title: Uncertain Reasoning Using Maximum Entropy Inference

abstract:
  The use of maximum entropy inference in reasoning with uncertain information
is commonly justified by an information-theoretic argument. This paper
discusses a possible objection to this information-theoretic justification and
shows how it can be met. I then compare maximum entropy inference with certain
other currently popular methods for uncertain reasoning. In making such a
comparison, one must distinguish between static and dynamic theories of degrees
of belief: a static theory concerns the consistency conditions for degrees of
belief at a given time; whereas a dynamic theory concerns how one's degrees of
belief should change in the light of new information. It is argued that maximum
entropy is a dynamic theory and that a complete theory of uncertain reasoning
can be gotten by combining maximum entropy inference with probability theory,
which is a static theory. This total theory, I argue, is much better grounded
than are other theories of uncertain reasoning.


title: Independence and Bayesian Updating Methods

abstract:
  Duda, Hart, and Nilsson have set forth a method for rule-based inference
systems to use in updating the probabilities of hypotheses on the basis of
multiple items of new evidence. Pednault, Zucker, and Muresan claimed to give
conditions under which independence assumptions made by Duda et al. preclude
updating-that is, prevent the evidence from altering the probabilities of the
hypotheses. Glymour refutes Pednault et al.'s claim with a counterexample of a
rather special form (one item of evidence is incompatible with all but one of
the hypotheses); he raises, but leaves open, the question whether their result
would be true with an added assumption to rule out such special cases. We show
that their result does not hold even with the added assumption, but that it can
nevertheless be largely salvaged. Namely, under the conditions assumed by
Pednault et al., at most one of the items of evidence can alter the probability
of any given hypothesis; thus, although updating is possible, multiple updating
for any of the hypotheses is precluded.


title: A Constraint Propagation Approach to Probabilistic Reasoning

abstract:
  The paper demonstrates that strict adherence to probability theory does not
preclude the use of concurrent, self-activated constraint-propagation
mechanisms for managing uncertainty. Maintaining local records of
sources-of-belief allows both predictive and diagnostic inferences to be
activated simultaneously and propagate harmoniously towards a stable
equilibrium.


title: Relative Entropy, Probabilistic Inference and AI

abstract:
  Various properties of relative entropy have led to its widespread use in
information theory. These properties suggest that relative entropy has a role
to play in systems that attempt to perform inference in terms of probability
distributions. In this paper, I will review some basic properties of relative
entropy as well as its role in probabilistic inference. I will also mention
briefly a few existing and potential applications of relative entropy to
so-called artificial intelligence (AI).


title:
Foundations of Probability Theory for AI - The Application of
  Algorithmic Probability to Problems in Artificial Intelligence

abstract:
  This paper covers two topics: first an introduction to Algorithmic Complexity
Theory: how it defines probability, some of its characteristic properties and
past successful applications. Second, we apply it to problems in A.I. - where
it promises to give near optimum search procedures for two very broad classes
of problems.


title:
Selecting Uncertainty Calculi and Granularity: An Experiment in
  Trading-Off Precision and Complexity

abstract:
  The management of uncertainty in expert systems has usually been left to ad
hoc representations and rules of combinations lacking either a sound theory or
clear semantics. The objective of this paper is to establish a theoretical
basis for defining the syntax and semantics of a small subset of calculi of
uncertainty operating on a given term set of linguistic statements of
likelihood. Each calculus is defined by specifying a negation, a conjunction
and a disjunction operator. Families of Triangular norms and conorms constitute
the most general representations of conjunction and disjunction operators.
These families provide us with a formalism for defining an infinite number of
different calculi of uncertainty. The term set will define the uncertainty
granularity, i.e. the finest level of distinction among different
quantifications of uncertainty. This granularity will limit the ability to
differentiate between two similar operators. Therefore, only a small finite
subset of the infinite number of calculi will produce notably different
results. This result is illustrated by two experiments where nine and eleven
different calculi of uncertainty are used with three term sets containing five,
nine, and thirteen elements, respectively. Finally, the use of context
dependent rule set is proposed to select the most appropriate calculus for any
given situation. Such a rule set will be relatively small since it must only
describe the selection policies for a small number of calculi (resulting from
the analyzed trade-off between complexity and precision).


title: A Framework for Non-Monotonic Reasoning About Probabilistic Assumptions

abstract:
  Attempts to replicate probabilistic reasoning in expert systems have
typically overlooked a critical ingredient of that process. Probabilistic
analysis typically requires extensive judgments regarding interdependencies
among hypotheses and data, and regarding the appropriateness of various
alternative models. The application of such models is often an iterative
process, in which the plausibility of the results confirms or disconfirms the
validity of assumptions made in building the model. In current expert systems,
by contrast, probabilistic information is encapsulated within modular rules
(involving, for example, "certainty factors"), and there is no mechanism for
reviewing the overall form of the probability argument or the validity of the
judgments entering into it.


title: Metaprobability and Dempster-Shafer in Evidential Reasoning

abstract:
  Evidential reasoning in expert systems has often used ad-hoc uncertainty
calculi. Although it is generally accepted that probability theory provides a
firm theoretical foundation, researchers have found some problems with its use
as a workable uncertainty calculus. Among these problems are representation of
ignorance, consistency of probabilistic judgements, and adjustment of a priori
judgements with experience. The application of metaprobability theory to
evidential reasoning is a new approach to solving these problems.
Metaprobability theory can be viewed as a way to provide soft or hard
constraints on beliefs in much the same manner as the Dempster-Shafer theory
provides constraints on probability masses on subsets of the state space. Thus,
we use the Dempster-Shafer theory, an alternative theory of evidential
reasoning to illuminate metaprobability theory as a theory of evidential
reasoning. The goal of this paper is to compare how metaprobability theory and
Dempster-Shafer theory handle the adjustment of beliefs with evidence with
respect to a particular thought experiment. Sections 2 and 3 give brief
descriptions of the metaprobability and Dempster-Shafer theories.
Metaprobability theory deals with higher order probabilities applied to
evidential reasoning. Dempster-Shafer theory is a generalization of probability
theory which has evolved from a theory of upper and lower probabilities.
Section 4 describes a thought experiment and the metaprobability and
DempsterShafer analysis of the experiment. The thought experiment focuses on
forming beliefs about a population with 6 types of members {1, 2, 3, 4, 5, 6}.
A type is uniquely defined by the values of three features: A, B, C. That is,
if the three features of one member of the population were known then its type
could be ascertained. Each of the three features has two possible values, (e.g.
A can be either "a0" or "al"). Beliefs are formed from evidence accrued from
two sensors: sensor A, and sensor B. Each sensor senses the corresponding
defining feature. Sensor A reports that half of its observations are "a0" and
half the observations are 'al'. Sensor B reports that half of its observations
are ``b0,' and half are "bl". Based on these two pieces of evidence, what
should be the beliefs on the distribution of types in the population? Note that
the third feature is not observed by any sensor.


title: Implementing Probabilistic Reasoning

abstract:
  General problems in analyzing information in a probabilistic database are
considered. The practical difficulties (and occasional advantages) of storing
uncertain data, of using it conventional forward- or backward-chaining
inference engines, and of working with a probabilistic version of resolution
are discussed. The background for this paper is the incorporation of uncertain
reasoning facilities in MRS, a general-purpose expert system building tool.


title: Probability Judgement in Artificial Intelligence

abstract:
  This paper is concerned with two theories of probability judgment: the
Bayesian theory and the theory of belief functions. It illustrates these
theories with some simple examples and discusses some of the issues that arise
when we try to implement them in expert systems. The Bayesian theory is well
known; its main ideas go back to the work of Thomas Bayes (1702-1761). The
theory of belief functions, often called the Dempster-Shafer theory in the
artificial intelligence community, is less well known, but it has even older
antecedents; belief-function arguments appear in the work of George Hooper
(16401723) and James Bernoulli (1654-1705). For elementary expositions of the
theory of belief functions, see Shafer (1976, 1985).


title: A Framework for Comparing Uncertain Inference Systems to Probability

abstract:
  Several different uncertain inference systems (UISs) have been developed for
representing uncertainty in rule-based expert systems. Some of these, such as
Mycin's Certainty Factors, Prospector, and Bayes' Networks were designed as
approximations to probability, and others, such as Fuzzy Set Theory and
DempsterShafer Belief Functions were not. How different are these UISs in
practice, and does it matter which you use? When combining and propagating
uncertain information, each UIS must, at least by implication, make certain
assumptions about correlations not explicily specified. The maximum entropy
principle with minimum cross-entropy updating, provides a way of making
assumptions about the missing specification that minimizes the additional
information assumed, and thus offers a standard against which the other UISs
can be compared. We describe a framework for the experimental comparison of the
performance of different UISs, and provide some illustrative results.


title: Inductive Inference and the Representation of Uncertainty

abstract:
  The form and justification of inductive inference rules depend strongly on
the representation of uncertainty. This paper examines one generic
representation, namely, incomplete information. The notion can be formalized by
presuming that the relevant probabilities in a decision problem are known only
to the extent that they belong to a class K of probability distributions. The
concept is a generalization of a frequent suggestion that uncertainty be
represented by intervals or ranges on probabilities. To make the representation
useful for decision making, an inductive rule can be formulated which
determines, in a well-defined manner, a best approximation to the unknown
probability, given the set K. In addition, the knowledge set notion entails a
natural procedure for updating -- modifying the set K given new evidence.
Several non-intuitive consequences of updating emphasize the differences
between inference with complete and inference with incomplete information.


title: Machine Learning, Clustering, and Polymorphy

abstract:
  This paper describes a machine induction program (WITT) that attempts to
model human categorization. Properties of categories to which human subjects
are sensitive includes best or prototypical members, relative contrasts between
putative categories, and polymorphy (neither necessary or sufficient features).
This approach represents an alternative to usual Artificial Intelligence
approaches to generalization and conceptual clustering which tend to focus on
necessary and sufficient feature rules, equivalence classes, and simple search
and match schemes. WITT is shown to be more consistent with human
categorization while potentially including results produced by more traditional
clustering schemes. Applications of this approach in the domains of expert
systems and information retrieval are also discussed.


