  This paper studies MapReduce-based heterogeneous coded distributed computing
(CDC) where, besides different computing capabilities at workers, input files
to be accessed by computing jobs have nonuniform popularity. We propose a file
placement strategy that can handle an arbitrary number of input files.
Furthermore, we design a nested coded shuffling strategy that can efficiently
manage the nonuniformity of file popularity to maximize the coded multicasting
opportunity. We then formulate the joint optimization of the proposed file
placement and nested shuffling design variables to optimize the proposed CDC
scheme. To reduce the high computational complexity in solving the resulting
mixed-integer linear programming (MILP) problem, we propose a simple
two-file-group-based file placement approach to obtain an approximate solution.
Numerical results show that the optimized CDC scheme outperforms other
alternatives. Also, the proposed two-file-group-based approach achieves nearly
the same performance as the conventional branch-and-cut method in solving the
MILP problem but with substantially lower computational complexity that is
scalable over the number of files and workers. For computing jobs with
aggregate target functions that commonly appear in machine learning
applications, we propose a heterogeneous compressed CDC (C-CDC) scheme to
further improve the shuffling efficiency. The C-CDC scheme uses a local data
aggregation technique to compress the data to be shuffled for the shuffling
load reduction. We again optimize the proposed C-CDC scheme and explore the
two-file-group-based low-complexity approach for an approximate solution.
Numerical results show the proposed C-CDC scheme provides a considerable
shuffling load reduction over the CDC scheme, and also, the
two-file-group-based file placement approach maintains good performance.


  Time-reversal symmetry of most conservative forces constrains the properties
of linear transport in most physical systems. Here, I study the efficiency of
energy transfer in oscillator networks where time-reversal symmetry is broken
locally by Lorentz-force-like couplings. Despite their linearity, such networks
can exhibit mono-directional transport and allow to isolate energy transfer in
subsystems. New mechanisms and general rules for mono-directional transport are
discussed. It is shown that the efficiency at maximum power can exceed $1/2$
and may even approach the upper bound of unity.


  In this paper, we propose a novel asymmetric $\epsilon$-insensitive pinball
loss function for quantile estimation. There exists some pinball loss functions
which attempt to incorporate the $\epsilon$-insensitive zone approach in it
but, they fail to extend the $\epsilon$-insensitive approach for quantile
estimation in true sense. The proposed asymmetric $\epsilon$-insensitive
pinball loss function can make an asymmetric $\epsilon$- insensitive zone of
fixed width around the data and divide it using $\tau$ value for the estimation
of the $\tau$th quantile. The use of the proposed asymmetric
$\epsilon$-insensitive pinball loss function in Support Vector Quantile
Regression (SVQR) model improves its prediction ability significantly. It also
brings the sparsity back in SVQR model. Further, the numerical results obtained
by several experiments carried on artificial and real world datasets
empirically show the efficacy of the proposed `$\epsilon$-Support Vector
Quantile Regression' ($\epsilon$-SVQR) model over other existing SVQR models.


  Infrared Imaging Surveyor (IRIS) is a satellite which will be launched at the
beginning of 2003. One of the main purposes of the IRIS mission is an all-sky
survey in the far-infrared region with a flux limit much deeper than that of
IRAS. Detection of a large number of galaxies ($\sim several \times 10^6$ in
the whole sky) is expected in this survey. We investigated the expected optical
and near-infrared (NIR) number counts of galaxies detected by the far-infrared
scanner (FIS) of IRIS (hereafter, IRIS galaxies) and possibility of optical and
NIR follow-up of them. The spectral energy distribution and the luminosity
function of the IRIS galaxies are modeled based on the properties of galaxies
observed by IRAS. The IRIS galaxies are divided into two populations according
to their infrared luminosities ($L_{IR}$); normal spirals ($L_{IR}<10^{10}\LO$)
and starbursts ($L_{IR}>10^{10}\LO$). The expected number counts of IRIS
galaxies for both of the populations are calculated in $B$ and $H$ bands. We
show that about 60 normal galaxies and about 80 starburst galaxies are detected
per square degree in both of the two bands, when galaxy evolution is not taken
into account. All of the normal population of IRIS galaxies are located at the
redshift $z\ltsim 0.1$. As for the starburst population, we also calculated
number of galaxies with a simple model of evolution. The total number of
starburst population predicted by the evolution model is larger by 20% than
that expected from the non-evolution model. In the evolution model, the numbers
of low-z ($z<1$), intermediate-z ($1<z<3$), and high-z ($z>3$) galaxies are
100, 20, and 0.2 per square degree, respectively.


  An extra large metric is a spherical cone metric with all cone angles greater
than 2 pi and every closed geodesic longer than 2pi. We show that every
two-dimensional extra large metric can be triangulated with vertices at cone
points only. The argument implies the same result for Euclidean and hyperbolic
cone metrics, and can be modified to show a similar result for
higher-dimensional extra-large metrics. The extra-large hypothesis is
necessary.


  Nambu-Goldstone modes associated with (topological) defects such as vortices
and domain walls in (super)fluids are known to possess quadratic/non-integer
dispersion relations in finite/infinite-size systems. Here, we report
interpolating formulas connecting the dispersion relations in finite- and
infinite-size systems for Kelvin modes along a quantum vortex and ripplons on a
domain wall in superfluids. Our method can provide not only the dispersion
relations but also the explicit forms of quasiparticle wavefunctions $(u,v)$.
We find a complete agreement between the analytical formulas and numerical
simulations. All these formulas are derived in a fully analytical way, and
hence not empirical ones. We also discuss common structures in the derivation
of these formulas and speculate on the general procedure.


