title:
Supermultiplicative relations in models of interacting self-avoiding
  walks and polygons

abstract:
  Fekete's lemma shows the existence of limits in subadditive sequences. This
lemma, and generalisations of it, also have been used to prove the existence of
thermodynamic limits in statistical mechanics. In this paper it is shown that
the two variable supermultiplicative relation $$ p_{n_1}(m_1)\,p_{n_2}(m_2)
\leq p_{n_1+n_2}(m_1 + m_2) $$ together with mild assumptions, imply the
existence of the limit $$ \log \mathcal{P}_\#(\epsilon) = \lim_{n\to\infty}
\frac{1}{n} \log p_n(\lfloor \epsilon n \rfloor).$$ This is a generalisation of
Fekete's lemma. The existence of $\mathcal{P}_\#(\epsilon)$ are proven for
models of adsorbing walks and polygons, and for pulled polygons. In addition,
numerical data are presented estimating the general shape of $\log
\mathcal{P}_\# (\epsilon)$ of models of square lattice self-avoiding walks and
polygons.


title:
Stabilisers as a design tool for new forms of Lechner-Hauke-Zoller
  Annealer

abstract:
  In a recent paper Lechner, Hauke and Zoller (LHZ) described a means to
translate a Hamiltonian of $N$ spin-$\frac{1}{2}$ particles with 'all-to-all'
interactions into a larger physical lattice with only on-site energies and
local parity constraints. LHZ used this mapping to propose a novel form of
quantum annealing. Here we provide a stabiliser-based formulation within which
we can describe both this prior approach and a wide variety of variants.
Examples include a triangular array supporting all-to-all connectivity, and
moreover arrangements requiring only $2N$ or $N\log N$ spins but providing
interesting bespoke connectivities. Further examples show that arbitrarily high
order logical terms can be efficiently realised, even in a strictly 2D layout.
Our stabilisers can correspond to either even-parity constraints, as in the LHZ
proposal, or as odd-parity constraints. Considering the latter option applied
to the original LHZ layout, we note it may simplify the physical realisation
since the required ancillas are only spin-$\frac{1}{2}$ systems (i.e. qubits,
rather than qutrits) and moreover the interactions are very simple. We make a
preliminary assessment of the impact of this design choices by simulating small
(few-qubit) systems; we find some indications that the new variant may maintain
a larger minimum energy gap during the annealing process.


title:
Effect of quantum phase transition in the disentanglement of three spins
  coupled to an XY spin chain

abstract:
  Recently, along with the development of quantum information, quantum
entanglemant became a hot topic of people. Quantum entanglemant is one of the
most amazing phenomenon in quantum mechanics that is totally different from
classical physics. However, system would interact with environment in the
practical quantum information process. The entanglement would be broken. In
this paper, we study the disentanglement evolution of three spin qubits in an
XY spin-chain environment. The dynamical process of the disentanglement is
investigated. We found the exact expression of the coherence factor. We discuss
the coherence factor and the parameters, and then we illustrate that the
disentanglement of central spins is best enhanced by the quantum critical
behavior of the environmental spin chain. Furthermore, a scaling rule is
obtained.


title: Thermodynamics of the Katok Map

abstract:
  We effect thermodynamical formalism for the non-uniformly hyperbolic
$C^\infty$ map of the two dimensional torus known as the Katok map. It is a
slowdown of a linear Anosov map near the origin and it is a local (but not
small) perturbation. We prove the existence of equilibrium measures for any
continuous potential function and obtain uniqueness of equilibrium measures
associated to the geometric $t$-potential $\varphi_t=-t\log |df|_{E^u(x)}|$ for
any $t\in(t_0,\infty)$, $t\neq 1$ where $E^u(x)$ denotes the unstable
direction. We show that $t_0$ tends to $-\infty$ as the size of the
perturbation tends to zero. Finally, we establish exponential decay of
correlations as well as the Central Limit Theorem for the equilibrium measures
associated to $\varphi_t$ for all values of $t\in (t_0, 1)$.


title: Systematic Error Estimation for Chemical Reaction Energies

abstract:
  For the theoretical understanding of the reactivity of complex chemical
systems accurate relative energies between intermediates and transition states
are required. Despite its popularity, density functional theory (DFT) often
fails to provide sufficiently accurate data, especially for molecules
containing transition metals. Due to the huge number of intermediates that need
to be studied for all but the simplest chemical processes, DFT is to date the
only method that is computationally feasible. Here, we present a Bayesian
framework for DFT that allows for error estimation of calculated properties.
Since the optimal choice of parameters in present-day density functionals is
strongly system dependent, we advocate for a system-focused
re-parameterization. While, at first sight, this approach conflicts with the
first-principles character of DFT that should make it in principle system
independent, we deliberately introduce system dependence because we can then
assign a stochastically meaningful error to the system-dependent
parametrization that makes it non-arbitrary. By re-parameterizing a functional
that was derived on a sound physical basis to a chemical system of interest we
obtain a functional that yields reliable confidence intervals for reaction
energies. We demonstrate our approach at the example of catalytic nitrogen
fixation.

categories: physics.chem-ph cond-mat.str-el physics.comp-ph physics.data-an


title:
Degrees of freedom of massless boson and fermion fields in any even
  dimension

abstract:
  This is a discussion on degrees of freedom of massless fermion and boson
fields, if they are free or weakly interacting. We generalize the gauge fields
of $S^{ab}$ - $\omega_{abc}$ - and of $\tilde{S}^{ab}$ - $
\tilde{\omega}_{abc}$ - of the spin-charge-family to the gauge fields of all
possible products of $\gamma^a$'s and of all possible products of
$\tilde{\gamma}^a$'s, the first taking care in the {\it spin-charge-family}
theory of the spins and charges quantum numbers ($\tau^{Ai}=\sum_{a,b}
c^{Ai}{}_{ab} \,S^{ab}$) of fermions, the second ($\tilde{\tau}^{Ai}=
\sum_{a,b} \tilde{c}^{Ai}{}_{ab}\, \tilde{S}^{ab}$) taking care of the families
quantum numbers.


title:
On the existence of $W^{2}_{p}$ solutions for fully nonlinear elliptic
  equations under either relaxed or no convexity assumptions

abstract:
  We establish the existence of solutions of fully nonlinear elliptic
second-order equations like $H(v,Dv,D^{2}v,x)=0$ in smooth domains without
requiring $H$ to be convex or concave with respect to the second-order
derivatives. Apart from ellipticity nothing is required of $H$ at points at
which $|D^{2}v|\leq K$, where $K$ is any given constant. For large $|D^{2}v|$
some kind of relaxed convexity assumption with respect to $D^{2}v$ mixed with a
VMO condition with respect to $x$ are still imposed. The solutions are sought
in Sobolev classes. We also establish the solvability without almost any
conditions on $H$, apart from ellipticity, but of a "cut-off" version of the
equation $H(v,Dv,D^{2}v,x)=0$.


title: Large spaces of symmetric or alternating matrices with bounded rank

abstract:
  Let $r$ and $n$ be positive integers such that $r<n$, and $\mathbb{K}$ be an
arbitrary field. In a recent work, we have determined the maximal dimension for
a linear subspace of $n$ by $n$ symmetric matrices with rank less than or equal
to $r$, and we have classified the spaces having that maximal dimension. In
this article, provided that $\mathbb{K}$ has more than two elements, we extend
this classification to spaces whose dimension is close to the maximal one: this
generalizes a result of Loewy. We also prove a similar result on spaces of
alternating matrices with bounded rank, with no restriction on the cardinality
of the underlying field.


title:
Shuffle and Learn: Unsupervised Learning using Temporal Order
  Verification

abstract:
  In this paper, we present an approach for learning a visual representation
from the raw spatiotemporal signals in videos. Our representation is learned
without supervision from semantic labels. We formulate our method as an
unsupervised sequential verification task, i.e., we determine whether a
sequence of frames from a video is in the correct temporal order. With this
simple task and no semantic labels, we learn a powerful visual representation
using a Convolutional Neural Network (CNN). The representation contains
complementary information to that learned from supervised image datasets like
ImageNet. Qualitative results show that our method captures information that is
temporally varying, such as human pose. When used as pre-training for action
recognition, our method gives significant gains over learning without external
data on benchmark datasets like UCF101 and HMDB51. To demonstrate its
sensitivity to human pose, we show results for pose estimation on the FLIC and
MPII datasets that are competitive, or better than approaches using
significantly more supervision. Our method can be combined with supervised
representations to provide an additional boost in accuracy.


title: Zeros of the zeta series of a poset and iterated barycentric subdivision

abstract:
  We study the limiting behavior of the zeros of the zeta series of a finite
poset under iterated barycentric subdivision, and we indicate the possibility
of its application to number theory.


title:
Enhancement of the electrocaloric cooling by electric field reversal:
  simulation and experiment

abstract:
  An improved thermodynamic cycle is proposed, where the cooling effect of an
electrocaloric refrigerant is enhanced by applying a reversed electric field.
In contrast to conventional adiabatic heating or cooling by on-off cycles of
the external electric field, applying a reversed field is significantly
improving the cooling efficiency, since the variation in configurational
entropy is increased. By comparing results from computer simulations using
Monte-Carlo algorithms and experiments using direct electrocaloric
measurements, we show that the electrocaloric cooling efficiency can be
enhanced by more than 20\% in standard ferroelectrics and also relaxor
ferroelectrics, like Pb(Mg$_{1/3}$/Nb$_{2/3}$)$_{0.71}$Ti$_{0.29}$O$_3$.


title:
Kernelized Weighted SUSAN based Fuzzy C-Means Clustering for Noisy Image
  Segmentation

abstract:
  The paper proposes a novel Kernelized image segmentation scheme for noisy
images that utilizes the concept of Smallest Univalue Segment Assimilating
Nucleus (SUSAN) and incorporates spatial constraints by computing circular
colour map induced weights. Fuzzy damping coefficients are obtained for each
nucleus or center pixel on the basis of the corresponding weighted SUSAN area
values, the weights being equal to the inverse of the number of horizontal and
vertical moves required to reach a neighborhood pixel from the center pixel.
These weights are used to vary the contributions of the different nuclei in the
Kernel based framework. The paper also presents an edge quality metric obtained
by fuzzy decision based edge candidate selection and final computation of the
blurriness of the edges after their selection. The inability of existing
algorithms to preserve edge information and structural details in their
segmented maps necessitates the computation of the edge quality factor (EQF)
for all the competing algorithms. Qualitative and quantitative analysis have
been rendered with respect to state-of-the-art algorithms and for images ridden
with varying types of noises. Speckle noise ridden SAR images and Rician noise
ridden Magnetic Resonance Images have also been considered for evaluating the
effectiveness of the proposed algorithm in extracting important segmentation
information.


