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Record W2728077148 · doi:10.1093/pasj/psx072

Search for thermal X-ray features from the Crab nebula with the Hitomi soft X-ray spectrometer

2017· article· en· W2728077148 on OpenAlexafffund
Hiroki Akamatsu, Fumie Akimoto, S. W. Allen, L. Angelini, M. Audard, Hisamitsu Awaki, M. Axelsson, Aya Bamba, M. Bautz, Roger Blandford, Laura Brenneman, G. V. Brown, Esra Bülbül, Edward Cackett, M. Chernyakova, Meng P. Chiao, P. Coppi, J. de Plaa, C. P. de Vries, Jan-Willem den Herder, Chris Done, Tadayasu Dotani, Ken Ebisawa, Megan E. Eckart, Teruaki Enoto, Yuichiro Ezoe, Andrew C Fabian, C. Ferrigno, Adam Foster, Ryuichi Fujimoto, Yasushi Fukazawa, Akihiro Furuzawa, Massimiliano Galeazzi, Luigi Gallo, Poshak Gandhi, M. Giustini, A. Goldwurm, Liyi Gu, M. Guainazzi, Yoshito Haba, Kouichi Hagino, Kenji Hamaguchi, I. Harrus, Isamu Hatsukade, Katsuhiro Hayashi, Takayuki Hayashi, Kiyoshi Hayashida, Junko S Hiraga, A. E. Hornschemeier, Akio Hoshino, John P. Hughes, Yuto Ichinohe, Ryo Iizuka, Hajime Inoue, Yoshiyuki Inoue, M. Ishida, Kumi Ishikawa, Yoshitaka Ishisaki, J. S. Kaastra, Tim Kallman, T. Kamae, Jun Kataoka, Satoru Katsuda, N. Kawai, Richard L Kelley, Caroline A Kilbourne, Takao Kitaguchi, Shunji Kitamoto, Tetsu Kitayama, Takayoshi Kohmura, M. Kokubun, Katsuji Koyama, Shu Koyama, P. Kretschmar, H. Krimm, Aya Kubota, Hideyo Kunieda, Philippe Laurent, S.-H. Lee, Maurice A. Leutenegger, Olivier Limousin, Michael Loewenstein, Knox S. Long, David Lumb, Greg Madejski, Yoshitomo Maeda, Daniel Maier, Kazuo Makishima, Maxim Markevitch, Hironori Matsumoto, Kyoko Matsushita, D. McCammon, Brian R McNamara, M. Mehdipour, Eric D. Miller, J. M. Mïller, Shin Mineshige, Kazuhisa Mitsuda, Ikuyuki Mitsuishi, Takuya Miyazawa, Tsunefumi Mizuno, Hideyuki Mori, Koji Mori, Koji Mukai, Hiroshi Murakami, R. F. Mushotzky, Takao Nakagawa, Hiroshi Nakajima, Takeshi Nakamori, Shinya Nakashima, Kazuhiro Nakazawa, Kumiko Nobukawa, Masayoshi Nobukawa, Hirofumi Noda, Hirokazu Odaka, Takaya Ohashi, Masanori Ohno, Takashi Okajima, Naomi Ota, Masanobu Ozaki, Frits Paerels, Stéphane Paltani, Robert Petre, C. Pinto, Frederick S Porter, K. Pottschmidt, C. S. Reynolds, Samar Safí-Harb, Shinya Saito, Kazuhiro Sakai, Toru Sasaki, Goro Sato, Kosuke Sato, Rie Sato, Toshiki Sato, Makoto Sawada, N. Schartel, Peter J Serlemtsos, Hiromi Seta, M. Shidatsu, A. Simionescu, Randall K Smith, Yang Soong, Ł. Stawarz, Y. Sugawara, Satoshi Sugita, Andrew Szymkowiak, H. Tajima, H. Takahashi, Tadayuki Takahashi, Shin ́ichiro Takeda, Yoh Takei, Toru Tamagawa, Takayuki Tamura, Takaaki Tanaka, Yasuo Tanaka, Yasuyuki T Tanaka, Makoto S Tashiro, Yuzuru Tawara, Y. Terada, Yuichi Terashima, Francesco Tombesi, Hiroshi Tomida, Y. Tsuboi, Masahiro Tsujimoto, H. Tsunemi, Takeshi Go Tsuru, Hiroyuki Uchida, Hideki Uchiyama, Y. Uchiyama, Shutaro Ueda, Yoshihiro Ueda, S. Uno, C. M. Urry, Eugenio Ursino, Shin Watanabe, Norbert Werner, Dan Wilkins, Brian J Williams, Hiroya Yamaguchi, K. Yamaoka, Noriko Y. Yamasaki, M. Yamauchi, Shigeo Yamauchi, Tahir Yaqoob, Yoichi Yatsu, Daisuke Yonetoku, Irina Zhuravleva, Abderahmen Zoghbi, Nozomu Tominaga, Takashi J Moriya

