For an open quantum reservoir, how the system forgets is part of how it computes. Quantum reservoir computing processes input streams with fixed quantum dynamics and trains only a linear readout. Dissipation can make old inputs fade, but prior studies commonly fix the environmental process and tune only its strength. Here we show numerically that the coupling pattern, meaning whether transitions connect to separate or shared environmental channels, changes which parts of the input history remain accessible. Paired simulations of finite spin reservoirs keep the Hamiltonian, inputs, measurements, and readout fixed. The tested patterns produce distinct task profiles, with no universal winner. Shared relaxation preserves more recent input history than independent local loss, and the retained memory changes when the qubits contribute with different relative phases to the shared decay channel. This ordering recurs across system sizes, Hamiltonians, input protocols, and targeted controls. Environmental coupling is therefore more than a damping parameter: it is a design layer that shapes not only how quickly information fades, but which input history remains available for computation.
Quantum reservoir computing processes temporal information through driven many-body dynamics, but its performance is ultimately limited by how accurately past inputs can be extracted from finite measurements. Here we formulate this limitation as a local multiparameter estimation problem and introduce a delay-space quantum Fisher information matrix to quantify the distinguishability of information stored at different delays. This perspective identifies Fisher-orthogonal memory as a measurement-efficient design principle: different delays should perturb the reservoir state along mutually Fisher-orthogonal directions. We first analyze the single-qubit limit using the Gill--Massar bound, revealing an optimal write-store-routing trade-off. Guided by this structure, we construct solvable multi-qubit reservoirs based on Clifford routing orbits and Singer-cycle Pauli algebra. The resulting dynamics yield diagonal delay-space QFIMs with analytically programmable fading profiles. Under finite-shot local Pauli readout, these reservoirs retain sharp memory windows that are absent in a validation-selected Ising baseline. Their product-task behavior is governed by second-order responses inherited from the same Pauli-routing algebra. Our results provide an analytically controlled route toward measurement-efficient quantum reservoir computing.
Tuning the reservoir Hamiltonian and the evolution time with Bayesian optimization at each encoding length, it is found that recurrent quantum memory is essential when a task must reach far into the past, and dispensable when the relevant history is short, where the memoryless reset limit already suffices.
Carlos Ramon-Escandell, Arnau Riera, Marcin Płodzień· 0 citations
Quantum reservoir computing (QRC) uses quantum dynamics to represent input histories for prediction through a trained classical readout. Discrete time crystals (DTCs) exhibit robust subharmonic responses under periodic driving, and previous work has used their dynamics to construct DTC-QRC. Here we construct a DTC-based reservoir architecture to predict molecular properties from structural and dynamical observations. Coherent Floquet evolution processes local molecular graph events and surface-hopping frames, while controlled reset regulates the contribution of earlier inputs. Measurements at the end of each input sequence yield a feature vector of fixed dimension. Trained classical decoders use this vector for inhibitor-activity and blood--brain-barrier permeability classification and electronic-gap forecasting, while the reservoir parameters remain fixed during training. With matched input lengths and output widths, DTC-QRC outperforms echo-state networks on long-prefix graph classification and the studied ethene gap forecasting tasks. Dephasing lowers performance in both applications, consistent with a role for coherent propagation. Experiments on the Quafu superconducting quantum cloud platform show that pair observables retain task information under device noise. The architecture provides a common framework for molecular screening and time-resolved property prediction using quantum reservoir computing.
Luo-Fei Wang, Da Zhang, Cong-Ren Wang et al.· 0 citations
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.
Yuval Idan, Ofek Nourian, E. Mentovich et al.· 0 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
This work introduces a classical-quantum state derived from the process tensor representing the dynamical part of this process for typical QRC protocols found in the literature, and extracts two diagnostics that characterise the nonlocal scrambling of information within, and loss of information from the substrate.
Nathan Keenan, Roberta Zambrini· 1 citation
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
