Academia Sinica

About: Academia Sinica is a facility organization based out in Taipei, Taiwan. It is known for research contribution in the topics: Population & Gene. The organization has 52086 authors who have published 65998 publications receiving 1728114 citations. The organization is also known as: Central Research Academy.

The DEEP2 Galaxy Redshift Survey: Design, Observations, Data Reduction, and Redshifts

Abstract: We describe the design and data analysis of the DEEP2 Galaxy Redshift Survey, the densest and largest high-precision redshift survey of galaxies at z ~ 1 completed to date. The survey was designed to conduct a comprehensive census of massive galaxies, their properties, environments, and large-scale structure down to absolute magnitude M_B = −20 at z ~ 1 via ~90 nights of observation on the Keck telescope. The survey covers an area of 2.8 deg^2 divided into four separate fields observed to a limiting apparent magnitude of R_(AB) = 24.1. Objects with z ≾0.7 are readily identifiable using BRI photometry and rejected in three of the four DEEP2 fields, allowing galaxies with z > 0.7 to be targeted ~2.5 times more efficiently than in a purely magnitude-limited sample. Approximately 60% of eligible targets are chosen for spectroscopy, yielding nearly 53,000 spectra and more than 38,000 reliable redshift measurements. Most of the targets that fail to yield secure redshifts are blue objects that lie beyond z ~ 1.45, where the [O ii] 3727 A doublet lies in the infrared. The DEIMOS 1200 line mm^(−1) grating used for the survey delivers high spectral resolution (R ~ 6000), accurate and secure redshifts, and unique internal kinematic information. Extensive ancillary data are available in the DEEP2 fields, particularly in the Extended Groth Strip, which has evolved into one of the richest multiwavelength regions on the sky. This paper is intended as a handbook for users of the DEEP2 Data Release 4, which includes all DEEP2 spectra and redshifts, as well as for the DEEP2 DEIMOS data reduction pipelines. Extensive details are provided on object selection, mask design, biases in target selection and redshift measurements, the spec2d two-dimensional data-reduction pipeline, the spec1d automated redshift pipeline, and the zspec visual redshift verification process, along with examples of instrumental signatures or other artifacts that in some cases remain after data reduction. Redshift errors and catastrophic failure rates are assessed through more than 2000 objects with duplicate observations. Sky subtraction is essentially photon-limited even under bright OH sky lines; we describe the strategies that permitted this, based on high image stability, accurate wavelength solutions, and powerful B-spline modeling methods. We also investigate the impact of targets that appear to be single objects in ground-based targeting imaging but prove to be composite in Hubble Space Telescope data; they constitute several percent of targets at z ~ 1, approaching ~5%–10% at z > 1.5. Summary data are given that demonstrate the superiority of DEEP2 over other deep high-precision redshift surveys at z ~ 1 in terms of redshift accuracy, sample number density, and amount of spectral information. We also provide an overview of the scientific highlights of the DEEP2 survey thus far.

Perturbation-theory without gauge fixing

Abstract: We propose to formulate the perturbative expausion for field theory starting from the Langevin equation which describes the approach to equilibriumWe show that this formulation can be applied to gauge theories to compute gauge invariant quantities without fixing the gauge A very simple example is worked out in detail We also discuss the speed of approaching to equilibrium of the solution of the Langevin equation in the framework of perturbation theory

Planck 2013 results. XI. All-sky model of thermal dust emission

Abstract: This paper presents an all-sky model of dust emission from the Planck 857, 545 and 353 GHz, and IRAS 100 micron data. Using a modified black-body fit to the data we present all-sky maps of the dust optical depth, temperature, and spectral index over the 353-3000 GHz range. This model is a tight representation of the data at 5 arcmin. It shows variations of the order of 30 % compared with the widely-used model of Finkbeiner, Davis, and Schlegel. The Planck data allow us to estimate the dust temperature uniformly over the whole sky, providing an improved estimate of the dust optical depth compared to previous all-sky dust model, especially in high-contrast molecular regions. An increase of the dust opacity at 353 GHz, tau_353/N_H, from the diffuse to the denser interstellar medium (ISM) is reported. It is associated with a decrease in the observed dust temperature, T_obs, that could be due at least in part to the increased dust opacity. We also report an excess of dust emission at HI column densities lower than 10^20 cm^-2 that could be the signature of dust in the warm ionized medium. In the diffuse ISM at high Galactic latitude, we report an anti-correlation between tau_353/N_H and T_obs while the dust specific luminosity, i.e., the total dust emission integrated over frequency (the radiance) per hydrogen atom, stays about constant. The implication is that in the diffuse high-latitude ISM tau_353 is not as reliable a tracer of dust column density as we conclude it is in molecular clouds where the correlation of tau_353 with dust extinction estimated using colour excess measurements on stars is strong. To estimate Galactic E(B-V) in extragalactic fields at high latitude we develop a new method based on the thermal dust radiance, instead of the dust optical depth, calibrated to E(B-V) using reddening measurements of quasars deduced from Sloan Digital Sky Survey data.

A five-gene signature and clinical outcome in non-small-cell lung cancer

Abstract: BACKGROUND Current staging methods are inadequate for predicting the outcome of treatment of non-small-cell lung cancer (NSCLC). We developed a five-gene signature that is closely associated with survival of patients with NSCLC. METHODS We used computer-generated random numbers to assign 185 frozen specimens for microarray analysis, real-time reverse-transcriptase polymerase chain reaction (RT-PCR) analysis, or both. We studied gene expression in frozen specimens of lung-cancer tissue from 125 randomly selected patients who had undergone surgical resection of NSCLC and evaluated the association between the level of expression and survival. We used risk scores and decision-tree analysis to develop a gene-expression model for the prediction of the outcome of treatment of NSCLC. For validation, we used randomly assigned specimens from 60 other patients. RESULTS Sixteen genes that correlated with survival among patients with NSCLC were identified by analyzing microarray data and risk scores. We selected five genes (DUSP6, MMD, STAT1, ERBB3, and LCK) for RT-PCR and decision-tree analysis. The five-gene signature was an independent predictor of relapse-free and overall survival. We validated the model with data from an independent cohort of 60 patients with NSCLC and with a set of published microarray data from 86 patients with NSCLC. CONCLUSIONS Our five-gene signature is closely associated with relapse-free and overall survival among patients with NSCLC.