Search

Several approaches have been developed to mitigate algorithmic bias stemming from health data poverty, where minority groups are underrepresented in training datasets. Augmenting the minority class using resampling (such as SMOTE) is a widely used approach due to the simplicity of the algorithms. However, these algorithms decrease data variability and may introduce correlations between samples, giving rise to the use of generative approaches based on GAN. Generation of high-dimensional, time-series, authentic data that provides a wide distribution coverage of the real data, remains a challenging task for both resampling and GAN-based approaches. In this work we propose CA-GAN architecture that addresses some of the shortcomings of the current approaches, where we provide a detailed comparison with both SMOTE and WGAN-GP*, using a high-dimensional, time-series, real dataset of 3343 hypotensive Caucasian and Black patients. We show that our approach is better at both generating authentic data of the minority class and remaining within the original distribution of the real data., Comment: Accepted at NeurIPS 2022 Workshop on Synthetic Data for Empowering ML Research (Neurips 2022 SyntheticData4ML)

We present the results of the broadband X-ray spectral analysis of simultaneous NuSTAR and XMM-Newton observations of four nearby Compton-thick active galactic nuclei (AGN) candidates selected from the Swift-Burst Alert Telescope (BAT) 150-month catalog. This work is part of a larger effort to identify and characterize all Compton-thick (NH >= 10^24 cm^-2) AGN in the local Universe (z < 0.05). We used three physically motivated models -- MYTorus, borus02, and UXClumpy -- to fit and characterize these sources. Of the four candidates analyzed, 2MASX J02051994-0233055 was found to be an unobscured (NH < 10^22 cm^-2) AGN, 2MASX J04075215-6116126 and IC 2227 to be Compton-thin (10^22 cm^-2 < NH < 10^24 cm^-2) AGN, and one, ESO 362-8, was confirmed to be a Compton-thick AGN. Additionally, every source was found to have a statistically significant difference between their line-of-sight and average torus hydrogen column density, further supporting the idea that the obscuring material in AGN is inhomogeneous. Furthermore, half of the sources in our sample (2MASX J02051994-0233055 and 2MASX J04075215-6116126) exhibited significant luminosity variation in the last decade, suggesting that this might be a common feature of AGN.

We constrain the intrinsic Eddington ratio (\lamEdd ) distribution function for local AGN in bins of low and high obscuration (log NH <= 22 and 22 < log NH < 25), using the Swift-BAT 70-month/BASS DR2 survey. We interpret the fraction of obscured AGN in terms of circum-nuclear geometry and temporal evolution. Specifically, at low Eddington ratios (log lamEdd < -2), obscured AGN outnumber unobscured ones by a factor of ~4, reflecting the covering factor of the circum-nuclear material (0.8, or a torus opening angle of ~ 34 degrees). At high Eddington ratios (\log lamEdd > -1), the trend is reversed, with < 30% of AGN having log NH > 22, which we suggest is mainly due to the small fraction of time spent in a highly obscured state. Considering the Eddington ratio distribution function of narrow-line and broad-line AGN from our prior work, we see a qualitatively similar picture. To disentangle temporal and geometric effects at high lamEdd, we explore plausible clearing scenarios such that the time-weighted covering factors agree with the observed population ratio. We find that the low fraction of obscured AGN at high lamEdd is primarily due to the fact that the covering factor drops very rapidly, with more than half the time is spent with < 10% covering factor. We also find that nearly all obscured AGN at high-lamEdd exhibit some broad-lines. We suggest that this is because the height of the depleted torus falls below the height of the broad-line region, making the latter visible from all lines of sight., Comment: Accepted by ApJL

We present X-ray spectral analysis of XMM and Chandra observations in the 31.3 deg$^2$ Stripe-82X (S82X) field. Of the 6181 X-ray sources in this field, we analyze a sample of 2937 active galactic nuclei (AGN) with solid redshifts and sufficient counts determined by simulations. Our results show a population with median values of spectral index $\Gamma=1.94_{-0.39}^{+0.31}$, column density log$\,N_{\mathrm{H}}/\mathrm{cm}^{-2}=20.7_{-0.5}^{+1.2}$ and intrinsic, de-absorbed, 2-10 keV luminosity log$\,L_{\mathrm{X}}/\mathrm{erg\,s}^{-1}=44.0_{-1.0}^{+0.7}$, in the redshift range 0-4. We derive the intrinsic fraction of AGN that are obscured ($22\leq\mathrm{log}\,N_{\mathrm{H}}/\mathrm{cm}^{-2}<24$), finding a significant increase in the obscured AGN fraction with redshift and a decline with increasing luminosity. The average obscured AGN fraction is $57\pm4\%$ for log$\,L_{\mathrm{X}}/\mathrm{erg\,s}^{-1}>43$. This work constrains the AGN obscuration and spectral shape of the still uncertain high-luminosity and high-redshift regimes (log$\,L_{\mathrm{X}}/\mathrm{erg\,s}^{-1}>45.5$, $z>3$), where the obscured AGN fraction rises to $64\pm12\%$. We report a luminosity and density evolution of the X-ray luminosity function, with obscured AGN dominating at all luminosities at $z>2$ and unobscured sources prevailing at log$\,L_{\mathrm{X}}/\mathrm{erg\,s}^{-1}>45$ at lower redshifts. Our results agree with evolutionary models in which the bulk of AGN activity is triggered by gas-rich environments and in a downsizing scenario. Also, the black hole accretion density (BHAD) is found to evolve similarly to the star formation rate density, confirming the co-evolution between AGN and host-galaxy, but suggesting different time scales in their growing history. The derived BHAD evolution shows that Compton-thick AGN contribute to the accretion history of AGN as much as all other AGN populations combined., Comment: 31 pages, 35 figures, Accepted for publication in ApJ

Observations and simulations of interacting galaxies and mergers in the local universe have shown that interactions can significantly enhance the star formation rates (SFR) and fueling of Active Galactic Nuclei (AGN). However, at higher redshift, some simulations suggest that the level of star formation enhancement induced by interactions is lower due to the higher gas fractions and already increased SFRs in these galaxies. To test this, we measure the SFR enhancement in a total of 2351 (1327) massive ($M_*>10^{10}M_\odot$) major ($1