title: Induction, of and by Probability

abstract:
  This paper examines some methods and ideas underlying the author's successful
probabilistic learning systems(PLS), which have proven uniquely effective and
efficient in generalization learning or induction. While the emerging
principles are generally applicable, this paper illustrates them in heuristic
search, which demands noise management and incremental learning. In our
approach, both task performance and learning are guided by probability.
Probabilities are incrementally normalized and revised, and their errors are
located and corrected.


title: An Odds Ratio Based Inference Engine

abstract:
  Expert systems applications that involve uncertain inference can be
represented by a multidimensional contingency table. These tables offer a
general approach to inferring with uncertain evidence, because they can embody
any form of association between any number of pieces of evidence and
conclusions. (Simpler models may be required, however, if the number of pieces
of evidence bearing on a conclusion is large.) This paper presents a method of
using these tables to make uncertain inferences without assumptions of
conditional independence among pieces of evidence or heuristic combining rules.
As evidence is accumulated, new joint probabilities are calculated so as to
maintain any dependencies among the pieces of evidence that are found in the
contingency table. The new conditional probability of the conclusion is then
calculated directly from these new joint probabilities and the conditional
probabilities in the contingency table.


title: A Framework for Control Strategies in Uncertain Inference Networks

abstract:
  Control Strategies for hierarchical tree-like probabilistic inference
networks are formulated and investigated. Strategies that utilize staged
look-ahead and temporary focus on subgoals are formalized and refined using the
Depth Vector concept that serves as a tool for defining the 'virtual tree'
regarded by the control strategy. The concept is illustrated by four types of
control strategies for three-level trees that are characterized according to
their Depth Vector, and according to the way they consider intermediate nodes
and the role that they let these nodes play. INFERENTI is a computerized
inference system written in Prolog, which provides tools for exercising a
variety of control strategies. The system also provides tools for simulating
test data and for comparing the relative average performance under different
strategies.


title: Combining Uncertain Estimates

abstract:
  In a real expert system, one may have unreliable, unconfident, conflicting
estimates of the value for a particular parameter. It is important for decision
making that the information present in this aggregate somehow find its way into
use. We cast the problem of representing and combining uncertain estimates as
selection of two kinds of functions, one to determine an estimate, the other
its uncertainty. The paper includes a long list of properties that such
functions should satisfy, and it presents one method that satisfies them.


title:
Confidence Factors, Empiricism and the Dempster-Shafer Theory of
  Evidence

abstract:
  The issue of confidence factors in Knowledge Based Systems has become
increasingly important and Dempster-Shafer (DS) theory has become increasingly
popular as a basis for these factors. This paper discusses the need for an
empirical lnterpretatlon of any theory of confidence factors applied to
Knowledge Based Systems and describes an empirical lnterpretatlon of DS theory
suggesting that the theory has been extensively misinterpreted. For the
essentially syntactic DS theory, a model is developed based on sample spaces,
the traditional semantic model of probability theory. This model is used to
show that, if belief functions are based on reasonably accurate sampling or
observation of a sample space, then the beliefs and upper probabilities as
computed according to DS theory cannot be interpreted as frequency ratios.
Since many proposed applications of DS theory use belief functions in
situations with statistically derived evidence (Wesley [1]) and seem to appeal
to statistical intuition to provide an lnterpretatlon of the results as has
Garvey [2], it may be argued that DS theory has often been misapplied.


title: Incidence Calculus: A Mechanism for Probabilistic Reasoning

abstract:
  Mechanisms for the automation of uncertainty are required for expert systems.
Sometimes these mechanisms need to obey the properties of probabilistic
reasoning. A purely numeric mechanism, like those proposed so far, cannot
provide a probabilistic logic with truth functional connectives. We propose an
alternative mechanism, Incidence Calculus, which is based on a representation
of uncertainty using sets of points, which might represent situations, models
or possible worlds. Incidence Calculus does provide a probabilistic logic with
truth functional connectives.


title: Evidential Confirmation as Transformed Probability

abstract:
  A considerable body of work in AI has been concerned with aggregating
measures of confirmatory and disconfirmatory evidence for a common set of
propositions. Claiming classical probability to be inadequate or inappropriate,
several researchers have gone so far as to invent new formalisms and methods.
We show how to represent two major such alternative approaches to evidential
confirmation not only in terms of transformed (Bayesian) probability, but also
in terms of each other. This unifies two of the leading approaches to
confirmation theory, by showing that a revised MYCIN Certainty Factor method
[12] is equivalent to a special case of Dempster-Shafer theory. It yields a
well-understood axiomatic basis, i.e. conditional independence, to interpret
previous work on quantitative confirmation theory. It substantially resolves
the "taxe-them-or-leave-them" problem of priors: MYCIN had to leave them out,
while PROSPECTOR had to have them in. It recasts some of confirmation theory's
advantages in terms of the psychological accessibility of probabilistic
information in different (transformed) formats. Finally, it helps to unify the
representation of uncertain reasoning (see also [11]).


title: Interval-Based Decisions for Reasoning Systems

abstract:
  This essay looks at decision-making with interval-valued probability
measures. Existing decision methods have either supplemented expected utility
methods with additional criteria of optimality, or have attempted to supplement
the interval-valued measures. We advocate a new approach, which makes the
following questions moot: 1. which additional criteria to use, and 2. how wide
intervals should be. In order to implement the approach, we need more
epistemological information. Such information can be generated by a rule of
acceptance with a parameter that allows various attitudes toward error, or can
simply be declared. In sketch, the argument is: 1. probability intervals are
useful and natural in All. systems; 2. wide intervals avoid error, but are
useless in some risk sensitive decision-making; 3. one may obtain narrower
intervals if one is less cautious; 4. if bodies of knowledge can be ordered by
their caution, one should perform the decision analysis with the acceptable
body of knowledge that is the most cautious, of those that are useful. The
resulting behavior differs from that of a behavioral probabilist (a Bayesian)
because in the proposal, 5. intervals based on successive bodies of knowledge
are not always nested; 6. if the agent uses a probability for a particular
decision, she need not commit to that probability for credence or future
decision; and 7. there may be no acceptable body of knowledge that is useful;
hence, sometimes no decision is mandated.


title:
Machine Generalization and Human Categorization: An
  Information-Theoretic View

abstract:
  In designing an intelligent system that must be able to explain its reasoning
to a human user, or to provide generalizations that the human user finds
reasonable, it may be useful to take into consideration psychological data on
what types of concepts and categories people naturally use. The psychological
literature on concept learning and categorization provides strong evidence that
certain categories are more easily learned, recalled, and recognized than
others. We show here how a measure of the informational value of a category
predicts the results of several important categorization experiments better
than standard alternative explanations. This suggests that information-based
approaches to machine generalization may prove particularly useful and natural
for human users of the systems.


title: Exact Reasoning Under Uncertainty

abstract:
  This paper focuses on designing expert systems to support decision making in
complex, uncertain environments. In this context, our research indicates that
strictly probabilistic representations, which enable the use of
decision-theoretic reasoning, are highly preferable to recently proposed
alternatives (e.g., fuzzy set theory and Dempster-Shafer theory). Furthermore,
we discuss the language of influence diagrams and a corresponding methodology
-decision analysis -- that allows decision theory to be used effectively and
efficiently as a decision-making aid. Finally, we use RACHEL, a system that
helps infertile couples select medical treatments, to illustrate the
methodology of decision analysis as basis for expert decision systems.


title:
The Estimation of Subjective Probabilities via Categorical Judgments of
  Uncertainty

abstract:
  Theoretically as well as experimentally it is investigated how people
represent their knowledge in order to make decisions or to share their
knowledge with others. Experiment 1 probes into the ways how people 6ather
information about the frequencies of events and how the requested response
mode, that is, numerical vs. verbal estimates interferes with this knowledge.
The least interference occurs if the subjects are allowed to give verbal
responses. From this it is concluded that processing knowledge about
uncertainty categorically, that is, by means of verbal expressions, imposes
less mental work load on the decision matter than numerical processing.
Possibility theory is used as a framework for modeling the individual usage of
verbal categories for grades of uncertainty. The 'elastic' constraints on the
verbal expressions for every sing1e subject are determined in Experiment 2 by
means of sequential calibration. In further experiments it is shown that the
superiority of the verbal processing of knowledge about uncertainty guise
generally reduces persistent biases reported in the literature: conservatism
(Experiment 3) and neg1igence of regression (Experiment 4). The reanalysis of
Hormann's data reveal that in verbal Judgments people exhibit sensitivity for
base rates and are not prone to the conjunction fallacy. In a final experiment
(5) about predictions in a real-life situation it turns out that in a numerical
forecasting task subjects restricted themselves to those parts of their
knowledge which are numerical. On the other hand subjects in a verbal
forecasting task accessed verbally as well as numerically stated knowledge.
Forecasting is structurally related to the estimation of probabilities for rare
events insofar as supporting and contradicting arguments have to be evaluated
and the choice of the final Judgment has to be Justified according to the
evidence brought forward. In order to assist people in such choice situations a
formal model for the interactive checking of arguments has been developed. The
model transforms the normal-language quantifiers used in the arguments into
fuzzy numbers and evaluates the given train of arguments by means of fuzzy
numerica1 operations. Ambiguities in the meanings of quantifiers are resolved
interactively.


title: A Cure for Pathological Behavior in Games that Use Minimax

abstract:
  The traditional approach to choosing moves in game-playing programs is the
minimax procedure. The general belief underlying its use is that increasing
search depth improves play. Recent research has shown that given certain
simplifying assumptions about a game tree's structure, this belief is
erroneous: searching deeper decreases the probability of making a correct move.
This phenomenon is called game tree pathology. Among these simplifying
assumptions is uniform depth of win/loss (terminal) nodes, a condition which is
not true for most real games. Analytic studies in [10] have shown that if every
node in a pathological game tree is made terminal with probability exceeding a
certain threshold, the resulting tree is nonpathological. This paper considers
a new evaluation function which recognizes increasing densities of forced wins
at deeper levels in the tree. This property raises two points that strengthen
the hypothesis that uniform win depth causes pathology. First, it proves
mathematically that as search deepens, an evaluation function that does not
explicitly check for certain forced win patterns becomes decreasingly likely to
force wins. This failing predicts the pathological behavior of the original
evaluation function. Second, it shows empirically that despite recognizing
fewer mid-game wins than the theoretically predicted minimum, the new function
is nonpathological.


