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The High Energy Modular Array (HEMA) is one of three instruments that compose the STROBE-X mission concept. The HEMA is a large-area, high-throughput non-imaging pointed instrument based on the Large Area Detector developed as part of the LOFT mission concept. It is designed for spectral timing measurements of a broad range of sources and provides a transformative increase in sensitivity to X-rays in the energy range of 2--30 keV compared to previous instruments, with an effective area of 3.4 m$^{2}$ at 8.5 keV and an energy resolution of better than 300 eV at 6 keV in its nominal field of regard., Comment: 16 pages, 10 figures

HERMES-Pathfinder is a space-borne mission based on a constellation of six nano-satellites flying in a low-Earth orbit. The 3U CubeSats, to be launched in early 2025, host miniaturized instruments with a hybrid Silicon Drift Detector/scintillator photodetector system, sensitive to both X-rays and gamma-rays. A seventh payload unit is installed onboard SpIRIT, an Australian-Italian nano-satellite developed by a consortium led by the University of Melbourne and launched in December 2023. The project aims at demonstrating the feasibility of Gamma-Ray Burst detection and localization using miniaturized instruments onboard nano-satellites. The HERMES flight model payloads were exposed to multiple well-known radioactive sources for spectroscopic calibration under controlled laboratory conditions. The analysis of the calibration data allows both to determine the detector parameters, necessary to map instrumental units to accurate energy measurements, and to assess the performance of the instruments. We report on these efforts and quantify features such as spectroscopic resolution and energy thresholds, at different temperatures and for all payloads of the constellation. Finally we review the performance of the HERMES payload as a photon counter, and discuss the strengths and the limitations of the architecture.

HERMES (High Energy Rapid Modular Ensemble of Satellites) Pathfinder mission aims to observe and localize Gamma Ray Bursts (GRBs) and other transients using a constellation of nanosatellites in low-Earth orbit (LEO). Scheduled for launch in early 2025, the 3U CubeSats will host miniaturized instruments featuring a hybrid Silicon Drift Detector (SDD) and GAGG:Ce scintillator photodetector system, sensitive to X-rays and gamma-rays across a wide energy range. Each HERMES payload contains 120 SDD cells, each with a sensitive area of 45 mm^2, organized into 12 matrices, reading out 60 12.1x6.94x15.0 mm^3 GAGG:Ce scintillators. Photons interacting with an SDD are identified as X-ray events (2-60 keV), while photons in the 20-2000 keV range absorbed by the crystals produce scintillation light, which is read by two SDDs, allowing event discrimination. The detector system, including front-end and back-end electronics, a power supply unit, a chip-scale atomic clock, and a payload data handling unit, fits within a 10x10x10 cm^3 volume, weighs 1.5 kg, and has a maximum power consumption of about 2 W. This paper outlines the development of the HERMES constellation, the design and selection of the payload detectors, and laboratory testing, presenting the results of detector calibrations and environmental tests to provide a comprehensive status update of the mission., Comment: 8 pages, 6 figures. Proceedings of SPIE 13093, Space Telescopes and Instrumentation 2024: Ultraviolet to Gamma Ray

HERMES (High Energy Rapid Modular Ensemble of Satellites) Pathfinder is a space-borne mission based on a constellation of six nano-satellites flying in a low-Earth orbit (LEO). The 3U CubeSats, to be launched in early 2025, host miniaturized instruments with a hybrid Silicon Drift Detector/GAGG:Ce scintillator photodetector system, sensitive to X-rays and gamma-rays in a large energy band. HERMES will operate in conjunction with Australian Space Industry Responsive Intelligent Thermal (SpIRIT) 6U CubeSat, launched in December 2023. HERMES will probe the temporal emission of bright high-energy transients such as Gamma-Ray Bursts (GRBs), ensuring a fast transient localization in a field of view of several steradians exploiting the triangulation technique. HERMES intrinsically modular transient monitoring experiment represents a keystone capability to complement the next generation of gravitational wave experiments. In this paper we outline the scientific case, development and programmatic status of the mission, Comment: 13 pages, 16 figures. Proceedings of SPIE "Astronomical Telescopes and Instrumentation" 2024. arXiv admin note: text overlap with arXiv:2210.13866

