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One of the most fascinating aspects of quantum networks is their capability to distribute entanglement as a nonlocal communication resource. In a first step, this requires network-ready devices that can generate and store entangled states. Another crucial step, however, is to develop measurement techniques that allow for entanglement detection. Demonstrations for different platforms suffer from being either not complete, or destructive, or local. Here we demonstrate a complete and nondestructive measurement scheme that always projects any initial state of two spatially separated network nodes onto a maximally entangled state. Each node consists of an atom trapped inside an optical resonator from which two photons are successively reflected. Polarisation measurements on the photons discriminate between the four maximally entangled states. Remarkably, such states are not destroyed by our measurement. In the future, our technique might serve to probe the decay of entanglement and to stabilise it against dephasing via repeated measurements.

We present the framework for measuring angular power spectra in the Euclid mission. The observables in galaxy surveys, such as galaxy clustering and cosmic shear, are not continuous fields, but discrete sets of data, obtained only at the positions of galaxies. We show how to compute the angular power spectra of such discrete data sets, without treating observations as maps of an underlying continuous field that is overlaid with a noise component. This formalism allows us to compute exact theoretical expectations for our measured spectra, under a number of assumptions that we track explicitly. In particular, we obtain exact expressions for the additive biases ("shot noise") in angular galaxy clustering and cosmic shear. For efficient practical computations, we introduce a spin-weighted spherical convolution with a well-defined convolution theorem, which allows us to apply exact theoretical predictions to finite-resolution maps, including HEALPix. When validating our methodology, we find that our measurements are biased by less than 1% of their statistical uncertainty in simulations of Euclid's first data release., Comment: 27 pages, 12 figures. Submitted to A&A. Code available at https://github.com/heracles-ec/heracles

Speech dysfluency modeling is the core module for spoken language learning, and speech therapy. However, there are three challenges. First, current state-of-the-art solutions suffer from poor scalability. Second, there is a lack of a large-scale dysfluency corpus. Third, there is not an effective learning framework. In this paper, we propose \textit{SSDM: Scalable Speech Dysfluency Modeling}, which (1) adopts articulatory gestures as scalable forced alignment; (2) introduces connectionist subsequence aligner (CSA) to achieve dysfluency alignment; (3) introduces a large-scale simulated dysfluency corpus called Libri-Dys; and (4) develops an end-to-end system by leveraging the power of large language models (LLMs). We expect SSDM to serve as a standard in the area of dysfluency modeling. Demo is available at \url{https://eureka235.github.io}.

We study the impact of forbidding short cycles to the edge density of $k$-planar graphs; a $k$-planar graph is one that can be drawn in the plane with at most $k$ crossings per edge. Specifically, we consider three settings, according to which the forbidden substructures are $3$-cycles, $4$-cycles or both of them (i.e., girth $\ge 5$). For all three settings and all $k\in\{1,2,3\}$, we present lower and upper bounds on the maximum number of edges in any $k$-planar graph on $n$ vertices. Our bounds are of the form $c\,n$, for some explicit constant $c$ that depends on $k$ and on the setting. For general $k \geq 4$ our bounds are of the form $c\sqrt{k}n$, for some explicit constant $c$. These results are obtained by leveraging different techniques, such as the discharging method, the recently introduced density formula for non-planar graphs, and new upper bounds for the crossing number of $2$-- and $3$-planar graphs in combination with corresponding lower bounds based on the Crossing Lemma., Comment: Appears in the Proceedings of the 32nd International Symposium on Graph Drawing and Network Visualization (GD 2024)

Dysfluent speech detection is the bottleneck for disordered speech analysis and spoken language learning. Current state-of-the-art models are governed by rule-based systems which lack efficiency and robustness, and are sensitive to template design. In this paper, we propose YOLO-Stutter: a first end-to-end method that detects dysfluencies in a time-accurate manner. YOLO-Stutter takes imperfect speech-text alignment as input, followed by a spatial feature aggregator, and a temporal dependency extractor to perform region-wise boundary and class predictions. We also introduce two dysfluency corpus, VCTK-Stutter and VCTK-TTS, that simulate natural spoken dysfluencies including repetition, block, missing, replacement, and prolongation. Our end-to-end method achieves state-of-the-art performance with a minimum number of trainable parameters for on both simulated data and real aphasia speech. Code and datasets are open-sourced at https://github.com/rorizzz/YOLO-Stutter, Comment: Interspeech 2024

The rise of Extended Reality (XR) requires efficient streaming of 3D online worlds, challenging current 3DGS representations to adapt to bandwidth-constrained environments. This paper proposes LapisGS, a layered 3DGS that supports adaptive streaming and progressive rendering. Our method constructs a layered structure for cumulative representation, incorporates dynamic opacity optimization to maintain visual fidelity, and utilizes occupancy maps to efficiently manage Gaussian splats. This proposed model offers a progressive representation supporting a continuous rendering quality adapted for bandwidth-aware streaming. Extensive experiments validate the effectiveness of our approach in balancing visual fidelity with the compactness of the model, with up to 50.71% improvement in SSIM, 286.53% improvement in LPIPS, and 318.41% reduction in model size, and shows its potential for bandwidth-adapted 3D streaming and rendering applications.

