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D-Wave's 2,000-Qubit Quantum Annealing Computer Now 1,000x Faster Than Previous Generation (tomshardware.com)
An anonymous reader quotes a report from Tom's Hardware: D-Wave, a Canadian company developing the first commercial "quantum computer," announced its next-generation quantum annealing computer with 2,000 qubits, which is twice as many as its previous generation had. One highly exciting aspect of quantum computers of all types is that beyond the seemingly Moore's Law-like increase in number of qubits every two years, their performance increases much more than just 2x, unlike with regular microprocessors. This is because qubits can hold a value of 0, 1, or a superposition of the two, making quantum systems able to deal with much more complex information. If D-Wave's 2,000-qubit computer is now 1,000 faster than the previous 1,000-qubit generation (D-Wave 2X), that would mean that, for the things Google tested last year, it should now be 100 billion times faster than a single-core CPU. The new generation also comes with control features, which allows users to modify how D-Wave's quantum system works to better optimize their solutions. These control features include the following capabilities: The ability to tune the rate of annealing of individual qubits to enhance application performance; The ability to sample the state of the quantum computer during the quantum annealing process to power hybrid quantum-classical machine learning algorithms that were not previously possible; The ability to combine quantum processing with classical processing to improve the quality of both optimization and sampling results returned from the system. D-Wave's CEO, Vern Brownell, also said that D-Wave's quantum computers could also be used for machine learning task in ways that wouldn't be possible on classical computers. The company is also training the first generation of programmers to develop applications for D-Wave quantum systems. Last year, Google said that D-Wave's 1,000 qubit computer proved to be 100 million times faster than a classical computer with a single core: "We found that for problem instances involving nearly 1,000 binary variables, quantum annealing significantly outperforms its classical counterpart, simulated annealing. It is more than 10^8 times faster than simulated annealing running on a single core," said Hartmut Neven, Google's Director of Engineering.
Someone downvoted you, possibly due to a lack of sourcing. So in case anyone is in doubt, they should look at this blog by Scott Aaronson http://www.scottaaronson.com/blog/?p=2555 and the discussion. Aaronson is one of the top quantum computing experts on the planet. The comments there are also very relevant. Alex Shelby notes that the algorithms that D-Wave has used to compare on conventional (classical) computers are substantially less efficient than the best classical algorithms. We are going to eventually have actual quantum computers, and when we do they will be awesome. Right now, it isn't clear that D-Wave's system can be reasonably called a quantum computer, and is even more clear that they aren't useful at all.
You'll hear about it when real quantum computers reach commercial maturity, because a bunch of Slashdot articles will appear about how everyone is in a panic to rush and replace RSA with something else. :-)
"commercial maturity" being the key word here, because we should assume that significant portions of major classified intelligence budgets are being thrown at the problem by the US and China, maybe also by a few other players (India? Israel? The UK? Russia?). Like how it's widely believed that differential cryptanalysis was known to the NSA well before it became known to the world, only today encryption is much more prevalent and much more important to anyone doing signals analysis.
Real lawyers write in C++
Can you provide links?
Here you go.
TL;DR? The basic idea behind a simulated annealing algorithm is that it searches for successively better solutions, but occasionally accepts a "worse" one, so as to reduce the possibility of getting stuck in a local minimum when there is a better minimum nearby (sort of like jumping out of a caldera at the top of a mountain, so that you can reach a a better minimum closer to ground level.) As time goes on, the probability of accepting a worse solution is reduced, according to an "annealing schedule" until finally only better solutions are accepted.
Seriously, I (and I suspect many others) have a decent idea of the *concept* of quantum computers, but understanding actual application is... elusive.
Simulated annealing is not an exclusively quantum-based algorithm. It works quite well on classical computers. But it is a method that would perform very well on a quantum computer.
If it weren't for deadlines, nothing would be late.
On the contrary simulated annealing fell out of common usage due to other stochastic search methods being better at solving many problems types.
.. see the big paragraph above. "Better" means searches a different solution space and therefore cannot solve all the same problems.
For instance the Extended Compact Genetic Algorithm converges much faster, and dont let its name fool you its not a genetic algorithm as the name Compact Genetic Algorithm is derived not from the technique, but instead the name is derived from the space it searches which is exactly equivalent to a simple genetic algorithm with a crossover probability of 0.5. The Compact Genetic Algorithms is instead an estimation of distribution algorithm, and the Extended version detects and leverages the dependencies between different elements of the solution vector in a theoretically optimal (information theory) way, which gives it an advantage over algorithms that don't (which includes Simulated Annealing, which is why it fell out of favor.)
Annealing is still used for problem sets where there isnt a lot of dependencies within the solution vector.
Some of the d-wave haters have moved onto the argument that the system isnt faster than a conventional one when the conventional one runs a "better" algorithm
"His name was James Damore."