title: An Evaluation of Two Alternatives to Minimax

abstract:
  In the field of Artificial Intelligence, traditional approaches to choosing
moves in games involve the we of the minimax algorithm. However, recent
research results indicate that minimizing may not always be the best approach.
In this paper we summarize the results of some measurements on several model
games with several different evaluation functions. These measurements, which
are presented in detail in [NPT], show that there are some new algorithms that
can make significantly better use of evaluation function values than the
minimax algorithm does.


title: Intelligent Probabilistic Inference

abstract:
  The analysis of practical probabilistic models on the computer demands a
convenient representation for the available knowledge and an efficient
algorithm to perform inference. An appealing representation is the influence
diagram, a network that makes explicit the random variables in a model and
their probabilistic dependencies. Recent advances have developed solution
procedures based on the influence diagram. In this paper, we examine the
fundamental properties that underlie those techniques, and the information
about the probabilistic structure that is available in the influence diagram
representation. The influence diagram is a convenient representation for
computer processing while also being clear and non-mathematical. It displays
probabilistic dependence precisely, in a way that is intuitive for decision
makers and experts to understand and communicate. As a result, the same
influence diagram can be used to build, assess and analyze a model,
facilitating changes in the formulation and feedback from sensitivity analysis.
The goal in this paper is to determine arbitrary conditional probability
distributions from a given probabilistic model. Given qualitative information
about the dependence of the random variables in the model we can, for a
specific conditional expression, specify precisely what quantitative
information we need to be able to determine the desired conditional probability
distribution. It is also shown how we can find that probability distribution by
performing operations locally, that is, over subspaces of the joint
distribution. In this way, we can exploit the conditional independence present
in the model to avoid having to construct or manipulate the full joint
distribution. These results are extended to include maximal processing when the
information available is incomplete, and optimal decision making in an
uncertain environment. Influence diagrams as a computer-aided modeling tool
were developed by Miller, Merkofer, and Howard [5] and extended by Howard and
Matheson [2]. Good descriptions of how to use them in modeling are in Owen [7]
and Howard and Matheson [2]. The notion of solving a decision problem through
influence diagrams was examined by Olmsted [6] and such an algorithm was
developed by Shachter [8]. The latter paper also shows how influence diagrams
can be used to perform a variety of sensitivity analyses. This paper extends
those results by developing a theory of the properties of the diagram that are
used by the algorithm, and the information needed to solve arbitrary
probability inference problems. Section 2 develops the notation and the
framework for the paper and the relationship between influence diagrams and
joint probability distributions. The general probabilistic inference problem is
posed in Section 3. In Section 4 the transformations on the diagram are
developed and then put together into a solution procedure in Section 5. In
Section 6, this procedure is used to calculate the information requirement to
solve an inference problem and the maximal processing that can be performed
with incomplete information. Section 7 contains a summary of results.


title:
Developing and Analyzing Boundary Detection Operators Using
  Probabilistic Models

abstract:
  Most feature detectors such as edge detectors or circle finders are
statistical, in the sense that they decide at each point in an image about the
presence of a feature, this paper describes the use of Bayesian feature
detectors.


title: Strong & Weak Methods: A Logical View of Uncertainty

abstract:
  The last few years has seen a growing debate about techniques for managing
uncertainty in AI systems. Unfortunately this debate has been cast as a rivalry
between AI methods and classical probability based ones. Three arguments for
extending the probability framework of uncertainty are presented, none of which
imply a challenge to classical methods. These are (1) explicit representation
of several types of uncertainty, specifically possibility and plausibility, as
well as probability, (2) the use of weak methods for uncertainty management in
problems which are poorly defined, and (3) symbolic representation of different
uncertainty calculi and methods for choosing between them.


abstract:
  It is proposed to apply modern methods of nonlinear nonequilibrium
statistical mechanics to develop software algorithms that will optimally
respond to targets within short response times with minimal computer resources.
This Statistical Mechanics Algorithm for Response to Targets (SMART) can be
developed with a view towards its future implementation into a hardwired
Statistical Algorithm Multiprocessor (SAM) to enhance the efficiency and speed
of response to targets (SMART_SAM).


title: Probabilistic Conflict Resolution in Hierarchical Hypothesis Spaces

abstract:
  Artificial intelligence applications such as industrial robotics, military
surveillance, and hazardous environment clean-up, require situation
understanding based on partial, uncertain, and ambiguous or erroneous evidence.
It is necessary to evaluate the relative likelihood of multiple possible
hypotheses of the (current) situation faced by the decision making program.
Often, the evidence and hypotheses are hierarchical in nature. In image
understanding tasks, for example, evidence begins with raw imagery, from which
ambiguous features are extracted which have multiple possible aggregations
providing evidential support for the presence of multiple hypothesis of objects
and terrain, which in turn aggregate in multiple ways to provide partial
evidence for different interpretations of the ambient scene. Information fusion
for military situation understanding has a similar evidence/hypothesis
hierarchy from multiple sensor through message level interpretations, and also
provides evidence at multiple levels of the doctrinal hierarchy of military
forces.


title: Knowledge Structures and Evidential Reasoning in Decision Analysis

abstract:
  The roles played by decision factors in making complex subject are decisions
are characterized by how these factors affect the overall decision. Evidence
that partially matches a factor is evaluated, and then effective computational
rules are applied to these roles to form an appropriate aggregation of the
evidence. The use of this technique supports the expression of deeper levels of
causality, and may also preserve the cognitive structure of the decision maker
better than the usual weighting methods, certainty-factor or other
probabilistic models can.


title:
Environment-induced anisotropy and the sensitivity of the radical pair
  mechanism in the avian compass

abstract:
  Several experiments over the years have shown that the Earth's magnetic field
is essential for orientation in birds migration. The most promising explanation
for this orientation is the photo-stimulated radical pair (RP) mechanism. In
order to define a reference frame for the orientation task radicals must have
an intrinsic anisotropy. We show that this kind of anisotropy, and consequently
the entanglement in the model, are not necessary for the proper functioning of
the compass. Classically correlated initial conditions for the RP, subjected to
a fast decoherence process, are able to provide the anisotropy required. Even a
dephasing environment can provide the necessary frame for the compass to work,
and also implies fast decay of any quantum correlation in the system without
damaging the orientation ability. This fact significantly expands the range of
applicability of the RP mechanism providing more elements for experimental
search.


title:
Nonlinearity and linearity, friends or enemies? Algebraic Analyzation of
  Science:)

abstract:
  Certain operator-valued functions and new generating structures (instead of
generating functionals) are proposed for the analysis of equations for n-point
information (n-pi). Some remarks are made concerning the intertwining of
linearity and nonlinearity, and functions defined on non-numerical objects.


title:
Steps towards a solution of the FS Aurigae puzzle. II. Confirmation of
  the intermediate polar status

abstract:
  FS Aur is famous for a variety of uncommon and puzzling periodic photometric
and spectroscopic variabilities. It was previously proposed that the precession
of a fast-rotating magnetically accreting white dwarf can successfully explain
these phenomena. We present a study of FS Aur based on two extensive sets of
optical photometric observations and three X-ray data sets in which we intended
to verify whether the observational properties of the long period modulations
observed in FS Aur and V455 And are similar in appearance to the spin
modulation in ordinary IPs. These new optical observations have revealed, for
the first time in photometric data, the variability with the presumed
precession period of the white dwarf, previously seen only spectroscopically.
We also found that the modulations with the precession and orbital periods are
evident in X-ray data. We show that the observed properties of FS Aur closely
resemble those of other intermediate polars, thus confirming this cataclysmic
variable as a member of the class.
  Our analysis of multicolour observations of intermediate polars has shown
that time-series analysis of colour indices appears to be a powerful technique
for revealing hidden variabilities and shedding light on their nature. We have
found that the (B-I) power spectrum of V1223 Sgr indicates the presence in the
data of the spin pulsation which is not seen in the optical light curve at all.
Also, the analysis of the colour indices of V455 And revealed the presence of
the photometric variations which, similarly to FS Aur, was previously observed
only spectroscopically.


title: LSST's DC Bias Against Planets and Galactic-Plane Science

abstract:
  An LSST-like survey of the Galactic plane (deep images every 3-4 days) could
probe the Galactic distribution of planets by two distinct methods:
gravitational microlensing of planets beyond the snow line and transits by
planets very close to their hosts. The survey would identify over 250
disk-lens/disk-source microlensing events per year that peak at r<19, including
10% reaching the high magnification A>100 that makes them especially sensitive
to planets. Intensive followup of these events would be required to find
planets, similar to what is done presently for Galactic bulge microlensing. The
same data would enable a wealth of other science, including detection of
isolated black holes, systematic study of brown-dwarf binaries, a pre-explosion
lightcurve of the next Galactic supernova, pre-explosion lightcurves of stellar
mergers, early nova lightcurves, proper motions of many more stars than can be
reached by GAIA, and probably much more. As usual, the most exciting
discoveries from probing the huge parameter space encompassed by Galactic-plane
stellar populations might well be serendipitous. Unfortunately, the LSST
collaboration plans to exclude the first and fourth quadrants of the Galactic
plane from their "synoptic" observations because the DC image that resulted
from repeated observations would be limited by crowding. I demonstrate that the
majority of this science can be recovered by employing well-developed image
subtraction analysis methods, and that the cost to other (high Galactic
latitude) science would be negligible.


title:
Convergence of AMR and SPH simulations - I. Hydrodynamical resolution
  and convergence tests

abstract:
  We compare the results for a set of hydrodynamical tests performed with the
AMR finite volume code, MG and the SPH code, SEREN. The test suite includes
shock tube tests, with and without cooling, the non-linear thin-shell
instability and the Kelvin-Helmholtz instability. The main conclusions are :
(i) the two methods converge in the limit of high resolution and accuracy in
most cases. All tests show good agreement when numerical effects (e.g.
discontinuities in SPH) are properly treated. (ii) Both methods can capture
adiabatic shocks and well-resolved cooling shocks perfectly well with standard
prescriptions. However, they both have problems when dealing with
under-resolved cooling shocks, or strictly isothermal shocks, at high Mach
numbers. The finite volume code only works well at 1st order and even then
requires some additional artificial viscosity. SPH requires either a larger
value of the artificial viscosity parameter, alpha_AV, or a modified form of
the standard artificial viscosity term using the harmonic mean of the density,
rather than the arithmetic mean. (iii) Some SPH simulations require larger
kernels to increase neighbour number and reduce particle noise in order to
achieve agreement with finite volume simulations. However, this is partly due
to the need to reduce noise that can corrupt the growth of small-scale
perturbations. In contrast, instabilities seeded from large-scale perturbations
do not require more neighbours and hence work well with standard SPH
formulations and converge with the finite volume simulations. (iv) For purely
hydrodynamical problems, SPH simulations take an order of magnitude longer to
run than finite volume simulations when running at equivalent resolutions, i.e.
when they both resolve the underlying physics to the same degree. This requires
about 2-3 times as many particles as the number of cells.


