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Physicists can’t find “now” anywhere in the universe | Jim Al-Khalili

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We would hope that the moment that we eternally live in, the “now,” would have a concrete scientific explanation. But the truth is far more complicated, says the relativity of simultaneity.

Jim Al-Khalili explains how the past and future are more fluid than we may think.

Preorder Jim Al-Khalili’s forthcoming book, On Time: The Physics That Makes the Universe, here: https://www.amazon.com/Time-Physics-T?tag=lifeboatfound-20…

About Jim Al-Khalili: Jim is a multiple award-winning science communicator renowned for his public engagement around the world through writing and broadcasting and a leading academic making fundamental contributions to theoretical physics, particularly in nuclear reaction theory, quantum effects in biology, open quantum systems and the foundations of quantum mechanics. Jim is a theoretical physicist at the University of Surrey where he holds a Distinguished Chair in physics as well as a university chair in the public engagement in science. He received his PhD in nuclear reaction theory in 1989 and has published widely in the field. His current interest is in open quantum systems and the application of quantum mechanics in biology.

About Jim Al-Khalili:

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Val Kilmer Resurrected by AI: ‘As Deep as the Grave’ Trailer Brings Late Actor Back to the Big Screen (EXCLUSIVE)

The filmmakers behind “As Deep as the Grave” have debuted the trailer for the upcoming historical drama, giving viewers a first look at the AI technology that was used to create Val Kilmer’s performance.

Kilmer, who died in 2025 after battling throat cancer, was cast as Father Fintan, a Catholic priest and Native American spiritualist, but was too sick to shoot his role. With the cooperation of Kilmer’s estate and his daughter Mercedes, the “As Deep as the Grave” team used generative AI to include the actor in the finished film.

DESI Completes Planned 3D Map of the Universe and Continues Exploring

DESI has mapped more than 47 million galaxies and quasars, creating the largest high-resolution 3D map of our Universe to date. Because of the instrument’s excellent performance and hints that dark energy might evolve, DESI will continue observations into 2028 and further expand the map. DESI was constructed with funding from the U.S. Department of Energy Office of Science and is mounted on the U.S. National Science Foundation Nicholas U. Mayall 4-meter telescope.

Last night, the 5,000 fiber-optic eyes of the Dark Energy Spectroscopic Instrument (DESI) swiveled onto a patch of sky near the Little Dipper. Roughly every 20 minutes, they locked onto distant pinpricks of light, gathering photons that had traveled toward Earth for billions of years. When the Sun rose, DESI collaborators marked the completion of a major milestone: successfully surveying all of the area in DESI’s planned map of the Universe.

The five-year survey, finished ahead of schedule and with vastly more data than expected, has produced the largest high-resolution 3D map of the Universe ever made. Researchers use that map to explore dark energy, the fundamental ingredient that makes up about 70% of our Universe and is driving its accelerating expansion.

Jellyfish-Inspired Ultrafast and Versatile Magnetic Soft Robots for Biomedical Applications

JUST PUBLISHED: jellyfish-inspired ultrafast and versatile magnetic soft robots for biomedical applications

Click here to read the latest free, Open Access article from Cyborg and Bionic Systems.

Superconductor Theory Under Cold-Atom Scrutiny

Snapshot measurements of cold-atom gases reveal hidden spin correlations that could force an update of some superconductivity theories.

Our understanding of nature is inherently bound to the experimental tools we build to observe the world. Superconductivity, for example, has been traditionally studied using current and voltage meters under a variety of temperatures and other environmental conditions. From these observations, theorists have developed models—notably the Bardeen-Cooper-Schrieffer (BCS) theory, which assumes that the zero-resistance flow in a superconductor arises from electrons forming so-called Cooper pairs. This theory has been successful in explaining a large class of superconductors, but Tarik Yefsah from the Ecole Normale Supérieure in Paris and colleagues have now observed behavior that contradicts BCS predictions [1]. Using a recently developed technique called atom-resolved continuum quantum gas microscopy, the researchers directly observed spatial correlations in cold atoms that mimic superconducting electrons.

Machine learning accelerates analysis of fusion materials

Tungsten’s superior performance in extreme environments makes it a leading candidate for plasma-facing components (PFCs) in fusion reactors, but the ultra-high heat can damage its microscopic structure and lead to component failure. Scanning electron microscopy (SEM) can capture and quantify these microstructure changes, but assembling a sufficiently large dataset of SEM imagery is expensive and logistically challenging.

To augment this dataset, researchers at Oak Ridge National Laboratory trained a generative machine learning model using 3,200 SEM images of tungsten samples exposed to fusion-relevant conditions. The model can generate novel SEM images with realistic microstructures and surface features, such as cracks and pores, without replicating the original images.

“This work is not about making pretty pictures, it’s about capturing the statistics of real damage on these materials,” said ORNL’s Rinkle Juneja, the project’s principal investigator. “We train our generative workflow to learn tungsten’s microstructure signatures, like crack patterns, so it can generate new, statistically consistent microstructures, laying the groundwork for robust, data-driven assessment of PFC fusion materials.”

Gravity follows Newton and Einstein’s rules, even at cosmic scales

Gravity, as most people understand it, is the familiar force that pulls a falling apple toward Earth. But for astronomers and theoretical physicists, it is also a vexing invisible architect that guides the shape and evolution of the largest cosmic structures across the universe.

For decades, puzzling observations of unusually fast-moving galaxies have forced cosmologists like the University of Pennsylvania’s Patricio A. Gallardo to revisit the fundamentals of physics, exploring, for example, whether the laws of gravity as described by Isaac Newton and Albert Einstein truly apply everywhere.

“Astrophysics has been plagued by a massive discrepancy in the cosmic ledger,” says Gallardo. “When we look at how stars orbit within galaxies or how galaxies move within galaxy clusters, some appear to be traveling way too fast for the amount of visible matter they contain.”

Quantum-inspired algorithm solves 268 million-site quasicrystal simulation in a heartbeat

Quantum technologies like quantum computers are built from quantum materials. These types of materials exhibit quantum properties when exposed to the right conditions. Curiously, engineers can also trigger quantum behavior by manipulating a material’s structure; for example, by stacking layers of graphene on top of each other and twisting them to create a moiré pattern, which suddenly turns them into a superconductor.

The layers can be arranged in increasingly complex ways all the way to quasicrystals and super-moiré materials. The fundamental problem is that scientists must first calculate the properties of potential new materials to predict if they could be useful. Quasicrystals, for example, are so complex they can require processing more than a quadrillion numbers—far beyond the capacity of the world’s most powerful supercomputers.

Now researchers at Aalto University’s Department of Applied Physics have shown how a quantum-inspired algorithm makes solving these colossal, non-periodic quantum materials possible in a heartbeat. The research is published in the journal Physical Review Letters as an Editor’s suggestion.

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