title:
Charging of small grains in a space plasma: Application to Jovian stream
  particles

abstract:
  Most theoretical investigations of dust charging processes in space have
treated the current balance condition as independent of grain size. However,
for small grains, as they are often observed in space environments, a
dependence on grain size is expected due to secondary electron emission (SEE).
Here, by the term "small" we mean a particle size comparable to the typical
penetration depth for given primary electron energy. The results are relevant
for the dynamics of small, charged dust particles emitted by the volcanic moon
Io, which form the Jovian dust streams. We revise the theory of charging of
small (sub-micron sized) micrometeoroids to take into account a high production
of secondary electrons for small grains immersed in an isotropic flux of
electrons. We apply our model to obtain an improved estimate for the charge of
the dust streams leaving the Jovian system, detected by several spacecraft. For
the Jupiter plasma environment we derive the surface potential of grains
composed of NaCl (believed to be the major constituent of Jovian dust stream
particles) or silicates. For small particles the potential depends on grain
size and the secondary electron current induces a sensitivity to material
properties. As a result of the small particle effect, the estimates for the
charging times and for the fractional charge fluctuations of NaCl grains
obtained using our general approach to SEE give results qualitatively different
from the analogous estimates derived from the traditional approach to SEE. We
find that for the charging environment considered in this paper field emission
does not limit the charging of NaCl grains.


title: Exact discretization of harmonic tensors

abstract:
  Lyons and Sullivan have shown how to discretize harmonic functions on a
Riemannian manifold $M$ whose Brownian motion satisfies a certain recurrence
property called $\ast$-recurrence. We study analogues of this discretization
for tensor fields which are harmonic in the sense of the covariant Laplacian.
We show that, under certain restrictions on the holonomy of the connection, the
lifted diffusion on the orthonormal frame bundle has the same $\ast$-recurrence
property as the original Brownian motion. This observation permits us to reduce
to the discretization of ordinary harmonic functions by a device called
scalarization.


title:
Edge effects in the magnetic interference pattern of a ballistic SNS
  junction

abstract:
  We investigate the Josephson critical current $I_c(\Phi)$ of a wide
superconductor-normal metal-superconductor (SNS) junction as a function of the
magnetic flux $\Phi$ threading it. Electronic trajectories reflected from the
side edges alter the function $I_c(\Phi)$ as compared to the conventional
Fraunhofer-type dependence. At weak magnetic fields, $B\lesssim \Phi_0/d^2$,
the edge effect lifts zeros in $I_c(\Phi)$ and gradually shifts the minima of
that function toward half-integer multiples of the flux quantum. At
$B>\Phi_0/d^2$, the edge effect leads to an accelerated decay of the critical
current $I_c(\Phi)$ with increasing $\Phi$. At larger fields, eventually, the
system is expected to cross into a regime of "classical" mesoscopic
fluctuations that is specific for wide ballistic SNS junctions with rough
edges.


title:
Co-Dimension One Area-Minimizing Currents with $C^{1,\alpha}$
  Tangentially Immersed Boundary

abstract:
  We introduce and study co-dimension one area-minimizing locally rectifiable
currents $T$ with $C^{1,\alpha}$ tangentially immersed boundary: $\partial T$
is locally a finite sum of orientable co-dimension two submanifolds which only
intersect tangentially with equal orientation. We show that any such $T$ is
supported in a smooth hypersurface near any point on the support of $\partial
T$ where $T$ has tangent cone which is a hyperplane with constant orientation
but non-constant multiplicity. We also introduce and study co-dimensional one
area-minimizing locally rectifiable currents $T$ with boundary having
co-oriented mean curvature: $\partial T$ has generalized mean curvature
$H_{\partial T} = h \nu_{T}$ with $h$ a real-valued function and $\nu_{T}$ the
generalized outward pointing unit normal of $\partial T$ with respect to $T.$


title: Supercharacters for Normal Supercharacter Theory

abstract:
  In order to find a tractable theory to substitute for the wild character
theory of the group of $n\times n$ unipotent upper-triangular matrices over a
finite field $\mathbb{F}_q$, Andr\'e and Yan introduced the notion of
supercharacter theory. In this paper, we construct a supercharacter theory from
an arbitrary set $S$ of normal subgroups of $G$. We call such supercharacter
theory the normal supercharacter theory generated by $S$. It is shown that
normal supercharacter theories are integral, and a recursive formula for
supercharacters of the normal supercharacter theory is provided. The normal
supercharacter theory provides many substitutions for wild character theories.
Also, we indicate that the superclasses of the normal supercharacter theory
generated by all normal subgroups of $G$ are given by certain values on the
primitive central idempotents. We study the connection between the finest
normal supercharacter theory and faithful irreducible characters. Moreover, an
algorithm is presented to construct the supercharacter table of the finest
normal supercharacter theory from the character table. Finally, We justify that
normal supercharacter theories cannot be obtained by preceding supercharacter
theory constructions.


title: Three-Terminal Energy Harvester with Coupled Quantum Dots

abstract:
  Rectification of thermal fluctuations in mesoscopic conductors is the key
idea of today's attempts to build nanoscale thermoelectric energy harvesters in
order to convert heat into a useful electric power. So far, most concepts make
use of the Seebeck effect in a two-terminal geometry where heat and charge are
both carried by the same particles. Here, we experimentally demonstrate the
working principle of a new kind of energy harvester, proposed recently using
two capacitively coupled quantum dots. We show that due to its novel
three-terminal design which spatially separates the heat reservoir from the
conductor circuit, the directions of charge and heat flow become decoupled in
our device. This enables us to manipulate the direction of the generated charge
current by means of external gate voltages while leaving the direction of heat
flow unaffected. Our results pave the way for a new generation of
multi-terminal, highly efficient nanoscale heat engines.


title:
Stable Generalized Finite Element Method and associated iterative
  schemes; application to interface problems

abstract:
  The Generalized Finite Element Method (GFEM) is an extension of the Finite
Element Method (FEM), where the standard finite element space is augmented with
a space of non-polynomial functions, called the enrichment space. The functions
in the enrichment space mimic the local behavior of the unknown solution of the
underlying variational problem. GFEM has been successfully applied to a wide
range of problems. However, it often suffers from bad conditioning, i.e., its
conditioning may not be robust with respect to the mesh and in fact, the
conditioning could be much worse than that of the standard FEM. In this paper,
we present a numerical study that shows that if the "angle" between the finite
element space and the enrichment space is bounded away from 0, uniformly with
respect to the mesh, then the GFEM is stable, i.e., the conditioning of GFEM is
not worse than that of the standard FEM. A GFEM with this property is called a
Stable GFEM (SGFEM). The last part of the paper is devoted to the derivation of
a robust iterative solver exploiting this angle condition. It is shown that the
required "wall-clock" time is greatly reduced compared to popular GFEMs used in
the literature.


title:
A robust and efficient adaptive multigrid solver for the optimal control
  of phase field formulations of geometric evolution laws

abstract:
  We propose and investigate a novel solution strategy to efficiently and
accurately compute approximate solutions to semilinear optimal control
problems, focusing on the optimal control of phase field formulations of
geometric evolution laws. The optimal control of geometric evolution laws
arises in a number of applications in fields including material science, image
processing, tumour growth anda cell motility. In the current work we focus on a
phase field formulation of the optimal control problem, hence exploiting the
well developed mathematical theory for the optimal control of semilinear
parabolic partial differential equations. Approximation of the resulting
optimal control problem is computationally challenging, requiring massive
amounts of computational time and memory storage. The main focus of this work
is to propose, derive, implement and test an efficient solution method for such
problems. The solver for the discretised partial differential equations is
based upon a geometric multigrid method incorporating advanced techniques to
deal with the nonlinearities in the problem and utilising adaptive mesh
refinement. An in-house two-grid solution strategy for the forward and adjoint
problems, that significantly reduces memory requirements and CPU time, is
proposed and investigated computationally. Furthermore, parallelisation as well
as an adaptivestep gradient update for the control are employed to further
improve efficiency. Along with a detailed description of our proposed solution
method together with its implementation we present a number of computational
results that demonstrate and evaluate our algorithms with respect to accuracy
and efficiency. A highlight of the present work is simulation results on the
optimal control in 3-D which would be computationally infeasible without the
solution strategies proposed in the present work.


title: GSC 03144-595, a new triple-mode HADS

abstract:
  We present results of a multi-year study of the high-amplitude $\delta$ Scuti
(HADS) star GSC 03144-595. The star was observed between June and September in
2011 and 2014 for 13 nights and 28 nights respectively. Based on our results we
argue that GSC 03144-595 is a new triple-mode radially pulsating HADS, only the
fifth discovered and only the second that has a fundamental frequency in the
traditional $\delta$ Scuti regime. While the frequencies and amplitudes of the
fundamental and first harmonic were found to be unchanged between 2011 and
2014, we found that the amplitude of the second harmonic increased by 44\%, a
form of evolution not previously seen. This finding suggests that the second
harmonic may be transient, thus explaining the scarcity of triple mode HADS
stars.


title: Stokesian swimming of a prolate spheroid at low Reynolds number

abstract:
  The swimming of a spheroid immersed in a viscous fluid and performing surface
deformations periodically in time is studied on the basis of Stokes equations
of low Reynolds number hydrodynamics. The average over a period of time of the
swimming velocity and the rate of dissipation are given by integral expressions
of second order in the amplitude of surface deformations. The first order flow
velocity and pressure, as functions of spheroidal coordinates, are expressed as
sums of basic solutions of Stokes equations. Sets of superposition coefficients
of these solutions which optimize the mean swimming speed for given power are
derived from an eigenvalue problem. The maximum eigenvalue is a measure of the
efficiency of the optimal stroke within the chosen class of motions. The
maximum eigenvalue for sets of low order is found to be a strongly increasing
function of the aspect ratio of the spheroid.


