title: Bayesian Prediction for Artificial Intelligence

abstract:
  This paper shows that the common method used for making predictions under
uncertainty in A1 and science is in error. This method is to use currently
available data to select the best model from a given class of models-this
process is called abduction-and then to use this model to make predictions
about future data. The correct method requires averaging over all the models to
make a prediction-we call this method transduction. Using transduction, an AI
system will not give misleading results when basing predictions on small
amounts of data, when no model is clearly best. For common classes of models we
show that the optimal solution can be given in closed form.


title: Can Evidence Be Combined in the Dempster-Shafer Theory

abstract:
  Dempster's rule of combination has been the most controversial part of the
Dempster-Shafer (D-S) theory. In particular, Zadeh has reached a conjecture on
the noncombinability of evidence from a relational model of the D-S theory. In
this paper, we will describe another relational model where D-S masses are
represented as conditional granular distributions. By comparing it with Zadeh's
relational model, we will show how Zadeh's conjecture on combinability does not
affect the applicability of Dempster's rule in our model.


title:
An Interesting Uncertainty-Based Combinatoric Problem in Spare Parts
  Forecasting: The FRED System

abstract:
  The domain of spare parts forecasting is examined, and is found to present
unique uncertainty based problems in the architectural design of a
knowledge-based system. A mixture of different uncertainty paradigms is
required for the solution, with an intriguing combinatoric problem arising from
an uncertain choice of inference engines. Thus, uncertainty in the system is
manifested in two different meta-levels. The different uncertainty paradigms
and meta-levels must be integrated into a functioning whole. FRED is an example
of a difficult real-world domain to which no existing uncertainty approach is
completely appropriate. This paper discusses the architecture of FRED,
highlighting: the points of uncertainty and other interesting features of the
domain, the specific implications of those features on the system design
(including the combinatoric explosions), their current implementation & future
plans,and other problems and issues with the architecture.


title: Bayesian Inference in Model-Based Machine Vision

abstract:
  This is a preliminary version of visual interpretation integrating multiple
sensors in SUCCESSOR, an intelligent, model-based vision system. We pursue a
thorough integration of hierarchical Bayesian inference with comprehensive
physical representation of objects and their relations in a system for
reasoning with geometry, surface materials and sensor models in machine vision.
Bayesian inference provides a framework for accruing_ probabilities to rank
order hypotheses.


title: Using the Dempster-Shafer Scheme in a Diagnostic Expert System Shell

abstract:
  This paper discusses an expert system shell that integrates rule-based
reasoning and the Dempster-Shafer evidence combination scheme. Domain knowledge
is stored as rules with associated belief functions. The reasoning component
uses a combination of forward and backward inferencing mechanisms to allow
interaction with users in a mixed-initiative format.


title: Stochastic Simulation of Bayesian Belief Networks

abstract:
  This paper examines Bayesian belief network inference using simulation as a
method for computing the posterior probabilities of network variables.
Specifically, it examines the use of a method described by Henrion, called
logic sampling, and a method described by Pearl, called stochastic simulation.
We first review the conditions under which logic sampling is computationally
infeasible. Such cases motivated the development of the Pearl's stochastic
simulation algorithm. We have found that this stochastic simulation algorithm,
when applied to certain networks, leads to much slower than expected
convergence to the true posterior probabilities. This behavior is a result of
the tendency for local areas in the network to become fixed through many
simulation cycles. The time required to obtain significant convergence can be
made arbitrarily long by strengthening the probabilistic dependency between
nodes. We propose the use of several forms of graph modification, such as graph
pruning, arc reversal, and node reduction, in order to convert some networks
into formats that are computationally more efficient for simulation.


title: Temporal Reasoning About Uncertain Worlds

abstract:
  We present a program that manages a database of temporally scoped beliefs.
The basic functionality of the system includes maintaining a network of
constraints among time points, supporting a variety of fetches, mediating the
application of causal rules, monitoring intervals of time for the addition of
new facts, and managing data dependencies that keep the database consistent. At
this level the system operates independent of any measure of belief or belief
calculus. We provide an example of how an application program mi9ght use this
functionality to implement a belief calculus.


title:
A Perspective on Confidence and Its Use in Focusing Attention During
  Knowledge Acquisition

abstract:
  We present a representation of partial confidence in belief and preference
that is consistent with the tenets of decision-theory. The fundamental insight
underlying the representation is that if a person is not completely confident
in a probability or utility assessment, additional modeling of the assessment
may improve decisions to which it is relevant. We show how a traditional
decision-analytic approach can be used to balance the benefits of additional
modeling with associated costs. The approach can be used during knowledge
acquisition to focus the attention of a knowledge engineer or expert on parts
of a decision model that deserve additional refinement.


title: Practical Issues in Constructing a Bayes' Belief Network

abstract:
  Bayes belief networks and influence diagrams are tools for constructing
coherent probabilistic representations of uncertain knowledge. The process of
constructing such a network to represent an expert's knowledge is used to
illustrate a variety of techniques which can facilitate the process of
structuring and quantifying uncertain relationships. These include some
generalizations of the "noisy OR gate" concept. Sensitivity analysis of generic
elements of Bayes' networks provides insight into when rough probability
assessments are sufficient and when greater precision may be important.


title:
NAIVE: A Method for Representing Uncertainty and Temporal Relationships
  in an Automated Reasoner

abstract:
  This paper describes NAIVE, a low-level knowledge representation language and
inferencing process. NAIVE has been designed for reasoning about
nondeterministic dynamic systems like those found in medicine. Knowledge is
represented in a graph structure consisting of nodes, which correspond to the
variables describing the system of interest, and arcs, which correspond to the
procedures used to infer the value of a variable from the values of other
variables. The value of a variable can be determined at an instant in time,
over a time interval or for a series of times. Information about the value of a
variable is expressed as a probability density function which quantifies the
likelihood of each possible value. The inferencing process uses these
probability density functions to propagate uncertainty. NAIVE has been used to
develop medical knowledge bases including over 100 variables.


title: Objective Probability

abstract:
  A distinction is sometimes made between "statistical" and "subjective"
probabilities. This is based on a distinction between "unique" events and
"repeatable" events. We argue that this distinction is untenable, since all
events are "unique" and all events belong to "kinds", and offer a conception of
probability for A1 in which (1) all probabilities are based on -- possibly
vague -- statistical knowledge, and (2) every statement in the language has a
probability. This conception of probability can be applied to very rich
languages.


title: Coefficients of Relations for Probabilistic Reasoning

abstract:
  Definitions and notations with historical references are given for some
numerical coefficients commonly used to quantify relations among collections of
objects for the purpose of expressing approximate knowledge and probabilistic
reasoning.


title: Satisfaction of Assumptions is a Weak Predictor of Performance

abstract:
  This paper demonstrates a methodology for examining the accuracy of uncertain
inference systems (UIS), after their parameters have been optimized, and does
so for several common UIS's. This methodology may be used to test the accuracy
when either the prior assumptions or updating formulae are not exactly
satisfied. Surprisingly, these UIS's were revealed to be no more accurate on
the average than a simple linear regression. Moreover, even on prior
distributions which were deliberately biased so as give very good accuracy,
they were less accurate than the simple probabilistic model which assumes
marginal independence between inputs. This demonstrates that the importance of
updating formulae can outweigh that of prior assumptions. Thus, when UIS's are
judged by their final accuracy after optimization, we get completely different
results than when they are judged by whether or not their prior assumptions are
perfectly satisfied.


title: Structuring Causal Tree Models with Continuous Variables

abstract:
  This paper considers the problem of invoking auxiliary, unobservable
variables to facilitate the structuring of causal tree models for a given set
of continuous variables. Paralleling the treatment of bi-valued variables in
[Pearl 1986], we show that if a collection of coupled variables are governed by
a joint normal distribution and a tree-structured representation exists, then
both the topology and all internal relationships of the tree can be uncovered
by observing pairwise dependencies among the observed variables (i.e., the
leaves of the tree). Furthermore, the conditions for normally distributed
variables are less restrictive than those governing bi-valued variables. The
result extends the applications of causal tree models which were found useful
in evidential reasoning tasks.


title: Implementing Evidential Reasoning in Expert Systems

abstract:
  The Dempster-Shafer theory has been extended recently for its application to
expert systems. However, implementing the extended D-S reasoning model in
rule-based systems greatly complicates the task of generating informative
explanations. By implementing GERTIS, a prototype system for diagnosing
rheumatoid arthritis, we show that two kinds of knowledge are essential for
explanation generation: (l) taxonomic class relationships between hypotheses
and (2) pointers to the rules that significantly contribute to belief in the
hypothesis. As a result, the knowledge represented in GERTIS is richer and more
complex than that of conventional rule-based systems. GERTIS not only
demonstrates the feasibility of rule-based evidential-reasoning systems, but
also suggests ways to generate better explanations, and to explicitly represent
various useful relationships among hypotheses and rules.


title: Decision Tree Induction Systems: A Bayesian Analysis

abstract:
  Decision tree induction systems are being used for knowledge acquisition in
noisy domains. This paper develops a subjective Bayesian interpretation of the
task tackled by these systems and the heuristic methods they use. It is argued
that decision tree systems implicitly incorporate a prior belief that the
simpler (in terms of decision tree complexity) of two hypotheses be preferred,
all else being equal, and that they perform a greedy search of the space of
decision rules to find one in which there is strong posterior belief. A number
of improvements to these systems are then suggested.


title:
The Automatic Training of Rule Bases that Use Numerical Uncertainty
  Representations

abstract:
  The use of numerical uncertainty representations allows better modeling of
some aspects of human evidential reasoning. It also makes knowledge acquisition
and system development, test, and modification more difficult. We propose that
where possible, the assignment and/or refinement of rule weights should be
performed automatically. We present one approach to performing this training -
numerical optimization - and report on the results of some preliminary tests in
training rule bases. We also show that truth maintenance can be used to make
training more efficient and ask some epistemological questions raised by
training rule weights.