We consider a dilute Bose gas in the thermodynamic limit and prove a lower bound on the free energy for low temperatures which is in agreement with the conjecture of Lee-Huang-Yang on the excitation spectrum of the system. Combining techniques of \cite{FS2} and \cite{HHNST}, we give a simpler and shorter proof resolving the case of strong interactions, including the hard-core potential., Comment: 33 pages

This technical report introduces Docling, an easy to use, self-contained, MIT-licensed open-source package for PDF document conversion. It is powered by state-of-the-art specialized AI models for layout analysis (DocLayNet) and table structure recognition (TableFormer), and runs efficiently on commodity hardware in a small resource budget. The code interface allows for easy extensibility and addition of new features and models.

Routine computed tomography (CT) scans often detect a wide range of renal cysts, some of which may be malignant. Early and precise localization of these cysts can significantly aid quantitative image analysis. Current segmentation methods, however, do not offer sufficient interpretability at the feature and pixel levels, emphasizing the necessity for an explainable framework that can detect and rectify model inaccuracies. We developed an interpretable segmentation framework and validated it on a multi-centric dataset. A Variational Autoencoder Generative Adversarial Network (VAE-GAN) was employed to learn the latent representation of 3D input patches and reconstruct input images. Modifications in the latent representation using the gradient of the segmentation model generated counterfactual explanations for varying dice similarity coefficients (DSC). Radiomics features extracted from these counterfactual images, using a ground truth cyst mask, were analyzed to determine their correlation with segmentation performance. The DSCs for the original and VAE-GAN reconstructed images for counterfactual image generation showed no significant differences. Counterfactual explanations highlighted how variations in cyst image features influence segmentation outcomes and showed model discrepancies. Radiomics features correlating positively and negatively with dice scores were identified. The uncertainty of the predicted segmentation masks was estimated using posterior sampling of the weight space. The combination of counterfactual explanations and uncertainty maps provided a deeper understanding of the image features within the segmented renal cysts that lead to high uncertainty. The proposed segmentation framework not only achieved high segmentation accuracy but also increased interpretability regarding how image features impact segmentation performance.

This paper investigates tree species classification using Sentinel-2 multispectral satellite image time-series. Despite their critical importance for many applications, such maps are often unavailable, outdated, or inaccurate for large areas. The interest of using remote sensing time series to produce these maps has been highlighted in many studies. However, many methods proposed in the literature still rely on a standard classification algorithm, usually the Random Forest (RF) algorithm with vegetation indices. This study shows that the use of deep learning models can lead to a significant improvement in classification results, especially in an imbalanced context where the RF algorithm tends to predict towards the majority class. In our use case in the center of France with 10 tree species, we obtain an overall accuracy (OA) around 95% and a F1-macro score around 80% using three different benchmark deep learning architectures. In contrast, using the RF algorithm yields an OA of 93% and an F1 of 60%, indicating that the minority classes are not classified with sufficient accuracy. Therefore, the proposed framework is a strong baseline that can be easily implemented in most scenarios, even with a limited amount of reference data. Our results highlight that standard multilayer perceptron can be competitive with batch normalization and a sufficient amount of parameters. Other architectures (convolutional or attention-based) can also achieve strong results when tuned properly. Furthermore, our results show that DL models are naturally robust to imbalanced data, although similar results can be obtained using dedicated techniques.

In the last decade, remarkable advances in integrated photonic technologies have enabled table-top experiments and instrumentation to be scaled down to compact chips with significant reduction in size, weight, power consumption, and cost. Here, we demonstrate an integrated continuously tunable laser in a heterogeneous gallium arsenide-on-silicon nitride (GaAs-on-SiN) platform that emits in the far-red radiation spectrum near 780 nm, with 20 nm tuning range, <6 kHz intrinsic linewidth, and a >40 dB side-mode suppression ratio. The GaAs optical gain regions are heterogeneously integrated with low-loss SiN waveguides. The narrow linewidth lasing is achieved with an extended cavity consisting of a resonator-based Vernier mirror and a phase shifter. Utilizing synchronous tuning of the integrated heaters, we show mode-hop-free wavelength tuning over a range larger than 100 GHz (200 pm). To demonstrate the potential of the device, we investigate two illustrative applications: (i) the linear characterization of a silicon nitride microresonator designed for entangled-photon pair generation, and (ii) the absorption spectroscopy and locking to the D1 and D2 transition lines of 87-Rb. The performance of the proposed integrated laser holds promise for a broader spectrum of both classical and quantum applications in the visible range, encompassing communication, control, sensing, and computing.

