Enhancing Taiji's Parameter Estimation under Non-Stationarity: a Time-Frequency Domain Framework for Galactic Binaries and Instrumental Noises
Fuente:
arXiv
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866908414489133056 |
|---|---|
| author | Du, Minghui Luo, Ziren Xu, Peng |
| author_facet | Du, Minghui Luo, Ziren Xu, Peng |
| contents | The data analysis of space-based gravitational wave detectors like Taiji faces significant challenges from non-stationary noise, which compromises the efficacy of traditional frequency-domain analysis. This work proposes a unified framework based on short-time Fourier transform (STFT) to enhance parameter estimation of Galactic binary and characterization of instrumental noise under non-stationarity. Segmenting data into locally stationary intervals, we derive STFT-based models for signals and noises, and implement Bayesian inference via the extended Whittle likelihood. Validated through the analysis of verification Galactic binaries and instrumental noises, our STFT approach outperforms frequency-domain methods by reducing the uncertainty and bias of estimation, successfully recovering low signal-to-noise ratio signals missed by frequency-domain analysis, and mitigating the degeneracy among noise parameters. The framework's robustness against noise drifts and computational efficiency highlight its potential for integration into future global analysis pipelines. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_10599 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Enhancing Taiji's Parameter Estimation under Non-Stationarity: a Time-Frequency Domain Framework for Galactic Binaries and Instrumental Noises Du, Minghui Luo, Ziren Xu, Peng General Relativity and Quantum Cosmology Instrumentation and Methods for Astrophysics The data analysis of space-based gravitational wave detectors like Taiji faces significant challenges from non-stationary noise, which compromises the efficacy of traditional frequency-domain analysis. This work proposes a unified framework based on short-time Fourier transform (STFT) to enhance parameter estimation of Galactic binary and characterization of instrumental noise under non-stationarity. Segmenting data into locally stationary intervals, we derive STFT-based models for signals and noises, and implement Bayesian inference via the extended Whittle likelihood. Validated through the analysis of verification Galactic binaries and instrumental noises, our STFT approach outperforms frequency-domain methods by reducing the uncertainty and bias of estimation, successfully recovering low signal-to-noise ratio signals missed by frequency-domain analysis, and mitigating the degeneracy among noise parameters. The framework's robustness against noise drifts and computational efficiency highlight its potential for integration into future global analysis pipelines. |
| title | Enhancing Taiji's Parameter Estimation under Non-Stationarity: a Time-Frequency Domain Framework for Galactic Binaries and Instrumental Noises |
| topic | General Relativity and Quantum Cosmology Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2506.10599 |