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The energy released by AGN has the potential to heat or remove the gas of the ISM, thus likely impacting the cold molecular gas reservoir of host galaxies at first, with star formation following on longer timescales. Previous works on high-z galaxies have yielded conflicting results, possibly due to selection biases and other systematics. To provide a reliable benchmark for galaxy evolution models at cosmic noon (z=1-3), two surveys were conceived: SUPER and KASHz, both targeting unbiased X-ray-selected AGN at z>1 that span a wide bolometric luminosity range. In this paper, we assess the effects of AGN feedback on the molecular gas content of host galaxies in a statistically robust, uniformly selected, coherently analyzed sample of AGN at z=1-2.6, drawn from the KASHz and SUPER surveys. By using ALMA data in combination with dedicated SED modeling, we retrieve CO and FIR luminosity as well as $M_*$ of SUPER and KASHz AGN. We selected non-active galaxies from PHIBBS, ASPECS and multiple ALMA/NOEMA surveys of sub-mm galaxies. By matching the samples in z, $M_*$ and $L_{FIR}$, we compared the properties of AGN and non-active galaxies within a Bayesian framework. We find that AGN hosts at given $L_{FIR}$ are on average CO depleted compared to non-active galaxies, confirming what was previously found in the SUPER survey. Moreover, the molecular gas fraction distributions of AGN and non-active galaxies are statistically different, with that of of AGN being skewed to lower values. Our results indicate that AGN can indeed reduce the total cold molecular gas reservoir of their host galaxies. Lastly, by comparing our results with predictions from three cosmological simulations (TNG, Eagle and Simba) filtered to match the observed properties, we confirm already known discrepancies and highlight new ones between observations and simulations.[Abridged], Comment: 26 pages (17 in the main body of the paper and 9 in the appendix), 14 figures (11 in the main body of the paper and 3 in the appendix), 8 tables (2 in the main body of the paper and 6 in the appendix). Accepted for publication in A&A, in press

We present a deep X-Shooter rest-frame UV to optical spectral analysis of the heavily reddened quasar, ULASJ2315+043 at z=2.566, known to reside in a major-merger host galaxy. The rest-frame optical is best-fit by a dust-reddened quasar E(B-V)_QSO = 1.55 with black-hole mass log10(Hbeta, MBH [M_sol]) = 10.26 +\- 0.05, bolometric luminosity L_Bol = 10^48.16 erg s^-1 and Eddington-scaled accretion rate log10(\lambda_Edd) = -0.19. We find remarkable similarities between ULASJ2315+043 and the high-redshift Little Red Dots (LRDs). The rest-frame UV cannot be explained by a dusty quasar component alone and requires an additional blue component consistent with either a star-forming host galaxy or scattered AGN light. We detect broad high-ionisation emission lines in the rest-UV, supporting the scattered light interpretation for the UV excess. The scattering fraction represents just 0.05% of the total luminosity of ULASJ2315+043. Analysis of the mid infra-red SED suggests an absence of hot dust on torus-scales similar to what is observed for LRDs. The obscuring medium is therefore likely on galaxy scales. We detect narrow, blueshifted associated absorption line systems in CIV, NV, SiIV and SiIII. There is evidence for significant high-velocity (>1000 km s^-1) outflows in both the broad and narrow line regions as traced by CIV and [OIII] emission. The kinetic power of the [OIII] wind is e_ion = 10^44.61 erg s^-1 ~ 0.001 L_Bol. ULASJ2315+043 is likely in an important transition phase where star formation, black-hole accretion and multi-phase gas flows are simultaneously occurring., Comment: Accepted to MNRAS: 13th Aug 2024. 18 pages, 12 figures

AI-generated synthetic media, also called Deepfakes, have significantly influenced so many domains, from entertainment to cybersecurity. Generative Adversarial Networks (GANs) and Diffusion Models (DMs) are the main frameworks used to create Deepfakes, producing highly realistic yet fabricated content. While these technologies open up new creative possibilities, they also bring substantial ethical and security risks due to their potential misuse. The rise of such advanced media has led to the development of a cognitive bias known as Impostor Bias, where individuals doubt the authenticity of multimedia due to the awareness of AI's capabilities. As a result, Deepfake detection has become a vital area of research, focusing on identifying subtle inconsistencies and artifacts with machine learning techniques, especially Convolutional Neural Networks (CNNs). Research in forensic Deepfake technology encompasses five main areas: detection, attribution and recognition, passive authentication, detection in realistic scenarios, and active authentication. This paper reviews the primary algorithms that address these challenges, examining their advantages, limitations, and future prospects.

The majority of stars in today's Universe reside within spheroids, which are bulges of spiral galaxies and elliptical galaxies. Their formation is still an unsolved problem. Infrared/submm-bright galaxies at high redshifts have long been suspected to be related to spheroids formation. Proving this connection has been hampered so far by heavy dust obscuration when focusing on their stellar emission or by methodologies and limited signal-to-noise ratios when looking at submm wavelengths. Here we show that spheroids are directly generated by star formation within the cores of highly luminous starburst galaxies in the distant Universe. This follows from the ALMA submillimeter surface brightness profiles which deviate significantly from those of exponential disks, and from the skewed-high axis-ratio distribution, both derived with a novel analysis technique. These galaxies are fully triaxial rather than flat disks: scale-height ratios are 0.5 on average and $>0.6$ for most spatially compact systems. These observations, supported by simulations, reveal a cosmologically relevant pathway for in-situ spheroid formation through starbursts likely preferentially triggered by interactions (and mergers) acting on galaxies fed by non co-planar gas accretion streams., Comment: Resubmitted to Nature after replying to the first round of referee reports

