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M. Juvela

Publications and source records attributed to M. Juvela.

At least 91 records · Page 5Linked to original sources

Mapping of interstellar clouds with infrared light scattered from dust: TMC-1N

Mapping of near-infrared (NIR) scattered light is a recent method for the study of interstellar clouds, complementing other, more commonly used methods, like dust emission and extinction. Our goal is to study the usability of this method on larger scale, and compare the properties of a filament using NIR scattering and other methods. We also study the radiation field and differences in grain emissivity between diffuse and dense areas. We have used scattered J, H, and K band surface brightness WFCAM-observations to map filament TMC-1N in Taurus, covering an area of 1dx1d corresponding to ~(2.44 pc)^2. We have converted the data into optical depth and compared the results with NIR extinction and Herschel observations of submm dust emission. We see the filament in scattered light in all three NIR bands. We note that our WFCAM observations in TMC-1N show notably lower intensity than previous results in Corona Australis using the same method. We show that 3D radiative transfer simulations predict similar scattered surface brightness levels as seen in the observations. However, changing the assumptions about the background can change the results of simulations notably. We derive emissivity by using optical depth in the J band as an independent tracer of column density. We obtain opacity sigma(250um) values 1.7-2.4x10^-25 cm^2/H, depending on assumptions of the extinction curve, which can change the results by over 40%. These values are twice as high as obtained for diffuse areas, at the lower limit of earlier results for denser areas. We show that NIR scattering can be a valuable tool in making high resolution maps. We conclude, however, that NIR scattering observations can be complicated, as the data can show relatively low-level artefacts. This suggests caution when planning and interpreting the observations.

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Multiwavelength study of the high-latitude cloud L1642: chain of star formation

L1642 is one of the two high galactic latitude (|b| > 30deg) clouds confirmed to have active star formation. We examine the properties of this cloud, especially the large-scale structure, dust properties, and compact sources in different stages of star formation. We present high-resolution far-infrared and submm observations with the Herschel and AKARI satellites and mm observations with the AzTEC/ASTE telescope, which we combined with archive data from near- and mid-infrared (2MASS, WISE) to mm observations (Planck). The Herschel observations, combined with other data, show a sequence of objects from a cold clump to young stellar objects at different evolutionary stages. Source B-3 (2MASS J04351455-1414468) appears to be a YSO forming inside the L1642 cloud, instead of a foreground brown dwarf, as previously classified. Herschel data reveal striation in the diffuse dust emission around L1642. The western region shows striation towards NE and has a steeper column density gradient on its southern side. The densest central region has a bow-shock like structure showing compression from the west and a filamentary tail extending towards east. The differences suggest that these may be spatially distinct structures, aligned only in projection. We derive values of the dust emission cross-section per H nucleon for different regions of the cloud. Modified black-body fits to the spectral energy distribution of Herschel and Planck data give emissivity spectral index beta values 1.8-2.0 for the different regions. The compact sources have lower beta values and show an anticorrelation between T and beta. Markov chain Monte Carlo calculations demonstrate the strong anticorrelation between beta and T errors and the importance of mm Planck data in constraining the estimates. L1642 reveals a more complex structure and sequence of star formation than previously known.

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Planck intermediate results. XIII. Constraints on peculiar velocities

Using \Planck\ data combined with the Meta Catalogue of X-ray detected Clusters of galaxies (MCXC), we address the study of peculiar motions by searching for evidence of the kinetic Sunyaev-Zeldovich effect (kSZ). By implementing various filters designed to extract the kSZ generated at the positions of the clusters, we obtain consistent constraints on the radial peculiar velocity average, root mean square (rms), and local bulk flow amplitude at different depths. For the whole cluster sample of average redshift 0.18, the measured average radial peculiar velocity with respect to the cosmic microwave background (CMB) radiation at that redshift, i.e., the kSZ monopole, amounts to $72 \pm 60$ km s$^{-1}$. This constitutes less than 1% of the relative Hubble velocity of the cluster sample with respect to our local CMB frame. While the linear $Λ$CDM prediction for the typical cluster radial velocity rms at $z=0.15$ is close to 230km s$^{-1}$, the upper limit imposed by \Planck\ data on the cluster subsample corresponds to 800 km s$^{-1}$ at 95% confidence level, i.e., about three times higher. \Planck\ data also set strong constraints on the local bulk flow in volumes centred on the Local Group. There is no detection of bulk flow as measured in any comoving sphere extending to the maximum redshift covered by the cluster sample. A blind search for bulk flows in this sample has an upper limit of 254 km s$^{-1}$ (95% confidence level) dominated by CMB confusion and instrumental noise, indicating that the Universe is largely homogeneous on Gpc scales. In this context, in conjunction with supernova observations, \Planck\ is able to rule out a large class of inhomogeneous void models as alternatives to dark energy or modified gravity. The \Planck\ constraints on peculiar velocities and bulk flows are thus consistent with the $Λ$CDM scenario.

