Joint measurement of multiple noncommuting parameters

Although quantum metrology allows us to make precision measurements beyond the standard quantum limit, it mostly works on the measurement of only one observable due to the Heisenberg uncertainty relation on the measurement precision of noncommuting observables for one system. In this paper, we study the schemes of joint measurement of multiple observables which do not commute with each other using the quantum entanglement between two systems. We focus on analyzing the performance of a SU(1,1) nonlinear interferometer on fulfilling the task of joint measurement. The results show that the information encoded in multiple noncommuting observables on an optical field can be simultaneously measured with a signal-to-noise ratio higher than the standard quantum limit, and the ultimate limit of each observable is still the Heisenberg limit. Moreover, we find a resource conservation rule for the joint measurement

Aspects of the Hydrocarbon Potential of the Coals and Associated Shales and Mudstones of the Mamu Formation in Anambra Basin, Nigeria

Coals and associated shales and mudstones of the Mamu Formation in Anambra basin were examined for their hydrocarbon potentials by subjecting them to total organic carbon (TOC) and Rock-eval Pyrolysis analyses. The TOC results range from 45.56 to 67.68 wt. %, 0.07 to 5.65 wt. % and 0.12 to 4.46 wt. % for the coals, shales and mudstones respectively, suggesting that the sediments contain appreciably high quantity of organic matter that can generate hydrocarbon. Ranges of Hydrogen Index (HI) and Genetic Potential (GP) for the coals, shales and mudstones are 167 to 327 mg/g and 114.99 to 159.54 mg/g, 50 to 288 mg/g and 2.85 to 15.66 mg/g TOC, 41 to 239 mg/g and 0.54 to 10.96 mg/g respectively. Tmax and Calculated vitrinite reflectance (% Ro) of sediments range from 412 to 432 oC and 0.26 to 0.62 respectively. The Rock-eval data suggested poor to very good source rocks in the sediments, with the shales as good source rocks, the mudstones as poor to good source rocks and the coals as very good source rocks. The predominant organic matter types in the sediments are kerogen type II/III and type III which are oil and gas prone. The coals are dominated by kerogen type II/III while the shales and mudstones are dominated by kerogen type III. Thermal maturity from Rock-eval data indicated that the sediments are immature with respect to hydrocarbon generation and generally at low level conversion. The coals and the associated shales and mudstones of Mamu Formation are therefore capable of generating oil and gas at appropriate maturity. Keywords: Mamu Formation, Coals, Shales, Mudstones, Hydrocarbon generation, Kerogen, Thermal maturit

Max-margin Multiple-Instance Learning via Semidefinite Programming

In this paper, we present a novel semidefinite programming approach for multiple-instance learning. We first formulate the multiple-instance learning as a combinatorial maximum margin optimization problem with additional instance selection constraints within the framework of support vector machines. Although solving this primal problem requires non-convex programming, we nevertheless can then derive an equivalent dual formulation that can be relaxed into a novel convex semidefinite programming (SDP). The relaxed SDP has free parameters where T is the number of instances, and can be solved using a standard interior-point method. Empirical study shows promising performance of the proposed SDP in comparison with the support vector machine approaches with heuristic optimization procedures

Quantum information tapping using a fiber optical parametric amplifier with noise figure improved by correlated inputs

One of the important function in optical communication system is the distribution of information encoded in an optical beam. It is not a problem to accomplish this in a classical system since classical information can be copied at will. However, challenges arise in quantum system because extra quantum noise is often added when the information content of a quantum state is distributed to various users. Here, we experimentally demonstrate a quantum information tap by using a fiber optical parametric amplifier (FOPA) with correlated inputs, whose noise is reduced by the destructive quantum interference through quantum entanglement between the signal and the idler input fields. By measuring the noise figure of the FOPA and comparing with a regular FOPA, we observe an improvement of 0.7+-0.1 dB and 0.84+-0.09 dB from the signal and idler outputs, respectively. When the low noise FOPA functions as an information splitter, the device has a total information transfer coefficient of Ts+Ti=1.47+-0.2, which is greater than the classical limit of 1. Moreover, this fiber based device works at the 1550 nm telecom band, so it is compatible with the current fiber-optical network.Comment: 28 pages, 6 figure

Quantum enhanced joint measurement of two conjugate observables with an SU(1, 1) interferometer

We jointly measure the phase and amplitude modulation of an optical field with the newly developed SU(1,1) interferometer. We simultaneously achieve a signal-to-noise ratio improvement of 1.1 and 1 dB over the standard quantum limit in amplitude and phase measurement

Approaching single temporal mode operation in twin beams generated by pulse pumped high gain spontaneous four wave mixing