The Enhanced Resolution Imager and Spectrograph (ERIS) is the new near-infrared instrument at the VLT-UT4. ERIS replaces and extends the observational capabilities formerly provided by SINFONI and NACO: integral field spectroscopy at 1 - 2.5 $\mu$m, imaging at 1 - 5 $\mu$m with several options for high-contrast imaging, and long-slit spectroscopy. In particular, a vortex coronagraph is now available for high contrast observations at L and M band. It is implemented using annular groove (or vortex) phase masks (one for each of the L and M bands) in a focal plane, and a Lyot stop in a downstream pupil plane. The vortex coronagraph has a discovery space starting already at $\sim$1$\lambda/D$, and works well in broadbands. However, to reach its optimal performance, it is critical to correct for slow pointing errors onto the vortex phase mask, which mandates a dedicated pointing control strategy. To do so, a control loop based on the QACITS algorithm has been developed and commissioned for ERIS. Good pointing stability is now regularly achieved with errors between 0.01 and 0.02 $\lambda/D$ and a correction rate of 0.2 Hz. In this contribution, we first review the design of the ERIS vortex coronagraph. We then detail the implementation of the QACITS algorithm describing the entire observing sequence, including the calibration steps, the initial centering, and the stabilization during the observing template. We then discuss performance based on commissioning data in terms of pointing accuracy and stability. Finally, we present post-processed contrast curves obtained during commissioning and compare them with NACO vortex data, showing a significant improvement of about 1 mag at all separations., Comment: 15 pages, 13 figures, paper presented at SPIE Astronomical Telescopes + Instrumentation 2024

We present spatially resolved VLT/SINFONI spectroscopy with adaptive optics of type-2 active galactic nuclei (AGN) from the SINFONI Survey for Unveiling the Physics and Effect of Radiative feedback (SUPER), which targeted X-ray bright ($L_{2-10 keV}\gtrsim10^{42}$ erg s$^{-1}$) AGN at Cosmic Noon ($z\sim2$). Our analysis of the rest-frame optical spectra unveils ionised outflows in all seven examined targets, as traced via [OIII]$\lambda$5007 line emission, moving at $v\gtrsim600$ km s$^{-1}$. In six objects these outflows are clearly spatially resolved and extend on 2-4 kpc scales, whereas marginally resolved in the remaining one. Interestingly, these SUPER type-2 AGN are all heavily obscured sources ($N_{H}\gtrsim10^{23}$ cm$^{-2}$) and host faster ionised outflows than their type-1 counterparts within the same range of bolometric luminosity ($L_{bol} \sim 10^{44.8-46.5}$ erg s$^{-1}$). SUPER has hence provided observational evidence that the type-1/type-2 dichotomy at $z\sim2$ might not be driven simply by projection effects, but might reflect two distinct obscuring life stages of active galaxies, as predicted by evolutionary models. Within this picture, SUPER type-2 AGN might be undergoing the 'blow-out' phase, where the large amount of obscuring material efficiently accelerates large-scale outflows via radiation pressure on dust, eventually unveiling the central active nucleus and signal the start of the bright, unobscured type-1 AGN phase. Moreover, the overall population of ionised outflows detected in SUPER has velocities comparable with the escape speed of their dark matter halos, and in general high enough to reach 30-50 kpc distances from the centre. These outflows are hence likely to sweep away the gas (at least) out of the baryonic disk and/or to heat the host gas reservoir, thus reducing and possibly quenching star formation., Comment: 21 pages, 13 figures. Key figure is 8. Accepted for publication in A&A

We present ForSE+, a Python package that produces non-Gaussian diffuse Galactic thermal dust emission maps at arcminute angular scales and that has the capacity to generate random realizations of small scales. This represents an extension of the ForSE (Foreground Scale Extender) package, which was recently proposed to simulate non-Gaussian small scales of thermal dust emission using generative adversarial networks (GANs). With the input of the large-scale polarization maps from observations, ForSE+ has been trained to produce realistic polarized small scales at 3' following the statistical properties, mainly the non-Gaussianity, of observed intensity small scales, which are evaluated through Minkowski functionals. Furthermore, by adding different realizations of random components to the large-scale foregrounds, we show that ForSE+ is able to generate small scales in a stochastic way. In both cases, the output small scales have a similar level of non-Gaussianity compared with real observations and correct amplitude scaling as a power law. These realistic new maps will be useful, in the future, to understand the impact of non-Gaussian foregrounds on the measurements of the cosmic microwave background (CMB) signal, particularly on the lensing reconstruction, de-lensing, and the detection of cosmological gravitational waves in CMB polarization B-modes., Comment: Published in A&A. Comments welcome

In a hierarchical, dark matter-dominated Universe, stellar mass functions (SMFs), galaxy merger rates, star formation histories (SFHs), satellite abundances, and intracluster light, should all be intimately connected observables. However, the systematics affecting observations still prevent universal and uniform measurements of, for example, the SMF and the SFHs, inevitably preventing theoretical models to compare with multiple data sets robustly and simultaneously. We here present our holistic semi-empirical model DECODE (Discrete statistical sEmi-empiriCal mODEl) that converts via abundance matching dark matter merger trees into galaxy assembly histories, using different SMFs in input and predicting all other observables in output in a fully data-driven and self-consistent fashion with minimal assumptions. We find that: 1) weakly evolving or nearly constant SMFs below the knee ($M_\star \lesssim 10^{11} \, M_\odot$) are the best suited to generate star formation histories aligned with those inferred from MaNGA, SDSS, GAMA, and, more recently, JWST; 2) the evolution of satellites after infall only affects the satellite abundances and star formation histories of massive central galaxies but not their merger histories; 3) the resulting SFR-$M_\star$ relation is lower in normalization by a factor of $\sim 2$ with respect to observations, with a flattening at high masses more pronounced in the presence of mergers; 4) the latest data on intracluster light can be reproduced if mass loss from mergers is included in the models. Our findings are pivotal in acting as pathfinder to test the self-consistency of the high-quality data from, e.g., JWST and Euclid., Comment: 21 pages, 12 figures, MNRAS accepted

Brain age is a critical measure that reflects the biological ageing process of the brain. The gap between brain age and chronological age, referred to as brain PAD (Predicted Age Difference), has been utilized to investigate neurodegenerative conditions. Brain age can be predicted using MRIs and machine learning techniques. However, existing methods are often sensitive to acquisition-related variabilities, such as differences in acquisition protocols, scanners, MRI sequences, and resolutions, significantly limiting their application in highly heterogeneous clinical settings. In this study, we introduce Synthetic Brain Age (SynthBA), a robust deep-learning model designed for predicting brain age. SynthBA utilizes an advanced domain randomization technique, ensuring effective operation across a wide array of acquisition-related variabilities. To assess the effectiveness and robustness of SynthBA, we evaluate its predictive capabilities on internal and external datasets, encompassing various MRI sequences and resolutions, and compare it with state-of-the-art techniques. Additionally, we calculate the brain PAD in a large cohort of subjects with Alzheimer's Disease (AD), demonstrating a significant correlation with AD-related measures of cognitive dysfunction. SynthBA holds the potential to facilitate the broader adoption of brain age prediction in clinical settings, where re-training or fine-tuning is often unfeasible. The SynthBA source code and pre-trained models are publicly available at https://github.com/LemuelPuglisi/SynthBA.

