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Category: computing – Page 226

The idea of simulating quantum physics with controllable quantum devices had been proposed several decades ago. With the extensive development of quantum technology, large-scale simulation, such as the analog quantum simulation tailoring an artificial Hamiltonian mimicking the system of interest, has been implemented on elaborate quantum experimental platforms. However, due to the limitations caused by the significant noises and the connectivity, analog simulation is generically infeasible on near-term quantum computing platforms. Here we propose an alternative analog simulation approach on near-term quantum devices. Our approach circumvents the limitations by adaptively partitioning the bath into several groups based on the performance of the quantum devices.

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Year 2015 face_with_colon_three

(Phys.org)—Quantum computers are inherently different from their classical counterparts because they involve quantum phenomena, such as superposition and entanglement, which do not exist in classical digital computers. But in a new paper, physicists have shown that a classical analog computer can be used to emulate a quantum computer, along with quantum superposition and entanglement, with the result that the fully classical system behaves like a true quantum computer.

Physicist Brian La Cour and electrical engineer Granville Ott at Applied Research Laboratories, The University of Texas at Austin (ARL: UT), have published a paper on the classical emulation of a quantum computer in a recent issue of The New Journal of Physics. Besides having fundamental interest, using classical systems to emulate quantum computers could have practical advantages, since such quantum emulation devices would be easier to build and more robust to decoherence compared with true quantum computers.

“We hope that this work removes some of the mystery and ‘weirdness’ associated with quantum computing by providing a concrete, classical analog,” La Cour told Phys.org. “The insights gained should help develop exciting new technology in both classical analog computing and true quantum computing.”

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Two-dimensional (2D) materials, composed of a single or a few layers of atoms, are at the forefront of material science, promising revolutionary advancements in technology. These ultra-thin materials exhibit unique and exotic properties, particularly when their layers are stacked and twisted in specific ways.

This manipulation of layers can significantly alter their electronic characteristics, presenting exciting opportunities for the development of next-generation technologies such as more efficient computers and reliable electricity storage systems.

Understanding the intricate relationship between the atomic structure and electronic properties of these materials, however, poses a significant challenge. Traditional microscopy techniques struggle to capture the complete 3D atomic structure of these layered materials, especially when the layers are oriented differently or composed of light elements.

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“Our goal is to revolutionize the field of ultrafast photonics by transforming large lab-based systems into chip-sized ones that can be mass produced and field deployed.”

On the tip of a fingerprint

However, these lasers are notoriously large and expensive making them impractical for constant use. Now, researchers have made a version of these devices that can fit on the tip of a fingertip or more conveniently on a small chip, more precisely a nanophotonic chip.

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Have you ever wished you could go back in time and invest in trailblazing companies like Apple (NASDAQ: AAPL), Amazon (NASDAQ: AMZN), or Tesla (NASDAQ: TSLA) before they hit it big? Well, you may just have that chance again today with quantum computing stocks.

The futuristic field of quantum computing has faced some bumps on its road to mainstream adoption lately. The recent Nasdaq correction has hit many once-hot quantum computing stocks hard. But this correction also presents a golden buying opportunity for investors who take the long view.

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Lasers are essential tools for observing, detecting, and measuring things in the natural world that we can’t see with the naked eye. But the ability to perform these tasks is often restricted by the need to use expensive and large instruments.

In a newly published cover-story paper in the journal Science, researcher Qiushi Guo demonstrates a novel approach for creating high-performance ultrafast lasers on nanophotonic chips. His work centers on miniaturizing mode-lock lasers—a unique laser that emits a train of ultrashort, coherent light pulses in femtosecond intervals, which is an astonishing quadrillionth of a second.

Ultrafast mode-locked lasers are indispensable to unlocking the secrets of the fastest timescales in nature, such as the making or breaking of molecular bonds during chemical reactions, or light propagation in a turbulent medium. The high-speed, pulse-peak intensity and broad-spectrum coverage of mode-locked lasers have also enabled numerous photonics technologies, including optical atomic clocks, biological imaging, and computers that use light to calculate and process data.

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Elon Musk’s Neuralink is looking for a volunteer for its first clinical trial of a brain implant chip. The trial, which begins next year, has attracted thousands of prospective patients. The ideal candidate must be an adult under 40 with all four limbs paralyzed. The procedure involves inserting electrodes and wires into the brain, with a small computer replacing part of the skull. The computer will collect and analyze brain activity, sending the data wirelessly to a nearby device. Neuralink aims to translate thoughts into computer commands. However, the company has faced criticism for animal testing practices.

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