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Category: particle physics – Page 26

Carnegie Mellon University’s Professor Curtis Meyer and his research colleagues explore an uncharted world inside protons and neutrons. For the first time, researchers have provided measurements describing a maximum boundary for a subatomic particle known as a hybrid meson in a journal paper published in Physical Review Letters. The measurements show scientists a path forward in a search for these elusive particles that provide a new look at the force that holds all matter together.

“The stage is set for future discoveries,” said Meyer, senior associate dean for CMU’s Mellon College of Science and the Otto Stern Professor of Physics. “We’re at an exciting phase where we’re able to analyze a great deal of data. This paper is the first to address one of the experiment’s foundational questions.”

Applying a symmetry property of the strong force, the team set the upper limit on the photoproduction cross sections of a hybrid meson known as the spin-exotic π1 (1600).

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Scattering takes place across the universe at large and miniscule scales. Billiard balls clank off each other in bars, the nuclei of atoms collide to power the stars and create heavy elements, and even sound waves deviate from their original trajectory when they hit particles in the air.

Understanding such scattering can lead to discoveries about the forces that govern the universe. In a recent publication in Physical Review C, researchers from Lawrence Livermore National Laboratory (LLNL), the InQubator for Quantum Simulations and the University of Trento developed an algorithm for a quantum computer that accurately simulates scattering.

“Scattering experiments help us probe and their interactions,” said LLNL scientist Sofia Quaglioni. “The scattering of particles in matter [materials, atoms, molecules, nuclei] helps us understand how that matter is organized at a .”

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To identify signs of particles like the Higgs boson, CERN researchers work with mountains of data generated by LHC collisions.

Hunting for evidence of an object whose behavior is predicted by existing theories is one thing. But having successfully observed the elusive boson, identifying new and unexpected particles and interactions is an entirely different matter.

To speed up their analysis, physicists feed data from the billions of collisions that occur in LHC experiments into machine learning algorithms. These models are then trained to identify anomalous patterns.

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Imagine a world where your thoughts aren’t confined to the boundaries of your skull, where your consciousness is intimately connected to the universe around you, and where the neurons in your brain communicate instantly across vast distances.

This isn’t science fiction — it’s the intriguing possibility suggested by applying the principle of quantum entanglement to the realm of consciousness.

Quantum entanglement, often described as the “spooky action at a distance,” is a phenomenon that baffled even Einstein. In essence, it describes a scenario where two particles become so deeply linked that they share the same fate, regardless of the distance separating them. Measuring the state of one instantly reveals the state of its partner, even if they are light-years apart.

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A theoretical particle that travels faster than light, the tachyon has long intrigued physicists and fueled decades of speculation. Initially conceived as a possible solution to quantum and relativity paradoxes, tachyons remain purely hypothetical. Despite the lack of experimental evidence, they continue to serve as a thought-provoking concept in modern physics.

A recent study by an international team of researchers has reignited interest in tachyons, suggesting they might be possible within the framework of Einstein’s special theory of relativity. This bold claim challenges conventional understandings of causality and time, raising fundamental questions about the structure of reality. If confirmed, it could lead to a radical shift in how scientists perceive the limits of physical laws.

Physicist Gerald Feinberg introduced the idea of tachyons in 1962, proposing that such particles could always travel faster than light without ever slowing down to subluminal speeds. His argument was based on the concept of imaginary mass, a theoretical construct involving the square root of a negative number. This allowed for the mathematical possibility of faster-than-light motion without explicitly violating relativity.

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The rapid advancement of technologies like artificial intelligence (AI) and the Internet of Things (IoT) has heightened the demand for high-speed, energy-efficient memory devices. Traditional memory technologies often struggle to balance performance with power consumption.

Spintronic devices, which leverage electron spin rather than charge, present a promising alternative. In particular, TMD materials are attractive due to their unique electronic properties and potential for miniaturization.

Researchers have proposed the development of gate-controllable TMD spin valves to address these challenges. By integrating a gate mechanism, these devices can modulate spin transport properties, enabling precise control over memory operations. This approach aims to enhance tunneling magnetoresistance (TMR) ratios, improve spin current densities, and reduce during read and write processes. The study is published in the Journal of Alloys and Compounds.

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Enter laser-plasma accelerators (LPAs). LPAs use high-intensity lasers to strike a target, generating charged particle beams that reach comparable speeds to those produced using traditional accelerators – but in a fraction of the distance. Scientists are exploring LPAs as a compact, cost-effective way to generate proton beams, but several technical challenges have hindered their progress.

One challenge arises from the high-intensity laser, which destroys the targets after each pulse, requiring a new target for every shot. Another issue is the beam divergence – proton beams produced by LPAs typically spread out like a floodlight rather than maintaining a narrow focus. Both the need for target replacement and the beam divergence significantly reduce the efficiency of LPA systems.

In this recent study, researchers made an unexpected breakthrough, simultaneously resolving multiple problems although they had only aimed to address one.

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Entanglement—linking distant particles or groups of particles so that one cannot be described without the other—is at the core of the quantum revolution changing the face of modern technology.

While entanglement has been demonstrated in very small particles, new research from the lab of University of Chicago Pritzker School of Molecular Engineering (UChicago PME) Prof. Andrew Cleland is thinking big, demonstrating high-fidelity entanglement between two acoustic wave resonators.

The paper is published in Nature Communications.

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In a major milestone for particle physics, scientists at CERN’s Large Hadron Collider (LHC) have successfully observed top quarks—one of the most elusive and short-lived fundamental particles—being produced in a laboratory setting. This historic discovery sheds light on the nature of matter and offers new insights into the early Universe, marking a turning point in our understanding of subatomic particles.

Quarks are the fundamental building blocks of protons and neutrons, which in turn make up the atoms forming all matter in the Universe. There are six known types of quarks: up, down, charm, strange, top, and bottom. Among these, the top quark stands out due to its heavy mass and extreme instability.

Unlike protons or neutrons, which persist indefinitely under normal conditions, the top quark decays almost instantly, with a lifetime of just 5×10^−25 seconds. This fleeting existence has made direct observation challenging, making the latest results from the LHC a remarkable breakthrough in experimental physics.

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Scientists in Japan have now developed a groundbreaking spintronic device that allows for electrical control of magnetic states, drastically reducing power consumption. This breakthrough could revolutionize AI hardware by making chips far more energy-efficient, mirroring the way neural networks function.

Spintronic Devices: A Game-Changer for AI Hardware

AI is rapidly transforming industries, but as these technologies evolve, so does their demand for power. To sustain further advancements, AI chips must become more energy efficient.

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