128,264 research outputs found
Quantum metrology with full and fast quantum control
We establish general limits on how precise a parameter, e.g. frequency or the
strength of a magnetic field, can be estimated with the aid of full and fast
quantum control. We consider uncorrelated noisy evolutions of N qubits and show
that fast control allows to fully restore the Heisenberg scaling (~1/N^2) for
all rank-one Pauli noise except dephasing. For all other types of noise the
asymptotic quantum enhancement is unavoidably limited to a constant-factor
improvement over the standard quantum limit (~1/N) even when allowing for the
full power of fast control. The latter holds both in the single-shot and
infinitely-many repetitions scenarios. However, even in this case allowing for
fast quantum control helps to increase the improvement factor. Furthermore, for
frequency estimation with finite resource we show how a parallel scheme
utilizing any fixed number of entangled qubits but no fast quantum control can
be outperformed by a simple, easily implementable, sequential scheme which only
requires entanglement between one sensing and one auxiliary qubit.Comment: 17 pages, 7 figures, 6 appendice
Nonlinearity Mitigation in WDM Systems: Models, Strategies, and Achievable Rates
After reviewing models and mitigation strategies for interchannel nonlinear
interference (NLI), we focus on the frequency-resolved logarithmic perturbation
model to study the coherence properties of NLI. Based on this study, we devise
an NLI mitigation strategy which exploits the synergic effect of phase and
polarization noise compensation (PPN) and subcarrier multiplexing with
symbol-rate optimization. This synergy persists even for high-order modulation
alphabets and Gaussian symbols. A particle method for the computation of the
resulting achievable information rate and spectral efficiency (SE) is presented
and employed to lower-bound the channel capacity. The dependence of the SE on
the link length, amplifier spacing, and presence or absence of inline
dispersion compensation is studied. Single-polarization and dual-polarization
scenarios with either independent or joint processing of the two polarizations
are considered. Numerical results show that, in links with ideal distributed
amplification, an SE gain of about 1 bit/s/Hz/polarization can be obtained (or,
in alternative, the system reach can be doubled at a given SE) with respect to
single-carrier systems without PPN mitigation. The gain is lower with lumped
amplification, increases with the number of spans, decreases with the span
length, and is further reduced by in-line dispersion compensation. For
instance, considering a dispersion-unmanaged link with lumped amplification and
an amplifier spacing of 60 km, the SE after 80 spans can be be increased from
4.5 to 4.8 bit/s/Hz/polarization, or the reach raised up to 100 spans (+25%)
for a fixed SE.Comment: Submitted to Journal of Lightwave Technolog
Updating and downdating techniques for optimizing network communicability
The total communicability of a network (or graph) is defined as the sum of
the entries in the exponential of the adjacency matrix of the network, possibly
normalized by the number of nodes. This quantity offers a good measure of how
easily information spreads across the network, and can be useful in the design
of networks having certain desirable properties. The total communicability can
be computed quickly even for large networks using techniques based on the
Lanczos algorithm.
In this work we introduce some heuristics that can be used to add, delete, or
rewire a limited number of edges in a given sparse network so that the modified
network has a large total communicability. To this end, we introduce new edge
centrality measures which can be used to guide in the selection of edges to be
added or removed.
Moreover, we show experimentally that the total communicability provides an
effective and easily computable measure of how "well-connected" a sparse
network is.Comment: 20 pages, 9 pages Supplementary Materia
Noisy Optimization: Convergence with a Fixed Number of Resamplings
It is known that evolution strategies in continuous domains might not
converge in the presence of noise. It is also known that, under mild
assumptions, and using an increasing number of resamplings, one can mitigate
the effect of additive noise and recover convergence. We show new sufficient
conditions for the convergence of an evolutionary algorithm with constant
number of resamplings; in particular, we get fast rates (log-linear
convergence) provided that the variance decreases around the optimum slightly
faster than in the so-called multiplicative noise model. Keywords: Noisy
optimization, evolutionary algorithm, theory.Comment: EvoStar (2014
Nonequilibrium entropic bounds for Darwinian replicators
Life evolved on our planet by means of a combination of Darwinian selection
and innovations leading to higher levels of complexity. The emergence and
selection of replicating entities is a central problem in prebiotic evolution.
Theoretical models have shown how populations of different types of replicating
entities exclude or coexist with other classes of replicators. Models are
typically kinetic, based on standard replicator equations. On the other hand,
the presence of thermodynamical constrains for these systems remain an open
question. This is largely due to the lack of a general theory of out of
statistical methods for systems far from equilibrium. Nonetheless, a first
approach to this problem has been put forward in a series of novel
developements in non-equilibrium physics, under the rubric of the extended
second law of thermodynamics. The work presented here is twofold: firstly, we
review this theoretical framework and provide a brief description of the three
fundamental replicator types in prebiotic evolution: parabolic, malthusian and
hyperbolic. Finally, we employ these previously mentioned techinques to explore
how replicators are constrained by thermodynamics.Comment: 12 Pages, 5 Figure
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