A Fast Data Processing Technique for Continuous Gravitational Wave Searches

This article discusses the potential advantages of a data processing technique for continuous gravitational wave signals searches in the data measured by ground-based gravitational wave interferometers. Its main advantage over other techniques is that it does not need to search over the signal’s direction of propagation. Although it is a “coherent method” (i.e., it coherently processes year-long data), it is applied to a data set obtained by multiplying the original time-series with a (half-year) time-shifted copy of it. As a result, the phase modulation due to the interferometer motion around the Sun is automatically canceled in the signal of the synthesized time-series. Although the resulting signal-to-noise ratio is not as high as that of a coherent search, it equals that of current hierarchical methods. In addition, since the signal search is performed over a parameters space of smaller dimensionality, the associated false-alarm probability should be smaller than those characterizing hierarchical methods and result in an improved likelihood of detection.

A Fast Data Processing Technique for Continuous Gravitational Wave Searches

This article discusses the potential advantages of a data processing technique for continuous gravitational wave signals searches in the data measured by ground-based gravitational wave interferometers. Its main advantage over other techniques is that it does not need to search over the signal’s direction of propagation. Although it is a “ coherent method” (i.e. it coherently processes year-long data), it is applied to a data set obtained by multiplying the original time-series with a (half-year) time-shifted copy of it. As a result, the phase modulation due to the interferometer motion around the Sun is automatically canceled in the signal of the synthesized time-series. Although the resulting signal-to-noise ratio is not as high as that of a coherent search, it equals that of current hierarchical methods. In addition, since the signal search is performed over a parameters space of smaller dimensionality, the associated false-alarm probability should be smaller than those characterizing hierarchical methods and result in an improved likelihood of detection.

Transit-period search from single-event space-based data: the role of wide-field surveys

We investigate the optimization of dataset weighting in searching for the orbital period of transiting planets when high-precision space-based data with a single transit event are combined with (relatively) low-precision ground-based (wide-field) data. The optimization stems from the lack of multiple events in the high-precision data and the likely presence of such events in the low-precision data. With noise minimization, we combined two types of frequency spectra: (i) spectra that use two fixed transit parameters (moment of the center of the transit and duration of the event) derived from the space data alone; (ii) spectra that result from the traditional weighted box signal search with optimized transit parameters for each trial period. We used many mock signals to test the detection power of the method. Marginal or no detections in the ground-based data may lead to secure detections in the combined data with the above weighting. Depending on the coverage and quality of the ground-based data, transit depths of ~0.05% and periods up to ~100 days are accessible by the suggested optimum combination of the data.

RADIO NAVIGATION SYSTEM BROADBAND SIGNAL SEARCH

The study object is the search procedure for a ground-based radionavigation system signal using noise-like discrete signals with a long baseline. A comparative analysis of the signal search quality indicators is carried out, which is the most time-consuming procedure with different navigation signal modulation formats in the worst-case conditions and with a limited frequency resource allocated to the system. Bandwidth efficiency of noise-like signals (NLS) with phase shift keying (PSK) and minimal frequency shift keying (MFSK) are analyzed. Relations are obtained for the average maximum search time of the navigation signal with a fixed probability of correct search completion. The qualitative indicators of the search procedure for PSK and MFSK are compared for the same band pass effectiveness and elementary symbol duration. The analysis results show that under the conditions of equal restrictions on the occupied frequency range and the same requirements for the search procedure reliability, NLS MFSK search is effective and implementable at much lower time costs than NLS with traditional binary PSK.

Deep-sea search and recovery: with and without operating an underwater vehicle

Deep-sea search and recovery mainly refers to the search, recovery, and salvage of objects with high value that are lost on the deep-sea bottom. Deep-sea search and recovery objects include aircraft black boxes, underwater vehicles, and other types of objects. The recovery and salvage of objects involves accurately obtaining their underwater positions. Depending on whether or not the salvage object carries an acoustic beacon, two methods are available: onboard acoustic signal search and near-bottom sweep search and search. Once the underwater position of a salvage object is known, it can be recovered and salvaged with a remotely operated underwater vehicle (ROV) and/or human-occupied vehicle (HOV). However, there are many difficulties with the practical application of existing deep-sea recovery systems that are based on the deep-sea operation of ROVs and HOVs. Based on the design idea and working mode of TV-grab in oceanography, this paper proposes a new type of deep-sea recovery system that does not rely on operating underwater vehicles and presents its recovery process. The new deep-sea recovery system combines underwater optical imaging, mechanical docking/grasping, acoustic imaging and positioning, and propeller operating to provide low-cost and rapid deep-sea recovery. Compared to the deep-sea recovery system with a ROV and/or HOV, the new deep-sea recovery system without an operating underwater vehicle described in this paper is proposed to be used, but not tested yet.

New likelihoods for shape analysis

We introduce a new kind of likelihood function based on the sequence of moments of the data distribution. Both binned and unbinned data samples are discussed, and the multivariate case is also derived. Building on this approach we lay out the formalism of shape analysis for signal searches. In addition to moment-based likelihoods, standard likelihoods and approximate statistical tests are provided. Enough material is included to make the paper self-contained from the perspective of shape analysis. We argue that the moment-based likelihoods can advantageously replace unbinned standard likelihoods for the search of nonlocal signals, by avoiding the step of fitting Monte Carlo generated distributions. This benefit increases with the number of variables simultaneously analyzed. The moment-based signal search is exemplified and tested in various 1D toy models mimicking typical high-energy signal-background configurations. Moment-based techniques should be particularly appropriate for the searches for effective operators at the LHC.