Abstract
Star formation primarily occurs in filaments where magnetic fields are expected to be dynamically important. The largest and densest filaments trace the spiral structure within galaxies. Over a dozen of these dense (∼104 cm−3) and long (>10 pc) filaments have been found within the Milky Way, and they are often referred to as "bones." Until now, none of these bones has had its magnetic field resolved and mapped in its entirety. We introduce the SOFIA legacy project FIELDMAPS which has begun mapping ∼10 of these Milky Way bones using the HAWC+ instrument at 214 μm and 182 resolution. Here we present a first result from this survey on the ∼60 pc long bone G47. Contrary to some studies of dense filaments in the Galactic plane, we find that the magnetic field is often not perpendicular to the spine (i.e., the center line of the bone). Fields tend to be perpendicular in the densest areas of active star formation and more parallel or random in other areas. The average field is neither parallel nor perpendicular to the Galactic plane or the bone. The magnetic field strengths along the spine typically vary from ∼20 to ∼100 μG. Magnetic fields tend to be strong enough to suppress collapse along much of the bone, but for areas that are most active in star formation, the fields are notably less able to resist gravitational collapse.
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1. Introduction
High-mass star-forming molecular clouds in spiral galaxies primarily follow the spiral arms. As such, these molecular clouds and their young stellar objects (YSOs) are used to trace spiral structure within the Milky Way (e.g,. Reid et al. 2014). Observations from Spitzer revealed that some of these star-forming clouds are dense (∼104 cm−3), high-mass, and exceptionally elongated (e.g., over 80 pc × 0.5 pc for the Nessie filament; Jackson et al. 2010; Goodman et al. 2014). These filamentary structures are called bones because they delineate the densest parts of arms in a spiral galaxy, just as bones delineate the densest parts of arms in a human skeleton (Goodman et al. 2014). Zucker et al. (2015, 2018) identified 18 bone candidates in the Milky Way using strict criteria: they must be velocity-coherent along the structure, have aspect ratios of >50:1, lie within 20 pc of the Galactic plane, and lie mostly parallel to the Galactic plane. The physical properties of these bones are well characterized, including measurements of lengths, widths, aspect ratios, masses, column densities, dust temperatures, Galactic altitudes, kinematic separation from arms in l − v space, and distances (Zucker et al. 2015, 2018). However, the magnetic field (henceforth, B-field), which can potentially support the clouds against gravitational collapse or guide mass flow, has been mostly unconstrained for bones.
Since nonspherical dust grains align with their short axis along the direction of the B-field, thermal dust emission is polarized perpendicular to the B-field (e.g., Andersson et al. 2015). Consequently, in star-forming clouds, polarimetric observations at (sub)millimeter wavelengths are the most common way to constrain the B-field morphology. Pillai et al. (2015) used the James Clerk Maxwell Telescope (JCMT) SCUBAPOL polarimetric observations at 20'' (0.3 pc) resolution to constrain the B-field morphology of a small, bright section of the bone G11.11–0.12 (also known as the Snake). They found that the field toward this section is perpendicular to the bone, and they estimated the B-field to be ∼300 μG and found a mass-to-flux parameter that is approximately unstable to gravitational collapse. Until this work, these observations were the only published measurements of the field morphology of part of a bone at these scales. However, other studies have probed B-fields in shorter, high-mass filamentary structures, such as G35.39–0.33 (Juvela et al. 2018; Liu et al. 2018), NGC 6334 (Arzoumanian et al. 2021), and G34.43+0.24 (Soam et al. 2019). In general, these studies found that the field is perpendicular to the filament (i.e., elongated dense clouds) in their densest regions and parallel in the less dense regions, such that the parallel fields may feed material into the denser regions of the filament. Moreover, the B-fields may provide some support against collapse. On much smaller scales (1000–10000 au), YSOs themselves can have diverse magnetic field morphologies such as spiral-like, hourglass, and radial (e.g., as seen in the MAGMAR survey; Cortes et al. 2021; Fernández-López et al. 2021; Sanhueza et al. 2021). Focusing on the large-scale observations of filaments, it is important to establish if fields are universally perpendicular to the spines of the main filament and whether the B-field strength is sufficient to help support the filament from collapse. As such, polarization maps of the largest filamentary structures, i.e., the bones, will be one of the best ways to investigate field alignment with filamentary structures. Such observations also constrain the importance of magnetic fields for star formation within spiral arms. Based on polarization observations of face-on spiral galaxies, the inferred large-scale field appears to be along spiral arms (Li & Henning 2011; Beck 2015).
