
Three Major Physics Discoveries and Counting - tokenadult
https://www.quantamagazine.org/sau-lan-wus-three-major-physics-discoveries-and-counting-20180718/
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abecedarius
A intriguing remark near the end: _We are also very excited about the near
future, because we plan to start using quantum computing to do our data
analysis._

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mathgenius
It was nice to see this comment, because to me it means that she is always
looking to the future & optimistic.

One of the near-term applications of quantum computing is for machine
learning. For example, the D-wave chip is for optimising a binary fitness
function. We will soon see if it works out.

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sempron64
Interestingly, she mentions using machine learning for analysis of the Higgs
Boson data. Does anyone here know more about this?

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DuskStar
In my opinion, CERN is one of the few groups out there that can call their
data set "big data" without talking out of their ass. (If it can fit in RAM,
it ain't Big Data. Multiple TBs fit in RAM) Their detectors produce something
on the order of a petabyte _per second_ which is then pared back immensely to
become something that's actually storable. Most of the machine learning I've
heard of involving CERN is in reducing that data stream and then highlighting
"interesting" things for researchers to take a look at.

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frumiousirc
Although LHC experiments are toward the top of the heap in terms of data
rates, many particle and astronomical experiments produce "big data". One
quarter of the DUNE experiment will acquire about 50 EB/year (that's exabyte),
outputting about 10 PB/year to tape. LSST will produce data in the few PB/year
range.

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lokimedes
Not to belittle your examples, but in a historical context the LHC held a
specific position. Remember that the ATLAS/CMS/ALICE/LHCb experiments started
recording data at 10 GB/s back in 2008. Now, ten years later it is only
natural that large data rates are becoming the norm.

