, shedding light on the subtle relationship between quantum state manipulation and the parity of the number of subtracted photons. Furthermore, our integrated device facilitates the generation of multiphoton states with tunable correlations, offering significant potential for applications in quantum-enhanced technologies.

In recent years, graphene Field-Effect-Transistors (GFETs) have demonstrated an outstanding potential for Terahertz (THz) photodetection due to their fast response and high-sensitivity. Such features are essential to enable emerging THz applications, including 6G wireless communications, quantum information, bioimaging and security. However, the overall performance of these photodetectors may be utterly compromised by the impact of internal resistances presented in the device, so-called access or parasitic resistances. In this work, we provide a detailed study of the influence of internal device resistances in the photoresponse of high-mobility dual-gate GFET detectors. Such dual-gate architectures allow us to fine tune (decrease) the internal resistance of the device by an order of magnitude and consequently demonstrate an improved responsivity and noise-equivalent-power values of the photodetector, respectively. Our results can be well understood by a series resistance model, as shown by the excellent agreement found between the experimental data and theoretical calculations. These findings are therefore relevant to understand and improve the overall performance of existing high-mobility graphene photodetectors.

The quasi-projective dimension and quasi-injective dimension are recently introduced homological invariants that generalize the classical notions of projective dimension and injective dimension, respectively. For a local ring $R$ and finitely generated $R$-modules $M$ and $N$, we provide conditions involving quasi-homological dimensions where the equality $\sup \lbrace i\geq 0: \operatorname{Ext}_R^i(M,N)\not=0 \rbrace =\operatorname{depth} R-\operatorname{depth} M$, which we call Ischebeck's formula, holds. One of the results in this direction generalizes a well-known result of Ischebeck concerning modules of finite injective dimension, considering the quasi-injective dimension. On the other hand, we establish an inequality relating the quasi-projective dimension of a finitely generated module to its grade and introduce the concept of a quasi-perfect module as a natural generalization of a perfect module. We prove several results for this new concept similar to the classical results. Additionally, we provide a formula for the grade of finitely generated modules with finite quasi-injective dimension over a local ring, as well as grade inequalities for modules of finite quasi-projective dimension. In our study, Cohen-Macaulayness criteria are also obtained., Comment: 20 pages, comments and suggestions are welcome

Photonic integrated circuits (PICs) are crucial for advancing optical communications, promising substantial gains in data transmission speed, bandwidth, and energy efficiency compared to conventional electronics. Telecom-wavelength photodetectors, operating near 1550 nm, are indispensable in PICs, where they enable the sensitive and low-noise conversion of optical signals to electrical signals for efficient data processing. While silicon is ideal for passive optical components, its limited absorption in the optical telecommunication range (1260-1625 nm) typically necessitates integrating an alternative material, such as germanium, for photodetection - a process that introduces significant fabrication challenges. Here, we present a high-performance, all-silicon photodetector, grating- and waveguide-coupled, which operates at room temperature within the optical telecom C band. By introducing deep-level impurities into silicon at concentrations close to the solid-solubility limit, we enable efficient sub-bandgap absorption without compromising recombination carrier lifetimes and mobilities. This detector achieves a responsivity of 0.56 A/W, a quantum efficiency of 44.8%, a bandwidth of 5.9 GHz, and a noise-equivalent power of 4.2E-10 W/(Hz)1/2 at 1550 nm, fulfilling requirements for telecom applications. Our approach provides a scalable and cost-effective solution for the monolithic integration of telecom-wavelength photodetectors into silicon-based PICs, advancing the development of compact photonic systems for modern communication infrastructures., Comment: 19 pages, 3 figures

