Seconds-scale coherence in a tweezer-array optical clock

Optical clocks based on atoms and ions achieve exceptional precision and accuracy, with applications to relativistic geodesy, tests of relativity, and searches for dark matter. Achieving such performance requires balancing competing desirable features, including a high particle number, isolation of atoms from collisions, insensitivity to motional effects, and high duty-cycle operation. Here we demonstrate a new platform based on arrays of ultracold strontium atoms confined within optical tweezers that realizes a novel combination of these features by providing a scalable platform for isolated atoms that can be interrogated multiple times. With this tweezer-array clock, we achieve greater than 3 second coherence times and record duty cycles up to 96%, as well as stability commensurate with leading platforms. By using optical tweezer arrays --- a proven platform for the controlled creation of entanglement through microscopic control --- this work further promises a new path toward combining entanglement enhanced sensitivities with the most precise optical clock transitions

Formulation of the information capacity of the optical-mechanical line-scan imaging process

An expression for the information capacity of the optical-mechanical line-scan imaging process is derived which includes the effects of blurring of spatial, photosensor noise, aliasing, and quantization. Both the information capacity for a fixed data density and the information efficiency (the ratio of information capacity to data density) exhibit a distinct single maximum when displayed as a function of sampling rate, and the location of this maximum was determined by the system frequency-response shape, signal-to-noise ratio, and quantization interval

High performance architecture design for large scale fibre-optic sensor arrays using distributed EDFAs and hybrid TDM/DWDM

A distributed amplified dense wavelength division multiplexing (DWDM) array architecture is presented for interferometric fibre optic sensor array systems. This architecture employs a distributed erbium doped fibre amplifier (EDFA) scheme to decrease the array insertion loss, and employs time division multiplexing (TDM) at each wavelength to increase the number of sensors that can be supported. The first experimental demonstration of this system is reported including results which show the potential for multiplexing and interrogating up to 4096 sensors using a single telemetry fibre pair with good system performance. The number can be increased to 8192 by using dual pump sources

A 300-800MHz Tunable Filter and Linearized LNA applied in a Low-Noise Harmonic-Rejection RF-Sampling Receiver

A multiband flexible RF-sampling receiver aimed at software-defined radio is presented. The wideband RF sampling function is enabled by a recently proposed discrete-time mixing downconverter. This work exploits a voltage-sensing LNA preceded by a tunable LC pre-filter with one external coil to demonstrate an RF-sampling receiver with low noise figure (NF) and high harmonic rejection (HR). The second-order LC filter provides voltage pre-gain and attenuates the source noise aliasing, and it also improves the HR ratio of the sampling downconverter. The LNA consists of a simple amplifier topology built from inverters and resistors to improve the third-order nonlinearity via an enhanced voltage mirror technique. The RF-sampling receiver employs 8 times oversampling covering 300 to 800 MHz in two RF sub-bands. The chip is realized in 65 nm CMOS and the measured gain across the band is between 22 and 28 dB, while achieving a NF between 0.8 to 4.3 dB. The IIP2 varies between +38 and +49 dBm and the IIP3 between -14 dBm and -9 dBm, and the third and fifth order HR ratios are more than 60 dB. The LNA and downconverter consumes 6 mW, and the clock generator takes 12 mW at 800 MHz RF.\ud \u

The On The Fly Imaging Technique

The On-The-Fly (OTF) imaging technique enables single-dish radio telescopes to construct images of small areas of the sky with greater efficiency and accuracy. This paper describes the practical application of the OTF imaging technique. By way of example the implementation of the OTF imaging technique at the NRAO 12 Meter Telescope is described. Specific requirements for data sampling, image formation, and Doppler correction are discussed.Comment: 10 pages, 13 figures, accepted A&

Continuous Cold-atom Inertial Sensor with 1 nrad.s−11\ \text{nrad.s}^{-1} Rotation Stability

