76 research outputs found
Quantum walks: a comprehensive review
Quantum walks, the quantum mechanical counterpart of classical random walks,
is an advanced tool for building quantum algorithms that has been recently
shown to constitute a universal model of quantum computation. Quantum walks is
now a solid field of research of quantum computation full of exciting open
problems for physicists, computer scientists, mathematicians and engineers.
In this paper we review theoretical advances on the foundations of both
discrete- and continuous-time quantum walks, together with the role that
randomness plays in quantum walks, the connections between the mathematical
models of coined discrete quantum walks and continuous quantum walks, the
quantumness of quantum walks, a summary of papers published on discrete quantum
walks and entanglement as well as a succinct review of experimental proposals
and realizations of discrete-time quantum walks. Furthermore, we have reviewed
several algorithms based on both discrete- and continuous-time quantum walks as
well as a most important result: the computational universality of both
continuous- and discrete- time quantum walks.Comment: Paper accepted for publication in Quantum Information Processing
Journa
Principles of Bioimage Informatics: Focus on Machine Learning of Cell Patterns
Abstract. The field of bioimage informatics concerns the development and use of methods for computational analysis of biological images. Traditionally, analysis of such images has been done manually. Manual annotation is, however, slow, expensive, and often highly variable from one expert to another. Furthermore, with modern automated microscopes, hundreds to thousands of images can be collected per hour, making manual analysis infeasible. This field borrows from the pattern recognition and computer vision literature (which contain many techniques for image processing and recognition), but has its own unique challenges and tradeoffs. Fluorescence microscopy images represent perhaps the largest class of biological images for which automation is needed. For this modality, typical problems include cell segmentation, classification of phenotypical response, or decisions regarding differentiated responses (treatment vs. control setting). This overview focuses on the problem of subcellular location determination as a running example, but the techniques discussed are often applicable to other problems.
Roadmap on dynamics of molecules and clusters in the gas phase
status: publishe
Near-ground Effect of Height on Pollen Exposure
The effect of height on pollen concentration is not well documented and little is known about the near-ground
vertical profile of airborne pollen. This is important as most measuring stations are on roofs, but patient
exposure is at ground level. Our study used a big data approach to estimate the near-ground vertical profile
of pollen concentrations based on a global study of paired stations located at different heights. We
analyzed paired sampling stations located at different heights between 1.5 and 50m above ground level (AGL). This provided pollen data from 59 Hirst-type volumetric traps
from 25 different areas, mainly in Europe, but also covering North America and Australia, resulting in about
2,000,000 daily pollen concentrations analyzed. The daily ratio of the amounts of pollen from different heights
per location was used, and the values of the lower station were divided by the higher station. The lower station
of paired traps recorded more pollen than the higher trap. However, while the effect of height on pollen concentration
was clear, it was also limited (average ratio 1.3, range 0.7–2.2). The standard deviation of the pollen
ratio was highly variable when the lower station was located close to the ground level (below 10m AGL). We
show that pollen concentrations measured at >10m are representative for background near-ground levels
- …