4,727 research outputs found
Experimental realisation of Shor's quantum factoring algorithm using qubit recycling
Quantum computational algorithms exploit quantum mechanics to solve problems
exponentially faster than the best classical algorithms. Shor's quantum
algorithm for fast number factoring is a key example and the prime motivator in
the international effort to realise a quantum computer. However, due to the
substantial resource requirement, to date, there have been only four
small-scale demonstrations. Here we address this resource demand and
demonstrate a scalable version of Shor's algorithm in which the n qubit control
register is replaced by a single qubit that is recycled n times: the total
number of qubits is one third of that required in the standard protocol.
Encoding the work register in higher-dimensional states, we implement a
two-photon compiled algorithm to factor N=21. The algorithmic output is
distinguishable from noise, in contrast to previous demonstrations. These
results point to larger-scale implementations of Shor's algorithm by harnessing
scalable resource reductions applicable to all physical architectures.Comment: 7 pages, 3 figure
Reliable Linear, Sesquilinear and Bijective Operations On Integer Data Streams Via Numerical Entanglement
A new technique is proposed for fault-tolerant linear, sesquilinear and
bijective (LSB) operations on integer data streams (), such as:
scaling, additions/subtractions, inner or outer vector products, permutations
and convolutions. In the proposed method, the input integer data streams
are linearly superimposed to form numerically-entangled integer data
streams that are stored in-place of the original inputs. A series of LSB
operations can then be performed directly using these entangled data streams.
The results are extracted from the entangled output streams by additions
and arithmetic shifts. Any soft errors affecting any single disentangled output
stream are guaranteed to be detectable via a specific post-computation
reliability check. In addition, when utilizing a separate processor core for
each of the streams, the proposed approach can recover all outputs after
any single fail-stop failure. Importantly, unlike algorithm-based fault
tolerance (ABFT) methods, the number of operations required for the
entanglement, extraction and validation of the results is linearly related to
the number of the inputs and does not depend on the complexity of the performed
LSB operations. We have validated our proposal in an Intel processor (Haswell
architecture with AVX2 support) via fast Fourier transforms, circular
convolutions, and matrix multiplication operations. Our analysis and
experiments reveal that the proposed approach incurs between to
reduction in processing throughput for a wide variety of LSB operations. This
overhead is 5 to 1000 times smaller than that of the equivalent ABFT method
that uses a checksum stream. Thus, our proposal can be used in fault-generating
processor hardware or safety-critical applications, where high reliability is
required without the cost of ABFT or modular redundancy.Comment: to appear in IEEE Trans. on Signal Processing, 201
Theoretical and Experimental Analysis of a Randomized Algorithm for Sparse Fourier Transform Analysis
We analyze a sublinear RAlSFA (Randomized Algorithm for Sparse Fourier
Analysis) that finds a near-optimal B-term Sparse Representation R for a given
discrete signal S of length N, in time and space poly(B,log(N)), following the
approach given in \cite{GGIMS}. Its time cost poly(log(N)) should be compared
with the superlinear O(N log N) time requirement of the Fast Fourier Transform
(FFT). A straightforward implementation of the RAlSFA, as presented in the
theoretical paper \cite{GGIMS}, turns out to be very slow in practice. Our main
result is a greatly improved and practical RAlSFA. We introduce several new
ideas and techniques that speed up the algorithm. Both rigorous and heuristic
arguments for parameter choices are presented. Our RAlSFA constructs, with
probability at least 1-delta, a near-optimal B-term representation R in time
poly(B)log(N)log(1/delta)/ epsilon^{2} log(M) such that
||S-R||^{2}<=(1+epsilon)||S-R_{opt}||^{2}. Furthermore, this RAlSFA
implementation already beats the FFTW for not unreasonably large N. We extend
the algorithm to higher dimensional cases both theoretically and numerically.
The crossover point lies at N=70000 in one dimension, and at N=900 for data on
a N*N grid in two dimensions for small B signals where there is noise.Comment: 21 pages, 8 figures, submitted to Journal of Computational Physic
ARKCoS: Artifact-Suppressed Accelerated Radial Kernel Convolution on the Sphere
We describe a hybrid Fourier/direct space convolution algorithm for compact
radial (azimuthally symmetric) kernels on the sphere. For high resolution maps
covering a large fraction of the sky, our implementation takes advantage of the
inexpensive massive parallelism afforded by consumer graphics processing units
(GPUs). Applications involve modeling of instrumental beam shapes in terms of
compact kernels, computation of fine-scale wavelet transformations, and optimal
filtering for the detection of point sources. Our algorithm works for any
pixelization where pixels are grouped into isolatitude rings. Even for kernels
that are not bandwidth limited, ringing features are completely absent on an
ECP grid. We demonstrate that they can be highly suppressed on the popular
HEALPix pixelization, for which we develop a freely available implementation of
the algorithm. As an example application, we show that running on a high-end
consumer graphics card our method speeds up beam convolution for simulations of
a characteristic Planck high frequency instrument channel by two orders of
magnitude compared to the commonly used HEALPix implementation on one CPU core
while maintaining at typical a fractional RMS accuracy of about 1 part in 10^5.Comment: 10 pages, 6 figures. Submitted to Astronomy and Astrophysics.
Replaced to match published version. Code can be downloaded at
https://github.com/elsner/arkco
The Littlewood-Gowers problem
We show that if A is a subset of Z/pZ (p a prime) of density bounded away
from 0 and 1 then the A(Z/pZ)-norm (that is the l^1-norm of the Fourier
transform) of the characterstic function of A is bounded below by an absolute
constant times (log p)^{1/2 - \epsilon} as p tends to infinity. This improves
on the exponent 1/3 in recent work of Green and Konyagin.Comment: 31 pp. Corrected typos. Updated references
On error-spectrum shaping in state-space digital filters
A new scheme for shaping the error spectrum in state-space digital filter structures is proposed. The scheme is based on the application of diagonal second-order error feedback, and can be used in any arbitrary state-space structure having arbitrary order. A method to obtain noise-optimal state-space structures for fixed error feedback coefficients, starting from noise optimal structures in absence of error feedback (the Mullis and Roberts Structures), is also outlined. This optimization is based on the theory of continuous equivalence for state-space structures
On local Fourier analysis of multigrid methods for PDEs with jumping and random coefficients
In this paper, we propose a novel non-standard Local Fourier Analysis (LFA)
variant for accurately predicting the multigrid convergence of problems with
random and jumping coefficients. This LFA method is based on a specific basis
of the Fourier space rather than the commonly used Fourier modes. To show the
utility of this analysis, we consider, as an example, a simple cell-centered
multigrid method for solving a steady-state single phase flow problem in a
random porous medium. We successfully demonstrate the prediction capability of
the proposed LFA using a number of challenging benchmark problems. The
information provided by this analysis helps us to estimate a-priori the time
needed for solving certain uncertainty quantification problems by means of a
multigrid multilevel Monte Carlo method
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