title: Three-dimensional orbits of the triple-O stellar system HD 150136

abstract:
  Context. HD 150136 is a triple hierarchical system and a non-thermal radio
emitter. It is formed by an O3-3.5 V + O5.5-6 V close binary and a more distant
O6.5-7 V tertiary. So far, only the inner orbital properties have been reliably
constrained.
  Aims. To quantitatively understand the non-thermal emission process, accurate
knowledge of the physical and orbital properties of the object is crucial.
Here, we aim to investigate the orbital properties of the wide system and to
constrain the inclinations of the inner and outer binaries, and with these the
absolute masses of the system components.
  Methods. We used the PIONIER combiner at the Very Large Telescope
Interferometer to obtain the very first interferometric measurements of HD
150136. We combined the interferometric observations with new and existing high
resolution spectroscopic data to derive the orbital solution of the outer
companion in the three-dimensional space.
  Results. The wide system is clearly resolved by PIONIER, with a projected
separation on the plane of the sky of about 9 milli-arcsec. The best-fit
orbital period, eccentricity, and inclination are 8.2 yr, 0.73 and 108 degr. We
constrain the masses of the three stars of the system to 63 +/- 10, 40 +/- 6,
and 33 +/- 12 Msun for the O3-3.5 V, O5.5-6 V and O6.5-7 V components.
  Conclusions. The dynamical masses agree within errors with the evolutionary
masses of the components. Future interferometric and spectroscopic monitoring
of HD 150136 should allow one to reduce the uncertainties to a few per cent
only and to accurately constrain the distance to the system. This makes HD
150136 an ideal system to quantitatively test evolutionary models of high-mass
stars as well as the physics of non-thermal processes occurring in O-type
systems.


title:
Decoupling of High Dimension Operators from the Low Energy Sector in
  Holographic Models

abstract:
  We study the decoupling of high dimension operators from the the description
of the low-energy spectrum in theories where conformal symmetry is broken by a
single scale, which we refer to as `broken CFTs'. Holographic duality suggests
that this decoupling occurs in generic backgrounds. We show how the decoupling
of high mass states in the (d+1)-dimensional bulk relates to the decoupling of
high energy states in the d-dimensional broken CFT. In other words, we explain
why both high dimension operators and high mass states in the CFT decouple from
the low-energy physics of the mesons and glueballs. In many cases, the
decoupling can occur exponentially fast in the dimension of the operator.
Holography motivates a new kind of form factor proportional to the two point
function between broken CFT operators with very different scaling dimensions.
This new notion of decoupling can provide a systematic justification for
holographic descriptions of QCD and condensed matter systems with only light
degrees of freedom in the bulk.


title: The Universality of the Companion Mass Ratio Distribution

abstract:
  We present new results regarding the companion mass-ratio distribution (CMRD)
of stars, as a follow-up of our previous work. We used a
maximum-likelihood-estimation method to re-derive the field CMRD power law
avoiding dependence on the arbitrary binning. We also considered two new
surveys of multiples in the field for solar-type stars and M dwarfs to test the
universality of the CMRD. We found no significant differences in the CMRD for M
dwarfs and solar-type stars compared with previous results over the common mass
ratio and separation range. The new best-fit power law of the CMRD in the
field, combining two previous sets of data, is $dN/dq \propto q^{\beta}$, with
$\beta=0.25\pm0.29$.


title: Constraints on New Neutrino Interactions via Light Abelian Vector Bosons

abstract:
  We calculate new constraints on extra neutrino interactions via light Abelian
vector bosons, where the boson mass arises from Stuckelberg mechanism. We use
the requirement that $Z$, $W$, and kaon decays, as well as electron-neutrino
scattering, are not altered by the new interactions beyond what is allowed by
experimental uncertainties. These constraints are strong and apply to
neutrinophilic dark matter, where interactions of neutrinos and dark matter via
a new gauge boson are important. In particular, we show that models where
neutrino interactions are needed to solve the small-scale structure problems in
the $\Lambda$CDM cosmology are constrained.

categories: hep-ph astro-ph.CO astro-ph.HE hep-ex nucl-ex


title: Dark Matter Detectors as Dark Photon Helioscopes

abstract:
  Light new particles with masses below 10 keV, often considered as a plausible
extension of the Standard Model, will be emitted from the solar interior, and
can be detected on the Earth with a variety of experimental tools. Here we
analyze the new "dark" vector state V, a massive vector boson mixed with the
photon via an angle kappa, that in the limit of the small mass m_V has its
emission spectrum strongly peaked at low energies. Thus, we utilize the
constraints on the atomic ionization rate imposed by the results of the XENON10
experiment to set the limit on the parameters of this model: kappa times m_V< 3
times10^{-12} eV. This makes low-threshold Dark Matter experiments the most
sensitive dark vector helioscopes, as our result not only improves current
experimental bounds from other searches by several orders of magnitude, but
also surpasses even the most stringent astrophysical and cosmological limits in
a seven-decade-wide interval of m_V. We generalize this approach to other light
exotic particles, and set the most stringent direct constraints on
"mini-charged" particles.


title:
Large Scale Structure Constraints for a Class of f(R) Theories of
  Gravity

abstract:
  Over the last few years much attention has been given to the study of
modified gravity theories in order to find a more natural explanation for the
late time acceleration of the Universe. Nevertheless, a comparison of the
matter power spectrum predictions made by these theories with available data
has not yet been subjected to a detailed analysis. In the context of f(R)
theories of gravity we study the predicted power spectra using both a dynamical
systems approach for the background and solving for the matter perturbations
without using the quasi-static approximation, comparing the theoretical results
with several SDSS data. The importance of studying the first order perturbed
equations by assuming the correct background evolution and the relevance of the
initial conditions are also stressed. We determine the statistical significance
in relation to the observational data and demonstrate their conflict with
existing observations.


title: Millijansky Radio Variability in SDSS Stripe 82

abstract:
  We report on a blind survey for extragalactic radio variability that was
carried out by comparing two epochs of data from the FIRST survey with a third
epoch from a new 1.4 GHz survey of SDSS Stripe 82. The three epochs are spaced
seven years apart and have an overlapping area of 60 deg^2. We uncover 89
variable sources down to the millijansky level, 75 of which are
newly-identified, and we find no evidence for transient phenomena. This new
sample of variable sources allows us to infer an upper limit to the mean
characteristic timescale of AGN radio variability of 14 years. We find that
only 1% of extragalactic sources have fractional variability f_var >3, while
44% of Galactic sources vary by this much. The variable sample contains a
larger fraction of quasars than a comparable non-variable control sample,
though the majority of the variable sources appear to be extended galaxies in
the optical. This implies that either quasars are not the dominant contributor
to the variability of the sample, or that the deep optical data allow us to
detect the host galaxies of some low-z quasars. We use the new, higher
resolution data to report on the morphology of the variable sources. Finally,
we show that the fraction of sources that are variable remains constant or
increases at low flux densities. This may imply that next generation radio
surveys with telescopes like the Australian Square Kilometer Array Pathfinder
and MeerKAT will see a constant or even increasing fraction of variable sources
down into the submillijansky regime.


title: Higgsogenesis

abstract:
  In addition to explaining the masses of elementary particles, the Higgs boson
may have far-reaching implications for the generation of the matter content in
the Universe. For instance, the Higgs plays a key role in two main theories of
baryogenesis, namely electroweak baryogenesis and leptogenesis. In this letter,
we propose a new cosmological scenario where the Higgs chemical potential
mediates asymmetries between visible and dark matter sectors, either generating
a baryon asymmetry from a dark matter asymmetry or vice-versa. We illustrate
this mechanism with a simple model with two new fermions coupled to the Higgs
and discuss associated signatures.


title: Turbulence driven by structure formation in the circum-galactic medium

abstract:
  The injection of turbulence in the circum-galactic medium at redshift z = 2
is investigated using the mesh-based hydrodynamic code Enzo and a subgrid-scale
(SGS) model for unresolved turbulence. Radiative cooling and heating by a
uniform Ultraviolet (UV) background are included in our runs and compared with
the effect of turbulence modelling. Mechanisms of gas exchange between galaxies
and the surrounding medium, as well as metal enrichment, are not taken into
account, and turbulence is here driven solely by structure formation (mergers
and shocks). We find that turbulence, both at resolved and SGS scales, impacts
mostly the warm-hot intergalactic medium (WHIM), with temperature between 10^5
and 10^7 K, mainly located around collapsed and shock heated structures, and in
filaments. Typical values of the ratio of turbulent to thermal pressure is 0.1
in the WHIM, corresponding to a volume-weighted average of the SGS turbulent to
thermal Doppler broadening b_t / b_therm = 0.26, on length scales below the
grid resolution of 25 kpc/h. In the diffuse intergalactic medium (IGM), defined
in a range of baryon overdensity \delta\ between 1 and 50, the importance of
turbulence is smaller, but grows as a function of gas density, and the Doppler
broadening ratio is fitted by the function b_t / b_therm = 0.023 \delta^{0.58}.


title: Composition of Low Redshift Halo Gas

abstract:
  Halo gas in low-z (z<0.5) >0.1L* galaxies in high-resolution, large-scale
cosmological hydrodynamic simulations is examined with respect to three
components: (cold, warm, hot) with temperatures equal to (<10^5, 10^{5-6},
>10^6)K, respectively. The warm component is compared, utilizing O VI
\lambda\lambda 1032, 1038 absorption lines, to observations and agreement is
found with respect to the galaxy-O VI line correlation, the ratio of O VI line
incidence rate in blue to red galaxies and the amount of O VI mass in
star-forming galaxies. A detailed account of the sources of warm halo gas
(stellar feedback heating, gravitational shock heating and accretion from the
intergalactic medium), inflowing and outflowing warm halo gas metallicity
disparities and their dependencies on galaxy types and environment is also
presented. Having the warm component securely anchored, our simulations make
the following additional predictions. First, cold gas is the primary component
in inner regions, with its mass comprising 50% of all gas within
galacto-centric radius r=(30,150)kpc in (red, blue) galaxies. Second, at
r>(30,200)kpc in (red, blue) galaxies the hot component becomes the majority.
Third, the warm component is a perpetual minority, with its contribution
peaking at ~30% at r=100-300kpc in blue galaxies and never exceeding 5% in red
galaxies. The significant amount of cold gas in low-z early-type galaxies found
in simulations, in agreement with recent observations (Thom et al.), is
intriguing, so is the dominance of hot gas at large radii in blue galaxies.


