The genus of the configuration spaces for Artin groups of affine type

Let $(W,S)$ be a Coxeter system, $S$ finite, and let $G_{W}$ be the associated Artin group. One has configuration spaces $Y,\ Y_{W},$ where $G_{W}=\pi_1(Y_{W}),$ and a natural $W$-covering $f_{W}:\ Y\to Y_{W}.$ The Schwarz genus $g(f_{W})$ is a natural topological invariant to consider. In this paper we generalize this result by computing the Schwarz genus for a class of Artin groups, which includes the affine-type Artin groups. Let $K=K(W,S)$ be the simplicial scheme of all subsets $J\subset S$ such that the parabolic group $W_J$ is finite. We introduce the class of groups for which $dim(K)$ equals the homological dimension of $K,$ and we show that $g(f_{W})$ is always the maximum possible for such class of groups. For affine Artin groups, such maximum reduces to the rank of the group. In general, it is given by $dim(X_{W})+1,$ where $X_{ W}\subset Y_{ W}$ is a well-known $CW$-complex which has the same homotopy type as $Y_{ W}.$Comment: To appear in Atti Accad. Naz. Lincei Rend. Lincei Mat. App

Some issues concerning Large-Eddy Simulation of inertial particle dispersion in turbulent bounded flows

The problem of an accurate Eulerian-Lagrangian modeling of inertial particle dispersion in Large Eddy Simulation (LES) of turbulent wall-bounded flows is addressed. We run Direct Numerical Simulation (DNS) for turbulent channel flow at shear Reynolds numbers equal to 150 and 300 and corresponding a-priori and a-posteriori LES on differently coarse grids. We then tracked swarms of different inertia particles and we examined the influence of filtering and of Sub-Grid Scale (SGS) modeling for the fluid phase on particle velocity and concentration statistics. We also focused on how particle preferential segregation is predicted by LES. Results show that even ``well-resolved'' LES is unable to reproduce the physics as demonstrated by DNS, both for particle accumulation at the wall and for particle preferential segregation. Inaccurate prediction is observed for the entire range of particles considered in this study, even when the particle response time is much larger than the flow timescales not resolved in LES. Both a-priori and a-posteriori tests indicate that recovering the level of fluid and particle velocity fluctuations is not enough to have accurate prediction of near-wall accumulation and local segregation. This may suggest that reintroducing the correct amount of higher-order moments of the velocity fluctuations is also a key point for SGS closure models for the particle equation. Another important issue is the presence of possible flow Reynolds number effects on particle dispersion. Our results show that, in small Reynolds number turbulence and in the case of heavy particles, the shear fluid velocity is a suitable scaling parameter to quantify these effects

Supergiant Fast X-ray Transients uncovered by the EXTraS project: flares reveal the development of magnetospheric instability in accreting neutron stars

The low luminosity, X-ray flaring activity, of the sub-class of high mass X-ray binaries called Supergiant Fast X-ray Transients, has been investigated using XMM-Newton public observations, taking advantage of the products made publicly available by the EXTraS project. One of the goals of EXTraS was to extract from the XMM-Newton public archive information on the aperiodic variability of all sources observed in the soft X-ray range with EPIC (0.2-12 keV). Adopting a Bayesian block decomposition of the X-ray light curves of a sample of SFXTs, we picked out 144 X-ray flares, covering a large range of soft X-ray luminosities (1e32-1e36 erg/s). We measured temporal quantities, like the rise time to and the decay time from the peak of the flares, their duration and the time interval between adjacent flares. We also estimated the peak luminosity, average accretion rate and energy release in the flares. The observed soft X-ray properties of low-luminosity flaring activity from SFXTs is in qualitative agreement with what is expected by the application of the Rayleigh-Taylor instability model in accreting plasma near the neutron star magnetosphere. In the case of rapidly rotating neutron stars, sporadic accretion from temporary discs cannot be excluded.Comment: Accepted for publication in MNRAS (accepted 2019 May 1; received 2019 April 30; in original form 2019 February 25). 22 pages, 16 figures, 3 tables

Large Binocular Telescope observations of PSR J2043+2740

We present the results of deep optical imaging of the radio/$\gamma$-ray pulsar PSR J2043+2740, obtained with the Large Binocular Telescope (LBT). With a characteristic age of 1.2 Myr, PSR J2043+2740 is one of the oldest (non recycled) pulsars detected in $\gamma$-rays, although with still a quite high rotational energy reservoir ($\dot{E}_{\rm rot} = 5.6 \times 10^{34}$ erg s$^{-1}$). The presumably close distance (a few hundred pc), suggested by the hydrogen column density ($N_{\rm H} \lesssim 3.6 \times 10^{20}$ cm$^{-2}$), would make it a viable target for deep optical observations, never attempted until now. We observed the pulsar with the Large Binocular Camera of the LBT. The only object (V=25.44$\pm$0.05) detected within ~3" from the pulsar radio coordinates is unrelated to it. PSR J2043+2740 is, thus, undetected down to V~26.6 (3-$\sigma$), the deepest limit on its optical emission. We discuss the implications of this result on the pulsar emission properties.Comment: 4 pages, 3 figures, accepted for publication on MNRA

