Is Ursa Major II the progenitor of the Orphan Stream?

Prominent in the 'Field of Streams'– the Sloan Digital Sky Survey map of substructure in the Galactic halo – is an 'Orphan Stream' without obvious progenitor. In this numerical study, we show a possible connection between the newly found dwarf satellite Ursa Major II (UMa II) and the Orphan Stream. We provide numerical simulations of the disruption of UMa II that match the observational data on the position, distance and morphology of the Orphan Stream. We predict the radial velocity of UMa II as −100 km s⁻¹, as well as the existence of strong velocity gradients along the Orphan Stream. The velocity dispersion of UMa II is expected to be high, though this can be caused both by a high dark matter content or by the presence of unbound stars in a disrupted remnant. However, the existence of a gradient in the mean radial velocity across UMa II provides a clear-cut distinction between these possibilities. The simulations support the idea that some of the anomalous, young halo globular clusters like Palomar 1 or Arp 2 or Ruprecht 106 may be physically associated with the Orphan Stream.     

Cosmic dynamics in the era of Extremely Large Telescopes

The redshifts of all cosmologically distant sources are expected to experience a small, systematic drift as a function of time due to the evolution of the Universe's expansion rate. A measurement of this effect would represent a direct and entirely model-independent determination of the expansion history of the Universe over a redshift range that is inaccessible to other methods. Here we investigate the impact of the next generation of Extremely Large Telescopes on the feasibility of detecting and characterizing the cosmological redshift drift. We consider the Lyα forest in the redshift range  2 < z < 5  and other absorption lines in the spectra of high-redshift QSOs as the most suitable targets for a redshift drift experiment. Assuming photon-noise-limited observations and using extensive Monte Carlo simulations we determine the accuracy to which the redshift drift can be measured from the Lyα forest as a function of signal-to-noise ratio and redshift. Based on this relation and using the brightness and redshift distributions of known QSOs we find that a 42-m telescope is capable of unambiguously detecting the redshift drift over a period of ∼20 yr using 4000 h of observing time. Such an experiment would provide independent evidence for the existence of dark energy without assuming spatial flatness, using any other cosmological constraints or making any other astrophysical assumption.     

The structure of ocean-surface currents measured by Doppler radar

The spatial structure of surface currents collected using a Doppler Radar system off the Florida Keys has been investigated. Surface current vectors were acquired within a rectilinear grid containing 700 nodes, where each node was spaced 1 km apart. Principal component analyses indicate that at least 63% of the variance of the surface currents at the 700 nodal locations can be accounted for by only three principal components. The principal modes of circulation during two separate experiments were extracted and found to be basically the same, although the first two modes were reversed between the two experiments. Coherence spectra were determined for nodal spacings between 1.76 km and 10.48 km, and the results of these analyses indicate that over most of the experimental area, approximately 60% of the variance is coherent over separations of 10.48 km. Application of a synoptic time-series model indicates that accurate prediction of the mean currents over each of the 65-h subrecord lengths was the dominant factor in controlling model performance, and that on the order of 10% error could be expected in using the time-series model to predict the low-frequency fluctuations. This indicates that time-series modeling of surface currents may be feasible and useful in estimating the long-term mixing characteristics of contaminants transported in the surface layer     

tiravel– Template-Independent RAdial VELocity measurement

We describe the dynamical evolution of hotspots velocity, pressure and mass density in radio-loud active galactic nuclei (AGNs), taking proper account of (1) the conservations of the mass, momentum and kinetic energy flux of the unshocked jet, (2) the deceleration process of the jet by shocks and (3) the cocoon expansion without assuming the constant aspect ratio of the cocoon. By the detailed comparison with two-dimensional relativistic hydrodynamic simulations, we show that our model well reproduces the whole evolution of relativistic jets. Our model can explain also the observational trends of the velocity, the pressure, the size and mass density of hotspots in compact symmetric objects (CSOs) and Fanaroff–Riley type II (FR II) radio galaxies.     

Correcting systematic effects in a large set of photometric light curves

We suggest a new algorithm to remove systematic effects in a large set of light curves obtained by a photometric survey. The algorithm can remove systematic effects, such as those associated with atmospheric extinction, detector efficiency, or point spread function changes over the detector. The algorithm works without any prior knowledge of the effects, as long as they linearly appear in many stars of the sample. The approach, which was originally developed to remove atmospheric extinction effects, is based on a lower rank approximation of matrices, an approach which has already been suggested and used in chemometrics, for example. The proposed algorithm is especially useful in cases where the uncertainties of the measurements are unequal. For equal uncertainties, the algorithm reduces to the Principal Component Analysis (PCA) algorithm. We present a simulation to demonstrate the effectiveness of the proposed algorithm and we point out its potential, in the search for transit candidates in particular.     

