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High-dimensional count data poses significant challenges for statistical analysis, necessitating effective methods that also preserve explainability. We focus on a low rank constrained variant of the Poisson log-normal model, which relates the observed data to a latent low-dimensional multivariate Gaussian variable via a Poisson distribution. Variational inference methods have become a golden standard solution to infer such a model. While computationally efficient, they usually lack theoretical statistical properties with respect to the model. To address this issue we propose a projected stochastic gradient scheme that directly maximizes the log-likelihood. We prove the convergence of the proposed method when using importance sampling for estimating the gradient. Specifically, we obtain a rate of convergence of $O(T^{-1/2} + N^{-1})$ with $T$ the number of iterations and $N$ the number of Monte Carlo draws. The latter follows from a novel descent lemma for non convex $L$-smooth objective functions, and random biased gradient estimate. We also demonstrate numerically the efficiency of our solution compared to its variational competitor. Our method not only scales with respect to the number of observed samples but also provides access to the desirable properties of the maximum likelihood estimator.

Dye attenuation, or photometric imaging, is an optical technique commonly used in fluid dynamics to measure tracer concentration fields and fluid thicknesses under the assumption that the motion of the dye is representative of the fluid motion and that its presence does not affect the behaviour of the system. However, in some systems, particularly living biological systems or those with strong chemical interactions and reactions, the addition of dye may non-trivially influence the system and may not follow the fluid containing it. To overcome this, we demonstrate how short-wave infrared imaging can be used to measure concentration and height profiles of water and other liquids without the introduction of dye for heights down to 0.2mm with spatial and temporal resolutions of the order of 50 microns per pixel and 120 fps respectively. We showcase the utility of this technique by demonstrating its ability to accurately track the temporal evolution of the total water content of two model systems, namely a water drop spreading on a glass slide and spreading within a hydrogel sheet, validating both against an analytical mass balance. Finally, we discuss how the spectral resolution of the present setup could be increased to the point that concentrations within a multi-component system containing more than one type of liquid could be quantified.

From microactuators to biological tissues, non-porous materials with the ability to strongly expand when in contact with a solvent are ubiquitous. Consequently, the swelling of polymer systems such as hydrogel has received recently much research attention. However, the related dehydration of these systems has received much less attention. Here, we present experiments investigating the rapid dehydration of a swollen hydrogel sheet whose surface exhibits a transient crumpling instability characterised by line segments of cusps patterning the surface of the gel into an array of bumps. We perform this dehydration through immersion in acetone, which is highly miscible in water, but poorly miscible in the hydrogel. We report the onset of a fascinating pattern formation where regions of the hydrogel sheet turn turbid. We find that the emerging pattern is independent of the overall extent of the hydrated swollen surface. The pattern wavelength only depends on the duration of hydration before immersion in acetone, growing temporally with a power law behaviour. We conclude through drawing comparisons between features of this dehydration induced pattern and the original crumpling instability in the water swollen hydrogel sheet.

Virtual Production (VP) technologies have continued to improve the flexibility of on-set filming and enhance the live concert experience. The core technology of VP relies on high-resolution, high-brightness LED panels to playback/render video content. There are a number of technical challenges to effective deployment e.g. image tile synchronisation across the panels, cross panel colour balancing and compensating for colour fluctuations due to changes in camera angles. Given the complexity and potential quality degradation, the industry prefers "pristine" or lossless compressed source material for displays, which requires significant storage and bandwidth. Modern lossy compression standards like AV1 or H.265 could maintain the same quality at significantly lower bitrates and resource demands. There is yet no agreed methodology for assessing the impact of these standards on quality when the VP scene is recorded in-camera. We present a methodology to assess this impact by comparing lossless and lossy compressed footage displayed through VP screens and recorded in-camera. We assess the quality impact of HAP/NotchLC/Daniel2 and AV1/HEVC/H.264 compression bitrates from 2 Mb/s to 2000 Mb/s with various GOP sizes. Several perceptual quality metrics are then used to automatically evaluate in-camera picture quality, referencing the original uncompressed source content through the LED wall. Our results show that we can achieve the same quality with hybrid codecs as with intermediate encoders at orders of magnitude less bitrate and storage requirements., Comment: SMPTE Media Summit Paper on use of Compression in Virtual Production from TCD and Disguise

As AI systems are becoming more and more popular and used in various critical domains (health, transport, energy, ...), the need to provide guarantees and trust of their safety is undeniable. To this end, we present PyRAT, a tool based on abstract interpretation to verify the safety and the robustness of neural networks. In this paper, we describe the different abstractions used by PyRAT to find the reachable states of a neural network starting from its input as well as the main features of the tool to provide fast and accurate analysis of neural networks. PyRAT has already been used in several collaborations to ensure safety guarantees, with its second place at the VNN-Comp 2024 showcasing its performance.

