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Viscous Stars Can Reflect Gravitational Waves like Black Holes Do

A neutron star’s viscosity determines how the star interacts with gravitational waves, a behavior that could be useful to the study of neutron-star interiors.

The detection of gravitational waves from mergers of black holes and neutron stars has opened a window onto the strong-gravitational-field regime, allowing physicists to put constraints on various gravitational theories [1, 2]. These observations also have the power to probe the ways in which such compact objects interact with gravitational waves hitting their boundaries or, in the case of neutron stars, passing through their interiors [3]. Valentin Boyanov at the University of Lisbon in Portugal and his colleagues have now investigated such interactions in detail, analyzing how an object’s response to passing gravitational waves is influenced by its viscosity [4]. Their results could allow researchers to extract information about the internal structure of neutron stars from future gravitational-wave measurements.

Boyanov and colleagues tackle the following questions: Under what conditions do viscous compact objects such as neutron stars reflect or absorb gravitational waves? And to what extent do these interactions mimic those of black holes? At first, it might seem that black holes in particular cannot be reflective―after all, their defining feature is that they absorb everything that falls on them. But in practice, whether a black hole absorbs or reflects gravitational waves depends on the frequency of those waves. High-frequency gravitational waves cross the event horizon and are absorbed, adding to the black hole’s mass and angular momentum. For low-frequency waves, on the other hand, the curved space time around the black hole constitutes a potential barrier to the wave propagation: The waves are “reflected,” meaning that they scatter off this region with their phase or their propagation direction altered.

Researchers discover a hidden atomic order that persists in metals even after extreme processing

For decades, it’s been known that subtle chemical patterns exist in metal alloys, but researchers thought they were too minor to matter—or that they got erased during manufacturing. However, recent studies have shown that in laboratory settings, these patterns can change a metal’s properties, including its mechanical strength, durability, heat capacity, radiation tolerance, and more.

Now, researchers at MIT have found that these chemical patterns also exist in conventionally manufactured metals. The surprising finding revealed a new physical phenomenon that explains the persistent patterns.

In a paper published in Nature Communications today, the researchers describe how they tracked the patterns and discovered the physics that explains them. The authors also developed a simple model to predict chemical patterns in metals, and they show how engineers could use the model to tune the effect of such patterns on metallic properties, for use in aerospace, semiconductors, nuclear reactors, and more.

Physicists Predict When The Universe Will End in a Reverse Big Bang

If recent discoveries that dark energy is evolving hold any water, our Universe will collapse under its own gravity on a finite timeline, new calculations suggest.

Based on several recent dark energy results, a new model finds that the Universe has a lifespan of just 33.3 billion years. Since we are now 13.8 billion years after the Big Bang, this suggests that we have a smidge less than 20 billion years left.

For another 11 billion years, the Universe will continue to expand, before coming to a halt and reversing direction, collapsing down to the hypothetical Big Crunch, say physicists Hoang Nhan Luu of Donostia International Physics Center in Spain, Yu-Cheng Qiu of Shanghai Jiao Tong University in China, and corresponding author Henry Tye of Cornell University in the US.

Physicists detect water’s ultraviolet fingerprint in interstellar comet 3I/ATLAS

For millions of years, a fragment of ice and dust drifted between the stars—like a sealed bottle cast into the cosmic ocean. This summer, that bottle finally washed ashore in our solar system and was designated 3I/ATLAS, only the third known interstellar comet. When Auburn University scientists pointed NASA’s Neil Gehrels Swift Observatory toward it, they made a remarkable find: the first detection of hydroxyl (OH) gas from this object, a chemical fingerprint of water.

Swift’s space-based telescope could spot the faint ultraviolet glow that ground observatories can’t see—because, high above Earth’s atmosphere, it captures light that never reaches Earth’s surface.

Detecting water—through its ultraviolet by-product, hydroxyl—is a major breakthrough for understanding how interstellar comets evolve. In solar-system comets, water is the yardstick by which scientists measure their overall activity and track how sunlight drives the release of other gases. It’s the chemical benchmark that anchors every comparison of volatile ices in a ’s nucleus.

The Door That Opens to Another Universe: The True Science Behind SCP-4357 “Slimelord”

What if a simple apartment door in Boston opened into another universe?
SCP-4357, also known as “Slimelord,” is one of the strangest and most human anomalies ever recorded — a hyperspatial discontinuity leading to a world of intelligent slug-like beings with philosophy, humor, and heartbreak.

