315 results on '"Gomez, Thomas"'
Search Results
2. Enhancements of Electron-Atom Collisions due to Pauli Repulsion in Neutron-Star Magnetic Fields
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Gomez, Thomas, Zammit, Mark, Bray, Igor, Fontes, Christopher, and White, Jackson
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Astrophysics - High Energy Astrophysical Phenomena ,Astrophysics - Solar and Stellar Astrophysics ,Physics - Atomic Physics - Abstract
Neutron star surfaces and atmospheres are unique environments that sustain the largest-known magnetic fields in the universe. Our knowledge of neutron star material properties, including the composition and equation of state, remains highly unconstrained. Electron-atom collisions are integral to theoretical thermal conduction and spectral emission models that describe neutron star surfaces. The theory of scattering in magnetic fields was developed in the 1970s, but focused only on bare nuclei scattering. In this work, we present a quantum treatment of atom-electron collisions in magnetic fields; of significant importance is the inclusion of Pauli repulsion arising from two interacting electrons. We find strange behaviors not seen in collisions without a magnetic field. In high magnetic fields, Pauli repulsion can lead to orders of magnitude enhancements of collision cross sections. Additionally, the elastic collision cross sections that involve the ground state become comparable to those involving excited states, and states with large orbits have the largest contribution to the collisions. We anticipate significant changes to transport properties and spectral line broadening in neutron star surfaces and atmospheres, which will aid in spectral diagnostics of these extreme environments.
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- 2023
3. Second-order spectral line shift comparisons
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Iglesias, Carlos A. and Gomez, Thomas A.
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- 2024
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4. Comparison of second-order spectral line widths formulae
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Iglesias, Carlos A. and Gomez, Thomas A.
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- 2024
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5. Evaluation of ensemble methods for quantifying uncertainties in steady-state CFD applications with small ensemble sizes
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Zhang, Xinlei, Xiao, Heng, Gomez, Thomas, and Coutier-Delgosha, Olivier
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Physics - Computational Physics - Abstract
Bayesian uncertainty quantification (UQ) is of interest to industry and academia as it provides a framework for quantifying and reducing the uncertainty in computational models by incorporating available data. For systems with very high computational costs, for instance, the computational fluid dynamics (CFD) problem, the conventional, exact Bayesian approach such as Markov chain Monte Carlo is intractable. To this end, the ensemble-based Bayesian methods have been used for CFD applications. However, their applicability for UQ has not been fully analyzed and understood thus far. Here, we evaluate the performance of three widely used iterative ensemble-based data assimilation methods, namely ensemble Kalman filter, ensemble randomized maximum likelihood method, and ensemble Kalman filter with multiple data assimilation for UQ problems. We present the derivations of the three ensemble methods from an optimization viewpoint. Further, a scalar case is used to demonstrate the performance of the three different approaches with emphasis on the effects of small ensemble sizes. Finally, we assess the three ensemble methods for quantifying uncertainties in steady-state CFD problems involving turbulent mean flows. Specifically, the Reynolds averaged Navier--Stokes (RANS) equation is considered the forward model, and the uncertainties in the propagated velocity are quantified and reduced by incorporating observation data. The results show that the ensemble methods cannot accurately capture the true posterior distribution, but they can provide a good estimation of the uncertainties even when very limited ensemble sizes are used. Based on the overall performance and efficiency from the comparison, the ensemble randomized maximum likelihood method is identified as the best choice of approximate Bayesian UQ approach~among the three ensemble methods evaluated here.
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- 2020
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6. A multi-element non-intrusive Polynomial Chaos method using agglomerative clustering based on the derivatives to study irregular and discontinuous Quantities of Interest
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Vauchel, Nicolas, Garnier, Éric, and Gomez, Thomas
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- 2023
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7. A closure theory for the split energy-helicity cascades in homogeneous isotropic homochiral turbulence
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Briard, Antoine, Biferale, Luca, and Gomez, Thomas
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Physics - Fluid Dynamics - Abstract
We study the energy transfer properties of three dimensional homogeneous and isotropic turbulence where the non-linear transfer is altered in a way that helicity is made sign-definite, say positive. In this framework, known as homochiral turbulence, an adapted eddy-damped quasi-normal Markovian (EDQNM) closure is derived to analyze the dynamics at very large Reynolds numbers, of order $10^5$ based on the Taylor scale. In agreement with previous findings, an inverse cascade of energy with a kinetic energy spectrum like $\propto k^{-5/3}$ is found for scales larger than the forcing one. Conjointly, a forward cascade of helicity towards larger wavenumbers is obtained, where the kinetic energy spectrum scales like $\propto k^{-7/3}$. By following the evolution of the closed spectral equations for a very long time and over a huge extensions of scales, we found the developing of a non monotonic shape for the front of the inverse energy flux. The very long time evolution of the kinetic energy and integral scale in both the forced and unforced cases is analyzed also., Comment: 8 pages, 3 figures
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- 2017
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8. Machine learning for fluid flow reconstruction from limited measurements
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Dubois, Pierre, Gomez, Thomas, Planckaert, Laurent, and Perret, Laurent
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- 2022
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9. Nonstandard Errors
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MENKVELD, ALBERT J., primary, DREBER, ANNA, additional, HOLZMEISTER, FELIX, additional, HUBER, JUERGEN, additional, JOHANNESSON, MAGNUS, additional, KIRCHLER, MICHAEL, additional, NEUSÜß, SEBASTIAN, additional, RAZEN, MICHAEL, additional, WEITZEL, UTZ, additional, ABAD‐DÍAZ, DAVID, additional, ABUDY, MENACHEM (MENI), additional, ADRIAN, TOBIAS, additional, AIT‐SAHALIA, YACINE, additional, AKMANSOY, OLIVIER, additional, ALCOCK, JAMIE T., additional, ALEXEEV, VITALI, additional, ALOOSH, ARASH, additional, AMATO, LIVIA, additional, AMAYA, DIEGO, additional, ANGEL, JAMES J., additional, AVETIKIAN, ALEJANDRO T., additional, BACH, AMADEUS, additional, BAIDOO, EDWIN, additional, BAKALLI, GAETAN, additional, BAO, LI, additional, BARBON, ANDREA, additional, BASHCHENKO, OKSANA, additional, BINDRA, PARAMPREET C., additional, BJØNNES, GEIR H., additional, BLACK, JEFFREY R., additional, BLACK, BERNARD S., additional, BOGOEV, DIMITAR, additional, CORREA, SANTIAGO BOHORQUEZ, additional, BONDARENKO, OLEG, additional, BOS, CHARLES S., additional, BOSCH‐ROSA, CIRIL, additional, BOURI, ELIE, additional, BROWNLEES, CHRISTIAN, additional, CALAMIA, ANNA, additional, CAO, VIET NGA, additional, CAPELLE‐BLANCARD, GUNTHER, additional, ROMERO, LAURA M. CAPERA, additional, CAPORIN, MASSIMILIANO, additional, CARRION, ALLEN, additional, CASKURLU, TOLGA, additional, CHAKRABARTY, BIDISHA, additional, CHEN, JIAN, additional, CHERNOV, MIKHAIL, additional, CHEUNG, WILLIAM, additional, CHINCARINI, LUDWIG B., additional, CHORDIA, TARUN, additional, CHOW, SHEUNG‐CHI, additional, CLAPHAM, BENJAMIN, additional, COLLIARD, JEAN‐EDOUARD, additional, COMERTON‐FORDE, CAROLE, additional, CURRAN, EDWARD, additional, DAO, THONG, additional, DARE, WALE, additional, DAVIES, RYAN J., additional, BLASIS, RICCARDO DE, additional, NARD, GIANLUCA F. DE, additional, DECLERCK, FANY, additional, DEEV, OLEG, additional, DEGRYSE, HANS, additional, DEKU, SOLOMON