title:
An effective network reduction approach to find the dynamical repertoire
  of discrete dynamic networks

abstract:
  Discrete dynamic models are a powerful tool for the understanding and
modeling of large biological networks. Although a lot of progress has been made
in developing analysis tools for these models, there is still a need to find
approaches that can directly relate the network structure to its dynamics. Of
special interest is identifying the stable patterns of activity, i.e., the
attractors of the system. This is a problem for large networks, because the
state space of the system increases exponentially with network size. In this
work we present a novel network reduction approach that is based on finding
network motifs that stabilize in a fixed state. Notably, we use a topological
criterion to identify these motifs. Specifically, we find certain types of
strongly connected components in a suitably expanded representation of the
network. To test our method we apply it to a dynamic network model for a type
of cytotoxic T cell cancer and to an ensemble of random Boolean networks of
size up to 200. Our results show that our method goes beyond reducing the
network and in most cases can actually predict the dynamical repertoire of the
nodes (fixed states or oscillations) in the attractors of the system.


title: Neutrino masses and mixing in A4 models with three Higgs doublets

abstract:
  We study neutrino masses and mixing in the context of flavor models with A4
symmetry, three scalar doublets in the triplet representation, and three lepton
families. We show that there is no representation assignment that yields a
dimension-five mass operator consistent with experiment. We then consider a
type-I seesaw with three heavy right-handed neutrinos, explaining in detail why
it fails, and showing with a numerical example that agreement with the present
neutrino oscillation data can be recovered with the inclusion of
dimension-three heavy neutrino mass terms that break softly the A4 symmetry.


title:
Arbitrary non-paraxial accelerating periodic beams and spherical shaping
  of light

abstract:
  We report the observation of arbitrary accelerating beams designed using a
non-paraxial description of optical caustics. We use a spatial light
modulator-based setup and techniques of Fourier optics to generate circular and
Weber beams subtending over 95 degrees of arc. Applying a complementary binary
mask also allows the generation of periodic accelerating beams taking the forms
of snake-like trajectories, and the application of a rotation to the caustic
allows the first experimental synthesis of optical accelerating beams upon the
surface of a sphere in three dimensions.


title:
Spontaneous knotting and unknotting of flexible linear polymers:
  equilibrium and kinetic aspects

abstract:
  We report on a computational study of the statics and dynamics of long
flexible linear polymers that spontaneously knot and unknot. Specifically, the
equilibrium self-entanglement properties, such as the knotting probability,
knot length and position, are investigated with extensive Monte Carlo sampling
of chains of up to 15,000 beads. Tens of such equilibrated chains of up to 4,
096 beads are next used as starting points for Langevin dynamics simulations.
The complex interplay of chain dynamics and self-knotting is addressed by
monitoring the time evolution of various metric and entanglement properties. In
particular, the extensive duration of the simulations allows for observing the
spontaneous formation and disappearance of prime and composite physical knots
in linear chains. Notably, a sizeable fraction of self-knotting and unknotting
events is found to involve regions that are far away from the chain termini. To
the best of our knowledge this represents the first instance where spontaneous
changes in knotting for linear homopolymers are systematically characterized
using unbiased dynamics simulations.


title: Uniformly factoring weakly compact operators

abstract:
  Let $X$ and $Y$ be separable Banach spaces. Suppose $Y$ either has a
shrinking basis or $Y$ is isomorphic to $C(2^\mathbb{N})$ and $A$ is a subset
of weakly compact operators from $X$ to $Y$ which is analytic in the strong
operator topology. We prove that there is a reflexive space with a basis $Z$
such that every $T \in A$ factors through $Z$. Likewise, we prove that if $A
\subset L(X, C(2^\mathbb{N}))$ is a set of operators whose adjoints have
separable range and is analytic in the strong operator topology then there is a
Banach space $Z$ with separable dual such that every $T \in A$ factors through
$Z$. Finally we prove a uniformly version of this result in which we allow the
domain and range spaces to vary.


title:
Effect of charged line defects on conductivity in graphene: numerical
  Kubo and analytical Boltzmann approaches

abstract:
  Charge carrier transport in single-layer graphene with one-dimensional
charged defects is studied theoretically. Extended charged defects, considered
an important factor for mobility degradation in chemically-vapor-deposited
graphene, are described by a self-consistent Thomas-Fermi potential. A
numerical study of electronic transport is performed by means of a
time-dependent real-space Kubo approach in honeycomb lattices containing
millions of carbon atoms, capturing the linear response of realistic size
systems in the highly disordered regime. Our numerical calculations are
complemented with a kinetic transport theory describing charge transport in the
weak scattering limit. The semiclassical transport lifetimes are obtained by
computing scattered amplitudes within the second Born approximation. The
transport electron-hole asymmetry found in the semiclassical approach is
consistent with the Kubo calculations. In the strong scattering regime, the
conductivity is found to be a sublinear function of electronic density and
weakly dependent on the Thomas-Fermi screening wavelength. We attribute this
atypical behavior to the extended nature of one-dimensional charged defects.
Our results are consistent with recent experimental reports.


title:
Gravitational Wave Tests of General Relativity with Ground-Based
  Detectors and Pulsar Timing Arrays

abstract:
  This review is focused on tests of Einstein's theory of General Relativity
with gravitational waves that are detectable by ground-based interferometers
and pulsar timing experiments. Einstein's theory has been greatly constrained
in the quasi-linear, quasi-stationary regime, where gravity is weak and
velocities are small. Gravitational waves will allow us to probe a
complimentary, yet previously unexplored regime: the non-linear and dynamical
strong-field regime. Such a regime is, for example, applicable to compact
binaries coalescing, where characteristic velocities can reach fifty percent
the speed of light and compactnesses can reach a half. This review begins with
the theoretical basis and the predicted gravitational wave observables of
modified gravity theories. The review continues with a brief description of the
detectors, including both gravitational wave interferometers and pulsar timing
arrays, leading to a discussion of the data analysis formalism that is
applicable for such tests. The review ends with a discussion of gravitational
wave tests for compact binary systems.

categories: gr-qc astro-ph.CO astro-ph.HE hep-ph hep-th


title: The synergy between the Dark Energy Survey and the South Pole Telescope

abstract:
  The Dark Energy Survey (DES) has recently completed the Science Verification
phase (SV), collecting data over 150 sq. deg. of sky. In this work we analyze
to what extent it is beneficial to supplement the analysis of DES data with CMB
lensing data. We provide forecasts for both DES-SV and for the full survey
covering 5000 sq. deg. We show that data presently available from DES-SV and
SPT-SZ would allow a ~ 8% measurement of the linear galaxy bias in three out of
four redshift bins. We further show that a joint analysis of cosmic shear,
galaxy density and CMB lensing data allows to break the degeneracy between the
shear multiplicative bias, the linear galaxy bias and the normalization of the
matter power spectrum. We show that these observables can thus be self
calibrated to the percent or sub-percent level, depending on the quality of
available data, fraction of overlap of the footprints and priors included in
the analysis.


title: Fermi Discovers a New Population of Gamma-ray Novae

abstract:
  Novae had not been widely considered as high-energy (>100 MeV) gamma-ray
sources before the launch of the Fermi Large Area Telescope (LAT). In March
2010, the LAT made the first gamma-ray detection of a nova in the symbiotic
binary V407 Cygni. The LAT observations uniquely probed the high-energy
particle acceleration mechanism in the environs of the V407 Cyg binary system
consisting of a white dwarf and its red giant companion. Subsequently in June
2012, two more novae were detected with the LAT, Nova Sco 2012 and Nova Mon
2012, thus heralding novae as a new gamma-ray source class. For Nova Mon 2012,
the gamma-ray transient source was discovered first, followed by the optical
confirmation of the nova, showcasing how novae can be found with the LAT
independently from traditional optical searches. We discuss the LAT detected
gamma-ray novae together with observational limits on other optical novae over
the first four years of the Fermi mission and reconsider the possible
high-energy gamma-ray production mechanisms in novae in light of the new
detections.


title: Intrinsic Spin Hall Effect at Oxide Interfaces: a Simple Model

abstract:
  An asymmetric triangular potential well provides the simplest model for the
confinement of mobile electrons at the interface between two insulating oxides,
such as LaAlO_3 and SrTiO_3 (LAO/STO). These electrons have been recently shown
to exhibit a large spin-orbit coupling of the Rashba type, i.e., linear in the
in-plane momentum. In this paper we study the intrinsic spin Hall effect due to
Rashba coupling in an asymmetric triangular potential well. Besides splitting
each subband into two branches of opposite helicity, the spin-orbit interaction
causes the wave function in the direction perpendicular to the plane of the
quantum well (the z direction) to depend on the in-plane wave vector k. In
contrast to the extreme asymmetric case, i.e., the wedge-shaped quantum well,
for which the intrinsic spin Hall effect vanishes due to vertex corrections, we
find that the asymmetric well supports a non-vanishing intrinsic spin Hall
conductivity, which increases in magnitude as the well becomes more symmetric.
The spin Hall conductivity is found to be proportional to the square of the
spin-orbit coupling constant and, in the limit of low carrier density, depends
only on the effective mass renormalization associated with the k-dependence of
the wave functions in the z direction. Its origin lies in the non-vanishing
matrix elements of the spin current between subbands corresponding to different
states of quantized motion perpendicular to the plane of the well.


