Quantum random walk and tight-binding model subject to projective measurements at random times

TL;DR

This paper investigates how repeated projective measurements at random times affect the survival probability in quantum systems, revealing exponential decay and characteristic power-law regimes depending on the measurement process and system size.

Contribution

It provides analytical and numerical insights into the survival probability dynamics under different measurement protocols in quantum walks and tight-binding models, highlighting universal behaviors.

Findings

Survival probability decays exponentially for large number of measurements when evolving with the projected state.

Power-law decay regimes with exponents -2 and -3/2 occur before exponential decay dominates.

Results are robust across various distributions of measurement intervals.

Abstract

What happens when a quantum system undergoing unitary evolution in time is subject to repeated projective measurements to the initial state at random times? A question of general interest is: How does the survival probability $S_m$, namely, the probability that an initial state survives even after $m$ number of measurements, behave as a function of $m$? We address these issues in the context of two paradigmatic quantum systems, one, the quantum random walk evolving in discrete time, and the other, the tight-binding model evolving in continuous time, with both defined on a one-dimensional periodic lattice with a finite number of sites $N$. For these two models, we present several numerical and analytical results that hint at the curious nature of quantum measurement dynamics. In particular, we unveil that when evolution after every projective measurement continues with the projected component of the instantaneous state, the average and the typical survival probability decay as an exponential in $m$ for large $m$. By contrast, if the evolution continues with the leftover component, namely, what remains of the instantaneous state after a measurement has been performed, the survival probability exhibits two characteristic $m$ values, namely, $m_1^\star(N) \sim N$ and $m_2^\star(N) \sim N^\delta$ with $\delta >1$. These scales are such that (i) for $m$ large and satisfying $m < m_1^\star(N)$, the decay of the survival probability is as $m^{-2}$, (ii) for $m$ satisfying $m_1^\star(N) \ll m < m_2^\star(N)$, the decay is as $m^{-3/2}$, while (iii) for $m \gg m_2^\star(N)$, the decay is as an exponential. We find that our results hold independently of the choice of the distribution of times between successive measurements, as have been corroborated by our results for a wide range of distributions. This fact hints at robustness and ubiquity of our derived results.