Dependence of the Reconstructed Core-Collapse Supernova Gravitational Wave High-Frequency Feature on the Nuclear Equation of State, in Real Interferometric Data
R. Daniel Murphy, Alejandro Casallas-Lagos, Anthony Mezzacappa, Michele Zanolin, Ryan E. Landfield, Eric J. Lentz, Pedro Marronetti, Javier M. Antelis, Claudia Moreno
We present an analysis of gravitational wave (GW) predictions from five two-dimensional Core Collapse Supernova (CCSN) simulations that varied only in the Equation of State (EOS) implemented. The GW signals from these simulations are used to produce spectrograms in the absence of noise, and the emergent high-frequency feature (HFF) is found to differ quantitatively between simulations. Below 1 kHz, the HFF is well approximated by a first-order polynomial in time. The resulting slope was found to vary between 10-50% across all models. Further, using real interferometric noise we investigated the current capabilities of GW detectors to resolve these differences in HFF slope for a Galactic CCSN. We find that for distances up to 1 kpc, current detectors can resolve HFF slopes that vary by at least 30%. For further Galactic distances, current detectors are capable of distinguishing the upper and lower bounds of the HFF slope for groupings of our models that varied in EOS. With the higher sensitivity of future GW detectors, and with improved analysis of the HFF, our ability to resolve properties of the HFF will improve for all Galactic distances. This study shows the potential of using the HFF of CCSN produced GWs to provide insight into the physical processes occurring deep within CCSN during collapse, and in particular its potential to further constrain the EOS through GW detection.
Classifying the nuclear equation of state in LVK interferometric noise through core-collapse supernova gravitational-wave signatures using convolutional neural networks
University of Warsaw（华沙大学）；Embry-Riddle Aeronautical University（埃默里-里德尔航空大学）；University of Tennessee, Knoxville（田纳西大学诺克斯维尔分校）；Tecnológico de Monterrey（蒙特雷理工学院）；Universidad de Guadalajara（瓜达拉哈拉大学）
Assessing a Template-Based Approach for Core-Collapse Supernova Gravitational-Wave Detection
The Oskar Klein Centre, Department of Astronomy, Stockholm University（斯德哥尔摩大学天文学系奥斯卡·克莱因中心）；Department of Mathematics, University of Wisconsin–Madison（威斯康星大学麦迪逊分校数学系）
From the Early Slope to Curvature: Future Prospects and challenges for Astrophysical Parameter Estimation Using the Core-Collapse Supernova High-Frequency Feature
Faculty of Physics, University of Warsaw（华沙大学物理学院）；Department of Physics and Astronomy, ERAU（埃默里大学物理与天文系）；Department of Physics and Astronomy, University of Tennessee, Knoxville（田纳西大学诺克斯维尔分校物理与天文系）
Reconstructing Core-Collapse Supernova Gravitational-Wave Signals with Transdimensional Bayesian Inference
Swinburne University of Technology（斯威本科技大学）；ARC Centre of Excellence for Gravitational Wave Discovery (OzGrav)（引力波发现卓越研究中心）；Monash University（莫纳什大学）；University of Melbourne（墨尔本大学）
A high resolution HI study towards the supernova remnant Puppis A and its environments
我们观察超新星遗迹（SNR）船尾座A在21厘米线与澳大利亚望远镜紧凑阵列的目的是确定系统的速度，因此，相应的运动学距离。对于紧凑的，在现场的背景源，我们得到的吸收光谱，通过应用两种方法：（a）减去轮廓上和关闭源连续发射，和（b）过滤傅立叶平面中的短空间频率，以消除大规模的发射。船尾座A外壳东部最亮的特征之一被发现是背景源，可能是河外星系。除去这个和以前已知的不相关的源的贡献，船尾座A的系统速度被限制在8和12 km s $^{-1}$之间，这使得这个源的距离为1.3 $\pm$ 0.3 kpc。从包括单碟和干涉数据的组合图像中，我们分析了星际氢的分布。我们认为，如果距离为$\lesssim$ 1.2 kpc，那么在$v \sim $ +8 km s $^{-1}$处的椭球环可能是船尾座A的祖先吹出的气泡的遗迹。与以前的出版物（$v =$ +16 km s $^{-1}$和$d = $ 2.2 kpc）相比，新的系统速度和距离的主要结果是在东方没有一个致密的相互作用云来解释形态，以及壳层尺寸和中子星速度的减小，现在与统计值更好地吻合。
Joint Detection and Characterization of the Standing Accretion Shock Instability for Core-Collapse Supernovae with cWB XP
Universidad de Guadalajara（瓜达拉哈拉大学）；Sun Yat-Sen University（中山大学）；University of Tennessee Knoxville（田纳西大学诺克斯维尔分校）；University of New Hampshire（新罕布什尔大学）；Embry-Riddle Aeronautical University（埃姆布里-里德航空大学）；Tecnológico de Monterrey（蒙特雷理工学院）；University of Warsaw（华沙大学）
Constructing angular distributions of neutrinos in core collapse supernova from zero-th and first moments calibrated by full Boltzmann neutrino transport