In this work, we introduce Brain Latent Progression (BrLP), a novel spatiotemporal disease progression model based on latent diffusion. BrLP is designed to predict the evolution of diseases at the individual level on 3D brain MRIs. Existing deep generative models developed for this task are primarily data-driven and face challenges in learning disease progressions. BrLP addresses these challenges by incorporating prior knowledge from disease models to enhance the accuracy of predictions. To implement this, we propose to integrate an auxiliary model that infers volumetric changes in various brain regions. Additionally, we introduce Latent Average Stabilization (LAS), a novel technique to improve spatiotemporal consistency of the predicted progression. BrLP is trained and evaluated on a large dataset comprising 11,730 T1-weighted brain MRIs from 2,805 subjects, collected from three publicly available, longitudinal Alzheimer's Disease (AD) studies. In our experiments, we compare the MRI scans generated by BrLP with the actual follow-up MRIs available from the subjects, in both cross-sectional and longitudinal settings. BrLP demonstrates significant improvements over existing methods, with an increase of 22% in volumetric accuracy across AD-related brain regions and 43% in image similarity to the ground-truth scans. The ability of BrLP to generate conditioned 3D scans at the subject level, along with the novelty of integrating prior knowledge to enhance accuracy, represents a significant advancement in disease progression modeling, opening new avenues for precision medicine. The code of BrLP is available at the following link: https://github.com/LemuelPuglisi/BrLP.

We analyze the entropy production in run-and-tumble models. After presenting the general formalism in the framework of the Fokker-Planck equations in one space dimension, we derive some known exact results in simple physical situations (free run-and-tumble particles and harmonic confinement). We then extend the calculation to the case of anisotropic motion (different speeds and tumbling rates for right and left oriented particles), obtaining exact expressions of the entropy production rate. We conclude by discussing the general case of heterogeneous run-and-tumble motion described by space-dependent parameters and extending the analysis to the case of d-dimensional motions., Comment: 9 pages, 1 figure

We introduce height-bounded LZ encodings (LZHB), a new family of compressed representations that are variants of Lempel-Ziv parsings with a focus on bounding the worst-case access time to arbitrary positions in the text directly via the compressed representation. An LZ-like encoding is a partitioning of the string into phrases of length $1$ which can be encoded literally, or phrases of length at least $2$ which have a previous occurrence in the string and can be encoded by its position and length. An LZ-like encoding induces an implicit referencing forest on the set of positions of the string. An LZHB encoding is an LZ-like encoding where the height of the implicit referencing forest is bounded. An LZHB encoding with height constraint $h$ allows access to an arbitrary position of the underlying text using $O(h)$ predecessor queries. While computing the smallest LZHB encoding efficiently seems to be difficult [Cicalese \& Ugazio 2024, arxiv], we give the first linear time algorithm for strings over a constant size alphabet that computes the greedy LZHB encoding, i.e., the string is processed from beginning to end, and the longest prefix of the remaining string that can satisfy the height constraint is taken as the next phrase. Our algorithms significantly improve both theoretically and practically, the very recently and independently proposed algorithms by Lipt\'ak et al. (arxiv, to appear at CPM 2024). We also analyze the size of height bounded LZ encodings in the context of repetitiveness measures, and show for some constant $c$, the size $z_{HB}$ of the optimal LZHB encoding with height bound $c\log n$ is $O(g_{rl})$, where $g_{rl}$ is the size of the smallest run-length grammar. We also show $z_{HB} = o(g_{rl})$ for some family of strings, making $z_{HB}$ one of the smallest known repetitiveness measures for which $O({\sf polylog} n)$ time access is possible using linear space., Comment: abstract shortened to fit arxiv requirements

We study the effects due to mismatches in passbands, polarization angles, and temperature and polarization calibrations in the context of the upcoming cosmic microwave background experiment Simons Observatory (SO). Using the SO multi-frequency likelihood, we estimate the bias and the degradation of constraining power in cosmological and astrophysical foreground parameters assuming different levels of knowledge of the instrumental effects. We find that incorrect but reasonable assumptions about the values of all the systematics examined here can have significant effects on cosmological analyses, hence requiring marginalization approaches at the likelihood level. When doing so, we find that the most relevant effect is due to bandpass shifts. When marginalizing over them, the posteriors of parameters describing astrophysical microwave foregrounds (such as radio point sources or dust) get degraded, while cosmological parameters constraints are not significantly affected. Marginalization over polarization angles with up to 0.25$^\circ$ uncertainty causes an irrelevant bias $\lesssim 0.05 \sigma$ in all parameters. Marginalization over calibration factors in polarization broadens the constraints on the effective number of relativistic degrees of freedom $N_\mathrm{eff}$ by a factor 1.2, interpreted here as a proxy parameter for non standard model physics targeted by high-resolution CMB measurements., Comment: 61 pages (27 of which are appendices), 26 figures, 12 tables. (Replacement to update the acknowledgments)

