J/ApJ/852/22ivo://CDS.VizieR/J/ApJ/852/22doi:10.26093/cds/vizier.18520022CDSWalther M.Hennawi J.F.Hiss H.Onorbe J.Lee K.-G.Rorai A.,O'Meara J.2018-10-24T10:47:14Z2018-09-19T05:55:48ZCDS support team

CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France

cds-question@unistra.frquasarsvisible-astronomyspectroscopyredshiftedintergalactic-mediumWe present a new measurement of the Ly{alpha} forest power spectrum at 1.8<z<3.4 using 74 Keck/HIRES and VLT/UVES high-resolution, high-signal-to-noise-ratio quasar spectra. We developed a custom pipeline to measure the power spectrum and its uncertainty, which fully accounts for finite resolution and noise and corrects for the bias induced by masking missing data, damped Ly{alpha} absorption systems, and metal absorption lines. Our measurement results in unprecedented precision on the small-scale modes k>0.02s/km, inaccessible to previous SDSS/BOSS analyses. It is well known that these high-k modes are highly sensitive to the thermal state of the intergalactic medium, but contamination by narrow metal lines is a significant concern. We quantify the effect of metals on the small- scale power and find a modest effect on modes with k<0.1s/km. As a result, by masking metals and restricting to k<0.1s/km, their impact is completely mitigated. We present an end-to-end Bayesian forward-modeling framework whereby mock spectra with the same noise, resolution, and masking as our data are generated from Ly{alpha} forest simulations. These mock spectra are used to build a custom emulator, enabling us to interpolate between a sparse grid of models and perform Markov chain Monte Carlo fits. Our results agree well with BOSS on scales k<0.02s/km, where the measurements overlap. The combination of the percent-level low-k precision of BOSS with our 5%-15% high-k measurements results in a powerful new data set for precisely constraining the thermal history of the intergalactic medium, cosmological parameters, and the nature of dark matter.2018ApJ...852...22Whttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJ/852/22CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toJ/ApJ/457/102 : Lya Forest spectra simulation analysis. I. (Dobrzycki+ 1996)J/ApJS/163/80 : Ly{alpha} forest power spectrum from the SDSS (McDonald+, 2006)J/ApJ/728/23 : GALEX UV-bright high-redshift quasars (Worseck+, 2011)J/A+A/559/A85 : 1D Lya forest power spectrum (Palanque-Delabrouille+, 2013)J/ApJ/788/119 : Properties of the highly ionized gas of quasars (Lehner+, 2014)J/ApJ/803/34 : z~4-10 galaxies from HST legacy fields (Bouwens+, 2015)J/ApJ/814/40 : Nearby galaxy filaments with UV obs. (Wakker+, 2015)J/AJ/150/111 : KODIAQ DR1 (O'Meara+, 2015)J/MNRAS/448/3167 : z>~5 AGN in Chandra Deep Field-South (Weigel+, 2015)J/AJ/154/114 : KODIAQ DR2 (O'Meara+, 2017)J/ApJ/837/106 : UV bckgd photoionization & photoheating rates (Onorbe+, 2017)http://koa.ipac.caltech.edu/applications/KODIAQ/ : KODIAQ archive home pagehttps://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/ApJ/852/22https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/ApJ/852/22http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/ApJ/852/22https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/ApJ/852/22https://vizier.iucaa.in/viz-bin/votable?-source=J/ApJ/852/22http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/ApJ/852/22GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/ApJ/852/22/sample (VLT/UVES spectra from Dall'Aglio+ (2008A&A...491..465D) and keck/HIRES spectra from KODIAQ (O'Meara+ 2015, J/AJ/150/111) used for our analysis (tables 1 and 2))https://vizier.cds.unistra.fr/viz-bin/conesearch/J/ApJ/852/22/sample?https://vizier.iucaa.in/viz-bin/conesearch/J/ApJ/852/22/sample?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/ApJ/852/22/sample?GETtext/xml+votable180.050000true206.1127661-10.59493030.0055555555555555566/4168 5035 5272 6403 6652 7500 7741 8345 8552 8912 9112 9138 9272 10074 10312 10994 11418 11581 11596 11796 16269 16625 16656 17510 17749 17917 18029 18406 19458 19682 21990 25285 25344 25697 25827 26167 26453 27549 27578 27649 27667 27704 27728 27747 27845 28039 28532 28548 28648 29795 31313 34202 34379 34485 34503 34570 35213 35496 35595 35627 36130 36417 38878 40274 40446 43903 44269 46208 46418 46651 47007 47941 48474 48610https://cdsarc.cds.unistra.fr/viz-bin/moc/J/ApJ/852/22?format=asciiOpticaldefaultJ/ApJ/852/22/table6Measured flux power spectrum without masking of metals and after removing the window function due to maskingrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintz[1.8/3.4] Redshiftsrc.redshiftfloatk[0.002/0.4] Modes/kminstr.scaledoublek.P(k)/pi[0.0002/0.2] Power spectrumstat.fit.paramdoublee_k.P(k)/pi[3.6e-05/0.03] Statistical uncertainty in kPk/pistat.errordoubleJ/ApJ/852/22/table7Correlation