14771019
Pair production and optical lasers.
Electron-positron pair creation in a standing wave is explored using a parameter-free quantum kinetic equation. Field strengths and frequencies corresponding to modern optical lasers induce a material polarization of the QED vacuum, which may be characterized as a plasma of e+e- quasiparticle pairs with a density of approximately 10(20) cm-3. The plasma vanishes almost completely when the laser field is zero, leaving a very small residual pair density n(r) which is the true manifestation of vacuum decay. The average pair density per period is proportional to the laser intensity but independent of the frequency nu. The density of residual pairs also grows with laser intensity but n(r) proportional to nu(2). With optical lasers at the forefront of the current generation, these dynamical QED vacuum effects can plausibly generate 5-10 observable two-photon annihilation events per laser pulse.
17661148
Pair creation and an x-ray free electron laser.
Using a quantum kinetic equation we study the possibility that focused beams at proposed x-ray free electron laser facilities can initiate spontaneous electron-positron pair production from the QED vacuum. Under conditions reckoned achievable at planned facilities, repeated cycles of particle creation and annihilation will take place in tune with the laser frequency. The peak particle number density is insensitive to this frequency, and one can anticipate the production of a few hundred particle pairs per laser period.
119080896
Concerning the quark condensate
A continuum expression for the trace of the massive dressed-quark propagator is used to explicate a connection between the infrared limit of the QCD Dirac operator's spectrum and the quark condensate appearing in the operator product expansion. This connection is verified via comparison with a lattice-QCD simulation. The pseudoscalar vacuum polarization provides a good approximation to the condensate over a larger range of current-quark masses.
54796299
Galaxy-Mass Correlations on 10 Mpc Scales in the Deep Lens Survey
We examine the projected correlation of galaxies with mass from small scales (<few hundred kpc), where individual dark matter halos dominate, out to 15 Mpc, where correlated large-scale structure dominates. We investigate these profiles as a function of galaxy luminosity and redshift. Selecting 0.8 million galaxies in the Deep Lens Survey, we use photometric redshifts and stacked weak gravitational lensing shear tomography out to radial scales of 1° from the centers of foreground galaxies. We detect correlated mass density from multiple halos and large-scale structure at radii larger than the virial radius and find the first observational evidence for growth in the galaxy-mass correlation on 10 Mpc scales with decreasing redshift and fixed range of luminosity. For a fixed range of redshift, we find a scaling of projected halo mass with rest-frame luminosity similar to previous studies at lower redshift. We control systematic errors in shape measurement and photometric redshift, enforce volume completeness through absolute magnitude cuts, and explore residual sample selection effects via simulations.
118867010
Inferring the redshift distribution of the cosmic infrared background
Cross-correlating the Planck High Frequency Instrument (HFI) maps against quasars from the Sloan Digital Sky Survey (SDSS) DR7, we estimate the intensity distribution of the Cosmic Infrared Background (CIB) over the redshift range 0 < z < 5.We detect redshift-dependent spatial cross-correlations between the two datasets using the 857, 545 and 353 GHz channels and we obtain upper limits at 217 GHz consistent with expectations. At all frequencies with detectable signal we infer a redshift distribution peaking around z ~ 1.2 and find the recovered spectrum to be consistent with emission arising from star forming galaxies. By assuming simple modified blackbody and Kennicutt relations, we estimate dust and star formation rate density as a function of redshift, finding results consistent with earlier multiwavelength measurements over a large portion of cosmic history. However, we note that, lacking mid-infrared coverage, we are not able to make an accurate determination of the mean temperature for the dust responsible for the CIB. Our results demonstrate that clustering-based redshift inference is a valuable tool for measuring the entire evolution history of the cosmic star formation rate from a single and homogeneous dataset.
118578896
CHARACTERIZING AND PROPAGATING MODELING UNCERTAINTIES IN PHOTOMETRICALLY-DERIVED REDSHIFT DISTRIBUTIONS
The uncertainty in the redshift distributions of galaxies has a significant potential impact on the cosmological parameter values inferred from multi-band imaging surveys. The accuracy of the photometric redshifts measured in these surveys depends not only on the quality of the flux data, but also on a number of modeling assumptions that enter into both the training set and spectral energy distribution (SED) fitting methods of photometric redshift estimation. In this work we focus on the latter, considering two types of modeling uncertainties: uncertainties in the SED template set and uncertainties in the magnitude and type priors used in a Bayesian photometric redshift estimation method. We find that SED template selection effects dominate over magnitude prior errors. We introduce a method for parameterizing the resulting ignorance of the redshift distributions, and for propagating these uncertainties to uncertainties in cosmological parameters.