For a Banach space $X$, let $\mathcal{L}(X)$ denote the algebra of all bounded linear operators on $X$ and let $\mathcal{K}(X)$ denote the compact operator ideal in $\mathcal{L}(X)$. The quotient algebra $\mathcal{L}(X)/\mathcal{K}(X)$ is called the Calkin algebra of $X$, and it is denoted $\mathcal{C}al(X)$. We prove that the unitization of $\mathcal{K}(c_0)$ is isomorphic as a Banach algebra to the Calkin algebra of some Banach space $\mathcal{Z}_{\mathcal{K}(c_0)}$. This Banach space is an Argyros-Haydon sum $(\oplus_{n=1}^\infty X_n)_\mathrm{AH}$ of a sequence of copies $X_n$ of a single Argyros-Haydon space $\mathfrak{X}_\mathrm{AH}$, and the external versus the internal Argyros-Haydon construction parameters are chosen from disjoint sets., Comment: 23 pages, no figures

Inspired by recent experiments on fluctuations of the flagellar beating in sperms and C. reinhardtii, we investigate the precision of phase fluctuations in a system of nearest-neighbour-coupled molecular motors. We model the system as a Kuramoto chain of oscillators with coupling constant $k$ and noisy driving. The precision $p$ is a Fano-factor-like observable which obeys the Thermodynamic Uncertainty Relation (TUR), that is an upper bound related to dissipation. We first consider independent motor noises with diffusivity $D$: in this case the precision goes as $k/D$, coherently with the behavior of spatial order. The minimum observed precision is that of the uncoupled oscillator $p_{unc}$, the maximum observed one is $Np_{unc}$, saturating the TUR bound. Then we consider driving noises which are spatially correlated, as it may happen in the presence of some direct coupling between adjacent motors. Such a spatial correlation in the noise does not reduce evidently the degree of spatial correlation in the chain, but sensibly reduces the maximum attainable precision $p$, coherently with experimental observations. The limiting behaviors of the precision, in the two opposite cases of negligible interaction and strong interaction, are well reproduced by the precision of the single chain site $p_{unc}$ and the precision of the center of mass of the chain $N_{eff} p_{unc}$ with $N_{eff}

A new Thermodynamic Uncertainty Relation (TUR) is derived for systems described by linearly coupled Langevin equations in the presence of non-linear frictional forces. In our scheme, the main variable represents the velocity of a particle, while the other coupled variables describe memory effects which may arise from strongly correlated degrees of freedom with several time-scales and, in general, are associated with thermal baths at different temperatures. The new TUR gives a lower bound for the mean-squared displacement of the position of the particle, including its asymptotic diffusion coefficient. This bound, in several examples worked out here, appears to be a good analytical estimate of the real diffusion coefficient. The new TUR can be also applied in the absence of any external force (with or without thermal equilibrium between the baths), a case which usually goes beyond the scope of original TURs. We show applications to non-linear frictional models with memory, such as the Coulomb and the Prantdtl-Tomlinson models, usually representative of friction at the nano-scale and within atomic-force microscopy experiments., Comment: 10 pages, 9 figures

Random exchange kinetic models are widely employed to describe the conservative dynamics of large interacting systems. Due to their simplicity and generality, they are quite popular in several fields, from statistical mechanics to biophysics and economics. Here we study a version where bounds on the individual shares of the globally conserved quantity are introduced. We analytically show that this dynamics allows stationary states with population inversion, described by Boltzmann statistics at negative absolute temperature. Their genuine equilibrium nature is verified by checking the detailed balance condition. An H-theorem is proven: the Boltzmann entropy monotonically increases during the dynamics. Finally, we provide analytical and numerical evidence that a large intruder in contact with the system thermalizes, suggesting a practical way to design a thermal bath at negative temperature. These results open new research perspectives, creating a bridge between negative temperature statistical descriptions and kinetic models with bounds., Comment: 5 pages, 2 figures

We present a study of the impact of an uncertainty in the beam far side-lobe knowledge on the measurement of the Cosmic Microwave Background $B$-mode signal at large scale. It is expected to be one of the main source of systematic effects in future CMB observations. Because it is crucial for all-sky survey missions to take into account the interplays between beam systematic effects and all the data analysis steps, the primary goal of this paper is to provide the methodology to carry out the end-to-end study of their effect for a space-borne CMB polarization experiment, up to the cosmological results in the form of a bias $\delta r$ on the tensor-to-scalar ratio $r$. LiteBIRD is dedicated to target the measurement of CMB primordial $B$ modes by reaching a sensitivity of $\sigma \left( r \right) \leq 10^{-3}$ assuming $r=0$. As a demonstration of our framework, we derive the relationship between the knowledge of the beam far side-lobes and the tentatively allocated error budget under given assumptions on design, simulation and component separation method. We assume no mitigation of the far side-lobes effect at any stage of the analysis pipeline. We show that $\delta r$ is mostly due to the integrated fractional power difference between the estimated beams and the true beams in the far side-lobes region, with little dependence on the actual shape of the beams, for low enough $\delta r$. Under our set of assumptions, in particular considering the specific foreground cleaning method we used, we find that the integrated fractional power in the far side-lobes should be known at a level as tight as $\sim 10^{-4}$, to achieve the required limit on the bias $\delta r < 1.9 \times 10^{-5}$. The framework and tools developed for this study can be easily adapted to provide requirements under different design, data analysis frameworks and for other future space-borne experiments beyond LiteBIRD.

Modern (sub)millimeter interferometers, such as ALMA and NOEMA, offer high angular resolution and unprecedented sensitivity. This provides the possibility to characterize the morphology of the gas and dust in distant galaxies. To assess the capabilities of current softwares in recovering morphologies and surface brightness profiles in interferometric observations, we test the performance of the Spergel model for fitting in the $uv$-plane, which has been recently implemented in the IRAM software GILDAS (uv$\_$fit). Spergel profiles provide an alternative to the Sersic profile, with the advantage of having an analytical Fourier transform, making them ideal to model visibilities in the $uv$-plane. We provide an approximate conversion between Spergel index and Sersic index, which depends on the ratio of the galaxy size to the angular resolution of the data. We show through extensive simulations that Spergel modeling in the $uv$-plane is a more reliable method for parameter estimation than modeling in the image-plane, as it returns parameters that are less affected by systematic biases and results in a higher effective signal-to-noise ratio (S/N). The better performance in the $uv$-plane is likely driven by the difficulty of accounting for correlated signal in interferometric images. Even in the $uv$-plane, the integrated source flux needs to be at least 50 times larger than the noise per beam to enable a reasonably good measurement of a Spergel index. We characterise the performance of Spergel model fitting in detail by showing that parameters biases are generally low (< 10%) and that uncertainties returned by uv$\_$fit are reliable within a factor of two. Finally, we showcase the power of Spergel fitting by re-examining two claims of extended halos around galaxies from the literature, showing that galaxies and halos can be successfully fitted simultaneously with a single Spergel model., Comment: 23 pages, 15 figures, accepted for publication in A&A