We present the timing and spectral analysis of the Compton Thick Seyfert 2 active galactic nuclei NGC 1068 observed using {\it NuSTAR} and {\it XMM-Newton}. In this work for the first time we calculated the coronal temperature ($\rm{kT_{e}}$) of the source and checked for its variation between the epochs if any. The data analysed in this work comprised of (a) eight epochs of observations with {\it NuSTAR} carried out during the period December 2012 to November 2017, and, (b) six epochs of observations with {\it XMM-Newton} carried out during July 2000 to February 2015. From timing analysis of the {\it NuSTAR} observations, we found the source not to show any variations in the soft band. However, on examination of the flux at energies beyond 20 keV, during August 2014 and August 2017 the source was brighter by about 20\% and 30\% respectively compared to the mean flux of the three 2012 {\it NuSTAR} observations as in agreement with earlier results in literature. From an analysis of {\it XMM-Newton} data we found no variation in the hard band (2 $-$ 4 keV) between epochs as well as within epochs. In the soft band (0.2 $-$ 2 keV), while the source was found to be not variable within epochs, it was found to be brighter in epoch B relative to epoch A. By fitting physical models we determined $\rm{kT_{e}}$ to range between 8.46$^{+0.39}_{-0.66}$ keV and 9.13$^{+0.63}_{-0.98}$ keV. From our analysis, we conclude that we found no variation of $\rm{kT_{e}}$ in the source., Comment: 13 pages, 14 figures, accepted for publication in MNRAS

We study online learning problems in which a decision maker has to take a sequence of decisions subject to $m$ long-term constraints. The goal of the decision maker is to maximize their total reward, while at the same time achieving small cumulative constraints violation across the $T$ rounds. We present the first best-of-both-world type algorithm for this general class of problems, with no-regret guarantees both in the case in which rewards and constraints are selected according to an unknown stochastic model, and in the case in which they are selected at each round by an adversary. Our algorithm is the first to provide guarantees in the adversarial setting with respect to the optimal fixed strategy that satisfies the long-term constraints. In particular, it guarantees a $\rho/(1+\rho)$ fraction of the optimal reward and sublinear regret, where $\rho$ is a feasibility parameter related to the existence of strictly feasible solutions. Our framework employs traditional regret minimizers as black-box components. Therefore, by instantiating it with an appropriate choice of regret minimizers it can handle the full-feedback as well as the bandit-feedback setting. Moreover, it allows the decision maker to seamlessly handle scenarios with non-convex rewards and constraints. We show how our framework can be applied in the context of budget-management mechanisms for repeated auctions in order to guarantee long-term constraints that are not packing (e.g., ROI constraints).

We study a repeated information design problem faced by an informed sender who tries to influence the behavior of a self-interested receiver. We consider settings where the receiver faces a sequential decision making (SDM) problem. At each round, the sender observes the realizations of random events in the SDM problem. This begets the challenge of how to incrementally disclose such information to the receiver to persuade them to follow (desirable) action recommendations. We study the case in which the sender does not know random events probabilities, and, thus, they have to gradually learn them while persuading the receiver. We start by providing a non-trivial polytopal approximation of the set of sender's persuasive information structures. This is crucial to design efficient learning algorithms. Next, we prove a negative result: no learning algorithm can be persuasive. Thus, we relax persuasiveness requirements by focusing on algorithms that guarantee that the receiver's regret in following recommendations grows sub-linearly. In the full-feedback setting -- where the sender observes all random events realizations -- , we provide an algorithm with $\tilde{O}(\sqrt{T})$ regret for both the sender and the receiver. Instead, in the bandit-feedback setting -- where the sender only observes the realizations of random events actually occurring in the SDM problem -- , we design an algorithm that, given an $\alpha \in [1/2, 1]$ as input, ensures $\tilde{O}({T^\alpha})$ and $\tilde{O}( T^{\max \{ \alpha, 1-\frac{\alpha}{2} \} })$ regrets, for the sender and the receiver respectively. This result is complemented by a lower bound showing that such a regrets trade-off is essentially tight.

Designing efficient algorithms to find Nash equilibrium (NE) refinements in sequential games is of paramount importance in practice. Indeed, it is well known that the NE has several weaknesses, since it may prescribe to play sub-optimal actions in those parts of the game that are never reached at the equilibrium. NE refinements, such as the extensive-form perfect equilibrium (EFPE), amend such weaknesses by accounting for the possibility of players' mistakes. This is crucial in real-world applications, where bounded rationality players are usually involved, and it turns out being useful also in boosting the performances of superhuman agents for recreational games like Poker. Nevertheless, only few works addressed the problem of computing NE refinements. Most of them propose algorithms finding exact NE refinements by means of linear programming, and, thus, these do not have the potential of scaling up to real-world-size games. On the other hand, existing iterative algorithms that exploit the tree structure of sequential games only provide convergence guarantees to approximate refinements. In this paper, we provide the first efficient last-iterate algorithm that provably converges to an EFPE in two-player zero-sum sequential games with imperfect information. Our algorithm works by tracking a sequence of equilibria of suitably-defined, regularized-perturbed games. In order to do that, it uses a procedure that is tailored to converge last-iterate to the equilibria of such games. Crucially, the updates performed by such a procedure can be performed efficiently by visiting the game tree, thus making our algorithm potentially more scalable than its linear-programming-based competitors. Finally, we evaluate our algorithm on a standard testbed of games, showing that it produces strategies which are much more robust to players' mistakes than those of state-of-the-art NE-computation algorithms.

