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Title: The NANOGrav Nine-year Data Set: Measurement and Analysis of Variations in Dispersion Measures

Abstract

We analyze dispersion measure (DM) variations of 37 millisecond pulsars in the nine-year North American Nanohertz Observatory for Gravitational Waves (NANOGrav) data release and constrain the sources of these variations. DM variations can result from a changing distance between Earth and the pulsar, inhomogeneities in the interstellar medium, and solar effects. Variations are significant for nearly all pulsars, with characteristic timescales comparable to or even shorter than the average spacing between observations. Five pulsars have periodic annual variations, 14 pulsars have monotonically increasing or decreasing trends, and 14 pulsars show both effects. Of the four pulsars with linear trends that have line-of-sight velocity measurements, three are consistent with a changing distance and require an overdensity of free electrons local to the pulsar. Several pulsars show correlations between DM excesses and lines of sight that pass close to the Sun. Mapping of the DM variations as a function of the pulsar trajectory can identify localized interstellar medium features and, in one case, an upper limit to the size of the dispersing region of 4 au. Four pulsars show roughly Kolmogorov structure functions (SFs), and another four show SFs less steep than Kolmogorov. One pulsar has too large an uncertainty to allowmore » comparisons. We discuss explanations for apparent departures from a Kolmogorov-like spectrum, and we show that the presence of other trends and localized features or gradients in the interstellar medium is the most likely cause.« less

Authors:
; ;  [1]; ;  [2];  [3];  [4]; ;  [5];  [6];  [7]; ;  [8]; ;  [9]; ;  [10];  [11];  [12];  [13] more »; « less
  1. Department of Physics and Astronomy, West Virginia University, Morgantown, WV 26506 (United States)
  2. Department of Astronomy and Cornell Center for Astrophysics and Planetary Science, Cornell University, Ithaca, NY 14853 (United States)
  3. Jodrell Bank Centre for Astrophysics, Alan Turing Building, School of Physics and Astronomy, The University of Manchester, Oxford Road, Manchester, M13 9PL (United Kingdom)
  4. Center for Research and Exploration in Space Science and Technology and X-Ray Astrophysics Laboratory, NASA Goddard Space Flight Center, Code 662, Greenbelt, MD 20771 (United States)
  5. Department of Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1 (Canada)
  6. National Radio Astronomy Observatory, P.O. Box 0, Socorro, NM 87801 (United States)
  7. Department of Physics, Hillsdale College, 33 E. College Street, Hillsdale, MI 49242 (United States)
  8. Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr. Pasadena, CA 91109 (United States)
  9. Department of Physics, McGill University, 3600 rue Universite, Montreal, QC H3A 2T8 (Canada)
  10. Department of Physics, Columbia University, 550 W. 120th St. New York, NY 10027 (United States)
  11. Department of Physics, Lafayette College, Easton, PA 18042 (United States)
  12. National Radio Astronomy Observatory, 520 Edgemont Road, Charlottesville, VA 22903 (United States)
  13. Department of Physics and Astronomy, Oberlin College, Oberlin, OH 44074 (United States)
Publication Date:
OSTI Identifier:
22663539
Resource Type:
Journal Article
Resource Relation:
Journal Name: Astrophysical Journal; Journal Volume: 841; Journal Issue: 2; Other Information: Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
79 ASTROPHYSICS, COSMOLOGY AND ASTRONOMY; ANNUAL VARIATIONS; COMPARATIVE EVALUATIONS; CORRELATIONS; DISPERSIONS; GRAVITATIONAL WAVES; PERIODICITY; PULSARS; SPECTRA; STRUCTURE FUNCTIONS; SUN; TRAJECTORIES; VELOCITY