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Planck 2013 results. III. LFI systematic uncertainties

We present the current estimate of instrumental and systematic effect uncertainties for the Planck-Low Frequency Instrument relevant to the first release of the Planck cosmological results. We give an overview of the main effects and of the tools and methods applied to assess residuals in maps and power spectra. We also present an overall budget of known systematic effect uncertainties, which are dominated sidelobe straylight pick-up and imperfect calibration. However, even these two effects are at least two orders of magnitude weaker than the cosmic microwave background (CMB) fluctuations as measured in terms of the angular temperature power spectrum. A residual signal above the noise level is present in the multipole range $\ell<20$, most notably at 30 GHz, and is likely caused by residual Galactic straylight contamination. Current analysis aims to further reduce the level of spurious signals in the data and to improve the systematic effects modelling, in particular with respect to straylight and calibration uncertainties.

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Planck 2013 results. IV. Low Frequency Instrument beams and window functions

This paper presents the characterization of the in-flight beams, the beam window functions and the associated uncertainties for the Planck Low Frequency Instrument (LFI). Knowledge of the beam profiles is necessary for determining the transfer function to go from the observed to the actual sky anisotropy power spectrum. The main beam distortions affect the beam window function, complicating the reconstruction of the anisotropy power spectrum at high multipoles, whereas the sidelobes affect the low and intermediate multipoles. The in-flight assessment of the LFI main beams relies on the measurements performed during Jupiter observations. By stacking the data from multiple Jupiter transits, the main beam profiles are measured down to -20 dB at 30 and 44 GHz, and down to -25 dB at 70 GHz. The main beam solid angles are determined to better than 0.2% at each LFI frequency band. The Planck pre-launch optical model is conveniently tuned to characterize the main beams independently of any noise effects. This approach provides an optical model whose beams fully reproduce the measurements in the main beam region, but also allows a description of the beams at power levels lower than can be achieved by the Jupiter measurements themselves. The agreement between the simulated beams and the measured beams is better than 1% at each LFI frequency band. The simulated beams are used for the computation of the window functions for the effective beams. The error budget for the window functions is estimated from both main beam and sidelobe contributions, and accounts for the radiometer bandshapes. The total uncertainties in the effective beam window functions are: 2% and 1.2% at 30 and 44 GHz, respectively (at $\ell \approx 600$), and 0.7% at 70 GHz (at $\ell \approx 1000$).

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Planck 2013 results. II. Low Frequency Instrument data processing

We describe the data processing pipeline of the Planck Low Frequency Instrument (LFI) data processing centre (DPC) to create and characterize full-sky maps based on the first 15.5 months of operations at 30, 44 and 70 GHz. In particular, we discuss the various steps involved in reducing the data, starting from telemetry packets through to the production of cleaned, calibrated timelines and calibrated frequency maps. Data are continuously calibrated using the modulation induced on the mean temperature of the cosmic microwave background radiation by the proper motion of the spacecraft. Sky signals other than the dipole are removed by an iterative procedure based on simultaneous fitting of calibration parameters and sky maps. Noise properties are estimated from time-ordered data after the sky signal has been removed, using a generalized least square map-making algorithm. A destriping code (Madam) is employed to combine radiometric data and pointing information into sky maps, minimizing the variance of correlated noise. Noise covariance matrices, required to compute statistical uncertainties on LFI and Planck products, are also produced. Main beams are estimated down to the -20 dB level using Jupiter transits, which are also used for the geometrical calibration of the focal plane.

