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[tel-00726959, v1] Caractériser le milieu interstellaire ... - HAL - INRIA

[tel-00726959, v1] Caractériser le milieu interstellaire ... - HAL - INRIA

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J. R. Goicoechea et al.: Low sulfur dep<strong>le</strong>tion in the Horsehead PDR, Online Material p 3Fig. A.2. Thermalization tests for a plane-paral<strong>le</strong>l cloud illuminated by the cosmic background at both surfaces (z/z max = 0,1).In order to benchmark the spatial distribution of the PDR codeabundance predictions with our interferometric line observations,we now can use the simp<strong>le</strong> model described above to computethe synthetic spectrum of a required mo<strong>le</strong>cu<strong>le</strong>. To do that,the PDR code output was used as an input for the RT calculation.In particular, the density profi<strong>le</strong> (both n(H 2 )andn(H)), temperatureprofi<strong>le</strong> (both T k and T d ) and species abundance are carefullyinterpolated from the PDR spatial grid output. In practice,the slab discretization for the RT calculation has to be preciseenough to samp<strong>le</strong> the abundance, density and temperature varia<strong>tel</strong>-<strong>00726959</strong>,version 1 - 31 Aug 2012from different spatial regions contribute to J¯ij . Hence, the solutionof mo<strong>le</strong>cular excitation implicitly depends on the nonlocalradiation field, which obviously depends on <strong>le</strong>vel populationsin many cloud points. J¯ij is explicitly computed in theMonte Carlo approach, and thus, the RT-excitation prob<strong>le</strong>m issolved iteratively until desired convergence in some physical parameter(generally the <strong>le</strong>vel populations) is achieved. LTE <strong>le</strong>velpopulations at a constant fictitious T ex were used for the first iteration.In the case of CS modeling, T rot from the observationalrotational-diagrams (Fig. 5) was used.The RT prob<strong>le</strong>m is then simulated by the emission of a determinednumber of model photons (both sides external illumination,continuum and line photons) in a similar way to thatoriginally described by Bernes (1979). Model photons representa large quantity of real photons randomly distributed over theline profi<strong>le</strong> A.5 and emitted at random cloud positions and directions.Each model photon is followed through the differentslabs until it escapes the cloud or until the number of representedreal photons become insignificant. Note that the ang<strong>le</strong> θ betweenthe photon direction and the normal to the slabs remains constantin all the photon path. In spherical geometry the θ ang<strong>le</strong>between the photon direction and the radial direction changesin each photon step and thus has to be computed repeatedly.In addition, model photons sent in the cos θ ≃ 0 direction insemi-infinite plane-paral<strong>le</strong>l geometry will almost never escapethe cloud. Thus, a minimum number of represented real photonsis defined otherwise the photon is not followed anymore.In this way, the Monte Carlo simulation explicitly computes theinduced emissions caused by the different types of model photonsin all the slabs. At the end of the simulation, an averagedvalue for the B ij J¯ij that independently accounts for external illumination,continuum emission and line emission is stored forevery slab ( ∑ S ij,m in Bernes formalism). Populations are thenobtained in each slab by solving:∑ [ ∑ ] ∑n i Aij + S ij,m + C ij =jijin j[gig j∑S ij,m + C ji]. (A.9)A reference field for all types of model photons was included toreduce the inherent random fluctuations (i.e. the variance) of anyMonte Carlo simulation (see Bernes 1979, for details). Whena prescribed convergence in <strong>le</strong>vel the populations is reached, thetotal (gas+dust) source function is comp<strong>le</strong><strong>tel</strong>y determined andthe emergent intensity can be easily computed by integratingEq. (A.2).For spherical geometry, the code was successfully benchmarkedagainst two test prob<strong>le</strong>ms, the Bernes’ CO cloud (Bernes1979) and the HCO + collapsing cloud, prob<strong>le</strong>m 2a of the 1999Leiden benchmark (van Zadelhoff et al. 2002). In the caseof plane-paral<strong>le</strong>l geometry, several thermalization tests for theldepthδxinclination ang<strong>le</strong> ϕinterferometerFig. A.3. Adopted geometry for a plane-paral<strong>le</strong>l PDR inclined byan small ang<strong>le</strong> ϕ relative to the line of sight s. In this sketch, z denotesthe normal direction to the slabs and also the UV illumination direction.CS excitation (without dust emission) were successfully performed.Excitation temperatures as a function of the normal coordinateto slabs z are shown for CS J = 1–0, 2–1, 3–2 and5–4 transitions in Fig. A.2. Model parameters are T k = 20 K,n(H 2 ) = 10 5 cm −3 and χ(CS) = 7 × 10 −9 .Different excitationconditions are considered. Upper model: A ij /C ij = 0andT exis correctly thermalized to T kin (LTE). Midd<strong>le</strong> model: collisionalrates from Lique et al. (fil<strong>le</strong>d squares; 2006) and Turneret al. (empty circ<strong>le</strong>s; 1992) and resulting non-LTE excitation(see Sect. 5.1). As noted by Lique et al., their new collisionalrates produce larger excitation temperatures, especially as J increases.For the Horsehead physical conditions this implies thatthe estimated densities and/or abundances with Turner et al. collisionalrates are ∼10% larger. Lower model: collisional excitationneg<strong>le</strong>cted and T ex is radiatively thermalized to the cosmicbackground temperature at T bg = 2.7 K.A.2. A model for an edge-on cloud with inclinationϕUV illuminationsz

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