Maps of the Number of H i Clouds along the Line of Sight at High Galactic Latitude

Panopoulou, G. V.; Lenz, Daniel

doi:10.3847/1538-4357/abb6f5

Cited by 26 publications

(56 citation statements)

References 117 publications

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“…In order to identify LOSs where the LOS frequency decorrelation effect is most likely to be significant, we use two types of information that can be extracted from HI observations. The first A16, page 2 of 16 is the number of clouds along the LOS, obtained via a decomposition of HI spectra by Panopoulou & Lenz (2020). We use publicly available 1 results from this analysis to find sky pixels for which multiple clouds contribute to the dust emission signal in intensity.…”

Section: Data Setsmentioning

confidence: 99%

“…If multiple components of dust lie along the LOS, and have different bulk kinematic properties, then the emission spectrum of the HI line will show multiple peaks at different velocities with respect to the observer. This property of HI emission was used by Panopoulou & Lenz (2020) to measure the number of clouds along the LOS. The authors developed a method to identify the number of peaks in HI spectra and applied it to data from the HI4PI survey (HI4PI Collaboration 2016) over the high-Galactic-latitude sky.…”

Section: Hi Velocity Components Along the Line Of Sightmentioning

confidence: 99%

“…The analyzed area covers the parts of the sky where HI column density is well correlated with far-infrared dust emission, as defined by Lenz et al (2017). Panopoulou & Lenz (2020) decomposed each HI spectrum into a set of Gaussian components. The Gaussian parameters were grouped within HEALPix pixels of N side = 128 (termed 'superpixels'), in order to construct a probability distribution function (PDF) of the centroid velocity of the components.…”

Section: Hi Velocity Components Along the Line Of Sightmentioning

confidence: 99%

“…In sightlines with multiple components, not all components will contribute equally to the column density (and similarly to the total dust intensity). Panopoulou & Lenz (2020) introduced a measure of the number of clouds per LOS that takes into account the column densities of clouds, defined as:…”

Section: Hi Velocity Components Along the Line Of Sightmentioning

confidence: 99%

“…Specifically, we use HI emission data to identify sightlines that are potentially most susceptible to this effect. We combine information on the discrete number of HI clouds on each sightline (Panopoulou & Lenz 2020) with an estimate of the magnetic field orientation in each cloud inferred from the morphology of linear HI structures (Clark & Hensley 2019). This entirely HI-based sample selection is "agnostic" to the Planck dust polarization data.…”

Section: Introductionmentioning

confidence: 99%

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Evidence for line-of-sight frequency decorrelation of polarized dust emission in Planck data

Pelgrims

Clark

Hensley

et al. 2021

A&A

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If a single line of sight (LOS) intercepts multiple dust clouds with different spectral energy distributions and magnetic field orientations, then the frequency scaling of each of the Stokes Q and U parameters of the thermal dust emission may be different, a phenomenon we refer to as LOS frequency decorrelation. We present first evidence for LOS frequency decorrelation in Planck data using independent measurements of neutral-hydrogen (HI) emission to probe the 3D structure of the magnetized interstellar medium (ISM). We use HI-based measurements of the number of clouds per LOS and the magnetic field orientation in each cloud to select two sets of sightlines: (i) a target sample of pixels that are likely to exhibit LOS frequency decorrelation and (ii) a control sample of pixels that lack complex LOS structure. We test the null hypothesis that LOS frequency decorrelation is not detectable in Planck 353 and 217 GHz polarization data at high Galactic latitudes. We reject the null hypothesis at high significance based on data that show that the combined effect of polarization angle variation with frequency and depolarization are detected in the target sample. This detection is robust against the choice of cosmic microwave background (CMB) map and map-making pipeline. The observed change in polarization angle due to LOS frequency decorrelation is detectable above the Planck noise level. The probability that the detected effect is due to noise alone ranges from 5 × 10−2 to 4 × 10−7, depending on the CMB subtraction algorithm and treatment of residual systematic errors; correcting for residual systematic errors consistently increases the significance of the effect. Within the target sample, the LOS decorrelation effect is stronger for sightlines with more misaligned magnetic fields, as expected. With our sample, we estimate that an intrinsic variation of ~15% in the ratio of 353 to 217 GHz polarized emission between clouds is sufficient to reproduce the measured effect. Our finding underlines the importance of ongoing studies to map the three-dimensional structure of the magnetized and dusty ISM that could ultimately help component separation methods to account for frequency decorrelation effects in CMB polarization studies.

