Scientists have made the first experimental observation of matter wave diffraction in a short-lived electron-positron atom.
NPL, the UK’s National Metrology Institute (NMI), plays a central role in providing accurate and trusted measurement across emerging technology. Within its Institute for Quantum Standards and Technology (IQST), the team is developing methods to characterize and calibrate quantum devices, particularly quantum computing.
As part of a new collaboration, NPL is integrating NVIDIA’s Ising AI tools into its quantum measurement systems to automate key calibration tasks. This approach will help address one of the major challenges facing quantum computing: the need to manage large numbers of qubits, each affected by multiple sources of noise and instability.
Qubit performance is commonly assessed using metrics such as the qubit relaxation time, usually referred to as T1 time, which is a metric for the timescale at which a qubit decays from its excited state to the ground state. These values can fluctuate or drift due to interactions with the environment, requiring frequent checks to ensure reliable operation. Traditionally, such checks are carried out manually by experts.
Thin films might not come up in conversation every day, but they are all around us. Take the metallic plastic films of chip bags, for example, or the anti-reflective coatings on eyeglasses. Even the coatings on pills that make them easier to swallow are thin films. Depositing extremely thin layers of materials in a consistent and uniform way is also crucial to the production of semiconductors, which are the foundation of modern electronics.
Not all materials can be easily deposited in such thin layers, such as materials with very high melting points. Now, Caltech researchers led by Austin Minnich, professor of mechanical engineering and applied physics, and deputy chair of the Division of Engineering and Applied Science, have demonstrated a laser-based method for generating thin films of materials, such as niobium. The work could directly impact superconducting electronics used in quantum computers.
The team recently described the work in a paper published in the journal Applied Physics Letters.
A new Bar-Ilan University study points to a major advance in quantum information processing, demonstrating a way to send, manipulate, and measure quantum information across many frequency channels simultaneously, rather than one at a time. The study was recently published in the journal Science Advances.
The approach could allow quantum communication technologies, including secure key distribution and quantum teleportation, to operate far more efficiently by taking advantage of the enormous bandwidth already available in quantum light sources.
Today, one of the main limits in quantum information processing is not the light source itself, but the measurement technology. Quantum light sources can operate across an extremely broad optical spectrum, but standard detectors can measure only a tiny fraction of that bandwidth. As a result, much of the available capacity goes unused.
Also known as magnetoelectronics, spintronics rely on electron spin rather than electron charge, as found in traditional electronics. Although spintronics is still an emerging field, spintronic technologies are already found in hard disk drives and giant magnetoresistance sensors used in industrial and automotive applications. Once the right foundational materials are discovered and verified, including economical materials for altermagnets, spintronics could advance technologies from wireless communication to quantum computing.
Researchers using neutrons at the Department of Energy’s Oak Ridge National Laboratory’s Spallation Neutron Source (SNS) discovered that hematite, essentially rust, can help design energy-efficient spintronics.
The team’s findings, published in Physical Review Letters, confirmed a key signature of altermagnetism (a new type of magnetism discovered in 2022) in hematite. Altermagnets are magnetic materials in which electron spins align in opposite directions, allowing pure spin currents to flow without a net electric charge—ideal conditions for spintronics. The team measured spin waves, which move through a material’s magnetic order similar to how sound waves move through air. They discovered that these waves show a clear separation in energy, a unique signature that confirms the material’s altermagnetic nature.
The spin-off company ParityQC has implemented the largest quantum Fourier transform ever reported using an IBM quantum computer, thereby setting a new milestone on the path toward the industrial application of quantum computers. The quantum Fourier transform is a cornerstone algorithm with applications in cryptography, financial modeling, and materials science.
Innsbruck-based quantum architecture company ParityQC performed a quantum Fourier transform using 52 superconducting qubits on an IBM Heron quantum processor. This surpasses the previous record of 27 qubits, which was set two years ago using an ion-trap quantum computer. The results were published this week on the arXiv preprint server.
“This milestone was only possible through the synergy of IBM’s latest quantum hardware and the ParityQC Architecture, which unlocked an exponential improvement in efficiency,” say Wolfgang Lechner and Magdalena Hauser, Co-CEOs of ParityQC. “What we are witnessing is European quantum innovation taking a global lead in translating theoretical potential into real-world performance.”
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Physics is this close to understanding the entire universe. And what lives in this gap? Many physicists think it’s the elusive graviton—the quantum particle of gravity—whose discovery will finally allow us to stitch together our two great theories of nature into a single master theory. But what is the graviton, and does it even exist?
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The new research explores a universe with more dimensions than the familiar four. In this framework, the cosmos contains seven dimensions, three of which are compact and invisible at everyday scales.
“We experience three dimensions of space and one of time — four dimensions in total,” Pinčák said. “Our model proposes that the universe actually has seven dimensions: the four we know, plus three tiny extra dimensions curled up so tightly that we cannot directly perceive them.”
These extra dimensions are arranged in a highly symmetrical structure known as a G₂ geometry. This mathematical framework, often explored in advanced theories such as a version of string theory known as M-theory, determines how the hidden dimensions are “folded.”
Following thinkers like Aristotle—viewed infinity as a never-ending process rather than a completed object. In the late 19th century, Georg Cantor revolutionized this view by treating infinite sets as mathematical objects that could be compared and studied. His work showed that not all infinities are equal, and that there are infinitely many different sizes of infinity. While his ideas are foundational in modern mathematics, some philosophical schools, such as finitism and ultrafinitism, continue to question whether infinite objects meaningfully exist.
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We would hope that the moment that we eternally live in, the “now,” would have a concrete scientific explanation. But the truth is far more complicated, says the relativity of simultaneity.
Jim Al-Khalili explains how the past and future are more fluid than we may think.
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About Jim Al-Khalili: Jim is a multiple award-winning science communicator renowned for his public engagement around the world through writing and broadcasting and a leading academic making fundamental contributions to theoretical physics, particularly in nuclear reaction theory, quantum effects in biology, open quantum systems and the foundations of quantum mechanics. Jim is a theoretical physicist at the University of Surrey where he holds a Distinguished Chair in physics as well as a university chair in the public engagement in science. He received his PhD in nuclear reaction theory in 1989 and has published widely in the field. His current interest is in open quantum systems and the application of quantum mechanics in biology.
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