By investigating the intensity correlation function, we study the spectral/temporal mode properties of twin beams generated by the pulse-pumped high gain spontaneous four wave mixing (SFWM) in optical fiber from both the theoretical and experimental aspects. The results show that the temporal property depends not only on the phase matching condition and the filters applied in the signal and idler fields, but also on the gain of SFWM. When the gain of SFWM is low, the spectral/temporal mode properties of the twin beams are determined by the phase matching condition and optical filtering and are usually of multi-mode nature, which leads to a value larger than 1 but distinctly smaller than 2 for the normalized intensity correlation function of individual signal/idler beam. However, when the gain of SFWM is very high, we demonstrate the normalized intensity correlation function of individual signal/idler beam approaches to 2, which is a signature of single temporal mode. This is so even if the frequencies of signal and idler fields are highly correlated so that the twin beams have multiple modes in low gain regime. We find that the reason for this behavior is the dominance of the fundamental mode over other higher order modes at high gain. Our investigation is useful for constructing high quality multi-mode squeezed and entangled states by using pulse-pumped spontaneous parametric down-conversion and SFWM

Versatile and precise quantum state engineering by using nonlinear interferometers

The availability of photon states with well-defined temporal modes is crucial for photonic quantum technologies. Ever since the inception of generating photonic quantum states through pulse pumped spontaneous parametric processes, many exquisite efforts have been put on improving the modal purity of the photon states to achieve single-mode operation. However, because the nonlinear interaction and linear dispersion are often mixed in parametric processes, limited successes have been achieved so far only at some specific wavelengths with sophisticated design. In this paper, we resort to a different approach by exploiting an active filtering mechanism originated from interference fringe of nonlinear interferometer. The nonlinear interferometer is realized in a sequential array of nonlinear medium, with a gap in between made of a linear dispersive medium, in which the precise modal control is realized without influencing the phase matching of the parametric process. As a proof-of-principle demonstration of the capability, we present a photon pairs source using a two-stage nonlinear interferometer formed by two identical nonlinear fibers with a standard single mode fiber in between. The results show that spectrally correlated two-photon state via four wave mixing in a single piece nonlinear fiber is modified into factorable state and heralded single-photons with high modal purity and high heralding efficiency are achievable. This novel quantum interferometric method, which can improve the quality of the photon states in almost all the aspects such as modal purity, heralding efficiency, and flexibility in wavelength selection, is proved to be effective and easy to realize

Multi-label classification with output kernels

Although multi-label classification has become an increasingly important problem in machine learning, current approaches remain restricted to learning in the original label space (or in a simple linear projection of the original label space). Instead, we propose to use kernels on output label vectors to significantly expand the forms of label dependence that can be captured. The main challenge is to reformulate standard multi-label losses to handle kernels between output vectors. We first demonstrate how a state-of-the-art large margin loss for multi-label classification can be reformulated, exactly, to handle output kernels as well as input kernels. Importantly, the pre-image problem for multi-label classification can be easily solved at test time, while the training procedure can still be simply expressed as a quadratic program in a dual parameter space. We then develop a projected gradient descent training procedure for this new formulation. Our empirical results demonstrate the efficacy of the proposed approach on complex image labeling tasks

Multi-level adaptive active learning for scene classification

Semantic scene classification is a challenging problem in computer vision. In this paper, we present a novel multi-level active learning approach to reduce the human annotation effort for training robust scene classification models. Different from most existing active learning methods that can only query labels for selected instances at the target categorization level, i.e., the scene class level, our approach establishes a semantic framework that predicts scene labels based on a latent object-based semantic representation of images, and is capable to query labels at two different levels, the target scene class level (abstractive high level) and the latent object class level (semantic middle level). Specifically, we develop an adaptive active learning strategy to perform multi-level label query, which maintains the default label query at the target scene class level, but switches to the latent object class level whenever an "unexpected" target class label is returned by the labeler. We conduct experiments on two standard scene classification datasets to investigate the efficacy of the proposed approach. Our empirical results show the proposed adaptive multi-level active learning approach can outperform both baseline active learning methods and a state-of-the-art multi-level active learning method

Interrupted visual searches reveal volatile search memory.

This study investigated memory from interrupted visual searches. Participants conducted a change detection search task on polygons overlaid on scenes. Search was interrupted by various disruptions, including unfilled delay, passive viewing of other scenes, and additional search on new displays. Results showed that performance was unaffected by short intervals of unfilled delay or passive viewing, but it was impaired by additional search tasks. Across delays, memory for the spatial layout of the polygons was retained for future use, but memory for polygon shapes, background scene, and absolute polygon locations was not. The authors suggest that spatial memory aids interrupted visual searches, but the use of this memory is easily disrupted by additional searches