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Category: quantum physics – Page 697

As multiple research groups around the world race to build a scalable quantum computer, questions remain about how the achievement of quantum supremacy will be verified.

Quantum supremacy is the term that describes a quantum ’s ability to solve a computational task that would be prohibitively difficult for any classical algorithm. It is considered a critical milestone in , but because the very nature of quantum activity defies traditional corroboration, there have been parallel efforts to find a way to prove that quantum supremacy has been achieved.

Researchers at the University of California, Berkeley, have just weighed in by giving a leading practical proposal known as random circuit sampling (RCS) a qualified seal of approval with the weight of complexity theoretic evidence behind it. Random circuit sampling is the technique Google has put forward to prove whether or not it has achieved quantum supremacy with a 72-qubit computer chip called Bristlecone, unveiled earlier this year.

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Two teams demonstrate that they can count the number of quantized vibrations, or phonons, in cold mechanical oscillators by measuring the energy in the vibrations.

At the origin of every musical note is a mechanical oscillator that resonates at a specific frequency. But what the ear cannot distinguish is that the energy of these vibrations is discretized into an integer number of quanta of motion, or phonons. Most vibrating objects contain an uncountable number of phonons, but researchers have, for some time now, been able to prepare massive mechanical oscillators in their quantum ground state, where the average phonon number is smaller than one. This hard-won accomplishment not only involved getting rid of all thermal excitations in the oscillator through intense cooling, but it also required inventing a system of motion detection with a sensitivity at the quantum level [1]. An emerging technique consists of coupling the oscillator motion to another quantum object: a superconducting qubit, which can serve a role in the detection as well as the manipulation of states of motion [2–4].

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Researchers from the Moscow Institute of Physics and Technology (MIPT), Aalto University in Finland, and ETH Zurich have demonstrated a prototype device that uses quantum effects and machine learning to measure magnetic fields more accurately than its classical analogues. Such measurements are needed to seek mineral deposits, discover distant astronomical objects, diagnose brain disorders, and create better radars.

“When you study nature, whether you investigate the human brain or a supernova explosion, you always deal with some sort of electromagnetic signals,” explains Andrey Lebedev, a co-author of the paper describing the new device in npj Quantum Information. “So measuring magnetic fields is necessary across diverse areas of science and technology, and one would want to do this as accurately as possible.”

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It takes little more than logging on to see the flaws in today’s internet—mainly, how easy it is to steal or intercept data. One future solution for these problems could be an upgrade that relies on the latest advances in the science of subatomic particles: a quantum internet.

Just last week, three scientists from the renowned QuTech center at the Delft University of Technology (TU Delft) revealed a roadmap for how this quantum internet should develop. They also plan to connect four cities with a quantum link by 2020, reports MIT Tech Review. And today, University of Chicago scientists announced that they plan to set up a quantum link across a 30-mile distance. Scientists are really getting serious about this quantum internet idea.

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Quantum computers could solve complex tasks that are beyond the capabilities of conventional computers. However, the quantum states are extremely sensitive to constant interference from their environment. The plan is to combat this using active protection based on quantum error correction. Florian Marquardt, Director at the Max Planck Institute for the Science of Light, and his team have now presented a quantum error correction system that is capable of learning thanks to artificial intelligence.

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