It is important for performance studies in quantum technologies to analyze quantum circuits in the presence of noise. We introduce an error probability tensor, a tool to track generalized Pauli error statistics of qudits within quantum circuits composed of qudit Clifford gates. Our framework is compatible with qudit stabilizer quantum error-correcting codes. We show how the error probability tensor can be applied in the most general case, and we demonstrate an error analysis of bipartite qudit repeaters with quantum error correction. We provide an exact analytical solution of the error statistics of the state distributed by such a repeater. For a fixed number of degrees of freedom, we observe that higher dimensional qudits can outperform qubits in terms of distributed entanglement.
It is important for performance studies in quantum technologies to analyze quantum circuits in the presence of noise. We introduce an error probability tensor, a tool to track generalized Pauli error statistics of qudits within quantum circuits composed of qudit Clifford gates. Our framework is compatible with qudit stabilizer quantum error-correcting codes. We show how the error probability tensor can be applied in the most general case, and we demonstrate an error analysis of bipartite qudit repeaters with quantum error correction. We provide an exact analytical solution of the error statistics of the state distributed by such a repeater. For a fixed number of degrees of freedom, we observe that higher dimensional qudits can outperform qubits in terms of distributed entanglement.
Quantum noise is a central challenge in quantum computing across many applications. Extensive work has examined how qubits couple to their environment, leading to decoherence and irreversible relaxation. This work studies a continuous coherent noise model for quantum circuits and compares it with a discrete Pauli model. The focus is on small, coherent gate errors that accumulate across circuit depth. These errors are modeled as random rotations on the Bloch sphere using a von Mises-Fisher distribution. In the small-angle limit, the model reduces to an isotropic Gaussian distribution. We test the model on quantum error-correction circuits based on the [[5,1,3]] and [[7,1,3]] codes. A variant of Grover's search circuit with different qubit counts is also examined. To enable fair comparison, we introduce a model-independent matching scheme. Pauli and continuous noise channels are aligned using the binary entropy at readout. This isolates the effect of noise structure at fixed uncertainty. An approximate analytical method for the propagation of coherent errors is also developed. The method tracks error distributions both on Clifford and non-Clifford circuits without full Monte Carlo sampling. It reduces simulation cost while preserving accuracy for circuit-level error estimates. The approximation is validated against brute-force simulations, identifying its regime of validity with Clifford and non-Clifford circuits under error correction. Our results show that continuous coherent noise and Pauli noise lead to comparable logical-error trends in the stabilizer-code circuits studied here. This behavior is consistent with syndrome extraction projecting a general single-qubit error onto Pauli-error subspaces before recovery. They also show where simplified propagation models work well and where their accuracy is reduced.
A powerful method for analyzing quantum error-correcting codes is to map them onto classical statistical mechanics models. Such mappings have thus far mostly focused on static codes, possibly subject to repeated syndrome measurements. Recent progress in quantum error correction, however, has prompted new paradigms where codes emerge from stabilizer circuits in spacetime -- a unifying perspective encompassing syndrome extraction circuits of static codes, dynamically generated codes, and logical operations. We show how to construct statistical mechanical models for stabilizer circuits subject to independent Pauli errors, by mapping logical equivalence class probabilities of errors to partition functions using the spacetime subsystem code formalism. We also introduce a modular language of spin diagrams for constructing the spin Hamiltonians, which we describe in detail focusing on independent circuit-level X-Z error channels. With the repetition and toric codes as examples, we use our approach to analytically rank logical error rates and thresholds between code implementations with standard and dynamic syndrome extraction circuits, describe the effect of transversal logical Clifford gates on logical error rates, and perform Monte Carlo simulations to estimate maximum likelihood thresholds. Our framework offers a universal prescription to analyze, simulate, and compare the decoding properties of any stabilizer circuit, while revealing the innate connections between dynamical quantum systems and noise-resilient phases of matter.
