Droit et mémoire

Prolongeant la réflexion sur l’intégration des valeurs collectives dans le monde du droit, qui est au centre des travaux d’Andrée Lajoie, on entend ici s’interroger sur la relation entre « droit » et « mémoire », à partir de l’exemple français

Alpha radioactivity of E > 11 MEV in nature

Alpha particles with energies greater than those so far reported to occur in nature have been observed in minerals by emulsion and counting techniques

Evidence for new α-particle groups in nature

Alpha-particle spectra from a monazite are presented which show evidence for unreported groups at 6.52, 7.09, 9.02 and 9.07 MeV

Light emission from silicon with tin-containing nanocrystals

Tin-containing nanocrystals, embedded in silicon, have been fabricated by growing an epitaxial layer of Si_{1-x-y}Sn_{x}C_{y}, where x = 1.6 % and y = 0.04 %, followed by annealing at various temperatures ranging from 650 to 900 degrees C. The nanocrystal density and average diameters are determined by scanning transmission-electron microscopy to ~ 10^{17} cm^{-3} and ~ 5 nm, respectively. Photoluminescence spectroscopy demonstrates that the light emission is very pronounced for samples annealed at 725 degrees C, and Rutherford back-scattering spectrometry shows that the nanocrystals are predominantly in the diamond-structured phase at this particular annealing temperature. The origin of the light emission is discussed.Comment: 5 pages, 3 figures, submitted to AIP Advance

Périodes de niveaux excités du calcium 40 et de l'iode 132

Cet article présente la mesure de la période, T1/2 = (2,15 ± 0,08) ns du premier niveau excité de 40Ca. Les mesures de coïncidences différées dans 132I ont permis de fixer l'ordre d'émission des deux rayons gamma de 52 keV et 232 keV ; les périodes sont égales à T1/2 = (0,96 ± 0,04) ns pour le niveau à 52 keV et à T1/2 = (1,42 ± 0,05) ns pour le niveau à 284 keV. Ces valeurs, et des mesures du coefficient de conversion interne α K, permettent d'attribuer les ordres multipolaires M1 + E2 et E2 respectivement pour les transitions de 52 et 232 keV

Formalising the Foundations of Discrete Reinforcement Learning in Isabelle/HOL

We present a formalisation of finite Markov decision processes with rewards in the Isabelle theorem prover. We focus on the foundations required for dynamic programming and the use of reinforcement learning agents over such processes. In particular, we derive the Bellman equation from first principles (in both scalar and vector form), derive a vector calculation that produces the expected value of any policy p, and go on to prove the existence of a universally optimal policy where there is a discounting factor less than one. Lastly, we prove that the value iteration and the policy iteration algorithms work in finite time, producing an epsilon-optimal and a fully optimal policy respectively