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Layered van der Waals (vdW) materials have emerged as a promising platform for nanophotonics due to large refractive indexes and giant optical anisotropy. Unlike conventional dielectrics and semiconductors, the absence of covalent bonds between layers allows for novel degrees of freedom in designing optically resonant nanophotonic structures down to the atomic scale, from the precise stacking of vertical heterostructures to controlling the twist angle between crystallographic axes. Specifically, while transition metal dichalcogenides monolayers exhibit giant second order nonlinear responses, their bulk counterparts with 2H stacking have zero second order response. In this work, we show second harmonic generation (SHG) arising from the interface of WS$_2$/MoS$_2$ hetero-bilayer thin films with an additional SHG enhancement in nanostructured optical antennas mediated by both the excitonic resonances and the anapole condition. When both conditions are met, we observe up to $10^2$ SHG signal enhancement. Our results highlights vdW materials as a platform for designing unique multilayer optical nanostructures and metamaterial, paving the way for advanced applications in nanophotonics and nonlinear optics., Comment: Manuscript + Supplementary (21 pages, 3 Main figures 8 supplementary figures)

In the strong-coupling regime, the interaction between light and matter reaches a hybridization state where the photonic and material components become inseparably linked. Using tailored states of light to break symmetries in such systems can underpin the development of novel non-equilibrium quantum materials. Chiral optical cavities offer a promising way for this, enabling either temporal or spatial symmetry-breaking, both of which are unachievable with conventional mirror cavities. For spatial symmetry-breaking a cavity needs to discriminate the handedness of circularly polarized light, a functionality that can only be achieved with metamaterials. Here, we suggest and demonstrate experimentally a chiral transition metal dichalcogenide (TMDC) metasurface with broken out-of-plane symmetry, allowing for a selective formation of self-hybridized exciton-polaritons with specific chirality. Our metasurface cavity maintains maximum chirality for oblique incidence up to 20{\deg}, significantly outperforming all previously known designs, thereby turning the angle of incidence from a constraint to a new degree of freedom for sub-nanometer precise control of resonance wavelengths. Moreover, we study the chiral strong-coupling regime in nonlinear experiments and show the polariton-driven nature of chiral third-harmonic generation. Our results demonstrate a clear pathway towards novel quantum material engineering with implications in a wide range of photonics research, such as superconductivity and valleytronics., Comment: 34 pages, 4 figures, and 12 supporting figures

Photonics has been revolutionized by breakthroughs in optical metasurfaces and layered two-dimensional materials. Yet, integrating these two fields in a singular system has remained challenging. Here, we introduce the concept of van der Waals (vdW) heterostructure metasurfaces, where ultrathin multilayer vdW material stacks are shaped into precisely engineered resonant nanostructures for boosting light-matter interactions. By leveraging quasi-bound states in the continuum to create intrinsic cavities from WS$_2$ monolayers encapsulated in hexagonal boron nitride, we observe room-temperature strong coupling and polaritonic luminescence, which further unveils a saturation of the strong-coupling regime at ultralow fluences <1 nJ/cm2, more than three orders of magnitude smaller than in previous 2D-cavity systems. Our approach, seamlessly merging metasurfaces and vdW materials, unlocks new avenues for ultrathin optical devices with atomic-scale precision and control., Comment: main + supplementary (28 pages, 4 main figures, 9 supplementary figures)

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 studied the frequency and quality factor of mechanical plasmonic nanoresonators as a function of temperature, ranging from ambient to 4 K. Our investigation focused on individual gold nanorods and nanodisks of various sizes. We observed that oscillation frequencies increase linearly as temperature decreases until saturation is reached at cryogenic temperatures. This behavior is explained by the temperature dependence of the elastic modulus, with a Debye temperature compatible with reported bulk values for gold. To describe the behavior of the quality factor, we developed a model considering the nanostructures as anelastic solids, identifying a dissipation peak around 150 K due to a thermally activated process, likely of the Niblett-Wilks mechanism type. Importantly, our findings suggest that external dissipation factors are more critical to improving quality factors than internal friction, which can be increased by modifying the nanoresonator's environment. Our results enable the design of structures with high vibration frequencies and quality factors by effectively controlling external losses., Comment: Main text and supporting information, 18 pages, 6 figures

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.

