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The formation and differentiation of the crust of Mars in the first tens of millions of years after its accretion can only be deciphered from incredibly limited records. The martian breccia NWA 7034 and its paired stones is one of them. This meteorite contains the oldest martian igneous material ever dated: ~4.5 Ga old. However, its source and geological context have so far remained unknown. Here, we show that the meteorite was ejected 5–10 Ma ago from the north-east of the Terra Cimmeria—Sirenum province, in the southern hemisphere of Mars. More specifically, the breccia belongs to the ejecta deposits of the Khujirt crater formed 1.5 Ga ago, and it was ejected as a result of the formation of the Karratha crater 5–10 Ma ago. Our findings demonstrate that the Terra Cimmeria—Sirenum province is a relic of the differentiated primordial martian crust, formed shortly after the accretion of the planet, and that it constitutes a unique record of early crustal processes. This province is an ideal landing site for future missions aiming to unravel the first tens of millions of years of the history of Mars and, by extension, of all terrestrial planets, including the Earth. A new study pinpoints the ejection site of the 4.5-Ga-old Martian breccia NWA 7034 and paired stones to an area northeast of the Terra 679 Cimmeria–Sirenium province.

The lunar cratering record is used to constrain the bombardment history of both the Earth and the Moon. However, it is suggested from different perspectives, including impact crater dating, asteroid dynamics, lunar samples, impact basin-forming simulations, and lunar evolution modelling, that the Moon could be missing evidence of its earliest cratering record. Here we report that impact basins formed during the lunar magma ocean solidification should have produced different crater morphologies in comparison to later epochs. A low viscosity layer, mimicking a melt layer, between the crust and mantle could cause the entire impact basin size range to be susceptible to immediate and extreme crustal relaxation forming almost unidentifiable topographic and crustal thickness signatures. Lunar basins formed while the lunar magma ocean was still solidifying may escape detection, which is agreeing with studies that suggest a higher impact flux than previously thought in the earliest epoch of Earth-Moon evolution. Lunar impact basins formed during the magma ocean solidification should have formed almost unidentifiable topographic and crustal thickness signatures, thus may escape detection. This result allows for a higher impact flux in the earliest epoch of Earth-Moon evolution.

The only martian rock samples on Earth are meteorites ejected from the surface of Mars by asteroid impacts. The locations and geological contexts of the launch sites are currently unknown. Determining the impact locations is essential to unravel the relations between the evolution of the martian interior and its surface. Here we adapt a Crater Detection Algorithm that compile a database of 90 million impact craters, allowing to determine the potential launch position of these meteorites through the observation of secondary crater fields. We show that Tooting and 09-000015 craters, both located in the Tharsis volcanic province, are the most likely source of the depleted shergottites ejected 1.1 million year ago. This implies that a major thermal anomaly deeply rooted in the mantle under Tharsis was active over most of the geological history of the planet, and has sampled a depleted mantle, that has retained until recently geochemical signatures of Mars’ early history. The ejection sites of the martian meteorites are still unknown. Here, the authors build a database of 90 million craters and show that Tharsis region is the most likely source of depleted shergottites ejected 1.1 Ma ago, thus confirming that some portions of the mantle were recently anomalously hot.

Prior to becoming chondritic meteorites, primordial solids were a poorly consolidated mix of mm-scale igneous inclusions (chondrules) and high-porosity sub-μm dust (matrix). We used high-resolution numerical simulations to track the effect of impact-induced compaction on these materials. Here we show that impact velocities as low as 1.5 km s −1 were capable of heating the matrix to >1,000 K, with pressure–temperature varying by >10 GPa and >1,000 K over ~100 μm. Chondrules were unaffected, acting as heat-sinks: matrix temperature excursions were brief. As impact-induced compaction was a primary and ubiquitous process, our new understanding of its effects requires that key aspects of the chondrite record be re-evaluated: palaeomagnetism, petrography and variability in shock level across meteorite groups. Our data suggest a lithification mechanism for meteorites, and provide a ‘speed limit’ constraint on major compressive impacts that is inconsistent with recent models of solar system orbital architecture that require an early, rapid phase of main-belt collisional evolution. Collisions between primordial planetesimals led to the formation of our asteroids and meteorites. Here, the authors use modelling to explore the compaction of planetsimals, tracking how pressure, temperature and porosity may have varied during the impacts, helping interpret early Solar System processes.

