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Supercomputing Science

Quantum Computer To Launch Next Week 224

judgecorp writes "D-Wave Systems of British Columbia is all set to demonstrate a 16-qubit quantum computer. Simple devices have been built in the lab before, and this is still a prototype, but it is a commercial project that aims to get quantum devices into computer rooms, solving tricky problems such as financial optimization. Most quantum computers have to be isolated from the outside world (look at them and they stop working). This one is an 'adiabatic' quantum computer — which means (in theory, says D-Wave) that it can live with thermal noise and give results without having to be isolated. There's a description of it here — and pretty pictures too."
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Quantum Computer To Launch Next Week

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  • by LiquidCoooled ( 634315 ) on Thursday February 08, 2007 @10:25AM (#17933652) Homepage Journal
    It is not a general quantum computer.
    It is a single instance specific formula calculator.

    Any problem that can be recast as a two-dimensional Ising model in a magnetic field problem (AKA quadratic integer programming) can in principle be solved using the approach we'll be demo'ing.

    Thats from their blog [wordpress.com]

    There were some interesting questions asked and lots of people are sceptical.
  • Quantum mystery (Score:4, Informative)

    by suv4x4 ( 956391 ) on Thursday February 08, 2007 @10:34AM (#17933758)
    Most quantum computers have to be isolated from the outside world (look at them and they stop working)

    This is often misunderstood. Quantum computers don't stop working when you "look at them", the "observer" metaphor is just a fancy way to say that the wave propagation of a particle collapses when it interacts with another particle.

    Basically, imagine they are waves, propagating from the point of last interaction like expanding spheres. When two particles (spheres) touch each other, they collapse back to being single-point particles, and continue propagation anew until the next collision.

    Which means, look at them all you want, just don't crack the casing open and point a torch inside.
  • by rbarreira ( 836272 ) on Thursday February 08, 2007 @10:37AM (#17933806) Homepage

    It has been predicted that quantum computing will make current computer security obsolete, cracking any current cryptography scheme

    Wrong. As far as current knowledge goes, a quantum computer is not a big help for cracking symmetric ciphers such as Triple DES or AES. It is a big help for RSA, since it can factor numbers in O(number size) time.
  • by Viol8 ( 599362 ) on Thursday February 08, 2007 @10:39AM (#17933828) Homepage
    Quantum computers even if they can be made practical , will only solve a small subset of problems in computer science that involve highly parallel number calculations or searches. They'll be little or no better than a standard turing machine for sequential (ie most) computing problems where the steps in the program can't be reduced to a simple mathematical formula or sequence or where branching levels are high.

    So while various talking heads may waffle on about a new era in computing what they really mean is a new era in certain areas such as factorisation , whereas most of the computing world will carry on as before. Where not going to see quantum powered AI or whatever else we read about in the more on the fringe science mags anytime soon.
  • by eldavojohn ( 898314 ) * <eldavojohn@noSpAM.gmail.com> on Thursday February 08, 2007 @10:51AM (#17933984) Journal

    There were some interesting questions asked and lots of people are sceptical.
    Disclaimer, I'm not a physicist.

    Well, most importantly, a while back I had read up on the research being done at Los Alamos National Laboratory on quantum computers. Granted, this was 4 or 5 years ago, they have an interesting paper [lanl.gov][PDF warning] where, if you'll look at figures 1 & 2, you'll notice that the number of bits you are able to factor is directly related to the decoherence time.

    Now, if you're not familiar with Shor's Algorithm [wikipedia.org], the values in the first figure might not mean much but, in layman's terms, I believe they were experiencing problems with 8 or more qubits. I remember reading that decoherence would destroy the relationship between the qubits before they could prepare them and do a meaningful computation. I had always thought that this would be an upper bound until someone figured out a way around it. If this computer is also using similar means, I'd like to know what special modification they did to overcome these coherence problems.

    You're correct that there are a lot of important questions to be answered but a 16 qubit computer that is a "a single instance specific formula calculator" as you put it still interests me greatly and may be a giant leap forward in our ability to understand future computers that may be true full blown quantum computers. Why downplay this unless you can directly point out a problem with what they're doing and what they claim they can do?
  • by julesh ( 229690 ) on Thursday February 08, 2007 @10:52AM (#17933994)
    I'm thinking you maybe meant the number of digits? So a log(n)? What's the base?

    I believe this is correct. From my limited understanding, the base would be 2^(number of qubits), so for qubits > bits in key, effectively O(1).
  • Re:Just in time (Score:2, Informative)

    by Runefox ( 905204 ) on Thursday February 08, 2007 @11:01AM (#17934138)
    UP-UP-DOWN-DOWN-LEFT-LEFT-RIGHT-RIGHT-B-A-SELECT
    The actual Konami Kode is:

    UP-UP-DOWN-DOWN-LEFT-RIGHT-LEFT-RIGHT-B-A-(SELECT) -START

    Select was optional; It simply enabled two-player in Konomi games like Contra. Start isn't necessary, though unless you just want to sit at the title screen, you need to hit it to start the game. The actual code itself simply ends with "A".