Background: Graph Neural Networks (GNN) have emerged in very recent years as a powerful tool for supporting in silico Virtual Screening. In this work we present a GNN which uses Graph Convolutional architectures to achieve very accurate multi-target screening. We also devised a hierarchical Explainable Artificial Intelligence (XAI) technique to catch information directly at atom, ring, and whole molecule level by leveraging the message passing mechanism. In this way, we find the most relevant moieties involved in bioactivity prediction. Results: We report a state-of-the-art GNN classifier on twenty Cyclin-dependent Kinase targets in support of VS. Our classifier outperforms previous SOTA approaches proposed by the authors. Moreover, a CDK1-only high-sensitivity version of the GNN has been designed to use our explainer in order to avoid the inherent bias of multi-class models. The hierarchical explainer has been validated by an expert chemist on 19 approved drugs on CDK1. Our explainer provided information in accordance to the docking analysis for 17 out of the 19 test drugs. Conclusion: Our approach is a valid support for shortening both the screening and the hit-to-lead phase. Detailed knowledge about the molecular substructures that play a role in the inhibitory action, can help the computational chemist to gain insights into the pharmacophoric function of the molecule also for repurposing purposes. Scientific Contribution Statement: The core scientific innovation of our work is the use of a hierarchical XAI approach on a GNN trained for a ligand-based VS task. The application of the hierarchical explainer allows for eliciting also structural information...

Bandstructure engineering using alloying is widely utilised for achieving optimised performance in modern semiconductor devices. While alloying has been studied in monolayer transition metal dichalcogenides, its application in van der Waals heterostructures built from atomically thin layers is largely unexplored. Here, we fabricate heterobilayers made from monolayers of WSe$_2$ (or MoSe$_2$) and Mo$_x$W$_{1-x}$Se$_2$ alloy and observe nontrivial tuning of the resultant bandstructure as a function of concentration $x$. We monitor this evolution by measuring the energy of photoluminescence (PL) of the interlayer exciton (IX) composed of an electron and hole residing in different monolayers. In Mo$_x$W$_{1-x}$Se$_2$/WSe$_2$, we observe a strong IX energy shift of $\approx$100 meV for $x$ varied from 1 to 0.6. However, for $x<0.6$ this shift saturates and the IX PL energy asymptotically approaches that of the indirect bandgap in bilayer WSe$_2$. We theoretically interpret this observation as the strong variation of the conduction band K valley for $x>0.6$, with IX PL arising from the K-K transition, while for $x<0.6$, the bandstructure hybridization becomes prevalent leading to the dominating momentum-indirect K-Q transition. This bandstructure hybridization is accompanied with strong modification of IX PL dynamics and nonlinear exciton properties. Our work provides foundation for bandstructure engineering in van der Waals heterostructures highlighting the importance of hybridization effects and opening a way to devices with accurately tailored electronic properties., Comment: Supporting Information can be found downloading and extracting the gzipped tar source file listed under "Other formats"

Creating high-quality materials in computer graphics is a challenging and time-consuming task, which requires great expertise. To simplify this process, we introduce MatFuse, a unified approach that harnesses the generative power of diffusion models for creation and editing of 3D materials. Our method integrates multiple sources of conditioning, including color palettes, sketches, text, and pictures, enhancing creative possibilities and granting fine-grained control over material synthesis. Additionally, MatFuse enables map-level material editing capabilities through latent manipulation by means of a multi-encoder compression model which learns a disentangled latent representation for each map. We demonstrate the effectiveness of MatFuse under multiple conditioning settings and explore the potential of material editing. Finally, we assess the quality of the generated materials both quantitatively in terms of CLIP-IQA and FID scores and qualitatively by conducting a user study. Source code for training MatFuse and supplemental materials are publicly available at https://gvecchio.com/matfuse.

Along with the nearing completion of the Square Kilometre Array (SKA), comes an increasing demand for accurate and reliable automated solutions to extract valuable information from the vast amount of data it will allow acquiring. Automated source finding is a particularly important task in this context, as it enables the detection and classification of astronomical objects. Deep-learning-based object detection and semantic segmentation models have proven to be suitable for this purpose. However, training such deep networks requires a high volume of labeled data, which is not trivial to obtain in the context of radio astronomy. Since data needs to be manually labeled by experts, this process is not scalable to large dataset sizes, limiting the possibilities of leveraging deep networks to address several tasks. In this work, we propose RADiff, a generative approach based on conditional diffusion models trained over an annotated radio dataset to generate synthetic images, containing radio sources of different morphologies, to augment existing datasets and reduce the problems caused by class imbalances. We also show that it is possible to generate fully-synthetic image-annotation pairs to automatically augment any annotated dataset. We evaluate the effectiveness of this approach by training a semantic segmentation model on a real dataset augmented in two ways: 1) using synthetic images obtained from real masks, and 2) generating images from synthetic semantic masks. We show an improvement in performance when applying augmentation, gaining up to 18% in performance when using real masks and 4% when augmenting with synthetic masks. Finally, we employ this model to generate large-scale radio maps with the objective of simulating Data Challenges.

