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The NANOGrav 11-year Data Set: High-precision Timing of 45 Millisecond Pulsars
Zaven Arzoumanian
1
, Adam Brazier
2
, Sarah Burke-Spolaor
3,4
, Sydney Chamberlin
5
, Shami Chatterjee
2
, Brian Christy
6
,
James M. Cordes
2
, Neil J. Cornish
7
, Fronefield Crawford
8
, H. Thankful Cromartie
9
, Kathryn Crowter
10
,
Megan E. DeCesar
11,35
, Paul B. Demorest
12
, Timothy Dolch
13
, Justin A. Ellis
3,4,35
, Robert D. Ferdman
14
,
Elizabeth C. Ferrara
15
, Emmanuel Fonseca
16
, Nathan Garver-Daniels
3,4
, Peter A. Gentile
3,4
, Daniel Halmrast
13,17
, E. A. Huerta
18
,
Fredrick A. Jenet
19
, Cody Jessup
13
, Glenn Jones
20,35
, Megan L. Jones
3,4
, David L. Kaplan
21
, Michael T. Lam
3,4,35
,
T. Joseph W. Lazio
22
, Lina Levin
3,4
, Andrea Lommen
23
, Duncan R. Lorimer
3,4
, Jing Luo
19
, Ryan S. Lynch
24
,
Dustin Madison
25
, Allison M. Matthews
9
, Maura A. McLaughlin
3,4
, Sean T. McWilliams
3,4
, Chiara Mingarelli
26
,
Cherry Ng
10,27
, David J. Nice
11
, Timothy T. Pennucci
3,4,28,29,35
, Scott M. Ransom
25
, Paul S. Ray
30
, Xavier Siemens
21
,
Joseph Simon
22
, Renée Spiewak
21,31
, Ingrid H. Stairs
10
, Daniel R. Stinebring
32
, Kevin Stovall
12,35
,
Joseph K. Swiggum
21,35
, Stephen R. Taylor
22,35
, Michele Vallisneri
22
, Rutger van Haasteren
22,36
,
Sarah J. Vigeland
21,35
, and Weiwei Zhu
33,34
The NANOGrav Collaboration
1
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, USA
2
Department of Astronomy, Cornell University, Ithaca, NY 14853, USA
3
Department of Physics and Astronomy, West Virginia University, P.O. Box 6315, Morgantown, WV 26506, USA
4
Center for Gravitational Waves and Cosmology, West Virginia University, Chestnut Ridge Research Building, Morgantown, WV 26505, USA
5
Department of Astronomy and Astrophysics, Pennsylvania State University, University Park, PA 16802, USA
6
Department of Mathematics, Computer Science, and Physics, Notre Dame of Maryland University 4701 N Charles Street, Baltimore, MD 21210, USA
7
Department of Physics, Montana State University, Bozeman, MT 59717, USA
8
Department of Physics and Astronomy, Franklin & Marshall College, P.O. Box 3003, Lancaster, PA 17604, USA
9
University of Virginia, Department of Astronomy, P.O. Box 400325, Charlottesville, VA 22904, USA
10
Department of Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T 1Z1, Canada
11
Department of Physics, Lafayette College, Easton, PA 18042, USA; niced@lafayette.edu
12
National Radio Astronomy Observatory, 1003 Lopezville Road, Socorro, NM 87801, USA
13
Department of Physics, Hillsdale College, 33 E. College Street, Hillsdale, MI 49242, USA
14
School of Chemistry, University of East Anglia, Norwich, NR4 7TJ, UK
15
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
16
Department of Physics, McGill University, 3600 University Street, Montreal, QC H3A 2T8, Canada
17
Department of Mathematics, University of California, Santa Barbara, CA 93106, USA
18
NCSA and Department of Astronomy, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
19
Center for Gravitational Wave Astronomy, University of Texas-Rio Grande Valley, Brownsville, TX 78520, USA
20
Department of Physics, Columbia University, New York, NY 10027, USA
21
Center for Gravitation, Cosmology and Astrophysics, Department of Physics, University of Wisconsin-Milwaukee, P.O. Box 413, Milwaukee, WI 53201, USA
22
Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA
23
Department of Physics and Astronomy, Haverford College, Haverford, PA 19041, USA
24
Green Bank Observatory, P.O. Box 2, Green Bank, WV 24944, USA
25
