Physicists still divided about quantum world, 100 years on
"Shut up and calculate!" is a famous quote in quantum physics that illustrates the frustration of scientists struggling to unravel one of the world's great paradoxes.
For the last century, equations based on quantum mechanics have consistently and accurately described the behaviour of extremely small objects.
However, no one knows what is happening in the physical reality behind the mathematics.
The problem started at the turn of the 20th century, when scientists realised that the classical principles of physics did not apply to things on the level on atoms.
Bafflingly, photons and electrons appear to behave like both particles and waves. They can also be in different positions simultaneously -- and have different speeds or levels of energy.
In 1925, Austrian physicist Erwin Schroedinger and Germany's Werner Heisenberg developed a set of complex mathematical tools that describe quantum mechanics using probabilities.
This "wave function" made it possible to predict the results of measurements of a particle.
These equations led to the development of a huge amount of modern technology, including lasers, LED lights, MRI scanners and the transistors used in computers and phones.
But the question remained: what exactly is happening in the world beyond the maths?
- A confusing cat -
To mark the 100th year of quantum mechanics, many of the world's leading physicists gathered last month on the German island of Heligoland, where Heisenberg wrote his famous equation.
More than 1,100 of them responded to a survey conducted by the leading scientific journal Nature.
The results showed there is a "striking lack of consensus among physicists about what quantum theory says about reality", Nature said in a statement.
More than a third -- 36 percent -- of the respondents favoured the mostly widely accepted theory, known as the Copenhagen interpretation.
In the classical world, everything has defined properties -- such as position or speed -- whether we observe them or not.
But this is not the case in the quantum realm, according to the Copenhagen interpretation developed by Heisenberg and Danish physicist Niels Bohr in the 1920s.
It is only when an observer measures a quantum object that it settles on a specific state from the possible options, goes the theory. This is described as its wave function "collapsing" into a single possibility.
The most famous depiction of this idea is Schroedinger's cat, which remains simultaneously alive and dead in a box -- until someone peeks inside.
The Copenhagen interpretation "is the simplest we have", Brazilian physics philosopher Decio Krause told Nature after responding to the survey.
Despite the theory's problems -- such as not explaining why measurement has this effect -- the alternatives "present other problems which, to me, are worse," he said.
- Enter the multiverse -
But the majority of the physicists supported other ideas.
Fifteen percent of the respondents opted for the "many worlds" interpretation, one of several theories in physics that propose we live in a multiverse.
It asserts that the wave function does not collapse, but instead branches off into as many universes as there are possible outcomes.
So when an observer measures a particle, they get the position for their world -- but it is in all other possible positions across many parallel universes.
"It requires a dramatic readjustment of our intuitions about the world, but to me that's just what we should expect from a fundamental theory of reality," US theoretical physicist Sean Carroll said in the survey.
The quantum experts were split on other big questions facing the field.
Is there some kind of boundary between the quantum and classical worlds, where the laws of physics suddenly change?
Forty-five percent of the physicists responded yes to this question -- and the exact same percentage responded no.
Just 24 percent said they were confident the quantum interpretation they chose was correct.
And three quarters believed that it will be replaced by a more comprehensive theory one day.
ber/dl/jj
Solve the daily Crossword
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Yahoo
13 minutes ago
- Yahoo
An AI System Found a New Kind of Physics that Scientists Had Never Seen Before
"Hearst Magazines and Yahoo may earn commission or revenue on some items through these links." Here's what you'll learn when you read this story: For all the problems AI is causing society, one of its greatest benefits lies in the world of science. A new study focused on the chaotic dynamics of dusty plasmas found that, when trained properly, AI can actually discover new physics all on its own. By providing the most detailed description of this type of matter, the AI corrected long-held theoretical beliefs about how particles behave inside a dusty plasma. In more ways than one, artificial intelligence is making the world worse. Generative AI now spews countless amounts of 'AI slop,' and in classrooms, AI is slowly eroding critical thinking skills, which are… you know… critical. That's not even mentioning AI's unfortunate role as environmental decimator and job destroyer. Luckily, some artificial intelligence and machine learning (ML) models have grander ambitions than ripping off beloved animators and mass-producing essays at an eighth-grade reading level. Take, for instance, a new ML model developed by a team of Emory University scientists. Typically, machine-learning algorithms are used as a tool to help scientists sift through immense amounts of data or optimize experiments, but this particular ML model actually discovered new physics on its own—at least, as it relates to dusty plasma. You're likely familiar with plasma—that fourth state of matter that actually makes up 99.9% of all ordinary matter in the universe. Dusty plasma is simply the same mix of ionized gas, but with charged dust particles. This type of plasma can be found throughout both space and terrestrial environments. Wildfires, for example, generate dusty plasmas when charged particles of soot mixed with smoke. In this new study—published in the journal Proceedings of the National Academy of Sciences (PNAS)—a team of researchers describes how their trained ML model successfully provided the most detailed description of dusty plasma physics yet, creating precise predictions for non-reciprocal forces. 