    It's been added to certain newer Konami games (such as the lackluster AirForce Delta Strike, where IIRC, if you input a variant of the code (no A or B on the PS2) with the game paused as the unlockable Vic Viper, you self-destruct. Amazing cheat.)
  • by TheEmptySet ( 1060334 ) on Thursday February 08, 2007 @11:06AM (#17934202)
    Not entirely true. Naturally you can NEVER read the quantum state of the qbits, because observing them only yields one of the states each qbit is (or could be) in, not all of them. However, should the program be written well enough it is possible to gain information form the observed states. This is sufficient to crack RSA in a very short space of time with relatively few qbits (16 would suffice for many applications if the quantum computer were general purpose) AND give an observable result.
  • by sanermind ( 512885 ) on Thursday February 08, 2007 @11:42AM (#17934602)
    It's not a big deal that it only solves a particular NP-complete problem.. because if you can solve and one NP-complete problem, you can solve ALL of them. From the wikipedia article [wikipedia.org]

    a deterministic, polynomial-time solution to any NP-complete problem would also be a solution to every other problem in NP
    Anyone who took computer science at a decent school and remembers any of it would remember the whole issue of whether P=NP or not. One of great unsolved problems in mathematics, and the fundamental promise of quantum computers vs. classical ones. And the little tidbit that NP-c problems are cross equivalent.. that if you could solve any ONE of them, you could use that method, translating all others into a formalism that could be solved by the original solution. This is a VERY big thing if it's actually working. Still only 16 bits, but jeesh. Still, I'm not sure what the 'adiabatic' nature means. From perusing the article (which was over my head, to be sure) it sounds like they've achieved some sort of partially locked quantum state that's allowed to evolve slowly, not instantaniously. Sort of a quantum anealing, if you will? They are perhaps wiggling the system on a sort of clock while quantum information exchange can happen in parts between certain but not all parts of the system? In which case, it's still pretty neat, but I don't know about scaling.. It may still take quite some (unrealistic) time to solve problems of larger size with more bits
  • by exp(pi*sqrt(163)) ( 613870 ) on Thursday February 08, 2007 @11:42AM (#17934604) Journal

    Quantum computers even if they can be made practical , will only solve a small subset of problems in computer science
    Quantum computers are not simply massively parallel machines and there's no reason to expect problems that have significant branching to be any more difficult for quantum computers than problems without branching. Your statement about a "simple mathematical formula" is meaningless - there is (1) no simple formula for factoring and (2) all computer programs (classical of quantum) are built from simple mathemaical formulae.

    I swear, stories on /. about quantum computing are nothing but field days for people to post science-fiction they just made up.

  • by TheRaven64 ( 641858 ) on Thursday February 08, 2007 @11:50AM (#17934706) Journal
    This is quite misleading. If you can find a way of solving one NP-complete problem in polynomial time on a classical computing device, then you can solve all NP-complete problems in polynomial time on a classical computer. This is because any NP-complete problem can be reduced to any other NP-complete problem. However, the rules change when you are dealing with quantum computers. It may be that the reduction of one NP-complete problem to another is also an NP-complete problem, and one which the quantum computer won't help you with.
  • by Gospodin ( 547743 ) on Thursday February 08, 2007 @12:11PM (#17934954)

    How could the rules possibly change in this way? Suppose I have an NPC problem I wish to solve (call it P), and a known quantum algorithm that solves a different NPC problem in poly time (call it Q). In poly time I transform P into Q. In poly time I solve Q using the quantum computer. Then in poly time I transform the solution to Q into a solution for P. If I want, I can then check the solution to P in poly time using a conventional computer (this is guaranteed by the definition of NPC). I only need to invoke quantum computing when I'm solving Q - no other step requires nonpoly time.

  • by Tyler Durden ( 136036 ) on Thursday February 08, 2007 @12:26PM (#17935156)
    Fine, but you're still wrong about the running time of Shor's algorithm. It looks like you're saying it can factor numbers in O(b) time where b is the number of bits of the number we are factoring. Actually it factors the number in O(b^3) time. The running time is polynomial, not linear. See here [wikipedia.org].
  • by exp(pi*sqrt(163)) ( 613870 ) on Thursday February 08, 2007 @01:39PM (#17936048) Journal

    The great thing about quantum computers is they can reduce problems that live in exponential time (n^x) to polynomial time (x^n).
    I think you just made that up. Would you like to cite a reference?
  • by da cog ( 531643 ) on Thursday February 08, 2007 @02:05PM (#17936446)
    The idea behind an "adiabatic" quantum computer is that you can somehow set up a system so that the solution to a problem that you want to solve is encoded in the system's ground state. Thus, in principle all you have to do is cool the system down so that it's at its lowest possible energy level, measure it, and then "decode" the measurements to obtain your solution. The problem with this is that you can't necessarily know when you've gotten the system to be in the ground state; it is possible for it to get "stuck" in a slightly higher-energy state from which it cannot escape, as there might be a forbidden transition between its current level and the ground state.

