Modelling and solving central cycle problems with integer programming

We consider the problem of identifying a central subgraph of a given simple connected graph. The case where the subgraph comprises a discrete set of vertices is well known. However, the concept of eccentricity can be extended to connected subgraphs such as: paths, trees and cycles. Methods have been reported which deal with the requirement that the subgraph is a path or a constrained tree. We extend this work to the case where the subgraph is required to be a cycle. We report on computational experience with integer programming models of the problems of identifying cycle centres, cycle medians and cycle centroids, and also on a heuristic based on the first model. The problems have applications in facilities location, particularly the location of emergency facilities, and service facilities

Generalized Buneman pruning for inferring the most parsimonious multi-state phylogeny

Accurate reconstruction of phylogenies remains a key challenge in evolutionary biology. Most biologically plausible formulations of the problem are formally NP-hard, with no known efficient solution. The standard in practice are fast heuristic methods that are empirically known to work very well in general, but can yield results arbitrarily far from optimal. Practical exact methods, which yield exponential worst-case running times but generally much better times in practice, provide an important alternative. We report progress in this direction by introducing a provably optimal method for the weighted multi-state maximum parsimony phylogeny problem. The method is based on generalizing the notion of the Buneman graph, a construction key to efficient exact methods for binary sequences, so as to apply to sequences with arbitrary finite numbers of states with arbitrary state transition weights. We implement an integer linear programming (ILP) method for the multi-state problem using this generalized Buneman graph and demonstrate that the resulting method is able to solve data sets that are intractable by prior exact methods in run times comparable with popular heuristics. Our work provides the first method for provably optimal maximum parsimony phylogeny inference that is practical for multi-state data sets of more than a few characters.Comment: 15 page

ZARAMIT: A System for the Evolutionary Study of Human Mitochondrial DNA

Abstract. ZARAMIT is an information system capable of fully auto-mated phylogeny reconstruction. Methods have been tailored to mito-chondrial DNA sequences, with focus on subproblem partitioning. We have built exhaustive human mitochondrial phylogenies (∼5500 sequences) and detected problems in existing haplogroup hierarchies through data-driven classification. Information on the project can be found on zaramit.org. 1 The case for mitochondrial DNA Mitochondria, organelles present in most eukaryotic cells, are responsible for the generation of most of the cell’s chemical energy. They are also remarkable for possessing their own, separate genome, which coexists with nuclear DNA and is inherited independently. Further, mitochondrial DNA (mtDNA) has several features which make it an ideal candidate for conducting evolutionary studies. Firstly, it is small in mammals (15000 to 17000 base pairs) and encodes a homogeneous set of gene

Measurement of CP asymmetries and branching fraction ratios of B− decays to two charm mesons

The $CP$ asymmetries of seven $B^-$ decays to two charm mesons are measured using data corresponding to an integrated luminosity of $9\text{fb}^{-1}$ of proton-proton collisions collected by the LHCb experiment. Decays involving a $D^{*0}$ or $D^{*-}_s$ meson are analysed by reconstructing only the $D^0$ or $D^-_s$ decay products. This paper presents the first measurement of $\mathcal{A}^{CP}(B^- \rightarrow D^{*-}_s D^0)$ and $\mathcal{A}^{CP}(B^- \rightarrow D^{-}_s D^{*0})$, and the most precise measurement of the other five $CP$ asymmetries. There is no evidence of $CP$ violation in any of the analysed decays. Additionally, two ratios between branching fractions of selected decays are measured.The CP asymmetries of seven B$^{−}$ decays to two charm mesons are measured using data corresponding to an integrated luminosity of 9 fb$^{−1}$ of proton-proton collisions collected by the LHCb experiment. Decays involving a D$^{*0}$ or ${D}_s^{\ast -}$ meson are analysed by reconstructing only the D$^{0}$ or ${D}_s^{-}$ decay products. This paper presents the first measurement of $\mathcal{A} ^{CP}$(B$^{−}$→${D}_s^{\ast -}$D$^{0}$) and $\mathcal{A} ^{CP}$(B$^{−}$→${D}_s^{-}$D$^{∗0}$), and the most precise measurement of the other five CP asymmetries. There is no evidence of CP violation in any of the analysed decays. Additionally, two ratios between branching fractions of selected decays are measured.[graphic not available: see fulltext]The $CP$ asymmetries of seven $B^-$ decays to two charm mesons are measured using data corresponding to an integrated luminosity of $9\text{ fb}^{-1}$ of proton-proton collisions collected by the LHCb experiment. Decays involving a $D^{*0}$ or $D^{*-}_s$ meson are analysed by reconstructing only the $D^0$ or $D^-_s$ decay products. This paper presents the first measurement of $\mathcal{A}^{CP}(B^- \rightarrow D^{*-}_s D^0)$ and $\mathcal{A}^{CP}(B^- \rightarrow D^{-}_s D^{*0})$, and the most precise measurement of the other five $CP$ asymmetries. There is no evidence of $CP$ violation in any of the analysed decays. Additionally, two ratios between branching fractions of selected decays are measured

Helium identification with LHCb

The identification of helium nuclei at LHCb is achieved using a method based on measurements of ionisation losses in the silicon sensors and timing measurements in the Outer Tracker drift tubes. The background from photon conversions is reduced using the RICH detectors and an isolation requirement. The method is developed using pp collision data at √(s) = 13 TeV recorded by the LHCb experiment in the years 2016 to 2018, corresponding to an integrated luminosity of 5.5 fb-1. A total of around 105 helium and antihelium candidates are identified with negligible background contamination. The helium identification efficiency is estimated to be approximately 50% with a corresponding background rejection rate of up to O(10^12). These results demonstrate the feasibility of a rich programme of measurements of QCD and astrophysics interest involving light nuclei

Curvature-bias corrections using a pseudomass method

Momentum measurements for very high momentum charged particles, such as muons from electroweak vector boson decays, are particularly susceptible to charge-dependent curvature biases that arise from misalignments of tracking detectors. Low momentum charged particles used in alignment procedures have limited sensitivity to coherent displacements of such detectors, and therefore are unable to fully constrain these misalignments to the precision necessary for studies of electroweak physics. Additional approaches are therefore required to understand and correct for these effects. In this paper the curvature biases present at the LHCb detector are studied using the pseudomass method in proton-proton collision data recorded at centre of mass energy √(s)=13 TeV during 2016, 2017 and 2018. The biases are determined using Z→μ + μ - decays in intervals defined by the data-taking period, magnet polarity and muon direction. Correcting for these biases, which are typically at the 10-4 GeV-1 level, improves the Z→μ + μ - mass resolution by roughly 18% and eliminates several pathological trends in the kinematic-dependence of the mean dimuon invariant mass

Momentum scale calibration of the LHCb spectrometer

For accurate determination of particle masses accurate knowledge of the momentum scale of the detectors is crucial. The procedure used to calibrate the momentum scale of the LHCb spectrometer is described and illustrated using the performance obtained with an integrated luminosity of 1.6 fb-1 collected during 2016 in pp running. The procedure uses large samples of J/ψ → μ + μ - and B+ → J/ψ K + decays and leads to a relative accuracy of 3 × 10-4 on the momentum scale

Combinatorial optimization for undergraduate

xii, 227 p.; 24 cm