How many qubits are needed for quantum computational supremacy?

Author:

Dalzell Alexander M.12ORCID,Harrow Aram W.3ORCID,Koh Dax Enshan45ORCID,La Placa Rolando L.3ORCID

Affiliation:

1. Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, CA 91125, USA

2. Department of Physics, Massachusetts Institute of Technology, Cambrdige, Massachusetts 02139, USA

3. Center for Theoretical Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA

4. Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA

5. Zapata Computing, Inc., 100 Federal Street, 20th Floor, Boston, Massachusetts 02110, USA

Abstract

Quantum computational supremacy arguments, which describe a way for a quantum computer to perform a task that cannot also be done by a classical computer, typically require some sort of computational assumption related to the limitations of classical computation. One common assumption is that the polynomial hierarchy (PH) does not collapse, a stronger version of the statement thatPNP, which leads to the conclusion that any classical simulation of certain families of quantum circuits requires time scaling worse than any polynomial in the size of the circuits. However, the asymptotic nature of this conclusion prevents us from calculating exactly how many qubits these quantum circuits must have for their classical simulation to be intractable on modern classical supercomputers. We refine these quantum computational supremacy arguments and perform such a calculation by imposing fine-grained versions of the non-collapse conjecture. Our first two conjectures poly3-NSETH(a) and per-int-NSETH(b) take specific classical counting problems related to the number of zeros of a degree-3 polynomial innvariables overF2or the permanent of ann×ninteger-valued matrix, and assert that any non-deterministic algorithm that solves them requires2cntime steps, wherec{a,b}. A third conjecture poly3-ave-SBSETH(a) asserts a similar statement about average-case algorithms living in the exponential-time version of the complexity classSBP. We analyze evidence for these conjectures and argue that they are plausible whena=1/2,b=0.999anda=1/2.Imposing poly3-NSETH(1/2) and per-int-NSETH(0.999), and assuming that the runtime of a hypothetical quantum circuit simulation algorithm would scale linearly with the number of gates/constraints/optical elements, we conclude that Instantaneous Quantum Polynomial-Time (IQP) circuits with 208 qubits and 500 gates, Quantum Approximate Optimization Algorithm (QAOA) circuits with 420 qubits and 500 constraints and boson sampling circuits (i.e. linear optical networks) with 98 photons and 500 optical elements are large enough for the task of producing samples from their output distributions up to constant multiplicative error to be intractable on current technology. Imposing poly3-ave-SBSETH(1/2), we additionally rule out simulations with constant additive error for IQP and QAOA circuits of the same size. Without the assumption of linearly increasing simulation time, we can make analogous statements for circuits with slightly fewer qubits but requiring104to107gates.

Publisher

Verein zur Forderung des Open Access Publizierens in den Quantenwissenschaften

Subject

Physics and Astronomy (miscellaneous),Atomic and Molecular Physics, and Optics

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