Pub Date : 2024-08-06DOI: 10.3847/1538-4365/ad5835
Ranadeep Sarkar, Nandita Srivastava, Nat Gopalswamy and Emilia Kilpua
The INterplanetary Flux ROpe Simulator (INFROS) is an observationally constrained analytical model dedicated to forecasting the strength of the southward component (Bz) of the magnetic field embedded in interplanetary coronal mass ejections (ICMEs). In this work, we validate the model for six ICMEs sequentially observed by two radially aligned spacecraft positioned at different heliocentric distances. The six selected ICMEs in this study comprise cases associated with isolated coronal mass ejection (CME) evolution as well as those interacting with high-speed streams (HSSs) and high-density streams (HDSs). For the isolated CMEs, our results show that the model outputs at both spacecraft are in good agreement with in situ observations. However, for most of the interacting events, the model correctly captures the CME evolution only at the inner spacecraft. Due to the interaction with HSSs and HDSs, which in most cases occurred at heliocentric distances beyond the inner spacecraft, the ICME evolution no longer remains self-similar. Consequently, the model underestimates the field strength at the outer spacecraft. Our findings indicate that constraining the INFROS model with inner-spacecraft observations significantly enhances the prediction accuracy at the outer spacecraft for the three events undergoing self-similar expansion, achieving a 90% correlation between observed and predicted Bz profiles. This work also presents a quantitative estimation of the ICME magnetic field enhancement due to interaction which may lead to severe space weather. We conclude that the assumption of self-similar expansion provides a lower limit to the magnetic field strength estimated at any heliocentric distance, based on the remote-sensing observations.
{"title":"Modeling the Magnetic Vectors of Interplanetary Coronal Mass Ejections at Different Heliocentric Distances with INFROS","authors":"Ranadeep Sarkar, Nandita Srivastava, Nat Gopalswamy and Emilia Kilpua","doi":"10.3847/1538-4365/ad5835","DOIUrl":"https://doi.org/10.3847/1538-4365/ad5835","url":null,"abstract":"The INterplanetary Flux ROpe Simulator (INFROS) is an observationally constrained analytical model dedicated to forecasting the strength of the southward component (Bz) of the magnetic field embedded in interplanetary coronal mass ejections (ICMEs). In this work, we validate the model for six ICMEs sequentially observed by two radially aligned spacecraft positioned at different heliocentric distances. The six selected ICMEs in this study comprise cases associated with isolated coronal mass ejection (CME) evolution as well as those interacting with high-speed streams (HSSs) and high-density streams (HDSs). For the isolated CMEs, our results show that the model outputs at both spacecraft are in good agreement with in situ observations. However, for most of the interacting events, the model correctly captures the CME evolution only at the inner spacecraft. Due to the interaction with HSSs and HDSs, which in most cases occurred at heliocentric distances beyond the inner spacecraft, the ICME evolution no longer remains self-similar. Consequently, the model underestimates the field strength at the outer spacecraft. Our findings indicate that constraining the INFROS model with inner-spacecraft observations significantly enhances the prediction accuracy at the outer spacecraft for the three events undergoing self-similar expansion, achieving a 90% correlation between observed and predicted Bz profiles. This work also presents a quantitative estimation of the ICME magnetic field enhancement due to interaction which may lead to severe space weather. We conclude that the assumption of self-similar expansion provides a lower limit to the magnetic field strength estimated at any heliocentric distance, based on the remote-sensing observations.","PeriodicalId":22368,"journal":{"name":"The Astrophysical Journal Supplement Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.3847/1538-4365/ad5a08
Lei Tan, 磊 谈, Zhicun Liu, 志存 柳, Xiaolong Wang, 小龙 王, Ying Mei, 盈 梅, Feng Wang, 锋 王, Hui Deng, 辉 邓, Chao Liu and 超 刘
Young stellar objects (YSOs) represent the earliest stage in the process of star formation, offering insights that contribute to the development of models elucidating star formation and evolution. Recent advancements in deep-learning techniques have enabled significant strides in identifying special objects within vast data sets. In this paper, we present a YSO identification method based on deep-learning principles and spectra from the LAMOST. We designed a structure based on a long short-term memory network and a convolutional neural network and trained different models in two steps to identify YSO candidates. Initially, we trained a model to detect stellar spectra featuring the Hα emission line, achieving an accuracy of 98.67%. Leveraging this model, we classified 10,495,781 stellar spectra from LAMOST, yielding 76,867 candidates displaying a Hα emission line. Subsequently, we developed a YSO identification model, which achieved a recall rate of 95.81% for YSOs. Utilizing this model, we further identified 35,021 YSO candidates from the Hα emission-line candidates. Following cross validation, 3204 samples were identified as previously reported YSO candidates. We eliminated samples with low signal-to-noise ratios and M dwarfs by using the equivalent widths of the N ii and He i emission lines and visual inspection, resulting in a catalog of 20,530 YSO candidates. To facilitate future research endeavors, we provide the obtained catalogs of Hα emission-line star candidates and YSO candidates along with the code used for training the model.
