Search Results - "J. B. Jewell"

Joint Bayesian Component Separation and CMB Power Spectrum Estimation by Eriksen, H. K, Jewell, J. B, Dickinson, C, Banday, A. J, Górski, K. M, Lawrence, C. R

“…We describe and implement an exact, flexible, and computationally efficient algorithm for joint component separation and CMB power spectrum estimation,…”
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COSMOLOGICAL PARAMETERS FROM CMB MAPS WITHOUT LIKELIHOOD APPROXIMATION by Racine, B., Jewell, J. B., Eriksen, H. K., Wehus, I. K.

“…ABSTRACT We propose an efficient Bayesian Markov chain Monte Carlo (MCMC) algorithm for estimating cosmological parameters from cosmic microwave background…”
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Estimation of Polarized Power Spectra by Gibbs Sampling by Larson, D. L, Eriksen, H. K, Wandelt, B. D, Górski, K. M, Huey, Greg, Jewell, J. B, O’Dwyer, I. J

“…Earlier papers introduced a method of accurately estimating the angular cosmic microwave background temperature power spectrum based on Gibbs sampling. Here we…”
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Bayesian Component Separation and Cosmic Microwave Background Estimation for the Five-Year WMAP Temperature Data by Dickinson, C, Eriksen, H. K, Banday, A. J, Jewell, J. B, Górski, K. M, Huey, G, Lawrence, C. R, O'Dwyer, I. J, Wandelt, B. D

“…A well-tested and validated Gibbs sampling code, that performs component separation and cosmic microwave background (CMB) power spectrum estimation, was…”
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The Joint Large-Scale Foreground-CMB Posteriors of the 3 Year WMAP Data by Eriksen, H. K, Dickinson, C, Jewell, J. B, Banday, A. J, Górski, K. M, Lawrence, C. R

“…Using a Gibbs sampling algorithm for joint CMB estimation and component separation, we compute the large-scale CMB and foreground posteriors of the 3 yr WMAP…”
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A Reanalysis of the 3 Year Wilkinson Microwave Anisotropy Probe Temperature Power Spectrum and Likelihood by Eriksen, H. K, Huey, Greg, Saha, R, Hansen, F. K, Dick, J, Banday, A. J, Górski, K. M, Jain, P, Jewell, J. B, Knox, L, Larson, D. L, O’Dwyer, I. J, Souradeep, T, Wandelt, B. D

“…We analyze the 3 yr Wilkinson Microwave Anisotropy Probe (WMAP) temperature anisotropy data seeking to confirm the power spectrum and likelihoods published by…”
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Cosmic Microwave Background Likelihood Approximation by a Gaussianized Blackwell-Rao Estimator by Rudjord, Ø, Groeneboom, N. E, Eriksen, H. K, Huey, Greg, Górski, K. M, Jewell, J. B

“…We introduce a new cosmic microwave background (CMB) temperature likelihood approximation called the Gaussianized Blackwell-Rao estimator. This estimator is…”
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Bayesian Analysis of the Low-Resolution Polarized 3 Year WMAP Sky Maps by Eriksen, H. K, Huey, Greg, Banday, A. J, Górski, K. M, Jewell, J. B, O’Dwyer, I. J, Wandelt, B. D

“…We apply a previously developed Gibbs sampling framework to the foreground-corrected 3 yr WMAP polarization data and compute the power spectrum and residual…”
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Bayesian Power Spectrum Analysis of the First-Year Wilkinson Microwave Anisotropy Probe Data by O’Dwyer, I. J, Eriksen, H. K, Wandelt, B. D, Jewell, J. B, Larson, D. L, Górski, K. M, Banday, A. J, Levin, S, Lilje, P. B

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A Markov Chain Monte Carlo Algorithm for Analysis of Low Signal-To-Noise Cosmic Microwave Background Data by Jewell, J. B, Eriksen, H. K, Wandelt, B. D, O'Dwyer, I. J, Huey, Greg, Górski, K. M

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From BeyondPlanck to Cosmoglobe: Open Science, Reproducibility, and Data Longevity by Gerakakis, S., Brilenkov, M., Ieronymaki, M., San, M., Watts, D. J., Andersen, K. J., Aurlien, R., Banerji, R., Basyrov, A., Bersanelli, M., Bertocco, S., Carbone, M., Colombo, L. P. L., Eriksen, H. K., Eskilt, J. R., Foss, M. K., Franceschet, C., Fuskeland, U., Galeotta, S., Galloway, M., Gjerløw, E., Hensley, B., Herman, D., Iacobellis, M., Ihle, H. T., Jewell, J. B., Karakci, A., Keihänen, E., Keskitalo, R., Lunde, J. G. S., Maggio, G., Maino, D., Maris, M., Paradiso, S., Reinecke, M., Stutzer, N.-O., Suur-Uski, A.-S., Svalheim, T. L., Tavagnacco, D., Thommesen, H., Wehus, I. K., Zacchei, A.