Covariance matrices provide a valuable source of information about complex interactions and dependencies within the data. However, from a clustering perspective, this information has often been underutilized and overlooked. Indeed, commonly adopted distance-based approaches tend to rely primarily on mean levels to characterize and differentiate between groups. Recently, there have been promising efforts to cluster covariance matrices directly, thereby distinguishing groups solely based on the relationships between variables. From a model-based perspective, a probabilistic formalization has been provided by considering a mixture model with component densities following a Wishart distribution. Notwithstanding, this approach faces challenges when dealing with a large number of variables, as the number of parameters to be estimated increases quadratically. To address this issue, we propose a sparse Wishart mixture model, which assumes that the component scale matrices possess a cluster-dependent degree of sparsity. Model estimation is performed by maximizing a penalized log-likelihood, enforcing a covariance graphical lasso penalty on the component scale matrices. This penalty not only reduces the number of non-zero parameters, mitigating the challenges of high-dimensional settings, but also enhances the interpretability of results by emphasizing the most relevant relationships among variables. The proposed methodology is tested on both simulated and real data, demonstrating its ability to unravel the complexities of neuroimaging data and effectively cluster subjects based on the relational patterns among distinct brain regions.

Pairwise likelihood is a useful approximation to the full likelihood function for covariance estimation in high-dimensional context. It simplifies high-dimensional dependencies by combining marginal bivariate likelihood objects, thus making estimation more manageable. In certain models, including the Gaussian model, both pairwise and full likelihoods are maximized by the same parameter values, thus retaining optimal statistical efficiency, when the number of variables is fixed. Leveraging on this insight, we introduce estimation of sparse high-dimensional covariance matrices by maximizing a truncated version of the pairwise likelihood function, obtained by including pairwise terms corresponding to nonzero covariance elements. To achieve a meaningful truncation, we propose to minimize the $L_2$-distance between pairwise and full likelihood scores plus an $L_1$-penalty discouraging the inclusion of uninformative terms. Differently from other regularization approaches, our method focuses on selecting whole pairwise likelihood objects rather than shrinking individual covariance parameters, thus retaining the inherent unbiasedness of the pairwise likelihood estimating equations. This selection procedure is shown to have the selection consistency property as the covariance dimension increases exponentially fast. Consequently, the implied pairwise likelihood estimator is consistent and converges to the oracle maximum likelihood estimator assuming knowledge of nonzero covariance entries., Comment: 37 pages

Animals have evolved to rapidly detect and recognise brief and intermittent encounters with odour packages, exhibiting recognition capabilities within milliseconds. Artificial olfaction has faced challenges in achieving comparable results -- existing solutions are either slow; or bulky, expensive, and power-intensive -- limiting applicability in real-world scenarios for mobile robotics. Here we introduce a miniaturised high-speed electronic nose; characterised by high-bandwidth sensor readouts, tightly controlled sensing parameters and powerful algorithms. The system is evaluated on a high-fidelity odour delivery benchmark. We showcase successful classification of tens-of-millisecond odour pulses, and demonstrate temporal pattern encoding of stimuli switching with up to 60 Hz. Those timescales are unprecedented in miniaturised low-power settings, and demonstrably exceed the performance observed in mice. For the first time, it is possible to match the temporal resolution of animal olfaction in robotic systems. This will allow for addressing challenges in environmental and industrial monitoring, security, neuroscience, and beyond.