In a legacy project called FIlaments Extremely Long and Dark: a MAgnetic Polarization Survey (FIELDMAPS), we are using the High-resolution Airborne Wideband Camera Plus (HAWC+) polarimeter (Dowell et al. 2010; Harper et al. 2018) on the Stratospheric Observatory for Infrared Astronomy (SOFIA) to map 214 μm polarized dust emission across ∼10 of the 18 known bones. This survey is currently in progress, and this Letter focuses on the early results for the bone G47.06+0.26 (henceforth, G47). The HAWC+ polarimetric maps represent the most detailed probe of the B-field morphology across an entire bone to date. The resolution of Planck is too coarse (∼10'', e.g., Planck Collaboration et al. 2016) to resolve any bones.
The kinematic distance to G47 is 4.4 kpc (Wang et al. 2015), but based on a Bayesian distance calculator from Reid et al. (2016) and its close proximity to the Sagittarius Far Arm, Zucker et al. (2018) determined that the more likely distance is 6.6 kpc, which we adopt. Zucker et al. (2018) examined the physical properties of G47 in detail. The bone has a length of 59 pc and a width of ∼1.6 pc. The median dust temperature is Tdust = 18 K and the median H2 column density is =4.2 × 1021 cm−3. The total mass of the bone is 2.8 × 104 M⊙, and the linear mass density is 483 M⊙ pc−1. Xu et al. (2018) analyzed the kinematics of G47. Among their results, they found that the linear mass density is likely less than the critical mass density to be gravitationally bound, and suggested external pressure may help support the bone from dispersing under turbulence. They also found a velocity gradient across the width (but not the length) of G47, which may be due to the formation and growth of G47. In this Letter we analyze the inferred B-field morphology in G47 as mapped by SOFIA HAWC+.
2. Observations and Ancillary Data
2.1. SOFIA HAWC+ Observations
G47 was observed with SOFIA HAWC+ in Band E, which is centered at 214 μm and provides a resolution of 182 (Harper et al. 2018) or 0.58 pc resolution at a distance of 6.6 kpc. The observations were taken over multiple flights in September 2020 during the OC8E HAWC+ flight series as part of the FIELDMAPS legacy project. The polarimeter's Band E field of view is 42 × 62. The entire bone was mapped by mosaicking together four separate on-the-fly (SCANPOL) maps. The total time on source for the combined observations was 4070 s. We use the Level 4 delivered products from the SOFIA archive. 19 The pixel sizes are 37 × 37, which oversamples the 182 beam. Errors along the bone for the Stokes I, Q, and U maps varied from about 0.5–0.8 mJy pixel−1. From the Stokes parameters, the polarization angle, χ, at each pixel is calculated via
where the arctan2 is the four-quadrant arctangent. The positively biased polarization fraction, Pfrac,b, at each pixel is calculated via
Polarization maps have been de-biased in the pipeline via Pfrac = , where is the error on Pfrac,b (and Pfrac).
SOFIA HAWC+ is not sensitive to the absolute Stokes parameters, so some amount of spatial filtering via on-the-fly maps affects the data. These can lead to artifacts that show up as unrealistically large Pfrac values. However, large Pfrac values (>20%) are outside of the areas of interest in this paper, and thus will not be used for any analysis.
Delivered data were in equatorial coordinates, and we rotated them to Galactic coordinates via the python package reproject (Robitaille et al. 2020) and properly rotating position angles (Appenzeller 1968).
2.2. Ancillary Data
We use the Herschel 250 μm continuum data from Hi-GAL (Molinari et al. 2016), and H2 column density maps () generated by Zucker et al. (2018) from the multi-wavelength Hi-GAL Herschel data. These were subsequently converted to Ngas (i.e., + NHe) by multiplying by the ratio of the mean molecular weight per H2 molecule ( = 2.8) divided by the mean molecular weight per particle (μp = 2.37; Kauffmann et al. 2008). Zucker et al. (2018) also fit the "spine" of the bone—equivalent to a one-pixel-wide representation of its plane-of-the-sky morphology—using the RADFIL algorithm (Zucker & Chen 2018). The resolution of the column density and spine maps are 43'' (∼1.4 pc), and they have pixel sizes of 115 × 115.