The first generation of ELT instruments includes an optical-infrared high-resolution spectrograph, indicated as ELT-HIRES and recently christened ANDES (ArmazoNes high Dispersion Echelle Spectrograph). ANDES consists of three fibre-fed spectrographs ([U]BV, RIZ, YJH) providing a spectral resolution of $\sim$100,000 with a minimum simultaneous wavelength coverage of 0.4-1.8 $\mu$m with the goal of extending it to 0.35-2.4 $\mu$m with the addition of a U arm to the BV spectrograph and a separate K band spectrograph. It operates both in seeing- and diffraction-limited conditions and the fibre feeding allows several, interchangeable observing modes including a single conjugated adaptive optics module and a small diffraction-limited integral field unit in the NIR. Modularity and fibre-feeding allow ANDES to be placed partly on the ELT Nasmyth platform and partly in the Coud\'e room. ANDES has a wide range of groundbreaking science cases spanning nearly all areas of research in astrophysics and even fundamental physics. Among the top science cases, there are the detection of biosignatures from exoplanet atmospheres, finding the fingerprints of the first generation of stars, tests on the stability of Nature's fundamental couplings, and the direct detection of the cosmic acceleration. The ANDES project is carried forward by a large international consortium, composed of 35 Institutes from 13 countries, forming a team of almost 300 scientists and engineers which include the majority of the scientific and technical expertise in the field that can be found in ESO member states., Comment: SPIE astronomical telescope and instrumentation 2024, in press

We show that every $n$-vertex planar graph is contained in the graph obtained from a fan by blowing up each vertex by a complete graph of order $O(\sqrt{n}\log^2 n)$. Equivalently, every $n$-vertex planar graph $G$ has a set $X$ of $O(\sqrt{n}\log^2 n)$ vertices such that $G-X$ has bandwidth $O(\sqrt{n}\log^2 n)$. This result holds in the more general setting of graphs contained in the strong product of a bounded treewidth graph and a path, which includes bounded genus graphs, graphs excluding a fixed apex graph as a minor, and $k$-planar graphs for fixed $k$. These results are obtained using two ingredients. The first is a new local sparsification lemma, which shows that every $n$-vertex planar graph $G$ has a set of $O((n\log n)/D)$ vertices whose removal results in a graph with local density at most $D$. The second is a generalization of a method of Feige and Rao, that relates bandwidth and local density using volume-preserving Euclidean embeddings., Comment: 34 pages including 4 figures, many formulas, and two appendices

Background: The high dimensionality of radiomic feature sets, the variability in radiomic feature types and potentially high computational requirements all underscore the need for an effective method to identify the smallest set of predictive features for a given clinical problem. Purpose: Develop a methodology and tools to identify and explain the smallest set of predictive radiomic features. Materials and Methods: 89,714 radiomic features were extracted from five cancer datasets: low-grade glioma, meningioma, non-small cell lung cancer (NSCLC), and two renal cell carcinoma cohorts (n=2104). Features were categorized by computational complexity into morphological, intensity, texture, linear filters, and nonlinear filters. Models were trained and evaluated on each complexity level using the area under the curve (AUC). The most informative features were identified, and their importance was explained. The optimal complexity level and associated most informative features were identified using systematic statistical significance analyses and a false discovery avoidance procedure, respectively. Their predictive importance was explained using a novel tree-based method. Results: MEDimage, a new open-source tool, was developed to facilitate radiomic studies. Morphological features were optimal for MRI-based meningioma (AUC: 0.65) and low-grade glioma (AUC: 0.68). Intensity features were optimal for CECT-based renal cell carcinoma (AUC: 0.82) and CT-based NSCLC (AUC: 0.76). Texture features were optimal for MRI-based renal cell carcinoma (AUC: 0.72). Tuning the Hounsfield unit range improved results for CECT-based renal cell carcinoma (AUC: 0.86). Conclusion: Our proposed methodology and software can estimate the optimal radiomics complexity level for specific medical outcomes, potentially simplifying the use of radiomics in predictive modeling across various contexts.

