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We present a study of the galaxy Lyman-alpha luminosity function (LF) using a sample of 17 lensing clusters observed by the MUSE/VLT. Magnification from strong gravitational lensing by clusters of galaxies and MUSE apabilities allow us to blindly detect LAEs without any photometric pre-selection, reaching the faint luminosity regime. 600 lensed LAEs were selected behind these clusters in the redshift range 2.9<$z$< 6.7, covering four orders of magnitude in magnification-corrected Lyman-alpha luminosity (39.042 are consistent with those obtained from blank field observations. In the faint luminosity regime, the density of sources is well described by a steep slope, $\alpha\sim-2$ for the global redshift range. Up to log(L)$\sim$41, the steepening of the faint end slope with redshift, suggested by the earlier work of DLV19 is observed, but the uncertainties remain large. A significant flattening is observed towards the faintest end, for the highest redshift bins (log$L$<41). Using face values, the steep slope at the faint-end causes the SFRD to dramatically increase with redshift, implying that LAEs could play a major role in the process of cosmic reionization. The flattening observed towards the faint end for the highest redshift bins still needs further investigation. This turnover is similar to the one observed for the UV LF at $z\geq6$ in lensing clusters, with the same conclusions regarding the reliability of current results (e.g.arXiv:1803.09747(N); arXiv:2205.11526(N))., Comment: 20 pages, 15 figures, 6 tables. Accepted for publication in A\&A

Two-dimensional (2D) ferroelectric (FE) materials are promising compounds for next-generation nonvolatile memories, due to their low energy consumption and high endurance. Among them, {\alpha}-In$_{2}$Se$_{3}$ has drawn particular attention due to its in- and out-of-plane ferroelectricity, whose robustness has been demonstrated down to the monolayer limit. This is a relatively uncommon behavior since most bulk FE materials lose their ferroelectric character at the 2D limit due to depolarization field. Using angle resolved photoemission spectroscopy (ARPES), we unveil another unusual 2D phenomena appearing in 2H \alpha-In$_{2}$Se$_{3}$ single crystals, the occurrence of a highly metallic two-dimensional electron gas (2DEG) at the surface of vacuum-cleaved crystals. This 2DEG exhibits two confined states which correspond to an electron density of approximatively 10$^{13}$ electrons/cm$^{3}$, also confirmed by thermoelectric measurements. Combination of ARPES and density functional theory (DFT) calculations reveals a direct band gap of energy equal to 1.3 +/- 0.1 eV, with the bottom of the conduction band localized at the center of the Brillouin zone, just below the Fermi level. Such strong n-type doping further supports the quantum confinement of electrons and the formation of the 2DEG., Comment: 20 pages, 12 figures

Faint galaxies are theorised to have played a major role in reionising the Universe. Their properties as well as the Lyman-{\alpha} emitter fraction, could provide useful insight into this epoch. We use four galaxy clusters from the Lensed Lyman-alpha MUSE Arcs Sample (LLAMAS) which also have deep HST photometry to select a population of intrinsically faint Lyman Break Galaxies (LBGs) and Lyman-alpha Emitters (LAEs). We study the interrelation of these two populations, their properties, and the fraction of LBGs that display Lyman-alpha emission. The use of lensing clusters allows us to access an intrinsically faint population, the largest sample collected for this purpose: 263 LAEs and 972 LBGs between redshifts of 2.9 and 6.7, Lyman-alpha luminosities between 39.5 < log(L)(erg/s) < 42 and absolute UV magnitudes between -22 < M1500 < -12. We find a redshift evolution of the Lyman-alpha emitter fraction in line with past results, with diminished values above z = 6, taken to signify an increasingly neutral intervening IGM. Inspecting this redshift evolution with different limits on Lyman-alpha equivalent width (EW) and M1500 we find that the Lyman-alpha emitter fraction for the UV-brighter half of our sample is higher than the fraction for the UV-fainter half, a difference which increases at higher redshift. This is a surprising result and can be interpreted as a population of low Lyman-alpha EW, UV-bright galaxies situated in reionised bubbles. This result is especially interesting in the context of similar, UV-bright, low Lyman-alpha EW objects recently detected around the epoch of reionisation. We extend to intrinsically fainter objects the previously observed trends of LAEs among LBGs as galaxies with high star-formation rates and low dust content, as well as the strongest LAEs having in general fainter UV magnitudes and steeper UV slopes., Comment: 14 pages, 10 figures, accepted in A&A

