Measuring galaxy [OII] emission line doublet with future ground-based wide-field spectroscopic surveys

The next generation of wide-field spectroscopic redshift surveys will map the large-scale galaxy distribution in the redshift range 0.7< z<2 to measure baryonic acoustic oscillations (BAO). The primary optical signature used in this redshift range comes from the [OII] emission line doublet, which provides a unique redshift identification that can minimize confusion with other single emission lines. To derive the required spectrograph resolution for these redshift surveys, we simulate observations of the [OII] (3727,3729) doublet for various instrument resolutions, and line velocities. We foresee two strategies about the choice of the resolution for future spectrographs for BAO surveys. For bright [OII] emitter surveys ([OII] flux ~30.10^{-17} erg /cm2/s like SDSS-IV/eBOSS), a resolution of R~3300 allows the separation of 90 percent of the doublets. The impact of the sky lines on the completeness in redshift is less than 6 percent. For faint [OII] emitter surveys ([OII] flux ~10.10^{-17} erg /cm2/s like DESi), the detection improves continuously with resolution, so we recommend the highest possible resolution, the limit being given by the number of pixels (4k by 4k) on the detector and the number of spectroscopic channels (2 or 3).Comment: 5 pages, 1 figur

The Extended Baryon Oscillation Spectroscopic Survey: Variability Selection and Quasar Luminosity Function

The SDSS-IV/eBOSS has an extensive quasar program that combines several selection methods. Among these, the photometric variability technique provides highly uniform samples, unaffected by the redshift bias of traditional optical-color selections, when $z= 2.7 - 3.5$ quasars cross the stellar locus or when host galaxy light affects quasar colors at $z < 0.9$. Here, we present the variability selection of quasars in eBOSS, focusing on a specific program that led to a sample of 13,876 quasars to $g_{\rm dered}=22.5$ over a 94.5 deg$^2$ region in Stripe 82, an areal density 1.5 times higher than over the rest of the eBOSS footprint. We use these variability-selected data to provide a new measurement of the quasar luminosity function (QLF) in the redshift range $0.68<z<4.0$. Our sample is denser, reaches deeper than those used in previous studies of the QLF, and is among the largest ones. At the faint end, our QLF extends to $M_g(z\!=\!2)=-21.80$ at low redshift and to $M_g(z\!=\!2)=-26.20$ at $z\sim 4$. We fit the QLF using two independent double-power-law models with ten free parameters each. The first model is a pure luminosity-function evolution (PLE) with bright-end and faint-end slopes allowed to be different on either side of $z=2.2$. The other is a simple PLE at $z<2.2$, combined with a model that comprises both luminosity and density evolution (LEDE) at $z>2.2$. Both models are constrained to be continuous at $z=2.2$. They present a flattening of the bright-end slope at large redshift. The LEDE model indicates a reduction of the break density with increasing redshift, but the evolution of the break magnitude depends on the parameterization. The models are in excellent accord, predicting quasar counts that agree within 0.3\% (resp., 1.1\%) to $g<22.5$ (resp., $g<23$). The models are also in good agreement over the entire redshift range with models from previous studies.Comment: 15 pages, 12 figures, accepted for publication in A&

Characterizing unknown systematics in large scale structure surveys

Photometric large scale structure (LSS) surveys probe the largest volumes in the Universe, but are inevitably limited by systematic uncertainties. Imperfect photometric calibration leads to biases in our measurements of the density fields of LSS tracers such as galaxies and quasars, and as a result in cosmological parameter estimation. Earlier studies have proposed using cross-correlations between different redshift slices or cross-correlations between different surveys to reduce the effects of such systematics. In this paper we develop a method to characterize unknown systematics. We demonstrate that while we do not have sufficient information to correct for unknown systematics in the data, we can obtain an estimate of their magnitude. We define a parameter to estimate contamination from unknown systematics using cross-correlations between different redshift slices and propose discarding bins in the angular power spectrum that lie outside a certain contamination tolerance level. We show that this method improves estimates of the bias using simulated data and further apply it to photometric luminous red galaxies in the Sloan Digital Sky Survey as a case study.Comment: 24 pages, 6 figures; Expanded discussion of results, added figure 2; Version to be published in JCA

Magnetic order and spin dynamics in the proximity of a ferromagnetic quantum critical point: A {\mu}SR study of YbNi4P2

The local 4f-electronic spin dynamics and magnetic order in YbNi4P2 were studied by means of muon-spin relaxation measurements. Zero-field muon-spin relaxation proves static magnetic order with a strongly reduced ordered Yb3+ moment of (2.5-4.6) \times 10-2{\mu}B, below TC = 140 mK. Above TC, the muon-spin polarization P(t,B) is dominated by quasihomogeneous spin fluctuations and exhibits a time-field scaling relation P(t,B) = P(t/B{\gamma}), indicating cooperative critical spin dynamics in the system. At T = 190 mK, slightly above TC, {\gamma} = 0.81(5), suggesting time-scale invariant power-law behavior for the dynamic electronic spin-spin autocorrelation function.Comment: 5 pages, 4 figure

The SDSS-IV extended Baryon Oscillation Spectroscopic Survey: selecting emission line galaxies using the Fisher discriminant

