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Chimera states consisting of synchronous and asynchronous domains in a medium of nonlinearly coupled phase oscillators have been considered. Stationary inhomogeneous solutions of the Ott-Antonsen equation for a complex order parameter that correspond to fundamental chimeras have been constructed. The direct numerical simulation has shown that these structures under certain conditions are transformed to oscillatory (breathing) chimera regimes because of the development of instability.
We investigate both analytically and by computer simulations the ensemble- and time-averaged, nonergodic, and aging properties of massive particles diffusing in a medium with a time dependent diffusivity. We call this stochastic diffusion process the (aging) underdamped scaled Brownian motion (UDSBM). We demonstrate how the mean squared displacement (MSD) and the time-averaged MSD of UDSBM are affected by the inertial term in the Langevin equation, both at short, intermediate, and even long diffusion times. In particular, we quantify the ballistic regime for the MSD and the time-averaged MSD as well as the spread of individual time-averaged MSD trajectories. One of the main effects we observe is that, both for the MSD and the time-averaged MSD, for superdiffusive UDSBM the ballistic regime is much shorter than for ordinary Brownian motion. In contrast, for subdiffusive UDSBM, the ballistic region extends to much longer diffusion times. Therefore, particular care needs to be taken under what conditions the overdamped limit indeed provides a correct description, even in the long time limit. We also analyze to what extent ergodicity in the Boltzmann-Khinchin sense in this nonstationary system is broken, both for subdiffusive and superdiffusive UDSBM. Finally, the limiting case of ultraslow UDSBM is considered, with a mixed logarithmic and power-law dependence of the ensemble-and time-averaged MSDs of the particles. In the limit of strong aging, remarkably, the ordinary UDSBM and the ultraslow UDSBM behave similarly in the short time ballistic limit. The approaches developed here open ways for considering other stochastic processes under physically important conditions when a finite particle mass and aging in the system cannot be neglected.
Context. The Milky Way is surrounded by large amounts of diffuse gaseous matter that connects the stellar body of our Galaxy with its large-scale Local Group (LG) environment. Aims. To characterize the absorption properties of this circumgalactic medium (CGM) and its relation to the LG we present the so-far largest survey of metal absorption in Galactic high-velocity clouds (HVCs) using archival ultraviolet (UV) spectra of extragalactic background sources. The UV data are obtained with the Cosmic Origins Spectrograph (COS) onboard the Hubble Space Telescope (HST) and are supplemented by 21 cm radio observations of neutral hydrogen. Methods. Along 270 sightlines we measure metal absorption in the lines of Si II, Si III, C II, and C IV and associated H I 21 cm emission in HVCs in the velocity range vertical bar v(LSR)vertical bar = 100-500 km s(-1). With this unprecedented large HVC sample we were able to improve the statistics on HVC covering fractions, ionization conditions, small-scale structure, CGM mass, and inflow rate. For the first time, we determine robustly the angular two point correlation function of the high-velocity absorbers, systematically analyze antipodal sightlines on the celestial sphere, and compare the HVC absorption characteristics with that of damped Lyman alpha absorbers (DLAs) and constrained cosmological simulations of the LG (CLUES project).
The Milky Way is surrounded by large amounts of gaseous matter that are slowly being accreted over cosmic timescales to support star formation in the disk. The corresponding gas-accretion rate represents a key parameter for the past, present, and future evolution of the Milky Way. In this chapter, we discuss our current understanding of gas accretion processes in the Galaxy by reviewing past and recent observational and theoretical studies. The first part of this review deals with the spatial distribution of the different gas phases in the Milky Way halo, the origin of the gas, and its total mass. The second part discusses the gas dynamics and the physical processes that regulate the gas flow from the outer Galactic halo to the disk. From the most recent studies follows that the present-day gas accretion rate of the Milky Way is a few solar masses per year, which is sufficient to maintain the Galaxy’s star-formation rate at its current level.
Background: Inferring regulatory interactions between genes from transcriptomics time-resolved data, yielding reverse engineered gene regulatory networks, is of paramount importance to systems biology and bioinformatics studies. Accurate methods to address this problem can ultimately provide a deeper insight into the complexity, behavior, and functions of the underlying biological systems. However, the large number of interacting genes coupled with short and often noisy time-resolved read-outs of the system renders the reverse engineering a challenging task. Therefore, the development and assessment of methods which are computationally efficient, robust against noise, applicable to short time series data, and preferably capable of reconstructing the directionality of the regulatory interactions remains a pressing research problem with valuable applications.