title: Attend, Infer, Repeat: Fast Scene Understanding with Generative Models

abstract:
  We present a framework for efficient inference in structured image models
that explicitly reason about objects. We achieve this by performing
probabilistic inference using a recurrent neural network that attends to scene
elements and processes them one at a time. Crucially, the model itself learns
to choose the appropriate number of inference steps. We use this scheme to
learn to perform inference in partially specified 2D models (variable-sized
variational auto-encoders) and fully specified 3D models (probabilistic
renderers). We show that such models learn to identify multiple objects -
counting, locating and classifying the elements of a scene - without any
supervision, e.g., decomposing 3D images with various numbers of objects in a
single forward pass of a neural network. We further show that the networks
produce accurate inferences when compared to supervised counterparts, and that
their structure leads to improved generalization.


title:
Trace Ideals and Centers of Endomorphism Rings of Modules over
  Commutative Rings

abstract:
  Let $R$ be a commutative Noetherian ring and $M$ a finitely generated
$R$-module. Under various hypotheses, it is proved that the center of
$\mbox{End}_R(M)$ coincides with the endomorphism ring of the trace ideal of
$M$. These results are exploited to establish results for balanced and rigid
modules, and to settle certain cases of a conjecture of Huneke and Wiegand.


title:
Proceedings 7th International Workshop on Formal Methods and Analysis in
  Software Product Line Engineering

abstract:
  In Software Product Line Engineering (SPLE), a portfolio of similar systems
is developed from a shared set of software assets. Claimed benefits of SPLE
include reductions in the portfolio size, cost of software development and time
to production, as well as improvements in the quality of the delivered systems.
Yet, despite these benefits, SPLE is still in the early adoption stage. We
believe that automated approaches, tools and techniques that provide better
support for SPLE activities can further facilitate its adoption in practice and
increase its benefits.
  To promote work in this area, the FMSPLE'16 workshop focuses on automated
analysis and formal methods, which can (1) lead to a further increase in
development productivity and reduction in maintenance costs associated with
management of the SPLE artifacts, and (2) provide proven guarantees for the
correctness and quality of the delivered systems.


title:
Analysis of k-Nearest Neighbor Distances with Application to Entropy
  Estimation

abstract:
  Estimating entropy and mutual information consistently is important for many
machine learning applications. The Kozachenko-Leonenko (KL) estimator
(Kozachenko & Leonenko, 1987) is a widely used nonparametric estimator for the
entropy of multivariate continuous random variables, as well as the basis of
the mutual information estimator of Kraskov et al. (2004), perhaps the most
widely used estimator of mutual information in this setting. Despite the
practical importance of these estimators, major theoretical questions regarding
their finite-sample behavior remain open. This paper proves finite-sample
bounds on the bias and variance of the KL estimator, showing that it achieves
the minimax convergence rate for certain classes of smooth functions. In
proving these bounds, we analyze finite-sample behavior of k-nearest neighbors
(k-NN) distance statistics (on which the KL estimator is based). We derive
concentration inequalities for k-NN distances and a general expectation bound
for statistics of k-NN distances, which may be useful for other analyses of
k-NN methods.


title:
Negation and partial axiomatizations of dependence and independence
  logic revisited

abstract:
  In this paper, we axiomatize the negatable consequences in dependence and
independence logic by extending the systems of natural deduction of the logics
given in (Kontinen and Vaananen 2013) and (Hannula 2015). We prove a
characterization theorem for negatable formulas in independence logic and
negatable sentences in dependence logic, and identify an interesting class of
formulas that are negatable in independence logic. Dependence and independence
atoms, first-order formulas belong to this class. We also demonstrate our
extended system of independence logic by giving explicit derivations for
Armstrong's Axioms and the Geiger-Paz-Pearl axioms of dependence and
independence atoms.


title:
Development of an ADC Radiation Tolerance Characterization System for
  the Upgrade of the ATLAS LAr Calorimeter

abstract:
  ATLAS LAr calorimeter will perform its Phase-I upgrade during the long shut
down (LS2) in 2018, a new LAr Trigger Digitizer Board (LTDB) will be designed
and installed. Several commercial-off-the-shelf (COTS) multichannel high-speed
ADCs have been selected as possible backups of the radiation tolerant ADC ASICs
for LTDB. In order to evaluate the radiation tolerance of these back up
commercial ADCs, we developed an ADC radiation tolerance characterization
system, which includes the ADC boards, data acquisition (DAQ) board, signal
generator, external power supplies and a host computer. The ADC board is custom
designed for different ADCs, which has ADC driver and clock distribution
circuits integrated on board. The Xilinx ZC706 FPGA development board is used
as DAQ board. The data from ADC are routed to the FPGA through the FMC (FPGA
Mezzanine Card) connector, de-serialized and monitored by the FPGA, and then
transmitted to the host computer through the Gigabit Ethernet. A software
program has been developed with Python, and all the commands are sent to the
DAQ board through Gigabit Ethernet by this program. Two ADC boards have been
designed for the TI ADS52J90 and ADI AD9249 respectively. TID test of both ADCs
have been performed at BNL, and SEE test for ADS52J90 has been performed at
Massachusetts General Hospital (MGH). Test results have been analyzed and
presented. The test results demonstrate that our test system is very versatile,
and working well for the radiation tolerance characterization of commercial
multi-channel high-speed ADC for the upgrade of the ATLAS LAr calorimeter. It
is applicable to other collider physics experiments where radiation tolerance
is required as well.


title: Space-charge effects in high-energy photoemission

abstract:
  Pump-and-probe photoelectron spectroscopy (PES) with femtosecond pulsed
sources opens new perspectives in the investigation of the ultrafast dynamics
of physical and chemical processes at the surfaces and interfaces of solids.
Nevertheless, for very intense photon pulses a large number of photoelectrons
are simultaneously emitted and their mutual Coulomb repulsion is sufficiently
strong to significantly modify their trajectory and kinetic energy. This
phenomenon, referred as space-charge effect, determines a broadening and shift
in energy for the typical PES structures and a dramatic loss of energy
resolution. In this article we examine the effects of space charge in PES with
a particular focus on time-resolved hard X-ray (~10 keV) experiments. The
trajectory of the electrons photoemitted from pure Cu in a hard X-ray PES
experiment has been reproduced through $N$-body simulations and the broadening
of the photoemission core-level peaks has been monitored as a function of
various parameters (photons per pulse, linear dimension of the photon spot,
photon energy). The energy broadening results directly proportional to the
number $N$ of electrons emitted per pulse (mainly represented by secondary
electrons) and inversely proportional to the linear dimension $a$ of the photon
spot on the sample surface, in agreement with the literature data about
ultraviolet and soft X-ray experiments. The evolution in time of the energy
broadening during the flight of the photoelectrons is also studied. Despite its
detrimental consequences on the energy spectra, we found that space charge has
negligible effects on the momentum distribution of photoelectrons and a
momentum broadening is not expected to affect angle-resolved experiments.
Strategy to reduce the energy broadening and the feasibility of hard X-ray PES
experiments at the new free-electron laser facilities are discussed.


title:
Provably Safe and Deadlock-Free Execution of Multi-Robot Plans under
  Delaying Disturbances

abstract:
  One of the standing challenges in multi-robot systems is the ability to
reliably coordinate motions of multiple robots in environments where the robots
are subject to disturbances. We consider disturbances that force the robot to
temporarily stop and delay its advancement along its planned trajectory which
can be used to model, e.g., passing-by humans for whom the robots have to
yield. Although reactive collision-avoidance methods are often used in this
context, they may lead to deadlocks between robots. We design a multi-robot
control strategy for executing coordinated trajectories computed by a
multi-robot trajectory planner and give a proof that the strategy is safe and
deadlock-free even when robots are subject to delaying disturbances. Our
simulations show that the proposed strategy scales significantly better with
the intensity of disturbances than the naive liveness-preserving approach. The
empirical results further confirm that the proposed approach is more reliable
and also more efficient than state-of-the-art reactive techniques.


title: On a conjecture of Cigler

abstract:
  A conjecture of Cigler which realizes normalized q-Hermite polynomials as
moments is verified.


title: Exponential Concentration of a Density Functional Estimator

abstract:
  We analyze a plug-in estimator for a large class of integral functionals of
one or more continuous probability densities. This class includes important
families of entropy, divergence, mutual information, and their conditional
versions. For densities on the $d$-dimensional unit cube $[0,1]^d$ that lie in
a $\beta$-H\"older smoothness class, we prove our estimator converges at the
rate $O \left( n^{-\frac{\beta}{\beta + d}} \right)$. Furthermore, we prove the
estimator is exponentially concentrated about its mean, whereas most previous
related results have proven only expected error bounds on estimators.


title: On Fast Decoding of High Dimensional Signals from One-Bit Measurements

abstract:
  In the problem of one-bit compressed sensing, the goal is to find a
$\delta$-close estimation of a $k$-sparse vector $x \in \mathbb{R}^n$ given the
signs of the entries of $y = \Phi x$, where $\Phi$ is called the measurement
matrix. For the one-bit compressed sensing problem, previous work
\cite{Plan-robust,support} achieved $\Theta (\delta^{-2} k \log(n/k))$ and
$\tilde{ \Oh} ( \frac{1}{ \delta } k \log (n/k))$ measurements, respectively,
but the decoding time was $\Omega ( n k \log (n / k ))$. \ In this paper, using
tools and techniques developed in the context of two-stage group testing and
streaming algorithms, we contribute towards the direction of very fast decoding
time. We give a variety of schemes for the different versions of one-bit
compressed sensing, such as the for-each and for-all version, support recovery;
all these have $poly(k, \log n)$ decoding time, which is an exponential
improvement over previous work, in terms of the dependence of $n$.


title: Commensurability of groups quasi-isometric to RAAG's

abstract:
  Let $G$ be a right-angled Artin group with defining graph $\Gamma$ and let
$H$ be a finitely generated group quasi-isometric to $G(\Gamma)$. We show if
$G$ satisfies (1) its outer automorphism group is finite; (2) $\Gamma$ does not
have induced 4-cycle; (3) $\Gamma$ is star-rigid; then $H$ is commensurable to
$G$. We show condition (2) is sharp in the sense that if $\Gamma$ contains an
induced 4-cycle, then there exists an $H$ quasi-isometric to $G(\Gamma)$ but
not commensurable to $G(\Gamma)$. Moreover, one can drop condition (1) if $H$
is a uniform lattice acting on the universal cover of the Salvetti complex of
$G(\Gamma)$. As a consequence, we obtain a conjugation theorem for such uniform
lattices. The ingredients of the proof include a blow-up building construction
in \cite{cubulation} and a Haglund-Wise style combination theorem for certain
class of special cube complexes. However, in most of our cases, relative
hyperbolicity is absent, so we need new ingredients for the combination
theorem.


