I'm not sure how you arrived at your conclusion from reading that. I can only guess that you're reading something into this sentence:
> Approximately 6 minutes later, a gravitational-wave candidate (later designated GW170817) was registered in low latency (Cannon et al. 2012; Messick et al. 2017).
"Registered in low latency" means that it was detected by their data analysis algorithms, which directly contradicts your conclusion that "they found data their algorithms had previously rejected as noise." If you doubt me, you can follow the citations from that paper. Cannon et al. 2012 resolves to http://iopscience.iop.org/article/10.1088/0004-637X/748/2/13..., which discusses the data processing and latencies involved (~5 minutes to trigger a detection and ~30 minutes for human vetting), which is consistent with the timeline you quoted. They even published the source code:
> We have implemented a prototype of the low-latency filtering stage using an open-source signal processing environment called GStreamer. ... We have extended the GStreamer framework by developing a library called gstlal that provides elements for GW data analysis.
The part you quoted mentions a few notices that were circulated through GCN. That's basically a mailing list to coordinate observation of transient phenomena. It's home page is https://gcn.gsfc.nasa.gov/. The circulars discussing the GW are here: https://gcn.gsfc.nasa.gov/other/G298048.gcn3. From the first post in the circulars:
> The online CBC pipeline (gstlal) has made a preliminary
identification of a GW candidate associated with the time
of Fermi GBM trigger.
gstlal is the library we met earlier in Canon et al. 2012. "Online" means it was processing the data in real-time.
Your claim that the data was rejected by their algorithms as noise isn't supported by the paper you're quoting or the original sources.
> Approximately 6 minutes later, a gravitational-wave candidate (later designated GW170817) was registered in low latency (Cannon et al. 2012; Messick et al. 2017).
"Registered in low latency" means that it was detected by their data analysis algorithms, which directly contradicts your conclusion that "they found data their algorithms had previously rejected as noise." If you doubt me, you can follow the citations from that paper. Cannon et al. 2012 resolves to http://iopscience.iop.org/article/10.1088/0004-637X/748/2/13..., which discusses the data processing and latencies involved (~5 minutes to trigger a detection and ~30 minutes for human vetting), which is consistent with the timeline you quoted. They even published the source code:
> We have implemented a prototype of the low-latency filtering stage using an open-source signal processing environment called GStreamer. ... We have extended the GStreamer framework by developing a library called gstlal that provides elements for GW data analysis.
gstlal's home page is https://wiki.ligo.org/DASWG/GstLAL
The part you quoted mentions a few notices that were circulated through GCN. That's basically a mailing list to coordinate observation of transient phenomena. It's home page is https://gcn.gsfc.nasa.gov/. The circulars discussing the GW are here: https://gcn.gsfc.nasa.gov/other/G298048.gcn3. From the first post in the circulars:
> The online CBC pipeline (gstlal) has made a preliminary identification of a GW candidate associated with the time of Fermi GBM trigger.
gstlal is the library we met earlier in Canon et al. 2012. "Online" means it was processing the data in real-time.
Your claim that the data was rejected by their algorithms as noise isn't supported by the paper you're quoting or the original sources.