arXiv subjects

Michele Vallisneri

Publications and source records attributed to Michele Vallisneri.

At least 55 records · Page 3Linked to original sources

arXiv2020

The NANOGrav 12.5-year Data Set: Wideband Timing of 47 Millisecond Pulsars

We present a new analysis of the profile data from the 47 millisecond pulsars comprising the 12.5-year data set of the North American Nanohertz Observatory for Gravitational Waves (NANOGrav), which is presented in a parallel paper (Alam et al. 2021a; NG12.5). Our reprocessing is performed using "wideband" timing methods, which use frequency-dependent template profiles, simultaneous time-of-arrival (TOA) and dispersion measure (DM) measurements from broadband observations, and novel analysis techniques. In particular, the wideband DM measurements are used to constrain the DM portion of the timing model. We compare the ensemble timing results to NG12.5 by examining the timing residuals, timing models, and noise model components. There is a remarkable level of agreement across all metrics considered. Our best-timed pulsars produce encouragingly similar results to those from NG12.5. In certain cases, such as high-DM pulsars with profile broadening, or sources that are weak and scintillating, wideband timing techniques prove to be beneficial, leading to more precise timing model parameters by 10-15%. The high-precision, multi-band measurements of several pulsars indicate frequency-dependent DMs. Compared to the narrowband analysis in NG12.5, the TOA volume is reduced by a factor of 33, which may ultimately facilitate computational speed-ups for complex pulsar timing array analyses. This first wideband pulsar timing data set is a stepping stone, and its consistent results with NG12.5 assure us that such data sets are appropriate for gravitational wave analyses.

astro-ph.HE↗

arXiv2020

TDI-infinity: time-delay interferometry without delays

The space-based gravitational-wave observatory LISA relies on a form of synthetic interferometry (time-delay interferometry, or TDI) where the otherwise overwhelming laser phase noise is canceled by linear combinations of appropriately delayed phase measurements. These observables grow in length and complexity as the realistic features of the LISA orbits are taken into account. In this paper we outline an implicit formulation of TDI where we write the LISA likelihood directly in terms of the basic phase measurements, and we marginalize over the laser phase noises in the limit of infinite laser-noise variance. Equivalently, we rely on TDI observables that are defined numerically (rather than algebraically) from a discrete-filter representation of the laser propagation delays. Our method generalizes to any time dependence of the armlengths; it simplifies the modeling of gravitational-wave signals; and it allows a straightforward treatment of data gaps and missing measurements.

gr-qc↗

arXiv2020

Multi-Messenger Gravitational Wave Searches with Pulsar Timing Arrays: Application to 3C66B Using the NANOGrav 11-year Data Set

When galaxies merge, the supermassive black holes in their centers may form binaries and, during the process of merger, emit low-frequency gravitational radiation in the process. In this paper we consider the galaxy 3C66B, which was used as the target of the first multi-messenger search for gravitational waves. Due to the observed periodicities present in the photometric and astrometric data of the source of the source, it has been theorized to contain a supermassive black hole binary. Its apparent 1.05-year orbital period would place the gravitational wave emission directly in the pulsar timing band. Since the first pulsar timing array study of 3C66B, revised models of the source have been published, and timing array sensitivities and techniques have improved dramatically. With these advances, we further constrain the chirp mass of the potential supermassive black hole binary in 3C66B to less than $(1.65\pm0.02) \times 10^9~{M_\odot}$ using data from the NANOGrav 11-year data set. This upper limit provides a factor of 1.6 improvement over previous limits, and a factor of 4.3 over the first search done. Nevertheless, the most recent orbital model for the source is still consistent with our limit from pulsar timing array data. In addition, we are able to quantify the improvement made by the inclusion of source properties gleaned from electromagnetic data to `blind' pulsar timing array searches. With these methods, it is apparent that it is not necessary to obtain exact a priori knowledge of the period of a binary to gain meaningful astrophysical inferences.

astro-ph.GA↗

arXiv2020

On parametric tests of relativity with false degrees of freedom

General relativity can be tested by comparing the binary-inspiral signals found in LIGO--Virgo data against waveform models that are augmented with artificial degrees of freedom. This approach suffers from a number of logical and practical pitfalls. 1) It is difficult to ascribe meaning to the stringency of the resultant constraints. 2) It is doubtful that the Bayesian model comparison of relativity against these artificial models can offer actual validation for the former. 3) It is unknown to what extent these tests might detect alternative theories of gravity for which there are no computed waveforms; conversely, when waveforms are available, tests that employ them will be superior.