matrix for elements the measurement in Table 5recnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintz[1.8/3.4] Redshiftsrc.redshiftfloatk[0.002/0.4] Modes/kminstr.scaledoubleR1_j[-0.22/1] Column 1 of the correlation matrixstat.correlationdoubleR2_j[-0.19/1] Column 2 of the correlation matrixstat.correlationdoubleR3_j[-0.2/1] Column 3 of the correlation matrixstat.correlationdoubleR4_j[-0.2/1] Column 4 of the correlation matrixstat.correlationdoubleR5_j[-0.21/1] Column 5 of the correlation matrixstat.correlationdoubleR6_j[-0.22/1] Column 6 of the correlation matrixstat.correlationdoubleR7_j[-0.18/1] Column 7 of the correlation matrixstat.correlationdoubleR8_j[-0.16/1] Column 8 of the correlation matrixstat.correlationdoubleR9_j[-0.15/1] Column 9 of the correlation matrixstat.correlationdoubleR10_j[-0.13/1] Column 10 of the correlation matrixstat.correlationdoubleR11_j[-0.13/1] Column 11 of the correlation matrixstat.correlationdoubleR12_j[-0.14/1] Column 12 of the correlation matrixstat.correlationdoubleR13_j[-0.18/1] Column 13 of the correlation matrixstat.correlationdoubleR14_j[-0.19/1] Column 14 of the correlation matrixstat.correlationdoubleR15_j[-0.17/1] Column 15 of the correlation matrixstat.correlationdoubleR16_j[-0.20/1] Column 16 of the correlation matrixstat.correlationdoubleR17_j[-0.22/1] Column 17 of the correlation matrixstat.correlationdoubleR18_j[-0.22/1] Column 18 of the correlation matrixstat.correlationdoubleR19_j[-0.2/1] Column 19 of the correlation matrixstat.correlationdoubleR20_j[-0.14/1] Column 20 of the correlation matrixstat.correlationdoubleR21_j[-0.1/1] Column 21 of the correlation matrixstat.correlationdoubleR22_j[-0.09/1] Column 22 of the correlation matrixstat.correlationdoubleJ/ApJ/852/22/table8Correlation matrix for elements the measurement in Table 6z[1.8/3.4] Redshiftsrc.redshiftfloatk[0.002/0.4] Modes/kminstr.scaledoubleR1_j[-0.22/1] Column 1 of the correlation matrixstat.correlationdoublerecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintR2_j[-0.19/1] Column 2 of the correlation matrixstat.correlationdoubleR3_j[-0.2/1] Column 3 of the correlation matrixstat.correlationdoubleR4_j[-0.2/1] Column 4 of the correlation matrixstat.correlationdoubleR5_j[-0.21/1] Column 5 of the correlation matrixstat.correlationdoubleR6_j[-0.22/1] Column 6 of the correlation matrixstat.correlationdoubleR7_j[-0.18/1] Column 7 of the correlation matrixstat.correlationdoubleR8_j[-0.16/1] Column 8 of the correlation matrixstat.correlationdoubleR9_j[-0.15/1] Column 9 of the correlation matrixstat.correlationdoubleR10_j[-0.13/1] Column 10 of the correlation matrixstat.correlationdoubleR11_j[-0.13/1] Column 11 of the correlation matrixstat.correlationdoubleR12_j[-0.14/1] Column 12 of the correlation matrixstat.correlationdoubleR13_j[-0.18/1] Column 13 of the correlation matrixstat.correlationdoubleR14_j[-0.19/1] Column 14 of the correlation matrixstat.correlationdoubleR15_j[-0.17/1] Column 15 of the correlation matrixstat.correlationdoubleR16_j[-0.20/1] Column 16 of the correlation matrixstat.correlationdoubleR17_j[-0.22/1] Column 17 of the correlation matrixstat.correlationdoubleR18_j[-0.22/1] Column 18 of the correlation matrixstat.correlationdoubleR19_j[-0.2/1] Column 19 of the correlation matrixstat.correlationdoubleR20_j[-0.14/1] Column 20 of the correlation matrixstat.correlationdoubleR21_j[-0.1/1] Column 21 of the correlation matrixstat.correlationdoubleR22_j[-0.09/1] Column 22 of the correlation matrixstat.correlationdoubleJ/ApJ/852/22/sampleVLT/UVES spectra from Dall'Aglio+ (2008A&A...491..465D) and keck/HIRES spectra from KODIAQ (O'Meara+ 2015, J/AJ/150/111) used for our analysis (tables 1 and 2)SimbadNameSimbad column added by the CDSmeta.idcharf_Name[abc] Flag on Name (1)meta.codecharNameObject namemeta.id;meta.maincharrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintzQSO[2.1/3.8] Quasar redshiftsrc.redshift;pos.heliocentricfloatTelTelescope used (VLT/UVES or Keck/HIRES)meta.id;instrcharS/N[24.6/172] Median S/N per 6km/sstat.snrfloatKODIAQDisplay data from KODIAQ DR1 and DR2 (O'Meara+, 2015, J/AJ/150/111 ; 2017, J/AJ/154/114) and Lehner+, 2014, J/ApJ/788/119 within 10"meta.ref.urlintnullable_RARight Ascension (J2000) from SIMBAD (not part of the original data)degpos.eq.ra;meta.main_DEDeclination (J2000) from SIMBAD (not part of the original data)degpos.eq.dec;meta.mainJ/ApJ/852/22/table5Measured flux power spectrum after masking metals and removing the window function due to maskingrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintz[1.8/3.4] Redshiftsrc.redshiftfloatk[0.002/0.4] Modes/kminstr.scaledoublek.P(k)/pi[0.0002/0.2] Power spectrumstat.fit.paramdoublee_k.P(k)/pi[3.6e-05/0.03] Statistical uncertainty in kPk/pistat.errordouble