Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Automation of pulse identification at J-PARC1
by
Podlech, H.
, Liu, Y.
, Wagner, S.
in
Algorithms
/ Machine learning
/ Position measurement
2025
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Automation of pulse identification at J-PARC1
by
Podlech, H.
, Liu, Y.
, Wagner, S.
in
Algorithms
/ Machine learning
/ Position measurement
2025
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Automation of pulse identification at J-PARC1
2025
Request Book From Autostore
and Choose the Collection Method
Overview
At J-PARC, the 500 μs long macro-pulses generated by the LINAC are separated into intermediate-pulses to synchronize it to the frequency of the Rapid-Cycling-Synchrotron (RCS). To secure a stable operation, the knowledge of position and length of those intermediate pulses are crucial, as the pulses need to be adjusted to the RCS frequency. The measurement for this adjustment is done by a beam position monitor (BPM), positioned directly behind the LINAC section in the low energy beam transport (LEBT) section. Since the form of the detected pulses can vary, the implementation of classical algorithms for the automatic detection and identification of pulses proved unreliable. Because of that, it was decided to develop a machine learning algorithm for the automatic pulse identification. In this paper, the background, training and results of different machine learning algorithms developed for the described problem will be introduced and discussed. Additionally, a test of the developed program during active beam operation is being planned, and will be introduced.
Publisher
IOP Publishing
Subject
This website uses cookies to ensure you get the best experience on our website.