We report the operation of a cold-atom inertial sensor which continuously captures the rotation signal. Using a joint interrogation scheme, where we simultaneously prepare a cold-atom source and operate an atom interferometer (AI) enables us to eliminate the dead times. We show that such continuous operation improves the short-term sensitivity of AIs, and demonstrate a rotation sensitivity of $100\ \text{nrad.s}^{-1}.\text{Hz}^{-1/2}$ in a cold-atom gyroscope of $11 \ \text{cm}^2$ Sagnac area. We also demonstrate a rotation stability of $1 \ \text{nrad.s}^{-1}$ at $10^4$ s of integration time, which establishes the record for atomic gyroscopes. The continuous operation of cold-atom inertial sensors will enable to benefit from the full sensitivity potential of large area AIs, determined by the quantum noise limit.Comment: 4 pages, 3 figure

Metrology with Atom Interferometry: Inertial Sensors from Laboratory to Field Applications

Developments in atom interferometry have led to atomic inertial sensors with extremely high sensitivity. Their performances are for the moment limited by the ground vibrations, the impact of which is exacerbated by the sequential operation, resulting in aliasing and dead time. We discuss several experiments performed at LNE-SYRTE in order to reduce these problems and achieve the intrinsic limit of atomic inertial sensors. These techniques have resulted in transportable and high-performance instruments that participate in gravity measurements, and pave the way to applications in inertial navigation.Comment: 7 pages, 5 figure

Application of Fractal Dimension for Quantifying Noise Texture in Computed Tomography Images

Purpose Evaluation of noise texture information in CT images is important for assessing image quality. Noise texture is often quantified by the noise power spectrum (NPS), which requires numerous image realizations to estimate. This study evaluated fractal dimension for quantifying noise texture as a scalar metric that can potentially be estimated using one image realization. Methods The American College of Radiology CT accreditation phantom (ACR) was scanned on a clinical scanner (Discovery CT750, GE Healthcare) at 120 kV and 25 and 90 mAs. Images were reconstructed using filtered back projection (FBP/ASIR 0%) with varying reconstruction kernels: Soft, Standard, Detail, Chest, Lung, Bone, and Edge. For each kernel, images were also reconstructed using ASIR 50% and ASIR 100% iterative reconstruction (IR) methods. Fractal dimension was estimated using the differential box‐counting algorithm applied to images of the uniform section of ACR phantom. The two‐dimensional Noise Power Spectrum (NPS) and one‐dimensional‐radially averaged NPS were estimated using established techniques. By changing the radiation dose, the effect of noise magnitude on fractal dimension was evaluated. The Spearman correlation between the fractal dimension and the frequency of the NPS peak was calculated. The number of images required to reliably estimate fractal dimension was determined and compared to the number of images required to estimate the NPS‐peak frequency. The effect of Region of Interest (ROI) size on fractal dimension estimation was evaluated. Feasibility of estimating fractal dimension in an anthropomorphic phantom and clinical image was also investigated, with the resulting fractal dimension compared to that estimated within the uniform section of the ACR phantom. Results Fractal dimension was strongly correlated with the frequency of the peak of the radially averaged NPS curve, having a Spearman rank‐order coefficient of 0.98 (P‐value \u3c 0.01) for ASIR 0%. The mean fractal dimension at ASIR 0% was 2.49 (Soft), 2.51 (Standard), 2.52 (Detail), 2.57 (Chest), 2.61 (Lung), 2.66 (Bone), and 2.7 (Edge). A reduction in fractal dimension was observed with increasing ASIR levels for all investigated reconstruction kernels. Fractal dimension was found to be independent of noise magnitude. Fractal dimension was successfully estimated from four ROIs of size 64 × 64 pixels or one ROI of 128 × 128 pixels. Fractal dimension was found to be sensitive to non‐noise structures in the image, such as ring artifacts and anatomical structure. Fractal dimension estimated within a uniform region of an anthropomorphic phantom and clinical head image matched that estimated within the ACR phantom for filtered back projection reconstruction. Conclusions Fractal dimension correlated with the NPS‐peak frequency and was independent of noise magnitude, suggesting that the scalar metric of fractal dimension can be used to quantify the change in noise texture across reconstruction approaches. Results demonstrated that fractal dimension can be estimated from four, 64 × 64‐pixel ROIs or one 128 × 128 ROI within a head CT image, which may make it amenable for quantifying noise texture within clinical images