We also use 13CO(1–0) data from the Galactic Ring Survey (GRS; Jackson et al. 2006) and NH3(1,1) data from the Radio Ammonia Mid-plane Survey (RAMPS; Hogge et al. 2018), each of which we convert to velocity dispersion maps via Gaussian fits following Hogge et al. (2018). While 13CO(1–0) is detected everywhere along the bone, NH3(1,1) is only detected toward the densest parts. We make a "final velocity dispersion" map, which we will use to estimate B-field strengths, where we use the NH3(1,1) velocity dispersion when it is available for a particular pixel and 13CO(1–0) otherwise. We combine the two together in which we use NH3(1,1) velocity dispersion when it is available for a particular pixel; otherwise, we use 13CO(1–0). In the dense regions where NH3(1,1) is detected, 13CO(1–0) line widths tend to be higher (factor of ∼2) as they are the combination of diffuse and compact emission. Locations where NH3(1,1) is not detected are expected to be more diffuse, and thus 13CO(1–0) widths are mostly accurate in these areas.
Locations of the Class I and II YSOs were taken from Zhang et al. (2019), which were identified via Spitzer observations. Zhang et al. (2019) estimated the survey completeness for Class I YSOs to be a few tenths of a solar mass and for Class II YSOs to be a few solar masses. Class I YSOs are likely at locations of the highest star formation activity along the bone. Xu et al. (2018) identified several more YSO candidates toward G47, but unlike Zhang et al. (2019), they did not use criteria to exclude contaminants such as AGB stars.
3. Magnetic Field Morphology
Figure 1 shows the inferred B-field vectors (i.e., polarization rotated by 90°) with Ngas contours overlaid on a Herschel 250 μm map. Immediately evident is the fact that the B-field vectors are not always perpendicular to the filamentary bone.
To quantify the difference between the position angle (PA; measured counterclockwise from Galactic north) of the B-field and bone's direction, we need to quantify the PA at all locations along G47's spine. We do this by fitting the spine pixels (Section 2.2) with polynomials of different orders in l–b space, and we choose the one with the smallest reduced χ2. Since the fitted spine pixels are oversampled with 115 pixels for a 43'' resolution image, we approximate the degrees of freedom to be ν = (# of fitted points)/cf −(fit order), where the correction factor, cf, is selected so that the sampling is approximately Nyquist, i.e., cf = 0.5 × (43''/115) = 1.87. The best-fit polynomial is of 24th order with a reduced χ2 of 1.9. For each pixel where we detect polarization, we take the difference between the B-field and the bone PAs by matching them to the closest location to the bone's spine. These differences are shown in top panel of Figure 2. Clearly there are locations along G47 where the field is more perpendicular, more parallel, or somewhere in between. For the two largest column density peaks (see Figure 1), the field is mostly perpendicular. In the bottom panel, we convert vectors to a line integral convolution (LIC) map (Cabral & Leedom 1993) to help visualize the field morphology of G47. The LIC morphology agrees with the analysis presented here.
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Standard image High-resolution imageWe also calculate the average angle across the entire bone by summing Stokes Q and U wherever Ngas is larger than 8 × 1021 cm−2 and converting to a polarization angle. This column density cutoff encompasses the dense elongation of the bone. The polarization PA is 67° or an inferred B-field PA of −23°. This angle agrees with the histogram of the B-field angles at locations where Ngas > 8 × 1021 cm−2, which is shown in Figure 3. The PA of G47 is about 32° (Zucker et al. 2018), indicating a difference between the B-field and the angle of the bone of 55°. As such, this angle indicates that fields are neither preferentially parallel or perpendicular to the large-scale elongated structure of the bone. The Galactic field is expected to be along the spiral arms (b = 0°), and the PA of G47 is also not preferentially parallel or perpendicular to this field. These findings are consistent with results from Stephens et al. (2011), which showed that individual star-forming regions are randomly aligned with respect to the Galactic field.