Y., additional, DESAGRE, CHRISTOPHE, additional, DIJK, MATHIJS A. VAN, additional, DIM, CHUKWUMA, additional, DIMPFL, THOMAS, additional, DONG, YUN JIANG, additional, DRUMMOND, PHILIP A., additional, DUDDA, TOM, additional, DUEVSKI, TEODOR, additional, DUMITRESCU, ARIADNA, additional, DYAKOV, TEODOR, additional, DYHRBERG, ANNE HAUBO, additional, DZIELIŃSKI, MICHAŁ, additional, EKSI, ASLI, additional, KALAK, IZIDIN EL, additional, ELLEN, SASKIA TER, additional, EUGSTER, NICOLAS, additional, EVANS, MARTIN D. D., additional, FARRELL, MICHAEL, additional, FELEZ‐VINAS, ESTER, additional, FERRARA, GERARDO, additional, FERROUHI, EL MEHDI, additional, FLORI, ANDREA, additional, FLUHARTY‐JAIDEE, JONATHAN T., additional, FOLEY, SEAN D. V., additional, FONG, KINGSLEY Y. L., additional, FOUCAULT, THIERRY, additional, FRANUS, TATIANA, additional, FRANZONI, FRANCESCO, additional, FRIJNS, BART, additional, FRÖMMEL, MICHAEL, additional, FU, SERVANNA M., additional, FÜLLBRUNN, SASCHA C., additional, GAN, BAOQING, additional, GAO, GE, additional, GEHRIG, THOMAS P., additional, GEMAYEL, ROLAND, additional, GERRITSEN, DIRK, additional, GIL‐BAZO, JAVIER, additional, GILDER, DUDLEY, additional, GLOSTEN, LAWRENCE R., additional, GOMEZ, THOMAS, additional, GORBENKO, ARSENY, additional, GRAMMIG, JOACHIM, additional, GRÉGOIRE, VINCENT, additional, GÜÇBILMEZ, UFUK, additional, HAGSTRÖMER, BJÖRN, additional, HAMBUCKERS, JULIEN, additional, HAPNES, ERIK, additional, HARRIS, JEFFREY H., additional, HARRIS, LAWRENCE, additional, HARTMANN, SIMON, additional, HASSE, JEAN‐BAPTISTE, additional, HAUTSCH, NIKOLAUS, additional, HE, XUE‐ZHONG (TONY), additional, HEATH, DAVIDSON, additional, HEDIGER, SIMON, additional, HENDERSHOTT, TERRENCE, additional, HIBBERT, ANN MARIE, additional, HJALMARSSON, ERIK, additional, HOELSCHER, SETH A., additional, HOFFMANN, PETER, additional, HOLDEN, CRAIG W., additional, HORENSTEIN, ALEX R., additional, HUANG, WENQIAN, additional, HUANG, DA, additional, HURLIN, CHRISTOPHE, additional, ILCZUK, KONRAD, additional, IVASHCHENKO, ALEXEY, additional, IYER, SUBRAMANIAN R., additional, JAHANSHAHLOO, HOSSEIN, additional, JALKH, NAJI, additional, JONES, CHARLES M., additional, JURKATIS, SIMON, additional, JYLHÄ, PETRI, additional, KAECK, ANDREAS T., additional, KAISER, GABRIEL, additional, KARAM, ARZÉ, additional, KARMAZIENE, EGLE, additional, KASSNER, BERNHARD, additional, KAUSTIA, MARKKU, additional, KAZAK, EKATERINA, additional, KEARNEY, FEARGHAL, additional, KERVEL, VINCENT VAN, additional, KHAN, SAAD A., additional, KHOMYN, MARTA K., additional, KLEIN, TONY, additional, KLEIN, OLGA, additional, KLOS, ALEXANDER, additional, KOETTER, MICHAEL, additional, KOLOKOLOV, ALEKSEY, additional, KORAJCZYK, ROBERT A., additional, KOZHAN, ROMAN, additional, KRAHNEN, JAN P., additional, KUHLE, PAUL, additional, KWAN, AMY, additional, LAJAUNIE, QUENTIN, additional, LAM, F. Y. ERIC C., additional, LAMBERT, MARIE, additional, LANGLOIS, HUGUES, additional, LAUSEN, JENS, additional, LAUTER, TOBIAS, additional, LEIPPOLD, MARKUS, additional, LEVIN, VLADIMIR, additional, LI, YIJIE, additional, LI, HUI, additional, LIEW, CHEE YOONG, additional, LINDNER, THOMAS, additional, LINTON, OLIVER, additional, LIU, JIACHENG, additional, LIU, ANQI, additional, LLORENTE, GUILLERMO, additional, LOF, MATTHIJS, additional, LOHR, ARIEL, additional, LONGSTAFF, FRANCIS, additional, LOPEZ‐LIRA, ALEJANDRO, additional, MANKAD, SHAWN, additional, MANO, NICOLA, additional, MARCHAL, ALEXIS, additional, MARTINEAU, CHARLES, additional, MAZZOLA, FRANCESCO, additional, MELOSO, DEBRAH, additional, MI, MICHAEL G., additional, MIHET, ROXANA, additional, MOHAN, VIJAY, additional, MOINAS, SOPHIE, additional, MOORE, DAVID, additional, MU, LIANGYI, additional, MURAVYEV, DMITRIY, additional, MURPHY, DERMOT, additional, NESZVEDA, GABOR, additional, NEUMEIER, CHRISTIAN, additional, NIELSSON, ULF, additional, NIMALENDRAN, MAHENDRARAJAH, additional, NOLTE, SVEN, additional, NORDEN, LARS L., additional, O'NEILL, PETER, additional, OBAID, KHALED, additional, ØDEGAARD, BERNT A., additional, ÖSTBERG, PER, additional, PAGNOTTA, EMILIANO, additional, PAINTER, MARCUS, additional, PALAN, STEFAN, additional, PALIT, IMON J., additional, PARK, ANDREAS, additional, PASCUAL, ROBERTO, additional, PASQUARIELLO, PAOLO, additional, PASTOR, LUBOS, additional, PATEL, VINAY, additional, PATTON, ANDREW J., additional, PEARSON, NEIL D., additional, PELIZZON, LORIANA, additional, PELLI, MICHELE, additional, PELSTER, MATTHIAS, additional, PÉRIGNON, CHRISTOPHE, additional, PFIFFER, CAMERON, additional, PHILIP, RICHARD, additional, PLÍHAL, TOMÁŠ, additional, PRAKASH, PUNEET, additional, PRESS, OLIVER‐ALEXANDER, additional, PRODROMOU, TINA, additional, PROKOPCZUK, MARCEL, additional, PUTNINS, TALIS, additional, QIAN, YA, additional, RAIZADA, GAURAV, additional, RAKOWSKI, DAVID, additional, RANALDO, ANGELO, additional, REGIS, LUCA, additional, REITZ, STEFAN, additional, RENAULT, THOMAS, additional, RENJIE, REX W., additional, RENO, ROBERTO, additional, RIDDIOUGH, STEVEN J., additional, RINNE, KALLE, additional, RINTAMÄKI, PAUL, additional, RIORDAN, RYAN, additional, RITTMANNSBERGER, THOMAS, additional, LONGARELA, IÑAKI RODRÍGUEZ, additional, ROESCH, DOMINIK, additional, ROGNONE, LAVINIA, additional, ROSEMAN, BRIAN, additional, ROŞU, IOANID, additional, ROY, SAURABH, additional, RUDOLF, NICOLAS, additional, RUSH, STEPHEN R., additional, RZAYEV, KHALADDIN, additional, RZEŹNIK, ALEKSANDRA A., additional, SANFORD, ANTHONY, additional, SANKARAN, HARIKUMAR, additional, SARKAR, ASANI, additional, SARNO, LUCIO, additional, SCAILLET, OLIVIER, additional, SCHARNOWSKI, STEFAN, additional, SCHENK‐HOPPÉ, KLAUS R., additional, SCHERTLER, ANDREA, additional, SCHNEIDER, MICHAEL, additional, SCHROEDER, FLORIAN, additional, SCHÜRHOFF, NORMAN, additional, SCHUSTER, PHILIPP, additional, SCHWARZ, MARCO A., additional, SEASHOLES, MARK S., additional, SEEGER, NORMAN J., additional, SHACHAR, OR, additional, SHKILKO, ANDRIY, additional, SHUI, JESSICA, additional, SIKIC, MARIO, additional, SIMION, GIORGIA, additional, SMALES, LEE A., additional, SÖDERLIND, PAUL, additional, SOJLI, ELVIRA, additional, SOKOLOV, KONSTANTIN, additional, SÖNKSEN, JANTJE, additional, SPOKEVICIUTE, LAIMA, additional, STEFANOVA, DENITSA, additional, SUBRAHMANYAM, MARTI G., additional, SZASZI, BARNABAS, additional, TALAVERA, OLEKSANDR, additional, TANG, YUEHUA, additional, TAYLOR, NICK, additional, THAM, WING WAH, additional, THEISSEN, ERIK, additional, THIMME, JULIAN, additional, TONKS, IAN, additional, TRAN, HAI, additional, TRAPIN, LUCA, additional, TROLLE, ANDERS B., additional, VADUVA, M. ANDREEA, additional, VALENTE, GIORGIO, additional, NESS, ROBERT A. VAN, additional, VASQUEZ, AURELIO, additional, VEROUSIS, THANOS, additional, VERWIJMEREN, PATRICK, additional, VILHELMSSON, ANDERS, additional, VILKOV, GRIGORY, additional, VLADIMIROV, VLADIMIR, additional, VOGEL, SEBASTIAN, additional, VOIGT, STEFAN, additional, WAGNER, WOLF, additional, WALTHER, THOMAS, additional, WEISS, PATRICK, additional, WEL, MICHEL VAN DER, additional, WERNER, INGRID M., additional, WESTERHOLM, P. JOAKIM, additional, WESTHEIDE, CHRISTIAN, additional, WIKA, HANS C., additional, WIPPLINGER, EVERT, additional, WOLF, MICHAEL, additional, WOLFF, CHRISTIAN C. P., additional, WOLK, LEONARD, additional, WONG, WING‐KEUNG, additional, WRAMPELMEYER, JAN, additional, WU, ZHEN‐XING, additional, XIA, SHUO, additional, XIU, DACHENG, additional, XU, KE, additional, XU, CAIHONG, additional, YADAV, PRADEEP K., additional, YAGÜE, JOSÉ, additional, YAN, CHENG, additional, YANG, ANTTI, additional, YOO, WOONGSUN, additional, YU, WENJIA, additional, YU, YIHE, additional, YU, SHIHAO, additional, YUESHEN, BART Z., additional, YUFEROVA, DARYA, additional, ZAMOJSKI, MARCIN, additional, ZAREEI, ABALFAZL, additional, ZEISBERGER, STEFAN M., additional, ZHANG, LU, additional, ZHANG, S. SARAH, additional, ZHANG, XIAOYU, additional, ZHAO, LU, additional, ZHONG, ZHUO, additional, ZHOU, Z. IVY, additional, ZHOU, CHEN, additional, ZHU, XINGYU S., additional, ZOICAN, MARIUS, additional, and ZWINKELS, REMCO, additional
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- 2024
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10. A Quantum Mechanical Treatment of Electron Broadening in Strong Magnetic Fields. II. Large Enhancements due to Exchange Interactions
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Gomez, Thomas A., primary, Zammit, Mark C., additional, Bray, Igor, additional, Fontes, Christopher J., additional, and White, Jackson R., additional
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- 2024
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11. Helium at white dwarf photospheric conditions: preliminary laboratory results
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Schaeuble, Marc, Falcon, Ross E., Gomez, Thomas A., Winget, Don E., Montgomery, Michael H., and Bailey, James E.
