The stellar mass function of galaxies to z ~ 5 in the Fors Deep and GOODS-S fields

We present a measurement of the evolution of the stellar mass function (MF) of galaxies and the evolution of the total stellar mass density at 0<z<5. We use deep multicolor data in the Fors Deep Field (FDF; I-selected reaching I_AB=26.8) and the GOODS-S/CDFS region (K-selected reaching K_AB=25.4) to estimate stellar masses based on fits to composite stellar population models for 5557 and 3367 sources, respectively. The MF of objects from the GOODS-S sample is very similar to that of the FDF. Near-IR selected surveys hence detect the more massive objects of the same principal population as do I-selected surveys. We find that the most massive galaxies harbor the oldest stellar populations at all redshifts. At low z, our MF follows the local MF very well, extending the local MF down to 10^8 Msun. The faint end slope is consistent with the local value of alpha~1.1 at least up to z~1.5. Our MF also agrees very well with the MUNICS and K20 results at z<2. The MF seems to evolve in a regular way at least up to z~2 with the normalization decreasing by 50% to z=1 and by 70% to z=2. Objects having M>10^10 Msun which are the likely progenitors of todays L* galaxies are found in much smaller numbers above z=2. However, we note that massive galaxies with M>10^11 Msun are present even to the largest redshift we probe. Beyond z=2 the evolution of the mass function becomes more rapid. We find that the total stellar mass density at z=1 is 50% of the local value. At z=2, 25% of the local mass density is assembled, and at z=3 and z=5 we find that at least 15% and 5% of the mass in stars is in place, respectively. The number density of galaxies with M>10^11 Msun evolves very similarly to the evolution at lower masses. It decreases by 0.4 dex to z=1, by 0.6 dex to z=2, and by 1 dex to z=4.Comment: Accepted for publication in ApJ

Exploring the interaction between handedness and body parts ownership by means of the Implicit Association Test

The experience of owning a body is built upon the integration of exteroceptive, interoceptive, and proprioceptive signals. Recently, it has been suggested that motor signals could be particularly important in producing the feeling of body part ownership. One thus may hypothesize that the strength of this feeling may not be spatially uniform; rather, it could vary as a function of the degree by which different body parts are involved in motor behavior. Given that our dominant hand plays a leading role in our motor behavior, we hypothesized that it could be more strongly associated with one’s self compared to its non-dominant counterpart. To explore whether this possible asymmetry manifests as a stronger implicit association of the right hand (vs left hand) with the self, we administered the Implicit Association Test to a group of 70 healthy individuals. To control whether this asymmetric association is human-body specific, we further tested whether a similar asymmetry characterizes the association between a right (vs left) animal body part with the concept of self, in an independent sample of subjects (N = 70, 140 subjects total). Our results revealed a linear relationship between the magnitude of the implicit association between the right hand with the self and the subject’s handedness. In detail, the strength of this association increased as a function of hand preference. Critically, the handedness score did not predict the association of the right-animal body part with the self. These findings suggest that, in healthy individuals, the dominant and non-dominant hands are differently perceived at an implicit level as belonging to the self. We argue that such asymmetry may stem from the different roles that the two hands play in our adaptive motor behavior

Hybrid Superconducting Neutron Detectors

A new neutron detection concept is presented that is based on superconductive niobium (Nb) strips coated by a boron (B) layer. The working principle of the detector relies on the nuclear reaction 10B+n $\rightarrow$ $\alpha$+ 7Li , with $\alpha$ and Li ions generating a hot spot on the current-biased Nb strip which in turn induces a superconducting-normal state transition. The latter is recognized as a voltage signal which is the evidence of the incident neutron. The above described detection principle has been experimentally assessed and verified by irradiating the samples with a pulsed neutron beam at the ISIS spallation neutron source (UK). It is found that the boron coated superconducting strips, kept at a temperature T = 8 K and current-biased below the critical current Ic, are driven into the normal state upon thermal neutron irradiation. As a result of the transition, voltage pulses in excess of 40 mV are measured while the bias current can be properly modulated to bring the strip back to the superconducting state, thus resetting the detector. Measurements on the counting rate of the device are presented and the future perspectives leading to neutron detectors with unprecedented spatial resolutions and efficiency are highlighted.Comment: 8 pages 6 figure

Singularity Avoidance for Cart-Mounted Hand-Guided Collaborative Robots: A Variational Approach

