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D-Wave Systems today unveiled the roadmap for its 5,000-qubit quantum computer. Components of D-Wave’s next-generation quantum computing platform will come to market between now and mid-2020 via ongoing quantum processing unit (QPU) and cloud-delivered software updates. The complete system will be available through cloud access and for on-premise installation in mid-2020.

Binary digits (bits) are the basic units of information in classical computing while quantum bits (qubits) make up quantum computing. Bits are always in a state of 0 or 1, while qubits can be in a state of 0, 1, or a superposition of the two. Quantum computing leverages qubits to perform computations that would be much more difficult for a classical computer. Based in Burnaby, Canada, D-Wave has been developing its own quantum computers that use quantum annealing.

D-Wave is mainly focused on solving optimization problems, so its quantum computers can’t be directly compared to the competition. Indeed, many have questioned whether D-Wave’s systems have quantum properties, and thus performance that classical computers can’t match. In the meantime, D-Wave continues to improve and sell its systems.

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The techniques of microwave quantum optics are applied to collective spin excitations in a macroscopic sphere of ferromagnetic insulator. We demonstrate.

In the single-magnon limit, strong coupling between a magnetostatic mode in the sphere and a microwave cavity mode. Moreover, we introduce a superconducting qubit in the cavity and couple the qubit with the magnon excitation via the virtual photon excitation. We observe the magnon-vacuum-induced Rabi splitting.

The hybrid quantum system enables generation and characterization of non-classical quantum states of magnons.

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Also, loosely following technology that could be used to build a real working time machine. Anyone with an interest in time travel is welcome to participate.

But, I have been watching tech news for what could be used to build a time machine. I think we are pretty close. You’d still need a few physics guys with 150+ IQ’s to work on the equations, a guy with a 200+ IQ to figure out how to put the whole thing together, and a guy with billions of dollars to fund it. But most of this stuff is for sale to the public, (short list):

1. quantum computer; to run the calculations.

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We exhibit a simple, systematic procedure for detecting and correcting errors using any of the recently reported quantum error-correcting codes. The procedure is shown explicitly for a code in which one qubit is mapped into five. The quantum networks obtained are fault tolerant, that is, they can function successfully even if errors occur during the error correction. Our construction is derived using a recently introduced group-theoretic framework for unifying all known quantum codes.

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Gating—controlling the state of one qubit conditioned on the state of another—is a key procedure in all quantum information processors. As the scale of quantum processors increases, the qubits will need to interact over larger and larger distances, which presents an experimental challenge in solid-state architectures. Wan et al. implemented the 20-year-old theoretical proposal of quantum gate teleportation that allows separated qubits to interact effectively. They deterministically teleported a controlled-NOT gate between two computational qubits in spatially separated zones in a segmented ion trap, demonstrating a feasible route toward scalable quantum information processors.

Science, this issue p. 875

Large-scale quantum computers will require quantum gate operations between widely separated qubits. A method for implementing such operations, known as quantum gate teleportation (QGT), requires only local operations, classical communication, and shared entanglement. We demonstrate QGT in a scalable architecture by deterministically teleporting a controlled-NOT (CNOT) gate between two qubits in spatially separated locations in an ion trap. The entanglement fidelity of our teleported CNOT is in the interval (0.845, 0.872) at the 95% confidence level. The implementation combines ion shuttling with individually addressed single-qubit rotations and detections, same- and mixed-species two-qubit gates, and real-time conditional operations, thereby demonstrating essential tools for scaling trapped-ion quantum computers combined in a single device.

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Practical quantum computers may be another step closer to reality – and like so many technologies, we have graphene to thank for it. The bits of information in quantum computers (qubits) can famously exist in two states at once, and now researchers from MIT and other institutions have managed to record just how long that superposition state can last in a qubit made of graphene.

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Researchers at Technische Universität Darmstadt have recently demonstrated the defect-free assembly of versatile target patterns of up to 111 single-atom quantum systems. Their findings, outlined in a paper published in Physical Review Letters, could drive assembled-atom architectures beyond the threshold of quantum advantage, paving the way for new breakthroughs in quantum science and technology.

“Our research is driven by the observation that physical sciences are right in the middle of a paradigm shift in which the application of physics, i.e. quantum technologies, are becoming the leading technologies in the near future,” Gerhard Birkl, one of the researchers who carried out the study, told Phys.org. “A vast list of applications are already foreseeable but I am convinced that of most applications we are not even aware of.”

The next step for the field of and technology is the development of experimental platforms that offer extensive scalability, multisite quantum correlations and efficient quantum error correction. Over the past century or so, researchers have carried out a substantial amount of work on single quantum systems, laying the foundations for current developments. Atomic quantum systems have played a key role in these studies, particularly neutral atoms trapped by light, as they provide well-isolated quantum systems with favorable scaling.

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