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Researchers have found a way to control the interaction of light and quantum ‘spin’ in organic semiconductors, that works even at room temperature.

Spin is the term for the intrinsic angular momentum of electrons, which is referred to as up or down. Using the up/down spin states of electrons instead of the 0 and 1 in conventional computer logic could transform the way in which computers process information. And sensors based on quantum principles could vastly improve our abilities to measure and study the world around us.

An international team of researchers, led by the University of Cambridge, has found a way to use particles of light as a ‘switch’ that can connect and control the spin of electrons, making them behave like tiny magnets that could be used for quantum applications.

Quantum computers are the next step in computation. These devices can harness the peculiarities of quantum mechanics to dramatically boost the power of computers. Not even the most powerful supercomputer can compete with this approach. But to deliver on that incredible potential, the road ahead remains long.

Still, in the last few years, big steps have been taken, with simple quantum processors coming online. New breakthroughs have shown solutions to the major challenges in the discipline. The road is still long, but now we can see several opportunities along the way. For The Big Questions, IFLScience’s podcast, we spoke to Professor Winfried Hensinger, Professor of Quantum Technology at the University of Sussex and the Chief Scientific Officer for Universal Quantum, about the impact these devices will have.

AI can be fooled into making mistakes, sometimes risking lives, but quantum computing could provide a strong defence, say University of Melbourne experts.

A mysterious quantum phenomenon reveals an image of an atom like never before. You can even see the difference between protons and neutrons.

The Relativistic Heavy Ion Accelerator (RHIC), from the Brookhaven Laboratory in the United States, is a sophisticated device capable of accelerating gold ions to a speed of up to 99.995% that of light. Thanks to him, it has recently been possible to verify, for example, Einstein’s famous equation E=mc².

Timothy Gray of the Department of Energy’s Oak Ridge National Laboratory led a study that may have revealed an unexpected change in the shape of an atomic nucleus. The surprise finding could affect our understanding of what holds nuclei together, how protons and neutrons interact and how elements form.

“We used radioactive beams of excited sodium-32 nuclei to test our understanding of nuclear shapes far from stability and found an unexpected result that raises questions about how nuclear shapes evolve,” said Gray, a nuclear physicist. The results are published in Physical Review Letters.

The shapes and energies of atomic nuclei can shift over time between different configurations. Typically, nuclei live as quantum entities that have either spherical or deformed shapes. The former look like basketballs, and the latter resemble American footballs.

A breakthrough at the Massachusetts Institute of Technology (MIT), funded by the Department of Energy (DOE), is utilizing the power of DNA to align quantum rods that may help usher in a new era of enhanced televisions and ultra-realistic virtual reality (VR) devices.

Some modern high-end TVs already make use of the dynamic luminescent qualities of two-dimensional (2D) quantum dots, but finding a way to tap into the superior qualities of their two-dimensional cousins, quantum rods, has remained elusive. However, the researchers behind this latest effort claim that the situation has now changed.

The Secrets of Realistic VR and Star Trek Holodecks May Lie in the Quantum Realm.

UC San Diego’s Q-MEEN-C is developing brain-like computers through mimicking neurons and synapses in quantum materials. Recent discoveries in non-local interactions represent a critical step towards more efficient AI hardware that could revolutionize artificial intelligence technology.

We often believe that computers are more efficient than humans. After all, computers can solve complex math equations in an instant and recall names that we might forget. However, human brains can process intricate layers of information rapidly, accurately, and with almost no energy input. Recognizing a face after seeing it only once or distinguishing a mountain from an ocean are examples of such tasks. These seemingly simple human functions require considerable processing and energy from computers, and even then, the results may vary in accuracy.

How close the measured value conforms to the correct value.

A groundbreaking theoretical proof reveals that using a technique called overparametrization enhances performance in quantum machine learning.

Machine learning is a subset of artificial intelligence (AI) that deals with the development of algorithms and statistical models that enable computers to learn from data and make predictions or decisions without being explicitly programmed to do so. Machine learning is used to identify patterns in data, classify data into different categories, or make predictions about future events. It can be categorized into three main types of learning: supervised, unsupervised and reinforcement learning.

Scientists at University College Cork have uncovered a unique superconducting state in Uranium Ditelluride, which could pave the way for more stable and efficient quantum computers. This groundbreaking discovery offers a potential solution to one of quantum computing.

Performing computation using quantum-mechanical phenomena such as superposition and entanglement.