We present a new X-Ray Accretion Disk-wind Emulator (\textsc{xrade}) based on the 2.5D Monte Carlo radiative transfer code which provides a physically-motivated, self-consistent treatment of both absorption and emission from a disk-wind by computing the local ionization state and velocity field within the flow. \textsc{xrade} is then implemented through a process that combines X-ray tracing with supervised machine learning. We develop a novel emulation method consisting in training, validating, and testing the simulated disk-wind spectra into a purposely built artificial neural network. The trained emulator can generate a single synthetic spectrum for a particular parameter set in a fraction of a second, in contrast to the few hours required by a standard Monte Carlo radiative transfer pipeline. The emulator does not suffer from interpolation issues with multi-dimensional spaces that are typically faced by traditional X-ray fitting packages such as \textsc{xspec}. \textsc{xrade} will be suitable to a wide number of sources across the black-hole mass, ionizing luminosity, and accretion rate scales. As an example, we demonstrate the applicability of \textsc{xrade} to the physical interpretation of the X-ray spectra of the bright quasar PDS 456, which hosts the best-established accretion-disk wind observed to date. We anticipate that our emulation method will be an indispensable tool for the development of high-resolution theoretical models, with the necessary flexibility to be optimized for the next generation micro-calorimeters on board future missions, like \textit{XRISM/resolve} and \textit{Athena/X-IFU}. This tool can also be implemented across a wide variety of X-ray spectral models and beyond., Comment: 20 pages, 17 figures, MNRAS accepted for publication

We present the multi-epoch monitoring with NuSTAR and XMM-Newton of NGC 1358, a nearby Seyfert 2 galaxy whose properties made it a promising candidate X-ray changing look AGN, i.e., a source whose column density could transition from its 2017 Compton-thick (CT-, having line-of-sight Hydrogen column density NH,los>10^24 cm^-2) state to a Compton-thin (NH,los<10^24 cm^-2) one. The multi-epoch X-ray monitoring confirmed the presence of significant NH,los variability over time-scales as short as weeks, and allowed us to confirm the "changing look" nature of NGC 1358, which has most recently been observed in a Compton-thin status. Multi-epoch monitoring with NuSTAR and XMM-Newton is demonstrated to be highly effective in simultaneously constraining three otherwise highly degenerate parameters: the torus average column density and covering factor, and the inclination angle between the torus axis and the observer. We find a tentative anti-correlation between column density and luminosity, which can be understood in the framework of Chaotic Cold Accretion clouds driving recursive AGN feedback. The monitoring campaign of NGC 1358 has proven the efficiency of our newly developed method to select candidate NH,los-variable, heavily obscured AGN, which we plan to soon extend to a larger sample to better characterize the properties of the obscuring material surrounding accreting supermassive black holes, as well as constrain AGN feeding models., Comment: 24 pages, 13 figures: main results in Figures 4, 7, 8 and 9. Accepted for publication in the Astrophysical Journal

Active galactic nuclei (AGN) are powered by accreting supermassive black holes, surrounded by a torus of obscuring material. Recent studies have shown how the torus structure, formerly thought to be homogeneous, appears to be 'patchy': the detection of variability in the line-of-sight hydrogen column density, in fact, matches the description of an obscurer with a complex structure made of clouds with different column density. In this work, we perform a multi-epoch analysis of the X-ray spectra of the Seyfert 2 galaxy NGC 7479 in order to estimate its torus properties, such as the average column density and the covering factor. The measurement of the line-of-sight hydrogen column density variability of the torus allows us to obtain an upper limit on the cloud distance from the central engine. In addition, using the X-ray luminosity of the source, we estimate the Eddington ratio to be in a range of Edd=0.04-0.05 over all epochs., Comment: Re-submitted to ApJ after minor reviews

We aim to determine the intrinsic far-Infrared (far-IR) emission of X-ray-luminous quasars over cosmic time. Using a 16 deg^2 region of the Stripe 82 field surveyed by XMM-Newton and Herschel Space Observatory, we identify 2905 X-ray luminous (LX > 10^42 erg/s) Active Galactic Nuclei (AGN) in the range z ~ 0-3. The IR is necessary to constrain host galaxy properties such as star formation rate (SFR) and gas mass. However, only 10% of our AGN are detected both in the X-ray and IR. Because 90% of the sample is undetected in the far-IR by Herschel, we explore the mean IR emission of these undetected sources by stacking their Herschel/SPIRE images in bins of X-ray luminosity and redshift. We create stacked spectral energy distributions from the optical to the far-IR, and estimate the median star formation rate, dust mass, stellar mass, and infrared luminosity using a fitting routine. We find that the stacked sources on average have similar SFR/L_bol ratios as IR detected sources. The majority of our sources fall on or above the main sequence line suggesting that X-ray selection alone does not predict the location of a galaxy on the main sequence. We also find that the gas depletion timescales of our AGN are similar to those of dusty star forming galaxies. This suggests that X-ray selected AGN host high star formation and that there are no signs of declining star formation., Comment: 26 pages, 14 figures, 5 tables, submitted to MNRAS

Explaining the existence of $\gtrsim10^8\,\mathrm{M_\odot}$ SMBHs at $z>6$ is a persistent challenge to modern astrophysics. Multi-wavelength observations of $z\gtrsim6$ QSOs reveal that, on average, their accretion physics is similar to that of their counterparts at lower redshift. However, QSOs showing properties that deviate from the general behavior can provide useful insights into the physical processes responsible for the rapid growth of SMBHs in the early universe. We present X-ray (XMM-Newton, 100 ks) follow-up observations of a $z\approx6$ QSO, J1641+3755, which was found to be remarkably X-ray bright in a 2018 Chandra dataset. J1641+3755 is not detected in the 2021 XMM-Newton observation, implying that its X-ray flux decreased by a factor $\gtrsim7$ on a notably short timescale (i.e., $\approx115$ rest-frame days), making it the $z>4$ QSO with the largest variability amplitude. We also obtained rest-frame UV spectroscopic and photometric data with textit{LBT}, and compared them with archival datasets. Surprisingly, we found that J1641+3755 became brighter in the rest-frame UV band from 2003 to 2016, while no strong variation occurred from 2016 to 2021. Multiple narrow absorption features are detected in its rest-frame UV spectrum, and several of them can be associated with an intervening system at $z=5.67$. The variability properties of J1641+3755 can be due to intrinsic variations of the accretion rate, a small-scale obscuration event, gravitational lensing due to an intervening object, or an unrelated X-ray transient in a foreground galaxy in 2018. Accounting for all of the $z>6$ QSOs with multiple X-ray observations separated by $>10$ rest-frame days, we found an enhancement of strongly (i.e., by a factor $>3$) X-ray variable objects compared to QSOs at later cosmic times. This finding may be related to the physics of fast accretion in high-redshift QSOs., Comment: 14 pages. Accepted for publication on A&A