Many properties of soft contact interfaces are controlled by the contact area (e.g. friction, contact stiffness and surface charge generation). The contact area increases with the contact age at rest. In contrast, it usually reduces under unidirectional shear loading. Although the physical origin of such a reduction is still debated, it always happens in an anisotropic way because the reduction mainly occurs along the shearing direction. Whether such anisotropy is a necessary condition for shear-induced area reduction remains an open question. Here, we investigate the contact area evolution of elastomer-based sphere-plane contacts under an isotropic shear loading, i.e. torsional loading. We find that, when macroscopic sliding is reached, the contact area has undergone a net area reduction. However, the area evolves non-monotonically as the twisting angle increases, with an initial rise up to a maximum before dropping to the value during macroscopic sliding. The ratio of maximum to initial contact area is found weakly dependent on the normal load, angular velocity and dwell time (time interval between the instants when the normal load and twist motion are first applied) within the investigated ranges. We show that non-monotonic area evolution can also be found under unidirectional shear loading conditions under large normal force. These observations challenge the current descriptions of shear-induced contact area evolution and are expected to serve as a benchmark for future modelling attempts in the field.

We present the photometric performance of SPIRIT, a ground-based near-infrared InGaAs CMOS-based instrument (1280 by 1024 pixels, 12 micron pitch), using on-sky results from the SPECULOOS-Southern Observatory during 2022 - 2023. SPIRIT was specifically designed to optimise time-series photometric precision for observing late M and L type stars. To achieve this, a custom wide-pass filter (0.81 - 1.33 microns, zYJ ) was used, which was also designed to minimise the effects of atmospheric precipitable water vapour (PWV) variability on differential photometry. Additionally, SPIRIT was designed to be maintenance-free by eliminating the need for liquid nitrogen for cooling. We compared SPIRIT's performance with a deeply-depleted (2048 by 2048 pixels, 13.5 micron pitch) CCD-based instrument (using an I+z' filter, 0.7 - 1.1 microns) through simultaneous observations. For L type stars and cooler, SPIRIT exhibited better photometric noise performance compared to the CCD-based instrument. The custom filter also significantly minimised red noise in the observed light curves typically introduced by atmospheric PWV variability. In SPIRIT observations, the detector's read noise was the dominant limitation, although in some cases, we were limited by the lack of comparison stars., Comment: SPIE Astronomical Telescopes + Instrumentation 2024

We extend the Gibbs conditioning principle to an abstract setting combining infinitely many linear equality constraints and non-linear inequality constraints, which need not be convex. A conditional large large deviation principle (LDP) is proved in a Wassersteintype topology, and optimality conditions are written in this abstract setting. This setting encompasses versions of the Schr{\"o}dinger bridge problem with marginal non-linear inequality constraints at every time. In the case of convex constraints, stability results for perturbations both in the constraints and the reference measure are proved. We then specify our results when the reference measure is the path-law of a continuous diffusion process, whose law is constrained at each time. We obtain a complete description of the constrained process through an atypical mean-field PDE system involving a Lagrange multiplier.

In this work, we present a new unsupervised anomaly (outlier) detection (AD) method using the sliced-Wasserstein metric. This filtering technique is conceptually interesting for integration in MLOps pipelines deploying trustworthy machine learning models in critical sectors like energy. Additionally, we open the first dataset showcasing localized critical peak rebate demand response in a northern climate. We demonstrate the capabilities of our method on synthetic datasets as well as standard AD datasets and use it in the making of a first benchmark for our open-source localized critical peak rebate dataset.

Despite its widespread adoption, Adam's advantage over Stochastic Gradient Descent (SGD) lacks a comprehensive theoretical explanation. This paper investigates Adam's sensitivity to rotations of the parameter space. We demonstrate that Adam's performance in training transformers degrades under random rotations of the parameter space, indicating a crucial sensitivity to the choice of basis. This reveals that conventional rotation-invariant assumptions are insufficient to capture Adam's advantages theoretically. To better understand the rotation-dependent properties that benefit Adam, we also identify structured rotations that preserve or even enhance its empirical performance. We then examine the rotation-dependent assumptions in the literature, evaluating their adequacy in explaining Adam's behavior across various rotation types. This work highlights the need for new, rotation-dependent theoretical frameworks to fully understand Adam's empirical success in modern machine learning tasks.

In drug discovery, highly automated high-throughput laboratories are used to screen a large number of compounds in search of effective drugs. These experiments are expensive, so we might hope to reduce their cost by experimenting on a subset of the compounds, and predicting the outcomes of the remaining experiments. In this work, we model this scenario as a sequential subset selection problem: we aim to select the smallest set of candidates in order to achieve some desired level of accuracy for the system as a whole. Our key observation is that, if there is heterogeneity in the difficulty of the prediction problem across the input space, selectively obtaining the labels for the hardest examples in the acquisition pool will leave only the relatively easy examples to remain in the inference set, leading to better overall system performance. We call this mechanism inference set design, and propose the use of an uncertainty-based active learning solution to prune out these challenging examples. Our algorithm includes an explicit stopping criterion that stops running the experiments when it is sufficiently confident that the system has reached the target performance. Our empirical studies on image and molecular datasets, as well as a real-world large-scale biological assay, show that deploying active learning for inference set design leads to significant reduction in experimental cost while obtaining high system performance.

We describe Hopf-Galois objects over bicrossed product Hopf algebras. More precisely, we show that any right Hopf-Galois object over a bicrossed product of Hopf algebras is obtained from Hopf-Galois objects over the two factors and a certain twisting map, while the unique Hopf algebra making it into a bi-Galois object is again a bicrossed product.