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Astrophysics - Solar and Stellar Astrophysics - Abstract
We present preliminary results of an experimental study exploring helium at photospheric conditions of white dwarf stars. These data were collected at Sandia National Laboratories' Z-machine, the largest x-ray source on earth. Our helium results could have many applications ranging from validating current DB white dwarf model atmospheres to providing accurate He pressure shifts at varying temperatures and densities. In a much broader context, these helium data can be used to guide theoretical developments in new continuum-lowering models for two-electron atoms. We also discuss future applications of our updated experimental design, which enables us to sample a greater range of densities, temperatures, and gas compositions.
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- 2016
12. Non-Standard Errors
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Leerstoel Stigchel, Helmholtz Institute, Experimental Psychology (onderzoeksprogramma PF), Finance, UU LEG Research UUSE Multidisciplinary Economics, Sub General Pharmaceutics, Menkveld, Albert J., Abudy, Menachem (Meni), Grammig, Joachim, Gregoire, Vincent, Hagströmer, Björn, Hambuckers, Julien, Hapnes, Erik, Harris, Jeffrey H., Harris, Lawrence, Hartmann, Simon, Hasse, Jean-Baptiste, Hautsch, Nikolaus, Adrian, Tobias, He, Xue-Zhong 'Tony', Heath, Davidson, Hediger, Simon, Hendershott, Terrence J., Hibbert, Ann Marie, Hjalmarsson, Erik, Hoelscher, Seth, Hoffmann, Peter, Holden, Craig W., Horenstein, Alex R., Ait-Sahalia, Yacine, Huang, Wenqian, Huang, Da, Hurlin, Christophe, Ivashchenko, Alexey, Iyer, Subramanian R., Jahanshahloo, Hossein, Jalkh, Naji, Jones, Charles M., Jurkatis, Simon, Jylha, Petri, Akmansoy, Olivier, Kaeck, Andreas, Kaiser, Gabriel, Karam, Arzé, Karmaziene, Egle, Kassner, Bernhard, Kaustia, Markku, Kazak, Ekaterina, Kearney, Fearghal, van Kervel, Vincent, Khan, Saad, Alcock, Jamie, Khomyn, Marta, Klein, Tony, Klein, Olga, Klos, Alexander, Koetter, Michael, Krahnen, Jan Pieter, Kolokolov, Aleksey, Korajczyk, Robert A., Kozhan, Roman, Kwan, Amy, Alexeev, Vitali, Lajaunie, Quentin, Lam, Full Yet Eric Campbell, Lambert, Marie, Langlois, Hugues, Lausen, Jens, Lauter, Tobias, Leippold, Markus, Levin, Vladimir, Li, Yijie, Li, (Michael) Hui, Aloosh, Arash, Liew, Chee Yoong, Lindner, Thomas, Linton, Oliver B., Liu, Jiacheng, Liu, Anqi, Llorente-Alvarez, Jesus-Guillermo, Lof, Matthijs, Lohr, Ariel, Longstaff, Francis A., Lopez-Lira, Alejandro, Amato, Livia, Mankad, Shawn, Mano, Nicola, Marchal, Alexis, Martineau, Charles, Mazzola, Francesco, Meloso, Debrah C, Mihet, Roxana, Mohan, Vijay, Moinas, Sophie, Moore, David, Amaya, Diego, Mu, Liangyi, Muravyev, Dmitriy, Murphy, Dermot, Neszveda, Gabor, Neumeier, Christian, Nielsson, Ulf, Nimalendran, Mahendrarajah, Nolte, Sven, Nordén, Lars L., O'Neill, Peter, Angel, James J., Obaid, Khaled, Ødegaard, Bernt Arne, Östberg, Per, Painter, Marcus, Palan, Stefan, Palit, Imon, Park, Andreas, Pascual Gascó, Roberto, Pasquariello, Paolo, Pastor, Lubos, Dreber, Anna, Bach, Amadeus, Patel, Vinay, Patton, Andrew J., Pearson, Neil D., Pelizzon, Loriana, Pelster, Matthias, Pérignon, Christophe, Pfiffer, Cameron, Philip, Richard, Plíhal, Tomáš, Prakash, Puneet, Baidoo, Edwin, Press, Oliver-Alexander, Prodromou, Tina, Putnins, Talis J., Raizada, Gaurav, Rakowski, David A., Ranaldo, Angelo, Regis, Luca, Reitz, Stefan, Renault, Thomas, Wang, Renjie, Bakalli, Gaetan, Renò, Roberto, Riddiough, Steven, Rinne, Kalle, Rintamäki, Paul, Riordan, Ryan, Rittmannsberger, Thomas, Rodríguez Longarela, Iñaki, Rösch, Dominik, Rognone, Lavinia, Roseman, Brian, Barbon, Andrea, Rosu, Ioanid, Roy, Saurabh, Rudolf, Nicolas, Rush, Stephen, Rzayev, Khaladdin, Rzeźnik, Aleksandra, Sanford, Anthony, Sankaran, Harikumar, Sarkar, Asani, Sarno, Lucio, Bashchenko, Oksana, Scaillet, Olivier, Scharnowski, Stefan, Schenk-Hoppé, Klaus Reiner, Schertler, Andrea, Schneider, Michael, Schroeder, Florian, Schürhoff, Norman, Schuster, Philipp, Schwarz, Marco A., Seasholes, Mark S., Bindra, Parampreet Christopher, Seeger, Norman, Shachar, Or, Shkilko, Andriy, Shui, Jessica, Sikic, Mario, Simion, Giorgia, Smales, Lee A., Söderlind, Paul, Sojli, Elvira, Sokolov, Konstantin, Bjonnes, Geir Hoidal, Spokeviciute, Laima, Stefanova, Denitsa, Subrahmanyam, Marti G., Neusüss, Sebastian, Szaszi, Barnabas, Talavera, Oleksandr, Tang, Yuehua, Taylor, Nicholas, Tham, Wing Wah, Theissen, Erik, Black, Jeffrey R., Thimme, Julian, Tonks, Ian, Tran, Hai, Trapin, Luca, Trolle, Anders B., Valente, Giorgio, Van Ness, Robert A., Vasquez, Aurelio, Verousis, Thanos, Verwijmeren, Patrick, Black, Bernard S., Vilhelmsson, Anders, Vilkov, Grigory, Vladimirov, Vladimir, Vogel, Sebastian, Voigt, Stefan, Wagner, Wolf, Walther, Thomas, Weiss, Patrick, van der Wel, Michel, Werner, Ingrid M., Bohorquez, Santiago, Westerholm, P. Joakim, Westheide, Christian, Wipplinger, Evert, Wolf, Michael, Wolff, Christian C. P., Wolk, Leonard, Wong, Wing-Keung, Wrampelmeyer, Jan, Xia, Shuo, Xiu, Dacheng, Holzmeister, Felix, Bondarenko, Oleg, Xu, Ke, Xu, Caihong, Yadav, Pradeep K., Yagüe, José, Yan, Cheng, Yang, Antti, Yoo, Woongsun, Yu, Wenjia, Yu, Shihao, Yueshen, Bart Zhou, Bos, Charles S., Yuferova, Darya, Zamojski, Marcin, Zareei, Abalfazl, Zeisberger, Stefan, Zhang, Lu, Zhang, Xiaoyu, Zhong, Zhuo, Zhou, Z. Ivy, Zhou, Chen, Zhu, Xingyu, Bosch-Rosa, Ciril, Zoican, Marius, Zwinkels, Remco C.J., Chen, Jian, Duevski, Teodor, Gao, Ge, Gemayel, Roland, Gilder, Dudley, Kuhle, Paul, Pagnotta, Emiliano, Pelli, Michele, Bouri, Elie, Sönksen, Jantje, Ilczuk, Konrad, Bogoev, Dimitar, Qian, Ya, Wika, Hans C., Yu, Yihe, Zhao, Lu, Mi, Michael, Bao, Li, Brownlees, Christian T., Vaduva, Andreea, Prokopczuk, Marcel, Avetikian, Alejandro, Wu, Zhen-Xing, Calamia, Anna, Cao, Viet Nga, Capelle-Blancard, Gunther, Capera, Laura, Caporin, Massimiliano, Huber, Juergen, Carrion, Allen, Caskurlu, Tolga, Chakrabarty, Bidisha, Chernov, Mikhail, Cheung, William Ming Yan, Chincarini, Ludwig B., Chordia, Tarun, Chow, Sheung Chi, Clapham, Benjamin, Colliard, Jean-Edouard, Johanneson, Magnus, Comerton-Forde, Carole, Curran, Edward, Dao, Thong, Dare, Wale, Davies, Ryan J., De Blasis, Riccardo, De Nard, Gianluca, Declerck, Fany, Deev, Oleg, Degryse, Hans, Kirchler, Michael, Deku, Solomon, Desagre, Christophe, Dim, Chukwuma, Dimpfl, Thomas, Dong, Yun Jiang, Drummond, Philip, Dudda, Tom, Dumitrescu, Ariadna, Dyakov, Teodor, Razen, Michael, Dyhrberg, Anne Haubo, Dzieliński, Michał, Eksi, Asli, El Kalak, Izidin, ter Ellen, Saskia, Eugster, Nicolas, Evans, Martin