Although entanglement is both a central ingredient in our understanding of quantum many-body systems and an essential resource for quantum technologies, we only have a limited ability to quantify entanglement in real quantum materials. Thus far, entanglement metrology in quantum materials has been limited to measurements involving Hermitian operators, such as the detection of spin entanglement using inelastic neutron scattering. Here, we devise a method to extract the quantum Fisher information (QFI) from non-Hermitian operators and formulate an entanglement witness for resonant inelastic x-ray scattering (RIXS). Our approach is then applied to the model iridate dimer system Ba$_3$CeIr$_2$O$_9$ and used to directly test for entanglement of the electronic orbitals between neighboring Ir sites. We find that entanglement is challenging to detect under standard conditions, but that it could be achieved by analyzing the outgoing x-ray polarization or via specific choices of momentum and energy. Our protocol provides a new handle for entanglement detection, which offers routes to related types of entanglement witness (such as orbitally-resolved measurements) and to the generalization to out-of-equilibrium settings accessed in ultrafast settings., Comment: 10 pages, 8 figures

The HERMES Technologic and Scientific Pathfinder project is a constellation of six CubeSats aiming to observe transient high-energy events such as the Gamma Ray Bursts (GRBs). HERMES will be the first space telescope to include a siswich detector, able to perform spectroscopy in the 2 keV to 2 MeV energy band. The particular siswich architecture, which combines a solid-state Silicon Drift Detector and a scintillator crystal, requires specific calibration procedures that have not been yet standardized in a pipeline. We present in this paper the HERMES calibration pipeline, mescal, intended for raw HERMES data energy calibration and formatting. The software is designed to deal with the particularities of the siswich architecture and to minimize user interaction, including also an automated calibration line identification procedure, and an independent calibration of each detector pixel, in its two different operating modes. The mescal pipeline can set the basis for similar applications in future siswich telescopes.

The HERMES (High Energy Rapid Modular Ensemble of Satellites) Pathfinder mission aims to develop a constellation of nanosatellites to study astronomical transient sources, such as gamma-ray bursts, in the X and soft $\gamma$ energy range, exploiting a novel inorganic scintillator. This study presents the results obtained describing, with an empirical model, the unusually intense and long-lasting residual emission of the GAGG:Ce scintillating crystal after irradiating it with high energy protons (70 MeV) and ultraviolet light ($\sim$ 300 nm). From the model so derived, the consequences of this residual luminescence for the detector performance in operational conditions has been analyzed. It was demonstrated that the current generated by the residual emission peaks at 1-2 pA, thus ascertaining the complete compatibility of this detector with the HERMES Pathfinder nanosatellites.

Widespread commercial adoption of telecom-band quantum-key-distribution (QKD) will require fully integrated, room-temperature transmitters. Implementing highly efficient spontaneous parametric down-conversion (SPDC) on a platform that offers co-integration of the pump laser has been an outstanding challenge. Here, using such a platform based on AlGaAs-on-insulator waveguides, we report telecom-band SPDC (and second harmonic generation) with exceedingly large efficiencies of 26 GHz generated pairs/mW over a 7 THz bandwidth, which would saturate the usable photon-flux for a 70-channel wavelength-multiplexed QKD-system at merely 1.6 mW of pump laser power.

The $5d^1$ ordered double perovskites present an exotic playground for studying novel multi-polar physics due to large spin-orbit coupling. We present Re L3 edge resonant inelastic X-ray scattering (RIXS) results that reveal the presence of the dynamic Jahn-Teller effect in the A$_2$MgReO$_6$ (A = Ca, Sr, Ba) family of $5d^1$ double perovskites. The spin-orbit excitations in these materials show a strongly asymmetric lineshape and exhibit substantial temperature dependence, indicating that they are dressed with lattice vibrations. Our experimental results are explained quantitatively through a RIXS calculation based on a spin-orbit-lattice entangled electronic ground state with the dynamic Jahn-Teller effect taken into consideration. We find that the spin-orbit-lattice entangled state is robust against magnetic and structural phase transitions as well as against significant static Jahn-Teller distortions. Our results illustrate the importance of including vibronic coupling for a complete description of the ground state physics of $5d^1$ double perovskites. Usage: Secondary publications and information retrieval purposes.

