Pub Date : 2023-10-23DOI: 10.3847/1538-4365/acf3df
Robert F. Wilson, Thomas Barclay, Brian P. Powell, Joshua Schlieder, Christina Hedges, Benjamin T. Montet, Elisa Quintana, Iain Mcdonald, Matthew T. Penny, Néstor Espinoza, Eamonn Kerins
Abstract The Nancy Grace Roman Space Telescope (Roman) is NASA’s next astrophysics flagship mission, expected to launch in late 2026. As one of Roman’s core community science surveys, the Galactic Bulge Time Domain Survey (GBTDS) will collect photometric and astrometric data for over 100 million stars in the Galactic bulge in order to search for microlensing planets. To assess the potential with which Roman can detect exoplanets via transit, we developed and conducted pixel-level simulations of transiting planets in the GBTDS. From these simulations, we predict that Roman will find between ∼60,000 and ∼200,000 transiting planets—over an order of magnitude more planets than are currently known. While the majority of these planets will be giants ( R p > 4 R ⊕ ) on close-in orbits ( a < 0.3 au), the yield also includes between ∼7000 and ∼12,000 small planets ( R p < 4 R ⊕ ). The yield for small planets depends sensitively on the observing cadence and season duration, with variations on the order of ∼10%–20% for modest changes in either parameter, but is generally insensitive to the trade between surveyed area and cadence given constant slew/settle times. These predictions depend sensitively on the Milky Way’s metallicity distribution function, highlighting an opportunity to significantly advance our understanding of exoplanet demographics, in particular across stellar populations and Galactic environments.
南希·格蕾丝·罗曼太空望远镜(Roman)是美国宇航局的下一个天体物理学旗舰任务，预计将于2026年底发射。作为Roman的核心社区科学调查之一，银河凸起时间域调查(GBTDS)将收集银河凸起中超过1亿颗恒星的光度和天体测量数据，以寻找微透镜行星。为了评估Roman通过凌日探测系外行星的潜力，我们在GBTDS中开发并进行了凌日行星的像素级模拟。从这些模拟中，我们预测罗曼将发现6万到20万颗凌日行星——比目前已知的行星多一个数量级。虽然这些行星中的大多数将是巨星(R >4 R⊕)在近距离轨道上(a <0.3 au)，产量还包括约7000至约12000颗小行星(R p <4 r;小行星的产量敏感地取决于观测的节奏和季节持续时间，对于任何一个参数的适度变化，其变化顺序为~ 10%-20%，但在恒定的旋转/沉降时间下，通常对被测区域和节奏之间的交易不敏感。这些预测敏感地依赖于银河系的金属丰度分布函数，突出了一个显著推进我们对系外行星人口统计的理解的机会，特别是在恒星种群和银河系环境之间。
{"title":"Transiting Exoplanet Yields for the Roman Galactic Bulge Time Domain Survey Predicted from Pixel-level Simulations","authors":"Robert F. Wilson, Thomas Barclay, Brian P. Powell, Joshua Schlieder, Christina Hedges, Benjamin T. Montet, Elisa Quintana, Iain Mcdonald, Matthew T. Penny, Néstor Espinoza, Eamonn Kerins","doi":"10.3847/1538-4365/acf3df","DOIUrl":"https://doi.org/10.3847/1538-4365/acf3df","url":null,"abstract":"Abstract The Nancy Grace Roman Space Telescope (Roman) is NASA’s next astrophysics flagship mission, expected to launch in late 2026. As one of Roman’s core community science surveys, the Galactic Bulge Time Domain Survey (GBTDS) will collect photometric and astrometric data for over 100 million stars in the Galactic bulge in order to search for microlensing planets. To assess the potential with which Roman can detect exoplanets via transit, we developed and conducted pixel-level simulations of transiting planets in the GBTDS. From these simulations, we predict that Roman will find between ∼60,000 and ∼200,000 transiting planets—over an order of magnitude more planets than are currently known. While the majority of these planets will be giants ( R p > 4 R ⊕ ) on close-in orbits ( a < 0.3 au), the yield also includes between ∼7000 and ∼12,000 small planets ( R p < 4 R ⊕ ). The yield for small planets depends sensitively on the observing cadence and season duration, with variations on the order of ∼10%–20% for modest changes in either parameter, but is generally insensitive to the trade between surveyed area and cadence given constant slew/settle times. These predictions depend sensitively on the Milky Way’s metallicity distribution function, highlighting an opportunity to significantly advance our understanding of exoplanet demographics, in particular across stellar populations and Galactic environments.","PeriodicalId":8588,"journal":{"name":"Astrophysical Journal Supplement Series","volume":"15 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135368670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-23DOI: 10.3847/1538-4365/acf2f1
