Search Results - "Speagle, Joshua S."

dynesty: a dynamic nested sampling package for estimating Bayesian posteriors and evidences by Speagle, Joshua S

“…ABSTRACT We present dynesty, a public, open-source, python package to estimate Bayesian posteriors and evidences (marginal likelihoods) using the dynamic…”
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A 3D Dust Map Based on Gaia, Pan-STARRS 1, and 2MASS by Green, Gregory M., Schlafly, Edward, Zucker, Catherine, Speagle, Joshua S., Finkbeiner, Douglas

“…We present a new three-dimensional map of dust reddening, based on Gaia parallaxes and stellar photometry from Pan-STARRS 1 and 2MASS. This map covers the sky…”
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How to Measure Galaxy Star Formation Histories. II. Nonparametric Models by Leja, Joel, Carnall, Adam C., Johnson, Benjamin D., Conroy, Charlie, Speagle, Joshua S.

“…Nonparametric star formation histories (SFHs) have long promised to be the "gold standard" for galaxy spectral energy distribution (SED) modeling as they are…”
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A Large Catalog of Accurate Distances to Local Molecular Clouds: The Gaia DR2 Edition by Zucker, Catherine, Speagle, Joshua S., Schlafly, Edward F., Green, Gregory M., Finkbeiner, Douglas P., Goodman, Alyssa A., Alves, João

“…We present a uniform catalog of accurate distances to local molecular clouds informed by the Gaia DR2 data release. Our methodology builds on that of Schlafly…”
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An Older, More Quiescent Universe from Panchromatic SED Fitting of the 3D-HST Survey by Leja, Joel, Johnson, Benjamin D., Conroy, Charlie, Dokkum, Pieter van, Speagle, Joshua S., Brammer, Gabriel, Momcheva, Ivelina, Skelton, Rosalind, Whitaker, Katherine E., Franx, Marijn, Nelson, Erica J.

“…Galaxy observations are influenced by many physical parameters: stellar masses, star formation rates (SFRs), star formation histories (SFHs), metallicities,…”
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A New Census of the 0.2 < z < 3.0 Universe. I. The Stellar Mass Function by Leja, Joel, Speagle, Joshua S., Johnson, Benjamin D., Conroy, Charlie, van Dokkum, Pieter, Franx, Marijn

“…There has been a long-standing factor-of-two tension between the observed star formation rate density and the observed stellar mass buildup after z ∼ 2…”
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Photometric Completeness Modelled with Neural Networks by Harris, William E., Speagle, Joshua S.

“…Abstract In almost any study involving optical/near-infrared photometry, understanding the completeness of detection and recovery is an essential part of the…”
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Mapping Distances across the Perseus Molecular Cloud Using CO Observations, Stellar Photometry, and Gaia DR2 Parallax Measurements by Zucker, Catherine, Schlafly, Edward F., Speagle, Joshua S., Green, Gregory M., Portillo, Stephen K. N., Finkbeiner, Douglas P., Goodman, Alyssa A.

“…We present a new technique to determine distances to major star-forming regions across the Perseus Molecular Cloud, using a combination of stellar photometry,…”
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Should Zeros Count? Modeling the Galaxy–Globular Cluster Scaling Relation with(out) Zero-inflated Count Models by Berek, Samantha C., Eadie, Gwendolyn M., Speagle, Joshua S., Wang, Shu Yan

“…Abstract The scaling relation between the size of a galaxy’s globular cluster (GC) population ( N GC ) and the galaxy’s stellar mass ( M * ) is usually…”
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A New Census of the 0.2 < z < 3.0 Universe. II. The Star-forming Sequence by Leja, Joel, Speagle, Joshua S., Ting, Yuan-Sen, Johnson, Benjamin D., Conroy, Charlie, Whitaker, Katherine E., Nelson, Erica J., Dokkum, Pieter van, Franx, Marijn

“…Abstract We use the panchromatic spectral energy distribution (SED)-fitting code Prospector to measure the galaxy log M *–logSFR relationship (the star-forming…”
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SBI++: Flexible, Ultra-fast Likelihood-free Inference Customized for Astronomical Applications by Wang, Bingjie, Leja, Joel, Villar, V. Ashley, Speagle, Joshua S.