We reveal in this study the fundamental low-energy landscape in the ferrimagnetic Sr2CrReO6 double perovskite and describe the underlying mechanisms responsible for the three low-energy excitations below 1.4 eV. Based on resonant inelastic x-ray scattering and magnetic dynamics calculations, and experiments collected from both Sr2CrReO6 powders and epitaxially strained thin films, we reveal a strong competition between spin-orbit coupling, Hund's coupling, and the strain-induced tetragonal crystal field. We also demonstrate that a spin-flip process is at the origin of the lowest excitation at 200 meV, and we bring insights into the predicted presence of orbital ordering in this material. We study the nature of the magnons through a combination of ab initio and spin-wave theory calculations, and show that two nondegenerate magnon bands exist and are dominated either by rhenium or chromium spins. The rhenium band is found to be flat at about 200 meV ($\pm$25 meV) through X-L-W-U high-symmetry points and is dispersive toward $\Gamma$, Comment: 6 figures

A comparative resonant inelastic x-ray scattering (RIXS) study of three well-known Kitaev materials is presented: $\alpha$-Li$_2$IrO$_3$, Na$_2$IrO$_3$, and $\alpha$-RuCl$_3$. Despite similar low-energy physics, these materials show distinct electronic properties, such as the large difference in the size of the charge gap. The RIXS spectra of the spin-orbit exciton for these materials show remarkably similar three-peak features, including sharp low energy peak (peak A) as well as transitions between $j_{\text{eff}}=1/2$ and $j_{\text{eff}}=3/2$ states. Comparison of experimental spectra with cluster calculations reveals that the observed three-peak structure reflects the significant role that non-local physics plays in the electronic structure of these materials. In particular, the low-energy peak A arises from a holon-doublon pair rather than a conventional particle-hole exciton as proposed earlier. Our study suggests that while spin-orbit assisted Mott insulator is still the best description for these materials, electron itinerancy cannot be ignored when formulating low-energy Hamiltonian of these materials.

The attention towards food products characteristics, such as nutritional properties and traceability, has risen substantially in the recent years. Consequently, we are witnessing an increased demand for the development of modern tools to monitor, analyse and assess food quality and authenticity. Within this framework, an essential set of data collection techniques is provided by vibrational spectroscopy. In fact, methods such as Fourier near infrared and mid infrared spectroscopy have been often exploited to analyze different foodstuffs. Nonetheless, existing statistical methods often struggle to deal with the challenges presented by spectral data, such as their high dimensionality, paired with strong relationships among the wavelengths. Therefore, the definition of proper statistical procedures accounting for the peculiarities of spectroscopy data is paramount. In this work, motivated by two dairy science applications, we propose an adaptive functional regression framework for spectroscopy data. The method stems from the trend filtering literature, allowing the definition of a highly flexible and adaptive estimator able to handle different degrees of smoothness. We provide a fast optimization procedure that is suitable for both Gaussian and non Gaussian scalar responses, and allows for the inclusion of scalar covariates. Moreover, we develop inferential procedures for both the functional and the scalar component thus enhancing not only the interpretability of the results, but also their usability in real world scenarios. The method is applied to two sets of MIR spectroscopy data, providing excellent results when predicting milk chemical composition and cows' dietary treatments. Moreover, the developed inferential routine provides relevant insights, potentially paving the way for a richer interpretation and a better understanding of the impact of specific wavelengths on milk features., Comment: 20 pages, 3 figures

Mixtures of matrix Gaussian distributions provide a probabilistic framework for clustering continuous matrix-variate data, which are becoming increasingly prevalent in various fields. Despite its widespread adoption and successful application, this approach suffers from over-parameterization issues, making it less suitable even for matrix-variate data of moderate size. To overcome this drawback, we introduce a sparse model-based clustering approach for three-way data. Our approach assumes that the matrix mixture parameters are sparse and have different degree of sparsity across clusters, allowing to induce parsimony in a flexible manner. Estimation of the model relies on the maximization of a penalized likelihood, with specifically tailored group and graphical lasso penalties. These penalties enable the selection of the most informative features for clustering three-way data where variables are recorded over multiple occasions and allow to capture cluster-specific association structures. The proposed methodology is tested extensively on synthetic data and its validity is demonstrated in application to time-dependent crime patterns in different US cities.