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Standard image High-resolution image4. Magnetic Field Estimates
To estimate the plane-of-sky B-field strength (Bpos) from polarimetric observations, the Davis–Chandrasekhar–Fermi (DCF, Davis 1951; Chandrasekhar & Fermi 1953) technique is often used (also see Ostriker et al. 2001). The DCF technique relies on the assumption that turbulent motions of the gas excite Alfvén waves along the magnetic field lines. Skalidis & Tassis (2021) pointed out that for an interstellar medium that has anisotropic/compressible turbulence, the DCF typically overestimates Bpos, and a more accurate expression for the field strength can be derived. This equation, which we will refer to as the DCFST technique, is
where is the average density, δ vlos is the line-of-sight velocity dispersion, and δ θ is the dispersion in the B-field angles. The classical DCF equation is where (Ostriker et al. 2001). As such, Bpos,DCFST is related to the classical Bpos,DCF via the expressions for the two Bpos expressions are equal at the Alfvénic limit where δ θ = 0.5. Initial analysis indicates that the DCFST technique more accurately estimates the magnetic field strength than the classical DCF technique (Skalidis et al. 2021). However, given the potential shortcomings of the DCFST technique (Li et al. 2022), it is not yet settled that it is indeed more accurate.
We will use this technique in two different ways. First, we calculate the B-field strength across the entire bone by sliding a rectangular box down the spine of the bone and estimating the B-field strength via the DCFST technique for the data in each box. After this, we focus solely on the southwest region, which has the highest column density region and has evidence of a pinched morphology. We fit this morphology using the spheroidal flux-freezing (SFF) model outlined in Myers et al. (2018, 2020).
4.1. Sliding Box Analysis
To estimate how the B-field changes across the bone, we apply the DCFST technique along the bone's spine. We do this by "sliding" a rectangular box down the spine, allowing the box to rotate as the bone's spine change directions in the sky. The center of the box changes one column density/spine pixel at a time (one spine pixel is 11 5 × 115), and the PA of the rectangle is given by the instantaneous slope of the 24th ordered polynomial fit the spine, as discussed in Section 3. The sliding rectangular box has a width, w, of 20 HAWC+ pixels (74'') and a height, h, of 15 HAWC+ pixels (555), equivalent to a width and height of ∼4 and 3 HAWC+ beams, respectively. These dimensions allow for just over 10 independent beams for each box, which is a sufficient amount of data points for calculating the angular dispersion for the DCFST technique. We do not use a larger box since our underlying assumption is a uniform field in each box, and the field becomes less uniform at larger scales, resulting in an overestimate of the angle dispersion.
We create four image cutouts for each rectangular box sliding down the spine: one for the B-field PA map and another for its error map, one for the final velocity dispersion map, and one for the column density map (see Section 2.2 for discussion of the latter two). Appendix A.1 discusses how to determine whether a given pixel of a map is located within the sliding box. To apply the DCFST technique (Equation (3)), we need to estimate , δ vlos, and δ θ for each rectangular box. In the column density cutout, we take the median value as our measure of the mean column density, 20 , and subsequently convert it to a number density and then assuming a cylindrical bone (see Appendix A.2). δ vlos was chosen to be the median value in the final velocity dispersion cutout. From the B-field PA cutout, we calculate the standard deviation of the cutout, δ θobs, and for its error cutout, we take the median value, which we call σθ . The estimated intrinsic angle dispersion, δ θ, can be corrected for observational errors such that . From this we can estimate the plane-of-sky B-field strengths, Bpos. We do not calculate the B-fields at locations with δ θ > 25° (Ostriker et al. 2001) since the turbulence driving the angular dispersion would be super-Alfvénic.
The Bpos map is shown in the left panel of Figure 4, with fields ranging from ∼20 to 160 μG. We then solve for the critical ratio, λ, by taking the ratio of the observed and critical mass to magnetic flux ratios, i.e.,
(Crutcher et al. 2004). λ parameterizes the relative importance of gravity and magnetic fields. For λ > 1, the gas is unstable to gravitational collapse, and when λ < 1, fields can support the gas against collapse.
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Standard image High-resolution imageThe observed mass within the w × h box is Mobserved = μp . The magnetic flux is calculated via Appendix A.3, and we approximate as (McKee & Ostriker 2007). The λ map is shown in the right panel of Figure 4. Note that errors on these values are difficult to quantify given that some input parameters have non-Gaussian errors, and we make assumptions about the geometry of the bone. These values of Bpos and λ reflect our best guesses from the data, and we expect them to be correct within a factor of 2–3. However, since many of the uncertainties in our results are not dominated by random effects but are correlated, for example via the column density or geometrical assumptions, the relative change in these parameters along the bone are likely to be more accurately determined.
