Higgles Abound

Higgles in ATLAS, Machine Learning and Life as a Gypsy Physcicist.

Higgles and Taus with ATLAS

Entering into the second phase of running physics research at the Large Hadron Collider (LHC) all eyes are turning to the physicists that claimed the discovery of a new boson compatible with the Higgs Boson of the standard model. Are the properties of this new particle exactly as predicted? Does it interact with other particles with the same strength that It should? does it have the right symmetry properties that we expect?

My research uses the ATLAS detector to probe the nature of the Higgs Boson using Tau Leptons.

Tau Leptons are in the same family as electrons except much heavier. Because of all this extra mass they can decay either into other leptons such as electrons or composite particles made of quarks. To help improve the resolution of the information that these taus can give us about the particle that created them (such as the Higgs) I'm also involved in the development of algorithms that attempt to split the measurement of a hadronic tau into its visible components such that each component might be resolved with the best possible accuracy.

In the past I have also worked on searches for Higgs Bosons produced by vector boson fusion decaying into 2 W bosons and modeling of Z boson decaying into Taus in this channel. I've also been involved in improving the acuracy of the fast simulation of particles in the ATLAS calorimeter.

I work as a muon shifter in the ATLAS control room. I was sat in the corner on the 4th of April when the ATLAS detector saw the first beams of the LHC run 2. Splash Day!

Teaching/ Outreach

Assorted Jupyter(ipython) notebooks with notes on RooFit, Machine Learning, Extended Likelihood Models etc can be found on the notebooks page.

Notes on setting up ATLAS specific software can be found on the ATHENA and MC page.

I gave a series of lectures on exploratory data analysis, clustering and data preprocessing for the 2015 inverted CERN School of Computing. Slides for the lectures are found here and here. Acompagnying code for basic code in R found here. Python code for extracting LinkedIn data, PCA and k-means clustering found here

About Vince Croft

Born in the North West of England and attending school in Lancashire, Yorkshire and South Wales. I started my undergraduate studies in physics at the Royal Holloway College of the University of London.

I worked towards a bachelor project working on Tau Triggers for the ATLAS experiment as part of my year studying abroad with the Niels Bohr Institute in Copenhagen. From there I worked on developements to the Trigger Tool with the ATLAS group at DESY in hamburg before returning to finish my masters In london. First reviewing experimental searches for axions as a light dark matter candidate (Light in terms of weight. Dark in terms of visibility) before looking at optimising multivariate methods for searches for sypersymmetry with ATLAS

Upon leaving London I traveled to Paris to study higher courses in Particle Physics and Cosmology with the Ecole Polytechnique as part of their Joint High Energy Physics Program. There I worked with the 'Calorimeter for ILC experiment' (CALICE) group on developing clustering algorithms using bayesian pattern recognition for a Future linear collider.

After a short internship with searches for exotic physics with CMS I took up a PhD position with the ATLAS group in Nijmegen in association with the Dutch Institute for High Energy Physics, NIKHEF.

In addition to the research listed above I have also attended two meetings of the Belgian-Dutch-German doctoral school in high energy physics (BND school), and the CERN School of Computing CSC and have assisted in teaching two undergraduate lab courses, 3 courses in undergraduate particle physics (at varying levels, in both English and (bad) Dutch) as well as an introduction to Machine Learning.