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Category: quantum physics – Page 190

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Theoretical physicists employ their imaginations and their deep understanding of mathematics to decipher the underlying laws of the universe that govern particles, forces and everything in between. More and more often, theorists are doing that work with the help of machine learning.

As might be expected, the group of theorists using machine learning includes people classified as “computational” theorists. But it also includes “formal” theorists, the people interested in the self-consistency of theoretical frameworks, like string theory or quantum gravity. And it includes “phenomenologists,” the theorists who sit next to experimentalists, hypothesizing about new particles or interactions that could be tested by experiments; analyzing the data the experiments collect; and using results to construct new models and dream up how to test them experimentally.

In all areas of theory, machine-learning algorithms are speeding up processes, performing previously impossible calculations, and even causing theorists to rethink the way theoretical physics research is done.

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ARMONK, N.Y., April 30, 2024 — Today, IBM (NYSE: IBM) has announced an agreement with RIKEN, a Japanese national research laboratory, to deploy IBM’s next-generation quantum computer architecture and best-performing quantum processor at the RIKEN Center for Computational Science in Kobe, Japan. It will be the only instance of a quantum computer co-located with the supercomputer Fugaku.

This agreement was executed as part of RIKEN’s existing project, supported by funding from the New Energy and Industrial Technology Development Organization (NEDO), an organization under Japan’s Ministry of Economy, Trade and Industry (METI)’s “Development of Integrated Utilization Technology for Quantum and Supercomputers” as part of the “Project for Research and Development of Enhanced Infrastructures for Post 5G Information and Communications Systems.” RIKEN has dedicated use of an IBM Quantum System Two architecture for the purpose of implementation of its project. Under the project RIKEN and its co-PI SoftBank Corp., with its collaborators, University of Tokyo, and Osaka University, aim to demonstrate the advantages of such hybrid computational platforms for deployment as services in the future post-5G era, based on the vision of advancing science and business in Japan.

In addition to the project, IBM will work to develop the software stack dedicated to generating and executing integrated quantum-classical workflows in a heterogeneous quantum-HPC hybrid computing environment. These new capabilities will be geared towards delivering improvements in algorithm quality and execution times.

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The elegant equations of classical electromagnetism written by James Clark Maxwell in 1861 display a remarkable symmetry between electric and magnetic fields except for their sources. We know about electric charges but we have not found magnetic charges. Bar magnets are dipoles with two poles, north and south, for the magnetic field, resembling the configuration of an electric field sourced by a pair of positive and negative electric charges. However, we had never seen experimental evidence for a magnetic monopole, namely a magnetic charge with only one magnetic pole, a net north or south, from where magnetic field lines emanate, just like the electric field sourced by an electric charge. In a symmetric theory of electromagnetism, magnetic monopoles should exist.

The existence of monopoles with a net magnetic charge was proposed by Paul Dirac in 1931 to explain the quantized (discrete) values of electric charges. Dirac found that magnetic charges should be an integer multiple of a fundamental unit, g_D, equal to the electron charge, e, divided by twice the fine-structure constant, or about 68.5e.

In classical physics, the existence of magnetic monopoles restores symmetry to Maxwell’s equations. But in the broader context of quantum mechanics, Gerard ‘t Hooft and Alexander Polyakov showed in 1974 that magnetic monopoles are required in Grand Unified Theories of the strong, weak and electromagnetic interactions. Since the electric charge is quantized, magnetic charges are unavoidable in these theories. Magnetic charges with the lowest mass must be stable because magnetic charge is conserved and they cannot decay into lower-mass particles.

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Recently I saw a post on twitter claiming that AI could be powered with quantum vacuum energy. The post was accompanied by a figure from a paper published in Nature. Unfortunately for the poster, but fortunately for science, the paper had nothing to do with extracting energy from the vacuum. Rather, it was a description of an experimental realization of a transistor that uses the Casimir effect to mediate and amplify energy transfer across a new kind of transistor.

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