年轻恒星天体（YSOs）代表了恒星形成过程中的最早阶段，有助于阐明恒星形成和演化模型的发展。深度学习技术的最新进展使我们在识别庞大数据集中的特殊天体方面取得了长足进步。在本文中，我们介绍了一种基于深度学习原理和 LAMOST 光谱的 YSO 识别方法。我们设计了一种基于长短期记忆网络和卷积神经网络的结构，并分两步训练了不同的模型来识别 YSO 候选天体。首先，我们训练了一个模型来检测以Hα发射线为特征的恒星光谱，准确率达到98.67%。利用这个模型，我们对来自 LAMOST 的 10,495,781 条恒星光谱进行了分类，得到了 76,867 条显示 Hα 发射线的候选光谱。随后，我们建立了一个 YSO 识别模型，该模型对 YSO 的召回率达到了 95.81%。利用该模型，我们从 Hα 发射线候选天体中进一步识别出了 35021 个 YSO 候选天体。经过交叉验证，有 3204 个样本被确定为以前报告过的 YSO 候选样本。通过使用 N ii 和 He i 发射线的等效宽度以及目测，我们剔除了信噪比低的样本和 M 矮星，最终得到了一份包含 20,530 个 YSO 候选样本的星表。为了方便今后的研究工作，我们提供了所获得的 Hα 发射线候选星和 YSO 候选星星表以及用于训练模型的代码。
{"title":"A Robust Young Stellar Object Identification Method Based on Deep Learning","authors":"Lei Tan, 磊 谈, Zhicun Liu, 志存 柳, Xiaolong Wang, 小龙 王, Ying Mei, 盈 梅, Feng Wang, 锋 王, Hui Deng, 辉 邓, Chao Liu and 超 刘","doi":"10.3847/1538-4365/ad5a08","DOIUrl":"https://doi.org/10.3847/1538-4365/ad5a08","url":null,"abstract":"Young stellar objects (YSOs) represent the earliest stage in the process of star formation, offering insights that contribute to the development of models elucidating star formation and evolution. Recent advancements in deep-learning techniques have enabled significant strides in identifying special objects within vast data sets. In this paper, we present a YSO identification method based on deep-learning principles and spectra from the LAMOST. We designed a structure based on a long short-term memory network and a convolutional neural network and trained different models in two steps to identify YSO candidates. Initially, we trained a model to detect stellar spectra featuring the Hα emission line, achieving an accuracy of 98.67%. Leveraging this model, we classified 10,495,781 stellar spectra from LAMOST, yielding 76,867 candidates displaying a Hα emission line. Subsequently, we developed a YSO identification model, which achieved a recall rate of 95.81% for YSOs. Utilizing this model, we further identified 35,021 YSO candidates from the Hα emission-line candidates. Following cross validation, 3204 samples were identified as previously reported YSO candidates. We eliminated samples with low signal-to-noise ratios and M dwarfs by using the equivalent widths of the N ii and He i emission lines and visual inspection, resulting in a catalog of 20,530 YSO candidates. To facilitate future research endeavors, we provide the obtained catalogs of Hα emission-line star candidates and YSO candidates along with the code used for training the model.","PeriodicalId":22368,"journal":{"name":"The Astrophysical Journal Supplement Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141882119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.3847/1538-4365/ad5559
Yu Liu, Yu Yu, Pengjie Zhang, Hao-Ran Yu
The density fields constructed by traditional mass assignment methods are susceptible to irritating discreteness, which hinders morphological measurements of cosmic large-scale structure (LSS) through Minkowski functionals (MFs). To alleviate this issue, fixed-kernel smoothing methods are commonly used in the literature, at the expense of losing substantial structural information. In this work, we propose to measure MFs with the Delaunay tessellation field estimation (DTFE) technique, with the goal of maximizing the extraction of morphological information from sparse tracers. We perform our analyses starting from matter fields and progressively extending to halo fields. At the matter-field level, we elucidate how discreteness affects morphological measurements of LSS. Then, by comparing with the traditional Gaussian smoothing scheme, we preliminarily showcase the advantages of DTFE for enhancing measurements of MFs from sparse tracers. At the halo-field level, we first numerically investigate various systematic effects on MFs of DTFE fields, which are induced by finite voxel sizes, halo number densities, halo weightings, and redshift space distortions (RSDs), respectively. Then, we explore the statistical power of MFs measured with DTFE for extracting the cosmological information encoded in RSDs. We find that MFs measured with DTFE exhibit improvements by ∼2 orders of magnitude in discriminative power for RSD effects and by a factor of ∼3–5 in constraining power on the structure growth rate over the MFs measured with Gaussian smoothing. These findings demonstrate the remarkable enhancements in statistical power of MFs achieved by DTFE, showing enormous application potentials for our method in extracting various key cosmological information from galaxy surveys.
