Topics in Quantum Computers

I provide an introduction to quantum computers, describing how they might be realized using language accessible to a solid state physicist. A listing of the minimal requirements for creating a quantum computer is given. I also discuss several recent developments in the area of quantum error correction, a subject of importance not only to quantum computation, but also to some aspects of the foundations of quantum theory.Comment: 22 pages, Latex, 1 eps figure, Paper to be published in "Mesoscopic Electron Transport", edited by L. Kowenhoven, G. Schoen and L. Sohn, NATO ASI Series E, Kluwer Ac. Publ., Dordrecht. v2: typos in refrences fixe

Spectral plots and the representation and interpretation of biological data

It is basic question in biology and other fields to identify the char- acteristic properties that on one hand are shared by structures from a particular realm, like gene regulation, protein-protein interaction or neu- ral networks or foodwebs, and that on the other hand distinguish them from other structures. We introduce and apply a general method, based on the spectrum of the normalized graph Laplacian, that yields repre- sentations, the spectral plots, that allow us to find and visualize such properties systematically. We present such visualizations for a wide range of biological networks and compare them with those for networks derived from theoretical schemes. The differences that we find are quite striking and suggest that the search for universal properties of biological networks should be complemented by an understanding of more specific features of biological organization principles at different scales.Comment: 15 pages, 7 figure

A measure of individual role in collective dynamics

Identifying key players in collective dynamics remains a challenge in several research fields, from the efficient dissemination of ideas to drug target discovery in biomedical problems. The difficulty lies at several levels: how to single out the role of individual elements in such intermingled systems, or which is the best way to quantify their importance. Centrality measures describe a node's importance by its position in a network. The key issue obviated is that the contribution of a node to the collective behavior is not uniquely determined by the structure of the system but it is a result of the interplay between dynamics and network structure. We show that dynamical influence measures explicitly how strongly a node's dynamical state affects collective behavior. For critical spreading, dynamical influence targets nodes according to their spreading capabilities. For diffusive processes it quantifies how efficiently real systems may be controlled by manipulating a single node.Comment: accepted for publication in Scientific Report

Effect of correlations on network controllability

A dynamical system is controllable if by imposing appropriate external signals on a subset of its nodes, it can be driven from any initial state to any desired state in finite time. Here we study the impact of various network characteristics on the minimal number of driver nodes required to control a network. We find that clustering and modularity have no discernible impact, but the symmetries of the underlying matching problem can produce linear, quadratic or no dependence on degree correlation coefficients, depending on the nature of the underlying correlations. The results are supported by numerical simulations and help narrow the observed gap between the predicted and the observed number of driver nodes in real networks

Pulmonary function and diffusion capacity are associated with pulmonary arterial systolic pressure in the general population : the Rotterdam study

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Consensus clustering in complex networks

The community structure of complex networks reveals both their organization and hidden relationships among their constituents. Most community detection methods currently available are not deterministic, and their results typically depend on the specific random seeds, initial conditions and tie-break rules adopted for their execution. Consensus clustering is used in data analysis to generate stable results out of a set of partitions delivered by stochastic methods. Here we show that consensus clustering can be combined with any existing method in a self-consistent way, enhancing considerably both the stability and the accuracy of the resulting partitions. This framework is also particularly suitable to monitor the evolution of community structure in temporal networks. An application of consensus clustering to a large citation network of physics papers demonstrates its capability to keep track of the birth, death and diversification of topics.Comment: 11 pages, 12 figures. Published in Scientific Report

Health-related quality of life in Huntington’s Disease patients: a comparison of proxy assessment and patient self-rating using the disease-specific Huntington’s Disease health-related quality of life questionnaire (HDQoL)

Huntington’s disease (HD) is a fatal, neurodegenerative disease for which there is no known cure. Proxy evaluation is relevant for HD as its manifestation might limit the ability of persons to report their health-related quality of life (HrQoL). This study explored patient–proxy ratings of HrQoL of persons at different stages of HD, and examined factors that may affect proxy ratings. A total of 105 patient–proxy pairs completed the Huntington’s disease health-related quality of life questionnaire (HDQoL) and other established HrQoL measures (EQ-5D and SF-12v2). Proxy–patient agreement was assessed in terms of absolute level (mean ratings) and intraclass correlation. Proxies’ ratings were at a similar level to patients’ self-ratings on an overall Summary Score and on most of the six Specific Scales of the HDQoL. On the Specific Hopes and Worries Scale, proxies on average rated HrQoL as better than patients’ self-ratings, while on both the Specific Cognitive Scale and Specific Physical and Functional Scale proxies tended to rate HrQoL more poorly than patients themselves. The patient’s disease stage and mental wellbeing (SF-12 Mental Component scale) were the two factors that primarily affected proxy assessment. Proxy scores were strongly correlated with patients’ self-ratings of HrQoL, on the Summary Scale and all Specific Scales. The patient–proxy correlation was lower for patients at moderate stages of HD compared to patients at early and advanced stages. The proxy report version of the HDQoL is a useful complementary tool to self-assessment, and a promising alternative when individual patients with advanced HD are unable to self-report

Prevalence of pulmonary hypertension in the general population : the Rotterdam study

Background: Pulmonary hypertension is characterized by increased pulmonary artery pressure and carries an increased mortality. Population-based studies into pulmonary hypertension are scarce and little is known about its prevalence in the general population. We aimed to describe the distribution of echocardiographically-assessed pulmonary artery systolic pressure (ePASP) in the general population, to estimate the prevalence of pulmonary hypertension, and to identify associated factors. Methods: Participants (n = 3381, mean age 76.4 years, 59% women) from the Rotterdam Study, a population-based cohort, underwent echocardiography. Echocardiographic pulmonary hypertension was defined as ePASP>40 mmHg. Results: Mean ePASP was 26.3 mmHg (SD 7.0). Prevalence of echocardiographic pulmonary hypertension was 2.6% (95%CI: 2.0; 3.2). Prevalence was higher in older participants compared to younger ones (8.3% in those over 85 years versus 0.8% in those between 65 and 70), and in those with underlying disorders versus those without (5.9% in subjects with COPD versus 2.3%; 9.2% in those with left ventricular systolic dysfunction versus 2.3%; 23.1% in stages 3 or 4 left ventricular diastolic dysfunction versus 1.9% in normal or stage 1). Factors independently associated with higher ePASP were older age, higher BMI, left ventricular diastolic dysfunction, COPD and systemic hypertension. Conclusion: In this large population-based study, we show that pulmonary hypertension as measured by echocardiography has a low prevalence in the overall general population in the Netherlands, but estimates may be higher in specific subgroups, especially in those with underlying diseases. Increased pulmonary arterial pressure is likely to gain importance in the near future due to population aging and the accompanying prevalences of underlying disorders

Artificial Neural Network Inference (ANNI): A Study on Gene-Gene Interaction for Biomarkers in Childhood Sarcomas

Objective: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI). Method: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs) dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model. Results: Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS); FCGRT and OLFM1 in Ewing’s sarcoma (EWS)) suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen. Conclusions: The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas