561 research outputs found
Entanglement, decoherence and thermal relaxation in exactly solvable models
Exactly solvable models provide an opportunity to study different aspects of
reduced quantum dynamics in detail. We consider the reduced dynamics of a
single spin in finite XX and XY spin 1/2 chains. First we introduce a general
expression describing the evolution of the reduced density matrix. This
expression proves to be tractable when the combined closed system (i.e. open
system plus environment) is integrable. Then we focus on comparing decoherence
and thermalization timescales in the XX chain. We find that for a single spin
these timescales are comparable, in contrast to what should be expected for a
macroscopic body. This indicates that the process of quantum relaxation of a
system with few accessible states can not be separated in two distinct stages -
decoherence and thermalization. Finally, we turn to finite-size effects in the
time evolution of a single spin in the XY chain. We observe three consecutive
stages of the evolution: regular evolution, partial revivals, irregular
(apparently chaotic) evolution. The duration of the regular stage is
proportional to the number of spins in the chain. We observe a "quiet and cold
period" in the end of the regular stage, which breaks up abruptly at some
threshold time.Comment: talk at the Fifth International Workshop DICE-2010, Castiglioncello
(Italy), September 13-1
Quickest Online Selection of an Increasing Subsequence of Specified Size
Given a sequence of independent random variables with a common continuous
distribution, we consider the online decision problem where one seeks to
minimize the expected value of the time that is needed to complete the
selection of a monotone increasing subsequence of a prespecified length .
This problem is dual to some online decision problems that have been considered
earlier, and this dual problem has some notable advantages. In particular, the
recursions and equations of optimality lead with relative ease to asymptotic
formulas for mean and variance of the minimal selection time.Comment: 17 page
Reconstruction of Random Colourings
Reconstruction problems have been studied in a number of contexts including
biology, information theory and and statistical physics. We consider the
reconstruction problem for random -colourings on the -ary tree for
large . Bhatnagar et. al. showed non-reconstruction when and reconstruction when . We tighten this result and show non-reconstruction when and reconstruction when .Comment: Added references, updated notatio
A New Look at Survey Propagation and Its Generalizations
This article provides a new conceptual perspective on survey propagation, which is an iterative algorithm recently introduced by the statistical physics community that is very effective in solving random k-SAT problems even with densities close to the satisfiability threshold. We first describe how any SAT formula can be associated with a novel family of Markov random fields (MRFs), parameterized by a real number Ï â [0, 1]. We then show that applying belief propagation---a well-known âmessage-passingâ technique for estimating marginal probabilities---to this family of MRFs recovers a known family of algorithms, ranging from pure survey propagation at one extreme (Ï = 1) to standard belief propagation on the uniform distribution over SAT assignments at the other extreme (Ï = 0). Configurations in these MRFs have a natural interpretation as partial satisfiability assignments, on which a partial order can be defined. We isolate cores as minimal elements in this partial ordering, which are also fixed points of survey propagation and the only assignments with positive probability in the MRF for Ï = 1. Our experimental results for k = 3 suggest that solutions of random formulas typically do not possess non-trivial cores. This makes it necessary to study the structure of the space of partial assignments for Ï \u3c 1 and investigate the role of assignments that are very close to being cores. To that end, we investigate the associated lattice structure, and prove a weight-preserving identity that shows how any MRF with Ï \u3e 0 can be viewed as a âsmoothedâ version of the uniform distribution over satisfying assignments (Ï = 0). Finally, we isolate properties of Gibbs sampling and message-passing algorithms that are typical for an ensemble of k-SAT problems
Circular Networks from Distorted Metrics
Trees have long been used as a graphical representation of species
relationships. However complex evolutionary events, such as genetic
reassortments or hybrid speciations which occur commonly in viruses, bacteria
and plants, do not fit into this elementary framework. Alternatively, various
network representations have been developed. Circular networks are a natural
generalization of leaf-labeled trees interpreted as split systems, that is,
collections of bipartitions over leaf labels corresponding to current species.
Although such networks do not explicitly model specific evolutionary events of
interest, their straightforward visualization and fast reconstruction have made
them a popular exploratory tool to detect network-like evolution in genetic
datasets.