Zechang 泽昌 Sun 孙, Yuan-Sen 源森 Ting 丁, Zheng 峥 Cai 蔡
Abstract Since their first discovery, quasars have been essential probes of the distant Universe. However, due to our limited knowledge of its nature, predicting the intrinsic quasar continua has bottlenecked their usage. Existing methods of quasar continuum recovery often rely on a limited number of high-quality quasar spectra, which might not capture the full diversity of the quasar population. In this study, we propose an unsupervised probabilistic model, quasar factor analysis (QFA), which combines factor analysis with physical priors of the intergalactic medium to overcome these limitations. QFA captures the posterior distribution of quasar continua through generatively modeling quasar spectra. We demonstrate that QFA can achieve the state-of-the-art performance, ∼2% relative error, for continuum prediction in the Ly α forest region compared to previous methods. We further fit 90,678 2 < z < 3.5, signal-to-noise ratio >2 quasar spectra from Sloan Digital Sky Survey Data Release 16 and found that for ∼30% quasar spectra where the continua were ill-determined with previous methods, QFA yields visually more plausible continua. QFA also attains ≲1% error in the 1D Ly α power spectrum measurements at z ∼ 3 and ∼4% in z ∼ 2.4. In addition, QFA determines latent factors representing more physical motivation than principal component analysis. We investigate the evolution of the latent factors and report no significant redshift or luminosity dependency except for the Baldwin effect. The generative nature of QFA also enables outlier detection robustly; we showed that QFA is effective in selecting outlying quasar spectra, including damped Ly α systems and potential Type II quasar spectra.
{"title":"Quasar Factor Analysis—An Unsupervised and Probabilistic Quasar Continuum Prediction Algorithm with Latent Factor Analysis","authors":"Zechang 泽昌 Sun 孙, Yuan-Sen 源森 Ting 丁, Zheng 峥 Cai 蔡","doi":"10.3847/1538-4365/acf2f1","DOIUrl":"https://doi.org/10.3847/1538-4365/acf2f1","url":null,"abstract":"Abstract Since their first discovery, quasars have been essential probes of the distant Universe. However, due to our limited knowledge of its nature, predicting the intrinsic quasar continua has bottlenecked their usage. Existing methods of quasar continuum recovery often rely on a limited number of high-quality quasar spectra, which might not capture the full diversity of the quasar population. In this study, we propose an unsupervised probabilistic model, quasar factor analysis (QFA), which combines factor analysis with physical priors of the intergalactic medium to overcome these limitations. QFA captures the posterior distribution of quasar continua through generatively modeling quasar spectra. We demonstrate that QFA can achieve the state-of-the-art performance, ∼2% relative error, for continuum prediction in the Ly α forest region compared to previous methods. We further fit 90,678 2 < z < 3.5, signal-to-noise ratio >2 quasar spectra from Sloan Digital Sky Survey Data Release 16 and found that for ∼30% quasar spectra where the continua were ill-determined with previous methods, QFA yields visually more plausible continua. QFA also attains ≲1% error in the 1D Ly α power spectrum measurements at z ∼ 3 and ∼4% in z ∼ 2.4. In addition, QFA determines latent factors representing more physical motivation than principal component analysis. We investigate the evolution of the latent factors and report no significant redshift or luminosity dependency except for the Baldwin effect. The generative nature of QFA also enables outlier detection robustly; we showed that QFA is effective in selecting outlying quasar spectra, including damped Ly α systems and potential Type II quasar spectra.","PeriodicalId":8588,"journal":{"name":"Astrophysical Journal Supplement Series","volume":"85 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135367311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-18DOI: 10.3847/1538-4365/acfaa2
