It is well known that Einstein gravity can be formulated as a gauge theory of Lorentz group where spin connections play a role of gauge fields and Riemann curvature tensors correspond to their field strengths. One can then pose an interesting question: What is the Einstein equation from the gauge theory point of view? Or equivalently, what is the gauge theory object corresponding to Einstein manifolds? We show that the Einstein equations in four dimensions are precisely self-duality equations in Yang–Mills gauge theory and so Einstein manifolds correspond to Yang–Mills instantons in SO(4) = SU(2)_L × SU(2)_R gauge theory. Specifically, we prove that any Einstein manifold with or without a cosmological constant always arises as the sum of SU(2)_L instantons and SU(2)_R anti-instantons. This result explains why an Einstein manifold must be stable because two kinds of instantons belong to different gauge groups, instantons in SU(2)_L and anti-instantons in SU(2)_R, and so they cannot decay into a vacuum. We further illuminate the stability of Einstein manifolds by showing that they carry nontrivial topological invariants.

We report a search for gravitational waves from the inspiral, merger and ringdown of binary black holes (BBH) with total mass between 25 and 100 solar masses, in data taken at the LIGO and Virgo observatories between July 7, 2009 and October 20, 2010. The maximum sensitive distance of the detectors over this period for a $(20,20)M_{\odot }$ coalescence was 300 Mpc. No gravitational wave signals were found. We thus report upper limits on the astrophysical coalescence rates of BBH as a function of the component masses for nonspinning components, and also evaluate the dependence of the search sensitivity on component spins aligned with the orbital angular momentum. We find an upper limit at 90% confidence on the coalescence rate of BBH with nonspinning components of mass between 19 and $28M_{\odot }$ of $3.3\times {10}^{-7}$ mergers ${\mathrm{Mpc}}^{-3}{\mathrm{yr}}^{-1}$ .

The sensitivity of searches for astrophysical transients in data from the Laser Interferometer Gravitational-wave Observatory (LIGO) is generally limited by the presence of transient, non-Gaussian noise artifacts, which occur at a high enough rate such that accidental coincidence across multiple detectors is non-negligible. These “glitches” can easily be mistaken for transient gravitational-wave signals, and their robust identification and removal will help any search for astrophysical gravitational waves. We apply machine-learning algorithms (MLAs) to the problem, using data from auxiliary channels within the LIGO detectors that monitor degrees of freedom unaffected by astrophysical signals. Noise sources may produce artifacts in these auxiliary channels as well as the gravitational-wave channel. The number of auxiliary-channel parameters describing these disturbances may also be extremely large; high dimensionality is an area where MLAs are particularly well suited. We demonstrate the feasibility and applicability of three different MLAs: artificial neural networks, support vector machines, and random forests. These classifiers identify and re a substantial fraction of the glitches present in two different data sets: four weeks of LIGO’s fourth science run and one week of LIGO’s sixth science run. We observe that all three algorithms agree on which events are glitches to within 10% for the sixth-science-run data, and support this by showing that the different optimization criteria used by each classifier generate the same decision surface, based on a likelihood-ratio statistic. Furthermore, we find that all classifiers obtain similar performance to the benchmark algorithm, the ordered veto list, which is optimized to detect pairwise correlations between transients in LIGO auxiliary channels and glitches in the gravitational-wave data. This suggests that most of the useful information currently extracted from the auxiliary channels is already described by this model. Future performance gains are thus likely to involve additional sources of information, rather than improvements in the classification algorithms themselves. We discuss several plausible sources of such new information as well as the ways of propagating it through the classifiers into gravitational-wave searches.

Compact binary systems with neutron stars or black holes are one of the most promising sources for ground-based gravitational-wave detectors. Gravitational radiation encodes rich information about source physics; thus parameter estimation and model selection are crucial analysis steps for any detection candidate events. Detailed models of the anticipated waveforms enable inference on several parameters, such as component masses, spins, sky location and distance, that are essential for new astrophysical studies of these sources. However, accurate measurements of these parameters and discrimination of models describing the underlying physics are complicated by artifacts in the data, uncertainties in the waveform models and in the calibration of the detectors. Here we report such measurements on a selection of simulated signals added either in hardware or software to the data collected by the two LIGO instruments and the Virgo detector during their most recent joint science run, including a “blind injection” where the signal was not initially revealed to the collaboration. We exemplify the ability to extract information about the source physics on signals that cover the neutron-star and black-hole binary parameter space over the component mass range $1M_{\odot }–25M_{\odot }$ and the full range of spin parameters. The cases reported in this study provide a snapshot of the status of parameter estimation in preparation for the operation of advanced detectors.