High-performance, high-volume-manufacturing Si3N4 photonics requires extremely low waveguide losses augmented with heterogeneously integrated lasers for applications beyond traditional markets of high-capacity interconnects. State-of-the-art quality factors (Q) over 200 million at 1550 nm have been shown previously; however, maintaining high Qs throughout laser fabrication has not been shown. Here, Si3N4 resonator intrinsic Qs over 100 million are demonstrated on a fully integrated heterogeneous laser platform. Qi is measured throughout laser processing steps, showing degradation down to 50 million from dry etching, metal evaporation, and ion implant steps, and controllable recovery to over 100 million from annealing at 250C - 350C.

PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.

The accurate characterisation of the stellar magnetism of planetary host stars has been gaining momentum, especially in the context of transmission spectroscopy investigations of exoplanets. Indeed, the magnetic field regulates the amount of energetic radiation and stellar wind impinging on planets, as well as the presence of inhomogeneities on the stellar surface that hinder the precise extraction of the planetary atmospheric absorption signal. We initiated a spectropolarimetric campaign to unveil the magnetic field properties of known exoplanet hosting stars included in the current list of potential Ariel targets. In this work, we focus on HD 63433, a young solar-like star hosting two sub-Neptunes and an Earth-sized planet. These exoplanets orbit within 0.15 au from the host star and have likely experienced different atmospheric evolutionary paths. We analysed optical spectropolarimetric data collected with ESPaDOnS, HARPSpol, and Neo-Narval to compute the magnetic activity indices (log R'_HK , H$\alpha$, and Ca ii infrared triplet), measure the longitudinal magnetic field, and reconstruct the large-scale magnetic topology via Zeeman-Doppler imaging (ZDI). The magnetic field map was then employed to simulate the space environment in which the exoplanets orbit. The reconstructed stellar magnetic field has an average strength of 24 G and it features a complex topology with a dominant toroidal component, in agreement with other stars of a similar spectral type and age. Our simulations of the stellar environment locate 10% of the innermost planetary orbit inside the Alfv\'en surface and, thus, brief magnetic connections between the planet and the star can occur. The outer planets are outside the Alfv\'en surface and a bow shock between the stellar wind and the planetary magnetosphere could potentially form., Comment: 13 pages, 11 figures and 4 tables. Accepted in Astronomy and Astrophysics

LensMC is a weak lensing shear measurement method developed for Euclid and Stage-IV surveys. It is based on forward modelling to deal with convolution by a point spread function with comparable size to many galaxies; sampling the posterior distribution of galaxy parameters via Markov Chain Monte Carlo; and marginalisation over nuisance parameters for each of the 1.5 billion galaxies observed by Euclid. The scientific performance is quantified through high-fidelity images based on the Euclid Flagship simulations and emulation of the Euclid VIS images; realistic clustering with a mean surface number density of 250 arcmin$^{-2}$ ($I_{\rm E}<29.5$) for galaxies, and 6 arcmin$^{-2}$ ($I_{\rm E}<26$) for stars; and a diffraction-limited chromatic point spread function with a full width at half maximum of $0.^{\!\prime\prime}2$ and spatial variation across the field of view. Objects are measured with a density of 90 arcmin$^{-2}$ ($I_{\rm E}<26.5$) in 4500 deg$^2$. The total shear bias is broken down into measurement (our main focus here) and selection effects (which will be addressed elsewhere). We find: measurement multiplicative and additive biases of $m_1=(-3.6\pm0.2)\times10^{-3}$, $m_2=(-4.3\pm0.2)\times10^{-3}$, $c_1=(-1.78\pm0.03)\times10^{-4}$, $c_2=(0.09\pm0.03)\times10^{-4}$; a large detection bias with a multiplicative component of $1.2\times10^{-2}$ and an additive component of $-3\times10^{-4}$; and a measurement PSF leakage of $\alpha_1=(-9\pm3)\times10^{-4}$ and $\alpha_2=(2\pm3)\times10^{-4}$. When model bias is suppressed, the obtained measurement biases are close to Euclid requirement and largely dominated by undetected faint galaxies ($-5\times10^{-3}$). Although significant, model bias will be straightforward to calibrate given the weak sensitivity. LensMC is publicly available at https://gitlab.com/gcongedo/LensMC, Comment: 29 pages, 18 figures, 2 tables