We report the observation of spin-dependent force induced by Nitrogen Vacancy (NV) centers embedded in a diamond crystal attached to a tethered oscillator. This result was obtained using a spin-dependent torque generated by a micro-diamond containing billions of NV centers, placed at the end of a commercially available silicon cantilever. We demonstrate that the fundamental flexural mode of the cantilever is excited by the spins of the NV centers. These spins are uniformly coupled to an externally applied homogeneous magnetic field, which enables the NV centers to exert a measurable spin-dependent torque on the cantilever, driving its center of mass motion. Our experiment highlights the intricate interplay between the spin properties of NV centers and the mechanical behavior of the oscillator in the presence of a pure torque, providing a set of tools for exploring quantum effects in state of the art mechanical systems.

The persistence exponent, which characterises the long-time decay of the survival probability of stochastic processes in the presence of an absorbing target, plays a key role in quantifying the dynamics of fluctuating systems. Determining this exponent for non-Markovian processes is known to be a difficult task, and exact results remain scarce despite sustained efforts. In this Letter, we consider the fundamental class of self-interacting random walks (SIRWs), which display long-range memory effects that result from the interaction of the random walker at time $t$ with the territory already visited at earlier times $t'

Stellar limb darkening must be properly accounted for to accurately determine the radii of exoplanets at various wavelengths. The standard approach to address limb darkening involves either using laws with coefficients from modelled stellar spectra or determining the coefficients empirically during light curve fitting of the data. Here, we test how accurately three common laws -- quadratic, power, and a three-parameter law -- can reproduce stellar limb darkening at different wavelengths and across a broad range of stars. We show that using a quadratic limb darkening law, which is most frequently employed by the community, leads to wavelength-dependent offsets in retrieved transmission spectra. For planets with high impact parameters ($b$ larger than about 0.5) the amplitude of these offsets can reach 1\% of the transit depth which is some cases is comparable to and can even exceed the expected signals from the planetary atmosphere. Furthermore, the quadratic law causes an offset in the value of the impact parameter when it is determined by fitting the broadband transit light curves. In contrast, using the Kipping--Sing three-parameter law leads to robust retrievals. We advocate the use of this law in retrievals, especially for transits with large impact parameters., Comment: submitted to ApJ

Integrated circuit technology enables the scaling of circuit complexity and functionality while maintaining manufacturability and reliability. Integration is expected to play an important role in quantum information technologies, including in the highly demanding task of producing the classical signals to control and measure quantum circuits at scales needed for fault-tolerant quantum computation. Here we experimentally characterize the cryogenic performance of a miniaturized photonic integrated circuit fabricated by a commercial foundry that down-converts classical optical signals to microwave signals. The circuit consists of waveguide-integrated germanium PIN photodiodes packaged using a scalable photonic wire bonding approach to a multi-channel optical fiber array that provides the optical excitation. We find the peak optical-to-microwave conversion response to be $\sim 150 \pm 13$ mA/W in the O-band at 4.2 K, well below the temperature the circuit was designed for and tested at in the past, for two different diode designs. The second diode design operates to over 6 GHz of 3 dB bandwidth making it suitable for controlling quantum circuits, with improvements in bandwidth and response expected from improved packaging. The demonstrated miniaturization and integration offers new perspectives for wavelength-division multiplexed control of microwave quantum circuits and scalable processors using light delivered by optical fiber arrays., Comment: 8 pages, 6 figures, 5 Supplementary Figures, accepted for publication in APL Photonics

From the vasculature of animals to the porous media making up batteries, transport by fluid flow within complex networks is crucial to service all cells or media with resources. Yet, living flow networks have a key advantage over porous media: they are adaptive and can self-organize their geometry to achieve a homogeneous perfusion throughout the network. Here, we show that, through erosion, artificial flow networks self-organize to a geometry where perfusion is more homogeneous. Flowing a pulse of cleaving enzyme through a network patterned into an erodible hydrogel, with initial channels disparate in width, we observe a homogenization in channel resistances. Experimental observations are matched with numerical simulations of the diffusion-advection-sorption dynamics of an eroding enzyme within a network. Analyzing transport dynamics theoretically, we show that homogenization only occurs if the pulse of eroding enzyme lasts longer than the time it takes any channel to equilibrate to the pulse concentration. The equilibration time scale derived analytically is in agreement with simulations. Lastly, we show both numerically and experimentally that erosion leads to homogenization of complex networks containing loops. Erosion being an omnipresent reaction, our results pave the way for a very versatile self-organized increase in the performance of porous media.

