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Universal quantum computers don\u2019t exist, but that hasn\u2019t stopped D-Wave<\/a> from\u00a0carving out its\u00a0own place in the quantum computing market. Today, the 17-year-old company is announcing its forth quantum chip, the 2000Q, doubling the number of qubits<\/a> on its exiting 1000Q chip.<\/a><\/p>\n The Burnaby, British Columbia based company\u2019s\u00a0chips fall under a specific class of quantum computing <\/a>called quantum annealing. Annealing is useful for a subset of optimization computing problems.<\/p>\n Optimization regularly involves hunting for minimums and maximums.<\/p>\n If you remember\u00a0back to your days of beginner\u00a0calculus, you might remember a class of problems where you were asked to determine what size\u00a0squares should be\u00a0cut from the corners of a sheet of cardboard to produce the largest box. These \u201coptimization\u201d questions\u00a0scale up and serve as the underpinnings for many problems <\/a>in machine learning,\u00a0financial analysis and radiotherapy.<\/p>\n Vern Brownell, CEO of D-Wave explained to TechCrunch that he\u2019s seeing early interest in the 2000Q from companies in financial services and defense. For now, these groups are looking to get their hands on\u00a0the cutting-edge for research and development.<\/p>\n Lockheed Martin, Google, NASA Ames, and Los Alamos National Laboratory are all early customers of D-Wave. Some of these groups offer remote cloud access for compute. D-Wave also keeps its own machines in-house for remote access. The company offers an API that can be used with Python or Matlab.<\/p>\n D-Wave is the most commercialized entity in the quantum computing space, but others like\u00a0Y Combinator-backed\u00a0Rigetti Computing<\/a> and Microsoft<\/a> are taking their own approaches. Rigetti\u2019s solution is a gate-based system while Microsoft is chasing elusive topological computing. These forms of quantum computing are arguably more pure, but that doesn\u2019t mean annealing is useless.<\/p>\n Google published a paper\u00a0<\/a>in December 2015 noting that, \u201cFor problem instances involving nearly 1000 binary variables, quantum annealing significantly outperforms its classical counterpart.\u201d<\/p>\n![\"max_paraboloid-svg\"](\"https:\/\/i0.wp.com\/www.rsoftsolution.com\/blog\/wp-content\/plugins\/RSSPoster_PRO\/cache\/07728_max_paraboloid-svg.png?resize=390%2C312&ssl=1\")
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