354,949 research outputs found
Optimisation of Quantum Evolution Algorithms
Given a quantum Hamiltonian and its evolution time, the corresponding unitary
evolution operator can be constructed in many different ways, corresponding to
different trajectories between the desired end-points. A choice among these
trajectories can then be made to obtain the best computational complexity and
control over errors. As an explicit example, Grover's quantum search algorithm
is described as a Hamiltonian evolution problem. It is shown that the
computational complexity has a power-law dependence on error when a
straightforward Lie-Trotter discretisation formula is used, and it becomes
logarithmic in error when reflection operators are used. The exponential change
in error control is striking, and can be used to improve many importance
sampling methods. The key concept is to make the evolution steps as large as
possible while obeying the constraints of the problem. In particular, we can
understand why overrelaxation algorithms are superior to small step size
algorithms.Comment: 7 pages. Talk presented at the 32nd International Symposium on
Lattice Field Theory, 23-28 June 2014, Columbia University, New York, US
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Evolving cellular automata to generate nonlinear sequences with desirable properties
This paper presents a new chromosomal representation and associated genetic operators for the evolution of highly nonlinear cellular automata that generate pseudorandom number sequences with desirable properties ensured. This chromosomal representation reduces the computational complexity of genetic operators to evolve valid solutions while facilitating fitness evaluation based on the DIEHARD statistical tests
A low complexity resource allocation algorithm for multicast service delivery in OFDMA networks
Allocating and managing radio resources to multicast transmissions in Orthogonal Frequency-Division Multiple Access (OFDMA) systems is the challenging research issue addressed by this paper. A subgrouping technique, which divides the subscribers into subgroups according to the experienced channel quality, is considered to overcome the throughput limitations of conventional multicast data delivery schemes. A low complexity algorithm, designed to work with different resource allocation strategies, is also proposed to reduce the computational complexity of the subgroup formation problem. Simulation results, carried out by considering the Long Term Evolution (LTE) system based on OFDMA, testify the effectiveness of the proposed solution, which achieves a near-optimal performance with a limited computational load for the system
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