We construct a set of $2^n$ points in $\mathbb{R}^n$ such that all pairwise Manhattan distances are odd integers, which improves the recent linear lower bound of Golovanov, Kupavskii and Sagdeev. In contrast to the Euclidean and maximum metrics, this shows that the odd-distance set problem behaves very differently to the equilateral set problem under the Manhattan metric. Moreover, all coordinates of the points in our construction are integers or half-integers, and we show that our construction is optimal under this additional restriction., Comment: 6 pages

Motivated by recent observations of rapid (interannual) signals in the geomagnetic data, and by advances in numerical simulations approaching the Earth's outer core conditions, we present a study on the dynamics of hydromagnetic waves evolving over a static base state. Under the assumption of timescales separation between the rapid waves and the slow convection, we linearise the classical magneto-hydrodynamics equations over a steady non-axisymmetric background magnetic field and a zero velocity field. The initial perturbation is a super-rotating pulse of the inner core, which sets the amplitude and length-scales of the waves in the system. The initial pulse triggers axisymmetric, outward propagating torsional Alfv\'en waves, with characteristic thickness scaling with the magnetic Ekman number as $Ek_M^{1/4}$. Because the background state is non-axisymmetric, the pulse also triggers non-axisymmetric, quasi-geostrophic Alfv\'en waves. As these latter waves propagate outwards, they turn into quasi-geostrophic, magneto-Coriolis waves (QG-MC) as the Coriolis force supersedes inertia in the force balance. The period of the initial wave packet is preserved across the shell but the QG-MC wave front disperses and a westward drift is observed after this transformation. Upon reaching the core surface, the westward drift of the QG-MC waves presents an estimated phase speed of about $1100\,km/y$. This analysis confirms the QG-MC nature of the rapid magnetic signals observed in geomagnetic field models near the equator., Comment: 18 pages, 7 figures

We report on spin atomistic calculations used to model static and dynamic magnetic properties of inhomogeneous ultrathin iron films. Active magnetic layers in next-generation spintronic devices are becoming so thin that they exhibit some variable degree of roughness at the low-scale making them magnetically inhomogeneous. We propose a multiscale approach to progressively shift from a rough atomic-scale system to an ensemble of macrospins. By studying nanoscale islands of atoms in contact with each other, we demonstrate that ultrathin rough layers can be described by a set of macrospins coupled by a Heisenberg-like exchange interaction driven by the existence and shape of nanoconstrictions linking the islands. We show that the magnetization dynamics at 0 K is strongly impacted by this surface morphology since the resonant frequency of a typical ultrathin iron layer can drop by up to an order of magnitude due to inhomogeneities. Additionally, we used Monte Carlo simulations to determine the ferromagnetic-paramagnetic and spin reorientation transition temperatures for various morphology parameters and we show how nanoconstrictions and shapes of the atomic clusters can modify these transition temperatures. Our results demonstrate the possibility to account for the morphology of ultrathin structures with significant roughness. We believe that our approach makes it possible to model complete devices as close as possible to experimental reality.

We show that for a braided Hopf algebra in the category of comodules over a cosemisimple coquasitriangular Hopf algebra, the Hochschild cohomological dimension, the left and right global dimensions and the projective dimensions of the trivial left and right module all coincide. We also provide convenient criteria for smoothness and the twisted Calabi-Yau property for such braided Hopf algebras (without the cosemisimplicity assumption on $H$), in terms of properties of the trivial module.These generalize a well-known result in the case of ordinary Hopf algebras. As an illustration, we study the case of the coordinate algebra on the two-parameter braided quantum group $\textrm{SL}_{2}$.

We address several related problems on combinatorial discrepancy of trees in a setting introduced by Erd\H{o}s, F\"{u}redi, Loebl and S\'{o}s. Given a fixed tree $T$ on $n$ vertices and an edge-colouring of the complete graph $K_n$, for every colour, we find a copy of $T$ in $K_n$ where the number of edges in that colour significantly exceeds its expected count in a uniformly random embedding. This resolves a problem posed by Erd\H{o}s, F\"{u}redi, Loebl and S\'{o}s by generalising their work from two to many colours. Furthermore, if $T$ has maximum degree $\Delta\leq\epsilon n$ for sufficiently small $\epsilon > 0$ and the edge-colouring of $K_n$ is both balanced and ``not too close'' to one particular instance, we show that, for every colour, there is a copy of $T$ in $K_n$ where that colour appears on linearly more edges than any other colour. Several related examples are provided to demonstrate the necessity of the introduced structural restrictions. Our proofs combine saturation arguments for the existence of particular coloured substructures and analysis of conveniently defined local exchanges. Using similar methods, we investigate the existence of copies of a graph $H$ with prescribed number of edges in each colour in $2$-edge-coloured dense host graphs. In particular, for a graph $H$ with bounded maximum degree and balanced $2$-edge-colourings $\mathbf{c}$ of a host graph $G$ with minimum degree at least $(1-\epsilon)n$ for some $\epsilon > 0$, we show that, for any sufficiently large $n$ and sufficiently small $\epsilon$, there exists a copy of $H$ where the number of edges in the two colours differ by at most $2$. Moreover, we completely characterise the pairs $(H,\mathbf{c})$ for which the difference of $2$ cannot be improved, refuting a conjecture by Mohr, Pardey, and Rautenbach.