We demonstrate that small quantum memories, realised via quantum error correction in multi-qubit devices and implemented using noisy Clifford circuits, can benefit significantly from tailoring the choice of code to the error model of the Cliffords gates and environment. We present a simulation of these errors and the results of searching across random quantum error correcting codes and implementing the associated Clifford encoding circuits. This modeling incorporates a better representation of the experimental complexity involved in implementing these codes and demonstrates that tailored codes can outperform the Steane code with more realistic experimental noise. Depending on the error model, they are required to surpass the fault tolerant threshold. These Pauli error models correspond to individual Clifford generators and environmental noise on the wires. We present error models which incorporate independent identically distributed (IID) errors and biased Pauli errors in the construction and optimisation of Clifford circuits associated with maintaining a quantum memory.
We demonstrate that Pauli frames, a mathematical object used to efficiently sample qubit stabilizer circuits, can be used to efficiently sample qudit circuits of any prime dimension. Quantum error correcting codes are a central object of study in fault-tolerance quantum computing, which is necessary to realize useful universal quantum computing. Stabilizer codes belong to a large class of well-understood quantum codes that are crucially efficiently simulable on classical hardware using the so-called tableau representation. Popular simulation software like Stim exclusively studies and characterizes qubit codes, which entails repeatedly sampling a noisy quantum circuit with Pauli frames. We highlight the key differences (and fundamental similarities) between qubit and qudit stabilizer tableaus. It then teaches how Pauli frames generate batches of samples given a qudit tableau via two guided examples: one with a random measurement outcome but no noise, and one with a single noise gate.
Quantum computers are a revolutionary class of computational platforms with applications in combinatorial and global optimization, machine learning, and other domains involving computationally hard problems. While these machines typically operate on qubits—quantum information elements that can occupy superpositions of the basis∣0⟩and∣1⟩states—recent advances have demonstrated the practical implementation of higher-dimensional quantum systems (qudits) across various hardware platforms. In these hardware realizations, the higher-order states are less stable and thus remain coherent for a shorter duration than the basis∣0⟩and∣1⟩states. Moreover, formal methods for designing efficient encoder circuits for these systems remain underexplored. This limitation motivates the development of efficient circuit techniques for qudit systems (d-level quantum systems). Previous works have typically established generating gate sets for higher-dimensional codes by generalizing the methods used for qubits. In this work, we introduce a systematic framework for optimizing encoder circuits for prime-dimension stabilizer codes. This framework is based on novel generating gate sets whose elements map directly to efficient Clifford gate sequences. We demonstrate the effectiveness of this method on key codes, achieving a 13–44% reduction in encoder circuit gate count for the qutrit (d = 3)[[9,5,3]]3,[[5,1,3]]3, and[[7,1,3]]3codes, and a 9–21% reduction for the ququint (d = 5)[[10,6,3]]5code when compared to prior work. We also achieved circuit depth reductions up to 42%.
We analytically characterize how the location and the local or correlated structure of stochastic Pauli errors affect a three-qubit coherent quantum-teleportation circuit. Independent local channels and a fully correlated two-qubit channel are inserted separately in six configurations. Propagating each Pauli-error realization through the Clifford circuit yields the effective channel on Bob's qubit and analytical expressions for the average and state-resolved fidelities. Under a common ordered-pair probability convention, the six configurations form three pairs that induce equivalent reduced channels on Bob. Within each pair, corresponding Pauli-error realizations have the same probabilities and produce the same effective Pauli operator on Bob's output state. The equivalence therefore holds for every input state within the stochastic Pauli models considered here, rather than only for the average fidelity. Correlated Z errors do not affect the output for the first pair; local X and Z errors exhibit complementary qubit sensitivity for the second; and correlated same-axis Pauli errors cancel for the third. These results classify the error response of the selected circuit configurations and show that it depends jointly on the error statistics, Pauli axis, and position within the protocol.