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Quantum Simulation of Lindbladian Dynamics via Repeated Interactions

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arxiv 2312.05371 v4 pith:G2VUMGVB submitted 2023-12-08 quant-ph

classification quant-ph
keywords dynamicsquantumepsilonerrorlindbladianalgorithmsequationsimulate
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

The Lindblad equation generalizes the Schr\"{o}dinger equation to quantum systems that undergo dissipative dynamics. The quantum simulation of Lindbladian dynamics is therefore non-unitary, preventing a naive application of state-of-the-art quantum algorithms. Here, we make use of an approximate correspondence between Lindbladian dynamics and evolution based on Repeated Interaction (RI) CPTP maps to write down a Hamiltonian formulation of the Lindblad dynamics and derive a rigorous error bound on the master equation. Specifically, we show that the number of interactions needed to simulate the Liouvillian $e^{t\mathcal{L}}$ within error $\epsilon$ scales in a weak coupling limit as $\nu\in O(t^2\|\mathcal{L}\|_{1\rightarrow 1}^2/\epsilon)$. This is significant because the error in the Lindbladian approximation to the dynamics is not explicitly bounded in existing quantum algorithms for open system simulations. We then provide quantum algorithms to simulate RI maps using an iterative Qubitization approach and Trotter-Suzuki formulas and specifically show that for iterative Qubitization the number of operations needed to simulate the dynamics (for a fixed value of $\nu$) scales in a weak coupling limit as $O(\alpha_0 t + \nu \log(1/\epsilon)/\log\log(1/\epsilon))$ where $\alpha_0$ is the coefficient $1$-norm for the system and bath Hamiltonians. This scaling would appear to be optimal if the complexity of $\nu$ is not considered, which underscores the importance of considering the error in the Liouvillian that we reveal in this work.

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Cited by 5 Pith papers

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    A simplified Lindblad-based Gibbs state preparation protocol with local Pauli jumps is shown to mix polynomially under the eigenstate thermalization hypothesis, with numerical and noise-resilience analysis.

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