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Uchimoto Y.K.,Tohoku University | Uchimoto Y.K.,University of Tokyo | Uchimoto Y.K.,Japan National Astronomical Observatory | Yamada T.,Tohoku University | And 14 more authors.
Astrophysical Journal

We present the results of wide-field deep JHK imaging of the SSA22 field using the MOIRCS instrument equipped with the Subaru telescope. The observed field is 112 arcmin2 in area, which covers the z = 3.1 protocluster characterized by the overdensities of Lyα emitters (LAEs) and Lyα blobs (LABs). The 5σ limiting magnitude is K AB = 24.3. We extract the potential protocluster members from the K-selected sample by using the multi-band photometric-redshift selection as well as the simple color cut for distant red galaxies (DRGs; J - K AB > 1.4). The surface number density of DRGs in our observed fields shows clear excess compared with those in the blank fields, and the location of the densest area whose projected overdensity is twice the average coincides with the large-scale density peak of LAEs. We also found that K-band counterparts with z phot ≃ 3.1 are detected for 75% (15/20) of the LABs within their Lyα halo, and the 40% (8/20) of LABs have multiple components, which gives a direct evidence of the hierarchical multiple merging in galaxy formation. The stellar mass of LABs correlates with their luminosity, isophotal area, and the Lyα velocity widths, implying that the physical scale and the dynamical motion of Lyα emission are closely related to their previous star formation activities. Highly dust-obscured galaxies such as hyper extremely red objects (J - K AB > 2.1) and plausible K-band counterparts of submillimeter sources are also populated in the high-density region. © 2012. The American Astronomical Society. All rights reserved. Source

Kornilov V.,Moscow State University | Sarazin M.,European Southern Observatory | Tokovinin A.,Cerro Tololo Inter American Observatory | Travouillon T.,Thirty Meter Telescope Observatory Corporation | Voziakova O.,Moscow State University
Astronomy and Astrophysics

Aims. Scintillation noise is a major limitation of ground-based photometric precision. Methods. An extensive dataset of stellar scintillation collected at 11 astronomical sites world-wide with MASS instruments was used to estimate the scintillation noise of large telescopes in the fast photometry and traditional long-exposure regime. Results. Statistical distributions of the corresponding parameters are given. The scintillation noise is mostly determined by turbulence and wind in the upper atmosphere and is comparable at all sites, with slightly lower values at Mauna Kea and the highest noise at Tolonchar in Chile. We show that the classical Young's formula underestimates the scintillation noise. The temporal variations of the scintillation noise are also similar at all sites, showing short-term variability at time scales of 1-2 h and slower variations, including marked seasonal trends (stronger scintillation and less clear sky during local winter). Some correlation was found between nearby observatories. © ESO, 2012. Source

Gilles L.,Thirty Meter Telescope Observatory Corporation | Massioni P.,CNRS Ampere Laboratory | Kulcsar C.,University Paris - Sud | Raynaud H.-F.,University Paris - Sud | Ellerbroek B.,Thirty Meter Telescope Observatory Corporation
Journal of the Optical Society of America A: Optics and Image Science, and Vision

This paper discusses the performance and cost of two computationally efficient Fourier-based tomographic wavefront reconstruction algorithms for wide-field laser guide star (LGS) adaptive optics (AO). The first algorithm is the iterative Fourier domain preconditioned conjugate gradient (FDPCG) algorithm developed by Yang et al. [Appl. Opt. 45, 5281 (2006)], combined with pseudo-open-loop control (POLC). FDPCG's computational cost is proportional to N log(N), where N denotes the dimensionality of the tomography problem. The second algorithm is the distributed Kalman filter (DKF) developed by Massioni et al. [J. Opt. Soc. Am. A 28, 2298 (2011)], which is a noniterative spatially invariant controller. When implemented in the Fourier domain, DKF's cost is also proportional to N log(N). Both algorithms are capable of estimating spatial frequency components of the residual phase beyond the wavefront sensor (WFS) cutoff frequency thanks to regularization, thereby reducing WFS spatial aliasing at the expense of more computations. We present performance and cost analyses for the LGS multiconjugate AO system under design for the Thirty Meter Telescope, as well as DKF's sensitivity to uncertainties in wind profile prior information. We found that, provided the wind profile is known to better than 10% wind speed accuracy and 20 deg wind direction accuracy, DKF, despite its spatial invariance assumptions, delivers a significantly reduced wavefront error compared to the static FDPCG minimum variance estimator combined with POLC. Due to its nonsequential nature and high degree of parallelism, DKF is particularly well suited for real-time implementation on inexpensive off-the-shelf graphics processing units. © 2013 Optical Society of America. Source

Gilles L.,Thirty Meter Telescope Observatory Corporation | Massioni P.,CNRS Ampere Laboratory | Ellerbroek B.,Thirty Meter Telescope Observatory Corporation
Adaptive Optics: Analysis, Methods and Systems, AO 2015

We report on an Adaptive Distributed Kalman Filter (ADKF) for laser guide star tomography on extremely large telescopes capable of achieving the same performance level as the static minimum variance reconstructor (MVR) at a fraction of the computational cost. © 2015 OSA. Source

Massioni P.,University Claude Bernard Lyon 1 | Gilles L.,Thirty Meter Telescope Observatory Corporation | Ellerbroek B.,Thirty Meter Telescope Observatory Corporation
Journal of the Optical Society of America A: Optics and Image Science, and Vision

In the framework of adaptive optics (AO) for astronomy, it is a common assumption to consider the atmospheric turbulent layers as "frozen flows" sliding according to the wind velocity profile. For this reason, having knowledge of such a velocity profile is beneficial in terms of AO control system performance. In this paper we show that it is possible to exploit the phase estimate from a Kalman filter running on an AO system in order to estimate wind velocity. This allows the update of the Kalman filter itself with such knowledge, making it adaptive. We have implemented such an adaptive controller based on the distributed version of the Kalman filter, for a realistic simulation of a multi-conjugate AO system with laser guide stars on a 30 m telescope. Simulation results show that this approach is effective and promising and the additional computational cost with respect to the distributed filter is negligible. Comparisons with a previously published slope detection and ranging wind profiler are made and the impact of turbulence profile quantization is assessed. One of the main findings of the paper is that all flavors of the adaptive distributed Kalman filter are impacted more significantly by turbulence profile quantization than the static minimum mean square estimator which does not incorporate wind profile information. © 2015 Optical Society of America. Source

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