title: The Inductive Logic of Information Systems

abstract:
  An inductive logic can be formulated in which the elements are not
propositions or probability distributions, but information systems. The logic
is complete for information systems with binary hypotheses, i.e., it applies to
all such systems. It is not complete for information systems with more than two
hypotheses, but applies to a subset of such systems. The logic is inductive in
that conclusions are more informative than premises. Inferences using the
formalism have a strong justification in terms of the expected value of the
derived information system.


title:
Automated Generation of Connectionist Expert Systems for Problems
  Involving Noise and Redundancy

abstract:
  When creating an expert system, the most difficult and expensive task is
constructing a knowledge base. This is particularly true if the problem
involves noisy data and redundant measurements. This paper shows how to modify
the MACIE process for generating connectionist expert systems from training
examples so that it can accommodate noisy and redundant data. The basic idea is
to dynamically generate appropriate training examples by constructing both a
'deep' model and a noise model for the underlying problem. The use of
winner-take-all groups of variables is also discussed. These techniques are
illustrated with a small example that would be very difficult for standard
expert system approaches.


title: The Recovery of Causal Poly-Trees from Statistical Data

abstract:
  Poly-trees are singly connected causal networks in which variables may arise
from multiple causes. This paper develops a method of recovering ply-trees from
empirically measured probability distributions of pairs of variables. The
method guarantees that, if the measured distributions are generated by a causal
process structured as a ply-tree then the topological structure of such tree
can be recovered precisely and, in addition, the causal directionality of the
branches can be determined up to the maximum extent possible. The method also
pinpoints the minimum (if any) external semantics required to determine the
causal relationships among the variables considered.


title:
A Heuristic Bayesian Approach to Knowledge Acquisition: Application to
  Analysis of Tissue-Type Plasminogen Activator

abstract:
  This paper describes a heuristic Bayesian method for computing probability
distributions from experimental data, based upon the multivariate normal form
of the influence diagram. An example illustrates its use in medical technology
assessment. This approach facilitates the integration of results from different
studies, and permits a medical expert to make proper assessments without
considerable statistical training.


title:
Theory-Based Inductive Learning: An Integration of Symbolic and
  Quantitative Methods

abstract:
  The objective of this paper is to propose a method that will generate a
causal explanation of observed events in an uncertain world and then make
decisions based on that explanation. Feedback can cause the explanation and
decisions to be modified. I call the method Theory-Based Inductive Learning
(T-BIL). T-BIL integrates deductive learning, based on a technique called
Explanation-Based Generalization (EBG) from the field of machine learning, with
inductive learning methods from Bayesian decision theory. T-BIL takes as inputs
(1) a decision problem involving a sequence of related decisions over time, (2)
a training example of a solution to the decision problem in one period, and (3)
the domain theory relevant to the decision problem. T-BIL uses these inputs to
construct a probabilistic explanation of why the training example is an
instance of a solution to one stage of the sequential decision problem. This
explanation is then generalized to cover a more general class of instances and
is used as the basis for making the next-stage decisions. As the outcomes of
each decision are observed, the explanation is revised, which in turn affects
the subsequent decisions. A detailed example is presented that uses T-BIL to
solve a very general stochastic adaptive control problem for an autonomous
mobile robot.


title:
Using T-Norm Based Uncertainty Calculi in a Naval Situation Assessment
  Application

abstract:
  RUM (Reasoning with Uncertainty Module), is an integrated software tool based
on a KEE, a frame system implemented in an object oriented language. RUM's
architecture is composed of three layers: representation, inference, and
control. The representation layer is based on frame-like data structures that
capture the uncertainty information used in the inference layer and the
uncertainty meta-information used in the control layer. The inference layer
provides a selection of five T-norm based uncertainty calculi with which to
perform the intersection, detachment, union, and pooling of information. The
control layer uses the meta-information to select the appropriate calculus for
each context and to resolve eventual ignorance or conflict in the information.
This layer also provides a context mechanism that allows the system to focus on
the relevant portion of the knowledge base, and an uncertain-belief revision
system that incrementally updates the certainty values of well-formed formulae
(wffs) in an acyclic directed deduction graph. RUM has been tested and
validated in a sequence of experiments in both naval and aerial situation
assessment (SA), consisting of correlating reports and tracks, locating and
classifying platforms, and identifying intents and threats. An example of naval
situation assessment is illustrated. The testbed environment for developing
these experiments has been provided by LOTTA, a symbolic simulator implemented
in Flavors. This simulator maintains time-varying situations in a multi-player
antagonistic game where players must make decisions in light of uncertain and
incomplete data. RUM has been used to assist one of the LOTTA players to
perform the SA task.


title: A Study of Associative Evidential Reasoning

abstract:
  Evidential reasoning is cast as the problem of simplifying the
evidence-hypothesis relation and constructing combination formulas that possess
certain testable properties. Important classes of evidence as identifiers,
annihilators, and idempotents and their roles in determining binary operations
on intervals of reals are discussed. The appropriate way of constructing
formulas for combining evidence and their limitations, for instance, in
robustness, are presented.


title: A Measure-Free Approach to Conditioning

abstract:
  In an earlier paper, a new theory of measurefree "conditional" objects was
presented. In this paper, emphasis is placed upon the motivation of the theory.
The central part of this motivation is established through an example involving
a knowledge-based system. In order to evaluate combination of evidence for this
system, using observed data, auxiliary at tribute and diagnosis variables, and
inference rules connecting them, one must first choose an appropriate algebraic
logic description pair (ALDP): a formal language or syntax followed by a
compatible logic or semantic evaluation (or model). Three common choices- for
this highly non-unique choice - are briefly discussed, the logics being
Classical Logic, Fuzzy Logic, and Probability Logic. In all three,the key
operator representing implication for the inference rules is interpreted as the
often-used disjunction of a negation (b => a) = (b'v a), for any events a,b.
  However, another reasonable interpretation of the implication operator is
through the familiar form of probabilistic conditioning. But, it can be shown -
quite surprisingly - that the ALDP corresponding to Probability Logic cannot be
used as a rigorous basis for this interpretation! To fill this gap, a new ALDP
is constructed consisting of "conditional objects", extending ordinary
Probability Logic, and compatible with the desired conditional probability
interpretation of inference rules. It is shown also that this choice of ALDP
leads to feasible computations for the combination of evidence evaluation in
the example. In addition, a number of basic properties of conditional objects
and the resulting Conditional Probability Logic are given, including a
characterization property and a developed calculus of relations.


title: Convergent Deduction for Probabilistic Logic

abstract:
  This paper discusses the semantics and proof theory of Nilsson's
probabilistic logic, outlining both the benefits of its well-defined model
theory and the drawbacks of its proof theory. Within Nilsson's semantic
framework, we derive a set of inference rules which are provably sound. The
resulting proof system, in contrast to Nilsson's approach, has the important
feature of convergence - that is, the inference process proceeds by computing
increasingly narrow probability intervals which converge from above and below
on the smallest entailed probability interval. Thus the procedure can be
stopped at any time to yield partial information concerning the smallest
entailed interval.


title: Comparisons of Reasoning Mechanisms for Computer Vision

abstract:
  An evidential reasoning mechanism based on the Dempster-Shafer theory of
evidence is introduced. Its performance in real-world image analysis is
compared with other mechanisms based on the Bayesian formalism and a simple
weight combination method.


title: A Knowledge Engineer's Comparison of Three Evidence Aggregation Methods

abstract:
  The comparisons of uncertainty calculi from the last two Uncertainty
Workshops have all used theoretical probabilistic accuracy as the sole metric.
While mathematical correctness is important, there are other factors which
should be considered when developing reasoning systems. These other factors
include, among other things, the error in uncertainty measures obtainable for
the problem and the effect of this error on the performance of the resulting
system.


title:
Towards Solving the Multiple Extension Problem: Combining Defaults and
  Probabilities

abstract:
  The multiple extension problem arises frequently in diagnostic and default
inference. That is, we can often use any of a number of sets of defaults or
possible hypotheses to explain observations or make Predictions. In default
inference, some extensions seem to be simply wrong and we use qualitative
techniques to weed out the unwanted ones. In the area of diagnosis, however,
the multiple explanations may all seem reasonable, however improbable. Choosing
among them is a matter of quantitative preference. Quantitative preference
works well in diagnosis when knowledge is modelled causally. Here we suggest a
framework that combines probabilities and defaults in a single unified
framework that retains the semantics of diagnosis as construction of
explanations from a fixed set of possible hypotheses. We can then compute
probabilities incrementally as we construct explanations. Here we describe a
branch and bound algorithm that maintains a set of all partial explanations
while exploring a most promising one first. A most probable explanation is
found first if explanations are partially ordered.


title: Problem Structure and Evidential Reasoning

abstract:
  In our previous series of studies to investigate the role of evidential
reasoning in the RUBRIC system for full-text document retrieval (Tong et al.,
1985; Tong and Shapiro, 1985; Tong and Appelbaum, 1987), we identified the
important role that problem structure plays in the overall performance of the
system. In this paper, we focus on these structural elements (which we now call
"semantic structure") and show how explicit consideration of their properties
reduces what previously were seen as difficult evidential reasoning problems to
more tractable questions.


title: The Role of Calculi in Uncertain Inference Systems

abstract:
  Much of the controversy about methods for automated decision making has
focused on specific calculi for combining beliefs or propagating uncertainty.
We broaden the debate by (1) exploring the constellation of secondary tasks
surrounding any primary decision problem, and (2) identifying knowledge
engineering concerns that present additional representational tradeoffs. We
argue on pragmatic grounds that the attempt to support all of these tasks
within a single calculus is misguided. In the process, we note several
uncertain reasoning objectives that conflict with the Bayesian ideal of
complete specification of probabilities and utilities. In response, we advocate
treating the uncertainty calculus as an object language for reasoning
mechanisms that support the secondary tasks. Arguments against Bayesian
decision theory are weakened when the calculus is relegated to this role.
Architectures for uncertainty handling that take statements in the calculus as
objects to be reasoned about offer the prospect of retaining normative status
with respect to decision making while supporting the other tasks in uncertain
reasoning.