We present a new selection technique of producing spectroscopic target catalogues for massive spectroscopic surveys for cosmology. This work was conducted in the context of the extended Baryon Oscillation Spectroscopic Survey (eBOSS), which will use ~200 000 emission line galaxies (ELGs) at 0.6<zspec<1.0 to obtain a precise baryon acoustic oscillation measurement. Our proposed selection technique is based on optical and near-infrared broad-band filter photometry. We used a training sample to define a quantity, the Fisher discriminant (linear combination of colours), which correlates best with the desired properties of the target: redshift and [OII] flux. The proposed selections are simply done by applying a cut on magnitudes and this Fisher discriminant. We used public data and dedicated SDSS spectroscopy to quantify the redshift distribution and [OII] flux of our ELG target selections. We demonstrate that two of our selections fulfil the initial eBOSS/ELG redshift requirements: for a target density of 180 deg^2, ~70% of the selected objects have 0.6<zspec<1.0 and only ~1% of those galaxies in the range 0.6<zspec<1.0 are expected to have a catastrophic zspec estimate. Additionally, the stacked spectra and stacked deep images for those two selections show characteristic features of star-forming galaxies. The proposed approach using the Fisher discriminant could, however, be used to efficiently select other galaxy populations, based on multi-band photometry, providing that spectroscopic information is available. This technique could thus be useful for other future massive spectroscopic surveys such as PFS, DESI, and 4MOST.Comment: Version published in A&

A Simple Likelihood Method for Quasar Target Selection

We present a new method for quasar target selection using photometric fluxes and a Bayesian probabilistic approach. For our purposes we target quasars using Sloan Digital Sky Survey (SDSS) photometry to a magnitude limit of g=22. The efficiency and completeness of this technique is measured using the Baryon Oscillation Spectroscopic Survey (BOSS) data, taken in 2010. This technique was used for the uniformly selected (CORE) sample of targets in BOSS year one spectroscopy to be realized in the 9th SDSS data release. When targeting at a density of 40 objects per sq-deg (the BOSS quasar targeting density) the efficiency of this technique in recovering z>2.2 quasars is 40%. The completeness compared to all quasars identified in BOSS data is 65%. This paper also describes possible extensions and improvements for this techniqueComment: Updated to accepted version for publication in the Astrophysical Journal. 10 pages, 10 figures, 3 table

On model selection forecasting, Dark Energy and modified gravity

The Fisher matrix approach (Fisher 1935) allows one to calculate in advance how well a given experiment will be able to estimate model parameters, and has been an invaluable tool in experimental design. In the same spirit, we present here a method to predict how well a given experiment can distinguish between different models, regardless of their parameters. From a Bayesian viewpoint, this involves computation of the Bayesian evidence. In this paper, we generalise the Fisher matrix approach from the context of parameter fitting to that of model testing, and show how the expected evidence can be computed under the same simplifying assumption of a gaussian likelihood as the Fisher matrix approach for parameter estimation. With this `Laplace approximation' all that is needed to compute the expected evidence is the Fisher matrix itself. We illustrate the method with a study of how well upcoming and planned experiments should perform at distinguishing between Dark Energy models and modified gravity theories. In particular we consider the combination of 3D weak lensing, for which planned and proposed wide-field multi-band imaging surveys will provide suitable data, and probes of the expansion history of the Universe, such as proposed supernova and baryonic acoustic oscillations surveys. We find that proposed large-scale weak lensing surveys from space should be able readily to distinguish General Relativity from modified gravity models.Comment: 6 pages, 2 figure

Angular clustering properties of the DESI QSO target selection using DR9 Legacy Imaging Surveys

The quasar target selection for the upcoming survey of the Dark Energy Spectroscopic Instrument (DESI) will be fixed for the next 5 yr. The aim of this work is to validate the quasar selection by studying the impact of imaging systematics as well as stellar and galactic contaminants, and to develop a procedure to mitigate them. Density fluctuations of quasar targets are found to be related to photometric properties such as seeing and depth of the Data Release 9 of the DESI Legacy Imaging Surveys. To model this complex relation, we explore machine learning algorithms (random forest and multilayer perceptron) as an alternative to the standard linear regression. Splitting the footprint of the Legacy Imaging Surveys into three regions according to photometric properties, we perform an independent analysis in each region, validating our method using extended Baryon Oscillation Spectroscopic Survey (eBOSS) EZ-mocks. The mitigation procedure is tested by comparing the angular correlation of the corrected target selection on each photometric region to the angular correlation function obtained using quasars from the Sloan Digital Sky Survey (SDSS) Data Release 16. With our procedure, we recover a similar level of correlation between DESI quasar targets and SDSS quasars in two-thirds of the total footprint and we show that the excess of correlation in the remaining area is due to a stellar contamination that should be removed with DESI spectroscopic data. We derive the Limber parameters in our three imaging regions and compare them to previous measurements from SDSS and the 2dF QSO Redshift Survey.This research is supported by the Director, Office of Science, Office of High Energy Physics of the U.S. Department of Energy under contract no. DE-AC02-05CH11231, and by the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility under the same contract; additional support for DESI is provided by the U.S. National Science Foundation, Division of Astronomical Sciences under contract no. AST-0950945 to the NSF’s National Optical–Infrared Astronomy Research Laboratory; the Science and Technology Facilities Council of the United Kingdom; the Gordon and Betty Moore Foundation; the Heising-Simons Foundation; the French Alternative Energies and Atomic Energy Commission (CEA); the National Council of Science and Technology, Mexico; the Ministry of Economy of Spain, and by the DESI Member Institutions. ADM was supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics, under Award Number DE-SC0019022