12 research outputs found
Asymptotics with Numerical Relativity: Gravitational Memory, BMS Frames, and Nonlinearities
With the recent commencement of the LIGO-Virgo-KAGRA (LVK) Collaboration's fourth observing run, the field of gravitational-wave physics is uniquely poised to collect even more accurate data from compact binary coalescences. Consequently, we will soon be able to perform more stringent tests of general relativity (GR). Because GR must, in some regime, be violated---either because the Universe is described by an alternative theory or because of the emergence of quantum effects---these tests of GR are crucial for unveiling new physics. Performing such tests, however, requires that our understanding of GR and gravitational waves is reliable. And, while there are many tools for unraveling Einstein's equations, the only one that is robust in every regime of GR is numerical relativity (NR): a means for computing accurate solutions to Einstein's equations with supercomputers.
In this thesis, I highlight some recent and impactful advancements that have been incorporated into NR simulations of binary black holes. In particular, I show how a more robust procedure for calculating the radiative data at future null infinity from NR simulations, called Cauchy-characteristic evolution (CCE), produces waveforms that exhibit a not-yet observed prediction of GR colloquially referred to as memory. This phenomenon corresponds to the permanent net displacement that two observers will experience due to the passage of transient gravitational radiation. Memory is of particular interest in the testing GR and theory communities because of its relation to asymptotic symmetries and scattering amplitude calculations in particle physics. With these contemporary CCE waveforms, I provide explicit methods to calculate the various memory effects and I also comment on their relative magnitudes and detectability in the near future. Apart from this, I also demonstrate the importance of controlling the BMS freedoms of these waveforms, i.e., their frame freedom at future null infinity, for building waveform models as well as for extracting physics, such as GR's nonlinearities, from the ringdown phase of binary black hole mergers.
As we start to enter the next phase of high-precision gravitational-wave astronomy, correctly modeling gravitational waves with NR simulations will play a crucial role in pushing Einstein's theory of relativity to its limits. It is the aim of this thesis to illustrate the importance of combining gravitational-wave theory and NR to not only improve our understanding of black holes and gravitational waves, but also further our prospects for unveiling the true nature of gravity within our universe.</p
Computation of Displacement and Spin Gravitational Memory in Numerical Relativity
We present the first numerical relativity waveforms for binary black hole
mergers produced using spectral methods that show both the displacement and the
spin memory effects. Explicitly, we use the SXS Collaboration's
code to run a Cauchy evolution of a binary black hole merger and then extract
the gravitational wave strain using 's version of a
Cauchy-characteristic extraction. We find that we can accurately resolve the
strain's traditional memory modes and some of the oscillatory
memory modes that have previously only been theorized. We also perform a
separate calculation of the memory using equations for the Bondi-Metzner-Sachs
charges as well as the energy and angular momentum fluxes at asymptotic
infinity. Our new calculation uses only the gravitational wave strain and two
of the Weyl scalars at infinity. Also, this computation shows that the memory
modes can be understood as a combination of a memory signal throughout the
binary's inspiral and merger phases, and a quasinormal mode signal near the
ringdown phase. Additionally, we find that the magnetic memory, up to numerical
error, is indeed zero as previously conjectured. Lastly, we find that
signal-to-noise ratios of memory for LIGO, the Einstein Telescope (ET), and the
Laser Interferometer Space Antenna (LISA) with these new waveforms and new
memory calculation are larger than previous expectations based on
post-Newtonian or Minimal Waveform models.Comment: 20 pages, 11 figures; 10.1103/PhysRevD.102.104007. Corrected a minor
sign error in Eqs. 27, 40, 42, 43, and 5
Computation of displacement and spin gravitational memory in numerical relativity
We present the first numerical relativity waveforms for binary black hole mergers produced using spectral methods that show both the displacement and the spin memory effects. Explicitly, we use the SXS (Simulating eXtreme Spacetimes) Collaboration’s SpEC code to run a Cauchy evolution of a binary black hole merger and then extract the gravitational wave strain using SpECTRE’s version of a Cauchy-characteristic extraction. We find that we can accurately resolve the strain’s traditional m=0 memory modes and some of the m≠0 oscillatory memory modes that have previously only been theorized. We also perform a separate calculation of the memory using equations for the Bondi-Metzner-Sachs charges as well as the energy and angular momentum fluxes at asymptotic infinity. Our new calculation uses only the gravitational wave strain and two of the Weyl scalars at infinity. Also, this computation shows that the memory modes can be understood as a combination of a memory signal throughout the binary’s inspiral and merger phases, and a quasinormal mode signal near the ringdown phase. Additionally, we find that the magnetic memory, up to numerical error, is indeed zero as previously conjectured. Last, we find that signal-to-noise ratios of memory for LIGO, the Einstein Telescope, and the Laser Interferometer Space Antenna with these new waveforms and new memory calculation are larger than previous expectations based on post-Newtonian or minimal waveform models
Collective filters: a new approach to analyze the gravitational-wave ringdown of binary black-hole mergers
We propose two frequency-domain filters to analyze ringdown signals of binary
black hole mergers. The first rational filter is constructed based on a set of
(arbitrary) quasi-normal modes (QNMs) of the remnant black holes, whereas the
second full filter comes from the transmissivity of the remnant black holes.