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Planck 2013 results. VIII. HFI photometric calibration and mapmaking

This paper describes the processing applied to the HFI cleaned time-ordered data to produce photometrically calibrated maps. HFI observes the sky over a broad range of frequencies, from 100 to 857 GHz. To get the best accuracy on the calibration on such a large range, two different photometric calibration schemes have to be used. The 545 and 857 \GHz\ data are calibrated using Uranus and Neptune flux density measurements, compared with models of their atmospheric emissions to calibrate the data. The lower frequencies (below 353 GHz) are calibrated using the cosmological microwave background dipole.One of the components of this anisotropy results from the orbital motion of the satellite in the Solar System, and is therefore time-variable. Photometric calibration is thus tightly linked to mapmaking, which also addresses low frequency noise removal. The 2013 released HFI data show some evidence for apparent gain variations of the HFI bolometers' detection chain. These variations were identified by comparing observations taken more than one year apart in the same configuration. We developed an effective correction to limit its effect on calibration, and assess its accuracy. We present several methods used to estimate the precision of the photometric calibration. We distinguish relative (from one detector to another, or from one frequency to another) and absolute uncertainties. In both cases, we found that these uncertainties range from a few $10^{-3}$ to several per cents from 100 to 857 GHz. We describe the pipeline producing the maps from the HFI timelines, based on the photometric calibration parameters and we detail the scheme used to a posteriori set the zero level of the maps. We also briefly discuss the cross-calibration between HFI and the SPIRE instrument on board Herschel. We finally summarize the basic characteristics of the set of the HFI maps from the 2013 Planck data release.

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Planck 2013 results. XXVI. Background geometry and topology of the Universe

Planck CMB temperature maps allow detection of large-scale departures from homogeneity and isotropy. We search for topology with a fundamental domain nearly intersecting the last scattering surface (comoving distance $χ_r$). For most topologies studied the likelihood maximized over orientation shows some preference for multi-connected models just larger than $χ_r$. This effect is also present in simulated realizations of isotropic maps and we interpret it as the alignment of mild anisotropic correlations with chance features in a single realization; such a feature can also exist, in milder form, when the likelihood is marginalized over orientations. Thus marginalized, the limits on the radius $R_i$ of the largest sphere inscribed in a topological domain (at log-likelihood-ratio -5) are: in a flat Universe, $R_i>0.9χ_r$ for the cubic torus (cf. $R_i>0.9χ_r$ at 99% CL for a matched-circles search); $R_i>0.7χ_r$ for the chimney; $R_i>0.5χ_r$ for the slab; in a positively curved Universe, $R_i>1.0χ_r$ for the dodecahedron; $R_i>1.0χ_r$ for the truncated cube; $R_i>0.9χ_r$ for the octahedron. Similar limits apply to alternate topologies. We perform a Bayesian search for an anisotropic Bianchi VII$_h$ geometry. In a non-physical setting where the Bianchi parameters are decoupled from cosmology, Planck data favour a Bianchi component with a Bayes factor of at least 1.5 units of log-evidence: a Bianchi pattern is efficient at accounting for some large-scale anomalies in Planck data. However, the cosmological parameters are in strong disagreement with those found from CMB anisotropy data alone. In the physically motivated setting where the Bianchi parameters are fitted simultaneously with standard cosmological parameters, we find no evidence for a Bianchi VII$_h$ cosmology and constrain the vorticity of such models: $(ω/H)_0<8\times10^{-10}$ (95% CL). [Abridged]

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Planck 2013 results. VII. HFI time response and beams

This paper characterizes the effective beams,the effective beam window functions and the associated errors for the Planck HFI detectors. The effective beam is the angular response including the effect of the optics,detectors,data processing and the scan strategy. The window function is the representation of this beam in the harmonic domain which is required to recover an unbiased measurement of the CMB angular power spectrum. The HFI is a scanning instrument and its effective beams are the convolution of: (a) the optical response of the telescope and feeds;(b)the processing of the time-ordered data and deconvolution of the bolometric and electronic time response; and (c) the merging of several surveys to produce maps. The time response functions are measured using observations of Jupiter and Saturn and by minimizing survey difference residuals. The scanning beam is the post-deconvolution angular response of the instrument, and is characterized with observations of Mars. The main beam solid angles are determined to better than 0.5% at each HFI frequency band. Observations of Jupiter and Saturn limit near sidelobes (within 5deg) to about 0.1% of the total solid angle. Time response residuals remain as long tails in the scanning beams, but contribute less than 0.1% of the total. The bias and uncertainty in the beam products are estimated using ensembles of simulated planet observations that include the impact of instrumental noise and known systematic effects.The correlation structure of these ensembles is well-described by five error eigenmodes that are sub-dominant to sample variance and instrumental noise in the harmonic domain. A suite of consistency tests provide confidence that the error model represents a sufficient description of the data. The total error in the effective beam window functions is below 1% at 100GHz up to ell~1500$,and below 0.5% at 143 and 217GHz up to ~2000.

