LoTSS Jellyfish Galaxies. IV. Enhanced Star Formation on the Leading Half of Cluster Galaxies and Gas Compression in IC3949

Our parent sample of jellyfish galaxies is taken from Roberts et al. (2021b). From a large sample of star-forming galaxies in low-redshift clusters (z < 0.05), Roberts et al. (2021b) identify 95 jellyfish galaxies on the basis of one-sided radio continuum tails observed by LOFAR at 144 MHz as part of the LOFAR Two Meter Sky Survey (LoTSS; Shimwell et al. 2022). We match these 95 jellyfish galaxies against the final data release from the MaNGA survey (SDSS Data Release 17, DR17; Abdurro'uf et al. 2022) that includes public IFS for ∼10,000 galaxies in the main galaxy sample. Of the 95 jellyfish galaxies from Roberts et al. (2021b), 30 have MaNGA IFS. Sixteen of these 30 galaxies are part of the Coma Cluster, 10/30 are part of the A2197/A2199 system, 2/30 are part of the NGC6338 group, 1/30 is part of the NGC5098 group, and 1/30 is part of A2593. In Figure 1 (left-hand column) we show optical plus LOFAR overlay images for the galaxies that make up our final jellyfish galaxy sample.

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For these 30 galaxies we isolate star-forming spaxels according to emission line diagnostic diagrams (Baldwin et al. 1981). We first mask all spaxels with signal-to-noise ratio (S/N) < 3 in Hα, Hβ, [Oiii], [Nii], or [Sii]; we then mask all spaxels with EW(Hα) < 3 Å; and, finally, mask any spaxels that are not classified as "star-forming" according to both the [Oiii]/Hβ versus [Nii]/Hα and [Oiii]/Hβ versus [Sii]/Hα dividing lines from Kewley et al. (2001, 2006). We note that this does not exclude spaxels that would be classified as "composite" between the Kewley et al. (2001) and Kauffmann et al. (2003) dividing lines on the [Oiii]/Hβ versus [Nii]/Hα diagram. We reran our analysis with a stricter selection for star-forming spaxels where we only included spaxels that had EW(Hα) > 6 Å and added a requirement that spaxels are classified as "star-forming" according to the Kauffmann et al. (2003) dividing line on the [Oiii]/Hβ versus [Nii]/Hα diagram. This did not qualitatively change any of the conclusions from this work: therefore we opt for the slightly looser criteria which includes composite spaxels to avoid overmasking weakly star-forming regions. This star-forming spaxel selection results in one galaxy being completely removed from our sample (MaNGA plate-ifu: 11943-6104) as all of the detected spaxels for this galaxy are classified as Seyfert active galactic nucleus (AGN); however, the remaining 29 galaxies show emission dominated by star formation with a minority of spaxels masked due to this selection. With non-star-forming spaxels masked we produce resolved SFR surface density maps, Σ_SFR, for each jellyfish galaxy based on the MaNGA Hα emission line maps. We correct the Hα line fluxes for dust extinction using the Balmer decrement determined for each spaxel (see the Appendix of Vogt et al. 2013 for a detailed description). The SFR for each spaxel is calculated from the dust-corrected Hα luminosity using the calibration from Kennicutt (1998a). We then convert the SFR to a surface density in M_⊙ yr⁻¹ kpc⁻² using the MaNGA spaxel dimensions of 05 × 05 and the luminosity distance to the host cluster. We obtain resolved stellar mass maps from the Pipe3D Value Added Catalogs (Sánchez et al. 2016a, 2016b; Lacerda et al. 2022). We use the stellar mass maps with dust corrections and apply the "dezonification" map to each stellar mass map in order to reduce the signature of the Voronoi binning (see Cid Fernandes et al. 2013 for details). After multiplying by the dezonification map we follow Sánchez et al. (2016b) and smooth each stellar mass map with a Gaussian kernel with a FWHM equal to the MaNGA r-band FWHM (∼2''–3'', depending on the galaxy). Again, we convert the stellar mass maps to surface densities, Σ_⋆, with units of M_⊙ kpc⁻². All spaxels with S/N < 3 as well as all spaxels with Σ_⋆ < 10⁷ M_⊙ kpc⁻² in the stellar mass maps are masked. Both SFR and stellar mass surface density maps are inclination corrected using the optical axis ratio (b/a) for each galaxy taken from the NASA-Sloan Atlas. Finally, we create resolved maps of specific star formation rate (sSFR = SFR/M_⋆) by taking the ratio of the SFR and stellar mass surface density maps. In Figure 1 (right-hand three columns) we show the SFR surface density, stellar mass surface density, and sSFR maps for each jellyfish galaxy.

