Seven quantum hardware companies have been awarded multimillion-pound contracts to build a series of quantum testbeds at the National Quantum Computing Centre by March 2025.
Researchers at the University of California, Irvine and Los Alamos National Laboratory, publishing in the latest issue of Nature Communications, describe the discovery of a new method that transforms everyday materials like glass into materials scientists can use to make quantum computers.
“The materials we made are substances that exhibit unique electrical or quantum properties because of their specific atomic shapes or structures,” said Luis A. Jauregui, professor of physics & astronomy at UCI and lead author of the new paper. “Imagine if we could transform glass, typically considered an insulating material, and convert it into efficient conductors akin to copper. That’s what we’ve done.”
Conventional computers use silicon as a conductor, but silicon has limits. Quantum computers stand to help bypass these limits, and methods like those described in the new study will help quantum computers become an everyday reality.
Are you curious about the future of Artificial Intelligence (AI) and how it will be impacted by Quantum Computing? Join us on an exciting journey into the world of technology as we explore how Quantum Computing is set to revolutionize AI by the year 2027. In this video, we will delve into the fascinating realm of Quantum Computing and its implications for the future of AI.
Quantum Computing, a cutting-edge field in computer science, harnesses the principles of quantum mechanics to perform computations at speeds unimaginable with traditional computers. By leveraging the power of quantum bits or qubits, Quantum Computing has the potential to exponentially increase processing power, enabling AI systems to tackle complex problems with unprecedented efficiency and accuracy. Imagine a world where AI algorithms can analyze vast amounts of data in seconds, leading to groundbreaking discoveries and innovations across various industries.
Continue reading “Quantum Computing Will Transform AI by 2027” »
Quantum nanophotonics examines the interaction between emitters and light confined at the nanoscale. This Review highlights the experimental progress in the field, explains new light–matter interaction regimes and emphasizes their potential applications in quantum technologies.
Photonic integrated circuits are an important next-wave technology. These sophisticated microchips hold the potential to substantially decrease costs and increase speed and efficiency for electronic devices across a wide range of application areas, including automotive technology, communications, health care, data storage, and computing for artificial intelligence.
Photonic circuits use photons, fundamental particles of light, to move, store, and access information in much the same way that conventional electronic circuits use electrons for this purpose. Photonic chips are already in use today in advanced fiber-optic communication systems, and they are being developed for implementation in a broad spectrum of near-future technologies, including light detection and ranging, or LiDAR, for autonomous vehicles; light-based sensors for medical devices; 5G and 6G communication networks; and optical and quantum computing.
Given the broad range of existing and future uses for photonic integrated circuits, access to equipment that can fabricate chip designs for study, research and industrial applications is also important. However, today’s nanofabrication facilities cost millions of dollars to construct and are well beyond the reach of many colleges, universities, and research labs.
Using this technique, even a non-conducting material like glass could be turned into a conductor some day feel researchers.
A collaboration between scientists at the University of California, Irvine (UCI) and Los Alamos National Laboratory (LANL) has developed a method that converts everyday materials into conductors that can be used to build quantum computers, a press release said.
Computing devices that are ubiquitous today are built of silicon, a semiconductor material. Under certain conditions, silicon behaves like a conducting material but has limitations that impact its ability to compute larger numbers. The world’s fastest supercomputers are built by putting together silicon-based components but are touted to be slower than quantum computers.
Continue reading “Tiny ‘bending station’ transforms everyday materials into quantum conductors” »
The physicists found that if electron transport alone is taken into account, the cuprates’ Lorenz number – their ratio of thermal conductivity to electrical conductivity divided by temperature – approaches the value predicted by the Wiedemann-Franz law. The team suggest that other factors, such as lattice vibrations (or phonons), which are not included in the Hubbard model, could be responsible for discrepancies observed in experiments on strongly correlated materials that make it appear as if the law does not apply. Their results could help physicists interpret these experimental observations and could ultimately lead to a better understanding of how strongly correlated systems might be employed in applications such as data processing and quantum computing.
The team now plans to build on the result by exploring other transport channels such as thermal Hall effects. “This will deepen our understanding of transport theories in strongly correlated materials,” Wang tells Physics World.
The present study is published in Science.
An idea derived from string theory suggests that dark matter is hiding in a (relatively) large extra dimension. The theory makes testable predictions that physicists are investigating now.