We carry out dynamical microwave transport experiments in aperiodic Vogel spiral arrays of cylinders with high dielectric permittivity. We experimentally disclose the electromagnetic modal structure of these structures in real space showing that they simultaneously support long-lived modes with Gaussian, exponential, and power law spatial decay. This unique modal structure, which cannot be found in traditional periodic or disordered photonic materials, is shown to be at the origin of strong localization in Vogel spirals that survives even in three dimensions. Altogether our results unveil the manifestations of the rich, unprecedented, spatial structure of electromagnetic modes supported by aperiodic photonic systems in wave transport and localization., Comment: main text and Supplemental Material: 10 pages and 10 figures

Zinc phosphide (Zn3P2) has had a long history of scientific interest largely because of its potential for earth-abundant photovoltaics. To realize high-efficiency Zn3P2 solar cells, it is critical to understand and control point defects in this material. Using hybrid functional calculations, we assess the energetics and electronic behavior of intrinsic point defects and hydrogen impurities in Zn3P2. All intrinsic defects are found to act as compensating centers in p-type Zn3P2 and have deep levels in the band gap, except for zinc vacancies which are shallow acceptors and can act as a source of doping. Our work highlights that zinc vacancies rather than phosphorus interstitials are likely to be the main source of p-type doping in as-grown Zn3P2. We also show that Zn-poor and P-rich growth conditions, which are usually used for enhancing p-type conductivity of Zn3P2, will facilitate the formation of certain deep-level defects (P_Zn and P_i) which might be detrimental to solar cell efficiency. For hydrogen impurities, which are frequently present in the growth environment of Zn3P2, we study interstitial hydrogen and hydrogen complexes with vacancies. The results suggest small but beneficial effects of hydrogen on the electrical properties of Zn3P2.

We study cross-modal recommendation of music tracks to be used as soundtracks for videos. This problem is known as the music supervision task. We build on a self-supervised system that learns a content association between music and video. In addition to the adequacy of content, adequacy of structure is crucial in music supervision to obtain relevant recommendations. We propose a novel approach to significantly improve the system's performance using structure-aware recommendation. The core idea is to consider not only the full audio-video clips, but rather shorter segments for training and inference. We find that using semantic segments and ranking the tracks according to sequence alignment costs significantly improves the results. We investigate the impact of different ranking metrics and segmentation methods.

Secure computation often benefits from the use of correlated randomness to achieve fast, non-cryptographic online protocols. A recent paradigm put forth by Boyle $\textit{et al.}$ (CCS 2018, Crypto 2019) showed how pseudorandom correlation generators (PCG) can be used to generate large amounts of useful forms of correlated (pseudo)randomness, using minimal interactions followed solely by local computations, yielding silent secure two-party computation protocols (protocols where the preprocessing phase requires almost no communication). An additional property called programmability allows to extend this to build N-party protocols. However, known constructions for programmable PCG's can only produce OLE's over large fields, and use rather new splittable Ring-LPN assumption. In this work, we overcome both limitations. To this end, we introduce the quasi-abelian syndrome decoding problem (QA-SD), a family of assumptions which generalises the well-established quasi-cyclic syndrome decoding assumption. Building upon QA-SD, we construct new programmable PCG's for OLE's over any field $\mathbb{F}_q$ with $q>2$. Our analysis also sheds light on the security of the ring-LPN assumption used in Boyle $\textit{et al.}$ (Crypto 2020). Using our new PCG's, we obtain the first efficient N-party silent secure computation protocols for computing general arithmetic circuit over $\mathbb{F}_q$ for any $q>2$., Comment: This is a long version of a paper accepted at CRYPTO'23

Authoring high-quality digital materials is key to realism in 3D rendering. Previous generative models for materials have been trained exclusively on synthetic data; such data is limited in availability and has a visual gap to real materials. We circumvent this limitation by proposing PhotoMat: the first material generator trained exclusively on real photos of material samples captured using a cell phone camera with flash. Supervision on individual material maps is not available in this setting. Instead, we train a generator for a neural material representation that is rendered with a learned relighting module to create arbitrarily lit RGB images; these are compared against real photos using a discriminator. We then train a material maps estimator to decode material reflectance properties from the neural material representation. We train PhotoMat with a new dataset of 12,000 material photos captured with handheld phone cameras under flash lighting. We demonstrate that our generated materials have better visual quality than previous material generators trained on synthetic data. Moreover, we can fit analytical material models to closely match these generated neural materials, thus allowing for further editing and use in 3D rendering.