Citation Formats

Jones, M. L., McLaughlin, M. A., Lam, M. T., Cordes, J. M., Chatterjee, S., Levin, L., Arzoumanian, Z., Crowter, K., Gonzalez, M. E., Demorest, P. B., Dolch, T., Ellis, J. A, Lazio, T. J. W., Ferdman, R. D., Fonseca, E., Jones, G., Pennucci, T. T., Nice, D. J., Ransom, S. M., Stinebring, D. R., and and others. The NANOGrav Nine-year Data Set: Measurement and Analysis of Variations in Dispersion Measures. United States: N. p., 2017. Web. doi:10.3847/1538-4357/AA73DF.
Jones, M. L., McLaughlin, M. A., Lam, M. T., Cordes, J. M., Chatterjee, S., Levin, L., Arzoumanian, Z., Crowter, K., Gonzalez, M. E., Demorest, P. B., Dolch, T., Ellis, J. A, Lazio, T. J. W., Ferdman, R. D., Fonseca, E., Jones, G., Pennucci, T. T., Nice, D. J., Ransom, S. M., Stinebring, D. R., & and others. The NANOGrav Nine-year Data Set: Measurement and Analysis of Variations in Dispersion Measures. United States. doi:10.3847/1538-4357/AA73DF.
Jones, M. L., McLaughlin, M. A., Lam, M. T., Cordes, J. M., Chatterjee, S., Levin, L., Arzoumanian, Z., Crowter, K., Gonzalez, M. E., Demorest, P. B., Dolch, T., Ellis, J. A, Lazio, T. J. W., Ferdman, R. D., Fonseca, E., Jones, G., Pennucci, T. T., Nice, D. J., Ransom, S. M., Stinebring, D. R., and and others. Thu . "The NANOGrav Nine-year Data Set: Measurement and Analysis of Variations in Dispersion Measures". United States. doi:10.3847/1538-4357/AA73DF.
@article{osti_22663539,
title = {The NANOGrav Nine-year Data Set: Measurement and Analysis of Variations in Dispersion Measures},
author = {Jones, M. L. and McLaughlin, M. A. and Lam, M. T. and Cordes, J. M. and Chatterjee, S. and Levin, L. and Arzoumanian, Z. and Crowter, K. and Gonzalez, M. E. and Demorest, P. B. and Dolch, T. and Ellis, J. A and Lazio, T. J. W. and Ferdman, R. D. and Fonseca, E. and Jones, G. and Pennucci, T. T. and Nice, D. J. and Ransom, S. M. and Stinebring, D. R. and and others},
abstractNote = {We analyze dispersion measure (DM) variations of 37 millisecond pulsars in the nine-year North American Nanohertz Observatory for Gravitational Waves (NANOGrav) data release and constrain the sources of these variations. DM variations can result from a changing distance between Earth and the pulsar, inhomogeneities in the interstellar medium, and solar effects. Variations are significant for nearly all pulsars, with characteristic timescales comparable to or even shorter than the average spacing between observations. Five pulsars have periodic annual variations, 14 pulsars have monotonically increasing or decreasing trends, and 14 pulsars show both effects. Of the four pulsars with linear trends that have line-of-sight velocity measurements, three are consistent with a changing distance and require an overdensity of free electrons local to the pulsar. Several pulsars show correlations between DM excesses and lines of sight that pass close to the Sun. Mapping of the DM variations as a function of the pulsar trajectory can identify localized interstellar medium features and, in one case, an upper limit to the size of the dispersing region of 4 au. Four pulsars show roughly Kolmogorov structure functions (SFs), and another four show SFs less steep than Kolmogorov. One pulsar has too large an uncertainty to allow comparisons. We discuss explanations for apparent departures from a Kolmogorov-like spectrum, and we show that the presence of other trends and localized features or gradients in the interstellar medium is the most likely cause.},
doi = {10.3847/1538-4357/AA73DF},
journal = {Astrophysical Journal},
number = 2,
volume = 841,
place = {United States},
year = {Thu Jun 01 00:00:00 EDT 2017},
month = {Thu Jun 01 00:00:00 EDT 2017}
}
  • We present high-precision timing observations spanning up to nine years for 37 millisecond pulsars monitored with the Green Bank and Arecibo radio telescopes as part of the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) project. We describe the observational and instrumental setups used to collect the data, and methodology applied for calculating pulse times of arrival; these include novel methods for measuring instrumental offsets and characterizing low signal-to-noise ratio timing results. The time of arrival data are fit to a physical timing model for each source, including terms that characterize time-variable dispersion measure and frequency-dependent pulse shape evolution. Inmore » conjunction with the timing model fit, we have performed a Bayesian analysis of a parameterized timing noise model for each source, and detect evidence for excess low-frequency, or “red,” timing noise in 10 of the pulsars. For 5 of these cases this is likely due to interstellar medium propagation effects rather than intrisic spin variations. Subsequent papers in this series will present further analysis of this data set aimed at detecting or limiting the presence of nanohertz-frequency gravitational wave signals.« less