title: Pointwise differentiability of higher order for sets

abstract:
  The present paper develops two concepts of pointwise differentiability of
higher order for arbitrary subsets of Euclidean space defined by comparing
their distance functions to those of smooth submanifolds. Results include that
differentials are Borel functions, higher order rectifiability of the set of
differentiability points, and a Rademacher result. One concept is characterised
by a limit procedure involving inhomogeneously dilated sets.
  The original motivation to formulate the concepts stems from studying the
support of stationary integral varifolds. In particular, strong pointwise
differentiability of every positive integer order is shown at almost all points
of the intersection of the support with a given plane.


title:
The network survival method for estimating adult mortality: Evidence
  from a survey experiment in Rwanda

abstract:
  Adult death rates are a critical indicator of population health and
wellbeing. Wealthy countries have high-quality vital registration systems, but
poor countries lack this infrastructure and must rely on estimates that are
often problematic. In this paper, we introduce the network survival method, a
new approach for estimating adult death rates. We derive the precise conditions
under which it produces estimates that are consistent and unbiased. Further, we
develop an analytical framework for sensitivity analysis. To assess the
performance of the network survival method in a realistic setting, we conducted
a nationally-representative survey experiment in Rwanda (n=4,669). Network
survival estimates were similar to estimates from other methods, even though
the network survival estimates were made with substantially smaller samples and
are based entirely on data from Rwanda, with no need for model life tables or
pooling of data from other countries. Our analytic results demonstrate that the
network survival method has attractive properties, and our empirical results
show that it can be used in countries where reliable estimates of adult death
rates are sorely needed.


title:
Generalized Exponential Concentration Inequality for R\'enyi Divergence
  Estimation

abstract:
  Estimating divergences in a consistent way is of great importance in many
machine learning tasks. Although this is a fundamental problem in nonparametric
statistics, to the best of our knowledge there has been no finite sample
exponential inequality convergence bound derived for any divergence estimators.
The main contribution of our work is to provide such a bound for an estimator
of R\'enyi-$\alpha$ divergence for a smooth H\"older class of densities on the
$d$-dimensional unit cube $[0, 1]^d$. We also illustrate our theoretical
results with a numerical experiment.


title: Homology of Associative Shelves

abstract:
  Homology theories for associative algebraic structures are well established
and have been studied for a long time. More recently, homology theories for
self-distributive algebraic structures motivated by knot theory, such as
quandles and their relatives, have been developed and investigated. In this
paper, we study associative self-distributive algebraic structures and their
one-term and two-term (rack) homology groups.


title: A simple alternative to the Crystal Ball function

abstract:
  We present a simple alternative to the Crystal Ball function that has an
exponential tail stitched to a Gaussian core. It has one parameter less than
the Crystal Ball function and, where appropriate, offers more stable fits to
peaks that continue into exponential tails. The function may also be extended
with two exponential tails on each side of the Gaussian, and this has two
parameters less than the corresponding double-shouldered Crystal Ball function.
This function has been used to model background and signal processes in a
recent Higgs pair production search and may be of versatile use in experimental
physics and other fields.


title:
Exploring Local Context for Multi-target Tracking in Wide Area Aerial
  Surveillance

abstract:
  Tracking many vehicles in wide coverage aerial imagery is crucial for
understanding events in a large field of view. Most approaches aim to associate
detections from frame differencing into tracks. However, slow or stopped
vehicles result in long-term missing detections and further cause tracking
discontinuities. Relying merely on appearance clue to recover missing
detections is difficult as targets are extremely small and in grayscale. In
this paper, we address the limitations of detection association methods by
coupling it with a local context tracker (LCT), which does not rely on motion
detections. On one hand, our LCT learns neighboring spatial relation and tracks
each target in consecutive frames using graph optimization. It takes the
advantage of context constraints to avoid drifting to nearby targets. We
generate hypotheses from sparse and dense flow efficiently to keep solutions
tractable. On the other hand, we use detection association strategy to extract
short tracks in batch processing. We explicitly handle merged detections by
generating additional hypotheses from them. Our evaluation on wide area aerial
imagery sequences shows significant improvement over state-of-the-art methods.


title: Self-Triggered Time-Varying Convex Optimization

abstract:
  In this paper, we propose a self-triggered algorithm to solve a class of
convex optimization problems with time-varying objective functions. It is known
that the trajectory of the optimal solution can be asymptotically tracked by a
continuous-time state update law. Unfortunately, implementing this requires
continuous evaluation of the gradient and the inverse Hessian of the objective
function which is not amenable to digital implementation. Alternatively, we
draw inspiration from self-triggered control to propose a strategy that
autonomously adapts the times at which it makes computations about the
objective function, yielding a piece-wise affine state update law. The
algorithm does so by predicting the temporal evolution of the gradient using
known upper bounds on higher order derivatives of the objective function. Our
proposed method guarantees convergence to arbitrarily small neighborhood of the
optimal trajectory in finite time and without incurring Zeno behavior. We
illustrate our framework with numerical simulations.


title:
Prepositional Attachment Disambiguation Using Bilingual Parsing and
  Alignments

abstract:
  In this paper, we attempt to solve the problem of Prepositional Phrase (PP)
attachments in English. The motivation for the work comes from NLP applications
like Machine Translation, for which, getting the correct attachment of
prepositions is very crucial. The idea is to correct the PP-attachments for a
sentence with the help of alignments from parallel data in another language.
The novelty of our work lies in the formulation of the problem into a dual
decomposition based algorithm that enforces agreement between the parse trees
from two languages as a constraint. Experiments were performed on the
English-Hindi language pair and the performance improved by 10% over the
baseline, where the baseline is the attachment predicted by the MSTParser model
trained for English.


title: Fano Interference in Two-Photon Transport

abstract:
  We present a general input-output formalism for the few-photon transport in
multiple waveguide channels coupled to a local cavity. Using this formalism, we
study the effect of Fano interference in two-photon quantum transport. We show
that the physics of Fano interference can manifest as an asymmetric spectral
line shape in the frequency dependence of the two-photon correlation function.
The two-photon fluorescence spectrum, on the other hand, does not exhibit the
physics of Fano interference.


title: Terminal chords in connected chord diagrams

abstract:
  Rooted connected chord diagrams form a nice class of combinatorial objects.
Recently they were shown to index solutions to certain Dyson-Schwinger
equations in quantum field theory. Key to this indexing role are certain
special chords which are called terminal chords. Terminal chords provide a
number of combinatorially interesting parameters on rooted connected chord
diagrams which have not been studied previously. Understanding these parameters
better has implications for quantum field theory.
  Specifically, we show that the distributions of the number of terminal chords
and the number of adjacent terminal chords are asymptotically Gaussian with
logarithmic means, and we prove that the average index of the first terminal
chord is $2n/3$. Furthermore, we obtain a method to determine any next-to${}^i$
leading log expansion of the solution to these Dyson-Schwinger equations, and
have asymptotic information about the coefficients of the log expansions.


title: The Conditional Lucas & Kanade Algorithm

abstract:
  The Lucas & Kanade (LK) algorithm is the method of choice for efficient dense
image and object alignment. The approach is efficient as it attempts to model
the connection between appearance and geometric displacement through a linear
relationship that assumes independence across pixel coordinates. A drawback of
the approach, however, is its generative nature. Specifically, its performance
is tightly coupled with how well the linear model can synthesize appearance
from geometric displacement, even though the alignment task itself is
associated with the inverse problem. In this paper, we present a new approach,
referred to as the Conditional LK algorithm, which: (i) directly learns linear
models that predict geometric displacement as a function of appearance, and
(ii) employs a novel strategy for ensuring that the generative pixel
independence assumption can still be taken advantage of. We demonstrate that
our approach exhibits superior performance to classical generative forms of the
LK algorithm. Furthermore, we demonstrate its comparable performance to
state-of-the-art methods such as the Supervised Descent Method with
substantially less training examples, as well as the unique ability to "swap"
geometric warp functions without having to retrain from scratch. Finally, from
a theoretical perspective, our approach hints at possible redundancies that
exist in current state-of-the-art methods for alignment that could be leveraged
in vision systems of the future.


title:
Model Completeness for Henselian Fields with finite ramification valued
  in a $Z$-Group

abstract:
  We prove that the theory of a Henselian valued field of characteristic zero,
with finite ramification, and whose value group is a $Z$-group, is
model-complete in the language of rings if the theory of its residue field is
model-complete in the language of rings. We apply this to prove that every
infinite algebraic extension of the field of $p$-adic numbers $\Bbb Q_p$ with
finite ramification is model-complete in the language of rings. For this, we
give a necessary and sufficient condition for model-completeness of the theory
of a perfect pseudo-algebraically closed field with pro-cyclic absolute Galois
group.


title:
Direct Evidence for Suppression of the Kondo Effect due to Pure Spin
  Current

abstract:
  We study the effect of a pure spin current on the Kondo singlet in a diluted
magnetic alloy using non-local lateral spin valve structures with highly spin
polarized Co2FeSi electrodes. Temperature dependence of the non-local spin
signals shows a sharp reduction with decreasing temperature, followed by a
plateau corresponding to the low temperature Fermi liquid regime below the
Kondo temperature (TK). The spin diffusion length of the Kondo alloy is found
to increase with the evolution of spin accumulation. The results are in
agreement with the intuitive description that the Kondo singlet cannot survive
any more in sufficiently large spin accumulation even below TK.


title: The mass formula for an exotic BTZ black hole

abstract:
  An exotic Banados-Teitelboim-Zanelli (BTZ) black hole has an angular momentum
larger than its mass in three dimension (3D), which suggests the possibility
that cosmic censorship could be violated if angular momentum is extracted by
the Penrose process. In this paper, we propose a mass formula for the exotic
BTZ black hole and show no violation of weak cosmic censorship in the gedanken
process above by understanding properly its mass formula. Unlike the other
black holes, the total energy of the exotic BTZ black hole is represented by
the angular momentum instead of the mass, which supports a basic point of view
that the same geometry should be determined by the same energy in 3D general
relativity whose equation of motion can be given either by normal 3D Einstein
gravity or by exotic 3D Einstein gravity. However, only the mass of the exotic
black hole is related to the thermodynamics and other forms of energy are
"dumb", which is consistent with the earlier thermodynamic analysis about
exotic black holes.