The paper introduces a novel framework for safe and autonomous aerial physical interaction in industrial settings. It comprises two main components: a neural network-based target detection system enhanced with edge computing for reduced onboard computational load, and a control barrier function (CBF)-based controller for safe and precise maneuvering. The target detection system is trained on a dataset under challenging visual conditions and evaluated for accuracy across various unseen data with changing lighting conditions. Depth features are utilized for target pose estimation, with the entire detection framework offloaded into low-latency edge computing. The CBF-based controller enables the UAV to converge safely to the target for precise contact. Simulated evaluations of both the controller and target detection are presented, alongside an analysis of real-world detection performance., Comment: 8 pages,14 figures, ICUAS 2024

This paper introduces a novel compliant mechanism combining lightweight and energy dissipation for aerial physical interaction. Weighting 400~g at take-off, the mechanism is actuated in the forward body direction, enabling precise position control for force interaction and various other aerial manipulation tasks. The robotic arm, structured as a closed-loop kinematic chain, employs two deported servomotors. Each joint is actuated with a single tendon for active motion control in compression of the arm at the end-effector. Its elasto-mechanical design reduces weight and provides flexibility, allowing passive-compliant interactions without impacting the motors' integrity. Notably, the arm's damping can be adjusted based on the proposed inner frictional bulges. Experimental applications showcase the aerial system performance in both free-flight and physical interaction. The presented work may open safer applications for \ac{MAV} in real environments subject to perturbations during interaction., Comment: 6 pages, 7 figures, ROBOSOFT 2024

We study two continuous and isotropic analogues of the model of greedy lattice animals introduced by Cox, Gandolfi, Griffin and Kesten in 1993. In our framework, animals collect masses scattered on a Poisson point process on $\mathbb R^d$, and are allowed to have vertices outside the process or not, depending on the model. The author recently proved in a more general setting that for all $u$ in the Euclidean open unit ball, the maximal mass of animals with length $\ell$, containing $0$ and $\ell u$ satisfies a law of large numbers. We prove some additional properties in the Poissonian case, including an extension of the functional law of large numbers to the closed unit ball, and study strict monotonicity of the limit function along a radius. Moreover, we prove that a third, penalized model is a suitable interpolation between the former two.

We present 850 {\mu}m thermal dust polarization observations with a resolution of 14.4"(~ 0.13 pc) towards an infrared dark cloud G16.96+0.27 using JCMT/POL-2. The average magnetic field orientation, which roughly agrees with the larger-scale magnetic field orientation traced by the Planck 353 GHz data, is approximately perpendicular to the filament structure. The estimated plane-of-sky magnetic field strength is ~ 96 {\mu}G and ~ 60 {\mu}G using two variants of the Davis-Chandrasekhar-Fermi methods. We calculate the virial and magnetic critical parameters to evaluate the relative importance of gravity, the magnetic field, and turbulence. The magnetic field and turbulence are both weaker than gravity, but magnetic fields and turbulence together are equal to gravity, suggesting that G16.96+0.27 is in a quasi-equilibrium state. The cloud-magnetic-field alignment is found to have a trend moving away from perpendicularity in the dense regions, which may serve as a tracer of potential fragmentation in such quiescent filaments., Comment: Accepted by ApJ. 13 pages, 5 figures

Fabrication of quantum processors in advanced 300 mm wafer-scale complementary metal-oxide-semiconductor (CMOS) foundries provides a unique scaling pathway towards commercially viable quantum computing with potentially millions of qubits on a single chip. Here, we show precise qubit operation of a silicon two-qubit device made in a 300 mm semiconductor processing line. The key metrics including single- and two-qubit control fidelities exceed 99% and state preparation and measurement fidelity exceeds 99.9%, as evidenced by gate set tomography (GST). We report coherence and lifetimes up to $T_\mathrm{2}^{\mathrm{*}} = 30.4$ $\mu$s, $T_\mathrm{2}^{\mathrm{Hahn}} = 803$ $\mu$s, and $T_1 = 6.3$ s. Crucially, the dominant operational errors originate from residual nuclear spin carrying isotopes, solvable with further isotopic purification, rather than charge noise arising from the dielectric environment. Our results answer the longstanding question whether the favourable properties including high-fidelity operation and long coherence times can be preserved when transitioning from a tailored academic to an industrial semiconductor fabrication technology., Comment: 10 pages, 4 figures, 4 extended data figures

Most telemanipulation systems for aerial robots provide the operator with only 2D screen visual information. The lack of richer information about the robot's status and environment can limit human awareness and, in turn, task performance. While the pilot's experience can often compensate for this reduced flow of information, providing richer feedback is expected to reduce the cognitive workload and offer a more intuitive experience overall. This work aims to understand the significance of providing additional pieces of information during aerial telemanipulation, namely (i) 3D immersive visual feedback about the robot's surroundings through mixed reality (MR) and (ii) 3D haptic feedback about the robot interaction with the environment. To do so, we developed a human-robot interface able to provide this information. First, we demonstrate its potential in a real-world manipulation task requiring sub-centimeter-level accuracy. Then, we evaluate the individual effect of MR vision and haptic feedback on both dexterity and workload through a human subjects study involving a virtual block transportation task. Results show that both 3D MR vision and haptic feedback improve the operator's dexterity in the considered teleoperated aerial interaction tasks. Nevertheless, pilot experience remains the most significant factor., Comment: 12 pages, 11 figures, journal paper

We address the task of uplifting visual features or semantic masks from 2D vision models to 3D scenes represented by Gaussian Splatting. Whereas common approaches rely on iterative optimization-based procedures, we show that a simple yet effective aggregation technique yields excellent results. Applied to semantic masks from Segment Anything (SAM), our uplifting approach leads to segmentation quality comparable to the state of the art. We then extend this method to generic DINOv2 features, integrating 3D scene geometry through graph diffusion, and achieve competitive segmentation results despite DINOv2 not being trained on millions of annotated masks like SAM.