We combine results from deep ALMA observations of massive ($M_*>10^{10}\;M_{\odot}$) galaxies at different redshifts to show that the column density of their inter stellar medium (ISM) rapidly increases towards early cosmic epochs. Our analysis includes objects from the ASPECS and ALPINE large programs, as well as individual observations of $z\sim 6$ QSO hosts. When accounting for non-detections and correcting for selection effects, we find that the median surface density of the ISM of the massive galaxy population evolves as $\sim(1+z)^{3.3}$. This means that the ISM column density towards the nucleus of a $z>3$ galaxy is typically $>100$ times larger than locally, and it may reach values as high as Compton-thick at $z\gtrsim6$. Remarkably, the median ISM column density is of the same order of what is measured from X-ray observations of large AGN samples already at $z\gtrsim2$. We develop a simple analytic model for the spatial distribution of ISM clouds within galaxies, and estimate the total covering factor towards active nuclei when obscuration by ISM clouds on the host scale is added to that of pc-scale circumnuclear material (the so-called 'torus'). The model includes clouds with a distribution of sizes, masses, and surface densities, and also allows for an evolution of the characteristic cloud surface density with redshift, $\Sigma_{c,*}\propto(1+z)^\gamma$. We show that, for $\gamma=2$, such a model successfully reproduces the increase of the obscured AGN fraction with redshift that is commonly observed in deep X-ray surveys, both when different absorption thresholds and AGN luminosities are considered. Our results suggest that 80-90\% of supermassive black holes in the early Universe ($z>6-8$) are hidden to our view, primarily by the ISM in their hosts. [abridged], Comment: 22 pages, 15 figures, accepted for publication in A&A

The increasing competition in digital advertising induced a proliferation of media agencies playing the role of intermediaries between advertisers and platforms selling ad slots. When a group of competing advertisers is managed by a common agency, many forms of collusion, such as bid rigging, can be implemented by coordinating bidding strategies, dramatically increasing advertisers' value. We study the problem of finding bids and monetary transfers maximizing the utility of a group of colluders, under GSP and VCG mechanisms. First, we introduce an abstract bid optimization problem -- called weighted utility problem (WUP) -- , which is useful in proving our results. We show that the utilities of bidding strategies are related to the length of paths in a directed acyclic weighted graph, whose structure and weights depend on the mechanism under study. This allows us to solve WUP in polynomial time by finding a shortest path of the graph. Next, we switch to our original problem, focusing on two settings that differ for the incentives they allow for. Incentive constraints ensure that colluders do not leave the agency, and they can be enforced by implementing monetary transfers between the agency and the advertisers. In particular, we study the arbitrary transfers setting, where any kind of monetary transfer to and from the advertisers is allowed, and the more realistic limited liability setting, in which no advertiser can be paid by the agency. In the former, we cast the problem as a WUP instance and solve it by our graph-based algorithm, while, in the latter, we formulate it as a linear program with exponentially-many variables efficiently solvable by applying the ellipsoid algorithm to its dual. This requires to solve a suitable separation problem in polynomial time, which can be done by reducing it to a WUP instance.

We present a multi-wavelength study of the molecular gas properties of a sample of local Seyfert 2 galaxies to assess if, and to what extent, the presence of an active galactic nucleus (AGN) can affect the Interstellar Medium (ISM) properties in a sample of 33 local Seyfert 2 galaxies. We compare the molecular gas content (MH2), derived from new and archival low-J CO line measurements of a sample of AGN and a control sample of star-forming galaxies (SFGs). Both the AGN and the control sample are characterised in terms of host-galaxy properties (e.g., stellar and dust masses, Mstar and Mdust, respectively; and star formation rate, SFR). We also investigate the effect of AGN activity onto the emission of polycyclic aromatic hydrocarbon (PAH) molecules in the mid-infrared (MIR), a waveband where the dust-reprocessed emission from the obscured AGN contributes the most. The AGN hosted in less massive galaxies (i.e., log(Mstar/Msun)<10.5; log(Mdust/Msun)<7.5) show larger molecular gas content with respect to SFGs matched in stellar and dust mass. When comparing their depletion time(tdep~MH2/SFR), AGN show tdep~0.3-1.0 Gyr, similar to those observed in the control sample of SFGs. Seyfert 2 galaxies show fainter PAH luminosity at increasingly larger dominance of the nuclear activity in the MIR. We find no clear evidence for a systematic reduction of the molecular gas reservoir at galactic scale in Seyfert galaxies with respect to SFGs. This is in agreement with recent studies showing that molecular gas content only is reduced in regions of sub-kpc size, where the emission from the accreting supermassive black hole dominates. Nonetheless, we show that the impact of AGN activity on the ISM is clearly visible as suppression of the PAH luminosity., Comment: Accepted for publication by A&A. 22 pages, 9 figures, 3 tables. APEX spectra available through CDS archive

We characterize the average X-ray and radio properties of quiescent galaxies (QGs) with $\log{(M_\star/M_\odot)}>10$ at $01.5$ is higher than that of star-forming galaxies (SFGs), derived in the same manner as QGs. The stacking analysis of the VLA-COSMOS images is conducted for the identical sample, and the radio signal for QGs is also detected up to $z\sim5$. We find that the radio AGN luminosity of QGs at $z>1.5$ is also higher than SFGs, which is in good agreement with the X-ray analysis. The enhanced AGN activity in QGs suggested by the individual analysis in the X-ray and radio wavelength supports its important role for quenching at high redshift. Their enhanced AGN activity is less obvious at $z<1.5$, which can be interpreted as an increasing role of others at lower redshifts, such as environmental quenching., Comment: 24 pages, 20 figures, 2 tables, Accepted for publication in ApJ