title:
Model theory of finite-by-Presburger Abelian groups and finite
  extensions of $p$-adic fields

abstract:
  We define a class of pre-ordered abelian groups that we call
finite-by-Presburger groups, and prove that their theory is model-complete. We
show that certain quotients of the multiplicative group of a local field of
characteristic zero are finite-by-Presburger and interpret the higher residue
rings of the local field. We apply these results to give a new proof of the
model completeness in the ring language of a local field of characteristic zero
(a result that follows also from work of Prestel-Roquette).


title:
A weakly informative prior for Bayesian dynamic model selection with
  applications in fMRI

abstract:
  In recent years, Bayesian statistics methods in neuroscience have been
showing important advances. In particular, detection of brain signals for
studying the complexity of the brain is an active area of research. Functional
magnetic resonance imagining (fMRI) is an important tool to determine which
parts of the brain are activated by different types of physical behavior.
According to recent results there is evidence that the values of the
connectivity brain signal parameters are close to zero and due to the nature of
time series fMRI data with high frequency behavior, Bayesian dynamic models for
identifying sparsity are indeed far-reaching. We propose a multivariate
Bayesian dynamic approach for model selection and shrinkage estimation of the
connectivity parameters. We describe the coupling or lead-lag between any pair
of regions by using mixture priors for the connectivity parameters and propose
a new weakly informative default prior for the state variances. This framework
produces one-step-ahead proper posterior predictive results and induces
shrinkage and robustness suitable for fMRI data in the presence of sparsity. To
explore the performance of the proposed methodology we present simulation
studies and an application to functional magnetic resonance imaging data.


title:
Comprehensive investigation on the correlation of growth, structural and
  optical properties of GaN nanowires grown on Si(111) substrates by plasma
  assisted molecular beam epitaxy technique

abstract:
  The present study elucidates the correlation between the structural and
optical properties of GaN nanowires grown on Si(111) substrate by plasma
assisted molecular beam epitaxy (PA-MBE) technique under various growth
conditions. GaN NWs exhibiting different shapes, sizes and distribution were
grown at various substrate temperatures with same Ga-N (III-V) ratio of 0.4. We
observe that sample grown at lower substrate temperature (~700 degC) results
2-dimensional island like structure with almost very little (~30%) circularity
while increasing substrate temperature (>770 degC) leads to growth of
individual GaN NW (>80% circularity) with excellent structural properties. The
temperature dependent photoluminescence measurement together with analysis of
RAMAN active modes provides legitimate evidences of strong correlation between
the structure and optical properties GaN nanowires grown on Si substrates.


title:
Classification-based Financial Markets Prediction using Deep Neural
  Networks

abstract:
  Deep neural networks (DNNs) are powerful types of artificial neural networks
(ANNs) that use several hidden layers. They have recently gained considerable
attention in the speech transcription and image recognition community
(Krizhevsky et al., 2012) for their superior predictive properties including
robustness to overfitting. However their application to algorithmic trading has
not been previously researched, partly because of their computational
complexity. This paper describes the application of DNNs to predicting
financial market movement directions. In particular we describe the
configuration and training approach and then demonstrate their application to
backtesting a simple trading strategy over 43 different Commodity and FX future
mid-prices at 5-minute intervals. All results in this paper are generated using
a C++ implementation on the Intel Xeon Phi co-processor which is 11.4x faster
than the serial version and a Python strategy backtesting environment both of
which are available as open source code written by the authors.


title:
On the Bernoulli property for certain partially hyperbolic
  diffeomorphisms

abstract:
  We address the classical problem of equivalence between Kolmogorov and
Bernoulli property of smooth dynamical systems. In a natural class of volume
preserving partially hyperbolic diffeomorphisms homotopic to Anosov ("derived
from Anosov") on 3-torus, we prove that Kolmogorov and Bernoulli properties are
equivalent.
  In our approach, we propose to study the conditional measures of volume along
central foliation to recover fine ergodic properties for partially hyperbolic
diffeomorphisms. As an important consequence we obtain that there exists an
almost everywhere conjugacy between any volume preserving derived from Anosov
diffeomorphism of 3-torus and its linearization.
  Our results also hold in higher dimensional case when central bundle is one
dimensional and stable and unstable foliations are quasi-isometric.


title:
Confirming the intrinsic abundance spread in the globular cluster NGC
  6273 (M 19) with calcium triplet spectroscopy

abstract:
  We present metallicities for red giant stars in the globular cluster NGC 6273
based on intermediate resolution GMOS-S spectra of the calcium triplet region.
For the 42 radial velocity members with reliable calcium triplet line strength
measurements, we obtain metallicities, [Fe/H], using calibrations established
from standard globular clusters. We confirm the presence of an intrinsic
abundance dispersion identified by Johnson et al. (2015). The total range in
[Fe/H] is ~1.0 dex and after taking into account the measurement errors, the
intrinsic abundance dispersion is \sigma[Fe/H] = 0.17 dex. Among the Galactic
globular clusters, the abundance dispersion in NGC 6273 is only exceeded by
omega Cen, which is regarded as the remnant of a disrupted dwarf galaxy, and M
54, which is the nuclear star cluster of the Sagittarius dwarf galaxy. If these
three globular clusters share the same formation mechanism, then NGC 6273 may
also be the remnant nucleus of a disrupted dwarf galaxy.


title: Comments on the two-photon interferometry

abstract:
  In this article we try to describe the physics of a standard optical
interferometer fed by "quantum" photons in terms of primitive, nevertheless
accurate formulation. We derive explicit interferene patterns and show how they
vary depending on the input photon state.


title:
Subarcsecond Analysis of Infalling-Rotating Envelope around the Class I
  Protostar IRAS 04365+2535

abstract:
  Sub-arcsecond images of the rotational line emission of CS and SO have been
obtained toward the Class I protostar IRAS 04365$+$2535 in TMC-1A with ALMA. A
compact component around the protostar is clearly detected in the CS and SO
emission. The velocity structure of the compact component of CS reveals
infalling-rotating motion conserving the angular momentum. It is well explained
by a ballistic model of an infalling-rotating envelope with the radius of the
centrifugal barrier (a half of the centrifugal radius) of 50 AU, although the
distribution of the infalling gas is asymmetric around the protostar. The
distribution of SO is mostly concentrated around the radius of the centrifugal
barrier of the simple model. Thus a drastic change in chemical composition of
the gas infalling onto the protostar is found to occur at a 50 AU scale
probably due to accretion shocks, demonstrating that the infalling material is
significantly processed before being delivered into the disk.


title:
Covariance in the Thermal SZ-Weak Lensing Mass Scaling Relation of
  Galaxy Clusters

abstract:
  The thermal Sunyaev-Zel'dovich (tSZ) effect signal is widely recognized as a
robust mass proxy of galaxy clusters with small intrinsic scatter. However,
recent observational calibration of the tSZ scaling relation using weak lensing
(WL) mass exhibits considerably larger scatter than the intrinsic scatter
predicted from numerical simulations. This raises a question as to whether we
can realize the full statistical power of ongoing and upcoming tSZ-WL
observations of galaxy clusters. In this work, we investigate the origin of
observed scatter in the tSZ-WL scaling relation, using mock maps of galaxy
clusters extracted from cosmological hydrodynamic simulations. We show that the
inferred intrinsic scatter from mock tSZ-WL analyses is considerably larger
than the intrinsic scatter measured in simulations, and comparable to the
scatter in the observed tSZ-WL relation. We show that this enhanced scatter
originates from the combination of the projection of correlated structures
along the line of sight and the uncertainty in the cluster radius associated
with WL mass estimates, causing the amplitude of the scatter to depend on the
covariance between tSZ and WL signals. We present a statistical model to
recover the unbiased cluster scaling relation and cosmological parameter by
taking into account the covariance in the tSZ-WL mass relation from
multi-wavelength cluster surveys.


title: Systems of reflected quasilinear stochastic PDEs in a convex domain

abstract:
  This paper presents existence and uniqueness results for reflected system of
quasilinear stochastic partial differential equations in a convex domain D from
Rk. The method is based on the probabilistic interpretation of the solution by
using the backward doubly stochastic differential equation. The solution is
expressed as a pair (u,{\nu}) where u is a predictable continuous process which
takes values in a proper Sobolev space and {\nu} is a random signed regular
measure satisfying the minimal Skohorod condition.


title:
Spectral geometry approach to Horava-Lifshitz type theories: gravity and
  matter sectors in IR regime

abstract:
  We give a brief exposition of the approach based on the methods of spectral
geometry and the spectral action principle to construction and analysis of
models on a foliated space-time.


title: Multidimensional Compound Poisson Distributions in Free Probability

abstract:
  Inspired by R. Speicher's multidimensional free central limit theorem and
semicircle families, we prove an infinite dimensional compound Poisson limit
theorem in free probability, and define infinite dimensional compound free
Poisson distributions in a non-commutative probability space. Infinite
dimensional free infinitely divisible distributions are defined and
characterized in terms of its free cumulants. It is proved that for a
distribution of a sequence of random variables, the following statements are
equivalent. (1) The distribution is multidimensional free infinitely divisible.
(2) The distribution is the limit distribution of triangular trays of families
of random variables. (3) The distribution is the distribution of $\{a_1^{(i)}:
i=1, 2, \cdots\}$ of a multidimensional free Levy process $\{\{a_t^{(i)}:i=1,
2, \cdots\}: t\ge 0\}$. (4) The distribution is the limit distribution of a
sequence of multidimensional compound free Poisson distributions.


title:
Quantum and classical control of single photon states via a mechanical
  resonator

abstract:
  Optomechanical systems typically use light to control the quantum state of a
mechanical resonator. In this paper, we propose a scheme for controlling the
quantum state of light using the mechanical degree of freedom as a controlled
beam splitter. Preparing the mechanical resonator in non-classical states
enables an optomechanical Stern-Gerlach interferometer. When the mechanical
resonator has a small coherent amplitude it acts as a quantum control,
entangling the optical and mechanical degrees of freedom. As the coherent
amplitude of the resonator increases, we recover single photon and two-photon
interference via a classically controlled beam splitter. The visibility of the
two-photon interference is particularly sensitive to coherent excitations in
the mechanical resonator and this could form the basis of an optically
transduced weak-force sensor.