title: The Role of Tuning Uncertain Inference Systems

abstract:
  This study examined the effects of "tuning" the parameters of the incremental
function of MYCIN, the independent function of PROSPECTOR, a probability model
that assumes independence, and a simple additive linear equation. me parameters
of each of these models were optimized to provide solutions which most nearly
approximated those from a full probability model for a large set of simple
networks. Surprisingly, MYCIN, PROSPECTOR, and the linear equation performed
equivalently; the independence model was clearly more accurate on the networks
studied.


title: Evidential Reasoning in Image Understanding

abstract:
  In this paper, we present some results of evidential reasoning in
understanding multispectral images of remote sensing systems. The
Dempster-Shafer approach of combination of evidences is pursued to yield
contextual classification results, which are compared with previous results of
the Bayesian context free classification, contextual classifications of dynamic
programming and stochastic relaxation approaches.


title: Implementing a Bayesian Scheme for Revising Belief Commitments

abstract:
  Our previous work on classifying complex ship images [1,2] has evolved into
an effort to develop software tools for building and solving generic
classification problems. Managing the uncertainty associated with feature data
and other evidence is an important issue in this endeavor. Bayesian techniques
for managing uncertainty [7,12,13] have proven to be useful for managing
several of the belief maintenance requirements of classification problem
solving. One such requirement is the need to give qualitative explanations of
what is believed. Pearl [11] addresses this need by computing what he calls a
belief commitment-the most probable instantiation of all hypothesis variables
given the evidence available. Before belief commitments can be computed, the
straightforward implementation of Pearl's procedure involves finding an
analytical solution to some often difficult optimization problems. We describe
an efficient implementation of this procedure using tensor products that solves
these problems enumeratively and avoids the need for case by case analysis. The
procedure is thereby made more practical to use in the general case.


title: Integrating Logical and Probabilistic Reasoning for Decision Making

abstract:
  We describe a representation and a set of inference methods that combine
logic programming techniques with probabilistic network representations for
uncertainty (influence diagrams). The techniques emphasize the dynamic
construction and solution of probabilistic and decision-theoretic models for
complex and uncertain domains. Given a query, a logical proof is produced if
possible; if not, an influence diagram based on the query and the knowledge of
the decision domain is produced and subsequently solved. A uniform declarative,
first-order, knowledge representation is combined with a set of integrated
inference procedures for logical, probabilistic, and decision-theoretic
reasoning.


title: Compiling Fuzzy Logic Control Rules to Hardware Implementations

abstract:
  A major aspect of human reasoning involves the use of approximations.
Particularly in situations where the decision-making process is under stringent
time constraints, decisions are based largely on approximate, qualitative
assessments of the situations. Our work is concerned with the application of
approximate reasoning to real-time control. Because of the stringent processing
speed requirements in such applications, hardware implementations of fuzzy
logic inferencing are being pursued. We describe a programming environment for
translating fuzzy control rules into hardware realizations. Two methods of
hardware realizations are possible. The First is based on a special purpose
chip for fuzzy inferencing. The second is based on a simple memory chip. The
ability to directly translate a set of decision rules into hardware
implementations is expected to make fuzzy control an increasingly practical
approach to the control of complex systems.


title: Steps Towards Programs that Manage Uncertainty

abstract:
  Reasoning under uncertainty in Al hats come to mean assessing the credibility
of hypotheses inferred from evidence. But techniques for assessing credibility
do not tell a problem solver what to do when it is uncertain. This is the focus
of our current research. We have developed a medical expert system called MUM,
for Managing Uncertainty in Medicine, that plans diagnostic sequences of
questions, tests, and treatments. This paper describes the kinds of problems
that MUM was designed to solve and gives a brief description of its
architecture. More recently, we have built an empty version of MUM called MU,
and used it to reimplement MUM and a small diagnostic system for plant
pathology. The latter part of the paper describes the features of MU that make
it appropriate for building expert systems that manage uncertainty.


title: An Algorithm for Computing Probabilistic Propositions

abstract:
  A method for computing probabilistic propositions is presented. It assumes
the availability of a single external routine for computing the probability of
one instantiated variable, given a conjunction of other instantiated variables.
In particular, the method allows belief network algorithms to calculate general
probabilistic propositions over nodes in the network. Although in the worst
case the time complexity of the method is exponential in the size of a query,
it is polynomial in the size of a number of common types of queries.


title: Combining Symbolic and Numeric Approaches to Uncertainty Management

abstract:
  A complete approach to reasoning under uncertainty requires support for
incremental and interactive formulation and revision of, as well as reasoning
with, models of the problem domain capable of representing our uncertainty. We
present a hybrid reasoning scheme which combines symbolic and numeric methods
for uncertainty management to provide efficient and effective support for each
of these tasks. The hybrid is based on symbolic techniques adapted from
Assumption-based Truth Maintenance systems (ATMS), combined with numeric
methods adapted from the Dempster/Shafer theory of evidence, as extended in
Baldwin's Support Logic Programming system. The hybridization is achieved by
viewing an ATMS as a symbolic algebra system for uncertainty calculations. This
technique has several major advantages over conventional methods for performing
inference with numeric certainty estimates in addition to the ability to
dynamically determine hypothesis spaces, including improved management of
dependent and partially independent evidence, faster run-time evaluation of
propositional certainties, the ability to query the certainty value of a
proposition from multiple perspectives, and the ability to incrementally extend
or revise domain models.


title: Explanation of Probabilistic Inference for Decision Support Systems

abstract:
  An automated explanation facility for Bayesian conditioning aimed at
improving user acceptance of probability-based decision support systems has
been developed. The domain-independent facility is based on an information
processing perspective on reasoning about conditional evidence that accounts
both for biased and normative inferences. Experimental results indicate that
the facility is both acceptable to naive users and effective in improving
understanding.


title: Estimation Procedures for Robust Sensor Control

abstract:
  Many robotic sensor estimation problems can characterized in terms of
nonlinear measurement systems. These systems are contaminated with noise and
may be underdetermined from a single observation. In order to get reliable
estimation results, the system must choose views which result in an
overdetermined system. This is the sensor control problem. Accurate and
reliable sensor control requires an estimation procedure which yields both
estimates and measures of its own performance. In the case of nonlinear
measurement systems, computationally simple closed-form estimation solutions
may not exist. However, approximation techniques provide viable alternatives.
In this paper, we evaluate three estimation techniques: the extended Kalman
filter, a discrete Bayes approximation, and an iterative Bayes approximation.
We present mathematical results and simulation statistics illustrating
operating conditions where the extended Kalman filter is inappropriate for
sensor control, and discuss issues in the use of the discrete Bayes
approximation.


title: Efficient Inference on Generalized Fault Diagrams

abstract:
  The generalized fault diagram, a data structure for failure analysis based on
the influence diagram, is defined. Unlike the fault tree, this structure allows
for dependence among the basic events and replicated logical elements. A
heuristic procedure is developed for efficient processing of these structures.


title:
Reasoning About Beliefs and Actions Under Computational Resource
  Constraints

abstract:
  Although many investigators affirm a desire to build reasoning systems that
behave consistently with the axiomatic basis defined by probability theory and
utility theory, limited resources for engineering and computation can make a
complete normative analysis impossible. We attempt to move discussion beyond
the debate over the scope of problems that can be handled effectively to cases
where it is clear that there are insufficient computational resources to
perform an analysis deemed as complete. Under these conditions, we stress the
importance of considering the expected costs and benefits of applying
alternative approximation procedures and heuristics for computation and
knowledge acquisition. We discuss how knowledge about the structure of user
utility can be used to control value tradeoffs for tailoring inference to
alternative contexts. We address the notion of real-time rationality, focusing
on the application of knowledge about the expected timewise-refinement
abilities of reasoning strategies to balance the benefits of additional
computation with the costs of acting with a partial result. We discuss the
benefits of applying decision theory to control the solution of difficult
problems given limitations and uncertainty in reasoning resources.


title: Advantages and a Limitation of Using LEG Nets in a Real-TIme Problem

abstract:
  After experimenting with a number of non-probabilistic methods for dealing
with uncertainty many researchers reaffirm a preference for probability methods
[1] [2], although this remains controversial. The importance of being able to
form decisions from incomplete data in diagnostic problems has highlighted
probabilistic methods [5] which compute posterior probabilities from prior
distributions in a way similar to Bayes Rule, and thus are called Bayesian
methods. This paper documents the use of a Bayesian method in a real time
problem which is similar to medical diagnosis in that there is a need to form
decisions and take some action without complete knowledge of conditions in the
problem domain. This particular method has a limitation which is discussed.


title:
Probing the Leggett-Garg Inequality for Oscillating Neutral Kaons and
  Neutrinos

abstract:
  The Leggett-Garg inequality (LGI) as a temporal analogue of Bell's
inequality, derived using the notion of realism, is applied in a hitherto
unexplored context involving the weak interaction induced two-state
oscillations of decaying neutral kaons and neutrinos. The maximum violation of
LGI obtained from the quantum mechanical results is significantly higher for
the oscillating neutrinos compared to that for the kaons. Interestingly, the
effect of CP non-invariance for the kaon oscillation is to enhance this
violation while, for neutrinos, it is sensitive to the value of the mixing
parameter.


title:
Some Generalizations of Hermite-Hadamard type Integral Inequalities and
  their Applications

abstract:
  In this paper, we establish various inequalities for some differentiable
mappings that are linked with the illustrious Hermite- Hadamard integral
inequality for mappings whose derivatives are (h -($\alpha$?;m))-convex.The
generalized integral inequalities contribute some better estimates than some
already presented. The inequalities are then applied to numerical integration
and some special means.


title:
Paramagnetic Fe_xTa_{1-x} alloys for engineering of perpendicularly
  magnetized tunnel junctions

abstract:
  Exchange coupling between two magnetic layers through an interlayer is of
broad interest for numerous recent applications of nano-magnetic systems. In
this Letter we study ferromagnetic exchange coupling through amorphous
paramagnetic Fe-Ta alloys. We show that the exchange coupling depends
exponentially on spacer thickness and scales with the Fe-Ta susceptibility,
which can be tuned via the alloy composition and/or temperature. Such materials
are of high interest for the engineering of perpendicularly magnetized
CoFeB-MgO based tunnel junctions as it enables ferromagnetic coupling of
magnetic layers with differing crystalline lattices, suppresses dead layers and
can act as an inter-diffusion barrier during annealing.


