ATLAS
UPGRADE STRIP-TRACKER MODULE PRODUCTION
The ATLAS detector is one of two large general-purpose detectors designed to probe new physics at the Large Hadron Collider (LHC) at CERN. The LHC has an ambitious upgrade program, known as the High Luminosity LHC (HL-LHC) that will greatly extend the sensitivity to new physics. To achieve this, the LHC will shut down for a period of ~3 years to allow for improvements to the LHC accelerator systems. The HL-LHC will increase the luminosity of the proton beam by a factor of between five and seven, meaning that the average number of particle interactions per passing beam crossing increases greatly.
The HL-LHC presents an extremely challenging environment to the ATLAS experiment, far beyond that for which it was originally designed. An upgrade of the ATLAS detector is needed to cope with the high radiation environment. RAL is heavily involved in the upgrade of the silicon tracking detector, the ITk, which surrounds the interaction region of the ATLAS experiment. The tracker measures the momentum and trajectory of charged particles.
At RAL, silicon strip detector modules will be built and tested and we are looking for summer students to join our team during the pre-production phase. Central to the preproduction phase will be ensuring the quality of assembled modules via so-called Quality Control measurements. The student will work on the software required to fully analyse such test measurements and upload them to a production database. The analysis will also be performed on data from across the international collaboration by extracting and analysing summary measurements from the production database. Finally, careful monitoring of laboratory conditions is vital for the project. The student will work on the deployment and testing of a Raspberry Pi or Arduino-based monitoring system.
The project is intended to include time in the lab but in the event of this not being possible due to Covid, will be run remotely and concentrate on the software and data analysis aspects of the project.
Desired Skills: some programming experience is required, ideally in C++ and/or Python. Experience with Arduino or Raspberry Pi would be useful but not required.
STRIP MODULE TESTBEAN
The ATLAS detector is one of two large general-purpose detectors designed to probe new physics at the Large Hadron Collider (LHC) at CERN. The LHC has an ambitious upgrade program, known as the High Luminosity LHC (HL-LHC) that will greatly extend the sensitivity to new physics. To achieve this, the LHC will shut down for a period of ~3 years to allow for improvements to the LHC accelerator systems. The HL-LHC will increase the luminosity of the proton beam by a factor of between five and seven, meaning that the average number of particle interactions per passing beam crossing increases greatly.
The HL-LHC presents an extremely challenging environment to the ATLAS experiment, far beyond that for which it was originally designed. An upgrade of the ATLAS detector is needed to cope with the high radiation environment. RAL is heavily involved in the upgrade of the silicon tracking detector, the ITk, which surrounds the interaction region of the ATLAS experiment. The tracker measures the momentum and trajectory of charged particles.
At RAL, silicon strip detector modules will be built and tested and we are looking for summer students to join our team during the pre-production phase. Central to the preproduction phase will be ensuring the quality of assembled modules via so-called test-beam and irradiation measurements. Modules are tested in beam-line experiments by putting modules into particle beams and analysing their behaviour and detection efficiency. In addition, module components are irradiated to analyse their expected performance in the high-radiation environment of the HL-LHC. In this project, the student will work with data from both irradiation and test beam measurements to analyse the performance of strip modules in the challenging environment for which they have been designed.
The project is intended to include time in the lab but in the event of this not being possible due to Covid, will be run remotely and concentrate on the software and data analysis aspects of the project.
Desired Skills: Some programming experience is required, ideally in C++ and/or Python.
PIXEL ENDCAP ASSEMBLY at RAL
The Upgraded ATLAS Pixel Tracker will be the biggest pixel detector system ever built, with over a billion detector channels. At RAL we will be a key player in the assembly of the Pixel Endcaps for the Tracker Upgrade. RAL will assemble hybrid pixel detector modules onto lightweight carbon fibre half-rings for the Upgrade.
Over the next few months, we will continue our work on the precision placement of detector modules onto the half-rings. We seek a student to undertake refinement of placement methods, and measurement of the achievable placement accuracy. This will be carried out using our high-precision motorised gantry system, equipped with a camera, laser displacement sensor and adhesive dispense system.
Specific tasks include calibrating the accuracy of the gantry itself against an OGP Smartscope. We will build prototype detector assemblies, which will be tested by our collaborators to verify the electrical and cooling system design for the Upgrade. We will carry out trials with different candidate adhesives and dispensing methods, assembling dummy and mechanical grade components.
As part of the work, we must be able to test the electrical functionality of the detector modules before and after mounting them to the half-ring structure. This will require the programming of automated test routines.