title: Probabilistic Forecasting of the Masses and Radii of Other Worlds

abstract:
  Mass and radius are two of the most fundamental properties of an astronomical
object. Increasingly, new planet discoveries are being announced with a
measurement of one of these terms, but not both. This has led to a growing need
to forecast the missing quantity using the other, especially when predicting
the detectability of certain follow-up observations. We present am unbiased
forecasting model built upon a probabilistic mass-radius relation conditioned
on a sample of 316 well-constrained objects. Our publicly available code,
Forecaster, accounts for observational errors, hyper-parameter uncertainties
and the intrinsic dispersions observed in the calibration sample. By
conditioning our model upon a sample spanning dwarf planets to late-type stars,
Forecaster can predict the mass (or radius) from the radius (or mass) for
objects covering nine orders-of-magnitude in mass. Classification is naturally
performed by our model, which uses four classes we label as Terran worlds,
Neptunian worlds, Jovian worlds and stars. Our classification identifies dwarf
planets as merely low-mass Terrans (like the Earth), and brown dwarfs as merely
high-mass Jovians (like Jupiter). We detect a transition in the mass-radius
relation at $2.0_{-0.6}^{+0.7} M_\oplus$, which we associate with the divide
between solid, Terran worlds and Neptunian worlds. This independent analysis
adds further weight to the emerging consensus that rocky Super-Earths represent
a narrower region of parameter space than originally thought. Effectively,
then, the Earth is the Super-Earth we have been looking for.


title:
The enclosure method for inverse obstacle scattering over a finite time
  interval: IV. Extraction from a single point on the graph of the response
  operator

abstract:
  Now a final and maybe simplest formulation of the enclosure method applied to
inverse obstacle problems governed by partial differential equations in a {\it
spacial domain with an outer boundary} over a finite time interval is fixed.
The method employs only a single pair of a quite natural Neumann data
prescribed on the outer boundary and the corresponding Dirichlet data on the
same boundary of the solution of the governing equation over a finite time
interval, that is a single point on the graph of the so-called {\it response
operator}. It is shown that the methods enables us to extract the distance of a
given point outside the domain to an embedded unknown obstacle, that is the
maximum sphere centered at the point whose exterior encloses the unknown
obstacle. To make the explanation of the idea clear only an inverse obstacle
problem governed by the wave equation is considered.


title: Submodular Variational Inference for Network Reconstruction

abstract:
  In real-world and online social networks, individuals receive and transmit
information in real time. Cascading information transmissions (e.g. phone
calls, text messages, social media posts) may be understood as a realization of
a diffusion process operating on the network, and its branching path can be
represented by a directed tree. The process only traverses and thus reveals a
limited portion of the edges. The network reconstruction/inference problem is
to infer the unrevealed connections. Most existing approaches derive a
likelihood and attempt to find the network topology maximizing the likelihood,
a problem that is highly intractable. In this paper, we focus on the network
reconstruction problem for a broad class of real-world diffusion processes,
exemplified by a network diffusion scheme called respondent-driven sampling
(RDS). We prove that under realistic and general models of network diffusion,
the posterior distribution of an observed RDS realization is a Bayesian
log-submodular model.We then propose VINE (Variational Inference for Network
rEconstruction), a novel, accurate, and computationally efficient variational
inference algorithm, for the network reconstruction problem under this model.
Crucially, we do not assume any particular probabilistic model for the
underlying network. VINE recovers any connected graph with high accuracy as
shown by our experimental results on real-life networks.


title:
Inferring Morphology and Strength of Magnetic Fields From Proton
  Radiographs

abstract:
  Proton radiography is an important diagnostic method for laser plasma
experiments, and is particularly important in the analysis of magnetized
plasmas. The theory of radiographic image analysis has heretofore only
permitted somewhat limited analysis of the radiographs of such plasmas. We
furnish here a theory that remedies this deficiency. We show that to linear
order in magnetic field gradients, proton radiographs are projection images of
the MHD current along the proton trajectories. We demonstrate that in the
linear approximation, the full structure of the perpedicular magnetic field can
be reconstructed by solving a steady-state inhomogeneous 2-dimensional
diffusion equation sourced by the radiograph fluence contrast data. We explore
limitations of the inversion method due to Poisson noise, to discretization
errors, to radiograph edge effects, and to obstruction by laser target
structures. We also provide a separate analysis that is well-suited to the
inference of isotropic-homogeneous magnetic turbulence spectra. We discuss
extension of these results to the nonlinear contrast regime.


title:
Revealing the nature of magnetic phases in the semi-Heusler alloy
  Cu0.85Ni0.15MnSb

abstract:
  We report the magnetic, magnetocaloric, and magnetotransport properties of
the semi-Heusler alloy Cu0.85Ni0.15MnSb, which exhibits coexistence of
antiferromagnetic (AFM) and ferromagnetic (FM) phases. A broad magnetic phase
transition is evident from the temperature variations of magnetization, heat
capacity, and isothermal magnetic entropy change. This is due to the presence
of both AFM and FM phases at low temperatures. The variation of electrical
resistivity with temperature shows three distinct regions of magnetic phases.
The magnetoresistance (MR) results also show the presence of AFM and FM phases
at temperatures below 45 K, and a FM phase at temperature above 45K. Though
there is no signature of a spin-glass state at low temperatures, various
results point towards the presence of short-range magnetic correlations at low
temperatures.


title:
Evaluating the Performance Impact of Multiple Streams on the MIC-based
  Heterogeneous Platform

abstract:
  Using \textit{multiple streams} can improve the overall system performance by
mitigating the data transfer overhead on heterogeneous systems. Prior work
focuses a lot on GPUs but little is known about the performance impact on
(Intel Xeon) Phi. In this work, we apply multiple streams into six real-world
applications on Phi. We then systematically evaluate the performance benefits
of using multiple streams. The evaluation work is performed at two levels: the
microbenchmarking level and the real-world application level. Our experimental
results at the microbenchmark level show that data transfers and kernel
execution can be overlapped on Phi, while data transfers in both directions are
performed in a serial manner. At the real-world application level, we show that
both overlappable and non-overlappable applications can benefit from using
multiple streams (with an performance improvement of up to 24\%). We also
quantify how task granularity and resource granularity impact the overall
performance. Finally, we present a set of heuristics to reduce the search space
when determining a proper task granularity and resource granularity. To
conclude, our evaluation work provides lots of insights for runtime and
architecture designers when using multiple streams on Phi.


title:
Evidences of spin-temperature in Dynamic Nuclear Polarization: an exact
  computation of the EPR spectrum

abstract:
  In dynamic nuclear polarization (DNP) experiments, the compound is driven
out-of-equilibrium by microwave (MW) irradiation of the radical electron spins.
Their stationary state has been recently probed via electron double resonance
(ELDOR) techniques showing, at low temperature, a broad depolarization of the
electron paramagnetic resonance (EPR) spectrum under microwave irradiation. In
this theoretical manuscript, we develop a numerical method to compute exactly
the EPR spectrum in presence of dipolar interactions. Our results reproduce the
observed broad depolarisation and provide a microscopic justification for
spectral diffusion mechanism. We show the validity of the spin-temperature
approach for typical radical concentration used in dissolution DNP protocols.
In particular once the interactions are properly taken into account, the
spin-temperature is consistent with the non-monotonic behavior of the EPR
spectrum with a wide minimum around the irradiated frequency.


title:
Conditionally expectations and martingales in noncommutative
  $L_p$-spaces associated with center-valued traces

abstract:
  In this paper we prove the existence of conditional expectations in the
noncommutative $L_p(M,\Phi)$ spaces associated with center-valued traces.
Moreover, their description is also provided. As an application of the obtained
results, we establish the norm convergence of the martingales in noncommutative
$L_p(M,\Phi)$ spaces.


title: Convergence of Brownian motions on RCD(K,infty) spaces

abstract:
  Suppose that metric measure spaces X_n=(X_n, d_n, m_n) satisfy RCD(K,infty)
conditions with m_n(X_n)=1. Then the measured Gromov convergence (introduced by
Gigili-Mondino-Savare '13) of X_n is equivalent to the weak convergence of the
laws of Brownian motions on X_n with initial distributions m_n.


title:
A positive proportion of Thue equations fail the integral Hasse
  principle

abstract:
  For any nonzero $h\in\mathbb{Z}$, we prove that a positive proportion of
integral binary cubic forms $F$ do locally everywhere represent $h$ but do not
globally represent $h$; that is, a positive proportion of cubic Thue equations
$F(x,y)=h$ fail the integral Hasse principle. Here, we order all classes of
such integral binary cubic forms $F$ by their absolute discriminants. We prove
the same result for Thue equations $G(x,y)=h$ of any fixed degree $n \geq 3$,
provided that these integral binary $n$-ic forms $G$ are ordered by the maximum
of the absolute values of their coefficients.


title: Geodesic Motions in AdS Soliton Background Space-time

abstract:
  We study both massive and massless particle's geodesic motion in the
background of general dimensional AdS-Sol space-time. We find that the massive
particles oscillate along the radial direction, while massless particles
experience one-time bouncing as they approach the "horizon" line of the
soliton. Our results provide a direct way to understand the negative
energy/masses leading to the AdS-Sol geometry. As a potential application, we
extend the point particle to a 3-brane and fix the background as a 5+1
dimension AdS-Sol, thus obtain a very natural bouncing/cyclic cosmological
model.


title: Theory of the Integer and Fractional Quantum Hall Effects

abstract:
  The present theory has investigated the FQHE without any quasi-particle. The
electric field due to the Hall voltage is taken into consideration. We find the
ground state where the electron configuration is uniquely determined so as to
have the minimum classical Coulomb energy. Residual Coulomb interaction HI
yields quantum transitions which satisfy the momentum conservation along the
current direction. The number of Coulomb transitions from nearest electron
pairs is dependent sensitively upon the fractional number of the filling
factor. For example, the number u(2/3) of allowed transitions at nu=2/3
abruptly decreases when the filling factor nu deviates slightly from 2/3. The
limiting value of the number is equal to half of u(2/3). The discontinuous
behavior produces the valley structure in the energy spectrum. This mechanism
produces the Hall plateaus at the specific filling factors nu=1/(2j+1), 2j
/(2j+1), j/(2j+1), j/(2j-1) etc. and also at the non-standard filling factors
nu=7/11, 4/11, 4/13, 5/13, 5/17, 6/17 etc. We have studied the pair energies of
more distant electron pairs in Chapter 5. Thereby the small valley structure
yields at nu=5/2, 7/2 and so on. The shapes of polarization curves depend
mainly upon the numerator of the fractional filling factor in nu<1 because the
spin polarization belongs to electrons only. There are many spin-arrangements
with the same eigen-energy of HD. The Coulomb interaction HI yields quantum
transitions among these degenerate ground states. The partial Hamiltonian has
been diagonalized exactly. The eigen-states give the spin polarization versus
magnetic field strength. The theoretical curves of the spin polarization are in
good agreement with the experimental data as studied in Chapter 9. Thus the
present theory has well explained the various phenomena of the FQHE.