We use resonant inelastic x-ray scattering (RIXS) at the O $K$- and Cu $K$-edges to investigate the doping- and temperature dependence of low-energy plasmon excitations in La$_{2-x}$Sr$_{x}$CuO$_4$. We observe a monotonic increase of the energy scale of the plasmons with increasing doping $x$ in the underdoped regime, whereas a saturation occurs above optimal doping $x \gtrsim 0.16$ and persists at least up to $x = 0.4$. Furthermore, we find that the plasmon excitations show only a marginal temperature dependence, and possible effects due to the superconducting transition and the onset of strange metal behavior are either absent or below the detection limit of our experiment. Taking into account the strongly correlated character of the cuprates, we show that layered $t$-$J$-$V$ model calculations accurately capture the increase of the plasmon energy in the underdoped regime. However, the computed plasmon energy continues to increase even for doping levels above $x \gtrsim 0.16$, which is distinct from the experimentally observed saturation, and reaches a broad maximum around $x = 0.55$. We discuss whether possible lattice disorder in overdoped samples, a renormalization of the electronic correlation strength at high dopings, or an increasing relevance of non-planar Cu and O orbitals could be responsible for the discrepancy between experiment and theory for doping levels above $x = 0.16$., Comment: 19 pages, 11 figures

HERMES (High Energy Rapid Modular Ensemble of Satellites) is a space-borne mission based on a constellation of nano-satellites flying in a low-Earth orbit (LEO). The six 3U CubeSat buses host new miniaturized instruments hosting a hybrid Silicon Drift Detector/GAGG:Ce scintillator photodetector system sensitive to X-rays and gamma-rays. HERMES will probe the temporal emission of bright high-energy transients such as Gamma-Ray Bursts (GRBs), ensuring a fast transient localization (with arcmin-level accuracy) in a field of view of several steradians exploiting the triangulation technique. With a foreseen launch date in late 2023, HERMES transient monitoring represents a keystone capability to complement the next generation of gravitational wave experiments. Moreover, the HERMES constellation will operate in conjunction with the Space Industry Responsive Intelligent Thermal (SpIRIT) 6U CubeSat, to be launched in early 2023. SpIRIT is an Australian-Italian mission for high-energy astrophysics that will carry in a Sun-synchronous orbit (SSO) an actively cooled HERMES detector system payload. On behalf of the HERMES collaboration, in this paper we will illustrate the HERMES and SpIRIT payload design, integration and tests, highlighting the technical solutions adopted to allow a wide-energy-band and sensitive X-ray and gamma-ray detector to be accommodated in a 1U Cubesat volume., Comment: arXiv admin note: substantial text overlap with arXiv:2101.03032

HERMES (High Energy Rapid Modular Ensemble of Satellites) is a space-borne mission based on a constellation of six 3U CubeSats flying in a low-Earth orbit, hosting new miniaturized instruments based on a hybrid Silicon Drift Detector/GAGG:Ce scintillator photodetector system sensitive to X-rays and gamma-rays. Moreover, the HERMES constellation will operate in conjunction with the Australian-Italian Space Industry Responsive Intelligent Thermal (SpIRIT) 6U CubeSat, that will carry in a Sun-synchronous orbit (SSO) an actively cooled HERMES detector system payload. In this paper we provide an overview of the ground calibrations of the first HERMES and SpIRIT flight detectors, outlining the calibration plan, detector performance and characterization., Comment: 9 pages, 7 figures. Proceedings of SPIE Astronomical Telescopes and Instrumentation 2022