We also compile a sample of matched control galaxies that are not members of massive groups or galaxy clusters. Comparing our results for jellyfish galaxies to the same properties measured for our control sample is critical for isolating the influence of the cluster environment, and in turn the process of RPS. We note that even galaxies in that are not in massive groups or clusters (e.g., galaxy pairs) can experience "environmental-like" effects on their star formation (e.g., Moon et al. 2019; Yang et al. 2022). It is possible that cases such as this exist in our control sample, but the implicit assumption that we are making is that these types of perturbations will be significantly smaller than those experienced by satellite galaxies in massive clusters. To generate our matched control sample we first consider all star-forming galaxies (i.e., sSFR > 10⁻¹¹ yr⁻¹) in the Data Release 17 (DR17) MaNGA release (Abdurro'uf et al. 2022). We then restrict this to only those galaxies that are isolated (i.e., part of a single-member "group") or part of a group with halo mass, M_H , <10¹³ M_⊙ in the Lim et al. (2017) SDSS group/cluster catalog. This ensures that our control sample does not contain galaxies in clusters or massive groups. We also restrict this sample to only contain galaxies that are detected by LOFAR at 144 MHz as part of the LoTSS Data Release 2 source catalog (Williams et al. 2019; Shimwell et al. 2022). This matches the selection criteria for the LOFAR jellyfish galaxy sample, which by definition are detected at 144 MHz.

At this point we have an "unmatched" control sample of ∼800 star-forming MaNGA galaxies in low-density environments that have significant radio continuum emission at 144 MHz. We now match this sample to the stellar mass and redshift distribution of the jellyfish galaxy sample. By matching in stellar mass and redshift we ensure that the comparison between the jellyfish and control samples is unbiased in terms of differences in galaxy mass and physical resolution. For each jellyfish galaxy we find all galaxies in the unmatched control sample where:

• 1.  
  the control galaxy and jellyfish galaxy stellar masses are consistent within their respective 1σ error ranges; and
• 2.  
  the difference between the control galaxy and jellyfish galaxy redshifts is given by Δz < 0.005.

This gives a list of matches for each jellyfish galaxy, some jellyfish galaxies having ∼5 matched galaxies and some having tens of matched galaxies. To ensure that all jellyfish galaxies have equal weight in the final matched control sample, we randomly draw five matched control galaxies for each jellyfish galaxy, giving a final control sample of 145 galaxies that are well matched to the jellyfish galaxy sample. The redshift and stellar mass distributions for both the jellyfish and control galaxy samples are shown in Figure 2.

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In Troncoso-Iribarren et al. (2020) the "leading" and "trailing" halves of galaxies are defined relative to the three-dimensional velocity vector for each galaxy, such that the plane that passes through the galaxy center and is normal to the velocity vector divides the LH and TH. This is a natural choice as ram pressure is maximal along the direction of motion, but the three-dimensional velocity vector is not an observable quantity. We approximate this by using the direction of the observed radio continuum tail as a proxy for the direction of motion for each of the jellyfish galaxies in our sample. Tail directions are taken from Roberts et al. (2021b) and range between 0° and 360°, where 0° = west and 90° = north. We assume that the radio continuum tail points opposite to the direction of motion, and thus we observationally divide the LH and TH by the line passing through the optical galaxy center that is normal to the projected tail direction. For each galaxy in our control sample we also define a LH and TH by dividing the galaxy with a line through the optical galaxy center at a random orientation. This division is not physically motivated but it does quantify the level of intrinsic anisotropy expected between two halves of a "normal" galaxy not part of an overdense environment. This allows us to isolate the impact of environment for our jellyfish sample by determining whether anisotropies between the LH and TH of jellyfish galaxies systematically differ from those found by randomly dividing galaxies in our control sample.

