arXiv:2412.10501v1 Announce Type: new
Abstract: This paper reports the first search for stellar-origin binary black holes within the LISA Data Challenges (LDC). The search algorithm and the Yorsh LDC datasets, both previously described elsewhere, are only summarized briefly; the primary focus here is to present the results of applying the search to the challenge of data. The search employs a hierarchical approach, leveraging semi-coherent matching of template waveforms to the data using a variable number of segments, combined with a particle swarm algorithm for parameter space exploration. The computational pipeline is accelerated using GPU hardware. The results of two searches using different models of the LISA response are presented. The most effective search finds all five sources in the data challenge with injected signal-to-noise ratios $gtrsim 12$. Rapid parameter estimation is performed for these sources.
This article presents the results of a search for stellar-origin binary black holes within the LISA Data Challenges (LDC). The search algorithm and the Yorsh LDC datasets are briefly summarized, with the primary focus being the presentation of the results.
Roadmap:
1. Introduction
- Briefly explain the purpose of the study and the importance of searching for stellar-origin binary black holes.
2. Search Algorithm and Datasets
- Summarize the search algorithm and the Yorsh LDC datasets.
- Explain the hierarchical approach and the use of semi-coherent matching of template waveforms.
- Describe the particle swarm algorithm for parameter space exploration.
- Mention the acceleration of the computational pipeline using GPU hardware.
3. Results of the Search
- Present the results of two searches using different models of the LISA response.
- Highlight the effectiveness of the search in finding all five sources in the data challenge with injected signal-to-noise ratios ≥ 12.
4. Rapid Parameter Estimation
- Explain the process of rapid parameter estimation performed for the identified sources.
Potential Challenges:
- One potential challenge in future searches for stellar-origin binary black holes is the increasing complexity of the data.
- The computational resources required for processing and analyzing the data may pose a challenge.
- Developing more efficient and accurate algorithms for parameter estimation could be a challenge.
Potential Opportunities:
- Advancements in GPU hardware and other computational technologies could provide opportunities for faster and more efficient data analysis.
- Collaboration with researchers from various fields could lead to innovative approaches and algorithms for data processing.
- Improvements in the modeling of the LISA response could enhance the accuracy of the search results.
Conclusion:
This study successfully applied a hierarchical search algorithm to the LISA Data Challenges and achieved promising results in detecting stellar-origin binary black holes. The rapid parameter estimation process further contributes to our understanding of these sources. However, future searches may face challenges related to the complexity of the data and the computational resources required. Nonetheless, advancements in technology and collaborative efforts offer opportunities to overcome these challenges and improve the accuracy and efficiency of the search.