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This research investigates the classical and quantum complexity of simulating all-to-all spin Hamiltonian dynamics within logarithmic space, specifically targeting models like Sherrington-Kirkpatrick and Hopfield networks. The authors propose a quantum algorithm that achieves simultaneous advantages in both time and space resources for certain regimes, while establishing theoretical bounds where classical simulation would imply significant collapses in complexity classes. These findings advance the understanding of quantum advantage in constrained resource settings for many-body physics simulations.
Classical and Quantum Simulation of All-to-All Quantum Dynamics in Logarithmic Space
arXiv:2609.40162v1 Announce Type: new Abstract: We study both the classical and the quantum complexity of the problem of estimating disorder-averaged quench dynamics for all-to-all spin Hamiltonians such as quantum Hopfield, Sherrington--Kirkpatrick (SK) or Dicke-type models. Disorder averaging restores permutation invariance in this setting, so states of $N$ spins can be stored in $\mathcal O(\log N)$ qubits. While logarithmic-space quantum computations are known to be simulatable classically in polynomial time or in polylogarithmic space, whether a single algorithm can achieve both is open, raising the possibility of simultaneous quantum advantage. To this end, we give a quantum algorithm for permutation-invariant $k$-local dynamics without disorder using polynomial time and $\mathcal O(\log N)$ quantum and classical space. We show that any classical algorithm matching these resources would imply $\mathsf{BQL}\subseteq \mathsf{SC}$. For short times, however, we provide such algorithms, including for SK models. For Hopfield models, we discuss how dilating the disorder to ancilla qubits reduces the problem to the disorder-free case on an enlarged system, thus extending both classical and quantum results to them. We give some evidence that their long-time dynamics are non-trivial. They thus emerge as a candidate for a simultaneous time--space advantage in quantum simulation.
Abstract:We study both the classical and the quantum complexity of the problem of estimating disorder-averaged quench dynamics for all-to-all spin Hamiltonians such as quantum Hopfield, Sherrington--Kirkpatrick (SK) or Dicke-type models. Disorder averaging restores permutation invariance in this setting, so states of $N$ spins can be stored in $\mathcal O(\log N)$ qubits. While logarithmic-space quantum computations are known to be simulatable classically in polynomial time or in polylogarithmic space, whether a single algorithm can achieve both is open, raising the possibility of simultaneous quantum advantage. To this end, we give a quantum algorithm for permutation-invariant $k$-local dynamics without disorder using polynomial time and $\mathcal O(\log N)$ quantum and classical space. We show that any classical algorithm matching these resources would imply $\mathsf{BQL}\subseteq \mathsf{SC}$. For short times, however, we provide such algorithms, including for SK models. For Hopfield models, we discuss how dilating the disorder to ancilla qubits reduces the problem to the disorder-free case on an enlarged system, thus extending both classical and quantum results to them. We give some evidence that their long-time dynamics are non-trivial. They thus emerge as a candidate for a simultaneous time--space advantage in quantum simulation.
arXiv:2609.40162 [quant-ph]
(or arXiv:2609.40162v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2609.40162 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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