With a LH and TH defined for each galaxy in our jellyfish and control samples, we now define two quantities, the sSFR excess and the SFR excess, to measure the degree of star formation anisotropy between these two galaxy halves. We calculate these quantities as follows:

$$\begin{eqnarray}&&\mathrm{sSFR}\ \mathrm{excess}={\mathrm{log}}_{10}\left(\,{\overline{\mathrm{sSFR}}}_{\mathrm{LH}}/{\overline{\mathrm{sSFR}}}_{\mathrm{TH}}\,\right),\end{eqnarray} \tag{ 1 }$$

and

$$\begin{eqnarray}&&\mathrm{SFR}\ \mathrm{excess}={\mathrm{log}}_{10}\left(\,{\overline{\mathrm{SFR}}}_{\mathrm{LH}}/{\overline{\mathrm{SFR}}}_{\mathrm{TH}}\,\right),\end{eqnarray} \tag{ 2 }$$

where ${\overline{\mathrm{sSFR}}}_{\mathrm{LH}}$ and ${\overline{\mathrm{sSFR}}}_{\mathrm{TH}}$ are the average sSFRs measured over the LH and TH of the galaxy, and ${\overline{\mathrm{SFR}}}_{\mathrm{LH}}$ and ${\overline{\mathrm{SFR}}}_{\mathrm{TH}}$ are defined analogously for SFR. Positive values of the sSFR and SFR excess indicate enhanced star formation on the LH relative to the TH and vice versa for sSFR/SFR excess < 0. We list the measured sSFR excess and SFR excess values for each jellyfish galaxy in Table 1. There are six jellyfish galaxies in our sample (MaNGA plate-ifus: 8931-3703, 8442-1901, 12673-6101, 11942-103, 9869-12702, and 9869-9102) where only ∼2 resolution elements (MaNGA r-band FWHM) span across the Σ_SFR map along the axis of the observed radio tail. These are primarily edge-on galaxies with stripped tails that are roughly aligned with the galaxy minor axis. For these galaxies, the distinction between LH and TH is only marginally resolved, and thus the measurement of sSFR/SFR excess is likely less reliable than for the rest of the sample. We have tested removing these galaxies from the sample and rerunning our analysis, and we confirm that the qualitative results from this work do not change based on the inclusion or exclusion of these six galaxies. The median sSFR/SFR excess for the jellyfish sample is 0.07/0.11 when including these poorly resolved cases and 0.06/0.10 when excluding them. We opt to include these galaxies in our analysis but highlight them with open markers in Figures 3, 5, and 6, and with asterisks in Table 1.

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In Figure 3(a) we show the sSFR excess and in Figure 3(b) we show the SFR excess, both plotted against integrated galaxy stellar mass for galaxies in our jellyfish sample. We also show the median sSFR and SFR excess for our control sample (dashed line) as well as the interquartile range (shaded regions). Jellyfish galaxies are skewed to positive values for both the sSFR and SFR excess; this is clear both in the upper panels of Figure 3 as well as lower panels, where we show the mean/median (solid/dashed vertical lines) values and the full distributions of sSFR and SFR excess for both the jellyfish and the control samples. For the control sample the sSFR and SFR excess is centered on zero, which is expected given that we are defining the LH and TH along a random axis for these galaxies. There is statistical evidence that the distributions of the sSFR excess and SFR excess for jellyfish galaxies and galaxies in the control sample are distinct. According to the two-sample Anderson–Darling test (Scholz & Stephens 1987), this difference is significant at >99.9% significance for both sSFR and SFR. While the distributions of sSFR and SFR excess for jellyfish galaxies are skewed to positive values and are consistent with enhanced star formation on the LH, not all jellyfish galaxies show this signature. A ram-pressure-induced burst of star formation is likely a transient phenomenon and thus we do not expect to observe all jellyfish galaxies in this state. It is also possible that for some galaxies there is a clear star formation excess signal in three dimensions that is being obscured by projection effects. Furthermore, the degree to which the ISM is perturbed by ram pressure will depend on a given galaxy's orbital history and position within its host cluster. We explore whether jellyfish galaxies with enhanced star formation on the LH occupy a distinct part of projected phase space relative to jellyfish galaxies without strong SFR anisotropies, but do not find any significant difference. If we divide our sample into two subsamples split at the median value of the SFR excess (the results are similar for sSFR excess) then the median and interquartile range of the clustercentric radius (i.e., R/R₁₈₀ as given in Roberts et al. 2021b) distribution is 0.41 [0.22, 0.53] for galaxies with large excesses and 0.37 [0.28, 0.48] for galaxies with small excesses. Doing the same for the velocity offset (i.e., cΔz/σ as given in Roberts et al. 2021b) gives 0.69 [0.45, 1.95] for galaxies with large excesses and 0.75 [0.40, 1.55] for galaxies with small excesses. According to the two-sample Anderson–Darling test there is no evidence for a difference between the phase-space distributions for galaxies with large and small star formation excesses, but we note that with our modest sample size of 29 jellyfish galaxies it is difficult to subdivide the sample in such a way while maintaining statistical power.

