A Comprehensive Framework for F-statistic-based Parameter Estimation of Binary Black Hole Signals

Fs_standard-s1_p1: Results based on the F-statistic method with the configuration 's1'; Fs_standard-v2_p1: Results based on the F-statistic method with the configuration 's2'; standard-s1_p1: Results based on the full Bayesian inference method with the configuration 's1'; standard-v2: Results based on the full Bayesian inference method with the configuration 's2'.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-18
DOI
https://doi.org/10.5281/zenodo.16484750
Primary Topic
Mathematics, Computing, and Information Processing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Comprehensive Framework for F-statistic-based Parameter Estimation of Binary Black Hole Signals

Zenodo (CERN European Organization for Nuclear Research)
Mathematics, Computing, and Information Processing
article

A Comprehensive Framework for F-statistic-based Parameter Estimation of Binary Black Hole Signals

article en

Abstract

Fs_standard-s1_p1: Results based on the F-statistic method with the configuration 's1'; Fs_standard-v2_p1: Results based on the F-statistic method with the configuration 's2'; standard-s1_p1: Results based on the full Bayesian inference method with the configuration 's1'; standard-v2: Results based on the full Bayesian inference method with the configuration 's2'.

Zenodo (CERN European Organization for Nuclear Research)
Dalian University of Technology (CN)
Openalex Percentile: Top 46%
Mathematics, Computing, and Information Processing
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.