Equipment control using Labview software plays an important part in the work. We are currently working on improvements to the existing software, which controls detector module placement, adhesive deposition and survey. Opportunities exist to work on developing these improved programs and developing software for our new OGP Smartscope.
We seek a dextrous student with good practical skills and patience. Some programming experience is needed for the control of equipment and analysis of results. A basic understanding of experimental errors and statistics is important, as is basic mathematical proficiency. Experience with Labview software, Arduino or Raspberry Pi would be useful, but is not essential, as would knowledge of a mechanical CAD package.
If no Lab/Cleanroom access is possible due to Covid-19 regulations, many programming tasks can be completed remotely. We may look at reproducing the functionality of the present Labview software using an alternative such as Matlab. We also have an alternative ongoing project, simulating hybrid pixel detectors with 3D-printed tungsten collimators, for gamma-ray detection in nuclear medicine. This can be done remotely using the GATE interface to the GEANT4 Monte Carlo software.
TRIGGER UPGRADE
The ATLAS Trigger system makes fast real-time decisions on whether to keep data from interesting proton-proton collision events at the LHC to be studied later, or discard them. We can only keep about 1 in 100,000 collisions. The trigger software makes this selection by identifying characteristic features within the data, for example looking for tracks that could be from the decay of a Higgs or a new exotic particle. This requires a data centre with over 50,000 CPU cores. The trigger software is being upgraded ready for the start of a new period of LHC data-taking starting in 2022. You will analyse the performance of the new trigger software on data and simulation and help to optimise the performance to maximise the ATLAS physics potential. You will implement improvements to the software and measure the changes. Desired Skills: You should have an interest in computing with some experience in programming in C++ or a similar language. Some knowledge of ROOT would be helpful but is not essential.
CMS
RECONSTRUCTION ALGORITHMS on FPGAs for the TRIGGER UPGRADE
The Large Hadron Collider will be upgraded to a much higher luminosity machine for operation beyond 2027. The resulting huge number of interactions (a few hundred) in each bunch crossing must be disentangled and to cope with this the CMS detector will be upgraded. A critical element is the first level of triggering which must decide whether an event has the potential to include evidence of physics beyond the standard model within a few microseconds. One completely new feature of this hardware trigger is the availability of tracks reconstructed in the Silicon Tracker. This enables algorithms to be executed at this trigger level that is beyond the capability of the current CMS detector, such as the reconstruction of the origin ('vertex') of interactions. Both conventional and machine-learning algorithms will be considered, with a focus on their viability for implementation in programmable fast electronics (FPGAs). Algorithms will be implemented on Xilinx® FPGAs using High-Level Synthesis (HLS).
Not suitable for remote working
DARK MATTER
OBSERVATION of the MIGDAL EFFECT from NEUTRON SCATTERING
The Dark Matter group at RAL has been involved in the construction of the LUX-ZEPLIN double phase LXe detector at Homestake in the US. We are also involved in the R&D programme for the future G3 Liquid Xenon Dark Matter project. One of the R&D elements is to measure the so-called "Migdal effect" which detection will significantly improve the detector sensitivity to low mass WIMP searches. The success of the future experiment depends on a careful understanding of this effect.
Summer students will be involved in the low-pressure optical time projection chamber simulations and data analysis including study of the detector response to low energy electrons and nuclear recoils created in the process of the neutron scattering.
Desired Skills: You should have an interest in computing with some experience of programming in C++, Python or a similar language. Some knowledge of Matlab or ROOT would be helpful but is not essential.
OTHER PROJECTS
DESIGNING and BUILDING PARTICLE PHYSICS EXHIBITS for PUBLIC ENGAGEMENT
This project is earmarked for students from SEPnet Universities.
The Particle Physics Department (PPD) at Rutherford Appleton Laboratory (RAL) participates in and supports the UK particle physics experimental programme. Our mission includes public engagement and we run a number of Public Understanding of Science events. We are currently finalising a number of exhibits to explain our to the public, including a lego LHC, an LED detector and a system using pattern recognition to analyse live data from a cloud chamber. Once completed, these exhibits will be on display in the RAL visitor’s centre.
The student will help with managing the day-to-day outreach activities (newsletters, social media etc.) as well as working on the finalisation and deployment of our exhibits, particularly developing software for both the LED detector and the cloud chamber exhibits. The student should have a strong interest in explaining science to the public and a basic knowledge of programming.
Desired skills: Some programming experience is required, ideally in C++ or Python. Experience in Arduino programming would be useful but is not essential.
