Space News & Blog Articles

Planetary scientists estimate that each year, about 500 meteorites survive the fiery trip through Earth’s atmosphere and fall to our planet’s surface. Most are quite small, and less than 2% of them are ever recovered. While the majority of rocks from space may not be recoverable due to ending up in oceans or remote, inaccessible areas, other meteorite falls are just not witnessed or known about.

But new technology has upped the number known falls in recent years. Doppler radar has detected meteorite falls, as well as all-sky camera networks specifically on the lookout for meteors. Additionally, increased use of dashcams and security cameras have allowed for more serendipitous sightings and data on fireballs and potential meteorite falls.

A team of researchers is now taking advantage of additional technology advances by testing out drones and machine learning for automated searches for small meteorites.  The drones are programmed to fly a grid search pattern in a projected ‘strewn field’ for a recent meteorite fall, taking systematic pictures of the ground over a large survey area. Artificial intelligence is then used to search through the pictures to identify potential meteorites.  

“Those images can be analyzed using a machine learning classifier to identify meteorites in the field among many other features,” said Robert Citron of the University of California, Davis, in a recent paper published in published in Meteoritics & Planetary Science.

Citron and his colleagues have tested their conceptual drone setup several times, mostly recently in the area of a known 2019 meteorite fall near Walker Lake, Nevada. Their proof-of-concept meteorite classifier deploys a combination of “different convolution neural networks to recognize meteorites from images taken by drones in the field,” the team writes.

As usual, the SpaceX South Texas Launch Facility, located near the village of Boca Chica, is the focal point of a lot of attention. Almost two months ago, crews at the facility began working on the first true Super Heavy prototype, the launch stage of SpaceX’s Starship. After six weeks of assembly, SpaceX rolled the Super Heavy Booster 3 (B3) out of the “High Bay” (where it was assembled) and installed it onto the launch pad.

The assembly process began on May 15th, which was assisted by the new Bridge Crane (added to the High Bay back in March) and wrapped up on Thursday, July 1st. The B3 was then moved out and loaded aboard the companies Self-Propelled Modular Transporter (SPMT) and transported down Highway 4 to the launch facility, where it was transferred by another crane onto Test Pad A.

Once it is ready to conduct commercial missions, the Starship and Super Heavy will be the world’s first entirely reusable launch system. As the booster element (aka. first stage) of the system, the Super Heavy stands about 65 meters (215 ft) tall and will be equipped with 32 Raptor engines. This record number of engines (more than any rocket in history) will allow the Super Heavy to produce 72 meganewtons (MN), or 16 million pounds/thrust (lbf).

This is more than twice the thrust generated by the first stage of the Saturn V booster, which NASA used to send the Apollo astronauts to the Moon – 35.1 MN, or 7.89 million lbf. When paired with the Starship – the orbital vehicle element that will rely on 6 Raptors engines – the launch system will be capable of sending 100 metric tons (110 US tons) to Low Earth Orbit (LEO).

According to a statement made by Musk via Twitter, the B3 prototype will be used for ground tests, similar to the ground tests conducted with the Starship (SN) prototypes. This differentiates it from Booster 1 (BN1), the first Super Heavy prototype to complete stacking inside the High Bay, which served as a

The standard model of cosmology is known as the LCDM model. Here, CDM stands for Cold Dark Matter, which makes up most of the matter in the universe, and L stands for Lambda, which is the symbol used in general relativity to represent dark energy or cosmic expansion. While the observational evidence we have largely supports the LCDM model, there are some issues with it. One of the most bothersome is known as cosmic tension.

It centers on our measurement of the Hubble constant, which tells us the rate at which the universe has expanded over time. There are lots of ways to measure the Hubble constant, from the brightness of distant supernovae, to the clustering of galaxies, to fluctuations in the cosmic background, to the light of microwave lasers. All of these methods have advantages and disadvantages, but if our cosmological model is right they should all agree within the limits of uncertainty.

The problem is, they don’t agree. Back in the early days of cosmology the uncertainty of our measurement was so large that all these results overlapped, but as our measurements got better it became clear different methods gave slightly different values for the Hubble constant. In polite company, astronomers say there is tension between these values.

This tension means that either our measurements are a bit off, or there is something wrong with our model. This has led some astronomers to propose some missing aspects to our model, such as how the mass of neutrinos might realign our Hubble values. But as new measurements of the Hubble constant keep coming in, it looks as if the tension is just getting worse. Now a new paper from Wendy Freedman argues that the tension problem isn’t that bad and that the tension will likely fade as the next generation of telescopes gives us even better data.

As it stands, the main tension in Hubble values arises between methods that rely upon the cosmic distance ladder, such as supernova observations, and those that don’t, such as the cosmic microwave background (CMB).