title:
Neutron-capture element deficiency of the Hercules dwarf spheroidal
  galaxy

abstract:
  We present an assessment of the barium abundance ratios for red giant member
stars in the faint Hercules dwarf spheroidal (dSph) galaxy. Our results are
drawn from intermediate-resolution FLAMES/GIRAFFE spectra around the Ba II
6141.71 AA absorption line at low signal-to-noise ratios. For three brighter
stars we were able to gain estimates from direct equivalent-width measurements,
while for the remaining eight stars only upper limits could be obtained. These
results are investigated in a statistical manner and indicate very low Ba
abundances of log epsilon (Ba) < 0.7 dex (3 sigma). We discuss various possible
systematic biasses, first and foremost, a blend with the Fe I 6141.73 AA-line,
but most of those would only lead to even lower abundances. A better match with
metal-poor halo and dSph stars can only be reached by including a large
uncertainty in the continuum placement. This contrasts with the high
dispersions in iron and calcium (in excess of 1 dex) in this galaxy. While the
latter spreads are typical of the very low luminosity, dark-matter dominated
dSphs, a high level of depletion in heavy elements suggests that chemical
enrichment in Hercules was governed by very massive stars, coupled with a very
low star formation efficiency. While very low abundances of some heavy elements
are also found in individual stars of other dwarf galaxies, this is the first
time that a very low Ba abundance is found within an entire dSph over a broad
metallicity range.


title: Rotational signature of the Milky Way stellar halo

abstract:
  We measure the rotation of the Milky Way stellar halo on two samples of Blue
Horizontal Branch (BHB) field halo stars from the Sloan Digital Sky Survey
(SDSS) with four different methods. The two samples comprise 1582 and 2563
stars respectively and reach out to ~50 kpc in galactocentric distance. Two of
the methods to measure rotation rely exclusively on line-of-sight velocities,
namely the popular double power-law model and a direct estimate of the
de-projected l.o.s. velocity. The other two techniques use the full 3D motions:
the radial velocity based rotation estimator of Sch\"onrich, Binney & Asplund
(2012) and a simple 3D azimuthal velocity mean. In this context we a) critique
the popular model and b) assess the reliability of the estimators. All four
methods agree on a weakly prograde or non-rotating halo. Further, we observe no
duality in the rotation of sub-samples with different metallicities or at
different radii. We trace the rotation gradient across metallicity measured by
Deason et al. (2011) on a similar sample of BHB stars back to the inclusion of
regions in the apparent magnitude-surface gravity plane known to be
contaminated. In the spectroscopically selected sample of Xue et al. (2011), we
flag ~500 hot metal-poor stars for their peculiar kinematics w.r.t. to both
their cooler metal-poor counter-parts and to the metal-rich stars in the same
sample. They show a seemingly retrograde behaviour in line-of-sight velocities,
which is not confirmed by the 3D estimators. Their anomalous vertical motion
hints at either a pipeline problem or a stream-like component rather than a
smooth retrograde population.


title: Spin-orbital liquids in non-Kramers magnet on Kagome lattice

abstract:
  Localized magnetic moments with crystal-field doublet or pseudo-spin 1/2 may
arise in correlated insulators with even number of electrons and strong
spin-orbit coupling. Such a non-Kramers pseudo-spin 1/2 is the consequence of
crystalline symmetries as opposed to the Kramers doublet arising from
time-reversal invariance, and is necessarily a composite of spin and orbital
degrees of freedom. We investigate possible spin-orbital liquids with fermionic
spinons for such non-Kramers pseudo-spin 1/2 systems on the Kagome lattice.
Using the projective symmetry group analysis, we find {\it ten} new phases that
are not allowed in the corresponding Kramers systems. These new phases are
allowed due to unusual action of the time reversal operation on non-Kramers
pseudo-spins. We compute the spin-spin dynamic structure factor that shows
characteristic features of these non-Kramers spin-orbital liquids arising from
their unusual coupling to neutrons, which is therefore relevant for neutron
scattering experiments. We also point out possible anomalous broadening of
Raman scattering intensity that may serve as a signature experimental feature
for gapless non-Kramers spin-orbital liquids.


title: The Higgs mass from a String-Theoretic Perspective

abstract:
  The Higgs quartic coupling has now been indirectly measured at the
electroweak scale. Assuming no new low-scale physics, its running is known and,
together with gauge and Yukawa couplings, it is a crucial new piece of
information constraining UV completions of the Standard Model. In particular,
supersymmetry broken at an intermediate or high energy scale with tan(beta)=1
(i.e. lambda=0) is consistent with present data and has an independent
theoretical appeal. We analyze the possible string-theoretic motivations for
tan(beta)=1 (including both the shift-symmetry and the more economical variant
of a Z_2 symmetry) in a Higgs sector realized on either 6- or 7-branes. We
identify specific geometries where lambda ~ 0 may arise naturally and specify
the geometrical problems which need to be solved to determine its precise value
in the generic case. We then analyze the radiative corrections to lambda.
Finally we show that, in contrast to naive expectations, lambda<0 at the SUSY
breaking scale is also possible. Specifically, string theory may produce an
MSSM plus chiral singlet at a very high scale, which immediately breaks to a
non-SUSY Standard Model with lambda<0. This classically unstable theory then
becomes metastable through running towards the IR.


title:
Resolving the gap and AU-scale asymmetries in the pre-transitional disk
  of V1247 Orionis

abstract:
  Pre-transitional disks are protoplanetary disks with a gapped disk structure,
potentially indicating the presence of young planets in these systems. In order
to explore the structure of these objects and their gap-opening mechanism, we
observed the pre-transitional disk V1247 Orionis using the Very Large Telescope
Interferometer, the Keck Interferometer, Keck-II, Gemini South, and IRTF. This
allows us spatially resolve the AU-scale disk structure from near- to
mid-infrared wavelengths (1.5 to 13 {\mu}m), tracing material at different
temperatures and over a wide range of stellocentric radii. Our observations
reveal a narrow, optically-thick inner-disk component (located at 0.18 AU from
the star) that is separated from the optically thick outer disk (radii >46 AU),
providing unambiguous evidence for the existence of a gap in this
pre-transitional disk. Surprisingly, we find that the gap region is filled with
significant amounts of optically thin material with a carbon-dominated dust
mineralogy. The presence of this optically thin gap material cannot be deduced
solely from the spectral energy distribution, yet it is the dominant
contributor at mid-infrared wavelengths. Furthermore, using Keck/NIRC2 aperture
masking observations in the H, K', and L' band, we detect asymmetries in the
brightness distribution on scales of about 15-40 AU, i.e. within the gap
region. The detected asymmetries are highly significant, yet their amplitude
and direction changes with wavelength, which is not consistent with a companion
interpretation but indicates an inhomogeneous distribution of the gap material.
We interpret this as strong evidence for the presence of complex density
structures, possibly reflecting the dynamical interaction of the disk material
with sub-stellar mass bodies that are responsible for the gap clearing.


title:
On Poincar\'e gauge theory of gravity, its equations of motion, and
  Gravity Probe B

abstract:
  Ever since E.Cartan in the 1920s enriched the geometric framework of general
relativity (GR) by introducing a {\it torsion} of spacetime, the question arose
whether one could find a measurement technique for detecting the presence of a
torsion field. Mao et al.(2007) claimed that the rotating quartz balls in the
gyroscopes of the Gravity Probe B experiment, falling freely on an orbit around
the Earth, should "feel" the torsion. Similarly, March et al.(2011) argue with
the precession of the Moon and the Mercury and extend later their
considerations to the Lageos satellite.--- A consistent theory of gravity with
torsion emerged during the early 1960's as gauge theory of the Poincar\'e
group. This Poincar\'e gauge theory of gravity incorporates as simplest viable
cases the Einstein-Cartan(-Sciama-Kibble) theory (EC), the teleparallel
equivalent GR|| of GR, and GR itself. So far, PG and, in particular, the
existence of torsion have {\it not} been experimentally confirmed. However, PG
is to be considered as the standard theory of gravity with torsion because of
its very convincing gauge structure.--- Since the early 1970s up to today,
different groups have shown more or less independently that torsion couples
only to the {\it elementary particle spin} and under no circumstances to the
orbital angular momentum of test particles. This is established knowledge and
we reconfirm this conclusion by discussing the energy-momentum law of PG, which
has same form for all versions of PG. Therefore, we conclude that,
unfortunately, the investigations of Mao et al. and March et al. do not yield
any information on torsion.


title: Age-dating the Tully-Fisher relation at moderate redshift

abstract:
  We analyse the Tully-Fisher relation at moderate redshift from the point of
view of the underlying stellar populations, by comparing optical and NIR
photometry with a phenomenological model that combines population synthesis
with a simple prescription for chemical enrichment. The sample comprises 108
late-type galaxies extracted from the FORS Deep Field (FDF) and William
Herschel Deep Field (WHDF) surveys at z<1 (median redshift z=0.45). A
correlation is found between stellar mass and the parameters that describe the
star formation history, with massive galaxies forming their populations early
(zFOR~3), with star formation timescales, tau1~4Gyr; although with very
efficient chemical enrichment timescales (tau2~1Gyr). In contrast, the
stellar-to-dynamical mass ratio - which, in principle, would track the
efficiency of feedback in the baryonic processes driving galaxy formation -
does not appear to correlate with the model parameters. On the Tully-Fisher
plane, no significant age segregation is found at fixed circular speed, whereas
at fixed stellar-to-dynamical mass fraction, age splits the sample, with older
galaxies having faster circular speeds at fixed Ms/Mdyn. Although our model
does not introduce any prior constraint on dust reddening, we obtain a strong
correlation between colour excess and stellar mass.