Along the spine of the bone, there are two main groups of YSOs: one toward the northeast and one toward the southwest. At both these locations, λ tends to be close to or larger than one, indicating that the areas are typically supercritical to collapse. However, there are several areas along the bone where λ < 1, indicating that B-fields are potentially strong enough to resist local gravitational contraction. For each position along the spine for which we have a measurement of the B-field, Figure 5 shows Bpos and λ as a function of the average number density, . The figure also indicates whether most of the velocity dispersion pixels in the sliding box are based on 13CO or NH3(1,1) since this tracer governs the median velocity dispersion. For densities ≲1700 cm−3 ( cm−2), λ is typically less than 1 (subcritical), while for higher densities (locations of most YSOs), λ is typically higher and often supercritical. Overall, there is little change in Bpos as a function of . However, if we only consider the field strengths where NH3 primarily traces the velocity dispersion, i.e., the black points in Figure 5, the field strength increases slightly as a function of density. Based on the linear regression fit to these points, the slope is 0.022 ±0.006 μG/cm−3. However, given the dispersion of points over a small range of densities, we cannot draw conclusions from this relation.
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Standard image High-resolution imageTogether, these results indicate that the field in some parts of the bone can support against collapse, while in other areas, it is insufficiently strong and thus the gas collapses to form stars. Since YSOs are forming in areas where λ is equal to or less than one, this indicates that either we are underestimating λ or that the high values of λ are more localized to YSOs and would necessitate higher resolution polarimetric observations for proper measurement of the higher λ values.
We note that for the Bpos vs. panel, there are 3 points with higher field strengths (>100 μG) than others. These points are sequentially located next to each other along the spine (see Figure 4). While at these scales G47 has mostly one main velocity component, at this location there appear to be potentially two velocity components that cause the velocity dispersion (and thus the B-field strength) to be overestimated by a factor of ∼2. Nevertheless, our fitting routine finds that a one component is slightly better than two, so we only consider it as one component.
4.2. Spheroidal Flux Freezing
The column density peaks toward the southwest show a pinched B-field morphology. Field lines that are frozen to the gas can create such pinched morphology during collapse. Mestel (1966) and Mestel & Strittmatter (1967) calculated the B-field distribution via nonhomologous spherical collapse assuming flux freezing. Myers et al. (2018, 2020) extended these calculations for a uniform field collapsing to Plummer spheroids. Since the southwest peaks of G47 have two column density peaks, 21 we apply this technique using two Plummer spheroids. We first rotate the delivered G47 data (i.e., in equatorial coordinates) clockwise by 12° to align the column density peaks in the up–down direction. We then fit the column density maps with two p = 2 Plummer spheroids. With the assumption of an initial uniform field and flux freezing, we can use the resulting Plummer spheroids to predict the field morphology by summing the contributions to horizontal and vertical B-field components from each spheroid (see Sections 2 and 3 of Myers et al. 2020). The resulting column density and plane-of-sky B-field lines for the model are shown in the top left panel of Figure 6.
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Standard image High-resolution imageWe overlay the model on top of the HAWC+ polarimetric map (Figure 6, top right panel). We mask out angles where the uncertainty in the angle is >5°. We also mask out angles that differ from the model by more than 25° since these angles are poorly described by the SFF model (i.e., they are outliers that make the distribution non-Gaussian), and these areas may harbor systematic gas flows not included by the model. We calculate the difference in angles between the unmasked inferred field directions and the model (bottom left panel). The dispersion of this distribution is δ θ = 11° 22 , which is ∼75% of the value of δ θ if we did not apply a model. From these data, we can again apply the DCFST technique on the unmasked area. The area is 5.4 pc2 in size and the median velocity dispersion based on NH3 data is δ vlos = 0.8 km s−1. From our model, we find an average number density of 4300 cm−3. 23 From these values, we calculate a mean field in the plane of sky in the unmasked area of Bpos = 56 μG. The peak total field strength for the SOFIA beam is then B0 = 108 μG, assuming (Crutcher et al. 2004) and . The total mass in this region is 1170 M⊙, resulting in a mass-to-flux parameter of λ = 1.7. The sliding box analysis along the spine of this area found comparable B-field strengths in this region of ∼30–75 μG with values of λ between 0.8 and 1.4. We note the sliding box is ∼70% of the size of the unmasked region. These mass-to-flux ratios lie within the range of mass-to-flux ratios in low-mass star-forming cores, according to a recent study (Myers & Basu 2021).