The purpose of this short note is to establish a connection between a one-dimensional random walk in a random sparse environment and the random pinning model. We show that the grand canonical partition function of the pinning model coincides with the mean number of returns to the origin for a random walk in a random sparse environment averaged on the randomness location. We obtain thereof some information on the integrability of the number of return times in the annealed and partially annealed setups.

This paper presents the design and implementation of the Scintillation Filter by Kalman-colored algorithm (SciFi), which is used to remove tropospheric scintillation from Q/V bands total attenuation data series. In contrast to the classical methods using low-pass filters, the SciFi algorithm allows to estimate both the attenuation, its slope and a confidence interval. Moreover, the linear observer structure of the Kalman filter allows it to operate in real time. Therefore, the states and uncertainties estimated by SciFi can be used as input for Fade Mitigation Techniques (FMT) such as Adaptive Coding and Modulation (ACM) or Site Diversity (SD). In this article, we propose a method to tune the noise level based on recommendations approved by the ITU-R. Finally, some results of filtering on Alphasat experimental data are discussed., Comment: Ka and Broadband Communications Conference, Seattle, WA, USA, Sept 2024

Return words are a classical tool for studying shift spaces with low factor complexity. In recent years, their projection inside groups have attracted some attention, for instance in the context of dendric shift spaces, of generation of pseudorandom numbers (through the welldoc property), and of profinite invariants of shift spaces. Aiming at unifying disparate works, we introduce a notion of stability for subgroups generated by return words. Within this framework, we revisit several existing results and generalize some of them. We also study general aspects of stability, such as decidability or closure under certain operations.

This report summarizes what has happened in the mini-workshops entitled ''My Earth in 180 minutes'' organized during the lunch break at the SF2A 2024 conference in Marseille. The project showcased an innovative serious game designed to raise awareness of greenhouse gas (GHG) emissions in astronomical research laboratories. Participants, organized into teams, simulate strategies to reduce their carbon footprints by 50\%, focusing on key astronomical activities such as space instrumentation, data analysis, and laboratory work. The sessions highlight the challenges of achieving significant emissions reductions without disrupting core research activities, such as telescope observations. While the serious game facilitates important discussions on sustainable practices, the results point to the need for broader engagement, adaptation to different cultural contexts, and institutional support. The project highlights the importance of integrating climate action into the academic environment and suggests potential future directions for expanding its impact., Comment: SF2A 2024, Jun 2024, Marseille, France

We present significant upgrades to the VAMPIRES instrument, a visible-light (600 nm to 800 nm) high-contrast imaging polarimeter integrated within SCExAO on the Subaru telescope. Key enhancements include new qCMOS detectors, coronagraphs, polarization optics, and a multiband imaging mode, improving sensitivity, resolution, and efficiency. These upgrades position VAMPIRES as a powerful tool for studying sub-stellar companions, accreting protoplanets, circumstellar disks, stellar jets, stellar mass-loss shells, and solar system objects. The instrument achieves angular resolutions from 17 mas to 21 mas and Strehl ratios up to 60\%, with 5$\sigma$ contrast limits of $10^{\text{-}4}$ at 0.1'' to $10^{\text{-}6}$ beyond 0.5''. We demonstrate these capabilities through spectro-polarimetric coronagraphic imaging of the HD 169142 circumstellar disk, ADI+SDI imaging of the sub-stellar companion HD 1160B, narrowband H$\alpha$ imaging of the R Aqr emission nebula, and spectro-polarimetric imaging of Neptune., Comment: 36 pages, 33 figures, accepted to PASP

This work is motivated by the following problem: Can we identify the disease-causing gene in a patient affected by a monogenic disorder? This problem is an instance of root cause discovery. In particular, we aim to identify the intervened variable in one interventional sample using a set of observational samples as reference. We consider a linear structural equation model where the causal ordering is unknown. We begin by examining a simple method that uses squared z-scores and characterize the conditions under which this method succeeds and fails, showing that it generally cannot identify the root cause. We then prove, without additional assumptions, that the root cause is identifiable even if the causal ordering is not. Two key ingredients of this identifiability result are the use of permutations and the Cholesky decomposition, which allow us to exploit an invariant property across different permutations to discover the root cause. Furthermore, we characterize permutations that yield the correct root cause and, based on this, propose a valid method for root cause discovery. We also adapt this approach to high-dimensional settings. Finally, we evaluate the performance of our methods through simulations and apply the high-dimensional method to discover disease-causing genes in the gene expression dataset that motivates this work.