The use of synthetic images in medical imaging Artificial Intelligence (AI) solutions has been shown to be beneficial in addressing the limited availability of diverse, unbiased, and representative data. Despite the extensive use of synthetic image generation methods, controlling the semantics variability and context details remains challenging, limiting their effectiveness in producing diverse and representative medical image datasets. In this work, we introduce a scalable semantic and context-conditioned generative model, coined CSG (Context-Semantic Guidance). This dual conditioning approach allows for comprehensive control over both structure and appearance, advancing the synthesis of realistic and diverse ultrasound images. We demonstrate the ability of CSG to generate findings (pathological anomalies) in musculoskeletal (MSK) ultrasound images. Moreover, we test the quality of the synthetic images using a three-fold validation protocol. The results show that the synthetic images generated by CSG improve the performance of semantic segmentation models, exhibit enhanced similarity to real images compared to the baseline methods, and are undistinguishable from real images according to a Turing test. Furthermore, we demonstrate an extension of the CSG that allows enhancing the variability space of images by synthetically generating augmentations of anatomical geometries and textures.

As the data resources grow, providing recommendations that best meet the demands has become a vital requirement in business and life to overcome the information overload problem. However, building a system suggesting relevant recommendations has always been a point of debate. One of the most cost-efficient techniques in terms of producing relevant recommendations at a low complexity is Product Quantization (PQ). PQ approaches have continued developing in recent years. This system's crucial challenge is improving product quantization performance in terms of recall measures without compromising its complexity. This makes the algorithm suitable for problems that require a greater number of potentially relevant items without disregarding others, at high-speed and low-cost to keep up with traffic. This is the case of online shops where the recommendations for the purpose are important, although customers can be susceptible to scoping other products. This research proposes a fuzzy approach to perform norm-based product quantization. Type-2 Fuzzy sets (T2FSs) define the codebook allowing sub-vectors (T2FSs) to be associated with more than one element of the codebook, and next, its norm calculus is resolved by means of integration. Our method finesses the recall measure up, making the algorithm suitable for problems that require querying at most possible potential relevant items without disregarding others. The proposed method outperforms all PQ approaches such as NEQ, PQ, and RQ up to +6%, +5%, and +8% by achieving a recall of 94%, 69%, 59% in Netflix, Audio, Cifar60k datasets, respectively. More and over, computing time and complexity nearly equals the most computationally efficient existing PQ method in the state-of-the-art.

This work investigates a dynamical system functioning as a nonsmooth adaptation of the continuous Newton method, aimed at minimizing the sum of a primal lower-regular and a locally Lipschitz function, both potentially nonsmooth. The classical Newton method's second-order information is extended by incorporating the graphical derivative of a locally Lipschitz mapping. Specifically, we analyze the existence and uniqueness of solutions, along with the asymptotic behavior of the system's trajectories. Conditions for convergence and respective convergence rates are established under two distinct scenarios: strong metric subregularity and satisfaction of the Kurdyka-Lojasiewicz inequality.

We analyzed the 7.92$\times 10^{11}$ cosmic-ray-induced muon events collected by the IceCube Neutrino Observatory from May 13, 2011, when the fully constructed experiment started to take data, to May 12, 2023. This dataset provides an up-to-date cosmic-ray arrival direction distribution in the Southern Hemisphere with unprecedented statistical accuracy covering more than a full period length of a solar cycle. Improvements in Monte Carlo event simulation and better handling of year-to-year differences in data processing significantly reduce systematic uncertainties below the level of statistical fluctuations compared to the previously published results. We confirm the observation of a change in the angular structure of the cosmic-ray anisotropy between 10 TeV and 1 PeV, more specifically in the 100-300 TeV energy range.

The increasing transition of human-robot interaction (HRI) context from controlled settings to dynamic, real-world public environments calls for enhanced adaptability in robotic systems. This can go beyond algorithmic navigation or traditional HRI strategies in structured settings, requiring the ability to navigate complex public urban systems containing multifaceted dynamics and various socio-technical needs. Therefore, our proposed workshop seeks to extend the boundaries of adaptive HRI research beyond predictable, semi-structured contexts and highlight opportunities for adaptable robot interactions in urban public environments. This half-day workshop aims to explore design opportunities and challenges in creating contextually-adaptive HRI within these spaces and establish a network of interested parties within the OzCHI research community. By fostering ongoing discussions, sharing of insights, and collaborations, we aim to catalyse future research that empowers robots to navigate the inherent uncertainties and complexities of real-world public interactions.

