Abstract
We describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars ...using a purpose-built instrument on the 4 m Mayall Telescope at Kitt Peak National Observatory. The main goal of DESI is to measure with unprecedented precision the expansion history of the universe with the baryon acoustic oscillation technique and the growth rate of structure with redshift space distortions. Ten spectrographs with three cameras each disperse the light from 5000 fibers onto 30 CCDs, covering the near-UV to near-infrared (3600–9800 Å) with a spectral resolution ranging from 2000 to 5000. The DESI data pipeline generates wavelength- and flux-calibrated spectra of all the targets, along with spectroscopic classifications and redshift measurements. Fully processed data from each night are typically available to the DESI collaboration the following morning. We give details about the pipeline’s algorithms, and provide performance results on the stability of the optics, the quality of the sky background subtraction, and the precision and accuracy of the instrumental calibration. This pipeline has been used to process the DESI Survey Validation data set, and has exceeded the project’s requirements for redshift performance, with high efficiency and a purity greater than 99% for all target classes.
Abstract Highly multiplexed, fiber-fed spectroscopy is enabling surveys of millions of stars and galaxies. The performance of these surveys depends on accurately positioning fibers in the focal plane ...to capture target light. We describe a technique to measure the positioning accuracy of fibers by dithering fibers slightly around their ideal locations. This approach also enables measurement of the total system throughput and point-spread function delivered to the focal plane. We then apply this technique to observations from the Dark Energy Survey Instrument (DESI), and demonstrate that DESI positions fibers to within 0.″08 of their targets (5% of a fiber diameter) and achieves a system throughput within about 7% of expectations.
ABSTRACT The arrival directions of TeV-PeV cosmic rays show weak but significant anisotropies with relative intensities at the level of one per mille. Due to the smallness of the anisotropies, ...quantitative studies require careful disentanglement of detector effects from the observation. We discuss an iterative maximum-likelihood reconstruction that simultaneously fits cosmic-ray anisotropies and detector acceptance. The method does not rely on detector simulations and provides an optimal anisotropy reconstruction for ground-based cosmic-ray observatories located in the middle latitudes. It is particularly well suited to the recovery of the dipole anisotropy, which is a crucial observable for the study of cosmic-ray diffusion in our Galaxy. We also provide general analysis methods for recovering large- and small-scale anisotropies that take into account systematic effects of the observation by ground-based detectors.
Abstract
The highest-energy known gamma-ray sources are all located within 0.°5 of extremely powerful pulsars. This raises the question of whether ultra-high-energy (UHE; >56 TeV) gamma-ray emission ...is a universal feature expected near pulsars with a high spin-down power. Using four years of data from the High Altitude Water Cherenkov Gamma-Ray Observatory, we present a joint-likelihood analysis of 10 extremely powerful pulsars to search for subthreshold UHE gamma-ray emission correlated with these locations. We report a significant detection (>3
σ
), indicating that UHE gamma-ray emission is a generic feature of powerful pulsars. We discuss the emission mechanisms of the gamma rays and the implications of this result. The individual environment, such as the magnetic field and particle density in the surrounding area, appears to play a role in the amount of emission.
We have searched for correlations between the pointing directions of ultrahigh energy cosmic rays observed by the High Resolution Fly’s Eye experiment and active galactic nuclei (AGN) visible from ...its northern hemisphere location. No correlations, other than random correlations, have been found. We report our results using search parameters prescribed by the Pierre Auger collaboration. Using these parameters, the Auger collaboration concludes that a positive correlation exists for sources visible to their southern hemisphere location. We also describe results using two methods for determining the chance probability of correlations: one in which a hypothesis is formed from scanning one half of the data and tested on the second half, and another which involves a scan over the entire data set. The most significant correlation found occurred with a chance probability of 24%.
A common problem in ultra-high energy cosmic ray physics is the comparison of energy spectra. The question is whether the spectra from two experiments or two regions of the sky agree within their ...statistical and systematic uncertainties. We develop a method to directly compare energy spectra for ultra-high energy cosmic rays from two different regions of the sky in the same experiment without reliance on agreement with a theoretical model of the energy spectra. The consistency between the two spectra is expressed in terms of a Bayes factor, defined here as the ratio of the likelihood of the two-parent source hypothesis to the likelihood of the one-parent source hypothesis. Unlike other methods, for example Delta *y2 tests, the Bayes factor allows for the calculation of the posterior odds ratio and correctly accounts for non-Gaussian uncertainties. The latter is particularly important at the highest energies, where the number of events is very small.
Searches for statistically significant correlations between arrival directions of ultra-high-energy cosmic rays and classes of astrophysical objects are common in astroparticle physics. We present a ...method to test potential correlation signals of a priori unknown strength and evaluate their statistical significance sequentially, i.e., after each incoming new event in a running experiment. The method can be applied to data taken after the test has concluded, allowing for further monitoring of the signal significance. It adheres to the likelihood principle and rigorously accounts for our ignorance of the signal strength.
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