Pattern recognition on a quantum computer

By means of a simple example it is demonstrated that the task of finding and identifying certain patterns in an otherwise (macroscopically) unstructured picture (data set) can be accomplished efficiently by a quantum computer. Employing the powerful tool of the quantum Fourier transform the proposed quantum algorithm exhibits an exponential speed-up in comparison with its classical counterpart. The digital representation also results in a significantly higher accuracy than the method of optical filtering. PACS: 03.67.Lx, 03.67.-a, 42.30.Sy, 89.70.+c.Comment: 6 pages RevTeX, 1 figure, several correction

Improved Bounds on Quantum Learning Algorithms

In this article we give several new results on the complexity of algorithms that learn Boolean functions from quantum queries and quantum examples. Hunziker et al. conjectured that for any class C of Boolean functions, the number of quantum black-box queries which are required to exactly identify an unknown function from C is $O(\frac{\log |C|}{\sqrt{{\hat{\gamma}}^{C}}})$, where $\hat{\gamma}^{C}$ is a combinatorial parameter of the class C. We essentially resolve this conjecture in the affirmative by giving a quantum algorithm that, for any class C, identifies any unknown function from C using $O(\frac{\log |C| \log \log |C|}{\sqrt{{\hat{\gamma}}^{C}}})$ quantum black-box queries. We consider a range of natural problems intermediate between the exact learning problem (in which the learner must obtain all bits of information about the black-box function) and the usual problem of computing a predicate (in which the learner must obtain only one bit of information about the black-box function). We give positive and negative results on when the quantum and classical query complexities of these intermediate problems are polynomially related to each other. Finally, we improve the known lower bounds on the number of quantum examples (as opposed to quantum black-box queries) required for $(\epsilon,\delta)$-PAC learning any concept class of Vapnik-Chervonenkis dimension d over the domain $\{0,1\}^n$ from $\Omega(\frac{d}{n})$ to $\Omega(\frac{1}{\epsilon}\log \frac{1}{\delta}+d+\frac{\sqrt{d}}{\epsilon})$. This new lower bound comes closer to matching known upper bounds for classical PAC learning.Comment: Minor corrections. 18 pages. To appear in Quantum Information Processing. Requires: algorithm.sty, algorithmic.sty to buil

Precision calculation of the pi^- deuteron scattering length and its impact on threshold pi-N scattering

We present a calculation of the pi^- d scattering length with an accuracy of a few percent using chiral perturbation theory. For the first time isospin-violating corrections are included consistently. Using data on pionic deuterium and pionic hydrogen atoms, we extract the isoscalar and isovector pion-nucleon scattering lengths and obtain a^+=(7.6 +/- 3.1) x 10^{-3} mpi^{-1} and a^-=(86.1 +/- 0.9) x 10^{-3} mpi^{-1}. Via the Goldberger-Miyazawa-Oehme sum rule, this leads to a charged-pion-nucleon coupling constant g_c^2/4 pi = 13.69 +/- 0.20.Comment: 6 pages, 2 figures. Discussion of several points expanded, references added in this version, which will appear in Physics Letters

The modelery: a collaborative web based repository

Software development processes are known to produce a large set of artifacts such as models, code and documentation. Keeping track of these artifacts without supporting tools is not easy, and making them available to others can be even harder. Standard version control systems are not able to solve this issue. More than keeping track of versions, a system to help organize and make artifacts available in meaningful ways is needed. In this paper we review a number of alternative systems, and present the requirements and the implementation of a collaborative web repository which we developed to solve this issue.Project LATiCES: Languages And Tools for Critical rEal-time Systems (Ref. NORTE-07-0124-FEDER-000062) is financed by the North Portugal Regional Operational Programme (ON.2 - O Novo Norte), under the National Strategic Reference Framework (NSRF), through the European Regional Development Fund (ERDF), and by national funds, through the Portuguese funding agency, Fundacão para a Ciência e a Tecnologia (FCT)

Precision calculation of threshold pi^- d scattering, pi N scattering lengths, and the GMO sum rule

We use chiral perturbation theory (ChPT) to calculate the $\pi^- d$ scattering length with an accuracy of a few percent, including isospin-violating corrections both in the two- and three-body sector. In particular, we provide the technical details of a recent letter, where we used data on pionic deuterium and pionic hydrogen atoms to extract the isoscalar and isovector pion-nucleon scattering lengths $a^+$ and $a^-$. We study isospin-breaking contributions to the three-body part of $a_{\pi^-d}$ due to mass differences, isospin violation in the $\pi N$ scattering lengths, and virtual photons. This last class of effects is ostensibly infrared enhanced due to the smallness of the deuteron binding energy. However, we show that the leading virtual-photon effects that might undergo such enhancement cancel, and hence the standard ChPT counting provides a reliable estimate of isospin violation in $a_{\pi^- d}$ due to virtual photons. Finally, we discuss the validity of the Goldberger-Miyazawa-Oehme sum rule in the presence of isospin violation, and use it to determine the charged-pion-nucleon coupling constant.Comment: 46 pages, 7 figures. Discussion of several points expanded, references added, version published in Nuclear Physics

The ‘mosaic habitat’ concept in human evolution: past and present

The habitats preferred by hominins and other species are an important theme in palaeoanthropology, and the ‘mosaic habitat’ (also referred to as habitat heterogeneity) has been a central concept in this regard for the last four decades. Here we explore the development of this concept – loosely defined as a range of different habitat types, such as woodlands, riverine forest and savannah within a limited spatial area– in studies of human evolution in the last sixty years or so. We outline the key developments that took place before and around the time when the term ‘mosaic’ came to wider palaeoanthropological attention. To achieve this we used an analysis of the published literature, a study of illustrations of hominin evolution from 1925 onwards and an email survey of senior researchers in palaeoanthropology and related fields. We found that the term mosaic starts to be applied in palaeoanthropological thinking during the 1970’s due to the work of a number of researchers, including Karl Butzer and Glynn Isaac , with the earliest usage we have found of ‘mosaic’ in specific reference to hominin habitats being by Adriaan Kortlandt (1972). While we observe a steady increase in the numbers of publications reporting mosaic palaeohabitats, in keeping with the growing interest and specialisation in various methods of palaeoenvironmental reconstruction, we also note that there is a lack of critical studies that define this habitat, or examine the temporal and spatial scales associated with it. The general consensus within the field is that the concept now requires more detailed definition and study to evaluate its role in human evolution

Measurement of the cross section of high transverse momentum Z→bb̄ production in proton–proton collisions at √s = 8 TeV with the ATLAS detector

This Letter reports the observation of a high transverse momentum Z→bb̄ signal in proton–proton collisions at √s=8 TeV and the measurement of its production cross section. The data analysed were collected in 2012 with the ATLAS detector at the LHC and correspond to an integrated luminosity of 19.5 fb−¹. The Z→bb̄ decay is reconstructed from a pair of b -tagged jets, clustered with the anti-ktkt jet algorithm with R=0.4R=0.4, that have low angular separation and form a dijet with pT>200 GeVpT>200 GeV. The signal yield is extracted from a fit to the dijet invariant mass distribution, with the dominant, multi-jet background mass shape estimated by employing a fully data-driven technique that reduces the dependence of the analysis on simulation. The fiducial cross section is determined to be σZ→bb¯fid=2.02±0.20 (stat.) ±0.25 (syst.)±0.06 (lumi.) pb=2.02±0.33 pb, in good agreement with next-to-leading-order theoretical predictions