title: Concurrent learning-based approximate optimal regulation

abstract:
  In deterministic systems, reinforcement learning-based online approximate
optimal control methods typically require a restrictive persistence of
excitation (PE) condition for convergence. This paper presents a concurrent
learning-based solution to the online approximate optimal regulation problem
that eliminates the need for PE. The development is based on the observation
that given a model of the system, the Bellman error, which quantifies the
deviation of the system Hamiltonian from the optimal Hamiltonian, can be
evaluated at any point in the state space. Further, a concurrent learning-based
parameter identifier is developed to compensate for parametric uncertainty in
the plant dynamics. Uniformly ultimately bounded (UUB) convergence of the
system states to the origin, and UUB convergence of the developed policy to the
optimal policy are established using a Lyapunov-based analysis, and simulations
are performed to demonstrate the performance of the developed controller.


title: Sparse Stable Matrices

abstract:
  In the design of decentralized networked systems, it is useful to know
whether a given network topology can sustain stable dynamics. We consider a
basic version of this problem here: given a vector space of sparse real
matrices, does it contain a stable (Hurwitz) matrix? Said differently, is a
feedback channel (corresponding to a non-zero entry) necessary for
stabilization or can it be done without. We provide in this paper a set of
necessary and a set of sufficient conditions for the existence of stable
matrices in a vector space of sparse matrices. We further prove some properties
of the set of sparse matrix spaces that contain Hurwitz matrices. The
conditions we exhibit are most easily stated in the language of graph theory,
which we thus adopt in this paper.


title:
Approximate optimal cooperative decentralized control for consensus in a
  topological network of agents with uncertain nonlinear dynamics

abstract:
  Efforts in this paper seek to combine graph theory with adaptive dynamic
programming (ADP) as a reinforcement learning (RL) framework to determine
forward-in-time, real-time, approximate optimal controllers for distributed
multi-agent systems with uncertain nonlinear dynamics. A decentralized
continuous time-varying control strategy is proposed, using only local
communication feedback from two-hop neighbors on a communication topology that
has a spanning tree. An actor-critic-identifier architecture is proposed that
employs a nonlinear state derivative estimator to estimate the unknown dynamics
online and uses the estimate thus obtained for value function approximation.


title: Friendship Paradox Redux: Your Friends Are More Interesting Than You

abstract:
  Feld's friendship paradox states that "your friends have more friends than
you, on average." This paradox arises because extremely popular people, despite
being rare, are overrepresented when averaging over friends. Using a sample of
the Twitter firehose, we confirm that the friendship paradox holds for >98% of
Twitter users. Because of the directed nature of the follower graph on Twitter,
we are further able to confirm more detailed forms of the friendship paradox:
everyone you follow or who follows you has more friends and followers than you.
This is likely caused by a correlation we demonstrate between Twitter activity,
number of friends, and number of followers. In addition, we discover two new
paradoxes: the virality paradox that states "your friends receive more viral
content than you, on average," and the activity paradox, which states "your
friends are more active than you, on average." The latter paradox is important
in regulating online communication. It may result in users having difficulty
maintaining optimal incoming information rates, because following additional
users causes the volume of incoming tweets to increase super-linearly. While
users may compensate for increased information flow by increasing their own
activity, users become information overloaded when they receive more
information than they are able or willing to process. We compare the average
size of cascades that are sent and received by overloaded and underloaded
users. And we show that overloaded users post and receive larger cascades and
they are poor detector of small cascades.

categories: cs.SI cs.CY nlin.AO physics.soc-ph stat.AP


title: Quadruply-graded colored homology of knots

abstract:
  We conjecture the existence of four independent gradings in the colored
HOMFLY homology. We describe these gradings explicitly for the rectangular
colored homology of torus knots and make qualitative predictions of various
interesting structures and symmetries in the colored homology of general knots.
We also give a simple representation-theoretic model for the HOMFLY homology of
the unknot colored by any representation. While some of these structures have a
natural interpretation in the physical realization of knot homologies based on
counting supersymmetric configurations (BPS states, instantons, and vortices),
others are completely new. They suggest new geometric and physical realizations
of colored HOMFLY homology as the Hochschild homology of the category of branes
in a Landau-Ginzburg B-model or, equivalently, in the mirror A-model.
Supergroups and supermanifolds are surprisingly ubiquitous in all aspects of
this work.


title:
Variant N= 1 Supersymmetric Non-Abelian Proca-Stueckelberg Formalism in
  Four Dimensions

abstract:
  We present a new (variant) formulation of N=1 supersymmetric compensator
mechanism for an arbitrary non-Abelian group in four dimensions. We call this
`variant supersymmetric non-Abelian Proca-Stueckelberg formalism'. Our field
content is economical, consisting only of the two multiplets: (i) A Non-Abelian
vector multiplet (A_\mu{}^I, \lambda^I, C_{\mu\nu\rho}{}^I) and (ii) A
compensator tensor multiplet (B_{\mu\nu}{}^I, \chi^I, \varphi^I). The index I
is for the adjoint representation of a non-Abelian gauge group. The
C_{\mu\nu\rho}{}^I is originally an auxiliary field Hodge-dual to the
conventional auxiliary field D^I. The \varphi^I and B_{\mu\nu}{}^I are
compensator fields absorbed respectively into the longitudinal components of
A_\mu{}^I and C_{\mu\nu\rho}{}^I which become massive. After the absorption,
C_{\mu\nu\rho}{}^I becomes no longer auxiliary, but starts propagating as a
massive scalar field. We fix all non-trivial cubic interactions in the total
lagrangian, and quadratic interactions in all field equations. The superpartner
fermion \chi^I acquires a Dirac mass shared with the gaugino \lambda^I. As an
independent confirmation, we give the superspace re-formulation of the
component results.


title: Faster sparse interpolation of straight-line programs

abstract:
  We give a new probabilistic algorithm for interpolating a "sparse" polynomial
f given by a straight-line program. Our algorithm constructs an approximation
f* of f, such that their difference probably has at most half the number of
terms of f, then recurses on their difference. Our approach builds on previous
work by Garg and Schost (2009), and Giesbrecht and Roche (2011), and is
asymptotically more efficient in terms of the total cost of the probes required
than previous methods, in many cases.


title: Fractional Discrete Systems with Sequential h-differences

abstract:
  In the paper we study the subject of positivity of systems with sequential
fractional difference. We give formulas for the unique solutions of systems in
linear and semi-linear cases. The positivity of systems is considered.


title: Random Lattice Gauge Theories and Differential Forms

abstract:
  We provide a brief overview on the application of the exterior calculus of
differential forms to the ab initio formulation of field theories on random
simplicial lattices. In this framework, discrete analogues of the exterior
derivative and the Hodge star operator are employed for the factorization of
discrete field equations into a purely combinatorial (metric-free) part and a
metric-dependent part. The Hodge star duality (isomorphism) is invoked to
motivate the use of primal and dual lattices (a dual cell complex). The natural
role of Whitney forms in the construction of discrete Hodge star operators is
stressed.


title:
Scattering of Cold Atom Coherences by Hot Atoms: Frequency Shifts from
  Background Gas Collisions

abstract:
  Frequency shifts from background gas collisions currently contribute
significantly to the inaccuracy of atomic clocks. Because nearly all collisions
with room-temperature background gases that transfer momentum eject the cold
atoms from the clock, the interference between the scattered and unscattered
waves in the forward direction dominates these frequency shifts. We show they
are ~10 times smaller than in room-temperature clocks and that van der Waals
interactions produce the cold-atom background-gas shift. General considerations
allow the loss of Ramsey fringe amplitude to bound this frequency shift.


title: A categorical invariant of flow equivalence of shifts

abstract:
  We prove that the Karoubi envelope of a shift --- defined as the Karoubi
envelope of the syntactic semigroup of the language of blocks of the shift ---
is, up to natural equivalence of categories, an invariant of flow equivalence.
More precisely, we show that the action of the Karoubi envelope on the Krieger
cover of the shift is a flow invariant. An analogous result concerning the
Fischer cover of a synchronizing shift is also obtained. From these main
results, several flow equivalence invariants --- some new and some old --- are
obtained. We also show that the Karoubi envelope is, in a natural sense, the
best possible syntactic invariant of flow equivalence of sofic shifts. Another
application concerns the classification of Markov-Dyck and Markov-Motzkin
shifts: it is shown that, under mild conditions, two graphs define flow
equivalent shifts if and only if they are isomorphic. Shifts with property (A)
and their associated semigroups, introduced by Wolfgang Krieger, are
interpreted in terms of the Karoubi envelope, yielding a proof of the flow
invariance of the associated semigroups in the cases usually considered (a
result recently announced by Krieger), and also a proof that property (A) is
decidable for sofic shifts.


title: Omega-Deformed Seiberg-Witten Effective Action from the M5-brane

abstract:
  We obtain the leading order corrections to the effective action of an
M5-brane wrapping a Riemann surface in the eleven-dimensional supergravity
Omega-background. The result can be identified with the first order
epsilon-deformation of the Seiberg-Witten effective action of pure SU(2) gauge
theory. We also comment on the second order corrections and the generalization
to arbitrary gauge group and matter content.


title: Logical Stochastic Optimization

abstract:
  We present a logical framework to represent and reason about stochastic
optimization problems based on probability answer set programming. This is
established by allowing probability optimization aggregates, e.g., minimum and
maximum in the language of probability answer set programming to allow
minimization or maximization of some desired criteria under the probabilistic
environments. We show the application of the proposed logical stochastic
optimization framework under the probability answer set programming to two
stages stochastic optimization problems with recourse.


title: Sign-reversal of the in-plane resistivity anisotropy in iron pnictides

abstract:
  The concept of an electronically-driven breaking of the rotational symmetry
of a crystal, without involving magnetic order, has found experimental support
in several systems, from semiconductor heterostructures and ruthenates, to
cuprate and iron-pnictide superconductors. In the pnictide BaFe$_{2}$As$_{2}$,
such an "electronic nematic state" appears above the magnetic transition dome,
over a temperature range that can be controlled by external strain. Here, by
measuring the in-plane resistivity anisotropy, we probe the electronic
anisotropy of this material over the entire nematic/magnetic dome, whose end
points coincide with the optimal superconducting transition temperatures.
Counter-intuitively, we find that, unlike other materials, the resistivity
anisotropy in BaFe$_{2}$As$_{2}$ changes sign across the doping phase diagram,
even though the signs of the magnetic, nematic, and orthorhombic order
parameters are kept fixed. This behavior is explained by the Fermi surface
reconstruction in the magnetic phase and spin-fluctuation scattering in the
nematic phase. The unique behavior of the transport anisotropy unveils that the
primary role is played by magnetic scattering in the normal state transport
properties of the iron pnictides, suggesting a close connection between
magnetism, nematicity, and unconventional superconductivity.