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Section: Data Setsmentioning

confidence: 99%

Section: Hi Velocity Components Along the Line Of Sightmentioning

confidence: 99%

Section: Hi Velocity Components Along the Line Of Sightmentioning

confidence: 99%

Section: Hi Velocity Components Along the Line Of Sightmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Evidence for line-of-sight frequency decorrelation of polarized dust emission in Planck data

Pelgrims

Clark

Hensley

et al. 2021

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Local H I filaments driven by a small-scale dynamo

Kalberla¹,

Kerp²,

Haud

2021

A&A

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Context. H I filaments are closely related to dusty magnetized structures that are observable in the far infrared (FIR). Recently it was proposed that the coherence of oriented H I structures in velocity traces the line of sight magnetic field tangling. Aims. We study the velocity-dependent coherence between FIR emission at 857 GHz and H I on angular scales of 18′. Methods. We use HI4PI H I data and Planck FIR data and apply the Hessian operator to extract filaments. For coherence, we require that local orientation angles θ in the FIR at 857 GHz along the filaments be correlated with the H I. Results. We find some correlation for H I column densities at |vLSR| < 50 km s−1, but a tight agreement between FIR and H I orientation angles θ exists only in narrow velocity intervals of 1 km s−1. Accordingly, we assign velocities to FIR filaments. Along the line of sight these H I structures show a high degree of the local alignment with θ, as well as in velocity space. Interpreting these aligned structures in analogy to the polarization of dust emission defines an H I polarization. We observe polarization fractions of up to 80%, with averages of 30%. Orientation angles θ along the filaments, projected perpendicular to the line of sight, are fluctuating systematically and allow a characteristic distribution of filament curvatures to be determined. Conclusions. Local H I and FIR filaments identified by the Hessian analysis are coherent structures with well-defined radial velocities. H I structures are also organized along the line of sight with a high degree of coherence. The observed bending of these structures in the plane of the sky is consistent with models for magnetic field curvatures induced by a Galactic small-scale turbulent dynamo.

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Starlight-polarization-based tomography of the magnetized ISM: PASIPHAE’s line-of-sight inversion method

Pelgrims

Panopoulou

Tassis

et al. 2023

A&A

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We present the first Bayesian method for tomographic decomposition of the plane-of-sky orientation of the magnetic field with the use of stellar polarimetry and distance. This standalone tomographic inversion method presents an important step forward in reconstructing the magnetized interstellar medium (ISM) in three dimensions within dusty regions. We develop a model in which the polarization signal from the magnetized and dusty ISM is described by thin layers at various distances, a working assumption which should be satisfied in small-angular circular apertures. Our modeling makes it possible to infer the mean polarization (amplitude and orientation) induced by individual dusty clouds and to account for the turbulence-induced scatter in a generic way. We present a likelihood function that explicitly accounts for uncertainties in polarization and parallax. We develop a framework for reconstructing the magnetized ISM through the maximization of the log-likelihood using a nested sampling method. We test our Bayesian inversion method on mock data, representative of the high Galactic latitude sky, taking into account realistic uncertainties from Gaia and as expected for the optical polarization survey Pasiphae according to the currently planned observing strategy. We demonstrate that our method is effective at recovering the cloud properties as soon as the polarization induced by a cloud to its background stars is higher than ∼ 0.1% for the adopted survey exposure time and level of systematic uncertainty. The larger the induced polarization is, the better the method's performance, and the lower the number of required stars. Our method makes it possible to recover not only the mean polarization properties but also to characterize the intrinsic scatter, thus creating new ways to characterize ISM turbulence and the magnetic field strength. Finally, we apply our method to an existing data set of starlight polarization with known line-of-sight decomposition, demonstrating agreement with previous results and an improved quantification of uncertainties in cloud properties.

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Maps of the Number of H i Clouds along the Line of Sight at High Galactic Latitude

Cited by 26 publications

References 117 publications

Evidence for line-of-sight frequency decorrelation of polarized dust emission in Planck data

Evidence for line-of-sight frequency decorrelation of polarized dust emission in Planck data

Local H I filaments driven by a small-scale dynamo

Starlight-polarization-based tomography of the magnetized ISM: PASIPHAE’s line-of-sight inversion method

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Maps of the Number of H i Clouds along the Line of Sight at High Galactic Latitude

Cited by 26 publications

References 117 publications

Evidence for line-of-sight frequency decorrelation of polarized dust emission in Planck data

Evidence for line-of-sight frequency decorrelation of polarized dust emission in Planck data

Local H I filaments driven by a small-scale dynamo

Starlight-polarization-based tomography of the magnetized ISM: PASIPHAE’s line-of-sight inversion method

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Product

Resources

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Local H I filaments driven by a small-scale dynamo