SWaB: DAMA/Libra DM "detection" fails replication

[notFritzArgelander]

I'm generally not reading SWaB since they have monetized their offerings but this article is exceptionally important. It also has a plausible account for how the team generated their signal through faulty analysis.

https://www.forbes.com/sites/startswith ... 5d03863e5c

[The Happy Parrot]

Very interesting and odd they refused to share their data for twenty years. The article seems to imply shenanigans though they don't outright say it. They also don't mention who "they" are running the DAMA/Libra experiment. Who are they?

[notFritzArgelander]

Very interesting and odd they refused to share their data for twenty years. The article seems to imply shenanigans though they don't outright say it. They also don't mention who "they" are running the DAMA/Libra experiment. Who are they?

It would be premature to take away the sense of shenanigans in the sense of skullduggery. Perhaps shenanigans in the sense of self delusion. The main point is that the method of subtracting each year's AVERAGE noise from the signal would work if the noise were truly random. The fact that the noise increases in time can give rise to a false positive signal.

The folks have been criticized for years for not doing a full release of all data. The lab Gran Sasso National Laboratory in Italy, a solid center for nuclear physics research. The theorist who came up with the concept for the experiment is Katherine Freese at U of Michigan. The chief investigator and leader of the experimental team is Rita Bernabei of the University of Rome Tor Vergata. Bernabei is responsible (IMO) for the tight hold on the data stream.

The lab has been a target for neutrinos from the LHC at Geneva 730 km away from the Gran Sasso lab.

Bernabei never presented the complete data stream, only 6 years of processed data as mentioned in this oder article.

https://www.quantamagazine.org/trouble- ... -20180412/

It's going to be a modern object lesson in the unwholesomeness of mere authority versus the raw facts.

[The Happy Parrot]

I think you are right nFA. Mean centering, or "removal of the DC component" as electrical engineers might call it, is a useful technique to interpret noisy data. Patient monitors, for example, use these techniques to eliminate data spikes from patients sneezing or moving around.

Of course, if the raw data you are removing is integral to the experiment results (non-random), you'd be massaging the results to fit the desired conclusion.

One wonders if this would have been noticed long ago if the data had been available. What a setback.