One of the strategies to detect the pose and shape of unknown objects is their geometric modeling, consisting on fitting known geometric entities. Classical geometric modeling fits simple shapes such as spheres or cylinders, but often those don't cover the variety of shapes that can be encountered. For those situations, one solution is the use of superquadrics, which can adapt to a wider variety of shapes. One of the limitations of superquadrics is that they cannot model objects with holes, such as those with handles. This work aims to fit supersurfaces of degree four, in particular supertoroids, to objects with a single hole. Following the results of superquadrics, simple expressions for the major and minor radial distances are derived, which lead to the fitting of the intrinsic and extrinsic parameters of the supertoroid. The differential geometry of the surface is also studied as a function of these parameters. The result is a supergeometric modeling that can be used for symmetric objects with and without holes with a simple distance function for the fitting. The proposed algorithm expands considerably the amount of shapes that can be targeted for geometric modeling.

Large language models (LLMs) have shown impressive capabilities in generating program code, opening exciting opportunities for applying program synthesis to games. In this work, we explore the potential of LLMs to directly synthesize usable code for a wide range of gaming applications, focusing on two programming languages, Python and Java. We use an evolutionary hill-climbing algorithm, where the mutations and seeds of the initial programs are controlled by LLMs. For Python, the framework covers various game-related tasks, including five miniature versions of Atari games, ten levels of Baba is You, an environment inspired by Asteroids, and a maze generation task. For Java, the framework contains 12 games from the TAG tabletop games framework. Across 29 tasks, we evaluated 12 language models for Python and 8 for Java. Our findings suggest that the performance of LLMs depends more on the task than on model size. While larger models generate more executable programs, these do not always result in higher-quality solutions but are much more expensive. No model has a clear advantage, although on any specific task, one model may be better. Trying many models on a problem and using the best results across them is more reliable than using just one., Comment: Submitted to Transactions on Games Special Issue on Large Language Models and Games

We introduce Best-of-N (BoN) Jailbreaking, a simple black-box algorithm that jailbreaks frontier AI systems across modalities. BoN Jailbreaking works by repeatedly sampling variations of a prompt with a combination of augmentations - such as random shuffling or capitalization for textual prompts - until a harmful response is elicited. We find that BoN Jailbreaking achieves high attack success rates (ASRs) on closed-source language models, such as 89% on GPT-4o and 78% on Claude 3.5 Sonnet when sampling 10,000 augmented prompts. Further, it is similarly effective at circumventing state-of-the-art open-source defenses like circuit breakers. BoN also seamlessly extends to other modalities: it jailbreaks vision language models (VLMs) such as GPT-4o and audio language models (ALMs) like Gemini 1.5 Pro, using modality-specific augmentations. BoN reliably improves when we sample more augmented prompts. Across all modalities, ASR, as a function of the number of samples (N), empirically follows power-law-like behavior for many orders of magnitude. BoN Jailbreaking can also be composed with other black-box algorithms for even more effective attacks - combining BoN with an optimized prefix attack achieves up to a 35% increase in ASR. Overall, our work indicates that, despite their capability, language models are sensitive to seemingly innocuous changes to inputs, which attackers can exploit across modalities.