title:
The Composite Spectrum of BOSS Quasars Selected for Studies of the
  Lyman-alpha Forest

abstract:
  The Baryon Oscillation Spectroscopic Survey (BOSS) has collected more than
150,000 $2.1 \leq z \leq 3.5$ quasar spectra since 2009. Using this
unprecedented sample, we create a composite spectrum in the rest-frame of
102,150 quasar spectra from 800 \AA\ to 3300 \AA\ at a signal-to-noise ratio
close to 1000 per pixel ($\Delta v$ of 69 km~s$^{-1}$). Included in this
analysis is a correction to account for flux calibration residuals in the BOSS
spectrophotometry. We determine the spectral index as a function of redshift of
the full sample, warp the composite spectrum to match the median spectral
index, and compare the resulting spectrum to SDSS photometry used in target
selection. The quasar composite matches the color of the quasar population to
within 0.02 magnitudes in $g-r$, 0.03 magnitudes in $r-i$, and 0.01 magnitudes
in $i-z$ over the redshift range $2.2<z<2.6$. The composite spectrum deviates
from the imaging photometry by 0.05 magnitudes around $z = 2.7$, likely due to
differences in target selection as the quasar colors become similar to the
stellar locus at this redshift. Finally, we characterize the line features in
the high signal-to-noise composite and identify nine faint lines not found in
the previous composite spectrum from SDSS.


title: On the Shoshan-Zwick Algorithm for the All-Pairs Shortest Path Problem

abstract:
  The Shoshan-Zwick algorithm solves the all pairs shortest paths problem in
undirected graphs with integer edge costs in the range $\{1, 2, \dots, M\}$. It
runs in $\tilde{O}(M\cdot n^{\omega})$ time, where $n$ is the number of
vertices, $M$ is the largest integer edge cost, and $\omega < 2.3727$ is the
exponent of matrix multiplication. It is the fastest known algorithm for this
problem. This paper points out the erroneous behavior of the Shoshan-Zwick
algorithm and revises the algorithm to resolve the issues that cause this
behavior. Moreover, it discusses implementation aspects of the Shoshan-Zwick
algorithm using currently-existing sub-cubic matrix multiplication algorithms.


title: Equilibration Properties of Classical Integrable Field Theories

abstract:
  We study the equilibration properties of classical integrable field theories
at a finite energy density, with a time evolution that starts from initial
conditions far from equilibrium. These classical field theories may be regarded
as quantum field theories in the regime of high occupation numbers. This
observation permits to recover the classical quantities from the quantum ones
by taking a proper $\hbar \rightarrow 0$ limit. In particular, the time
averages of the classical theories can be expressed in terms of a suitable
version of the LeClair-Mussardo formula relative to the Generalized Gibbs
Ensemble. For the purposes of handling time averages, our approach provides a
solution of the problem of the {\em infinite gap solutions} of the Inverse
Scattering Method.


title: Spherically symmetric collapse of a perfect fluid in f(R) gravity

abstract:
  The present work investigates the gravitational collapse of a perfect fluid
in $f(R)$ gravity models. For a general $f(R)$ theory, it is shown analytically
that a collapse is quite possible. The singularity formed as a result of the
collapse is found to be a curvature singularity of shell focusing type. The
possibility of the formation of an apparent horizon hiding the central
singularity depends on the initial conditions.


title:
Fe-K Line Time variability and Ni abundance of Distant Reflector in
  Seyfert Galaxies

abstract:
  We have performed systematic studies of narrow Fe-K line (6.4 keV) flux
variability and Ni-K line intensity for Seyfert galaxies, using {\em Suzaku}
and {\em XMM-Newton} archival data. Significant Fe-K line variability of
several tens percents was detected for a pair of observations separated by
1000--2000 days (Cen A, IC 4329 A, NGC 3516, and NGC 4151) and 158 days (NGC
3516). These timescales are larger by a factor of 10--100 than the inner radius
of torus, consistent with the view that X-ray reflection by torus is a main
origin of a narrow Fe-K line. Ni-K line was detected with $>2\sigma$ level for
the Circinus galaxy, Cen A, MRK 3, NGC 4388, and NGC 4151. A mean and variance
of Ni-K$\alpha$ to Fe-K$\alpha$ line intensity ratio are 0.066 and 0.026,
respectively. Comparing this with the Monte-Carlo simulation of reflection, Ni
to Fe abundance ratio is 1.9$\pm$0.8 solar. We discuss the results and
possibility of Ni abundance enhancement.


title:
Classification of Alzheimer's Disease using fMRI Data and Deep Learning
  Convolutional Neural Networks

abstract:
  Over the past decade, machine learning techniques especially predictive
modeling and pattern recognition in biomedical sciences from drug delivery
system to medical imaging has become one of the important methods which are
assisting researchers to have deeper understanding of entire issue and to solve
complex medical problems. Deep learning is power learning machine learning
algorithm in classification while extracting high-level features. In this
paper, we used convolutional neural network to classify Alzheimer's brain from
normal healthy brain. The importance of classifying this kind of medical data
is to potentially develop a predict model or system in order to recognize the
type disease from normal subjects or to estimate the stage of the disease.
Classification of clinical data such as Alzheimer's disease has been always
challenging and most problematic part has been always selecting the most
discriminative features. Using Convolutional Neural Network (CNN) and the
famous architecture LeNet-5, we successfully classified functional MRI data of
Alzheimer's subjects from normal controls where the accuracy of test data on
trained data reached 96.85%. This experiment suggests us the shift and scale
invariant features extracted by CNN followed by deep learning classification is
most powerful method to distinguish clinical data from healthy data in fMRI.
This approach also enables us to expand our methodology to predict more
complicated systems.


title: Validating an Approach to Formalize Use Cases with Ontologies

abstract:
  Use case driven development methodologies put use cases at the center of the
software development process. However, in order to support automated
development and analysis, use cases need to be appropriately formalized. This
will also help guarantee consistency between requirements specifications and
the developed solutions. Formal methods tend to suffer from take up issues, as
they are usually hard to accept by industry. In this context, it is relevant
not only to produce languages and approaches to support formalization, but also
to perform their validation. In previous works we have developed an approach to
formalize use cases resorting to ontologies. In this paper we present the
validation of one such approach. Through a three stage study, we evaluate the
acceptance of the language and supporting tool. The first stage focusses on the
acceptance of the process and language, the second on the support the tool
provides to the process, and finally the third one on the tool's usability
aspects. Results show test subjects found the approach feasible and useful and
the tool easy to use.


title:
Industrial Experiences with a Formal DSL Semantics to Check the
  Correctness of DSL Artifacts

abstract:
  A domain specific language (DSL) abstracts from implementation details and is
aligned with the way domain experts reason about a software component. The
development of DSLs is usually centered around a grammar and transformations
that generate implementation code or analysis models. The semantics of the
language is often defined implicitly and in terms of a transformation to
implementation code. In the presence of multiple transformations from the DSL,
the correctness of the generated artifacts with respect to the semantics of the
DSL is a relevant issue. We show that a formal semantics is essential for
checking the correctness of the generated artifacts. We exploit the formal
semantics in an industrial project and use formal techniques based on
equivalence checking and model-based testing for validating the correctness of
the generated artifacts. We report about our experience with this approach in
an industrial development project.


title: Device-Centric Monitoring for Mobile Device Management

abstract:
  The ubiquity of computing devices has led to an increased need to ensure not
only that the applications deployed on them are correct with respect to their
specifications, but also that the devices are used in an appropriate manner,
especially in situations where the device is provided by a party other than the
actual user. Much work which has been done on runtime verification for mobile
devices and operating systems is mostly application-centric, resulting in
global, device-centric properties (e.g. the user may not send more than 100
messages per day across all applications) being difficult or impossible to
verify. In this paper we present a device-centric approach to runtime verify
the device behaviour against a device policy with the different applications
acting as independent components contributing to the overall behaviour of the
device. We also present an implementation for Android devices, and evaluate it
on a number of device-centric policies, reporting the empirical results
obtained.


title:
Development and Validation of Functional Model of a Cruise Control
  System

abstract:
  Modern automobiles can be considered as a collection of many subsystems
working with each other to realize safe transportation of the occupants.
Innovative technologies that make transportation easier are increasingly
incorporated into the automobile in the form of functionalities. These new
functionalities in turn increase the complexity of the system framework present
and traceability is lost or becomes very tricky in the process. This hugely
impacts the development phase of an automobile, in which, the safety and
reliability of the automobile design should be ensured. Hence, there is a need
to ensure operational safety of the vehicles while adding new functionalities
to the vehicle. To address this issue, functional models of such systems are
created and analysed. The main purpose of developing a functional model is to
improve the traceability and reusability of a system which reduces development
time and cost. Operational safety of the system is ensured by analysing the
system with respect to random and systematic failures and including safety
mechanism to prevent such failures. This paper discusses the development and
validation of a functional model of a conventional cruise control system in a
passenger vehicle based on the ISO 26262 Road Vehicles - Functional Safety
standard. A methodology for creating functional architectures and an
architecture of a cruise control system developed using the methodology are
presented.


title:
Towards an Automated Requirements-driven Development of Smart
  Cyber-Physical Systems

abstract:
  The Invariant Refinement Method for Self Adaptation (IRM-SA) is a design
method targeting development of smart Cyber-Physical Systems (sCPS). It allows
for a systematic translation of the system requirements into the system
architecture expressed as an ensemble-based component system (EBCS). However,
since the requirements are captured using natural language, there exists the
danger of their misinterpretation due to natural language requirements'
ambiguity, which could eventually lead to design errors. Thus, automation and
validation of the design process is desirable. In this paper, we (i) analyze
the translation process of natural language requirements into the IRM-SA model,
(ii) identify individual steps that can be automated and/or validated using
natural language processing techniques, and (iii) propose suitable methods.


