Simplified models for photohadronic interactions in cosmic accelerators

We discuss simplified models for photo-meson production in cosmic accelerators, such as Active Galactic Nuclei and Gamma-Ray Bursts. Our self-consistent models are directly based on the underlying physics used in the SOPHIA software, and can be easily adapted if new data are included. They allow for the efficient computation of neutrino and photon spectra (from pi^0 decays), as a major requirement of modern time-dependent simulations of the astrophysical sources and parameter studies. In addition, the secondaries (pions and muons) are explicitely generated, a necessity if cooling processes are to be included. For the neutrino production, we include the helicity dependence of the muon decays which in fact leads to larger corrections than the details of the interaction model. The separate computation of the pi^0, pi^+, and pi^- fluxes allows, for instance, for flavor ratio predictions of the neutrinos at the source, which are a requirement of many tests of neutrino properties using astrophysical sources. We confirm that for charged pion generation, the often used production by the Delta(1232)-resonance is typically not the dominant process in Active Galactic Nuclei and Gamma-Ray Bursts, and we show, for arbitrary input spectra, that the number of neutrinos are underestimated by at least a factor of two if they are obtained from the neutral to charged pion ratio. We compare our results for several levels of simplification using isotropic synchrotron and thermal spectra, and we demonstrate that they are sufficiently close to the SOPHIA software.Comment: Treatment of high energy interactions refined, additional black body benchmark added (v2), some references corrected (v3). A Mathematica notebook which illustrates the implementation of one model can be found at http://theorie.physik.uni-wuerzburg.de/~winter/Resources/AstroModel/Sim-B.html . 46 pages, 14 (color) figures, 7 tables. Final version, accepted for publication in Ap

Magnetic Phase Diagrams of Manganites-like Local-Moment Systems with Jahn-Teller distortions

We use an extended two-band Kondo lattice model (KLM) to investigate the occurrence of different (anti-)ferromagnetic phases or phase separation depending on several model parameters. With regard to CMR-materials like the manganites we have added a Jahn-Teller term, direct antiferromagnetic coupling and Coulomb interaction to the KLM. The electronic properties are self-consistently calculated in an interpolating self-energy approach with no restriction to classical spins and going beyond mean-field treatments. Further on we do not have to limit the Hund's coupling to low or infinite values. Zero-temperature phase diagrams are presented for large parameter intervals. There are strong influences of the type of Coulomb interaction (intraband, interband) and of the important parameters (Hund's coupling, direct antiferromagnetic exchange, Jahn-Teller distortion), especially at intermediate couplings.Comment: 11 pages, 9 figures. Accepted for publication in Phys. Rev.

Markov chain generative adversarial neural networks for solving Bayesian inverse problems in physics applications

In the context of solving inverse problems for physics applications within a Bayesian framework, we present a new approach, the Markov Chain Generative Adversarial Neural Network (MCGAN), to alleviate the computational costs associated with solving the Bayesian inference problem. GANs pose a very suitable framework to aid in the solution of Bayesian inference problems, as they are designed to generate samples from complicated high-dimensional distributions. By training a GAN to sample from a low-dimensional latent space and then embedding it in a Markov Chain Monte Carlo method, we can highly efficiently sample from the posterior, by replacing both the high-dimensional prior and the expensive forward map. This comes at the cost of a potentially expensive offline stage in which training data must be simulated or gathered and the GAN has to be trained. We prove that the proposed methodology converges to the true posterior in the Wasserstein-1 distance and that sampling from the latent space is equivalent to sampling in the high-dimensional space in a weak sense. The method is showcased in two test cases where we perform both state and parameter estimation simultaneously and it is compared with two conventional approaches, polynomial chaos expansion and ensemble Kalman filter, and a deep learning-based approach, deep Bayesian inversion. The method is shown to be more accurate than alternative approaches while also being computationally faster, in multiple test cases, including the important engineering setting of detecting leaks in pipelines