  Reference arXiv:physics/0408021 claims that matter--free regions of spacetime
may support electromagnetic waves for which the phase velocity 3-vector is
oppositely directed to the power flow 3-vector. This was the definition of
negative refraction adopted in \cite{ML}. We here show that this cannot occur
in regions of spacetime for which the electromagnetic energy density is
positive.


  We examine whether it is possible for one-dimensional
translationally-invariant Hamiltonians to have ground states with a high degree
of entanglement. We present a family of translationally invariant Hamiltonians
{H_n} for the infinite chain. The spectral gap of H_n is Omega(1/poly(n)).
Moreover, for any state in the ground space of H_n and any m, there are regions
of size m with entanglement entropy Omega(min{m,n}). A similar construction
yields translationally-invariant Hamiltonians for finite chains that have
unique ground states exhibiting high entanglement. The area law proven by
Hastings gives a constant upper bound on the entanglement entropy for 1D ground
states that is independent of the size of the region but exponentially
dependent on 1/Delta, where Delta is the spectral gap. This paper provides a
lower bound, showing a family of Hamiltonians for which the entanglement
entropy scales polynomially with 1/Delta. Previously, the best known such bound
was logarithmic in 1/Delta.


  I present a new technique for the measurement of the growth of cosmic
structures via the power spectrum of weak lensing cosmic shear. It is based on
a template-fitting approach, where a redshift-dependent amplitude of lensing
modulates a fixed template power spectrum. Such an amplitude, which is promoted
to a free parameter and fit against tomographic cosmic shear data, reads
$D(z)\,\sigma_8\,\Omega_{{\rm m},0}=:\Omega\sigma_8(z)$, with $D(z)$ the growth
factor, $\sigma_8$ a proxy for the overall amplitude of the matter power
spectrum, and $\Omega_{{\rm m},0}$ the present-day matter abundance. I show
that this method is able to correctly reconstruct $\Omega\sigma_8$ at the per
cent level across redshift, thus allowing us to measure the growth of
structures unbiased by observing discrete tracers. Moreover, I only makes use
of measurements on linear scales. The method is highly complementary to
measurements of the bias and growth, $b\sigma_8(z)$ and $f\sigma_8(z)$, from
galaxy clustering analysis. I also demonstrate that the method is robust
against an incorrect choice of cosmological parameters in the template, thanks
to the inclusion of an Alcock-Paczy\'nski parameter.


  Master equations are commonly employed in cosmology to model the effect of
additional degrees of freedom, treated as an "environment", onto a given
"system". However, they rely on assumptions that are not necessarily satisfied
in cosmology, where the environment may be out of equilibrium and the
background is dynamical. In this work, we apply the master-equation program to
a model that is exactly solvable, and which consists of two linearly coupled
scalar fields evolving on a cosmological background. The light field plays the
role of the system and the heavy field is the environment. By comparing the
exact solution to the output of the master equation, we can critically assess
its performance. We find that the master equation exhibits a set of "spurious"
terms that explicitly depend on the initial conditions, and which arise as a
consequence of working on a dynamical background. Although they cancel out in
the perturbative limit of the theory (i.e. at leading orders in the interaction
strength), they spoil resummation. However, when those terms are removed, the
master equation performs impressively well to reproduce the power spectra and
the amount of the decoherence of the light field, even in the strongly
decohered regime. We conclude that master equations are able to perform
late-time resummation, even though the system is far from the Markovian limit,
provided spurious contributions are suppressed.


  We review in a unified way results for two types of stochastic chemical
reaction systems for which moments can be effectively computed: feedforward
networks and complex-balanced networks.


  We present several recent results from the BaBar collaboration in the areas
of initial state radiation physics and transition form factors. An updated
study of the processes e+e- -> K+K-pi+pi- and e+e- -> K+K-pi0pi0 provides an
improved understanding of the Y(2175) meson. A very precise study of the
process e+e- -> pi+pi- improves the precision on the calculated anomalous
magnetic moment of the muon and provides by far the best information on excited
rho states. Our previous measurements of the timelike transition form factors
(TFF) of the eta and eta' mesons at Q^2=112 GeV^2, combined with new
measurements of the their spacelike TFFs and those of the pi0 and eta_c mesons,
provide powerful tests of QCD and models of the distribution amplitudes of
quarks inside these mesons. The eta_c TFF shows the expected behavior over the
Q^2 range 1-50 GeV^2, and we are sensitive to next-to-leading-order QCD
corrections. The eta and eta' TFFs are consistent with expected behavior, but
those for the pi0 are not. Extracting the strange and nonstrange components of
the eta and eta' TFFs, we find the nonstrange component to be consistent with
theoretical expectations and inconsistent with the measured pi0 TFF.


