45 research outputs found
Positive contraction mappings for classical and quantum Schrodinger systems
The classical Schrodinger bridge seeks the most likely probability law for a
diffusion process, in path space, that matches marginals at two end points in
time; the likelihood is quantified by the relative entropy between the sought
law and a prior, and the law dictates a controlled path that abides by the
specified marginals. Schrodinger proved that the optimal steering of the
density between the two end points is effected by a multiplicative functional
transformation of the prior; this transformation represents an automorphism on
the space of probability measures and has since been studied by Fortet,
Beurling and others. A similar question can be raised for processes evolving in
a discrete time and space as well as for processes defined over non-commutative
probability spaces. The present paper builds on earlier work by Pavon and
Ticozzi and begins with the problem of steering a Markov chain between given
marginals. Our approach is based on the Hilbert metric and leads to an
alternative proof which, however, is constructive. More specifically, we show
that the solution to the Schrodinger bridge is provided by the fixed point of a
contractive map. We approach in a similar manner the steering of a quantum
system across a quantum channel. We are able to establish existence of quantum
transitions that are multiplicative functional transformations of a given Kraus
map, but only for the case of uniform marginals. As in the Markov chain case,
and for uniform density matrices, the solution of the quantum bridge can be
constructed from the fixed point of a certain contractive map. For arbitrary
marginal densities, extensive numerical simulations indicate that iteration of
a similar map leads to fixed points from which we can construct a quantum
bridge. For this general case, however, a proof of convergence remains elusive.Comment: 27 page
Anisotropic Strain Induced Soliton Movement Changes Stacking Order and Bandstructure of Graphene Multilayers
The crystal structure of solid-state matter greatly affects its electronic
properties. For example in multilayer graphene, precise knowledge of the
lateral layer arrangement is crucial, since the most stable configurations,
Bernal and rhombohedral stacking, exhibit very different electronic properties.
Nevertheless, both stacking orders can coexist within one flake, separated by a
strain soliton that can host topologically protected states. Clearly, accessing
the transport properties of the two stackings and the soliton is of high
interest. However, the stacking orders can transform into one another and
therefore, the seemingly trivial question how reliable electrical contact can
be made to either stacking order can a priori not be answered easily. Here, we
show that manufacturing metal contacts to multilayer graphene can move solitons
by several m, unidirectionally enlarging Bernal domains due to arising
mechanical strain. Furthermore, we also find that during dry transfer of
multilayer graphene onto hexagonal Boron Nitride, such a transformation can
happen. Using density functional theory modeling, we corroborate that
anisotropic deformations of the multilayer graphene lattice decrease the
rhombohedral stacking stability. Finally, we have devised systematics to avoid
soliton movement, and how to reliably realize contacts to both stacking
configurations
Discrete-time classical and quantum Markovian evolutions: Maximum entropy problems on path space
The theory of Schroedinger bridges for diffusion processes is extended to
classical and quantum discrete-time Markovian evolutions. The solution of the
path space maximum entropy problems is obtained from the a priori model in both
cases via a suitable multiplicative functional transformation. In the quantum
case, nonequilibrium time reversal of quantum channels is discussed and
space-time harmonic processes are introduced.Comment: 34 page
Resistance training preserves bone in vegans
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Doob-Martin boundary of RĂ©my's tree growth chain
RĂ©my's algorithm is a Markov chain that iteratively generates a sequence of random trees in such a way that the nth tree is uniformly distributed over the set of rooted, planar, binary trees with 2n + 1 vertices. We obtain a concrete characterization of the Doob-Martin boundary of this transient Markov chain and thereby delineate all the ways in which, loosely speaking, this process can be conditioned to "go to infinity" at large times. A (deterministic) sequence of finite rooted, planar, binary trees converges to a point in the boundary if for each m the random rooted, planar, binary tree spanned by m + 1 leaves chosen uniformly at random from the nth tree in the sequence converges in distribution as n tends to infinity-a notion of convergence that is analogous to one that appears in the recently developed theory of graph limits. We show that a point in the Doob-Martin boundary may be identified with the following ensemble of objects: a complete separable â-tree that is rooted and binary in a suitable sense, a diffuse probability measure on the R-tree that allows us to make sense of sampling points from it, and a kernel on the R-tree that describes the probability that the first of a given pair of points is below and to the left of their most recent common ancestor while the second is below and to the right. Two such ensembles represent the same point in the boundary if for each m the random, rooted, planar, binary trees spanned by m + 1 independent points chosen according to the respective probability measures have the same distribution. Also, the Doob-Martin boundary corresponds bijectively to the set of extreme point of the closed convex set of nonnegative harmonic functions that take the value 1 at the binary tree with 3 vertices; in other words, the minimal and full Doob-Martin boundaries coincide. These results are in the spirit of the identification of graphons as limit objects in the theory of graph limits
Self-reported resistance training is associated with better bone microarchitecture in vegans
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Doob-Martin boundary of RĂ©my's tree growth chain
RĂ©my's algorithm is a Markov chain that iteratively generates a sequence of random trees in such a way that the nth tree is uniformly distributed over the set of rooted, planar, binary trees with 2n + 1 vertices. We obtain a concrete characterization of the Doob-Martin boundary of this transient Markov chain and thereby delineate all the ways in which, loosely speaking, this process can be conditioned to "go to infinity" at large times. A (deterministic) sequence of finite rooted, planar, binary trees converges to a point in the boundary if for each m the random rooted, planar, binary tree spanned by m + 1 leaves chosen uniformly at random from the nth tree in the sequence converges in distribution as n tends to infinity-a notion of convergence that is analogous to one that appears in the recently developed theory of graph limits. We show that a point in the Doob-Martin boundary may be identified with the following ensemble of objects: a complete separable â-tree that is rooted and binary in a suitable sense, a diffuse probability measure on the R-tree that allows us to make sense of sampling points from it, and a kernel on the R-tree that describes the probability that the first of a given pair of points is below and to the left of their most recent common ancestor while the second is below and to the right. Two such ensembles represent the same point in the boundary if for each m the random, rooted, planar, binary trees spanned by m + 1 independent points chosen according to the respective probability measures have the same distribution. Also, the Doob-Martin boundary corresponds bijectively to the set of extreme point of the closed convex set of nonnegative harmonic functions that take the value 1 at the binary tree with 3 vertices; in other words, the minimal and full Doob-Martin boundaries coincide. These results are in the spirit of the identification of graphons as limit objects in the theory of graph limits
Self-reported resistance training is associated with better bone microarchitecture in vegans
supplementary filesTHIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV