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Category: quantum physics – Page 623

Researchers have found a way to protect highly fragile quantum systems from noise, which could aid in the design and development of new quantum devices, such as ultra-powerful quantum computers.

The researchers, from the University of Cambridge, have shown that microscopic particles can remain intrinsically linked, or entangled, over long distances even if there are random disruptions between them. Using the mathematics of quantum theory, they discovered a simple setup where entangled particles can be prepared and stabilized even in the presence of noise by taking advantage of a previously unknown symmetry in .

Their results, reported in the journal Physical Review Letters, open a new window into the mysterious quantum world that could revolutionize future technology by preserving in , which is the single biggest hurdle for developing such technology. Harnessing this capability will be at the heart of ultrafast quantum computers.

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Quantum computing startup IonQ today announced its road map for the next few years — following a similar move from IBM in September — and it’s quite ambitious, to say the least.

At our Disrupt event earlier this year, IonQ CEO and president Peter Chapman suggested that we were only five years away from having desktop quantum computers. That’s not something you’ll likely hear from the company’s competitors — who also often use a very different kind of quantum technology — but IonQ now says that it will be able to sell modular, rack-mounted quantum computers for the data center in 2023 and that by 2025, its systems will be powerful enough to achieve broad quantum advantage across a wide variety of use cases.

In an interview ahead of today’s announcement, Chapman showed me a prototype of the hardware the company is working on for 2021, which fits on a workbench. The actual quantum chip is currently the size of a half-dollar and the company is now working on essentially putting the core of its technology on a single chip, with all of the optics that make its system work integrated.

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In groundbreaking new research, an international team of researchers led by the University of Minnesota Twin Cities has developed a unique process for producing a quantum state that is part light and part matter.

The discovery provides fundamental new insights for more efficiently developing the next generation of quantum-based optical and electronic devices. The research could also have an impact on increasing efficiency of nanoscale chemical reactions.

The research is published in Nature Photonics.

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In what could be one of the significant developments in the field of quantum computing, Chinese researchers suggest having achieved quantum supremacy with the capability of performing calculations 100 trillion times faster than the world’s most advanced supercomputer. Researchers from the University of Science and Technology of China, Hefei, believe that when put into practical use, it can carry calculations in minutes which would have otherwise taken two billion years to perform. The fastest supercomputers, before this, claimed to have achieved computational efficiency easing up to 10,000 years of calculations.

Jiuzhang, as the supercomputer is called, has outperformed Google’s supercomputer, which the company had claimed last year to have achieved quantum computing supremacy. The supercomputer by Google named Sycamore is a 54-qubit processor, consisting of high-fidelity quantum logic gates that could perform the target computation in 200 seconds.

The researchers explored Boson sampling, a task considered to be a strong candidate to demonstrate quantum computational advantage. As the researcher cited in the research paper, they performed Gaussian boson sampling (GBS), which is a new paradigm of boson sampling, one of the first feasible protocols for quantum computational advantage. In boson sampling and its variants, nonclassical light is injected into a linear optical network, which generates highly random photon-number, measured by single-photon detectors.

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Columbia team discovers 6-nanometer-long single-molecule circuit with enormous on/off ratio due to quantum interference; finding could enable faster, smaller, and more energy-efficient devices.

Researchers, led by Columbia Engineering Professor Latha Venkataraman, report today that they have discovered a new chemical design principle for exploiting destructive quantum interference. They used their approach to create a six-nanometer single-molecule switch where the on-state current is more than 10,000 times greater than the off-state current–the largest change in current achieved for a single-molecule circuit to date.

This new switch relies on a type of quantum interference that has not, up to now, been explored. The researchers used long molecules with a special central unit to enhance destructive quantum interference between different electronic energy levels. They demonstrated that their approach can be used to produce very stable and reproducible single-molecule switches at room temperature that can carry currents exceeding 0.1 microamps in the on-state. The length of the switch is similar to the size of the smallest computer chips currently on the market and its properties approach those of commercial switches. The study is published today in Nature Nanotechnology.

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Scientists discovered a strategy for layering dissimilar crystals with atomic precision to control the size of resulting magnetic quasi-particles called skyrmions. This approach could advance high-density data storage and quantum magnets for quantum information science.

In typical ferromagnets, magnetic spins align up or down. Yet in skyrmions, they twist and swirl, forming unique shapes like petite porcupines or tiny tornadoes.

The tiny intertwined magnetic structures could innovate high-density data storage, for which size does matter and must be small. The Oak Ridge National Laboratory-led project produced skyrmions as small as 10 nanometers – 10,000 times thinner than a human hair.

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Understanding how matter interacts with light—its optical properties—is critical in a myriad of energy and biomedical technologies, such as targeted drug delivery, quantum dots, fuel combustion, and cracking of biomass. But calculating these properties is computationally intensive, and the inverse problem—designing a structure with desired optical properties—is even harder.

Now Berkeley Lab scientists have developed a machine learning model that can be used for both problems—calculating of a known structure and, inversely, designing a structure with desired optical properties. Their study was published in Cell Reports Physical Science.

“Our model performs bi-directionally with high accuracy and its interpretation qualitatively recovers physics of how metal and dielectric materials interact with light,” said corresponding author Sean Lubner.

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