{"title":"Enhancing Morphological Measurements of the Cosmic Web with Delaunay Tessellation Field Estimation","authors":"Yu Liu, Yu Yu, Pengjie Zhang, Hao-Ran Yu","doi":"10.3847/1538-4365/ad5559","DOIUrl":"https://doi.org/10.3847/1538-4365/ad5559","url":null,"abstract":"The density fields constructed by traditional mass assignment methods are susceptible to irritating discreteness, which hinders morphological measurements of cosmic large-scale structure (LSS) through Minkowski functionals (MFs). To alleviate this issue, fixed-kernel smoothing methods are commonly used in the literature, at the expense of losing substantial structural information. In this work, we propose to measure MFs with the Delaunay tessellation field estimation (DTFE) technique, with the goal of maximizing the extraction of morphological information from sparse tracers. We perform our analyses starting from matter fields and progressively extending to halo fields. At the matter-field level, we elucidate how discreteness affects morphological measurements of LSS. Then, by comparing with the traditional Gaussian smoothing scheme, we preliminarily showcase the advantages of DTFE for enhancing measurements of MFs from sparse tracers. At the halo-field level, we first numerically investigate various systematic effects on MFs of DTFE fields, which are induced by finite voxel sizes, halo number densities, halo weightings, and redshift space distortions (RSDs), respectively. Then, we explore the statistical power of MFs measured with DTFE for extracting the cosmological information encoded in RSDs. We find that MFs measured with DTFE exhibit improvements by ∼2 orders of magnitude in discriminative power for RSD effects and by a factor of ∼3–5 in constraining power on the structure growth rate over the MFs measured with Gaussian smoothing. These findings demonstrate the remarkable enhancements in statistical power of MFs achieved by DTFE, showing enormous application potentials for our method in extracting various key cosmological information from galaxy surveys.","PeriodicalId":22368,"journal":{"name":"The Astrophysical Journal Supplement Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141865407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.3847/1538-4365/ad571a
Jialu Li, Adwin Boogert, Alexander G. G. M. Tielens
Rovibrational absorption lines of H2O in the 5–8 μm wavelength range selectively probe gas against the mid-infrared continuum-emitting background of the inner regions of young stellar objects and active galactic nuclei and deliver important information about these warm, dust-obscured environments. JWST/Mid-Infrared Instrument (MIRI) detects these lines in many lines of sight at a moderate spectral resolving power of R ∼ 3500 (full width at half-maximum of 85 km s−1). Based on our analysis of high-resolution SOFIA/EXES observations, we find that the interpretation of JWST/MIRI absorption spectra can be severely hampered by the blending of individual transitions and the lost information on the intrinsic line width or the partial coverage of the background continuum source. In this paper, we point out problems such as degeneracy that arise in deriving physical properties from an insufficiently resolved spectrum. This can lead to differences in the column density by 2 orders of magnitude. We emphasize the importance of weighting optically thin and weak lines in spectral analyses and provide recipes for breaking down the coupled parameters. We also provide an online tool to generate the H2O absorption line spectra that can be compared to observations.