    This is analgous to a situation in atomic physics: if you've got an electron in an n=2, l=0 state, then it is hard for it to fall all the way down to the n=1 state because in order to change energy it has to emit a photon which changes its angular momentum and thus increases l, but there is no n=1, l=1 state there's only a n=1, l=0 state, and so the transition is forbidden. (Of course, this is an over-simplification that neglects things like the fact that the electron can change it's spin, but you get the idea.)

    So you don't try to go straight to the ground system that you are interested in, because you don't know for sure that you can get there consistently. Instead, you build a system whose ground state you are sure you can get to, and then you slowly change the configuration of that system until it matches the one that you want to solve. Because you are changing it slowly -- i.e., "adiabatically" -- you should never leave the ground state (even though the ground state itself is changing right under you) and thus when you are done you are guaranteed to be in the ground state of your system of interest, from which you can obtain the solution to your NP complete problem.

    There is a catch, though, which is that you have to have the system be *very* cold, and you have to change it *very*, *very* slowly. And here's where the catch can kill you: as the size of your system increases, the gap between the lowest two energy states decreases *exponentially*. This means that you have to make the system exponentially colder, *and* that you have to change it exponentially slower. Thus, adiabatic computers are not expected to be able to solve NP-complete problems in linear time, as there is still a cost in time (and cooling effort) which grows exponentially with the size of your problem. Nonetheless, it's likely that you can get a quadratic speed-up equivalent to Grover's search algorithm by building such a computer.

    This, by-the-way, is why many quantum computing people believe that D-wave is ultimately going to fail -- probably not with this particular computer, but with scaling it up to the point where it's actually useful. But hey, maybe we're wrong and they've figured it all out; we can certainly hope that's the case. :-)
  • by da cog ( 531643 ) on Thursday February 08, 2007 @02:16PM (#17936624)
    For those of you who know some quantum mechanics, here's what's going on:

    The idea behind an "adiabatic" quantum computer is that you can somehow set up a system so that the solution to a problem that you want to solve is encoded in the system's ground state. Thus, in principle all you have to do is cool the system down so that it's at its lowest possible energy level, measure it, and then "decode" the measurements to obtain your solution. The problem with this is that you can't necessarily know when you've gotten the system to be in the ground state; it is possible for it to get "stuck" in a slightly higher-energy state from which it cannot escape, as there might be a forbidden transition between its current level and the ground state.

    This is analgous to a situation in atomic physics: if you've got an electron in an n=2, l=0 state, then it is hard for it to fall all the way down to the n=1 state because in order to change energy it has to emit a photon which changes its angular momentum and thus increases l, but there is no n=1, l=1 state, there's only a n=1, l=0 state, and so the transition is forbidden. (Of course, this is an over-simplification that neglects things like the fact that the electron can change it's spin, but you get the idea.)

    So you don't try to go straight to the ground system that you are interested in, because you don't know for sure that you can get there consistently. Instead, you build a system whose ground state you are sure you can get to, and then you slowly change the configuration of that system until it matches the one that you want to solve. Because you are changing it slowly -- i.e., "adiabatically" -- you should never leave the ground state (even though the ground state itself is changing right under you) and thus when you are done you are guaranteed to be in the ground state of your system of interest, from which you can obtain the solution to your NP-complete problem.

    There is a catch, though, which is that you have to have the system be *very* cold, and you have to change it *very*, *very* slowly. And here's where the catch can kill you: as the size of your system increases, the gap between the lowest two energy states can decrease *exponentially*. This means that you have to make the system exponentially colder, *and* that you have to change it exponentially slower. In general systems do not behave this badly, but it is expected (and possibly has been shown, I don't remember) that systems which can solve NP-complete problems *do* behave this badly. Thus, adiabatic computers are not expected to be able to solve NP-complete problems in linear time, as there is still a cost in time (and cooling effort) which grows exponentially with the size of your problem. Mind you, you aren't *forced* to move so slowly, but if you don't then you have a good chance of effectively kicking the system into an excited state and thus ending up with something that is not a solution to your problem. Nonetheless, it's likely that you can get somehow a quadratic speed-up (equivalent to Grover's search algorithm) over classical computation by building such a computer.

    This, by-the-way, is why many quantum computing people believe that D-wave is ultimately going to fail -- probably not with this particular computer, but with scaling it up to the point where it's actually useful. But hey, maybe we're wrong and they've figured it all out; we can certainly hope that's the case. :-)
  • by arrrrg ( 902404 ) on Thursday February 08, 2007 @02:32PM (#17936866)
    There are way too many misunderstandings in this thread. I've taken a class at Berkeley on QC, and the best known quantum algorithm for solving NP-C problems is Grover's algorithm: http://en.wikipedia.org/wiki/Grover's_algorithm [wikipedia.org] The hitch is, it only provides quadratic speedup rather than polynomial. So, a problem you can solve in O(2^n) time now takes O(2^(n/2)) time. This would be a big deal if you could make a sufficiently big QC, but it's nothing like the polytime algorithm you get for factoring with Shor's algorithm. There are almost undoubtedly other undiscovered quantum algorithms out there (for the most part there is only Grover's and Shor's so far), but I seem to remember a proof of some sort that you can't do much better unless P=NP (in which case you could solve NP-C problems efficiently on classical computers too!).

For God's sake, stop researching for a while and begin to think!

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