We analyze near-infrared integral field spectropolarimetry of the AB Aurigae protoplanetary disk and protoplanet (AB Aur b), obtained with SCExAO/CHARIS in 22 wavelength channels covering the J, H, and K passbands ($\lambda_{\rm o}$ = 1.1--2.4 $\mu m$) over angular separations of $\rho$ $\approx$ 0.13" to 1.1" ($\sim$20--175 au). Our images resolve spiral structures in the disk in each CHARIS channel. At the longest wavelengths, the data may reveal an extension of the western spiral seen in previous polarimetric data at $\rho$ $<$ 0.3" out to larger distances clockwise from the protoplanet AB Aur b, coincident with the ALMA-detected $CO$ gas spiral. While AB Aur b is detectable in complementary total intensity data, it is a non-detection in polarized light at $\lambda$ $>$ 1.3 $\mu $m. While the observed disk color is extremely red across $JHK$, the disk has a blue intrinsic scattering color consistent with small dust grains. The disk's polarization spectrum is redder than AB Aur b's total intensity spectrum. The polarization fraction peaks at $\sim$ 0.6 along the major disk axis. Radiative transfer modeling of the CHARIS data shows that small, porous dust grains with a porosity of $p$ = 0.6--0.8 better reproduce the scattered-light appearance of the disk than more compact spheres ($p$ = 0.3), especially the polarization fraction. This work demonstrates the utility of integral field spectropolarimetry to characterize structures in protoplanetary disks and elucidate the properties of the disks' dust., Comment: 23 pages, 17 Figures, accepted to AAS Journals

We tackle the problem of highly-accurate, holistic performance capture for the face, body and hands simultaneously. Motion-capture technologies used in film and game production typically focus only on face, body or hand capture independently, involve complex and expensive hardware and a high degree of manual intervention from skilled operators. While machine-learning-based approaches exist to overcome these problems, they usually only support a single camera, often operate on a single part of the body, do not produce precise world-space results, and rarely generalize outside specific contexts. In this work, we introduce the first technique for marker-free, high-quality reconstruction of the complete human body, including eyes and tongue, without requiring any calibration, manual intervention or custom hardware. Our approach produces stable world-space results from arbitrary camera rigs as well as supporting varied capture environments and clothing. We achieve this through a hybrid approach that leverages machine learning models trained exclusively on synthetic data and powerful parametric models of human shape and motion. We evaluate our method on a number of body, face and hand reconstruction benchmarks and demonstrate state-of-the-art results that generalize on diverse datasets.

MicroLED displays are the result of a complex manufacturing chain. Each stage of this process, if optimized, contributes to achieving the highest levels of final efficiencies. Common works carried out by Pollen Metrology, Aledia, and Universit{\'e} Clermont-Auvergne led to a generic process optimization workflow. This software solution offers a holistic approach where stages are chained together for gaining a complete optimal solution. This paper highlights key corners of the methodology, validated by the experiments and process experts: data cleaning and multi-objective optimization., Comment: Eurodisplay 2024, Sep 2024, Grenoble, France

The extreme environments of transiting close-in exoplanets in highly-eccentric orbits are ideal for testing exo-climate physics. Spectroscopically resolved phase curves not only allow for the characterization of their thermal response to irradiation changes but also unveil phase-dependent atmospheric chemistry and dynamics. We observed a partial phase curve of the highly-eccentric close-in giant planet HAT-P-2b ($e=0.51,M=9M_{\rm{Jup}}$) with the Wide Field Camera 3 aboard the Hubble Space Telescope. Using these data, we updated the planet's orbital parameters and radius, and retrieved high-frequency pulsations consistent with the planet-induced pulsations reported in Spitzer data. We found that the peak in planetary flux occurred at $6.7\pm0.6$ hr after periastron, with a heating and cooling timescales of $9.0^{+3.5}_{-2.1}$ hr, and $3.6^{+0.7}_{-0.6}$ hr, respectively. We compare the light-curve to various 1-dimensional and 3-dimensional forward models, varying the planet's chemical composition. The strong contrast in flux increase and decrease timescales before and after periapse indicates an opacity term that emerges during the planet's heating phase, potentially due to more H$^{-}$ than expected from chemical equilibrium models. The phase-resolved spectra are largely featureless, that we interpret as indicative an inhomogeneous dayside. However, we identified an anomalously high flux in the spectroscopic bin coinciding with the hydrogen Paschen $\beta$ line and that is likely connected to the planet's orbit. We interpret this as due to shock heating of the upper atmosphere given the short timescale involved, or evidence for other star-planet interactions., Comment: In review in AJ

We provide a conformal field theory (CFT) description of the probabilistic model of boundary effects in the wired uniform spanning tree (UST) and its algebraic content, concerning the entire first row of the Kac table with central charge $c=-2$. Namely, we prove that all boundary-to-boundary connection probabilities for (potentially fused) branches in the wired UST converge in the scaling limit to explicit CFT quantities, expressed in terms of determinants, which can also be viewed as conformal blocks of degenerate primary fields in a boundary CFT with central charge $c=-2$. Moreover, we verify that the Belavin-Polyakov-Zamolodchikov (BPZ) PDEs (i.e., Virasoro degeneracies) of arbitrary orders hold, and we also reveal an underlying valenced Temperley-Lieb algebra action on the space of boundary correlation functions of primary fields in this model. To prove these results, we combine probabilistic techniques with representation theory., Comment: 49 pages, 7 figures

We introduce a class of polynomials that we call fused Specht polynomials and use them to characterize irreducible representations of the fused Hecke algebra with parameter $q=-1$ in the space of polynomials. We apply the fused Specht polynomials to construct a basis for a space of holomorphic (chiral) conformal blocks with central charge $c=1$ which are degenerate at each point. In conformal field theory, this corresponds to all primary fields having conformal weight in the Kac table. The associated correlation functions are expected to give rise to conformally invariant boundary conditions for the Gaussian free field, which has also been verified in special cases., Comment: 48 pages