{"title":"On the Interpretation of Mid-infrared Absorption Lines of Gas-phase H2O as Observed by JWST/MIRI","authors":"Jialu Li, Adwin Boogert, Alexander G. G. M. Tielens","doi":"10.3847/1538-4365/ad571a","DOIUrl":"https://doi.org/10.3847/1538-4365/ad571a","url":null,"abstract":"Rovibrational absorption lines of H<sub>2</sub>O in the 5–8 <italic toggle=\"yes\">μ</italic>m wavelength range selectively probe gas against the mid-infrared continuum-emitting background of the inner regions of young stellar objects and active galactic nuclei and deliver important information about these warm, dust-obscured environments. JWST/Mid-Infrared Instrument (MIRI) detects these lines in many lines of sight at a moderate spectral resolving power of <italic toggle=\"yes\">R</italic> ∼ 3500 (full width at half-maximum of 85 km s<sup>−1</sup>). Based on our analysis of high-resolution SOFIA/EXES observations, we find that the interpretation of JWST/MIRI absorption spectra can be severely hampered by the blending of individual transitions and the lost information on the intrinsic line width or the partial coverage of the background continuum source. In this paper, we point out problems such as degeneracy that arise in deriving physical properties from an insufficiently resolved spectrum. This can lead to differences in the column density by 2 orders of magnitude. We emphasize the importance of weighting optically thin and weak lines in spectral analyses and provide recipes for breaking down the coupled parameters. We also provide an online tool to generate the H<sub>2</sub>O absorption line spectra that can be compared to observations.","PeriodicalId":22368,"journal":{"name":"The Astrophysical Journal Supplement Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141865497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the continuous development of large optical surveys, a large number of light curves of late-type contact binary systems (CBs) have been released. Deriving parameters for CBs using the the Wilson–Devinney program and the PHOEBE program poses a challenge. Therefore, this study developed a method for rapidly deriving light curves based on the Neural Networks model combined with the Hamiltonian Monte Carlo (HMC) algorithm (NNHMC). The neural network was employed to establish the mapping relationship between the parameters and the pregenerated light curves by the PHOEBE program, and the HMC algorithm was used to obtain the posterior distribution of the parameters. The NNHMC method was applied to a large contact binary sample from the Catalina Sky Survey, and a total of 19,104 late-type contact binary parameters were derived. Among them, 5172 have an inclination greater than 70° and a temperature difference less than 400 K. The obtained results were compared with the previous studies for 30 CBs, and there was an essentially consistent goodness-of-fit (R2) distribution between them. The NNHMC method possesses the capability to simultaneously derive parameters for a vast number of targets. Furthermore, it can provide an extremely efficient tool for the rapid derivation of parameters in future sky surveys involving large samples of CBs.
