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(PhysOrg.com) — By greatly amplifying one photon from an entangled photon pair, physicists have theoretically shown that human eyes can be used as detectors to observe quantum effects. Usually, detecting quantum phenomena requires sensitive photon detectors or similar technology, keeping the quantum world far removed from our everyday experience. By showing that it’s possible to perform quantum optics experiments with human eyes as detectors, the physicists can bring quantum phenomena closer to the macroscopic level and to everyday life.

The group of physicists is from the University of Geneva, and includes Pavel Sekatski, Nicolas Brunner (also from the University of Bristol), Cyril Branciard, Nicolas Gisin, and Christoph Simon. In their study published in a recent issue of Physical Review Letters, the scientists theoretically show how human eyes can be used to detect a large Bell inequality violation, which proves the existence of quantum entanglement.

As the physicists explain, the key to achieving human-eye detection of quantum effects is to use the process of quantum cloning by stimulated emission. Recently, using quantum cloning, researchers in Rome have experimentally created tens of thousands of clones starting from a single-photon. Then, by amplifying one photon of an entangled pair, the researchers managed to demonstrate entanglement. In order to do this, specific detectors are required, which can distinguish two orthogonal amplified states with a high success rate.

James McKenzie is excited about the prospects of firms that are developing technology based on seemingly esoteric fundamental quantum phenomena.

Physicists have long boasted of their success in what’s known as “quantum 1.0” technology – semiconductor junctions, transistors, lasers and so on. Thanks to their efforts over the last 75 years, we have smart phones, computers, laptops and other quantum-enabled devices that have transformed our lives. But the future will increasingly depend on “quantum 2.0” technology, which taps into phenomena like superposition and entanglement to permit everything from quantum computing and cryptography to quantum sensing, timing and imaging.

The incredible possibilities of quantum 2.0 were brought home to me when I attended the UK’s National Quantum Technologies Showcase in central London last month. The event featured more than 60 exhibitors and I was amazed how far things have progressed. In fact, it coincided with two positive developments. One was an announcement by UK Research and Innovation (UKRI) of a further £50m to support quantum industrial projects. The other was the UK and US signing a joint “statement of intent” to boost collaboration on quantum science and technologies.

What’s New: In its relentless pursuit of Moore’s Law, Intel is unveiling key packaging, transistor and quantum physics breakthroughs fundamental to advancing and accelerating computing well into the next decade. At IEEE International Electron Devices Meeting (IEDM) 2021, Intel outlined its path toward more than 10x interconnect density improvement in packaging with hybrid bonding, 30% to 50% area improvement in transistor scaling, major breakthroughs in new power and memory technologies, and new concepts in physics that may one day revolutionize computing.

“At Intel, the research and innovation necessary for advancing Moore’s Law never stops. Our Components Research Group is sharing key research breakthroughs at IEDM 2021 in bringing revolutionary process and packaging technologies to meet the insatiable demand for powerful computing that our industry and society depend on. This is the result of our best scientists’ and engineers’ tireless work. They continue to be at the forefront of innovations for continuing Moore’s Law.” –Robert Chau, Intel Senior Fellow and general manager of Components Research

Why It Matters: Moore’s Law has been tracking innovations in computing that meet the demands of every technology generation from mainframes to mobile phones. This evolution is continuing today as we move into a new era of computing with unlimited data and artificial intelligence.

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Researchers in Finland have developed a circuit that produces the high-quality microwave signals required to control quantum computers while operating at temperatures near absolute zero. This is a key step towards moving the control system closer to the quantum processor, which may make it possible to greatly increase the number of qubits in the processor.

One of the factors limiting the size of quantum computers is the mechanism used to control the qubits in quantum processors. This is normally accomplished using a series of microwave pulses, and because quantum processors operate at temperatures near absolute zero, the control pulses are normally brought into the cooled environment via broadband cables from room temperature.

As the number of qubits grows, so does the number of cables needed. This limits the potential size of a quantum processor, because the refrigerators cooling the qubits would have to become larger to accommodate more and more cables while also working harder to cool them down—ultimately a losing proposition.

While they wrestle with the immediate danger posed by hackers today, US government officials are preparing for another, longer-term threat: attackers who are collecting sensitive, encrypted data now in the hope that they’ll be able to unlock it at some point in the future.

The threat comes from quantum computers, which work very differently from the classical computers we use today. Instead of the traditional bits made of 1s and 0s, they use quantum bits that can represent different values at the same time. The complexity of quantum computers could make them much faster at certain tasks, allowing them to solve problems that remain practically impossible for modern machines—including breaking many of the encryption algorithms currently used to protect sensitive data such as personal, trade, and state secrets.

While quantum computers are still in their infancy, incredibly expensive and fraught with problems, officials say efforts to protect the country from this long-term danger need to begin right now.

These longstanding challenges are both related to how functionals behave when presented with a system that exhibits “fractional electron character.” By using a neural network to represent the functional and tailoring our training dataset to capture the fractional electron behaviour expected for the exact functional, we found that we could solve the problems of delocalization and spin symmetry-breaking. Our functional also showed itself to be highly accurate on broad, large-scale benchmarks, suggesting that this data-driven approach can capture aspects of the exact functional that have thus far been elusive.

For years, computer simulations have played a central role in modern engineering, making it possible to provide reliable answers to questions like “will this bridge stay up?” to “will this rocket make it into space?” As technology increasingly turns to the quantum scale to explore questions about materials, medicines, and catalysts, including those we’ve never seen or even imagined, deep learning shows promise to accurately simulate matter at this quantum mechanical level.

Researchers at Lawrence Berkeley National Laboratory’s Advanced Quantum Testbed (AQT) demonstrated that an experimental method known as randomized compiling (RC) can dramatically reduce error rates in quantum algorithms and lead to more accurate and stable quantum computations. No longer just a theoretical concept for quantum computing, the multidisciplinary team’s breakthrough experimental results are published in Physical Review X.

The experiments at AQT were performed on a four-qubit superconducting quantum processor. The researchers demonstrated that RC can suppress one of the most severe types of errors in quantum computers: coherent errors.

Akel Hashim, AQT researcher, involved in the experimental breakthrough and a graduate student at the University of California, Berkeley explained: “We can perform quantum computations in this era of noisy intermediate-scale quantum (NISQ) computing, but these are very noisy, prone to errors from many different sources, and don’t last very long due to the decoherence—that is, information loss—of our qubits.”