Troncoso-Iribarren et al. (2020) compute an analogous quantity to our SFR excess for the simulated group/cluster galaxies in their work (Equation (8) in Troncoso-Iribarren et al. 2020). In these simulations the SFR for each gas particle is set according to the observed Kennicutt–Schmidt (KS) relation, with a metallicity-dependent density threshold to prevent the unrealistic case of hot, low-density gas-forming stars. We note that these SFR excesses are measured in a relative sense within individual galaxies, and this adds some degree of robustness in terms of uncertainties surrounding the specifics of star formation prescriptions between observations and simulations. In their simulated data, Troncoso-Iribarren et al. (2020) find enhanced star formation on the LH with a typical SFR excess of ∼0.05. They show that their simulated group/cluster galaxies have enhanced gas pressures on their leading sides (both relative to the trailing sides and relative to EAGLE main-sequence galaxies). This increased pressure feeds into their SFR prescription (Equation (1) in Troncoso-Iribarren et al. 2020) and thus this SFR excess is attributed to this gas compression on the leading side. We find a typical SFR excess of ∼0.1 for the observed jellyfish galaxies in this work, slightly larger than is found by Troncoso-Iribarren et al. (2020). This contrast may be explained by differences in the sample definitions. In particular, Troncoso-Iribarren et al. (2020) include all star-forming group/cluster galaxies from the simulation box in their analysis, whereas we are restricted to only star-forming galaxies with an observed radio continuum tail. Our jellyfish galaxy sample is likely skewed toward stronger RPS in order to produce an observable tail, which in turn may drive a stronger enhancement of star formation on the LH. Furthermore, our jellyfish sample is drawn from massive clusters (M_halo > 10¹⁴ M_⊙), whereas the galaxy sample in Troncoso-Iribarren et al. (2020) has a substantial number of galaxies hosted by group-mass systems (M_halo < 10¹⁴ M_⊙). Roberts et al. (2021a) and Roberts et al. (2022b) have shown that global SFR enhancements in galaxies undergoing RPS are stronger in massive clusters and more marginal in group-mass systems. All said, the qualitative results between this work and Troncoso-Iribarren et al. (2020) are in good agreement, as both works find evidence for enhanced star formation on the LH of galaxies likely due to RPS.

In the previous section we show that our sample of jellyfish galaxies display evidence for enhanced star formation on their LH, opposite to the direction of the RPS tail. We define the LH and TH of our galaxies according to the direction of observed radio continuum tails, though an alternative approach to quantify star formation anisotropy in galaxies is with a dividing line that maximizes the sSFR or SFR excess. In the case of ram-pressure-induced star formation from gas compression, these two definitions should be similar. In other words, if ram pressure is driving enhanced star formation, then the dividing line that maximizes the sSFR or SFR excess should be roughly normal to the observed tail direction (modulo projection effects). Maximizing this star formation anisotropy is also suggested by Troncoso-Iribarren et al. (2020) as a viable method for determining the LH and TH of group/cluster galaxies observationally, which may be particularly useful in cases where a clear RPS tail is not observed.

