Stuart E. Harper

We describe a time-domain technique for separating 1/ f gain fluctuations and continuum signal for a total power spectrometer, such as the CO Mapping Array Project (COMAP) Pathfinder instrument. The 1/ f gain fluctuations of such a system are expected to be common-mode across frequency channels. If the instrument’s system temperature is not constant across channels, a continuum signal exhibits a frequency dependence different from that of common-mode gain fluctuations. Our technique leverages this difference to fit a three-parameter frequency model to each time sample in the time-domain data, separating gain and continuum. We show that this technique can be applied to the COMAP Pathfinder instrument, which exhibits a series of temporally stable resonant noise spikes that effectively act as calibrators, breaking the gain degeneracy with continuum signals. Using both simulations and observations of Jupiter, we explore the effect of a 1/ f prior for the gain model. We show that the model is capable of cleanly separating Jupiter, a bright continuum source, from the gain fluctuations in the scan. The technique has two applications to COMAP. For the COMAP observations performing line intensity mapping (LIM), the technique better suppresses atmospheric fluctuations and foregrounds than the COMAP LIM pipeline. For the Galactic COMAP observations, which map Galactic continuum signals, the technique can suppress 1/ f gain fluctuations while retaining all continuum signals. This is demonstrated by the latest COMAP observations of λ-Orionis, for which our method produces far cleaner maps than a destriper alone, typically reducing the noise power by a factor of 7 on beam scales and up to 15 on larger scales.

Anomalous Microwave Emission (AME) is a diffuse microwave component thought to arise from spinning dust grains, though it remains poorly understood. We analyzed AME in 144 Galactic clouds by combining low-frequency maps from S-PASS (2.3 GHz), C-BASS (4.76 GHz), and QUIJOTE (10–20 GHz) with 21 ancillary maps. Using aperture photometry and parametric spectral energy distribution (SED) fitting via Markov chain Monte Carlo methods without informative priors, we measured AME emissivity, peak frequency, and spectral width. We achieved peak frequency constraints nearly three times tighter than previous work and identify 83 new AME sources. The AME spectra are generally broader than predicted by spinning dust models for a single phase of the interstellar medium, suggesting either multiple spinning dust components along the line of sight or incomplete representation of the grain size distribution in current models. However, the narrowest observed widths match theoretical predictions, supporting the spinning dust hypothesis. The AME amplitude correlates most strongly with the thermal dust peak flux and radiance, showing ∼30% scatter and sublinear scaling, which suggests reduced AME efficiency in regions with brighter thermal dust emission. The AME peak frequency increases with thermal dust temperature in a trend current theoretical models do not reproduce, indicating that spinning dust models must incorporate dust evolution and radiative transfer in a self-consistent framework where environmental parameters and grain properties are interdependent. Polycyclic aromatic hydrocarbon tracers correlate with AME emissivity, supporting a physical link to small dust grains. Finally, a log-Gaussian function provides a good empirical description of the AME spectrum across the sample, given current data quality and frequency coverage.

Radio frequency interference (RFI) is emitted from various sources, terrestrial or orbital, and creates a nuisance for ground-based 21-cm experiments. In particular, single-dish observations will be highly susceptible to RFI due to their wide primary beam and sensitivity. This work aimed to simulate the contamination effects from the Radio Navigational Satellite System (RNSS) within the 1100–1350 (MHz) frequency band. The simulation can be divided into two parts: (i) satellite positioning, emission power, and the beam response on the telescope, and (ii) calibration of the satellite signals to data to improve the original model. We utilize previously observed single-dish L-band data from the Meer-Karoo Array Telescope (MeerKAT), which requires special calibration to account for regions contaminated by satellite-based RFI. We find that we can recreate the satellite contamination with high accuracy around its peak frequencies provided the satellite is not too close to the telescope’s pointing direction. The simulation can predict satellite movements and signals for past and future observations, aiding in RFI avoidance and testing novel cleaning methods. The predicted signal sits below the noise in the target cosmology window in the L band (970–1015 MHz) making it difficult to confirm any out-of-band emission from satellites. However, in our simulations, this contamination still overwhelmed the 21-cm auto-power spectrum. Nevertheless, it is possible to detect the signal in cross-correlations after mild foreground cleaning. Whether such out of band contamination does exist will require further characterization of the satellite signals far away from their peak frequencies.

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.

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.

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.

Anomalous Microwave Emission (AME) is an important emission component between 10 and 60 GHz that is not yet fully understood. It seems to be ubiquituous in our Galaxy and is observed at a broad range of angular scales. Here we use the new QUIJOTE-MFI wide survey data at 11, 13, 17 and 19 GHz to constrain the AME in the Galactic plane (|b| < 10^○) on degree scales. We built the spectral energy distribution between 0.408 and 3000 GHz for each of the 5309 0.9^○ pixels in the Galactic plane, and fitted a parametric model by considering five emission components: synchrotron, free-free, AME, thermal dust and CMB anisotropies. We show that not including QUIJOTE-MFI data points leads to the underestimation (up to 50 per cent) of the AME signal in favour of free-free emission. The parameters describing these components are then intercompared, looking for relations that help to understand AME physical processes. We find median values for the AME width, W_AME, and for its peak frequency, ν_AME, respectively of |$0.560^{+0.059}_{-0.050}$| and |$20.7^{+2.0}_{-1.9}$| GHz, slightly in tension with current theoretical models. We find spatial variations throughout the Galactic plane for ν_AME, but only with reduced statistical significance. We report correlations of AME parameters with certain ISM properties, such as that between the AME emissivity (which shows variations with the Galactic longitude) and the interstellar radiation field, and that between the AME peak frequency and dust temperature. Finally, we discuss the implications of our results on the possible molecules responsible for AME.