Toggle light / dark theme

A Widening Anomaly Strains the Standard Model

Does a new measurement of a rare decay of the neutral B meson portend new physics?

In particle physics, ten years is a long time to sit with a puzzle. Since 2013, measurements of a rare decay—a neutral B meson (B0) transforming into an excited kaon (K*0) and a muon–antimuon pair (µ+µ )—have stubbornly refused to match the predictions of the standard model, the theory that describes all known particles and forces [1]. Small enough to be dismissed at first as a statistical fluctuation, the pattern of discrepancies has grown with each new dataset into one of the most tantalizing hints of new physics in experimental particle physics. Now the LHCb Collaboration at CERN in Switzerland has published its most comprehensive analysis of the decay to date [2]. The result is clear: The anomaly persists. Encouragingly, the theoretical and experimental tools to understand it have never been sharper.

Within the mathematical framework of the standard model, the decay in question, B0 → K*0µ+µ, can occur only through so-called higher-order electroweak loop diagrams in which a bottom, or b, quark transforms into a strange, or s, quark [3]. As a result, the decay is extraordinarily rare. In every million B-meson decays of all kinds, you can expect to find only one. That rarity makes the decay valuable: It could bear measurable imprints of particles beyond the standard model that contribute to the same loop processes but have so far escaped detection because they are too heavy.

George Dyson on Turing’s Cathedral: In Wildness Is The Preservation Of The World

Fourteen years ago, I sat down with George Dyson to talk about “Turing’s Cathedral.”

We talked about the machines that were coming. Now they are here.

Dyson watched the digital revolution get built from the inside. His father was Freeman Dyson. Einstein’s secretary was his babysitter. He grew up at the Institute for Advanced Study in Princeton, playing in the halls where Turing’s ideas became von Neumann’s machines.

He gave me a line I still cannot shake:

“There is no way to completely govern the digital universe. It will always be a wildness, not a bureaucracy or a national park.”

Read it again. Then look at every #AI governance debate happening right now.

Hy3 (free) — API Pricing & Providers

Hy3 is a 295B-parameter Mixture-of-Experts model from Tencent (21B active, 192 experts with top-8 routing) built for reasoning, agentic workflows, and real-world production use. It supports a configurable reasoning effort: a direct no-think mode by default, plus low and high chain-of-thought modes for complex math, coding, and multi-step problems. With a 256K context window, Hy3 targets long-horizon tasks, including improved coreference resolution, multi-turn constraint tracking, and stable tool-calling that generalizes across agent scaffoldings.

Tencent positions it as a reliable, cost-effective option across coding, document processing, financial analysis, game development, and frontend design, with a strong emphasis on grounded, anti-hallucination behavior that answers when grounded and flags when evidence is missing rather than fabricating.

7 Mind-Bending Physics Questions Sci-Fi Made Me Ask

Science fiction does more than imagine the future — it pushes the human mind to the edge of what it can understand.

In this video, we look at seven strange physics and philosophy questions inspired by sci-fi: Does the universe balance every action? What if our universe is not a closed system? If infinity is real, does everything eventually happen? When physics “breaks down,” is reality failing — or are we? Are human minds evolved to misunderstand the deepest universe? Is individuality just a useful illusion? And is math discovered, invented, or the best tool humans have for reaching beyond their own understanding?

Featuring ideas and examples inspired by Interstellar, Warhammer 40K, Interstellar, Star Trek, The Matrix, Dune, The Three-Body Problem, Arrival, Foundation, 2001: A Space Odyssey, The Expanse, Annihilation, Project Hail Mary, and more.

Science fiction begins where certainty ends.

#SciFi #Physics #Interstellar #Warhammer40K #TheMatrix #Dune #ThreeBodyProblem #Arrival #Foundation #VideoEssay #FilmAnalysis #ScienceFiction