Models of planet-disk interaction are mainly based on 2D and 3D viscous hydrodynamical simulations. Accretion is classically prescribed by an alpha parameter which characterizes the turbulent radial transport of angular momentum (AM) in the disk. This accretion scenario has been questioned for a few years and an alternative paradigm has been proposed that involves the vertical transport of AM by MHD winds. We revisit planet-disk interaction in such context, with a focus on the planet's ability to open a gap and produce meridional flows. Accretion, magnetic field and wind torque in the gap are also explored, as well as the gravitational torque exerted by the disk onto the planet. We carry out high-resolution 3D global non-ideal MHD simulations of a gaseous disk threaded by a large-scale vertical magnetic field harboring a planet in a fixed circular orbit using the GPU-accelerated code Idefix. We consider various planet masses and disk magnetizations. We find that gap-opening always occurs for sufficiently massive planets, with deeper gaps when the planet mass increases and when the initial magnetization decreases. We propose a gap opening criterion when accretion is dominated by MHD winds. We show that accretion is unsteady and comes from surface layers in the outer disk, bringing material directly towards the planet poles. A planet gap is a privileged region for magnetic field accumulation, leading to nearly sonic accretion stream through the gap. For massive planets, the wind torque induces an asymmetric gap, both in depth and in width, that gradually erodes the outer gap edge, reducing the outer Lindblad torque and potentially reversing the migration direction of Jovian planets in magnetized disks after a few hundreds of orbits. For low-mass planets, we find strongly fluctuating gravitational torques that are mostly positive on average, indicating a stochastic outward migration.

Expander graphs, due to their mixing properties, are useful in many algorithms and combinatorial constructions. One can produce an expander graph with high probability by taking a random graph (e.g., the union of $d$ random bijections for a bipartite graph of degree $d$). This construction is much simpler than all known explicit constructions of expanders and gives graphs with good mixing properties (small second largest eigenvalue) with high probability. However, from the practical viewpoint, it uses too many random bits, so it is difficult to generate and store these bits for large graphs. The natural idea is to restrict the class of the bijections that we use. For example, if both sides are linear spaces $\mathbb{F}_q^k$ over a finite field $\mathbb{F}_q$, we may consider only \emph{linear} bijections, making the number of random bits polynomial in $k$ (and not $q^k$). In this paper we provide some experimental data that shows that this approach conserves the mixing properties (the second eigenvalue) for several types of graphs (undirected regular and biregular bipartite graphs). We also prove some upper bounds for the second eigenvalue (though they are quite weak compared with the experimental results). Finally, we discuss the possibility to decrease the number of random bits further by using Toeplitz matrices; our experiments show that this change makes the mixing properties only marginally worse while the number of random bits decreases significantly., Comment: 36 pages, 8 figures

We propose a linear algebraic method, rooted in the spectral properties of graphs, that can be used to prove lower bounds in communication complexity. Our proof technique effectively marries spectral bounds with information-theoretic inequalities. The key insight is the observation that, in specific settings, even when data sets $X$ and $Y$ are closely correlated and have high mutual information, the owner of $X$ cannot convey a reasonably short message that maintains substantial mutual information with $Y$. In essence, from the perspective of the owner of $Y$, any sufficiently brief message $m=m(X)$ would appear nearly indistinguishable from a random bit sequence. We employ this argument in several problems of communication complexity. Our main result concerns cryptographic protocols. We establish a lower bound for communication complexity of multi-party secret key agreement with unconditional, i.e., information-theoretic security. Specifically, for one-round protocols (simultaneous messages model) of secret key agreement with three participants we obtain an asymptotically tight lower bound. This bound implies optimality of the previously known omniscience communication protocol (this result applies to a non-interactive secret key agreement with three parties and input data sets with an arbitrary symmetric information profile). We consider communication problems in one-shot scenarios when the parties' inputs are not produced by any i.i.d. sources, and there are no ergodicity assumptions on the input data. In this setting, we found it natural to present our results using the framework of Kolmogorov complexity., Comment: 28 pages, 6 figures. Major revision of the previous version