An $\ell$-vertex-ranking of a graph $G$ is a colouring of the vertices of $G$ with integer colours so that in any connected subgraph $H$ of $G$ with diameter at most $\ell$, there is a vertex in $H$ whose colour is larger than that of every other vertex in $H$. The $\ell$-vertex-ranking number, $\chi_{\ell-\mathrm{vr}}(G)$, of $G$ is the minimum integer $k$ such that $G$ has an $\ell$-vertex-ranking using $k$ colours. We prove that, for any fixed $d$ and $\ell$, every $d$-degenerate $n$-vertex graph $G$ satisfies $\chi_{\ell-\mathrm{vr}}(G)= O(n^{1-2/(\ell+1)}\log n)$ if $\ell$ is even and $\chi_{\ell-\mathrm{vr}}(G)= O(n^{1-2/\ell}\log n)$ if $\ell$ is odd. The case $\ell=2$ resolves (up to the $\log n$ factor) an open problem posed by \citet{karpas.neiman.ea:on} and the cases $\ell\in\{2,3\}$ are asymptotically optimal (up to the $\log n$ factor)., Comment: 15 pages, zero figures

Rapid progress in photonics has led to an explosion of integrated devices that promise to deliver the same performance as table-top technology at the nanoscale; heralding the next generation of optical communications, sensing and metrology, and quantum technologies. However, the challenge of co-integrating the multiple components of high-performance laser systems has left application of these nanoscale devices thwarted by bulky laser sources that are orders of magnitude larger than the devices themselves. Here we show that the two main ingredients for high-performance lasers -- noise reduction and isolation -- currently requiring serial combination of incompatible technologies, can be sourced simultaneously from a single, passive, CMOS-compatible nanophotonic device. To do this, we take advantage of both the long photon lifetime and the nonreciprocal Kerr nonlinearity of a high quality factor silicon nitride ring resonator to self-injection lock a semiconductor laser chip while also providing isolation. Additionally, we identify a previously unappreciated power regime limitation of current on-chip laser architectures which our system overcomes. Using our device, which we term a unified laser stabilizer, we demonstrate an on-chip integrated laser system with built-in isolation and noise reduction that operates with turnkey reliability. This approach departs from efforts to directly miniaturize and integrate traditional laser system components and serves to bridge the gap to fully integrated optical technologies.

A subset $S$ of vertices in a planar graph $G$ is a free set if, for every set $P$ of $|S|$ points in the plane, there exists a straight-line crossing-free drawing of $G$ in which vertices of $S$ are mapped to distinct points in $P$. In this survey, we review - several equivalent definitions of free sets, - results on the existence of large free sets in planar graphs and subclasses of planar graphs, - and applications of free sets in graph drawing. The survey concludes with a list of open problems in this still very active research area., Comment: 31 pages

Entanglement has evolved from an enigmatic concept of quantum physics to a key ingredient of quantum technology. It explains correlations between measurement outcomes that contradict classical physics, and has been widely explored with small sets of individual qubits. Multi-partite entangled states build up in gate-based quantum-computing protocols, and $\unicode{x2013}$ from a broader perspective $\unicode{x2013}$ were proposed as the main resource for measurement-based quantum-information processing. The latter requires the ex-ante generation of a multi-qubit entangled state described by a graph. Small graph states such as Bell or linear cluster states have been produced with photons, but the proposed quantum computing and quantum networking applications require fusion of such states into larger and more powerful states in a programmable fashion. Here we achieve this goal by employing an optical resonator containing two individually addressable atoms. Ring and tree graph states with up to eight qubits, with the names reflecting the entanglement topology, are efficiently fused from the photonic states emitted by the individual atoms. The fusion process itself employs a cavity-assisted gate between the two atoms. Our technique is in principle scalable to even larger numbers of qubits, and is the decisive step towards, for instance, a memory-less quantum repeater in a future quantum internet., Comment: 18 pages, 5 figures, 2 tables

Dynamo models of stellar magnetic fields for partly and fully convective stars are guided by observational constraints. Zeeman-Doppler imaging has revealed a variety of magnetic field geometries and, for fully convective stars in particular, a dichotomy: either strong, mostly axisymmetric, and dipole-dominated or weak, non-axisymmetric, and multipole-dominated. This dichotomy is explained by dynamo bistability or by long-term magnetic cycles, but there is no definite conclusion on the matter. We analysed optical spectropolarimetric data sets collected with ESPaDOnS and Narval between 2005 and 2016, and near-infrared SPIRou data obtained between 2019 and 2022 for three active M dwarfs with masses between 0.1 and 0.6 MSun: EV Lac, DS Leo, and CN Leo. We looked for changes in time series of longitudinal magnetic field, width of unpolarised mean-line profiles, and large-scale field topology as retrieved with principal component analysis and Zeeman-Doppler imaging. We retrieved pulsating (EV Lac), stable (DS Leo), and sine-like (CN Leo) long-term trends in longitudinal field. The width of near-infrared mean-line profiles exhibits rotational modulation only for DS Leo, whereas in the optical it is evident for both EV Lac and DS Leo. The line width variations are not necessarily correlated to those of the longitudinal field, suggesting complex relations between small- and large-scale field. We also recorded topological changes: a reduced axisymmetry for EV Lac and a transition from toroidal- to poloidal-dominated regime for DS Leo. For CN Leo, the topology remained dipolar and axisymmetric, with only an oscillation in field strength. Our results show a peculiar evolution of the magnetic field for each M dwarf, confirming that M dwarfs with distinct masses and rotation periods can undergo magnetic long-term variations, and suggesting a variety of cyclic behaviours of their magnetic fields., Comment: 50 pages, 26 figures, 12 tables, accepted in Astronomy & Astrophysics