We estimate the efficiency of mitigating the lensing $B$-mode polarization, the so-called delensing, for the $LiteBIRD$ experiment with multiple external data sets of lensing-mass tracers. The current best bound on the tensor-to-scalar ratio, $r$, is limited by lensing rather than Galactic foregrounds. Delensing will be a critical step to improve sensitivity to $r$ as measurements of $r$ become more and more limited by lensing. In this paper, we extend the analysis of the recent $LiteBIRD$ forecast paper to include multiple mass tracers, i.e., the CMB lensing maps from $LiteBIRD$ and CMB-S4-like experiment, cosmic infrared background, and galaxy number density from $Euclid$- and LSST-like survey. We find that multi-tracer delensing will further improve the constraint on $r$ by about $20\%$. In $LiteBIRD$, the residual Galactic foregrounds also significantly contribute to uncertainties of the $B$-modes, and delensing becomes more important if the residual foregrounds are further reduced by an improved component separation method., Comment: 21 pages, 7 figures

We explore the capability of measuring lensing signals in $LiteBIRD$ full-sky polarization maps. With a $30$ arcmin beam width and an impressively low polarization noise of $2.16\,\mu$K-arcmin, $LiteBIRD$ will be able to measure the full-sky polarization of the cosmic microwave background (CMB) very precisely. This unique sensitivity also enables the reconstruction of a nearly full-sky lensing map using only polarization data, even considering its limited capability to capture small-scale CMB anisotropies. In this paper, we investigate the ability to construct a full-sky lensing measurement in the presence of Galactic foregrounds, finding that several possible biases from Galactic foregrounds should be negligible after component separation by harmonic-space internal linear combination. We find that the signal-to-noise ratio of the lensing is approximately $40$ using only polarization data measured over $90\%$ of the sky. This achievement is comparable to $Planck$'s recent lensing measurement with both temperature and polarization and represents a four-fold improvement over $Planck$'s polarization-only lensing measurement. The $LiteBIRD$ lensing map will complement the $Planck$ lensing map and provide several opportunities for cross-correlation science, especially in the northern hemisphere.

We study the possibility of using the $LiteBIRD$ satellite $B$-mode survey to constrain models of inflation producing specific features in CMB angular power spectra. We explore a particular model example, i.e. spectator axion-SU(2) gauge field inflation. This model can source parity-violating gravitational waves from the amplification of gauge field fluctuations driven by a pseudoscalar "axionlike" field, rolling for a few e-folds during inflation. The sourced gravitational waves can exceed the vacuum contribution at reionization bump scales by about an order of magnitude and can be comparable to the vacuum contribution at recombination bump scales. We argue that a satellite mission with full sky coverage and access to the reionization bump scales is necessary to understand the origin of the primordial gravitational wave signal and distinguish among two production mechanisms: quantum vacuum fluctuations of spacetime and matter sources during inflation. We present the expected constraints on model parameters from $LiteBIRD$ satellite simulations, which complement and expand previous studies in the literature. We find that $LiteBIRD$ will be able to exclude with high significance standard single-field slow-roll models, such as the Starobinsky model, if the true model is the axion-SU(2) model with a feature at CMB scales. We further investigate the possibility of using the parity-violating signature of the model, such as the $TB$ and $EB$ angular power spectra, to disentangle it from the standard single-field slow-roll scenario. We find that most of the discriminating power of $LiteBIRD$ will reside in $BB$ angular power spectra rather than in $TB$ and $EB$ correlations., Comment: 22 pages, 13 figures. Submitted to JCAP

We present observations and analysis of the starburst, PACS-819, at z=1.45 ($M_*=10^{10.7}$ M$_{ \odot}$), using high-resolution ($0^{\prime \prime}.1$; 0.8 kpc) ALMA and multi-wavelength JWST images from the COSMOS-Web program. Dissimilar to HST/ACS images in the rest-frame UV, the redder NIRCam and MIRI images reveal a smooth central mass concentration and spiral-like features, atypical for such an intense starburst. Through dynamical modeling of the CO J=5--4 emission with ALMA, PACS-819 is rotation-dominated thus has a disk-like nature. However, kinematic anomalies in CO and asymmetric features in the bluer JWST bands (e.g., F150W) support a more disturbed nature likely due to interactions. The JWST imaging further enables us to map the distribution of stellar mass and dust attenuation, thus clarifying the relationships between different structural components, not discernable in the previous HST images. The CO J = 5 -- 4 and FIR dust continuum emission are co-spatial with a heavily-obscured starbursting core (<1 kpc) which is partially surrounded by much less obscured star-forming structures including a prominent arc, possibly a tidally-distorted dwarf galaxy, and a clump, either a sign of an ongoing violent disk instability or a recently accreted low-mass satellite. With spatially-resolved maps, we find a high molecular gas fraction in the central area reaching $\sim3$ ($M_{\text{gas}}$/$M_*$) and short depletion times ($M_{\text{gas}}/SFR\sim$ 120 Myrs) across the entire system. These observations provide insights into the complex nature of starbursts in the distant universe and underscore the wealth of complementary information from high-resolution observations with both ALMA and JWST., Comment: 21 pages(including appendix), 13 figures, accepted by ApJ

