546 research outputs found
Educational Magic Tricks Based on Error-Detection Schemes
Magic tricks based on computer science concepts help grab student attention and can motivate them to delve more deeply. Error detection ideas long used by computer scientists provide a rich basis for working magic; probably the most well known trick of this type is one included in the CS Unplugged activities. This paper shows that much more powerful variations of the trick can be performed, some in an unplugged environment and some with computer assistance. Some of the tricks also show off additional concepts in computer science and discrete mathematics
Rapid Measurement of Quantum Systems using Feedback Control
We introduce a feedback control algorithm that increases the speed at which a
measurement extracts information about a -dimensional system by a factor
that scales as . Generalizing this algorithm, we apply it to a register of
qubits and show an improvement O(n). We derive analytical bounds on the
benefit provided by the feedback and perform simulations that confirm that this
speedup is achieved.Comment: 4 pages, 4 figures. V2: Minor correction
Numerical Analysis of Boosting Scheme for Scalable NMR Quantum Computation
Among initialization schemes for ensemble quantum computation beginning at
thermal equilibrium, the scheme proposed by Schulman and Vazirani [L. J.
Schulman and U. V. Vazirani, in Proceedings of the 31st ACM Symposium on Theory
of Computing (STOC'99) (ACM Press, New York, 1999), pp. 322-329] is known for
the simple quantum circuit to redistribute the biases (polarizations) of qubits
and small time complexity. However, our numerical simulation shows that the
number of qubits initialized by the scheme is rather smaller than expected from
the von Neumann entropy because of an increase in the sum of the binary
entropies of individual qubits, which indicates a growth in the total classical
correlation. This result--namely, that there is such a significant growth in
the total binary entropy--disagrees with that of their analysis.Comment: 14 pages, 18 figures, RevTeX4, v2,v3: typos corrected, v4: minor
changes in PROGRAM 1, conforming it to the actual programs used in the
simulation, v5: correction of a typographical error in the inequality sign in
PROGRAM 1, v6: this version contains a new section on classical correlations,
v7: correction of a wrong use of terminology, v8: Appendix A has been added,
v9: published in PR
Trajectory generation for road vehicle obstacle avoidance using convex optimization
This paper presents a method for trajectory generation using convex optimization to find a feasible, obstacle-free path for a road vehicle. Consideration of vehicle rotation is shown to be necessary if the trajectory is to avoid obstacles specified in a fixed Earth axis system. The paper establishes that, despite the presence of significant non-linearities, it is possible to articulate the obstacle avoidance problem in a tractable convex form using multiple optimization passes. Finally, it is shown by simulation that an optimal trajectory that accounts for the vehicle’s changing velocity throughout the manoeuvre is superior to a previous analytical method that assumes constant speed
Ordered Measurements of Permutationally-Symmetric Qubit Strings
We show that any sequence of measurements on a permutationally-symmetric
(pure or mixed) multi-qubit string leaves the unmeasured qubit substring also
permutationally-symmetric. In addition, we show that the measurement
probabilities for an arbitrary sequence of single-qubit measurements are
independent of how many unmeasured qubits have been lost prior to the
measurement. Our results are valuable for quantum information processing of
indistinguishable particles by post-selection, e.g. in cases where the results
of an experiment are discarded conditioned upon the occurrence of a given event
such as particle loss. Furthermore, our results are important for the design of
adaptive-measurement strategies, e.g. a series of measurements where for each
measurement instance, the measurement basis is chosen depending on prior
measurement results.Comment: 13 page
A generalization of Hausdorff dimension applied to Hilbert cubes and Wasserstein spaces
A Wasserstein spaces is a metric space of sufficiently concentrated
probability measures over a general metric space. The main goal of this paper
is to estimate the largeness of Wasserstein spaces, in a sense to be precised.
In a first part, we generalize the Hausdorff dimension by defining a family of
bi-Lipschitz invariants, called critical parameters, that measure largeness for
infinite-dimensional metric spaces. Basic properties of these invariants are
given, and they are estimated for a naturel set of spaces generalizing the
usual Hilbert cube. In a second part, we estimate the value of these new
invariants in the case of some Wasserstein spaces, as well as the dynamical
complexity of push-forward maps. The lower bounds rely on several embedding
results; for example we provide bi-Lipschitz embeddings of all powers of any
space inside its Wasserstein space, with uniform bound and we prove that the
Wasserstein space of a d-manifold has "power-exponential" critical parameter
equal to d.Comment: v2 Largely expanded version, as reflected by the change of title; all
part I on generalized Hausdorff dimension is new, as well as the embedding of
Hilbert cubes into Wasserstein spaces. v3 modified according to the referee
final remarks ; to appear in Journal of Topology and Analysi
Evaluating implicit feedback models using searcher simulations
In this article we describe an evaluation of relevance feedback (RF) algorithms using searcher simulations. Since these algorithms select additional terms for query modification based on inferences made from searcher interaction, not on relevance information searchers explicitly provide (as in traditional RF), we refer to them as implicit feedback models. We introduce six different models that base their decisions on the interactions of searchers and use different approaches to rank query modification terms. The aim of this article is to determine which of these models should be used to assist searchers in the systems we develop. To evaluate these models we used searcher simulations that afforded us more control over the experimental conditions than experiments with human subjects and allowed complex interaction to be modeled without the need for costly human experimentation. The simulation-based evaluation methodology measures how well the models learn the distribution of terms across relevant documents (i.e., learn what information is relevant) and how well they improve search effectiveness (i.e., create effective search queries). Our findings show that an implicit feedback model based on Jeffrey's rule of conditioning outperformed other models under investigation
Algorithm to estimate the Hurst exponent of high-dimensional fractals
We propose an algorithm to estimate the Hurst exponent of high-dimensional
fractals, based on a generalized high-dimensional variance around a moving
average low-pass filter. As working examples, we consider rough surfaces
generated by the Random Midpoint Displacement and by the Cholesky-Levinson
Factorization algorithms. The surrogate surfaces have Hurst exponents ranging
from 0.1 to 0.9 with step 0.1, and different sizes. The computational
efficiency and the accuracy of the algorithm are also discussed
Spectral Simplicity of Apparent Complexity, Part I: The Nondiagonalizable Metadynamics of Prediction
Virtually all questions that one can ask about the behavioral and structural
complexity of a stochastic process reduce to a linear algebraic framing of a
time evolution governed by an appropriate hidden-Markov process generator. Each
type of question---correlation, predictability, predictive cost, observer
synchronization, and the like---induces a distinct generator class. Answers are
then functions of the class-appropriate transition dynamic. Unfortunately,
these dynamics are generically nonnormal, nondiagonalizable, singular, and so
on. Tractably analyzing these dynamics relies on adapting the recently
introduced meromorphic functional calculus, which specifies the spectral
decomposition of functions of nondiagonalizable linear operators, even when the
function poles and zeros coincide with the operator's spectrum. Along the way,
we establish special properties of the projection operators that demonstrate
how they capture the organization of subprocesses within a complex system.
Circumventing the spurious infinities of alternative calculi, this leads in the
sequel, Part II, to the first closed-form expressions for complexity measures,
couched either in terms of the Drazin inverse (negative-one power of a singular
operator) or the eigenvalues and projection operators of the appropriate
transition dynamic.Comment: 24 pages, 3 figures, 4 tables; current version always at
http://csc.ucdavis.edu/~cmg/compmech/pubs/sdscpt1.ht
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