  • We report on an effort to extract and monitor interstellar scintillation parameters in regular timing observations collected for the North American Nanohertz Observatory for Gravitational Waves pulsar timing array. Scattering delays are measured by creating dynamic spectra for each pulsar and observing epoch of wide-band observations centered near 1500 MHz and carried out at the Green Bank Telescope and the Arecibo Observatory. The ∼800 MHz wide frequency bands imply dramatic changes in scintillation bandwidth across the bandpass, and a stretching routine has been included to account for this scaling. For most of the 10 pulsars for which the scaling hasmore » been measured, the bandwidths scale with frequency less steeply than expected for a Kolmogorov medium. We find estimated scattering delay values that vary with time by up to an order of magnitude. The mean measured scattering delays are similar to previously published values and are slightly higher than predicted by interstellar medium models. We investigate the possibility of increasing the timing precision by mitigating timing errors introduced by the scattering delays. For most of the pulsars, the uncertainty in the time of arrival of a single timing point is much larger than the maximum variation of the scattering delay, suggesting that diffractive scintillation remains as only a negligible part of their noise budget.« less
  • Gravitational wave (GW) astronomy using a pulsar timing array requires high-quality millisecond pulsars (MSPs), correctable interstellar propagation delays, and high-precision measurements of pulse times of arrival. Here we identify noise in timing residuals that exceeds that predicted for arrival time estimation for MSPs observed by the North American Nanohertz Observatory for Gravitational Waves. We characterize the excess noise using variance and structure function analyses. We find that 26 out of 37 pulsars show inconsistencies with a white-noise-only model based on the short timescale analysis of each pulsar, and we demonstrate that the excess noise has a red power spectrum formore » 15 pulsars. We also decompose the excess noise into chromatic (radio-frequency-dependent) and achromatic components. Associating the achromatic red-noise component with spin noise and including additional power-spectrum-based estimates from the literature, we estimate a scaling law in terms of spin parameters (frequency and frequency derivative) and data-span length and compare it to the scaling law of Shannon and Cordes. We briefly discuss our results in terms of detection of GWs at nanohertz frequencies.« less
  • We have improved further the error sensitive Richardson-Lucy deconvolution algorithm making it applicable directly on the un-binned measured angular power spectrum of Cosmic Microwave Background observations to reconstruct the form of the primordial power spectrum. This improvement makes the application of the method significantly more straight forward by removing some intermediate stages of analysis allowing a reconstruction of the primordial spectrum with higher efficiency and precision and with lower computational expenses. Applying the modified algorithm we fit the WMAP 9 year data using the optimized reconstructed form of the primordial spectrum with more than 300 improvement in χ{sup 2}{sub eff}more » with respect to the best fit power-law. This is clearly beyond the reach of other alternative approaches and reflects the efficiency of the proposed method in the reconstruction process and allow us to look for any possible feature in the primordial spectrum projected in the CMB data. Though the proposed method allow us to look at various possibilities for the form of the primordial spectrum, all having good fit to the data, proper error-analysis is needed to test for consistency of theoretical models since, along with possible physical artefacts, most of the features in the reconstructed spectrum might be arising from fitting noises in the CMB data. Reconstructed error-band for the form of the primordial spectrum using many realizations of the data, all bootstrapped and based on WMAP 9 year data, shows proper consistency of power-law form of the primordial spectrum with the WMAP 9 data at all wave numbers. Including WMAP polarization data in to the analysis have not improved much our results due to its low quality but we expect Planck data will allow us to make a full analysis on CMB observations on both temperature and polarization separately and in combination.« less
  • The WMAP team subtracted template-based foreground models to produce foreground-reduced maps, and masked point sources and uncertain sky regions directly; however, whether foreground residuals exist in the WMAP foreground-reduced maps is still an open question. Here, we use Pearson correlation coefficient analysis with AS-γ TeV cosmic ray (CR) data to probe possible foreground residuals in the WMAP nine-year data. The correlation results between the CR and foreground-contained maps (WMAP foreground-unreduced maps, WMAP template-based, and Maximum Entropy Method foreground models) suggest that: (1) CRs can trace foregrounds in the WMAP data; (2) at least some TeV CRs originate from the Milkymore » Way; (3) foregrounds may be related to the existence of CR anisotropy (loss-cone and tail-in structures); (4) there exist differences among different types of foregrounds in the decl. range of <15°. Then, we generate 10,000 mock cosmic microwave background (CMB) sky maps to describe the cosmic variance, which is used to measure the effect of the fluctuations of all possible CMB maps to the correlations between CR and CMB maps. Finally, we do correlation analysis between the CR and WMAP foreground-reduced maps, and find that: (1) there are significant anticorrelations; and (2) the WMAP foreground-reduced maps are credible. However, the significant anticorrelations may be accidental, and the higher signal-to-noise ratio Planck SMICA map cannot reject the hypothesis of accidental correlations. We therefore can only conclude that the foreground residuals exist with ∼95% probability.« less