Results: Here we perform the largest systematic analysis of a set of similarity measures and scoring schemes within the scope of the relevance network approach which are commonly used for gene regulatory network reconstruction from time series data. In addition, we define and analyze several novel measures and schemes which are particularly suitable for short transcriptomics time series. We also compare the considered 21 measures and 6 scoring schemes according to their ability to correctly reconstruct such networks from short time series data by calculating summary statistics based on the corresponding specificity and sensitivity. Our results demonstrate that rank and symbol based measures have the highest performance in inferring regulatory interactions. In addition, the proposed scoring scheme by asymmetric weighting has shown to be valuable in reducing the number of false positive interactions. On the other hand, Granger causality as well as information-theoretic measures, frequently used in inference of regulatory networks, show low performance on the short time series analyzed in this study.
Conclusions: Our study is intended to serve as a guide for choosing a particular combination of similarity measures and scoring schemes suitable for reconstruction of gene regulatory networks from short time series data. We show that further improvement of algorithms for reverse engineering can be obtained if one considers measures that are rooted in the study of symbolic dynamics or ranks, in contrast to the application of common similarity measures which do not consider the temporal character of the employed data. Moreover, we establish that the asymmetric weighting scoring scheme together with symbol based measures (for low noise level) and rank based measures (for high noise level) are the most suitable choices.
Identifying causal relations from observational data sets has posed great challenges in data-driven causality inference studies. One of the successful approaches to detect direct coupling in the information theory framework is transfer entropy. However, the core of entropy-based tools lies on the probability estimation of the underlying variables. Herewe propose a data-driven approach for causality inference that incorporates recurrence plot features into the framework of information theory. We define it as the recurrence measure of conditional dependence (RMCD), and we present some applications. The RMCD quantifies the causal dependence between two processes based on joint recurrence patterns between the past of the possible driver and present of the potentially driven, excepting the contribution of the contemporaneous past of the driven variable. Finally, it can unveil the time scale of the influence of the sea-surface temperature of the Pacific Ocean on the precipitation in the Amazonia during recent major droughts.
The SusKat-ABC (Sustainable Atmosphere for the Kathmandu Valley-Atmospheric Brown Clouds) international air pollution measurement campaign was carried out from December 2012 to June 2013 in the Kathmandu Valley and surrounding regions in Nepal. The Kathmandu Valley is a bowl-shaped basin with a severe air pollution problem. This paper reports measurements of two major greenhouse gases (GHGs), methane (CH4) and carbon dioxide (CO2), along with the pollutant CO, that began during the campaign and were extended for 1 year at the SusKat-ABC supersite in Bode, a semi-urban location in the Kathmandu Valley. Simultaneous measurements were also made during 2015 in Bode and a nearby rural site (Chanban) similar to 25 km (aerial distance) to the southwest of Bode on the other side of a tall ridge. The ambient mixing ratios of methane (CH4), carbon dioxide (CO2), water vapor, and carbon monoxide (CO) were measured with a cavity ring-down spectrometer (G2401; Picarro, USA) along with meteorological parameters for 1 year (March 2013-March 2014). These measurements are the first of their kind in the central Himalayan foothills. At Bode, the annual average mixing ratios of CO2 and CH4 were 419.3 (+/- 6.0) ppm and 2.192 (+/- 0.066) ppm, respectively. These values are higher than the levels observed at background sites such as Mauna Loa, USA (CO2: 396.8 +/- 2.0 ppm, CH4: 1.831 +/- 0.110 ppm) and Waliguan, China (CO2: 397.7 +/- 3.6 ppm, CH4: 1.879 +/- 0.009 ppm) during the same period and at other urban and semi-urban sites in the region, such as Ahmedabad and Shadnagar (India). They varied slightly across the seasons at Bode, with seasonal average CH4 mixing ratios of 2.157 (+/- 0.230) ppm in the pre-monsoon season, 2.199 (+/- 0.241) ppm in the monsoon, 2.210 (+/- 0.200) ppm in the post-monsoon, and 2.214 (+/- 0.209) ppm in the winter season. The average CO2 mixing ratios