gr-qc↗

arXiv2020

GipsyX/RTGx, A New Tool Set for Space Geodetic Operations and Research

GipsyX/RTGx is the Jet Propulsion Laboratory's (JPL) next generation software package for positioning, navigation, timing, and Earth science using measurements from three geodetic techniques: Global Navigation Satellite Systems (GNSS), Satellite Laser Ranging (SLR), and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS); with Very Long Baseline Interferometry (VLBI) under development. The software facilitates combined estimation of geodetic and geophysical parameters using a Kalman filter approach on real or simulated data in both post-processing and in real-time. The estimated parameters include station coordinates and velocities, satellite orbits and clocks, Earth orientation, ionospheric and tropospheric delays. The software is also capable of full realization of a dynamic terrestrial reference through analysis and combination of time series of ground station coordinates. We present some key aspects of its new architecture, and describe some of its major applications, including Real-time orbit determination and ephemeris predictions in the U.S. Air Force Next Generation GPS Operational Control Segment (OCX), as well as in JPL's Global Differential GPS (GDGPS) System, supporting User Range Error (URE) of $<$ 5 cm RMS; precision post-processing GNSS orbit determination, including JPL's contributions to the International GNSS Service (IGS) with URE in the 2 cm RMS range; Precise point positioning (PPP) with ambiguity resolution, both statically and kinematically, for geodetic applications with 2 mm horizontal, and 6.5 mm vertical repeatability for static positioning; Operational orbit and clock determination for Low Earth Orbiting (LEO) satellites, such as NASA's Gravity Recovery and Climate Experiment (GRACE) mission with GRACE relative clock alignment at the 20 ps level.

physics.geo-ph↗

arXiv2020

Learning Bayesian posteriors with neural networks for gravitational-wave inference

We seek to achieve the Holy Grail of Bayesian inference for gravitational-wave astronomy: using deep-learning techniques to instantly produce the posterior $p(θ|D)$ for the source parameters $θ$, given the detector data $D$. To do so, we train a deep neural network to take as input a signal + noise data set (drawn from the astrophysical source-parameter prior and the sampling distribution of detector noise), and to output a parametrized approximation of the corresponding posterior. We rely on a compact representation of the data based on reduced-order modeling, which we generate efficiently using a separate neural-network waveform interpolant [A. J. K. Chua, C. R. Galley & M. Vallisneri, Phys. Rev. Lett. 122, 211101 (2019)]. Our scheme has broad relevance to gravitational-wave applications such as low-latency parameter estimation and characterizing the science returns of future experiments. Source code and trained networks are available online at https://github.com/vallis/truebayes.

gr-qc↗

arXiv2019

The Laser Interferometer Space Antenna: Unveiling the Millihertz Gravitational Wave Sky

The first terrestrial gravitational wave interferometers have dramatically underscored the scientific value of observing the Universe through an entirely different window, and of folding this new channel of information with traditional astronomical data for a multimessenger view. The Laser Interferometer Space Antenna (LISA) will broaden the reach of gravitational wave astronomy by conducting the first survey of the millihertz gravitational wave sky, detecting tens of thousands of individual astrophysical sources ranging from white-dwarf binaries in our own galaxy to mergers of massive black holes at redshifts extending beyond the epoch of reionization. These observations will inform - and transform - our understanding of the end state of stellar evolution, massive black hole birth, and the co-evolution of galaxies and black holes through cosmic time. LISA also has the potential to detect gravitational wave emission from elusive astrophysical sources such as intermediate-mass black holes as well as exotic cosmological sources such as inflationary fields and cosmic string cusps.

astro-ph.IM↗

arXiv2019

Reduced-order modeling with artificial neurons for gravitational-wave inference

Gravitational-wave data analysis is rapidly absorbing techniques from deep learning, with a focus on convolutional networks and related methods that treat noisy time series as images. We pursue an alternative approach, in which waveforms are first represented as weighted sums over reduced bases (reduced-order modeling); we then train artificial neural networks to map gravitational-wave source parameters into basis coefficients. Statistical inference proceeds directly in coefficient space, where it is theoretically straightforward and computationally efficient. The neural networks also provide analytic waveform derivatives, which are useful for gradient-based sampling schemes. We demonstrate fast and accurate coefficient interpolation for the case of a four-dimensional binary-inspiral waveform family, and discuss promising applications of our framework in parameter estimation.

astro-ph.IM↗

arXiv2019

Bayesian cross validation for gravitational-wave searches in pulsar-timing array data

