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Category: particle physics – Page 328

Researchers at the Max Planck Institute for Intelligent Systems (MPI-IS), Cornell University and Shanghai Jiao Tong University have developed collectives of microrobots which can move in any desired formation. The miniature particles are capable of reconfiguring their swarm behavior quickly and robustly. Floating on the surface of water, the versatile microrobotic disks can go round in circles, dance the boogie, bunch up into a clump, spread out like gas or form a straight line like beads on a string.

Each robot is slightly bigger than a hair’s width. They are 3D printed using a polymer and then coated with a thin top layer of cobalt. Thanks to the metal the microrobots become miniature magnets. Meanwhile, wire coils which create a magnetic field when electricity flows through them surround the setup. The magnetic field allows the particles to be precisely steered around a one-centimeter-wide pool of water. When they form a line, for instance, the researchers can move the robots in such a way that they “write” letters in the water. The research project of Gaurav Gardi and Prof. Metin Sitti from MPI-IS, Steven Ceron and Prof. Kirstin Petersen from Cornell University and Prof. Wendong Wang from Shanghai Jiao Tong University titled “Microrobot Collectives with Reconfigurable Morphologies, Behaviors, and Functions” was published in Nature Communications on April 26, 2022.

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Are you ready?

In the control room at CERN (The European Center for Nuclear Research) is a row of empty champagne bottles. Scientists popped open each one to celebrate a successful landmark, like the discovery of the Higgs boson particle, the long-elusive particle that gives all other subatomic particles their mass.

⚛️ Science explains the world around us. We’ll help you unravel its mysteries.

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April 26 (Reuters) — Computers using light rather than electric currents for processing, only years ago seen as research projects, are gaining traction and startups that have solved the engineering challenge of using photons in chips are getting big funding.

In the latest example, Ayar Labs, a startup developing this technology called silicon photonics, said on Tuesday it had raised $130 million from investors including chip giant Nvidia Corp (NVDA.O).

While the transistor-based silicon chip has increased computing power exponentially over past decades as transistors have reached the width of several atoms, shrinking them further is challenging. Not only is it hard to make something so miniscule, but as they get smaller, signals can bleed between them.

The Large Hadron Collider. xenotar/iStock

Whoosh!

After three years of maintenance and upgrades, the Large Hadron Collider — one of the most powerful scientific instruments ever built — has whizzed past its own record. In preparation for its third major run of experiments, the particle accelerator has created the most energetic beams of protons ever made by humans. The particles went racing around the 17-mile (27 km) tunnel near Geneva, Switzerland, with an energy of 6.8 trillion electronvolts (TeV).

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“You can do it quickly, you can do it cheaply, or you can do it right. We did it right.” These were some of David Toback opening remarks when the leader of Fermilab’s Collider Detector unveiled the results of a decade-long experiment to measure the mass of a particle known as the W boson.

I am a high energy particle physicist, and I am part of the team of hundreds of scientists that built and ran the Collider Detector at Fermilab in Illinois – known as CDF.

After trillions of collisions and years of data collection and number crunching, the CDF team found that the W boson has slightly more mass than expected. Though the discrepancy is tiny, the results, described in a paper published in the journal Science on April 7, 2022, have electrified the particle physics world. If the measurement is indeed correct, it is yet another strong signal that there are missing pieces to the physics puzzle of how the universe works.

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April, 2022

Sean Carroll (Caltech and Santa Fe Institute)
https://simons.berkeley.edu/events/causality-program-externa…-institute.
Causality.

Abstract:

A macroscopic arrow of time can be derived from reversible and time-symmetric fundamental laws if we assume an appropriate notion of coarse-graining and a Past Hypothesis of low entropy at early times. It is an ongoing project to show how familiar aspects of time’s arrow, such as the fact that causes precede effects, can be derived from such a formalism. I will argue that the causal arrow arises naturally when we describe macroscopic systems in terms of a causal network, and make some suggestions about how to fit prediction and memory into this framework.

Sean Carroll is a Research Professor of theoretical physics at the California Institute of Technology, and Fractal Faculty at the Santa Fe Institute. He received his Ph.D. in 1993 from Harvard University. His research focuses on foundational questions in quantum mechanics, spacetime, cosmology, emergence, entropy, and complexity, occasionally touching on issues of dark matter, dark energy, symmetry, and the origin of the universe. Carroll is the author of Something Deeply Hidden, The Big Picture, The Particle at the End of the Universe, From Eternity to Here, and Spacetime and Geometry: An Introduction to General Relativity. He has been awarded prizes and fellowships by the National Science Foundation, NASA, the Sloan Foundation, the Packard Foundation, the American Physical Society, the American Institute of Physics, the American Association for the Advancement of Science, the Freedom From Religion Foundation, the Royal Society of London, and the Guggenheim Foundation. Carroll has appeared on TV shows such as The Colbert Report, PBS’s NOVA, and Through the Wormhole with Morgan Freeman, and frequently serves as a science consultant for film and television. He is host of the weekly Mindscape podcast. He lives in Los Angeles with his wife, writer Jennifer Ouellette.

Continue reading “The Arrow of Time in Causal Networks” | >

Over the course of almost 60 years, the information age has given the world the internet, smart phones, and lightning-fast computers. This has been made possible by about doubling the number of transistors that can be packed onto a computer chip every two years, resulting in billions of atomic-scale transistors that can fit on a fingernail-sized device. Even individual atoms may be observed and counted within such “atomic scale” lengths.

Physical limit

With this doubling reaching its physical limit, the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) has joined industry efforts to prolong the process and find new techniques to make ever-more powerful, efficient, and cost-effective chips. In the first PPPL research conducted under a Cooperative Research and Development Agreement (CRADA) with Lam Research Corp., a global producer of chip-making equipment, laboratory scientists properly predicted a fundamental phase in atomic-scale chip production through the use of modeling.

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Where is all the new physics? In the decade since the Higgs boson’s discovery, there have been no statistically significant hints of new particles in data from the Large Hadron Collider (LHC). Could they be sneaking past the standard searches? At the recent Rencontres de Moriond conference, the ATLAS collaboration at the LHC presented several results of novel types of searches for particles predicted by supersymmetry.

Supersymmetry, or SUSY for short, is a promising theory that gives each elementary particle a “superpartner”, thus solving several problems in the current Standard Model of particle physics and even providing a possible candidate for dark matter. ATLAS’s new searches targeted charginos and neutralinos – the heavy superpartners of force-carrying particles in the Standard Model – and sleptons – the superpartners of Standard Model matter particles called leptons. If produced at the LHC, these particles would each transform, or “decay”, into Standard Model particles and the lightest neutralino, which does not further decay and is taken to be the dark-matter candidate.

ATLAS’s newest search for charginos and sleptons studied a particle-mass region previously unexplored due to a challenging background of Standard Model processes that mimics the signals from the sought-after particles. The ATLAS researchers designed dedicated searches for each of these SUSY particle types, using all the data recorded from Run 2 of the LHC and looking at the particles’ decays into two charged leptons (electrons or muons) and “missing energy” attributed to neutralinos. They used new methods to extract the putative signals from the background, including machine-learning techniques and “data-driven” approaches.

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