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Seth Lloyd: Quantum Computer Reality

from Long Now [alt+shift+b] in science

### Quantum Computer Reality The 15th-century Renaissance was triggered, Lloyd began, by a flood of new information which changed how people thought about everything, and the same thing is happening now. All of us have had to shift, just in the last couple decades, from hungry hunters and gatherers of information to overwhelmed information filter-feeders. Information is physical. A bit can be represented by an electron _here_ to signify 0, and _there_ to signify 1. Information processing is moving electrons from here to there. But for a “qubit" in a quantum computer, an electron is both _here_ and _there_ at the same time, thanks to "wave-particle duality.” Thus with “quantum parallelism” you can do massively more computation than in classical computers. It’s like the difference between the simple notes of plainsong and all that a symphony can do—a huge multitude of instruments interacting simultaneously, playing arrays of sharps and flats and complex chords. Quantum computers can solve important problems like enormous equations and factoring--cracking formerly uncrackable public-key cryptography, the basis of all online commerce. With their ability to do “oodles of things at once," quantum computers can also simulate the behavior of larger quantum systems, opening new frontiers of science, as Richard Feynman pointed out in the 1980s. Simple quantum computers have been built since 1995, by Lloyd and ever more others. Mechanisms tried so far include: electrons within electric fields; nuclear spin (clockwise and counter); atoms in ground state and excited state simultaneously; photons polarized both horizontally and vertically; and super-conducting loops going clockwise and counter-clockwise at the same time; and many more. To get the qubits to perform operations—to compute—you can use an optical lattice or atoms in whole molecules or integrated circuits, and more to come. The more qubits, the more interesting the computation. Starting with 2 qubits back in...
10th Aug 2016

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Stephen J Gould (still my favorite science essayist) wrote an excellent article in 1985 (Red Wings in the Sunset, later published in his book, Bully for Brontosaurus) about artist and naturalist Abbott Handerson Thayer. Thayer wrote about how animals use coloration as camouflage – what he called “cryptic coloration”. His ideas were solid, but he made a classic mistake that scientists sometimes make, overapplying their key discovery. Thayer argued that all animal coloration is cryptic. For example, he argued that flamingos are pink because it hides them in the setting sun (hence the title of the essay). This is a transparently absurd argument, and it shows how Thayer tried to shoehorn all evidence into his preferred and absolute narrative. It is better to assume that nature is complex, and all explanations are at best partial (unless proven otherwise). Animal coloration, in fact, can serve many different purposes, only one of which is camouflage. Thayer also struggled with the male peacock, for example. Butterflies appear to be another example. Actually, many butterflies are camouflaged on the underside of their wings, so that when they are at rest with their wings up they tend to blend into their surroundings. But the top side of their wings are often very colorful and not camouflaged at all. One assumption is that the brightly colored part of their wings is to attract mates. This may be true, but that does not mean the coloration does not serve another function. Often animals use visual cues when choosing their mates that are markers for health and success. As evidence that butterfly wing color may be serving a survival benefit, if you look at birds that feed on insects during flight, they target dully-colored moths much more than brightly colored butterflies, even though the butterflies should be easier to see. 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Similarly, the wing patterns combined with the way butterflies move their wings and their flight dynamics combine to create a similar barber pole illusion, making the butterfly look like it is moving down when it is in fact moving up. They also showed that this strategy is phylogenetically widespread. They then did modeling in silico and showed digital creatures converge on butterfly-like patterns. To understand how effective this strategy can be it’s important to understand how catching a butterfly in midflight works. Butterflies have a very jumpy pattern of flight. In order to grab them in flight, a bird will have to zero in on their exact location with a few hundred millisecond and millimeter precision. If the butterfly suddenly zigs while the bird perceives that they zagged, the birdy will miss. Alternatively they may make only a glancing blow or grab an edge of a wing rather than their body. Either way, the butterfly lives another day and the bird goes hungry. 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Spatiotemporal aliasing has to do with ratio of the movement with the “refresh” speed of the brain’s visual processing. You have likely seen this with spinning wheels that have spoke-like features. As the wheel slows down, at one point the spinning will appear to stop completely, and then will appear to spin backwards. This is simply an artifact of your brain’s visual processing speed. Now imagine being surrounded by a field of rapidly moving and zig-zagging stripes, and your brain trying to make sense of all this information, while trying to compensate for these powerful optical illusions. Butterflies don’t have a herd to hide in, but they do have the added element of their flapping wings. Not only are they moving in a way to maximize these optical illusions, their wings are also doing this, while alternating top-side and bottom-side. 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