“…The BeyondPlanck and Cosmoglobe collaborations have implemented the first integrated Bayesian end-to-end analysis pipeline for CMB experiments. The primary…”
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COSMIC MICROWAVE BACKGROUND LIKELIHOOD APPROXIMATION FOR BANDED PROBABILITY DISTRIBUTIONS by Gjerlow, E, Mikkelsen, K, Eriksen, H K, Gorski, K M, Huey, G, Jewell, J B, Naess, S K, Rocha, G, SELJEBOTN, D S, WEHUS, I K

“…We investigate sets of random variables that can be arranged sequentially such that a given variable only depends conditionally on its immediate predecessor…”
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Osmotically regulated transport of proline by Lactobacillus acidophilus IFO 3532 by JEWELL, J. B, KASHKET, E. R

“…Classifications Services AEM Citing Articles Google Scholar PubMed Related Content Social Bookmarking CiteULike Delicious Digg Facebook Google+ Mendeley Reddit…”
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BeyondPlanck XIII. Intensity foreground sampling, degeneracies, and priors by Andersen, K. J, Herman, D, Aurlien, R, Banerji, R, Basyrov, A, Bersanelli, M, Bertocco, S, Brilenkov, M, Carbone, M, Colombo, L. P. L, Eriksen, H. K, Eskilt, J. R, Foss, M. K, Franceschet, C, Fuskeland, U, Galeotta, S, Galloway, M, Gerakakis, S, Gjerløw, E, Hensley, B, Iacobellis, M, Ieronymaki, M, Ihle, H. T, Jewell, J. B, Karakci, A, Keihänen, E, Keskitalo, R, Lunde, J. G. S, Maggio, G, Maino, D, Maris, M, Mennella, A, Paradiso, S, Partridge, B, Reinecke, M, San, M, Stutzer, N. -O, Suur-Uski, A. -S, Svalheim, T. L, Tavagnacco, D, Thommesen, H, Watts, D. J, Wehus, I. K, Zacchei, A

“…A&A 675, A13 (2023) We present the intensity foreground algorithms and model employed within the BeyondPlanck analysis framework. The BeyondPlanck analysis is…”
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BeyondPlanck I. Global Bayesian analysis of the Planck Low Frequency Instrument data by BeyondPlanck Collaboration, Andersen, K. J, Aurlien, R, Banerji, R, Basyrov, A, Bersanelli, M, Bertocco, S, Brilenkov, M, Carbone, M, Colombo, L. P. L, Eriksen, H. K, Eskilt, J. R, Foss, M. K, Franceschet, C, Fuskeland, U, Galeotta, S, Galloway, M, Gerakakis, S, Gjerløw, E, Hensley, B, Herman, D, Iacobellis, M, Ieronymaki, M, Ihle, H. T, Jewell, J. B, Karakci, A, Keihänen, E, Keskitalo, R, Lunde, J. G. S, Maggio, G, Maino, D, Maris, M, Mennella, A, Paradiso, S, Partridge, B, Reinecke, M, San, M, Stutzer, N. -O, Suur-Uski, A. -S, Svalheim, T. L, Tavagnacco, D, Thommesen, H, Watts, D. J, Wehus, I. K, Zacchei, A

“…A&A 675, A1 (2023) We describe the BeyondPlanck project in terms of motivation, methodology and main products, and provide a guide to a set of companion papers…”
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BeyondPlanck XI. Bayesian CMB analysis with sample-based end-to-end error propagation by Colombo, L. P. L, Eskilt, J. R, Paradiso, S, Thommesen, H, Andersen, K. J, Aurlien, R, Banerji, R, Bersanelli, M, Bertocco, S, Brilenkov, M, Carbone, M, Eriksen, H. K, Foss, M. K, Franceschet, C, Fuskeland, U, Galeotta, S, Galloway, M, Gerakakis, S, Gjerløw, E, Hensley, B, Herman, D, Iacobellis, M, Ieronymaki, M, Ihle, H. T, Jewell, J. B, Karakci, A, Keihänen, E, Keskitalo, R, Maggio, G, Maino, D, Maris, M, Partridge, B, Reinecke, M, Suur-Uski, A. -S, Svalheim, T. L, Tavagnacco, D, Watts, D. J, Wehus, I. K, Zacchei, A

