A Birkhoff connection between quantum circuits and linear classical reversible circuits

Birkhoff's theorem tells how any doubly stochastic matrix can be decomposed as a weighted sum of permutation matrices. Similar theorems on unitary matrices reveal a connection between quantum circuits and linear classical reversible circuits. It triggers the question whether a quantum computer can be regarded as a superposition of classical reversible computers

Local times of Bernoulli walk

Economics

Environmental monitoring in heterogeneous soil-landscapes; A Dutch case study

The spatial heterogeneity of agricultural soil-landscapes is mostly not taken into account in environmental policies. Most environmental goals have been defined at national level or farm level but not at the landscape level. The potential for setting up a regional environmental monitoring network that supports self governance was explored. The research was performed in the Northern Friesian Woodland

The phenomenology of electric dipole moments in models of scalar leptoquarks

We study the phenomenology of electric dipole moments (EDMs) induced in various scalar leptoquark models. We consider generic leptoquark couplings to quarks and leptons and match to Standard Model effective field theory. After evolving the resulting operators to low energies, we connect to EDM experiments by using up-to-date hadronic, nuclear, and atomic matrix elements. We show that current experimental limits set strong constraints on the possible CP-violating phases in leptoquark models. Depending on the quarks and leptons involved in the interaction, the existing searches for EDMs of leptons, nucleons, atoms, and molecules all play a role in constraining the CP-violating couplings. We discuss the impact of hadronic and nuclear uncertainties as well as the sensitivities that can be achieved with future EDM experiments. Finally, we study the impact of EDM constraints on a specific leptoquark model that can explain the recent $B$-physics anomalies.Comment: Published versio

DYNAMIC ELUTRIATION MEASUREMENT IN A CONTINUOUSLY OPERATED BUBBLING FLUIDIZED BED

Measurements were performed using a novel thermal mass flow meter. The dynamic behaviour of the total elutriation rate was monitored from start-up until a steady rate was achieved. It was found that the elutriation rate at unsteady conditions can be as much as 5 times that of the steady value and that it can take more than an hour to reach steady state. This is attributed to the dynamic changes of the fines distribution between the fluidized bed and dipleg. It was further shown that a steady dipleg height does not indicate steady elutriation rates. Using the flow meter to confirm steady state measurements, elutriation constants were determined for the glass bead - air system at different superficial velocities

Automatic Segmentation of the Left Ventricle in Cardiac CT Angiography Using Convolutional Neural Network

Accurate delineation of the left ventricle (LV) is an important step in evaluation of cardiac function. In this paper, we present an automatic method for segmentation of the LV in cardiac CT angiography (CCTA) scans. Segmentation is performed in two stages. First, a bounding box around the LV is detected using a combination of three convolutional neural networks (CNNs). Subsequently, to obtain the segmentation of the LV, voxel classification is performed within the defined bounding box using a CNN. The study included CCTA scans of sixty patients, fifty scans were used to train the CNNs for the LV localization, five scans were used to train LV segmentation and the remaining five scans were used for testing the method. Automatic segmentation resulted in the average Dice coefficient of 0.85 and mean absolute surface distance of 1.1 mm. The results demonstrate that automatic segmentation of the LV in CCTA scans using voxel classification with convolutional neural networks is feasible.Comment: This work has been published as: Zreik, M., Leiner, T., de Vos, B. D., van Hamersvelt, R. W., Viergever, M. A., I\v{s}gum, I. (2016, April). Automatic segmentation of the left ventricle in cardiac CT angiography using convolutional neural networks. In Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on (pp. 40-43). IEE