Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userThe rise and fall of top-down models as main UHECR sources
64
0
0.0
(
0
)
Added by
Michael Kachelrie{\\ss}
Publication date
2008
fields
Physics
and research's language is
English
Authors
M. Kachelriess
Ask ChatGPT about the research
No Arabic abstract
The motivation and the current status of top-down models as sources of ultrahigh energy cosmic rays (UHECR) are reviewed. Stimulated by the AGASA excess, they were proposed as the main source of UHECRs beyond the GZK cutoff. Meanwhile searches for their signatures have limited their contribution to the UHECR flux to be subdominant, while the theoretical motivation for these searches remained strong: Topological defects are a generic consequence of Grand Unified Theories and superheavy particles are a creditable dark matter candidate. While Fermi/GLAST results should help to improve soon bounds on topological defects from the diffuse gamma-ray background, the most promising detection method are UHE neutrino searches. Superheavy dark matter can be restricted or detected by its characteristic galactic anisotropy combined with searches for UHE photons.
rate research
Read More
Ultra-high energy cosmic rays (UHECRs) are particles, likely protons and/or nuclei, with energies up to $10^{20}$ eV that are observed through the giant air showers they produce in the atmosphere. These particles carry the information on the most extreme phenomena in the Universe. At these energies, even charged particles could be magnetically rigid enough to keep track of, or even point directly to, the original positions of their sources on the sky. The discovery of anisotropy of UHECRs would thus signify opening of an entirely new window onto the Universe. With the construction and operation of the new generation of cosmic ray experiments -- the Pierre Auger Observatory in the Southern hemisphere and the Telescope Array in the Northern one -- the study of these particles, the most energetic ever detected, has experienced a jump in statistics as well as in the data quality, allowing for a much better sensitivity in searching for their sources. In this review, we summarize the searches for anisotropies and the efforts to identify the sources of UHECRs which have been carried out using these new data.
HS Hydrae is a short period eclipsing binary (P_orb=1.57 day) that belongs to a rare group of systems observed to have rapidly changing inclinations. This evolution is due to a third star on an intermediate orbit, and results in significant differences in eclipse depths and timings year-to-year. Zasche & Paschke (2012) revealed that HS Hydraes eclipses were rapidly fading from view, predicting they would cease around 2022. Using 25 days of photometric data from Sector 009 of the Transiting Exoplanet Survey Satellite (TESS), we find that the primary eclipses for HS Hydrae were only 0.00173+/-0.00007 mag in depth in March 2019. This data from TESS likely represents the last eclipses detected from HS Hydrae. We also searched the Digitization of the Harvard Astronomical Plate Collection (DASCH) archive for historic data from the system. With a total baseline of over 125 years, this unique combination of data sets - from photographic plates to precision space-based photometry - allows us to trace the emergence and decay of eclipses from HS Hydrae, and further constrain its evolution. Recent TESS observations from Sector 035 confirm that eclipses have ceased for HS Hya, and we estimate they will begin again in 2195.
We carried out deep searches for CO line emission in the outer disk of M33, at R>7 kpc, and examined the dynamical conditions that can explain variations in the mass distribution of the molecular cloud throughout the disk of M33. We used the IRAM-30~m telescope to search for CO lines in the outer disk toward 12 faint mid-infrared (MIR) selected sources and in an area of the southern outer disk hosting MA1, a bright HII region. We detect narrow CO lines at the location of two MIR sources at galactocentric distances of about 8 kpc that are associated with low-mass young stellar clusters, and at four locations in the proximity of MA1. The paucity of CO lines at the location of weak MIR-selected sources probably arises because most of them are not star-forming sites in M33, but background sources. Although very uncertain, the total molecular mass of the detected clouds around MA1 is lower than expected given the stellar mass of the cluster, because dispersal of the molecular gas is taking place as the HII region expands. The mean mass of the giant molecular clouds (GMCs) in M33 decreases radially by a factor 2 from the center out to 4 kpc, then it stays constant until it drops at R>7 kpc. We suggest that GMCs become more massive toward the center because of the fast rotation of the disk, which drives mass growth by coalescence of smaller condensations as they cross the arms. The analysis of both HI and CO spectral data gives the consistent result that corotation of the two main arms in this galaxy is at a radius of 4.7+-0.3 kpc, and spiral shock waves become subsonic beyond 3.9 kpc. Perturbations are quenched beyond 6.5 kpc, where CO lines have been detected only around sporadic condensations associated with UV and MIR emission.
Modeling the distribution of high dimensional data by a latent tree graphical model is a common approach in multiple scientific domains. A common task is to infer the underlying tree structure given only observations of the terminal nodes. Many algorithms for tree recovery are computationally intensive, which limits their applicability to trees of moderate size. For large trees, a common approach, termed divide-and-conquer, is to recover the tree structure in two steps. First, recover the structure separately for multiple randomly selected subsets of the terminal nodes. Second, merge the resulting subtrees to form a full tree. Here, we develop Spectral Top-Down Recovery (STDR), a divide-and-conquer approach for inference of large latent tree models. Unlike previous methods, STDRs partitioning step is non-random. Instead, it is based on the Fiedler vector of a suitable Laplacian matrix related to the observed nodes. We prove that under certain conditions this partitioning is consistent with the tree structure. This, in turn leads to a significantly simpler merging procedure of the small subtrees. We prove that STDR is statistically consistent, and bound the number of samples required to accurately recover the tree with high probability. Using simulated data from several common tree models in phylogenetics, we demonstrate that STDR has a significant advantage in terms of runtime, with improved or similar accuracy.
Landau suggested that the low-temperature properties of metals can be understood in terms of long-lived quasiparticles with all complex interactions included in Fermi-liquid parameters, such as the effective mass $m^{star}$. Despite its wide applicability, electronic transport in bad or strange metals and unconventional superconductors is controversially discussed towards a possible collapse of the quasiparticle concept. Here we explore the electrodynamic response of correlated metals at half filling for varying correlation strength upon approaching a Mott insulator. We reveal persistent Fermi-liquid behavior with pronounced quadratic dependences of the optical scattering rate on temperature and frequency, along with a puzzling elastic contribution to relaxation. The strong increase of the resistivity beyond the Ioffe-Regel-Mott limit is accompanied by a `displaced Drude peak in the optical conductivity. Our results, supported by a theoretical model for the optical response, demonstrate the emergence of a bad metal from resilient quasiparticles that are subject to dynamical localization and dissolve near the Mott transition.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