In April 2022, the Vistamilk SFI Research Centre organized the second edition of the "International Workshop on Spectroscopy and Chemometrics - Applications in Food and Agriculture". Within this event, a data challenge was organized among participants of the workshop. Such data competition aimed at developing a prediction model to discriminate dairy cows' diet based on milk spectral information collected in the mid-infrared region. In fact, the development of an accurate and reliable discriminant model for dairy cows' diet can provide important authentication tools for dairy processors to guarantee product origin for dairy food manufacturers from grass-fed animals. Different statistical and machine learning modelling approaches have been employed during the workshop, with different pre-processing steps involved and different degree of complexity. The present paper aims to describe the statistical methods adopted by participants to develop such classification model., Comment: 27 pages, 9 figures

CASA, the Common Astronomy Software Applications, is the primary data processing software for the Atacama Large Millimeter/submillimeter Array (ALMA) and the Karl G. Jansky Very Large Array (VLA), and is frequently used also for other radio telescopes. The CASA software can handle data from single-dish, aperture-synthesis, and Very Long Baseline Interferometery (VLBI) telescopes. One of its core functionalities is to support the calibration and imaging pipelines for ALMA, VLA, VLA Sky Survey (VLASS), and the Nobeyama 45m telescope. This paper presents a high-level overview of the basic structure of the CASA software, as well as procedures for calibrating and imaging astronomical radio data in CASA. CASA is being developed by an international consortium of scientists and software engineers based at the National Radio Astronomical Observatory (NRAO), the European Southern Observatory (ESO), the National Astronomical Observatory of Japan (NAOJ), and the Joint Institute for VLBI European Research Infrastructure Consortium (JIV-ERIC), under the guidance of NRAO., Comment: Accepted for publication in PASP (20 pages, 4 figures). Joint publication with CASA-VLBI paper

Coexistence of localized and extended excitations is central to the macroscopic properties of correlated materials. For 5d transition metal compounds, electron correlations alone generally do not lead to a metal-insulator (Mott) transition, with insulating behavior usually resulting from their coupling with magnetic ordering and/or structural distortions. 1$T$-TaS$_2$ is a prototypical example of such correlated insulating behavior, with a high-symmetry metallic phase transforming into a distorted, charge density wave (CDW) insulating state at low temperatures. The relevance of the localized electron physics at play in 3d compounds to these 5d transition metal compounds remains an open question. We resolved this standing controversy in 1$T$-TaS$_2$ combining resonant inelastic X-ray spectroscopy and first-principles calculations. We observed five electronic excitations arising from the interband transitions of the Ta 5d orbitals and the S 3p ligand state, with none of the excitations on the order of the Mott gap. These excitations cannot be explained within the framework of standard multiplet calculations that assume a localized wavefunction, but instead, are captured by a band theory framework accounting for the low symmetry of the crystal field in the CDW state. Our findings suggest that the electronic property of 1$T$-TaS$_2$ is dominated by both plasmonic quasiparticles and inter-band transitions associated with a Drude-type response, with no resonance associated with a putative Mott transition. Our discovery provides new insights into the electron localization and the onset of insulating behavior in 5d transition metal materials.

The Spin-Orbit Proximity Effect is the raise of Spin-Orbit Coupling at a layer near to the interface with a strong spin-orbit material. It has been seen in several system such as graphene and ferromagnetic layers. The control of the Spin-Orbit Coupling can be a pathway to discover novel and exotic phases in superconductor and semimetallic systems. Here, we study the magnetoelectrical transport, i.e., magnetoresistance and anomalous Hall effect, in Cobalt/Bismuth multilayers looking for traces of spin-orbit proximity effect and evaluate the origin of such effect. Our results point for an increase of Spontaneous Magnetic Anisotropy of Resistivity and Anomalous Hall Resistivity at very low thicknesses of Cobalt. The analysis of the Anomalous Hall Resisitivity indicate that the Bismuth layers change the scattering mechanism of Hall effect to the extrinsic skew-scattering type, indicating that the spin-orbit proximity effect could be related to the elastic scattering of cobalt free carriers by bismuth sites at the interface., Comment: 6 pages, 4 figures