Most collaborative robots (cobots) can be taught by hand guiding: essentially, by manually jogging the robot, an operator teaches some configurations to be employed as via points. Based on those via points, Cartesian end-effector trajectories such as straight lines, circular arcs or splines are then constructed. Such methods can, in principle, be employed for cart-mounted cobots (i.e., when the jogging involves one or two linear axes, besides the cobot axes). However, in some applications, the sole imposition of via points in Cartesian space is not sufficient. On the contrary, albeit the overall system is redundant, (i) the via points must be reached at the taught joint configurations, and (ii) the undesirable singularity (and near-singularity) conditions must be avoided. The naive approach, consisting of setting the cart trajectory beforehand (for instance, by imposing a linear-in-time motion law that crosses the taught cart configurations), satisfies the first need, but does not guarantee the satisfaction of the second. Here, we propose an approach consisting of (i) a novel strategy for decoupling the planning of the cart trajectory and that of the robot joints, and (ii) a novel variational technique for computing the former in a singularity-aware fashion, ensuring the avoidance of a class of workspace singularity and near-singularity configurations

A tidal disruption flare in a massive galaxy? Implications for the fuelling mechanisms of nuclear black holes

We argue that the `changing look' AGN recently reported by LaMassa et al. could be a luminous flare produced by the tidal disruption of a super-solar mass star passing just a few gravitational radii outside the event horizon of a $\sim 10^8 M_{\odot}$ nuclear black hole. This flare occurred in a massive, star forming galaxy at redshift $z=0.312$, robustly characterized thanks to repeated late-time photometric and spectroscopic observations. By taking difference-photometry of the well sampled multi-year SDSS Stripe-82 light-curve, we are able to probe the evolution of the nuclear spectrum over the course of the outburst. The tidal disruption event (TDE) interpretation is consistent with the very rapid rise and the decay time of the flare, which displays an evolution consistent with the well-known $t^{-5/3}$ behaviour (with a clear superimposed re-brightening flare). Our analysis places constraints on the physical properties of the TDE, such as the putative disrupted star's mass and orbital parameters, as well as the size and temperature of the emitting material. The properties of the broad and narrow emission lines observed in two epochs of SDSS spectra provide further constraints on the circum-nuclear structure, and could be indicative that the system hosted a moderate-luminosity AGN as recently as a few $10^4$ years ago, and is likely undergoing residual accretion as late as ten years after peak, as seen from the broad H$\alpha$ emission line. We discuss the complex interplay between tidal disruption events and gas accretion episodes in galactic nuclei, highlighting the implications for future TDE searches and for estimates of their intrinsic rates.Comment: 20 pages, 9 figures, 3 tables. Accepted for publication in MNRA

Closed-loop Control from Data-Driven Open-Loop Optimal Control Trajectories

We show how the recent works on data driven open-loop minimum-energy control for linear systems can be exploited to obtain closed-loop piecewise-affine control laws, by employing a state-space partitioning technique which is at the basis of the static relatively optimal control. In addition, we propose a way for employing portions of the experimental input and state trajectories to recover information about the natural movement of the state and dealing with non-zero initial conditions. The same idea can be used for formulating several open-loop control problems entirely based on data, possibly including input and state constraints

Integrating Superconductive and Optical Circuits

We have integrated on oxidized silicon wafers superconductive films and Josephson junctions along with sol-gel optical channel waveguides. The fabrication process is carried out in two steps that result to be solid and non-invasive. It is demonstrated that 660 nm light, coupled from an optical fibre into the channel sol-gel waveguide, can be directed toward superconducting tunnel junctions whose current-voltage characteristics are affected by the presence of the radiation. The dependence of the change in the superconducting energy gap under optical pumping is discussed in terms of a non-equilibrium superconductivity model.Comment: Document composed of 7 pages of text and 3 figure

Improving the reliability of photometric redshift with machine learning

In order to answer the open questions of modern cosmology and galaxy evolution theory, robust algorithms for calculating photometric redshifts (photo-z) for very large samples of galaxies are needed. Correct estimation of the various photo-z algorithms' performance requires attention to both the performance metrics and the data used for the estimation. In this work, we use the supervised machine learning algorithm MLPQNA (Multi-Layer Perceptron with Quasi-Newton Algorithm) to calculate photometric redshifts for the galaxies in the COSMOS2015 catalogue and the unsupervised Self-Organizing Maps (SOM) to determine the reliability of the resulting estimates. We find that for zspec < 1.2, MLPQNA photo-z predictions are on the same level of quality as spectral energy distribution fitting photo-z. We show that the SOM successfully detects unreliable zspec that cause biases in the estimation of the photo-z algorithms' performance. Additionally, we use SOM to select the objects with reliable photo-z predictions. Our cleaning procedures allow us to extract the subset of objects for which the quality of the final photo-z catalogues is improved by a factor of 2, compared to the overall statistics