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The Carbon monOxide Mapping Array Project (COMAP) Pathfinder survey continues to demonstrate the feasibility of line-intensity mapping using high-redshift carbon monoxide (CO) line emission traced at cosmological scales. The latest COMAP Pathfinder power spectrum analysis is based on observations through the end of Season 2, covering the first three years of Pathfinder operations. We use our latest constraints on the CO(1–0) line-intensity power spectrum atz~ 3 to update corresponding constraints on the cosmological clustering of CO line emission and thus the cosmic molecular gas content at a key epoch of galaxy assembly. We first mirror the COMAP Early Science interpretation, considering how Season 2 results translate to limits on the shot noise power of CO fluctuations and the bias of CO emission as a tracer of the underlying dark matter distribution. The COMAP Season 2 results place the most stringent limits on the CO tracer bias to date, at ⟨T b⟩ < 4.8 μK, which translates to a molecular gas density upper limit ofρ_H2< 1.6 × 10⁸M_⊙Mpc⁻³atz~ 3 given additional model assumptions. These limits narrow the model space significantly compared to previous CO line-intensity mapping results while maintaining consistency with small-volume interferometric surveys of resolved line candidates. The results also express a weak preference for CO emission models used to guide fiducial forecasts from COMAP Early Science, including our data-driven priors. We also consider directly constraining a model of the halo–CO connection, and show qualitative hints of capturing the total contribution of faint CO emitters through the improved sensitivity of COMAP data. With continued observations and matching improvements in analysis, the COMAP Pathfinder remains on track for a detection of cosmological clustering of CO emission. 

The CO Mapping Array Project (COMAP) Pathfinder is performing line intensity mapping of CO emission to trace the distribution of unresolved galaxies at redshiftz ∼ 3. We present an improved version of the COMAP data processing pipeline and apply it to the first two Seasons of observations. This analysis improves on the COMAP Early Science (ES) results in several key aspects. On the observational side, all second season scans were made in constant-elevation mode, after noting that the previous Lissajous scans were associated with increased systematic errors; those scans accounted for 50% of the total Season 1 data volume. In addition, all new observations were restricted to an elevation range of 35–65 degrees to minimize sidelobe ground pickup. On the data processing side, more effective data cleaning in both the time and map domain allowed us to eliminate all data-driven power spectrum-based cuts. This increases the overall data retention and reduces the risk of signal subtraction bias. However, due to the increased sensitivity, two new pointing-correlated systematic errors have emerged, and we introduced a new map-domain PCA filter to suppress these errors. Subtracting only five out of 256 PCA modes, we find that the standard deviation of the cleaned maps decreases by 67% on large angular scales, and after applying this filter, the maps appear consistent with instrumental noise. Combining all of these improvements, we find that each hour of raw Season 2 observations yields on average 3.2 times more cleaned data compared to the ES analysis. Combining this with the increase in raw observational hours, the effective amount of data available for high-level analysis is a factor of eight higher than in the ES analysis. The resulting maps have reached an uncertainty of 25–50 μK per voxel, providing by far the strongest constraints on cosmological CO line emission published to date. 

We present updated constraints on the cosmological 3D power spectrum of carbon monoxide CO(1–0) emission in the redshift range 2.4–3.4. The constraints are derived from the two first seasons of Carbon monOxide Mapping Array Project (COMAP) Pathfinder line intensity mapping observations aiming to trace star formation during the epoch of galaxy assembly. These results improve on the previous Early Science results through both increased data volume and an improved data processing methodology. On the methodological side, we now perform cross-correlations between groups of detectors (“feed groups”), as opposed to cross-correlations between single feeds, and this new feed group pseudo power spectrum (FGPXS) is constructed to be more robust against systematic effects. In terms of data volume, the effective mapping speed is significantly increased due to an improved observational strategy as well as a better data selection methodology. The updated spherically and field-averaged FGPXS,C^~(k), is consistent with zero, at a probability-to-exceed of around 34%, with an excess of 2.7σin the most sensitive bin. Our power spectrum estimate is about an order of magnitude more sensitive in our six deepest bins across 0.09 Mpc⁻¹<k< 0.73 Mpc⁻¹, compared to the feed-feed pseudo power spectrum (FPXS) of COMAP ES. Each of these bins individually constrains the CO power spectrum tok P_CO(k) < 2400–4900 μK²Mpc²at 95% confidence. To monitor potential contamination from residual systematic effects, we analyzed a set of 312 difference-map null tests and found that these are consistent with the instrumental noise prediction. In sum, these results provide the strongest direct constraints on the cosmological 3D CO(1–0) power spectrum published to date. 

We present the first degree-scale tomography map of the dusty magnetized interstellar medium (ISM) from stellar polarimetry and distance measurements. We used the RoboPol polarimeter at Skinakas Observatory to conduct a survey of the polarization of starlight in a region of the sky of about four square degrees. We propose a Bayesian method to decompose the stellar-polarization source field along the distance to invert the three-dimensional (3D) volume occupied by the observed stars. We used this method to obtain the first 3D map of the dusty magnetized ISM. Specifically, we produced a tomography map of the orientation of the plane-of-sky component of the magnetic field threading the diffuse, dusty regions responsible for the stellar polarization. For the targeted region centered on Galactic coordinates (l,b) ≈ (103.3°, 22.3°), we identified several ISM clouds. Most of the lines of sight intersect more than one cloud. A very nearby component was detected in the foreground of a dominant component from which most of the polarization signal comes and which we identified as being an intersection of the wall of the Local Bubble and the Cepheus Flare. Farther clouds, with a distance of up to 2 kpc, were similarly detected. Some of them likely correspond to intermediate-velocity clouds seen in HIspectra in this region of the sky. We found that the orientation of the plane-of-sky component of the magnetic field changes along distance for most of the lines of sight. Our study demonstrates that starlight polarization data coupled to distance measures have the power to reveal the great complexity of the dusty magnetized ISM in 3D and, in particular, to provide local measurements of the plane-of-sky component of the magnetic field in dusty regions. This demonstrates that the inversion of large data volumes, as expected from the PASIPHAEsurvey, will provide the necessary means to move forward in the modeling of the Galactic magnetic field and of the dusty magnetized ISM as a contaminant in observations of the cosmic microwave background polarization. 

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 P ASIPHAE 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.