On Finding Maximum Cardinality Subset of Vectors with a Constraint on Normalized Squared Length of Vectors Sum

In this paper, we consider the problem of finding a maximum cardinality subset of vectors, given a constraint on the normalized squared length of vectors sum. This problem is closely related to Problem 1 from (Eremeev, Kel'manov, Pyatkin, 2016). The main difference consists in swapping the constraint with the optimization criterion. We prove that the problem is NP-hard even in terms of finding a feasible solution. An exact algorithm for solving this problem is proposed. The algorithm has a pseudo-polynomial time complexity in the special case of the problem, where the dimension of the space is bounded from above by a constant and the input data are integer. A computational experiment is carried out, where the proposed algorithm is compared to COINBONMIN solver, applied to a mixed integer quadratic programming formulation of the problem. The results of the experiment indicate superiority of the proposed algorithm when the dimension of Euclidean space is low, while the COINBONMIN has an advantage for larger dimensions.Comment: To appear in Proceedings of the 6th International Conference on Analysis of Images, Social Networks, and Texts (AIST'2017

Tunable Semiconductors: Control over Carrier States and Excitations in Layered Hybrid Organic-Inorganic Perovskites

For a class of 2D hybrid organic-inorganic perovskite semiconductors based on $\pi$-conjugated organic cations, we predict quantitatively how varying the organic and inorganic component allows control over the nature, energy and localization of carrier states in a quantum-well-like fashion. Our first-principles predictions, based on large-scale hybrid density-functional theory with spin-orbit coupling, show that the interface between the organic and inorganic parts within a single hybrid can be modulated systematically, enabling us to select between different type-I and type-II energy level alignments. Energy levels, recombination properties and transport behavior of electrons and holes thus become tunable by choosing specific organic functionalizations and juxtaposing them with suitable inorganic components

Phonon-mediated and weakly size-dependent electron and hole cooling in CsPbBr3 nanocrystals revealed by atomistic simulations and ultrafast spectroscopy

We combine state-of-the-art ultrafast photoluminescence and absorption spectroscopy and nonadiabatic molecular dynamics simulations to investigate charge-carrier cooling in CsPbBr3 nanocrystals over a very broad size regime, from 0.8 to 12 nm. Contrary to the prevailing notion that polaron formation slows down charge-carrier cooling in lead-halide perovskites, no suppression of carrier cooling is observed in CsPbBr3 nanocrystals except for a slow cooling (over similar to 10 ps) of "warm" electrons in the vicinity (within similar to 0.1 eV) of the conduction band edge. At higher excess energies, electrons and holes cool with similar rates, on the order of 1 eV ps(-1) carrier(-1), increasing weakly with size. Our ab initio simulations suggest that cooling proceeds via fast phonon-mediated intraband transitions driven by strong and size-dependent electron-phonon coupling. The presented experimental and computational methods yield the spectrum of involved phonons and may guide the development of devices utilizing hot charge carriers

Automating Fault Tolerance in High-Performance Computational Biological Jobs Using Multi-Agent Approaches

Background: Large-scale biological jobs on high-performance computing systems require manual intervention if one or more computing cores on which they execute fail. This places not only a cost on the maintenance of the job, but also a cost on the time taken for reinstating the job and the risk of losing data and execution accomplished by the job before it failed. Approaches which can proactively detect computing core failures and take action to relocate the computing core's job onto reliable cores can make a significant step towards automating fault tolerance. Method: This paper describes an experimental investigation into the use of multi-agent approaches for fault tolerance. Two approaches are studied, the first at the job level and the second at the core level. The approaches are investigated for single core failure scenarios that can occur in the execution of parallel reduction algorithms on computer clusters. A third approach is proposed that incorporates multi-agent technology both at the job and core level. Experiments are pursued in the context of genome searching, a popular computational biology application. Result: The key conclusion is that the approaches proposed are feasible for automating fault tolerance in high-performance computing systems with minimal human intervention. In a typical experiment in which the fault tolerance is studied, centralised and decentralised checkpointing approaches on an average add 90% to the actual time for executing the job. On the other hand, in the same experiment the multi-agent approaches add only 10% to the overall execution time.Comment: Computers in Biology and Medicin