John Moustakas, Dustin Lang, Arjun Dey, Stéphanie Juneau, Aaron Meisner, Adam D. Myers, Edward F. Schlafly, David J. Schlegel, Francisco Valdes, Benjamin A. Weaver, Rongpu Zhou
Abstract We present the 2020 version of the Siena Galaxy Atlas (SGA-2020), a multiwavelength optical and infrared imaging atlas of 383,620 nearby galaxies. The SGA-2020 uses optical grz imaging over ≈20,000 deg 2 from the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 9 and infrared imaging in four bands (spanning 3.4–22 μ m) from the 6 year unWISE coadds; it is more than 95% complete for galaxies larger than R (26) ≈ 25″ and r < 18 measured at the 26 mag arcsec −2 isophote in the r band. The atlas delivers precise coordinates, multiwavelength mosaics, azimuthally averaged optical surface-brightness profiles, model images and photometry, and additional ancillary metadata for the full sample. Coupled with existing and forthcoming optical spectroscopy from the DESI, the SGA-2020 will facilitate new detailed studies of the star formation and mass assembly histories of nearby galaxies; enable precise measurements of the local velocity field via the Tully–Fisher and fundamental plane relations; serve as a reference sample of lasting legacy value for time-domain and multimessenger astronomical events; and more.
{"title":"Siena Galaxy Atlas 2020","authors":"John Moustakas, Dustin Lang, Arjun Dey, Stéphanie Juneau, Aaron Meisner, Adam D. Myers, Edward F. Schlafly, David J. Schlegel, Francisco Valdes, Benjamin A. Weaver, Rongpu Zhou","doi":"10.3847/1538-4365/acfaa2","DOIUrl":"https://doi.org/10.3847/1538-4365/acfaa2","url":null,"abstract":"Abstract We present the 2020 version of the Siena Galaxy Atlas (SGA-2020), a multiwavelength optical and infrared imaging atlas of 383,620 nearby galaxies. The SGA-2020 uses optical grz imaging over ≈20,000 deg 2 from the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 9 and infrared imaging in four bands (spanning 3.4–22 μ m) from the 6 year unWISE coadds; it is more than 95% complete for galaxies larger than R (26) ≈ 25″ and r < 18 measured at the 26 mag arcsec −2 isophote in the r band. The atlas delivers precise coordinates, multiwavelength mosaics, azimuthally averaged optical surface-brightness profiles, model images and photometry, and additional ancillary metadata for the full sample. Coupled with existing and forthcoming optical spectroscopy from the DESI, the SGA-2020 will facilitate new detailed studies of the star formation and mass assembly histories of nearby galaxies; enable precise measurements of the local velocity field via the Tully–Fisher and fundamental plane relations; serve as a reference sample of lasting legacy value for time-domain and multimessenger astronomical events; and more.","PeriodicalId":8588,"journal":{"name":"Astrophysical Journal Supplement Series","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135823842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-16DOI: 10.3847/1538-4365/acf31a
Yong Zhao, Dongdong Ni, Zibo Liu
Abstract Characterizing the interiors of rocky exoplanets is important to understand planetary populations and further investigate planetary habitability. New observable constraints and inference techniques have been explored for this purpose. In this work, we design and train mixture density networks (MDNs) to predict the interior properties of rocky exoplanets with large compositional diversity. In addition to measurements of mass and radius, bulk refractory elemental abundance ratios and the static Love number k 2 are used to constrain the interior of rocky exoplanets. It is found that the MDNs are able to infer the interior properties of rocky exoplanets from the available measurements of exoplanets. Compared with powerful inversion methods based on Bayesian inference, the trained MDNs provide a more rapid characterization of planetary interiors for each individual planet. The MDN model offers a convenient and practical tool for probabilistic inferences of planetary interiors.
