Browsing by Author "Sullivan, M"
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Item Open Access Electron-Ion Collider: The next QCD frontier: Understanding the glue that binds us all(European Physical Journal A, 2016-09-01) Accardi, A; Albacete, JL; Anselmino, M; Armesto, N; Aschenauer, EC; Bacchetta, A; Boer, D; Brooks, WK; Burton, T; Chang, NB; Deng, WT; Deshpande, A; Diehl, M; Dumitru, A; Dupré, R; Ent, R; Fazio, S; Gao, H; Guzey, V; Hakobyan, H; Hao, Y; Hasch, D; Holt, R; Horn, T; Huang, M; Hutton, A; Hyde, C; Jalilian-Marian, J; Klein, S; Kopeliovich, B; Kovchegov, Y; Kumar, K; Kumerički, K; Lamont, MAC; Lappi, T; Lee, JH; Lee, Y; Levin, EM; Lin, FL; Litvinenko, V; Ludlam, TW; Marquet, C; Meziani, ZE; McKeown, R; Metz, A; Milner, R; Morozov, VS; Mueller, AH; Müller, B; Müller, D; Nadel-Turonski, P; Paukkunen, H; Prokudin, A; Ptitsyn, V; Qian, X; Qiu, JW; Ramsey-Musolf, M; Roser, T; Sabatié, F; Sassot, R; Schnell, G; Schweitzer, P; Sichtermann, E; Stratmann, M; Strikman, M; Sullivan, M; Taneja, S; Toll, T; Trbojevic, D; Ullrich, T; Venugopalan, R; Vigdor, S; Vogelsang, W; Weiss, C; Xiao, BW; Yuan, F; Zhang, YH; Zheng, L© 2016, The Author(s). This White Paper presents the science case of an Electron-Ion Collider (EIC), focused on the structure and interactions of gluon-dominated matter, with the intent to articulate it to the broader nuclear science community. It was commissioned by the managements of Brookhaven National Laboratory (BNL) and Thomas Jefferson National Accelerator Facility (JLab) with the objective of presenting a summary of scientific opportunities and goals of the EIC as a follow-up to the 2007 NSAC Long Range plan. This document is a culmination of a community-wide effort in nuclear science following a series of workshops on EIC physics over the past decades and, in particular, the focused ten-week program on “Gluons and quark sea at high energies” at the Institute for Nuclear Theory in Fall 2010. It contains a brief description of a few golden physics measurements along with accelerator and detector concepts required to achieve them. It has been benefited profoundly from inputs by the users’ communities of BNL and JLab. This White Paper offers the promise to propel the QCD science program in the US, established with the CEBAF accelerator at JLab and the RHIC collider at BNL, to the next QCD frontier.Item Open Access First Cosmology Results using Type Ia Supernovae from the Dark Energy Survey: The Effect of Host Galaxy Properties on Supernova LuminositySmith, M; Sullivan, M; Wiseman, P; Kessler, R; Scolnic, D; Brout, D; D'Andrea, CB; Davis, TM; Foley, RJ; Frohmaier, C; Galbany, L; Gupta, RR; Gutiérrez, CP; Hinton, SR; Kelsey, L; Lidman, C; Macaulay, E; Möller, A; Nichol, RC; Nugent, P; Palmese, A; Pursiainen, M; Sako, M; Swann, E; Thomas, RC; Tucker, BE; Vincenzi, M; Carollo, D; Lewis, GF; Sommer, NE; Abbott, TMC; Aguena, M; Allam, S; Avila, S; Bertin, E; Bhargava, S; Brooks, D; Buckley-Geer, E; Burke, DL; Rosell, AC; Kind, MC; Costanzi, M; da Costa, LN; de Vicente, J; Desai, S; Diehl, HT; Doel, P; Eifler, TF; Everett, S; Flaugher, B; Fosalba, P; Frieman, J; García-Bellido, J; Gaztanaga, E; Glazebrook, K; Gruen, D; Gruendl, RA; Gschwend, J; Gutierrez, G; Hartley, WG; Hollowood, DL; Honscheid, K; James, DJ; Krause, E; Kuehn, K; Kuropatkin, N; Lima, M; MacCrann, N; Maia, MAG; Marshall, JL; Martini, P; Melchior, P; Menanteau, F; Miquel, R; Paz-Chinchón, F; Plazas, AA; Romer, AK; Roodman, A; Rykoff, ES; Sanchez, E; Scarpine, V; Schubnell, M; Serrano, S; Sevilla-Noarbe, I; Suchyta, E; Swanson, MEC; Tarle, G; Thomas, D; Tucker, DL; Varga, TN; Walker, ARWe present improved photometric measurements for the host galaxies of 206 spectroscopically confirmed type Ia supernovae discovered