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DTSTART;TZID=Europe/Paris:20260416T103000
DTEND;TZID=Europe/Paris:20260416T120000
DTSTAMP:20260416T131541
CREATED:20260414T083059Z
LAST-MODIFIED:20260414T085123Z
UID:12107-1776335400-1776340800@fermi.univ-tlse3.fr
SUMMARY:"La Coordination Nationale de la Sécurité des Systèmes d'Information (CNSSI) et ses activités"  &  "Le Numérique\, un enjeu de souveraineté" .  - (Michel Chabanne / CEMES /  Seminar). - 16/04/2026\, 10H30
DESCRIPTION:Séminaire du Jeudi\, CEMES \nMichel Chabanne RSSI du CNRS\,\n \nCEMES\, 16/04/2026\, 10H30 \nLein web : https://visio.numerique.gouv.fr/bpw-acmf-gtt
URL:https://fermi.univ-tlse3.fr/event/la-coordination-nationale-de-la-securite-des-systemes-dinformation-cnssi-et-ses-activites-le-numerique-un-enjeu-de-souverainete-michel-chabanne-cemes-seminar-16-04-2026/
LOCATION:Salle de conférence\, Bâtiment 3R4
CATEGORIES:CEMES,Events,Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20260416T110000
DTEND;TZID=Europe/Paris:20260416T123000
DTSTAMP:20260416T131541
CREATED:20260414T082435Z
LAST-MODIFIED:20260414T085115Z
UID:12105-1776337200-1776342600@fermi.univ-tlse3.fr
SUMMARY:Quantum key distribution: an information-theoretic view. - ( Meryem BENAMMAR / LCAR / Seminar). - 16/04/2026\, 11H
DESCRIPTION:Séminaire LCAR \nMeryem BENAMMAR\,  Institut Supérieur de l’Aéronautique et de l’Espace (ISAE)\, Toulouse  \nSummary\nWith the ever-growing need for secure communication links\, and the rapid evolving of quantum computing\, secret key generation has become a corner stone in the design of modern communication networks. Quantum key distribution (QKD) is one of the effective approaches for secret key generation under a quantum computing threat\, since its security stems from quantum mechanics (physics) and not from computational hardness of some mathematical problem. Hence\, QKD falls under the so-called physical layer secret key generation. While secret key generation from classical physical sources is well established in the information-theoretic literature since the seventies\, secret key generation from quantum sources is\, in turn\, more challenging to analyze from an information-theoretic perspective due to intrinsic differences between classical and quantum information processing tools. In this talk\, based on a simple BB84 protocol\, we describe an information theoretical framework to analyze and design QKD schemes by resorting to tools and results of quantum information theory\, while highlighting the main differences with classical secret key generation.
URL:https://fermi.univ-tlse3.fr/event/quantum-key-distribution-an-information-theoretic-view-meryem-benammar-lcar-seminar-16-04-2026-11h/
LOCATION:Salle de conférence\, Bâtiment 3R4
CATEGORIES:Events,LCAR,Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20260416T140000
DTEND;TZID=Europe/Paris:20260416T153000
DTSTAMP:20260416T131541
CREATED:20260414T082808Z
LAST-MODIFIED:20260414T085135Z
UID:11988-1776348000-1776353400@fermi.univ-tlse3.fr
SUMMARY:TS-Free Prediction of Activation Strain Components of Diels–Alder Reactions with Graph Neural Networks. - ( Daiann Sosa Carrizo / LPCNO / Seminar). - 16/04/2026\, 14H
DESCRIPTION:Séminaire du LCPQ \nDaiann Sosa Carrizo\, LPCNO \nSeminar LCPQ\, 16/04/2026\, 14H \nSummary :\nMachine learning is transforming computational chemistry. From predicting molecular properties — solubility\, spectroscopic\, and drug-likeness — to guiding retrosynthetic planning and catalyst design\, ML models have progressively replaced expensive quantum-chemical calculations with fast\, learned approximations. Yet some class of properties has remained largely out of reach: those that encode transition-state geometry.[1]\nThe Activation Strain Model (ASM) decomposes activation barriers into fragment deformation energies (ΔE‡_strain) and interfragment interaction energy (ΔE‡_int)\, explaining why a reaction is fast or slow rather than merely predicting trends. Computing these quantities requires explicit DFT transition-state optimisation — costly and incompatible with high-throughput screening.[2-3]\nIn this seminar\, I will discuss the application of the directed message-passing neural network (Dual D-MPNN) to predict ASM components from reactant SMILES\, without TS optimisation or hand-crafted descriptors. The model was trained on 802 endo Diels–Alder reactions computed at the M06-2X/6-311+G(d\,p) level of theory.[4] \nError analysis reveals a chemically interpretable result: diene conformational rigidity\, not electronic complexity\, is the primary determinant of model accuracy. Rigid heteroaromatic dienes such as furans are predicted near chemical accuracy\, while flexible hetero-acyclic dienes bearing conjugated carbonyl groups remain the principal failure mode. This is not an architectural limitation — it reflects a fundamental constraint of 2D molecular graphs\, which cannot encode the conformational ambiguity that determines TS geometry in flexible systems. \nAs a prospective application\, this model will be used to screen virtual diene libraries and identify reactive candidates for Diels–Alder reactions targeting terpenoid and alkaloid natural products. In these systems\, the ASM decomposition provides design principles — distinguishing strain-controlled from interaction-controlled reactivity — that barrier heights alone cannot offer. \n\n[1]. Chen\, X. et al. Nat. Synth. 2025\, 4\, 877–887.\n[2] Bickelhaupt\, F. M. et al. Angew. Chem. Int. Ed. 2017\, 56\, 10070–10086\n[3] Brunard\, E. et al. J. Am. Chem. Soc. 2024\, 146\, 5843–5854.\n[4] Vargas\, S. et al. J. Chem. Theory Comput. 2021\, 17\, 6098–6110.
URL:https://fermi.univ-tlse3.fr/event/ts-free-prediction-of-activation-strain-components-of-diels-alder-reactions-with-graph-neural-networks-daiann-sosa-carrizo-lpcno-seminar-2-02-2026-14h/
LOCATION:Salle de conférence\, Bâtiment 3R4
CATEGORIES:Events,LCPQ,Seminars
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