Impact craters are the most common feature on the Moon’s surface. Crater size–frequency distributions provide critical insight into the timing of geological events, surface erosion rates, and impact fluxes. The impact crater size–frequency follows a power law (meter‐sized craters are a few orders of magnitude more numerous than kilometric ones), making it tedious to manually measure all the craters within an area to the smallest sizes. We can bridge this gap by using a machine learning algorithm. We adapted a Crater Detection Algorithm to work on the highest resolution lunar image data set (Lunar Reconnaissance Orbiter‐Narrow‐Angle Camera [NAC] images). We describe the retraining and application of the detection model to preprocessed NAC images and discussed the accuracy of the resulting crater detections. We evaluated the model by assessing the results across six NAC images, each covering a different lunar area at differing lighting conditions. We present the model’s average true positive rate for small impact craters (down to 20 m in diameter) is 93%. The model does display a 15% overestimation in calculated crater diameters. The presented crater detection model shows acceptable performance on NAC images with incidence angles ranging between ∼50° and ∼70° and can be applied to many lunar sites independent to morphology. Plain Language Summary The Moon’s surface is covered in impact craters and recording their spatial density gives researchers the ability to study the geological evolution of our satellite. Analyzing craters helps in determining the physical properties of planetary surfaces and how/if impact rates change over time. These analyses rely on recording spatial densities for numerous surfaces, which has been achieved for craters >1–2 km on the Moon. Manually counting the smaller craters, which number in the hundreds of millions, is a daunting task. We adapted a Crater Detection Algorithm and applied it to the highest resolution lunar imagery data set. We describe our method for gathering, reformatting, and detecting craters across lunar images down to 20 m in diameter. The detection model performance was quantitatively evaluated across six different regions, each with different terrain and lighting conditions. Comparison between manually mapped craters and detections from our model allows us to conclude that the model has an acceptable performance in detecting fresh to moderately degraded craters of all sizes, down to 20 m in diameter, when compared to other studies. Automated crater detection complements manual counting methods and aids in unlocking secrets of the Moon’s surface. Key Points Adapted and retrained a Crater Detection Algorithm (using YOLOv3) to work on high‐resolution Lunar Reconnaissance Orbiter‐Narrow‐Angle Camera (NAC) images Developed a workflow for georeferencing and detecting craters down to 10 pixels in diameter across multiple overlapping NAC images Evaluation reveals acceptable performance in detecting craters on diverse terrains, across images with 50–70° incidence angles

Impact craters on solar system bodies are used to determine the relative ages of surfaces. The smaller the limiting primary crater size, the higher the spatial resolution in surface/resurfacing age dating. A manually counted database (Robbins & Hynek, 2012, https://doi.org/10.1029/2011JE003966) of >384,000 craters on Mars >1 km in diameter exists. But because crater size scales as a power law, the number of impact craters in the size range 10 m to 1 km is in the tens of millions, a number making precise analysis of local variations of age, over an entire surface, impossible to perform by manual counting. To decode this crater size population at a planetary scale, we developed an automated Crater Detection Algorithm based on the You Only Look Once v3 object detection system. The algorithm was trained by annotating images of the controlled Thermal Emission Imaging System daytime infrared data set. This training data set contains 7,048 craters that the algorithm used as a learning benchmark. The results were validated against the manually counted database as the ground truth data set. We applied our algorithm to the Thermal Emission Imaging System global mosaic between ±65° of latitude, returning a true positive detection rate of 91% and a diameter estimation error (~15%) consistent with typical manual count variation. Importantly, although a number of automated crater counting algorithms have been published, for the first time we demonstrate that automatic counting can be routinely used to derive robust surface ages. Plain Language Summary Crater counting is the traditional method of determining the surface ages of planets throughout the solar system. This method, up to now, has used data that have been painstakingly counted by hand. The current published database for Mars contains hundreds of thousands of craters for diameters larger than 1 km. If we can count craters smaller than this, we will be able to target specific areas of interest to date. But the rate of impacts on planetary surfaces follows a power law such that the number of small (less than 1 km) craters is exponentially higher than the number of large craters. To count these requires an automated tool. Here we show that we have developed such a tool. We have validated the results against current manual databases. Importantly, and for the first time, we demonstrate that an automated crater counting tool can deliver geologically meaningful ages. Key Points We built a library of 7,048 craters to train a Crater Detection Algorithm (CDA) that we developed based on a neural network architecture We applied our algorithm to the Mars global THEMIS mosaic, generating results comparable to manual counting We applied the CDA to higher‐resolution images generating model ages indistinguishable (within error) from literature ages