title: The Web of D-branes at Singularities in Compact Calabi-Yau Manifolds

abstract:
  We present novel continuous supersymmetric transitions which take place among
different chiral configurations of D3/D7 branes at singularities in the context
of type IIB Calabi-Yau compactifications. We find that distinct local models
which admit a consistent global embedding can actually be connected to each
other along flat directions by means of transitions of bulk-to-flavour branes.
This has interesting interpretations in terms of brane recombination/splitting
and brane/anti-brane creation/annihilation. These transitions give rise to a
large web of quiver gauge theories parametrised by splitting/recombination
modes of bulk branes which are not present in the non-compact case. We
illustrate our results in concrete global embeddings of chiral models at a dP_0
singularity.


title:
Stellar ages and convective cores in field main-sequence stars: first
  asteroseismic application to two Kepler targets

abstract:
  Using asteroseismic data and stellar evolution models we make the first
detection of a convective core in a Kepler field main-sequence star, putting a
stringent constraint on the total size of the mixed zone and showing that extra
mixing beyond the formal convective boundary exists. In a slightly less massive
target the presence of a convective core cannot be conclusively discarded, and
thus its remaining main-sequence life time is uncertain. Our results reveal
that best-fit models found solely by matching individual frequencies of
oscillations corrected for surface effects do not always properly reproduce
frequency combinations. Moreover, slightly different criteria to define what
the best-fit model is can lead to solutions with similar global properties but
very different interior structures. We argue that the use of frequency ratios
is a more reliable way to obtain accurate stellar parameters, and show that our
analysis in field main-sequence stars can yield an overall precision of 1.5%,
4%, and 10% in radius, mass and age, respectively. We compare our results with
those obtained from global oscillation properties, and discuss the possible
sources of uncertainties in asteroseismic stellar modeling where further
studies are still needed.


title:
Role of inter-edge tunneling in localizing Majorana zero modes at the
  ends of quasi one-dimensional p+ip systems

abstract:
  Potter and Lee have demonstrated the presence of Majorana zero modes at the
ends of quasi one-dimensional (1-D) p+ip superconductors. We use conformal
field theory (CFT) methods to show that inter-edge tunneling of the vortex
excitations along the length of the channel is crucial for such localization.
We show that localization of Majorana modes occurs also in quasi 1-D channels
of the 5/2 fractional quantum Hall (FQH) systems when modeled, following Moore
and Read, as the p+ip paired state of composite fermions. We propose a
tunnel-interferometry experiment to detect these modes, which should show a \pi
-phase shift of oscillations depending on whether a localized Majorana zero
mode is present or not, which, in turn, can be controlled by varying the
tunneling strength.


title:
The simplest model of galaxy formation I: A formation history model of
  galaxy stellar mass growth

abstract:
  We introduce a simple model to self-consistently connect the growth of
galaxies to the formation history of their host dark matter haloes. Our model
is defined by two simple functions: the "baryonic growth function" which
controls the rate at which new baryonic material is made available for star
formation, and the "physics function" which controls the efficiency with which
this material is converted into stars. Using simple, phenomenologically
motivated forms for both functions that depend only on a single halo property,
we demonstrate the model's ability to reproduce the z=0 red and blue stellar
mass functions. Furthermore, by adding redshift as a second input variable to
the physics function we show that the reproduction of the global stellar mass
function out to z=3 is improved. We conclude by discussing the general utility
of our new model, highlighting its usefulness for creating mock galaxy samples
which have a number of key advantages over those generated by other techniques.


title: The Dynamical Significance of Triple Star Systems in Star Clusters

abstract:
  Over the last few decades, observational surveys have revealed that
high-order multiple-star systems (e.g. triples, quadruples, etc.), and triples
in particular, are common in our Galaxy. In this paper, we consider the
dynamical significance of this transformation in our understanding of stellar
multiplicity. Using empirically constrained binary and triple fractions in
those star clusters for which these values are available in the literature, we
compare analytic rates for encounters involving single, binary, and triple
stars. Our results show that, \textit{even for relatively low triple fractions,
dynamical interactions involving triples occur roughly as often as encounters
involving either single or binary stars alone, particularly in low-mass star
clusters}. More generally, using empirically-derived multiple star catalogues
for the young star-forming association Taurus-Auriga and the Galactic field, we
show that the data are consistent with the gravitationally-focused cross
section for encounters increasing with increasing multiplicity. Consequently,
triple stars, and even higher-order multiples, could be more important than
previously realized for a number of astrophysical phenomena, including the
formation and destruction of compact binaries and various types of stellar
exotica, and the dynamical evolution of star clusters.


title:
Investigating the relationship between AGN activity and stellar mass in
  zCOSMOS galaxies at 0<z<1 using emission line diagnostic diagrams

abstract:
  We investigate the link between AGN activity, star-formation and stellar mass
of the host galaxy at 0<z<1, looking for spectroscopic traces of AGN and aging
of the host. This work provides an extension of the existing studies at z<0.1
and contributes to shed light on galaxy evolution at intermediate redshifts. We
used the zCOSMOS 20k data to create a sample of galaxies at z<1. We divided the
sample in several mass-redshift bins to obtain stacked galaxy spectra with an
improved S/N. We exploited emission-line diagnostic diagrams to separate AGN
from star-forming galaxies. We found indication of a role for the total galaxy
stellar mass in leading galaxy classification. Stacked spectra show AGN
signatures above the log M_*/M_sun>10.2 threshold. Moreover, the stellar
populations of AGN hosts are found to be older with respect to star-forming and
composites galaxies. This could be due to the the tendency of AGN to reside in
massive hosts. The dependence of the AGN classification on the stellar mass is
in agreement with what has been already found in previous studies. It is
consistent with, together with the evidence of older stellar populations
inhabiting the AGN-like galaxies, the downsizing scenario. In particular, our
evidence points to an evolutionary scenario where the AGN-feedback is capable
of quenching the star formation in the most massive galaxies. Therefore, the
AGN-feedback is the best candidate for initiating the passive evolutionary
phase of galaxies.


title:
Gamma-ray diagnostics of Type Ia supernovae: Predictions of observables
  from three-dimensional modeling

abstract:
  Besides the fact that the gamma-ray emission due to radioactive decays is
responsible for powering the light curves of Type Ia supernovae (SNe Ia), gamma
rays themselves are of particular interest as a diagnostic tool because they
provide a direct way to obtain deeper insights into the nucleosynthesis and the
kinematics of these explosion events. Focusing on two of the most broadly
discussed SN Ia progenitor scenarios - a delayed detonation in a
Chandrasekhar-mass white dwarf (WD) and a violent merger of two WDs - we use
three-dimensional explosion models and perform radiative transfer simulations
to obtain synthetic gamma-ray spectra. Both chosen models produce the same mass
of 56Ni and have similar optical properties that are in reasonable agreement
with the recently observed supernova SN 2011fe. In contrast to the optical
regime, the gamma-ray emission of our two chosen models proves to be rather
different. The almost direct connection of the emission of gamma rays to
fundamental physical processes occuring in SNe Ia permits additional
constraints concerning several explosion model properties that are not easily
accessible within other wavelength ranges. Proposed future MeV missions such as
GRIPS will resolve all spectral details only for nearby SNe Ia, but hardness
ratio and light curve measurements still allow for a distinction of the two
different models at 10 and 16 Mpc for an exposure time of 10^6 s, respectively.
The possibility to detect the strongest line features up to the Virgo distance
will offer the opportunity to build up a first sample of SN Ia detections in
the gamma-ray energy range and underlines the importance of future space
observatories for MeV gamma rays.


title:
Single-particle and many-body analyses of a quasiperiodic integrable
  system after a quench

abstract:
  In general, isolated integrable quantum systems have been found to relax to
an apparent equilibrium state in which the expectation values of few-body
observables are described by the generalized Gibbs ensemble. However, recent
work has shown that relaxation to such a generalized statistical ensemble can
be precluded by localization in a quasiperiodic lattice system. Here we
undertake complementary single-particle and many-body analyses of
noninteracting spinless fermions and hard-core bosons within the Aubry-Andre
model to gain insight into this phenomenon. Our investigations span both the
localized and delocalized regimes of the quasiperiodic system, as well as the
critical point separating the two. Considering first the case of spinless
fermions, we study the dynamics of the momentum distribution function and
characterize the effects of real-space and momentum-space localization on the
relevant single-particle wave functions and correlation functions. We show that
although some observables do not relax in the delocalized and localized
regimes, the observables that do relax in these regimes do so in a manner
consistent with a recently proposed Gaussian equilibration scenario, whereas
relaxation at the critical point has a more exotic character. We also construct
various statistical ensembles from the many-body eigenstates of the fermionic
and bosonic Hamiltonians and study the effect of localization on their
properties.


title:
Real-Space Tailoring of the Electron-Phonon Coupling in Ultra-Clean
  Nanotube Mechanical Resonators

abstract:
  The coupling between electrons and phonons is at the heart of many
fundamental phenomena in physics. In nature, this coupling is generally
predetermined for both, molecules and solids. Tremendous advances have been
made in controlling electrons and phonons in engineered nanosystems, yet,
control over the coupling between these degrees of freedom is still widely
lacking. Here, we use a new generation of carbon nanotube devices with movable
ultra-clean single and double quantum dots embedded in a mechanical resonator
to demonstrate the tailoring of the interactions between electronic and
mechanical degrees of freedom on the nanoscale. Exploiting this tunable
coupling, we directly image the spatial structure of phonon modes and probe
their parity in real space. Most interestingly, we demonstrate selective
coupling between individual mechanical modes and internal electronic degrees of
freedom. Our results open new vistas for engineering bulk quantum phenomena in
a controlled nanoscale setting and offer important new tools for entangling the
electronic and mechanical degrees of freedom at the quantum level.


title: Direct Ultraviolet Imaging and Spectroscopy of Betelgeuse

abstract:
  Direct images of Betelgeuse were obtained over a span of 4 years with the
Faint Object Camera on the Hubble Space Telescope. These images reveal the
extended ultraviolet continuum emission (about 2 times the optical diameter),
the varying overall ultraviolet flux levels and a pattern of bright surface
continuum features that change in position and appearance over several months
or less. Concurrent photometry and radial velocity measures support the model
of a pulsating star, first discovered in the ultraviolet from IUE. Spatially
resolved HST spectroscopy reveals a larger extention in chromospheric emissions
of Mg II as well as the rotation of the supergiant. Changing localized subsonic
flows occur in the low chromosphere that can cover a substantial fraction of
the stellar disk and may initiate the mass outflow.


