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arXiv:2307.04267 · Physical Review A

Phase transitions in sampling and error correction in local Brownian circuits

Subhayan Sahu, Shao-Kai Jian

Published Apr 15, 2024• 5 citations
arXivHTMLPDF

Abstract

We study the emergence of anticoncentration and approximate unitary design behavior in local Brownian circuits. The dynamics of circuit-averaged moments of the probability distribution and entropies of the output state can be represented as imaginary-time evolution with an effective local Hamiltonian in the replica space. This facilitates large-scale numerical simulation of the dynamics in $1+1$ dimensions of such circuit-averaged quantities using tensor network tools as well as identifying the various regimes of the Brownian circuit as distinct thermodynamic phases. In particular, we identify the emergence of anticoncentration as a sharp transition in the collision probability at $lnN$ timescale, where $N$ is the number of qubits. We also show evidence for a specific classical approximation algorithm undergoing a computational hardness transition at the same timescale. In the presence of noise, we show there is a noise-induced first-order phase transition in the linear cross entropy benchmark when the noise rate is scaled down as $1/N$. At longer times, the Brownian circuits approximate a unitary 2-design in $O(N)$ time. We directly probe the feasibility of quantum error correction by such circuits and identify a first-order transition at $O(N)$ timescales. The scaling behaviors for all these phase transitions are obtained from the large-scale numerics and corroborated by analyzing the spectrum of the effective replica Hamiltonian.

DOI
10.1103/physreva.109.042414

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We study the emergence of anticoncentration and approximate unitary design behavior in local Brownian circuits. The dynamics of circuit-averaged moments of the probability distribution and entropies of the output state can be represented as imaginary-time evolution with an effective local Hamiltonian in the replica space. This facilitates large-scale numerical simulation of the dynamics in 1+11+11+1 dimensions of such circuit-averaged quantities using tensor network tools as well as identifying the various regimes of the Brownian circuit as distinct thermodynamic phases. In particular, we identify the emergence of anticoncentration as a sharp transition in the collision probability at lnNlnNlnN timescale, where NNN is the number of qubits. We also show evidence for a specific classical approximation algorithm undergoing a computational hardness transition at the same timescale. In the presence of noise, we show there is a noise-induced first-order phase transition in the linear cross entropy benchmark when the noise rate is scaled down as 1/N1/N1/N. At longer times, the Brownian circuits approximate a unitary 2-design in O(N)O(N)O(N) time. We directly probe the feasibility of quantum error correction by such circuits and identify a first-order transition at O(N)O(N)O(N) timescales. The scaling behaviors for all these phase transitions are obtained from the large-scale numerics and corroborated by analyzing the spectrum of the effective replica Hamiltonian.
Competition between unitary dynamics that scrambles quantum information nonlocally and local measurements that probe and collapse the quantum state can result in a measurement-induced entanglement phase transition. Here we study this phenomenon in an analytically tractable all-to-all Brownian hybrid circuit model composed of qubits. The system is initially entangled with an equal sized reference, and the subsequent hybrid system dynamics either partially preserves or totally destroys this entanglement depending on the measurement rate. Our approach can access a variety of entropic observables which are distinguished by the averaging procedure, and for concreteness we focus on a particular purity quantity for which the averaging is particularly simple. We represent the purity as a path integral coupling four replicas with twisted boundary conditions. Saddle-point analysis reveals a second-order phase transition corresponding to replica permutation symmetry breaking below a critical measurement rate. The transition is mean-field-like and we characterize the critical properties near the transition in terms of a simple Ising field theory in 0+10+10+1 dimensions. In addition to studying the purity of the entire system, we study subsystem purities and relate these results to manifestations of quantum error correction in the model. We also comment on the experimental feasibility for simulating this averaged purity, and corroborate our results with exact diagonalization for modest system sizes.
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Measurement-induced entanglement phase transitions, caused by the competition between entangling unitary dynamics and disentangling projective measurements, have been studied in various random circuit models in recent years. In this paper, we study the dynamics of averaged purity for a simple NNN-qudit Brownian circuit model with all-to-all random interaction and measurements. In the large-NNN limit, our model is mapped to a one-dimensional quantum chain in the semi-classical limit, which allows us to analytically study critical behaviors and various other properties of the model. We show that there are two phases distinguished by the behavior of the total system entropy in the long time. In addition, the two phases also have distinct subsystem entropy behavior. The low measurement rate phase has a first-derivative discontinuity in the behavior of second Renyi entropy versus subsystem size, similar to the "Page curve" of a random state, while the other phase has a smooth entropy curve.
Random quantum circuits provide a framework for probing universal dynamical phenomena in chaotic quantum many-body systems, by circumventing the microscopic details of Hamiltonian evolution. Bipartite entanglement measures can be used to characterize the dynamical phases that emerge in these systems. Typically, under random unitary evolution, bipartite entanglement entropies exhibit a linear growth, and attain steady-state values that scale extensively with the system volume. However, when local projective measurements are introduced, a suppression of steady-state bipartite entropies occurs, leading to a sub-extensive scaling with the system volume. This class of entanglement scaling transitions, from an extensive to a sub-extensive scaling regime, has sparked interest in a broader class of measurement-induced phase transitions, with a potential to further our understanding of fault-tolerance in quantum computing, and in realizing synthetic quantum phases on digital quantum simulators. In this work, we characterize entanglement scaling transitions in one-dimensional random quantum circuits composed of q-level systems, with the local Hilbert space dimension q ≥ 2. This predominantly numerical study employs generalizations of the stabilizer formalism and the Clifford group to higher-dimensional Hilbert spaces to simulate the measurement-induced transitions. We find that the nature of the entanglement scaling transition remains invariant under changes in the local Hilbert space dimension. However, the critical measurement rate inducing the transition increases with q, asymptotically approaching 1/2 in the limit q → ∞. To further explore this classical limit, we develop a minimal dynamical model that captures entanglement structures under unitary evolution. We analyze the entanglement structures in thermal stabilizer states using this model, and propose an approach for incorporating measurements within this framework.
Random circuit sampling (RCS) remains one of the most competitive frameworks for demonstrating quantum advantage in near-term noisy intermediate-scale quantum (NISQ) hardware. Unfortunately, absent error-correction, existing benchmarks to characterize these experiments, like linear cross-entropy, have been classically spoofed due to noise. Because of this, there are interesting regimes, like shallow-depth random quantum circuits, where sampling is plausibly classically intractable, but no existing benchmark can distinguish between a noisy quantum computer and an adversarial classical spoofer. In this paper, we demonstrate that the nonlinear cross-entropy provides a sample-efficient benchmark for shallow-depth all-to-all random quantum circuits whose score cleanly separates noisy quantum computers from state-of-the-art classical spoofers, even in the presence of depolarizing noise. Further, we develop a binary classifier based on the notion of heavy output generation that features logarithmic sample complexity at short depth. Our evidence comes from exact analytic expressions for all-to-all Brownian circuit ensembles derived using replica tricks, and numerical simulations that corroborate these results for discrete Haar-random unitary circuits.