We study hidden-action principal-agent problems in which a principal commits to an outcome-dependent payment scheme (called contract) so as to incentivize the agent to take a costly, unobservable action leading to favorable outcomes. In particular, we focus on Bayesian settings where the agent has private information. This is collectively encoded by the agent's type, which is unknown to the principal, but randomly drawn according to a finitely-supported, commonly-known probability distribution. In Bayesian principal-agent problems, the principal may be better off by committing to a menu of contracts specifying a contract for each agent's type, rather than committing to a single contract. This induces a two-stage process that resembles interactions studied in classical mechanism design: after the principal has committed to a menu, the agent first reports a type to the principal, and, then, the latter puts in place the contract in the menu that corresponds to the reported type. Thus, the principal's computational problem boils down to designing a menu of contracts that incentivizes the agent to report their true type and maximizes expected utility. Previous works showed that computing an optimal menu of contracts is APX-hard. Crucially, previous works focus on menus of deterministic contracts. Surprisingly, we show that, if one considers menus of randomized contracts defined as probability distributions over payment vectors, then an "almost-optimal" menu can be computed in polynomial time. Indeed, the problem of computing a principal-optimal menu of randomized contracts may not admit a maximum, but only a supremum. Nevertheless, we show how to design a polynomial-time algorithm that guarantees the principal with an expected utility arbitrarily close to the supremum. Besides this main result, we also close several gaps in the analysis of menus of deterministic contracts.

We present the combined Chandra and Swift-BAT spectral analysis of nine low-redshift (z <= 0.10), candidate heavily obscured active galactic nuclei (AGN) selected from the Swift-BAT 150-month catalog. We located soft (1-10 keV) X-ray counterparts to these BAT sources and joint fit their spectra with physically motivated models.The spectral analysis in the 1-150 keV energy band determined that all sources are obscured, with a line-of-sight column density NH >= 10^22 cm^-2 at a 90% confidence level. Four of these sources show significant obscuration with NH >= 10^23 cm^-2 and two additional sources are candidate Compton-thick Active Galactic Nuclei (CT-AGNs) with NH >= 10^24 cm^-2.These two sources, 2MASX J02051994-0233055 and IRAS 11058-1131, are the latest addition to the previous 3 CT-AGN candidates found using our strategy for soft X-ray follow-up of BAT sources. In here we present the results of our methodology so far, and analyze the effectiveness of applying different selection criteria to discover CT-AGN in the local Universe. Our selection criteria has a ~20% success rate of discovering heavily obscured AGN whose CT nature is confirmed by follow-up NuSTAR observations. This is much higher than the ~5% found in blind surveys.

Bayesian persuasion studies how an informed sender should partially disclose information so as to influence the behavior of self-interested receivers. In the last years, a growing attention has been devoted to relaxing the assumption that the sender perfectly knows receiver's payoffs. The first crucial step towards such an achievement is to study settings where each receiver's payoffs depend on their unknown type, which is randomly determined by a known finite-supported probability distribution. This begets considerable computational challenges, as computing a sender-optimal signaling scheme is inapproximable up to within any constant factor. In this work, we circumvent this issue by leveraging ideas from mechanism design. In particular, we introduce a type reporting step in which the receiver is asked to report their type to the sender, after the latter has committed to a menu defining a signaling scheme for each possible receiver's type. We prove that, with a single receiver, the addition of this type reporting stage makes the sender's computational problem tractable. Then, we extend our framework to settings with multiple receivers, focusing on the case of no inter-agent externalities and binary actions. We show that it is possible to find a sender-optimal solution in polynomial-time by means of the ellipsoid method, given access to a suitable polynomial-time separation oracle. This can be implemented for supermodular and anonymous sender's utility functions. As for the case of submodular sender's utility functions, we first approximately cast the sender's problem into a linearly-constrained mathematical program whose objective function is the multi-linear extension of the sender's utility. Then, we show how to find in polynomial-time an approximate solution to the program by means of a continuous greedy algorithm. This provides a (1 -1/e)-approximation to the problem.

Most of the economic reports forecast that almost half of the worldwide market value unlocked by AI over the next decade (up to 6 trillion USD per year) will be in marketing&sales. In particular, AI will enable the optimization of more and more intricate economic settings, in which multiple different activities need to be jointly automated. This is the case of, e.g., Google Hotel Ads and Tripadvisor, where auctions are used to display ads of similar products or services together with their prices. As in classical ad auctions, the ads are ranked depending on the advertisers' bids, whereas, differently from classical settings, ads are displayed together with their prices, so as to provide a direct comparison among them. This dramatically affects users' behavior, as well as the properties of ad auctions. We show that, in such settings, social welfare maximization can be achieved by means of a direct-revelation mechanism that jointly optimizes, in polynomial time, the ads allocation and the advertisers' prices to be displayed with them. However, in practice it is unlikely that advertisers allow the mechanism to choose prices on their behalf. Indeed, in commonly-adopted mechanisms, ads allocation and price optimization are decoupled, so that the advertisers optimize prices and bids, while the mechanism does so for the allocation, once prices and bids are given. We investigate how this decoupling affects the efficiency of mechanisms. In particular, we study the Price of Anarchy (PoA) and the Price of Stability (PoS) of indirect-revelation mechanisms with both VCG and GSP payments, showing that the PoS for the revenue may be unbounded even with two slots, and the PoA for the social welfare may be as large as the number of slots. Nevertheless, we show that, under some assumptions, simple modifications to the indirect-revelation mechanism with VCG payments achieve a PoS of 1 for the revenue.