5. Summary
We present the first results of the SOFIA Legacy FIELDMAPS survey, which is mapping the B-field morphology across ∼10 Milky Way bones. This initial study focuses on the cloud G47. We find that:
- 1.The plane-of-sky B-field directions tend to be perpendicular to the projected spine of G47 at the highest mean gas densities of a few thousand cm−3, but at lower densities the B-field structure is complex, including parallel and curving directions.
- 2.The total inferred B-field across the bone is inconsistent with fields that are parallel or perpendicular to the bone. They are also not aligned with the Galactic plane.
- 3.We estimate the field strengths using the DCF technique as updated by Skalidis & Tassis (2021) via two methods: by estimating the B-field within rectangular boxes along G47's spine and by using the SFF technique. We find agreement between the two methods in the area where both were applied. We find field strengths typically vary from ∼20 to ∼100 μG, but may be up to ∼200 μG.
- 4.The spine of G47 has mass to magnetic flux ratios of about 0.2 to 1.7 times the critical value for collapse. Most areas are not critical to collapse. B-fields are thus likely important for support against collapse at these scales in at least some parts of the bones. At the locations of the known YSOs and higher densities, the bone is likely to be more unstable to collapse (i.e., has higher values of λ). We suspect that high values of λ may be more localized with star formation, necessitating higher resolution polarimetric observations toward the YSOs.
B-fields likely play a role in supporting the G47 bone from collapse, and they may help shape the bones in areas of the highest column density. However, since the field directions for lower column densities are more complex, it is unclear how well B-fields shape or guide flows in the more diffuse areas for the bones. While there are considerable uncertainties in our estimates of the column densities and B-fields, the analysis of the larger sample of bones, available from the full FIELDMAPS survey, will allow more extensive testing of these parameters.
Based on observations made with the NASA/DLR Stratospheric Observatory for Infrared Astronomy (SOFIA). SOFIA is jointly operated by the Universities Space Research Association, Inc. (USRA), under NASA contract NNA17BF53C, and the Deutsches SOFIA Institut (DSI) under DLR contract 50 OK 0901 to the University of Stuttgart. Financial support for this work was provided by NASA through award #08_0186 issued by USRA. C.Z. acknowledges that support for this work was provided by NASA through the NASA Hubble Fellowship grant #HST-HF2-51498.001 awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS5-26555. R.J.S. acknowledges funding from an STFC ERF (grant ST/N00485X/1) C.B. gratefully acknowledges support from the National Science Foundation under Award Nos. 1816715 and 2108938. P.S. was partially supported by a Grant-in-Aid for Scientific Research (KAKENHI Number 18H01259) of the Japan Society for the Promotion of Science (JSPS). TGSP gratefully acknowledges support by the NSF under grant No. AST-2009842 and AST-2108989. Z.Y.L. is supported in part by NASA 80NSSC18K1095 and NSF AST-1815784. L.W.L. acknowledges support from NSF AST-1910364. We thank Michael Gordon for his effort in setting up the on-the-fly maps for the FIELDMAPS project and Sachin Shenoy for his work on the data reduction. We thank Miaomiao Zhang for sharing the locations of the YSOs for G47 based on Zhang et al. (2019). We thank Jin-Long Xu for providing us with Purple Mountain Observatory spectral data from Xu et al. (2018) even though we did not use these data for this Letter.
Facility: SOFIA. -
Software: APLpy (Robitaille & Bressert 2012), Astropy (Astropy Collaboration et al. 2013, 2018), MAGNETAR (Soler et al. 2013), Reproject (Robitaille et al. 2020).