Neural Structures to Predict River Stages in Heavily Urbanized Catchments

Accurate flow forecasting may support responsible institutions in managing river systems and limiting damages due to high water levels. Machine-learning models are known to describe many nonlinear hydrological phenomena, but up to now, they have mainly provided a single future value with a fixed information structure. This study trains and tests multi-step deep neural networks with different inputs to forecast the water stage of two sub-alpine urbanized catchments. They prove effective for one hour ahead flood stage values and occurrences. Convolutional neural networks (CNNs) perform better when only past information on the water stage is used. Long short-term memory nets (LSTMs) are more suited to exploit the data coming from the rain gauges. Predicting a set of water stages over the following hour rather than just a single future value may help concerned agencies take the most urgent actions. The paper also shows that the architecture developed for one catchment can be adapted to similar ones maintaining high accuracy

A candidate optical counterpart to the middle-aged gamma-ray pulsar PSR J1741-2054

We carried out deep optical observations of the middle-aged $\gamma$-ray pulsar PSR J1741-2054 with the Very Large Telescope (VLT). We identified two objects, of magnitudes $m_v=23.10\pm0.05$ and $m_v=25.32\pm0.08$, at positions consistent with the very accurate Chandra coordinates of the pulsar, the faintest of which is more likely to be its counterpart. From the VLT images we also detected the known bow-shock nebula around PSR J1741-2054. The nebula is displaced by \sim 0\farcs9 (at the $3\sigma$ confidence level) with respect to its position measured in archival data, showing that the shock propagates in the interstellar medium consistently with the pulsar proper motion. Finally, we could not find evidence of large-scale extended optical emission associated with the pulsar wind nebula detected by Chandra, down to a surface brightness limit of $\sim 28.1$ magnitudes arcsec$^{-2}$. Future observations are needed to confirm the optical identification of PSR J1741-2054 and characterise the spectrum of its counterpart.Comment: 8 pages, 3 figures, Astrophysical Journal, in pres

Classification and Ranking of Fermi LAT Gamma-ray Sources from the 3FGL Catalog using Machine Learning Techniques

We apply a number of statistical and machine learning techniques to classify and rank gamma-ray sources from the Third Fermi Large Area Telescope (LAT) Source Catalog (3FGL), according to their likelihood of falling into the two major classes of gamma-ray emitters: pulsars (PSR) or Active Galactic Nuclei (AGN). Using 1904 3FGL sources that have been identified/associated with AGN (1738) and PSR (166), we train (using 70% of our sample) and test (using 30%) our algorithms and find that the best overall accuracy (>96%) is obtained with the Random Forest (RF) technique, while using a logistic regression (LR) algorithm results in only marginally lower accuracy. We apply the same techniques on a sub-sample of 142 known gamma-ray pulsars to classify them into two major subcategories: young (YNG) and millisecond pulsars (MSP). Once more, the RF algorithm has the best overall accuracy (~90%), while a boosted LR analysis comes a close second. We apply our two best models (RF and LR) to the entire 3FGL catalog, providing predictions on the likely nature of {\it unassociated} sources, including the likely type of pulsar (YNG or MSP). We also use our predictions to shed light on the possible nature of some gamma-ray sources with known associations (e.g. binaries, SNR/PWN). Finally, we provide a list of plausible X-ray counterparts for some pulsar candidates, obtained using Swift, Chandra, and XMM. The results of our study will be of interest for both in-depth follow-up searches (e.g. pulsar) at various wavelengths, as well as for broader population studies.Comment: Accepted by Ap

Investigation of the steady engulfment regime in a three-dimensional T-mixer

The steady engulfment regime in a fully three-dimensional micro T-mixer is investigated. This regime is of significant interest for applications since it implies high mixing between the flow streams entering the device. Direct numerical simulations are first used to characterize this regime. In particular, the main vortical structures typical of the engulfment regime and their effects on mixing are investigated. Three-dimensional linear stability analysis is successively applied to the characterization of the instability leading to the engulfment regime. The critical Reynolds number and the global unstable mode are first computed for a configuration characterized by fully-developed inlet velocity conditions. The sensitivity of this instability to a generic modification of the base flow is then investigated, thanks to the computation of the mode adjoint to the direct unstable one. Finally, this kind of analysis is specialized to investigate the effect of a perturbation of the velocity distribution at the inlet of the T-mixer. Sensitivity analysis shows that non-fully developed inlet velocity conditions lead to an increase of the critical Reynolds number. More generally, the sensitivity maps can be used for the design of control strategies aimed at promoting or inhibiting the engulfment. An example is provided for a control based on blowing/suction through the mixer walls