We study single-item single-unit Bayesian posted price auctions, where buyers arrive sequentially and their valuations for the item being sold depend on a random, unknown state of nature. The seller has complete knowledge of the actual state and can send signals to the buyers so as to disclose information about it. For instance, the state of nature may reflect the condition and/or some particular features of the item, which are known to the seller only. The problem faced by the seller is about how to partially disclose information about the state so as to maximize revenue. Unlike classical signaling problems, in this setting, the seller must also correlate the signals being sent to the buyers with some price proposals for them. This introduces additional challenges compared to standard settings. We consider two cases: the one where the seller can only send signals publicly visible to all buyers, and the case in which the seller can privately send a different signal to each buyer. As a first step, we prove that, in both settings, the problem of maximizing the seller's revenue does not admit an FPTAS unless P=NP, even for basic instances with a single buyer. As a result, in the rest of the paper, we focus on designing PTASs. In order to do so, we first introduce a unifying framework encompassing both public and private signaling, whose core result is a decomposition lemma that allows focusing on a finite set of possible buyers' posteriors. This forms the basis on which our PTASs are developed. In particular, in the public signaling setting, our PTAS employs some ad hoc techniques based on linear programming, while our PTAS for the private setting relies on the ellipsoid method to solve an exponentially-sized LP in polynomial time. In the latter case, we need a custom approximate separation oracle, which we implement with a dynamic programming approach.

We study signaling in Bayesian ad auctions, in which bidders' valuations depend on a random, unknown state of nature. The auction mechanism has complete knowledge of the actual state of nature, and it can send signals to bidders so as to disclose information about the state and increase revenue. For instance, a state may collectively encode some features of the user that are known to the mechanism only, since the latter has access to data sources unaccessible to the bidders. We study the problem of computing how the mechanism should send signals to bidders in order to maximize revenue. While this problem has already been addressed in the easier setting of second-price auctions, to the best of our knowledge, our work is the first to explore ad auctions with more than one slot. In this paper, we focus on public signaling and VCG mechanisms, under which bidders truthfully report their valuations. We start with a negative result, showing that, in general, the problem does not admit a PTAS unless P = NP, even when bidders' valuations are known to the mechanism. The rest of the paper is devoted to settings in which such negative result can be circumvented. First, we prove that, with known valuations, the problem can indeed be solved in polynomial time when either the number of states d or the number of slots m is fixed. Moreover, in the same setting, we provide an FPTAS for the case in which bidders are single minded, but d and m can be arbitrary. Then, we switch to the random valuations setting, in which these are randomly drawn according to some probability distribution. In this case, we show that the problem admits an FPTAS, a PTAS, and a QPTAS, when, respectively, d is fixed, m is fixed, and bidders' valuations are bounded away from zero.

In this work we performed a spectral energy distribution (SED) analysis in the optical/infrared band of the host galaxy of a proto-brightest cluster galaxy (BCG, NVSS J103023+052426) in a proto-cluster at z = 1.7. We found that it features a vigorous star formation rate (SFR) of ${\sim}$570 $\mathrm{M_{\odot}}$/yr and a stellar mass of $M_{\ast} \sim 3.7 \times 10^{11}$ $\mathrm{M_{\odot}}$; the high corresponding specific SFR = $1.5 \pm 0.5$ $\mathrm{Gyr^{-1}}$ classifies this object as a starburst galaxy that will deplete its molecular gas reservoir in $\sim$ $3.5 \times 10^8$ yr. Thus, this system represents a rare example of a proto-BCG caught during the short phase of its major stellar mass assembly. Moreover, we investigated the nature of the host galaxy emission at 3.3 mm. We found that it originates from the cold dust in the interstellar medium, even though a minor non-thermal AGN contribution cannot be completely ruled out. Finally, we studied the polarized emission of the lobes at 1.4 GHz. We unveiled a patchy structure where the polarization fraction increases in the regions in which the total intensity shows a bending morphology; in addition, the magnetic field orientation follows the direction of the bendings. We interpret these features as possible indications of an interaction with the intracluster medium. This strengthens the hypothesis of positive AGN feedback, as inferred in previous studies of this object on the basis of X-ray/mm/radio analysis. In this scenario, the proto-BCG heats the surrounding medium and possibly enhances the SFR in nearby galaxies., Comment: 13 pages, 3 figures, 1 table. Accepted for publication in Galaxies

In recent years Smart Contracts and DApps are becoming increasingly important and widespread thanks to the properties of blockchain technology. In most cases DApps are business critical, and very strict security requirements should be assured. Developing safe and reliable Smart Contracts, however, is not a trivial task. Several researchers have studied the security issues, however none of these provide a simple and intuitive tool to overcome these problems. In this paper we collected a list of security patterns for DApps. Moreover, based on these patterns, we provide the reader with security assessment checklists that can be easily used for the development of SCs. We cover the phases of design, coding, and testing and deployment of the software lifecycle. In this way, we allow developers to easily verify if they applied all the relevant security patterns to their smart contracts. We focus all the analysis on the most popular Ethereum blockchain, and on the Solidity language., Comment: 13 pages, 5 tables. To be submitted to a Journal. arXiv admin note: substantial text overlap with arXiv:1912.09074

The Blockchain and the programs running on it, called Smart Contracts, are more and more applied in all fields requiring trust and strong certifications. In this work we compare public and permissioned blockchains for industrial applications. We propose a complete, original solution based on Ethereum to implement a decentralized application. This solution is characterized by a set of validator nodes running the blockchain using Proof-of-Authority consensus, and including an Explorer enabling users to check blockchain state, and the source code of the Smart Contracts running on it. From time to time, the hash digest of the last mined block is written into a public blockchain to guarantee immutability. The right to send transactions is granted by validator nodes to users by endowing them with the local Ethers mined. Overall, the proposed approach has the same transparency and immutability of a public blockchain, without its drawbacks., Comment: 6 pages, 1 figure

In this paper, we introduce the notion of a complete hypertetrahedral arrangement $\mathcal{A}$ in $\mathbb{P}^{n}$. We address two basic problems. First, we describe the local freeness of $\mathcal{A}$ in terms of smaller complete hypertetrahedral arrangements and graph theory properties, specializing the Musta\c{t}\u{a}-Schenck criterion. As an application, we obtain that general complete hypertetrahedral arrangements are not locally free. In the second part of this paper, we bound the initial degree of the first syzygy module of the Jacobian ideal of $\mathcal{A}$., Comment: 26 pages. To appear in Mathematische Zeitschrift. Comments are welcome