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Planck intermediate results. XVI. Profile likelihoods for cosmological parameters

We explore the 2013 Planck likelihood function with a high-precision multi-dimensional minimizer (Minuit). This allows a refinement of the Lambda-cdm best-fit solution with respect to previously-released results, and the construction of frequentist confidence intervals using profile likelihoods. The agreement with the cosmological results from the Bayesian framework is excellent, demonstrating the robustness of the Planck results to the statistical methodology. We investigate the inclusion of neutrino masses, where more significant differences may appear due to the non-Gaussian nature of the posterior mass distribution. By applying the Feldman--Cousins prescription, we again obtain results very similar to those of the Bayesian methodology. However, the profile-likelihood analysis of the CMB combination (Planck+WP+highL) reveals a minimum well within the unphysical negative-mass region. We show that inclusion of the Planck CMB-lensing information regularizes this issue, and provide a robust frequentist upper limit $M_ν< 0.26 eV$ ($95%$ confidence) from the CMB+lensing+BAO data combination.

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Planck 2013 Results. XXIV. Constraints on primordial non-Gaussianity

The Planck nominal mission cosmic microwave background (CMB) maps yield unprecedented constraints on primordial non-Gaussianity (NG). Using three optimal bispectrum estimators, separable template-fitting (KSW), binned, and modal, we obtain consistent values for the primordial local, equilateral, and orthogonal bispectrum amplitudes, quoting as our final result fNL^local= 2.7+/-5.8, fNL^equil= -42+/-75, and fNL^ortho= -25+\-39 (68% CL statistical). NG is detected in the data; using skew-C_l statistics we find a nonzero bispectrum from residual point sources, and the ISW-lensing bispectrum at a level expected in the LambdaCDM scenario. The results are based on comprehensive cross-validation of these estimators on Gaussian and non-Gaussian simulations, are stable across component separation techniques, pass an extensive suite of tests, and are confirmed by skew-C_l, wavelet bispectrum and Minkowski functional estimators. Beyond estimates of individual shape amplitudes, we present model-independent, 3-dimensional reconstructions of the Planck CMB bispectrum and thus derive constraints on early-Universe scenarios that generate primordial NG, including general single-field models of inflation, excited initial states (non-Bunch-Davies vacua), and directionally-dependent vector models. We provide an initial survey of scale-dependent feature and resonance models. These results bound both general single-field and multi-field model parameter ranges, such as the speed of sound, c_s \geq 0.02 (95% CL), in an effective field theory parametrization, and the curvaton decay fraction r_D \geq 0.15 (95% CL). The Planck data significantly limit the viable parameter space of the ekpyrotic/cyclic scenarios. The amplitude of the 4-point function in the local model tauNL < 2800 (95% CL). These constraints represent the highest precision tests to date of physical mechanisms for the origin of cosmic structure.

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Planck 2013 results. XXVIII. The Planck Catalogue of Compact Sources

The Planck Catalogue of Compact Sources (PCCS) is the catalogue of sources detected in the first 15 months of Planck operations, the "nominal" mission. It consists of nine single-frequency catalogues of compact sources, both Galactic and extragalactic, detected over the entire sky. The PCCS covers the frequency range 30--857\,GHz with higher sensitivity (it is 90% complete at 180 mJy in the best channel) and better angular resolution (from ~33' to ~5') than previous all-sky surveys in this frequency band. By construction its reliability is >80% and more than 65% of the sources have been detected at least in two contiguous Planck channels. In this paper we present the construction and validation of the PCCS, its contents and its statistical characterization.