were 426.2 (+/- 25.5) ppm in the pre-monsoon, 413.5 (+/- 24.2) ppm in the monsoon, 417.3 (+/- 23.1) ppm in the postmonsoon, and 421.9 (+/- 20.3) ppm in the winter season. The maximum seasonal mean mixing ratio of CH4 in winter was only 0.057 ppm or 2.6% higher than the seasonal minimum during the pre-monsoon period, while CO2 was 12.8 ppm or 3.1% higher during the pre-monsoon period (seasonal maximum) than during the monsoon (seasonal minimum). On the other hand, the CO mixing ratio at Bode was 191% higher during the winter than during the monsoon season. The enhancement in CO2 mixing ratios during the pre-monsoon season is associated with additional CO2 emissions from forest fires and agro-residue burning in northern South Asia in addition to local emissions in the Kathmandu Valley. Published CO = CO2 ratios of different emission sources in Nepal and India were compared with the observed CO = CO2 ratios in this study. This comparison suggested that the major sources in the Kathmandu Valley were residential cooking and vehicle exhaust in all seasons except winter. In winter, brick kiln emissions were a major source. Simultaneous measurements in Bode and Chanban (15 July-3 October 2015) revealed that the mixing ratios of CO2, CH4, and CO were 3.8, 12, and 64% higher in Bode than Chanban. The Kathmandu Valley thus has significant emissions from local sources, which can also be attributed to its bowl-shaped geography that is conducive to pollution build-up. At Bode, all three gas species (CO2, CH4, and CO) showed strong diurnal patterns in their mixing ratios with a pronounced morning peak (ca. 08:00), a dip in the afternoon, and a gradual increase again through the night until the next morning. CH4 and CO at Chanban, however, did not show any noticeable diurnal variations. These measurements provide the first insights into the diurnal and seasonal variation in key greenhouse gases and air pollutants and their local and regional sources, which is important information for atmospheric research in the region.
Prospects for Cherenkov Telescope Array Observations of the Young Supernova Remnant RX J1713.7-3946
(2017)
We perform simulations for future Cherenkov Telescope Array (CTA) observations of RX J1713.7-3946, a young supernova remnant (SNR) and one of the brightest sources ever discovered in very high energy (VHE) gamma rays. Special attention is paid to exploring possible spatial (anti) correlations of gamma rays with emission at other wavelengths, in particular X-rays and CO/H I emission. We present a series of simulated images of RX J1713.7-3946 for CTA based on a set of observationally motivated models for the gamma-ray emission. In these models, VHE gamma rays produced by high-energy electrons are assumed to trace the nonthermal X-ray emission observed by XMM-Newton, whereas those originating from relativistic protons delineate the local gas distributions. The local atomic and molecular gas distributions are deduced by the NANTEN team from CO and H I observations. Our primary goal is to show how one can distinguish the emission mechanism(s) of the gamma rays (i.e., hadronic versus leptonic, or a mixture of the two) through information provided by their spatial distribution, spectra, and time variation. This work is the first attempt to quantitatively evaluate the capabilities of CTA to achieve various proposed scientific goals by observing this important cosmic particle accelerator.
Imaging atmospheric Cherenkov telescopes (IACTs) are equipped with sensitive photomultiplier tube (PMT) cameras. Exposure to high levels of background illumination degrades the efficiency of and potentially destroys these photo-detectors over time, so IACTs cannot be operated in the same configuration in the presence of bright moonlight as under dark skies. Since September 2012, observations have been carried out with the VERITAS IACTs under bright moonlight (defined as about three times the night-sky-background (NSB) of a dark extragalactic field, typically occurring when Moon illumination > 35%) in two observing modes, firstly by reducing the voltage applied to the PMTs and, secondly, with the addition of ultra-violet (UV) bandpass filters to the cameras. This has allowed observations at up to about 30 times previous NSB levels (around 80% Moon illumination), resulting in 30% more observing time between the two modes over the course of a year. These additional observations have already allowed for the detection of a flare from the 1ES 1727 + 502 and for an observing program targeting a measurement of the cosmic-ray positron fraction. We provide details of these new observing modes and their performance relative to the standard VERITAS observations. (C) 2017 Elsevier B.V. All rights reserved.