The PAU Survey: Photometric redshifts using transfer learning from simulations

In this paper we introduce the \textsc{Deepz} deep learning photometric redshift (photo-$z$) code. As a test case, we apply the code to the PAU survey (PAUS) data in the COSMOS field. \textsc{Deepz} reduces the $\sigma_{68}$ scatter statistic by 50\% at $i_{\rm AB}=22.5$ compared to existing algorithms. This improvement is achieved through various methods, including transfer learning from simulations where the training set consists of simulations as well as observations, which reduces the need for training data. The redshift probability distribution is estimated with a mixture density network (MDN), which produces accurate redshift distributions. Our code includes an autoencoder to reduce noise and extract features from the galaxy SEDs. It also benefits from combining multiple networks, which lowers the photo-$z$ scatter by 10 percent. Furthermore, training with randomly constructed coadded fluxes adds information about individual exposures, reducing the impact of photometric outliers. In addition to opening up the route for higher redshift precision with narrow bands, these machine learning techniques can also be valuable for broad-band surveys.Comment: Accepted versio

Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing

Wide-field imaging surveys such as the Dark Energy Survey (DES) rely on coarse measurements of spectral energy distributions in a few filters to estimate the redshift distribution of source galaxies. In this regime, sample variance, shot noise, and selection effects limit the attainable accuracy of redshift calibration and thus of cosmological constraints. We present a new method to combine wide-field, few-filter measurements with catalogs from deep fields with additional filters and sufficiently low photometric noise to break degeneracies in photometric redshifts. The multi-band deep field is used as an intermediary between wide-field observations and accurate redshifts, greatly reducing sample variance, shot noise, and selection effects. Our implementation of the method uses self-organizing maps to group galaxies into phenotypes based on their observed fluxes, and is tested using a mock DES catalog created from N-body simulations. It yields a typical uncertainty on the mean redshift in each of five tomographic bins for an idealized simulation of the DES Year 3 weak-lensing tomographic analysis of $\sigma_{\Delta z} = 0.007$, which is a 60% improvement compared to the Year 1 analysis. Although the implementation of the method is tailored to DES, its formalism can be applied to other large photometric surveys with a similar observing strategy.Comment: 24 pages, 11 figures; matches version accepted to MNRA

The PAU Survey: Narrow-band image photometry

PAUCam is an innovative optical narrow-band imager mounted at the William Herschel Telescope built for the Physics of the Accelerating Universe Survey (PAUS). Its set of 40 filters results in images that are complex to calibrate, with specific instrumental signatures that cannot be processed with traditional data reduction techniques. In this paper we present two pipelines developed by the PAUS data management team with the objective of producing science-ready catalogues from the uncalibrated raw images. The Nightly pipeline takes care of all image processing, with bespoke algorithms for photometric calibration and scatter-light correction. The Multi-Epoch and Multi-Band Analysis (MEMBA) pipeline performs forced photometry over a reference catalogue to optimize the photometric redshift performance. We verify against spectroscopic observations that the current approach delivers an inter-band photometric calibration of 0.8% across the 40 narrow-band set. The large volume of data produced every night and the rapid survey strategy feedback constraints require operating both pipelines in the Port d'Informaci\'o Cientifica data centre with intense parallelization. While alternative algorithms for further improvements in photo-z performance are under investigation, the image calibration and photometry presented in this work already enable state-of-the-art photometric redshifts down to iAB=23.0.Comment: 32 pages, 26 figures, MNRAS in pres

Growth of Long Range Forward-Backward Multiplicity Correlations with Centrality in Au+Au Collisions at sNN\sqrt{s_{NN}} = 200 GeV

Forward-backward multiplicity correlation strengths have been measured with the STAR detector for Au+Au and $\textit{p+p}$ collisions at $\sqrt{s_{NN}}$ = 200 GeV. Strong short and long range correlations (LRC) are seen in central Au+Au collisions. The magnitude of these correlations decrease with decreasing centrality until only short range correlations are observed in peripheral Au+Au collisions. Both the Dual Parton Model (DPM) and the Color Glass Condensate (CGC) predict the existence of the long range correlations. In the DPM the fluctuation in the number of elementary (parton) inelastic collisions produces the LRC. In the CGC longitudinal color flux tubes generate the LRC. The data is in qualitative agreement with the predictions from the DPM and indicates the presence of multiple parton interactions.Comment: 6 pages, 3 figures The abstract has been slightly modifie

Longitudinal Spin Transfer to Λ\Lambda and Λˉ\bar{\Lambda} Hyperons in Polarized Proton-Proton Collisions at s\sqrt{s} = 200 GeV

The longitudinal spin transfer, $D_{LL}$, from high energy polarized protons to $\Lambda$ and $\bar{\Lambda}$ hyperons has been measured for the first time in proton-proton collisions at $\sqrt{s} = 200 \mathrm{GeV}$ with the STAR detector at RHIC. The measurements cover pseudorapidity, $\eta$, in the range $|\eta| < 1.2$ and transverse momenta, $p_\mathrm{T}$, up to $4 \mathrm{GeV}/c$. The longitudinal spin transfer is found to be $D_{LL}= -0.03\pm 0.13(\mathrm{stat}) \pm 0.04(\mathrm{syst})$ for inclusive $\Lambda$ and $D_{LL} = -0.12 \pm 0.08(\mathrm{stat}) \pm 0.03(\mathrm{syst})$ for inclusive $\bar{\Lambda}$ hyperons with $= 0.5$ and $= 3.7 \mathrm{GeV}/c$. The dependence on $\eta$ and $p_\mathrm{T}$ is presented.Comment: 5 pages, 4 figure

K/pi Fluctuations at Relativistic Energies

We report results for $K/\pi$ fluctuations from Au+Au collisions at $\sqrt{s_{NN}}$ = 19.6, 62.4, 130, and 200 GeV using the STAR detector at the Relativistic Heavy Ion Collider. Our results for $K/\pi$ fluctuations in central collisions show little dependence on the incident energies studied and are on the same order as results observed by NA49 at the Super Proton Synchrotron in central Pb+Pb collisions at $\sqrt{s_{NN}}$ = 12.3 and 17.3 GeV. We also report results for the collision centrality dependence of $K/\pi$ fluctuations as well as results for $K^{+}/\pi^{+}$, $K^{-}/\pi^{-}$, $K^{+}/\pi^{-}$, and $K^{-}/\pi^{+}$ fluctuations. We observe that the $K/\pi$ fluctuations scale with the multiplicity density, $dN/d\eta$, rather than the number of participating nucleons.Comment: 6 pages, 4 figure

Strangeness Enhancement in Cu+Cu and Au+Au Collisions at \sqrt{s_{NN}} = 200 GeV

We report new STAR measurements of mid-rapidity yields for the $\Lambda$, $\bar{\Lambda}$, $K^{0}_{S}$, $\Xi^{-}$, $\bar{\Xi}^{+}$, $\Omega^{-}$, $\bar{\Omega}^{+}$ particles in Cu+Cu collisions at \sNN{200}, and mid-rapidity yields for the $\Lambda$, $\bar{\Lambda}$, $K^{0}_{S}$ particles in Au+Au at \sNN{200}. We show that at a given number of participating nucleons, the production of strange hadrons is higher in Cu+Cu collisions than in Au+Au collisions at the same center-of-mass energy. We find that aspects of the enhancement factors for all particles can be described by a parameterization based on the fraction of participants that undergo multiple collisions