“…A&A 675, A11 (2023) We present posterior sample-based cosmic microwave background (CMB) constraints from Planck LFI and WMAP observations derived through…”
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BeyondPlanck X. Planck LFI frequency maps with sample-based error propagation by Basyrov, A, Suur-Uski, A. -S, Colombo, L. P. L, Eskilt, J. R, Paradiso, S, Andersen, K. J, Aurlien, R, Banerji, R, Bersanelli, M, Bertocco, S, Brilenkov, M, Carbone, M, Eriksen, H. K, Foss, M. K, Franceschet, C, Fuskeland, U, Galeotta, S, Galloway, M, Gerakakis, S, Gjerløw, E, Hensley, B, Herman, D, Iacobellis, M, Ieronymaki, M, Ihle, H. T, Jewell, J. B, Karakci, A, Keihänen, E, Keskitalo, R, Maggio, G, Maino, D, Maris, M, Partridge, B, Reinecke, M, Svalheim, T. L, Tavagnacco, D, Thommesen, H, Watts, D. J, Wehus, I. K, Zacchei, A

“…A&A 675, A10 (2023) We present Planck LFI frequency sky maps derived within the BeyondPlanck framework. This framework draws samples from a global posterior…”
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BeyondPlanck VI. Noise characterization and modelling by Ihle, H. T, Bersanelli, M, Franceschet, C, Gjerløw, E, Andersen, K. J, Aurlien, R, Banerji, R, Bertocco, S, Brilenkov, M, Carbone, M, Colombo, L. P. L, Eriksen, H. K, Eskilt, J. R, Foss, M. K, Fuskeland, U, Galeotta, S, Galloway, M, Gerakakis, S, Hensley, B, Herman, D, Iacobellis, M, Ieronymaki, M, Jewell, J. B, Karakci, A, Keihänen, E, Keskitalo, R, Maggio, G, Maino, D, Maris, M, Mennella, A, Paradiso, S, Partridge, B, Reinecke, M, San, M, Suur-Uski, A. -S, Svalheim, T. L, Tavagnacco, D, Thommesen, H, Watts, D. J, Wehus, I. K, Zacchei, A

“…A&A 675, A6 (2023) We present a Bayesian method for estimating instrumental noise parameters and propagating noise uncertainties within the global BeyondPlanck…”
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BeyondPlanck VII. Bayesian estimation of gain and absolute calibration for CMB experiments by Gjerløw, E, Ihle, H. T, Galeotta, S, Andersen, K. J, Aurlien, R, Banerji, R, Bersanelli, M, Bertocco, S, Brilenkov, M, Carbone, M, Colombo, L. P. L, Eriksen, H. K, Foss, M. K, Franceschet, C, Fuskeland, U, Galloway, M, Gerakakis, S, Hensley, B, Herman, D, Iacobellis, M, Ieronymaki, M, Jewell, J. B, Karakci, A, Keihänen, E, Keskitalo, R, Maggio, G, Maino, D, Maris, M, Paradiso, S, Partridge, B, Reinecke, M, Suur-Uski, A. -S, Svalheim, T. L, Tavagnacco, D, Thommesen, H, Watts, D. J, Wehus, I. K, Zacchei, A

“…We present a Bayesian calibration algorithm for CMB observations as implemented within the global end-to-end BeyondPlanck (BP) framework, and apply this to the…”
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BeyondPlanck XII. Cosmological parameter constraints with end-to-end error propagation by Paradiso, S, Colombo, L. P. L, Andersen, K. J, Aurlien, R, Banerji, R, Basyrov, A, Bersanelli, M, Bertocco, S, Brilenkov, M, Carbone, M, Eriksen, H. K, Eskilt, J. R, Foss, M. K, Franceschet, C, Fuskeland, U, Galeotta, S, Galloway, M, Gerakakis, S, Gjerløw, E, Hensley, B, Herman, D, Iacobellis, M, Ieronymaki, M, Ihle, H. T, Jewell, J. B, Karakci, A, Keihänen, E, Keskitalo, R, Maggio, G, Maino, D, Maris, M, Partridge, B, Reinecke, M, San, M, Suur-Uski, A. -S, Svalheim, T. L, Tavagnacco, D, Thommesen, H, Watts, D. J, Wehus, I. K, Zacchei, A

“…A&A 675, A12 (2023) We present cosmological parameter constraints as estimated using the Bayesian BeyondPlanck (BP) analysis framework. This method supports…”
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