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We present results in Gaussian data from a template-based multi-detector coherent search for perturbed-black-hole ringdown signals. Like the past “coincidence” ringdown searches in LIGO data, our method incorporates knowledge of the ringdown waveform in constructing the search templates. Additionally, it checks for consistency of signal amplitude and phase with the signals’ times-of-arrival at the detectors. The latter feature is common to both of our method and the Coherent WaveBurst algorithm, and can help bridge the gap in performance between the coincidence search and the coherent WaveBurst search for ringdown signals. [LIGO Document Control Center Number: LIGO-G1100036-x0.] Gravitational waves from perturbed black holes Several ground-based interferometric observatories, such as LIGO and Virgo, have collected data so that astronomers can search for gravitational-wave (GW) signals in them. One such signal is that arising from a perturbed black hole, which can result from the coalescence of a compact binary. This signal is initially in the form of a superposition of quasi-normal modes. However, at late times the waveform, which is known as a ringdown, is expected to be dominated by a single mode. The optimal method for searching such a signal buried in detector noise is to match-filter the detectors’ output with theoretically modeled waveforms. The coherent network statistic is optimal for detecting these signals in stationary, Gaussian noise [1, 2]. But in real noise, which is non-Gaussian and nonstationary, additional discriminators of noise artifacts are required for obtaining a (near-)optimal statistic. Here, we describe a hierarchical method for coherently searching ringdown signals in a network of detectors that is aided by such discriminators. The ringdown waveform The central frequency and the decay time of the quasinormal mode oscillation can be predicted with good accuracy by black-hole perturbation theory. The plus and cross polarizations of a ringdown waveform can be expressed in terms of the central frequency f0 and the quality factor Q as h+(t) = A r (1 + cos2 ι) e − πf0t Q cos(2πf0t) , h×(t) = A r 2 cos ι e − πf0t Q sin(2πf0t) , where A is the amplitude, r is the distance from the source and ι is the inclination angle of the source. We consider here only the dominant mode i.e, the most slowly damped mode, l = m = 2. The strain produced in the detector is then h(t) = h+(t)F+(θ, φ, ψ) + h×(t)F×(θ, φ, ψ) , where F+,× are the detector antenna-pattern functions, with ψ being the wave-polarization angle and (θ, φ) being the sky-position of the source. A search based on matched-filtering In GW data analysis, the data from multiple detectors is match-filtered with templates derived from theoretical waveforms to test the presence or absence of signals in the data. Filtering the data s(t) with a template h0(t;μi) characterized by the source parameters μi yields the signal-tonoise ratio (SNR) statistic given by