Rays and secondary craters of the Tycho impact event revealed through deep learning.

Introduction: The rays of Tycho crater are prominent features of the lunar nearside [1]. Rays and clusters of secondary craters from Tycho have been mapped as far as Taurus Littrow Valley (TLV), the Apollo 17 landing site, more than 2000 km from the impact crater [2]. It has been suggested that some Tycho ejecta hit the summit of the South Massif and triggered the Light Mantle avalanche in TLV [3,4]. One of the lines of evidence in support of Tycho-ejecta-triggered avalanching is the presence of a cluster of secondary craters on the crest of the South Massif, which is part of a more extended cluster that trends in the general direction of Tycho, spanning from the South Massif across the valley floor of TLV and the North Massif into Littrow crater [4,5] (Figure 1). A competing hypothesis suggests that the Light Mantle was instead triggered by seismic activity associated with the Lee-Lincoln lobate scarp in TLV [6,7]. Definitive evidence for the Light Mantle to be an avalanche either impact-related or seismic-related is yet to be found.

In this work, we aimed to further the understanding of the distribution of the rays and secondary craters of Tycho. Our main purpose is to further inform the discussion about the origin of the Light Mantle.

Methods: We defined a first region of interest (ROI-1) whose longitude and latitude limits are Tycho crater (SW corner) and TLV/Littrow crater (NE corner). This area covers 5,462,043 km² (Figure 2). We used YOLOLens, an object detection model with performance enhanced by super-resolution methodology [8], on Kaguya Terrain Camera (TC) imagery (~7 m/px resolution) to generate a dataset of craters >100 m in diameter (N_craters = 6,867,654) within ROI-1. The TC image resolution has been downsampled to 21 m/pixel. To generate the dataset, it took ~90 hours for pre-processing, ~25 hours for testing, ~6-8 hours for post-processing, and ~4 hours for a second post-processing stage. In ArcGIS Pro, we generated crater density diameter maps [e.g., 8] from the generated crater dataset.

In a narrower area about 150 km wide that extends between Tycho crater and TLV (ROI-2, Figure 2), we complemented the generated dataset with existing databases of lunar impact craters >1-2 km in diameter [9,10,11], and manual editing.

We used the ASCI (Algorithm for the Secondary Crater Identification) cluster analysis method [12] to identify clustered craters (thus potential secondary craters) based on deviations from a calculated random distribution: we defined 11 crater diameter ranges, and computed Voronoï polygon (VP) tesselation over the crater population of each size range; we then plot together the size-frequency distribution (SFD) of VPs of the mapped craters and of 300 simulations of the same crater population with a randomized distribution. The mean and the confidence envelope at ± 1σ of the simulated VPs SFD are computed. The intersection between the VPs SFD from mapped and simulated crater populations at +1σ corresponds to the threshold area below which polygons are described as clustered (thus the craters contained have a likely secondary origin), whereas those above the threshold value are considered random (thus considered primaries) (Figure 3).

Results: The dataset generated contains 6,867,654 craters. We generated RGB composite diameter density maps to visualize the crater distribution by size range (100-150 m; 150-250m; 250-400m) (Figure 2). This initial analysis of the crater population shows well the existence of several rays associated with Tycho crater (bottom half of Figure 2). Further away from Tycho crater (upper part of Figure 2), less prominent rays are still visible. Many of such further rays seem to also point back to the Tycho crater location. In particular, a swarm of such rays appear near to TLV.

The crater cluster analysis reveals that in ROI-1 2,863,257 craters are clustered, corresponding to 42% of the total population (Figure 4a). In ROI-2, the corridor from Tycho to A17 landing site, the analysis reveals that 240,546 are clustered craters (Figure 4b). When accounting for the expected maximum secondary crater size from Tycho (i.e., 5% of Tycho diameter), the number of clustered craters is 239,865, corresponding to 52% of the population in this region.

Discussion and Conclusions: The density maps that we have generated allow us to identify ray segments that would otherwise be hard to detect using optical and spectral imagery alone. In particular, such density maps enable us to identify proximal and distant ray material that could be potentially correlated with Tycho. Maps of clustered craters show that their density decreases with distance from Tycho and that such a crater population (assumed secondaries) is dominated by craters smaller than 1 km. Additionally, the ROI-1 clustered craters map shows local areas of high density around smaller craters.

We identify crater clusters aligned with the Tycho direction in TLV and beyond. This observation supports the previously mapped clustered craters at the Apollo 17 landing site as potentially derived from Tycho secondary impacts. Especially, identified clustered craters on the summit of the South Massif suggests that impacts may have destabilized slope material. However, we cannot comment whether these impacts were energetic enough to trigger the Light Mantle.

An important observation of this work is that potentially secondary craters from Tycho may represent a large percentage of the total crater population. Therefore, their effect on dating lunar surfaces may not be negligeable if not removed.

References: [1] Dundas and McEwen (2007), Icarus, 186(1), 31-40. [2] Lucchitta (1972), USGS Misc. Inv. Map 1-800. 1-800. [3] Muehlberger et al. (1973), USGS PSR, 70042539. [4] Lucchitta (1977), Icarus, 30(1), 80-96. [5] Iqbal et al. (2019), LPSC, Abstract 1005. [6] Schmitt et al (2017), Icarus, 298, 2-33. [7] Magnarini et al. (2023), JGR-Planets, 128(8), e2022JE007726. [8] Lagain et al. (2021a), Nat. Commun., 12, 6352. [9] La Grassa et al. (2023), Remote Sensing, 15(5), 1171. [10] Robbins (2019), JGR-Planets, 124(4), 871-892. [11] Wang et al. (2021), JGR-Planets, 126(9), e2020JE006728. [12] Lagain et al. (2021b), Earth and Space Science, 8(2), e2020EA001598.