Image: A schematic pulsar timing array. (Credit: NASA/DOE/Fermi LAT Collaboration via Nature)

• The IPTA observes the best astrophysical clocks in the Universe, millisecond pulsars. The pulsars spin rapidly and we see a beam of emission pass our line of sight many times per second. Since the emission is very stable, we can use each observed pulse as the "tick" of a clock, allowing us to measure time very precisely and accurately.
• As the distance between the pulsar and the Earth changes, the time it takes pulses to arrive at the Earth will also change. We develop models of radio-pulse arrival times which take into account the pulsar's spin and spindown rate, the position and motion on the sky relative to the Earth, and for many pulsars the orbital motions around a binary companion. With this information, we can predict when pulses will arrive at the Earth.
• Deviations from these timing models can be due to a wide range of effects. If a gravitational wave passes by the Earth or the pulsar, the distance will change ever so slightly. For a pulsar with a radius of about 10,000 meters, we expect a change of perhaps 10 to 1,000 meters depending on the type of passing gravitational wave. The distances to pulsars are of the order of 30,000,000,000,000,000,000 meters, which is why we need such precise clocks to measure distances so precisely.
• For gravitational waves that pass by the Earth, we can look for the correlation of arrival times between sets of pulsars either early or late. For example, if space stretches then two pulsars observed in the same direction will have their pulses both arrive later than we expect from our timing models. The pulses will arrive early if space contracts.
• The primary source of low-frequency GWs is expected to be from early inspiral phase of supermassive black hole binaries (SMBHBs), with masses greater than 1e8 solar masses. The incoherent superposition of these GWs should form a gravitational wave background (GWB) with an amplitude ranging anywhere from 1e−16−2e−15, at a reference frequency of 1/yr .
• The amplitude of the GWB depends strongly on the astrophysics underlying SMBH mergers: the merger rate (or stalling), the black hole masses, and the SMBH population fraction (how many galaxies host SMBHs). The shape of the spectrum can also be affected by stars and gas interacting with the binary, as well as binary eccentricity, all of which cause the strain spectrum toturn over at low frequencies.
• The most up-to-date analyses of PTA data have already set astrophysically interesting bounds on these processes.

• Read more

• Though millisecond pulsars are fairly precise clocks, there are intrinsic and extrinsic sources of noise that must be characterized in order to optimize the sensitivity of a pulsar timing array. Some of these varied and overlapping noise sources include radiometer noise, pulse template matching errors, intrinsic pulsar spin noise, pulse jitter, timing model errors, ephemeris errors, clock errors, the interstellar medium, and the interplanetary medium.
• In addition to white noise, time-correlated (or red) noise is also seen in PTA data. It is especially important to understand this latter type, as the GW background will manifest as a red noise process common to all pulsars.
• Radio waves are dispersed and scattered as they travel through the interstellar medium. The scattering results in temporal broadening of the pulses, scintillation of the signal at the observer, and second order frequency-dependent dispersive effects. Dispersion measure changes and lensing events can also add noise to the data.
• As PTAs have become more sensitive, new sources of error become important. Recently it was shown that errors in the modeling of the solar system ephemeris need to be taken into account when searching for the GW background

Image: Various types of noise that affect pulsar timing data sets. Image Credit: James Cordes

Image: Radio pulses scattering off of the interstellar medium. Image Credit: Jeffrey Hazboun

Image: The Hellings and Downs curve, showing the spatial correlations between pulsars in the presence of a stochastic background of gravitational waves.

• The IPTA is releasing 2 MDCs over the next few months. Each MDC will have two groups of three datasets. MDC2 begins now, while MDC3 will begin in a few months.
• MDC2, Group 1 is made up of open datasets. Each dataset contains a version of the data which is evenly spaced (a-version), and another set which has a more realistic, unevenly spaced cadence of observation epochs (b-version). Both the signal and noise injections for these datasets are identical, and the evenly-spaced dataset is provided as a simple first problem for students as well as a comparison of how unevenly-sampled data complicates PTA data analysis.
• Group 1, Dataset 1 contains only white noise, i.e. TOA measurement uncertainties, for the individual pulsars and only one signal; a stochastic gravitational wave background injected as appropriate spatial-correlations between the various pulsars.
• Group 1, Dataset 2 also contains a stochastic GWB and white noise, but additionally has red noise injections for the pulsars. Red noise here refers to a low-frequency process that produces errors in data that are correlated over long timescales. Details about the power-law amplitude and spectral index for each pulsar can be found in the specific dataset notes.
• Group 1, Dataset 3 contains no stochastic background, but does contain a single SMBHB source.
• Group 2 has a similar signal/noise content as Group 1, however there is no longer an evenly sampled version of the data. These datasets are closed in the sense that we do not reveal which dataset includes which noise and signal types. However, we do reveal that the dataset includes three combinations of signal.
• Group 2 Datasets Include: One containing only a stochastic GWB, one containing a stochastic GWB and a single-resolvable SMBHB source and one containing no stochastic background but two SMBHB signals. All contain both white noise and red noise.
• MDC3 will be released near the end of 2018 and will also have two groups of three datasets.

• MDC Questions: Contact: Dr. Jeffrey S. Hazboun (Data Challenge Working Group Co-Chair)
• General Questions: Contact: Dr. Ryan Shannon (IPTA Chair)

The IPTA Collaboration at the 2018 Summer meeting in Albequerque, NM