2,498 research outputs found
Penning traps with unitary architecture for storage of highly charged ions
Penning traps are made extremely compact by embedding rare-earth permanent
magnets in the electrode structure. Axially-oriented NdFeB magnets are used in
unitary architectures that couple the electric and magnetic components into an
integrated structure. We have constructed a two- magnet Penning trap with
radial access to enable the use of laser or atomic beams, as well as the
collection of light. An experimental apparatus equipped with ion optics is
installed at the NIST electron beam ion trap (EBIT) facility, constrained to
fit within 1 meter at the end of a horizontal beamline for transporting highly
charged ions. Highly charged ions of neon and argon, extracted with initial
energies up to 4000 eV per unit charge, are captured and stored to study the
confinement properties of a one-magnet trap and a two-magnet trap. Design
considerations and some test results are discussed
Distinguishing high-mass binary neutron stars from binary black holes with second- and third-generation gravitational wave observatories
(Abridged) While the gravitational-wave (GW) signal GW170817 was accompanied by a variety of electromagnetic (EM) counterparts, sufficiently high-mass binary neutron star (BNS) mergers are expected to be unable to power bright EM counterparts. The putative high-mass binary BNS merger GW190425, for which no confirmed EM counterpart has been identified, may be an example of such a system. It is thus important to understand how well we will be able to distinguish high-mass BNSs and low-mass binary black holes (BBHs) solely from their GW signals. To do this, we consider the imprint of the tidal deformability of the neutron stars on the GW signal for systems undergoing prompt black hole formation after merger. We model the BNS signals using hybrid numerical relativity -- tidal effective-one-body waveforms. Specifically, we consider a set of five nonspinning equal-mass BNS signals with masses of 2.7, 3.0, 3.2 Msun and with three different equations of state, as well as the analogous BBH signals. We perform parameter estimation on these signals in three networks: Advanced LIGO-Advanced Virgo and Advanced LIGO-Advanced Virgo-KAGRA with sensitivities similar to O3 and O4, respectively, and a 3G network of two Cosmic Explorers (CEs) and one Einstein Telescope, with a CE sensitivity similar to Stage 2. Our analysis suggests that we cannot distinguish the signals from high-mass BNSs and BBHs at a 90% credible level with the O3-like network even at 40 Mpc. However, we can distinguish all but the most compact BNSs that we consider in our study from BBHs at 40 Mpc at a >= 95% credible level using the O4-like network, and can even distinguish them at a > 99.2% (>= 97%) credible level at 369 (835) Mpc using the 3G network. Additionally, we present a simple method to compute the leading effect of the Earth's rotation on the response of a gravitational wave detector in the frequency domain
Investigating the relation between gravitational wave tests of general relativity
Gravitational wave observations of compact binary coalescences provide precision probes of strong-field gravity. There is thus now a standard set of null tests of general relativity (GR) applied to LIGO-Virgo detections and many more such tests proposed. However, the relation between all these tests is not yet well understood. We start to investigate this by applying a set of standard tests to simulated observations of binary black holes in GR and with phenomenological deviations from GR. The phenomenological deviations include self-consistent modifications to the energy flux in an effective-one-body (EOB) model, the deviations used in the second post-Newtonian (2PN) TIGER and FTA parameterized tests, and the dispersive propagation due to a massive graviton. We consider four types of tests: residuals, inspiral-merger-ringdown consistency, parameterized (TIGER and FTA), and modified dispersion relation. We also check the consistency of the unmodeled reconstruction of the waveforms with the waveform recovered using GR templates. These tests are applied to simulated observations similar to GW150914 with both large and small deviations from GR and similar to GW170608 just with small deviations from GR. We find that while very large deviations from GR are picked up with high significance by almost all tests, more moderate deviations are picked up by only a few tests, and some deviations are not recognized as GR violations by any test at the moderate signal-to-noise ratios we consider. Moreover, the tests that identify various deviations with high significance are not necessarily the expected ones. We also find that the 2PN (1PN) TIGER and FTA tests recover much smaller deviations than the true values in the modified EOB (massive graviton) case. Additionally, we find that of the GR deviations we consider, the residuals test is only able to detect extreme deviations from GR. (Abridged
Distinguishing binary black hole precessional morphologies with gravitational wave observations
The precessional motion of binary black holes can be classified into one of
three morphologies, based on the evolution of the angle between the components
of the spins in the orbital plane: Circulating, librating around 0, and
librating around . These different morphologies can be related to the
binary's formation channel and are imprinted in the binary's gravitational wave
signal. In this paper, we develop a Bayesian model selection method to
determine the preferred spin morphology of a detected binary black hole. The
method involves a fast calculation of the morphology which allows us to
restrict to a specific morphology in the Bayesian stochastic sampling. We
investigate the prospects for distinguishing between the different morphologies
using gravitational waves in the Advanced LIGO/Advanced Virgo network with
their plus-era sensitivities. For this, we consider fiducial high- and low-mass
binaries having different spin magnitudes and signal-to-noise ratios (SNRs). We
find that in the cases with high spin and high SNR, the true morphology is
strongly favored with Bayes factors compared to both
alternative morphologies when the binary's parameters are not close to the
boundary between morphologies. However, when the binary parameters are close to
the boundary between morphologies, only one alternative morphology is strongly
disfavored. In the low-spin, high-SNR cases, the true morphology is still
favored with a Bayes factor compared to one alternative
morphology. We also consider the gravitational wave signal from GW200129_065458
that has some evidence for precession (modulo data quality issues) and find
that there is no preference for a specific morphology. Our method for
restricting the prior to a given morphology is publicly available through an
easy-to-use Python package called bbh_spin_morphology_prior. (Abridged)Comment: 14 pages, 5 figures, version accepted by PR
Distinguishing binary black hole precessional morphologies with gravitational wave observations
The precessional motion of binary black holes can be classified into one of three morphologies, based on the evolution of the angle between the components of the spins in the orbital plane: Circulating, librating around 0, and librating around π. These different morphologies can be related to the binary’s formation channel and are imprinted in the binary’s gravitational wave signal. In this paper, we develop a Bayesian model selection method to determine the preferred spin morphology of a detected binary black hole. The method involves a fast calculation of the morphology which allows us to restrict to a specific morphology in the Bayesian stochastic sampling. We investigate the prospects for distinguishing between the different morphologies using gravitational waves in the Advanced LIGO/Advanced Virgo network with their plus-era sensitivities. For this, we consider fiducial high- and low-mass binaries having different spin magnitudes and signal-to-noise ratios (SNRs). We find that in the cases with high spin and high SNR, the true morphology is strongly favored with log10 Bayes factors ≳ 4 compared to both alternative morphologies when the binary’s parameters are not close to the boundary between morphologies. However, when the binary parameters are close to the boundary between morphologies, only one alternative morphology is strongly disfavored. In the low-spin, high-SNR cases, the true morphology is still favored with a log10 Bayes factor ∼ 2 compared to one alternative morphology, while in the low-SNR cases the log10 Bayes factors are at most ∼1 for many binaries. We also consider the gravitational wave signal from GW200129_065458 that has some evidence for precession (modulo data quality issues) and find that there is no preference for a specific morphology. Our method for restricting the prior to a given morphology is publicly available through an easy-to-use python package called bbh_spin_morphology_prior
- …