Abstract
Abstract
We provide a general framework to compute the probability distribution
F
r
(
t
)
of the first detection time of a ‘state of interest’ in a closed quantum system subjected to random projective measurements. In our ‘quantum resetting’ protocol, resetting of a state is not implemented by an additional classical stochastic move, but rather by the random projective measurement. We then apply this general framework to Poissonian measurement protocol with a constant rate r and demonstrate that exact results for
F
r
(
t
)
can be obtained for a generic two level system. Interestingly, the result depends crucially on the detection schemes involved and we have studied two complementary schemes, where the state of interest either coincides or differs from the initial state. We show that
F
r
(
t
)
at short times vanishes universally as
F
r
(
t
)
∼
t
2
as t → 0 in the first scheme, while it approaches a constant as t → 0 in the second scheme. The mean first detection time, as a function of the measurement rate r, also shows rather different behaviors in the two schemes. In the former, the mean detection time is a non-monotonic function of r with a single minimum at an optimal value
r
∗
, while in the later, it is a monotonically decreasing function of r, signaling the absence of a finite optimal value. These general predictions for arbitrary two level systems are then verified via explicit computation in the Jaynes–Cummings model of light–matter interaction. We also generalize our results to non-Poissonian measurement protocols with a renewal structure where the intervals between successive independent measurements are distributed via a general distribution
p
(
τ
)
and show that the short time behavior of
F
r
(
t
)
∼
p
(
0
)
t
2
is universal as long as
p
(
0
)
≠
0
. This universal t
2 law emerges from purely quantum dynamics that dominates at early times.
Funder
SERB
Department of Atomic Energy, Government of India
VAJRA
CEFIPRA, SERB, Ramanujan Fellowship
Subject
General Physics and Astronomy,Mathematical Physics,Modeling and Simulation,Statistics and Probability,Statistical and Nonlinear Physics
Cited by
4 articles.
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