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This seems a bit reductive. Sure. There are larger challenges but size, specialization and cost are three things that prevent adoption of this technology at al

This seems a bit reductive. Sure. There are larger challenges but size, specialization and cost are three things that prevent adoption of this technology at all universities and some companies. Having more adoption even if its "useless" right now means more people looking for useful things to do.

hannob 5y ago
I think this is a key misunderstanding. The issue is not that we don't know what useful things to do with a QC. The issue is the quantum computers that exist today are not able to do those things. "Adopting" a machine that can't do anything you couldn't do on your laptop won't help. The challenge for QC to become useful is to scale up and provide working error correction.
- eigenket 5y ago
  I agree completely, I would love quantum computers to be in a place where all universities and most companies can do useful stuff with them, but they aren't and these companies which pretend that they are seem like scams.
- peytoncasper 5y ago
  Genuinely curious then. When you say that it can't do anything that my laptop can't do. Is that based on simulation of actual quantum methods with all of the quirks or simply traditional algorithms? If it's not truly simulation, there seems to me a ton of value in having even a little bit of access to something like this.
  - hannob 5y ago
    It's both. You can easily simulate 11 qbits.
    - _8091149529 5y ago
      There's a commercial product for classical simulation of small QPUs [0]. With dedicated hardware handles up to 41 qubits. I'm not affiliated with the company or endorsing their products, just pointing out that they exist. [0] https://atos.net/en/solutions/quantum-learning-machine https://atos.net/en/solutions/quantum-learning-machine
      - reikonomusha 5y ago
        You can also do this with purely free and open source software like [0]. [0] https://github.com/quil-lang/qvm https://github.com/quil-lang/qvm
  - clavigne 5y ago
    The wavefunction of an n qubit system is representable by a 2^n vector of complex numbers [1]. Using single precision floats [2], a 10 qubit wavefunction is 8 KB, 20 qubit = 8 MB, 30 qubit = 8 GB and 40 qubit = 8 TB. Hence a run-of-the-mill laptop can easily simulate a perfect 30 qubit computer, provided you are using a sufficiently performant simulator (such as https://github.com/qulacs/qulacs https://github.com/qulacs/qulacs ). [1] This is actually a pessimistic upper bound for the classical simulation because current quantum hardware is not fully connected and not fully coherent. Most problems of interest (optimization, chemistry etc) also do not ever generate fully entangled wavefunctions and so can be simulated with significantly less resources. So for any applications (beyond simulating quantum advantage experiments built specifically to make classical simulation hard), classical computers are crushing quantum computers. [2] Because QM is a linear theory, numerical precision isnt an issue, as it would be in a chaotic classical simulation of eg fluid dynamics.
reikonomusha 5y ago
The rabbit hole goes deep in this. Form factor isn’t limiting adoption. Bad performance and the fact you need a team of physicists to calibrate the machine daily are two simple examples limiting adoption more than size. I’m not saying miniaturization isn’t useful, I’m saying it’s last on the list to care about.

hannob 5y ago

I think this is a key misunderstanding. The issue is not that we don't know what useful things to do with a QC. The issue is the quantum computers that exist today are not able to do those things. "Adopting" a machine that can't do anything you couldn't do on your laptop won't help. The challenge for QC to become useful is to scale up and provide working error correction.

eigenket 5y ago
I agree completely, I would love quantum computers to be in a place where all universities and most companies can do useful stuff with them, but they aren't and these companies which pretend that they are seem like scams.
peytoncasper 5y ago
Genuinely curious then. When you say that it can't do anything that my laptop can't do. Is that based on simulation of actual quantum methods with all of the quirks or simply traditional algorithms? If it's not truly simulation, there seems to me a ton of value in having even a little bit of access to something like this.
- hannob 5y ago
  It's both. You can easily simulate 11 qbits.
  - _8091149529 5y ago
    There's a commercial product for classical simulation of small QPUs [0]. With dedicated hardware handles up to 41 qubits. I'm not affiliated with the company or endorsing their products, just pointing out that they exist. [0] https://atos.net/en/solutions/quantum-learning-machine https://atos.net/en/solutions/quantum-learning-machine
    - reikonomusha 5y ago
      You can also do this with purely free and open source software like [0]. [0] https://github.com/quil-lang/qvm https://github.com/quil-lang/qvm
- clavigne 5y ago
  The wavefunction of an n qubit system is representable by a 2^n vector of complex numbers [1]. Using single precision floats [2], a 10 qubit wavefunction is 8 KB, 20 qubit = 8 MB, 30 qubit = 8 GB and 40 qubit = 8 TB. Hence a run-of-the-mill laptop can easily simulate a perfect 30 qubit computer, provided you are using a sufficiently performant simulator (such as https://github.com/qulacs/qulacs https://github.com/qulacs/qulacs ). [1] This is actually a pessimistic upper bound for the classical simulation because current quantum hardware is not fully connected and not fully coherent. Most problems of interest (optimization, chemistry etc) also do not ever generate fully entangled wavefunctions and so can be simulated with significantly less resources. So for any applications (beyond simulating quantum advantage experiments built specifically to make classical simulation hard), classical computers are crushing quantum computers. [2] Because QM is a linear theory, numerical precision isnt an issue, as it would be in a chaotic classical simulation of eg fluid dynamics.

reikonomusha 5y ago

The rabbit hole goes deep in this. Form factor isn’t limiting adoption. Bad performance and the fact you need a team of physicists to calibrate the machine daily are two simple examples limiting adoption more than size. I’m not saying miniaturization isn’t useful, I’m saying it’s last on the list to care about.