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Register a new userSelection and Characterization of Interesting Grism Spectra
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G.R. Meurer
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Observations with the ACS Wide Field Camera and G800L grism can produce thousands of spectra within a single WFC field producing a potentially rich treasure trove of information. However, the data are complicated to deal with. Here we describe algorithms to find and characterize spectra of emission line galaxies and supernovae using tools we have developed in conjunction with off the shelf software.
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We present complimentary techniques to find emission-line targets and measure their properties in a semi-automated fashion from grism observations obtained with the Advanced Camera for Surveys aboard the Hubble Space Telescope. The first technique is to find all likely sources in a direct image, extract their spectra and search them for emission lines. The second method is to look for emission-line sources as compact structures in an unsharp masked version of the grism image. Using these methods we identify 46 emission-line targets in the Hubble Deep Field North using a modest (3 orbit) expenditure of HST observing time. Grism spectroscopy is a powerful tool for efficiently identifying interesting low luminosity, moderate redshift emission-line field galaxies. The sources found here have a median i band flux 1.5 mag fainter than the spectroscopic redshift catalog of Cohen et al. They have redshift z <= 1.42, high equivalent widths (typically EW > 100{AA}), and are usually less luminous than the characteristic luminosity at the same redshift. The chief obstacle in interpreting the results is line identification, since the majority of sources have a single emission line and the spectral resolution is low. Photometric redshifts are useful for providing a first guess redshift. However, even at the depth of the state-of-the-art data used here, photometric errors can result in uncertainties in line identifications, especially for sources with i > ~24.5 ABmag. Reliable line identification for the faintest emission-line galaxies requires additional ground-based spectroscopy for confirmation. Of particular concern are the faint high EW [OII] emitters which could represent a strongly evolving galaxy population if the possibility that they are mis-identified lower redshift interlopers can be ruled out. (Slightly abridged)
In this paper we have evaluated the amount of available telescope time at four interesting sites for astronomical instrumentation. We use the GOES 12 data for the years 2008 and 2009. We use a homogeneous methodology presented in several previous papers to classify the nights as clear (completely cloud-free), mixed (partially cloud-covered), and covered. Additionally, for the clear nights, we have evaluated the amount of satellite stable nights which correspond to the amount of ground based photometric nights, and the clear nights corresponding to the spectroscopic nights. We have applied this model to two sites in the Northern Hemisphere (San Pedro Martir (SPM), Mexico; Izana, Canary Islands) and to two sites in the Southern Hemisphere (El Leoncito, Argentine; San Antonio de Los Cobres (SAC), Argentine). We have obtained, from the two years considered, a mean amount of cloud free nights of 68.6% at Izana, 76.0% at SPM, 70.6% at Leoncito and 70.0% at SAC. We have evaluated, among the cloud free nights, an amount of stable nights of 62.6% at Izana, 69.6% at SPM, 64.9% at Leoncito, and 59.7% at SAC.
Lyman-break galaxies are now regularly found in the high redshift Universe by searching for the break in the galaxy spectrum caused by the Lyman-limit redshifted into the optical or even near-IR. At lower redshift, this break is covered by the GALEX UV channels and small samples of z ~ 1 LBGs have been presented in the literature. Here we give results from fitting the spectral energy distributions of a small sub-set of low redshift LBGs and demonstrate the advantage of including photometric points derived from HST ACS slitless grism observations. The results show these galaxies to have very young, star forming populations, while still being massive and dusty. LBGs at low and high redshift show remarkable similarities in their properties, indicating that the LBG selection method picks similar galaxies throughout the Universe.
The scientific output of the proposed EChO mission (in terms of spectroscopic characterization of the atmospheres of transiting extrasolar planets) will be maximized by a careful selection of targets and by a detailed characterization of the main physical parameters (such as masses and radii) of both the planets and their stellar hosts. To achieve this aim, the availability of high-quality data from other space-borne and ground-based programs will play a crucial role. Here we identify and discuss the elements of the Gaia catalogue that will be of utmost relevance for the selection and characterization of transiting planet systems to be observed by the proposed EChO mission.
In this paper, we introduce some interesting features of a memristor CNN (Cellular Neural Network). We first show that there is the similarity between the dynamics of memristors and neurons. That is, some kind of flux-controlled memristors can not respond to the sinusoidal voltage source quickly, namely, they can not switch `on rapidly. Furthermore, these memristors have refractory period after switch `on, which means that it can not respond to further sinusoidal inputs until the flux is decreased. We next show that the memristor-coupled two-cell CNN can exhibit chaotic behavior. In this system, the memristors switch `off and `on at irregular intervals, and the two cells are connected when either or both of the memristors switches `on. We then propose the modified CNN model, which can hold a binary output image, even if all cells are disconnected and no signal is supplied to the cell after a certain point of time. However, the modified CNN requires power to maintain the output image, that is, it is volatile. We next propose a new memristor CNN model. It can also hold a binary output state (image), even if all cells are disconnected, and no signal is supplied to the cell, by memristors switching behavior. Furthermore, even if we turn off the power of the system during the computation, it can resume from the previous average output state, since the memristor CNN has functions of both short-term (volatile) memory and long-term (non-volatile) memory. The above suspend and resume feature are useful when we want to save the current state, and continue work later from the previous state. Finally, we show that the memristor CNN can exhibit interesting two-dimensional waves, if an inductor is connected to each memristor CNN cell.
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