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We investigate the topological properties of the Su-Schrieffer-Heeger (SSH) model under dissipative dynamics using the quantum trajectory approach. Our study explores the preservation or breakdown of topological edge states, particularly focusing on the effects of symmetry-preserving and symmetry-breaking dissipations. We employ the Disconnected Entanglement Entropy (DEE) as a marker for detecting topological phases in the system, which is subjected to Lindblad dynamics. The analysis reveals that, while dissipation in the bulk minimally affects the system's topological features, dissipation at the boundary leads to the destabilization of the edge modes, independently of the symmetry properties of the dissipation., Comment: 22 pages, 12 figures

In the present-day universe, the most massive galaxies are ellipticals located in the cores of galaxy clusters, harboring the heaviest super-massive black holes (SMBHs). However the mechanisms that drive the early growth phase and subsequent transformation of these morphology and kinematics of galaxies remain elusive. Here we report (sub)kiloparsec scale observations of stars, gas, and dust in ADF22.A1, a bright dusty starburst galaxy at z=3.1, hosting a heavily obscured active galactic nucleus and residing in a proto-cluster core. ADF22.A1 is a giant spiral galaxy with the kinematics of a rotating disk with rotation velocity Vrot=530+/-10km/s and diameter larger than 30 kpc. The high specific stellar angular momentum of this system, j*=3400+/-600 kpc km/s, requires a mechanism to effectively spin-up ADF22.A1, indicating the importance of accretion from the cosmic web to supply both gas and angular momentum to galaxies in their early gas-rich starburst phase. In its inner region, gas flows along dust lanes in a bar connected with the bright dusty core and the estimated mass ratio of a bulge to SMBH matches the local relation, suggesting that bars are a key mechanism to shape the early co-evolution of these components. Comparison with cosmological simulations shows that ADF22.A1 will likely evolve into a massive elliptical at the present day, experiencing a significant reduction in angular momentum associated with subsequent galaxy mergers., Comment: 13 pages, 12 figures. Submitted

Separation of the two mirror images of a chiral molecule, the enantiomers, is a historically complicated problem of major relevance for biological systems. Since chiral molecules are optically active, it has been speculated that strong coupling to circularly polarized fields may be used as a general procedure to unlock enantiospecific reactions. In this work, we focus on how chiral cavities can be used to drive asymmetry in the photochemistry of chiral molecular systems. We first show that strong coupling to circularly polarized fields leads to enantiospecific Rabi splittings, an effect that displays a collective behavior in line with other strong coupling phenomena. Additionally, entanglement with circularly polarized light generates an asymmetry in the enantiomer population of the polaritons, leading to a condensation of the excitation on a preferred molecular configuration. These results confirm that chiral cavities represent a tantalizing opportunity to drive asymmetric photochemistry in enantiomeric mixtures., Comment: 45 pages and 16 figures

The nearby transiting rocky exoplanet LTT 1445A b presents an ideal target for studying atmospheric retention in terrestrial planets orbiting M dwarfs. It is cooler than many rocky exoplanets yet tested for atmospheres, receiving a bolometric instellation similar to Mercury's. Previous transmission spectroscopy ruled out a light H/He-dominated atmosphere but could not distinguish between a bare-rock, a high-MMW, or a cloudy atmosphere. We present new secondary eclipse observations using JWST's MIRI/LRS, covering the 5-12 $\mu$m range. From these observations, we detect a broadband secondary eclipse depth of 41 $\pm$ 9 ppm and measure a mid-eclipse timing consistent with a circular orbit (at 1.7$\sigma$). From its emission spectrum, the planet's dayside brightness temperature is constrained to 525 $\pm$ 15 K, yielding a temperature ratio relative to the maximum average dayside temperature from instant thermal reradiation by a rocky surface $R$ = $T_{\rm day,obs}/T_{\rm max}$ = 0.952 $\pm$ 0.057, consistent with emission from a dark rocky surface. From an energy balance perspective, such a warm dayside temperature disfavors thick atmospheres, excluding $\sim$100 bar atmospheres with Bond albedo $>$ 0.08 at the 3$\sigma$ level. Furthermore, forward modeling of atmospheric emission spectra disfavor simple 100\% CO$_2$ atmospheres with surface pressures of 1, 10, and 100 bar at 4.2$\sigma$, 6.6$\sigma$, and 6.8$\sigma$ confidence, respectively. These results suggest that LTT 1445A b lacks a very thick CO$_2$ atmosphere, possibly due to atmospheric erosion driven by stellar activity. However, the presence of a moderately thin atmosphere (similar to those on Mars, Titan, or Earth) remains uncertain., Comment: 31 pages, 14 figures, submitted to AJ

We explore to which extent it is possible to construct efficient classical simulation of quantum many body systems using a combination of tensor network methods and the stabilizer formalism. For this we study both quantum circuit and Hamiltonian dynamics. We find that expectations of Pauli operators can be simulated efficiently even for deep Clifford circuits doped with T-gates or more general phase gates, provided the number of non-Clifford gates is smaller or approximately equal to the system size. This is despite the fact that the resulting states exhibit both extensive entanglement and extensive nonstabilizerness. For the Hamiltonian dynamics we find that the classical simulation generically quickly becomes inefficient, but suggest the use of matchgate circuits alongside tensor networks for the efficient simulation of many-body quantum systems near free-fermion integrability.