  Recently, there have been significant interests in studying the so-called
"double-descent" of the generalization error of linear regression models under
the overparameterized and overfitting regime, with the hope that such analysis
may provide the first step towards understanding why overparameterized deep
neural networks (DNN) still generalize well. However, to date most of these
studies focused on the min $\ell_2$-norm solution that overfits the data. In
contrast, in this paper we study the overfitting solution that minimizes the
$\ell_1$-norm, which is known as Basis Pursuit (BP) in the compressed sensing
literature. Under a sparse true linear regression model with $p$ i.i.d.
Gaussian features, we show that for a large range of $p$ up to a limit that
grows exponentially with the number of samples $n$, with high probability the
model error of BP is upper bounded by a value that decreases with $p$. To the
best of our knowledge, this is the first analytical result in the literature
establishing the double-descent of overfitting BP for finite $n$ and $p$.
Further, our results reveal significant differences between the double-descent
of BP and min $\ell_2$-norm solutions. Specifically, the double-descent
upper-bound of BP is independent of the signal strength, and for high SNR and
sparse models the descent-floor of BP can be much lower and wider than that of
min $\ell_2$-norm solutions.


  A general theory is presented for the spatial correlations in the intensity
of the radiation emitted by a random medium in thermal equilibrium. We find
that a non-zero correlation persists over distances large compared to the
transverse coherence length of the thermal radiation. This long-range
correlation vanishes in the limit of an ideal black body. We analyze two types
of systems (a disordered waveguide and an optical cavity with chaotic
scattering) where it should be observable.


  We consider the collective eavesdropping of the BB84 and six-state protocols.
Since these protocols are symmetric in the eigenstates of conjugate bases, we
consider collective attacks having the same kind of symmetry. We then show how
these symmetric collective attacks are sufficiently strong in order to minimize
the Devetak-Winter rates. In fact, it is quite easy to construct simple
examples able to reach the unconditionally-secure key-rates of these protocols.


  Known entanglement purification protocols for mixed states use collective
measurements on several copies of the state in order to increase the
entanglement of some of them. We address the question of whether it is possible
to purify the entanglement of a state by processing each copy separately. While
this is possible for pure states, we show that this is impossible, in general,
for mixed states. The importance of this result both conceptually and for
experimental realization of purification is discussed. We also give explicit
invariants of an entangled state of two qubits under local actions and
classical communication.


  Magnetic phase transitions have been explored in a superlattice formed by
stacking monolayers of $\rm LaTiO_{3}$ and $\rm LaVO_{3}$ alternately, using
ab-initio density functional theory (DFT) and Monte-Carlo (MC) simulations. DFT
derived intra-layer and inter-layer exchange interaction parameters were used
for the MC simulations on a Ising spin model Hamiltonian. Two sharp peaks
observed in specific heat without the interlayer exchange coupling indicate two
independent magnetic ordering in $\rm LaTiO_{3}$ and $\rm LaVO_{3}$ layers at
different temperatures. Inclusion of interlayer coupling leads to one sharp
peak at higher temperature with a broad hump like feature at lower temperature
in specific heat indicating a single magnetic phase transition to $C$-type
antiferromagnetic phase in the superlattice.


  We show that for a typical fundamental discriminant $D,$ the partial sums of
the real character $\chi_D$ change sign $\gg (\log\log D)/\log\log\log \log D$
times on a very short initial interval (which goes beyond the range in
Vinogradov's conjecture).
  We also prove that the number of real zeros (localized away from $1$) of
Fekete polynomials associated to a typical fundamental discriminant is $\gg
\frac{\log\log D}{\log\log\log\log D}.$ This comes close to establishing a
conjecture of Baker and Montgomery which predicts $\asymp \log \log D$ real
zeros.
  These results rely crucially on quantitative estimates for the joint
distribution of $-\frac{L'}{L}(s, \chi_D)$ at several points $s$ in the
vicinity of the central point $s=1/2$, as well as concentration results for
$\log L(s,\chi_D)$ in the same range, which we establish.
  In the second part of the paper, we obtain, for large families of
discriminants, non-trivial upper bounds on the number of real zeros of Fekete
polynomials, breaking the square root bound. Finally, we construct families of
discriminants with associated Fekete polynomials having no zeros away from $1.$


  Given a large collection of urban datasets, how can we find their hidden
correlations? For example, New York City (NYC) provides open access to taxi
data from year 2012 to 2015 with about half million taxi trips generated per
day. In the meantime, we have a rich set of urban data in NYC including
points-of-interest (POIs), geo-tagged tweets, weather, vehicle collisions, etc.
Is it possible that these ubiquitous datasets can be used to explain the city
traffic? Understanding the hidden correlation between external data and traffic
data would allow us to answer many important questions in urban computing such
as: If we observe a high traffic volume at Madison Square Garden (MSG) in NYC,
is it because of the regular peak hour or a big event being held at MSG? If a
disaster weather such as a hurricane or a snow storm hits the city, how would
the traffic be affected?
  While existing studies may utilize external datasets for prediction task,
they do not explicitly seek for direct explanations from the external datasets.
In this paper, we present our results in attempts to understand taxi traffic
dynamics in NYC from multiple external data sources. We use four real-world
ubiquitous urban datasets, including POI, weather, geo-tagged tweet, and
collision records. To address the heterogeneity of ubiquitous urban data, we
present carefully-designed feature representations for various datasets.
Extensive experiments on real data demonstrate the explanatory power on taxi
traffic by using external datasets. More specifically, our analysis suggests
that POIs can well describe the regular traffic patterns. At the same time,
geo-tagged tweets can explain irregular traffic caused by big events and
weather can explain the abnormal traffic drop.


