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In the past, high-z AGNs were given a minor role as possible drivers of reionization, despite initial evidences in favor of their large space densities at low luminosities by Chandra and HST. Recent observations from JWST are finding relatively large numbers of faint AGNs at z>4, convincingly confirming these early results. We present a sample of z~5 AGNs (both from wide, shallow ground-based surveys and from deep, pencil-beam observations from JWST), allowing to estimate their space densities with unprecedented accuracy. The bright end (M1450<-26) of the z~5 AGN luminosity function is well constrained, with a rather steep slope. The faint end (M1450>-22) indicates a high space density, the scatter is significant and the knee (M1450~-24) is mostly undetermined. Comparisons with state-of-the-art models find reasonable agreement with the observed AGN luminosity function at z=5, while the predicted space density evolution at higher redshifts appears to be too fast with respect to observational constraints. Given the large variance at the faint end, we consider different options in fitting the luminosity functions and deriving the ionizing emissivity. Even in the most conservative scenario, the photo-ionization rate produced by z~5 AGNs is consistent with the UV background measurements. A slow evolution of the space density of faint AGNs is observed, indicating that active SMBHs are probably producing large amounts of ionizing photons at z>6, well into the epoch of reionization. This is an important indication that high-z AGNs could be the major contributors to the reionization of the Universe., Comment: Accepted for publication on ApJ, 20 pages, 9 figures, 3 tables

Primordial abundances of light elements are sensitive to the physics of the early Universe and can directly constrain cosmological quantities, such as the baryon-to-photon ratio $\eta_{10}$, the baryon density and the number of neutrino families. Deuterium is especially suited for these studies: its primordial abundance is sensitive and monotonically dependent on $\eta_{10}$, allowing an independent measurement of the cosmic baryon density that can be compared, for instance, against the Planck satellite data. The primordial deuterium abundance can be measured in high $H_I$ column density absorption systems towards distant quasars. We report here a new measurement, based on high-resolution ESPRESSO data, of the primordial $D_I$ abundance of a system at redshift $z \sim 3.572$, towards PKS1937-101. Using only ESPRESSO data, we find a D/H ratio of $2.638\pm0.128 \times 10^{-5}$, while including the available UVES data improves the precision, leading to a ratio of $2.608 \pm 0.102 \times 10^{-5}$. The results of this analysis agree with those of the most precise existing measurements. We find that the relatively low column density of this system ($\log{N_{\rm H_I}/ {\rm cm}^{-2}}\sim18 $) introduces modelling uncertainties, which become the main contributor to the error budget., Comment: Accepted for publication in MNRAS. 16 pages, 10 figures and 6 tables (4 in main text, 2 in Appendix). Full model is available at the end of the manuscript

The gravitationally lensed quasar J014516.6-094517 at z=2.719 has been observed with the ESPRESSO instrument at the ESO VLT to obtain high-fidelity spectra of the two images A and B with a resolving power R=70000. At the redshifts under investigation (2.1 < z < 2.7), the Lyman forests along the two sightlines are separated by sub-kiloparsec physical distances and exhibit a strong correlation. We find that the two forests are indistinguishable at the present level of signal-to-noise ratio and do not show any global velocity shift, with the cross-correlation peaking at $\Delta v = 12 \pm 48$ m/s. The distribution of the difference in velocity of individual Lyman-$\alpha$ features is compatible with a null average and a mean absolute deviation of 930 m/s. Significant differences in NHI column density are not detected, putting a limit to the RMS fluctuation in the baryon density on $\leq 1$ proper kpc scales of $\Delta \rho / \rho < 3$%. On the other hand, metal lines show significant differences both in velocity structure and in column density. A toy model shows that the difference in velocity of the metal features between the two sightlines is compatible with the the motions of the baryonic component associated to dark matter halos of typical mass $M\simeq 2\times 10^{10} M_\odot$, also compatible with the observed incidence of the metal systems. The present observations confirm the feasibility of the Sandage test of the cosmic redshift drift with high-fidelity spectroscopy of the Lyman forest of distant, bright quasars, but also provide an element of caution about the intrinsic noise associated to the usage of metal features for the same purpose., Comment: 17 pages, 10 figures, 5 tables, accepted for publication in MNRAS

Inferring a process matrix characterizing a quantum channel from experimental measurements is a key issue of quantum information. Sometimes the noise affecting the measured counts brings to matrices very different from the expected ones and the mainly used estimation procedure, i.e. the maximum likelihood estimation (MLE), is also characterized by several drawbacks. To lower the noise could be necessary to increase the experimental resources, e.g. time for each measurement. In this paper, an alternative procedure, based on suitable Neural Networks, has been implemented and optimized to obtain a denoised process matrix and this approach has been tested with a specific quantum channel, i.e. a Control Phase. This promising method relies on the analogy that can be established between the elements of a process matrix and the pixels of an im

