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

Dispersion of Magnetic Fields in Molecular Clouds. III

We apply our technique on the dispersion of magnetic fields in molecular clouds to high spatial resolution Submillimeter Array polarization data obtained for Orion KL in OMC-1, IRAS 16293, and NGC 1333 IRAS 4A. We show how one can take advantage of such high resolution data to characterize the magnetized turbulence power spectrum in the inertial and dissipation ranges. For Orion KL we determine that in the inertial range the spectrum can be approximately fitted with a power law k^-(2.9\pm0.9) and we report a value of 9.9 mpc for {\lambda}_AD, the high spatial frequency cutoff presumably due to turbulent ambipolar diffusion. For the same parameters we have \sim k^-(1.4\pm0.4) and a tentative value of {\lambda}_AD \simeq 2.2 mpc for NGC 1333 IRAS 4A, and \sim k^-(1.8\pm0.3) with an upper limit of {\lambda}_AD < 1.8 mpc for IRAS 16293. We also discuss the application of the technique to interferometry measurements and the effects of the inherent spatial filtering process on the interpretation of the results.Comment: 25 pages, 9 figures; accepted for publication in The Astrophysical Journa

Reconstruction of signals with unknown spectra in information field theory with parameter uncertainty

The optimal reconstruction of cosmic metric perturbations and other signals requires knowledge of their power spectra and other parameters. If these are not known a priori, they have to be measured simultaneously from the same data used for the signal reconstruction. We formulate the general problem of signal inference in the presence of unknown parameters within the framework of information field theory. We develop a generic parameter uncertainty renormalized estimation (PURE) technique and address the problem of reconstructing Gaussian signals with unknown power-spectrum with five different approaches: (i) separate maximum-a-posteriori power spectrum measurement and subsequent reconstruction, (ii) maximum-a-posteriori power reconstruction with marginalized power-spectrum, (iii) maximizing the joint posterior of signal and spectrum, (iv) guessing the spectrum from the variance in the Wiener filter map, and (v) renormalization flow analysis of the field theoretical problem providing the PURE filter. In all cases, the reconstruction can be described or approximated as Wiener filter operations with assumed signal spectra derived from the data according to the same recipe, but with differing coefficients. All of these filters, except the renormalized one, exhibit a perception threshold in case of a Jeffreys prior for the unknown spectrum. Data modes, with variance below this threshold do not affect the signal reconstruction at all. Filter (iv) seems to be similar to the so called Karhune-Loeve and Feldman-Kaiser-Peacock estimators for galaxy power spectra used in cosmology, which therefore should also exhibit a marginal perception threshold if correctly implemented. We present statistical performance tests and show that the PURE filter is superior to the others.Comment: 21 pages, 5 figures, accepted by PR

Reconstruction of signals with unknown spectra in information field theory with parameter uncertainty

The optimal reconstruction of cosmic metric perturbations and other signals requires knowledge of their power spectra and other parameters. If these are not known a priori, they have to be measured simultaneously from the same data used for the signal reconstruction. We formulate the general problem of signal inference in the presence of unknown parameters within the framework of information field theory. We develop a generic parameter uncertainty renormalized estimation (PURE) technique and address the problem of reconstructing Gaussian signals with unknown power-spectrum with five different approaches: (i) separate maximum-a-posteriori power spectrum measurement and subsequent reconstruction, (ii) maximum-a-posteriori power reconstruction with marginalized power-spectrum, (iii) maximizing the joint posterior of signal and spectrum, (iv) guessing the spectrum from the variance in the Wiener filter map, and (v) renormalization flow analysis of the field theoretical problem providing the PURE filter. In all cases, the reconstruction can be described or approximated as Wiener filter operations with assumed signal spectra derived from the data according to the same recipe, but with differing coefficients. All of these filters, except the renormalized one, exhibit a perception threshold in case of a Jeffreys prior for the unknown spectrum. Data modes, with variance below this threshold do not affect the signal reconstruction at all. Filter (iv) seems to be similar to the so called Karhune-Loeve and Feldman-Kaiser-Peacock estimators for galaxy power spectra used in cosmology, which therefore should also exhibit a marginal perception threshold if correctly implemented. We present statistical performance tests and show that the PURE filter is superior to the others.Comment: 21 pages, 5 figures, accepted by PR

CMB Temperature Polarization Correlation and Primordial Gravitational Waves

We examine the use of the CMB's TE cross correlation power spectrum as a complementary test to detect primordial gravitational waves (PGWs). The first method used is based on the determination of the lowest multipole, $\ell_0$, where the TE power spectrum, $C_{\ell}^{TE}$, first changes sign. The second method uses Wiener filtering on the CMB TE data to remove the density perturbations contribution to the TE power spectrum. In principle this leaves only the contribution of PGWs. We examine two toy experiments (one ideal and another more realistic) to see their ability to constrain PGWs using the TE power spectrum alone. We found that an ideal experiment, one limited only by cosmic variance, can detect PGWs with a ratio of tensor to scalar metric perturbation power spectra $r=0.3$ at 99.9% confidence level using only the TE correlation. This value is comparable with current constraints obtained by WMAP based on the $2\sigma$ upper limits to the B-mode amplitude. We demonstrate that to measure PGWs by their contribution to the TE cross correlation power spectrum in a realistic ground based experiment when real instrumental noise is taken into account, the tensor-to-scalar ratio, $r$, should be approximately three times larger.Comment: 13 pages, 13 figures, version matches published version. Combined with 0710.365

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

Percolation Analysis of a Wiener Reconstruction of the IRAS 1.2 Jy Redshift Catalog

We present percolation analyses of Wiener Reconstructions of the IRAS 1.2 Jy Redshift Survey. There are ten reconstructions of galaxy density fields in real space spanning the range $\beta= 0.1$ to $1.0$, where ${\beta}={\Omega^{0.6}}/b$, $\Omega$ is the present dimensionless density and $b$ is the bias factor. Our method uses the growth of the largest cluster statistic to characterize the topology of a density field, where Gaussian randomized versions of the reconstructions are used as standards for analysis. For the reconstruction volume of radius, $R {\approx} 100 h^{-1}$ Mpc, percolation analysis reveals a slight `meatball' topology for the real space, galaxy distribution of the IRAS survey. cosmology-galaxies:clustering-methods:numericalComment: Revised version accepted for publication in The Astrophysical Journal, January 10, 1997 issue, Vol.47