title: Learning a Predictable and Generative Vector Representation for Objects

abstract:
  What is a good vector representation of an object? We believe that it should
be generative in 3D, in the sense that it can produce new 3D objects; as well
as be predictable from 2D, in the sense that it can be perceived from 2D
images. We propose a novel architecture, called the TL-embedding network, to
learn an embedding space with these properties. The network consists of two
components: (a) an autoencoder that ensures the representation is generative;
and (b) a convolutional network that ensures the representation is predictable.
This enables tackling a number of tasks including voxel prediction from 2D
images and 3D model retrieval. Extensive experimental analysis demonstrates the
usefulness and versatility of this embedding.


title:
Optimal order quadrature error bounds for infinite-dimensional higher
  order digital sequences

abstract:
  Quasi-Monte Carlo (QMC) quadrature rules using higher order digital nets and
sequences have been shown to achieve the almost optimal rate of convergence of
the worst-case error in Sobolev spaces of arbitrary fixed smoothness $\alpha\in
\mathbb{N}$, $\alpha\geq 2$. In a recent paper by the authors, it was proved
that randomly-digitally-shifted order $2\alpha$ digital nets in prime base $b$
achieve the best possible rate of convergence of the root mean square
worst-case error of order $N^{-\alpha}(\log N)^{(s-1)/2}$ for $N=b^m$, where
$N$ and $s$ denote the number of points and the dimension, respectively, which
implies the existence of an optimal order QMC rule. More recently, the authors
provided an explicit construction of such an optimal order QMC rule by using
Chen-Skriganov's digital nets in conjunction with Dick's digit interlacing
composition. These results were for fixed number of points. In this paper we
give a more general result on an explicit construction of optimal order QMC
rules for arbitrary fixed smoothness $\alpha\in \mathbb{N}$ including the
endpoint case $\alpha=1$. That is, we prove that the projection of any
infinite-dimensional order $2\alpha +1$ digital sequence in prime base $b$ onto
the first $s$ coordinates achieves the best possible rate of convergence of the
worst-case error of order $N^{-\alpha}(\log N)^{(s-1)/2}$ for $N=b^m$. The
explicit construction presented in this paper is not only easy to implement but
also extensible in both $N$ and $s$.


title:
Abundance of fast growth of the number of periodic points in
  2-dimensional area-preserving dynamics

abstract:
  We prove that there exists an open subset of the set of real-analytic
Hamiltonian diffeomorphisms of a closed surface in which diffeomorphisms
exhibiting fast growth of the number of periodic points are dense. We also
prove that there exists an open subset of the set of smooth area-preserving
diffeomorphisms of a closed surface in which typical diffeomorphisms exhibit
fast growth of the number of periodic points.


title: Fine Selmer groups of congruent Galois representations

abstract:
  In this paper, we study the fine Selmer groups of two congruent Galois
representations over an admissible $p$-adic Lie extension. We show that under
appropriate congruence conditions, if the dual fine Selmer group of one is
pseudo-null, so is the other. Our results also compare the $\pi$-primary
submodules of the two dual fine Selmer groups. We then apply our results to
compare the structure of Galois group of the maximal abelian unramified pro-$p$
extension of an admissible $p$-adic Lie extension and the structure of the dual
fine Selmer group over the said admissible $p$-adic Lie extension.


title:
Manipulating counter-rotating interactions in the quantum Rabi model via
  qubit frequency modulation

abstract:
  We propose a practical approach to manipulate the counter-rotating (CR)
interactions in the quantum Rabi model by introducing a sinusoidal modulation
to the transition frequency of the quantum two-level system in this model. By
choosing appropriate modulation frequency and amplitude, enhancement and
suppression of the CR interactions can be achieved in the Jaynes-Cummings
regime (including both weak- and strong-coupling cases) as well as the
ultrastrong-coupling regime. In particular, we calculate the output photon
emission of the cavity vacuum state under enhanced CR terms. Our results show
that continuous and steady photon emission from the cavity vacuum can be
observed in the Jaynes-Cummings regime as a consequence of this enhancement.
Our approach can be realized in superconducting quantum circuits.


title: Rearrangement Planning via Heuristic Search

abstract:
  We present a method to apply heuristic search algorithms to solve
rearrangement planning by pushing problems. In these problems, a robot must
push an object through clutter to achieve a goal. To do this, we exploit the
fact that contact with objects in the environment is critical to goal
achievement. We dynamically generate goal-directed primitives that create and
maintain contact between robot and object at each state expansion during the
search. These primitives focus exploration toward critical areas of
state-space, providing tractability to the high-dimensional planning problem.
We demonstrate that the use of these primitives, combined with an informative
yet simple to compute heuristic, improves success rate when compared to a
planner that uses only primitives formed from discretizing the robot's action
space. In addition, we show our planner outperforms RRT-based approaches by
producing shorter paths faster. We demonstrate our algorithm both in simulation
and on a 7-DOF arm pushing objects on a table.


title: Data-Driven CFD Modeling of Turbulent Flows Through Complex Structures

abstract:
  The growth of computational resources in the past decades has expanded the
application of Computational Fluid Dynamics (CFD) from the traditional fields
of aerodynamics and hydrodynamics to a number of new areas. Examples range from
the heat and fluid flows in nuclear reactor vessels and in data centers to the
turbulence flows through wind turbine farms and coastal vegetation plants.
However, in these new applications complex structures are often exist (e.g.,
rod bundles in reactor vessels and turbines in wind farms), which makes fully
resolved, first-principle based CFD modeling prohibitively expensive. This
obstacle seriously impairs the predictive capability of CFD models in these
applications. On the other hand, a limited amount of measurement data is often
available in the systems in the above-mentioned applications. In this work we
propose a data-driven, physics-based approach to perform full field inversion
on the effects of the complex structures on the flow. This is achieved by
assimilating observation data and numerical model prediction in an iterative
Ensemble Kalman method. Based on the inversion results, the velocity and
turbulence of the flow field can be obtained. A major novelty of the present
contribution is the non-parametric, full field inversion approach adopted,
which is in contrast to the inference of coefficient in the ad hoc models often
practiced in previous works. The merits of the proposed approach are
demonstrated on the flow past a porous disk by using both synthetic data and
real experimental measurements. The spatially varying drag forces of the porous
disk on the flow are inferred. The proposed approach has the potential to be
used in the monitoring of complex system in the above mentioned applications.


title: A Survey of Chemical Separation in Accreting Neutron Stars

abstract:
  The heavy element ashes of rp-process hydrogen and helium burning in
accreting neutron stars are compressed to high density where they freeze,
forming the outer crust of the star. We calculate the chemical separation on
freezing for a number of different nuclear mixtures resulting from a range of
burning conditions for the rp-process. We confirm the generic result that light
nuclei are preferentially retained in the liquid and heavy nuclei in the solid.
This is in agreement with the previous study of a 17-component mixture of
rp-process ashes by Horowitz et al. (2007), but extends that result to a much
larger range of compositions. We also find an alternate phase separation regime
for the lightest ash mixtures which does not demonstrate this generic
behaviour. With a few exceptions, we find that chemical separation reduces the
expected $Q_{\rm imp}$ in the outer crust compared to the initial rp-process
ash, where $Q_{\rm imp}$ measures the mean-square dispersion in atomic number
$Z$ of the nuclei in the mixture. We find that the fractional spread of $Z$
plays a role in setting the amount of chemical separation and is strongly
correlated to the divergence between the two/three-component approximations and
the full component model. The contrast in $Y_e$ between the initial rp-process
ashes and the equilibrium liquid composition is similar to that assumed in
earlier two-component models of compositionally driven convection, except for
very light compositions which produce nearly negligible convective driving. We
discuss the implications of these results for observations of accreting neutron
stars.


title:
Sensitivity of elements of the symmetry energy of nuclear matter to the
  properties of neutron-rich systems

abstract:
  The sensitivity of nuclear symmetry energy elements at the saturation density
to the binding energies of ultra neutron-rich nuclei (neutron to proton ratio
$\sim$ 2) and the maximum mass of neutron star is explored within a
relativistic mean field model. Values of the interaction parameters governing
the isovector strengths and the symmetry elements are determined in tighter
bounds. Assessments based on the sensitivity matrix reveal that the properties
of extreme neutron-rich systems play a predominant role in narrowing down the
uncertainties in the various symmetry energy parameters. The calculations are
extended over a wide range of nuclear matter density and the results are
discussed.


title: Striated Populations in Disordered Environments with Advection

abstract:
  Growth in static and controlled environments such as a Petri dish can be used
to study the spatial population dynamics of microorganisms. However, natural
populations such as marine microbes experience fluid advection and often grow
up in heterogeneous environments. We investigate a generalized
Fisher-Kolmogorov-Petrovsky-Piscounov (FKPP) equation describing single species
population subject to a constant flow field and quenched random spatially
inhomogeneous growth rates with a fertile overall growth condition. We
analytically and numerically demonstrate that the non-equilibrium steady-state
population density develops a flow-driven striation pattern. The striations are
highly asymmetric with a longitudinal correlation length that diverges linearly
with the flow speed and a transverse correlation length that approaches a
finite velocity-independent value. Linear response theory is developed to study
the statistics of the steady states. Theoretical predictions show excellent
agreement with the numerical steady states of the generalized FKPP equation
obtained from Lattice Boltzmann simulations. These findings suggest that,
although the growth disorder can be spatially uncorrelated, correlated
population structures with striations emerge naturally at sufficiently strong
advection.


title: A protrusion can "eclipse" looping of a long self-avoiding chain

abstract:
  We simulate long self-avoiding chains using a weighted-biased sampling
Monte-Carlo algorithm, and compute the probabilities for chain looping with and
without a protrusion. We find that a protrusion near one of the chain's termini
reduces the probability of looping, even for chains much longer than the
protrusion-chain-terminus distance. This effect increases with protrusion size,
and decreases with protrusion-terminus distance. We model the simulated results
theoretically by considering how the protrusion "eclipses" the chain terminus
closer to the protrusion from the more distant chain terminus. This eclipse
mechanism has implications for understanding the regulatory role of proteins
bound to DNA.


title: A Comparison of NOOP to Structural Domain-Theoretic Models of OOP

abstract:
  Mainstream object-oriented programming languages such as Java, C#, C++ and
Scala are all almost entirely nominally-typed. NOOP is a recently developed
domain-theoretic model of OOP that was designed to include full nominal
information found in nominally-typed OOP. This paper compares NOOP to the most
widely known domain-theoretic models of OOP, namely, the models developed by
Cardelli and Cook, which were structurally-typed models. Leveraging the
development of NOOP, the comparison presented in this paper provides a clear
and precise mathematical account for the relation between nominal and
structural OO type systems.