A biological sequence comparison algorithm using quantum computers

Genetic information is encoded in a linear sequence of nucleotides, represented by letters ranging from thousands to billions. Mutations refer to changes in the DNA or RNA nucleotide sequence. Thus, mutation detection is vital in all areas of biology and medicine. Careful monitoring of virulence-enhancing mutations is essential. However, an enormous amount of classical computing power is required to analyze genetic sequences of this size. Inspired by human perception of vision and pixel representation of images on quantum computers, we leverage these techniques to implement a pairwise sequence analysis. The methodology has a potential advantage over classical approaches and can be further applied to identify mutations and other modifications in genetic sequences. We present a method to display and analyze the similarity between two genome sequences on a quantum computer where a similarity score is calculated to determine the similarity between nucleotides.Comment: 14 pages, 8 figures, 3 tables New version: typo in figure 7 New version because of a missing information in affiliations in footer, page

Model-based probabilistic frequent itemset mining

Data uncertainty is inherent in emerging applications such as location-based services, sensor monitoring systems, and data integration. To handle a large amount of imprecise information, uncertain databases have been recently developed. In this paper, we study how to efficiently discover frequent itemsets from large uncertain databases, interpreted under the Possible World Semantics. This is technically challenging, since an uncertain database induces an exponential number of possible worlds. To tackle this problem, we propose a novel methods to capture the itemset mining process as a probability distribution function taking two models into account: the Poisson distribution and the normal distribution. These model-based approaches extract frequent itemsets with a high degree of accuracy and support large databases. We apply our techniques to improve the performance of the algorithms for (1) finding itemsets whose frequentness probabilities are larger than some threshold and (2) mining itemsets with the {Mathematical expression} highest frequentness probabilities. Our approaches support both tuple and attribute uncertainty models, which are commonly used to represent uncertain databases. Extensive evaluation on real and synthetic datasets shows that our methods are highly accurate and four orders of magnitudes faster than previous approaches. In further theoretical and experimental studies, we give an intuition which model-based approach fits best to different types of data sets. © 2012 The Author(s).published_or_final_versio

Uncertain voronoi cell computation based on space decomposition

LNCS v. 9239 entitled: Advances in Spatial and Temporal Databases: 14th International Symposium, SSTD 2015 ... ProceedingsThe problem of computing Voronoi cells for spatial objects whose locations are not certain has been recently studied. In this work, we propose a new approach to compute Voronoi cells for the case of objects having rectangular uncertainty regions. Since exact computation of Voronoi cells is hard, we propose an approximate solution. The main idea of this solution is to apply hierarchical access methods for both data and object space. Our space index is used to efficiently find spatial regions which must (not) be inside a Voronoi cell. Our object index is used to efficiently identify Delauny relations, i.e., data objects which affect the shape of a Voronoi cell. We develop three algorithms to explore index structures and show that the approach that descends both index structures in parallel yields fast query processing times. Our experiments show that we are able to approximate uncertain Voronoi cells much more effectively than the state-of-the-art, and at the same time, improve run-time performance.postprin

Metacognition as Evidence for Evidentialism

Metacognition is the monitoring and controlling of cognitive processes. I examine the role of metacognition in ‘ordinary retrieval cases’, cases in which it is intuitive that via recollection the subject has a justified belief. Drawing on psychological research on metacognition, I argue that evidentialism has a unique, accurate prediction in each ordinary retrieval case: the subject has evidence for the proposition she justifiedly believes. But, I argue, process reliabilism has no unique, accurate predictions in these cases. I conclude that ordinary retrieval cases better support evidentialism than process reliabilism. This conclusion challenges several common assumptions. One is that non-evidentialism alone allows for a naturalized epistemology, i.e., an epistemology that is fully in accordance with scientific research and methodology. Another is that process reliabilism fares much better than evidentialism in the epistemology of memory

Vector Correlators in Lattice QCD: methods and applications

We discuss the calculation of the leading hadronic vacuum polarization in lattice QCD. Exploiting the excellent quality of the compiled experimental data for the e^+e^- --> hadrons cross-section, we predict the outcome of large-volume lattice calculations at the physical pion mass, and design computational strategies for the lattice to have an impact on important phenomenological quantities such as the leading hadronic contribution to (g-2)mu and the running of the electromagnetic coupling constant. First, the R(s) ratio can be calculated directly on the lattice in the threshold region, and we provide the formulae to do so with twisted boundary conditions. Second, the current correlator projected onto zero spatial momentum, in a Euclidean time interval where it can be calculated accurately, provides a potentially critical test of the experimental R(s) ratio in the region that is most relevant for (g-2)mu. This observation can also be turned around: the vector correlator at intermediate distances can be used to determine the lattice spacing in fm, and we make a concrete proposal in this direction. Finally, we quantify the finite-size effects on the current correlator coming from low-energy two-pion states and provide a general parametrization of the vacuum polarization on the torus.Comment: 16 pages, 9 figure files; corrected a factor 2 in Eq. (7) over the published versio