We publicly release the spectroscopic and photometric redshift catalog of the sources detected with Chandra in the field of the $z$=6.3 quasar SDSS J1030+0525. This is currently the fifth deepest X-ray field, and reaches a 0.5-2 keV flux limit $f_{\rm 0.5-2}$=6$\times$10$^{-17}$ erg s$^{-1}$ cm$^{-2}$. By using two independent methods, we measure a photometric redshift for 243 objects, while 123 (51%) sources also have a spectroscopic redshift, 110 of which coming from an INAF-Large Binocular Telescope (LBT) Strategic Program. We use the spectroscopic redshifts to determine the quality of the photometric ones, and find it in agreement with that of other X-ray surveys which used a similar number of photometric data-points. In particular, we measure a sample normalized median absolute deviation $\sigma_{NMAD}$=1.48||$z_{phot}$-$z_{spec}$||/(1+$z_{spec}$)=0.065. We use these new spectroscopic and photometric redshifts to study the properties of the Chandra J1030 field. We observe several peaks in our spectroscopic redshift distribution between $z$=0.15 and $z$=1.5, and find that the sources in each peak are often distributed across the whole Chandra field of view. This evidence confirms that X-ray selected AGN can efficiently track large-scale structures over physical scales of several Mpc. Finally, we computed the Chandra J1030 $z>$3 number counts: while the spectroscopic completeness at high-redshift of our sample is limited, our results point towards a potential source excess at $z\geq$4, which we plan to either confirm or reject in the near future with dedicated spectroscopic campaigns., Comment: 21 pages, 15 figures. Accepted for publication in Astronomy and Astrophysics

We present the analysis of simultaneous NuSTAR and XMM-Newton data of 8 Compton-thick (CT-) active galactic nuclei (AGN) candidates selected in the Swift-Burst Alert Telescope (BAT) 100 month survey. This work is part of an ongoing effort to find and characterize all CT-AGN in the local ($z\leq$0.05) Universe. We used two physically motivated models, MYTorus and borus02, to characterize the sources in the sample, finding 5 of them to be confirmed CT-AGN. These results represent an increase of $\sim19$% over the previous NuSTAR-confirmed, BAT-selected CT-AGN at $z\leq0.05$, bringing the total number to 32. This corresponds to an observed fraction of $\sim 8$\% of all AGN within this volume-limited sample, although it increases to $20\pm5$% when limiting the sample to $z\leq0.01$. Out of a sample of 48 CT-AGN candidates, selected using BAT and soft (0.3$-$10 keV) X-ray data, only 24 are confirmed as CT-AGN with the addition of the NuSTAR data. This highlights the importance of NuSTAR when classifying local obscured AGN. We also note that most of the sources in our full sample of 48 Seyfert 2 galaxies with NuSTAR data have significantly different line-of-sight and average torus column densities, favouring a patchy torus scenario., Comment: 31 pages, 13 figures, accepted for publication in ApJ

We present the joint Chandra, XMM-Newton and NuSTAR analysis of two nearby Seyfert galaxies, NGC 3081 and ESO 565-G019. These are the only two having Chandra data in a larger sample of ten low redshift ($z \le 0.05$), candidates Compton-thick Active Galactic Nuclei (AGN) selected in the 15-150 keV band with Swift-BAT that were still lacking NuSTAR data. Our spectral analysis, performed using physically-motivated models, provides an estimate of both the line-of-sight (l.o.s.) and average (N$_{H,S}$) column densities of the two torii. NGC 3081 has a Compton-thin l.o.s. column density N$_{H,z}$=[0.58-0.62] $\times 10^{24}$cm$^{-2}$, but the N$_{H,S}$, beyond the Compton-thick threshold (N$_{H,S}$=[1.41-1.78] $\times 10^{24}$cm$^{-2}$), suggests a "patchy" scenario for the distribution of the circumnuclear matter. ESO 565-G019 has both Compton-thick l.o.s. and N$_{H,S}$ column densities (N$_{H,z}>$2.31 $\times 10^{24}$cm$^{-2}$ and N$_{H,S} >$2.57 $\times 10^{24}$cm$^{-2}$, respectively). The use of physically-motivated models, coupled with the broad energy range covered by the data (0.6-70 keV and 0.6-40 keV, for NGC 3081 and ESO 565-G019, respectively) allows us to constrain the covering factor of the obscuring material, which is C$_{TOR}$=[0.63-0.82] for NGC 3081, and C$_{TOR}$=[0.39-0.65] for ESO 565-G019., Comment: 15 pages, 22 figures, Accepted for publication on ApJ

We studied a sample of 274 radio and X-ray selected quasars (XQSOs) detected in the COSMOS and XXL-S radio surveys at 3 GHz and 2.1 GHz, respectively. This sample was identified by adopting a conservative threshold in X-ray luminosity, Lx [2-10\ keV] >= 10^44 erg/s, selecting only the most powerful quasars. Using available multiwavelength data, we examined various criteria for the selection of radio-loud (RL) and radio-quiet (RQ) XQSOs, finding that the number of RL/RQ XQSOs changes significantly depending on the chosen criterion. This discrepancy arises due to the different criteria tracing different physical processes and due to our sample being selected from flux-limited radio and X-ray surveys. Another approach to study the origin of radio emission in XQSOs is via their radio luminosity function (RLF). We constructed the XQSO 1.4 GHz radio luminosity functions (RLFs) in six redshift bins at 0.5 <= z <= 3.7. The lower-1.4 GHz luminosity end shows a higher normalization than expected only from AGN contribution in all studied redshift bins. The found "bump" is mostly dominated by emission due to star-forming (SF) processes within the XQSO host galaxies. As expected, AGN-related radio emission dominates at the higher-luminosity end of RLF. The evolution of XQSO RLF was studied via combination of analytic forms from the literature to constrain the lower-luminosity "bump" and the higher-luminosity AGN part of the RLF. We defined two 1.4 GHz luminosity thresholds, L_th,SF and L_th,AGN, below and above which more than 80% of sources contributing to the RLF are dominated by SF and AGN-related activity, respectively. These thresholds evolve with redshift, most likely due to the strong evolution of SFRs of the XQSO host galaxies., Comment: 14 pages, 11 figures