  The Clifford algebra over the three-dimensional real linear space includes
its linear structure and its exterior algebra, the subspaces spanned by
multivectors of the same degree determine a gradation of the Clifford algebra.
Through these geometric notions, natural one-to-one and two-to-one
homomorphisms from $\mbox{SO}(3)$ into $\mbox{SU}(2)$ are built conventionally,
and the set of qubits, is identified with a subgroup of $\mbox{SU}(2)$. These
constructions are suitable to be extended to corresponding tensor powers. The
notions of qubits, quregisters and qugates are translated into the language of
symmetry groups. The corresponding elements to entangled states in the tensor
product of Hilber spaces. realise a notion of entanglement in the tensor
product of symmetry groups.


  Knowledge of lattice anharmonicity is essential to elucidate distinctive
thermal properties in crystalline solids. Yet, accurate \textit{ab initio}
investigations of lattice anharmonicity encounter difficulties owing to the
cumbersome computations. Here we introduce the phonon quasiparticle approach
and review its application to various materials. This method efficiently and
reliably addresses lattice anharmonicity by combining \textit{ab initio}
molecular dynamics and lattice dynamics calculations. Thus, in principle, it
accounts for full anharmonic effects and overcomes finite-size effects typical
of \textit{ab initio} molecular dynamics. The validity and effectiveness of the
current approach are demonstrated in the computation of thermodynamic and heat
transport properties of weakly and strongly anharmonic systems.


  If we consider Big History as simply 'our' example of the process of cosmic
evolution playing out, then we can seek to broaden our view of our possible
fate as a species by asking questions about what paths or trajectories other
species' own versions of Big History might take or have taken. This paper
explores the broad outlines of possible scenarios for the evolution of
long-lived intelligent engineering species---scenarios which might have been
part of another species' own Big History story, or which may yet lie ahead in
our own distant future. A sufficiently long-lived engineering-oriented species
may decide to undertake a program of macro-engineering projects that might
eventually lead to a re-engineered galaxy so altered that its artificiality may
be detectable from Earth. We consider activities that lead ultimately to a
galactic structure consisting of a central inner core surrounded by a more
distant ring of stars separated by a relatively sparser 'gap', where star
systems and stellar materials may have been removed, 'lifted' or turned into
Dyson Spheres. When one looks to the sky, one finds that such galaxies do
indeed exist---including the beautiful ringed galaxy known as 'Hoag's Object'
(PGC 54559) in the constellation Serpens. This leads us to pose the question:
Is Hoag's Object an example of galaxy-scale macro-engineering? And this
suggests a program of possible observational activities and theoretical
explorations, several of which are presented here, that could be carried out in
order to begin to investigate this beguiling question.


  On [3, p. 199] one says "We mention parenthetically that the proof of [99,
Lemma 41.3] is incorrect, and we do not know whether it, [99, Theorem 41.5] and
[99, Theorem 41.6] are true". The previously cited reference [99] is our
reference [2]. The aim of this short note is to provide a result that improves
upon [2, Lemma 41. 3].


  For a germ $(X,0) \subset (\mathbb{C}^n,0)$ of reduced, equidimensional
complex analytic singularity its Nash modification can be constructed as an
analytic subvariety $ Z \subset \mathbb{C}^n \times G(k,n)$. We give a
characterization of the subvarieties of $\mathbb{C}^n \times G(k,n)$ that are
the Nash modification of its image under the projection to $\mathbb{C}^n$. This
result generalizes the characterization of conormal varieties as Legendrian
subvarieties of $\mathbb{C}^n \times \check{\mathbb{P}}^{n-1}$ with its
canonical contact structure. As a by-product we define the $d$-conormal space
of $(X,0)$ for any $d \in \{k, \ldots, n-1\}$ which is a generalization of both
the Nash modification and the conormal variety of $(X,0)$.


  Language agents have shown some ability to interact with an external
environment, e.g., a virtual world such as ScienceWorld, to perform complex
tasks, e.g., growing a plant, without the startup costs of reinforcement
learning. However, despite their zero-shot capabilities, these agents to date
do not continually improve over time beyond performance refinement on a
specific task. Here we present CLIN, the first language-based agent to achieve
this, so that it continually improves over multiple trials, including when both
the environment and task are varied, and without requiring parameter updates.
Our approach is to use a persistent, dynamic, textual memory centered on causal
abstractions (rather than general "helpful hints") that is regularly updated
after each trial so that the agent gradually learns useful knowledge for new
trials. In the ScienceWorld benchmark, CLIN is able to continually improve on
repeated trials on the same task and environment, outperforming
state-of-the-art reflective language agents like Reflexion by 23 absolute
points. CLIN can also transfer its learning to new environments (or new tasks),
improving its zero-shot performance by 4 points (13 for new tasks) and can
further improve performance there through continual memory updates, enhancing
performance by an additional 17 points (7 for new tasks). This suggests a new
architecture for agents built on frozen models that can still continually and
rapidly improve over time.


  The entertainment industry relies on 3D visual content to create immersive
experiences, but traditional methods for creating textured 3D models can be
time-consuming and subjective. Generative networks such as StyleGAN have
advanced image synthesis, but generating 3D objects with high-fidelity textures
is still not well explored, and existing methods have limitations. We propose
the Semantic-guided Conditional Texture Generator (CTGAN), producing
high-quality textures for 3D shapes that are consistent with the viewing angle
while respecting shape semantics. CTGAN utilizes the disentangled nature of
StyleGAN to finely manipulate the input latent codes, enabling explicit control
over both the style and structure of the generated textures. A coarse-to-fine
encoder architecture is introduced to enhance control over the structure of the
resulting textures via input segmentation. Experimental results show that CTGAN
outperforms existing methods on multiple quality metrics and achieves
state-of-the-art performance on texture generation in both conditional and
unconditional settings.