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Planck 2013 results. IX. HFI spectral response

The Planck High Frequency Instrument (HFI) spectral response was determined through a series of ground based tests conducted with the HFI focal plane in a cryogenic environment prior to launch. The main goal of the spectral transmission tests was to measure the relative spectral response (including out-of-band signal rejection) of all HFI detectors. This was determined by measuring the output of a continuously scanned Fourier transform spectrometer coupled with all HFI detectors. As there is no on-board spectrometer within HFI, the ground-based spectral response experiments provide the definitive data set for the relative spectral calibration of the HFI. The spectral response of the HFI is used in Planck data analysis and component separation, this includes extraction of CO emission observed within Planck bands, dust emission, Sunyaev-Zeldovich sources, and intensity to polarization leakage. The HFI spectral response data have also been used to provide unit conversion and colour correction analysis tools. Verifications of the HFI spectral response data are provided through comparisons with photometric HFI flight data. This validation includes use of HFI zodiacal emission observations to demonstrate out-of-band spectral signal rejection better than 10^8. The accuracy of the HFI relative spectral response data is verified through comparison with complementary flight-data based unit conversion coefficients and colour correction coefficients. These coefficients include those based upon HFI observations of CO, dust, and Sunyaev-Zeldovich emission. General agreement is observed between the ground-based spectral characterization of HFI and corresponding in-flight observations, within the quoted uncertainty of each; explanations are provided for any discrepancies.

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Planck 2013 results. XXX. Cosmic infrared background measurements and implications for star formation

We present new measurements of CIB anisotropies using Planck. Combining HFI data with IRAS, the angular auto- and cross frequency power spectrum is measured from 143 to 3000 GHz, and the auto-bispectrum from 217 to 545 GHz. The total areas used to compute the CIB power spectrum and bispectrum are about 2240 and 4400 deg^2, respectively. After careful removal of the contaminants, and a complete study of systematics, the CIB power spectrum and bispectrum are measured with unprecedented signal to noise ratio from angular multipoles ell~150 to 2500, and ell~130 to 1100, respectively. Two approaches are developed for modelling CIB power spectrum anisotropies. The first approach takes advantage of the unique measurements by Planck at large angular scales, and models only the linear part of the power spectrum, with a mean bias of dark matter halos hosting dusty galaxies at a given redshift weighted by their contribution to the emissivities. The second approach is based on a model that associates star-forming galaxies with dark matter halos and their subhalos, using a parametrized relation between the dust-processed infrared luminosity and (sub-)halo mass. The two approaches simultaneously fit all auto- and cross- power spectra very well. We find that the star formation history is well constrained up to z~2. However, at higher redshift, the accuracy of the star formation history measurement is strongly degraded by the uncertainty in the spectral energy distribution of CIB galaxies. We also find that CIB galaxies have warmer temperatures as redshift increases. The CIB bispectrum is steeper than that expected from the power spectrum, although well fitted by a power law; this gives some information about the contribution of massive halos to the CIB bispectrum.

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Estimation of high-resolution dust column density maps: Empirical model fits

Sub-millimetre dust emission is an important tracer of density N of dense interstellar clouds. One has to combine surface brightness information at different spatial resolutions, and specific methods are needed to derive N at a resolution higher than the lowest resolution of the observations. Some methods have been discussed in the literature, including a method (in the following, method B) that constructs the N estimate in stages, where the smallest spatial scales being derived only use the shortest wavelength maps. We propose simple model fitting as a flexible way to estimate high-resolution column density maps. Our goal is to evaluate the accuracy of this procedure and to determine whether it is a viable alternative for making these maps. The new method consists of model maps of column density (or intensity at a reference wavelength) and colour temperature. The model is fitted using Markov chain Monte Carlo (MCMC) methods, comparing model predictions with observations at their native resolution. We analyse simulated surface brightness maps and compare its accuracy with method B and the results that would be obtained using high-resolution observations without noise. The new method is able to produce reliable column density estimates at a resolution significantly higher than the lowest resolution of the input maps. Compared to method B, it is relatively resilient against the effects of noise. The method is computationally more demanding, but is feasible even in the analysis of large Herschel maps. The proposed empirical modelling method E is demonstrated to be a good alternative for calculating high-resolution column density maps, even with considerable super-resolution. Both methods E and B include the potential for further improvements, e.g., in the form of better a priori constraints.

