Open data from the third observing run of LIGO, Virgo, KAGRA and GEO

The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in April of 2019 and lasting six months, O3b starting in November of 2019 and lasting five months, and O3GK starting in April of 2020 and lasting 2 weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main dataset, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages.Comment: 27 pages, 3 figure

Search for Eccentric Black Hole Coalescences during the Third Observing Run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass $M>70$ $M_\odot$) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities $0 < e \leq 0.3$ at $0.33$ Gpc$^{-3}$ yr$^{-1}$ at 90\% confidence level.Comment: 24 pages, 5 figure

Robust image analysis with sparse representation on quantized visual features

10.1109/TIP.2012.2219543IEEE Transactions on Image Processing223860-871IIPR

Open data from the third observing run of LIGO, Virgo, KAGRA, and GEO

The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in 2019 April and lasting six months, O3b starting in 2019 November and lasting five months, and O3GK starting in 2020 April and lasting two weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main data set, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages

WHEN FOURTH MOMENTS ARE ENOUGH

This note concerns a somewhat innocent question motivated by an observation concerning the use of Chebyshev bounds on sample estimates of p in the binomial distribution with parameters n, p, namely, what moment order produces the best Chebyshev estimate of p ? If S-n(p) has a binomial distribution with parameters n, p, then it is readily observed that argmax(0 <= p <= 1) ESn2 (p) = argmax(0 <= p <= 1) np(1 - p) = 1/2, and ESn2(1/2) = n/4. Bhattacharya [2] observed that, while the second moment Chebyshev sample size for a 95 percent confidence estimate within +/- 5 percentage points is n = 2000, the fourth moment yields the substantially reduced polling requirement of n = 775. Why stop at the fourth moment ? Is the argmax achieved at p = 1/2 for higher order moments, and, if so, does it help in computing ESn2m (1/2)? As captured by the title of this note, answers to these questions lead to a simple rule of thumb for the best choice of moments in terms of an effective sample size for Chebyshev concentration inequalities

Reducing Head CT Use for Children With Head Injuries in a Community Emergency Department.

BACKGROUND AND OBJECTIVE: Clinical decision rules have reduced use of computed tomography (CT) to evaluate minor pediatric head injury in pediatric emergency departments (EDs). CT use remains high in community EDs, where the majority of children seek medical care. We sought to reduce the rate of CT scans used to evaluate pediatric head injury from 29% to 20% in a community ED. METHODS: We evaluated a quality improvement (QI) project in a community ED aimed at decreasing the use of head CT scans in children by implementing a validated head trauma prediction rule for traumatic brain injury. A multidisciplinary team identified key drivers of CT use and implemented decision aids to improve the use of prediction rules. The team identified and mitigated barriers. An affiliated children\u27s hospital offered Maintenance of Certification credit and QI coaching to participants. We used statistical process control charts to evaluate the effect of the intervention on monthly CT scan rates and performed a Wald test of equivalence to compare preintervention and postintervention CT scan proportions. RESULTS: The baseline period (February 2013-July 2014) included 695 patients with a CT scan rate of 29.2% (95% confidence interval, 25.8%-32.6%). The postintervention period (August 2014-October 2015) included 651 patients with a CT scan rate of 17.4% (95% confidence interval, 14.5%-20.2%, CONCLUSIONS: We demonstrate that a Maintenance of Certification QI project sponsored by a children\u27s hospital can facilitate evidence-based pediatric care and decrease the rate of unnecessary CT use in a community setting

Partitions associated with the Ramanujan/Watson mock theta functions ω(q), ν(q) and φ(q)

The generating function of partitions with repeated (resp. distinct) parts such that each odd part is less than twice the smallest part is shown to be the third order mock theta function ω(q) (resp. ν(−q)). Similar results for partitions with the corresponding restriction on each even part are also obtained, one of which involves the third order mock theta function ϕ(q). Congruences for the smallest parts partition function(s) associated to such partitions are obtained. Two analogues of the partition-theoretic interpretation of Euler’s pentagonal number theorem are also obtained.by George E. Andrews, Atul Dixit and Ae Ja Ye