BICEP2 II: Experiment and Three-Year Data Set

We report on the design and performance of the BICEP2 instrument and on its three-year data set. BICEP2 was designed to measure the polarization of the cosmic microwave background (CMB) on angular scales of 1 to 5 degrees ($\ell$=40-200), near the expected peak of the B-mode polarization signature of primordial gravitational waves from cosmic inflation. Measuring B-modes requires dramatic improvements in sensitivity combined with exquisite control of systematics. The BICEP2 telescope observed from the South Pole with a 26~cm aperture and cold, on-axis, refractive optics. BICEP2 also adopted a new detector design in which beam-defining slot antenna arrays couple to transition-edge sensor (TES) bolometers, all fabricated on a common substrate. The antenna-coupled TES detectors supported scalable fabrication and multiplexed readout that allowed BICEP2 to achieve a high detector count of 500 bolometers at 150 GHz, giving unprecedented sensitivity to B-modes at degree angular scales. After optimization of detector and readout parameters, BICEP2 achieved an instrument noise-equivalent temperature of 15.8 $\mu$K sqrt(s). The full data set reached Stokes Q and U map depths of 87.2 nK in square-degree pixels (5.2 $\mu$K arcmin) over an effective area of 384 square degrees within a 1000 square degree field. These are the deepest CMB polarization maps at degree angular scales to date. The power spectrum analysis presented in a companion paper has resulted in a significant detection of B-mode polarization at degree scales.Comment: 30 pages, 24 figure

Experimental Bayesian Quantum Phase Estimation on a Silicon Photonic Chip

Quantum phase estimation is a fundamental subroutine in many quantum algorithms, including Shor's factorization algorithm and quantum simulation. However, so far results have cast doubt on its practicability for near-term, non-fault tolerant, quantum devices. Here we report experimental results demonstrating that this intuition need not be true. We implement a recently proposed adaptive Bayesian approach to quantum phase estimation and use it to simulate molecular energies on a Silicon quantum photonic device. The approach is verified to be well suited for pre-threshold quantum processors by investigating its superior robustness to noise and decoherence compared to the iterative phase estimation algorithm. This shows a promising route to unlock the power of quantum phase estimation much sooner than previously believed

Speckle reduction in SAR imagery

Synthetic Aperture Radar (SAR) is a popular tool for airborne and space-borne remote sensing. Inherent to SAR imagery is a type of multiplicative noise known as speckle. There are a number of different approaches which may be taken in order to reduce the amount of speckle noise in SAR imagery. One of the approaches is termed post image formation processing and this is the main concern of this thesis. Background theory relevant to the speckle reduction problem is presented. The physical processes which lead to the formation of speckle are investigated in order to understand the nature of speckle noise. Various statistical properties of speckle noise in different types of SAR images are presented. These include Probability Distribution Functions as well as means and standard deviations. Speckle is considered as a multiplicative noise and a general model is discussed. The last section of this chapter deals with the various approaches to speckle reduction. Chapter three contains a review of the literature pertaining to speckle reduction. Multiple look methods are covered briefly and then the various classes of post image formation processing are reviewed. A number of non-adaptive, adaptive and segmentation-based techniques are reviewed. Other classes of technique which are reviewed include Morphological filtering, Homomorphic processing and Transform domain methods. From this review, insights can be gained as to the advantages and disadvantages of various methods. A number of filtering algorithms which are either promising, or are representative of a class of techniques, are chosen for implementation and analysis

An Atrial Activity Based Algorithm for the Single-Beat Rate-Independent Detection of Atrial Fibrillation