by the Dark Energy Survey Supernova Program (DES-SN) and used in the first DES-SN cosmological analysis. Fitting spectral energy distributions to the $griz$ photometric measurements of the DES-SN host galaxies, we derive stellar masses and star-formation rates. For the DES-SN sample, when considering a 5D ($z$, $x_1$, $c$, $\alpha$, $\beta$) bias correction, we find evidence of a Hubble residual `mass step', where SNe Ia in high mass galaxies ($>10^{10} \textrm{M}_{\odot}$) are intrinsically more luminous (after correction) than their low mass counterparts by $\gamma=0.040\pm0.019$mag. This value is larger by $0.031$mag than the value found in the first DES-SN cosmological analysis. This difference is due to a combination of updated photometric measurements and improved star formation histories and is not from host-galaxy misidentification. When using a 1D (redshift-only) bias correction the inferred mass step is larger, with $\gamma=0.066\pm0.020$mag. The 1D-5D $\gamma$ difference for DES-SN is $0.026\pm0.009$mag. We show that this difference is due to a strong correlation between host galaxy stellar mass and the $x_1$ component of the 5D distance-bias correction. To better understand this effect, we include an intrinsic correlation between light-curve width and stellar mass in simulated SN Ia samples. We show that a 5D fit recovers $\gamma$ with $-9$mmag bias compared to a $+2$mmag bias for a 1D fit. This difference can explain part of the discrepancy seen in the data. Improvements in modeling correlations between galaxy properties and SN is necessary to determine the implications for $\gamma$ and ensure unbiased precision estimates of the dark energy equation-of-state as we enter the era of LSST.Item Open Access SNIa-Cosmology Analysis Results from Simulated LSST Images: from Difference Imaging to Constraints on Dark EnergySánchez, B; Kessler, R; Scolnic, D; Armstrong, B; Biswas, R; Bogart, J; Chiang, J; Cohen-Tanugi, J; Fouchez, D; Gris, Ph; Heitmann, K; Hložek, R; Jha, S; Kelly, H; Liu, S; Narayan, G; Racine, B; Rykoff, E; Sullivan, M; Walter, C; Wood-Vasey, M; Collaboration, The LSST Dark Energy ScienceThe Vera Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to process ${\sim}10^6$ transient detections per night. For precision measurements of cosmological parameters and rates, it is critical to understand the detection efficiency, magnitude limits, artifact contamination levels, and biases in the selection and photometry. Here we rigorously test the LSST Difference Image Analysis (DIA) pipeline using simulated images from the Rubin Observatory LSST Dark Energy Science Collaboration (DESC) Data Challenge (DC2) simulation for the Wide-Fast-Deep (WFD) survey area. DC2 is the first large-scale (300 deg$^2$) image simulation of a transient survey that includes realistic cadence, variable observing conditions, and CCD image artifacts. We analyze ${\sim}$15 deg$^2$ of DC2 over a 5-year time-span in which artificial point-sources from Type Ia Supernovae (SNIa) light curves have been overlaid onto the images. We measure the detection efficiency as a function of Signal-to-Noise Ratio (SNR) and find a $50\%$ efficiency at $\rm{SNR}=5.8$. The magnitude limits for each filter are: $u=23.66$, $g=24.69$, $r=24.06$, $i=23.45$, $z=22.54$, $y=21.62$ $\rm{mag}$. The artifact contamination is $\sim90\%$ of detections, corresponding to $\sim1000$ artifacts/deg$^2$ in $g$ band, and falling to 300 per deg$^2$ in $y$ band. The photometry has biases $<1\%$ for magnitudes $19.5 < m <23$. Our DIA performance on simulated images is similar to that of the Dark Energy Survey pipeline applied to real images. We also characterize DC2 image properties to produce catalog-level simulations needed for distance bias corrections. We