The interplay between ion beam modification techniques in the MeV range and the controlled generation of negatively charged nitrogen-vacancy (NV-) centers in nitrogen-doped synthetic diamond crystals is explored. An experimental approach employing both light (H+) and heavy (Br+6) ions was followed to assess their respective impacts on the creation of NV- centers, using different ion energies or fluences to generate varying amounts of vacancies. Photoluminescence spectroscopy was applied to characterize NV- and neutral NV0 centers. Initially, no NV centers were detected post-irradiation, despite the presence of substitutional nitrogen and vacancies. However, after annealing at 800C (and in some cases at 900C), most samples exhibited a high density of NV0 and especially NV- centers. This demonstrates that thermal treatment is essential for vacancy-nitrogen recombination and NV- formation, often through electron capture from nearby nitrogen atoms. Notably, we achieved high NV- densities without graphitization, which is essential for preserving the material's properties for quantum applications. This study underscores and quantifies the effectiveness of MeV-range ions in controlling vacancy distributions and highlights their potential for optimizing NV- center formation to enhance the sensitivity of diamond-based quantum magnetic sensors., Comment: 21 pages, 10 figures, 3 tables

Since the influential work of ten Wolde, Ruiz-Montero, and Frenkel [Phys. Rev. Lett. 75, 2714 (1995)], crystal nucleation from a Lennard-Jones fluid has been regarded as a paradigmatic example of metastable crystal ordering at the surface of a critical nucleus. We apply seven commonly used local structure detection algorithms to characterize crystal nuclei obtained from transition path sampling simulations. The polymorph composition of these nuclei varies significantly depending on the algorithm used. Our results indicate that one should be very careful when characterizing the local structure near solid-solid and solid-fluid interfaces. Particles near such interfaces exhibit a local structure distinct from that of bulk fluid or bulk crystal phases. We argue that incorporating outlier detection into the local structure detection method is beneficial, leading to greater confidence in the classification results. Interestingly, the bcc coating nearly disappears when adopting a machine learning method with outlier detection.

This letter presents a spatial filter based on saturated absorption in gas as a replacement for the solid pinhole in a lens-pinhole-lens filtering system. We show that an ultraviolet laser pulse focused through ozone will have its spatial profile cleaned if its peak fluence rises above the ozone saturation fluence. Specifically, we demonstrate that a 5 ns 266 nm beam with 4.2 mJ of initial energy can be effectively cleaned by focusing through a 1.4% ozone-oxygen mixture, with about 76% of the main beam energy transmitted and 89% of the side lobe energy absorbed. This process can be adapted to other gases and laser wavelengths, providing alignment-insensitive and damage-resistant pinholes for high-repetition-rate high-energy lasers.

The cross-correlation of cosmic voids with the lensing convergence ($\kappa$) map of the Cosmic Microwave Background (CMB) fluctuations provides a powerful tool to refine our understanding of the cosmological model. However, several studies have reported a moderate tension between the lensing imprint of cosmic voids on the observed CMB and the simulated $\mathrm{\Lambda}$CDM signal. To address this "lensing-is-low" tension and to obtain new, precise measurements, we exploit the large DESI Legacy Survey Luminous Red Galaxy (LRG) dataset, covering approximately 19,500 $\deg^2$ of the sky and including about 10 million LRGs at $z < 1.05$. Our $\mathrm{\Lambda}$CDM template was created using the Buzzard mocks, which we specifically calibrated to match the clustering properties of the observed galaxy sample by exploiting more than one million DESI spectra. We identified our catalogs of 3D voids in the range $0.35 < z < 0.95$, dividing the sample into bins according to the redshift and $\lambda_\mathrm{v}$ values of the voids. We report a 14$\sigma$ detection of the lensing signal, with $A_\kappa = 1.016 \pm 0.054$, which increases to 17$\sigma$ when considering the void-in-void ($A_\kappa = 0.944 \pm 0.064$) and the void-in-cloud ($A_\kappa = 0.975 \pm 0.060$) populations individually, the highest detection significance for studies of this kind. We observe a full agreement between the observations and $\mathrm{\Lambda}$CDM predictions across all redshift bins, sky regions, and void populations considered. In addition to these findings, our analysis highlights the importance of matching sparseness and redshift error distributions between mocks and observations, as well as the role of $\lambda_\mathrm{v}$ in enhancing the signal-to-noise ratio., Comment: 19 pages, 13 figures