An AI-assisted error-mitigation framework for quantum diffusion processes generated by sequential local weak measurements that provides a hybrid classical-quantum approach for approximating non-unitary dynamics and mitigating coherence loss.
Abstract
Coupling between a quantum system and its environment causes decoherence by transferring information from the system to environmental degrees of freedom. When discretized in time, such interactions can be interpreted as sequences of weak measurements that provide an effective model of noisy quantum dynamics. Motivated by this picture, we propose an AI-assisted error-mitigation framework for quantum diffusion processes generated by sequential local weak measurements. The forward process progressively erases information from the input state through weak measurements performed in randomly selected Pauli bases, producing basis-dependent local dephasing and locally depolarizing dynamics on average. Machine-learning models are trained on exact synthetic density matrices to learn a channel- and distribution-specific denoising map and estimate the corresponding pre-noise state. We benchmark the approach on single-qubit states and separable and entangled multi-qubit registers. We also study distribution-dependent local-to-global reconstruction, in which local reduced density matrices are used to reconstruct the global state. This experimentally motivated setting relies on locally accessible information and is therefore compatible with noisy and distributed quantum systems. More broadly, the framework provides a hybrid classical-quantum approach for approximating non-unitary dynamics and mitigating coherence loss.
Quantum-enhanced sensing with atomic ensembles has predominantly focused on qubit-based protocols, despite the growing ability of many experimental platforms to coherently control and entangle multi-level systems. Here, we investigate quantum-enhanced sensing with qutrit ensembles by introducing three experimentally feasible qutrit generalisations of the one-axis twisting (OAT) model that involve entangling operations only between two levels, while the third level primarily acts as a spectator. We characterize the metrological utility of the dynamically generated states using the quantum Fisher information toolbox. We find numerically that all three models offer considerable freedom in encoding direction for quantum-enhanced sensing, with up to 6 out of 8 possible directions exhibit near-Heisenberg scaling after a short evolution time. We discuss experimental access to this enhanced metrological precision via effective time-reversal protocols. Furthermore, we examine the practical issues of estimation ambiguity and local dissipation, and show that they can be largely overcome by optimizing the sensor operating point. Finally, we show that the measurement incompatibility in estimating multiple parameters simultaneously encoded in different directions with near-Heisenberg scaling of precision is suppressed at the zero operating point as the system size increases. In the process, we find that one of the models enables near-Heisenberg scaling metrology with a pair of commuting generators, a possibility that arises from the $su(3)$ algebra and is thus absent in qubit-ensemble based sensors of collective $SU(2)$ rotations.
Deepshikha Datta, Sayam Chakraborty, J. D. Wilson et al.· 0 citations
We investigate the simultaneous control of quantum parameter-estimation precision and non-Markovian memory effects in a driven two-qubit system that is collectively coupled to a leaky cavity. Using a dressed-state formalism, we derive analytical solutions for identical and non-identical qubits and analyze how classical driving and detuning affect metrological performance. Classical driving enhances the quantum Fisher information (QFI) by sustaining coherence and shifting effective transitions away from cavity resonance, thereby suppressing decoherence in both weak- and strong-coupling regimes. The steady-state QFI is further improved by positive classical-field detuning, which reduces spectral overlap with the lossy reservoir. To characterize memory effects, we examine the QFI-flow and the Breuer–Laine–Piilo (BLP) trace-distance measure. Our results reveal a nontrivial control trade-off: increasing the Rabi frequency suppresses non-Markovian information backflow, whereas increasing qubit detuning enhances memory effects by promoting system–environment correlations. Despite their different definitions, the QFI-flow and BLP measures yield consistent qualitative behavior in this system. These findings demonstrate that classical-field parameter tuning empowers researchers to optimize estimation precision and non-Markovianity in dissipative cavity-QED, with direct applicability to superconducting circuit platforms.