A key challenge in observing measurement-induced phase transitions is the mitigation of the post-selection barrier, which causes the reproducibility of specific sequences of measurement readouts--the trajectory--to be exponentially small in system size. Recent studies suggest that some classes of monitored infinite-range systems alleviate this problem by exhibiting a fast saturation of entanglement, resulting in only a polynomial post-selection overhead. This paper answers whether this feature is inherent in infinite-range systems, due to their underlying semiclassical dynamics. We consider three experimentally relevant monitored models: a Tavis-Cummings model, a Superradiance model, and a Bose-Hubbard dimer, each exhibiting non-trivial monitored dynamics. We unveil the occurrence of entanglement phase transitions in these models, showing how the saturation time is strongly affected by bistability regions, which also prevent the mitigation of the post-selection barrier. Finally, we propose experimental realizations of these models, providing a discussion of post selection from an experimental perspective., Comment: 31 pages, 27 figures

We present statistics of quantum jumps in the two-level system with landau-Zener Hamiltonian that undergoes a Markovian process. For the Landau-Zener model, which is successful in simulating adiabatic/non-adiabatic evolution and quantum annealing, we consider two types of dissipation. In the first one, the jump operators project states to the initial ground state and excited state of the Hamiltonian at $t\to -\infty$. In the second type, the jump operators project to the instantaneous eigenstates of the Hamiltonian. By the quantum trajectories approach, we present the probability of the number of jumps in adiabatic and non-adiabatic regimes for both models. Furthermore, we demonstrate the statistics of jumps in time intervals of the evolutions. Also, we show the role of bath temperature, coupling strength to the environment, and spin-coupling directions on the statistics of quantum jumps.

Plasma membranes appear as deformable systems wherein molecules are free to move and diffuse giving rise to condensed microdomains (composed of ordered lipids, transmembrane proteins and cholesterol) surrounded by disordered lipid molecules. Such denser and thicker regions, namely lipid rafts, are important communication hubs for cells. Indeed, recent experiments revealed how the most of active signaling proteins co-localize on such domains, thereby intensifying the biochemical trafficking of substances. From a material standpoint, it is reasonable to assume the bilayer as a visco-elastic body accounting for both in-plane fluidity and elasticity. Consequently, lipid rafts contribute to membrane heterogeneity by typically exhibiting higher stiffness and viscosity and by locally altering the bilayer dynamics and proteins activity. A chemo-mechanical model of lipid bilayer coupled with interspecific dynamics among the resident species (typically transmembrane receptors and trasporters) has been recently formulated to explain and predict how proteins regulate the dynamic heterogeneity of membrane. However, the explicit inclusion of the membrane viscosity in the model was not considered. To this aim, the present work enriches the constitutive description of the bilayer by modeling its visco-elastic behavior. This is done through a strain-level dependent viscosity able to theoretically trace back the alteration of membrane fluidity experimentally observed in lipid phase transitions. This provides new insights into how the quasi-solid and fluid components of lipid membrane response interact with the evolution of resident proteins by affecting the activity of raft domains, with effects on cell mechano-signaling., Comment: 26 pages, 7 figures

We focus on agile, continuous, and terrain-adaptive jumping of quadrupedal robots in discontinuous terrains such as stairs and stepping stones. Unlike single-step jumping, continuous jumping requires accurately executing highly dynamic motions over long horizons, which is challenging for existing approaches. To accomplish this task, we design a hierarchical learning and control framework, which consists of a learned heightmap predictor for robust terrain perception, a reinforcement-learning-based centroidal-level motion policy for versatile and terrain-adaptive planning, and a low-level model-based leg controller for accurate motion tracking. In addition, we minimize the sim-to-real gap by accurately modeling the hardware characteristics. Our framework enables a Unitree Go1 robot to perform agile and continuous jumps on human-sized stairs and sparse stepping stones, for the first time to the best of our knowledge. In particular, the robot can cross two stair steps in each jump and completes a 3.5m long, 2.8m high, 14-step staircase in 4.5 seconds. Moreover, the same policy outperforms baselines in various other parkour tasks, such as jumping over single horizontal or vertical discontinuities. Experiment videos can be found at https://yxyang.github.io/jumping_cod/, Comment: Website: https://yxyang.github.io/jumping_cod/

These Lecture Notes discuss the recent theoretical advances in the understanding of open quantum many-body physics in platforms where both dissipative and coherent processes can be tuned and controlled to a high degree. We start by reviewing the theoretical frameworks and methods used to describe and tackle open quantum many-body systems. We then discuss the use of dissipative processes to engineer many-body stationary states with desired properties and the emergence of dissipative phase transitions arising out of the competition between coherent evolution and dissipation. We review the dynamics of open quantum many body systems in the presence of correlated many-body dissipative processes, such as heating and many-body losses. Finally we provide a different perspective on open quantum many-body systems by looking at stochastic quantum trajectories, relevant for the case in which the environment represents a monitoring device, and the associated measurement-induced phase transitions., Comment: Lecture Notes, 185 pages, 40 figure