We discuss a micro-swimmer model made of three spheres actuated by an internal active time-periodic force, tied by an elastic potential and submitted to hydrodynamic interactions with thermal noise. The dynamical approach we use, replacing the more common kinetic one, unveils the instability of the original model and the need of a confining potential to prevent the evaporation of the swimmer. We investigate the effect of the main parameters of the model, such as the frequency and phase difference of the periodic active force, the stiffness of the confining potential, the length of the swimmer and the temperature and viscosity of the fluid. Our observables of interest are the averages of the swim velocity, of the energy consumption rate, the diffusion coefficient and the swimming precision, which is limited by the energy consumption through the celebrated Thermodynamic Uncertainty Relations. An optimum for velocity and precision is found for an intermediate frequency. Reducing the potential stiffness, the viscosity or the length, is also beneficial for the swimming performance, but these parameters are limited by the consistency of the model. Analytical approximation for many of the interesting observables is obtained for small deformations of the swimmer. We also discuss the efficiency of the swimmer in terms of its maximum precision and of the hydrodynamic, or Lighthill, criterion, and how they are connected., Comment: 17 pages, 18 figures, submitted

Methods: Broad- and narrow-band imaging of AFGL 5180 was made in the NIR with the LBT, in both seeing-limited ($\sim0.5\arcsec$) and high angular resolution ($\sim0.09\arcsec$) Adaptive Optics (AO) modes, as well as with HST. Archival ALMA continuum data was also utilized. Results: At least 40 jet knots were identified via NIR emission from H$_2$ and [FeII] tracing shocked gas. Bright jet knots outflowing from the central most massive protostar, S4, are detected towards the east of the source and are resolved in fine detail with the AO imaging. Additional knots are distributed throughout the field, likely indicating the presence of multiple driving sources. Sub-millimeter sources detected by ALMA are shown to be grouped in two main complexes, AFGL 5180 M and a small cluster $\sim15\arcsec$ to the south, AFGL 5180 S. From our NIR continuum images we identify YSO candidates down to masses of $\sim 0.1\:M_\odot$. Combined with the sub-mm sources, this yields a surface number density of such YSOs of $N_* \sim 10^3 {\rm pc}^{-2}$ within a projected radius of about 0.1 pc. Such a value is similar to those predicted by models of both Core Accretion from a turbulent clump environment and Competitive Accretion. The radial profile of $N_*$ is relatively flat on scales out to 0.2~pc, with only modest enhancement around the massive protostar inside 0.05~pc. Conclusions: This study demonstrates the utility of high-resolution NIR imaging, in particular with AO, for detecting outflow activity and YSOs in distant regions. The presented images reveal the complex morphology of outflow-shocked gas within the large-scale bipolar flow of a massive protostar, as well as clear evidence for several other outflow driving sources in the region. Finally, this work presents a novel approach to compare the observed YSO surface number density from our study against different models of massive star formation., Comment: Accepted to Astronomy & Astrophysics (A&A)

It is well known that energy dissipation and finite size can deeply affect the dynamics of granular matter, often making usual hydrodynamic approaches problematic. Here we report on the experi-mental investigation of a small model system, made of ten beads constrained into a 1-d geometry by a narrow vertical pipe and shaken at the base by a piston excited by a periodic wave. Recording the beads motion with high frame rate camera allows to investigate in detail the microscopic dynamics and test hydrodynamic and kinetic models. Varying the energy we explore different regimes from fully fluidized to the edge of condensation, observing good hydrodynamic behavior down to the edge of fluidization, despite the small system size. Density and temperature fields for different system energies can be collapsed by suitable space and time rescaling, and the expected constitutive equation holds very well when the particle diameter is considered. At the same time the balance between dissipated and fed energy is not well described by commonly adopted dependence, due to the up-down symmetry breaking. Our observations, supported by the measured particle velocity distributions, show a different phenomenological temperature dependence, which yields equation solutions in agreement with experimental results.

Deep Audio Analyzer is an open source speech framework that aims to simplify the research and the development process of neural speech processing pipelines, allowing users to conceive, compare and share results in a fast and reproducible way. This paper describes the core architecture designed to support several tasks of common interest in the audio forensics field, showing possibility of creating new tasks thus customizing the framework. By means of Deep Audio Analyzer, forensics examiners (i.e. from Law Enforcement Agencies) and researchers will be able to visualize audio features, easily evaluate performances on pretrained models, to create, export and share new audio analysis workflows by combining deep neural network models with few clicks. One of the advantages of this tool is to speed up research and practical experimentation, in the field of audio forensics analysis thus also improving experimental reproducibility by exporting and sharing pipelines. All features are developed in modules accessible by the user through a Graphic User Interface. Index Terms: Speech Processing, Deep Learning Audio, Deep Learning Audio Pipeline creation, Audio Forensics.

The origin of obscuration in Active Galactic Nuclei (AGN) is still an open debate. In particular, it is unclear what drives the relative contributions to the line-of-sight column densities from galaxy-scale and torus-linked obscuration. The latter source is expected to play a significant role in Unification Models, while the former is thought to be relevant in both Unification and Evolutionary Models. In this work, we make use of a combination of cosmological semi-analytic models and semi-empirical prescriptions for the properties of galaxies and AGN, to study AGN obscuration. We consider a detailed object-by-object modelling of AGN evolution, including different AGN light curves (LCs), gas density profiles, and also AGN feedback-induced gas cavities. Irrespective of our assumptions on specific AGN LC or galaxy gas fractions, we find that, on the strict assumption of an exponential profile for the gas component, galaxy-scale obscuration alone can hardly reproduce the fraction of $\log (N_{\rm H}/$cm$^{-2}) \geq 24$ sources at least at $z\lesssim3$. This requires an additional torus component with a thickness that decreases with luminosity to match the data. The torus should be present in all evolutionary stages of a visible AGN to be effective, although galaxy-scale gas obscuration may be sufficient to reproduce the obscured fraction with $22<\log (N_{\rm H}/$cm$^{-2})<24$ (Compton-thin, CTN) if we assume extremely compact gas disc components. The claimed drop of CTN fractions with increasing luminosity does not appear to be a consequence of AGN feedback, but rather of gas reservoirs becoming more compact with decreasing stellar mass., Comment: MNRAS, accepted, 19 pages, 15 figures, 3 appendices