D.D., Farrell, Michael, Félez-Viñas, Ester, Ferrara, Gerardo, Weitzel, Utz, FERROUHI, El Mehdi, Flori, Andrea, Fluharty-Jaidee, Jonathan, Foley, Sean, Fong, Kingsley Y. L., Foucault, Thierry, Franus, Tatiana, Franzoni, Francesco A., Frijns, Bart, Frömmel, Michael, Abad, David, Fu, Servanna Mianjun, Füllbrunn, Sascha, Gan, Baoqing, Gehrig, Thomas, Gerritsen, Dirk, Gil-Bazo, Javier, Glosten, Lawrence R., Gomez, Thomas, Gorbenko, Arseny, Güçbilmez, Ufuk, Van Dijk, Matthijs A., Leerstoel Stigchel, Helmholtz Institute, Experimental Psychology (onderzoeksprogramma PF), Finance, UU LEG Research UUSE Multidisciplinary Economics, Sub General Pharmaceutics, Menkveld, Albert J., Abudy, Menachem (Meni), Grammig, Joachim, Gregoire, Vincent, Hagströmer, Björn, Hambuckers, Julien, Hapnes, Erik, Harris, Jeffrey H., Harris, Lawrence, Hartmann, Simon, Hasse, Jean-Baptiste, Hautsch, Nikolaus, Adrian, Tobias, He, Xue-Zhong 'Tony', Heath, Davidson, Hediger, Simon, Hendershott, Terrence J., Hibbert, Ann Marie, Hjalmarsson, Erik, Hoelscher, Seth, Hoffmann, Peter, Holden, Craig W., Horenstein, Alex R., Ait-Sahalia, Yacine, Huang, Wenqian, Huang, Da, Hurlin, Christophe, Ivashchenko, Alexey, Iyer, Subramanian R., Jahanshahloo, Hossein, Jalkh, Naji, Jones, Charles M., Jurkatis, Simon, Jylha, Petri, Akmansoy, Olivier, Kaeck, Andreas, Kaiser, Gabriel, Karam, Arzé, Karmaziene, Egle, Kassner, Bernhard, Kaustia, Markku, Kazak, Ekaterina, Kearney, Fearghal, van Kervel, Vincent, Khan, Saad, Alcock, Jamie, Khomyn, Marta, Klein, Tony, Klein, Olga, Klos, Alexander, Koetter, Michael, Krahnen, Jan Pieter, Kolokolov, Aleksey, Korajczyk, Robert A., Kozhan, Roman, Kwan, Amy, Alexeev, Vitali, Lajaunie, Quentin, Lam, Full Yet Eric Campbell, Lambert, Marie, Langlois, Hugues, Lausen, Jens, Lauter, Tobias, Leippold, Markus, Levin, Vladimir, Li, Yijie, Li, (Michael) Hui, Aloosh, Arash, Liew, Chee Yoong, Lindner, Thomas, Linton, Oliver B., Liu, Jiacheng, Liu, Anqi, Llorente-Alvarez, Jesus-Guillermo, Lof, Matthijs, Lohr, Ariel, Longstaff, Francis A., Lopez-Lira, Alejandro, Amato, Livia, Mankad, Shawn, Mano, Nicola, Marchal, Alexis, Martineau, Charles, Mazzola, Francesco, Meloso, Debrah C, Mihet, Roxana, Mohan, Vijay, Moinas, Sophie, Moore, David, Amaya, Diego, Mu, Liangyi, Muravyev, Dmitriy, Murphy, Dermot, Neszveda, Gabor, Neumeier, Christian, Nielsson, Ulf, Nimalendran, Mahendrarajah, Nolte, Sven, Nordén, Lars L., O'Neill, Peter, Angel, James J., Obaid, Khaled, Ødegaard, Bernt Arne, Östberg, Per, Painter, Marcus, Palan, Stefan, Palit, Imon, Park, Andreas, Pascual Gascó, Roberto, Pasquariello, Paolo, Pastor, Lubos, Dreber, Anna, Bach, Amadeus, Patel, Vinay, Patton, Andrew J., Pearson, Neil D., Pelizzon, Loriana, Pelster, Matthias, Pérignon, Christophe, Pfiffer, Cameron, Philip, Richard, Plíhal, Tomáš, Prakash, Puneet, Baidoo, Edwin, Press, Oliver-Alexander, Prodromou, Tina, Putnins, Talis J., Raizada, Gaurav, Rakowski, David A., Ranaldo, Angelo, Regis, Luca, Reitz, Stefan, Renault, Thomas, Wang, Renjie, Bakalli, Gaetan, Renò, Roberto, Riddiough, Steven, Rinne, Kalle, Rintamäki, Paul, Riordan, Ryan, Rittmannsberger, Thomas, Rodríguez Longarela, Iñaki, Rösch, Dominik, Rognone, Lavinia, Roseman, Brian, Barbon, Andrea, Rosu, Ioanid, Roy, Saurabh, Rudolf, Nicolas, Rush, Stephen, Rzayev, Khaladdin, Rzeźnik, Aleksandra, Sanford, Anthony, Sankaran, Harikumar, Sarkar, Asani, Sarno, Lucio, Bashchenko, Oksana, Scaillet, Olivier, Scharnowski, Stefan, Schenk-Hoppé, Klaus Reiner, Schertler, Andrea, Schneider, Michael, Schroeder, Florian, Schürhoff, Norman, Schuster, Philipp, Schwarz, Marco A., Seasholes, Mark S., Bindra, Parampreet Christopher, Seeger, Norman, Shachar, Or, Shkilko, Andriy, Shui, Jessica, Sikic, Mario, Simion, Giorgia, Smales, Lee A., Söderlind, Paul, Sojli, Elvira, Sokolov, Konstantin, Bjonnes, Geir Hoidal, Spokeviciute, Laima, Stefanova, Denitsa, Subrahmanyam, Marti G., Neusüss, Sebastian, Szaszi, Barnabas, Talavera, Oleksandr, Tang, Yuehua, Taylor, Nicholas, Tham, Wing Wah, Theissen, Erik, Black, Jeffrey R., Thimme, Julian, Tonks, Ian, Tran, Hai, Trapin, Luca, Trolle, Anders B., Valente, Giorgio, Van Ness, Robert A., Vasquez, Aurelio, Verousis, Thanos, Verwijmeren, Patrick, Black, Bernard S., Vilhelmsson, Anders, Vilkov, Grigory, Vladimirov, Vladimir, Vogel, Sebastian, Voigt, Stefan, Wagner, Wolf, Walther, Thomas, Weiss, Patrick, van der Wel, Michel, Werner, Ingrid M., Bohorquez, Santiago, Westerholm, P. Joakim, Westheide, Christian, Wipplinger, Evert, Wolf, Michael, Wolff, Christian C. P., Wolk, Leonard, Wong, Wing-Keung, Wrampelmeyer, Jan, Xia, Shuo, Xiu, Dacheng, Holzmeister, Felix, Bondarenko, Oleg, Xu, Ke, Xu, Caihong, Yadav, Pradeep K., Yagüe, José, Yan, Cheng, Yang, Antti, Yoo, Woongsun, Yu, Wenjia, Yu, Shihao, Yueshen, Bart Zhou, Bos, Charles S., Yuferova, Darya, Zamojski, Marcin, Zareei, Abalfazl, Zeisberger, Stefan, Zhang, Lu, Zhang, Xiaoyu, Zhong, Zhuo, Zhou, Z. Ivy, Zhou, Chen, Zhu, Xingyu, Bosch-Rosa, Ciril, Zoican, Marius, Zwinkels, Remco C.J., Chen, Jian, Duevski, Teodor, Gao, Ge, Gemayel, Roland, Gilder, Dudley, Kuhle, Paul, Pagnotta, Emiliano, Pelli, Michele, Bouri, Elie, Sönksen, Jantje, Ilczuk, Konrad, Bogoev, Dimitar, Qian, Ya, Wika, Hans C., Yu, Yihe, Zhao, Lu, Mi, Michael, Bao, Li, Brownlees, Christian T., Vaduva, Andreea, Prokopczuk, Marcel, Avetikian, Alejandro, Wu, Zhen-Xing, Calamia, Anna, Cao, Viet Nga, Capelle-Blancard, Gunther, Capera, Laura, Caporin, Massimiliano, Huber, Juergen, Carrion, Allen, Caskurlu, Tolga, Chakrabarty, Bidisha, Chernov, Mikhail, Cheung, William Ming Yan, Chincarini, Ludwig B., Chordia, Tarun, Chow, Sheung Chi, Clapham, Benjamin, Colliard, Jean-Edouard, Johanneson, Magnus, Comerton-Forde, Carole, Curran, Edward, Dao, Thong, Dare, Wale, Davies, Ryan J., De Blasis, Riccardo, De Nard, Gianluca, Declerck, Fany, Deev, Oleg, Degryse, Hans, Kirchler, Michael, Deku, Solomon, Desagre, Christophe, Dim, Chukwuma, Dimpfl, Thomas, Dong, Yun Jiang, Drummond, Philip, Dudda, Tom, Dumitrescu, Ariadna, Dyakov, Teodor, Razen, Michael, Dyhrberg, Anne Haubo, Dzieliński, Michał, Eksi, Asli, El Kalak, Izidin, ter Ellen, Saskia, Eugster, Nicolas, Evans, Martin D.D., Farrell, Michael, Félez-Viñas, Ester, Ferrara, Gerardo, Weitzel, Utz, FERROUHI, El Mehdi, Flori, Andrea, Fluharty-Jaidee, Jonathan, Foley, Sean, Fong, Kingsley Y. L., Foucault, Thierry, Franus, Tatiana, Franzoni, Francesco A., Frijns, Bart, Frömmel, Michael, Abad, David, Fu, Servanna Mianjun, Füllbrunn, Sascha, Gan, Baoqing, Gehrig, Thomas, Gerritsen, Dirk, Gil-Bazo, Javier, Glosten, Lawrence R., Gomez, Thomas, Gorbenko, Arseny, Güçbilmez, Ufuk, and Van Dijk, Matthijs A.