We investigate the electronic structure of two Ir$^{5+}$ honeycomb iridates, Sr$_3$CaIr$_2$O$_9$ and NaIrO$_3$, by means of resonant x-ray techniques. We confirm that Sr$_3$CaIr$_2$O$_9$ realizes a large spin-orbit driven non-magnetic $J = 0$ singlet ground state despite sizable tetragonal distortions of Ir coordinating octahedra. On the other hand, the resonant inelastic x-ray spectra of NaIrO$_3$ are drastically different from expectations for a Mott insulator with octahedrally coordinated Ir$^{5+}$. We find that the data for NaIrO$_3$ can be best interpreted as originating from a narrow gap non-magnetic $S = 0$ band insulating ground state. Our results highlight the complex role of the ligand environment in the electronic structure of honeycomb iridates and the essential role of x-ray spectroscopy to characterize electronic ground states of insulating materials.

By performing resonant inelastic x-ray scattering (RIXS) measurements at the Ir $\mathit{L_{\mathrm{3}}}$ edge, we have investigated the low-energy elementary excitations in a series of double perovskite iridate single crystals, La$_{2}$$\mathit{M}$IrO$_{6}$ ($\mathit{M}$ = Co, Ni, and Zn). Almost dispersionless magnetic excitations at $\sim$ 42(6) meV and $\sim$ 35(5) meV have been observed in crystals containing magnetic 3$\mathit{d}$ ions, La$_{2}$CoIrO$_{6}$ and La$_{2}$NiIrO$_{6}$, respectively. In contrast, this low-energy magnetic excitation is absent in La$_{2}$ZnIrO$_{6}$ in which the 3$\mathit{d}$ ions are non-magnetic, suggesting the importance of 3$\mathit{d}$-5$\mathit{d}$ hybridization in the magnetic properties of these double perovskite iridates. The magnetic excitation is suppressed completely above the magnetic ordering temperature, suggesting the inadequacy of using a simple spin Hamiltonian to describe magnetism of these materials., Comment: 8 pages, 4 figures, accepted for publication in Physical Review B

Excitonic insulators are usually considered to form via the condensation of a soft charge mode of bound electron-hole pairs. This, however, presumes that the soft exciton is of spin-singlet character. Early theoretical considerations have also predicted a very distinct scenario, in which the condensation of magnetic excitons results in an antiferromagnetic excitonic insulator state. Here we report resonant inelastic x-ray scattering (RIXS) measurements of Sr3Ir2O7. By isolating the longitudinal component of the spectra, we identify a magnetic mode that is well-defined at the magnetic and structural Brillouin zone centers, but which merges with the electronic continuum in between these high-symmetry points and which decays upon heating concurrent with a decrease in the material's resistivity. We show that a bilayer Hubbard model, in which electron-hole pairs are bound by exchange interactions, consistently explains all the electronic and magnetic properties of Sr3Ir2O7 indicating that this material is a realization of the long-predicted antiferromagnetic excitonic insulators phase., Comment: accepted in Nature Communications; 6 pages main materials

Spinons are well-known as the elementary excitations of one-dimensional antiferromagnetic chains, but means to realize spinons in higher dimensions is the subject of intense research. Here, we use resonant x-ray scattering to study the layered trimer iridate Ba4Ir3O10, which shows no magnetic order down to 0.2 K. An emergent one-dimensional spinon continuum is observed that can be well-described by XXZ spin-1/2 chains with magnetic exchange of ~55 meV and a small Ising-like anisotropy. With 2% isovalent Sr doping, magnetic order appears below TN=130 K along with sharper excitations, indicating that the spinons become more confined in (Ba1-xSrx)4Ir3O10. We propose that the frustrated intra-trimer interactions effectively reduce the system into decoupled spin chains, the subtle balance of which can be easily tipped by perturbations such as chemical doping. Our results put Ba4Ir3O10 between the one-dimensional chain and two-dimensional quantum spin liquid scenarios, illustrating a new way to suppress magnetic order and realize fractional spinons., Comment: Accepted in Physical Review Letters; 5 pages not including references or supplementary