Bayesian persuasion studies how an informed sender should partially disclose information to influence the behavior of a self-interested receiver. Classical models make the stringent assumption that the sender knows the receiver's utility. This can be relaxed by considering an online learning framework in which the sender repeatedly faces a receiver of an unknown, adversarially selected type. We study, for the first time, an online Bayesian persuasion setting with multiple receivers. We focus on the case with no externalities and binary actions, as customary in offline models. Our goal is to design no-regret algorithms for the sender with polynomial per-iteration running time. First, we prove a negative result: for any $0 < \alpha \leq 1$, there is no polynomial-time no-$\alpha$-regret algorithm when the sender's utility function is supermodular or anonymous. Then, we focus on the case of submodular sender's utility functions and we show that, in this case, it is possible to design a polynomial-time no-$(1 - \frac{1}{e})$-regret algorithm. To do so, we introduce a general online gradient descent scheme to handle online learning problems with a finite number of possible loss functions. This requires the existence of an approximate projection oracle. We show that, in our setting, there exists one such projection oracle which can be implemented in polynomial time.

We study principal-agent problems in which a principal commits to an outcome-dependent payment scheme (a.k.a. contract) so as to induce an agent to take a costly, unobservable action. We relax the assumption that the principal perfectly knows the agent by considering a Bayesian setting where the agent's type is unknown and randomly selected according to a given probability distribution, which is known to the principal. Each agent's type is characterized by her own action costs and action-outcome distributions. In the literature on non-Bayesian principal-agent problems, considerable attention has been devoted to linear contracts, which are simple, pure-commission payment schemes that still provide nice approximation guarantees with respect to principal-optimal (possibly non-linear) contracts. While in non-Bayesian settings an optimal contract can be computed efficiently, this is no longer the case for our Bayesian principal-agent problems. This further motivates our focus on linear contracts, which can be optimized efficiently given their single-parameter nature. Our goal is to analyze the properties of linear contracts in Bayesian settings, in terms of approximation guarantees with respect to optimal contracts and general tractable contracts (i.e., efficiently-computable ones). First, we study the approximation guarantees of linear contracts with respect to optimal ones, showing that the former suffer from a multiplicative loss linear in the number of agent's types. Nevertheless, we prove that linear contracts can still provide a constant multiplicative approximation $\rho$ of the optimal principal's expected utility, though at the expense of an exponentially-small additive loss $2^{-\Omega(\rho)}$. Then, we switch to tractable contracts, showing that, surprisingly, linear contracts perform well among them.

As a follow-up of the optical spectroscopic campaign aimed at achieving completeness in the Third Catalog of Hard Fermi-LAT Sources (3FHL), we present here the results of a sample of 28 blazars of uncertain type observed using the 4m telescope at Cerro Tololo Inter-American Observatory (CTIO) in Chile. Out of these 28 sources, we find that 25 are BL Lacertae objects (BL Lacs) and 3 are Flat Spectrum Radio Quasars (FSRQs). We measure redshifts or lower limits for 16 of these blazars, whereas it is observed that the 12 remaining blazars have featureless optical spectra. These results are part of a more extended campaign of optical spectroscopy follow-up of 3FHL blazars, where until now 51 blazars of uncertain type have been classified into BL Lac and FSRQ categories. Further, this campaign has resulted in redshift measurements and lower limits for 15 of these sources. Our results contribute towards attaining a complete sample of blazars above 10 GeV, which then will be crucial in extending our knowledge on blazar emission mechanisms and the extragalactic background light.

The existence of simple uncoupled no-regret learning dynamics that converge to correlated equilibria in normal-form games is a celebrated result in the theory of multi-agent systems. Specifically, it has been known for more than 20 years that when all players seek to minimize their internal regret in a repeated normal-form game, the empirical frequency of play converges to a normal-form correlated equilibrium. Extensive-form games generalize normal-form games by modeling both sequential and simultaneous moves, as well as imperfect information. Because of the sequential nature and presence of private information in the game, correlation in extensive-form games possesses significantly different properties than its counterpart in normal-form games, many of which are still open research directions. Extensive-form correlated equilibrium (EFCE) has been proposed as the natural extensive-form counterpart to the classical notion of correlated equilibrium in normal-form games. Compared to the latter, the constraints that define the set of EFCEs are significantly more complex, as the correlation device must keep into account the evolution of beliefs of each player as they make observations throughout the game. Due to that significant added complexity, the existence of uncoupled learning dynamics leading to an EFCE has remained a challenging open research question for a long time. In this article, we settle that question by giving the first uncoupled no-regret dynamics that converge to the set of EFCEs in n-player general-sum extensive-form games with perfect recall. We show that each iterate can be computed in time polynomial in the size of the game tree, and that, when all players play repeatedly according to our learning dynamics, the empirical frequency of play is proven to be a O(T^-0.5)-approximate EFCE with high probability after T game repetitions, and an EFCE almost surely in the limit., Comment: Extended version of our NeurIPS 2020 paper. Compared to the conference version, this preprint gives finer, in-high-probability regret bounds. We also better connected our work to the phi-regret minimization framework

Supply chain management, product provenance and quality certification are among the first and most popular applications of blockchain technology, due to the inherent trust and inalterability provided by the blockchain technology. However, the proposed supply chain management systems based on blockchain and smart contract technology tend to be specific to the particular production and production process. In this paper we present a general-purpose approach for the agri-food supply chain management, proposing a system that can be configured for most agri-food productions. The primary purpose is to provide a methodology to facilitate and make more efficient the development of such applications. It is based on general smart contracts and apps interacting with the same smart contracts, which are configured, starting from the description of the specific system to be managed, given using json files. A case study on olive oil production is described, to show how our approach works.