Van der Waals (vdW) materials, including hexagonal boron nitride (hBN), are layered crystalline solids with appealing properties for investigating light-matter interactions at the nanoscale. hBN has emerged as a versatile building block for nanophotonic structures, and the recent identification of native optically addressable spin defects has opened up exciting possibilities in quantum technologies. However, these defects exhibit relatively low quantum efficiencies and a broad emission spectrum, limiting potential applications. Optical metasurfaces present a novel approach to boost light emission efficiency, offering remarkable control over light-matter coupling at the sub-wavelength regime. Here, we propose and realise a monolithic scalable integration between intrinsic spin defects in hBN metasurfaces and high quality (Q) factor resonances leveraging quasi-bound states in the continuum (qBICs). Coupling between spin defect ensembles and qBIC resonances delivers a 25-fold increase in photoluminescence intensity, accompanied by spectral narrowing to below 4 nm linewidth facilitated by Q factors exceeding $10^2$. Our findings demonstrate a new class of spin based metasurfaces and pave the way towards vdW-based nanophotonic devices with enhanced efficiency and sensitivity for quantum applications in imaging, sensing, and light emission., Comment: accepted version

Two-dimensional (2D) semiconductors possess strongly bound excitons, opening novel opportunities for engineering light-matter interaction at the nanoscale. However, their in-plane confinement leads to large non-radiative exciton-exciton annihilation (EEA) processes, setting a fundamental limit for their photonic applications. In this work, we demonstrate suppression of EEA via enhancement of light-matter interaction in hybrid 2D semiconductor-dielectric nanophotonic platforms, by coupling excitons in WS$ _2 $ monolayers with optical Mie resonances in dielectric nanoantennas. The hybrid system reaches an intermediate light-matter coupling regime, with photoluminescence enhancement factors up to 10$ ^2 $. Probing the exciton ultrafast dynamics reveal suppressed EEA for coupled excitons, even under high exciton densities $>$ 10$^{12}$ cm$^{-2} $. We extract EEA coefficients in the order of 10$^{-3} $, compared to 10$^{-2} $ for uncoupled monolayers, as well as absorption enhancement of 3.9 and a Purcell factor of 4.5. Our results highlight engineering the photonic environment as a route to achieve higher quantum efficiencies for low-power hybrid devices, and larger exciton densities, towards strongly correlated excitonic phases in 2D semiconductors., Comment: Main text and supporting information, 32 pages, 4 Figures manuscript + 13 Supporting Figures

In recent years, deep learning has been successfully applied in various scientific domains. Following these promising results and performances, it has recently also started being evaluated in the domain of radio astronomy. In particular, since radio astronomy is entering the Big Data era, with the advent of the largest telescope in the world - the Square Kilometre Array (SKA), the task of automatic object detection and instance segmentation is crucial for source finding and analysis. In this work, we explore the performance of the most affirmed deep learning approaches, applied to astronomical images obtained by radio interferometric instrumentation, to solve the task of automatic source detection. This is carried out by applying models designed to accomplish two different kinds of tasks: object detection and semantic segmentation. The goal is to provide an overview of existing techniques, in terms of prediction performance and computational efficiency, to scientists in the astrophysics community who would like to employ machine learning in their research.

Graph-structured scene descriptions can be efficiently used in generative models to control the composition of the generated image. Previous approaches are based on the combination of graph convolutional networks and adversarial methods for layout prediction and image generation, respectively. In this work, we show how employing multi-head attention to encode the graph information, as well as using a transformer-based model in the latent space for image generation can improve the quality of the sampled data, without the need to employ adversarial models with the subsequent advantage in terms of training stability. The proposed approach, specifically, is entirely based on transformer architectures both for encoding scene graphs into intermediate object layouts and for decoding these layouts into images, passing through a lower dimensional space learned by a vector-quantized variational autoencoder. Our approach shows an improved image quality with respect to state-of-the-art methods as well as a higher degree of diversity among multiple generations from the same scene graph. We evaluate our approach on three public datasets: Visual Genome, COCO, and CLEVR. We achieve an Inception Score of 13.7 and 12.8, and an FID of 52.3 and 60.3, on COCO and Visual Genome, respectively. We perform ablation studies on our contributions to assess the impact of each component. Code is available at https://github.com/perceivelab/trf-sg2im

