Entropic uncertainty under indefinite causal order and input-output direction
Göktuğ Karpat
TL;DR
This work analyzes memory-assisted entropic uncertainty relations (MA-EUR) under Pauli-channel noise affecting the memory qubit, using higher-order quantum processes—the quantum switch and quantum time-flip—to create indefinite causal order and indefinite input-output direction. By modeling the memory as a Bell-diagonal state and evaluating $S(Q|B)+S(R|B)$ for $Q=\sigma_x$ and $R=\sigma_z$, the authors derive explicit expressions for the left-hand side and the MA-EUR bound under three regimes: single-use, self-switched, and time-flipped Pauli channels. They show that both switch and time-flip can reduce the total uncertainty relative to direct noise, with a clear threshold $p>1/2$ for self-switch advantages and a simple condition $|\tau_x|>|\lambda_x|$ for time-flip advantages, highlighting indefinite causal structures as practical resources for noise mitigation in MA-EUR tasks. The results imply that indefinite causal order and input-output direction can enhance robustness of MA-EUR-based protocols and related quantum information applications.
Abstract
Entropic uncertainty relations quantify the limits on the predictability of quantum measurements. When the measured system is correlated with a quantum memory, these limits are described by the memory-assisted entropic uncertainty relation (MA-EUR). We examine the behavior of MA-EUR when the memory qubit undergoes noisy dynamics implemented via high-order controlled processes, namely, the quantum switch and the quantum time-flip. We consider a setting in which the control qubit is the very system on which the measurements are performed, while the target qubit serves as a noisy quantum memory. Focusing on Pauli channels, we show that feeding them into the quantum switch and the quantum time-flip can significantly reduce the total entropic uncertainty as compared to their direct application. Our results reveal that indefinite causal order and input-output direction can serve as resources to mitigate the effects of noise in the context of MA-EUR and its applications.