Gravitational-wave data analysis demands sophisticated statistical noise models in a bid to extract highly obscured signals from data. In Bayesian model comparison, we choose among a landscape of models by comparing their marginal likelihoods. However, this computation is numerically fraught and can be sensitive to arbitrary choices in the specification of parameter priors. In Bayesian cross validation, we characterize the fit and predictive power of a model by computing the Bayesian posterior of its parameters in a training dataset, and then use that posterior to compute the averaged likelihood of a different testing dataset. The resulting cross-validation scores are straightforward to compute; they are insensitive to prior tuning; and they penalize unnecessarily complex models that overfit the training data at the expense of predictive performance. In this article, we discuss cross validation in the context of pulsar-timing-array data analysis, and we exemplify its application to simulated pulsar data (where it successfully selects the correct spectral index of a stochastic gravitational-wave background), and to a pulsar dataset from the NANOGrav 11-year release (where it convincingly favors a model that represents a transient feature in the interstellar medium). We argue that cross validation offers a promising alternative to Bayesian model comparison, and we discuss its use for gravitational-wave detection, by selecting or refuting models that include a gravitational-wave component.

astro-ph.IM↗

arXiv2019

The Discovery Potential of Space-Based Gravitational Wave Astronomy

A space-based interferometer operating in the previously unexplored mHz gravitational band has tremendous discovery potential. If history is any guide, the opening of a new spectral band will lead to the discovery of entirely new sources and phenomena. The mHz band is ideally suited to exploring beyond standard model processes in the early universe, and with the sensitivities that can be reached with current technologies, the discovery space for exotic astrophysical systems is vast.

astro-ph.HE↗

arXiv2019

Astro2020 Decadal Science White Paper: The state of gravitational-wave astrophysics in 2020

While still in its infancy, the budding field of gravitational-wave astronomy has so far exceeded most expectations, and the achievements that have already been made bode well for the decade to come. While the discoveries made possible by LIGO have captured the imagination of experts and nonexperts alike, it is important when looking ahead to consider those discoveries in the context of the field as a whole. Just as radio, optical, and x-ray radiation probe different physical phenomena occurring on a range of length and energy scales, the future of gravitational-wave astrophysics depends on our ability to open up the entire spectrum. We will describe the scientific prospects for the field of gravitational-wave astronomy as a whole as we enter the coming decade, and we will place the specific contributions from a future space-based gravitational-wave observatory within this context.

astro-ph.HE↗

arXiv2019

What we can learn from multi-band observations of black hole binaries

The LIGO/Virgo gravitational-wave (GW) interferometers have to-date detected ten merging black hole (BH) binaries, some with masses considerably larger than had been anticipated. Stellar-mass BH binaries at the high end of the observed mass range (with "chirp mass" ${\cal M} \gtrsim 25 M_{\odot}$) should be detectable by a space-based GW observatory years before those binaries become visible to ground-based GW detectors. This white paper discusses some of the synergies that result when the same binaries are observed by instruments in space and on the ground. We consider intermediate-mass black hole binaries (with total mass $M \sim 10^2 -10^4 M_{\odot}$) as well as stellar-mass black hole binaries. We illustrate how combining space-based and ground-based data sets can break degeneracies and thereby improve our understanding of the binary's physical parameters. While early work focused on how space-based observatories can forecast precisely when some mergers will be observed on the ground, the reverse is also important: ground-based detections will allow us to "dig deeper" into archived, space-based data to confidently identify black hole inspirals whose signal-to-noise ratios were originally sub-threshold, increasing the number of binaries observed in both bands by a factor of $\sim 4 - 7$.

astro-ph.HE↗

arXiv2019

Tests of General Relativity and Fundamental Physics with Space-based Gravitational Wave Detectors

Low-frequency gravitational-wave astronomy can perform precision tests of general relativity and probe fundamental physics in a regime previously inaccessible. A space-based detector will be a formidable tool to explore gravity's role in the cosmos, potentially telling us if and where Einstein's theory fails and providing clues about some of the greatest mysteries in physics and astronomy, such as dark matter and the origin of the Universe.

astro-ph.HE↗

arXiv2018

The NANOGrav 11-year Data Set: High-precision timing of 45 Millisecond Pulsars

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, with six high--timing-precision pulsars observed weekly, and 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, if necessary, binary parameters, in addition to time-variable dispersion delays and parameters that quantify pulse-profile evolution with frequency. The new timing solutions provide three new parallax measurements, two new Shapiro delay measurements, and two new measurements of large 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. Future papers will use these data to constrain or detect the signatures of gravitational-wave signals.