A data‐mining approach for assessing consistency between multiple representations in spatial databases

When different spatial databases are combined, an important issue is the identification of inconsistencies between data. Quite often, representations of the same geographical entities in databases are different and reflect different points of view. In order to fully take advantage of these differences when object instances are associated, a key issue is to determine whether the differences are normal, i.e. explained by the database specifications, or if they are due to erroneous or outdated data in one database. In this paper, we propose a knowledge‐based approach to partially automate the consistency assessment between multiple representations of data. The inconsistency detection is viewed as a knowledge‐acquisition problem, the source of knowledge being the data. The consistency assessment is carried out by applying a proposed method called MECO. This method is itself parameterized by some domain knowledge obtained from a second method called MACO. MACO supports two approaches (direct or indirect) to perform the knowledge acquisition using data‐mining techniques. In particular, a supervised learning approach is defined to automate the knowledge acquisition so as to drastically reduce the human‐domain expert's work. Thanks to this approach, the knowledge‐acquisition process is sped up and less expert‐dependent. Training examples are obtained automatically upon completion of the spatial data matching. Knowledge extraction from data following this bottom‐up approach is particularly useful, since the database specifications are generally complex, difficult to analyse, and manually encoded. Such a data‐driven process also sheds some light on the gap between textual specifications and those actually used to produce the data. The methodology is illustrated and experimentally validated by comparing geometrical representations and attribute values of different vector spatial databases. The advantages and limits of such partially automatic approaches are discussed, and some future works are suggested.     

Human virus and microbial indicator occurrence in public-supply groundwater systems: meta-analysis of 12 international studies

Groundwater quality is often evaluated using microbial indicators. This study examines data from 12 international groundwater studies (conducted 1992–2013) of 718 public drinking-water systems located in a range of hydrogeological settings. Focus was on testing the value of indicator organisms for identifying virus-contaminated wells. One or more indicators and viruses were present in 37 and 15% of 2,273 samples and 44 and 27% of 746 wells, respectively. Escherichia coli (E. coli) and somatic coliphage are 7–9 times more likely to be associated with culturable virus-positive samples when the indicator is present versus when it is absent, while F-specific and somatic coliphages are 8–9 times more likely to be associated with culturable virus-positive wells. However, single indicators are only marginally associated with viruses detected by molecular methods, and all microbial indicators have low sensitivity and positive predictive values for virus occurrence, whether by culturable or molecular assays, i.e., indicators are often absent when viruses are present and the indicators have a high false-positive rate. Wells were divided into three susceptibility subsets based on presence of (1) total coliform bacteria or (2) multiple indicators, or (3) location of wells in karst, fractured bedrock, or gravel/cobble settings. Better associations of some indicators with viruses were observed for (1) and (3). Findings indicate the best indicators are E. coli or somatic coliphage, although both indicators may underestimate virus occurrence. Repeat sampling for indicators improves evaluation of the potential for viral contamination in a well.     

The Spectroscopic Orbit of the Planetary Companion Transiting HD 209458

Three new silicon-bearing radicals of astrophysical interest, SiCCH and the two nearly isoenergetic isomers SiCN and SiNC, were detected in a laboratory discharge in their X2Pi ground states by Fourier transform microwave and millimeter-wave absorption spectroscopy. Hyperfine structure was observed in the low rotational transitions of the (2)Pi(1/2) ladder, and well-resolved Lambda-doubling was observed in both fine-structure ladders. With the spectroscopic constants derived from the laboratory measurements, the spectra of all three can be calculated to an uncertainty of less than 0.1 km s(-1) in equivalent radial velocity over the entire range of interest to radio astronomers. SiCN, with a dipole moment of 2.9 D, is probably the most promising of the three for astronomical discovery.     

Two-Micron All-Sky Survey J01542930+0053266: a new eclipsing M dwarf binary system

We report on Two-Micron All-Sky Survey (2MASS) J01542930+0053266, a faint eclipsing system composed of two M dwarfs. The variability of this system was originally discovered during a pilot study of the 2MASS Calibration Point Source Working Data base. Additional photometry from the Sloan Digital Sky Survey yields an eight-passband light curve from which we derive an orbital period of  2.639 0157 ± 0.000 0016  d. Spectroscopic followup confirms our photometric classification of the system, which is likely composed of M0 and M1 dwarfs. Radial velocity measurements allow us to derive the masses  (M₁= 0.66 ± 0.03 M_⊙; M₂= 0.62 ± 0.03 M_⊙)  and radii  (R₁= 0.64 ± 0.08 R_⊙; R₂= 0.61 ± 0.09 R_⊙)  of the components, which are consistent with empirical mass–radius relationships for low-mass stars in binary systems. We perform Monte Carlo simulations of the light curves which allow us to uncover complicated degeneracies between the system parameters. Both stars show evidence of Hα emission, something not common in early-type M dwarfs. This suggests that binarity may influence the magnetic activity properties of low-mass stars; activity in the binary may persist long after the dynamos in their isolated counterparts have decayed, yielding a new potential foreground of flaring activity for next generation variability surveys.