{"title":"A Method of Rapidly Deriving Late-type Contact Binary Parameters and Its Application in the Catalina Sky Survey","authors":"JinLiang Wang, Xu Ding, JiaJia Li, JianPing Xiong, QiYuan Cheng, KaiFan Ji","doi":"10.3847/1538-4365/ad5953","DOIUrl":"https://doi.org/10.3847/1538-4365/ad5953","url":null,"abstract":"With the continuous development of large optical surveys, a large number of light curves of late-type contact binary systems (CBs) have been released. Deriving parameters for CBs using the the Wilson–Devinney program and the PHOEBE program poses a challenge. Therefore, this study developed a method for rapidly deriving light curves based on the Neural Networks model combined with the Hamiltonian Monte Carlo (HMC) algorithm (NNHMC). The neural network was employed to establish the mapping relationship between the parameters and the pregenerated light curves by the PHOEBE program, and the HMC algorithm was used to obtain the posterior distribution of the parameters. The NNHMC method was applied to a large contact binary sample from the Catalina Sky Survey, and a total of 19,104 late-type contact binary parameters were derived. Among them, 5172 have an inclination greater than 70° and a temperature difference less than 400 K. The obtained results were compared with the previous studies for 30 CBs, and there was an essentially consistent goodness-of-fit (<italic toggle=\"yes\">R</italic>\u0000<sup>2</sup>) distribution between them. The NNHMC method possesses the capability to simultaneously derive parameters for a vast number of targets. Furthermore, it can provide an extremely efficient tool for the rapid derivation of parameters in future sky surveys involving large samples of CBs.","PeriodicalId":22368,"journal":{"name":"The Astrophysical Journal Supplement Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141865499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-30DOI: 10.3847/1538-4365/ad5184
Netai Bhukta, Souvik Manik, Sabyasachi Pal, Sushanta K. Mondal
Giant radio sources (GRSs) are the single largest astrophysical objects known in the Universe that have grown to megaparsec scales (≥0.7 Mpc). GRSs are much rarer compared with normal-sized radio galaxies. Still, the reason for the formation of their gigantic sizes is under debate. We systematically search for GRSs from the TIFR Giant Metrewave Radio Telescope Sky Survey Alternative Data Release 1 at 150 MHz. We have newly identified 34 GRSs from this study. We have also studied the multiwavelength properties (radio, optical, and infrared) of these GRSs. We have used the likelihood ratio method to identify highly reliable multiwavelength counterparts of GRSs from Pan-STARRS (optical) and Wide-field Infrared Survey Explorer (mid-IR) data. We have classified GRSs based on their accretion mode of the central black holes using optical and mid-IR data. For all sources, we also discuss the principal characteristic parameters (redshift distribution, angular and projected linear size, total integrated radio flux density, spectral index, and radio power). We show the radio evolution track and the location of the GRSs in the P–D diagram. Using a radio–optical luminosity diagram, we identify GRSs in the Fanaroff–Riley classification. Only two GRGs in our sample reside close to the centers of galaxy clusters.
{"title":"Discovery of Giant Radio Sources from TGSS Alternative Data Release 1: Radio, Optical, and Infrared Properties","authors":"Netai Bhukta, Souvik Manik, Sabyasachi Pal, Sushanta K. Mondal","doi":"10.3847/1538-4365/ad5184","DOIUrl":"https://doi.org/10.3847/1538-4365/ad5184","url":null,"abstract":"Giant radio sources (GRSs) are the single largest astrophysical objects known in the Universe that have grown to megaparsec scales (≥0.7 Mpc). GRSs are much rarer compared with normal-sized radio galaxies. Still, the reason for the formation of their gigantic sizes is under debate. We systematically search for GRSs from the TIFR Giant Metrewave Radio Telescope Sky Survey Alternative Data Release 1 at 150 MHz. We have newly identified 34 GRSs from this study. We have also studied the multiwavelength properties (radio, optical, and infrared) of these GRSs. We have used the likelihood ratio method to identify highly reliable multiwavelength counterparts of GRSs from Pan-STARRS (optical) and Wide-field Infrared Survey Explorer (mid-IR) data. We have classified GRSs based on their accretion mode of the central black holes using optical and mid-IR data. For all sources, we also discuss the principal characteristic parameters (redshift distribution, angular and projected linear size, total integrated radio flux density, spectral index, and radio power). We show the radio evolution track and the location of the GRSs in the <italic toggle=\"yes\">P</italic>–<italic toggle=\"yes\">D</italic> diagram. Using a radio–optical luminosity diagram, we identify GRSs in the Fanaroff–Riley classification. Only two GRGs in our sample reside close to the centers of galaxy clusters.","PeriodicalId":22368,"journal":{"name":"The Astrophysical Journal Supplement Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141865411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-29DOI: 10.3847/1538-4365/ad5720
Julia Martikainen, Olga Muñoz, Juan Carlos Gómez Martín, Teresa Jardiel, Marco Peiteado, Amador C. Caballero, Santiago Pérez-Hoyos, Agustin Sánchez Lavega, Tim Becker, Gerhard Wurm, Yannick Willame, Ann Carine Vandaele
We present experimental scattering matrices of the JSC Mars-1, MMS-2, and MGS-1 simulants at 488 and 640 nm. The analogs were processed so that narrow size distributions representative of Martian dust aerosols during different dust cycles were obtained. We find that the forward peak of the phase function depends on particle size as it becomes narrower with increasing size, whereas the side- and backscattering directions depend on both composition and size so that increasing size and decreasing absorption produce a flatter curve. The position and maximum of the degree of linear polarization varies based on particle size and composition, and the negative polarization branch is more prominent for wavelength-scale particles diminishing with increasing size. The linear depolarization is strongly affected by size and composition. Finally, we compare sky-brightness curves measured by the Navcam and Hazcam engineering cameras on board the Mars Science Laboratory rover to the measured phase functions. The observations show a narrower peak at the forward direction and a flatter curve toward the side- and backscattering directions with an increasing dust load in the atmosphere, similar to what can be seen for the measured phase functions of the analogs with increasing particle size. In the case of the analogs, the flattening of the curve can be caused by an increase in multiple scattering within a particle by wavelength-scale surface roughness and/or internal inclusions. For the observed sky brightnesses, particle aggregation and multiple scattering among particles in denser dust conditions play a major role.