Ghasem Zare Firozi, A. Mortezapour, Borhan Arghavani Nia et al.· AVS Quantum Science· 0 citations
Continuous weak measurements of quantum systems are of great relevance in quantum foundations and applications. They can be achieved by probing the quantum system of interest by repeatedly measuring an auxiliary system weakly coupled to it. Here we study two qubits coupled in different points to a common one-dimensional electromagnetic field and simultaneously monitored in the right- and left-propagating output channels by homodyne detection. Using a collision-model description, we derive an analytical Stochastic Master Equation (SME) governing the resulting diffusive quantum trajectories, including the interference between the two measurement channels. For nonlinear functions of the quantum state, such as entropies, averages over quantum trajectories generally differ from the corresponding quantities evaluated on the unconditional state. Through this mechanism, we show that continuous monitoring generates entanglement, absent in the unconditional dynamics, and enhances quantum magic in the qubit pair during the decay. Both resources can be tuned through the optical phase accumulated between the qubits and the phases of homodyne local oscillators. Our results establish continuous homodyne monitoring of multiple emitters as a tunable mechanism for generating quantum resources.
Debmalya Das, Giuseppe Magnifico, Maria Maffei· 0 citations
Neural quantum states (NQSs) have emerged as a powerful ansatz for quantum dynamics. Their high entanglement capacity promises to overcome the entanglement barrier. However, existing time-dependent NQS methods are ill-equipped to propagate sparsely supported initial states due to the inherent mismatch between the supports of such states and their time derivatives. To address this issue, we introduce the interpolation sampling method as a novel form of importance sampling, where samples are drawn from a distribution that interpolates between the wave function and its time derivative. Combined with a global-in-time variational principle, we demonstrate with the example of the two-dimensional transverse-field Ising model that interpolation sampling allows for accurate propagation of extremely peaked states that standard wave function sampling could not tackle. We further improve sampling efficiency by introducing (i) a configuration-time joint sampling scheme where spin configurations and time are both treated as random variables, and (ii) a hybrid strategy for sample proposal that incorporates the knowledge of a Krylov subspace. Our work extends the scope of time-dependent NQS methods to a wider range of physically relevant scenarios, while challenging the prevailing reliance on the Born distribution and its close variants as the default basis for sampling.
Learning unknown noise processes in quantum systems reveals their physical origin and informs error suppression, mitigation, and correction. Characterizing a general quantum process requires exponentially many parameters inferred from noncommuting measurements. Because these measurements cannot be performed simultaneously, the sample complexity grows exponentially. For Pauli channels, quantum memory and entangling operations can transform this task into measurements of commuting observables, reducing complexity exponentially. However, noise in these resources increases the overhead, leaving open whether any advantage remains in realistic devices. Here, we introduce error-mitigated entanglement-enhanced learning, analyze it theoretically, and demonstrate it experimentally. We quantify the noise-induced overhead, perform hypothesis testing with up to 64 qubits, and learn intrinsic noise in parallel-gate layers using up to 16 qubits of a superconducting processor. We show that noisy quantum memory provides a learning advantage, with a current experimental overhead of 1.33 ± 0.05 per qubit, below the no-entanglement lower bound of 2. The authors show that entanglement with noisy quantum memory can significantly speed up learning of quantum processes. With error mitigation, their method characterizes quantum noise at scale and outperforms entanglement-free approaches.
A. Seif, Senrui Chen, Swarnadeep Majumder et al.· Nature Communications· 12 citations
We study quantum resources in tilted‐Dirac materials using a thermal state and reservoir‐driven dynamics in dissipative weak‐coupling and memory‐bearing strong‐coupling regimes. In contrast to the usual treatments based on the Bellomo formalism and relying on Bell or Werner states, the present approach starts from a physically motivated thermal state of two qubits whose initial properties are determined by the system temperature and the velocity parameters of the underlying Dirac material. The subsequent dynamics is modeled using the Bellomo formalism for two independent qubits, each locally coupled to an independent reservoir. To characterize the evolution, we analyze coherence quantified by the ‐norm and local quantum Fisher information. Weak, effectively Markovian coupling yields monotonic coherence decay, while local quantum Fisher information depends more strongly on parameters, especially at low reservoir temperatures; varying velocity parameters together obscures their individual effects. With strong, memory‐bearing coupling, coherence remains suppressed at long times, whereas local quantum Fisher information decreases then recovers to a large asymptotic value. The two measures thus respond differently to thermal, material, and reservoir effects, without implying general practical metrological superiority of local quantum Fisher information.
A. El Mouatasim, A. El Houri, Brahim el Houari et al.· Annals of Physics· 0 citations
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