1,358 research outputs found
Quantum Computers, Factoring, and Decoherence
In a quantum computer any superposition of inputs evolves unitarily into the
corresponding superposition of outputs. It has been recently demonstrated that
such computers can dramatically speed up the task of finding factors of large
numbers -- a problem of great practical significance because of its
cryptographic applications. Instead of the nearly exponential (, for a number with digits) time required by the fastest classical
algorithm, the quantum algorithm gives factors in a time polynomial in
(). This enormous speed-up is possible in principle because quantum
computation can simultaneously follow all of the paths corresponding to the
distinct classical inputs, obtaining the solution as a result of coherent
quantum interference between the alternatives. Hence, a quantum computer is
sophisticated interference device, and it is essential for its quantum state to
remain coherent in the course of the operation. In this report we investigate
the effect of decoherence on the quantum factorization algorithm and establish
an upper bound on a ``quantum factorizable'' based on the decoherence
suffered per operational step.Comment: 7 pages,LaTex + 2 postcript figures in a uuencoded fil
Using error correction to determine the noise model
Quantum error correcting codes have been shown to have the ability of making
quantum information resilient against noise. Here we show that we can use
quantum error correcting codes as diagnostics to characterise noise. The
experiment is based on a three-bit quantum error correcting code carried out on
a three-qubit nuclear magnetic resonance (NMR) quantum information processor.
Utilizing both engineered and natural noise, the degree of correlations present
in the noise affecting a two-qubit subsystem was determined. We measured a
correlation factor of c=0.5+/-0.2 using the error correction protocol, and
c=0.3+/-0.2 using a standard NMR technique based on coherence pathway
selection. Although the error correction method demands precise control, the
results demonstrate that the required precision is achievable in the
liquid-state NMR setting.Comment: 10 pages, 3 figures. Added discussion section, improved figure
Introduction to Quantum Error Correction
In this introduction we motivate and explain the ``decoding'' and
``subsystems'' view of quantum error correction. We explain how quantum noise
in QIP can be described and classified, and summarize the requirements that
need to be satisfied for fault tolerance. Considering the capabilities of
currently available quantum technology, the requirements appear daunting. But
the idea of ``subsystems'' shows that these requirements can be met in many
different, and often unexpected ways.Comment: 44 pages, to appear in LA Science. Hyperlinked PDF at
http://www.c3.lanl.gov/~knill/qip/ecprhtml/ecprpdf.pdf, HTML at
http://www.c3.lanl.gov/~knill/qip/ecprhtm
Statistical comparison of ensemble implementations of Grover's search algorithm to classical sequential searches
We compare pseudopure state ensemble implementations, quantified by their
initial polarization and ensemble size, of Grover's search algorithm to
probabilistic classical sequential search algorithms in terms of their success
and failure probabilities. We propose a criterion for quantifying the resources
used by the ensemble implementation via the aggregate number of oracle
invocations across the entire ensemble and use this as a basis for comparison
with classical search algorithms. We determine bounds for a critical
polarization such that the ensemble algorithm succeeds with a greater
probability than the probabilistic classical sequential search. Our results
indicate that the critical polarization scales as N^(-1/4) where N is the
database size and that for typical room temperature solution state NMR, the
polarization is such that the ensemble implementation of Grover's algorithm
would be advantageous for N > 10^2
Experimental approximation of the Jones polynomial with DQC1
We present experimental results approximating the Jones polynomial using 4
qubits in a liquid state nuclear magnetic resonance quantum information
processor. This is the first experimental implementation of a complete problem
for the deterministic quantum computation with one quantum bit model of quantum
computation, which uses a single qubit accompanied by a register of completely
random states. The Jones polynomial is a knot invariant that is important not
only to knot theory, but also to statistical mechanics and quantum field
theory. The implemented algorithm is a modification of the algorithm developed
by Shor and Jordan suitable for implementation in NMR. These experimental
results show that for the restricted case of knots whose braid representations
have four strands and exactly three crossings, identifying distinct knots is
possible 91% of the time.Comment: 5 figures. Version 2 changes: published version, minor errors
corrected, slight changes to improve readabilit
Introduction to Quantum Information Processing
As a result of the capabilities of quantum information, the science of
quantum information processing is now a prospering, interdisciplinary field
focused on better understanding the possibilities and limitations of the
underlying theory, on developing new applications of quantum information and on
physically realizing controllable quantum devices. The purpose of this primer
is to provide an elementary introduction to quantum information processing, and
then to briefly explain how we hope to exploit the advantages of quantum
information. These two sections can be read independently. For reference, we
have included a glossary of the main terms of quantum information.Comment: 48 pages, to appear in LA Science. Hyperlinked PDF at
http://www.c3.lanl.gov/~knill/qip/prhtml/prpdf.pdf, HTML at
http://www.c3.lanl.gov/~knill/qip/prhtm
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