title: On Deligne's category $\uRep^{ab}(S_d)$

abstract:
  We prove a universal property of Deligne's category $\uRep^{ab}(S_d)$. Along
the way, we classify tensor ideals in the category $\uRep(S_d)$.


title: Estimating gas masses and dust-to-gas ratios from optical spectroscopy

abstract:
  We present a method to estimate the total gas column density, dust-to-gas and
dust-to-metal ratios of distant galaxies from rest-frame optical spectra. The
technique exploits the sensitivity of certain optical lines to changes in
depletion of metals onto dust grains and uses photo-ionization models to
constrain these physical ratios along with the metallicity (Z) and dust column
density. We compare our gas column density estimates with HI and CO gas mass
estimates in nearby galaxies to show that we recover their total gas mass
surface density to within a factor of 2 up to a total surface gas mass density
of ~75 Mo/pc^2. Our technique is independent of the conversion factor of CO to
H2 and we show that a Z-dependent XCO is required to achieve good agreement
between our measurements and that provided by CO and HI. However we also show
that our method can not be reliably aperture corrected to total gas mass. We
calculate dust-to-gas ratios for all star-forming galaxies in the SDSS DR7 and
show the resulting dependence on Z agrees well with the trend inferred from
modelling of the dust emission of nearby galaxies using FIR data. We also
present estimates of the variation of the dust-to-metal ratio with Z and show
that this is poorly constrained at Z<~0.5Z_sun. We end with a study of the
inventory of gas in the central regions, defined both in terms of a fixed
physical radius and as a fixed fraction of the half-light radius, of ~70,000
star-forming galaxies from the Sloan Digital Sky Survey. We show that their
central gas content and gas depletion times are not accurately predicted by a
single parameter, but in agreement with recent studies we find that a
combination of the M* and some measure of central concentration provides a good
predictor of gas content in galaxies. We also identify a population of galaxies
with low surface densities of stars and very long gas depletion times.


title: Generating functions of orthogonal polynomials in higher dimensions

abstract:
  In this paper two important classes of orthogonal polynomials in higher
dimensions using the framework of Clifford analysis are considered, namely the
Clifford-Hermite and the Clifford-Gegenbauer polynomials. For both classes an
explicit generating function is obtained.


title: Charm quark mass dependence in a global QCD analysis

abstract:
  We study the effect of the charm quark mass in the CTEQ global analysis of
parton distribution functions (PDFs) of the proton. Constraints on the
$\bar{\rm MS}$ mass of the charm quark are examined at the
next-to-next-to-leading order (NNLO) accuracy in the S-ACOT-$\chi$ heavy-quark
factorization scheme. The value of the charm quark mass from the hadronic
scattering data in the CT10 NNLO fit, including semiinclusive charm production
in DIS at HERA collider, is found to agree with the world average value.
Various approaches for constraining $m_{c}$ in the global analysis and impact
on LHC cross sections are reviewed.


title: Laval nozzle as an acoustic analogue of a massive field

abstract:
  We study a gas flow in the Laval nozzle, which is a convergent-divergent tube
that has a sonic point in its throat. We show how to obtain the appropriate
form of the tube, so that the acoustic perturbations of the gas flow in it
satisfy any given wavelike equation. With the help of the proposed method we
find the Laval nozzle, which is an acoustic analogue of the massive scalar
field in the background of the Schwarzschild black hole. This gives us a
possibility to observe in a laboratory the quasinormal ringing of the massive
scalar field, which, for special set of the parameters, can have infinitely
long-living oscillations in its spectrum.


title:
Whispering gallery modes in hexagonal microcavities fabricated by
  crystal growth

abstract:
  We investigated the whispering gallery modes of cavities with a hexagonal
cross-section. We found two different modes, namely perturbed and quasi-WGMs,
of which the former exhibits the higher Q when the corner radius is large. We
studied the dependence of Q on the curvature radius of the polygonal cavities
and found that the coupling between the two modes determines the Q of the
cavity. In addition we fabricated a cavity by employing laser heated pedestal
growth and demonstrated a high Q.


title:
Angular distributions of higher order splitting functions in the vacuum
  and in dense QCD matter

abstract:
  We study the collinear splitting functions needed for next-to-next-to-leading
order calculations of jet production in the vacuum and in dense QCD matter.
These splitting functions describe the probability of a parton to evolve into
three-parton final state and are generalizations of the traditional DGLAP
splitting kernels to a higher perturbative order. Of particular interest are
the angular distributions of such splitting functions, which can elucidate the
significance of multiple parton branching for jet observables and guide the
construction of parton shower Monte Carlo generators. We find that to ${\cal
O}(\alpha_s^2)$ both the vacuum and the in-medium collinear splitting functions
are neither angular ordered nor anti-angular ordered. Specifically, in dense
QCD matter they retain the characteristic broad angular distribution already
found in the ${\cal O}(\alpha_s)$ result.


title:
Comparison of quenched and annealed invariance principles for random
  conductance model

abstract:
  We show that there exists an ergodic conductance environment such that the
weak (annealed) invariance principle holds for the corresponding continuous
time random walk but the quenched invariance principle does not hold.


title:
Properties of young star cluster systems: the age signature from
  near-infrared integrated colours

abstract:
  A recent JHKs study of several grand-design spiral galaxies shows a bimodal
distribution of their system of star clusters and star forming complexes in
colour-magnitude and colour-colour diagrams. In a comparison with stellar
population models including gas, the (J-H) vs (H-Ks) diagram reveals that
embedded clusters, still immersed in their parental clouds of gas and dust,
generally have a redder (H-Ks) colour than older clusters, whose gas and dust
have already been ejected. This bimodal behaviour is also evident in the
colour-magnitude diagram MK vs (J-Ks), where the brightest clusters split into
two sequences separating younger from older clusters. In addition, the
reddening-free index Qd = (H-Ks) - 0.884 (J-H) has been shown to correlate with
age for the young clusters and thus provided an effective way to differentiate
the embedded clusters from the older ones. We aim to study the behaviour of
these photometric indices for star cluster systems in the Local Group. We
investigate the effectiveness of the Qd index in sorting out clusters of
different ages at their early evolutionary stages. Surface photometry was
carried out for 2MASS images of populous clusters younger than ~100Myr whose
ages were available. Some clusters, particularly the embedded ones, were
studied for the first time using this method. The integrated magnitudes and
colours extracted from the surface photometry of the most populous
clusters/complexes in the Local Group shows the expected bimodal distribution
in the colour-colour and colour-magnitude diagrams. In particular, we confirm
the index Qd as a powerful tool for distinguishing clusters younger than about
7Myr from older clusters. (abridged)


title:
Fluctuation-stabilized marginal networks and anomalous entropic
  elasticity

abstract:
  We study the elastic properties of thermal networks of Hookean springs. In
the purely mechanical limit, such systems are known to have vanishing rigidity
when their connectivity falls below a critical, isostatic value. In this work
we show that thermal networks exhibit a non-zero shear modulus $G$ well below
the isostatic point, and that this modulus exhibits an anomalous, sublinear
dependence on temperature $T$. At the isostatic point, $G$ increases as the
square-root of $T$, while we find $G \propto T^{\alpha}$ below the isostatic
point, where ${\alpha} \simeq 0.8$. We show that this anomalous $T$ dependence
is entropic in origin.


title: Efficient algorithms computing distances between Radon measures on R

abstract:
  In this paper numerical methods of computing distances between two Radon
measures on R are discussed. Efficient algorithms for Wasserstein-type metrics
are provided. In particular, we propose a novel algorithm to compute the flat
metric (bounded Lipschitz distance) with a computational cost O(nlogn). The
flat distance has recently proven to be adequate for the Escalator Boxcar Train
(EBT) method for solving transport equations with growth terms. Therefore,
finding efficient numerical algorithms to compute the flat distance between two
measures is important for finding the residual error and validating empirical
convergence of different methods.


title: Unitary equivalence of automorphisms of separable C*-algebras

abstract:
  We prove that the automorphisms of any separable C*-algebra that does not
have continuous trace are not classifiable by countable structures up to
unitary equivalence. This implies a dichotomy for the Borel complexity of the
relation of unitary equivalence of automorphisms of a separable unital
C*-algebra: Such relation is either smooth or not even classifiable by
countable structures.


title:
Measurement of CP-violating asymmetries in B^0 -> (rho pi)^0 decays
  using a time-dependent Dalitz plot analysis

abstract:
  We present results for a time-dependent Dalitz plot measurement of
CP-violating asymmetries in the mode B^0 -> pi^+ pi^- pi^0. The dataset is
derived from the complete sample of 471 x 10^6 BBbar meson pairs collected with
the BABAR detector at the PEP-II asymmetric-energy e^+e^- collider at the SLAC
National Accelerator Laboratory operating on the Upsilon(4S) resonance. We
extract parameters describing the time-dependent B^0 -> rho pi decay
probabilities and CP asymmetries, including C = 0.016\pm0.059\pm0.036, DeltaC =
0.234\pm0.061\pm0.048, S = 0.053\pm0.081\pm0.034, and DeltaS =
0.054\pm0.082\pm0.039, where the uncertainties are statistical and systematic,
respectively. We perform a two-dimensional likelihood scan of the direct
CP-violation asymmetry parameters for B^0 -> rho^\pm pi^\mp decays, finding the
change in chi^2 between the minimum and the origin (corresponding to no direct
CP violation) to be Delta(chi^2)=6.42. We present information on the
CP-violating parameter alpha in a likelihood scan that incorporates B^\pm ->
rho pi measurements.


title: The positive mass Theorem and Penrose inequality for graphical manifolds

abstract:
  We give, via elementary methods, explicit formulas for the ADM mass which
allow us to conclude the positive mass theorem and Penrose inequality for a
class of graphical manifolds which includes, for instance, that ones with flat
normal bundle.