In this section we test how closely our definition of the LH and TH (based on the observed tail directions) corresponds to the dividing line that maximizes the sSFR and SFR excess for each galaxy. For each jellyfish galaxy we first find two maximal dividing lines: one to maximize the sSFR excess and one to maximize the SFR excess. All dividing lines must pass through the optical galaxy center and are otherwise defined by an orientation, α, where α ∈ [0°, 360°). An orientation of 0° corresponds to a horizontal line along the W–E axis with the northern side of the galaxy as the LH, and an orientation of 90° corresponds to a vertical line along the N–S axis with the eastern side of the galaxy as the LH. From the orientation that maximizes the sSFR and SFR excess, ${\alpha }_{\max ,\ \mathrm{sSFR}}$ and ${\alpha }_{\max ,\ \mathrm{SFR}}$, we then infer a "tail direction" that is normal to this angle and can be compared to the observed tail direction. In Figure 4 we show these different tail direction definitions graphically, and in Figure 5 we plot the sSFR/SFR excess versus the difference between the observed tail direction and the direction that is normal to the line maximizing the sSFR excess (Δθ_sSFR) and the SFR excess (Δθ_SFR). A value of 0° corresponds to the case where the tail direction inferred from maximizing the sSFR/SFR excess is identical to the observed tail direction, for 90° the two are perpendicular, and for 180° the two point in opposite directions. In Figure 5 there is a clear anticorrelation between both the sSFR excess and Δθ_sSFR as well as the SFR excess and Δθ_SFR. This shows that jellyfish galaxies with large sSFR/SFR excess also have observed tail directions that roughly maximize the difference in star formation between the LH and TH, in agreement with expectations from RPS. Jellyfish galaxies with sSFR/SFR excess ∼ 0 have values of Δθ_sSFR and Δθ_SFR that span the full range between 0° and 180° and thus do no appear to be tied to the observed tail direction. Finally, there is a hint that the few galaxies with large negative sSFR/SFR excesses tend to have Δθ_sSFR/SFR near 180°. Even in these cases the orientation that maximizes the sSFR/SFR excess seems to be connected to the tail direction. This may be an indicator of star formation occurring in the stripped gas being transported along the tail direction; we also briefly discuss this possibility in the next Section 3.3. If strong star formation anistropies are observed in cluster galaxies, these results suggest that it may be possible to infer a RPS tail direction by maximizing this anisotropy (as also suggested by Troncoso-Iribarren et al. 2020). That said, such an exercise should always be taken with significant caution as there are physical mechanisms in cluster environments beyond RPS that can produce asymmetric star formation.

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In Sections 3.1 and 3.2 we have shown that jellyfish galaxies have enhanced sSFRs on their LH and that the dividing line between the LH and TH inferred from observed tail directions is close to the dividing line that maximizes the star formation anisotropy for the majority of jellyfish galaxies in our sample. As a final test to confirm enhanced star formation on the LH of these galaxies we explore the position of the sSFR peak for each galaxy with respect to the observed radio continuum tail. We use the peak of sSFR instead of SFR since most galaxies will have a SFR peak near the galaxy center due to the high concentration of mass, whereas by using sSFR we are probing a relative increase in SFR modulated by the local stellar mass surface density.

We identify the position of the pixel with the highest sSFR, ${p}_{\max }\,=\,({x}_{\max },{y}_{\max })$, and compare the location of p_max to the observed direction of the stripped tail. When determining p_max we filter the sSFR map with a 3 × 3 uniform kernel such that each pixel is averaged with its eight nearest neighbors. This is to ensure that our measurement is robust against random pixel-to-pixel varations. We quantify the orientation between the two with an angle such that p_max on the LH of the galaxy will have an orientation between 0° and 180° (with 90° is directly opposite to the tail direction) and p_max on the TH will have an orientation between 180° and 360° (with 270° being directly in line with the tail). For brevity we will refer to this orientation as Δφ. We also record the radial offset of p_max with respect to the galaxy center in units of the galaxy effective radius, which we denote as r_max. In Figure 6 we plot Δφ (azimuthal axis) and r_max (radial axis) on a polar plot for each jellyfish galaxy. The distribution of points is asymmetric, with the majority of jellyfish galaxies having 0 < Δφ < 180, demonstrating that the regions of peak star formation (per unit stellar mass) are systematically found on the LH. The two galaxies in Figure 6 with sSFR peaks that are on the TH and significantly offset from the galaxy center are GMP2599 (MaNGA plate-ifu: 9862-9101) and MRK0881 (MaNGA plate-ifu: 8604-9102). These sSFR peaks may be indicative of ongoing star formation along the stripped tail for these galaxies, as has been seen previously for some jellyfish galaxies (e.g., Gavazzi et al. 2001; Yagi et al. 2010; Poggianti et al. 2017; Boselli et al. 2018; Lee et al. 2022b; Hess et al. 2022). The MaNGA field of view (FOV) is too small to directly probe these stripped tails; however, for both galaxies the Hα emission fills the MaNGA FOV toward the direction of the observed radio tail, suggesting that there may be extraplanar star formation along the tail beyond the MaNGA coverage.

