This computational notebook presents a toy quantum error-correction simulation for studying coherent non-Markovian noise in a distance-5 repetition code. The model uses five data qubits and five environment qubits. Each data qubit is coupled to its own environment qubit through a coherent system-environment interaction, and the environment is not reset between QEC rounds. This allows memory effects to build up over repeated correction cycles. The notebook compares two descriptions of the same noisy QEC experiment: 1. full coherent non-Markovian system-environment evolution, and2. a Pauli-twirled / SPP-style stochastic Pauli baseline. The main quantity studied is the logical failure probability as a function of coupling strength. The aim is to test the limits of Pauli-twirled or SPP-style approximations by checking when coherent memory effects change the logical error rate. This is an exploratory notebook and a first-stage QEC-level toy model before moving to larger surface-code simulations.
This computational notebook presents a toy quantum error-correction simulation for studying coherent non-Markovian noise in a distance-5 repetition code. The model uses five data qubits and five environment qubits. Each data qubit is coupled to its own environment qubit through a coherent system-environment interaction, and the environment is not reset between QEC rounds. This allows memory effects to build up over repeated correction cycles. The notebook compares two descriptions of the same noisy QEC experiment: 1. full coherent non-Markovian system-environment evolution, and2. a Pauli-twirled / SPP-style stochastic Pauli baseline. The main quantity studied is the logical failure probability as a function of coupling strength. The aim is to test the limits of Pauli-twirled or SPP-style approximations by checking when coherent memory effects change the logical error rate. This is an exploratory notebook and a first-stage QEC-level toy model before moving to larger surface-code simulations.
Correlated noise is a critical failure mode in quantum error correction (QEC), yet a gap remains between the stochastic Pauli models used for scalable QEC analyses and the microscopic, non-Markovian descriptions of noise in physical devices. We bridge this gap by introducing Spatiotemporal Pauli Processes (SPPs): the natural multi-time generalization of Pauli channels, joint probability distributions over Pauli faults across space and time, obtained exactly from any noise process, however non-Markovian, under standard Pauli-frame randomization. SPPs thereby provide a single language in which correlated noise can be recast, compared, and extended, compatible with both microscopic open systems modeling and the stabilizer workflow of QEC design and analysis. Our central result is constructive: the multi-time Pauli twirl acts by local contractions on a process tensor network, yielding an explicit classical tensor network whose virtual bonds encode memory, bounded by the environment's Liouville-space dimension. Transfer operator diagnostics link memory spectra to correlation decay, and hidden Markov representations enable efficient sampling of correlated Pauli fault trajectories, mapping microscopically derived noise directly into circuit-level QEC simulation. We demonstrate this with surface code memory and stability benchmarks up to distance 19. A temporal "storm" model with tunable correlation time shows that memory alone, at strictly fixed marginal error rates, systematically erodes the exponential error suppression expected from code distance. A genuinely spatiotemporal quantum cellular automaton bath maps exactly, under system twirling, to a nonlinear probabilistic cellular automaton; tuning its coherent interactions drives the noise into a pseudo-critical regime with critical slowing down and macroscopic error avalanches that reverse surface code distance scaling.
This computational notebook tests the limits of Spatiotemporal Pauli Process (SPP)-style approximations against full coherent non-Markovian noise in a small quantum error-correction simulation. The notebook constructs a microscopic system-environment noise model where data qubits are coherently coupled to environment qubits. The environment is not reset between QEC rounds, allowing temporal memory effects to accumulate. Two descriptions of the same noisy process are compared: 1. full coherent non-Markovian system-environment evolution, and2. an SPP / Pauli-trajectory approximation extracted from the coherent bath. The simulation uses a small rotated surface-code-style patch and compares the logical failure probability under both descriptions. Coupling strength and number of QEC rounds are varied to identify regimes where the SPP approximation agrees with, or deviates from, the full coherent model. The purpose of the notebook is not to claim a complete large-scale surface-code result, but to provide an exploratory testbed for studying when coherent and memory effects become important for QEC-level logical performance.
