A new method clarifies how memory effects impact informational steady states, points where information gain from measurements balances information lost to the environment. This extends previous studies by explicitly accounting for ‘information backflow’, known as non-Markovianity, previously overlooked in models of these quantum systems and enabling more realistic simulations. Researchers at The University of Tokyo found that ‘memory’ within quantum systems affects their capacity to retain information when continuously monitored; stronger memory effects diminish the amount of stable information obtained from repeated measurements.

This finding relates to informational steady states, points where incoming data balances information lost to surrounding environments. Understanding how these influences operate is vital for building more accurate models of complex quantum processes impacted by past interactions. The researchers has demonstrated how ‘memory’ within quantum systems impacts their ability to reliably retain information when repeatedly measured; specifically, stronger memory effects reduce the amount of stable data obtained from these measurements.

The work builds upon existing studies by explicitly considering ‘information backflow’, or non-Markovianity, a phenomenon akin to short-term memory where a system’s present state depends on its recent past rather than solely current conditions. The team modelled interactions between quantum systems using what they call ‘collision models’, imagining billiard balls colliding and exchanging energy as a simplified way to represent environmental influences.

Understanding informational steady states is key for advancing accurate modelling of complex quantum processes. These are balancing acts where gaining new observational data matches losing old data to environmental ‘noise’. This latest research reveals how prior interactions sharply affect the formation of these stable information points, prompting further investigation into their properties.

Information gain improves with modelling of quantum system memory effects

Steady-state information gain per measurement increased from 0.13 bits to approximately 0.28 bits when non-Markovianity was removed. Previously, this threshold prevented accurate modelling of quantum systems possessing memory effects. University of Tokyo researchers explicitly modelled ‘information backflow’, allowing characterisation of how past states influence present measurements and informational steady states where gained data balances environmental losses.

Prior simulations relied on Markovian assumptions, that future behaviour depends only on current state, but the new approach enables more realistic analysis of complex quantum processes impacted by prior interactions, revealing a negative correlation between system “memory” and its capacity for stable information acquisition during continuous monitoring. The team further detailed how ‘information backflow’ impacts informational steady states using a specific quantum system model involving sequential two-qubit ‘ancillas’.

Simulations revealed an increase in interaction strength between ancillary qubits directly correlated with reduced achievable stable information; greater non-Markovianity corresponded to diminished capacity. Numerical analysis mapped variations in both system-ancilla and ancilla-ancilla interactions onto changes in steady-state information gain, confirming sensitivity to memory effects within the monitored process. Their collision models, simplified representations of complex environmental interactions, effectively capture key features of open quantum systems despite their relative simplicity. Reduced measurable information from increased feedback offers vital guidance for designing strong quantum technologies and will begin to unlock more durable quantum systems.

Non-Markovian dynamics enable sustained qubit stability despite environmental interference

Quantum systems can maintain stable information during continuous monitoring, an important step towards building resilient data processing technologies for noisy environments. This work reveals that ‘memory effects’, specifically non-Markovianity where past states influence present behaviour, fundamentally alter informational steady states; quantifying this impact presents challenges. Beyond simply identifying these points of balance between incoming observational data and environmental losses, the research characterises their properties under realistic conditions incorporating prior interactions. Establishing this link opens avenues for investigating how manipulating memory effects could optimise measurement processes in future technologies.

The researchers found a negative correlation between the degree of “memory” within a quantum system and its ability to sustain stable information acquisition during continuous monitoring. This means greater feedback from previous measurements diminished the capacity for maintaining measurable information. Using collision models with two-qubit ancillas, they demonstrated that increased interaction strength between ancillary qubits corresponded to reduced steady-state information gain. The study clarifies how non-Markovianity, the influence of past states on present behaviour, affects informational steady states, offering guidance for designing more durable quantum systems.

👉 More information
🗞 Non-Markovian effects on informational steady states
✍️ Jacob Werner (The University of Tokyo)
🧠 ArXiv: https://arxiv.org/abs/2610.01782

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