{"title":"Machine-learning Inferences of the Interior Structure of Rocky Exoplanets from Bulk Observational Constraints","authors":"Yong Zhao, Dongdong Ni, Zibo Liu","doi":"10.3847/1538-4365/acf31a","DOIUrl":"https://doi.org/10.3847/1538-4365/acf31a","url":null,"abstract":"Abstract Characterizing the interiors of rocky exoplanets is important to understand planetary populations and further investigate planetary habitability. New observable constraints and inference techniques have been explored for this purpose. In this work, we design and train mixture density networks (MDNs) to predict the interior properties of rocky exoplanets with large compositional diversity. In addition to measurements of mass and radius, bulk refractory elemental abundance ratios and the static Love number k 2 are used to constrain the interior of rocky exoplanets. It is found that the MDNs are able to infer the interior properties of rocky exoplanets from the available measurements of exoplanets. Compared with powerful inversion methods based on Bayesian inference, the trained MDNs provide a more rapid characterization of planetary interiors for each individual planet. The MDN model offers a convenient and practical tool for probabilistic inferences of planetary interiors.","PeriodicalId":8588,"journal":{"name":"Astrophysical Journal Supplement Series","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136113389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-16DOI: 10.3847/1538-4365/acf4ef
Joseph Saji, Shabnam Iyyani, Kratika Mazde
Abstract The extensive observations done by the X-ray Telescope on board Neil Gehrels Swift Observatory have revealed the presence of late-time flares concurrent with the decaying afterglow emission. However, the origins of these flares are elusive. In this work, we make use of the large database of Swift observations (2005–2020) of long gamma-ray bursts (GRBs) to conduct a systematic statistical study between the prompt gamma-ray emission and X-ray flares by characterizing their temporal and spectral properties of duration, quiescent period, peak flux, fluence, minimum variability timescale, and spectral power-law index. The multidimensional database of parameters thereby generated was investigated by principal component analysis, which revealed there is no evident correlation between the different parameters of the prompt emission and X-ray flares. Furthermore, the correlation studies revealed that while there is a trend of positive correlation between the minimum variability timescale of the flare and its duration, and of strong negative correlation with its peak flux, there are no such correlations observed in the prompt emission. Similarly, we find a positive correlation between the quiescent period and the flare duration, and a negative correlation with the flare peak flux, while no such correlations are observed for the prompt emission of the GRBs. Finally, among the X-ray flares, we find two dominant classes, whose variations are driven by the minimum variability timescale, peak flux, and fluence of the flares. A catalog of these different parameters characterizing the prompt and flare emissions is presented.
Neil Gehrels Swift天文台的x射线望远镜进行了广泛的观测，揭示了与衰减余辉发射同时存在的晚时间耀斑。然而，这些耀斑的起源难以捉摸。本文利用2005-2020年快速伽玛射线暴(GRBs)观测的大型数据库，对瞬发伽玛射线发射与x射线耀斑之间的时间和光谱特性进行了系统的统计研究，包括持续时间、静止周期、峰值通量、通量、最小变率时间尺度和光谱幂律指数。通过主成分分析对生成的多维参数数据库进行了研究，结果表明，提示发射的不同参数与x射线耀斑之间没有明显的相关性。此外，相关研究表明，耀斑最小变率时间尺度与耀斑持续时间有正相关趋势，与耀斑峰值通量有很强的负相关趋势，而在瞬发期则没有这种相关性。同样，我们发现静止周期与耀斑持续时间呈正相关，与耀斑峰值通量呈负相关，而对于grb的快速发射则没有观察到这种相关性。最后，在x射线耀斑中，我们发现了两种主要的类型，它们的变化是由最小变异时间尺度、峰值通量和耀斑的影响驱动的。提出了表征瞬发和耀斑发射的这些不同参数的目录。
{"title":"Statistical Analysis of Long GRBs’ Prompt Emission and X-Ray Flares: Multivariate Clustering and Correlations","authors":"Joseph Saji, Shabnam Iyyani, Kratika Mazde","doi":"10.3847/1538-4365/acf4ef","DOIUrl":"https://doi.org/10.3847/1538-4365/acf4ef","url":null,"abstract":"Abstract The extensive observations done by the X-ray Telescope on board Neil Gehrels Swift Observatory have revealed the presence of late-time flares concurrent with the decaying afterglow emission. However, the origins of these flares are elusive. In this work, we make use of the large database of Swift observations (2005–2020) of long gamma-ray bursts (GRBs) to conduct a systematic statistical study between the prompt gamma-ray emission and X-ray flares by characterizing their temporal and spectral properties of duration, quiescent period, peak flux, fluence, minimum variability timescale, and spectral power-law index. The multidimensional database of parameters thereby generated was investigated by principal component analysis, which revealed there is no evident correlation between the different parameters of the prompt emission and X-ray flares. Furthermore, the correlation studies revealed that while there is a trend of positive correlation between the minimum variability