We analyze JWST MIRI/MRS IFU observations of three Seyferts and showcase the intriguing polycyclic aromatic hydrocarbon (PAH) emission characteristics in regions of $\sim 500\,\rm pc$ scales over or around their active galactic nuclei (AGN). Combining the model predictions and the measurements of PAH features and other infrared emission lines, we find that the central regions containing a high fraction of neutral PAHs with small sizes, e.g., those in ESO137-G034, are in highly heated environments, due to collisional shock heating, with hard and moderately intense radiation fields. Such environments are proposed to be associated with inhibited growth or preferential erosion of PAHs, decreasing the average PAH size and the overall abundance of PAHs. We additionally find that the central regions containing a high fraction of ionized PAHs with large sizes, e.g., those in MCG-05-23-016, are likely experiencing severe photo-ionization because of the radiative effects from the radiative shock precursor besides the AGN. The severe photo-ionization can contribute to the ionization of all PAHs and further destruction of small PAHs. Overall, different Seyferts, even different regions in the same galaxy, e.g., those in NGC\,3081, can contain PAH populations of different properties. Specifically, Seyferts that exhibit similar PAH characteristics to ESO137-G034 and MCG-05-23-016 also tend to have similar emission line properties to them, suggesting that the explanations for PAH characteristics of ESO137-G034 and MCG-05-23-016 may also apply generally. These results have promising application in the era of JWST, especially in diagnosing different (i.e., radiative, and kinetic) AGN feedback modes., Comment: ApJL accepted on September 26th, title slightly modified in accordance with ApJL standards, Fig. 2 updated with additional labels

Utilizing JWST MIRI/MRS IFU observations of the kiloparsec scale central regions, we showcase the diversity of ionized gas distributions and kinematics in six nearby Seyfert galaxies included in the GATOS survey. Specifically, we present spatially resolved flux distribution and velocity field maps of six ionized emission lines covering a large range of ionization potentials ($15.8-97.1$ eV). Based on these maps, we showcase the evidence of ionized gas outflows in the six targets, and find some highly disturbed regions in NGC\,5728, NGC\,5506, and ESO137-G034. We propose AGN-driven radio jets plausibly play an important role in triggering these highly disturbed regions. With the outflow rates estimated based on [Ne~{\footnotesize V}] emission, we find the six targets tend to have ionized outflow rates converged to a narrower range than previous finding. These results have important implication for the outflow properties in AGN of comparable luminosity., Comment: 34 pages (11 pages in the appendix), 18 figures in the main text, ApJ in press (accepted on July 26th)

Memristive systems exhibit dynamics that depend on their past states, making them useful as memory units. Due to their functional resemblance to real synapses, memristors can also constitute the building blocks of neural networks for a variety of tasks. Recently, quantum memristor models have been proposed and notably, a photonic quantum memristor (PQM) has been experimentally proven. In this work, we explore and characterize various quantum properties that emerge from this specific model of PQM. Firstly, we find that a single PQM displays memristive dynamics on its quantum coherence. Secondly, we show that a network made of two independent PQMs can manifest memory effects on the dynamics of both entanglement and coherence of correlated photons traveling through the network, regardless of their distance. Additionally, we build and run a circuit-model of the PQM on a real qubit-based quantum computer (IBM-Q), showing that: (i) this system can effectively be used for non-linear quantum computing under specific conditions, and (ii) digital quantum simulations can reproduce the dynamics of a memristive quantum system in a non-Markovian regime., Comment: 9 pages, 7 figures

In modern society, service robots are increasingly recognized for their wide range of practical applications. In large and crowded social spaces, such as museums and hospitals, these robots are required to safely move in the environment while exhibiting user-friendly behavior. Ensuring the safe and socially acceptable operation of robots in such settings presents several challenges. To enhance the social acceptance in the design process of service robots, we present a systematic analysis of requirements, categorized into functional and non-functional. These requirements are further classified into different categories, with a single requirement potentially belonging to multiple categories. Finally, considering the specific case of a receptionist robotic agent, we discuss the requirements it should possess to ensure social acceptance.

Generative adversarial network (GAN) is a strong deep learning model that has shown its value in practical applications such as image processing and data enhancement. Here, we propose a quantum topological code decoder based on GAN and we apply it to optimize the fault-tolerant quantum teleportation system. We construct the generator and discriminator networks of GAN, train the network using the eigenvalue dataset of the topological code, and obtain an optimized decoder with high decoding threshold. The decoding experiments at code distances $d=3$ and $d=5$ show that the error correction success rate of this model reaches 99.895\%. In the experiment, the fidelity threshold of this GAN decoder is about $P=0.2108$, which is significantly improved compared with the threshold $P=0.1099$ of the classical decoding model. In addition, the quantum teleportation system, optimized for noise resistance under $d=3$ topological code, shows a noticeable fidelity improvement within the non-polarized noise threshold range of $P<0.06503$, while under $d=5$ topological code optimization, there is a significant fidelity improvement within the non-polarized noise threshold range of $P<0.07512$. The proposed GAN model supplies a novel approach for topological code decoders and its principles can be applied to different kinds of noise processing., Comment: 12 pages, 11 figures

The utility of Synthetic Aperture Radar (SAR) imagery in remote sensing and satellite image analysis is well established, offering robustness under various weather and lighting conditions. However, SAR images, characterized by their unique structural and texture characteristics, often pose interpretability challenges for analysts accustomed to electrooptical (EO) imagery. This application compares state-of-the-art Generative Adversarial Networks (GANs) including Pix2Pix, CycleGan, S-CycleGan, and a novel dual?generator GAN utilizing partial convolutions and a novel dual-generator architecture utilizing transformers. These models are designed to progressively refine the realism in the translated optical images, thereby enhancing the visual interpretability of SAR data. We demonstrate the efficacy of our approach through qualitative and quantitative evaluations, comparing the synthesized EO images with actual EO images in terms of visual fidelity and feature preservation. The results show significant improvements in interpretability, making SAR data more accessible for analysts familiar with EO imagery. Furthermore, we explore the potential of this technology in various applications, including environmental monitoring, urban planning, and military reconnaissance, where rapid, accurate interpretation of SAR data is crucial. Our research contributes to the field of remote sensing by bridging the gap between SAR and EO imagery, offering a novel tool for enhanced data interpretation and broader application of SAR technology in various domains.

