17 research outputs found
Quantum search algorithms, quantum wireless, and a low-complexity maximum likelihood iterative quantum multi-user detector design
The high complexity of numerous optimal classic communication schemes, such as the maximum likelihood (ML) multiuser detector (MUD), often prevents their practical implementation. In this paper, we present an extensive review and tutorial on quantum search algorithms (QSA) and their potential applications, and we employ a QSA that finds the minimum of a function in order to perform optimal hard MUD with a quadratic reduction in the computational complexity when compared to that of the ML MUD. Furthermore, we follow a quantum approach to achieve the same performance as the optimal soft-input soft-output classic detectors by replacing them with a quantum algorithm, which estimates the weighted sum of a function’s evaluations. We propose a soft-input soft-output quantum-assisted MUD (QMUD) scheme, which is the quantum-domain equivalent of the ML MUD. We then demonstrate its application using the design example of a direct-sequence code division multiple access system employing bit-interleaved coded modulation relying on iterative decoding, and compare it with the optimal ML MUD in terms of its performance and complexity. Both our extrinsic information transfer charts and bit error ratio curves show that the performance of the proposed QMUD and that of the optimal classic MUD are equivalent, but the QMUD’s computational complexity is significantly lower
Noise-based information processing: Noise-based logic and computing: what do we have so far?
We briefly introduce noise-based logic. After describing the main motivations
we outline classical, instantaneous (squeezed and non-squeezed), continuum,
spike and random-telegraph-signal based schemes with applications such as
circuits that emulate the brain functioning and string verification via a slow
communication channel.Comment: Invited talk at the 21st International Conference on Noise and
Fluctuations, Toronto, Canada, June 12-16, 201
Fast quantum search algorithm modelling on conventional computers: Information analysis of termination problem
The simplest technique for simulating a quantum algorithm - QA described
based on the direct matrix representation of the quantum operators. Using this
approach, it is relatively simple to simulate the operation of a QA and to
perform fidelity analysis. A more efficient fast QA simulation technique is
based on computing all or part of the operator matrices on an as needed current
computational basis. Using this technique, it is possible to avoid storing all
or part of the operator matrices. The compute on demand approach benefits from
a study of the quantum operators, and their structure so that the matrix
elements can be computed more efficiently. Effective simulation of Grover
quantum search algorithm as example on computer with classical architecture is
considered