arXiv:2501.06315v1 Announce Type: new
Abstract: The orbiting LISA instrument is designed to detect gravitational waves in the millihertz band, produced by sources including galactic binaries and extreme mass ratio inspirals, among others. The detector consists of three spacecraft, each carrying a pair of free-falling test masses. A technology-demonstration mission, LISA Pathfinder, was launched in 2015, and observed several sudden changes in test mass acceleration, referred to as “glitches.” Similar glitches in the full LISA mission have the potential to contaminate the Time-Delay Interferometry outputs that are the detector’s primary data product. In this paper, we describe an optimization technique using maximum likelihood estimation for detecting and removing glitches with a known waveform.
Future Roadmap: Challenges and Opportunities
1. Challenges
- Contamination of Time-Delay Interferometry Outputs: Glitches observed in test mass acceleration during the LISA mission have the potential to contaminate the primary data product of the detector, the Time-Delay Interferometry outputs. This contamination can lead to inaccurate gravitational wave detection and analysis.
- Identification and Removing Glitches: The optimization technique using maximum likelihood estimation described in the paper aims to detect and remove glitches with a known waveform. However, accurately identifying and removing glitches can be challenging, especially if the glitches have unknown or unpredictable waveforms.
- Improving Detector Sensitivity: Another challenge for the LISA mission is to improve the detector’s sensitivity to gravitational waves in the millihertz band. Enhancements in technology and instrumentation will be crucial to achieving this goal.
2. Opportunities
- Advancement in Technology: The glitches observed during the LISA Pathfinder mission provide valuable insights into the behavior of the test masses and potential sources of contamination. Further research and technological advancements can help in developing robust techniques to identify and remove glitches effectively.
- Collaborative Efforts: Collaboration among scientists, engineers, and researchers from various disciplines will play a vital role in overcoming the challenges associated with glitch detection and removal. Sharing knowledge, expertise, and resources can result in significant breakthroughs.
- Data Analysis Techniques: Developing advanced data analysis techniques, such as machine learning algorithms and artificial intelligence, can help in automated glitch detection and removal, making the process more efficient and accurate.
3. Future Roadmap
- Continue research and development efforts to improve the detector sensitivity of LISA instrument in detecting gravitational waves.
- Investigate and analyze the glitches observed during the LISA Pathfinder mission to gain a better understanding of their characteristics and potential sources.
- Develop and refine optimization techniques, such as maximum likelihood estimation, to enhance the detection and removal of glitches with known waveforms.
- Explore and invest in innovative technologies and instrumentation that can improve glitch detection, identification, and removal.
- Encourage collaboration among scientists, engineers, and researchers to share knowledge and expertise in developing effective glitch detection and removal techniques.
- Investigate the feasibility of utilizing advanced data analysis techniques, such as machine learning algorithms and artificial intelligence, for automated glitch detection and removal.
- Continuously test and validate glitch detection and removal techniques using simulated and real data from the LISA instrument.
- Ensure regular updates and improvements to the LISA instrument based on the research findings and technological advancements.
Conclusion
The detection and removal of glitches in the LISA instrument’s data is crucial for accurate gravitational wave detection and analysis. While challenges such as contamination of outputs and identifying unknown waveforms exist, there are opportunities for improvement through advancements in technology, collaborative efforts, and data analysis techniques. Following the outlined future roadmap will contribute to overcoming these challenges and ensuring the success of the LISA mission.