Because of the diversity in lighting environments, existing illumination estimation techniques have been designed explicitly on indoor or outdoor environments. Methods have focused specifically on capturing accurate energy (e.g., through parametric lighting models), which emphasizes shading and strong cast shadows; or producing plausible texture (e.g., with GANs), which prioritizes plausible reflections. Approaches which provide editable lighting capabilities have been proposed, but these tend to be with simplified lighting models, offering limited realism. In this work, we propose to bridge the gap between these recent trends in the literature, and propose a method which combines a parametric light model with 360{\deg} panoramas, ready to use as HDRI in rendering engines. We leverage recent advances in GAN-based LDR panorama extrapolation from a regular image, which we extend to HDR using parametric spherical gaussians. To achieve this, we introduce a novel lighting co-modulation method that injects lighting-related features throughout the generator, tightly coupling the original or edited scene illumination within the panorama generation process. In our representation, users can easily edit light direction, intensity, number, etc. to impact shading while providing rich, complex reflections while seamlessly blending with the edits. Furthermore, our method encompasses indoor and outdoor environments, demonstrating state-of-the-art results even when compared to domain-specific methods., Comment: ICCV 2023, https://lvsn.github.io/everlight/

Low-dimensional materials have remarkable properties that are distinct from their bulk counterparts. A paradigmatic example is Ising superconductivity that occurs in monolayer materials such as NbSe2 which show a strong violation of the Pauli limit. In monolayers, this occurs due to a combination of broken inversion symmetry and spin-orbit coupling that locks the spins of the electrons out-of-plane. Bulk NbSe2 is centrosymmetric and is therefore not an Ising superconductor. We show that bulk misfit compound superconductors, (LaSe)1.14(NbSe2) and (LaSe)1.14(NbSe2)2, comprised of monolayers and bilayers of NbSe2, exhibit unexpected Ising protection with a Pauli-limit violation comparable to monolayer NbSe2, despite formally having inversion symmetry. We study these misfit compounds using complementary experimental methods in combination with first-principles calculations. We propose theoretical mechanisms of how the Ising protection can survive in bulk materials. We show how some of these mechanisms operate in these bulk compounds due to a concerted effect of charge-transfer, defects, reduction of interlayer hopping, and stacking. This highlights how Ising superconductivity can, unexpectedly, arise in bulk materials, and possibly enable the design of bulk superconductors that are resilient to magnetic fields., Comment: 14 pages, 4 figures, 4 extended data items

Lighting effects such as shadows or reflections are key in making synthetic images realistic and visually appealing. To generate such effects, traditional computer graphics uses a physically-based renderer along with 3D geometry. To compensate for the lack of geometry in 2D Image compositing, recent deep learning-based approaches introduced a pixel height representation to generate soft shadows and reflections. However, the lack of geometry limits the quality of the generated soft shadows and constrain reflections to pure specular ones. We introduce PixHt-Lab, a system leveraging an explicit mapping from pixel height representation to 3D space. Using this mapping, PixHt-Lab reconstructs both the cutout and background geometry and renders realistic, diverse, lighting effects for image compositing. Given a surface with physically-based materials, we can render reflections with varying glossiness. To generate more realistic soft shadows, we further propose to use 3D-aware buffer channels to guide a neural renderer. Both quantitative and qualitative evaluations demonstrate that PixHt-Lab significantly improves soft shadow generation., Comment: 11 pages, 10 figures

Neural network-based anomaly detection remains challenging in clinical applications with little or no supervised information and subtle anomalies such as hardly visible brain lesions. Among unsupervised methods, patch-based auto-encoders with their efficient representation power provided by their latent space, have shown good results for visible lesion detection. However, the commonly used reconstruction error criterion may limit their performance when facing less obvious lesions. In this work, we design two alternative detection criteria. They are derived from multivariate analysis and can more directly capture information from latent space representations. Their performance compares favorably with two additional supervised learning methods, on a difficult de novo Parkinson Disease (PD) classification task.

Optically active quantum defects play an important role in quantum sensing, computing, and communication. The electronic structure and the single-particle energy levels of these quantum defects in the semiconducting host have been used to understand their opto-electronic properties. Optical excitations that are central for their initialization and readout are linked to transitions between occupied and unoccupied single-particle states. It is commonly assumed that only quantum defects introducing levels well within the band gap and far from the band edges are of interest for quantum technologies as they mimic an isolated atom embedded in the host. In this perspective, we contradict this common assumption and show that optically active defects with energy levels close to the band edges can display similar properties. We highlight quantum defects that are excited through transitions to or from a band-like level (bound exciton), such as the T center and Se$\rm _{Si}^+$ in silicon. We also present how defects such as the silicon divacancy in diamond can involve transitions between localized levels that are above the conduction band or below the valence band. Loosening the commonly assumed requirement on the electronic structure of quantum defects offers opportunities in quantum defects design and discovery, especially in smaller band gap hosts such as silicon. We discuss the challenges in terms of operating temperature for photoluminescence or radiative lifetime in this regime. We also highlight how these alternative type of defects bring their own needs in terms of theoretical developments and fundamental understanding. This perspective clarifies the electronic structure requirement for quantum defects and will facilitate the identification and design of new color centers for quantum applications especially driven by first principles computations.

