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Sökning: WFRF:(Petit Pascal) > (2019)

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1.
  • Faure, Quentin, et al. (författare)
  • Tomonaga-Luttinger Liquid Spin Dynamics in the Quasi-One-Dimensional Ising-Like Antiferromagnet BaCo2V2O8
  • 2019
  • Ingår i: Physical Review Letters. - : American Physical Society. - 0031-9007 .- 1079-7114. ; 123:2
  • Tidskriftsartikel (refereegranskat)abstract
    • Combining inelastic neutron scattering and numerical simulations, we study the quasi-one-dimensional Ising anisotropic quantum antiferromagnet BaCo2V2O8 in a longitudinal magnetic field. This material shows a quantum phase transition from a Neel ordered phase at zero field to a longitudinal incommensurate spin density wave at a critical magnetic field of 3.8 T. Concomitantly, the excitation gap almost closes and a fundamental reconfiguration of the spin dynamics occurs. These experimental results are well described by the universal Tomonaga-Luttinger liquid theory developed for interacting spinless fermions in one dimension. We especially observe the rise of mainly longitudinal excitations, a hallmark of the unconventional low-field regime in Ising-like quantum antiferromagnetic chains.
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2.
  • Vono, Maxime, et al. (författare)
  • A Fully Bayesian Approach for Inferring Physical Properties with Credibility Intervals from Noisy Astronomical Data
  • 2019
  • Ingår i: 2019 10TH WORKSHOP ON HYPERSPECTRAL IMAGING AND SIGNAL PROCESSING - EVOLUTION IN REMOTE SENSING (WHISPERS). - 2158-6268. - 9781728152943
  • Konferensbidrag (refereegranskat)abstract
    • The atoms and molecules of interstellar clouds emit photons when passing from an excited state to a lower energy state. The resulting emission lines can be detected by telescopes in the different wavelength domains (radio, infrared, visible, UV...). Through the excitation and chemical conditions they reveal, these lines provide key constraints on the local physical conditions reigning in giant molecular clouds (GMCs), which constitute the birthplace of stars in galaxies. Inferring these physical conditions from observed maps of GMCs using complex astrophysical models of these regions remains a complicated challenge due to potentially degenerate solutions and widely varying signal-to-noise ratios over the map. We propose a Bayesian framework to infer the probability distributions associated to each of these physical parameters, taking a spatial smoothness prior into account to tackle the challenge of low signal-to-noise ratio regions of the observed maps. A numerical astrophysical model of the cloud is involved in the likelihood within an approximate Bayesian computation (ABC) method. This enables to both infer point-wise estimators (e.g., minimum mean square or maximum a posteriori) and quantify the uncertainty associated to the estimation process. The benefits of the proposed approach are illustrated based on noisy synthetic observation maps.
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