“…Abstract Flagship near-future surveys targeting 10 8 –10 9 galaxies across cosmic time will soon reveal the processes of galaxy assembly in unprecedented…”
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The first-year shear catalog of the Subaru Hyper Suprime-Cam Subaru Strategic Program Survey by Mandelbaum, Rachel, Miyatake, Hironao, Hamana, Takashi, Oguri, Masamune, Simet, Melanie, Armstrong, Robert, Bosch, James, Murata, Ryoma, Lanusse, François, Leauthaud, Alexie, Coupon, Jean, More, Surhud, Takada, Masahiro, Miyazaki, Satoshi, Speagle, Joshua S, Shirasaki, Masato, Sifón, Cristóbal, Huang, Song, Nishizawa, Atsushi J, Medezinski, Elinor, Okura, Yuki, Okabe, Nobuhiro, Czakon, Nicole, Takahashi, Ryuichi, Coulton, William R, Hikage, Chiaki, Komiyama, Yutaka, Lupton, Robert H, Strauss, Michael A, Tanaka, Masayuki, Utsumi, Yousuke

“…Abstract We present and characterize the catalog of galaxy shape measurements that will be used for cosmological weak lensing measurements in the Wide layer of…”
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Stochastic Modeling of Star Formation Histories. III. Constraints from Physically Motivated Gaussian Processes by Iyer, Kartheik G., Speagle, Joshua S., Caplar, Neven, Forbes, John C., Gawiser, Eric, Leja, Joel, Tacchella, Sandro

“…Abstract Galaxy formation and evolution involve a variety of effectively stochastic processes that operate over different timescales. The extended regulator…”
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On the Three-dimensional Structure of Local Molecular Clouds by Zucker, Catherine, Goodman, Alyssa, Alves, João, Bialy, Shmuel, Koch, Eric W., Speagle, Joshua S., Foley, Michael M., Finkbeiner, Douglas, Leike, Reimar, Enßlin, Torsten, Peek, Joshua E. G., Edenhofer, Gordian

“…Abstract We leverage the 1 pc spatial resolution of the Leike et al. three-dimensional (3D) dust map to characterize the 3D structure of nearby molecular…”
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Improving Power Spectrum Estimation Using Multitapering: Efficient Asteroseismic Analyses for Understanding Stars, the Milky Way, and Beyond by Patil, Aarya A., Eadie, Gwendolyn M., Speagle, Joshua S., Thomson, David J.

“…Abstract Asteroseismic time series data have imprints of stellar oscillation modes, whose detection and characterization through time series analysis allows us…”
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The Dark Energy Camera Plane Survey 2 (DECaPS2): More Sky, Less Bias, and Better Uncertainties by Saydjari, Andrew K., Schlafly, Edward F., Lang, Dustin, Meisner, Aaron M., Green, Gregory M., Zucker, Catherine, Zelko, Ioana, Speagle, Joshua S., Daylan, Tansu, Lee, Albert, Valdes, Francisco, Schlegel, David, Finkbeiner, Douglas P.

“…Abstract Deep optical and near-infrared imaging of the entire Galactic plane is essential for understanding our Galaxy’s stars, gas, and dust. The second data…”
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An optically-selected cluster catalog at redshift 0.1 < z < 1.1 from the Hyper Suprime-Cam Subaru Strategic Program S16A data by Oguri, Masamune, Lin, Yen-Ting, Lin, Sheng-Chieh, Nishizawa, Atsushi J, More, Anupreeta, More, Surhud, Hsieh, Bau-Ching, Medezinski, Elinor, Miyatake, Hironao, Jian, Hung-Yu, Lin, Lihwai, Takada, Masahiro, Okabe, Nobuhiro, Speagle, Joshua S, Coupon, Jean, Leauthaud, Alexie, Lupton, Robert H, Miyazaki, Satoshi, Price, Paul A, Tanaka, Masayuki, Chiu, I-Non, Komiyama, Yutaka, Okura, Yuki, Tanaka, Manobu M, Usuda, Tomonori

“…Abstract We present an optically-selected cluster catalog from the Hyper Suprime-Cam (HSC) Subaru Strategic Program. The HSC images are sufficiently deep to…”
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The HERBAL Model: A Hierarchical Errors-in-variables Bayesian Lognormal Hurdle Model for Galactic Globular Cluster Populations by Berek, Samantha C., Eadie, Gwendolyn M., Speagle, Joshua S., Harris, William E.

“…Abstract Galaxy stellar mass is known to be monotonically related to the size of the galaxy’s globular cluster (GC) population for Milky Way sized and larger…”
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Disentangling Stellar Age Estimates from Galactic Chemodynamical Evolution by Shen, Jeff, Speagle, Joshua S., Mackereth, J. Ted, Ting, Yuan-Sen, Bovy, Jo

“…Abstract Stellar ages are key for determining the formation history of the Milky Way, but are difficult to measure precisely. Furthermore, methods that use…”
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As Simple as Possible but No Simpler: Optimizing the Performance of Neural Net Emulators for Galaxy SED Fitting by Mathews, Elijah P., Leja, Joel, Speagle, Joshua S., Johnson, Benjamin D., Gibson, Justus, Nelson, Erica J., Suess, Katherine A., Tacchella, Sandro, Whitaker, Katherine E., Wang, Bingjie

“…Abstract Artificial neural network emulators have been demonstrated to be a very computationally efficient method to rapidly generate galaxy spectral energy…”
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