Context. The identification of bright QSOs is of great importance to probe the intergalactic medium and address open questions in cosmology. Several approaches have been adopted to find such sources in currently available photometric surveys, including machine learning methods. However, the rarity of bright QSOs at high redshifts compared to contaminating sources (such as stars and galaxies) makes the selection of reliable candidates a difficult task, especially when high completeness is required. Aims. We present a novel technique to boost recall (i.e., completeness within the considered sample) in the selection of QSOs from photometric datasets dominated by stars, galaxies, and low-z QSOs (imbalanced datasets). Methods. Our method operates by iteratively removing sources whose probability of belonging to a noninteresting class exceeds a user-defined threshold, until the remaining dataset contains mainly high-z QSOs. Any existing machine learning method can be used as underlying classifier, provided it allows for a classification probability to be estimated. We applied the method to a dataset obtained by cross-matching PanSTARRS1, Gaia, and WISE, and identified the high-z QSO candidates using both our method and its direct multi-label counterpart. Results. We ran several tests by randomly choosing the training and test datasets, and achieved significant improvements in recall which increased from 50% to 85% for QSOs with z>2.5, and from 70% to 90% for QSOs with z>3. Also, we identified a sample of 3098 new QSO candidates on a sample of 2.6x10^6 sources with no known classification. We obtained follow-up spectroscopy for 121 candidates, confirming 107 new QSOs with z>2.5. Finally, a comparison of our candidates with those selected by an independent method shows that the two samples overlap by more than 90% and that both methods are capable of achieving a high level of completeness., Comment: Accepted for publication on A&A

One of the key open questions in Cosmology is the nature of the sources that completed the cosmological hydrogen Reionization at z~5.2. High-z primeval galaxies have been long considered the main drivers for Reionization, with a minor role played by high-z AGN. However, in order to confirm this scenario, it is fundamental to measure the photo-ionization rate produced by active SMBHs close to the epoch of Reionization. Given the pivotal role played by spectroscopically complete observations of high-z QSOs, in this paper we present the first results of the RUBICON (Reionizing the Universe with BrIght COsmological Nuclei) survey. It consists of a color selected sample of bona-fide z~5 QSO candidates from the Hyper Suprime-Cam Subaru Strategic Survey. Our QSO candidates have been validated both by photometric redshifts based on SED fitting and by spectroscopic redshifts, confirming that they lie at 4.5

The analysis of absorption features along the line of sight to distant sources is an invaluable tool for observational cosmology, giving a direct insight into the physical and chemical state of the inter/circumgalactic medium. Such endeavour entails the accessibility of bright QSOs as background beacons, and the availability of software tools to extract the information in a reproducible way. In this article, we will present the latest results we obtained in both directions within the QUBRICS project: we will describe how machine learning techniques were applied to detect hundreds of previously unknown QSOs in the southern hemisphere, and how state-of-the art software like QSFit and Astrocook was integrated in the analysis of the targets, opening up new possibilities for the next era of observations., Comment: 4 pages, 2 figures; proceedings of ADASS XXXI, accepted by ASP Conference Series

The QUBRICS (QUasars as BRIght beacons for Cosmology in the Southern hemisphere) survey aims at constructing a sample of the brightest quasars with z>~2.5, observable with facilities in the Southern Hemisphere. QUBRICS makes use of the available optical and IR wide-field surveys in the South and of Machine Learning techniques to produce thousands of bright quasar candidates of which only a few hundred have been confirmed with follow-up spectroscopy. Taking advantage of the recent Gaia Data Release 3, which contains 220 million low-resolution spectra, and of a newly developed spectral energy distribution fitting technique, designed to combine the photometric information with the Gaia spectroscopy, it has been possible to measure 1672 new secure redshifts of QUBRICS candidates, with a typical uncertainty $\sigma_z = 0.02$. This significant progress of QUBRICS brings it closer to (one of) its primary goals: providing a sample of bright quasars at redshift 2.5 < z < 5 to perform the Sandage test of the cosmological redshift drift. A Golden Sample of seven quasars is presented that makes it possible to carry out this experiment in about 1500 hours of observation in 25 years, using the ANDES spectrograph at the 39m ELT, a significant improvement with respect to previous estimates., Comment: 11 pages, 10 figures, accepted for publication in MNRAS