We discuss the results of a proton irradiation campaign of a GAGG:Ce (Cerium-doped Gadolinium Aluminium Gallium Garnet) scintillation crystal, carried out in the framework of the HERMES-TP/SP (High Energy Rapid Modular Ensemble of Satellites -- Technological and Scientific Pathfinder) mission. A scintillator sample was irradiated with 70 MeV protons, at levels equivalent to those expected in equatorial and sun-synchronous low-Earth orbits over orbital periods spanning 6 months to 10 years. The data we acquired are used to introduce an original model of GAGG:Ce afterglow emission. Results from this model are applied to the HERMES-TP/SP scenario, aiming at an upper-bound estimate of the detector performance degradation resulting from afterglow emission.

A chemometric data analysis challenge has been arranged during the first edition of the "International Workshop on Spectroscopy and Chemometrics", organized by the Vistamilk SFI Research Centre and held online in April 2021. The aim of the competition was to build a calibration model in order to predict milk quality traits exploiting the information contained in mid-infrared spectra only. Three different traits have been provided, presenting heterogeneous degrees of prediction complexity thus possibly requiring trait-specific modelling choices. In this paper the different approaches adopted by the participants are outlined and the insights obtained from the analyses are critically discussed., Comment: 17 pages, 6 figures, 6 tables

We use x-ray spectroscopy at Ir L$_3$/L$_2$ absorption edge to study powder samples of the intercalated honeycomb magnet Ag$_3$LiIr$_2$O$_6$. Based on x-ray absorption and resonant inelastic x-ray scattering measurements, and exact diagonalization calculations including next-neighbour Ir-Ir electron hoping integrals, we argue that the intercalation of Ag atoms results in a nearly itinerant electronic structure with enhanced Ir-O hybridization. As a result of the departure from the local relativistic $j_{\rm eff}\! = \!1/2$ state, we find that the relative orbital contribution to the magnetic moment is increased, and the magnetization density is spatially extended and asymmetric. Our results confirm the importance of metal - ligand hybridazation in the magnetism of transition metal oxides and provide empirical guidance for understanding the collective magnetism in intercalated honeycomb iridates.

Finite Gaussian mixture models provide a powerful and widely employed probabilistic approach for clustering multivariate continuous data. However, the practical usefulness of these models is jeopardized in high-dimensional spaces, where they tend to be over-parameterized. As a consequence, different solutions have been proposed, often relying on matrix decompositions or variable selection strategies. Recently, a methodological link between Gaussian graphical models and finite mixtures has been established, paving the way for penalized model-based clustering in the presence of large precision matrices. Notwithstanding, current methodologies implicitly assume similar levels of sparsity across the classes, not accounting for different degrees of association between the variables across groups. We overcome this limitation by deriving group-wise penalty factors, which automatically enforce under or over-connectivity in the estimated graphs. The approach is entirely data-driven and does not require additional hyper-parameter specification. Analyses on synthetic and real data showcase the validity of our proposal., Comment: 41 pages, 11 figures

Between the years 2015 and 2019, members of the Horizon 2020-funded Innovative Training Network named "AMVA4NewPhysics" studied the customization and application of advanced multivariate analysis methods and statistical learning tools to high-energy physics problems, as well as developed entirely new ones. Many of those methods were successfully used to improve the sensitivity of data analyses performed by the ATLAS and CMS experiments at the CERN Large Hadron Collider; several others, still in the testing phase, promise to further improve the precision of measurements of fundamental physics parameters and the reach of searches for new phenomena. In this paper, the most relevant new tools, among those studied and developed, are presented along with the evaluation of their performances., Comment: 101 pages, 21 figures, submitted to Elsevier. [v2]: Updated to published version (in 'Reviews in Physics')