title: Modeling and Analysing Respondent Driven Sampling as a Counting Process

abstract:
  Respondent-driven sampling (RDS) is an approach to sampling design and
analysis which utilizes the networks of social relationships that connect
members of the target population, using chain-referral methods to facilitate
sampling. RDS typically leads to biased sampling, favoring participants with
many acquaintances. Naive estimates, such as the sample average, which are
uncorrected for the sampling bias, will themselves be biased. To compensate for
this bias, current methodology suggests inverse-degree weighting, where the
"degree" is the number of acquaintances. This stems from the fundamental RDS
assumption that the probability of sampling an individual is proportional to
their degree. Since this assumption is tenuous at best, we propose to harness
the additional information encapsulated in the time of recruitment, into a
model-based inference framework for RDS. This information is typically
collected by researchers, but ignored. We adapt methods developed for inference
in epidemic processes to estimate the population size, degree counts and
frequencies. While providing valuable information in themselves, these
quantities ultimately serve to debias other estimators, such a disease's
prevalence. A fundamental advantage of our approach is that, being model-based,
it makes all assumptions of the data-generating process explicit. This enables
verification of the assumptions, maximum likelihood estimation, extension with
covariates, and model selection. We develop asymptotic theory, proving
consistency and asymptotic normality properties. We further compare these
estimators to the standard inverse-degree weighting through simulations, and
using real-world data. In both cases we find our estimators to outperform
current methods. The likelihood problem in the model we present is convex, and
thus efficiently solvable. We implement these estimators in an R package,
chords, available on CRAN.


title:
CMB Aberration and Doppler Effects as a Source of Hemispherical
  Asymmetries

abstract:
  Our peculiar motion with respect to the CMB rest frame represents a preferred
direction in the observed CMB sky since it induces an apparent deflection of
the observed CMB photons (aberration) and a shift in their frequency (Doppler).
Both effects distort the multipoles $a_{\ell m}$'s at all $\ell$'s. Such
effects are real as it has been recently measured for the first time by Planck
according to what was forecast in some recent papers. However, the common lore
when estimating a power spectrum from CMB is to consider that Doppler affects
only the $\ell=1$ multipole, neglecting any other corrections. In this work we
use simulations of the CMB sky in a boosted frame with a peculiar velocity
$\beta = v/c = 1.23 \times 10^{-3}$ in order to assess the impact of such
effect on power spectrum estimations in different regions of the sky. We show
that the boost induces a north-south asymmetry in the power spectrum which is
highly significant and non-negligible, of about (0.58 $\pm$ 0.10)% for half-sky
cuts when going up to $\ell$ = 2500. We suggest that these effects are relevant
and may account for some of the north-south asymmetries seen in the Planck
data, being especially important at small scales. Finally we analyze the
particular case of the ACT experiment, which observed only a small fraction of
the sky and show that it suffers a bias of about 1% on the power spectrum and
of similar size on some cosmological parameters: for example the position of
the peaks shifts by 0.5% and the overall amplitude of the spectrum is about
0.4% lower than a full-sky case.


title:
Hardware Acceleration of the Gipps Model for Real-Time Traffic
  Simulation

abstract:
  Traffic simulation software is becoming increasingly popular as more cities
worldwide use it to better manage their crowded traffic networks. An important
requirement for such software is the ability to produce accurate results in
real time, requiring great computation resources. This work proposes an
ASIC-based hardware accelerated approach for the AIMSUN traffic simulator,
taking advantage of repetitive tasks in the algorithm. Different system
configurations using this accelerator are also discussed. Compared with the
traditional software simulator, it has been found to improve the performance by
as much as 9x when using a single processing element approach, or more
depending on the chosen hardware configuration.


title: Cyclic homology, tight crossed products, and small stabilizations

abstract:
  In \verb|arXiv:1212.5901| we associated an algebra $\Gami(\fA)$ to every
bornological algebra $\fA$ and an ideal $I_{S(\fA)}\triqui\Gami(\fA)$ to every
symmetric ideal $S\triqui\elli$. We showed that $I_{S(\fA)}$ has
$K$-theoretical properties which are similar to those of the usual
stabilization with respect to the ideal $J_S\triqui\cB$ of the algebra $\cB$ of
bounded operators in Hilbert space which corresponds to $S$ under Calkin's
correspondence. In the current article we compute the relative cyclic homology
$HC_*(\Gami(\fA):I_{S(\fA)})$. Using these calculations, and the results of
\emph{loc. cit.}, we prove that if $\fA$ is a $C^*$-algebra and $c_0$ the
symmetric ideal of sequences vanishing at infinity, then $K_*(I_{c_0(\fA)})$ is
homotopy invariant, and that if $*\ge 0$, it contains $K^{\top}_*(\fA)$ as a
direct summand. This is a weak analogue of the Suslin-Wodzicki theorem
(\cite{sw1}) that says that for the ideal $\cK=J_{c_0}$ of compact operators
and the $C^*$-algebra tensor product $\fA\sotimes\cK$, we have
$K_*(\fA\sotimes\cK)=K^{\top}_*(\fA)$. Similarly, we prove that if $\fA$ is a
unital Banach algebra and $\ell^{\infty-}=\bigcup_{q<\infty}\ell^q$, then
$K_*(I_{\ell^{\infty-}(\fA)})$ is invariant under H\"older continuous
homotopies, and that for $*\ge 0$ it contains $K^{\top}_*(\fA)$ as a direct
summand. These $K$-theoretic results are obtained from cyclic homology
computations. We also compute the relative cyclic homology groups
$HC_*(\Gami(\fA):I_{S(\fA)})$ in terms of $HC_*(\elli(\fA):S(\fA))$ for general
$\fA$ and $S$. For $\fA=\C$ and general $S$, we further compute the latter
groups in terms of algebraic differential forms. We prove that the map
$HC_n(\Gami(\C):I_{S(\C)})\to HC_n(\cB:J_S)$ is an isomorphism in many cases.


title: On compact hyperbolic manifolds of Euler characteristic two

abstract:
  We prove that for n>4 there is no compact arithmetic hyperbolic n-manifold
whose Euler characteristic has absolute value equal to 2. In particular, this
shows the nonexistence of arithmetically defined hyperbolic rational homology
n-sphere with n even different than 4.


title: An evolving compact jet in the black hole X-ray binary MAXI J1836-194

abstract:
  We report striking changes in the broadband spectrum of the compact jet of
the black hole transient MAXI J1836-194 over state transitions during its
discovery outburst in 2011. A fading of the optical-infrared (IR) flux occurred
as the source entered the hard-intermediate state, followed by a brightening as
it returned to the hard state. The optical-IR spectrum was consistent with a
power law from optically thin synchrotron emission, except when the X-ray
spectrum was softest. By fitting the radio to optical spectra with a broken
power law, we constrain the frequency and flux of the optically thick/thin
break in the jet synchrotron spectrum. The break gradually shifted to higher
frequencies as the source hardened at X-ray energies, from ~ 10^11 to ~ 4 x
10^13 Hz. The radiative jet luminosity integrated over the spectrum appeared to
be greatest when the source entered the hard state during the outburst decay
(although this is dependent on the high energy cooling break, which is not seen
directly), even though the radio flux was fading at the time. The physical
process responsible for suppressing and reactivating the jet (neither of which
are instantaneous but occur on timescales of weeks) is uncertain, but could
arise from the varying inner accretion disk radius regulating the fraction of
accreting matter that is channeled into the jet. This provides an unprecedented
insight into the connection between inflow and outflow, and has implications
for the conditions required for jets to be produced, and hence their launching
process.


title: High Speed, High Fidelity Detection of an Atomic Hyperfine Qubit

abstract:
  Fast and efficient detection of the qubit state in trapped ion quantum
information processing is critical for implementing quantum error correction
and performing fundamental tests such as a loophole-free Bell test. In this
work we present a simple qubit state detection protocol for a $^{171}$Yb$^+$
hyperfine atomic qubit trapped in a microfabricated surface trap, enabled by
high collection efficiency of the scattered photons and low background photon
count rate. We demonstrate average detection times of 10.5, 28.1 and
99.8\,$\upmu$s, corresponding to state detection fidelities of 99%, 99.85(1)%
and 99.915(7)%, respectively.


title:
On almost everywhere convergence of strong arithmetic means of Fourier
  series

abstract:
  This article establishes a real-variable argument for Zygmund's theorem on
almost everywhere convergence of strong arithmetic means of partial sums of
Fourier series on $\mathbb{T}$, up to passing to a subsequence. Our approach
extends to, among other cases, functions that are defined on $\mathbb{T}^d$,
which allows us to establish an analogue of Zygmund's theorem in higher
dimensions.


title:
Eat the Cake and Have It Too: Privacy Preserving Location Aggregates in
  Geosocial Networks

abstract:
  Geosocial networks are online social networks centered on the locations of
subscribers and businesses. Providing input to targeted advertising, profiling
social network users becomes an important source of revenue. Its natural
reliance on personal information introduces a trade-off between user privacy
and incentives of participation for businesses and geosocial network providers.
In this paper we introduce location centric profiles (LCPs), aggregates built
over the profiles of users present at a given location. We introduce PROFILR, a
suite of mechanisms that construct LCPs in a private and correct manner. We
introduce iSafe, a novel, context aware public safety application built on
PROFILR . Our Android and browser plugin implementations show that PROFILR is
efficient: the end-to-end overhead is small even under strong correctness
assurances.


title:
CP violating anomalous couplings in $W\gamma$ and $Z\gamma$ production
  at the LHC

abstract:
  The ATLAS and CMS collaborations have recently published new limits on CP
conserving anomalous couplings from the $W\gamma$ and $Z\gamma$ production
processes. We study the corresponding limits that can be placed on the CP
violating anomalous couplings $\kappa_tilde_\gamma$ and $h^1_{\gamma, Z}$ at
the LHC. We find that the process $pp --> W\gamma$ at 14 TeV can place the 95%
CL limit $|\kappa_tilde_\gamma| <~ 0.05$ with 10 fb^{-1} which is comparable to
the existing LHC bound on the CP conserving anomalous couplings
$\kappa_\gamma$. Similarly, the process $pp --> Z\gamma$ can place the 95% CL
limits $|h^1_\gamma| <~ 20$ and $|h^1_Z| <~ 40$ respectively. None of these
limits is derived from a truly CP-odd observable so that it is not possible to
separate the effects of the CP violating anomalous couplings from the rest.


title:
Comment to "General Solution to Unidimensional Hamilton-Jacobi Equation"
  [arXiv:1302.0591v1]

abstract:
  We present previous results on the general solution of the multidimensional
Hamilton-Jacobi equation $\frac{\partial u}{\partial t} - \frac{\partial
u}{\partial x_a} \frac{\partial u}{\partial x_a}= 0$ and methods that were used
to find such general solution.