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- 2024
13. Improving Predictive Capability in REHEDS Simulations with Fast, Accurate, and Consistent Non-Equilibrium Material Properties
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Hansen, Stephanie, primary, Baczewski, Andrew, additional, Gomez, Thomas, additional, Hentschel, T., additional, Jennings, Christopher, additional, Kononov, Alina, additional, Nagayama, Taisuke, additional, Adler, Kelsey, additional, Cangi, A., additional, Cochrane, Kyle, additional, Robinson, Brian, additional, and Schleife, A., additional
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- 2022
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14. Infrared Dynamics and Decay of Helicity in Homogeneous Isotropic Turbulence
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Briard, Antoine, Gomez, Thomas, Geurts, Bernard, Series Editor, Salvetti, Maria Vittoria, Series Editor, Gorokhovski, Mikhael, editor, and Godeferd, Fabien S., editor
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- 2019
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15. Data-driven predictions of the Lorenz system
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Dubois, Pierre, Gomez, Thomas, Planckaert, Laurent, and Perret, Laurent
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- 2020
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16. Second-Order Spectral Line Shift Comparisons
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Iglesias, Carlos, primary and Gomez, Thomas, additional
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- 2024
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17. Characteristic pancreatic and splenic immune cell infiltration patterns in mouse acute pancreatitis
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Yang, Baibing, Davis, Joy M., Gomez, Thomas H., Younes, Mamoun, Zhao, Xiurong, Shen, Qiang, Wang, Run, Ko, Tien C., and Cao, Yanna
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- 2021
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18. Chemical Abundances of RR Lyrae Type C Star AS162158
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Govea, Jose, Gomez, Thomas, Preston, George W., and Sneden, Christopher
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Astrophysics - Solar and Stellar Astrophysics - Abstract
We report the first extensive model atmosphere and detailed chemical abundance study of eight RR Lyrae variable stars of c subclass throughout their pulsation cycles. Atmospheric parameters effective temperature, surface gravity, microturbulent velocity, and metallicity have been derived. Spectra for this abundace analysis have been obtained with the echelle spectrograph of 100-inch du Pont telescope at Las Campanas Observatory. We have found metallicities and element abundance ratios to be constant within observational uncertainties at all phases of all stars. Moreover, the $\alpha$-element and Fe-group abundance ratios with respect to iron are consistent with other horizontal-branch members (RRab, blue and red non-variables). The [Fe/H] values of these eight RRc stars have been used to anchor the metallicity scale of a much larger sample of RRc stars obtained with low S/N "snapshot" spectra., Comment: Presented at the "40 Years of Variable Stars: A Celebration of Contributions by Horace A. Smith" conference (arXiv:1310.0149). 5 pages, 1 figure
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- 2013
19. Outflows from Evolved Stars: The Rapidly Changing Fingers of CRL618
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Balick, Bruce, Huarte-Espinosa, Martín, Frank, Adam, Gomez, Thomas, Alcolea, Javier, Corradi, Romano L. M., and Vinković, Dejan
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Astrophysics - Solar and Stellar Astrophysics - Abstract
Our ultimate goal is to probe the nature of the collimator of the outflows in the pre PN CRL618. CRL618 is uniquely suited for this purpose owing to its multiple, bright, and carefully studied finger-shaped outflows east and west of its nucleus. We compare new HST images to images in the same filters observed as much as 11 y previously to uncover large proper motions and surface brightness changes in its multiple finger-shaped outflows. The expansion age of the ensemble of fingers is close to 100y. We find strong brightness variations at the fingertips during the past decade. Deep IR images reveal a multiple ring- like structure of the surrounding medium into which the outflows propagate and interact. Tightly constrained three-dimensional ("3D") hydrodynamic models link the properties of the fingers to their possible formation histories. We incorporate previously published complementary information to discern whether each of the fingers of CRL618 are the results of steady, collimated outflows or a brief ejection event that launched a set of bullets about a century ago. Finally, we argue on various physical grounds that fingers of CRL618 are likely to be the result of a spray of clumps ejected at the nucleus of CRL618 since any mechanism that form a sustained set of unaligned jets is unprecedented., Comment: 18 pdf pages
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- 2013
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20. The [Fe/H] Dependence on the Ca {\sc ii}-$M_V$ Relationship
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Gomez, Thomas, Wallerstein, George, and Pancino, Elena
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Astrophysics - Solar and Stellar Astrophysics - Abstract
We examined the Wilson-Bappu effect, a relationship between the absolute magnitude of the star, $M_V$, and the logarithm of the Ca {\sc ii} emission width, $W_0$, over the largest $M_V$ range to date, +13 to -5, covering M-dwarfs to type Ia supergiants. We used an extensive literature, the latest Hipparcos reduction, data from two globular clusters, and new observations from Apache Point Observatory to compile a sample that allowed us to study the effect of [Fe/H] on the Wilson-Bappu relationship. Our results include reporting the deviations from linearity and demonstrating that the Wilson-Bappu relationship is insensitive to metallicity., Comment: 16 pages, 5 figures, accepted for publication in PASP
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- 2012
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21. The Illumination and Growth of CRL 2688: An Analysis of New & Archival HST Observations
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Balick, Bruce, Gomez, Thomas, Vinković, Dejan, Alcolea, Javier, Corradi, Romano L. M., and Frank, Adam
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Astrophysics - Solar and Stellar Astrophysics - Abstract
We present four-color images of CRL 2688 obtained in 2009 using the Wide-Field Camera 3 on HST. The F606W image is compared with archival images in very similar filters to monitor the proper motions of nebular structure. We find that the bright N-S lobes have expanded uniformly by 2.5% and that the ensemble of rings has translated radially by 0.07 in 6.65 y. The rings were ejected every 100y for ~4 millennia until the lobes formed 250y ago. Starlight scattered from the edges of the dark E-W dust lane is coincident with extant H2 images and leading tips of eight pairs of CO outflows. We interpret this as evidence that fingers lie within geometrically opposite cones of opening angles {\approx} 30{\circ} like those in CRL618. By combining our results of the rings with 12CO absorption from the extended AGB wind we ascertain that the rings were ejected at ~18 km s-1 with very little variation and that the distance to CRL2688, v_{exp}$ / ${\dot\theta}_exp$, is 300 - 350 pc. Our 2009 imaging program included filters that span 0.6 to 1.6{\mu}m. We constructed a two-dimensional dust scattering model of stellar radiation through CRL2688 that successfully reproduces the details of the nebular geometry, its integrated spectral energy distribution, and nearly all of its color variations. The model implies that the optical opacity of the lobes >~ 1, the dust particle density in the rings decreases as radius^{-3} and that the mass and momentum of the AGB winds and their rings have increased over time., Comment: (51 pages, 6 figures; accepted by ApJ)
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- 2011
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22. Metal Abundance Calibration of the Ca II Triplet Lines in RR Lyrae Stars
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Wallerstein, George, Gomez, Thomas, and Huang, Wenjin
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Astrophysics - Solar and Stellar Astrophysics - Abstract
The GAIA satellite is likely to observe thousands of RR Lyrae stars within a small spectral window, between 8470A and 8750A, at a resolution of 11,500. In order to derive the metallicity of RR Lyrae stars from Gaia, we have obtained numerous spectra of RR Lyrae stars at a resolution of 35,000 with the Apache Point Observatory 3.5 m echelle spectrograph. We have correlated the Ca II triplet line strengths with metallicity as derived from Fe II abundances, analogous to Preston's (1959) use of the Ca II K line to estimate the metallicity of RR Lyrae stars. The Ca II line at 8498A is the least blended with neighboring Paschen lines and thus provides the best correlation., Comment: Accepted for publication in Astrophysics & Space Science
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- 2011
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23. Estimating Risk to Responders Exposed to Avian Influenza A H5 and H7 Viruses in Poultry, United States, 2014-2017
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Olsen, Sonja J., Rooney, Jane A., Blanton, Lenee, Rolfes, Melissa A., Nelson, Deborah I., Gomez, Thomas M., Karli, Steven A., Trock, Susan C., and Fry, Alicia M.
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United States. Department of Agriculture ,United States. Centers for Disease Control and Prevention ,Avian influenza -- Health aspects ,Poultry industry -- Health aspects ,Avian influenza viruses -- Health aspects ,Influenza ,Health ,World Health Organization - Abstract
In late 2014 and early 2015, highly pathogenic avian influenza (HPAI) A(H5N2), A(H5N1), and A(H5N8) viruses were detected in poultry and wild birds in the United States and Canada. A [...]
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- 2019
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24. A Quantum-mechanical Treatment of Electron Broadening in Strong Magnetic Fields
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Gomez, Thomas A., primary, Zammit, Mark C., additional, Fontes, Christopher J., additional, and White, Jackson R., additional
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- 2023
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25. Predicting unresolved scales interactions with 3D neural networks in homogeneous isotropic turbulence
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Saura, Nathaniel, primary and Gomez, Thomas, additional
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- 2023
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26. Infrared Dynamics and Decay of Helicity in Homogeneous Isotropic Turbulence
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Briard, Antoine, primary and Gomez, Thomas, additional
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- 2019
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27. Equal response rates maintained by concurrent drug and nondrug reinforcers: a design for treatment evaluation
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Meisch, Richard A., Gomez, Thomas H., and Lane, Scott D.
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- 2020
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28. Pre-Procedural Considerations and Post-Procedural Care for Animal Models with Experimental Traumatic Brain Injury
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Robinson, Mary A., primary, Jaber, Samer M., additional, Piotrowski, Stacey L., additional, and Gomez, Thomas H., additional
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- 2018
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29. Does U.S. Monetary Policy Respond to Macroeconomic Uncertainty?
