13,222 research outputs found
Detection of weak stochastic force in a parametrically stabilized micro opto-mechanical system
Measuring a weak force is an important task for micro-mechanical systems,
both when using devices as sensitive detectors and, particularly, in
experiments of quantum mechanics. The optimal strategy for resolving a weak
stochastic signal force on a huge background (typically given by thermal noise)
is a crucial and debated topic, and the stability of the mechanical resonance
is a further, related critical issue. We introduce and analyze the parametric
control of the optical spring, that allows to stabilize the resonance and
provides a phase reference for the oscillator motion, yet conserving a free
evolution in one quadrature of the phase space. We also study quantitatively
the characteristics of our micro opto-mechanical system as detector of
stochastic force for short measurement times (for quick, high resolution
monitoring) as well as for the longer term observations that optimize the
sensitivity. We compare a simple, naive strategy based on the evaluation of the
variance of the displacement (that is a widely used technique) with an optimal
Wiener-Kolmogorov data analysis. We show that, thanks to the parametric
stabilization of the effective susceptibility, we can more efficiently
implement Wiener filtering, and we investigate how this strategy improves the
performance of our system. We finally demonstrate the possibility to resolve
stochastic force variations well below 1% of the thermal noise
Correlated noise in networks of gravitational-wave detectors: subtraction and mitigation
One of the key science goals of advanced gravitational-wave detectors is to
observe a stochastic gravitational-wave background. However, recent work
demonstrates that correlated magnetic fields from Schumann resonances can
produce correlated strain noise over global distances, potentially limiting the
sensitivity of stochastic background searches with advanced detectors. In this
paper, we estimate the correlated noise budget for the worldwide Advanced LIGO
network and conclude that correlated noise may affect upcoming measurements. We
investigate the possibility of a Wiener filtering scheme to subtract correlated
noise from Advanced LIGO searches, and estimate the required specifications. We
also consider the possibility that residual correlated noise remains following
subtraction, and we devise an optimal strategy for measuring astronomical
parameters in the presence of correlated noise. Using this new formalism, we
estimate the loss of sensitivity for a broadband, isotropic stochastic
background search using 1 yr of LIGO data at design sensitivity. Given our
current noise budget, the uncertainty with which LIGO can estimate energy
density will likely increase by a factor of ~4--if it is impossible to achieve
significant subtraction. Additionally, narrowband cross-correlation searches
may be severely affected at low frequencies f < 45 Hz without effective
subtraction.Comment: 16 pages, 8 figure
Detection of noise-corrupted sinusoidal signals with Josephson junctions
We investigate the possibility of exploiting the speed and low noise features
of Josephson junctions for detecting sinusoidal signals masked by Gaussian
noise. We show that the escape time from the static locked state of a Josephson
junction is very sensitive to a small periodic signal embedded in the noise,
and therefore the analysis of the escape times can be employed to reveal the
presence of the sinusoidal component. We propose and characterize two detection
strategies: in the first the initial phase is supposedly unknown (incoherent
strategy), while in the second the signal phase remains unknown but is fixed
(coherent strategy). Our proposals are both suboptimal, with the linear filter
being the optimal detection strategy, but they present some remarkable
features, such as resonant activation, that make detection through Josephson
junctions appealing in some special cases.Comment: 22 pages, 13 figure
Evaluation of bistable systems versus matched filters in detecting bipolar pulse signals
This paper presents a thorough evaluation of a bistable system versus a
matched filter in detecting bipolar pulse signals. The detectability of the
bistable system can be optimized by adding noise, i.e. the stochastic resonance
(SR) phenomenon. This SR effect is also demonstrated by approximate statistical
detection theory of the bistable system and corresponding numerical
simulations. Furthermore, the performance comparison results between the
bistable system and the matched filter show that (a) the bistable system is
more robust than the matched filter in detecting signals with disturbed pulse
rates, and (b) the bistable system approaches the performance of the matched
filter in detecting unknown arrival times of received signals, with an
especially better computational efficiency. These significant results verify
the potential applicability of the bistable system in signal detection field.Comment: 15 pages, 9 figures, MikTex v2.
Detection of subthreshold pulses in neurons with channel noise
Neurons are subject to various kinds of noise. In addition to synaptic noise,
the stochastic opening and closing of ion channels represents an intrinsic
source of noise that affects the signal processing properties of the neuron. In
this paper, we studied the response of a stochastic Hodgkin-Huxley neuron to
transient input subthreshold pulses. It was found that the average response
time decreases but variance increases as the amplitude of channel noise
increases. In the case of single pulse detection, we show that channel noise
enables one neuron to detect the subthreshold signals and an optimal membrane
area (or channel noise intensity) exists for a single neuron to achieve optimal
performance. However, the detection ability of a single neuron is limited by
large errors. Here, we test a simple neuronal network that can enhance the
pulse detecting abilities of neurons and find dozens of neurons can perfectly
detect subthreshold pulses. The phenomenon of intrinsic stochastic resonance is
also found both at the level of single neurons and at the level of networks. At
the network level, the detection ability of networks can be optimized for the
number of neurons comprising the network.Comment: 14 pages, 9 figure
Measurement and control of a mechanical oscillator at its thermal decoherence rate
In real-time quantum feedback protocols, the record of a continuous
measurement is used to stabilize a desired quantum state. Recent years have
seen highly successful applications in a variety of well-isolated
micro-systems, including microwave photons and superconducting qubits. By
contrast, the ability to stabilize the quantum state of a tangibly massive
object, such as a nanomechanical oscillator, remains a difficult challenge: The
main obstacle is environmental decoherence, which places stringent requirements
on the timescale in which the state must be measured. Here we describe a
position sensor that is capable of resolving the zero-point motion of a
solid-state, nanomechanical oscillator in the timescale of its thermal
decoherence, a critical requirement for preparing its ground state using
feedback. The sensor is based on cavity optomechanical coupling, and realizes a
measurement of the oscillator's displacement with an imprecision 40 dB below
that at the standard quantum limit, while maintaining an
imprecision-back-action product within a factor of 5 of the Heisenberg
uncertainty limit. Using the measurement as an error signal and radiation
pressure as an actuator, we demonstrate active feedback cooling (cold-damping)
of the 4.3 MHz oscillator from a cryogenic bath temperature of 4.4 K to an
effective value of 1.10.1 mK, corresponding to a mean phonon number of
5.30.6 (i.e., a ground state probability of 16%). Our results set a new
benchmark for the performance of a linear position sensor, and signal the
emergence of engineered mechanical oscillators as practical subjects for
measurement-based quantum control.Comment: 24 pages, 10 figures; typos corrected in main text and figure
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