From ea199b80df2a36a4216ecbffebdf34e40b5ceb86 Mon Sep 17 00:00:00 2001 From: mbarbetti Date: Fri, 8 Mar 2024 12:15:00 +0100 Subject: [PATCH] implemented Mark's suggestions --- docs/poster-A3-h.pdf | Bin 3279550 -> 3279436 bytes docs/poster-A3-v.pdf | Bin 3278647 -> 3278367 bytes docs/poster.html | 30 +++++++++++++++--------------- docs/src_poster.jinja2 | 32 ++++++++++++++++---------------- 4 files changed, 31 insertions(+), 31 deletions(-) diff --git a/docs/poster-A3-h.pdf b/docs/poster-A3-h.pdf index cb600e7025569b329a5af555895ef7b28b51f3d1..a10b6f51d56e2da1ef23697dda4b459385fb8bf1 100644 GIT binary patch delta 41308 zcmV(%K;pl?mB<0il*j>)Kz}eaG$1}c3UhRFWnpa!cmdqK*|Ma^ap!rTPmvn4HanQX zN#?%vTuehC2$EBP&_q!jGeH-{s)ATVEkG@zsE4IqrGI~qaF6BtzFba0Gu=Z-l_w)( z@$m3HJR*LY|M&S%^CkbSR;ShcxLwcRKA-<#{(An4&)==)Pv6a#i+}ZUb6T(V{Ixml zmxtqyzxLbBYIE4k-#w+NTD_V@2QO1!%lS*|_~rah^Y6V@8D_Lr0_LzkqUdD3jYw>fSX%kBPn*v$_|D(?^L`F^=L zY}c#Pe6wHhc|68o-+w%R`}Fyb?>{_wIe+^C{8-H;^X5ORyqT-JL+)$0n?HRu|HW@! 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Lamarr: implementing a flash-simulation paradigm at LHCb

in 22nd International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2024)

-
+
M. Mazureka on behalf of the LHCb Simulation Project @@ -50,8 +50,8 @@

Lamarr: implementing a flash-simulation paradigm at LHCb The detailed simulation of the interaction between the traversing particles and the LHCb active volumes is the major consumer of CPU resources. During the LHC Run2, the LHCb experiment has spent more than 90% of the pledged CPU time to produce - simulations. Matching the upcoming and future demand for simulated samples make unavoidable - the upgrade of the current technologies developing faster simulation options. + simulations. Matching the upcoming and future demand for simulated samples means that the + development of faster simulation options is critical.

@@ -113,8 +113,8 @@

Lamarr: implementing a flash-simulation paradigm at LHCb

4. Models under the \(k\)-to-\(k\) hypothesis

- Assuming valid the existence of an unambiguous (\(k\)-to-\(k\)) relation - between generated particles and reconstructed objects, the detector high-level response can be modeled in terms + Assuming the existence of an unambiguous (\(k\)-to-\(k\)) relation + between generated particles and reconstructed objects, the high-level detector response can be modeled in terms of efficiency and "resolution" (i.e., analysis-level quantities):

  • Efficiency: Deep Neural Networks (DNN) trained to perform @@ -133,8 +133,8 @@

    Lamarr: implementing a flash-simulation paradigm at LHCb Lamarr parameterizes the high-level response of the LHCb tracking system relying on the following models:
      -
    • propagation: approximates the trajectory of a charged particles through - the dipole magnetic field (parametric model);
    • +
    • propagation: approximates the trajectory of charged particles through the + dipole magnetic field (parametric model);
    • geometrical acceptance: predicts which of the generated tracks lay within a sensitive area of the detector (DNN model);
    • tracking efficiency: predicts which of the generated tracks in acceptance are properly @@ -230,9 +230,9 @@

      Lamarr: implementing a flash-simulation paradigm at LHCb

      Lamarr provides the high-level response of the LHCb detector by relying on a pipeline of (subsequent) ML-based modules. To validate the charged particles chain, the distributions - of a set of analysis-level reconstructed quantities resulting from Lamarr have been - compared with what obtained from detailed simulation for \(\Lambda_b^0 \to \Lambda_c^+ \mu^- X\) decays with - \(\Lambda_c^+ \to p K^- \pi^+\). + of a set of analysis-level reconstructed quantities resulting from Lamarr have been + compared with that obtained from detailed simulation for \(\Lambda_b^0 \to \Lambda_c^+ \mu^- X\) decays + with \(\Lambda_c^+ \to p K^- \pi^+\).

