论文标题
基于图像的搜索使用MWA VCS数据搜索PULSAR候选
Image-based searches for pulsar candidates using MWA VCS data
论文作者
论文摘要
事实证明，脉冲星有助于探索各种物理学。低无线电频率处的脉冲星对于进一步了解光谱特性和发射机制至关重要。默奇森广场阵列电压捕获系统（MWA-VC）通常用于研究和发现低频的脉冲星，以录制复杂电压的独特机会，可以在线构成型号的时间，以找到毫无疑问的时间。 candidates, which can be verified in beamformed data, can accelerate the complete process and lead to more pulsar detections by reducing the number of tied-array beams required, increasing compute resource efficiency.Despite a factor of ~4 loss in sensitivity, searching for pulsar candidates in images from the MWA-VCS, we can explore a larger parameter space, potentially leading to discoveries of pulsars missed by high-frequency通过传播效果通过高级分辨率的脉冲分段数据中遮盖的脉冲星的调查。基于图像的搜索对于探测参数空间的一部分至关重要的，对于传统的光束搜索无法访问的一部分，使用MWA进行。在本文中，我们描述了创新的方法和Dual-Prococessing MWA VCS数据的创新方法和能力。基于图像的基于图像的测试方法，基于脉冲星的特性，例如光谱指数，极化和可变性。这些方法的效率已在已知的脉冲星上得到验证，并且在敏感性和低频谱频谱中所解释的主要限制是对某些Pulsars的低频谱的范围。 Pulsar发现了MWA的发现，并通过SKA-LOW加速了未来的搜索。
Pulsars have proven instrumental in exploring a wide variety of physics. Pulsars at low radio frequencies is crucial to further our understanding of spectral properties and emission mechanisms.The Murchison Widefield Array Voltage Capture System (MWA-VCS) has been routinely used to study and discover pulsars at low frequencies, offering the unique opportunity of recording complex voltages ,which can be off-line beamformed or imaged at millisecond time resolution.Devising imaged-based methods for finding pulsar candidates, which can be verified in beamformed data, can accelerate the complete process and lead to more pulsar detections by reducing the number of tied-array beams required, increasing compute resource efficiency.Despite a factor of ~4 loss in sensitivity, searching for pulsar candidates in images from the MWA-VCS, we can explore a larger parameter space, potentially leading to discoveries of pulsars missed by high-frequency surveys such as pulsars obscured in high-time resolution timeseries data by propagation effects.Image-based searches are also essential to probing parts of parameter space inaccessible to traditional beamformed searches with the MWA.In this paper we describe the innovative approach and capability of dual-processing MWA VCS data, i.e. finding pulsar candidates in these images, and verifying by forming tied-array beam.We developed and tested image-based methods of finding pulsar candidates, based on pulsar properties such as spectral index, polarisation and variability.The efficiency of these methodologies has been verified on known pulsars, and the main limitations explained in terms of sensitivity and low-frequency spectral turnover of some pulsars.No candidates were confirmed to be a new pulsar.This new capability will now be applied to multiple observations to accelerate pulsar discoveries with MWA and speed up future searches with the SKA-Low.
