20,583 research outputs found

    Energy Complexity of Distance Computation in Multi-hop Networks

    Full text link
    Energy efficiency is a critical issue for wireless devices operated under stringent power constraint (e.g., battery). Following prior works, we measure the energy cost of a device by its transceiver usage, and define the energy complexity of an algorithm as the maximum number of time slots a device transmits or listens, over all devices. In a recent paper of Chang et al. (PODC 2018), it was shown that broadcasting in a multi-hop network of unknown topology can be done in polylogn\text{poly} \log n energy. In this paper, we continue this line of research, and investigate the energy complexity of other fundamental graph problems in multi-hop networks. Our results are summarized as follows. 1. To avoid spending Ω(D)\Omega(D) energy, the broadcasting protocols of Chang et al. (PODC 2018) do not send the message along a BFS tree, and it is open whether BFS could be computed in o(D)o(D) energy, for sufficiently large DD. In this paper we devise an algorithm that attains O~(n)\tilde{O}(\sqrt{n}) energy cost. 2. We show that the framework of the Ω(n){\Omega}(n) round lower bound proof for computing diameter in CONGEST of Abboud et al. (DISC 2017) can be adapted to give an Ω~(n)\tilde{\Omega}(n) energy lower bound in the wireless network model (with no message size constraint), and this lower bound applies to O(logn)O(\log n)-arboricity graphs. From the upper bound side, we show that the energy complexity of O~(n)\tilde{O}(\sqrt{n}) can be attained for bounded-genus graphs (which includes planar graphs). 3. Our upper bounds for computing diameter can be extended to other graph problems. We show that exact global minimum cut or approximate ss--tt minimum cut can be computed in O~(n)\tilde{O}(\sqrt{n}) energy for bounded-genus graphs

    Toward a unified interpretation of quark and lepton mixing from flavor and CP symmetries

    Full text link
    We discussed the scenario that a discrete flavor group combined with CP symmetry is broken to Z2×CPZ_2\times CP in both neutrino and charged lepton sectors. All lepton mixing angles and CP violation phases are predicted to depend on two free parameters θl\theta_{l} and θν\theta_{\nu} varying in the range of [0,π)[0, \pi). As an example, we comprehensively study the lepton mixing patterns which can be derived from the flavor group Δ(6n2)\Delta(6n^2) and CP symmetry. Three kinds of phenomenologically viable lepton mixing matrices are obtained up to row and column permutations. We further extend this approach to the quark sector. The precisely measured quark mixing angles and CP invariant can be accommodated for certain values of the free parameters θu\theta_{u} and θd\theta_{d}. A simultaneous description of quark and lepton flavor mixing structures can be achieved from a common flavor group Δ(6n2)\Delta(6n^2) and CP, and accordingly the smallest value of the group index nn is n=7n=7.Comment: 40 pages, 8 figure

    A Time Hierarchy Theorem for the LOCAL Model

    Full text link
    The celebrated Time Hierarchy Theorem for Turing machines states, informally, that more problems can be solved given more time. The extent to which a time hierarchy-type theorem holds in the distributed LOCAL model has been open for many years. It is consistent with previous results that all natural problems in the LOCAL model can be classified according to a small constant number of complexities, such as O(1),O(logn),O(logn),2O(logn)O(1),O(\log^* n), O(\log n), 2^{O(\sqrt{\log n})}, etc. In this paper we establish the first time hierarchy theorem for the LOCAL model and prove that several gaps exist in the LOCAL time hierarchy. 1. We define an infinite set of simple coloring problems called Hierarchical 2122\frac{1}{2}-Coloring}. A correctly colored graph can be confirmed by simply checking the neighborhood of each vertex, so this problem fits into the class of locally checkable labeling (LCL) problems. However, the complexity of the kk-level Hierarchical 2122\frac{1}{2}-Coloring problem is Θ(n1/k)\Theta(n^{1/k}), for kZ+k\in\mathbb{Z}^+. The upper and lower bounds hold for both general graphs and trees, and for both randomized and deterministic algorithms. 2. Consider any LCL problem on bounded degree trees. We prove an automatic-speedup theorem that states that any randomized no(1)n^{o(1)}-time algorithm solving the LCL can be transformed into a deterministic O(logn)O(\log n)-time algorithm. Together with a previous result, this establishes that on trees, there are no natural deterministic complexities in the ranges ω(logn)\omega(\log^* n)---o(logn)o(\log n) or ω(logn)\omega(\log n)---no(1)n^{o(1)}. 3. We expose a gap in the randomized time hierarchy on general graphs. Any randomized algorithm that solves an LCL problem in sublogarithmic time can be sped up to run in O(TLLL)O(T_{LLL}) time, which is the complexity of the distributed Lovasz local lemma problem, currently known to be Ω(loglogn)\Omega(\log\log n) and O(logn)O(\log n)
    corecore