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Differential wavefront sensing is an essential technique for optimising the performance of many precision interferometric experiments. Perhaps the most extensive application of this is for alignment sensing using radio-frequency beats…
Alignment control in gravitational-wave detectors has consistently proven to be a difficult problem due to the stringent noise contamination requirement for the gravitational wave readout and the radiation-pressure-induced angular…
To address the complex beam control in traditional multiple-input multiple-output (MIMO) systems, researchers have proposed adaptive beam alignment using retro-directive antenna (RDA) arrays. This approach creates echo resonance between the…
We adopt the Ramsey's method of separated oscillatory fields to study coherences of the mechanical system in an optomechanical resonator. The high resolution Ramsey fringes are observed in the emission optical field, when two pulses…
For wideband spectrum sensing, compressive sensing has been proposed as a solution to speed up the high dimensional signals sensing and reduce the computational complexity. Compressive sensing consists of acquiring the essential information…
A folded resonant Fabry-Perot cavity has the potential to significantly reduce the impact of coating thermal noise on the performance of kilometer scale gravitational wave detectors. When constructed using only spherical mirror surfaces it…
We propose to selectively engineer a single cavity resonance to achieve frequency matching for optical parametric processes in high-Q microresonators. For this purpose, we demonstrate an approach, selective mode splitting (SMS), to…
Frequency combs spanning over an octave have been successfully demonstrated in Kerr nonlinear microresonators on-chip. These micro-combs rely on both engineered dispersion, to enable generation of frequency components across the octave, and…
Existing approaches to compressive sensing of frequency-sparse signals focuses on signal recovery rather than spectral estimation. Furthermore, the recovery performance is limited by the coherence of the required sparsity dictionaries and…
We carried out a computer simulation of a large gravitational wave (GW) interferometer using the specifications of the LIGO instruments. We find that if in addition to the carrier, a single sideband offset from the carrier by the fsr…
The detection and subsequent inference of binary black hole signals rely heavily on the accuracy of the waveform model employed. In the highly non-linear, dynamic, and strong-field regime near merger, these waveforms can only be accurately…
The crucial limitation of improving the sensitivity of the detection of weak magnetic fields is the unavoidable measurement noise. In this paper, we propose a scheme to achieve precise sensing robust against additional noise by employing a…
Energy consumption and hardware cost of signal digitization together with the management of the resulting data volume form serious issues for high-rate measurement systems with multiple sensors. Switching to binary sensing front-ends…
RF-ICE is a signal processing platform for the readout of large arrays of superconducting resonators. Designed for flexibility, the system's low digital latency and ability to independently and dynamically set the frequency and amplitude of…
Sensor selection refers to the problem of intelligently selecting a small subset of a collection of available sensors to reduce the sensing cost while preserving signal acquisition performance. The majority of sensor selection algorithms…
The ultrahigh frequency emission of gravitational waves by binary systems of black holes has recently been investigated in details in the framework of new experimental ideas around resonant cavities. In this article, we consider the case of…
Precise alignment sensing and control are essential for maintaining the stability of laser interferometric gravitational-wave detectors. Conventional Wave Front Sensing technique (WFS), which relies on the beat between the carrier and…
We propose a technique of signal acquisition using a combination of two devices with different sampling rates and quantization accuracies. Subsequent processing involving sparsity regularization enables us to reconstruct the signal at such…
One of the key challenges in sensor networks is the extraction of information by fusing data from a multitude of distinct, but possibly unreliable sensors. Recovering information from the maximum number of dependable sensors while…
This contribution introduces a novel signal extrapolation algorithm and its application to image error concealment. The signal extrapolation is carried out by iteratively generating a model of the signal suffering from distortion. Thereby,…