Quantum error correction (QEC), the lynchpin of fault-tolerant quantum computing (FTQC), is designed and validated against well-behaved Pauli stochastic error models. But in real-world deployment, QEC protocols encounter a vast array of other errors -- coherent and non-Pauli errors -- whose impacts on quantum circuits are vastly different than those of stochastic Pauli errors. The impacts of these errors on QEC and FTQC protocols have been largely unpredictable to date due to exponential classical simulation cost. Here, we show how to accurately and efficiently model the effects of coherent and non-Pauli errors on FTQC, and we study the effects of such errors on syndrome extraction for surface and bivariate bicycle codes, and on magic state cultivation. Our analysis suggests that coherent error can shift fault-tolerance thresholds, increase the space-time cost of magic state cultivation, and can increase logical error rates by an order of magnitude compared to equivalent stochastic errors. These analyses are enabled by a new technique for mapping any Markovian circuit-level error model with sufficiently small error rates onto a detector error model (DEM) for an FTQC circuit. The resulting DEM enables Monte Carlo estimation of logical error rates and noise-adapted decoding, and its parameters can be analytically related to the underlying physical noise parameters to enable approximate strong simulation.
Abstract Quantum computers are powerful tools for certain computational problems, but their fragile quantum states are easily disrupted by environmental noise, causing errors that degrade computational accuracy. Quantum error correction (QEC) addresses this challenge by encoding one logical qubit across multiple physical qubits, so that individual errors can be identified and reversed through redundancy. We used Qiskit Aer, a free open-source quantum circuit simulator, to test the repetition code, one of the simplest QEC methods, under three types of noise: bit-flip, phase-flip, and depolarizing. We compared an unprotected single-qubit baseline (n = 1) to 3-qubit (n = 3) and 5-qubit (n = 5) repetition codes, sweeping the physical error rate p from 0 to 0.15 with 4,000 simulation shots per data point. We hypothesized that larger codes would achieve higher logical success probabilities at all tested noise levels, with n = 5 outperforming n = 3, which would outperform the unprotected baseline. Our results confirmed this scaling trend across all three noise types. At p = 0.10 under bit-flip noise, the baseline achieved 0.713 logical success, while n = 3 reached 0.791 and n = 5 reached 0.843. At low noise (p = 0.02), the n = 5 code approached 0.994 logical success. Simulation results closely matched exact theoretical predictions derived from the binomial failure probability formula, validating our experimental implementation. These findings confirm that even the simplest QEC methods provide meaningful error reduction and that larger codes offer greater protection, demonstrating a foundational principle of quantum error correction using only free simulation tools.
The performance of quantum error correction (QEC) codes is limited by the underlying physical noise. Theoretical studies show that coherent and stochastic noise have different effects when performing QEC with either surface or repetition codes. We use the bitflip repetition code, realized in a transmon quantum processor, as a testbed to experimentally study the impact of injecting coherent versus stochastic errors on the logical performance. We adapt a scalable free-fermion simulator to simulate the experiments and we modify a subset sampling technique to efficiently sample stochastic noise in the quantum circuit. In the experiment, we do not observe the difference in logical fidelity predicted by simulation for either the distance-3 or distance-5 repetition codes. We hypothesize that this discrepancy could be explained by small drifts in qubit frequencies, which introduce phase-coherent noise that `stochastifies' the injected coherent errors. Our work contributes to advancing an understanding of how coherent errors affect experimental QEC.
The demonstration of quantum error correction (QEC) is one of the most important milestones in the realization of fully-fledged quantum computers. Toward this, QEC experiments using the surface codes have recently been actively conducted. However, it has not yet been realized to protect logical quantum information beyond the physical coherence time. In this work, we performed a full simulation of QEC for the rotated surface codes with a code distance 5, which employs 49 qubits and is within reach of the current state-of-the-art quantum computers. In particular, we evaluate the logical error probability in a realistic noise model that incorporates not only stochastic Pauli errors but also coherent errors due to a systematic control error or unintended interactions. While a straightforward simulation of 49 qubits is not tractable within a reasonable computational time, we reduced the number of qubits required to 26 qubits by delaying the syndrome measurement in simulation. This and a fast quantum computer simulator, , implemented on GPU allows us to simulate full QEC with an arbitrary local noise within reasonable simulation time. Based on the numerical results, we also construct and verify an effective model to incorporate the effect of the coherent error into a stochastic noise model. This allows us to understand what the effect coherent error has on the logical error probability on a large scale without full simulation based on the detailed full simulation of a small scale. The present simulation framework and effective model, which can handle arbitrary local noise, will play a vital role in clarifying the physical parameters that future experimental QEC should target. Published by the American Physical Society 2024