Bibliographic record

VenuePublications of the Astronomical Society of Japan · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsUniversity of ManitobaUniversity of WaterlooSaint Mary's University
FundersLawrence Livermore National LaboratoryJapan Aerospace Exploration AgencyEurostarsJapan Society for the Promotion of ScienceEuropean Research CouncilCanadian Space AgencySLAC National Accelerator LaboratorySmithsonian Astrophysical ObservatoryGoddard Space Flight CenterMagyar Tudományos AkadémiaMinistry of Education, Culture, Sports, Science and TechnologyCentre National d’Etudes SpatialesScience and Technology Facilities CouncilStrongAstronomical Society of JapanScience Mission DirectorateUniversity of Maryland, Baltimore CountyEuropean Space AgencyNational Aeronautics and Space AdministrationNederlandse Organisatie voor Wetenschappelijk OnderzoekNatural Sciences and Engineering Research Council of CanadaSmithsonian Institution
KeywordsPhysicsCrab NebulaSupernovaAstrophysicsEjectaRADIUSPlasmaNebulaSurface brightnessSupernova remnantGamma rayGalaxyStarsNuclear physics

Abstract

fetched live from OpenAlex

Abstract The Crab nebula originated from a core-collapse supernova (SN) explosion observed in 1054 ad. When viewed as a supernova remnant (SNR), it has an anomalously low observed ejecta mass and kinetic energy for an Fe-core-collapse SN. Intensive searches have been made for a massive shell that solves this discrepancy, but none has been detected. An alternative idea is that SN 1054 is an electron-capture (EC) explosion with a lower explosion energy by an order of magnitude than Fe-core-collapse SNe. X-ray imaging searches were performed for the plasma emission from the shell in the Crab outskirts to set a stringent upper limit on the X-ray emitting mass. However, the extreme brightness of the source hampers access to its vicinity. We thus employed spectroscopic technique using the X-ray micro-calorimeter on board the Hitomi satellite. By exploiting its superb energy resolution, we set an upper limit for emission or absorption features from as yet undetected thermal plasma in the 2–12 keV range. We also re-evaluated the existing Chandra and XMM-Newton data. By assembling these results, a new upper limit was obtained for the X-ray plasma mass of ≲ 1 M⊙ for a wide range of assumed shell radius, size, and plasma temperature values both in and out of collisional equilibrium. To compare with the observation, we further performed hydrodynamic simulations of the Crab SNR for two SN models (Fe-core versus EC) under two SN environments (uniform interstellar medium versus progenitor wind). We found that the observed mass limit can be compatible with both SN models if the SN environment has a low density of ≲ 0.03 cm−3 (Fe core) or ≲ 0.1 cm−3 (EC) for the uniform density, or a progenitor wind density somewhat less than that provided by a mass loss rate of 10−5 M⊙ yr−1 at 20 km s−1 for the wind environment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.235
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2017
Admission routes2
Has abstractyes

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