We present the results of a directed search for continuous gravitational waves from unknown, isolated neutron stars in the Galactic center region, performed on two years of data from LIGO’s fifth science run from two LIGO detectors. The search uses a semicoherent approach, analyzing coherently 630 segments, each spanning 11.5 hours, and then incoherently combining the results of the single segments. It covers gravitational wave frequencies in a range from 78 to 496 Hz and a frequency-dependent range of first-order spindown values down to $-7.86\times {10}^{-8}\mathrm{Hz}/s$ at the highest frequency. No gravitational waves were detected. The 90% confidence upper limits on the gravitational wave amplitude of sources at the Galactic center are $\sim 3.35\times {10}^{-25}$ for frequencies near 150 Hz. These upper limits are the most constraining to date for a large-parameter-space search for continuous gravitational wave signals.

Long gamma-ray bursts (GRBs) have been linked to extreme core-collapse supernovae from massive stars. Gravitational waves (GW) offer a probe of the physics behind long GRBs. We investigate models of long-lived ($\sim 10–1000s$ ) GW emission associated with the accretion disk of a collapsed star or with its protoneutron star remnant. Using data from LIGO’s fifth science run, and GRB triggers from the Swift experiment, we perform a search for unmodeled long-lived GW transients. Finding no evidence of GW emission, we place 90% confidence-level upper limits on the GW fluence at Earth from long GRBs for three waveforms inspired by a model of GWs from accretion disk instabilities. These limits range from $F<3.5\mathrm{ergs}{\mathrm{cm}}^{-2}$ to $F<1200\mathrm{ergs}{\mathrm{cm}}^{-2}$ , depending on the GRB and on the model, allowing us to probe optimistic scenarios of GW production out to distances as far as $\approx 33\mathrm{Mpc}$ . Advanced detectors are expected to achieve strain sensitivities $10\times$ better than initial LIGO, potentially allowing us to probe the engines of the nearest long GRBs.

Nearly a century after Einstein first predicted the existence of gravitational waves, a global network of Earth-based gravitational wave observatories^1,2,3,4 is seeking to directly detect this faint radiation using precision laser interferometry. Photon shot noise, due to the quantum nature of light, imposes a fundamental limit on the attometre-level sensitivity of the kilometre-scale Michelson interferometers deployed for this task. Here, we inject squeezed states to improve the performance of one of the detectors of the Laser Interferometer Gravitational-Wave Observatory (LIGO) beyond the quantum noise limit, most notably in the frequency region down to 150 Hz, critically important for several astrophysical sources, with no deterioration of performance observed at any frequency. With the injection of squeezed states, this LIGO detector demonstrated the best broadband sensitivity to gravitational waves ever achieved, with important implications for observing the gravitational-wave Universe with unprecedented sensitivity.

Magnetic resonance electrical impedance tomography (MREIT) is a new medical imaging modality visualizing static conductivity images of electrically conducting subjects. Recently, MREIT has rapidly progressed in its theory, algorithm, and experiment technique and now reached to the stage of in vivo animal experiments. In this paper, we present a software, named CoReHA 2.0 standing for the second version of conductivity reconstructor using harmonic algorithms, to facilitate in vivo MREIT reconstruction of conductivity image. This software offers various computational tools including preprocessing of MREIT data, identification of 2D geometry of the imaging domain and electrode positions, and reconstruction of cross-sectional scaled conductivity images from MREIT data. In particular, in the new version, we added several tools including ramp-preserving denoising, harmonic inpainting, and local harmonic algorithm to deal with data from in vivo experiments. The presented software will be useful to researchers in the field of MREIT for simulation, validation, and further technical development.

This paper proposes a robust real-time myocardial border tracking algorithm for echocardiography. Commonly, after an initial contour of LV border is traced at one or two frames from the entire cardiac cycle, LV contour tracking is performed over the remaining frames. Among a variety of tracking techniques, optical flow method is the most widely used for motion estimation of moving objects. However, when echocardiography data is heavily corrupted in some local regions, the errors bring the tracking point out of the endocardial border, resulting in distorted LV contours. This shape distortion often occurs in practice since the data acquisition is affected by ultrasound artifacts, outs, or shadowing phenomena of cardiac walls. The proposed method is designed to deal with this shape distortion problem by integrating local optical flow motion and global deformation into a variational framework. The proposed descent method controls the individual tracking points to follow the local motions of a specific speckle pattern, while their overall motions are confined to the global motion constraint being approximately an affine transform of the initial tracking points. Many real experiments show that the proposed method achieves better overall performance than conventional methods.