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Gomez, Thomas, primary and Piccillo, Giulia, additional
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- 2023
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30. Non-Standard Errors
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Menkfeld, Albert J., Dreber, Anna, Holzmeister, Felix, Huber, Juergen, Johannesson, Magnus, Kirchler, Michael, Neusüss, Sebastian, Razen, Michael, Weitzel, Utz, Abad-Díaz, David, Abudy, Menachem, Adrian, Tobias, Ait-Sahalia, Yacine, Akmansoy, Olivier, Alcock, Jamie T., Alexeev, Vitali, Aloosh, Arash, Amato, Livia, Amaya, Diego, Angel, James J., Avetikian, Alejandro T., Bach, Amadeus, Baidoo, Edwin, Bakalli, Gaetan, Bao, Li, Barbon, Andrea, Bashchenko, Oksana, Bindra, Parampreet C., Bjønnes, Geir H., Black, Jeffrey R., Black, Bernard S., Bogoev, Dimitar, Bohorquez Correa, Santiago, Bondarenko, Oleg, Bos, Charles S., Bosch-Rosa, Ciril, Bouri, Elie, Brownlees, Christian, Calamia, Anna, Cao, Viet Nga, Capelle-Blancard, Gunther, Capera Romero, Laura M., Caporin, Massimiliano, Carrion, Allen, Caskurlu, Tolga, Chakrabarty, Bidisha, Chen, Jian, Chernov, Mikhail, Cheung, William, Chincarini, Ludwig B., Chordia, Tarun, Chow, Sheung-Chi, Clapham, Benjamin, Colliard, Jean-Edouard, Comerton-Forde, Carole, Curran, Edward, Dao, Thong, Dare, Wale, Davies, Ryan J., De Blasis, Riccardo, De Nard, Gianluca F., Declerck, Fany, Deev, Oleg, Degryse, Hans, Deku, Solomon Y., Desagre, Christophe, van Dijk, Mathijs A., Dim, Chukwuma, Dimpfl, Thomas, Dong, Yun Jiang, Drummond, Philip A., Dudda, Tom, Duevski, Teodor, Dumitrescu, Ariadna, Dyakov, Teodor, Dyhrberg, Anne Haubo, Dzielinski, Michał, Eksi, Asli, El Kalak, Izidin, ter Ellen, Saskia, Eugster, Nicolas, Evans, Martin D. D., Farrell, Michael, Felez-Vinas, Ester, Ferrara, Gerardo, Ferrouhi, El Mehdi, Flori, Andrea, Fluharty, Jonathan T., Foley, Sean D. V., Fong, Kingsley Y. L., Foucault, Thierry, Franus, Tatiana, Franzoni, Francesco, Frijns, Bart, Frömmel, Michael, Fu, Servanna M., Füllbrunn, Sascha C., Gan, Baoqing, Gao, Ge, Gehrig, Thomas P., Gemayel, Roland, Gerritsen, Dirk, Gil-Bazo, Javier, Gilder, Dudley, Glosten, Lawrence R., Gomez, Thomas, Gorbenko, Arseny, Grammig, Joachim, Grégoire, Vincent, Güçbilmez, Ufuk, Hagströmer, Björn, Hambuckers, Julien, Hapnes, Erik, Harris, Jeffrey H., Harris, Lawrence, Hartmann, Simon, Hasse, Jean-Baptiste, Hautsch, Nikolaus, He, Xue-Zhong (Tony), Heath, Davidson, Hediger, Simon, Hendershott, Terrence, Hibbert, Ann Marie, Hjalmarsson, Erik, Hoelscher, Seth, Hoffmann, Peter, Holden, Craig W., Horenstein, Alex R., Huang, Wenqian, Huang, Da, Hurlin, Christophe, Ilczuk, Konrad, Ivashchenko, Alexey, Iyer, Subramanian R., Jahanshahloo, Hossein, Jalkh, Naji P., Jones, Charles M., Jurkatis, Simon, Jylhä, Petri, Kaeck, Andreas T., Kaiser, Gabriel, Karam, Arzé, Karmaziene, Egle, Kassner, Bernhard, Kaustia, Markku, Kazak, Ekaterina, Kearney, Fearghal, Kervel, Vincent van, Khan, Saad A., Khomyn, Marta K., Klein, Tony, Klein, Olga, Klos, Alexander, Koetter, Michael, Kolokolov, Aleksey, Korajczyk, Robert A., Kozhan, Roman, Krahnen, Jan P., Kuhle, Paul, Kwan, Amy, Lajaunie, Quentin, Lam, F. Y. Eric C., Lambert, Marie, Langlois, Hugues, Lausen, Jens, Lauter, Tobias, Leippold, Markus, Levin, Vladimir, Li, Yijie, Li, Hui, Liew, Chee Yoong, Lindner, Thomas, Linton, Oliver, Liu, Jiacheng, Liu, Anqi, Llorente, Guillermo, Lof, Matthijs, Lohr, Ariel, Longstaff, Francis, Lopez-Lira, Alejandro, Mankad, Shawn, Mano, Nicola, Marchal, Alexis, Martineau, Charles, Mazzola, Francesco, Meloso, Debrah, Mi, Michael G., Mihet, Roxana, Mohan, Vijay, Moinas, Sophie, Moore, David, Mu, Liangyi, Muravyev, Dmitriy, Murphy, Dermot, Neszveda, Gabor, Neumeier, Christian, Nielsson, Ulf, Nimalendran, Mahendrarajah, Nolte, Sven, Norden, Lars L., O'Neill, Peter W., Obaid, Khaled, Ødegaard, Bernt A., Östberg, Per, Pagnotta, Emiliano, Painter, Marcus, Palan, Stefan, Palit, Imon J., Park, Andreas, Pascual, Roberto, Pasquariello, Paolo, Pastor, Lubos, Patel, Vinay, Patton, Andrew J., Pearson, Neil D., Pelizzon, Loriana, Pelli, Michele, Pelster, Matthias, Pérignon, Christophe, Pfiffer, Cameron, Philip, Richard, Plíhal, Tomáš, Prakash, Puneet, Press, Oliver-Alexander, Prodromou, Tina, Prokopczuk, Marcel, Putnins, Talis, Qian, Ya, Raizada, Gaurav, Rakowski, David, Ranaldo, Angelo, Regis, Luca, Reitz, Stefan, Renault, Thomas, Renjie, Rex W., Reno, Roberto, Riddiough, Steven J., Rinne, Kalle, Rintamäki, Paul J., Riordan, Ryan, Rittmannsberger, Thomas, Rodríguez Longarela, Iñaki, Roesch, Dominik, Rognone, Lavinia, Roseman, Brian, Rosu, Ioanid, Roy, Saurabh, Rudolf, Nicolas, Rush, Stephen R., Rzayev, Khaladdin, Rzeznik, Aleksandra A., Sanford, Anthony, Sankaran, Harikumar, Sarkar, Asani, Sarno, Lucio, Scaillet, Olivier, Scharnowski, Stefan, Schenk-Hoppé, Klaus R., Schertler, Andrea, Schneider, Michael, Schroeder, Florian, Schürhoff, Norman, Schuster, Philipp, Schwarz, Marco A., Seasholes, Mark S., Seeger, Norman J., Shachar, Or, Shkilko, Andriy, Shui, Jessica, Sikic, Mario, Simion, Giorgia, Smales, Lee A., Söderlind, Paul, Sojli, Elvira, Sokolov, Konstantin, Sönksen, Jantje, Spokeviciute, Laima, Stefanova, Denitsa, Subrahmanyam, Marti G., Szaszi, Barnabas, Talavera, Oleksandr, Tang, Yuehua, Taylor, Nick, Tham, Wing Wah, Theissen, Erik, Thimme, Julian, Tonks, Ian, Tran, Hai, Trapin, Luca, Trolle, Anders B., Vaduva, M. Andreea, Valente, Giorgio, Van Ness, Robert A., Vasquez, Aurelio, Verousis, Thanos, Verwijmeren, Patrick, Vilhelmsson, Anders, Vilkov, Grigory, Vladimirov, Vladimir, Vogel, Sebastian, Voigt, Stefan, Wagner, Wolf, Walther, Thomas, Weiss, Patrick, van der Wel, Michel, Werner, Ingrid M., Westerholm, Joakim, Westheide, Christian, Wika, Hans C., Wipplinger, Evert, Wolf, Michael, Wolff, Christian C. P., Wolk, Leonard, Wong, Wink-Keung, Wrampelmeyer, Jan, Wu, Zhen-Xing, Xia, Shuo, Xiu, Dacheng, Xu, Ke, Xu, Caihong, Yadav, Pradeep K., Yagüe, José, Yan, Cheng, Yang, Antti, Yoo, Woongsun, Yu, Wenjia, Yu, Yihe, Yu, Shihao, Yueshen, Bart Z., Yuferova, Darya, Zamojski, Marcin, Zareei, Abalfazl, Zeisberger, Stefan M., Zhang, Lu, Zhang, S. Sarah, Zhang, Xiaoyu, Zhao, Lu, Zhong, Zhuo, Zhou, Zeyang (Ivy), Zhou, Chen, Zhu, Xingyu S., Zoican, Marius, Zwinkels, Remco, Finance, and Tinbergen Institute
- Subjects
jel:G14 ,jel:G1 ,ddc:330 ,jel:C12 - Abstract
In statistics, samples are drawn from a population in a data- generating process (DGP). Standard errors measure the uncer- tainty in sample estimates of population parameters. In sci- ence, evidence is generated to test hypotheses in an evidence- generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sam- ple. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
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- 2023
- Full Text
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31. The roles of uncertainty and beliefs in the economy
- Author
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Gomez, Thomas, UU LEG Research UUSE Multidisciplinary Economics, Finance, Weitzel, Utz, Frank, Jason, Piccillo, Giulia, Lugo, Stefano, and University Utrecht
- Subjects
Rational Beliefs ,Real-time data ,Heterogeneous expectations ,Bounded rationality ,Uncertainty ,Onzekerheid ,Asset pricing ,Animal spirits ,Begrensde rationaliteit ,Monetair beleid ,Sentiment ,Heterogene risico aversiteit ,Monetary policy ,Heuristic switching ,Heterogeneous risk aversion ,Heterogene verwachtingen - Abstract
In this dissertation, I examine the roles of uncertainty and beliefs in the economy. In chapter 2, I investigate whether macroeconomic uncertainty affects monetary-policy decisions in the US. Eight times per year, the Federal Open Market Committee (FOMC) meets to review monetary policy in light of current economic conditions. I assume that the FOMC members use a standard macroeconomic model to make sense of the economic conditions. It captures the relationships between economic growth, inflation, and the interest rate. I further assume that the policymakers are Bayesian learners: as new data comes in, they update their beliefs about the model’s parameters. These beliefs are represented by a probability distribution. I derive a measure of macroeconomic uncertainty from its dispersion. In constructing this uncertainty measure, I use macroeconomic data as it was available at each FOMC meeting. I estimate the impact of this real-time, Bayesian measure of macroeconomic uncertainty on the FOMC’s interest rate decisions. I find that policymakers set a significantly lower interest rate in times of higher macroeconomic uncertainty. In the third chapter of this dissertation, I investigate how risk attitudes influence beliefs. I adopt the heuristic switching model, in which economic agents choose between simple forecasting rules to form beliefs. I introduce a role for risk aversion in agents’ choice between these rules: they choose a rule based on its performance and the variability of that performance. Agents have different risk preferences, and therefore choose different rules, leading to heterogeneous expectations. To empirically validate the model, I draw the agents’ risk aversions from a distribution based on survey data. I incorporate this belief-formation model in a stylized financial market. I prove that a representative agent cannot capture this model. Simulations show that the resulting belief dynamics can drive unpredictable booms and busts in the asset price. Introducing small stochastic price shocks leads to larger asset price bubbles and can destabilize markets. In chapter 4, I propose an explanation for the mixed results from studies about the role of sentiment in economics: these studies measure different dimensions of sentiment that have distinct macroeconomic impacts. To test this hypothesis, I rely on Rational Beliefs theory. It implies that sentiment can be measured as the difference between observed forecasts and non-judgmental forecasts based on the available data. I use observed forecasts from the Survey of Professional Forecasters, covering 50 years, approximately 40 forecasters per survey, various economic variables (e.g., output, prices, interest rates, housing), and multiple forecasting horizons. I approximate the non-judgmental forecasts by collecting a large panel of real-time data covering all relevant aspects of the economy and using a statistical model to produce predictions. I use factor analysis to identify three dimensions that together capture about 50% of forecasters’ sentiment. I find that sentiment is indeed multidimensional, with the first dimension explaining only about a fifth of its variation. I furthermore find that each dimension has a distinct macroeconomic impact, supporting my hypothesis. My results also indicate that the survey forecasts are not always rational.