  In this work, we prove a shape theorem for Poisson cylinders and give a power
law bound on surface fluctuations. We prove that for any $a \in (1/2, 1)$,
conditioned on the origin being in the set of cylinders, every point in this
set, whose Euclidean norm is less than $R$, lies at an internal distance less
than $R+O(R^a)$ from the origin.


  We present a novel linear solver that works well for large systems obtained
from discretizing PDEs. It is robust and, for the examples we studied, the
computational effort scales linearly with the number of equations. The
algorithm is based on a wavelength decomposition that combines conjugate
gradient, multi-scaling and iterative splitting methods into a single approach.
On the surface, the algorithm is a simple preconditioned conjugate gradient
with all the sophistication of the algorithm in the choice of the
preconditioning matrix. The preconditioner is a very good approximate inverse
of the linear operator. It is constructed from the inverse of the coarse
grained linear operator and from smoothing operators that are based on an
operator splitting on the fine grid. The coarse graining captures the long
wavelength behavior of the inverse operator while the smoothing operator
captures the short wavelength behavior. The conjugate gradient iteration
accounts for the coupling between long and short wavelengths. The coarse
grained operator corresponds to a lowerresolution approximation to the PDEs.
While the coarse grained inverse is not known explicitly, the algorithm only
requires that the preconditioner can be a applied to a vector. The coarse
inverse applied to a vector can be obtained as the solution of another
preconditioned conjugate gradient solver that applies the same algorithm to the
smaller problem. Thus, the method is naturally recursive. The recursion ends
when the matrix is sufficiently small for a solution to be obtained efficiently
with a standard solver. We have tested our solver on the porous flow equation.
On a workstation we have solved problems on grids ranging in dimension from
$10^3$ to $10^6$, and found that the linear scaling holds.


  We present a first numerical implementation of the Loop-Tree Duality (LTD)
method for the direct numerical computation of multi-leg one-loop Feynman
integrals. We discuss in detail the singular structure of the dual integrands
and define a suitable contour deformation in the loop three-momentum space to
carry out the numerical integration. Then, we apply the LTD method to the
computation of ultraviolet and infrared finite integrals, and present explicit
results for scalar integrals with up to five external legs (pentagons) and
tensor integrals with up to six legs (hexagons). The LTD method features an
excellent performance independently of the number of external legs.


  In this paper, we study the optimal degrees of freedom (DoF) region for the
two-pair MIMO two-way relay channel (TWRC) with asymmetric antenna setting,
where two pairs of users exchange information with the help of a common relay.
Each user $i$ is equipped with $M_i$ antennas, for $i=1,2,3,4$, and the relay
is equipped with $N$ antennas. First, we derive an outer bound of the DoF
region by using the cut-set theorem and the genie-message approach. Then, we
propose a new transmission scheme to achieve the outer bound of the DoF region.
Due to the asymmetric data exchange, where the two users in each pair can
communicate a different number of data streams, we not only need to form the
network-coded symbols but also need to process the additional asymmetric data
streams at the relay. This is realized through the joint design of relay
compression matrix and source precoding matrices. After obtaining the optimal
DoF region, we study the optimal sum DoF by solving a linear programming
problem. From the optimal DoF region of this channel, we show that in the
asymmetric antenna setting, some antennas at certain source nodes are redundant
and cannot contribute to enlarge the DoF region. We also show that there is no
loss of optimality in terms of the sum DoF by enforcing symmetric data
exchange, where the two users in each pair are restricted to communicate the
same number of data streams.


  Recent progress in language model pre-training has achieved a great success
via leveraging large-scale unstructured textual data. However, it is still a
challenge to apply pre-training on structured tabular data due to the absence
of large-scale high-quality tabular data. In this paper, we propose TAPEX to
show that table pre-training can be achieved by learning a neural SQL executor
over a synthetic corpus, which is obtained by automatically synthesizing
executable SQL queries and their execution outputs. TAPEX addresses the data
scarcity challenge via guiding the language model to mimic a SQL executor on
the diverse, large-scale and high-quality synthetic corpus. We evaluate TAPEX
on four benchmark datasets. Experimental results demonstrate that TAPEX
outperforms previous table pre-training approaches by a large margin and
achieves new state-of-the-art results on all of them. This includes the
improvements on the weakly-supervised WikiSQL denotation accuracy to 89.5%
(+2.3%), the WikiTableQuestions denotation accuracy to 57.5% (+4.8%), the SQA
denotation accuracy to 74.5% (+3.5%), and the TabFact accuracy to 84.2%
(+3.2%). To our knowledge, this is the first work to exploit table pre-training
via synthetic executable programs and to achieve new state-of-the-art results
on various downstream tasks. Our code can be found at
https://github.com/microsoft/Table-Pretraining.


