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Active noise cancellation in a suspended interferometer
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10.1063/1.3675891
/content/aip/journal/rsi/83/2/10.1063/1.3675891
http://aip.metastore.ingenta.com/content/aip/journal/rsi/83/2/10.1063/1.3675891
View: Figures

Figures

Image of FIG. 1.
FIG. 1.

Locations of seismometers and accelerometers in relation to the cavity mirrors. Round trip length of the triangular cavity is 27 m.

Image of FIG. 2.
FIG. 2.

Result of offline seismic Wiener filtering on suspended triangular cavity. (a) Spectrogram showing the efficacy of a Wiener filter applied offline over a several hours period. Noticeably different traces between ∼28 h and ∼34 h are the result of non-stationary anthropogenic noise, not a decay of the filter's efficacy. (b) Amplitude spectral density of the control signal. Dotted trace is without subtraction, solid traces are 0, 10, 20 and 30 hours after filter was trained.

Image of FIG. 3.
FIG. 3.

Shown are the spectra of the individual seismometers (dashed and dash-dot), the manufacturer's spec for the seismometers' internal noise (solid-circle), and the differential ground motion along the 13.5 m length of the cavity (solid). We also show the differential noise of the seismometers with the seismometers collocated in a stiff seismic vault (dash-circle); in principle, this is a measurement of the actual seismometer noise floor. It is unknown what uncorrelated noise is present in our sensors which makes the teal trace so much larger than the specification.

Image of FIG. 4.
FIG. 4.

Schematic layout of seismometers relative to interferometer mirrors.

Image of FIG. 5.
FIG. 5.

Result of offline simulated seismic Wiener filtering on the 4 km LIGO Hanford interferometer. (a) Traces are amplitude spectra normalized to the unfiltered control signal (dotted trace in b), which is at a time during the filter's training. Filter was trained on 6 h of data, then applied in 10 min segments. Vertical stripes indicate times when the interferometer was not operational. Seismic subtraction is fairly constant on a one month time scale, although it is not particularly effective for times when seismic noise is significantly different from the training time. (b) Selected individual spectra from (a) above. Dotted trace is before subtraction, solid traces are 0, 10, 20 and 30 days after the filter was trained.

Image of FIG. 6.
FIG. 6.

Result of offline simulated seismic Wiener filtering on the 4 km LIGO Hanford interferometer, using an acausal filter on the same 30 days data set. (a) Traces are amplitude spectra normalized to the unfiltered control signal (dotted trace in b). A filter is trained on, and then applied to, 10 min segments of data. Seismic noise is more effectively suppressed using this constantly updated filter, implying that the transfer function is changing on a relatively short time scale, and that it is advantageous to update the filter more often than once per month. (b) Selected individual spectra from (a) above. Dotted trace is before subtraction, solid traces are 0, 10, 20 and 30 days after beginning.

Image of FIG. 7.
FIG. 7.

Block diagram of the FxLMS algorithm used.

Image of FIG. 8.
FIG. 8.

Online adaptive filter performance: the spectral density of the cavity length fluctuations are shown with the feed-forward on (lower trace) and off (upper trace).

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/content/aip/journal/rsi/83/2/10.1063/1.3675891
2012-02-02
2014-04-17
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Active noise cancellation in a suspended interferometer
http://aip.metastore.ingenta.com/content/aip/journal/rsi/83/2/10.1063/1.3675891
10.1063/1.3675891
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