From 357e443dde7f01b0a2bfaacfd131738673383473 Mon Sep 17 00:00:00 2001 From: Valentin Volkl Date: Thu, 27 Feb 2025 21:57:59 +0100 Subject: [PATCH 1/2] fixes for quantum tracking proposal --- .../2025/proposal_SustainableQuantum.md | 31 +++++++++++-------- 1 file changed, 18 insertions(+), 13 deletions(-) diff --git a/_gsocproposals/2025/proposal_SustainableQuantum.md b/_gsocproposals/2025/proposal_SustainableQuantum.md index 70d1a2ced..c0611cfb2 100644 --- a/_gsocproposals/2025/proposal_SustainableQuantum.md +++ b/_gsocproposals/2025/proposal_SustainableQuantum.md @@ -1,14 +1,24 @@ - --- -+ project: Quantum for tracking -+ title: Sustainable Quantum Computing algorithms for particle physics reconstruction -+ layout: default -+ Difficulty: medium -+ Duration: 350h -+ Mentor availability: July-December -+ Organization: CERN +project: QuantumForTracking +title: Sustainable Quantum Computing algorithms for particle physics reconstruction +layout: gsoc_proposal +difficulty: medium +duration: 350 +mentor_avail: July-December +organization: CERN +project_mentors: + - email: miriam.lucio.martinez@cern.ch + organization: CERN + first_name: Miriam + last_name: Lucio + - email: arantza.de.oyanguren.campos@cern.ch + first_name: Arantza + last_name: Oyanguren + organization: IFIC-Valencia --- + + ## Description Reconstructing the trajectories of charged particles as they traverse several detector layers is a key ingredient for event reconstruction at any LHC experiment. The limited bandwidth available, together with the high rate of tracks per second, makes this problem exceptionally challenging from the computational perspective. With this in mind, Quantum Computing is being explored as a new technology for future detectors, where larger datasets will further complicate this task. Furthermore, when choosing such alternative sustainability will play a crucial role and needs to be studied in detail. This project will consist in the implementation of both Quantum and Classical Machine Learning algorithms for track reconstruction, and using open-source, realistic event simulations to benchmark them from both a physics performance and an energy consumption perspective. @@ -38,11 +48,6 @@ Reconstructing the trajectories of charged particles as they traverse several de * To be completed -## Mentors: - -* [Miriam Lucio](mailto:miriam.lucio.martinez@cern.ch) -* [Arantza Oyanguren (IFIC-Valencia)](mailto:arantza.de.oyanguren.campos@cern.ch) - From e3a68e39e25a5595873789ce3a1397066b459b94 Mon Sep 17 00:00:00 2001 From: Wouter Deconinck Date: Mon, 3 Mar 2025 15:06:20 -0600 Subject: [PATCH 2/2] gsoc: SustainableQuantum: fix pennylane.io link --- _gsocproposals/2025/proposal_SustainableQuantum.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_gsocproposals/2025/proposal_SustainableQuantum.md b/_gsocproposals/2025/proposal_SustainableQuantum.md index c0611cfb2..c2880ee05 100644 --- a/_gsocproposals/2025/proposal_SustainableQuantum.md +++ b/_gsocproposals/2025/proposal_SustainableQuantum.md @@ -27,7 +27,7 @@ Reconstructing the trajectories of charged particles as they traverse several de * Basic understanding of track reconstruction at LHC using [ACTS](https://acts.readthedocs.io/en/latest/) and/or [Allen framework](https://allen-doc.docs.cern.ch/index.html). * Familiarizing her/himself with trackML simulation datasets . -* Learning how to use the quantum simulator for QML algorithms https://pennylane.ai/. +* Learning how to use the quantum simulator for QML algorithms . ## Milestones