timescale of the flare and its duration, and of strong negative correlation with its peak flux, there are no such correlations observed in the prompt emission. Similarly, we find a positive correlation between the quiescent period and the flare duration, and a negative correlation with the flare peak flux, while no such correlations are observed for the prompt emission of the GRBs. Finally, among the X-ray flares, we find two dominant classes, whose variations are driven by the minimum variability timescale, peak flux, and fluence of the flares. A catalog of these different parameters characterizing the prompt and flare emissions is presented.","PeriodicalId":8588,"journal":{"name":"Astrophysical Journal Supplement Series","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136115062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.3847/1538-4365/acee7f
Xin Zhou, Yang Su, Ji Yang, Xuepeng Chen, Yan Sun, Zhibo Jiang, Min Wang, Hongchi Wang, Shaobo Zhang, Ye Xu, Qingzeng Yan, Lixia Yuan, Zhiwei Chen, Yiping Ao, Yuehui Ma
We universally search for evidence of kinematic and spatial correlation of supernova remnant (SNR) and molecular cloud (MC) associations for nearly all SNRs in the coverage of the Milky Way Imaging Scroll Painting CO survey, i.e., 149 SNRs, 170 SNR candidates, and 18 pure pulsar wind nebulae in 1° < l < 230° and −5.°5 < b < 5.°5. Based on high-quality and unbiased 12CO/13CO/C18O (J = 1–0) survey data, we apply automatic algorithms to identify broad lines and spatial correlations for molecular gas in each SNR region. The 91% of SNR–MC associations detected previously are identified in this paper by CO line emission. Overall, there could be as high as 80% of SNRs associated with MCs. The proportion of SNRs associated with MCs is high within the Galactic longitude less than ∼50°. Kinematic distances of all SNRs that are associated with MCs are estimated based on systemic velocities of associated MCs. The radii of SNRs associated with MCs follow a lognormal distribution, which peaks at ∼8.1 pc. The progenitor initial mass of these SNRs follows a power-law distribution with an index of ∼−2.3 that is consistent with the Salpeter index of −2.35. We find that SNR–MC associations are mainly distributed in a thin disk along the Galactic plane, while a small number are distributed in a thick disk. With the height of these SNRs from the Galactic plane below ∼45 pc, the distribution of the average radius relative to the height of them is roughly flat, and the average radius increases with the height when above ∼45 pc.
{"title":"A Systematic Study of Associations between Supernova Remnants and Molecular Clouds","authors":"Xin Zhou, Yang Su, Ji Yang, Xuepeng Chen, Yan Sun, Zhibo Jiang, Min Wang, Hongchi Wang, Shaobo Zhang, Ye Xu, Qingzeng Yan, Lixia Yuan, Zhiwei Chen, Yiping Ao, Yuehui Ma","doi":"10.3847/1538-4365/acee7f","DOIUrl":"https://doi.org/10.3847/1538-4365/acee7f","url":null,"abstract":"We universally search for evidence of kinematic and spatial correlation of supernova remnant (SNR) and molecular cloud (MC) associations for nearly all SNRs in the coverage of the Milky Way Imaging Scroll Painting CO survey, i.e., 149 SNRs, 170 SNR candidates, and 18 pure pulsar wind nebulae in 1° < l < 230° and −5.°5 < b < 5.°5. Based on high-quality and unbiased 12CO/13CO/C18O (J = 1–0) survey data, we apply automatic algorithms to identify broad lines and spatial correlations for molecular gas in each SNR region. The 91% of SNR–MC associations detected previously are identified in this paper by CO line emission. Overall, there could be as high as 80% of SNRs associated with MCs. The proportion of SNRs associated with MCs is high within the Galactic longitude less than ∼50°. Kinematic distances of all SNRs that are associated with MCs are estimated based on systemic velocities of associated MCs. The radii of SNRs associated with MCs follow a lognormal distribution, which peaks at ∼8.1 pc. The progenitor initial mass of these SNRs follows a power-law distribution with an index of ∼−2.3 that is consistent with the Salpeter index of −2.35. We find that SNR–MC associations are mainly distributed in a thin disk along the Galactic plane, while a small number are distributed in a thick disk. With the height of these SNRs from the Galactic plane below ∼45 pc, the distribution of the average radius relative to the height of them is roughly flat, and the average radius increases with the height when above ∼45 pc.","PeriodicalId":8588,"journal":{"name":"Astrophysical Journal Supplement Series","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134977834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.3847/1538-4365/acf218
Y. Yang, J. J. Liu, X. S. Feng, P. F. Chen, B. Zhang
