7,168 research outputs found

    Supersymmetry Across Nanoscale Heterojunction

    Full text link
    We argue that supersymmetric transformation could be applied across the heterojunction formed by joining of two mixed semiconductors. A general framework is described by specifying the structure of ladder operators at the junction for making quantitative estimation of physical quantities. For a particular heterojunction device, we show that an exponential grading inside a nanoscale doped layer is amenable to exact analytical treatment for a class of potentials distorted by the junctions through the solutions of transformed Morse-Type potentials.Comment: 7 pages, 2 figure

    Minimum-Weight Edge Discriminator in Hypergraphs

    Full text link
    In this paper we introduce the concept of minimum-weight edge-discriminators in hypergraphs, and study its various properties. For a hypergraph H=(V,E)\mathcal H=(\mathcal V, \mathcal E), a function λ:VZ+{0}\lambda: \mathcal V\rightarrow \mathbb Z^{+}\cup\{0\} is said to be an {\it edge-discriminator} on H\mathcal H if vEiλ(v)>0\sum_{v\in E_i}{\lambda(v)}>0, for all hyperedges EiEE_i\in \mathcal E, and vEiλ(v)vEjλ(v)\sum_{v\in E_i}{\lambda(v)}\ne \sum_{v\in E_j}{\lambda(v)}, for every two distinct hyperedges Ei,EjEE_i, E_j \in \mathcal E. An {\it optimal edge-discriminator} on H\mathcal H, to be denoted by λH\lambda_\mathcal H, is an edge-discriminator on H\mathcal H satisfying vVλH(v)=minλvVλ(v)\sum_{v\in \mathcal V}\lambda_\mathcal H (v)=\min_\lambda\sum_{v\in \mathcal V}{\lambda(v)}, where the minimum is taken over all edge-discriminators on H\mathcal H. We prove that any hypergraph H=(V,E)\mathcal H=(\mathcal V, \mathcal E), with E=n|\mathcal E|=n, satisfies vVλH(v)n(n+1)/2\sum_{v\in \mathcal V} \lambda_\mathcal H(v)\leq n(n+1)/2, and equality holds if and only if the elements of E\mathcal E are mutually disjoint. For rr-uniform hypergraphs H=(V,E)\mathcal H=(\mathcal V, \mathcal E), it follows from results on Sidon sequences that vVλH(v)Vr+1+o(Vr+1)\sum_{v\in \mathcal V}\lambda_{\mathcal H}(v)\leq |\mathcal V|^{r+1}+o(|\mathcal V|^{r+1}), and the bound is attained up to a constant factor by the complete rr-uniform hypergraph. Next, we construct optimal edge-discriminators for some special hypergraphs, which include paths, cycles, and complete rr-partite hypergraphs. Finally, we show that no optimal edge-discriminator on any hypergraph H=(V,E)\mathcal H=(\mathcal V, \mathcal E), with E=n(3)|\mathcal E|=n (\geq 3), satisfies vVλH(v)=n(n+1)/21\sum_{v\in \mathcal V} \lambda_\mathcal H (v)=n(n+1)/2-1, which, in turn, raises many other interesting combinatorial questions.Comment: 22 pages, 5 figure

    New classes of quasi-solvable potentials, their exactly-solvable limit and related orthogonal polynomials

    Full text link
    We have generated, using an sl(2,R) formalism, several new classes of quasi-solvable elliptic potentials, which in the appropriate limit go over to the exactly solvable forms. We have obtained exact solutions of the corresponding spectral problems for some real values of the potential parameters. We have also given explicit expressions of the families of associated orthogonal polynomials in the energy variable.Comment: 14 pages, 5 tables, LaTeX2

    Enhanced information retrieval using domain-specific recommender models

    Get PDF
    The objective of an information retrieval (IR) system is to retrieve relevant items which meet a user information need. There is currently significant interest in personalized IR which seeks to improve IR effectiveness by incorporating a model of the user’s interests. However, in some situations there may be no opportunity to learn about the interests of a specific user on a certain topic. In our work, we propose an IR approach which combines a recommender algorithm with IR methods to improve retrieval for domains where the system has no opportunity to learn prior information about the user’s knowledge of a domain for which they have not previously entered a query. We use search data from other previous users interested in the same topic to build a recommender model for this topic. When a user enters a query on a topic, new to this user, an appropriate recommender model is selected and used to predict a ranking which the user may find interesting based on the behaviour of previous users with similar queries. The recommender output is integrated with a standard IR method in a weighted linear combination to provide a final result for the user. Experiments using the INEX 2009 data collection with a simulated recommender training set show that our approach can improve on a baseline IR system

    Upper tails and independence polynomials in random graphs

    Full text link
    The upper tail problem in the Erd\H{o}s--R\'enyi random graph GGn,pG\sim\mathcal{G}_{n,p} asks to estimate the probability that the number of copies of a graph HH in GG exceeds its expectation by a factor 1+δ1+\delta. Chatterjee and Dembo showed that in the sparse regime of p0p\to 0 as nn\to\infty with pnαp \geq n^{-\alpha} for an explicit α=αH>0\alpha=\alpha_H>0, this problem reduces to a natural variational problem on weighted graphs, which was thereafter asymptotically solved by two of the authors in the case where HH is a clique. Here we extend the latter work to any fixed graph HH and determine a function cH(δ)c_H(\delta) such that, for pp as above and any fixed δ>0\delta>0, the upper tail probability is exp[(cH(δ)+o(1))n2pΔlog(1/p)]\exp[-(c_H(\delta)+o(1))n^2 p^\Delta \log(1/p)], where Δ\Delta is the maximum degree of HH. As it turns out, the leading order constant in the large deviation rate function, cH(δ)c_H(\delta), is governed by the independence polynomial of HH, defined as PH(x)=iH(k)xkP_H(x)=\sum i_H(k) x^k where iH(k)i_H(k) is the number of independent sets of size kk in HH. For instance, if HH is a regular graph on mm vertices, then cH(δ)c_H(\delta) is the minimum between 12δ2/m\frac12 \delta^{2/m} and the unique positive solution of PH(x)=1+δP_H(x) = 1+\delta

    Quantum Cloning, Bell's Inequality and Teleportation

    Full text link
    We analyze a possibility of using the two qubit output state from Buzek-Hillery quantum copying machine (not necessarily universal quantum cloning machine) as a teleportation channel. We show that there is a range of values of the machine parameter ξ\xi for which the two qubit output state is entangled and violates Bell-CHSH inequality and for a different range it remains entangled but does not violate Bell-CHSH inequality. Further we observe that for certain values of the machine parameter the two-qubit mixed state can be used as a teleportation channel. The use of the output state from the Buzek-Hillery cloning machine as a teleportation channel provides an additional appeal to the cloning machine and motivation of our present work.Comment: 7 pages and no figures, Accepted in Journal of Physics
    corecore