The redshift drift is a small, dynamic change in the redshift of objects following the Hubble flow. Its measurement provides a direct, real-time, model-independent mapping of the expansion rate of the Universe. It is fundamentally different from other cosmological probes: instead of mapping our (present-day) past light-cone, it directly compares different past light-cones. Being independent of any assumptions on gravity, geometry or clustering, it directly tests the pillars of the Lambda-CDM paradigm. Recent theoretical studies have uncovered unique synergies with other cosmological probes, including the characterization of the physical properties of dark energy. At the time of the original proposal by Sandage (1962) the expected change in the redshift of objects at cosmological distances appeared to be exceedingly small for reasonable observing times and beyond technological capabilities. In the last decades progress in the spectrographs (e.g. ESPRESSO), in the collecting area of telescopes and in the samples of cosmic beacons, enabled by new datasets and new machine-learning-based selections, have drastically changed the situation, bringing the Redshift Drift Grail within reach. As a consequence, this measurement is a flagship objective of the Extremely Large Telescope (ELT), specifically of its high-resolution spectrograph, ANDES., Comment: Proceedings of the Conference "Past, Present and Future of Astrophysical Spectroscopy", Trieste, 6-10 June 2022; accepted for publication; 8 pages, 4 figures

The evolution of the luminosity function (LF) of Active Galactic Nuclei (AGNs) at $z \gtrsim 5$ represents a key constraint to understand their contribution to the ionizing photon budget necessary to trigger the last phase transition in the Universe, i.e. the epoch of Reionization. Recent searches for bright high-z AGNs suggest that the space densities of this population at $z>4$ has to be revised upwards, and sparks new questions about their evolutionary paths. Gas accretion is the key physical mechanism to understand both the distribution of luminous sources and the growth of central Super-Massive Black Holes (SMBHs). In this work, we model the high-z AGN-LF assuming that high-z luminous AGN shine at their Eddington limit: we derive the expected evolution as a function of the ``duty-cycle'' ($f_{\rm dc}$), i.e. the fraction of life-time that a given SMBH spends accreting at the Eddington rate. Our results show that intermediate values ($f_{\rm dc} \simeq 0.1$) predict the best agreement with the ionizing background and photoionization rate, but do not provide enough ionizing photons to account for the observed evolution of the hydrogen neutral fraction. Smaller values ($f_{\rm dc} \lesssim 0.05$) are required for AGNs to be the dominant population responsible for Hydrogen reionization in the Early Universe. We then show that this low-$f_{\rm dc}$ evolution can be reconciled with the current constraints on Helium reionization, although it implies a relatively large number of inactive SMBHs at $z\gtrsim5$, in tension with SMBH growth models based on heavy seeding., Comment: 11 pages, 5 figures, MNRAS accepted

Characterization of quantum objects, being them states, processes, or measurements, complemented by previous knowledge about them is a valuable approach, especially as it leads to routine procedures for real-life components. To this end, Machine Learning algorithms have demonstrated to successfully operate in presence of noise, especially for estimating specific physical parameters. Here we show that a neural network (NN) can improve the tomographic estimate of parameters by including a convolutional stage. We applied our technique to quantum process tomography for the characterization of several quantum channels. We demonstrate that a stable and reliable operation is achievable by training the network only with simulated data. The obtained results show the viability of this approach as an effective tool based on a completely new paradigm for the employment of NNs operating on classical data produced by quantum systems.

Several recent works have focused on the search for bright, high-z quasars (QSOs) in the South. Among them, the QUasars as BRIght beacons for Cosmology in the Southern hemisphere (QUBRICS) survey has now delivered hundreds of new spectroscopically confirmed QSOs selected by means of machine learning algorithms. Building upon the results obtained by introducing the probabilistic random forest (PRF) for the QUBRICS selection, we explore in this work the feasibility of training the algorithm on synthetic data to improve the completeness in the higher redshift bins. We also compare the performances of the algorithm if colours are used as primary features instead of magnitudes. We generate synthetic data based on a composite QSO spectral energy distribution. We first train the PRF to identify QSOs among stars and galaxies, then separate high-z quasar from low-z contaminants. We apply the algorithm on an updated dataset, based on SkyMapper DR3, combined with Gaia eDR3, 2MASS and WISE magnitudes. We find that employing colours as features slightly improves the results with respect to the algorithm trained on magnitude data. Adding synthetic data to the training set provides significantly better results with respect to the PRF trained only on spectroscopically confirmed QSOs. We estimate, on a testing dataset, a completeness of ~86% and a contamination of ~36%. Finally, 207 PRF-selected candidates were observed: 149/207 turned out to be genuine QSOs with z > 2.5, 41 with z < 2.5, 3 galaxies and 14 stars. The result confirms the ability of the PRF to select high-z quasars in large datasets., Comment: 18 pages, 15 figures. Accepted for publication (MNRAS). Removed a source from the catalogue due to uncertain classification (a star, QID = 1016233)