Statistical Constraints on State Preparation for a Quantum Computer

Quantum computing algorithms require that the quantum register be initially present in a superposition state. To achieve this, we consider the practical problem of creating a coherent superposition state of several qubits. Owing to considerations of quantum statistics, this requires that the entropy of the system go down. This, in turn, has two practical implications: (i) the initial state cannot be controlled; (ii) the temperature of the system must be reduced. These factors, in addition to decoherence and sensitivity to errors, must be considered in the implementation of quantum computers.Comment: 7 pages; the final published versio

Three-dimensional phase retrieval in propagation-based phase-contrast imaging

We present a solution to the phase problem in near-field x-ray (propagation) imaging. The three-dimensionalcomplex-valued index of refraction is reconstructed from a set of projections recorded in the near-field (Fresnel)setting at a single detector distance. The solution is found by an iterative algorithm based only on the measureddata and the three-dimensional tomographic (Helgason-Ludwig) consistency constraint without the need forfurther a priori knowledge or other restrictive assumptions

A Multi-Channel DART algorithm

Tomography deals with the reconstruction of objects from their projections, acquired along a range of angles. Discrete tomography is concerned with objects that consist of a small number of materials, which makes it possible to compute accurate reconstructions from highly limited projection data. For cases where the allowed intensity values in the reconstruction are known a priori, the discrete algebraic reconstruction technique (DART) has shown to yield accurate reconstructions from few projections. However, a key limitation is that the benefit of DART diminishes as the number of different materials increases. Many tomographic imaging techniques can simultaneously record tomographic data at multiple channels, each corresponding to a different weighting of the materials in the object. Whenever projection data from more than one channel is available, this additional information can potentially be exploited by the reconstruction algorithm. In this paper we present Multi-Channel DART (MC-DART), which deals effectively with multi-channel data. This class of algorithms is a generalization of DART to multiple channels and combines the information for each separate channel-reconstruction in a multi-channel segmentation step. We demonstrate that in a range of simulation experiments, MC-DART is capable of producing more accurate reconstructions compared to single-channel DART

Atomic super-resolution tomography

We consider the problem of reconstructing a nanocrystal at atomic resolution from electron microscopy images taken at a few tilt angles. A popular reconstruction approach called discrete tomography confines the atom locations to a coarse spatial grid, which is inspired by the physical a priori knowledge that atoms in a crystalline solid tend to form regular lattices. Although this constraint has proven to be powerful for solving this very under-determined inverse problem in many cases, its key limitation is that, in practice, defects may occur that cause atoms to deviate from regular lattice positions. Here we propose a grid-free discrete tomography algorithm that allows for continuous deviations of the atom locations similar to super-resolution approaches for microscopy. The new formulation allows us to define atomic interaction potentials explicitly, which results in a both meaningful and powerful incorporation of the available physical a priori knowledge about the crystal's properties. In computational experiments, we compare the proposed grid-free method to established grid-based approaches and show that our approach can indeed recover the atom positions more accurately for common lattice defects

Experimental observation and analysis of inverse transients for pipeline leak detection

Fluid transients result in a substantial amount of data as pressure waves propagate throughout pipes. A new generation of leak detection and pipe roughness calibration techniques has arisen to exploit those data. Using the interactions of transient waves with leaks, the detection, location, and quantification of leakage using a combination of transient analysis and inverse mathematics is possible using inverse transient analysis (ITA). This paper presents further development of ITA and experimental observations for leak detection in a laboratory pipeline. The effects of data and model error on ITA results have been explored including strategies to minimize their effects using model error compensation techniques and ITA implementation approaches. The shape of the transient is important for successful application of ITA. A rapid input transient (which may be of small magnitude) contains maximum system response information, thus improving the uniqueness and quality of the ITA solution. The effect of using head measurements as boundary conditions for ITA has been shown to significantly reduce sensitivity, making both detection and quantification problematic. Model parsimony is used to limit the number of unknown leak candidates in ITA, thus reducing the minimization problem complexity. Experimental observations in a laboratory pipeline confirm the analysis and illustrate successful detection and quantification of both single and multiple leaks. © 2007 ASCE.John P. Vítkovský, Martin F. Lambert, Angus R. Simpson, and James A. Ligget

