Abstract Radio pulsar signals are significantly perturbed by their propagation through the ionized interstellar medium. In addition to the frequency-dependent pulse times of arrival due to dispersion, pulse shapes are also distorted and shifted, having been scattered by the inhomogeneous interstellar plasma, affecting pulse arrival times. Understanding the degree to which scattering affects pulsar timing is important for gravitational-wave detection with pulsar timing arrays (PTAs), which depend on the reliability of pulsars as stable clocks with an uncertainty of ∼100 ns or less over ∼10 yr or more. Scattering can be described as a convolution of the intrinsic pulse shape with an impulse response function representing the effects of multipath propagation. In previous studies, the technique of cyclic spectroscopy has been applied to pulsar signals to deconvolve the effects of scattering from the original emitted signals, increasing the overall timing precision. We present an analysis of simulated data to test the quality of deconvolution using cyclic spectroscopy over a range of parameters characterizing interstellar scattering and pulsar signal-to-noise ratio (S/N). We show that cyclic spectroscopy is most effective for high S/N and/or highly scattered pulsars. We conclude that cyclic spectroscopy could play an important role in scattering correction to distant populations of highly scattered pulsars not currently included in PTAs. For future telescopes and for current instruments such as the Green Bank Telescope upgraded with the ultrawide bandwidth receiver, cyclic spectroscopy could potentially double the number of PTA-quality pulsars.
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Scattering Delay Mitigation in High-accuracy Pulsar Timing: Cyclic Spectroscopy Techniques
We simulate scattering delays from the interstellar medium to examine the effectiveness of three estimators in recovering these delays in pulsar timing data. Two of these estimators use the more traditional process of fitting autocorrelation functions to pulsar dynamic spectra to extract scintillation bandwidths, while the third estimator uses the newer technique of cyclic spectroscopy on baseband pulsar data to recover the interstellar medium’s impulse response function. We find that either fitting a Lorentzian or Gaussian distribution to an autocorrelation function or recovering the impulse response function from the cyclic spectrum are, on average, accurate in recovering scattering delays, although autocorrelation function estimators have a large variance, even at high signal-to-noise ratio (S/N). We find that, given sufficient S/N, cyclic spectroscopy is more accurate than both Gaussian and Lorentzian fitting for recovering scattering delays at specific epochs, suggesting that cyclic spectroscopy is a superior method for scattering estimation in high-quality data.
more » « less- Award ID(s):
- 2020265
- NSF-PAR ID:
- 10399183
- Publisher / Repository:
- DOI PREFIX: 10.3847
- Date Published:
- Journal Name:
- The Astrophysical Journal
- Volume:
- 944
- Issue:
- 2
- ISSN:
- 0004-637X
- Format(s):
- Medium: X Size: Article No. 191
- Size(s):
- ["Article No. 191"]
- Sponsoring Org:
- National Science Foundation
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Significance Statement Accurately correcting for systematic errors in observational records of land surface air temperature (LSAT) is critical for quantifying historical warming. Existing LSAT estimates are subject to systematic offsets associated with processes including changes in instrumentation and station movement. This study improves a pairwise homogenization algorithm by accounting for the fact that climate signals are correlated over time. The revised algorithms outperform the original in identifying discontinuities and recovering accurate warming trends. Applied to monthly station temperatures, the revised algorithms adjust trends in continental mean LSAT since the 1880s to be 0.16°C century−1greater relative to raw data. Our estimate is most consistent with that from Berkeley Earth and indicates lesser and greater warming than estimates from NOAA and the Met Office, respectively.
