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

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.

Optical cavities as amplitude filters for squeezed fields

We explore the use of Fabry-P\'erot cavities as high-pass filters for squeezed light, and show that they can increase the sensitivity of interferometric gravitational-wave detectors without the need for long (kilometer scale) filter cavities. We derive the parameters for the filters, and analyze the performance of several possible cavity configurations in the context of a future gravitational-wave interferometer with squeezed light (vacuum) injected into the output port.Comment: 9 pages, 6 figure

Composite-pulse magnetometry with a solid-state quantum sensor

The sensitivity of quantum magnetometers is challenged by control errors and, especially in the solid-state, by their short coherence times. Refocusing techniques can overcome these limitations and improve the sensitivity to periodic fields, but they come at the cost of reduced bandwidth and cannot be applied to sense static (DC) or aperiodic fields. Here we experimentally demonstrate that continuous driving of the sensor spin by a composite pulse known as rotary-echo (RE) yields a flexible magnetometry scheme, mitigating both driving power imperfections and decoherence. A suitable choice of RE parameters compensates for different scenarios of noise strength and origin. The method can be applied to nanoscale sensing in variable environments or to realize noise spectroscopy. In a room-temperature implementation based on a single electronic spin in diamond, composite-pulse magnetometry provides a tunable trade-off between sensitivities in the microT/sqrt(Hz) range, comparable to those obtained with Ramsey spectroscopy, and coherence times approaching T1

On Noise-Enhanced Distributed Inference in the Presence of Byzantines

This paper considers the noise-enhanced distributed detection problem in the presence of Byzantine (malicious) nodes by suitably adding stochastic resonance (SR) noise. We consider two metrics - the minimum number of Byzantines (alpha_blind) needed to blind the fusion center as a security metric and the Kullback- Leibler divergence (DKL) as a detection performance metric. We show that alpha_blind increases when SR noise is added at the honest nodes. When Byzantines also start adding SR noise to their observations, we see no gain in terms of alpha_blind . However, the detection performance of the network does improve with SR. We also consider a game theoretic formulation where this problem of distributed detection in the presence of Byzantines is modeled as a minimax game between the Byzantines and the inference network, and numerically find Nash equilibria. The case when SR noise is added to the signals received at the fusion center (FC) from the sensors is also considered. Our numerical results indicate that while there is no gain in terms of , the network-wide performance measured in terms of alpha_blind the deflection coefficient does improve in this cas

Noise Enhanced M-ary Composite Hypothesis-Testing in the Presence of Partial Prior Information

Cataloged from PDF version of article.In this correspondence, noise enhanced detection is studied for M-ary composite hypothesis-testing problems in the presence of partial prior information. Optimal additive noise is obtained according to two criteria, which assume a uniform distribution (Criterion 1) or the least-favorable distribution (Criterion 2) for the unknown priors. The statistical characterization of the optimal noise is obtained for each criterion. Specifically, it is shown that the optimal noise can be represented by a constant signal level or by a randomization of a finite number of signal levels according to Criterion 1 and Criterion 2, respectively. In addition, the cases of unknown parameter distributions under some composite hypotheses are considered, and upper bounds on the risks are obtained. Finally, a detection example is provided in order to investigate the theoretical results. © 2010 IEEE

The impact of spike timing variability on the signal-encoding performance of neural spiking models

It remains unclear whether the variability of neuronal spike trains in vivo arises due to biological noise sources or represents highly precise encoding of temporally varying synaptic input signals. Determining the variability of spike timing can provide fundamental insights into the nature of strategies used in the brain to represent and transmit information in the form of discrete spike trains. In this study, we employ a signal estimation paradigm to determine how variability in spike timing affects encoding of random time-varying signals. We assess this for two types of spiking models: an integrate-and-fire model with random threshold and a more biophysically realistic stochastic ion channel model. Using the coding fraction and mutual information as information-theoretic measures, we quantify the efficacy of optimal linear decoding of random inputs from the model outputs and study the relationship between efficacy and variability in the output spike train. Our findings suggest that variability does not necessarily hinder signal decoding for the biophysically plausible encoders examined and that the functional role of spiking variability depends intimately on the nature of the encoder and the signal processing task; variability can either enhance or impede decoding performance

Using low levels of stochastic vestibular stimulation to improve locomotor stability

Low levels of bipolar binaural white noise based imperceptible stochastic electrical stimulation to the vestibular system (stochastic vestibular stimulation, SVS) have been shown to improve stability during balance tasks in normal, healthy subjects by facilitating enhanced information transfer using stochastic resonance (SR) principles. We hypothesize that detection of time-critical sub-threshold sensory signals using low levels of bipolar binaural SVS based on SR principles will help improve stability of walking during support surface perturbations. In the current study 13 healthy subjects were exposed to short continuous support surface perturbations for 60 s while walking on a treadmill and simultaneously viewing perceptually matched linear optic flow. Low levels of bipolar binaural white noise based SVS were applied to the vestibular organs. Multiple trials of the treadmill locomotion test were performed with stimulation current levels varying in the range of 0–1500 μA, randomized across trials. The results show that subjects significantly improved their walking stability during support surface perturbations at stimulation levels with peak amplitude predominantly in the range of 100–500 μA consistent with the SR phenomenon. Additionally, objective perceptual motion thresholds were measured separately as estimates of internal noise while subjects sat on a chair with their eyes closed and received 1 Hz bipolar binaural sinusoidal electrical stimuli. The optimal improvement in walking stability was achieved on average with peak stimulation amplitudes of approximately 35% of perceptual motion threshold. This study shows the effectiveness of using low imperceptible levels of SVS to improve dynamic stability during walking on a laterally oscillating treadmill via the SR phenomenon

Quantum state preparation and macroscopic entanglement in gravitational-wave detectors

Long-baseline laser-interferometer gravitational-wave detectors are operating at a factor of 10 (in amplitude) above the standard quantum limit (SQL) within a broad frequency band. Such a low classical noise budget has already allowed the creation of a controlled 2.7 kg macroscopic oscillator with an effective eigenfrequency of 150 Hz and an occupation number of 200. This result, along with the prospect for further improvements, heralds the new possibility of experimentally probing macroscopic quantum mechanics (MQM) - quantum mechanical behavior of objects in the realm of everyday experience - using gravitational-wave detectors. In this paper, we provide the mathematical foundation for the first step of a MQM experiment: the preparation of a macroscopic test mass into a nearly minimum-Heisenberg-limited Gaussian quantum state, which is possible if the interferometer's classical noise beats the SQL in a broad frequency band. Our formalism, based on Wiener filtering, allows a straightforward conversion from the classical noise budget of a laser interferometer, in terms of noise spectra, into the strategy for quantum state preparation, and the quality of the prepared state. Using this formalism, we consider how Gaussian entanglement can be built among two macroscopic test masses, and the performance of the planned Advanced LIGO interferometers in quantum-state preparation