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Revolutionise what? Sure, we can hand-wave away that it'll revolutionise something, but there's no direct candidate on the horizon. As of today, at best we c

Revolutionise what? Sure, we can hand-wave away that it'll revolutionise *something*, but there's no direct candidate on the horizon. As of today, at best we can hope that more accurate quantum simulations could lead to some breakthrough tech, but that's a very indirect revolution at best. With LASER, at least, there was a bunch of known use-cases that were blocked by the availability of the tech. There are no such equivalents here.

pooloo 4y ago
If you build it, they will come... Most of the time, technology that is leading edge is only there for a short period, as its either bought out or lacks funding. With IBM, they have the funds to start revolutions, and have a larger vision at play. However, quantum computing is not a widely accepted concept due to a lot of its complexities, which is likely why its such a niche area. Given time and money, which IBM can handle, something will happen.
- deleted 4y ago
  [deleted]
mabbo 4y ago
The Quantum Algorithm Zoo website[0] gives some examples of problems where the quantum algorithm is much faster than the classical one. My own view is that for a lot of (but not all[1]) problems for which we have a quantum algorithm improvement, we maybe already have a heuristic that gets us 95% of the way there just as quickly. So the application of a QC on these problems is buying us a massive speedup, but only if you need to get the perfect, optimal answer. And sometimes you do! [0]https://quantumalgorithmzoo.org/ https://quantumalgorithmzoo.org/ [1]Factoring large primes is a good counter example.
- inasio 4y ago
  An issue highlighted there is that there are very few algorithms where you have an exponential advantage vs classical hardware
  - sudosysgen 4y ago
    I mean, even just going from n2 to n1.5 is huge.
    - rdlw 4y ago
      It's nice if you can do it in software, but this necessarily requires hardware. Any algorithm can be sped up by a constant factor with specialized hardware: for example, addition is 2n if you need to perform an addition with an optional carry for each digit. With specialized hardware, 64-bit numbers can be added in one operation, which makes the algorithm n/32. This kind of improvement is nice, but it would mean that quantum computers are no moe exciting than video cards. Edit: This is a result of the linear speedup theorem. https://en.wikipedia.org/wiki/Linear_speedup_theorem https://en.wikipedia.org/wiki/Linear_speedup_theorem
      - refulgentis 4y ago
        I don't know if this sort of analogy illuminates, seems rather it hides. If we assume quantum computing is the same as SIMD, yeah, I wouldn't be excited either.
        rdlw 4y ago
        What I mean is that I would consider quantum computing a failure if it took us "from n2 to n1.5". That would make it the same as SIMD or parallel computing. I still think that linear-time factoring or sorting could be revolutionary, but only if enough interesting problems can be reduced to them. I'm holding out hope for a fast quantum SAT3 solver, at that point it will just be a waiting game until you can get an expansion card for solving NP-hard problems.
      - macksd 4y ago
        > no more exciting than video cards Um... That seems like a pretty high bar to me, actually. Are you forgetting about how much they've done to speed up the training of quite a lot of deep-learning models? And really the only competition is TPUs and other dedicated chips that, at the end of the day, are also just chips optimized for matrix operations. The graphics in state of the art video games? Were I fan of crypto, mining rigs? That's some pretty impactful tech right there.
- thowieuroweiu4 4y ago
  while BQP vs P is all nice and good, afaik, the scaling just isn't there yet on the hardware. one, the noise is too high, two the bits are too low, and apparently we don't have error correction whatsoever. i remember that even the 'factoring of 15' on a quantum computer uses some special hacks (that needs the answer) to code it in.
ejiblabahaba 4y ago
Aside from the much-touted uses in cryptography, probably the biggest use will be as universal quantum simulators. A lot of quantum simulations are infeasible beyond trivial interactions, because the classical memory and number of computations required to capture and progress the state of the quantum system grows exponentially with each interacting element in the system. Simplifying exponentially increasing memory/computation time requirements to linearly increasing qubit/simulation time requirements will make a lot of chemistry and material science way easier.
shireboy 4y ago
I thought cryptography was the big thing here. Whoever has a big enough one of these could break tls and other encryption. Which means we enter an arms race where we need quantum to build qc-proof encryption before qc gets cheap and easy enough for the bad guys. https://www.microsoft.com/en-us/research/project/post-quantum-tls/ https://www.microsoft.com/en-us/research/project/post-quantu...
- tsimionescu 4y ago
  Not really - you don't need QCs to do encryption that (as far as we know right now at least) is just as infeasible to break on QCs as it is on classical computers. For example, most symmetric key algorithms are already QC-safe; in particular, AES would still be safe even in a world where you could build a QC with as many gates as a modern chip. Of course, there is an asterisk here, as the set of all problems for which QCs give exponential/super-polynomial speedups over known classical algorithms is not yet known (not even at the level where we have some confidence that P != NP). Everything I'm claiming is based on currently known quantum algorithms, and on belief about the properties of QCs in general (i.e. that they can only solve more efficiently problems that display certain rare characteristics).