SOXS (Son Of X-Shooter) is the new single object spectrograph for the ESO New Technology Telescope (NTT) at the La Silla Observatory, able to cover simultaneously both the UV-VIS and NIR bands (350-2000 nm). The instrument is currently in the integration and test phase, approaching the Preliminary Acceptance in Europe (PAE) before shipment to Chile for commissioning. After the assembly and preliminary test of the control electronics at INAF - Astronomical Observatory of Capodimonte (Napoli), the two main control cabinets of SOXS are now hosted in Padova, connected to the real hardware. This contribution describes the final electronic cabinets layout, the control strategy and the different integration phases, waiting for the Preliminary Acceptance in Europe and the installation of the instrument in Chile.

The Son Of X-Shooter (SOXS) will be the specialized facility to observe any transient event with a flexible scheduler at the ESO New Technology Telescope (NTT) at La Silla, Chile. SOXS is a single object spectrograph offering simultaneous spectral coverage in UV-VIS (350-850 nm) and NIR (800-2000 nm) wavelength regimes with an average of R~4500 for a 1arcsec slit. SOXS also has imaging capabilities in the visible wavelength regime. Currently, SOXS is being integrated at the INAF-Astronomical Observatory of Padova. Subsystem- and system-level tests and verification are ongoing to ensure and confirm that every requirement and performance are met. In this paper, we report on the integration and verification of SOXS as the team and the instrument prepare for the Preliminary Acceptance Europe (PAE).

The Son Of X-Shooter (SOXS) is a single object spectrograph, built by an international consortium for the 3.58-m ESO New Technology Telescope at the La Silla Observatory [1]. It offers a simultaneous spectral coverage over 350-2000 nm, with two separate spectrographs. In this paper we present the status of the Near InfraRed (NIR) cryogenic echelle cross-dispersed spectrograph [1], in the range 0.80-2.00 {\mu}m with 15 orders, equipped with an 2k x 2k Hawaii H2RG IR array from Teledyne, working at 40K, that is currently assembled and tested on the SOXS instrument, in the premises of INAF in Padova. We describe the different tests and results of the cryo, vacuum, opto-mechanics and detector subsystems that finally will be part of the PAE by ESO., Comment: 8 Pages, 7 Figures, Astronomical Telescopes and Instrumentation, SPIE Proceedings 2024

We present the advancements in the development of the scheduler for the Son Of X-shooter instrument at the ESO-NTT 3.58-m telescope in La Silla, Chile. SOXS is designed as a single-object spectroscopic facility and features a high-efficiency spectrograph with two arms covering the spectral range of 350-2000 nm and a mean resolving power of approximately R=4500. It will conduct UV-visible and near-infrared follow-up observations of astrophysical transients, drawing from a broad pool of targets accessible through the streaming services of wide-field telescopes, both current and future, as well as high-energy satellites. The instrument will cater to various scientific objectives within the astrophysical community, each entailing specific requirements for observation planning. SOXS will operate at the European Southern Observatory (ESO) in La Silla, without the presence of astronomers on the mountain. This poses a unique challenge for the scheduling process, demanding a fully automated algorithm that is autonomously interacting with the appropriate databases and the La Silla Weather API, and is capable of presenting the operator not only with an ordered list of optimal targets (in terms of observing constraints) but also with optimal backups in the event of changing weather conditions. This imposes the necessity for a scheduler with rapid-response capabilities without compromising the optimization process, ensuring the high quality of observations and best use of the time at the telescope. We thus developed a new highly available and scalable architecture, implementing API Restful applications like Docker Containers, API Gateway, and Python-based Flask frameworks. We provide an overview of the current state of the scheduler, which is now ready for the approaching on-site testing during Commissioning phase, along with insights into its web interface and preliminary performance tests.

The Instrument Control Software of SOXS (Son Of X-Shooter), the forthcoming spectrograph for the ESO New Technology Telescope at the La Silla Observatory, has reached a mature state of development and is approaching the crucial Preliminary Acceptance in Europe phase. Now that all the subsystems have been integrated in the laboratories of the Padova Astronomical Observatory, the team operates for testing purposes with the whole instrument at both engineering and scientific level. These activities will make use of a set of software peculiarities that will be discussed in this contribution. In particular, we focus on the synoptic panel, the co-rotator system special device, on the Active Flexure Compensation system which controls two separate piezo tip-tilt devices., Comment: 6 pages, 3 figures, SPIE conference

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.

Deep learning (DL) strategies have recently been utilized to diagnose motor faults by simply analyzing motor phase current signals, offering a less costly and non-intrusive alternative to vibration sensors. This research transforms these time-series current signals into time-frequency 2D representations via Wavelet Transform (WT). The dataset for motor current signals includes 3,750 data points across five categories: one representing normal conditions and four representing artificially induced faults, each under five different load conditions: 0, 25, 50, 75, and 100%. The study employs five WT-based techniques: WT-Amor, WT-Bump, WT-Morse, WSST-Amor, and WSST-Bump. Subsequently, five DL models adopting prior Convolutional Neural Network (CNN) architecture were developed and tested using the transformed 2D plots from each method. The DL models for WT-Amor, WT-Bump, and WT-Morse showed remarkable effectiveness with peak model accuracy of 90.93, 89.20, and 93.73%, respectively, surpassing previous 2D-image-based methods that recorded accuracy of 80.25, 74.80, and 82.80% respectively using the identical dataset and validation protocol. Notably, the WT-Morse approach slightly exceeded the formerly highest ML technique, achieving a 93.20% accuracy. However, the two WSST methods that utilized synchrosqueezing techniques faced difficulty accurately classifying motor faults. The performance of Wavelet-based deep learning methods offers a compelling alternative for machine condition monitoring., Comment: 4 pages, 6 figures, presented at the 2024 International Conference on Diagnostics in Electrical Engineering (Diagnostika)