Light, being massless, casts no shadow; under ordinary circumstances, photons pass right through each other unimpeded. Here, we demonstrate a laser beam acting like an object - the beam casts a shadow upon a surface when the beam is illuminated by another light source. We observe a regular shadow in the sense it can be seen by the naked eye, it follows the contours of the surface it falls on, and it follows the position and shape of the object (the laser beam). Specifically, we use a nonlinear optical process involving four atomic levels of ruby. We are able to control the intensity of a transmitted laser beam by applying another perpendicular laser beam. We experimentally measure the dependence of the contrast of the shadow on the power of the object laser beam, finding a maximum of approximately of approximately 22 percent, similar to that of a shadow of a tree on a sunny day. We provide a theoretical model that predicts the contrast of the shadow. Making light itself cast a shadow opens new possibilities for fabrication, imaging, and illumination.

Let $T$ be a tree on $t$ vertices. We prove that for every positive integer $k$ and every graph $G$, either $G$ contains $k$ pairwise vertex-disjoint subgraphs each having a $T$ minor, or there exists a set $X$ of at most $t(k-1)$ vertices of $G$ such that $G-X$ has no $T$ minor. The bound on the size of $X$ is best possible and improves on an earlier $f(t)k$ bound proved by Fiorini, Joret, and Wood (2013) with some very fast growing function $f(t)$. Moreover, our proof is very short and simple.

Ellipsephic or Kempner-like harmonic series are series of inverses of integers whose expansion in base $B$, for some $B \geq 2$, contains no occurrence of some fixed digit or some fixed block of digits. A prototypical example was proposed by Kempner in 1914, namely the sum inverses of integers whose expansion in base $10$ contains no occurrence of a nonzero given digit. Results about such series address their convergence as well as closed expressions for their sums (or approximations thereof). Another direction of research is the study of sums of inverses of integers that contain only a given finite number, say $k$, of some digit or some block of digits, and the limits of such sums when $k$ goes to infinity. Generalizing partial results in the literature, we give a complete result for any digit or block of digits in any base., Comment: This paper generalizes arxiv:2305.18180

A hallmark of human intelligence is the ability to infer abstract rules from limited experience and apply these rules to unfamiliar situations. This capacity is widely studied in the visual domain using the Raven's Progressive Matrices. Recent advances in deep learning have led to multiple artificial neural network models matching or even surpassing human performance. However, while humans can identify and express the rule underlying these tasks with little to no exposure, contemporary neural networks often rely on massive pattern-based training and cannot express or extrapolate the rule inferred from the task. Furthermore, most Raven's Progressive Matrices or Raven-like tasks used for neural network training used symbolic representations, whereas humans can flexibly switch between symbolic and continuous perceptual representations. In this work, we present an algorithmic approach to rule detection and application using feature detection, affine transformation estimation and search. We applied our model to a simplified Raven's Progressive Matrices task, previously designed for behavioral testing and neuroimaging in humans. The model exhibited one-shot learning and achieved near human-level performance in the symbolic reasoning condition of the simplified task. Furthermore, the model can express the relationships discovered and generate multi-step predictions in accordance with the underlying rule. Finally, the model can reason using continuous patterns. We discuss our results and their relevance to studying abstract reasoning in humans, as well as their implications for improving intelligent machines.

The height of a random PATRICIA tree built from independent, identically distributed infinite binary strings with arbitrary diffuse probability distribution $\mu$ on $\{0,1\}^\mathbb{N}$ is studied. We show that the expected height grows asymptotically sublinearly in the number of leaves for any such $\mu$, but can be made to exceed any specific sublinear growth rate by choosing $\mu$ appropriately., Comment: Revised version. Accepted for publication in the proceedings of the 35th International Conference on Probabilistic, Combinatorial and Asymptotic Methods for the Analysis of Algorithms (AofA2024)