Standard reconstruction methods for circular networks, such as Neighbor-Net,
rely on an associated metric on the species set. Such a metric is first
estimated from DNA sequences, which leads to a key difficulty: distantly
related sequences produce statistically unreliable estimates. This is
problematic for Neighbor-Net as it is based on the popular tree reconstruction
method Neighbor-Joining, whose sensitivity to distance estimation errors is
well established theoretically. In the tree case, more robust reconstruction
methods have been developed using the notion of a distorted metric, which
captures the dependence of the error in the distance through a radius of
accuracy. Here we design the first circular network reconstruction method based
on distorted metrics. Our method is computationally efficient. Moreover, the
analysis of its radius of accuracy highlights the important role played by the
maximum incompatibility, a measure of the extent to which the network differs
from a tree.Comment: Submitte
Harnessing the Bethe Free Energy
Gibbs measures induced by random factor graphs play a prominent role in computer science, combinatorics and physics. A key problem is to calculate the typical value of the partition function. According to the "replica symmetric cavity method", a heuristic that rests on non-rigorous considerations from statistical mechanics, in many cases this problem can be tackled by way of maximising a functional called the "Bethe free energy". In this paper we prove that the Bethe free energy upper-bounds the partition function in a broad class of models. Additionally, we provide a sufficient condition for this upper bound to be tight
Sorting and Selection in Posets
Classical problems of sorting and searching assume an underlying linear ordering of the objects being compared. In this paper, we study these problems in the context of partially ordered sets, in which some pairs of objects are incomparable. This generalization is interesting from a combinatorial perspective, and it has immediate applications in ranking scenarios where there is no underlying linear ordering, e.g., conference submissions. It also has applications in reconstructing certain types of networks, including biological networks. Our results represent significant progress over previous results from two decades ago by Faigle and TurĂĄn. In particular, we present the first algorithm that sorts a width-w poset of size n with query complexity O(n(w+\log n)) and prove that this query complexity is asymptotically optimal. We also describe a variant of Mergesort with query complexity O(wn log n/w) and total complexity O(w2n log n/w); an algorithm with the same query complexity was given by Faigle and TurĂĄn, but no efficient implementation of that algorithm is known. Both our sorting algorithms can be applied with negligible overhead to the more general problem of reconstructing transitive relations. We also consider two related problems: finding the minimal elements, and its generalization to finding the bottom k âlevels,â called the k-selection problem. We give efficient deterministic and randomized algorithms for finding the minimal elements with query complexity and total complexity O(wn). We provide matching lower bounds for the query complexity up to a factor of 2 and generalize the results to the k-selection problem. Finally, we present efficient algorithms for computing a linear extension of a poset and computing the heights of all elements
Cake Cutting Algorithms for Piecewise Constant and Piecewise Uniform Valuations
Cake cutting is one of the most fundamental settings in fair division and
mechanism design without money. In this paper, we consider different levels of
three fundamental goals in cake cutting: fairness, Pareto optimality, and
strategyproofness. In particular, we present robust versions of envy-freeness
and proportionality that are not only stronger than their standard
counter-parts but also have less information requirements. We then focus on
cake cutting with piecewise constant valuations and present three desirable
algorithms: CCEA (Controlled Cake Eating Algorithm), MEA (Market Equilibrium
Algorithm) and CSD (Constrained Serial Dictatorship). CCEA is polynomial-time,
robust envy-free, and non-wasteful. It relies on parametric network flows and
recent generalizations of the probabilistic serial algorithm. For the subdomain
of piecewise uniform valuations, we show that it is also group-strategyproof.
Then, we show that there exists an algorithm (MEA) that is polynomial-time,
envy-free, proportional, and Pareto optimal. MEA is based on computing a
market-based equilibrium via a convex program and relies on the results of
Reijnierse and Potters [24] and Devanur et al. [15]. Moreover, we show that MEA
and CCEA are equivalent to mechanism 1 of Chen et. al. [12] for piecewise
uniform valuations. We then present an algorithm CSD and a way to implement it
via randomization that satisfies strategyproofness in expectation, robust
proportionality, and unanimity for piecewise constant valuations. For the case
of two agents, it is robust envy-free, robust proportional, strategyproof, and
polynomial-time. Many of our results extend to more general settings in cake
cutting that allow for variable claims and initial endowments. We also show a
few impossibility results to complement our algorithms.Comment: 39 page
- âŠ