High energy neutrino early afterglows from gamma-ray bursts revisited

The high energy neutrino emission from gamma-ray bursts (GRBs) has been expected in various scenarios. In this paper, we study the neutrino emission from early afterglows of GRBs, especially under the reverse-forward shock model and late prompt emission model. In the former model, the early afterglow emission occurs due to dissipation made by an external shock with the circumburst medium (CBM). In the latter model, internal dissipation such as internal shocks produces the shallow decay emission in early afterglows. We also discuss implications of recent Swift observations for neutrino signals in detail. Future neutrino detectors such as IceCube may detect neutrino signals from early afterglows, especially under the late prompt emission model, while the detection would be difficult under the reverse-forward shock model. Contribution to the neutrino background from the early afterglow emission may be at most comparable to that from the prompt emission unless the outflow making the early afterglow emission loads more nonthermal protons, and it may be important in the very high energies. Neutrino-detections are inviting because they could provide us with not only information on baryon acceleration but also one of the clues to the model of early afterglows. Finally, we compare various predictions for the neutrino background from GRBs, which are testable by future neutrino-observations.Comment: 18 pages, 12 figures, accepted for publication in PR

A Probabilistic Digital Twin for Leak Localization in Water Distribution Networks Using Generative Deep Learning

Localizing leakages in large water distribution systems is an important and ever-present problem. Due to the complexity originating from water pipeline networks, too few sensors, and noisy measurements, this is a highly challenging problem to solve. In this work, we present a methodology based on generative deep learning and Bayesian inference for leak localization with uncertainty quantification. A generative model, utilizing deep neural networks, serves as a probabilistic surrogate model that replaces the full equations, while at the same time also incorporating the uncertainty inherent in such models. By embedding this surrogate model into a Bayesian inference scheme, leaks are located by combining sensor observations with a model output approximating the true posterior distribution for possible leak locations. We show that our methodology enables producing fast, accurate, and trustworthy results. It showed a convincing performance on three problems with increasing complexity. For a simple test case, the Hanoi network, the average topological distance (ATD) between the predicted and true leak location ranged from 0.3 to 3 with a varying number of sensors and level of measurement noise. For two more complex test cases, the ATD ranged from 0.75 to 4 and from 1.5 to 10, respectively. Furthermore, accuracies upwards of 83%, 72%, and 42% were achieved for the three test cases, respectively. The computation times ranged from 0.1 to 13 s, depending on the size of the neural network employed. This work serves as an example of a digital twin for a sophisticated application of advanced mathematical and deep learning techniques in the area of leak detection

High-Energy Neutrinos from Photomeson Processes in Blazars

An important radiation field for photomeson neutrino production in blazars is shown to be the radiation field external to the jet. Assuming that protons are accelerated with the same power as electrons and injected with a -2 number spectrum, we predict that km^2 neutrino telescopes will detect about 1-to-several neutrinos per year from flat spectrum radio quasars (FSRQs) such as 3C 279. The escaping high-energy neutron and photon beams transport inner jet energy far from the black-hole engine, and could power synchrotron X-ray jets and FR II hot spots and lobes.Comment: revised paper (minor revisions), accepted for publication in PR

Propagation of ultra-high energy protons in the nearby universe

We present a new calculation of the propagation of protons with energies above $10^{19}$ eV over distances of up to several hundred Mpc. The calculation is based on a Monte Carlo approach using the event generator SOPHIA for the simulation of hadronic nucleon-photon interactions and a realistic integration of the particle trajectories in a random extragalactic magnetic field. Accounting for the proton scattering in the magnetic field affects noticeably the nucleon energy as a function of the distance to their source and allows us to give realistic predictions on arrival energy, time delay, and arrival angle distributions and correlations as well as secondary particle production spectra.Comment: 12 pages, 9 figures, ReVTeX. Physical Review D, accepte

The new model of fitting the spectral energy distributions of Mkn 421 and Mkn 501

The spectral energy distribution (SED) of TeV blazars has a double-humped shape that is usually interpreted as Synchrotron Self Compton (SSC) model. The one zone SSC model is used broadly but cannot fit the high energy tail of SED very well. It need bulk Lorentz factor which is conflict with the observation. Furthermore one zone SSC model can not explain the entire spectrum. In the paper, we propose a new model that the high energy emission is produced by the accelerated protons in the blob with a small size and high magnetic field, the low energy radiation comes from the electrons in the expanded blob. Because the high and low energy photons are not produced at the same time, the requirement of large Doppler factor from pair production is relaxed. We present the fitting results of the SEDs for Mkn 501 during April 1997 and Mkn 421 during March 2001 respectively.Comment: 5 pages, 1 figures, 1table. accepted for publication in Sciences in China --