title: Progress in the NNPDF global analysis

abstract:
  We report on recent progress in the NNPDF framework of global PDF analysis.
The NNPDF2.3 set is the first and only available PDF set with includes LHC
data. A recent benchmark comparison of NNPDF2.3 and all other modern NNLO PDF
sets with LHC data was performed. We have also studied theoretical
uncertainties due to heavy quark renormalization schemes, higher twists and
deuterium corrections in PDFs. Finally, we report on the release of positive
definite PDF sets, based on the NNPDF2.3 analysis, specially suited for use in
Monte Carlo event generators.


title: Non-universal conductance in quasi-helical quantum wires

abstract:
  In a quantum wire with ideal helical modes, the conductance is quantized in
units of e^2/h, provided the wire is connected to Fermi liquid leads. We show
that this universality does not hold in partially gapped quasi-helical systems
such as Rashba nanowires subject to a magnetic field, which are commonly used
to mimic helical Luttinger liquids. Instead, their conductance takes a
non-universal value that depends on the interactions in the wire, even in the
presence of Fermi liquid leads. The non-universal conductance is rooted in a
non-trivial mixing of spin and charge degrees of freedom, which in turn defines
a non-helical low-energy Hamiltonian.


title: New Constraints on General Slepton Flavor Mixing

abstract:
  We explore the phenomenological implications on charged lepton flavor
violating (LFV) processes from slepton flavor mixing within the Minimal
Supersymmetric Standard Model. We work under the model-independent hypothesis
of general flavor mixing in the slepton sector, being parametrized by a
complete set of dimensionless delta^AB_ij (A,B = L,R; i,j = 1, 2, 3)
parameters. The present upper bounds on the most relevant LFV processes,
together with the requirement of compatibility in the choice of the MSSM
parameters with the recent LHC and (g-2) data, lead to updated constraints on
all slepton flavor mixing parameters. A comparative discussion of the most
effective LFV processes to constrain the various generation mixings is
included.


title: The Intriguing Structure of Non-geometric Frames in String Theory

abstract:
  Non-geometric frames in string theory are related to the geometric ones by
certain local O(D,D) transformations, the so-called $\beta$-transforms. For
each such transformation, we show that there exists both a natural field
redefinition of the metric and the Kalb-Ramond two-form as well as an
associated Lie algebroid. We furthermore prove that the all-order low-energy
effective action of the superstring, written in terms of the redefined fields,
can be expressed through differential-geometric objects of the corresponding
Lie algebroid. Thus, the latter provides a natural framework for effective
superstring actions in non-geometric frames. Relations of this new formalism to
double field theory and to the description of non-geometric backgrounds such as
T-folds are discussed as well.


title: Inflationary paradigm in trouble after Planck2013

abstract:
  Recent results from the Planck satellite combined with earlier observations
from WMAP, ACT, SPT and other experiments eliminate a wide spectrum of more
complex inflationary models and favor models with a single scalar field, as
reported by the Planck Collaboration. More important, though, is that all the
simplest inflaton models are disfavored statistically relative to those with
plateau-like potentials. We discuss how a restriction to plateau-like models
has three independent serious drawbacks: it exacerbates both the initial
conditions problem and the multiverse-unpredictability problem and it creates a
new difficulty that we call the inflationary "unlikeliness problem." Finally,
we comment on problems reconciling inflation with a standard model Higgs, as
suggested by recent LHC results. In sum, we find that recent experimental data
disfavors all the best-motivated inflationary scenarios and introduces new,
serious difficulties that cut to the core of the inflationary paradigm.
Forthcoming searches for B-modes, non-Gaussianity and new particles should be
decisive.


title: Crossover from Bosonic to Fermionic features in Composite Boson Systems

abstract:
  We study the quantum dynamics of conversion of composite bosons into
fermionic fragment species with increasing densities of bound fermion pairs
using the open quantum system approach. The Hilbert space of $N$-state-function
is decomposed into a composite boson subspace and an orthogonal fragment
subspace of quasi-free fermions that enlarges as the composite boson
constituents deviate from ideal boson commutation relations. The tunneling
dynamics of coupled composite boson states in confined systems is examined, and
the appearance of exceptional points under experimentally testable conditions
(densities, lattice temperatures) is highlighted. The theory is extended to
examine the energy transfer between macroscopically coherent systems such as
multichromophoric macromolecules (MCMMs) in photosynthetic light harvesting
complexes.


title:
The Optical Gravitational Lensing Experiment. The OGLE-III Catalog of
  Variable Stars. XV. Long-Period Variables in the Galactic Bulge

abstract:
  The fifteenth part of the OGLE-III Catalog of Variable Stars (OIII-CVS)
contains 232,406 long-period variables (LPVs) detected in the OGLE-II and
OGLE-III fields toward the Galactic bulge. The sample consists of 6528 Mira
stars, 33,235 semiregular variables and 192,643 OGLE small amplitude red
giants. The catalog data and data resources that are being published include
observational parameters of stars, finding charts, and time-series I- and
V-band photometry obtained between 1997 and 2009.
  We discuss statistical features of the sample and compare it with collections
of LPVs in the Magellanic Clouds. The vast majority of red giant stars in the
Galactic bulge have an oxygen-rich chemistry. Mira variables form a separate
group in the period-amplitude diagram, which was not noticed for oxygen-rich
Miras in the Magellanic Clouds. We find a clear deficit of long-secondary
period stars toward the Galactic center compared to the sample of Magellanic
Clouds' LPVs.


title: Quantum states as virtual singletons: converting duality into symmetry

abstract:
  In a predicative framework from basic logic, defined for a model of quantum
parallelism by sequents, we characterize a class of first order domains, termed
{\em virtual singletons}, which allows a generalization of the notion of
duality, termed {\em symmetry}. Although consistent with the classical notion
of duality, symmetry creates an environment where negation has fixed points,
for which the direction of logical consequence is irrelevant. Symmetry can
model Bell's states. So, despite its nonsense in a traditional logical setting,
symmetry can hide the peculiar advantage for the treatment of information, that
is proper of quantum mechanics.


title: Density, forcing, and the covering problem

abstract:
  We present a notion of forcing that can be used, in conjunction with other
results, to show that there is a Martin-L\"of random set X such that X does not
compute 0' and X computes every K-trivial set.


title: Power series determined by an experiment on the unit interval

abstract:
  We consider the linear combinations of elements of two sequences: the first
one a priory given nonnegative sequence and the second random sequence from the
unit interval. We investigate the expected value of the smallest natural number
such that the value of these linear combinations exceed a positive number.
After very clear geometrical conclusions, we find the function which expresses
the expected value. Here, we recognize a few known results like the special
cases.


title:
Phase transitions for rates of convergence in the Blume-Emery-Griffiths
  model

abstract:
  We derive rates of convergence for limit theorems that reveal the intricate
structure of the phase transitions in a mean-field version of the
Blume-Emery-Griffith model. The theorems consist of scaling limits for the
total spin. The model depends on the inverse temperature $\beta$ and the
interaction strength $K$. The rates of convergence results are obtained as
$(\beta,K)$ converges along appropriate sequences $(\beta_n,K_n)$ to points
belonging to various subsets of the phase diagram which include a curve of
second-order points and a tricritical point. We apply Stein's method for normal
and non-normal approximation avoiding the use of transforms and supplying
bounds, such as those of Berry-Esseen quality, on approximation error. We
observe an additional phase transition phenomenon in the sense that depending
on how fast $K_n$ and $\beta_n$ are converging to points in various subsets of
the phase diagram, different rates of convergences to one and the same limiting
distribution occur.


title: Calculus of Operators: Covariant Transform and Relative Convolutions

abstract:
  This paper outlines a covariant theory of operators defined on groups and
homogeneous spaces. A systematic use of groups and their representations allows
to obtain results of algebraic and analytical nature. The consideration is
systematically illustrated by a representative collection of examples.
  Keywords: Lie groups and algebras, convolution operator, relative
convolution, representation theory, pseudo-differential operators, PDO,
singular integral operator, SIO, the Heisenberg group, SL(2,R), induced
representation, Fock-Segal-Bargmann (FSB) representation, Shrodinger
representation, covariant transform, contravariant transform, wavelet
transform, square integrable representations, reproducing kernel,
Fourier-Wigner transform, deformation quantization, Bergman space, Berezin's
symbol, Wick symbol, Schwartz kernel, Toeplitz operator, operators of local
type, Simonenko's localisation, reproducing kernel thesis, Dynin group, twisted
convolution, star product, Groenewold-Moyal, composition operator.

categories: math.RT math-ph math.FA math.MP math.OA quant-ph


title: Thermal Emission in Gamma-Ray Burst Afterglows

abstract:
  We study thermal emission from circumstellar structures heated by gamma-ray
burst (GRB) radiation and ejecta and calculate its contribution to GRB optical
and X-ray afterglows using the modified radiation hydro-code small STELLA. It
is shown that thermal emission originating in heated dense shells around the
GRB progenitor star can reproduce X-ray plateaus (like observed in GRB 050904,
070110) as well as deviations from a power law fading observed in optical
afterglows of some GRBs (e.g. 020124, 030328, 030429X, 050904). Thermal
radiation pressure in the heated circumburst shell dominates the gas pressure,
producing rapid expansion of matter similar to supenova-like explosions close
to opacity or radiation flux density jumps in the circumburst medium. This
phenomenon can be responsible for so-called supernova bumps in optical
afterglows of several GRBs. Such a `quasi-supernova' suggests interpretation of
the GRB-SN connection which does not directly involve the explosion of the GRB
progenitor star.