Revolutionise what? Sure, we can hand-wave away that it'll revolutionise *something*, but there's no direct candidate on the horizon. As of today, at best we c

pooloo 4y ago

If you build it, they will come... Most of the time, technology that is leading edge is only there for a short period, as its either bought out or lacks funding. With IBM, they have the funds to start revolutions, and have a larger vision at play. However, quantum computing is not a widely accepted concept due to a lot of its complexities, which is likely why its such a niche area. Given time and money, which IBM can handle, something will happen.

deleted 4y ago
[deleted]

mabbo 4y ago

The Quantum Algorithm Zoo website[0] gives some examples of problems where the quantum algorithm is much faster than the classical one. My own view is that for a lot of (but not all[1]) problems for which we have a quantum algorithm improvement, we maybe already have a heuristic that gets us 95% of the way there just as quickly. So the application of a QC on these problems is buying us a massive speedup, but only if you need to get the perfect, optimal answer. And sometimes you do! [0]https://quantumalgorithmzoo.org/ https://quantumalgorithmzoo.org/ [1]Factoring large primes is a good counter example.

inasio 4y ago
An issue highlighted there is that there are very few algorithms where you have an exponential advantage vs classical hardware
- sudosysgen 4y ago
  I mean, even just going from n2 to n1.5 is huge.
  - rdlw 4y ago
    It's nice if you can do it in software, but this necessarily requires hardware. Any algorithm can be sped up by a constant factor with specialized hardware: for example, addition is 2n if you need to perform an addition with an optional carry for each digit. With specialized hardware, 64-bit numbers can be added in one operation, which makes the algorithm n/32. This kind of improvement is nice, but it would mean that quantum computers are no moe exciting than video cards. Edit: This is a result of the linear speedup theorem. https://en.wikipedia.org/wiki/Linear_speedup_theorem https://en.wikipedia.org/wiki/Linear_speedup_theorem
    - refulgentis 4y ago
      I don't know if this sort of analogy illuminates, seems rather it hides. If we assume quantum computing is the same as SIMD, yeah, I wouldn't be excited either.
      - rdlw 4y ago
        What I mean is that I would consider quantum computing a failure if it took us "from n2 to n1.5". That would make it the same as SIMD or parallel computing. I still think that linear-time factoring or sorting could be revolutionary, but only if enough interesting problems can be reduced to them. I'm holding out hope for a fast quantum SAT3 solver, at that point it will just be a waiting game until you can get an expansion card for solving NP-hard problems.
    - macksd 4y ago
      > no more exciting than video cards Um... That seems like a pretty high bar to me, actually. Are you forgetting about how much they've done to speed up the training of quite a lot of deep-learning models? And really the only competition is TPUs and other dedicated chips that, at the end of the day, are also just chips optimized for matrix operations. The graphics in state of the art video games? Were I fan of crypto, mining rigs? That's some pretty impactful tech right there.
thowieuroweiu4 4y ago
while BQP vs P is all nice and good, afaik, the scaling just isn't there yet on the hardware. one, the noise is too high, two the bits are too low, and apparently we don't have error correction whatsoever. i remember that even the 'factoring of 15' on a quantum computer uses some special hacks (that needs the answer) to code it in.

ejiblabahaba 4y ago

Aside from the much-touted uses in cryptography, probably the biggest use will be as universal quantum simulators. A lot of quantum simulations are infeasible beyond trivial interactions, because the classical memory and number of computations required to capture and progress the state of the quantum system grows exponentially with each interacting element in the system. Simplifying exponentially increasing memory/computation time requirements to linearly increasing qubit/simulation time requirements will make a lot of chemistry and material science way easier.

shireboy 4y ago

I thought cryptography was the big thing here. Whoever has a big enough one of these could break tls and other encryption. Which means we enter an arms race where we need quantum to build qc-proof encryption before qc gets cheap and easy enough for the bad guys. https://www.microsoft.com/en-us/research/project/post-quantum-tls/ https://www.microsoft.com/en-us/research/project/post-quantu...

tsimionescu 4y ago
Not really - you don't need QCs to do encryption that (as far as we know right now at least) is just as infeasible to break on QCs as it is on classical computers. For example, most symmetric key algorithms are already QC-safe; in particular, AES would still be safe even in a world where you could build a QC with as many gates as a modern chip. Of course, there is an asterisk here, as the set of all problems for which QCs give exponential/super-polynomial speedups over known classical algorithms is not yet known (not even at the level where we have some confidence that P != NP). Everything I'm claiming is based on currently known quantum algorithms, and on belief about the properties of QCs in general (i.e. that they can only solve more efficiently problems that display certain rare characteristics).