This paper introduces Mamba4Cast, a zero-shot foundation model for time series forecasting. Based on the Mamba architecture and inspired by Prior-data Fitted Networks (PFNs), Mamba4Cast generalizes robustly across diverse time series tasks without the need for dataset specific fine-tuning. Mamba4Cast's key innovation lies in its ability to achieve strong zero-shot performance on real-world datasets while having much lower inference times than time series foundation models based on the transformer architecture. Trained solely on synthetic data, the model generates forecasts for entire horizons in a single pass, outpacing traditional auto-regressive approaches. Our experiments show that Mamba4Cast performs competitively against other state-of-the-art foundation models in various data sets while scaling significantly better with the prediction length. The source code can be accessed at https://github.com/automl/Mamba4Cast.

This work establishes a linear response formula for sequential intermittent dynamical systems, consisting of Liverani-Saussol-Vaienti maps with varying parameters. As a consequence, we establish quenched (trajectory-wise) linear response for random compositions of these maps, complementing recent annealed (averaged) results in this setting. As an intermediate step, we show existence, uniqueness and statistical stability of the sequential equivariant densities for such non-uniformly expanding systems. Our arguments rely on the cone technique introduced by Baladi and Todd and further developed by Lepp{\"a}nen.

Fully actuated aerial robot proved their superiority for Aerial Physical Interaction (APhI) over the past years. This work proposes a minimal setup for aerial telemanipulation, enhancing accessibility of these technologies. The design and the control of a 6-DoF joystick with 4-DoF haptic feedback is detailed. It is the first haptic device with standard Remote Controller (RC) form factor for APhI. By miniaturizing haptic device, it enhances RC with the sense of touch, increasing physical awareness. The goal is to give operators an extra sense, other than vision and sound, to help to perform safe APhI. To the best of the authors knowledge, this is the first teleoperation system able to decouple each single axis input command. On the omnidirectional quadrotor, by reducing the number of components with a new design, we aim a simplified maintenance, and improved force and thrust to weight ratio. Open-sourced physic based simulation and successful preliminary flight tests highlighted the tool as promising for future APhI applications., Comment: 6 pages, 6 figures

We address the online unconstrained submodular maximization problem (Online USM), in a setting with stochastic bandit feedback. In this framework, a decision-maker receives noisy rewards from a nonmonotone submodular function, taking values in a known bounded interval. This paper proposes Double-Greedy - Explore-then-Commit (DG-ETC), adapting the Double-Greedy approach from the offline and online full-information settings. DG-ETC satisfies a O(d log(dT)) problemdependent upper bound for the 1/2-approximate pseudo-regret, as well as a O(dT^{2/3}log(dT)^{1/3}) problem-free one at the same time, outperforming existing approaches. To that end, we introduce a notion of hardness for submodular functions, characterizing how difficult it is to maximize them with this type of strategy.

We study the defect CFT associated with the half-BPS Wilson line in $\mathcal{N}=4$ Super Yang-Mills theory in four dimensions. Using a perturbative bootstrap approach, we derive new analytical results for multipoint correlators of protected defect operators at large $N$ and weak coupling. At next-to-next-to-leading order, we demonstrate that the simplest five- and six-point functions are fully determined by non-perturbative constraints -- which include superconformal symmetry, crossing symmetry, and the pinching of operators to lower-point functions -- as well as by a single integral, known as the train track integral. Additionally, we present new analytical results for the four-point functions $\langle 1122 \rangle$ and $\langle 1212 \rangle$., Comment: 51 pages, 3 figures, 3 tables

We study the correlators of bulk and defect half-BPS operators in $\mathcal{N}=4$ super Yang-Mills theory with a Maldacena-Wilson line defect, focusing on the case involving one bulk and two defect local operators. We analyze the non-perturbative constraints on these correlators, which include a topological sector, pinching and splitting limits, as well as a compatibility with expanding in superconformal blocks. Using these constraints, we compute a variety of bulk-defect-defect correlators up to next-to-leading order at weak coupling, and observe that transcendental terms cancel. Additionally, we study the two leading terms in the strong-coupling regime, and present partial results for the next-to-next-to-leading order., Comment: 40 pages, 8 figures, 2 tables

We apply the Effective Field Theory of Large Scale Structure (EFTofLSS) to non-standard models of dark matter with suppressed small-scale structure imprinted by early-time physics, here exemplified by interacting dark matter (IDM) coupled to standard model neutrinos, and cross-check that the EFTofLSS has no trouble replicating the real-space halo-halo power spectrum from N-body simulations. We perform forecasts for a DESI ELG-like experiment using the redshift-space power spectrum and find that, under very conservative priors on these parameters, the EFTofLSS is not expected to yield strong constraints on dark matter interactions. However, with a better understanding of the evolution of counterterms and stochastic terms with redshift, realistic IDM models could in principle be detected using the full-shape power spectrum analysis of such a spectroscopic galaxy survey., Comment: 23 pages, 7 figures