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- 2022
32. Multistate Outbreak of Human Salmonella Infections Linked to Live Poultry from a Mail-Order Hatchery in Ohio — February–October 2014
- Author
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Basler, Colin, Forshey, Tony M., Machesky, Kimberly, Erdman, C. Matthew, Gomez, Thomas M., Brinson, Denise L., Nguyen, Thai-An, Behravesh, Casey Barton, and Bosch, Stacey
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- 2015
33. Estimation des indices de Sobol pour les solutions d’Équations Différentielles Ordinaires à l’aide d’un modèle multi-élément par chaos polynomial
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Vauchel, Nicolas, Garnier, Eric, Gomez, Thomas, DAAA, ONERA [Lille], ONERA, Laboratoire de Mécanique des Fluides de Lille – Kampé de Fériet - UMR 9014 (LMFL), Centrale Lille-ONERA-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Sciences et Technologies, and HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)
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indices de Sobol ,[PHYS]Physics [physics] ,[SPI]Engineering Sciences [physics] ,Équations Différentielles Ordinaires ,Machine learning ,Quantification d’incertitude ,Uncertainty Quantification ,Chaos polynomial multi-élément ,Apprentissage automatique ,Multi-element polynomial chaos ,Flight Dynamics ,Sobol indices - Abstract
International audience; Flight Dynamics aims at studying the motion of an aircraft modelled as a solid. The equations of motion are gathered in a dynamical system of coupled Ordinary Differential Equations. Classically, behaviours of the aircraft are linked to equilibria of this system, and bifurcation theory is used. In the dynamical system, the forces and the moments from the fluid on the aircraft rely on models with a chosen structure, constructed with data coming from experiments. These models are therefore uncertain. It had be shown that the uncertainties of these models can have influence on some equilibria, notably on their stability. In this paper, a joint Uncertainty Quantification and Global Sensitivity Analysis study is conducted on the temporal evolution of a given predicted behaviour of a light aircraft. As different combinations of the uncertain parameters can lead to instability of the behaviour and other combinations to stability, the state variables of the dynamical system can present some irregularities or some discontinuities with respect to the uncertain parameters at a given instant. In this paper, a method to estimate Sobol indices of a solution of an Ordinary Differential Equation approximated with a multi-element polynomial chaos model is therefore used. It relies on two upcoming papers. The first paper presents a method relying on Machine learning methods to get a multi-element polynomial chaos model for a non-time dependent Quantity of Interest. The second one extends the analytical formula between the Sobol indices and the coefficients of a polynomial chaos surrogate model to the case of a multi-element polynomial chaos model. In the present paper, the time-dependent extension of the multi-element model is introduced. The analytical formula permits to find Sobol indices from the coefficients of the local polynomial models at every considered instants. Conversely to standard polynomial chaos models, the use of a multi-element model permits to accurately approximate solutions of Ordinary Differential Equation with bifurcations, being irregular or discontinuous with respect to the input parameters at some instants. This approach is then used to conduct the sensitivity study on the state variables of an aircraft behaviour predicted by the Flight Dynamics system.; La Quantification d’incertitude a pour but d’étudier l’impact de certains paramètres sur une Quantité d’intérêt (QOI). Les paramètres sélectionnés sont nommés les paramètres d’entrée. Ils sont supposés aléatoires, indépendants, et sont supposés suivre une loi de distribution stochastique de densité de probabilité connue. Les indices de Sobol, reposant sur la définition des variances partielles, classent les actions des paramètres d’entrée et les interactions entre ces paramètres d’après leur impact sur la QOI. Les indices donnent également un aspect quantitatif de ces impacts. Les indices de Sobol au premier ordre et les indices de Sobol totaux peuvent être estimés avec des méthodes de Monte-Carlo, mais nécessitent souvent un grand nombre de simulations. Approchant la relation entre le QOI et les paramètres d’entrée utilisant un méta-modèle par chaos polynomial avec le « generalised Polynomials Chaos » (gPC) framework permet d’établir un lien analytique entre les coefficients du métamodèle et les indices de Sobol. Une fois le métamodèle obtenu, les indices de Sobol sont accessibles. Néanmoins, les modèles par chaos polynomial ne sont pas précis en présence d’irrégularités ou de discontinuités. Un grand nombre de termes de la série est parfois nécessaire pour obtenir une précision acceptable, ce qui peut devenir problématique avec la célèbre malédiction de la dimensionnalité. De plus, le phénomène de Gibbs perdure et s’amplifie lorsque le degré de troncature de la série est augmenté alors que la QOI est discontinue.Les modèles multi-élément (ME) ont été développé pour résoudre ce problème. L’espace des paramètres, espace abstrait contenant toutes les valeurs possibles des paramètres d’entrée, est partitionné en sous-ensembles nommés éléments où la QOI est plus régulière et des modèles gPC locaux sont entrainés sur chacun de ces éléments. Le modèle global est donc un modèle par morceaux et contient une méthode afin de déterminer quel modèle local utiliser lors d’une évaluation. Néanmoins, avec ce modèle par morceaux, le lien analytique avec les indices de Sobol est perdu. Dans un article en cours d’écriture qui sera bientôt soumis, le lien analytique entre les indices de Sobol et les coefficients du chaos sera étendu dans les cas des modèles ME avec une QOI ne dépendant pas du temps. Dans cet article, une nouvelle approche est présentée. En premier lieu, les paramètres d’entrée subissent une bijection vers des nouvelles variables contenues dans l’hypercube unité. Ensuite, une matrice d’interaction contenant toutes les informations nécessaires pour obtenir les variances partielles et l’espérance est calculée. Les indices de Sobol sont ainsi accessibles à l’aide de cette matrice. Ce lien analytique entre les coefficients du métamodèle ME et les indices de Sobol est une extension de la formule effectuant le lien entre les indices de Sobol et les modèles gPC standards.Dans le présent article, nous étendons cette approche aux QOIs étant solutions de systèmes d’Équations Différentielles Ordinaires (ODE), et donc dépendantes du temps. La version dépendante du temps d’une nouvelle méthode ME appelée ME-ACD, développée dans un article qui sera également bientôt soumis, est utilisée. N’importe quelle méthode ME pourrait être utilisée à la place. La nouvelle approche est ainsi capable de donner une estimation des indices de Sobol avec un nombre de résolutions du système relativement bas, même si à un certain instant, la QOI est irrégulière ou discontinue (traduisant la présence de bifurcations) par rapport aux paramètres d’entrée. La précision de l’approche est étudiée sur plusieurs applications. Tout d’abord, une ODE classique est testée. Ensuite, la précision de la méthode est testée sur un système théorique modélisant l’apparition d’une bifurcation. En dernier lieu, l’approche est utilisée dans un cas pratique de Dynamique du vol.
- Published
- 2022
34. Alcool, fisc et santé publique en Nouvelle-Grenade au XVIIIe siècle
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Gomez, Thomas
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HBLL ,influence espagnole ,péninsule ibérique ,History ,histoire ,civilisations précolombiennes ,HBJK ,1500-1800 ,HIS038000 ,Amérique latine ,HIS037030 - Abstract
La consommation et la distribution de l’alcool de fabrication locale firent l’objet de polémiques incessantes tout au long de la période coloniale en Nouvelle-Grenade. Cependant, durant la deuxième moitié du xviie siècle, le pouvoir essaya de donner à ce produit de consommation courante une légitimité d’autant plus souhaitable qu’il constituait une source de revenus non négligeable pour le trésor public. En effet, par ordre décroissant de rentabilité, le monopole de l’alcool sous différentes ...