New developments in data processing and visualization are being made in preparation for upcoming radioastronomical surveys planned with the Square Kilometre Array (SKA) and its precursors. A major goal is enabling extraction of science information from the data in a mostly automated way, possibly exploiting the capabilities offered by modern computing infrastructures and technologies. In this context, the integration of source analysis algorithms into data visualization tools is expected to significantly improve and speed up the cataloguing process of large area surveys. To this aim, the CIRASA (Collaborative and Integrated platform for Radio Astronomical Source Analysis) project was recently started to develop and integrate a set of services for source extraction, classification and analysis into the ViaLactea visual analytic platform and knowledge base archive. In this contribution, we will present the project objectives and tools that have been developed, interfaced and deployed so far on the prototype European Open Science Cloud (EOSC) infrastructure provided by the H2020 NEANIAS project., Comment: 4 pages, 3 figures, proceedings of ADASS XXXI conference, to be published in ASP Conference Series

Source finding is one of the most challenging tasks in upcoming radio continuum surveys with SKA precursors, such as the Evolutionary Map of the Universe (EMU) survey of the Australian SKA Pathfinder (ASKAP) telescope. The resolution, sensitivity, and sky coverage of such surveys is unprecedented, requiring new features and improvements to be made in existing source finders. Among them, reducing the false detection rate, particularly in the Galactic plane, and the ability to associate multiple disjoint islands into physical objects. To bridge this gap, we developed a new source finder, based on the Mask R-CNN object detection framework, capable of both detecting and classifying compact, extended, spurious, and poorly imaged sources in radio continuum images. The model was trained using ASKAP EMU data, observed during the Early Science and pilot survey phase, and previous radio survey data, taken with the VLA and ATCA telescopes. On the test sample, the final model achieves an overall detection completeness above 85\%, a reliability of $\sim$65\%, and a classification precision/recall above 90\%. Results obtained for all source classes are reported and discussed., Comment: 18 pages, 11 figures

All-dielectric optical metasurfaces with high quality (Q) factors have so far been hampered by the lack of simultaneously lossless and high refractive index (RI) materials over the full visible spectrum. To achieve broad spectral coverage, the use of low-index materials is, in fact, unavoidable due to the inverse correlation between the band-gap energy (and therefore the optical losses) and the RI. However, for Mie resonant photonics, smaller RIs are associated with reduced Q factors and mode volume confinement. In this work, we leverage symmetry-broken bound states in the continuum (BICs) to efficiently suppress radiation losses from the low-index (n~2) van der Waals material hexagonal boron nitride (hBN), realizing metasurfaces with high-Q resonances over the complete visible spectrum. In particular, we analyze the rational use of low and high RI materials as resonator components and harness our insights to experimentally demonstrate sharp BIC resonances with Q factors above 300, spanning wavelengths between 400 nm and 1000 nm from a single hBN flake. Moreover, we utilize the enhanced electric near-fields to demonstrate second harmonic generation (SHG) with enhancement factors above 102. Our results provide a theoretical and experimental framework for the implementation of low RI materials as photonic media for metaoptics., Comment: Main text and supporting information, 23 pages, 4 Figures manuscript + 4 Supporting Figures

The NISP (Near Infrared Spectrometer and Photometer) is one of the two Euclid instruments. It operates in the near-IR spectral region (950-2020nm) as a photometer and spectrometer. The instrument is composed of: a cold (135 K) optomechanical subsystem consisting of a Silicon carbide structure, an optical assembly, a filter wheel mechanism, a grism wheel mechanism, a calibration unit, and a thermal control system, a detection system based on a mosaic of 16 H2RG with their front-end readout electronic, and a warm electronic system (290 K) composed of a data processing / detector control unit and of an instrument control unit that interfaces with the spacecraft via a 1553 bus for command and control and via Spacewire links for science data. This paper presents: the final architecture of the flight model instrument and subsystems, and the performance and the ground calibration measurement done at NISP level and at Euclid Payload Module level at operational cold temperature., Comment: 18 pages, to appear in Proceedings of the SPIE