The two filters can remove corresponding QNMs from original time-domain
ringdowns, while changing early inspiral signals in a trivial way - merely a
time and phase shift. After filtering out dominant QNMs, we can visualize the
existence of various subdominant effects. For example, by applying our filters
to a GW150914-like numerical relativity (NR) waveform, we find second-order
effects in the (l = 4, m = 4), (l = 5, m = 4) and (l = 5, m = 5) harmonics; the
spherical-spheroidal mixing mode in the (l = 2,m = 2) harmonic; and a mixing
mode in the (l = 2,m = 1) harmonic due to a gravitational recoil. In another NR
simulation where two component spins are anti-aligned with the orbital angular
momentum, we also find retrograde modes. Additionally, we propose to use the
rational filter to estimate the start time of a QNM. The filters are sensitive
to the remnant properties (i.e., mass and spin) and thus have a potential
application to future data analyses and parameter estimations. We also
investigate the stability of the full filter. Its connection to the instability
of QNM spectra is discussed
Comparing Remnant Properties from Horizon Data and Asymptotic Data in Numerical Relativity
We present a new study of remnant black hole properties from 13 binary black
hole systems, numerically evolved using the Spectral Einstein Code. The mass,
spin, and recoil velocity of each remnant were determined quasi-locally from
apparent horizon data and asymptotically from Bondi data computed at future null infinity using SpECTRE's Cauchy
characteristic evolution. We compare these independent measurements of the
remnant properties in the bulk and on the boundary of the spacetime, giving
insight into how well asymptotic data are able to reproduce local properties of
the remnant black hole in numerical relativity. We also discuss the theoretical
framework for connecting horizon quantities to asymptotic quantities and how it
relates to our results. This study recommends a simple improvement to the
recoil velocities reported in the Simulating eXtreme Spacetimes waveform
catalog, provides an improvement to future surrogate remnant models, and offers
new analysis techniques for evaluating the physical accuracy of numerical
simulations.Comment: 14 pages, 4 figures, 1 table; published Physical Review
Numerical relativity surrogate model with memory effects and post-Newtonian hybridization
Numerical relativity simulations provide the most precise templates for the
gravitational waves produced by binary black hole mergers. However, many of
these simulations use an incomplete waveform extraction technique --
extrapolation -- that fails to capture important physics, such as gravitational
memory effects. Cauchy-characteristic evolution (CCE), by contrast, is a much
more physically accurate extraction procedure that fully evolves Einstein's
equations to future null infinity and accurately captures the expected physics.
In this work, we present a new surrogate model, NRHybSur3dq8CCE, built from
CCE waveforms that have been mapped to the post-Newtonian (PN) BMS frame and
then hybridized with PN and effective one-body (EOB) waveforms. This model is
trained on 102 waveforms with mass ratios and aligned spins
. The model spans the
entire LIGO-Virgo-KAGRA (LVK) frequency band (with
) for total masses and
includes the and spin-weight spherical
harmonic modes, but not the , or modes. We find that
NRHybSur3dq8CCE can accurately reproduce the training waveforms with
mismatches for total masses and can, for a modest degree of extrapolation, capably model
outside of its training region. Most importantly, unlike previous waveform
models, the new surrogate model successfully captures memory effects.Comment: 14 pages, 11 figures. Accepted for publication in PR
Extending black-hole remnant surrogate models to extreme mass ratios
Numerical-relativity surrogate models for both black-hole merger waveforms
and remnants have emerged as important tools in gravitational-wave astronomy.
