Mutual information in classical spin models

The total many-body correlations present in finite temperature classical spin systems are studied using the concept of mutual information. As opposed to zero-temperature quantum phase transitions, the total correlations are not maximal at the phase transition, but reach a maximum in the high temperature paramagnetic phase. The Shannon and Renyi mutual information in both Ising and Potts models in 2 dimensions are calculated numerically by combining matrix product states algorithms and Monte Carlo sampling techniques

Twelve and a Half Years of Observations of Centaurus A with RXTE

The Rossi X-ray Timing Explorer has observed the nearest radio galaxy, Centaurus A, in 13 intervals from 1966 August to 2009 February over the 3--200 keV band. Spectra accumulated over the 13 intervals were well described with an absorbed power law and iron line. Cut-off power laws and Compton reflection from cold matter did not provide a better description. For the 2009 January observation, we set a lower limit on the cut-off energy at over 2 MeV. The power spectral density function was generated from RXTE/ASM and PCA data, as well as an XMM-Newton long look, and clear evidence for a break at 18+10-7 days (68% conf.) was seen. Given Cen A's high black hole mass and very low value of Lx/LEdd, the break was a factor of 17+/-9 times higher than the break frequency predicted by the McHardy and co-workers' relation, which was empirically derived for a sample of objects, which are radio-quiet and accreting at relatively high values of Lbol/LEdd. We have interpreted our observations in the context of a clumpy molecular torus. The variability characteristics and the broadband spectral energy distribution, when compared to Seyferts, imply that the bright hard X-ray continuum emission may originate at the base of the jet, yet from behind the absorbing line of sight material, in contrast to what is commonly observed from blazars.Comment: 56 pages, 12 figures, 4 tables, revised manuscript submitted to The Astrophysical Journa

X-ray monitoring of the radio and gamma-ray loud Narrow-Line Seyfert 1 Galaxy PKS 2004-447

We present preliminary results of the X-ray analysis of XMM-Newton and Swift observations as part of a multi-wavelength monitoring campaign in 2012 of the radio-loud narrow line Seyfert 1 galaxy PKS 2004-447. The source was recently detected in gamma-rays by Fermi/LAT among only four other galaxies of that type. The 0.5-10 keV X-ray spectrum is well-described by a simple absorbed powerlaw (photon index ~ 1.6). The source brightness exhibits variability on timescales of months to years with indications for spectral variability, which follows a 'bluer-when-brighter' behaviour, similar to blazars.Comment: Proceedings for the 'Jet 2013' conference. Includes 3 pages, 3 figure

Evidence for different accretion regimes in GRO J1008-57

We present a comprehensive spectral analysis of the BeXRB GRO J1008-57 over a luminosity range of three orders of magnitude using NuSTAR, Suzaku and RXTE data. We find significant evolution of the spectral parameters with luminosity. In particular the photon index hardens with increasing luminosity at intermediate luminosities between $10^{36}$ $-$ $10^{37}$ erg s$^{-1}$. This evolution is stable and repeatedly observed over different outbursts. However, at the extreme ends of the observed luminosity range, we find that the correlation breaks down, with a significance level of at least $3.7\sigma$. We conclude that these changes indicate transitions to different accretion regimes, which are characterized by different deceleration processes, such as Coulomb or radiation breaking. We compare our observed luminosity levels of these transitions to theoretical predications and discuss the variation of those theoretical luminosity values with fundamental neutron star parameters. Finally, we present detailed spectroscopy of the unique "triple peaked" outburst in 2014/15 which does not fit in the general parameter evolution with luminosity. The pulse profile on the other hand is consistent with what is expected at this luminosity level, arguing against a change in accretion geometry. In summary, GRO J1008-57 is an ideal target to study different accretion regimes due to the well constrained evolution of its broad-band spectral continuum over several orders of magnitude in luminosity.Comment: 13 pages, 7 figures, 3 tables. Accepted for publication in A&

Multimodal brain age prediction fusing morphometric and imaging data and association with cardiovascular risk factors

IntroductionThe difference between the chronological and biological brain age, called the brain age gap (BAG), has been identified as a promising biomarker to detect deviation from normal brain aging and to indicate the presence of neurodegenerative diseases. Moreover, the BAG has been shown to encode biological information about general health, which can be measured through cardiovascular risk factors. Current approaches for biological brain age estimation, and therefore BAG estimation, either depend on hand-crafted, morphological measurements extracted from brain magnetic resonance imaging (MRI) or on direct analysis of brain MRI images. The former can be processed with traditional machine learning models while the latter is commonly processed with convolutional neural networks (CNNs). Using a multimodal setting, this study aims to compare both approaches in terms of biological brain age prediction accuracy and biological information captured in the BAG.MethodsT1-weighted MRI, containing brain tissue information, and magnetic resonance angiography (MRA), providing information about brain arteries, from 1,658 predominantly healthy adults were used. The volumes, surface areas, and cortical thickness of brain structures were extracted from the T1-weighted MRI data, while artery density and thickness within the major blood flow territories and thickness of the major arteries were extracted from MRA data. Independent multilayer perceptron and CNN models were trained to estimate the brain age from the hand-crafted features and image data, respectively. Next, both approaches were fused to assess the benefits of combining image data and hand-crafted features for brain age prediction.ResultsThe combined model achieved a mean absolute error of 4 years between the chronological and predicted biological brain age. Among the independent models, the lowest mean absolute error was observed for the CNN using T1-weighted MRI data (4.2 years). When evaluating the BAGs obtained using the different approaches and imaging modalities, diverging associations between cardiovascular risk factors were found. For example, BAGs obtained from the CNN models showed an association with systolic blood pressure, while BAGs obtained from hand-crafted measurements showed greater associations with obesity markers.DiscussionIn conclusion, the use of more diverse sources of data can improve brain age estimation modeling and capture more diverse biological deviations from normal aging