  We present the Quantum Virtual Machine (QVM), an end-to-end generic system
for scalable execution of large quantum circuits with high fidelity on noisy
and small quantum processors (QPUs) by leveraging gate virtualization. QVM
exposes a virtual circuit intermediate representation (IR) that extends the
notion of quantum circuits to incorporate gate virtualization. Based on the
virtual circuit as our IR, we propose the QVM compiler - an extensible compiler
infrastructure to transpile a virtual circuit through a series of modular
optimization passes to produce a set of optimized circuit fragments. Lastly,
these transpiled circuit fragments are executed on QPUs using our QVM runtime -
a scalable and distributed infrastructure to virtualize and execute circuit
fragments on a set of distributed QPUs. We evaluate QVM on IBM's 7- and
27-qubit QPUs. Our evaluation shows that using our system, we can scale the
circuit sizes executable on QPUs up to double the size of the QPU while
improving fidelity by 4.7$\times$ on average compared to larger QPUs and that
we can effectively reduce circuit depths to only 40\% of the original circuit
depths.


  We study a Cooper-pair transistor realized by two Josephson weak links that
enclose a superconducting island in an InSb-Al hybrid nanowire. When the
nanowire is subject to a magnetic field, isolated subgap levels arise in the
superconducting island and, due to the Coulomb blockade,mediate a supercurrent
by coherent co-tunneling of Cooper pairs. We show that the supercurrent
resulting from such co-tunneling events exhibits, for low to moderate magnetic
fields, a phase offset that discriminates even and odd charge ground states on
the superconducting island. Notably,this phase offset persists when a subgap
state approaches zero energy and, based on theoretical considerations, permits
parity measurements of subgap states by supercurrent interferometry. Such
supercurrent parity measurements could, in a new series of experiments, provide
an alternative approach for manipulating and protecting quantum information
stored in the isolated subgap levels of superconducting islands.


  We call Krawtchouk-Griffiths systems, KG-systems, systems of multivariate
polynomials orthogonal with respect to corresponding multinomial distributions.
The original Krawtchouk polynomials are orthogonal with respect to a binomial
distribution. Here we present a Fock space construction with raising and
lowering operators. The operators of "multiplication by X" are found in terms
of boson operators and corresponding recurrence relations presented. The
Riccati partial differential equations for the differentiation operators,
Berezin transform and associated partial differential equations are found.
These features provide the specifications for a Bernoulli system as a
quantization formulation of multivariate Krawtchouk polynomials.


  We study a model of a polling system, that is, a collection of $d$ queues
with a single server that switches from queue to queue. The service time
distribution and arrival rates change randomly every time a queue is emptied.
This model is mapped to a mathematically equivalent model of a random walk with
random choice of transition probabilities, a model which is of independent
interest. All our results are obtained using methods from the constructive
theory of Markov chains. We determine conditions for the existence of
polynomial moments of hitting times for the random walk. An unusual phenomenon
of thickness of the region of null recurrence for both the random walk and the
queueing model is also proved.


  The differential form of the Maxwell's equations was first derived based on
an assumption that the media are stationary, which is the foundation for
describing the electro-magnetic coupling behavior of a system. For a general
case in which the medium has a time-dependent volume, shape and boundary and
may move at an arbitrary velocity field v(r,t) and along a general trajectory,
we derived the Maxwell's equations for a mechano-driven slow-moving media
system directly starting from the integral forms of four physics laws, which
should be accurate enough for describing the coupling among
mechano-electro-magnetic interactions of a general system in practice although
it may not be Lorentz covarance. Our key point is directly from the four
physics laws by describing all of the fields, the space and the time in the
frame where the observation is done. The equations should be applicable to not
only moving charged solid and soft media that has acceleration, but also
charged fluid/liquid media, e.g., fluid electrodynamics. This is a step toward
the electrodynamics in non-inertia frame of references. General strategies for
solving the Maxwell's equations for mechano-driven slowing moving medium are
presented using the perturbation theory both in time and frequency spaces.
Finally, approaches for the electrodynamics of moving media are compared, and
related discussions are given about a few interesting questions.


  The North Carolina Agriculture and Technical State University (NC A&T) in
collaboration with Georgia Tech Research Institute (GTRI) has developed
methodologies for creating simulation-based technology tools that are capable
of inferring the perceptions and behavioral states of autonomous systems. These
methodologies have the potential to provide the Test and Evaluation (T&E)
community at the Department of Defense (DoD) with a greater insight into the
internal processes of these systems. The methodologies use only external
observations and do not require complete knowledge of the internal processing
of and/or any modifications to the system under test. This paper presents an
example of one such simulation-based technology tool, named as the Data-Driven
Intelligent Prediction Tool (DIPT). DIPT was developed for testing a
multi-platform Unmanned Aerial Vehicle (UAV) system capable of conducting
collaborative search missions. DIPT's Graphical User Interface (GUI) enables
the testers to view the aircraft's current operating state, predicts its
current target-detection status, and provides reasoning for exhibiting a
particular behavior along with an explanation of assigning a particular task to
it.


  We prove that the atom spectrum, which is a topological space associated to
an arbitrary abelian category introduced by Kanda, of the category of finitely
presented graded modules over a graded ring $R$ is given as a union of the
homogeneous spectrum of $R$ with some additional points, which we call
non-standard points. This description of the atom spectrum helps in
understanding the sheafification process in toric geometry: if $S$ is the Cox
ring of a normal toric variety $X$ without torus factors, then a finitely
presented graded $S$-module sheafifies to zero if and only if its atom support
consists only of points in the atom spectrum of $S$ which either lie in the
vanishing locus of the irrelevant ideal of $X$ or are non-standard.