- Published
- 2022
35. Des Indes occidentales à l’Amérique latine
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Acuña Ortega, Victor Hugo, Allard, Jeanne, Alvarez Santaló, León Carlos, Bazarte Martínez, Alicia, Béligand, Nadine, Berthe, Jean-Pierre, Bertrand, Michel, Borah, Woodrow, Bouysse Cassagne, Thérèse, Calvo, Thomas, Casanueva, Fernando, Castañeda, Carmen, Castillo Palma, Norma Angélica, Chenu, Jeanne, Cramaussel, Chantal, Cuevas, Mario M. A., Dehouve, Danièle, Del Pino Díaz, Fermín, Demélas-Bohy, Marie-Danielle, Durand-Forest, Jacqueline de, Fernández Tejedo, Isabel, G. de los Arcos, María Fernanda, Garcia-Baquero González, Antonio, Garner, Richard L., Girard, Pascale, Gomez, Thomas, González-Hermosillo Adams, Francisco, Herrejón Peredo, Carlos, Hirzy, Jacques, Lavrín, Asunción, Mansuy Diniz Silva, Andrée, Mazín, Oscar, Meyer, Jean, Morin, Claude, Musset, Alain, Pérez-Mallaína, Pablo Emilio, Ponsot, Pierre, Pouligny-Gresle, Dominique, Rodríguez Álvarez, María de los Angeles, Rucquoi, Adeline, Solórzano Fonseca, Juan Carlos, Stein, Stanley J., Stresser-Péan, Guy, Taracena Arriola, Arturo, Val Julián, Carmen, Viqueira, Juan Pedro, von Wobeser, Gisela, Womack, John, Musset, Alain, and Calvo, Thomas
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HBLL ,influence espagnole ,péninsule ibérique ,History ,histoire ,civilisations précolombiennes ,HBJK ,1500-1800 ,HIS038000 ,Amérique latine ,HIS037030 - Abstract
L’Amérique latine et ses relations avec la péninsule ibérique. En hommage à Jean-Pierre Berthe, ces quarante-six contributions veulent donner de ce vaste ensemble, hétérogène sur le plan politique mais cohérent sur le plan culturel, une vision dynamique fondée sur la prise en compte de la longue durée. Le regard croisé d’historiens, de géographes, de sociologues, d’ethnologues et de linguistes permet de varier les approches scientifiques et de comparer des problématiques de recherche. Un outil de recherche qui offre au lecteur curieux mille sujets de réflexion.
- Published
- 2022
36. Balrog Code Description.
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Gomez, Thomas, primary
- Published
- 2022
- Full Text
- View/download PDF
37. A Statistical Approach to Stark Broadening for Complex Ions.
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Adler, Kelsey, primary, Gomez, Thomas, additional, Shaffer, Nathaniel, additional, Starrett, Charles, additional, and Hansen, Stephanie, additional
- Published
- 2022
- Full Text
- View/download PDF
38. Anesthesia for Echocardiography and Magnetic Resonance Imaging in the African Clawed Frog (Xenopus laevis)
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Corno, Antonio F, primary, Flores, Noelia E, additional, Li, Wen, additional, Gomez, Thomas H, additional, and Salazar, Jorge D, additional
- Published
- 2022
- Full Text
- View/download PDF
39. H2+ Quasi Molecular Line Shape Profiles in Stellar Atmospheres.
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White, Jackson, primary, Gomez, Thomas, additional, Montgomery, Michael, additional, and Dunlap, Bart, additional
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- 2022
- Full Text
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40. Backyard Poultry Flocks and Salmonellosis: A Recurring, Yet Preventable Public Health Challenge
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Behravesh, Casey Barton, Brinson, Denise, Hopkins, Brett A., and Gomez, Thomas M.
- Published
- 2014
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- View/download PDF
41. Multistate Outbreak of Human Salmonella Infections Linked to Live Poultry from a Mail-Order Hatchery in Ohio — March–September 2013
- Author
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Basler, Colin, Forshey, Tony M., Machesky, Kimberly, Erdman, C. Matthew, Gomez, Thomas M., Nguyen, Thai-An, and Behravesh, Casey Barton
- Published
- 2014
42. A multi-element non-intrusive Polynomial Chaos method using agglomerative clustering based on the derivatives to study irregular and discontinuous Quantities of Interest
- Author
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Vauchel, Nicolas, Garnier, Éric, Gomez, Thomas, DAAA, ONERA [Lille], ONERA, Laboratoire de Mécanique des Fluides de Lille – Kampé de Fériet - UMR 9014 (LMFL), Centrale Lille-ONERA-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Sciences et Technologies, and HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)
- Subjects
[PHYS]Physics [physics] ,[SPI]Engineering Sciences [physics] ,Machine learning ,MULTI-ELEMENT ,Uncertainty Quantification ,CHAOS POLYNOMIAL ,APPRENTISSAGE NUMERIQUE ,Multi-element polynomial chaos ,QUANTIFICATION INCERTITUDE - Abstract
A non-intrusive method to get a multi-element polynomial chaos model is developed. This method is called ME-ACD, for Multi-Element based on Agglomerative Clustering on Derivatives. It aims at approximating a Quantity of Interest which presents discontinuities or irregularities making it difficult to be accurately approximated by standard Polynomial Chaos models. The method permits to efficiently split the parameter space and to train local polynomial models of lower degrees on every element where the local pieces of the Quantity of Interest are smoother. The algorithm is based on agglomerative clustering of the observations in a well-chosen abstract space taking into account the value of the Quantity of Interest and of its derivatives with respect to the stochastic input parameters. The same observations are used for both partitioning the space and training the local models. Several partitions of the parameter space are tested, and the one leading to local models minimizing a crossvalidation error is selected. Once the training observations are labelled with a class number indicating the element they are located in, a neural network classifier is trained to determine which local model to use for further evaluations. The method has proven to efficiently split the parameter space for a set of applications and the piecewise chaos model is compared with a standard Polynomial Chaos non-intrusive method and a Gradient Tree Boosting in terms of accuracy.; Une méthode non-intrusive ayant pour but d’obtenir un modèle par chaos polynomial multi-élément est développée. La méthode se nomme ME-ACD, acronyme Anglais signifiant « méthode multi-élément basée sur la classification hiérarchique ascendante des dérivées ». Le modèle a pour objectif d’approcher les Quantités d’intérêt présentant des discontinuités et/ou des irrégularités altérant la précision des modèles par chaos polynomial standards qui l’approchent. La méthode permet de partitionner efficacement l’espace des paramètres et d’entrainer des méta-modèles par chaos polynomial locaux de degrés inférieurs sur chaque sous-ensemble de l’espace des paramètres où les morceaux de la Quantité d’intérêt est plus régulière localement. L’algorithme repose sur le regroupement hiérarchique ascendant des observations représentées par des points dans un espace abstrait prenant en compte la valeur de la Quantité ainsi que les valeurs de ses dérivées par rapport aux paramètres d’entrée stochastiques. Les mêmes observations sont utilisées pour la partition de l’espace et pour l’entrainement des modèles locaux. Plusieurs partitions de l’espace sont testées, et celle menant à des modèles locaux minimisant une erreur de validation croisée est sélectionnée. Une fois que les observations d’entrainement sont associées à un numéro indiquant dans quel élément elles sont localisées, un réseau de neurones est entrainé pour déterminer quel modèle local sera utilisé pour les évaluations à venir. L’efficacité de la méthode est montrée sur un ensemble d’applications et la précision du modèle par morceaux est comparée avec celle d’un modèle par chaos polynomial standard obtenu par une méthode non-intrusive et celle d’un modèle « Gradient Tree Boosting ».
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- 2022
43. Spiral small-scale structures in compressible turbulent flows
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Gomez, Thomas, Politano, Hélène, Pouquet, Annick, LarchevÊque, Michèle, Moreau, R., editor, Bajer, K., editor, and Moffatt, H. K., editor
- Published
- 2002
- Full Text
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44. Human Infections With Influenza A(H3N2) Variant Virus in the United States, 2011–2012
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Influenza A (H3N2)v Virus Investigation Teama, Epperson, Scott, Jhung, Michael, Richards, Shawn, Quinlisk, Patricia, Ball, Lauren, Moll, Mària, Boulton, Rachelle, Haddy, Loretta, Biggerstaff, Matthew, Brammer, Lynnette, Trock, Susan, Burns, Erin, Gomez, Thomas, Wong, Karen K., Katz, Jackie, Lindstrom, Stephen, Klimov, Alexander, Bresee, Joseph S., Jernigan, Daniel B., Cox, Nancy, and Finelli, Lyn
- Published
- 2013
- Full Text
- View/download PDF
45. Virus sensor based on single-walled carbon nanotube: improved theory incorporating surface effects
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Elishakoff, Isaac, Challamel, Noël, Soret, Clément, Bekel, Yannis, and Gomez, Thomas
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- 2013
- Full Text
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46. Mantle Sources of Martian Basalts as Constrained by MAGMARS, a New Melting Model for FeO-rich Peridotite
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Collinet, Max, Plesa, Ana-Catalina, Ruedas Gomez, Thomas, Schwinger, Sabrina, and Breuer, Doris
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Mars ,InSight - Published
- 2022
47. The roles of uncertainty and beliefs in the economy
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UU LEG Research UUSE Multidisciplinary Economics, Finance, Weitzel, Utz, Frank, Jason, Piccillo, Giulia, Lugo, Stefano, Gomez, Thomas, UU LEG Research UUSE Multidisciplinary Economics, Finance, Weitzel, Utz, Frank, Jason, Piccillo, Giulia, Lugo, Stefano, and Gomez, Thomas
- Published
- 2022
48. Lecture Notes on Turbulence
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Sagaut, Pierre, primary and Gomez, Thomas, additional
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- 2022
- Full Text
- View/download PDF
49. Subgrid Stress Tensor Prediction in Homogeneous Isotropic Turbulence Using 3D-Convolutional Neural Networks
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Saura, Nathaniel, primary and Gomez, Thomas, additional
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- 2022
- Full Text
- View/download PDF
50. All-Order Full-Coulomb Quantum Spectral Line Shape Calculations.
- Author
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Gomez, Thomas, primary
- Published
- 2021
- Full Text
- View/download PDF
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