Appendix: Rectangle Box Analysis
A.1. Rectangle for Sliding Box
In Section 4.1, a rectangular box was moved across the spine of the bone, and we only considered pixels within this box for the DCFST technique. We want to determine whether or not a pixel at location xc , zc is within a particular rectangle. Consider a rectangle centered at location xc0, zc0 with height h, width w, and angle θ which is measured counterclockwise from up (north), as shown in Figure 7. We define one set of axes with respect to the rectangle, where x is in the direction of the width and z is in the direction of the height. We define a second set of axes in the coordinate system of the map (Galactic north–south, west–east for our case), with the axes centered on the pixel of interest relative to the center of the rectangle, i.e., xc –xc0 and zc –zc0. The transformation between the coordinate system is then
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Standard image High-resolution imagePixel xc , zc will be inside the rectangle if ∣x∣ ≤ w/2 and ∣z∣ ≤ h/2. All pixels meeting these criteria in a given SOFIA map are considered within a particular rectangular box. For our analysis, we used w = 20 pixels = 74'' and h = 15 pixels =555. In our particular case, the chosen pixel size oversamples the beam. However, oversampling does not change the true dispersion, mean, or median, and potentially can estimate these parameters more accurately since at least Nyquist sampling is needed to capture all features of a map.
A.2. Inferring ngas and ρ from Ngas
We want to calculate the volume density for the sliding box to apply the DCFST method. Consider a cylinder (approximation for a bone or filament) with the x-axis along the length of the cylinder, the z-axis perpendicular to the x-axis and in the plane of sky, the y-axis along the line of sight, and a center at (x, y, z) = (0, 0, 0). This box has a height h (Figure 7), which we define to extend from − z1 to z1 so that z1 = h/2. If the observed mean column density within the box, , is calculated, then the mean number density within the box, , is
where is the path length averaged over the heights 0 to z1. Substituting the path length in the above equation, we arrive at the final equation for of
For G47, we take R = 1.6 pc (Zucker et al. 2018) and h = 2z1 = 15 pixels = 555. To convert to the mean mass volume density, , should be multiplied by the mean molecular weight times the hydrogen mass, mH . If is the gas volume density (used in this study), the mean molecular weight per particle, μp = 2.37, should be used; if is the H2 volume density, then the mean molecular weight per H2 molecule, = 2.8, should be used (Kauffmann et al. 2008).
A.3. Magnetic Flux
We draw the sliding rectangular box we use in Figure 8 from the plane-of-sky perspective (left panel) and a three-dimensional view (right panel). The x, y, and z axes are along the bone's short axis, the line of sight (LOS), and the bone's long axis, respectively. The magnetic flux is simply the sum of the flux in each dimension, i.e.,
where Ai and Bi are the areas and B-fields for each axis direction. We measure the Bpos from the DCFST method, and we have a typical B-field direction, θB , which we take to be the median angle in the sliding box analysis. The true B-field direction has an inclination i along the line of sight (Bpos = B for i = 0). For a rectangular box rotated so that the z-axis has a PA of θ, we define Δθ ≡ θB −θ. The solutions for the parameterization for each Ai and Bi are indicated in Figure 8. The formula for Ax accounts for the fact that it is the crosssectional area of a circular cylinder with parallel planar sides. The inclination i is unknown. The true B-field is typically chosen based on a statistical average with inclination such that Bpos/B = π/4 (Crutcher et al. 2004). We choose i to be based on this average so that . For a given bone radius R and w × h rectangular box, we can now calculate Φ from the measurements of Bpos and θB in each box.
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Standard image High-resolution imageFor a given field strength and orientation, the magnetic flux depends on the geometry of the smoothing box since the projected box area in the field direction varies with the relative box dimensions and with the box inclination. As such, the measurements should be placed in the context of the box dimensions and field direction. Nevertheless, for the adopted box dimensions, changing box orientation by 90° changes the derived flux by less than 25%. For a typical box orientation, reducing the adopted box width w by a factor of 2 reduces the derived flux by ∼35%.
Footnotes
- 19
- 20
This removes potential outliers. The percent difference between the mean and median for each box is typically less than 5% and never more than ∼10%
- 21
SOFIA 214 μm and Herschel 160/250 μm maps resolve the top core into two more cores, but for simplicity and to perhaps better reflect the initial collapse, we consider them as one core.
- 22
Observational errors, i.e., σθ , in this area are typically only ∼2° and thus do not significantly affect δ θ.
- 23
The number densities of the SFF analysis are slightly higher than that of the sliding box analysis because the line-of-sight path length for the SFF model is the width of the masked region, which is smaller than the diameter of the bone.