'Our AI method is not a black box: we understand how and why it works,' Justin Burton, a co-author of the study from Emory, said in a press statement. 'The framework it provides is also universal. It could potentially be applied to other many-body systems to open new routes to discovery.' Put simply, non-reciprocal forces (as their name suggests) occur when forces exerted between two particles in a plasma are not the same. The authors describe the phenomenon as two boats impacted by the wake of the other—relative position can impact the particles' attractive or repulsive forces. 'In a dusty plasma, we described how a leading particle attracts the trailing particle, but the trailing particle always repels the leading one,' Ilya Nemenman, another co-author of the study from Emory, said in a press statement. 'This phenomenon was expected by some but now we have a precise approximation for it which didn't exist previously.' The ML algorithm was also able to correct some theoretical misconceptions about dusty plasma. For example, scientists thought that the charge of the particle was proportional to its size, but the model confirms that while a larger particle does contain a larger charge, it isn't proportional, as it can also be influenced by density and temperature. They also found that the charge between particles isn't only influenced by the distance between two particles, but also by the particles' sizes. One the trickiest parts of this project, according to the authors, was designing the ML algorithm in the first place. Generally, AI acquires its abilities by being fed (or training on) datasets—give AI one million pictures of a monkey, and it'll get progressively better at identifying a monkey when it sees one. However, when it comes to discovering new physics, there isn't much training data to go on. So, the team had to create a structure that allowed it to work with the data it did have while still giving it latitude to explore unknown physics. 'I think of it like the Star Trek motto, to boldly go where no one has before,' Burton said. 'Used properly, AI can open doors to whole new realms to explore.' You Might Also Like The Do's and Don'ts of Using Painter's Tape The Best Portable BBQ Grills for Cooking Anywhere Can a Smart Watch Prolong Your Life? Solve the daily Crossword
Yahoo
39 minutes ago
- Yahoo
Zealand Pharma conference call on August 14 at 2pm CET (8am ET) to present second quarter 2025 financial results
Press Release – No. 11 / 2025 Zealand Pharma conference call on August 14 at 2pm CET (8am ET) to present second quarter 2025 financial results Copenhagen, Denmark, August 7, 2025 – Zealand Pharma A/S (Nasdaq Copenhagen: ZEAL) (CVR-no. 20045078), a biotechnology company focused on the discovery and development of innovative peptide-based medicines, announced that it will host a conference call on August 14, 2025, at 2:00 pm CET (8:00 am ET) following the announcement of financial results for the second quarter of 2025. Participating in the call will be President and Chief Executive Officer, Adam Steensberg; Chief Financial Officer, Henriette Wennicke; Chief Medical Officer, David Kendall; and Chief Commercial Officer, Eric Cox. The presentation will be followed by a Q&A session. The live listen-only audio webcast of the call and accompanying slide presentation will be accessible at . To receive telephone dial-in information and a unique personal access PIN, please register at Participants are advised to register for the call or webcast approximately 10 minutes before the start. A recording of the event will be available following the call on the Investor section of Zealand Pharma's website at About Zealand Pharma A/SZealand Pharma A/S (Nasdaq: ZEAL) is a biotechnology company focused on the discovery and development of peptide-based medicines. More than 10 drug candidates invented by Zealand Pharma have advanced into clinical development, of which two have reached the market and three candidates are in late-stage development. The company has development partnerships with a number of pharma companies as well as commercial partnerships for its marketed Pharma was founded in 1998 and is headquartered in Copenhagen, Denmark, with a presence in the U.S. For more information about Zealand Pharma's business and activities, please visit ContactsAdam Lange (Investors)Vice President, Investor Relationsalange@ Neshat Ahmadi (Investors)Investor Relations Managerneahmadi@ Anna Krassowska, PhD (Investor and Media)Vice President, Investor Relations & Corporate Communicationsakrassowska@ in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Yahoo
2 hours ago
- Yahoo
Avidity (RNA) Gets 26% Jump on Potential Takeover
We recently published . Avidity Biosciences, Inc. (NASDAQ:RNA) is one of the best-performing stocks on Wednesday. Avidity Biosciences rallied for a third day on Wednesday, jumping 26.14 percent to close at $48.26 as investors gobbled up shares following reports that it received an acquisition bid from Swiss drugmaker Novartis AG (NYSE:NVS). A report by the Financial Times, citing people privy to the matter, said that Novartis AG (NYSE:NVS) offered Avidity Biosciences, Inc. (NASDAQ:RNA) to acquire the company, in line with the former's plans to boost its pipeline of medicines targeting rare genetic disorders. Meanwhile, the report said that Avidity Biosciences, Inc. (NASDAQ:RNA) was mulling over the offer, although the talks could still collapse as other companies have emerged with separate takeover offers. Late last month, Avidity Biosciences, Inc. (NASDAQ:RNA) secured a Breakthrough Therapy designation from the Food and Drug Administration for its del-zota treatment for Duchenne muscular dystrophy (DMD) in patients with DMD44. DMD is a rare genetic condition characterized by progressive muscle damage and weakness due to the loss of dystrophin protein that typically starts at a young age. Del-zota, on the other hand, was designed to deliver phosphorodiamidate morpholino oligomers (PMOs) to skeletal muscle and heart tissue to specifically skip exon 44 of the dystrophin gene and enable production of near-full length dystrophin. While we acknowledge the potential of RNA as an investment, our conviction lies in the belief that some AI stocks hold greater promise for delivering higher returns and have limited downside risk. If you are looking for an extremely cheap AI stock that is also a major beneficiary of Trump tariffs and onshoring, see our free report on the .
