Evidence for accretion rate change during type I X-ray bursts

The standard approach for time-resolved X-ray spectral analysis of thermonuclear bursts involves subtraction of the pre-burst emission as background. This approach implicitly assumes that the persistent flux remains constant throughout the burst. We reanalyzed 332 photospheric radius expansion bursts observed from 40 sources by the Rossi X-ray Timing Explorer, introducing a multiplicative factor $f_a$ to the persistent emission contribution in our spectral fits. We found that for the majority of spectra the best-fit value of $f_a$ is significantly greater than 1, suggesting that the persistent emission typically increases during a burst. Elevated $f_a$ values were not found solely during the radius expansion interval of the burst, but were also measured in the cooling tail. The modified model results in a lower average value of the $\chi^2$ fit statistic, indicating superior spectral fits, but not yet to the level of formal statistical consistency for all the spectra. We interpret the elevated $f_a$ values as an increase of the mass accretion rate onto the neutron star during the burst, likely arising from the effects of Poynting-Robertson drag on the disk material. We measured an inverse correlation of $f_a$ with the persistent flux, consistent with theoretical models of the disc response. We suggest that this modified approach may provide more accurate burst spectral parameters, as well as offering a probe of the accretion disk structure.Comment: 15 pages, 12 figures, 4 table

Evidence for enhanced persistent emission during sub-Eddington thermonuclear bursts

The standard approach for time-resolved X-ray spectral analysis of thermonuclear bursts involves subtraction of the pre-burst emission as background. This approach implicitly assumes that the persistent flux remains constant throughout the burst. We reanalyzed 332 photospheric radius expansion bursts observed from 40 sources by the Rossi X-ray Timing Explorer, introducing a multiplicative factor $f_a$ to the persistent emission contribution in our spectral fits. We found that for the majority of spectra the best-fit value of $f_a$ is significantly greater than 1, suggesting that the persistent emission typically increases during a burst. Elevated $f_a$ values were not found solely during the radius expansion interval of the burst, but were also measured in the cooling tail. The modified model results in a lower average value of the $\chi^2$ fit statistic, indicating superior spectral fits, but not yet to the level of formal statistical consistency for all the spectra. We interpret the elevated $f_a$ values as an increase of the mass accretion rate onto the neutron star during the burst, likely arising from the effects of Poynting-Robertson drag on the disk material. We measured an inverse correlation of $f_a$ with the persistent flux, consistent with theoretical models of the disc response. We suggest that this modified approach may provide more accurate burst spectral parameters, as well as offering a probe of the accretion disk structure.Comment: 15 pages, 9 figure

Hierarchical Bayesian Inference in Psychosis

Schizophrenia is a severe mental illness that affects millions of people worldwide and can have a drastic impact on a patient’s life. The illness is characterised by symptoms such as hallucinations and delusions. In recent years, a powerful theoretical framework has been developed to understand better how such symptoms emerge, the predictive coding account of psychosis. In this thesis, I cast different symptoms of psychosis as instances of hierarchical Bayesian inference in a series of studies. The first study examined the question of how persecutory delusions emerge in early psychosis. We derived hypotheses based on previous literature and simulations and tested them empirically in a sample of 18 first-episode psychosis patients, 19 individuals at clinical high risk for psychosis (CHR) and 19 matched healthy controls (HC). Our results suggest that emerging psychosis may be accompanied by an altered perception of environmental volatility. In a second study, this modelling approach was applied to delusions more broadly in a large dataset including 261 patients with psychotic disorders and 56 HC to examine the relationship between delusions and reasoning biases that were previously reported in psychosis. The results of this study suggest that beliefs of patients with psychotic disorders were characterised by increased belief instability, which explained increased belief updating in light of disconfirmatory evidence. We also assessed the clinical utility of this approach by testing its ability to predict treatment response to a psychotherapeutic intervention and found that the parameters of the computational model were able to predict treatment outcome in individual patients. Lastly, in a final study, we modelled brain activity during an implicit sensory learning task in a third independent sample of 38 CHR, 18 early-illness schizophrenia patients, and 44 HC to assess the biological plausibility of this approach. Our results suggest that hierarchical precision-weighted prediction errors derived from the model modulate electroencephalography (EEG) amplitudes. Moreover, we found not only differences in the expression of precision-weighted prediction errors between schizophrenia patients and HC, but also between CHR, who later converted to a psychotic disorder, and non-converters. Jointly, this work demonstrates that this computational approach may not only be conceptually useful to understand the computational mechanisms underlying psychosis, but also clinically relevant and biologically plausible