find good agreement between DC2 data and simulations for distributions of SNR, redshift, and fitted light-curve properties. Applying a realistic SNIa-cosmology analysis for redshifts $z<1$, we recover the input cosmology parameters to within statistical uncertainties.Item Open Access Supernova Host Galaxies in the Dark Energy Survey: I. Deep Coadds, Photometry, and Stellar MassesWiseman, P; Smith, M; Childress, M; Kelsey, L; Möller, A; Gupta, RR; Swann, E; Angus, CR; Brout, D; Davis, TM; Foley, RJ; Frohmaier, C; Galbany, L; Gutiérrez, CP; Inserra, C; Kessler, R; Lewis, GF; Lidman, C; Macaulay, E; Nichol, RC; Pursiainen, M; Sako, M; Scolnic, D; Sommer, NE; Sullivan, M; Tucker, BE; Abbott, TMC; Aguena, M; Allam, S; Avila, S; Bertin, E; Brooks, D; Buckley-Geer, E; Burke, DL; Rosell, AC; Carollo, D; Kind, MC; da Costa, LN; de Vicente, J; Desai, S; Diehl, HT; Doel, P; Eifler, TF; Everett, S; Fosalba, P; Frieman, J; García-Bellido, J; Gaztanaga, E; Gerdes, DW; Gill, MSS; Glazebrook, K; Gruendl, RA; Gschwend, J; Hartley, WG; Hinton, SR; Hollowood, DL; Honscheid, K; James, DJ; Kuehn, K; Kuropatkin, N; Lima, M; Maia, MAG; March, M; Martini, P; Melchior, P; Menanteau, F; Miquel, R; Ogando, RLC; Paz-Chinchón, F; Plazas, AA; Romer, AK; Roodman, A; Sanchez, E; Scarpine, V; Serrano, S; Suchyta, E; Swanson, MEC; Tarle, G; Thomas, D; Tucker, DL; Varga, TN; Walker, AR; Wilkinson, RDThe five-year Dark Energy Survey supernova programme (DES-SN) is one of the largest and deepest transient surveys to date in terms of volume and number of supernovae. Identifying and characterising the host galaxies of transients plays a key role in their classification, the study of their formation mechanisms, and the cosmological analyses. To derive accurate host galaxy properties, we create depth-optimised coadds using single-epoch DES-SN images that are selected based on sky and atmospheric conditions. For each of the five DES-SN seasons, a separate coadd is made from the other 4 seasons such that each SN has a corresponding deep coadd with no contaminating SN emission. The coadds reach limiting magnitudes of order $\sim 27$ in $g$-band, and have a much smaller magnitude uncertainty than the previous DES-SN host templates, particularly for faint objects. We present the resulting multi-band photometry of host galaxies for samples of spectroscopically confirmed type Ia (SNe Ia), core-collapse (CCSNe), and superluminous (SLSNe) as well as rapidly evolving transients (RETs) discovered by DES-SN. We derive host galaxy stellar masses and probabilistically compare stellar-mass distributions to samples from other surveys. We find that the DES spectroscopically confirmed sample of SNe Ia selects preferentially fewer high mass hosts at high redshift compared to other surveys, while at low redshift the distributions are consistent. DES CCSNe and SLSNe hosts are similar to other samples, while RET hosts are unlike the hosts of any other transients, although these differences have not been disentangled from selection effects.Item Open Access Supernova Siblings: Assessing the Consistency of Properties of Type Ia Supernovae that Share the Same Parent GalaxiesScolnic, D; Smith, M; Massiah, A; Wiseman, P; Brout, D; Kessler, R; Davis, TM; Foley, RJ; Galbany, L; Hinton, SR; Hounsell, R; Kelsey, L; Lidman, C; Macaulay, E; Morgan, R; Nichol, RC; Möller, A; Popovic, B; Sako, M; Sullivan, M; Thomas, BP; Tucker, BE; Abbott, TMC; Aguena, M; Allam, S; Annis, J; Avila, S; Bechtol, K; Bertin, E; Brooks, D; Burke, DL; Rosell, AC; Carollo, D; Kind, MC; Carretero, J; Costanzi, M; Da Costa, LN; De