Abstract Coronal mass ejections (CMEs), a kind of violent solar eruptive activity, can exert a significant impact on space weather. When arriving at the Earth, they interact with the geomagnetic field, which can boost the energy supply to the geomagnetic field and may further result in geomagnetic storms, thus having potentially catastrophic effects on human activities. Therefore, accurate forecasting of the transit time of CMEs from the Sun to the Earth is vital for mitigating the relevant losses brought by them. XGBoost, an ensemble model that has better performance in some other fields, is applied to the space weather forecast for the first time. During multiple tests with random data splits, the best mean absolute error (MAE) of ∼5.72 hr was obtained, and in this test, 62% of the test CMEs had absolute arrival time error of less than 5.72 hr. The average MAE over all random tests was ∼10 hr. It indicates that our method has a better predictive potential and baseline. Moreover, we introduce two effective feature importance ranking methods. One is the information gain method, a built-in method of ensemble models. The other is the permutation method. These two methods combine the learning process of the model and its performance to rank the CME features, respectively. Compared with the direct correlation analysis on the sample data set, they can help select the important features that closely match the model. These two methods can assist researchers to process large sample data sets, which often require feature selection in advance.
{"title":"Prediction of the Transit Time of Coronal Mass Ejections with an Ensemble Machine-learning Method","authors":"Y. Yang, J. J. Liu, X. S. Feng, P. F. Chen, B. Zhang","doi":"10.3847/1538-4365/acf218","DOIUrl":"https://doi.org/10.3847/1538-4365/acf218","url":null,"abstract":"Abstract Coronal mass ejections (CMEs), a kind of violent solar eruptive activity, can exert a significant impact on space weather. When arriving at the Earth, they interact with the geomagnetic field, which can boost the energy supply to the geomagnetic field and may further result in geomagnetic storms, thus having potentially catastrophic effects on human activities. Therefore, accurate forecasting of the transit time of CMEs from the Sun to the Earth is vital for mitigating the relevant losses brought by them. XGBoost, an ensemble model that has better performance in some other fields, is applied to the space weather forecast for the first time. During multiple tests with random data splits, the best mean absolute error (MAE) of ∼5.72 hr was obtained, and in this test, 62% of the test CMEs had absolute arrival time error of less than 5.72 hr. The average MAE over all random tests was ∼10 hr. It indicates that our method has a better predictive potential and baseline. Moreover, we introduce two effective feature importance ranking methods. One is the information gain method, a built-in method of ensemble models. The other is the permutation method. These two methods combine the learning process of the model and its performance to rank the CME features, respectively. Compared with the direct correlation analysis on the sample data set, they can help select the important features that closely match the model. These two methods can assist researchers to process large sample data sets, which often require feature selection in advance.","PeriodicalId":8588,"journal":{"name":"Astrophysical Journal Supplement Series","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135706507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.3847/1538-4365/acefba
Fabio Bacchini
Abstract We present a novel Relativistic Semi-Implicit Method (RelSIM) for particle-in-cell (PIC) simulations of astrophysical plasmas, implemented in a code framework ready for production runs. While explicit PIC methods have gained widespread recognition in the astrophysical community as a reliable tool to simulate plasma phenomena, implicit methods have been seldom explored. This is partly due to the lack of a reliable relativistic implicit PIC formulation that is applicable to state-of-the-art simulations. We propose the RelSIM to fill this gap: our new method is relatively simple, being free of nonlinear iterations and only requiring a global linear solve of the field equations. With a set of one- and two-dimensional tests, we demonstrate that the RelSIM produces more accurate results with much smaller numerical errors in the total energy than standard explicit PIC, in particular when characteristic plasma scales (skin depth and plasma frequency) are heavily underresolved on the numerical grid. By construction, the RelSIM also performs much better than the relativistic implicit-moment method, originally proposed for semi-implicit PIC simulations in the relativistic regime. Our results are promising to conduct large-scale (in terms of duration and domain size) PIC simulations of astrophysical plasmas, potentially reaching physical regimes inaccessible by standard explicit PIC codes.