Petrogenesis of diachronous mixed siliciclastic-carbonate megafacies in the cool-water Oligocene Tikorangi Formation, Taranaki Basin, New Zealand

The Oligocene (Whaingaroan-Waitakian) Tikorangi Formation is a totally subsurface, lithostratigraphically complex, mixed siliciclastic-limestone-rich sequence forming an important fracture reservoir within Taranaki Basin, New Zealand. Petrographically the formation comprises a spectrum of interbedded rock types ranging from calcareous mudstone to wackestone to packstone to clean sparry grainstone. Skeletal and textural varieties within these rock types have aided in the identification of three environmentally distinctive megafacies for the Tikorangi Formation rocks-shelfal, foredeep, and basinal. Data from these megafacies have been used to detail previous conclusions on the petrogenesis and to further refine depositional paleoenvironmental models for the Tikorangi Formation in the central eastern Taranaki Basin margin.Shelfal Megafacies 1 rocks (reference well Hu Road-1A) are latest Oligocene (early Waitakian) in age and formed on or proximal to the Patea-Tongaporutu-Herangi basement high. They are characterised by coarse, skeletal-rich, pure sparry grainstone comprising shallow water, high energy taxa (bryozoans, barnacles, red algae) and admixtures of coarse well-rounded lithic sand derived from Mesozoic basement greywacke. This facies type has previously gone unrecorded in the Tikorangi Formation. Megafacies 2 is a latest Oligocene (early Waitakian) foredeep megafacies (formerly named shelfal facies) formed immediately basinward and west of the shelfal basement platform. It accumulated relatively rapidly (>20 cm/ka) from redeposition of shelfal megafacies biota that became intermixed with bathyal taxa to produce a spectrum of typically mudstone through to sparry grainstone. The resulting skeletal mix (bivalve, echinoderm, planktic and benthic foraminiferal, red algal, bryozoan, nannofossil) is unlike that in any of the age-equivalent limestone units in neighbouring onland King Country Basin. Megafacies 3 is an Oligocene (Whaingaroan-Waitakian) offshore basinal megafacies (formerly termed bathyal facies) of planktic foraminiferal-nannofossil-siliciclastic wackestone and mudstone formed away from redepositional influences. The siliciclastic input in this distal basinal setting (sedimentation rates <7 mm/ka) was probably sourced mainly from oceanic currents carrying suspended sediment from South Island provenances exposed at this time.Tikorangi Formation rocks record the Taranaki Basin’s only period of carbonate-dominated sedimentation across a full range of shelfal, foredeep, and basinal settings. Depositional controls on the three contrasting megafacies were fundamentally the interplay of an evolving and complex plate tectonic setting, including development of a carbonate foredeep, changes in relative sea level within an overall transgressive regime, and changing availability, sources, and modes of deposition of both bioclastic and siliciclastic sediments. The mixed siliciclastic-carbonate nature of the formation, and its skeletal assemblages, low-Mg calcite mineralogy, and delayed deep burial diagenetic history, are features consistent with formation in temperate-latitude cool waters

The hadronic vacuum polarization contribution to the muon g − 2 from lattice QCD

We present a calculation of the hadronic vacuum polarization contribution to the muon anomalous magnetic moment, $a_\mu^{\mathrm hvp}$, in lattice QCD employing dynamical up and down quarks. We focus on controlling the infrared regime of the vacuum polarization function. To this end we employ several complementary approaches, including Pad\'e fits, time moments and the time-momentum representation. We correct our results for finite-volume effects by combining the Gounaris-Sakurai parameterization of the timelike pion form factor with the L\"uscher formalism. On a subset of our ensembles we have derived an upper bound on the magnitude of quark-disconnected diagrams and found that they decrease the estimate for $a_\mu^{\mathrm hvp}$ by at most 2%. Our final result is $a_\mu^{\mathrm hvp}=(654\pm32\,{}^{+21}_{-23})\cdot 10^{-10}$, where the first error is statistical, and the second denotes the combined systematic uncertainty. Based on our findings we discuss the prospects for determining $a_\mu^{\mathrm hvp}$ with sub-percent precision.Comment: 42 pages, 7 figures, version published in JHE