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Categories: Dwave google HPC IBM quantum computers

For a technology that’s usually characterized as far off and in a distant galaxy, #quantumcomputing has been steadily picking up steam. Just how close real-world applications are depends on whom you talk to and for what kinds of applications. Los Alamos National Lab, for example, has an active application development effort for its #DWave system and LANL researcher Susan Mniszewski and colleagues have made progress on using the D-Wave machine for aspects of quantum molecular dynamics (QMD) simulations. At CeBIT this week #DWave and #Volkswagen will discuss their pilot project to monitor and control taxi traffic in Beijing using a hybrid #HPC-quantum system – this is on the heels of recent customer upgrade news from D-Wave (more below). Last week #IBM announced expanded access to its five-qubit cloud-based quantum developer platform. In early March, researchers from the #GoogleQuantumAILab published an excellent commentary in Nature examining real-world opportunities, challenges and timeframes for quantum computing more broadly. Google is also considering making its homegrown quantum capability available through the cloud. As an overview, the Google commentary provides a great snapshot, noting soberly that challenges such as the lack of solid error correction and the small size (number of qubits) in today’s machines – whether “universal” digital machines like IBM’s or “analog” adiabatic annealing machines like D-Wave’s – have prompted many observers to declare useful quantum computing is still a decade way. Not so fast, says Google. “This conservative view of quantum computing gives the impression that investors will benefit only in the long term. We contend that short-term returns are possible with the small devices that will emerge within the next five years, even though these will lack full error correction…Heuristic ‘hybrid’ methods that blend quantum and classical approaches could be the foundation for powerful future applications. The recent success of neural networks in machine learning is a good example,” write Masoud Mohseni, Peter Read, and John Martinis (a 2017 HPCwire Person to Watch) and colleagues (Nature, March 8, “Commercialize early quantum technologies”)

https://www.hpcwire.com/2017/03/21/quantum-bits-d-wave-vw-google-quantum-lab-ibm-expands-access/

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