We studied the effect of nuclear-quadrupole interactions on the field-free impulsive alignment of different asymmetric-top molecules. Our analysis is focused on the influence of the hyperfine- and rotational-energy-level structures. These depend on the number of nuclear spins, the rotational constants, and the symmetry of the tensors involved in the nuclear spin and external field interactions. Comparing the prototypical large-nuclear-spin molecules iodobenzene, 1,2-diiodobenzene, 1,3-diiodobenzene, and 2,5-diiodobenzonitrile, we demonstrate that the magnitude of the hyperfine splittings compared to the rotational-energy splittings plays a crucial role in the spin-rotational dynamics after the laser pulse. Moreover, we point out that the impact of the quadrupole coupling on the rotational dynamics decreases when highly excited rotational states dominate the dynamics.

We report the spectroscopic confirmation and fundamental properties of TOI-757 b, a mini-Neptune on a 17.5-day orbit transiting a bright star ($V = 9.7$ mag) discovered by the TESS mission. We acquired high-precision radial velocity measurements with the HARPS, ESPRESSO, and PFS spectrographs to confirm the planet detection and determine its mass. We also acquired space-borne transit photometry with the CHEOPS space telescope to place stronger constraints on the planet radius, supported with ground-based LCOGT photometry. WASP and KELT photometry were used to help constrain the stellar rotation period. We also determined the fundamental parameters of the host star. We find that TOI-757 b has a radius of $R_{\mathrm{p}} = 2.5 \pm 0.1 R_{\oplus}$ and a mass of $M_{\mathrm{p}} = 10.5^{+2.2}_{-2.1} M_{\oplus}$, implying a bulk density of $\rho_{\text{p}} = 3.6 \pm 0.8$ g cm$^{-3}$. Our internal composition modeling was unable to constrain the composition of TOI-757 b, highlighting the importance of atmospheric observations for the system. We also find the planet to be highly eccentric with $e$ = 0.39$^{+0.08}_{-0.07}$, making it one of the very few highly eccentric planets among precisely characterized mini-Neptunes. Based on comparisons to other similar eccentric systems, we find a likely scenario for TOI-757 b's formation to be high eccentricity migration due to a distant outer companion. We additionally propose the possibility of a more intrinsic explanation for the high eccentricity due to star-star interactions during the earlier epoch of the Galactic disk formation, given the low metallicity and older age of TOI-757., Comment: Accepted for publication in MNRAS; 26 pages, 14 figures, 6 tables

We consider the following problem in computational geometry: given, in the d-dimensional real space, a set of points marked as positive and a set of points marked as negative, such that the convex hull of the positive set does not intersect the negative set, find K hyperplanes that separate, if possible, all the positive points from the negative ones. That is, we search for a convex polyhedron with at most K faces, containing all the positive points and no negative point. The problem is known in the literature for pure convex polyhedral approximation; our interest stems from its possible applications in constraint learning, where points are feasible or infeasible solutions of a Mixed Integer Program, and the K hyperplanes are linear constraints to be found. We cast the problem as an optimization one, minimizing the number of negative points inside the convex polyhedron, whenever exact separation cannot be achieved. We introduce models inspired by support vector machines and we design two mathematical programming formulations with binary variables. We exploit Dantzig-Wolfe decomposition to obtain extended formulations, and we devise column generation algorithms with ad-hoc pricing routines. We compare computing time and separation error values obtained by all our approaches on synthetic datasets, with number of points from hundreds up to a few thousands, showing our approaches to perform better than existing ones from the literature. Furthermore, we observe that key computational differences arise, depending on whether the budget K is sufficient to completely separate the positive points from the negative ones or not. On 8-dimensional instances (and over), existing convex hull algorithms become computational inapplicable, while our algorithms allow to identify good convex hull approximations in minutes of computation.

Artificial intelligence (AI) has become a commodity for people because of the advent of generative AI (GenAI) models that bridge the usability gap of AI by providing a natural language interface to interact with complex models. These GenAI models range from text generation - such as two-way chat systems - to the generation of image or video from textual descriptions input by a user. These advancements in AI have impacted Dentistry in multiple aspects. In dental education, the student now has the opportunity to solve a plethora of questions by only prompting a GenAI model and have the answer in a matter of seconds. GenAI models can help us deliver better patient healthcare by helping practitioners gather knowledge quickly and efficiently. Finally, GenAI can also be used in dental research, where the applications range from new drug discovery to assistance in academic writing. In this review, we first define GenAI models and describe their multiple generation modalities; then, we explain and discuss their current and potential applications in Dentistry; and finally, we describe the challenges these new technologies impose in our area.