      The deployment of the ML-based models follows a transcompilation approach based on @@ -292,13 +292,13 @@

      Lamarr: implementing a flash-simulation paradigm at LHCb

      10. Conclusions and outlook

      - Great effort is ongoing to put into production a fully parametric simulation - of the LHCb experiment, aiming to reduce the pressure on the CPU computing resources. + Great effort is ongoing to put a fully parametric simulation of the LHCb experiment + into production, aiming to reduce the pressure on computing resources.

      - DNN-based and GAN-based models succeed in describing the high-level response of the LHCb - tracking and PID detectors for charged particles, while work is still required to - parameterize the response of the ECAL detector due to the particle-to-particle . + DNN-based and GAN-based models succeed in describing the high-level response of the LHCb tracking and + PID detectors for charged particles, while work is still required to parameterize the + response of the ECAL detector due to the particle-to-particle correlation problem.

      The future development of Lamarr looks to design a flash-simulation framework that, although diff --git a/docs/src_poster.jinja2 b/docs/src_poster.jinja2 index 896892c..2a81951 100644 --- a/docs/src_poster.jinja2 +++ b/docs/src_poster.jinja2 @@ -21,8 +21,8 @@ {% endblock %} {% block badges %} - {# indico event #} - {# indico contribution #} + {# indico event + indico contribution #} {# poster PDF #} {# arXiv preprint #} {% endblock %} @@ -77,8 +77,8 @@ The detailed simulation of the interaction between the traversing particles and the LHCb active volumes is the major consumer of CPU resources. During the LHC Run2, the LHCb experiment has spent more than 90% of the pledged CPU time to produce - simulations. Matching the upcoming and future demand for simulated samples make unavoidable - the upgrade of the current technologies developing faster simulation options. + simulations. Matching the upcoming and future demand for simulated samples means that the + development of faster simulation options is critical.

      @@ -151,8 +151,8 @@

      4. Models under the \(k\)-to-\(k\) hypothesis

      - Assuming valid the existence of an unambiguous (\(k\)-to-\(k\)) relation - between generated particles and reconstructed objects, the detector high-level response can be modeled in terms + Assuming the existence of an unambiguous (\(k\)-to-\(k\)) relation + between generated particles and reconstructed objects, the high-level detector response can be modeled in terms of efficiency and "resolution" (i.e., analysis-level quantities):

      • Efficiency: Deep Neural Networks (DNN) trained to perform @@ -172,8 +172,8 @@ Lamarr parameterizes the high-level response of the LHCb tracking system relying on the following models:
          -
        • propagation: approximates the trajectory of a charged particles through - the dipole magnetic field (parametric model);
        • +
        • propagation: approximates the trajectory of charged particles through the + dipole magnetic field (parametric model);
        • geometrical acceptance: predicts which of the generated tracks lay within a sensitive area of the detector (DNN model);
        • tracking efficiency: predicts which of the generated tracks in acceptance are properly @@ -272,9 +272,9 @@

          Lamarr provides the high-level response of the LHCb detector by relying on a pipeline of (subsequent) ML-based modules. To validate the charged particles chain, the distributions - of a set of analysis-level reconstructed quantities resulting from Lamarr have been - compared with what obtained from detailed simulation for \(\Lambda_b^0 \to \Lambda_c^+ \mu^- X\) decays with - \(\Lambda_c^+ \to p K^- \pi^+\). + of a set of analysis-level reconstructed quantities resulting from Lamarr have been + compared with that obtained from detailed simulation for \(\Lambda_b^0 \to \Lambda_c^+ \mu^- X\) decays + with \(\Lambda_c^+ \to p K^- \pi^+\).

          The deployment of the ML-based models follows a transcompilation approach based on @@ -342,13 +342,13 @@

          10. Conclusions and outlook

          - Great effort is ongoing to put into production a fully parametric simulation - of the LHCb experiment, aiming to reduce the pressure on the CPU computing resources. + Great effort is ongoing to put a fully parametric simulation of the LHCb experiment + into production, aiming to reduce the pressure on computing resources.

          - DNN-based and GAN-based models succeed in describing the high-level response of the LHCb - tracking and PID detectors for charged particles, while work is still required to - parameterize the response of the ECAL detector due to the particle-to-particle . + DNN-based and GAN-based models succeed in describing the high-level response of the LHCb tracking and + PID detectors for charged particles, while work is still required to parameterize the + response of the ECAL detector due to the particle-to-particle correlation problem.

          The future development of Lamarr looks to design a flash-simulation framework that, although