A near-Earth object recently classified as an asteroid has been identified as Elon Musk’s Tesla Roadster, which was launched into space in 2018 aboard a SpaceX Falcon Heavy rocket. The object was mistakenly listed as a new near-Earth asteroid by the International Astronomical Union’s Minor Planet Center (MPC) on January 2, before the classification was withdrawn within hours. The error, made by an amateur astronomer in Turkey using publicly available data, underscores growing concerns over the tracking of space debris and its impact on astronomical observations.

Identification Error and Retraction

According to astronomy.com, the object was initially recorded in the MPC’s database under the designation 2018 CN41. The classification was based on historical tracking data, but after a review, the discovery was rescinded just 17 hours later. The astronomer who reported the object recognised the mistake upon further analysis.

The Tesla Roadster was launched on February 6, 2018, as a test payload for SpaceX’s Falcon Heavy’s maiden flight. Positioned in the driver’s seat was a mannequin named “Starman,” dressed in a prototype spacesuit. The car was intended to enter a stable orbit around Mars but instead settled into a heliocentric orbit, periodically passing near Earth and Mars.

Implications for Space Tracking

Jonathan McDowell, an astronomer at the Harvard-Smithsonian Center for Astrophysics, told astronomy.com that the misidentification of human-made objects as natural space bodies is becoming more frequent. He warned that such mistakes could lead to significant financial losses, stating that the worst-case scenario was that a billion dollars were spent launching a space probe to study an asteroid, only to realise it’s not an asteroid when you get there.

Over the years, multiple spacecraft and discarded rocket boosters have been temporarily classified as asteroids. Among them are the European Space Agency’s Rosetta spacecraft, NASA’s Lucy probe, and the European-Japanese BepiColombo mission. With the increasing number of space missions, experts anticipate that misidentifications will become more common.

Lack of Regulations on Deep Space Debris

As per reports, space agencies and private companies are required to track satellites and debris in Earth’s orbit. However, no regulatory framework mandates tracking objects that have moved beyond Earth’s gravity, such as the Tesla Roadster. In a 2024 statement, the American Astronomical Society called for transparency in tracking space objects to minimise interference with scientific observations and prevent potential collisions. With space exploration accelerating, concerns over orbital debris and misidentified objects continue to grow, reinforcing the need for stricter monitoring and classification systems.g

A new research study has examined the mathematical principles governing creativity and innovation, shedding light on how novel ideas emerge. By analysing data across different domains, researchers have identified patterns that could refine the understanding of how individuals and societies generate new concepts. The study investigates two types of novelty—discovering an entirely new element and forming unique combinations of existing elements. The findings could be crucial in fields such as science, literature, and technology, where innovation plays a vital role in advancement.

Mathematical Framework for Creativity

According to the study published in Nature Communications, researchers introduced a framework to model how new ideas emerge. Led by Professor Vito Latora from Queen Mary University of London, the team focused on higher-order novelties—combinations of familiar elements that create something new. Speaking to Phys.org, Prof. Latora stated that the study is part of a broader effort to understand the mechanisms underlying creativity, aiming to identify factors that contribute to the success of ideas, products, and technologies.

A mathematical model called Edge-Reinforced Random Walk with Triggering (ERRWT) was developed to simulate how people discover and combine elements. Unlike traditional random walks, which assume equal probability for each step, ERRWT strengthens frequently used connections and triggers new links when novel combinations occur. This process mirrors real-world discovery, where repeated exposure to certain elements increases the likelihood of making new associations.

Analysing Patterns Across Domains

The research team applied the ERRWT model to three distinct datasets—music listening habits from Last.fm, literary texts from Project Gutenberg, and scientific publications from Semantic Scholar. The findings revealed that while individuals might have similar rates of discovering new elements, the sequences in which they arrange them differ significantly.

For music listeners, certain users developed unique listening patterns despite discovering the same number of new songs. In literature, writers frequently created new word pairings rather than introducing entirely new words. Scientific papers, particularly titles, demonstrated a higher tendency for novel word combinations compared to narrative texts.

Predicting Innovation with Heaps’ Law

The study also highlighted that the process of novelty creation follows Heaps’ law, a power-law relationship describing how new elements and combinations emerge over time. By applying this principle, researchers could predict different rates of innovation across disciplines. The results indicated that while some fields prioritise the discovery of individual elements, others focus on recombining existing ones in unique ways.

Implications for Future Research

The findings suggest that understanding how creative processes unfold could help refine strategies for fostering innovation. Prof. Latora noted that studying novelty creation is essential for identifying factors that contribute to the rise and decline of trends, products, and ideas. Future research aims to expand the model by incorporating a social component, which could provide insights into how external influences shape creative developments.