Details
| Original language | English |
|---|---|
| Article number | 104063 |
| Journal | Physical Review D |
| Volume | 106 |
| Issue number | 10 |
| Publication status | Published - 30 Nov 2022 |
Abstract
Searches for continuous gravitational waves target nearly monochromatic gravitational wave emission from, e.g., nonaxisymmetric fast-spinning neutron stars. Broad surveys often require us to explicitly search for a very large number of different waveforms, easily exceeding ∼1017 templates. In such cases, for practical reasons, only the top, say ∼1010, results are saved and followed up through a hierarchy of stages. Most of these candidates are not completely independent of neighboring ones, but arise due to some common cause: a fluctuation, a signal, or a disturbance. By judiciously clustering together candidates stemming from the same root cause, the subsequent follow-ups become more effective. A number of clustering algorithms have been employed in past searches based on iteratively finding symmetric and compact overdensities around candidates with high detection statistic values. The new clustering method presented in this paper is a significant improvement over previous methods: it is agnostic about the shape of the overdensities, is very efficient and it is effective: at a very high detection efficiency, it has a noise rejection of 99.99%, is capable of clustering two orders of magnitude more candidates than attainable before and, at fixed sensitivity it enables more than a factor of 30 faster follow-ups. We also demonstrate how to optimally choose the clustering parameters.
ASJC Scopus subject areas
- Physics and Astronomy(all)
- Nuclear and High Energy Physics
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In: Physical Review D, Vol. 106, No. 10, 104063, 30.11.2022.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Density-clustering of continuous gravitational wave candidates from large surveys
AU - Steltner, B.
AU - Menne, T.
AU - Papa, M. A.
AU - Eggenstein, H. B.
PY - 2022/11/30
Y1 - 2022/11/30
N2 - Searches for continuous gravitational waves target nearly monochromatic gravitational wave emission from, e.g., nonaxisymmetric fast-spinning neutron stars. Broad surveys often require us to explicitly search for a very large number of different waveforms, easily exceeding ∼1017 templates. In such cases, for practical reasons, only the top, say ∼1010, results are saved and followed up through a hierarchy of stages. Most of these candidates are not completely independent of neighboring ones, but arise due to some common cause: a fluctuation, a signal, or a disturbance. By judiciously clustering together candidates stemming from the same root cause, the subsequent follow-ups become more effective. A number of clustering algorithms have been employed in past searches based on iteratively finding symmetric and compact overdensities around candidates with high detection statistic values. The new clustering method presented in this paper is a significant improvement over previous methods: it is agnostic about the shape of the overdensities, is very efficient and it is effective: at a very high detection efficiency, it has a noise rejection of 99.99%, is capable of clustering two orders of magnitude more candidates than attainable before and, at fixed sensitivity it enables more than a factor of 30 faster follow-ups. We also demonstrate how to optimally choose the clustering parameters.
AB - Searches for continuous gravitational waves target nearly monochromatic gravitational wave emission from, e.g., nonaxisymmetric fast-spinning neutron stars. Broad surveys often require us to explicitly search for a very large number of different waveforms, easily exceeding ∼1017 templates. In such cases, for practical reasons, only the top, say ∼1010, results are saved and followed up through a hierarchy of stages. Most of these candidates are not completely independent of neighboring ones, but arise due to some common cause: a fluctuation, a signal, or a disturbance. By judiciously clustering together candidates stemming from the same root cause, the subsequent follow-ups become more effective. A number of clustering algorithms have been employed in past searches based on iteratively finding symmetric and compact overdensities around candidates with high detection statistic values. The new clustering method presented in this paper is a significant improvement over previous methods: it is agnostic about the shape of the overdensities, is very efficient and it is effective: at a very high detection efficiency, it has a noise rejection of 99.99%, is capable of clustering two orders of magnitude more candidates than attainable before and, at fixed sensitivity it enables more than a factor of 30 faster follow-ups. We also demonstrate how to optimally choose the clustering parameters.
UR - http://www.scopus.com/inward/record.url?scp=85143339384&partnerID=8YFLogxK
U2 - 10.1103/PhysRevD.106.104063
DO - 10.1103/PhysRevD.106.104063
M3 - Article
AN - SCOPUS:85143339384
VL - 106
JO - Physical Review D
JF - Physical Review D
SN - 2470-0010
IS - 10
M1 - 104063
ER -