  Crystals are the materials which can be described by uniform periodic
lattices. Traditionally, only the 1-, 2-, 3-, 4- and 6-fold rotation symmetries
are allowed in crystals because other n-fold rotation symmetries are forbidden
by the fully periodic translation symmetry. Materials containing rotation
symmetries forbidden in crystals can be optionally described as quasicrystals
with aperiodicity. The theoretical predictions and experimental discoveries of
quasicrystals have enriched the knowledge of crystallography and topology, and
expanded the capability of growing novel materials. Mathematically, one can
fill the whole space with quasi-uniform lattices through divisional
translations and arbitrary n-fold central rotations, including the 5-fold
symmetry. However, it is unknown if such pseudo-crystals with 5-fold symmetry
exist in reality. Here we propose a generalized crystal-prediction-method which
can be used to search for potential pseudo-crystals possessing both arbitrary
n-fold rotation symmetry and divisional translation symmetry. Successful
examples with 5-fold central rotation symmetry based on the group 14 elements
are discussed. We expect timely experimental explorations on such peculiar
structures, especially on the very promising clathrate phases of the group 14
elements with only slightly larger binding energies compared with the diamond
phases.


  We study the limits to the localizability of events and reference frames in
the $\kappa$-Minkowski quantum spacetime. Our main tool will be a
representation of the $\kappa$-Minkowski commutation relations between
coordinates, and the operator and measurement theory borrowed from ordinary
quantum mechanics. Spacetime coordinates are described by operators on a
Hilbert space, and a complete set of commuting observables cannot contain the
radial coordinate and time at the same time. The transformation between the
complete sets turns out to be the Mellin transform, which allows us to discuss
the localizability properties of states both in space and time. We then discuss
the transformation rules between inertial observers, which are described by the
quantum $\kappa$-Poincar\'e group. These too are subject to limitations in the
localizability of states, which impose further restrictions on the ability of
an observer to localize events defined in a different observer's reference
frame.


  We consider an integrable scalar partial differential equation (PDE) that is
second order in time. By rewriting it as a system and applying the
Wahlquist-Estabrook prolongation algebra method, we obtain the zero curvature
representation of the equation, which leads to a Lax representation in terms of
an energy-dependent Schr\"{o}dinger spectral problem of the type studied by
Antonowicz and Fordy. The solutions of this PDE system, and of its associated
hierarchy of commuting flows, display weak Painlev\'e behaviour, i.e. they have
algebraic branching. By considering the travelling wave solutions of the next
flow in the hierarchy, we find an integrable perturbation of the case (ii)
Henon-Heiles system which has the weak Painlev\'{e} property. We perform
separation of variables for this generalized Henon-Heiles system, and describe
the corresponding solutions of the PDE.


  Let $G$ be a simple, simply connected algebraic group over an algebraically
closed field of positive characteristic $p$. In recent work, the authors have
studied a graded analogue of the category of rational $G$-modules. These
gradings are not natural but are "forced" on related algebras though
filtrations, often obtained from appropriate quantum structures. This paper
presents new results on Koszul modules for the graded algebras obtained through
this forced grading process. Most of these results require that the Lusztig
character formula holds for all restricted $p$-regular weights, but the paper
begins to investigate how these and previous results might be established when
the Lusztig character formula is only assumed to hold on a proper poset ideal
in the Jantzen region. This opens up the possibility of inductive arguments.


  In this work, a recently developed fracture modeling method called localizing
gradient damage method (LGDM) is implemented in MATLAB. MATLAB is well-known in
the computational research community for its simple and easy-to-learn coding
interface. As a result, MATLAB is generally preferred for the initial
development (prototyping) of computational models by researchers. However,
MATLAB-developed codes are seldom used for large-scale simulations (after
initial development is complete) due to their computational inefficiency.
Hence, a computationally efficient implementation of LGDM using MATLAB
vectorization is presented in this work. The choice of LGDM (as the fracture
modeling method) is based on its thermodynamically consistent formulation built
upon the micromorphic framework. Moreover, the non-linear coupled field
formulation of LGDM makes it suitable for testing the computational efficiency
of vectorized MATLAB implementation in a non-linear finite element setting. It
is shown in this work that the vectorized MATLAB implementation can save
significant computational resources and time as compared to non-vectorized
implementations (that are parallelized with MATLAB parfor). The vectorized
MATLAB implementation is tested by solving numerical problems in 1D, 2D and 3D
on a consumer-grade PC, demonstrating the capability of vectorized
implementation to run simulations efficiently on systems with limited
resources. The sample source codes are provided as supplementary materials that
would be helpful to researchers working on similar coupled field models.


  We present ALMA observations of the CO(2-1) and CO(3-2) molecular gas
transitions and associated (sub)-mm continua of the nearby Seyfert 1.5 galaxy
NGC3227 with angular resolutions 0.085-0.21" (7-15pc). On large scales the cold
molecular gas shows circular motions as well as streaming motions on scales of
a few hundred parsecs associated with a large scale bar. We fitted the nuclear
ALMA 1.3mm emission with an unresolved component and an extended component. The
850$\mu$m emission shows at least two extended components, one along the major
axis of the nuclear disk and the other along the axis of the ionization cone.
The molecular gas in the central region (1" ~73pc) shows several CO clumps with
complex kinematics which appears to be dominated by non-circular motions. While
we cannot demonstrate conclusively the presence of a warped nuclear disk, we
also detected non-circular motions along the kinematic minor axis. They reach
line-of-sight velocities of v-vsys =150-200km/s. Assuming that the radial
motions are in the plane of the galaxy, then we interpret them as a nuclear
molecular outflow due to molecular gas in the host galaxy being entrained by
the AGN wind. We derive molecular outflow rates of $5\,M_\odot\,{\rm yr}^{-1}$
and $0.6\,M_\odot\,{\rm yr}^{-1}$ at projected distances of up to 30pc to the
northeast and southwest of the AGN, respectively. At the AGN location we
estimate a mass in molecular gas of $5\times 10^{5}\,M_\odot$ and an average
column density $N({\rm H}_2) = 2-3\times 10^{23}\,{\rm cm}^{-2}$ in the inner
15pc. The nuclear molecular gas and sub-mm continuum emission of NGC3227 do not
resemble the classical compact torus. Rather, these emissions extend for
several tens of parsecs and appear connected with the circumnuclear ring in the
host galaxy disk, as found in other local AGN. (Abridged)