National Radio Astronomy Observatory, 520 Edgemont Road, Charlottesville, VA 22903, USA
26
Center for Computational Astrophysics, Flatiron Institute, 162 5th Avenue, New York, New York, 10010, USA
27
Dunlap Institute for Astronomy and Astrophysics, University of Toronto, 50 St. George Street, Toronto, ON M5S 3H4, Canada
28
Institute of Physics, Eötvös Loránd University, Pázmány P.s. 1/A, 1117 Budapest, Hungary
29
Hungarian Academy of Sciences MTA-ELTE Extragalatic Astrophysics Research Group, 1117 Budapest, Hungary
30
Space Science Division, Naval Research Laboratory, Washington, DC 20375-5352, USA
31
Centre for Astrophysics and Supercomputing, Swinburne University of Technology, P.O. Box 218, Hawthorn, Victoria 3122, Australia
32
Department of Physics and Astronomy, Oberlin College, Oberlin, OH 44074, USA
33
National Astronomical Observatories, Chinese Academy of Science, 20A Datun Road, Chaoyang District, Beijing 100012, People’s Republic of China
34
Max Planck Institute for Radio Astronomy, Auf dem Hügel 69, D-53121 Bonn, Germany
Received 2017 December 23; revised 2018 March 2; accepted 2018 March 3; published 2018 April 9
Abstract
We present high-precision timing data over time spans of up to 11 years for 45 millisecond pulsars observed as part
of the North American Nanohertz Observatory for Gravitational Waves ( NANOGrav) project, aimed at detecting
and characterizing low-frequency gravitational waves. The pulsars were observed with the Arecibo Observatory
and/or the Green Bank Telescope at frequencies ranging from 327 MHz to 2.3 GHz. Most pulsars were observed
with approximately monthly cadence, and six high-timing-precision pulsars were observed weekly. All were
observed at widely separated frequencies at each observing epoch in order to fit for time-variable dispersion delays.
We describe our methods for data processing, time-of-arrival (TOA) calculation, and the implementation of a new,
automated method for removing outlier TOAs. We fit a timing model for each pulsar that includes spin,
astrometric, and (for binary pulsars) orbital parameters; time-variable dispersion delays; and parameters that
The Astrophysical Journal Supplement Series, 235:37 (41pp), 2018 April https://doi.org/10.3847/1538-4365/aab5b0
© 2018. The American Astronomical Society. All rights reserved.
35
NANOGrav Physics Frontiers Center Postdoctoral Fellow.
36
Currently employed at Microsoft Corporation.
1
quantify pulse-profile evolution with frequency. The timing solutions provide three new parallax measurements,
two new Shapiro delay measurements, and two new measurements of significant orbital-period variations. We fit
models that characterize sources of noise for each pulsar. We find that 11 pulsars show significant red noise, with
generally smaller spectral indices than typically measured for non-recycled pulsars, possibly suggesting a different
origin. A companion paper uses these data to constrain the strength of the gravitational-wave background.
Key words: binaries: general – gravitational waves – parallaxes – proper motions – pulsars: general – stars: neutron
Supporting material: tar.gz file
1. Introduction
High-precision timing of millisecond pulsars offers the
promise of detecting gravitational waves with periods of a few
years, i.e., in the nanohertz (nHz) band of the gravitational-
wave spectrum (Burke-Spolaor 2015; Lommen 2015).An
expected signal in this band is the incoherent superposition of
gravitational waves from the cosmic merger history of
supermassive black hole binaries, i.e., a gravitational-wave
background (Phinney 2001;Jaffe&Backer2003; Sesana 2013).
