Caltech: Blackburn, Lazzarini,
Shawhan, Zweizig
Dublin: Ottewill
Hanford: Landry, Schofield
Michigan: Gustafson,
Riles
MIT: Sylvestre
Introduction (KR):
Gaby, Michael Hsu (an undergraduate REU student) and I have had great success in applying wavelet-based methods for automatically characterizing and identifying transients of different kinds in the 40M and the April 2Km engineering data run.
In the 40M these techniques automatically find several of the transients that have been found through "listening" to the IFO_DMRO channel, and have correlated these with activity in some of the other channels (e.g., the seismometers, the PSL). We have found a definite case of a strong non-linear upconversion from a low frequency (on order 2 Hz) oscillation in the seismometer channel to a pair of closely-spaced broadband bursts at about 100 Hz in DMRO. This pattern is repeated several times throughout the data. I can't post a figure from here but will try to do so on my return. We (Gaby and I) would like to talk about this method of analysis and some of our experiences with it as applied to the 2Km data at the next LSC meeting.
We are in the midst of applying these methods to the engineering data.
We have found trong evidence for what looks to be discrete jumps in light
intensity, lasting exactly 1/16 s (1024 samples) randomly interspersed
in the data. These discrete jumps show up in the H2:LSC-AS-Q_TEMP channel,
and have cognates in the PSL-FSS_FAST_F channel. (KR note: this may
be the same problem reported by John at the May teleconference.)
A second set of artifacts involve a discrete jump in H2:LSC-AS-Q_TEMP,
followed by a brief, high
frequency ringing in the channel. These appear to be strongly correlated
with clearly identifiable artifacts in the H2:IOO-MC_I channel as well
as the PSL-FSS_FAST_F channel. They look very much like some features that
Rick Savage just showed at the MG9 Meeting which are associated with laser
frequency noise.
There are two other category of events, represented by one or two examples each. These are, in the first case, high frequency bursts that last for on order 1/8 s, and a low frequency burst that lasts for about 1 or 2 cycles at about 2 Hz.
The principal value that I see for these techniques at the moment are
1) an automatic way of identifying artifacts that are not at all visible
to
the eye or by study of a single channel;
2) as a way of diagnosing the instrument by identifying anomalies that
have
similar characteristics (i.e., this technique can classify anomalies).
Light-weight filters that are very effective at looking for events
like
these can then be designed and run on-line in the DMT or in LDAS.
3) Identified events can either be removed via a targeted regression
or the
data can be vetoed during some period involving the artifact.
We're continuing our investigations and will have more to report at
a later
time. We intend to develop an engine for doing this in the context
of the
DMT. I can't give a time scale for that yet - I've not yet talked with
the
student I have in mind for it - but it may be as early as Thanksgiving.
A.O.B.