Determining when an impact crater formed is a complex and tedious task. However, this knowledge is crucial to understanding the geological history of planetary bodies and, more specifically, gives information on erosion rate measurements, meteorite ejection location, impact flux evolution and the loss of a magnetic field. The derivation of an individual crater's age is currently performed through manual counting. Because crater size scales as a power law, this method is limited to small (and/or young) surface areas and, in the case of the derivation of crater emplacement age, to a small set of impact craters. Here, we used a Crater Detection Algorithm, specifically retrained to detect small impact craters on large‐ and high‐resolution imagery data set to solve this issue. We applied it to a global, 5 m/pixel resolution mosaic of Mars. Here, we test the use of this data set to date 10 large impact craters. We developed a cluster analysis tool in order to distinguish potential secondary crater clusters from the primary crater population. We then use this, filtered, crater population to date each large impact crater and evaluate our results against literature ages. We found that automated counting filtered through clustering analysis produced similar model ages to manual counts. This technique can now be expanded to much wider crater dating surveys, and by extension to any other kind of Martian surface. We anticipate that this new tool will considerably expand our knowledge of the geological events that have shaped the surface of Mars, their timing and duration. Plain Language Summary The age of an impact crater on a planetary surface is a crucial constraint in determining erosion rate, the crater source of Martian meteorites and the impact cratering flux evolution. This kind of measurement requires the counting of many impact craters superposed on the ejecta blanket of the considered crater and is therefore limited by human capability. To solve this issue, we adapted an automatic tool to detect small impact craters on the surface of Mars. We also developed an automatic approach to identify and remove clusters of small likely secondary craters detected by our algorithm. We assume these clusters of craters are formed by fragments ejected by an impact that formed a primary crater and need to be removed from crater densities used for age derivations. We applied our technique on 10 large Martian impact craters whose the formation age has been derived using manual counts and reported in the literature. We compared these ages to ours, derived from automatic count and automatic secondary craters filtering. Our results are consistent and indistinguishable from an age inferred from a manual count. For the first time, we demonstrate that an automated approach can deliver geologically meaningful model ages. Key Points Automatic detection of small craters on ejecta blanket of 10 large Martian craters Identification of secondary craters through cluster analysis Model ages from our semi‐automatic approach are similar from manual counts

Accurate modelling of the interaction between the atmosphere and an incoming bolide is a complex task, but crucial to determining the fraction of small asteroids that actually hit the Earth's surface. Most semi-analytical approaches have simplified the problem by considering the impactor as a strengthless liquid-like object ('pancake' models), but recently a more realistic model has been developed that calculates motion, aerodynamic loading and ablation for each separate particle or fragment in a disrupted impactor. Here we report the results of a large number of simulations in which we use both models to develop a statistical picture of atmosphere-bolide interaction for iron and stony objects with initial diameters up to approximately 1 km. We show that the separated-fragments model predicts the total atmospheric disruption of much larger stony bodies than previously thought. In addition, our data set of >1,000 simulated impacts, combined with the known pre-atmospheric flux of asteroids with diameters less than 1 km, elucidates the flux of small bolides at the Earth's surface. We estimate that bodies >220 m in diameter will impact every 170,000 years.

Impact glass associated with 11 elongate depressions in the Pampean Plain of Argentina, north of the city of Rio Cuarto, was suggested to be proximal ejecta related to a highly oblique impact event. We have identified about 400 additional elongate features in the area that indicate an aeolian, rather than an impact, origin. We have also dated fragments of glass found at the Río Cuarto depressions; the age is similar to that of glass recovered 800 kilometers to the southeast. This material may be tektite glass from an impact event around 0.48 million years ago, representing a new tektite strewn field.