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Planck intermediate results. XII: Diffuse Galactic components in the Gould Belt System

We perform an analysis of the diffuse low-frequency Galactic components in the Southern part of the Gould Belt system (130^\circ\leq l\leq 230^\circ and -50^\circ\leq b\leq -10^\circ). Strong ultra-violet (UV) flux coming from the Gould Belt super-association is responsible for bright diffuse foregrounds that we observe from our position inside the system and that can help us improve our knowledge of the Galactic emission. Free-free emission and anomalous microwave emission (AME) are the dominant components at low frequencies (ν< 40 GHz), while synchrotron emission is very smooth and faint. We separate diffuse free-free emission and AME from synchrotron emission and thermal dust emission by using Planck data, complemented by ancillary data, using the "Correlated Component Analysis" (CCA) component separation method and we compare with the results of cross-correlation of foreground templates with the frequency maps. We estimate the electron temperature T_e from H$α$ and free-free emission using two methods (temperature-temperature plot and cross-correlation) and we obtain T_e ranging from 3100 to 5200 K, for an effective fraction of absorbing dust along the line of sight of 30% (f_d=0.3). We estimate the frequency spectrum of the diffuse AME and we recover a peak frequency (in flux density units) of 25.5 \pm 1.5 GHz. We verify the reliability of this result with realistic simulations that include the presence of biases in the spectral model for the AME and in the free-free template. By combining physical models for vibrational and rotational dust emission and adding the constraints from the thermal dust spectrum from Planck and IRAS we are able to get a good description of the frequency spectrum of the AME for plausible values of the local density and radiation field.

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The degeneracy between dust colour temperature and spectral index. Comparison of methods for estimating the beta(T) relation

Sub-millimetre dust emission provides information on the physics of interstellar clouds and dust. Noise can produce anticorrelation between the colour temperature T_C and the spectral index beta. This must be separated from the intrinsic beta(T) relation of dust. We compare methods for the analysis of the beta(T) relation. We examine sub-millimetre observations simulated as simple modified black body emission or using 3D radiative transfer modelling. In addition to chi^2 fitting, we examine the results of the SIMEX method, basic Bayesian model, hierarchical models, and one method that explicitly assumes a functional form for beta(T). All methods exhibit some bias. Bayesian method shows significantly lower bias than direct chi^2 fits. The same is true for hierarchical models that also result in a smaller scatter in the temperature and spectral index values. However, significant bias was observed in cases with high noise levels. Beta and T estimates of the hierarchical model are biased towards the relation determined by the data with the highest S/N ratio. This can alter the recovered beta(T) function. With the method where we explicitly assume a functional form for the beta(T) relation, the bias is similar to the Bayesian method. In the case of an actual Herschel field, all methods agree, showing some degree of anticorrelation between T and beta. The Bayesian method and the hierarchical models can both reduce the noise-induced parameter correlations. However, all methods can exhibit non-negligible bias. This is particularly true for hierarchical models and observations of varying signal-to-noise ratios and must be taken into account when interpreting the results.

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Estimation of high-resolution dust column density maps. Comparison of modified black-body fits and radiative transfer modelling

Sub-millimetre dust emission is often used to derive the column density N of dense interstellar clouds. The observations consist of data at several wavelengths but of variable resolution. We examine two procedures that been proposed for the estimation of high resolution N maps. Method A uses a low-resolution temperature map combined with higher resolution intensity data while Method B combines N estimates from different wavelength ranges. Our aim is to determine the accuracy of the methods relative to the true column densities and the estimates obtainable with radiative transfer modelling. We use magnetohydrodynamical (MHD) simulations and radiative transfer calculations to simulate sub-millimetre observations at the wavelengths of the Herschel Space Observatory. The observations are analysed with the methods and the results compared to the true values and to the results from radiative transfer modelling of observations. Both methods A and B give relatively reliable column density estimates at the resolution of 250um data while also making use of the longer wavelengths. For high signal-to-noise data, the results of Method B are better correlated with the true column density, while Method A is less sensitive to noise. When the cloud has internal heating, results of Method B are consistent with those that would be obtained with high-resolution data. Because of line-of-sight temperature variations, these underestimate the true column density and, because of a favourable cancellation of errors, Method A can sometimes give more correct values. Radiative transfer modelling, even with very simple 3D cloud models, can provide better results. However, the complexity of the models required for improvements increases rapidly with the complexity and opacity of the clouds.

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