Bulk-driven non-equilibrium phase transitions in a mesoscopic ring

We study a periodic one-dimensional exclusion process composed of a driven and a diffusive part. In a mesoscopic limit where both dynamics compete we identify bulk-driven phase transitions. We employ mean-field theory complemented by Monte-Carlo simulations to characterize the emerging non-equilibrium steady states. Monte-Carlo simulations reveal interesting correlation effects that we explain phenomenologically.Comment: 4 pages, 3 figure

Lattice Models of Quantum Gravity

Standard Regge Calculus provides an interesting method to explore quantum gravity in a non-perturbative fashion but turns out to be a CPU-time demanding enterprise. One therefore seeks for suitable approximations which retain most of its universal features. The $Z_2$-Regge model could be such a desired simplification. Here the quadratic edge lengths $q$ of the simplicial complexes are restricted to only two possible values $q=1+\epsilon\sigma$, with $\sigma=\pm 1$, in close analogy to the ancestor of all lattice theories, the Ising model. To test whether this simpler model still contains the essential qualities of the standard Regge Calculus, we study both models in two dimensions and determine several observables on the same lattice size. In order to compare expectation values, e.g. of the average curvature or the Liouville field susceptibility, we employ in both models the same functional integration measure. The phase structure is under current investigation using mean field theory and numerical simulation.Comment: 4 pages, 1 figure

The Clustering Of Galaxies Around Radio-Loud AGNs

We examine the hypothesis that mergers and close encounters between galaxies can fuel AGNs by increasing the rate at which gas accretes towards the central black hole. We compare the clustering of galaxies around radio-loud AGNs with the clustering around a population of radio-quiet galaxies with similar masses, colors and luminosities. Our catalog contains 2178 elliptical radio galaxies with flux densities greater than 2.8 mJy at 1.4 GHz from the 6dFGS survey. We find that radio AGNs with more than 200 times the median radio power have, on average, more close (r<160 kpc) companions than their radio-quiet counterparts, suggestive that mergers play a role in forming the most powerful radio galaxies. For ellipticals of fixed stellar mass, the radio power is not a function of large-scale environment nor halo mass, consistent with the radio powers of ellipticals varying by orders of magnitude over billions of years.Comment: 12 pages, 6 figure

Simulation of low-speed buoyant flows with a stabilized compressible/incompressible formulation: the Full Navier–Stokes approach versus the Boussinesq model

This paper compares two strategies to compute buoyancy-driven flows using stabilized methods. Both formulations are based on a unified approach for solving compressible and incompressible flows, which solves the continuity, momentum, and total energy equations in a coupled entropy-consistent way. The first approach introduces the variable density thermodynamics of the liquid or gas without any artificial buoyancy terms, i.e., without applying any approximate models into the Navier–Stokes equations. Furthermore, this formulation holds for flows driven by high temperature differences. Further advantages of this formulation are seen in the fact that it conserves the total energy and it lacks the incompressibility inconsistencies due to volume changes induced by temperature variations. The second strategy uses the Boussinesq approximation to account for temperature-driven forces. This method models the thermal terms in the momentum equation through a temperature-dependent nonlinear source term. Computer examples show that the thermodynamic approach, which does not introduce any artificial terms into the Navier–Stokes equations, is conceptually simpler and, with the incompressible stabilization matrix, attains similar residual convergence with iteration count to methods based on the Boussinesq approximation. For the Boussinesq model, the SUPG and SGS methods are compared, displaying very similar computational behavior. Finally, the VMS a posteriori error estimator is applied to adapt the mesh, helping to achieve better accuracy for the same number of degrees of freedom