Vicente, J; Desai, S; Diehl, HT; Doel, P; Drlica-Wagner, A; Eckert, K; Eifler, TF; Everett, S; Flaugher, B; Fosalba, P; Frieman, J; Garciá-Bellido, J; Gaztanaga, E; Gerdes, DW; Glazebrook, K; Gruen, D; Gruendl, RA; Gschwend, J; Gutierrez, G; Hartley, WG; Hollowood, DL; Honscheid, K; James, DJ; Kuehn, K; Kuropatkin, N; Lewis, GF; Li, TS; Lima, M; Maia, MAG; Marshall, JL; Menanteau, F; Miquel, R; Palmese, A; Paz-Chinchón, F; Plazas, AA; Pursiainen, M; Sanchez, E; Scarpine, V; Schubnell, M; Serrano, S; Sevilla-Noarbe, I; Sommer, NE; Suchyta, E; Swanson, MEC; Tarle, G; Varga, TN; Walker, AR; Wilkinson, RWhile many studies have shown a correlation between properties of the light curves of Type Ia SN (SNe Ia) and properties of their host galaxies, it remains unclear what is driving these correlations. We introduce a new direct method to study these correlations by analyzing `parent' galaxies that host multiple SNe Ia 'siblings'. Here, we search the Dark Energy Survey SN sample, one of the largest samples of discovered SNe, and find 8 galaxies that hosted two likely Type Ia SNe. Comparing the light-curve properties of these SNe and recovered distances from the light curves, we find no better agreement between properties of SNe in the same galaxy as any random pair of galaxies, with the exception of the SN light-curve stretch. We show at $2.8\sigma$ significance that at least 1/2 of the intrinsic scatter of SNe Ia distance modulus residuals is not from common host properties. We also discuss the robustness with which we could make this evaluation with LSST, which will find $100\times$ more pairs of galaxies, and pave a new line of study on the consistency of Type Ia supernovae in the same parent galaxies. Finally, we argue that it is unlikely some of these SNe are actually single, lensed SN with multiple images.Item Open Access The Dark Energy Survey Supernova Program: Cosmological biases from supernova photometric classificationVincenzi, M; Sullivan, M; Möller, A; Armstrong, P; Bassett, BA; Brout, D; Carollo, D; Carr, A; Davis, TM; Frohmaier, C; Galbany, L; Glazebrook, K; Graur, O; Kelsey, L; Kessler, R; Kovacs, E; Lewis, GF; Lidman, C; Malik, U; Nichol, RC; Popovic, B; Sako, M; Scolnic, D; Smith, M; Taylor, G; Tucker, BE; Wiseman, P; Aguena, M; Allam, S; Annis, J; Asorey, J; Bacon, D; Bertin, E; Brooks, D; Burke, DL; Rosell, A Carnero; Carretero, J; Castander, FJ; Costanzi, M; Costa, LN da; Pereira, MES; Vicente, J De; Desai, S; Diehl, HT; Doel, P; Everett, S; Ferrero, I; Flaugher, B; Fosalba, P; Frieman, J; García-Bellido, J; Gerdes, DW; Gruen, D; Gutierrez, G; Hinton, SR; Hollowood, DL; Honscheid, K; James, DJ; Kuehn, K; Kuropatkin, N; Lahav, O; Li, TS; Lima, M; Maia, MAG; Marshall, JL; Miquel, R; Morgan, R; Ogando, RLC; Palmese, A; Paz-Chinchón, F; Pieres, A; Malagón, AA Plazas; Reil, K; Roodman, A; Sanchez, E; Schubnell, M; Serrano, S; Sevilla-Noarbe, I; Suchyta, E; Tarle, G; To, C; Varga, TN; Weller, J; Wilkinson, RDCosmological analyses of samples of photometrically-identified Type Ia supernovae (SNe Ia) depend on understanding the effects of 'contamination' from core-collapse and peculiar SN Ia events. We employ a rigorous analysis on state-of-the-art simulations of photometrically identified SN Ia samples and determine cosmological biases due to such 'non-Ia' contamination in the Dark Energy Survey (DES) 5-year SN sample. As part of the analysis, we test on our DES simulations the performance of SuperNNova, a photometric SN classifier based on recurrent neural networks. Depending on the choice of non-Ia SN models in both the simulated data sample and training sample, contamination ranges from 0.8-3.5 %, with the efficiency of the classification from 97.7-99.5 %. Using the Bayesian Estimation Applied to Multiple Species (BEAMS) framework and its extension 'BEAMS with Bias Correction' (BBC), we produce a redshift-binned Hubble diagram marginalised over contamination