Being in a computing class, 85% of whose students are men, can be discouraging for women. This, however, did not deter my passion for computing, so when I was offered a PhD at CERN, needless to say I took it.
The Large Hadron Collider (LHC) at CERN is the largest particle accelerator in the world, accelerating two counter-rotating particle beams at the speed of light. The LHC is susceptible to beam losses that can damage its equipment, so 100 collimators are installed to absorb them before they can cause any damage.
A collimator is made of two parallel absorbing blocks, referred to as jaws, inside a vacuum tank. To absorb these losses, the collimators need to be individually aligned around the beam. Alignments are performed on multiple occasions for a minimum of three hours during the night, and my doctoral studies focused on automating this alignment.
During my first year, Dr Fabiola Gianotti was selected as the first woman to be the director general of CERN. This is a positive step towards welcoming women at CERN, however there is still a long way to go. The current percentage of women in the scientific population at CERN is about 18%, compared to eight% in 1995.
Women make up 47% of employed adults in the US, but as of 2015 they hold only 25% of computing roles, according to data from the National Center for Women and Information Technology.
To reduce the gender disparity in science so that both genders are equally represented in research institutions, scholarship programmes have opened specifically for women in science.
Women with the same qualifications as men are prioritised for certain scientific jobs, and various Women in Technology (WIT) groups are forming in research facilities all around the world, with CERN’s WIT group founded in 2016.
Working as a female computer scientist surrounded by physicists meant that I needed to work a little extra to prove myself and my work in this community. Fully automating the collimator alignment and speeding it up by 70% was my contribution to great results achieved for the LHC.
Women used to start off at a disadvantage in the scientific community, but nowadays their contribution is being recognised. Credit is given to a job well done and not diminished ‘just because a woman did it’. This also applies to people coming from different races, countries of origin and scientific fields.
Gabriella Azzopardi, Computer Scientist, post-doc at CERN
Did you know?
• Fabiola Gianotti is the first person in CERN’s history to be renewed for a second term as director general.
• The beam size is 3mm whereas a collimator is 1m long and 25cm wide.
• The fully-automatic alignment software developed is the first application of Machine Learning in the LHC operation.
• CERN’s first female football team was formed in 2018.
• To increase the number of collisions, the LHC will be upgraded in 2024 to High Luminosity LHC (HL-LHC).
For more trivia see: www.um.edu.mt/think
Sound bites
• The LHC usually operates for three to four years and is then shut down for one or two years to upgrade various equipment and to ensure reliable LHC operation. The first shutdown began at the end of 2012 and lasted 20 months. Due to COVID delays, the LHC’s second shutdown, which started at the end of 2018, is expected to last around 40 months. Katy Foraz has been at the forefront of LHC equipment maintenance and upgrades for both LHC shutdowns, and after over a decade she has recently been appointed as the head of the Engineering department at CERN.
https://cds.cern.ch/record/1492974/files/KF_5_01.pdf
• Machine Learning is used in various fields, and most commonly in Computer Vision. A recent study by Laura Leal-Taixé introduces a new method for object tracking in images. It uses the underlying graph rather than extracting features from the images, making it faster and less restrictive. This research was partially funded by the Humboldt Foundation through the Sofja Kovalevskaja Award of €1.65 million that she was awarded for her project socialMaps. Currently, Leal-Taixé is a tenure-track professor at the Technical University of Munich, Germany, leading the Dynamic Vision and Learning Group group in Computer Vision.
https://arxiv.org/pdf/1912.07515.pdf
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