Its detection is likely within a few years (Taylor et al. 2016),
depending on the underlying astrophysics of supermassive black
hole binary mergers (Kocsis & Sesana 2011;Roedigetal.2012;
Sampson et al. 2015; Arzoumanian et al. 2016; Taylor et al.
2017). Other possible sources of gravitational waves in this band
are individual massive binary systems (Arzoumanian et al. 2014;
Babak et al. 2016), gravitational bursts with memory (e.g.,
Seto 2009; Madison et al. 2014; Zhu et al. 2014; Arzoumanian
et al. 2015a), primordial gravitational waves from inflation
(Grishchuk 1976, 1977; Starobinsky 1980; Lentati et al. 2015;
Lasky et al. 2016), and gravitational waves originating from
cosmic strings (e.g., Kibble 1976; Vilenkin 1981;Sanidas
et al. 2012; Arzoumanian et al. 2015a; Lentati et al. 2015).
Robust detection of nHz gravitational waves requires
observing and measuring pulse arrival times for an ensemble
of millisecond pulsars; the gravitational-wave signal is
manifested as perturbations in the arrival time measurements
that are correlated between pulsars, depending on their relative
positions (Hellings & Downs 1983; Cornish & Sesana 2013;
Taylor & Gair 2013; Mingarelli & Sidery 2014). For this
reason, the North American Nanohertz Observatory for
Gravitational Waves (NANOGrav) collaboration
37
has under-
taken high-precision timing observations of a large and
growing number of millisecond pulsars spread across the sky.
Similar programs are being carried out by the Parkes Pulsar
Timing Array (Hobbs 2013; Reardon et al. 2016) and the
European Pulsar Timing Array (Kramer & Champion 2013;
Desvignes et al. 2016).
Pulsar-timing experiments at nHz frequencies explore grav-
itational waves in a band entirely distinct from other techniques
used to explore the gravitational-wave spectrum, hence they are
sensitive to a completely different class of gravitational-wave
sources. For comparison, gravitational waves have been detected
directly by the LIGO ground-based interferometers in the
∼100Hz band (Abbott et al. 2016a, 2016b; The LIGO Scientific
Collaboration et al. 2017), and indirectly via binary-pulsar
orbital-decay measurements in the ∼100μHz band (e.g.,
Kramer et al. 2006; Fonseca et al. 2014;Weisberg&
Huang 2016); proposed space-based detectors will be sensitive
in the ∼10
−2
Hz band (Amaro-Seoane et al. 2017).
In addition to gravitational-wave detection, high-precision
pulsar data can be used for a variety of other applications,
including studies of binary systems and neutron-star masses
(Fonseca et al. 2016), measurements of pulsar astrometry and
space velocities (Matthews et al. 2016), tests of general
relativity (Zhu et al. 2015), and analysis of the ionized
interstellar medium (Lam et al. 2016a; Levin et al. 2016; Jones
et al. 2017).
This paper describes NANOGrav data collected over
11years, our “11-year Data Set.” It builds on our previous
paper describing our “Nine-year Data Set” (Arzoumanian et al.
2015b, herein NG9). This paper is organized as follows. In
Section 2, we describe the observations and data reduction.
In Section 3, we characterize the noise properties of the pulsars.
In Section 4, we present an astrometric analysis of the pulsars,
including distance estimates. In Section 5, we give updated
parameters of those pulsars in our observations that are in
binary systems, including refined measurement of pulsar and
companion-star masses. In Section 6, we summarize our
presentation. In the Appendix, we present timing residuals and
dispersion measure (DM) variations for all pulsars under
observation. A search for a gravitational-wave background in
these data is presented in a separate paper ( Arzoumanian
et al. 2018).
2. Observations, Data Reduction, and Timing Models
The NANOGrav 11-year data set consists of time-of-arrival
(TOA) measurements of 45 pulsars made over time spans of up
to 11 years, along with a parameterized model fit to the TOAs
of each pulsar.