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In this section we analyze the bulk molecular gas distribution in IC3949, as traced by CO J = 1 − 0 emission. We use CO products that were reduced and imaged by the ALMaQUEST team. Here we provide a description of the key components of this data processing; for a more detailed outline of the ALMaQUEST reduction procedure, please see Lin et al. (2020). IC3949 was observed in the C43-2 configuration of the ALMA 12 m array with an on-source integration time of ∼22 min. The data were calibrated using Common Astronomy Software Applications (CASA) v5.4 (McMullin et al. 2007) and the standard ALMA pipeline. The continuum was subtracted from the visibilities and CLEAN was used to clean the continuum-subtracted data down to 1σ. A Briggs' weighting with a robust parameter of 0.5 was used for the imaging. In order to match the pixel scale and the typical resolution of MaNGA data products, a user-specified pixel size of 0and a restoring beam size of 2FWHM were set. The resulting spectral line cube for CO J = 1 − 0 has a velocity channel width of ∼11 km s⁻¹ and an rms of 0.6 mJy beam⁻¹. A CO moment-zero map for IC3949 was produced with immoments in CASA including only velocity channels where CO emission is present. We estimate the rms noise from source-free regions in the CO moment-zero map and any pixels with S/N < 3 are masked. The CO moment-zero map is converted to an H₂ surface density by adopting a constant conversion factor of ${\alpha }_{\mathrm{CO}}=4.35\,{M}_{\odot }\,{(K\,{km}\,{s}^{-1}\,{{pc}}^{-2})}^{-1}$ (e.g., Bolatto et al. 2013); this map is shown in Figure 7(b). In Figure 7 we also show maps of H₂ gas fraction and depletion time that are obtained by dividing the H₂ surface density map by the stellar mass and SFR surface density maps, respectively (see Figure 1 for the Σ_⋆ and Σ_SFR maps for IC3949). In each panel we show an arrow denoting the projected orientation of the observed radio continuum tail and an open circle highlighting the region of enhanced star formation on the LH.

Relative to the galaxy center, the molecular gas disk of IC3949 is clearly asymmetric, being truncated on the LH of the galaxy (opposite to the tail direction) and more extended along the TH. This can likely be attributed to RPS which is transporting gas from the leading side of IC3949 "downstream" along the direction of the stripped tail. This ALMA observation does not detect any molecular gas in the stripped tail itself, as has been seen previously for some jellyfish galaxies (Jáchym et al. 2014, 2017, 2019; Moretti et al. 2020a, 2020b). Though it is worth noting that the observational setup was designed for observing molecular gas in the disk, therefore the primary beam response is substantially lower in the tail region beyond the optical extent of the galaxy. Forthcoming CO J = 2 − 1 observations of IC3949 from the ALMA-JELLY survey (PI: Jáchym; 2021.1.01616.L) will place stronger constraints on the presence, or lack thereof, of molecular gas in the RPS tail of IC3949. There is molecular gas asymmetry in the disk of IC3949, not just in terms of extent but also in terms of H₂ surface density. The H₂ surface density surface density is larger on the leading side of the disk (at fixed galactocentric radius), coincident with the enhanced star formation seen on the LH. This enhanced CO emission is subtle in the moment-zero map (Figure 7(a)) but more clearly visible in both the H₂ gas fraction map (Figure 7(b)) and the position–velocity diagram (PVD) shown in Figure 8. This enhanced H₂ surface density is consistent with a framework where ram pressure compresses gas on the leading side of galaxies, in turn catalyzing increased star formation (e.g., Gavazzi et al. 2001; Cramer et al. 2020; Boselli et al. 2021; Cramer et al. 2021; Roberts et al. 2022a). The PVD also shows a faint collection of extraplanar gas located at an offset of ∼10'' along the trailing side of the galaxy. This gas is detached from the CO rotation curve and is potentially indicative of a plume of molecular gas being directly stripped from the disk of IC3949.