Quantum field theory | Free fields

Free field theory.
free field.
quantum field.theory.
quantum field theory in a nutshell pdf.
quantum field frequency.
quantum field theory problems and solutions pdf.
quantum field theory as simply as possible pdf.
quantum field theory for beginners.
quantum field theory books for beginners.
quantum field theory from basics to modern topics.
quantum field theory and critical phenomena pdf.
quantum field theory and critical phenomena.
quantum field theory problems and solutions.
difference between quantum field theory and quantum mechanics.
effective field theory mit.
e field equation.
effective field theory pdf.
fields in quantum field theory.
no-nonsense quantum field theory pdf.
quantum field theory and general relativity.
quantum field theory gravity.
h field equation.
free field hamiltonian.
quantum field theory handwritten notes.
the field quantum physics.
introduction to quantum field theory pdf.
quantum field theory pdf.
quantum field theory for mathematicians pdf.
m field theory.
quantum field theory mit.
no-nonsense quantum field theory a student-friendly introduction.
physics field theory.
philosophy of quantum field theory.
problems with quantum field theory.
quantum field theory vs quantum mechanics.
relativistic quantum field theory pdf.
relative quantum field theory.
quantum field theory research.
quantum field theory simple explanation.
quantum field theory srednicki pdf.
quantum field theory for undergraduates.
unified field theory vs quantum mechanics.
quantum field theory vs general relativity.
quantum field theory weinberg pdf.
quantum field theory experiments.
zee quantum field theory in a nutshell pdf.
quantum field theory zee pdf.
quantum field theory zee.
zee quantum field theory in a nutshell.
field theory physics pdf.
the quantum theory of fields volume 1
how many fields are there in quantum field theory.
quantum field theory for dummies.

The Rosetta Manifold: How AI Erased the Boundary Between Human Thought and Machine Syntax

The barrier between human thought and machine code is officially gone. 🤯

In my last deep dive, we explored “Vibecoding” and how creators are bypassing traditional development bottlenecks using pure vision. But how does AI actually turn your spoken intent into architecture?

AI doesn’t just use a massive translation dictionary. Instead, it operates in a hidden mathematical geometry known as the Latent Space.

In this invisible architecture, an English phrase and a complex Python script are mapped into the exact same coordinate of pure logic. This triggers a massive paradigm shift called Decision Compression—completely erasing the buggy, high-friction “Telephone Game” of traditional software development by binding your raw idea directly to execution.

If AI completely bypasses the need for manual translation, what happens to traditional coding syntax like Java or C++?

And more importantly, who becomes the ultimate builder in this new paradigm?

Read the full deep dive into the engine of the AI revolution!

Cliff Pickover (@pickover) on X

We aren’t the authors of our thoughts. We’re just the user interface. We look at the universe and see a solid reality. The universe looks at us and sees a line of code. We spend our lives trying to leave a mark on the surface of reality. Oblivious to the fact that our existence is being computed from beneath. We aren’t separate individuals. We’re just the localized tips of a single, massive mathematical architecture.👇

(PDF) Holographic Entanglement-Weighted de Sitter Gravity

🌌 Holographic theory suggests a profound idea: the universe may store information on its boundary, while the spacetime we experience emerges from that information. In this view, gravity is not only a force between masses.

https://doi.org/10.13140/RG.2.2.17062.

It may also be a macroscopic effect of quantum information, especially entanglement, encoded on a cosmic horizon. 🧠✨

A simple way to express this is:

Horizon information → Entanglement → Spacetime geometry.

To describe how efficiently entanglement becomes geometry, we introduce an entanglement-weight field:

Here, W(x) represents the conversion efficiency from holographic entanglement to gravitational geometry.

This modifies the effective strength of gravity:

The secret code behind the universe | Stephen Wolfram

Simple rules. Infinite complexity. Physicist Stephen Wolfram has spent forty years working out the connection. Here’s the short version.

❍ Subscribe to The Well on YouTube: https://bit.ly/welcometothewell.
❍ Up next: Why the answers to big questions are fundamentally unknowable | L.A. Paul • Why the answers to big decisions are funda…

Physicist Stephen Wolfram spent decades running computer experiments on simple rules — not looking for anything grand, just seeing what happened. What he found turned into a model of how the universe works, an explanation for why evolution never gets stuck, and a mathematical argument for why your life can’t be shortcut or predicted by anyone.

Read the full video transcript: https://bigthink.com/videos/the-unive

❍ About The Well ❍

Do we inhabit a multiverse? Do we have free will? What is love? Is evolution directional? There are no simple answers to life’s biggest questions, and that’s why they’re the questions occupying the world’s brightest minds.

Method for stress-testing cloud computing algorithms helps avoid network failures

This new approach can identify worse-case scenarios that an engineer might miss if they use a traditional method that compares an algorithm against a set of human-designed past test cases. It is also less labor-intensive than other verification tools that require engineers to rewrite an algorithm in a complex mathematical code each time they want to test it.

Instead of needing a mathematical reformulation, the new method reads the algorithm’s source code directly and automatically searches for worse-case scenarios that lead to the highest level of underperformance.

By helping engineers quickly and easily stress-test a networking algorithm before deployment, the method could catch failure modes that might otherwise only appear in a real outage. The technique could also be used to analyze the risks of deploying AI-generated code.

/* */