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Pub Date : 2023-10-01DOI: 10.3847/1538-4365/acf130
Christina C. Williams, Sandro Tacchella, Michael V. Maseda, Brant E. Robertson, Benjamin D. Johnson, Chris J. Willott, Daniel J. Eisenstein, Christopher N. A. Willmer, Zhiyuan Ji, Kevin N. Hainline, Jakob M. Helton, Stacey Alberts, Stefi Baum, Rachana Bhatawdekar, Kristan Boyett, Andrew J. Bunker, Stefano Carniani, Stephane Charlot, Jacopo Chevallard, Emma Curtis-Lake, Anna de Graaff, Eiichi Egami, Marijn Franx, Nimisha Kumari, Roberto Maiolino, Erica J. Nelson, Marcia J. Rieke, Lester Sandles, Irene Shivaei, Charlotte Simmonds, Renske Smit, Katherine A. Suess, Fengwu Sun, Hannah Übler, Joris Witstok
Abstract We present JWST Extragalactic Medium-band Survey, the first public medium-band imaging survey carried out using JWST/NIRCam and NIRISS. These observations use ∼2 and ∼4 μ m medium-band filters (NIRCam F182M, F210M, F430M, F460M, F480M; and NIRISS F430M and F480M in parallel) over 15.6 arcmin 2 in the Hubble Ultra Deep Field (UDF), thereby building on the deepest multiwavelength public data sets available anywhere on the sky. We describe our science goals, survey design, NIRCam and NIRISS image reduction methods, and describe our first data release of the science-ready mosaics, which reach 5 σ point-source limits (AB mag) of ∼29.3–29.4 in 2 μ m filters and ∼28.2–28.7 at 4 μ m. Our chosen filters create a JWST imaging survey in the UDF that enables novel analysis of a range of spectral features potentially across the redshift range of 0.3 < z < 20, including Paschen- α , H α +[N ii ], and [O iii ]+H β emission at high spatial resolution. We find that our JWST medium-band imaging efficiently identifies strong line emitters (medium-band colors >1 mag) across redshifts 1.5 < z < 9.3, most prominently H α +[N ii ] and [O iii ]+H β . We present our first data release including science-ready mosaics of each medium-band image available to the community, adding to the legacy value of past and future surveys in the UDF. This survey demonstrates the power of medium-band imaging with JWST, informing future extragalactic survey strategies using JWST observations.