Neural fields, also known as implicit neural representations (INRs), have shown a remarkable capability of representing, generating, and manipulating various data types, allowing for continuous data reconstruction at a low memory footprint. Though promising, INRs applied to video compression still need to improve their rate-distortion performance by a large margin, and require a huge number of parameters and long training iterations to capture high-frequency details, limiting their wider applicability. Resolving this problem remains a quite challenging task, which would make INRs more accessible in compression tasks. We take a step towards resolving these shortcomings by introducing neural representations for videos NeRV++, an enhanced implicit neural video representation, as more straightforward yet effective enhancement over the original NeRV decoder architecture, featuring separable conv2d residual blocks (SCRBs) that sandwiches the upsampling block (UB), and a bilinear interpolation skip layer for improved feature representation. NeRV++ allows videos to be directly represented as a function approximated by a neural network, and significantly enhance the representation capacity beyond current INR-based video codecs. We evaluate our method on UVG, MCL JVC, and Bunny datasets, achieving competitive results for video compression with INRs. This achievement narrows the gap to autoencoder-based video coding, marking a significant stride in INR-based video compression research.

Recently, pretrained language models based on BERT have been introduced for the French biomedical domain. Although these models have achieved state-of-the-art results on biomedical and clinical NLP tasks, they are constrained by a limited input sequence length of 512 tokens, which poses challenges when applied to clinical notes. In this paper, we present a comparative study of three adaptation strategies for long-sequence models, leveraging the Longformer architecture. We conducted evaluations of these models on 16 downstream tasks spanning both biomedical and clinical domains. Our findings reveal that further pre-training an English clinical model with French biomedical texts can outperform both converting a French biomedical BERT to the Longformer architecture and pre-training a French biomedical Longformer from scratch. The results underscore that long-sequence French biomedical models improve performance across most downstream tasks regardless of sequence length, but BERT based models remain the most efficient for named entity recognition tasks.

Motivated by recent developments regarding the product structure of planar graphs, we study relationships between treewidth, grid minors, and graph products. We show that the Cartesian product of any two connected $n$-vertex graphs contains an $\Omega(\sqrt{n})\times\Omega(\sqrt{n})$ grid minor. This result is tight: The lexicographic product (which includes the Cartesian product as a subgraph) of a star and any $n$-vertex tree has no $\omega(\sqrt{n})\times\omega(\sqrt{n})$ grid minor.

The biomedical domain has sparked a significant interest in the field of Natural Language Processing (NLP), which has seen substantial advancements with pre-trained language models (PLMs). However, comparing these models has proven challenging due to variations in evaluation protocols across different models. A fair solution is to aggregate diverse downstream tasks into a benchmark, allowing for the assessment of intrinsic PLMs qualities from various perspectives. Although still limited to few languages, this initiative has been undertaken in the biomedical field, notably English and Chinese. This limitation hampers the evaluation of the latest French biomedical models, as they are either assessed on a minimal number of tasks with non-standardized protocols or evaluated using general downstream tasks. To bridge this research gap and account for the unique sensitivities of French, we present the first-ever publicly available French biomedical language understanding benchmark called DrBenchmark. It encompasses 20 diversified tasks, including named-entity recognition, part-of-speech tagging, question-answering, semantic textual similarity, and classification. We evaluate 8 state-of-the-art pre-trained masked language models (MLMs) on general and biomedical-specific data, as well as English specific MLMs to assess their cross-lingual capabilities. Our experiments reveal that no single model excels across all tasks, while generalist models are sometimes still competitive., Comment: Accepted at LREC-Coling 2024

Large Language Models (LLMs) have demonstrated remarkable versatility in recent years, offering potential applications across specialized domains such as healthcare and medicine. Despite the availability of various open-source LLMs tailored for health contexts, adapting general-purpose LLMs to the medical domain presents significant challenges. In this paper, we introduce BioMistral, an open-source LLM tailored for the biomedical domain, utilizing Mistral as its foundation model and further pre-trained on PubMed Central. We conduct a comprehensive evaluation of BioMistral on a benchmark comprising 10 established medical question-answering (QA) tasks in English. We also explore lightweight models obtained through quantization and model merging approaches. Our results demonstrate BioMistral's superior performance compared to existing open-source medical models and its competitive edge against proprietary counterparts. Finally, to address the limited availability of data beyond English and to assess the multilingual generalization of medical LLMs, we automatically translated and evaluated this benchmark into 7 other languages. This marks the first large-scale multilingual evaluation of LLMs in the medical domain. Datasets, multilingual evaluation benchmarks, scripts, and all the models obtained during our experiments are freely released., Comment: Accepted at ACL 2024 - Proceedings of the 62st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Rydberg states of excitons can reach microns in size and require extremely pure crystals. We introduce an experimental method for the rapid and spatially-resolved characterization of Rydberg excitons in copper oxide (Cu2O) with sub-micron resolution over large zones. Our approach involves illuminating and imaging the entire sample on a camera to realize a spatially-resolved version of resonant absorption spectroscopy, without any mobile part. This yields spatial maps of Rydberg exciton properties, including their energy, linewidth and peak absorption, providing a comprehensive quality assessment of the entire sample in a single shot. Furthermore, by imaging the sample photoluminescence over the same zone, we establish a strong relationship between the spectral quality map and the photoluminescence map of charged oxygen vacancies. This results in an independent, luminescence-based quality map that closely matches the results obtained through resonant spectroscopy. Our findings reveal that Rydberg excitons in natural Cu2O crystals are predominantly influenced by optically-active charged oxygen vacancies, which can be easily mapped. Together, these two complementary methods provide valuable insights into Cu2O crystal properties., Comment: 8 pages, 6 figures