The SOUL systems at the Large Bincoular Telescope can be seen such as precursor for the ELT SCAO systems, combining together key technologies such as EMCCD, Pyramid WFS and adaptive telescopes. After the first light of the first upgraded system on September 2018, going through COVID and technical stops, we now have all the 4 systems working on-sky. Here, we report about some key control improvements and the system performance characterized during the commissioning. The upgrade allows us to correct more modes (500) in the bright end and increases the sky coverage providing SR(K)>20% with reference stars G$_{RP}$<17, opening to extragalcatic targets with NGS systems. Finally, we review the first astrophysical results, looking forward to the next generation instruments (SHARK-NIR, SHARK-Vis and iLocater), to be fed by the SOUL AO correction., Comment: 13 pages, 10 figures, Adaptive Optics for Extremely Large Telescopes 7th Edition, 25-30 Jun 2023 Avignon (France)

MORFEO (Multi-conjugate adaptive Optics Relay For ELT Observations, formerly MAORY), the MCAO system for the ELT, will provide diffraction-limited optical quality to the large field camera MICADO. MORFEO has officially passed the Preliminary Design Review and it is entering the final design phase. We present the current status of the project, with a focus on the adaptive optics system aspects and expected milestones during the next project phase.

Recovering the polarized cosmic microwave background (CMB) is crucial for shading light on Cosmic Inflation. Methods with different characteristics should be developed and optimized. We aim to use a neural network called CENN and train it for recovering the E and B modes of the CMB. We train the network with realistic simulations of 256x256 pixel squared patches at 100, 143 and 217 GHz Planck channels, which contain the CMB, thermal dust, synchrotron, PS and noise. We make several trainings sets: 30, 25 and 20 arcmin resolution patches at the same position in the sky. After being trained, CENN is able to recover the CMB signal at 143 GHz in Q and U patches. Then, we use NaMaster for estimating the EE and BB power spectrum for each input and output patches in the test dataset, as well as the difference between input and output power spectra and the residuals. We also test the methodology using a different foreground model at 5 arcmin resolution without noise. We recover the E-mode generally founding residuals bellow the input signal at all scales. In particular, we found a value of about 0.1 muK2 at l<200, decreasing below 0.01 muK2 at smaller scales. For the B-mode, we similarly recover the CMB with residuals between 0.01 and 0.001 muK2. We also train the network with 5 arcmin Planck simulations without noise, obtaining clearly better results with respect the previous cases. For a different foreground model, the recovery is similar, although B-mode residuals increase above the input signal. In general, we found that, the network performs better when training with the same resolution used for testing. Based on the results, CENN seems to be a promising for recovering both E and B modes at sub-degree scales in ground-base experiments such as POLARBEAR, SO and CMB-S4. Once extending its applicability at all sky, it could be an alternative component separation method for LiteBIRD satellite., Comment: 11 pages, 10 figures, Submitted to A&A

In the standard quasar model, the accretion disk obscuration is due to the canonical dusty torus. Here, we argue that a substantial part of the quasar obscuration can come from the interstellar medium (ISM) when the quasars are embedded in compact starbursts. We use an obscuration-unbiased sample of 578 infrared (IR) quasars at $z\approx 1-3$ and archival ALMA submillimeter host galaxy sizes to investigate the ISM contribution to the quasar obscuration. We calculate SFR and ISM column densities for the IR quasars and a control sample of submillimeter galaxies (SMGs) not hosting quasar activity and show that: (1) the quasar obscured fraction is constant up to $\rm SFR\approx 300 \: M_{\odot} \: yr^{-1}$, and then increases towards higher SFR, suggesting that the ISM obscuration plays a significant role in starburst host galaxies, and (2) at $\rm SFR\gtrsim 300 \: M_{\odot} \: yr^{-1}$, the SMGs and IR quasars have similarly compact submillimeter sizes ($R_{\rm e}\approx 0.5-3\rm \: kpc$) and, consequently, the ISM can heavily obscure the quasar, even reaching Compton-thick ($N_{\rm H}>10^{24} \rm \: cm^{-2}$) levels in extreme cases. Based on our results, we infer that $\approx 10-30\%$ of the IR quasars with $\rm SFR\gtrsim 300 \: M_{\odot} \: yr^{-1}$ are obscured solely by the ISM., Comment: Accepted for publication in MNRAS Letters

Multiscale phenomena exhibit complex structure-function relationships, and predicting their macroscopic behavior requires deducing differential equations at different scales. The complexity of these equations and the number of essential parameters make developing effective, predictive models challenging. To overcome this, researchers explore leveraging advanced numerical techniques from artificial intelligence and machine learning. Here, we focus on a fundamental aspect in multiscale phenomena, i.e the recognition of the hierarchical role of variables. By adopting a Pareto front interpretation, we aim to deduce simple and accurate relations for material modeling, starting from experimental multiscale analyses. From a physical point of view, the aim is to deduce information at higher scales from lower scales data, possibly respecting their hierarchical order. A crucial aspect of the proposed approach is the deduction of causality relations among the different variables to be compared with the available theoretical notions and possibly new interpretations resulting by the data modelling. This result in a stepwise approximation going from data modelling to theoretical equations and back to data modelling. To demonstrate the key advantages of our multiscale numerical approach, compared to classical, non-physically based data modelling techniques, we consider the explicit example of spider silk, known for its exceptional properties and bioinspiration potential. Indeed, it presents a complex behavior resulting from mesostructures formed by the aggregation of amino acids at the molecular scale. We argue that, due to the generality of our results, our approach may represent a proof of concept in many fields where multiscale, hierarchical differential equations regulate the observed phenomenon.

