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Received β€” 11 September 2026 ⏭ Ars Technica - Science

Physicist does the math on Star Trek’s β€œPicard maneuver”

10 September 2026 at 18:54

It turns out Jean-Luc Picard was an even better starship helmsman than the writers knew. A physicist has gone through the details of a warp-speed trick from the first season of Star Trek: The Next Generation and found a subtlety the show missed. But instead of a plot hole, the detail he found actually makes the maneuver more impressive… as well as a great opportunity to teach about a lesser-known feature of the theory of relativity.

NΓ­ckolas de Aguiar Alves, a physicist at the Federal University of ABC in Brazil, first watched Next Generation as a master’s student. When he got to the episode "The Battle" in the show’s first season, the plot reminded him of his relativity coursework.

In "The Battle," a Ferengi leader reminds Picard of a battle he fought years ago as captain of a ship called the Stargazer. Under fire from a mysterious attacker, Picard’s ship’s shields were down. He had to get closer without taking a hit, so he made a gamble. Picard ordered the Stargazer to charge the enemy ship at warp speed (meaning faster than light), then stop abruptly and fire. By going faster than light, Picard anticipated that the other ship would see two images of the Stargazer: where it reached warp speed and where it stopped. If they fired on the wrong image, they would miss the Stargazer, and Picard could win the battle.

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Β© Paramount

When it comes to Beatles references, scientists can't let it be

9 September 2026 at 20:31

Scientists have an indisputable playful side, evidenced by frequent allusions to popular culture in their research publications. That includes popular song lyrics. And the most popular musical group, in terms of how frequently their songs and lyrics appear in the scientific literature, is The Beatles, according to a new paper published in the journal PLoS ONE.

β€œSome of these are genuinely brilliant," said co-author Gabriel Budel of Delft University of Technology in the Netherlands of the more than 3,000 references they found to The Beatles. "'The lung and winding road' is a paper on Long COVID that changes one vowel. 'Here comes the SU(N)' turns 'Here Comes the Sun' into a quantum computing paper about mathematical groups. Someone was having a very good day at their desk.”

Back in 2014, scientists at the Karolinska Institute in Sweden revealed that they had been deliberately inserting Bob Dylan lyrics into their papers as part of a long-running bet, starting with a 1997 Nature review entitled "Nitric Oxide and inflammation: The answer is blowing in the wind." That resulted in a 2015 study on whether Dylan lyrics appeared elsewhere in the biomedical literature; the most frequently referenced were "The Times They Are A'Changin'" and "Blowing in the Wind."

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Β© Ramon Dorenbos, CC-BY 4.0

Google's AI genome system evaluates every possible one-base change

9 September 2026 at 17:34

On Tuesday, Google announced AlphaGenome Atlas, a resource that attempts to predict the consequences of every possible single-base variant in the human genome. The human genome is about 3 billion bases long, so trying the other three DNA bases that don't appear in our reference genome means sending a total of 9 billion bases through AlphaGenome software.

AlphaGenome is designed to identify potential functions of non-coding DNA, which does not encode proteins but makes up the vast majority of the human genome. Some of this non-coding DNA is essential for controlling the activity of the protein-coding portionβ€”it tells the cell where and when to make messenger RNAs, how to process them into mature protein-coding forms, and so on. But much of it appears to be little more than the remains of viruses and other molecular parasites.

Being able to identify the functional portion is very useful, as is having all the analysis done by a single software package. But until biologists start to use it heavily (assuming they do), it won't be clear what AlphaGenome offers beyond what we could have gotten out of its training data.

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Β© Vertigo3D

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