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.
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?”
Well folks, it’s been quite a while since my last post; apologies for that, it’s been a busy few months recently.
Towards the end of last year I wrote a post on optimising the hyper parameters (depth, width, learning rate, et cetera) of neural networks. In this post I described how I was trying to use Bayesian methods to ‘quickly’ find useful sets of parameters. Continue reading “Hyper-parameters revisited”
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:
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”