Photonic bound states in the continuum (BICs) are a standout nanophotonic platform for strong light-matter coupling with transition metal dichalcogenides (TMDCs), but have so far mostly been employed as all-dielectric metasurfaces with adjacent TMDC layers, incurring limitations related to strain, mode overlap, and material integration. In this work, we experimentally demonstrate for the first time asymmetry-dependent BIC resonances in 2D arrays of monolithic metasurfaces composed solely of the nanostructured bulk TMDC WS$_2$ with BIC modes exhibiting sharp and tailored linewidths, ideal for selectively enhancing light-matter interactions. Geometrical variation enables the tuning of the BIC resonances across the exciton resonance in bulk WS$_2$, revealing the strong-coupling regime with an anti-crossing pattern and a Rabi splitting of 116 meV. The precise control over the radiative loss channel provided by the BIC concept is harnessed to tailor the Rabi splitting via a geometrical asymmetry parameter of the metasurface. Crucially, the coupling strength itself can be controlled and is shown to be independent of material-intrinsic losses. Our BIC-driven monolithic metasurface platform can readily incorporate other TMDCs or excitonic materials to deliver previously unavailable fundamental insights and practical device concepts for polaritonic applications., Comment: Main text and supporting information, 31 pages, 4 Figures manuscript + 8 Supporting Figures

Numerous optical phenomena and applications have been enabled by nanophotonic structures. Their current fabrication from high refractive index dielectrics, such as silicon or gallium phosphide, pose restricting fabrication challenges, while metals, relying on plasmons and thus exhibiting high ohmic losses, limit the achievable applications. Here, we present an emerging class of layered so-called van der Waals (vdW) crystals as a viable nanophotonics platform. We extract the dielectric response of 11 mechanically exfoliated thin-film (20-200 nm) van der Waals crystals, revealing high refractive indices up to n = 5, pronounced birefringence up to $\Delta$n = 3, sharp absorption resonances, and a range of transparency windows from ultraviolet to near-infrared. We then fabricate nanoantennas on SiO$_2$ and gold utilizing the compatibility of vdW thin films with a variety of substrates. We observe pronounced Mie resonances due to the high refractive index contrast on SiO$_2$ leading to a strong exciton-photon coupling regime as well as largely unexplored high-quality-factor, hybrid Mie-plasmon modes on gold. We demonstrate further vdW-material-specific degrees of freedom in fabrication by realizing nanoantennas from stacked twisted crystalline thin-films, enabling control of nonlinear optical properties, and post-fabrication nanostructure transfer, important for nano-optics with sensitive materials.

Generating images from semantic visual knowledge is a challenging task, that can be useful to condition the synthesis process in complex, subtle, and unambiguous ways, compared to alternatives such as class labels or text descriptions. Although generative methods conditioned by semantic representations exist, they do not provide a way to control the generation process aside from the specification of constraints between objects. As an example, the possibility to iteratively generate or modify images by manually adding specific items is a desired property that, to our knowledge, has not been fully investigated in the literature. In this work we propose a transformer-based approach conditioned by scene graphs that, conversely to recent transformer-based methods, also employs a decoder to autoregressively compose images, making the synthesis process more effective and controllable. The proposed architecture is composed by three modules: 1) a graph convolutional network, to encode the relationships of the input graph; 2) an encoder-decoder transformer, which autoregressively composes the output image; 3) an auto-encoder, employed to generate representations used as input/output of each generation step by the transformer. Results obtained on CIFAR10 and MNIST images show that our model is able to satisfy semantic constraints defined by a scene graph and to model relations between visual objects in the scene by taking into account a user-provided partial rendering of the desired target.

All-dielectric nanophotonics underpinned by the physics of bound states in the continuum (BICs) have demonstrated breakthrough applications in nanoscale light manipulation, frequency conversion and optical sensing. Leading BIC implementations range from isolated nanoantennas with localized electromagnetic fields to symmetry-protected metasurfaces with controllable resonance quality (Q) factors. However, they either require structured light illumination with complex beam-shaping optics or large, fabrication-intense arrays of polarization-sensitive unit cells, hindering tailored nanophotonic applications and on-chip integration. Here, we introduce radial quasi bound states in the continuum (radial BICs) as a new class of radially distributed electromagnetic modes controlled by structural asymmetry in a ring of dielectric rod pair resonators. The radial BIC platform provides polarization-invariant and tunable high-Q resonances with strongly enhanced near fields in an ultracompact footprint as low as 2 $\mu$m$^2$. We demonstrate radial BIC realizations in the visible for sensitive biomolecular detection and enhanced second-harmonic generation from monolayers of transition metal dichalcogenides, opening new perspectives for compact, spectrally selective, and polarization-invariant metadevices for multi-functional light-matter coupling, multiplexed sensing, and high-density on-chip photonics., Comment: Accepted version and supporting information, 4 Figures manuscript + 14 Supporting Figures