Detecting small low emission radiating sources

The article addresses the possibility of robust detection of geometrically small, low emission sources on a significantly stronger background. This problem is important for homeland security. A technique of detecting such sources using Compton type cameras is developed, which is shown on numerical examples to have high sensitivity and specificity and also allows to assign confidence probabilities of the detection. 2D case is considered in detail

Application of X-ray micro-computed tomography on high-speed cavitating diesel fuel flows

The flow inside a purpose built enlarged single-orifice nozzle replica is quantified using time-averaged X-ray micro-computed tomography (micro-CT) and high-speed shadowgraphy. Results have been obtained at Reynolds and cavitation numbers similar to those of real-size injectors. Good agreement for the cavitation extent inside the orifice is found between the micro-CT and the corresponding temporal mean 2D cavitation image, as captured by the high-speed camera. However, the internal 3D structure of the developing cavitation cloud reveals a hollow vapour cloud ring formed at the hole entrance and extending only at the lower part of the hole due to the asymmetric flow entry. Moreover, the cavitation volume fraction exhibits a significant gradient along the orifice volume. The cavitation number and the needle valve lift seem to be the most influential operating parameters, while the Reynolds number seems to have only small effect for the range of values tested. Overall, the study demonstrates that use of micro-CT can be a reliable tool for cavitation in nozzle orifices operating under nominal steady-state conditions

Leadership, action, learning and accountability to deliver quality care for women, newborns and children

Recognizing the need for action, the national governments of Bangladesh, Côte d’Ivoire, Ethiopia, Ghana, India, Malawi, Nigeria, Uganda and United Republic of Tanzania, together with WHO, the United Nations Children’s Fund (UNICEF), the United Nations Population Fund (UNFPA), implementation partners and other stakeholders, have established the Network for Improving Quality of Care for Maternal Newborn and Child Health care.10 The network has agreed to pursue the ambitious goals of halving maternal and newborn deaths and stillbirths and improving experience of care in participating health facilities within five years of implementation. Under the leadership of the participating countries’ health ministries, the network will support the implementation of national frameworks for quality improvement by pursuing four strategic objectives: (i) leadership by building and strengthening national institutions and processes for improving quality of care; (ii) action by accelerating and sustaining implementation of quality-of-care improvement packages through operationalizing a standards-based approach to quality improvement; (iii) learning by promoting joint learning and generating evidence on quality planning, improvement and control of health services; and (iv) accountability by developing, strengthening and sustaining institutions and mechanisms for accountability of quality maternal, neonatal and child health services that are equitable and dignified

Genomic Diversity and Introgression in O. sativa Reveal the Impact of Domestication and Breeding on the Rice Genome

The domestication of Asian rice (Oryza sativa) was a complex process punctuated by episodes of introgressive hybridization among and between subpopulations. Deep genetic divergence between the two main varietal groups (Indica and Japonica) suggests domestication from at least two distinct wild populations. However, genetic uniformity surrounding key domestication genes across divergent subpopulations suggests cultural exchange of genetic material among ancient farmers.In this study, we utilize a novel 1,536 SNP panel genotyped across 395 diverse accessions of O. sativa to study genome-wide patterns of polymorphism, to characterize population structure, and to infer the introgression history of domesticated Asian rice. Our population structure analyses support the existence of five major subpopulations (indica, aus, tropical japonica, temperate japonica and GroupV) consistent with previous analyses. Our introgression analysis shows that most accessions exhibit some degree of admixture, with many individuals within a population sharing the same introgressed segment due to artificial selection. Admixture mapping and association analysis of amylose content and grain length illustrate the potential for dissecting the genetic basis of complex traits in domesticated plant populations.Genes in these regions control a myriad of traits including plant stature, blast resistance, and amylose content. These analyses highlight the power of population genomics in agricultural systems to identify functionally important regions of the genome and to decipher the role of human-directed breeding in refashioning the genomes of a domesticated species