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Simulatability of locally-interacting open quantum spin systems

Rahul Trivedi, J. I. Cirac

Published Oct 20, 2021• 1 citation
OpenAlex

Abstract

We analyze the complexity of classically simulating the dynamics of locally interacting quantum spin systems with a constant rate of entanglement breaking noise. We show that for a system with $n$ spins, a polynomial time classical algorithm can be used to sample within a $O(1/\text{poly}(n))$ total-variation distance of the state of the spins when the rate of noise is sufficiently high. Furthermore, by encoding a 1D fault tolerant quantum computation into the dynamics of open quantum spin systems, we show that for certain physically relevant channels, the problem of sampling from the output state is BQP-complete in the low noise regime. Our results rigorously show the presence of phase transitions in the classical simulatability of the continuous time dynamics of open quantum spin systems.

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We analyze the complexity of classically simulating the dynamics of locally interacting quantum spin systems with a constant rate of entanglement breaking noise. We show that for a system with nnn spins, a polynomial time classical algorithm can be used to sample within a O(1/poly(n))O(1/\text{poly}(n))O(1/poly(n)) total-variation distance of the state of the spins when the rate of noise is sufficiently high. Furthermore, by encoding a 1D fault tolerant quantum computation into the dynamics of open quantum spin systems, we show that for certain physically relevant channels, the problem of sampling from the output state is BQP-complete in the low noise regime. Our results rigorously show the presence of phase transitions in the classical simulatability of the continuous time dynamics of open quantum spin systems.
We analyze the complexity of classically simulating continuous-time dynamics of locally interacting quantum spin systems with a constant rate of entanglement breaking noise. We prove that a polynomial time classical algorithm can be used to sample from the state of the spins when the rate of noise is higher than a threshold determined by the strength of the local interactions. Furthermore, by encoding a 1D fault tolerant quantum computation into the dynamics of spin systems arranged on two or higher dimensional grids, we show that for several noise channels, the problem of weakly simulating the output state of both purely Hamiltonian and purely dissipative dynamics is expected to be hard in the low-noise regime.
We analyze the complexity of classically simulating continuous-time dynamics of locally interacting quantum spin systems with a constant rate of entanglement breaking noise. We prove that a polynomial time classical algorithm can be used to sample from the state of the spins when the rate of noise is higher than a threshold determined by the strength of the local interactions. Furthermore, by encoding a 1D fault tolerant quantum computation into the dynamics of spin systems arranged on two or higher dimensional grids, we show that for several noise channels, the problem of weakly simulating the output state of both purely Hamiltonian and purely dissipative dynamics is expected to be hard in the low-noise regime.
We develop a recently introduced representation of quantum dynamics based on sampling negative Markov chain processes. By introducing particles and antiparticles, this formalism maps generic quantum dynamics onto a Markov process defined over an exponentially large configuration space. Within this framework, quantum complexity arises from the proliferation of stochastic particles, which ultimately renders classical simulation and sampling intractable beyond a certain timescale. In the presence of noise, we demonstrate that for any unitary evolution generated by a linear combination of local or pairwise interactions, there exists at least one noise channel that effectively classicalizes the system by suppressing particle growth and making Monte Carlo sampling efficient. As a corollary, we show that for this class of unitaries, the dynamics of an open quantum spin chain subject to depolarizing noise undergoes an exact transition to classical simulability once the noise strength exceeds a critical threshold which can be efficiently determined for any model.
Understanding the boundary between classical simulatability and the power of quantum computation is a fascinating topic. Direct simulation of noisy quantum computation requires solving an open quantum many-body system, which is very costly. Here, we develop a tensor network formalism to simulate the time-dynamics and the Fourier spectrum of noisy quantum circuits. We prove that under general conditions most of the quantum circuits at any constant level of noise per gate can be efficiently simulated classically with the cost increasing only polynomially with the size of the circuits. The result holds even if we have perfect noiseless quantum gates for some subsets of operations, such as all the gates in the Clifford group. This surprising result reveals the subtle relations between classical simulatability, quantum supremacy, and fault-tolerant quantum computation. The developed simulation tools may also be useful for solving other open quantum many-body systems.
We present an end-to-end quantum algorithm for simulating nonlinear dynamics described by a system of stochastic dissipative differential equations with a quadratic nonlinearity. The stochastic part of the system is modeled by a Gaussian noise in the equation of motion and in the initial conditions. Our algorithm can approximate the expected value of any correlation function that depends on O(1)O(1)O(1) variables with rigorous bounds on the approximation error. The runtime scales polynomially with log⁡N\log{N}logN, ttt, JJJ, and λ1−1λ_1^{-1}λ1−1​, where NNN is the total number of variables, ttt is the evolution time, JJJ is the nonlinearity strength, and λ1λ_1λ1​ is the smallest dissipation rate. However, the runtime scales exponentially with a parameter quantifying inverse relative error in the initial conditions. To the best of our knowledge, this is the first rigorous quantum algorithm capable of simulating strongly nonlinear systems with J≫λ1J\gg λ_1J≫λ1​ at the cost poly-logarithmic in NNN and polynomial in ttt. The considered simulation problem is shown to be BQP-complete, providing a strong evidence for a quantum advantage. We benchmark the quantum algorithm via numerical experiments by simulating a vortex flow in the 2D Navier Stokes equation.
While quantum computers promise to solve classically intractable problems, identifying the point at which fault-tolerant quantum computation outperforms the best classical algorithms for practical applications remains an outstanding challenge. Here we establish a concrete quantum-classical crossover for quantum many-body dynamics under realistic hardware conditions. We introduce a scalable fault-tolerant framework that combines coherent observable estimation with a space-time-efficient implementation of non-Clifford rotations, suppressing the residual logical errors that limit existing partially fault-tolerant approaches. A benchmark against state-of-the-art tensor-network and variational Monte Carlo algorithms reveals a concrete crossover for mixed-field Ising dynamics at modest system sizes. For a physical error rate of p=10−3p=10^{-3}p=10−3, fault-tolerant simulation requires approximately 2 hours and 3.7×1053.7 \times 10^53.7×105 physical qubits for a 100-site 1D system, whereas tensor network approaches would require about 100 years. For 2D models, where rapid entanglement growth limits the classical evolution time, we project quantum runtimes within minutes. A physical error rate of p=10−4p=10^{-4}p=10−4 leads to at least an order of magnitude reduction in qubit count (3.1×1043.1 \times 10^43.1×104 physical qubits) and runtime (minutes for 1D and seconds for 2D). The reduction in quantum runtime arises from our improved rotation-state injection and co-design of quantum error correction and observable-estimation protocols, which jointly suppress logical-error accumulation and reduce sampling overhead. Our results establish a scalable route towards practical quantum advantage and identify quantitative engineering targets for future fault-tolerant architectures.