title:
New Light on Infrared Problems: Sectors, Statistics, Symmetries and
  Spectrum

abstract:
  A new approach to the analysis of the physical state space of a theory is
presented within the general setting of local quantum physics. It also covers
theories with long range forces, such as Quantum Electrodynamics. Making use of
the notion of charge class, an extension of the concept of superselection
sector, infrared problems are avoided by restricting the states to observables
localized in a light cone. The charge structure of a theory can be explored in
a systematic manner. The present analysis focuses on simple charges, thus
including the electric charge. It is shown that any such charge has a conjugate
charge. There is a meaningful concept of statistics: the corresponding charge
classes are either of Bose or of Fermi type. The family of simple charge
classes is in one--to--one correspondence with the irreducible unitary
representations of a compact Abelian group. Moreover, there is a meaningful
definition of covariant charge classes. Any such class determines a continuous
unitary representation of the Poincar\'e group or its covering group satisfying
the relativistic spectrum condition. The resulting particle aspects are also
briefly discussed.


title:
Quartz Tuning Forks and Acoustic Phenomena - Application to Superfluid
  Helium

abstract:
  Immersed mechanical resonators are well suited for probing the properties of
fluids, since the surrounding environment influences the resonant
characteristics of such oscillators in several ways. Quartz tuning forks have
gained much popularity in recent years as the resonators of choice for studies
of liquid helium. They have many superior properties when compared to other
oscillating bodies conventionally used for this purpose, such as vibrating
wires. However, the intricate geometry of a tuning fork represents a challenge
for analyzing their behavior in a fluid environment - analytical approaches do
not carry very far. In this article the characteristics of immersed quartz
tuning fork resonators are studied by numerical simulations. We account for the
compressibility of the medium, that is acoustic phenomena, and neglect
viscosity, with the aim to realisticallymodel the oscillator response in
superfluid helium. The significance of different tuning fork shapes is studied.
Acoustic emission in infinite medium and acoustic resonances in confined
volumes are investigated. The results can aid in choosing a quartz tuning fork
with suitable properties for experiments, as well as interpreting measured
data.


title: Cosmology with a decaying vacuum

abstract:
  Properties of unstable false vacuum states are analyzed from the point of
view of the quantum theory of unstable states. Some of false vacuum states
survive up to times when their survival probability has a non-exponential form.
At times much latter than the transition time, when contributions to the
survival probability of its exponential and non-exponential parts are
comparable, the survival probability as a function of time t has an inverse
power-like form. We show that at this time region the instantaneous energy of
the false vacuum states tends to the energy of the true vacuum state as
$1/t^{2}$ for $t \to \infty$.


title: Logical Fuzzy Preferences

abstract:
  We present a unified logical framework for representing and reasoning about
both quantitative and qualitative preferences in fuzzy answer set programming,
called fuzzy answer set optimization programs. The proposed framework is vital
to allow defining quantitative preferences over the possible outcomes of
qualitative preferences. We show the application of fuzzy answer set
optimization programs to the course scheduling with fuzzy preferences problem.
To the best of our knowledge, this development is the first to consider a
logical framework for reasoning about quantitative preferences, in general, and
reasoning about both quantitative and qualitative preferences in particular.


title:
Optimal DNA shotgun sequencing: Noisy reads are as good as noiseless
  reads

abstract:
  We establish the fundamental limits of DNA shotgun sequencing under noisy
reads. We show a surprising result: for the i.i.d. DNA model, noisy reads are
as good as noiseless reads, provided that the noise level is below a certain
threshold which can be surprisingly high. As an example, for a uniformly
distributed DNA sequence and a symmetric substitution noisy read channel, the
threshold is as high as 19%.


title:
Nested Aggregates in Answer Sets: An Application to a Priori
  Optimization

abstract:
  We allow representing and reasoning in the presence of nested multiple
aggregates over multiple variables and nested multiple aggregates over
functions involving multiple variables in answer sets, precisely, in answer set
optimization programming and in answer set programming. We show the
applicability of the answer set optimization programming with nested multiple
aggregates and the answer set programming with nested multiple aggregates to
the Probabilistic Traveling Salesman Problem, a fundamental a priori
optimization problem in Operation Research.


title:
Hints of a Charge Asymmetry in the Electron and Positron Cosmic-Ray
  Excesses

abstract:
  By combining the recent data from AMS-02 with those from Fermi-LAT, we show
the emergence of a charge asymmetry in the electron and positron cosmic-ray
excesses, slightly favoring the electron component. Astrophysical and dark
matter inspired models introduced to explain the observed excesses can be
classified according to their prediction for the charge asymmetry and its
energy dependence. Future data confirming the presence of a charge asymmetry,
would imply that an asymmetric production mechanism is at play.


title: Curvature spectra of simple Lie groups

abstract:
  The Killing form \beta\ of a real (or complex) semisimple Lie group G is a
left-invariant pseudo-Riemannian (or, respectively, holomorphic) Einstein
metric. Let \Omega\ denote the multiple of its curvature operator, acting on
symmetric 2-tensors, with the factor chosen so that \Omega\beta=2\beta. The
result of Meyberg [8], describing the spectrum of \Omega\ in complex simple Lie
groups G, easily implies that 1 is not an eigenvalue of \Omega\ in any real or
complex simple Lie group G except those locally isomorphic to SU(p,q), or
SL(n,R), or SL(n,C) or, for even n only, SL(n/2,H), where p\ge q\ge0 and
p+q=n>2. Due to the last conclusion, on simple Lie groups G other the ones just
listed, nonzero multiples of the Killing form \beta\ are isolated among
left-invariant Einstein metrics. Meyberg's theorem also allows us to understand
the kernel of \Lambda, which is another natural operator. This in turn leads to
a proof of a known, yet unpublished, fact: namely, that a semisimple real or
complex Lie algebra with no simple ideals of dimension 3 is essentially
determined by its Cartan three-form.


title:
Quantum effects on the loss function of Pb(111) thin films: an ab initio
  study

abstract:
  A theoretical study of the surface energy-loss function of freestanding
Pb(111) thin films is presented, starting from the single monolayer case. The
calculations are carried applying the linear response theory, with inclusion of
the electron band structure by means of a first-principles pseudopotential
approach using a supercell scheme. Quantum-size effects on the plasmon modes of
the thinnest films are found in qualitative agreement with previous work based
on the jellium model. For thicker films, results show a dispersionless mode at
all thicknesses, in agreeement with electron energy-loss measurements. For
sizeable values of the momentum, the raising of the surface plasmon with
increasing thickness is retrieved.


title: Patterns formed by coins

abstract:
  This article is a gentle introduction to the mathematical area known as
circle packing, the study of the kinds of patterns that can be formed by
configurations of non-overlapping circles. The first half of the article is an
exposition of the two most important facts about circle packings, (1) that
essentially whatever pattern (i.e. combinatorics) we ask for, we may always
arrange circles in that pattern, and (2) that under simple conditions on the
pattern, there is an essentially unique arrangement of circles in that pattern.
In the second half of the article, we consider related questions, but where we
allow the circles to overlap. The article is written with the idea that no
mathematical background should be required to read it.


title: Possibility for exciton Bose-Einstein condensation in carbon nanotubes

abstract:
  We demonstrate a possibility for exciton Bose-Einstein condensation in
individual small-diameter (~1-2 nm) semiconducting carbon nanotubes. The effect
occurs under the exciton-interband-plasmon coupling controlled by an external
electrostatic field applied perpendicular to the nanotube axis. It requires
fields ~1 V/nm and temperatures below 100 K that are experimentally accessible.
The effect offers a testing ground for fundamentals of condensed matter physics
in one dimension and opens up perspectives to develop tunable coherent
polarized light source with carbon nanotubes.


title:
Absolutely continuous spectrum for limit-periodic Schr\"odinger
  operators

abstract:
  We show that a large class of limit-periodic Schr\"odinger operators has
purely absolutely continuous spectrum in arbitrary dimensions. This result was
previously known only in dimension one.
  The proof proceeds through the non-perturbative construction of
limit-periodic extended states. An essential step is a new estimate of the
probability (in quasi-momentum) that the Floquet Bloch operators have only
simple eigenvalues.


title: Operator Deformations in Quantum Measurement Theory

abstract:
  We describe rigorous quantum measurement theory in the Heisenberg picture by
applying operator deformation techniques previously used in noncommutative
quantum field theory. This enables the conventional observables (represented by
unbounded operators) to play a role also in the more general setting.


title:
Quantum circuit optimization by topological compaction in the surface
  code

abstract:
  The fragile nature of quantum information limits our ability to construct
large quantities of quantum bits suitable for quantum computing. An important
goal, therefore, is to minimize the amount of resources required to implement
quantum algorithms, many of which are serial in nature and leave large numbers
of qubits idle much of the time unless compression techniques are used.
Furthermore, quantum error-correcting codes, which are required to reduce the
effects of noise, introduce additional resource overhead. We consider a
strategy for quantum circuit optimization based on topological deformation in
the surface code, one of the best performing and most practical quantum
error-correcting codes. Specifically, we examine the problem of minimizing
computation time on a two-dimensional qubit lattice of arbitrary, but fixed
dimension, and propose two algorithms for doing so.


title: Convergence of trust-region methods based on probabilistic models

abstract:
  In this paper we consider the use of probabilistic or random models within a
classical trust-region framework for optimization of deterministic smooth
general nonlinear functions. Our method and setting differs from many
stochastic optimization approaches in two principal ways. Firstly, we assume
that the value of the function itself can be computed without noise, in other
words, that the function is deterministic. Secondly, we use random models of
higher quality than those produced by usual stochastic gradient methods. In
particular, a first order model based on random approximation of the gradient
is required to provide sufficient quality of approximation with probability
greater than or equal to 1/2. This is in contrast with stochastic gradient
approaches, where the model is assumed to be "correct" only in expectation. As
a result of this particular setting, we are able to prove convergence, with
probability one, of a trust-region method which is almost identical to the
classical method. Hence we show that a standard optimization framework can be
used in cases when models are random and may or may not provide good
approximations, as long as "good" models are more likely than "bad" models. Our
results are based on the use of properties of martingales. Our motivation comes
from using random sample sets and interpolation models in derivative-free
optimization. However, our framework is general and can be applied with any
source of uncertainty in the model. We discuss various applications for our
methods in the paper.


