This week the VII AMVA4NewPhysics workshop is under way in the premises of LIP in Lisbon. During these events the network gets together to discuss the status of the various projects, plan future events and activities, take action on arisen issues, and vote on budget and other topics. But this is a special event in the lifetime of the network, as we are getting toward the mature stage – we are in the Continue reading “Advanced Results in Lisbon”
Casual reader, be warned – the contents of this article, specifically the second part of it, are highly volatile, speculative stuff. But hey, that is the stuff that dreams are made of. And I have one or two good reasons to dream on.
The environment
Machine Learning is ubiquitous today. Self-driving cars; self-shaving robots (just kidding, but I’m sure they can be constructed if the need arises); programs that teach themselves chess and become world-champion-class players overnight; Siri; google search engines; google translate – okay, I am going too far. But you know it: machine learning has become a player in almost Continue reading “Can Neural Networks Design The Detector Of A Future Particle Collider?”
What is spectroscopy ?
(A) the observation of ghosts by infrared visors or other optical devices
(B) the study of excited states of matter through observation of energy emissions
If you answered (A), you are probably using a lousy internet search engine; and btw, you are rather dumb. Ghosts do not exist.
Otherwise you are welcome to read on. We are, in fact, about to discuss a cutting-edge spectroscopy measurement, performed by the CMS experiment using lots of proton-proton collisions by the CERN Large Hadron Collider (LHC).
A paper by B. Fornal and B. Grinstein published last week in Physical Review Letters is drawing a lot of interest to one of the most well-known pieces of subnuclear physics since the days of Enrico Fermi: beta decay.
The mechanism by means of which a neutron transmutes into a proton has been studied for decades before the neutron was officially discovered (by Chadwick, in 1932). That is because beta decay is at the heart of radioactive processes: nuclei of elements rich with neutrons can turn into others by turning one of their neutrons into a proton, with the emission of an electron and an antineutrino. The details of that reaction were understood thanks to Fermi and a handful of other Continue reading “Is Dark Matter Lurking in Neutron Decays?”
The week before last I was presenting an update of some of my analysis work to the rest of my group. The work involved developing a neural-network to classify particle-collisions at the LHC. Continue reading “Train-time/test-time data augmentation”
A few days before I returned from CERN at the beginning of the month, I attended a talk on the upcoming TrackML challenge. This is a competition beginning this month in which members of the public will be invited to try and find a solution to the quite tricky problem of accurate reconstruction of particle trajectories in the collisions at the LHC. The various detectors simply record the hits where particles pass by, however to make use of this data, the hits in surrounding detector layers must be combined into a single flight path, called a track. Continue reading “Higgs Hacking”
I am happy to report that an important new product of the AMVA4NewPhysics ITN is now public. This is generically titled “Report on a Statistical Learning Method for Model-Independent Searches for New Physics“, and labeled D4.2 as per the grant agreement we signed with the European Union. The document is available at the following link:
http://www.pd.infn.it/%7Edorigo/D4.2.pdf
What is this document about ? It is a description of the studies for the development of a software package aiming at automating the searches for new physics in LHC data, by evidencing anomalous clusterings of events that are hard to explain with known physics processes. I am sure that Fabricio and Grzegorz, the two main developers of the software (Deliverable 4.3, available on github at https://github.com/Grzes91/PenalizedAD) and its documentation (D4.2) will be happy to post in this blog a more complete description of the new package and its possible uses in particle physics research.
A few months ago I wrote about some work I was doing on improving the way a certain kind of particle is detected at CMS, by replacing the existing algorithm with a neural network. I recently resumed this work and have now got to the point where I show significant improvement over the existing method. The design of the neural network, however, was one that I imported from some other work, and what I want to do is to adjust it to better suit my problem. Continue reading “Adjusting hyper-parameters: First step into Bayesian optimisation of DNNs”
The last CMS week of the year was held two weeks ago, summarizing all the upgrades and changes that happened in 2017, but also the plans of the groups for 2018. Since my service work concerns the L1 muon trigger performance, I was asked by the data performance group conveners to give a talk about the muon trigger algorithms and the improvements that happened last year. Continue reading “The L1 muon trigger algorithms”
AMVA4NewPhysics 
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