  We study the low-temperature transport properties of out-of-equilibrium XXZ
spin-$1/2$ chains. We consider the protocol where two semi-infinite chains are
prepared in two thermal states at small but different temperatures and suddenly
joined together. We focus on the qualitative and quantitative features of the
profiles of local observables, which at large times $t$ and distances $x$ from
the junction become functions of the ratio $\zeta=x/t$. By means of the
generalized hydrodynamic equations, we analyse the rich phenomenology arising
by considering different regimes of the phase diagram. In the gapped phases,
variations of the profiles are found to be exponentially small in the
temperatures but described by non-trivial functions of $\zeta$. We provide
analytical formulae for the latter, which give accurate results also for small
but finite temperatures. In the gapless regime, we show how the three-step
conformal predictions for the profiles of energy density and energy current are
naturally recovered from the hydrodynamic equations. Moreover, we also recover
the recent non-linear Luttinger liquid predictions for low-temperature
transport: universal peaks of width $\Delta\zeta\propto T$ emerge at the edges
of the light cone in the profiles of generic observables. Such peaks are
described by the same function of $\zeta$ for all local observables.


  There is considerable evidence that powerful radio quasars and radio galaxies
are orientation-dependent manifestations of the same parent population: massive
spheroids containing correspondingly massive black holes. Following the
recognition of this unification, research is directed to the task of
elucidating the structure and composition of the active nuclei and their hosts
to understand the formation and evolution of what we expect to become the most
massive of galaxies. In contrast to the quasars, where the nucleus can outshine
the galaxy at optical/near infrared wavelengths by a large factor, the radio
galaxies contain a 'built-in coronograph' that obscures our direct view to the
nucleus. These objects present our best opportunity to study the host galaxy in
detail. Of particular interest are those sources with redshifts greater than
about 2 that represent an epoch when nuclear activity was much more common that
it is now and when we believe these objects were in the process of assembly. In
combination with high resolution imaging from space (HST), optical
spectropolarimetry with Keck II allows us to clearly separate the scattered
nuclear radiation from the stellar and gaseous emission from the host galaxy.
The rest-frame ultraviolet emission line spectra suggest that rapid chemical
evolution is occurring at this epoch. Near infrared spectroscopy with the VLT
is giving us access to both the lines and continuum in the rest-frame optical
spectrum, allowing investigations of the evolved stellar population and
extending the composition analysis with measurements of the familiar
forbidden-line spectrum.


  Effective fuzzing of programs that process structured binary inputs, such as
multimedia files, is a challenging task, since those programs expect a very
specific input format. Existing fuzzers, however, are mostly format-agnostic,
which makes them versatile, but also ineffective when a specific format is
required. We present FormatFuzzer, a generator for format-specific fuzzers.
FormatFuzzer takes as input a binary template (a format specification used by
the 010 Editor) and compiles it into C++ code that acts as parser, mutator, and
highly efficient generator of inputs conforming to the rules of the language.
The resulting format-specific fuzzer can be used as a standalone producer or
mutator in black-box settings, where no guidance from the program is available.
In addition, by providing mutable decision seeds, it can be easily integrated
with arbitrary format-agnostic fuzzers such as AFL to make them format-aware.
In our evaluation on complex formats such as MP4 or ZIP, FormatFuzzer showed to
be a highly effective producer of valid inputs that also detected previously
unknown memory errors in ffmpeg and timidity.


  The analogs of Chevalley generators are offered for simple (and close to
them) Z-graded complex Lie algebras and Lie superalgebras of polynomial growth
without Cartan matrix. We show how to derive the defining relations between
these generators and explicitly write them for a "most natural"
("distinguished" in terms of Penkov and Serganova) system of simple roots. The
results are given mainly for Lie superalgebras whose component of degree zero
is a Lie algebra (other cases being left to the reader). Observe presentations
of exceptional Lie superalgebras and Lie superalgebras of hamiltonian vector
fields. Now we can, at last, q-quantize the Lie Lie superalgebras of
hamiltonian vector fields and Poisson superalgebras.


  A spectrophotometric model able to compute the integrated spectrum of a
galaxy, including the contribution both of the stellar populations and of the
ionized interstellar gas of the HII regions powered by young hot stars, has
been used to study several spectral features and photometric quantities in
order to derive calibrations of the star formation history of late type
galaxies. Attention has been paid to analyze the emission of the Balmer lines
and the [OII]$\lambda$3727 line to test their attitude at providing estimates
of the present star formation rate in galaxies. Other features, like D$_{4000}$
and the equivalent width of the H$_{\delta}$ line, influenced by the presence
of intermediate age stars, have been considered. