Physics, Quantum Physics

Physicists find little agreement on universe’s biggest questions

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September 16, 2026 by Ivy Delaney

The largest ever survey of physicists reveals a surprising lack of consensus on fundamental questions, challenging established understandings of the universe. Led by Niayesh Afshordi of Perimeter Institute and the University of Waterloo, the study found that even the standard model of cosmology, ΛCDM, failed to achieve majority support, a result potentially influenced by recent data suggesting dark energy isn’t constant.

“The most striking result is how few of the ‘standard answers’ in fundamental physics command overwhelming support,” says Afshordi, “with most falling short of a majority.” Majority agreement was only reached on two points: 68% of physicists surveyed believe the Big Bang doesn’t necessarily mark the beginning of time, and a narrow majority of 51% support the theory of cosmic inflation.

ΛCDM Standard Model Faces Broad Physicist Disagreement

Only 51% of physicists surveyed expressed agreement with the theory of cosmic inflation, a rapid expansion event in the early universe, revealing a surprising level of uncertainty surrounding even this widely discussed concept. The findings, published in Physics Magazine, demonstrate that even established theories face significant scrutiny within the scientific community, particularly in light of new observational data.

A substantial 68% of physicists surveyed concur that the Big Bang does not necessarily represent the absolute beginning of time, a perspective diverging from common public understanding of the event; this viewpoint positions the Big Bang not as an initial singularity, but rather as a description of the universe’s evolution from a hot, dense state, leaving open the possibility of pre-existing conditions or cyclical models. The ΛCDM model, the prevailing standard model of cosmology, fared even worse, failing to achieve majority support among the surveyed physicists.

This lack of consensus may stem from recent data collected by the Dark Energy Spectroscopic Instrument (DESI), which suggests that dark energy, the mysterious force driving the accelerating expansion of the universe, may not be constant as the ΛCDM model assumes. Afshordi observes that “The interesting point is not that physicists are confused. It is that the frontier is genuinely alive.” This observation highlights a dynamic and open field where established theories are actively being challenged and refined.

Regarding the elusive nature of dark matter, the survey revealed a fragmented range of opinions. Only 17% of respondents favour the hypothesis of undiscovered low-mass particles as the primary constituent of dark matter, while 12% lean towards modifications of gravitational theory. A significant 21% believe the solution lies in a combination of various proposed explanations, suggesting a complex and multifaceted phenomenon.

Afshordi remains optimistic about the implications of this lack of consensus. “Scientific truth is not decided by a vote,” he states, “But consensus, or its absence, tells us where the evidence feels settled and where researchers still see room for radically different ideas.” He draws a parallel to the lyrics of Leonard Cohen, noting that “There is a crack in everything, that’s how the light gets in,” suggesting that these areas of disagreement represent opportunities for innovation and discovery. The results of the survey, accessible through an online dashboard, provide a valuable resource for the global physics community, fostering transparency and encouraging further investigation into these fundamental questions.

The most striking result is how few of the ‘standard answers’ in fundamental physics command overwhelming support, with most falling short of a majority.

Niayesh Afshordi, associate faculty member at Perimeter Institute and professor at the University of Waterloo
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Cosmology dark energy dark matter Standard Model
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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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