497,077 research outputs found
Trace Complexity of Chaotic Reversible Cellular Automata
Delvenne, K\r{u}rka and Blondel have defined new notions of computational
complexity for arbitrary symbolic systems, and shown examples of effective
systems that are computationally universal in this sense. The notion is defined
in terms of the trace function of the system, and aims to capture its dynamics.
We present a Devaney-chaotic reversible cellular automaton that is universal in
their sense, answering a question that they explicitly left open. We also
discuss some implications and limitations of the construction.Comment: 12 pages + 1 page appendix, 4 figures. Accepted to Reversible
Computation 2014 (proceedings published by Springer
Optimal query complexity for estimating the trace of a matrix
Given an implicit matrix with oracle access for any
, we study the query complexity of randomized algorithms for
estimating the trace of the matrix. This problem has many applications in
quantum physics, machine learning, and pattern matching. Two metrics are
commonly used for evaluating the estimators: i) variance; ii) a high
probability multiplicative-approximation guarantee. Almost all the known
estimators are of the form for being i.i.d. for some special distribution.
Our main results are summarized as follows. We give an exact characterization
of the minimum variance unbiased estimator in the broad class of linear
nonadaptive estimators (which subsumes all the existing known estimators). We
also consider the query complexity lower bounds for any (possibly nonlinear and
adaptive) estimators: (1) We show that any estimator requires
queries to have a guarantee of variance at most
. (2) We show that any estimator requires
queries to achieve a
-multiplicative approximation guarantee with probability at
least . Both above lower bounds are asymptotically tight.
As a corollary, we also resolve a conjecture in the seminal work of Avron and
Toledo (Journal of the ACM 2011) regarding the sample complexity of the
Gaussian Estimator.Comment: full version of the paper in ICALP 201
A program of research in environmental modeling
A theoretical framework for the interpretation of satellite measurements of stratospheric temperature and trace gases is provided. This problem is quite complicated since the distributions of trace gases are dependent on dynamics and photochemistry. Therefore, the problem was attacked with models employing varying degrees of photochemical and dynamical complexity. The relationship between dynamics and trace gas transport and wave transience, dissipation and critical levels and the net (permanent) transport of trace gases, the role of photochemistry in trace gas transport, photochemistry and dynamics and altering the mean-zonal distribution of stratospheric ozone, and approximations to simplify the interpretation of observations and General Circulation Models are discussed
Object identification by using orthonormal circus functions from the trace transform
In this paper we present an efficient way to both compute and extract salient information from trace transform signatures to perform object identification tasks. We also present a feature selection analysis of the classical trace-transform functionals, which reveals that most of them retrieve redundant information causing misleading similarity measurements. In order to overcome this problem, we propose a set of functionals based on Laguerre polynomials that return orthonormal signatures between these functionals. In this way, each signature provides salient and non-correlated information that contributes to the description of an image object. The proposed functionals were tested considering a vehicle identification problem, outperforming the classical trace transform functionals in terms of computational complexity and identification rate
Linear and Branching System Metrics
We extend the classical system relations of trace\ud
inclusion, trace equivalence, simulation, and bisimulation to a quantitative setting in which propositions are interpreted not as boolean values, but as elements of arbitrary metric spaces.\ud
\ud
Trace inclusion and equivalence give rise to asymmetrical and symmetrical linear distances, while simulation and bisimulation give rise to asymmetrical and symmetrical branching distances. We study the relationships among these distances, and we provide a full logical characterization of the distances in terms of quantitative versions of LTL and μ-calculus. We show that, while trace inclusion (resp. equivalence) coincides with simulation (resp. bisimulation) for deterministic boolean transition systems, linear\ud
and branching distances do not coincide for deterministic metric transition systems. Finally, we provide algorithms for computing the distances over finite systems, together with a matching lower complexity bound
On polyhedral approximations of the positive semidefinite cone
Let be the set of positive semidefinite matrices of trace
equal to one, also known as the set of density matrices. We prove two results
on the hardness of approximating with polytopes. First, we show that if and is an arbitrary matrix of trace equal to one, any
polytope such that must have
linear programming extension complexity at least where is a constant that depends on . Second, we show that any polytope
such that and such that the Gaussian width of is at most
twice the Gaussian width of must have extension complexity at least
. The main ingredient of our proofs is hypercontractivity of
the noise operator on the hypercube.Comment: 12 page
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