The accretion and ejection of mass in pre-main sequence (PMS) stars are key processes in stellar evolution as they shape the stellar angular momentum transport necessary for the stars' stability. Magnetospheric accretion onto classical T Tauri stars and low-mass PMS stars has been widely studied in the single-star case. This process can not be directly transferred to PMS binary systems, as tidal and gravitation effects, and/or accretion from a circumbinary disc (with variable separation of the components in the case of eccentric orbits) are in place. This work examines the accretion process of two PMS eccentric binaries, DQ Tau and AK Sco, using high-resolution spectropolarimetric time series. We investigate how magnetospheric accretion can be applied to these systems by studying the accretion-related emission lines and the magnetic field of each system. We discover that both systems are showing signs of magnetospheric accretion, despite their slightly different configurations, and the weak magnetic field of AK Sco. Furthermore, the magnetic topology of DQ Tau A shows a change relative to the previous orbital cycle studied: previously dominated by the poloidal component, it is now dominated by the toroidal component. We also report an increase of the component's accretion and the absence of an accretion burst at the apastron, suggesting that the component's magnetic variation might be the cause of the inter-cycle variations of the system's accretion. We conclude on the presence of magnetospheric accretion for both systems, together with gravitational effects, especially for AK Sco, composed of more massive components., Comment: 21 pages, 24 figures. Accepted for publication in Monthly Notices of the Royal Astronomical Society

We aim to characterise the magnetic field of the eclipsing binary CU Cnc. The determination of magnetic field parameters of this target enables comparisons with both observations of similar stars and theoretical predictions of the magnetic field strength for CU Cnc. The target is therefore providing an excellent opportunity to test our understanding of the generation of magnetic fields in low-mass stars and its impact on stellar structure. We use spectropolarimetric observations obtained with ESPaDOnS to investigate the magnetic properties of CU Cnc. We generate average line profiles with LSD, which are used to extract information about the radial velocities of the components, expanding the number of radial velocity measurements available and allowing for a determination of orbital parameters. Stokes V LSD profiles are used with ZDI to obtain large-scale magnetic field structures on both components. We also use polarised radiative transfer modelling to investigate the small-scale fields by utilising Zeeman splitting of magnetically sensitive Ti I lines in non-polarised spectra. The large-scale fields are dominantly poloidal and have an average strength of ~100 G on both components. This analysis of the large-scale fields likely suffers from some amount of hemisphere degeneracy due to the high inclination of the target. Both components also show unusual magnetic field configurations compared to stars with similar parameters, the primary is weakly axisymmetric (~10%) and the secondary has a strong torroidal contribution (~20%). The small-scale fields are significantly stronger, at 3.1 and 3.6 kG for the primary and secondary respectively. This measurement is in excellent agreement with surface field strength predictions for CU Cnc from magnetoconvective stellar evolution models. These results indicates that magnetic fields play a significant role in radius inflation of active stars., Comment: Accepted for A&A, 17 pages, 8 figures

Let $\mathbb{P}_{\kappa}(n)$ be the probability that $n$ points $z_1,\ldots,z_n$ picked uniformly and independently in $\mathfrak{C}_\kappa$, a regular $\kappa$-gon with area $1$, are in convex position, that is, form the vertex set of a convex polygon. In this paper, we give an equivalent of $\mathbb{P}_{\kappa}(n)$ for all $\kappa\geq 3$, which improves on a famous result of B\'ar\'any. A second aim of the paper is to establish a limit theorem which describes the fluctuations around the limit shape of a $n$-tuple of points in convex position when $n\to+\infty$. Finally, we give an algorithm asymptotically exact for the random generation of $z_1,\ldots,z_n$, conditioned to be in convex position in $\mathfrak{C}_\kappa$., Comment: 51 pages, 18 figures, 4 pictures