In this speculative science essay, we explore what SCP-4357 means for physics, biology, and the idea of consciousness itself. How could life evolve intelligence in a sulfur-rich world? Why do these beings mirror human culture so closely? And what happens when curiosity crosses the line into exploitation?

Join us as we break down the science, ethics, and wonder behind one of the SCP Foundation’s most thought-provoking entries.

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🌌 Because somewhere out there, even the slugs have opinions on Kant.

From engines to nanochips: Physicists redefine how heat really moves

Heat has always been something we thought we understood. From baking bread to running engines, the idea seemed simple: heat spreads out smoothly, like water soaking through a sponge. That simple picture, written down by Joseph Fourier 200 years ago, became the foundation of modern science and engineering.

But zoom into the nanoscale—inside the chips that power your smartphone, AI hardware, or next-generation solar panels—and the story changes. Here, heat doesn’t just “diffuse.” It can ripple like , remember its past, or flow in elegant streams like a fluid in a pipe. For decades, scientists had pieces of this puzzle but no unifying explanation.

Now, researchers at Auburn University and the U.S. Department of Energy’s National Renewable Energy Laboratory have delivered what they call a “unified statistical theory of heat conduction.”

The Holographic Paradigm: The Physics of Information, Consciousness, and Simulation Metaphysics

In this paradigm, the Simulation Hypothesis — the notion that we live in a computer-generated reality — loses its pejorative or skeptical connotation. Instead, it becomes spiritually profound. If the universe is a simulation, then who, or what, is the simulator? And what is the nature of the “hardware” running this cosmic program? I propose that the simulator is us — or more precisely, a future superintelligent Syntellect, a self-aware, evolving Omega Hypermind into which all conscious entities are gradually merging.

These thoughts are not mine alone. In Reality+ (2022), philosopher David Chalmers makes a compelling case that simulated realities — far from being illusory — are in fact genuine realities. He argues that what matters isn’t the substrate but the structure of experience. If a simulated world offers coherent, rich, and interactive experiences, then it is no less “real” than the one we call physical. This aligns deeply with my view in Theology of Digital Physics that phenomenal consciousness is the bedrock of reality. Whether rendered on biological brains or artificial substrates, whether in physical space or virtual architectures, conscious experience is what makes something real.

By embracing this expanded ontology, we are not diminishing our world, but re-enchanting it. The self-simulated cosmos becomes a sacred text — a self-writing code of divinity in which each of us is both reader and co-author. The holographic universe is not a prison of illusion, but a theogenic chrysalis, nurturing the birth of a higher-order intelligence — a networked superbeing that is self-aware, self-creating, and potentially eternal.

New approach to gravitational wave detection opens the milli-Hz frontier

Scientists have unveiled a new approach to detecting gravitational waves in the milli-Hertz frequency range, providing access to astrophysical and cosmological phenomena that are not detectable with current instruments.

Gravitational waves—ripples in spacetime predicted by Einstein—have been observed at high frequencies by ground-based interferometers such as LIGO and Virgo, and at ultra-low frequencies by pulsar timing arrays. However, the mid-band range has remained a scientific blind spot.

Developed by researchers at the Universities of Birmingham and Sussex, the new concept uses cutting-edge optical cavity and atomic clock technologies to sense gravitational waves in the elusive milli-Hertz frequency band (10⁻⁵–1 Hz).

AI techniques excel at solving complex equations in physics, especially inverse problems

Differential equations are fundamental tools in physics: they are used to describe phenomena ranging from fluid dynamics to general relativity. But when these equations become stiff (i.e. they involve very different scales or highly sensitive parameters), they become extremely difficult to solve. This is especially relevant in inverse problems, where scientists try to deduce unknown physical laws from observed data.

To tackle this challenge, the researchers have enhanced the capabilities of Physics-Informed Neural Networks (PINNs), a type of artificial intelligence that incorporates physical laws into its .

Their approach, reported in Communications Physics, combines two innovative techniques: Multi-Head (MH) training, which allows the neural network to learn a general space of solutions for a family of equations—rather than just one specific case—and Unimodular Regularization (UR), inspired by concepts from differential geometry and , which stabilizes the learning process and improves the network’s ability to generalize to new, more difficult problems.

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