Here, we describe the instrumentation, observations, and
data-reduction procedures applied to produce this data set. In
general, procedures closely follow those of NG9, so we provide
only a brief overview of details already covered in NG9,
highlighting any changes.
The data were collected from 2004 through the end of 2015.
For the 37 pulsars with data spans greater than 2.5 years (see
Table 1), observations taken though the end of 2013 were
previously reported in NG9. This work adds nine new pulsars
to the set; it removes one pulsar (PSR J1949+3106, which
provided relatively poor timing precision); and it extends the
time span of all remaining sources by approximately two years.
Five pulsars in NG9 had lengthy spans of single-receiver
observations at their initial years of observations; for four of
these pulsars (PSRs J1853+1303, J1910+1256, J1944+0907,
and B1953+29), we have removed those observations from the
present data set because of their susceptibility to unmodeled
variations in DM (see below). For the fifth (PSR J1741+1831),
we added observations with a second receiver at those epochs.
Observations were taken using two telescopes, the 305 m
William E. Gordon Telescope of the Arecibo Observatory, and
the 100 m Robert C. Byrd Green Bank Telescope (GBT) of the
37
North American Nanohertz Observatory for Gravitational Waves;http://
nanograv.org.
2
The Astrophysical Journal Supplement Series, 235:37 (41pp), 2018 April Arzoumanian et al.
Green Bank Observatory (formerly the National Radio
Astronomy Observatory). Pulsars at declinations 0°<δ<
+39° were observed with Arecibo, while all others were
observed with the GBT; two sources (PSRs J1713+0747
and B1937+21) were observed with both telescopes. An
approximately monthly observing cadence was used for most
of the observations. In addition, weekly observations were
made for two pulsars at the GBT beginning in 2013 (PSRs
J1713+0747 and J1909−3744) and for five pulsars at Arecibo
beginning in 2015 (PSRs J0030+0451, J1640+2224, J1713
Table 1
Basic Pulsar Parameters and TOA Statistics
Source PdP/dt DM P
b
Median Scaled TOA Uncertainty
a
(μs)/Number of Epochs
Span
(ms)(10
−20
)(pc cm
−3
)(day) 327MHz 430MHz 820MHz 1.4GHz 2.3GHz (year)
J0023+0923 3.05 1.14 14.3 LL0.132 42 L 0.153 50 L 4.4
J0030+0451 4.87 1.02 4.3 LL0.313 104 L 0.319 115 L 10.9
J0340+4130 3.30 0.70 49.6 LL L0.809 53 1.796 52 L 3.8
J0613−0200 3.06 0.96 38.8 1.2 LL0.108 119 0.433 115 L 10.8
J0636+5128 2.87 0.34 11.1 0.1 LL0.225 24 0.466 24 L 2.0
J0645+5158 8.85 0.49 18.2 LL L0.316 55 0.926 56 L 4.5
J0740+6620 2.89 1.22 15.0 4.8 LL0.523 22 0.570 24 L 2.0
J0931−1902 4.64 0.36 41.5 LL L0.778 36 1.559 35 L 2.8
J1012+5307 5.26 1.71 9.0 0.6 LL0.371 119 0.518 124 L 11.4