and corrected for selection effects and we use it to constrain the dark energy equation-of-state, $w$. Assuming a flat universe with Gaussian $\Omega_M$ prior of $0.311\pm0.010$, we show that biases on $w$ are $<0.008$ when using SuperNNova and accounting for a wide range of non-Ia SN models in the simulations. Systematic uncertainties associated with contamination are estimated to be at most $\sigma_{w, \mathrm{syst}}=0.004$. This compares to an expected statistical uncertainty of $\sigma_{w,\mathrm{stat}}=0.039$ for the DES-SN sample, thus showing that contamination is not a limiting uncertainty in our analysis. We also measure biases due to contamination on $w_0$ and $w_a$ (assuming a flat universe), and find these to be $<$0.009 in $w_0$ and $<$0.108 in $w_a$, hence 5 to 10 times smaller than the statistical uncertainties expected from the DES-SN sample.Item Open Access The Dark Energy Survey Supernova Program: Modelling selection efficiency and observed core collapse supernova contaminationVincenzi, M; Sullivan, M; Graur, O; Brout, D; Davis, TM; Frohmaier, C; Galbany, L; Gutiérrez, CP; Hinton, SR; Hounsell, R; Kelsey, L; Kessler, R; Kovacs, E; Kuhlmann, S; Lasker, J; Lidman, C; Möller, A; Nichol, RC; Sako, M; Scolnic, D; Smith, M; Swann, E; Wiseman, P; Asorey, J; Lewis, GF; Sharp, R; Tucker, BE; Aguena, M; Allam, S; Avila, S; Bertin, E; Brooks, D; Burke, DL; Rosell, AC; Kind, MC; Carretero, J; Castander, FJ; Choi, A; Costanzi, M; Da Costa, LN; Pereira, MES; De Vicente, J; Desai, S; Diehl, HT; Doel, P; Everett, S; Ferrero, I; Fosalba, P; Frieman, J; Garciá-Bellido, J; Gaztanaga, E; Gerdes, DW; Gruen, D; Gruendl, RA; Gutierrez, G; Hollowood, DL; Honscheid, K; Hoyle, B; James, DJ; Kuehn, K; Kuropatkin, N; Maia, MAG; Martini, P; Menanteau, F; Miquel, R; Morgan, R; Palmese, A; Paz-Chinchón, F; Plazas, AA; Romer, AK; Sanchez, E; Scarpine, V; Serrano, S; Sevilla-Noarbe, I; Soares-Santos, M; Suchyta, E; Tarle, G; Thomas, D; To, C; Varga, TN; Walker, AR; Wilkinson, RDThe analysis of current and future cosmological surveys of type Ia supernovae (SNe Ia) at high-redshift depends on the accurate photometric classification of the SN events detected. Generating realistic simulations of photometric SN surveys constitutes an essential step for training and testing photometric classification algorithms, and for correcting biases introduced by selection effects and contamination arising from core collapse SNe in the photometric SN Ia samples. We use published SN time-series spectrophotometric templates, rates, luminosity functions and empirical relationships between SNe and their host galaxies to construct a framework for simulating photometric SN surveys. We present this framework in the context of the Dark Energy Survey (DES) 5-year photometric SN sample, comparing our simulations of DES with the observed DES transient populations. We demonstrate excellent agreement in many distributions, including Hubble residuals, between our simulations and data. We estimate the core collapse fraction expected in the DES SN sample after selection requirements are applied and before photometric classification. After testing different modelling choices and astrophysical assumptions underlying our simulation, we find that the predicted contamination varies from 5.8 to 9.3 per cent, with an average of 7.0 per cent and r.m.s. of 1.1 per cent. Our simulations are the first to reproduce the observed photometric SN and host galaxy properties in high-redshift surveys without fine-tuning the input parameters. The simulation methods presented here will be a critical component of the cosmology analysis of the DES photometric SN Ia sample: correcting for biases arising from contamination, and evaluating the associated systematic uncertainty.