A PETITE Step Toward Accurate Predictions For Fixed-Target Experiments
APA
Blinov, N. (2024). A PETITE Step Toward Accurate Predictions For Fixed-Target Experiments. Perimeter Institute. https://pirsa.org/24020088
MLA
Blinov, Nikita. A PETITE Step Toward Accurate Predictions For Fixed-Target Experiments. Perimeter Institute, Feb. 20, 2024, https://pirsa.org/24020088
BibTex
@misc{ pirsa_PIRSA:24020088, doi = {10.48660/24020088}, url = {https://pirsa.org/24020088}, author = {Blinov, Nikita}, keywords = {Particle Physics}, language = {en}, title = {A PETITE Step Toward Accurate Predictions For Fixed-Target Experiments}, publisher = {Perimeter Institute}, year = {2024}, month = {feb}, note = {PIRSA:24020088 see, \url{https://pirsa.org}} }
An intense beam of Standard Model (SM) particles colliding with a fixed target is one of oldest types of accelerator-based experiments. With recent interest in production and detection of relatively light, weakly-coupled (``dark sector'') states, these set-ups are again playing a central role in the search for beyond-SM (BSM) physics. Signal rate prediction is often challenging in fixed-target experiments, requiring the simulation of many SM and BSM processes as the beam particle propagates through the target. Both play a key role in determining the flux of dark sector particles through a detector. An accurate description of these fluxes is needed, since small errors in angular and energy distribution predictions can lead to significant over or under estimates of signal rate in the detector. Focusing for simplicity on BSM particle production from electromagnetic cascades, I will describe how we can model production of BSM particles, highlighting some frequently-used approximations used in the past. I will then show that improvements in both SM and BSM modelling are desirable. We implemented several of these improvements in a code, PETITE. Using this tool we can show how mismodelling of SM or BSM processes can lead to orders of magnitude difference in signal rates at realistic experimental setups.
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