We present observations of the type-2 Seyfert NGC7172 obtained with the medium-resolution spectrometer (MRS) of the Mid-Infrared Instrument (MIRI) on board of the JWST. This galaxy hosts one of the lowest ionised gas mass outflow rates (Mout~0.005 M/yr) in a sample of six AGN with similar bolometric luminosities (log Lbol~44erg/s) within the Galactic Activity, Torus and Outflow Survey (GATOS). We aim to understand the properties of the ionised gas outflow, mainly using the emission lines from the neon transitions, that cover a broad range of ionisation potentials (IP) from ~20 eV to ~130 eV. We applied parametric and non-parametric methods to characterise the line emission and kinematics. The low excitation lines (IP<25eV, e.g.[NeII]) trace the rotating disc emission. The high excitation lines (IP>90eV, e.g.[NeV]), which are likely photoionised exclusively by the AGN, are expanding in the direction nearly perpendicular to the disc of the galaxy, with maximum projected velocities of ~350-500 km/s. In particular, [NeV] and [NeVI] lines reveal a biconical ionised gas outflow emerging N-S from the nuclear region, extending at least ~2.5"N and 3.8"S (projected distance of ~450 and 680 pc). Most of the emission arising in the northern part of the cone was not previously detected due to obscuration. Given the almost face-on orientation of the outflow and the almost edge-on orientation of the galaxy, NGC7172 may be a case of weak coupling. Nevertheless, we found evidence for positive feedback in two distinct outflowing clumps at projected distances of 3.1" and 4.3" (i.e. ~560 and 780 pc) SW from the AGN. We estimated a star formation rate in these regions using the [NeII] and [NeIII] luminosities of 0.08 M/yr, that is ~10% of that found in the circumnuclear ring. The star formation activity might have been triggered by the interaction between the ionised gas outflow and the ISM of the galaxy., Comment: 20 pages, 6 figures. Accepted for publication in A&A. Abstract adapted for the arxiv version

The increasing need to analyse large volumes of data has led to the development of Symbolic Data Analysis as a promising field to tackle the data challenges of our time. New data types, such as interval-valued data, have brought fresh theoretical and methodological problems to be solved. In this paper, we derive explicit formulas for computing the Mallows' distance, also known as $L_2$ Wasserstein distance, between two \textit{p}-dimensional intervals, using information regarding the distribution of the microdata. We establish this distance as a Mahalanobis' distance between two 2\textit{p}-dimensional vectors. Our comprehensive analysis leads to the generalisation of the definitions of the expected value and covariance matrix of an interval-valued random vector. These novel results bring theoretical support and interpretability to state-of-the-art contributions. Additionally, we discuss real examples that illustrate how we can model different levels of available information on the microdata, leading to proper estimates of the measures of location and association.

The increasing interest in developing Artificial Intelligence applications in the medical domain, suffers from the lack of high-quality dataset, mainly due to privacy-related issues. Moreover, the recent rising of Multimodal Large Language Models (MLLM) leads to a need for multimodal medical datasets, where clinical reports and findings are attached to the corresponding CT or MR scans. This paper illustrates the entire workflow for building the data set MedPix 2.0. Starting from the well-known multimodal dataset MedPix\textsuperscript{\textregistered}, mainly used by physicians, nurses and healthcare students for Continuing Medical Education purposes, a semi-automatic pipeline was developed to extract visual and textual data followed by a manual curing procedure where noisy samples were removed, thus creating a MongoDB database. Along with the dataset, we developed a GUI aimed at navigating efficiently the MongoDB instance, and obtaining the raw data that can be easily used for training and/or fine-tuning MLLMs. To enforce this point, we also propose a CLIP-based model trained on MedPix 2.0 for scan classification tasks.

The ionisation cones of NGC5728 have a deficit of molecular gas based on millimetre observations of CO(2-1) emission. Although photoionisation from the active nucleus may lead to suppression of this transition, warm molecular gas can still be present. We report the detection of eight mid-infrared rotational H$_2$ lines throughout the central kiloparsec, including the ionisation cones, using integral field spectroscopic observations with JWST/MIRI MRS. The H$_2$ line ratios, characteristic of a power-law temperature distribution, indicate that the gas is warmest where it enters the ionisation cone through disk rotation, suggestive of shock excitation. In the nucleus, where the data can be combined with an additional seven ro-vibrational H$_2$ transitions, we find that moderate velocity (30 km s$^{-1}$) shocks in dense ($10^5$ cm$^{-3}$) gas, irradiated by an external UV field ($G_0 = 10^3$), do provide a good match to the full set. The warm molecular gas in the ionisation cone that is traced by the H$_2$ rotational lines has been heated to temperatures $>200$ K. Outside of the ionisation cone the molecular gas kinematics are undisturbed. However, within the ionisation cone, the kinematics are substantially perturbed, indicative of a radial flow, but one that is quantitatively different from the ionised lines. We argue that this outflow is in the plane of the disk, implying a short 50 pc acceleration zone up to speeds of about 400 km s$^{-1}$ followed by an extended deceleration over $\sim$700 pc where it terminates. The deceleration is due to both the radially increasing galaxy mass, and mass-loading as ambient gas in the disk is swept up., Comment: A&A accepted; 16 pages

Huntington's disease (HD) is an inherited neurodegenerative disorder caused by an expanded CAG repeat in the coding sequence of the huntingtin protein. Initially, it predominantly affects medium-sized spiny neurons (MSSNs) of the corpus striatum. No effective treatment is available, thus urging the identification of potential therapeutic targets. While evidence of mitochondrial structural alterations in HD exists, previous studies mainly employed 2D approaches and were performed outside the strictly native brain context. In this study, we adopted a novel multiscale approach to conduct a comprehensive 3D in situ structural analysis of mitochondrial disturbances in a mouse model of HD. We investigated MSSNs within brain tissue under optimal structural conditions utilizing state-of-the-art 3D imaging technologies, specifically FIB/SEM for the complete imaging of neuronal somas and Electron Tomography for detailed morphological examination and image processing-based quantitative analysis. Our findings suggest a disruption of the mitochondrial network towards fragmentation in HD. The network of interlaced, slim, and long mitochondria observed in healthy conditions transforms into isolated, swollen, and short entities, with internal cristae disorganization, cavities, and abnormally large matrix granules., Comment: 31 pages 5 figures

