33 research outputs found
The information entropy of quantum mechanical states
It is well known that a Shannon based definition of information entropy leads
in the classical case to the Boltzmann entropy. It is tempting to regard the
Von Neumann entropy as the corresponding quantum mechanical definition. But the
latter is problematic from quantum information point of view. Consequently we
introduce a new definition of entropy that reflects the inherent uncertainty of
quantum mechanical states. We derive for it an explicit expression, and discuss
some of its general properties. We distinguish between the minimum uncertainty
entropy of pure states, and the excess statistical entropy of mixtures.Comment: 7 pages, 1 figur
Longest Increasing Subsequence under Persistent Comparison Errors
We study the problem of computing a longest increasing subsequence in a
sequence of distinct elements in the presence of persistent comparison
errors. In this model, every comparison between two elements can return the
wrong result with some fixed (small) probability , and comparisons cannot
be repeated. Computing the longest increasing subsequence exactly is impossible
in this model, therefore, the objective is to identify a subsequence that (i)
is indeed increasing and (ii) has a length that approximates the length of the
longest increasing subsequence.
We present asymptotically tight upper and lower bounds on both the
approximation factor and the running time. In particular, we present an
algorithm that computes an -approximation in time , with
high probability. This approximation relies on the fact that that we can
approximately sort elements in time such that the maximum
dislocation of an element is at most . For the lower bounds, we
prove that (i) there is a set of sequences, such that on a sequence picked
randomly from this set every algorithm must return an -approximation with high probability, and (ii) any -approximation
algorithm for longest increasing subsequence requires
comparisons, even in the absence of errors
Spacelike distance from discrete causal order
Any discrete approach to quantum gravity must provide some prescription as to
how to deduce continuum properties from the discrete substructure. In the
causal set approach it is straightforward to deduce timelike distances, but
surprisingly difficult to extract spacelike distances, because of the unique
combination of discreteness with local Lorentz invariance in that approach. We
propose a number of methods to overcome this difficulty, one of which
reproduces the spatial distance between two points in a finite region of
Minkowski space. We provide numerical evidence that this definition can be used
to define a `spatial nearest neighbor' relation on a causal set, and conjecture
that this can be exploited to define the length of `continuous curves' in
causal sets which are approximated by curved spacetime. This provides evidence
in support of the ``Hauptvermutung'' of causal sets.Comment: 32 pages, 16 figures, revtex4; journal versio
Emergence of spatial structure from causal sets
There are numerous indications that a discrete substratum underlies continuum
spacetime. Any fundamentally discrete approach to quantum gravity must provide
some prescription for how continuum properties emerge from the underlying
discreteness. The causal set approach, in which the fundamental relation is
based upon causality, finds it easy to reproduce timelike distances, but has a
more difficult time with spatial distance, due to the unique combination of
Lorentz invariance and discreteness within that approach. We describe a method
to deduce spatial distances from a causal set. In addition, we sketch how one
might use an important ingredient in deducing spatial distance, the `-link',
to deduce whether a given causal set is likely to faithfully embed into a
continuum spacetime.Comment: 21 pages, 21 figures; proceedings contribution for DICE 2008, to
appear in Journal of Physics: Conference Serie
Homogenization via formal multiscale asymptotics and volume averaging: How do the two techniques compare?
A wide variety of techniques have been developed to homogenize transport equations in multiscale and multiphase systems. This has yielded a rich and diverse field, but has also resulted in the emergence of isolated scientific communities and disconnected bodies of literature. Here, our goal is to bridge the gap between formal multiscale asymptotics and the volume averaging theory. We illustrate the methodologies via a simple example application describing a parabolic transport problem and, in so doing, compare their respective advantages/disadvantages from a practical point of view. This paper is also intended as a pedagogical guide and may be viewed as a tutorial for graduate students as we provide historical context, detail subtle points with great care, and reference many fundamental works