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The depletion time is not constant across the disk of IC3949 (see Figure 7(c)) but instead is longest at the galaxy center and decreases radially outwards, ranging between 1 Gyr and 11 Gyr. Previous studies have found a mixture of enhanced or suppressed depletion times in the centers of late-type galaxies, with the origin of these variations still being debated (e.g., Utomo et al. 2017; Colombo et al. 2018; Chown et al. 2019). Utomo et al. (2017) find, on average, shorter central gas depletion times in the EDGE-CALIFA sample of galaxies and argue that gas compression from a higher central stellar potential may shorten the depletion time. In contrast to this, Chown et al. (2019) find that it is primarily barred galaxies in the EDGE-CALIFA sample that have shorter central depletion times, while unbarred galaxies appear to have longer depletion times relative to their disks. In the center of IC3949, star formation appears suppressed relative to the molecular gas content, despite appearing to have a higher gas surface density. It is unclear what drives this suppression, but one explanation could be turbulence (e.g., Salas et al. 2021) that is potentially connected to the ongoing RPS. The spaxels within the galaxy center of IC3949 are classified as "composite" according to the resolved Baldwin, Phillips, & Terlevich diagram from MaNGA, thus it is possible that low-level AGN activity is contributing to the Hα flux in this region. This, however, will not resolve the difference between the central depletion time relative to the rest of the galaxy as this would actually imply that we are overestimating the central SFR and thus underestimating the depletion time. Finally, it is important to note that there is some evidence that α_CO is lower in galaxy centers (e.g., Sandstrom et al. 2013), which in turn would decrease the observed central depletion time. Over the region of enhanced star formation on the LH of IC3949 (circular aperture shown in Figure 7) the average depletion time is 2.7 Gyr, identical to the median value over the whole galaxy. Thus the enhanced star formation does not result from a high star formation efficiency (SFE) but instead an increase in molecular gas that is in line with the resolved Kennicutt–Schmidt (rKS; Schmidt 1959; Kennicutt 1998b) relation for IC3949.

For a subset of ALMaQUEST galaxies, including IC3949, follow-up observations of the J = 1 − 0 transitions for the dense gas molecular tracers HCN and HCO⁺ were obtained in ALMA Cycle 7. HCN and HCO⁺ have critical densities of ∼10⁵ cm⁻³ and ∼5 × 10⁴ cm⁻³ (Shirley 2015), respectively, compared to ∼10³ cm⁻³ for CO, and thus trace a denser component of the ISM. Here we describe and present the imaging of the HCN and HCO⁺ lines for IC3949. A full analysis of the five ALMaQUEST galaxies with dense gas observations will be presented in a forthcoming paper (L. Lin et al. 2022, in preparation).

Dense gas observations at 88.631 GHz (PI: Li; 2019.1.01178.S) were carried out with ALMA in Cycle 7 using the Band 3 receiver and C43-2 configuration. These observations cover the full FOV of the CO J = 1 − 0 observations described in the previous section. The spectral setup includes one line targeting HCN J = 1 − 0 and three low-resolution spectral windows for the continuum. The line spectral window has a bandwidth of ∼930 MHz (3200 km s⁻¹), with a native channel width of ∼2 km s⁻¹, and is sufficiently wide to also include the HCO⁺ J = 1 − 0 line (89.189 GHz). The data were processed by the standard pipeline in CASA 5.6. Continuum is subtracted from the data in the visibility domain. The task tclean was employed for deconvolution with a Briggs' robustness parameter of 0.5. We adopted a user-specified image center, pixel size (05), and restoring beam size (25) to match the image grid and the spatial resolution of the MaNGA images. The restoring beam size is similar to that of the native beam size reported by the tclean (27 × 24). The HCN and HCO⁺ lines were imaged separately, and to increase the S/N the spectral channels are binned to ∼50 km s⁻¹. The rms noise of the spectral line data cubes are 0.13 mJy beam⁻¹ and 0.14 mJy beam⁻¹ for HCN and HCO⁺, respectively. The integrated intensity maps of HCN and HCO⁺ were constructed using the task immoments in CASA by integrating emission from a velocity range set by hand to match the observed line profile without any clipping in signal.