While producing very accurate predictions, their applicability is limited to
the region of the parameter space where numerical-relativity simulations are
available and computationally feasible. Notably, this excludes extreme mass
ratios. We present a machine-learning approach to extend the validity of
existing and future numerical-relativity surrogate models toward the
test-particle limit, targeting in particular the mass and spin of post-merger
black-hole remnants. Our model is trained on both numerical-relativity
simulations at comparable masses and analytical predictions at extreme mass
ratios. We extend the gaussian-process-regression model NRSur7dq4Remnant,
validate its performance via cross validation, and test its accuracy against
additional numerical-relativity runs. Our fit, which we dub
NRSur7dq4EmriRemnant, reaches an accuracy that is comparable to or higher than
that of existing remnant models while providing robust predictions for
arbitrary mass ratios.Comment: 10 pages, 3 figures. Model publicly available at
https://pypi.org/project/surfinB
Laying the foundation of the effective-one-body waveform models SEOBNRv5: improved accuracy and efficiency for spinning non-precessing binary black holes
We present SEOBNRv5HM, a more accurate and faster inspiral-merger-ringdown
gravitational waveform model for quasi-circular, spinning, nonprecessing binary
black holes within the effective-one-body (EOB) formalism. Compared to its
predecessor, SEOBNRv4HM, the waveform model i) incorporates recent high-order
post- Newtonian results in the inspiral, with improved resummations, ii)
includes the gravitational modes (l, |m|) = (3, 2), (4, 3), in addition to the
(2, 2), (3, 3), (2, 1), (4, 4), (5, 5) modes already implemented in SEOBNRv4HM,
iii) is calibrated to larger mass-ratios and spins using a catalog of 442
numerical-relativity (NR) simulations and 13 additional waveforms from
black-hole perturbation theory, iv) incorporates information from second-order
gravitational self-force (2GSF) in the nonspinning modes and radiation-reaction
force. Computing the unfaithfulness against NR simulations, we find that for
the dominant (2, 2) mode the maximum unfaithfulness in the total mass range
is below for 90% of the cases (38% for
SEOBNRv4HM). When including all modes up to l = 5 we find 98% (49%) of the
cases with unfaithfulness below , while these numbers reduce
to 88% (5%) when using SEOBNRv4HM. Furthermore, the model shows improved
agreement with NR in other dynamical quantities (e.g., the angular momentum
flux and binding energy), providing a powerful check of its physical
robustness. We implemented the waveform model in a high-performance Python
package (pySEOBNR), which leads to evaluation times faster than SEOBNRv4HM by a
factor 10 to 50, depending on the configuration, and provides the flexibility
to easily include spin-precession and eccentric effects, thus making it the
starting point for a new generation of EOBNR waveform models (SEOBNRv5) to be
employed for upcoming observing runs of the LIGO-Virgo-KAGRA detectors
SXS BBH CCE Catalog
Catalog of CCE waveforms for binary black hole simulations.Files available via S3 at ttps://renc.osn.xsede.org/ini210004tommorrell/0_D1.20236/GW150914/Lev5/</p>Horizons.h5 1.5 MB
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r2News_BondiCce_R0100.h5 23.2 MB
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r2News_BondiCce_R0267.h5 19.5 MB
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r2News_BondiCce_R0433.h5 20.1 MB
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r2News_BondiCce_R0600.h5 21.7 MB
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r2Psi3_BondiCce_R0100.h5 25.9 MB
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r2Psi3_BondiCce_R0433.h5 24.7 MB
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r3Psi2OverM_BondiCce_R0100.h5 13.1 MB
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r4Psi1OverM2_BondiCce_R0100.h5 20.1 MB
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r5Psi0OverM3_BondiCce_R0100.h5 27.2 MB
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r5Psi0OverM3_BondiCce_R0433.h5 29.4 MB
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rMPsi4_BondiCce_R0100.h5 35.5 MB
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rMPsi4_BondiCce_R0100.json 840.0 B
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rMPsi4_BondiCce_R0267.h5 29.8 MB
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rMPsi4_BondiCce_R0267.json 840.0 B
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rMPsi4_BondiCce_R0433.h5 31.5 MB
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rMPsi4_BondiCce_R0433.json 840.0 B
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rMPsi4_BondiCce_R0600.h5 31.4 MB
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rMPsi4_BondiCce_R0600.json 840.0 B
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rhOverM_BondiCce_R0100.h5 23.9 MB
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rhOverM_BondiCce_R0100.json 837.0 B
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rhOverM_BondiCce_R0267.h5 16.4 MB
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rhOverM_BondiCce_R0267.json 837.0 B
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rhOverM_BondiCce_R0433.h5 16.3 MB
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rhOverM_BondiCce_R0433.json 837.0 B
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rhOverM_BondiCce_R0600.h5 19.2 MB
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rhOverM_BondiCce_R0600.json 837.0 B
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metadata.txt 4.8 kB
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Horizons.h5 1.5 MB
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r2News_BondiCce_R0100.h5 22.5 MB
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r2News_BondiCce_R0100.json 840.0 B
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r2News_BondiCce_R0267.h5 18.8 MB
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r2News_BondiCce_R0267.json 840.0 B
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r2News_BondiCce_R0433.h5 19.8 MB
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r2News_BondiCce_R0433.json 840.0 B
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r2News_BondiCce_R0600.h5 22.2 MB
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r2News_BondiCce_R0600.json 840.0 B
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r2Psi3_BondiCce_R0100.h5 25.5 MB
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r2Psi3_BondiCce_R0100.json 840.0 B
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r2Psi3_BondiCce_R0267.h5 21.6 MB
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r2Psi3_BondiCce_R0267.json 840.0 B
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> &