3 ms·

As someone who knows little about quantum computing, what is the significance of 127-qubits? (as opposed to classical computing's 128 bits, as a reference)

klyrs 5y ago
Thus far, only D-Wave has truly scalable control over their qubits. They accomplished that by moving to an entirely different computational regime. Until gate-model efforts find a solution to scalable control, every "we built a bigger chip" announcement is a milestone in microwave engineering.
krastanov 5y ago
Nothing. It is just how many they were able to manufacture and control reliably. Probably were aiming for some power-of-two number but had a couple of defects.
space_fountain 5y ago
As someone who is very much a lay person, my understanding is the qubitsness of a quantum computer is closer to the ram capacity of a classical computer than anything
tcgv 5y ago
Computational power for quantum computers goes as 2^n, where n is the number of qubits, so unlike classical computing this machine should be orders of magnitude superior to Google's 53-quibit Sycamore. If you wanna learn more about the subject, a couple of years back I wrote a introduction to quantum computing for programmers which you may find useful: - https://thomasvilhena.com/2019/11/quantum-computing-for-programmers https://thomasvilhena.com/2019/11/quantum-computing-for-prog...
- 7373737373 5y ago
  What does "computational power" mean though? Which specific problem can these systems solve that classical computers cannot, or more effectively?
  - tcgv 5y ago
    Roughly, computational power = number of operations per cycle. Classical computers can only perform a number of operations per cycle linearly proportional to the amount of hardware architecture available (ex: one core, two cores, quad-core). Quantum computers can take advantage of superposition and entanglement to, given some restrictions, perform multiple operations per cycle, proportional to "two" to the power of the number of qubits.
    - bnjemian 5y ago
      That's not quite it. The power of a QC comes from modeling an exponentially large probabilistic state space using entanglement and superposition. The operations performed by a QC are also different, they can be analog (arbitrary rotations), but circuit depths (i.e. the number of operations) are still expected to be polynomial. The difference is that the probabilistic state space uses probability amplitudes, which are complex valued and can be positive or negative, allowing for constructive and destructive interference over the probabilities tied to each state. Orchestrate the right kind of interference, and for some problems, you have an algorithm that outputs a solution to that problem with (relatively high probability) in time that, depending on the problem, may be exponentially faster. Examples of those problems include prime factorization/discrete logarithms (Shor's algorithm) and ones in quantum simulation (hence the interest in QC by chemists, physicists, etc.)
      - tcgv 5y ago
        Thanks for detailing. I was explaining in laymen terms, using less technical details, with some reservations ("roughly" and "given some restrictions"). > Orchestrate the right kind of interference, and for some problems, you have an algorithm that outputs a solution to that problem with (relatively high probability) in time that, depending on the problem, may be exponentially faster. Exactly. Given some restrictions, it's possible to implement algorithms that are equivalent to performing an exponentially large amount of classical operations per "cycle". > Examples of those problems include prime factorization/discrete logarithms (Shor's algorithm) Indeed. I provide an implementation of the Deutsch–Jozsa algorithm [1][2] based in my own quantum computing simulator that I linked in my blog post (in the original comment) to address this. [1] https://en.wikipedia.org/wiki/Deutsch%E2%80%93Jozsa_algorithm https://en.wikipedia.org/wiki/Deutsch%E2%80%93Jozsa_algorith... [2] https://github.com/TCGV/QuantumSim/blob/master/Tcgv.QuantumSim.UnitTest/Algorithms/DeutschAlgorithmTests.cs https://github.com/TCGV/QuantumSim/blob/master/Tcgv.QuantumS...

klyrs 5y ago

Thus far, only D-Wave has truly scalable control over their qubits. They accomplished that by moving to an entirely different computational regime. Until gate-model efforts find a solution to scalable control, every "we built a bigger chip" announcement is a milestone in microwave engineering.

krastanov 5y ago

Nothing. It is just how many they were able to manufacture and control reliably. Probably were aiming for some power-of-two number but had a couple of defects.

space_fountain 5y ago

As someone who is very much a lay person, my understanding is the qubitsness of a quantum computer is closer to the ram capacity of a classical computer than anything

tcgv 5y ago

Computational power for quantum computers goes as 2^n, where n is the number of qubits, so unlike classical computing this machine should be orders of magnitude superior to Google's 53-quibit Sycamore. If you wanna learn more about the subject, a couple of years back I wrote a introduction to quantum computing for programmers which you may find useful: - https://thomasvilhena.com/2019/11/quantum-computing-for-programmers https://thomasvilhena.com/2019/11/quantum-computing-for-prog...

7373737373 5y ago
What does "computational power" mean though? Which specific problem can these systems solve that classical computers cannot, or more effectively?
- tcgv 5y ago
  Roughly, computational power = number of operations per cycle. Classical computers can only perform a number of operations per cycle linearly proportional to the amount of hardware architecture available (ex: one core, two cores, quad-core). Quantum computers can take advantage of superposition and entanglement to, given some restrictions, perform multiple operations per cycle, proportional to "two" to the power of the number of qubits.
  - bnjemian 5y ago
    That's not quite it. The power of a QC comes from modeling an exponentially large probabilistic state space using entanglement and superposition. The operations performed by a QC are also different, they can be analog (arbitrary rotations), but circuit depths (i.e. the number of operations) are still expected to be polynomial. The difference is that the probabilistic state space uses probability amplitudes, which are complex valued and can be positive or negative, allowing for constructive and destructive interference over the probabilities tied to each state. Orchestrate the right kind of interference, and for some problems, you have an algorithm that outputs a solution to that problem with (relatively high probability) in time that, depending on the problem, may be exponentially faster. Examples of those problems include prime factorization/discrete logarithms (Shor's algorithm) and ones in quantum simulation (hence the interest in QC by chemists, physicists, etc.)
    - tcgv 5y ago
      Thanks for detailing. I was explaining in laymen terms, using less technical details, with some reservations ("roughly" and "given some restrictions"). > Orchestrate the right kind of interference, and for some problems, you have an algorithm that outputs a solution to that problem with (relatively high probability) in time that, depending on the problem, may be exponentially faster. Exactly. Given some restrictions, it's possible to implement algorithms that are equivalent to performing an exponentially large amount of classical operations per "cycle". > Examples of those problems include prime factorization/discrete logarithms (Shor's algorithm) Indeed. I provide an implementation of the Deutsch–Jozsa algorithm [1][2] based in my own quantum computing simulator that I linked in my blog post (in the original comment) to address this. [1] https://en.wikipedia.org/wiki/Deutsch%E2%80%93Jozsa_algorithm https://en.wikipedia.org/wiki/Deutsch%E2%80%93Jozsa_algorith... [2] https://github.com/TCGV/QuantumSim/blob/master/Tcgv.QuantumSim.UnitTest/Algorithms/DeutschAlgorithmTests.cs https://github.com/TCGV/QuantumSim/blob/master/Tcgv.QuantumS...