{"title":"Experimental Scattering Matrices of Martian Dust Aerosols with Narrow Particle-size Distributions","authors":"Julia Martikainen, Olga Muñoz, Juan Carlos Gómez Martín, Teresa Jardiel, Marco Peiteado, Amador C. Caballero, Santiago Pérez-Hoyos, Agustin Sánchez Lavega, Tim Becker, Gerhard Wurm, Yannick Willame, Ann Carine Vandaele","doi":"10.3847/1538-4365/ad5720","DOIUrl":"https://doi.org/10.3847/1538-4365/ad5720","url":null,"abstract":"We present experimental scattering matrices of the JSC Mars-1, MMS-2, and MGS-1 simulants at 488 and 640 nm. The analogs were processed so that narrow size distributions representative of Martian dust aerosols during different dust cycles were obtained. We find that the forward peak of the phase function depends on particle size as it becomes narrower with increasing size, whereas the side- and backscattering directions depend on both composition and size so that increasing size and decreasing absorption produce a flatter curve. The position and maximum of the degree of linear polarization varies based on particle size and composition, and the negative polarization branch is more prominent for wavelength-scale particles diminishing with increasing size. The linear depolarization is strongly affected by size and composition. Finally, we compare sky-brightness curves measured by the Navcam and Hazcam engineering cameras on board the Mars Science Laboratory rover to the measured phase functions. The observations show a narrower peak at the forward direction and a flatter curve toward the side- and backscattering directions with an increasing dust load in the atmosphere, similar to what can be seen for the measured phase functions of the analogs with increasing particle size. In the case of the analogs, the flattening of the curve can be caused by an increase in multiple scattering within a particle by wavelength-scale surface roughness and/or internal inclusions. For the observed sky brightnesses, particle aggregation and multiple scattering among particles in denser dust conditions play a major role.","PeriodicalId":22368,"journal":{"name":"The Astrophysical Journal Supplement Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141865501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-29DOI: 10.3847/1538-4365/ad528b
Chia-Ying Chung, Sean M. Andrews, Mark A. Gurwell, Melvyn Wright, Feng Long, Wenrui Xu, Hauyu Baobab Liu
We present a new Submillimeter Array survey of 47 Class II sources in the Taurus–Auriga region. Our observations made 12 independent samples of flux densities over the 200–400 GHz frequency range. We tightly constrained the spectral indices of most sources to a narrow range of 2.0 ± 0.2; only a handful of spatially resolved (e.g., diameter >250 au) disks present larger spectral indices. The simplest interpretation for this result is that the (sub)millimeter luminosities of all of the observed target sources are dominated by very optically thick (e.g., τ ≳ 5) dust thermal emission. Some previous works that were based on the optically thin assumption thus might have underestimated optical depths by at least 1 order of magnitude. Assuming DSHARP dust opacities, this corresponds to underestimates of dust masses by a similar factor. For our specific selected sample, the lower limits of dust masses implied by the optically thick interpretation are 1–3 times higher than those previous estimates that were made based on the optically thin assumption. Moreover, some population synthesis models show that, to explain the observed, narrowly distributed spectral indices, the disks in our selected sample need to have very similar dust temperatures (Tdust). Given a specific assumption of median Tdust, the maximum grain sizes (amax) can also be constrained, which is a few times smaller than 0.1 mm for Tdust ∼ 100 K and a few millimeters for Tdust ∼ 24 K. The results may indicate that dust grain growth outside the water snow line is limited by the bouncing/fragmentation barriers. This is consistent with the recent laboratory experiments, which indicated that the coagulation of water-ice-coated dust is not efficient, and the water-ice-free dust is stickier and thus can coagulate more efficiently. In the Class II disks, the dust mass budget outside of the water snow line may be largely retained instead of being mostly consumed by planet formation. While Class II disks still possess sufficient dust masses to feed planet formation at a later time, it is unknown whether or not dust coagulation and planet formation can be efficient or natural outside of the water snow line.
