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Category: quantum physics

The Singularity Needs a Navigator

In 2013, physicist Alex Wissner-Gross published a single equation for intelligence in [ITALIC] Physical Review Letters [/ITALIC]: # F = T∇Sτ

The force of an intelligent system equals its temperature — computational capacity, raw horsepower — multiplied by the gradient of its future option-space. Intelligence is not a mysterious property of carbon-based brains.

It is a physical force: the tendency of any sufficiently energetic system to maximize the number of future states accessible to it.

The equation was elegant. Correct. And incomplete.

It describes the force. It does not describe the geometry of the space through which that force navigates.

A gradient without a metric is a direction without distance — it tells the system where to push but not what distortion it will encounter on the way there.

We spent three years building the geometry. We tested it across 69 billion simulations. What we found changes everything. ## The Missing Geometry — From Force to Navigation.

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These Physicists Say They Found The Origin Of Reality

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One of the most perplexing questions in the foundations of physics is how our shared sense of reality emerges out of quantum mechanics. This is because in quantum mechanics, it seems, different observers can arrive at different conclusions about what is real and what not. A group of physicists now used an approach called “Quantum Darwinism” to solve this tricky problem. At least they say they solved it. I am not so sure. Let’s have a look.

Paper: https://journals.aps.org/pra/abstract… mugs, posters and more: ➜ https://sabines-store.dashery.com/ 💌 Support me on Donorbox ➜ https://donorbox.org/swtg 👉 Transcript with links to references on Patreon ➜ / sabine 📝 Transcripts and written news on Substack ➜ https://sciencewtg.substack.com/ 📩 Free weekly science newsletter ➜ https://sabinehossenfelder.com/newsle… 👂 Audio only podcast ➜ https://open.spotify.com/show/0MkNfXl… 🔗 Join this channel to get access to perks ➜ / @sabinehossenfelder 📚 Buy my book ➜ https://amzn.to/3HSAWJW #science #sciencenews #quantum #physics This video discusses the concept of “reality” in quantum physics, touching on how different observers can reach different conclusions. It features a presentation of a scientific paper on the “Metrological approach to the emergence of classical objectivity,” suggesting a potential solution to a long-standing problem in quantum mechanics. We explore how the “observer effect” and individual “consciousness” play a crucial role in shaping our understanding of “reality does not exist” within the realm of “quantum physics explained.” This deep dive connects the fundamental principles of “quantum mechanics” with profound questions in “philosophy.”

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💌 Support me on Donorbox ➜ https://donorbox.org/swtg.
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📝 Transcripts and written news on Substack ➜ https://sciencewtg.substack.com/
📩 Free weekly science newsletter ➜ https://sabinehossenfelder.com/newsle…
👂 Audio only podcast ➜ https://open.spotify.com/show/0MkNfXl…
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/ @sabinehossenfelder.
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#science #sciencenews #quantum #physics.

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3 Questions: On the future of AI and the mathematical and physical sciences

Curiosity-driven research has long sparked technological transformations. A century ago, curiosity about atoms led to quantum mechanics, and eventually the transistor at the heart of modern computing. Conversely, the steam engine was a practical breakthrough, but it took fundamental research in thermodynamics to fully harness its power.

Today, artificial intelligence and science find themselves at a similar inflection point. The current AI revolution has been fueled by decades of research in the mathematical and physical sciences (MPS), which provided the challenging problems, datasets, and insights that made modern AI possible. The 2024 Nobel Prizes in physics and chemistry, recognizing foundational AI methods rooted in physics and AI applications for protein design, made this connection impossible to miss.

In 2025, MIT hosted a Workshop on the Future of AI+MPS, funded by the National Science Foundation with support from the MIT School of Science and the MIT departments of Physics, Chemistry, and Mathematics. The workshop brought together leading AI and science researchers to chart how the MPS domains can best capitalize on — and contribute to — the future of AI. Now a white paper, with recommendations for funding agencies, institutions, and researchers, has been published in Machine Learning: Science and Technology. In this interview, Jesse Thaler, MIT professor of physics and chair of the workshop, describes key themes and how MIT is positioning itself to lead in AI and science.

Quantum dots generate entangled photon pairs on demand

For the first time, researchers in China have demonstrated how quantum dots can be engineered to consistently generate pairs of entangled photons. By carefully tailoring the photonic environment surrounding a single quantum dot, the team showed that it is possible to produce highly correlated photon pairs with remarkable efficiency, potentially opening new opportunities for emerging quantum technologies. The work, led by Zhiliang Yuan at the Beijing Academy of Quantum Information Sciences, is reported in Nature Materials.

In recent years, technologies capable of generating single photons on demand have advanced at an impressive pace. Already, these sources have led to substantial progress in fields ranging from quantum computing and secure communications, to advanced sensing and biomedical imaging.

A natural next step will be the ability to produce pairs of photons that are identical and strongly entangled. Even when separated by large distances, the properties of entangled photons remain linked: an effect that lies at the heart of many quantum technologies.

Quantum computers must overcome major technical hurdles before tackling quantum chemistry problems

Although the potential applications of quantum computing are widespread, a new feasibility study suggests quantum computers still face major hurdles in solving quantum chemistry problems. The study, published in Physical Review B, evaluates what criteria are needed for a quantum advantage in searching for the ground state energy of molecules. The researchers attempt this feat using two different algorithms with differing strengths and weaknesses.

The team first determined the criteria for the variational quantum eigensolver (VQE) algorithm, which is used for noisy, near-term devices and sets an upper bound to the level of imprecision or decoherence in quantum hardware. The researchers derived quantitative criteria for VQE and QPE based on error rates, energy scales, and overlap with the ground state.

Results showed that VQE is extremely sensitive to hardware errors and decoherence. The team says that achieving chemical accuracy would require error rates far below current hardware capabilities. Available error mitigation techniques offer only limited improvement and scale poorly with system size.

Inside the light: How invisible electric fields drive device luminescence

Fleeting electron-hole pairs are giving scientists a new window into optimizing light-emitting devices (LEDs). Using quantum magnetic resonance, Osaka Metropolitan University researchers have discovered how shifting internal electric fields dictate whether these devices shine brightly or dimly. Their study is published in the journal Advanced Optical Materials.

Light-emitting electrochemical cells (LECs) are simple, flexible, and low-cost thin-film devices that generate light from an electric current. Unlike conventional organic LEDs, LECs contain just a single active layer—an organic semiconductor blended with mobile ions—sandwiched between two electrodes. This structural simplicity makes them promising tools for next-generation light-emitting technologies.

Inside that apparently simple structure, however, things aren’t so simple after all.

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