In Figure 9 we show integrated intensity (moment-zero) maps of HCN and HCO⁺ for IC3949. We also show the outline of the detected CO emission from Figure 7(a) with the solid contour and the galaxy center with the cross. Emission in the moment-zero maps (for both HCN and HCO⁺) is restricted to the galaxy center and the LH of IC3949, with no significant emission detected on the TH. The fact that emission from these dense gas tracers is only detected along the leading side is additional evidence for gas compression from ram pressure, as was argued for in Section 4.1. There are also morphological differences between HCN and HCO⁺ in Figure 9. HCN emission peaks at the galaxy center and decreases radially toward the leading edge of the galaxy, whereas HCO⁺ emission is bimodal with a peak at the galaxy center and a second peak that is spatially coincident with the region of enhanced star formation on the LH. We also measure the intensity ratio between dense gas tracers and CO, I_dense/I_CO, where ${I}_{\mathrm{dense}}={I}_{\mathrm{HCN}}$ or ${I}_{\mathrm{dense}}={I}_{{\mathrm{HCO}}^{+}}$, and the HCN-to-HCO⁺ ratio (${I}_{\mathrm{HCN}}/{I}_{{\mathrm{HCO}}^{+}}$) in three rectangular apertures that span the detected dense gas emission in the moment-zero maps (see Figure 9). These apertures are oriented along the major axis of IC3949, are spaced in intervals of 25, i.e., one beam's width, and cover the area between the galaxy center (d_maj = 0'' in Figure 10) and the region of enhanced star formation on the leading edge of IC3949 (d_maj = 5'' in Figure 10). We color the data points in Figure 10 by the average sSFR in each aperture in order to further emphasize the increase in star formation toward the leading edge. As shown in Figure 10(a), the dense gas fraction traced by HCO⁺ increases monotonically toward the region of enhanced star formation on the leading side, whereas the dense gas fraction traced by HCN remains constant across all three apertures. These differences between HCN and HCO⁺ are further illustrated in Figure 10(b), where we plot the HCN-to-HCO⁺ ratio measured in each of the three apertures. This ratio is largest at the galaxy center and decreases monotonically toward the region of enhanced star formation on the leading side, where HCO⁺ becomes brighter than HCN and the ratio falls below unity. Previous works have found that low HCN-HCO⁺ ratios are typically associated with starburst regions in galaxies (e.g., Kohno et al. 2001; Meijerink et al. 2007; Privon et al. 2015; Bemis & Wilson 2019; Butterworth et al. 2022; Zhou et al. 2022). This is likely due to an increase in HCO⁺ abundance driven by the enhanced UV radiation fields and cosmic ray ionization expected in regions of strong star formation (e.g., Krips et al. 2008; Meijerink et al. 2011; Nayana et al. 2020). Our resolved observations of the HCN-to-HCO⁺ ratio in IC3949 supports such a picture as the region of enhanced star formation on the leading side is characterized by a particularly low HCN-to-HCO⁺ ratio. Though we also note that HCO⁺ has a lower critical density than HCN (e.g., Shirley 2015), thus the HCN-HCO⁺ ratio may be decreasing away from the galaxy center, in part, due to a decreasing average density of molecular gas.

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In this work we present clear evidence for an enhancement of star formation on the LH of galaxies undergoing RPS. This star formation enhancement is consistent with predictions from hydrodynamical simulations and is likely driven by gas compression via ram pressure. Below we highlight the main scientific conclusions from this work.

• 1.  
  Jellyfish galaxies show enhanced SFRs and sSFRs on the LH of the galaxy, opposite to the direction of the stripped tail (Figure 3).
• 2.  
  The dividing line that maximizes the star formation anisotropy for each jellyfish galaxy is systematically aligned with the dividing line between the leading and trailing halves of the galaxy as inferred from the observed tail direction (Figure 5).
• 3.  
  For the jellyfish galaxies in our sample, the locations of the maximum sSFR are preferentially found on the LH of the galaxy (Figure 6).
• 4.  
  The jellyfish galaxy IC3949 has an area of enhanced molecular gas surface density on the leading side of the galaxy that is spatially coincident with the observed star formation enhancement. This region has a typical H₂ depletion time (as traced by CO) compared to the rest of the galaxy, suggesting that the enhancement star formation is driven by an increase in molecular gas and not an abnormally high SFE (Figures 7 and 8).
• 5.  
  In IC3949, emission from dense molecular gas tracers HCN and HCO⁺ is only detected between the galaxy center and the leading edge, reinforcing the increase in ISM density on the leading side (Figure 9).

Recent and forthcoming ALMA large programs such as VERTICO (Brown et al. 2021) and ALMA-JELLY (PI: Jáchym; 2021.1.01616.L) will significantly increase the number of galaxies undergoing RPS with resolved CO observations and thus shed further light on the relationship between molecular gas and star formation in such systems. We find evidence for ram pressure compression of the ISM in IC3949, but it is still not clear whether this is a generic feature of all galaxies undergoing RPS. These large CO surveys will take a large step toward addressing this open question and will also provide a parent sample from which compelling targets can be selected for follow-up observations of dense gas tracers and/or CO at higher spatial resolution. For a more complete understanding of the impact of RPS on star formation and molecular gas, probing the ISM at cloud scales in jellyfish galaxies should be a priority, moving forward.