astro-ph.HE↗

arXiv2018

A Gaussian Mixture Model for Nulling Pulsars

The phenomenon of pulsar nulling -- where pulsars occasionally turn off for one or more pulses -- provides insight into pulsar-emission mechanisms and the processes by which pulsars turn off when they cross the "death line." However, while ever more pulsars are found that exhibit nulling behavior, the statistical techniques used to measure nulling are biased, with limited utility and precision. In this paper we introduce an improved algorithm, based on Gaussian mixture models, for measuring pulsar nulling behavior. We demonstrate this algorithm on a number of pulsars observed as part of a larger sample of nulling pulsars, and show that it performs considerably better than existing techniques, yielding better precision and no bias. We further validate our algorithm on simulated data. Our algorithm is widely applicable to a large number of pulsars even if they do not show obvious nulls. Moreover, it can be used to derive nulling probabilities of nulling for individual pulses, which can be used for in-depth studies.

astro-ph.IM↗

arXiv2017

Laser Interferometer Space Antenna

Following the selection of The Gravitational Universe by ESA, and the successful flight of LISA Pathfinder, the LISA Consortium now proposes a 4 year mission in response to ESA's call for missions for L3. The observatory will be based on three arms with six active laser links, between three identical spacecraft in a triangular formation separated by 2.5 million km. LISA is an all-sky monitor and will offer a wide view of a dynamic cosmos using Gravitational Waves as new and unique messengers to unveil The Gravitational Universe. It provides the closest ever view of the infant Universe at TeV energy scales, has known sources in the form of verification binaries in the Milky Way, and can probe the entire Universe, from its smallest scales near the horizons of black holes, all the way to cosmological scales. The LISA mission will scan the entire sky as it follows behind the Earth in its orbit, obtaining both polarisations of the Gravitational Waves simultaneously, and will measure source parameters with astrophysically relevant sensitivity in a band from below $10^{-4}\,$Hz to above $10^{-1}\,$Hz.

astro-ph.IM↗

arXiv2016

Taming outliers in pulsar-timing datasets with hierarchical likelihoods and Hamiltonian sampling

Pulsar-timing datasets have been analyzed with great success using probabilistic treatments based on Gaussian distributions, with applications ranging from studies of neutron-star structure to tests of general relativity and searches for nanosecond gravitational waves. As for other applications of Gaussian distributions, outliers in timing measurements pose a significant challenge to statistical inference, since they can bias the estimation of timing and noise parameters, and affect reported parameter uncertainties. We describe and demonstrate a practical end-to-end approach to perform Bayesian inference of timing and noise parameters robustly in the presence of outliers, and to identify these probabilistically. The method is fully consistent (i.e., outlier-ness probabilities vary in tune with the posterior distributions of the timing and noise parameters), and it relies on the efficient sampling of the hierarchical form of the pulsar-timing likelihood. Such sampling has recently become possible with a "no-U-turn" Hamiltonian sampler coupled to a highly customized reparametrization of the likelihood; this code is described elsewhere, but it is already available online. We recommend our method as a standard step in the preparation of pulsar-timing-array datasets: even if statistical inference is not affected, follow-up studies of outlier candidates can reveal unseen problems in radio observations and timing measurements; furthermore, confidence in the results of gravitational-wave searches will only benefit from stringent statistical evidence that datasets are clean and outlier-free.

astro-ph.IM↗

arXiv2016

The Emergence of Gravitational Wave Science: 100 Years of Development of Mathematical Theory, Detectors, Numerical Algorithms, and Data Analysis Tools

On September 14, 2015, the newly upgraded Laser Interferometer Gravitational-wave Observatory (LIGO) recorded a loud gravitational-wave (GW) signal, emitted a billion light-years away by a coalescing binary of two stellar-mass black holes. The detection was announced in February 2016, in time for the hundredth anniversary of Einstein's prediction of GWs within the theory of general relativity (GR). The signal represents the first direct detection of GWs, the first observation of a black-hole binary, and the first test of GR in its strong-field, high-velocity, nonlinear regime. In the remainder of its first observing run, LIGO observed two more signals from black-hole binaries, one moderately loud, another at the boundary of statistical significance. The detections mark the end of a decades-long quest, and the beginning of GW astronomy: finally, we are able to probe the unseen, electromagnetically dark Universe by listening to it. In this article, we present a short historical overview of GW science: this young discipline combines GR, arguably the crowning achievement of classical physics, with record-setting, ultra-low-noise laser interferometry, and with some of the most powerful developments in the theory of differential geometry, partial differential equations, high-performance computation, numerical analysis, signal processing, statistical inference, and data science. Our emphasis is on the synergy between these disciplines, and how mathematics, broadly understood, has historically played, and continues to play, a crucial role in the development of GW science. We focus on black holes, which are very pure mathematical solutions of Einstein's gravitational-field equations that are nevertheless realized in Nature, and that provided the first observed signals.

gr-qc↗