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Pub Date : 2024-07-25DOI: 10.3847/1538-4365/ad5558
Rahul Shah, Soumadeep Saha, Purba Mukherjee, Utpal Garain and Supratik Pal
We investigate the prospect of reconstructing the “cosmic distance ladder” of the Universe using a novel deep learning framework called LADDER—Learning Algorithm for Deep Distance Estimation and Reconstruction. LADDER is trained on the apparent magnitude data from the Pantheon Type Ia supernova compilation, incorporating the full covariance information among data points, to produce predictions along with corresponding errors. After employing several validation tests with a number of deep learning models, we pick LADDER as the best-performing one. We then demonstrate applications of our method in the cosmological context, including serving as a model-independent tool for consistency checks for other data sets like baryon acoustic oscillations, calibration of high-redshift data sets such as gamma-ray bursts, and use as a model-independent mock-catalog generator for future probes. Our analysis advocates for careful consideration of machine learning techniques applied to cosmological contexts.
{"title":"LADDER: Revisiting the Cosmic Distance Ladder with Deep Learning Approaches and Exploring Its Applications","authors":"Rahul Shah, Soumadeep Saha, Purba Mukherjee, Utpal Garain and Supratik Pal","doi":"10.3847/1538-4365/ad5558","DOIUrl":"https://doi.org/10.3847/1538-4365/ad5558","url":null,"abstract":"We investigate the prospect of reconstructing the “cosmic distance ladder” of the Universe using a novel deep learning framework called LADDER—Learning Algorithm for Deep Distance Estimation and Reconstruction. LADDER is trained on the apparent magnitude data from the Pantheon Type Ia supernova compilation, incorporating the full covariance information among data points, to produce predictions along with corresponding errors. After employing several validation tests with a number of deep learning models, we pick LADDER as the best-performing one. We then demonstrate applications of our method in the cosmological context, including serving as a model-independent tool for consistency checks for other data sets like baryon acoustic oscillations, calibration of high-redshift data sets such as gamma-ray bursts, and use as a model-independent mock-catalog generator for future probes. Our analysis advocates for careful consideration of machine learning techniques applied to cosmological contexts.","PeriodicalId":22368,"journal":{"name":"The Astrophysical Journal Supplement Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141782175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Extreme-mass-ratio inspirals (EMRIs) could be detected by space-borne gravitational-wave (GW) detectors, such as the Laser Interferometer Space Antenna (LISA), TianQin, and Taiji. Localizing EMRIs by GW detectors can help us select candidate host galaxies, which can be used to infer the cosmic expansion history. In this paper, we demonstrate that the localization information can also be used to infer the formation channel of EMRIs, and can hence allow us to extract more precisely the redshift probability distributions. By conducting mock observations of the EMRIs that can be detected by TianQin and LISA, as well as the galaxies that can be provided by the future Chinese Space Station Telescope, we find that TianQin can constrain the Hubble–Lemaître constant H0 to a precision of ∼3%–8% and the dark energy equation-of-state parameter w0 to ∼10%–40%. The TianQin+LISA network, by increasing the localization accuracy, can improve the precisions of H0 and w0 to ∼0.4%–7% and ∼4%–20%, respectively. Then, considering an illustrative case in which all EMRIs originate in active galactic nuclei (AGNs), and combining the mock EMRI observation with a mock AGN catalog, we show that TianQin can recognize the EMRI–AGN correlation with ∼1300 detections. The TianQin+LISA network can reduce this required number to ∼30. Additionally, we propose a statistical method to directly estimate the fraction of EMRIs produced in AGNs, fagn, and show that observationally deriving this value could significantly improve the constraints on the cosmological parameters. These results demonstrate the potentials of using EMRIs as well as galaxy and AGN surveys to improve the constraints on cosmological parameters and the formation channel of EMRIs.