Reconfigurable intelligent surface (RIS) devices have emerged as an effective way to control the propagation channels for enhancing the end-users' performance. However, RIS optimization involves configuring the radio frequency response of a large number of radiating elements, which is challenging in real-world applications due to high computational complexity. In this paper, a model-free cross-entropy (CE) algorithm is proposed to optimize the binary RIS configuration for improving the signal-to-noise ratio (SNR) at the receiver. One key advantage of the proposed method is that it only requires system performance indicators, e.g., the received SNR, without the need for channel models or channel state information. Both simulations and experiments are conducted to evaluate the performance of the proposed CE algorithm. This study provides an experimental demonstration of the channel hardening effect in a multi-antenna RIS-assisted wireless system under rich multipath fading., Comment: accepted by IEEE Wireless Communications Letters

Any Batalin-Vilkovisky algebra with a homotopy trivialization of the BV-operator gives rise to a hypercommutative algebra structure at the cochain level which, in general, contains more homotopical information than the hypercommutative algebra introduced by Barannikov and Kontsevich on cohomology. In this paper, we use the purity of mixed Hodge structures to show that the canonical hypercommutative algebra defined on any compact Calabi-Yau manifold is formal. We also study related hypercommutative algebras associated to compact K\"ahler and Hermitian manifolds.

We numerically study the statistical fluctuations of photonic band gaps in ensembles of stealthy hyperuniform disordered patterns. We find that at low stealthiness, where correlations are weak, band gaps of different system realizations appear over a wide frequency range, are narrow, and generally do not overlap. Interestingly, above a critical value of stealthiness $\chi \gtrsim 0.35$, the bandgaps become large and overlap significantly from realization to realization, while a second gap appears. These observations extend our understanding of photonic bandgaps in disordered systems and provide information on the robustness of gaps in practical applications., Comment: 7 pages, 4 figures. Luis S. Froufe-P\'erez, Geoffroy Aubry, and Frank Scheffold have equal first authorship

We present LM-GAN, an HDR sky model that generates photorealistic environment maps with weathered skies. Our sky model retains the flexibility of traditional parametric models and enables the reproduction of photorealistic all-weather skies with visual diversity in cloud formations. This is achieved with flexible and intuitive user controls for parameters, including sun position, sky color, and atmospheric turbidity. Our method is trained directly from inputs fitted to real HDR skies, learning both to preserve the input's illumination and correlate it to the real reference's atmospheric components in an end-to-end manner. Our main contributions are a generative model trained on both sky appearance and scene rendering losses, as well as a novel sky-parameter fitting algorithm. We demonstrate that our fitting algorithm surpasses existing approaches in both accuracy and sky fidelity, and also provide quantitative and qualitative analyses, demonstrating LM-GAN's ability to match parametric input to photorealistic all-weather skies. The generated HDR environment maps are ready to use in 3D rendering engines and can be applied to a wide range of image-based lighting applications.

In this work, we investigate the microscopic mechanisms of anharmonic lattice dynamics and thermal transport in lead-free halide double perovskite Cs2AgBiBr6 from first principles. We combine self-consistent phonon calculations with bubble diagram correction and a unified theory of lattice thermal transport that considers both the particle-like phonon propagation and wave-like tunnelling of phonons. An ultra-low thermal conductivity at room temperature (~0.21 Wm-1K-1) is predicted with weak temperature dependence(~T-0.45), in sharp contrast to the conventional ~T-1 dependence. Particularly, the vibrational properties of Cs2AgBiBr6 are featured by strong anharmonicity and wave-like tunnelling of phonons. Anharmonic phonon renormalization from both the cubic and quartic anharmonicities are found essential in precisely predicting the phase transition temperature in Cs2AgBiBr6 while the negative phonon energy shifts induced by cubic anharmonicity has a significant influence on particle-like phonon propagation. Further, the contribution of the wave-like tunnelling to the total thermal conductivity surpasses that of the particle-like propagation above around 340 K, indicating the breakdown of the phonon gas picture conventionally used in the Peierls-Boltzmann Transport Equation. Importantly, further including four-phonon scatterings is required in achieving the dominance of wave-like tunnelling, as compared to the dominant particle-like propagation channel when considering only three-phonon scatterings. Our work highlights the importance of lattice anharmonicity and wave-like tunnelling of phonons in the thermal transport in lead-free halide double perovskites.