Atrial fibrillation (AF) is the most common cardiac arrhythmia and is the cause of 15% of all ischemic strokes in the United States. In many cases, AF is episodic and/or asymptomatic and as a result, there is a strong need for algorithms capable of quickly and reliably detecting AF, even in cases where the heart rate is controlled through medication or with a pacemaker. Current RR interval (RRI)-based algorithms do not directly target atrial activity, cannot detect AF when the heart rate is controlled, and analyze relatively long intervals of the electrocardiography (ECG) to make an AF determination. This work proposes an algorithm for patient-specific, single-beat, rate-independent AF identification based on atrial activity (AA) analysis. The proposed algorithm develops a statistical model to describe the distribution of features extracted from AA during normal sinus rhythm (NSR). First, ECG segments preceding QRS complexes are identified potential P waves. A total of nine features - three higher order statistics (HOS) features and six features obtained through downsampling - are extracted from the P wave segment under consideration. The Expectation-Maximization algorithm is applied to a training set to create a multivariate Gaussian Mixture Model (GMM) of the feature space. This model is used to identify P wave absence (PWA) and, in turn, AF. An optional post-processing stage which takes a majority vote of successive outputs is applied to improve classifier performance. To evaluate the performance of the classifier, the algorithm was tested on 20 records in the MIT-BIH Atrial Fibrillation Database. Single-beat classification showed a sensitivity(Se) of 91.98%, a specificity(Sp) of 86.18%, a positive predictive value(PPV) of 70.70% and an error rate(Err) of 13.02%. Classification combining seven beats showed a Se of 99.28%, a Sp of 90.21%, a PPV of 80.42% and an Err of 7.12%. The presented algorithm has a classification performance comparable to current RRI-based algorithms yet is rate-independent and capable of making an AF determination in a single beat

A Millimeter-wave Galactic Plane Survey with the BICEP Polarimeter

In order to study inflationary cosmology and the Milky Way Galaxy's composition and magnetic field structure, Stokes I, Q, and U maps of the Galactic plane covering the Galactic longitude range 260° < ℓ < 340° in three atmospheric transmission windows centered on 100, 150, and 220 GHz are presented. The maps sample an optical depth 1 ≾ AV ≾ 30, and are consistent with previous characterizations of the Galactic millimeter-wave frequency spectrum and the large-scale magnetic field structure permeating the interstellar medium. The polarization angles in all three bands are generally perpendicular to those measured by starlight polarimetry as expected and show changes in the structure of the Galactic magnetic field on the scale of 60°. The frequency spectrum of degree-scale Galactic emission is plotted between 23 and 220 GHz (including WMAP data) and is fit to a two-component (synchrotron and dust) model showing that the higher frequency BICEP data are necessary to tightly constrain the amplitude and spectral index of Galactic dust. Polarized emission is detected over the entire region within two degrees of the Galactic plane, indicating the large-scale magnetic field is oriented parallel to the plane of the Galaxy. A trend of decreasing polarization fraction with increasing total intensity is observed, ruling out the simplest model of a constant Galactic magnetic field orientation along the line of sight in the Galactic plane. A generally increasing trend of polarization fraction with electromagnetic frequency is found, varying from 0.5%-1.5% at frequencies below 50 GHz to 2.5%-3.5% above 90 GHz. The effort to extend the capabilities of BICEP by installing 220 GHz band hardware is described along with analysis of the new band

Discrete Wavelet Methods for Interference Mitigation: An Application To Radio Astronomy

The field of wavelets concerns the analysis and alteration of signals at various resolutions. This is achieved through the use of analysis functions which are referred to as wavelets. A wavelet is a signal defined for some brief period of time that contains oscillatory characteristics. Generally, wavelets are intentionally designed to posses particular qualities relevant to a particular signal processing application. This research project makes use of wavelets to mitigate interference, and documents how wavelets are effective in the suppression of Radio Frequency Interference (RFI) in the context of radio astronomy. This study begins with the design of a library of smooth orthogonal wavelets well suited to interference suppression. This is achieved through the use of a multi-parameter optimization applied to a trigonometric parameterization of wavelet filters used for the implementation of the Discrete Wavelet Transform (DWT). This is followed by the design of a simplified wavelet interference suppression system, from which measures of performance and suitability are considered. It is shown that optimal performance metrics for the suppression system are that of Shannon’s entropy, Root Mean Square Error (RMSE) and normality testing using the Lilliefors test. From the application of these heuristics, the optimal thresholding mechanism was found to be the universal adaptive threshold and entropy based measures were found to be optimal for matching wavelets to interference. This in turn resulted in the implementation of the wavelet suppression system, which consisted of a bank of matched filters used to determine which interference source is present in a sampled time domain vector. From this, the astronomy based application was documented and results were obtained. It is shown that the wavelet based interference suppression system outperforms existing flagging techniques. This is achieved by considering measures of the number of sources within a radio-image of the Messier 83 (M83) galaxy and the power of the main source in the image. It is shown that designed system results in an increase of 27% in the number of sources in the recovered radio image and a 1.9% loss of power of the main source