激光干涉仪空间天线（LISA）、天琴号和太极号等空间引力波（GW）探测器可以探测到极端质量比吸气（EMRIs）。通过引力波探测器定位 EMRI 可以帮助我们选择候选宿主星系，从而推断宇宙膨胀的历史。在本文中，我们证明了定位信息也可以用来推断EMRIs的形成通道，从而可以更精确地提取红移概率分布。通过对天琴和LISA可以探测到的EMRIs以及未来中国空间站望远镜可以提供的星系进行模拟观测，我们发现天琴可以将哈勃-勒梅特常数H0的约束精度提高到∼3%-8%，将暗能量状态方程参数w0的约束精度提高到∼10%-40%。天琴+LISA网络通过提高定位精度，可以将H0和w0的精度分别提高到0.4%～7%和4%～20%。然后，考虑到所有 EMRI 都起源于活动星系核（AGN）的示例，并将模拟 EMRI 观测与模拟 AGN 目录相结合，我们证明天琴可以识别 EMRI 与 AGN 的相关性，其探测次数可达 1300 次。天琴+LISA网络可以将所需数量减少到∼30。此外，我们还提出了一种统计方法来直接估算AGN中产生的EMRIs的分量，即fagn，并表明观测得出的这个值可以显著改善对宇宙学参数的约束。这些结果表明，利用 EMRIs 以及星系和 AGN 勘测来改进对宇宙学参数和 EMRIs 形成通道的约束是很有潜力的。
{"title":"Improving Cosmological Constraints by Inferring the Formation Channel of Extreme-mass-ratio Inspirals","authors":"Liang-Gui Zhu, 良贵 朱, Hui-Min Fan, 会敏 范, Xian Chen, 弦 陈, Yi-Ming Hu, 一鸣 胡, Jian-dong Zhang and 建东 张","doi":"10.3847/1538-4365/ad5446","DOIUrl":"https://doi.org/10.3847/1538-4365/ad5446","url":null,"abstract":"Extreme-mass-ratio inspirals (EMRIs) could be detected by space-borne gravitational-wave (GW) detectors, such as the Laser Interferometer Space Antenna (LISA), TianQin, and Taiji. Localizing EMRIs by GW detectors can help us select candidate host galaxies, which can be used to infer the cosmic expansion history. In this paper, we demonstrate that the localization information can also be used to infer the formation channel of EMRIs, and can hence allow us to extract more precisely the redshift probability distributions. By conducting mock observations of the EMRIs that can be detected by TianQin and LISA, as well as the galaxies that can be provided by the future Chinese Space Station Telescope, we find that TianQin can constrain the Hubble–Lemaître constant H0 to a precision of ∼3%–8% and the dark energy equation-of-state parameter w0 to ∼10%–40%. The TianQin+LISA network, by increasing the localization accuracy, can improve the precisions of H0 and w0 to ∼0.4%–7% and ∼4%–20%, respectively. Then, considering an illustrative case in which all EMRIs originate in active galactic nuclei (AGNs), and combining the mock EMRI observation with a mock AGN catalog, we show that TianQin can recognize the EMRI–AGN correlation with ∼1300 detections. The TianQin+LISA network can reduce this required number to ∼30. Additionally, we propose a statistical method to directly estimate the fraction of EMRIs produced in AGNs, fagn, and show that observationally deriving this value could significantly improve the constraints on the cosmological parameters. These results demonstrate the potentials of using EMRIs as well as galaxy and AGN surveys to improve the constraints on cosmological parameters and the formation channel of EMRIs.","PeriodicalId":22368,"journal":{"name":"The Astrophysical Journal Supplement Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141782178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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