Juno Spacecraft Sky Map Products

Note: 2025 updated products have replaced preliminary 2024 versions.

From Anderson et al. (2025):

Juno's 6 microwave radiometers observed the sky at a decreased data rate during its ~5-year flight to Jupiter. We present 6 nearly all-sky maps made from that data. The maps are labeled by their receiver number, R1 through R6. Starting with receiver R1, the central frequencies are 600 MHz, 1.248 GHz, 2.597 GHz, 5.215 GHz, 10.004 GHz, and 21.9 GHz. Fractional bandwidths are approximately 4% for each receiver. The beams are approximately Gaussian. Their Full-Width-at-Half-Maxima are 19.7, 19.8, 11.9, 11.9, 11.9, and 10.7 degrees for R1 through R6. Maps are made in HEALPix format at Nside=64. Long time-scale noise drifts are removed with a MADAM-like algorithm. For maps R1 and R2, long time-scale gain drifts are also removed with an NPIPE-like extension to the MADAM formalism. The monopole level of the maps is not determined from the Juno radiometers, because the on-board absolute calibration is only accurate to +/-6 Kelvin. We choose to set the zero-level of the maps to match the ARCADE2 fit to the CMB + Radio Background.

In addition to the maps, we release hitmaps, diagonal thermal variance maps, estimated pointing error maps, simulated polarization leakage maps, simulated pixelization error correction maps, and estimates of the correlated map-space errors due to the slowly drifting gain and noise. At small angular scales, the statistical errors are well approximated by the thermal variance maps alone. However, correlated errors are larger than the diagonal thermal noise at large angular scales, particularly for the lower frequency maps (see figure 10 of the associated publication). For maps R1 and R2, systematic pixelization errors are significant near the Galactic plane. These can be approximately removed by adding the simulated pixelization error corrections.

Unconvolved Maps

The raw Juno brightness temperature maps in units of Kelvin. Pixels that are exactly zero have no sky coverage.

Convolved Maps

Juno brightness temperature maps in units of Kelvin, convolved to a common 21 degree Gaussian FWHM resolution. Pixels that are exactly zero have no sky coverage.

Hit Maps

Hitmaps for all the Juno maps.

Diagonal Thermal Noise Variance

Estimates of the diagonal thermal noise variance for each of the Juno maps, in units of Kelvin². These estimates are simply the average variance in the time-stream residuals divided by the hitmaps.

Pointing Errors

Estimates of the random pointing errors for the Juno maps. Except for a few pixels with very few hits, the pointing errors are very small.

Simulated Polarization Leakage

Estimates of the contamination to the Juno maps from polarization leakage. Made by simulating the polarized sky and viewing it with the Juno scan strategy and the measured Juno polarization leakage patterns.

Pixelization Noise Corrections

Estimates of the pixelization noise correction at Nside=64, made by viewing a Juno-beam-convolved PySM map with the Juno scan strategy. Pixelization noise is caused by the Juno scans having non-uniform sampling within each pixel. Adding these corrections to the raw Nside=64 maps will remove most of the pixelization noise.

Correlation Noise

An SVD of the estimated correlated covariance due to slow gain and offset drifts. Saved as an hdf5 file.

For R1 and R2, the MADAM gain and noise offsets are both solved for, and their errors are therefore correlated. Consequently, their effects are combined. The R1 and R2 files each contain 2 datasets. The 'singular_values' are in units of Kelvin². The 'singular_vectors' describe the map-space correlation shapes. An estimate of the correlated portion of the map-space covariance matrix can be computed as:
vectors*singular_values*vectors^T.

For R3 through R6, the MADAM noise offsets are solved for, but not the gain offsets. Gain errors are assumed to be uncorrelated with the noise offset errors. Thus, these files contain 4 datasets: 'offset_singular_values', 'offset_singular_vectors', 'gain_singular_values', and 'gain_singular_vectors'. All the singular values are in units of Kelvin². An estimate of the correlated portion of the map-space covariance matrix can be computed as:
offset_vectors*offset_singular_values*offset_vectors^T + gain_vectors*gain_singular_values*gain_vectors^T.

Additional Information:

The Radio and Microwave Sky as Seen by Juno on its Mission to Jupiter, Anderson et al. (2025) (ARXIV preprint 2405.08388)