{"title":"JEMS: A Deep Medium-band Imaging Survey in the Hubble Ultra Deep Field with JWST NIRCam and NIRISS","authors":"Christina C. Williams, Sandro Tacchella, Michael V. Maseda, Brant E. Robertson, Benjamin D. Johnson, Chris J. Willott, Daniel J. Eisenstein, Christopher N. A. Willmer, Zhiyuan Ji, Kevin N. Hainline, Jakob M. Helton, Stacey Alberts, Stefi Baum, Rachana Bhatawdekar, Kristan Boyett, Andrew J. Bunker, Stefano Carniani, Stephane Charlot, Jacopo Chevallard, Emma Curtis-Lake, Anna de Graaff, Eiichi Egami, Marijn Franx, Nimisha Kumari, Roberto Maiolino, Erica J. Nelson, Marcia J. Rieke, Lester Sandles, Irene Shivaei, Charlotte Simmonds, Renske Smit, Katherine A. Suess, Fengwu Sun, Hannah Übler, Joris Witstok","doi":"10.3847/1538-4365/acf130","DOIUrl":"https://doi.org/10.3847/1538-4365/acf130","url":null,"abstract":"Abstract We present JWST Extragalactic Medium-band Survey, the first public medium-band imaging survey carried out using JWST/NIRCam and NIRISS. These observations use ∼2 and ∼4 μ m medium-band filters (NIRCam F182M, F210M, F430M, F460M, F480M; and NIRISS F430M and F480M in parallel) over 15.6 arcmin 2 in the Hubble Ultra Deep Field (UDF), thereby building on the deepest multiwavelength public data sets available anywhere on the sky. We describe our science goals, survey design, NIRCam and NIRISS image reduction methods, and describe our first data release of the science-ready mosaics, which reach 5 σ point-source limits (AB mag) of ∼29.3–29.4 in 2 μ m filters and ∼28.2–28.7 at 4 μ m. Our chosen filters create a JWST imaging survey in the UDF that enables novel analysis of a range of spectral features potentially across the redshift range of 0.3 < z < 20, including Paschen- α , H α +[N ii ], and [O iii ]+H β emission at high spatial resolution. We find that our JWST medium-band imaging efficiently identifies strong line emitters (medium-band colors >1 mag) across redshifts 1.5 < z < 9.3, most prominently H α +[N ii ] and [O iii ]+H β . We present our first data release including science-ready mosaics of each medium-band image available to the community, adding to the legacy value of past and future surveys in the UDF. This survey demonstrates the power of medium-band imaging with JWST, informing future extragalactic survey strategies using JWST observations.","PeriodicalId":8588,"journal":{"name":"Astrophysical Journal Supplement Series","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135996809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.3847/1538-4365/acf033
M. Reichert, C. Winteler, O. Korobkin, A. Arcones, J. Bliss, M. Eichler, U. Frischknecht, C. Fröhlich, R. Hirschi, M. Jacobi, J. Kuske, G. Martínez-Pinedo, D. Martin, D. Mocelj, T. Rauscher, F.-K. Thielemann
Abstract We present the state-of-the-art single-zone nuclear reaction network WinNet , which is capable of calculating the nucleosynthetic yields of a large variety of astrophysical environments and conditions. This ranges from the calculation of the primordial nucleosynthesis, where only a few nuclei are considered, to the ejecta of neutron star mergers with several thousands of involved nuclei. Here we describe the underlying physics and implementation details of the reaction network. We additionally present the numerical implementation of two different integration methods, the implicit Euler method and Gears method, along with their advantages and disadvantages. We furthermore describe basic example cases of thermodynamic conditions that we provide together with the network and demonstrate the reliability of the code by using simple test cases. With this publication, WinNet will be publicly available and open source at GitHub and Zenodo.
{"title":"The Nuclear Reaction Network WinNet","authors":"M. Reichert, C. Winteler, O. Korobkin, A. Arcones, J. Bliss, M. Eichler, U. Frischknecht, C. Fröhlich, R. Hirschi, M. Jacobi, J. Kuske, G. Martínez-Pinedo, D. Martin, D. Mocelj, T. Rauscher, F.-K. Thielemann","doi":"10.3847/1538-4365/acf033","DOIUrl":"https://doi.org/10.3847/1538-4365/acf033","url":null,"abstract":"Abstract We present the state-of-the-art single-zone nuclear reaction network WinNet , which is capable of calculating the nucleosynthetic yields of a large variety of astrophysical environments and conditions. This ranges from the calculation of the primordial nucleosynthesis, where only a few nuclei are considered, to the ejecta of neutron star mergers with several thousands of involved nuclei. Here we describe the underlying physics and implementation details of the reaction network. We additionally present the numerical implementation of two different integration methods, the implicit Euler method and Gears method, along with their advantages and disadvantages. We furthermore describe basic example cases of thermodynamic conditions that we provide together with the network and demonstrate the reliability of the code by using simple test cases. With this publication, WinNet will be publicly available and open source at GitHub and Zenodo.","PeriodicalId":8588,"journal":{"name":"Astrophysical Journal Supplement Series","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136117414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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