464 research outputs found
Quantum Phase Estimation with Arbitrary Constant-precision Phase Shift Operators
While Quantum phase estimation (QPE) is at the core of many quantum
algorithms known to date, its physical implementation (algorithms based on
quantum Fourier transform (QFT)) is highly constrained by the requirement of
high-precision controlled phase shift operators, which remain difficult to
realize. In this paper, we introduce an alternative approach to approximately
implement QPE with arbitrary constant-precision controlled phase shift
operators.
The new quantum algorithm bridges the gap between QPE algorithms based on QFT
and Kitaev's original approach. For approximating the eigenphase precise to the
nth bit, Kitaev's original approach does not require any controlled phase shift
operator. In contrast, QPE algorithms based on QFT or approximate QFT require
controlled phase shift operators with precision of at least Pi/2n. The new
approach fills the gap and requires only arbitrary constant-precision
controlled phase shift operators. From a physical implementation viewpoint, the
new algorithm outperforms Kitaev's approach.Comment: 14 pages, 6 figures and 1 tabl
Deep Learning Meets Cognitive Radio: Predicting Future Steps
Learning the channel occupancy patterns to reuse
the underutilised spectrum frequencies without interfering with
the incumbent is a promising approach to overcome the spectrum
limitations. In this work we proposed a Deep Learning (DL)
approach to learn the channel occupancy model and predict its
availability in the next time slots. Our results show that the
proposed DL approach outperforms existing works by 5%. We
also show that our proposed DL approach predicts the availability
of channels accurately for more than one time slot
A Novel Airborne Self-organising Architecture for 5G+ Networks
Network Flying Platforms (NFPs) such as unmanned aerial vehicles, unmanned
balloons or drones flying at low/medium/high altitude can be employed to
enhance network coverage and capacity by deploying a swarm of flying platforms
that implement novel radio resource management techniques. In this paper, we
propose a novel layered architecture where NFPs, of various types and flying at
low/medium/high layers in a swarm of flying platforms, are considered as an
integrated part of the future cellular networks to inject additional capacity
and expand the coverage for exceptional scenarios (sports events, concerts,
etc.) and hard-to-reach areas (rural or sparsely populated areas). Successful
roll-out of the proposed architecture depends on several factors including, but
are not limited to: network optimisation for NFP placement and association,
safety operations of NFP for network/equipment security, and reliability for
NFP transport and control/signaling mechanisms. In this work, we formulate the
optimum placement of NFP at a Lower Layer (LL) by exploiting the airborne
Self-organising Network (SON) features. Our initial simulations show the NFP-LL
can serve more User Equipment (UE)s using this placement technique.Comment: 5 pages, 2 figures, conference paper in IEEE VTC-Fall 2017, in
Proceedings IEEE Vehicular Technology Conference (VTC-Fall 2017), Toronto,
Canada, Sep. 201
Identification of multiple-input single-output Hammerstein models using Bezier curves and Bernstein polynomials
AbstractThis paper considers the implementation of Bezier–Bernstein polynomials and the Levenberg–Marquart algorithm for identifying multiple-input single-output (MISO) Hammerstein models consisting of nonlinear static functions followed by a linear dynamical subsystem. The nonlinear static functions are approximated by the means of Bezier curves and Bernstein basis functions. The identification method is based on a hybrid scheme including the inverse de Casteljau algorithm, the least squares method, and the Levenberg–Marquart (LM) algorithm. Furthermore, results based on the proposed scheme are given which demonstrate substantial identification performance
The sound of getting rid of coronavirus by RNA interference technology: RNAi against COVID-19
No Abstract.
Efficient quantum processing of ideals in finite rings
Suppose we are given black-box access to a finite ring R, and a list of
generators for an ideal I in R. We show how to find an additive basis
representation for I in poly(log |R|) time. This generalizes a recent quantum
algorithm of Arvind et al. which finds a basis representation for R itself. We
then show that our algorithm is a useful primitive allowing quantum computers
to rapidly solve a wide variety of problems regarding finite rings. In
particular we show how to test whether two ideals are identical, find their
intersection, find their quotient, prove whether a given ring element belongs
to a given ideal, prove whether a given element is a unit, and if so find its
inverse, find the additive and multiplicative identities, compute the order of
an ideal, solve linear equations over rings, decide whether an ideal is
maximal, find annihilators, and test the injectivity and surjectivity of ring
homomorphisms. These problems appear to be hard classically.Comment: 5 page
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