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Army researchers developed a new way to protect and safeguard quantum information, moving quantum networks a step closer to reality.

Quantum information science is a rapidly growing interdisciplinary field exploring new ways of storing, manipulating and communicating information. Researchers want to create powerful computational capabilities using new hardware that operates on quantum physics principles.

For the Army, the new quantum paradigms could potentially lead to transformational capabilities in fast, efficient and secure collecting, exchanging and processing vast amounts of information on dynamic battlefields of the future.

Researchers at the Army Research Laboratory have developed a new method to protect and safeguard quantum information, moving quantum networks a step closer to reality.

Quantum information science is a rapidly growing interdisciplinary field exploring new ways of storing, manipulating and communicating information. Researchers aim to create powerful computational capabilities using new hardware that operates on quantum physics principles.

For the army, these new quantum paradigms could potentially lead to transformational capabilities in fast, efficient and secure collecting, exchanging and processing vast amounts of information on dynamic battlefields in the future.

Quantum information scientists have introduced a new method for machine learning classifications in quantum computing. The non-linear quantum kernels in a quantum binary classifier provide new insights for improving the accuracy of quantum machine learning, deemed able to outperform the current AI technology.

The research team led by Professor June-Koo Kevin Rhee from the School of Electrical Engineering, proposed a quantum classifier based on quantum state fidelity by using a different initial state and replacing the Hadamard classification with a swap test. Unlike the conventional approach, this method is expected to significantly enhance the classification tasks when the training dataset is small, by exploiting the quantum advantage in finding non-linear features in a large feature space.

Quantum machine learning holds promise as one of the imperative applications for quantum computing. In machine learning, one fundamental problem for a wide range of applications is classification, a task needed for recognizing patterns in labeled training data in order to assign a label to new, previously unseen data; and the kernel method has been an invaluable classification tool for identifying non-linear relationships in complex data.

MIT engineers develop a hybrid process that connects photonics with “artificial atoms,” to produce the largest quantum chip of its type.

Such noise nearly drowned out the signal in Google’s quantum supremacy experiment. Researchers began by setting the 53 qubits to encode all possible outputs, which ranged from zero to 2⁵³. They implemented a set of randomly chosen interactions among the qubits that in repeated trials made some outputs more likely than others. Given the complexity of the interactions, a supercomputer would need thousands of years to calculate the pattern of outputs, the researchers said. So by measuring it, the quantum computer did something that no ordinary computer could match. But the pattern was barely distinguishable from the random flipping of qubits caused by noise. “Their demonstration is 99% noise and only 1% signal,” Kuperberg says.

To realize their ultimate dreams, developers want qubits that are as reliable as the bits in an ordinary computer. “You want to have a qubit that stays coherent until you switch off the machine,” Neven says.

Scientists’ approach of spreading the information of one qubit—a “logical qubit”—among many physical ones traces its roots to the early days of ordinary computers in the 1950s. The bits of early computers consisted of vacuum tubes or mechanical relays, which were prone to flip unexpectedly. To overcome the problem, famed mathematician John von Neumann pioneered the field of error correction.

New insight into the spin behavior in an exotic state of matter puts us closer to next-generation spintronic devices.

Aside from the deep understanding of the natural world that quantum physics theory offers, scientists worldwide are working tirelessly to bring forth a technological revolution by leveraging this newfound knowledge in engineering applications. Spintronics is an emerging field that aims to surpass the limits of traditional electronics by using the spin of electrons, which can be roughly seen as their angular rotation, as a means to transmit information.

But the design of devices that can operate using spin is extremely challenging and requires the use of new materials in exotic states–even some that scientists do not fully understand and have not experimentally observed yet. In a recent study published in Nature Communications, scientists from the Department of Applied Physics at Tokyo University of Science, Japan, describe a newly synthesized compound with the formula KCu₆AlBiO₄(SO₄)₅Cl that may be key in understanding the elusive “quantum spin liquid (QSL)” state. Lead scientist Dr Masayoshi Fujihala explains his motivation: “Observation of a QSL state is one of the most important goals in condensed-matter physics as well as the development of new spintronic devices. However, the QSL state in two-dimensional (2D) systems has not been clearly observed in real materials owing to the presence of disorder or deviations from ideal models.”

A deep tech startup building cryptographic solutions to secure hardware, software, and communications systems for a future when quantum computers may render many current cybersecurity approaches useless is today emerging out of stealth mode with $7 million in funding and a mission to make cryptographic security something that cannot be hackable, even with the most sophisticated systems, by building systems today that will continue to be usable in a post-quantum future.

PQShield (PQ being short for “post-quantum”), a spin out from Oxford University, is being backed in a seed round led by Kindred Capital, with participation also Crane Venture Partners, Oxford Sciences Innovation and various angel investors, including Andre Crawford-Brunt, Deutsche Bank’s former global head of equities.

PQShield was founded in 2018, and its time in stealth has not been in vain.

A ringing bell vibrates simultaneously at a low-pitched fundamental tone and at many higher-pitched overtones, producing a pleasant musical sound. A recent study, just published in the Journal of the Atmospheric Sciences by scientists at Kyoto University and the University of Hawai’i at Mānoa, shows that the Earth’s entire atmosphere vibrates in an analogous manner, in a striking confirmation of theories developed by physicists over the last two centuries.

In the case of the atmosphere, the “music” comes not as a sound we could hear, but in the form of large-scale waves of atmospheric pressure spanning the globe and traveling around the equator, some moving east-to-west and others west-to-east. Each of these waves is a resonant vibration of the global atmosphere, analogous to one of the resonant pitches of a bell. The basic understanding of these atmospheric resonances began with seminal insights at the beginning of the 19th century by one of history’s greatest scientists, the French physicist and mathematician Pierre-Simon Laplace. Research by physicists over the subsequent two centuries refined the theory and led to detailed predictions of the wave frequencies that should be present in the atmosphere. However, the actual detection of such waves in the real world has lagged behind the theory.

Now in a new study by Takatoshi Sakazaki, an assistant professor at the Kyoto University Graduate School of Science, and Kevin Hamilton, an Emeritus Professor in the Department of Atmospheric Sciences and the International Pacific Research Center at the University of Hawai?i at Mānoa, the authors present a detailed analysis of observed atmospheric pressure over the globe every hour for 38 years. The results clearly revealed the presence of dozens of the predicted wave modes.

Although we usually have a pretty good handle on all the different kinds of blips and blobs detected by our telescopes, it would be unwise to assume we’ve seen everything there is to see out there in the big, wide Universe. Case in point: a new kind of signal spotted by radio telescopes, which has astronomers scratching their heads.

Four of these strange objects have been detected. All of them are circular in shape, and three are particularly bright around the edges — like a ring, or a bubble that is more opaque around the edges.

An international team of astronomers led by astrophysicist Ray Norris of Western Sydney University in Australia has nicknamed them ORCs — short for “Odd Radio Circles” — in a new paper posted to arXiv and submitted to Nature Astronomy, where it awaits peer review.