16575011
Spectroscopic Needs for Imaging Dark Energy Experiments
Ongoing and near-future imaging-based dark energy experiments are critically dependent upon photometric redshifts (a.k.a. photo-z's): i.e., estimates of the redshifts of objects based only on flux information obtained through broad filters. Higher-quality, lower-scatter photo-z's will result in smaller random errors on cosmological parameters; while systematic errors in photometric redshift estimates, if not constrained, may dominate all other uncertainties from these experiments. The desired optimization and calibration is dependent upon spectroscopic measurements for secure redshift information; this is the key application of galaxy spectroscopy for imaging-based dark energy experiments. Hence, to achieve their full potential, imaging-based experiments will require large sets of objects with spectroscopically-determined redshifts, for two purposes: Training: Objects with known redshift are needed to map out the relationship between object color and z (or, equivalently, to determine empirically-calibrated templates describing the rest-frame spectra of the full range of galaxies, which may be used to predict the color-z relation). The ultimate goal of training is to minimize each moment of the distribution of differences between photometric redshift estimates and the true redshifts of objects, making the relationship between them as tight as possible. The larger and more complete our "training set" of spectroscopic redshifts is, the smaller the RMS photo-z errors should be, increasing the constraining power of imaging experiments. Requirements: Spectroscopic redshift measurements for similar to 30,000 objects over >similar to 15 widely-separated regions, each at least similar to 20 arcmin in diameter, and reaching the faintest objects used in a given experiment, will likely be necessary if photometric redshifts are to be trained and calibrated with conventional techniques. Larger, more complete samples (i.e., with longer exposure times) can improve photo-z algorithms and reduce scatter further, enhancing the science return from planned experiments greatly (increasing the Dark Energy Task Force figure of merit by up to similar to 50%). Options: This spectroscopy will most efficiently be done by covering as much of the optical and near-infrared spectrum as possible at modestly high spectral resolution (lambda/Delta lambda > similar to 3000), while maximizing the telescope collecting area, field of view on the sky, and multiplexing of simultaneous spectra. The most efficient instrument for this would likely be either the proposed GMACS/MANIFEST spectrograph for the Giant Magellan Telescope or the OPTIMOS spectrograph for the European Extremely Large Telescope, depending on actual properties when built. The PFS spectrograph at Subaru would be next best and available considerably earlier, c. 2018; the proposed ngCFHT and SSST telescopes would have similar capabilities but start later. Other key options, in order of increasing total time required, are the WFOS spectrograph at TMT, MOONS at the VLT, and DESI at the Mayall 4 m telescope (or the similar 4MOST and WEAVE projects); of these, only DESI, MOONS, and PFS are expected to be available before 2020. Table 2-3 of this white paper summarizes the observation time required at each facility for strawman training samples. To attain secure redshift measurements for a high fraction of targeted objects and cover the full redshift span of future experiments, additional near-infrared spectroscopy will also be required; this is best done from space, particularly with WFIRST-2.4 and JWST. Calibration: The first several moments of redshift distributions (the mean, RMS redshift dispersion, etc.), must be known to high accuracy for cosmological constraints not to be systematics-dominated (equivalently, the moments of the distribution of differences between photometric and true redshifts could be determined instead). The ultimate goal of calibration is to characterize these moments for every subsample used in analyses - i.e., to minimize the uncertainty in their mean redshift, RMS dispersion, etc. - rather than to make the moments themselves small. Calibration may be done with the same spectroscopic dataset used for training if that dataset is extremely high in redshift completeness (i.e., no populations of galaxies to be used in analyses are systematically missed). Accurate photo-z calibration is necessary for all imaging experiments. Requirements: If extremely low levels of systematic incompleteness (<similar to 0.1%) are attained in training samples, the same datasets described above should be sufficient for calibration. However, existing deep spectroscopic surveys have failed to yield secure redshifts for 30-60% of targets, so that would require very large improvements over past experience. This incompleteness would be a limiting factor for training, but catastrophic for calibration. If <similar to 0.1% incompleteness is not attainable, the best known option for calibration of photometric redshifts is to utilize cross-correlation statistics in some form. The most direct method for this uses cross-correlations between positions on the sky of bright objects of known spectroscopic redshift with the sample of objects that we wish to calibrate the redshift distribution for, measured as a function of spectroscopic z. For such a calibration, redshifts of similar to 100,000 objects over at least several hundred square degrees, spanning the full redshift range of the samples used for dark energy, would be necessary. Options: The proposed BAO experiment eBOSS would provide sufficient spectroscopy for basic calibrations, particularly for ongoing and near-future imaging experiments. The planned DESI experiment would provide excellent calibration with redundant cross-checks, but will start after the conclusion of some imaging projects. An extension of DESI to the Southern hemisphere would provide the best possible calibration from cross-correlation methods for DES and LSST. We thus anticipate that our two primary needs for spectroscopy - training and calibration of photometric redshifts - will require two separate solutions. For ongoing and future projects to reach their full potential, new spectroscopic samples of faint objects will be needed for training; those new samples may be suitable for calibration, but the latter possibility is uncertain. In contrast, wide-area samples of bright objects are poorly suited for training, but can provide high-precision calibrations via cross-correlation techniques. Additional training/calibration redshifts and/or host galaxy spectroscopy would enhance the use of supernovae and galaxy clusters for cosmology. We also summarize additional work on photometric redshift techniques that will be needed to prepare for data from ongoing and future dark energy experiments. (C) 2014 Elsevier B.V. All rights reserved.
119259169
Recovering redshift distributions with cross-correlations: pushing the boundaries
Determining accurate redshift distributions for very large samples of objects has become increasingly important in cosmology. We investigate the impact of extending cross-correlation based redshift distribution recovery methods to include small scale clustering information. The major concern in such work is the ability to disentangle the amplitude of the underlying redshift distribution from the influence of evolving galaxy bias. Using multiple simulations covering a variety of galaxy bias evolution scenarios, we demonstrate reliable redshift recoveries using linear clustering assumptions well into the non-linear regime for redshift distributions of narrow redshift width. Including information from intermediate physical scales balances the increased information available from clustering and the residual bias incurred from relaxing of linear constraints. We discuss how breaking a broad sample into tomographic bins can improve estimates of the redshift distribution, and present a simple bias removal technique using clustering information from the spectroscopic sample alone.