A comprehensive theoretical understanding of electron-photon correlation is essential for describing the reshaping of molecular orbitals in quantum electrodynamics (QED) environments. The strong coupling QED Hartree-Fock (SC-QED-HF) theory tackles these aspects by providing consistent molecular orbitals in the strong coupling regime. The previous implementation, however, has significant convergence issues that limit the applicability. In this work we introduce two second-order algorithms that significantly reduce the computational requirements, thereby enhancing the modeling of large molecular systems in QED environments. Furthermore, the implementation will enable the development of correlated methods based on a reliable molecular orbital framework., Comment: 29 pages and 6 figures

Interactions between quasiparticles mediated by a surrounding environment are ubiquitous and lead to a range of important effects from collective modes of low temperature quantum gases, superconductivity, to the interaction between elementary particles at high energies. This perspective article is motivated by experimental progress in the fields of quantum degenerate atomic gases, cavity QED, and two-dimensional (2D) semi-conductors, which enable a systematic exploration of mediated interactions in new settings and regimes. We first describe how to microscopically calculate the quasiparticle interaction using perturbation theory, diagrammatics, and the path integral, highlighting the key role played by the quantum statistics of the quasiparticles. Recent theoretical and experimental insights into quasiparticle and mediated interactions in general obtained from atomic gases are then discussed, after which we focus on hybrid light-atom systems where a remarkable long range photon mediated interaction can be realised. Next, we describe new and puzzling results regarding the interaction between quasiparticles in 2D semiconductors. We then discuss how mediated interactions open up ways to realise new quantum phases in atomic and hybrid atom-photon systems as well as 2D semiconductors, and the perspective ends by posing some open questions and outlook.

We use a sample of 64 nearby (D=7-45 Mpc) disk galaxies including 45 AGN and 19 non-AGN, that have high spatial resolution multiline CO observations obtained with the ALMA and/or PdBI arrays to study the distribution of cold molecular gas in their circumunuclear disks (CND). We analyze whether the concentration of cold molecular gas changes as a function of the X-ray luminosity in the 2-10 keV range ($L_{\rm X}$). We also study the concentration of the hot molecular gas using NIR data obtained for the H2 1-0S(1) line. We find a turnover in the distribution of the cold molecular gas concentration as a function of $L_{\rm X}$ with a breakpoint which divides the sample into two branches: the AGN build-up branch ($L_{\rm X}\leq10^{41.5\pm0.3}$erg/s) and the AGN feedback branch ($L_{\rm X}\geq10^{41.5\pm0.3}$erg/s) . Lower luminosity AGN and non-AGN of the AGN build-up branch show high cold molecular gas concentrations and centrally peaked radial profiles on nuclear ($r\leq50$~pc) scales. Higher luminosity AGN of the AGN feedback branch, show a sharp decrease in the concentration of molecular gas and flat or inverted radial profiles. The cold molecular gas concentration index ($CCI$), defined as the ratio of surface densities at $r\leq50$~pc and $r\leq200$~pc , namely $CCI \equiv$~log$_{\rm 10}(\Sigma^{\rm gas}_{\rm 50}/\Sigma^{\rm gas}_{\rm 200}$), spans a factor ~4-5 between the galaxies lying at the high end of the AGN build-up branch and the galaxies of the AGN feedback branch. The concentration and radial distributions of the hot molecular gas in our sample follow less extreme trends as a function of the X-ray luminosity. These observations confirm, on a three times larger sample, previous evidence found by the GATOS survey that the imprint of AGN feedback on the CND-scale distribution of molecular gas is more extreme in higher luminosity Seyfert galaxies of the local universe., Comment: Accepted by Astronomy & Astrophysics (A&A) (14/06/2024), 26 pages, 16 figures

We investigate the use of a boundary time crystals (BTCs) as sensors of AC fields. Boundary time crystals are non-equilibrium phases of matter in contact to an environment, for which a macroscopic fraction of the many-body system breaks the time translation symmetry. We find an enhanced sensitivity of the BTC when its spins are resonant with the applied AC field, as quantified by the quantum Fisher information (QFI). The QFI dynamics in this regime is shown to be captured by a relatively simple ansatz consisting of an initial power-law growth and late-time exponential decay. We study the scaling of the ansatz parameters with resources (encoding time and number of spins) and identify a moderate quantum enhancement in the sensor performance through comparison with classical QFI bounds. Investigating the precise source of this performance, we find that despite of its long coherence time and multipartite correlations (advantageous properties for quantum metrology), the entropic cost of the BTC (which grows indefinitely in the thermodynamic limit) hinders an optimal decoding of the AC field information. This result has implications for future candidates of quantum sensors in open system and we hope it will encourage future study into the role of entropy in quantum metrology., Comment: 15 pages, 5 figures

The US Care Policy Scorecard seeks to assess the US care policy environment at the federal level by adapting and implementing the Care Policy Scorecard Framework and Tool in the US context. The US Scorecard looks at 30 federal policy indicators related to both unpaid care and underpaid care work (UUCW). Each policy indicator is measured by an average of 18 assessment criteria with the aim to determine the existence of the policy as well as to evaluate the performance and progress of the policy in relation to its design, implementation, and impact., The US Care Policy Scorecard demonstrates that federal UUCW policies are severely lacking, and the needs of caregivers and care workers are not being met by federal policies. It is women of color and immigrant women who are most harmed by the US’s failure to fully support working families, caregivers, and care workers. This is a result of a history of policymaking rooted in sexism and racism that makes care work invisible and undervalued. The US receives an aggregate score of 43%, meeting less than half of all possible criteria when all care policy indicators in the US Care Policy Scorecard are examined and aggregated., In addition to showcasing how each policy indicator and policy area measured scored, the report includes examples of states that have passed care policies in light of absent or weak federal policies, as well as policy recommendations to strengthen the care policy environment in the US.