J1024−0719 5.16 1.86 6.5 LL L0.559 77 0.836 78 L 6.2
J1125+7819 4.20 0.70 11.2 15.4 LL0.817 21 1.267 24 L 2.0
J1453+1902 5.79 1.17 14.1 LL1.642 21 L 2.261 23 L 2.4
J1455−3330 7.99 2.43 13.6 76.2 LL0.929 105 1.724 103 L 11.4
J1600−3053 3.60 0.95 52.3 14.3 LL0.258 94 0.201 100 L 8.1
J1614−2230 3.15 0.96 34.5 8.7 LL0.341 79 0.446 91 L 7.2
J1640+2224 3.16 0.28 18.5 175.5 L 0.084 119 L 0.095 130 L 11.1
J1643−1224 4.62 1.85 62.3 147.0 LL0.291 118 0.483 117 L 11.2
J1713+0747 4.57 0.85 15.9 67.8 LL0.101 117 0.051 326 0.030 111 10.9
J1738+0333 5.85 2.41 33.8 0.4 LL L0.385 53 0.385 47 6.1
J1741+1351 3.75 3.02 24.2 16.3 L 0.200 45 L 0.213 63 0.235 9 6.4
J1744−1134 4.07 0.89 3.1 LL L0.113 113 0.193 111 L 11.4
J1747−4036 1.65 1.31 153.0 LL L1.094 49 1.115 51 L 3.8
J1832−0836 2.72 0.83 28.2 LL L0.606 38 0.422 35 L 2.8
J1853+1303 4.09 0.87 30.6 115.7 L 0.390 49 L 0.413 55 L 4.5
B1855+09 5.36 1.78 13.3 12.3 L 0.159 101 L 0.154 111 L 11.0
J1903+
0327 2.15 1.88 297.5 95.2 LL L0.501 58 0.497 51 6.1
J1909−3744 2.95 1.40 10.4 1.5 LL0.041 113 0.090 195 L 11.2
J1910+1256 4.98 0.97 38.1 58.5 LL L0.301 67 0.326 56 6.8
J1911+1347 4.63 1.69 31.0 LL0.136 22 L 0.131 25 L 2.4
J1918−0642 7.65 2.57 6.1 10.9 LL0.328 110 0.548 114 L 11.2
J1923+2515 3.79 0.96 18.9 LL0.514 36 L 0.568 48 L 4.3
B1937+21 1.56 10.51 71.1 LL L0.007 119 0.012 197 0.007 63 11.3
J1944+0907 5.19 1.73 24.3 LL0.428 44 L 0.475 54 L 4.4
B1953+29 6.13 2.97 104.5 117.3 L 0.662 36 L 0.719 47 L 4.4
J2010−1323 5.22 0.48 22.2 LL L0.336 79 0.692 79 L 6.2
J2017+0603 2.90 0.80 23.9 2.2 L 0.262 6 L 0.277 54 0.283 32 3.8
J2033+1734 5.95 1.11 25.1 56.3 L 0.712 20 L 0.716 26 L 2.3
J2043+1711 2.38 0.52 20.7 1.5 L 0.124 75 L 0.139 89 L 4.5
J2145−0750 16.05 2.98 9.0 6.8 LL0.229 95 0.494 100 L
11.3
J2214+3000 3.12 1.47 22.5 0.4 LL L0.496 53 0.464 39 4.2
J2229+2643 2.98 0.15 22.7 93.0 L 0.522 21 L 0.527 22 L 2.4
J2234+0611 3.58 1.20 10.8 32.0 L 0.214 20 L 0.214 24 L 2.0
J2234+0944 3.63 2.01 17.8 0.4 L 0.278 4 L 0.280 27 0.240 18 2.5
J2302+4442 5.19 1.39 13.8 125.9 LL0.992 55 1.659 50 L 3.8
J2317+1439 3.45 0.24 21.9 2.5 0.071 80 0.114 132 L 0.180 76 L 11.0
Nominal scaling factor
b
(ASP/GASP) 0.6 0.4 0.8 0.8 0.8
Nominal scaling factor
b
(GUPPI/PUPPI) 0.7 0.5 1.4 2.5 2.1
Notes.
a
For this table, the original TOA uncertainties were scaled by their bandwidth-time product,
100 MHz 1800 s
12
ntD
(
)
, to remove variation due to different instrument
bandwidths and integration time.
b
TOA uncertainties can be rescaled to the nominal full instrumental bandwidth as listed in Table1 of Arzoumanian et al. (2015b) by dividing by the scaling factors
given here.
3
The Astrophysical Journal Supplement Series, 235:37 (41pp), 2018 April Arzoumanian et al.