Nowadays many tools, e.g. fluctuation relations, are available to characterize the statistical properties of non-equilibrium systems. However, most of these tools rely on the assumption that the driving noise is normally distributed. Here we consider a class of Markov processes described by Langevin equations driven by a mixture of Gaussian and Poissonian noises, focusing on their non-equilibrium properties. In particular, we prove that detailed balance does not hold even when correlation functions are symmetric under time reversal. In such cases, a breakdown of the time reversal symmetry can be highlighted by considering higher order correlation functions. Furthermore, the entropy production may be different from zero even for vanishing currents. We provide analytical expressions for the average entropy production rate in several cases. We also introduce a scale dependent estimate for entropy production, suitable for inference from experimental signals. The empirical entropy production allows us to discuss the role of spatial and temporal resolutions in characterizing non-equilibrium features. Finally, we revisit the Brownian gyrator introducing an additional Poissonian noise showing that it behaves as a two dimensional linear ratchet. It has also the property that when Onsager relations are satisfied its entropy production is positive although it is minimal. We conclude discussing estimates of entropy production for partially accessible systems, comparing our results with the lower bound provided by the thermodynamics uncertainty relations., Comment: 30 pages, 11 figures. 20 pages main text, 8 pages appendices

The k-spectrum of a string is the set of all distinct substrings of length k occurring in the string. K-spectra have many applications in bioinformatics including pseudoalignment and genome assembly. The Spectral Burrows-Wheeler Transform (SBWT) has been recently introduced as an algorithmic tool to efficiently represent and query these objects. The longest common prefix (LCP) array for a k-spectrum is an array of length n that stores the length of the longest common prefix of adjacent k-mers as they occur in lexicographical order. The LCP array has at least two important applications, namely to accelerate pseudoalignment algorithms using the SBWT and to allow simulation of variable-order de Bruijn graphs within the SBWT framework. In this paper we explore algorithms to compute the LCP array efficiently from the SBWT representation of the k-spectrum. Starting with a straightforward O(nk) time algorithm, we describe algorithms that are efficient in both theory and practice. We show that the LCP array can be computed in optimal O(n) time, where n is the length of the SBWT of the spectrum. In practical genomics scenarios, we show that this theoretically optimal algorithm is indeed practical, but is often outperformed on smaller values of k by an asymptotically suboptimal algorithm that interacts better with the CPU cache. Our algorithms share some features with both classical Burrows-Wheeler inversion algorithms and LCP array construction algorithms for suffix arrays.

We propose a new conceptual approach to reach unattained dissipative properties based on the friction of slender concentric sliding columns. We begin by searching for the optimal topology in the simplest telescopic system of two concentric columns. Interestingly, we obtain that the optimal shape parameters are material independent and scale invariant. Based on a multiscale self-similar reconstruction, we end-up with a theoretical optimal fractal limit system whose cross section resembles the classical Sierpi\'nski triangle. Our optimal construction is finally completed by considering the possibility of a complete plane tessellation. The direct comparison of the dissipation per unit volume with the material dissipation up to the elastic limit shows a great advantage: . Such result is already attained for a realistic case of three only scales of refinement leading almost (96%) the same dissipation of the fractal limit. We also show the possibility of easy recovering of the original configuration after dissipation and we believe that our schematic system can have interesting reliable applications in different technological fields. Interestingly, our multiscale dissipative mechanism is reminiscent of similar strategies observed in nature as a result of bioadaptation such as in the archetypical cases of bone, nacre and spider silk. Even though other phenomena such as inelastic behavior and full tridimensional optimization are surely important in such biological systems, we believe that the suggested dissipation mechanism and scale invariance properties can give insight also in the hierarchical structures observed in important biological examples.

The Gaia-Multi-Peak (GMP) technique can be used to identify large numbers of dual or lensed AGN candidates at sub-arcsec separation, allowing us to study both multiple SMBHs in the same galaxy and rare, compact lensed systems. The observed samples can be used to test the predictions of the models of SMBH merging once 1) the selection function of the GMP technique is known, and 2) each system has been classified as dual AGN, lensed AGN, or AGN/star alignment. Here we show that the GMP selection is very efficient for separations above 0.15'' when the secondary (fainter) object has magnitude G<20.5. We present the spectroscopic classification of five GMP candidates using VLT/ERIS and Keck/OSIRIS, and compare them with the classifications obtained from: a) the near-IR colors of 7 systems obtained with LBT/LUCI, and b) the analysis of the total, spatially-unresolved spectra. We conclude that colors and integrated spectra can already provide reliable classifications of many systems. Finally, we summarize the confirmed dual AGNs at z>0.5 selected by the GMP technique, and compare this sample with other such systems from the literature, concluding that GMP can provide a large number of confirmed dual AGNs at separations below 7 kpc., Comment: 14 pages,A&A, in press

We present first results from the KMOS Ultra-deep Rotation Velocity Survey (KURVS), aimed at studying the outer rotation curves shape and dark matter content of 22 star-forming galaxies at $z\sim1.5$. These galaxies represent `typical' star-forming discs at $z \sim 1.5$, being located within the star-forming main sequence and stellar mass-size relation with stellar masses $9.5\leqslant$log$(M_{\star}/\mathrm{M_{\odot}})\leqslant11.5$. We extract individual rotation curves out to 4 times the effective radius, on average, or $\sim 10-15$ kpc. Most rotation curves are flat or rising between three- and six-disc scale radii. Only three objects with dispersion-dominated dynamics ($v_{\rm rot}/\sigma_0\sim0.2$) have declining outer rotation curves at more than 5$\sigma$ significance. After accounting for seeing and pressure support, the nine rotation-dominated discs with $v_{\rm rot}/\sigma_0\geqslant1.5$ have average dark matter fractions of $50 \pm 20\%$ at the effective radius, similar to local discs. Together with previous observations of star-forming galaxies at cosmic noon, our measurements suggest a trend of declining dark matter fraction with increasing stellar mass and stellar mass surface density at the effective radius. Simulated EAGLE galaxies are in quantitative agreement with observations up to log$(M_{\star}R_{\rm eff}^{-2}/\mathrm{M_{\odot}kpc^{-2}}) \sim 9.2$, and over-predict the dark matter fraction of galaxies with higher mass surface densities by a factor of $\sim 3$. We conclude that the dynamics of typical rotationally-supported discs at $z \sim 1.5$ is dominated by dark matter from effective radius scales, in broad agreement with cosmological models. The tension with observations at high stellar mass surface density suggests that the prescriptions for baryonic processes occurring in the most massive galaxies (such as bulge growth and quenching) need to be reassessed., Comment: 23 pages, 9 figures. Resubmitted to MNRAS after addressing the referee's comments. Abstract slightly modified to compile with the arXiv formatting