The ability to summarize and organize knowledge into abstract concepts is key to learning and reasoning. Many industrial applications rely on the consistent and systematic use of concepts, especially when dealing with decision-critical knowledge. However, we demonstrate that, when methodically questioned, large language models (LLMs) often display and demonstrate significant inconsistencies in their knowledge. Computationally, the basic aspects of the conceptualization of a given domain can be represented as Is-A hierarchies in a knowledge graph (KG) or ontology, together with a few properties or axioms that enable straightforward reasoning. We show that even simple ontologies can be used to reveal conceptual inconsistencies across several LLMs. We also propose strategies that domain experts can use to evaluate and improve the coverage of key domain concepts in LLMs of various sizes. In particular, we have been able to significantly enhance the performance of LLMs of various sizes with openly available weights using simple knowledge-graph (KG) based prompting strategies., Comment: 15 pages, 5 figures, 3 tables

Data show that the presence of women in quantum science is affected by a number of detriments and their percentage decreases even further for higher positions. Beyond data, from our shared personal experiences as female tenured quantum physics professors, we believe that the current model of scientific leadership, funding, and authority fails to represent many of us. It is time for a real change that calls for a different kind of force and for the participation of everyone. Women for quantum calls for a joint effort and aims with this initiative to contribute to such a transformation.

Robots today can exploit the rich world knowledge of large language models to chain simple behavioral skills into long-horizon tasks. However, robots often get interrupted during long-horizon tasks due to primitive skill failures and dynamic environments. We propose VADER, a plan, execute, detect framework with seeking help as a new skill that enables robots to recover and complete long-horizon tasks with the help of humans or other robots. VADER leverages visual question answering (VQA) modules to detect visual affordances and recognize execution errors. It then generates prompts for a language model planner (LMP) which decides when to seek help from another robot or human to recover from errors in long-horizon task execution. We show the effectiveness of VADER with two long-horizon robotic tasks. Our pilot study showed that VADER is capable of performing complex long-horizon tasks by asking for help from another robot to clear a table. Our user study showed that VADER is capable of performing complex long-horizon tasks by asking for help from a human to clear a path. We gathered feedback from people (N=19) about the performance of the VADER performance vs. a robot that did not ask for help. https://google-vader.github.io/, Comment: 9 pages, 4 figures

We consider solving a combinatorial optimization problem with an unknown linear constraint using a membership oracle that, given a solution, determines whether it is feasible or infeasible with absolute certainty. The goal of the decision maker is to find the best possible solution subject to a budget on the number of oracle calls. Inspired by active learning based on Support Vector Machines (SVMs), we adapt a classical framework in order to solve the problem by learning and exploiting a surrogate linear constraint. The resulting new framework includes training a linear separator on the labeled points and selecting new points to be labeled, which is achieved by applying a sampling strategy and solving a 0-1 integer linear program. Following the active learning literature, one can consider using SVM as a linear classifier and the information-based sampling strategy known as Simple margin. We improve on both sides: we propose an alternative sampling strategy based on mixed-integer quadratic programming and a linear separation method inspired by an algorithm for convex optimization in the oracle model. We conduct experiments on the pure knapsack problem and on a college study plan problem from the literature to show how different linear separation methods and sampling strategies influence the quality of the results in terms of objective value.

Many novel methods have been proposed to mitigate stellar activity for exoplanet detection as the presence of stellar activity in radial velocity (RV) measurements is the current major limitation. Unlike traditional methods that model stellar activity in the RV domain, more methods are moving in the direction of disentangling stellar activity at the spectral level. The goal of this paper is to present a novel convolutional neural network-based algorithm that efficiently models stellar activity signals at the spectral level, enhancing the detection of Earth-like planets. We trained a convolutional neural network to build the correlation between the change in the spectral line profile and the corresponding RV, full width at half maximum (FWHM) and bisector span (BIS) values derived from the classical cross-correlation function. This algorithm has been tested on three intensively observed stars: Alpha Centauri B (HD128621), Tau ceti (HD10700), and the Sun. By injecting simulated planetary signals at the spectral level, we demonstrate that our machine learning algorithm can achieve, for HD128621 and HD10700, a detection threshold of 0.5 m/s in semi-amplitude for planets with periods ranging from 10 to 300 days. This threshold would correspond to the detection of a $\sim$4$\mathrm{M}_{\oplus}$ in the habitable zone of those stars. On the HARPS-N solar dataset, our algorithm is even more efficient at mitigating stellar activity signals and can reach a threshold of 0.2 m/s, which would correspond to a 2.2$\mathrm{M}_{\oplus}$ planet on the orbit of the Earth. To the best of our knowledge, it is the first time that such low detection thresholds are reported for the Sun, but also for other stars, and therefore this highlights the efficiency of our convolutional neural network-based algorithm at mitigating stellar activity in RV measurements., Comment: Accepted for publication in A&A