اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدالاستنتاج على النظم الثنائية للأخصائي الأبيض باستخدام مجموعات البيانات الأولى لمشاريع تحديات داتا موك ليزا
Inference on white dwarf binary systems using the first round Mock LISA Data Challenges data sets
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نحن نقدم تحليلا لمجموعات البيانات المصدر المحدد من الجولة الأولى من مهارات بيانات موك ليسا للأشبال البيضاء. أدينا برنامجا كاملا مؤلفا من وحدة معالجة موحدة معتمدة على الشبكة للكشف عن الإشارة، ووحدة معالجة ماركوف الشاملة التلقائية لتقييم الإشارة. نظرنا إلى أن الكشف عن الإشارة باستخدام طريقتنا الموحدة آمنة ودقيقة، وأنها تزداد بالدقة وتزيد مع المعلومات الإضافية على عوامل الإشارة من خلال طريقتنا ماركوف الشاملة. كما أظهرنا أن الطريقة الماركوف الشاملة قادرة على تحديد بدقة مستوى الضوضاء في نافذة التردد المعنية.
We report on the analysis of selected single source data sets from the first round of the Mock LISA Data Challenges (MLDC) for white dwarf binaries. We implemented an end-to-end pipeline consisting of a grid-based coherent pre-processing unit for signal detection, and an automatic Markov Chain Monte Carlo post-processing unit for signal evaluation. We demonstrate that signal detection with our coherent approach is secure and accurate, and is increased in accuracy and supplemented with additional information on the signal parameters by our Markov Chain Monte Carlo approach. We also demonstrate that the Markov Chain Monte Carlo routine is additionally able to determine accurately the noise level in the frequency window of interest.
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The Mock LISA Data Challenges (MLDCs) have the dual purpose of fostering the development of LISA data analysis tools and capabilities, and demonstrating the technical readiness already achieved by the gravitational-wave community in distilling a rich
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