title: On partial sparse recovery

abstract:
  We consider the problem of recovering a partially sparse solution of an
underdetermined system of linear equations by minimizing the $\ell_1$-norm of
the part of the solution vector which is known to be sparse. Such a problem is
closely related to a classical problem in Compressed Sensing where the
$\ell_1$-norm of the whole solution vector is minimized. We introduce analogues
of restricted isometry and null space properties for the recovery of partially
sparse vectors and show that these new properties are implied by their original
counterparts. We show also how to extend recovery under noisy measurements to
the partially sparse case.


title: High-dimensional Mixed Graphical Models

abstract:
  While graphical models for continuous data (Gaussian graphical models) and
discrete data (Ising models) have been extensively studied, there is little
work on graphical models linking both continuous and discrete variables (mixed
data), which are common in many scientific applications. We propose a novel
graphical model for mixed data, which is simple enough to be suitable for
high-dimensional data, yet flexible enough to represent all possible graph
structures. We develop a computationally efficient regression-based algorithm
for fitting the model by focusing on the conditional log-likelihood of each
variable given the rest. The parameters have a natural group structure, and
sparsity in the fitted graph is attained by incorporating a group lasso
penalty, approximated by a weighted $\ell_1$ penalty for computational
efficiency. We demonstrate the effectiveness of our method through an extensive
simulation study and apply it to a music annotation data set (CAL500),
obtaining a sparse and interpretable graphical model relating the continuous
features of the audio signal to categorical variables such as genre, emotions,
and usage associated with particular songs. While we focus on binary discrete
variables, we also show that the proposed methodology can be easily extended to
general discrete variables.


title:
Energy relaxation of exciton-polariton condensates in quasi-1D
  microcavities

abstract:
  We present a time-resolved study of energy relaxation and trapping dynamics
of polariton condensates in a semiconductor microcavity ridge. The combination
of two non-resonant, pulsed laser sources in a GaAs ridge-shaped microcavity
gives rise to profuse quantum phenomena where the repulsive potentials created
by the lasers allow the modulation and control of the polariton flow. We
analyze in detail the dependence of the dynamics on the power of both lasers
and determine the optimum conditions for realizing an all-optical polariton
condensate transistor switch. The experimental results are interpreted in the
light of simulations based on a generalized Gross-Pitaevskii equation,
including incoherent pumping, decay and energy relaxation within the
condensate.


title: Free actions of compact quantum group on unital C*-algebras

abstract:
  Let F be a field, G a finite group, and Map(G,F) the Hopf algebra of all
set-theoretic maps G->F. If E is a finite field extension of F and G is its
Galois group, the extension is Galois if and only if the canonical map
resulting from viewing E as a Map(G,F)-comodule is an isomorphism. Similarly, a
finite covering space is regular if and only if the analogous canonical map is
an isomorphism. In this paper we extend this point of view to actions of
compact quantum groups on unital C*-algebras. We prove that such an action is
free if and only if the canonical map (obtained using the underlying Hopf
algebra of the compact quantum group) is an isomorphism. In particular, we are
able to express the freeness of a compact Hausdorff topological group action on
a compact Hausdorff topological space in algebraic terms.


title: The EMC Effect and High Momentum Nucleons in Nuclei

abstract:
  Recent developments in understanding the influence of the nucleus on
deep-inelastic structure functions, the EMC effect, are reviewed. A new data
base which expresses ratios of structure functions in terms of the Bjorken
variable $x_A=AQ^2/(2M_A q_0)$ is presented. Information about two-nucleon
short-range correlations from experiments is also discussed and the remarkable
linear relation between short-range correlations and teh EMC effect is
reviewed. A convolution model that relates the underlying source of the EMC
effect to modification of either the mean-field nucleons or the short-range
correlated nucleons is presented. It is shown that both approaches are equally
successful in describing the current EMC data.


title: On MITL and alternating timed automata

abstract:
  One clock alternating timed automata OCATA have been recently introduced as
natural extension of (one clock) timed automata to express the semantics of MTL
(Ouaknine, Worrell 2005). We consider the application of OCATA to problem of
model-checking MITL formulas (a syntactic fragment of MTL) against timed
automata. We introduce a new semantics for OCATA where, intuitively, clock
valuations are intervals instead of single real values. Thanks to this new
semantics, we show that we can bound the number of clock copies that are
necessary to allow an OCATA to recognise the models of an MITL formula.
Equipped with this technique, we propose a new algorithm to translate an MITL
formula into a timed automaton, and we sketch several ideas to define new model
checking algorithms for MITL.


title:
Very Low Mass Stellar and Substellar Companions to Solar-Like Stars From
  MARVELS V: A Low Eccentricity Brown Dwarf from the Driest Part of the Desert,
  MARVELS-6b

abstract:
  We describe the discovery of a likely brown dwarf (BD) companion with a
minimum mass of 31.7 +/- 2.0 M_Jup to GSC 03546-01452 from the MARVELS radial
velocity survey, which we designate as MARVELS-6b. For reasonable priors, our
analysis gives a probability of 72% that MARVELS-6b has a mass below the
hydrogen-burning limit of 0.072 M_Sun, and thus it is a high-confidence BD
companion. It has a moderately long orbital period of 47.8929 +0.0063/-0.0062
days with a low eccentricty of 0.1442 +0.0078/-0.0073, and a semi-amplitude of
1644 +12/-13 m/s. Moderate resolution spectroscopy of the host star has
determined the following parameters: T_eff = 5598 +/- 63, log g = 4.44 +/-
0.17, and [Fe/H] = +0.40 +/- 0.09. Based upon these measurements, GSC
03546-01452 has a probable mass and radius of M_star = 1.11 +/- 0.11 M_Sun and
R_star = 1.06 +/- 0.23 R_Sun with an age consistent with less than ~6 Gyr at a
distance of 219 +/- 21 pc from the Sun. Although MARVELS-6b is not observed to
transit, we cannot definitively rule out a transiting configuration based on
our observations. There is a visual companion detected with Lucky Imaging at
7.7 arcsec from the host star, but our analysis shows that it is not bound to
this system. The minimum mass of MARVELS-6b exists at the minimum of the mass
functions for both stars and planets, making this a rare object even compared
to other BDs.


title: Asymptotic Behaviour and Ratios of Complexity in Cellular Automata

abstract:
  We study the asymptotic behaviour of symbolic computing systems, notably
one-dimensional cellular automata (CA), in order to ascertain whether and at
what rate the number of complex versus simple rules dominate the rule space for
increasing neighbourhood range and number of symbols (or colours), and how
different behaviour is distributed in the spaces of different cellular automata
formalisms. Using two different measures, Shannon's block entropy and
Kolmogorov complexity, the latter approximated by two different methods
(lossless compressibility and block decomposition), we arrive at the same trend
of larger complex behavioural fractions. We also advance a notion of asymptotic
and limit behaviour for individual rules, both over initial conditions and
runtimes, and we provide a formalisation of Wolfram's classification as a limit
function in terms of Kolmogorov complexity.


title:
High-order multiderivative time integrators for hyperbolic conservation
  laws

abstract:
  Multiderivative time integrators have a long history of development for
ordinary differential equations, and yet to date, only a small subset of these
methods have been explored as a tool for solving partial differential equations
(PDEs). This large class of time integrators include all popular (multistage)
Runge-Kutta as well as single-step (multiderivative) Taylor methods. (The
latter are commonly referred to as Lax-Wendroff methods when applied to PDEs.)
In this work, we offer explicit multistage multiderivative time integrators for
hyperbolic conservation laws. Like Lax-Wendroff methods, multiderivative
integrators permit the evaluation of higher derivatives of the unknown in order
to decrease the memory footprint and communication overhead. Like traditional
Runge-Kutta methods, multiderivative integrators admit the addition of extra
stages, which introduce extra degrees of freedom that can be used to increase
the order of accuracy or modify the region of absolute stability. We describe a
general framework for how these methods can be applied to two separate spatial
discretizations: the discontinuous Galerkin (DG) method and the finite
difference essentially non-oscillatory (FD-WENO) method. The two proposed
implementations are substantially different: for DG we leverage techniques that
are closely related to generalized Riemann solvers; for FD-WENO we construct
higher spatial derivatives with central differences. Among multiderivative time
integrators, we argue that multistage two-derivative methods have the greatest
potential for multidimensional applications, because they only require the flux
function and its Jacobian, which is readily available. Numerical results
indicate that multiderivative methods are indeed competitive with popular
strong stability preserving time integrators.


title: The Bayesian Block Algorithm

abstract:
  This presentation describes the Bayesian Block algorithm in the context of
its application to analysis of time series data from the Fermi Gamma Ray Space
Telescope. More generally this algorithm performs optimal segmentation analysis
on sequential data in any mode, with arbitrary sampling and in the presence of
gaps and exposure variations. A new procedure for correcting for backgrounds is
also described.


title:
Long-term optical polarization variability of the tev blazar
  1es~1959+650

abstract:
  A detailed analysis of the optical polarimetric variability of the TeV blazar
1ES 1959+650 from 2007 October 18 to 2011 May 5 is presented. The source showed
a maximum and minimum brightness states in the R-band of 14.08$\pm$0.03 mag and
15.20$\pm$0.03 mag, respectively, with a maximum variation of 1.12 mag, and
also a maximum polarization degree of $P=$(12.2$\pm$0.7)%, with a maximum
variation of 10.7%. From August to November 2009, a correlation between the
optical $R$-band flux and the degree of linear polarization was found, with a
correlation coefficient $r_{pol}$=0.984$\pm$0.025. The source presented a
preferential position angle of optical polarization of $\sim153^{\circ}$, with
variations of $10\degr$-$50\degr$, that is in agreement with the projected
position angle of the parsec scale jet found at 43 GHz. From the Stokes
parameters we infer the existence of two optically-thin synchrotron components
that contribute to the polarized flux. One of them is stable, with a constant
polarization degree of 4%. Assuming a stationary shock for the variable
component, we estimated some parameters associated with the physics of the
relativistic jet: the magnetic field, $B\sim$0.06 G, the Doppler factor,
$\delta_{0}\sim$23, the viewing angle, $\Phi\sim2.4\degr$, and the size of the
emission region $r_b\sim5.6\times10^{17}$ cm. Our study is consistent with the
spine-sheath model to explain the polarimetric variability displayed by this
source during our monitoring.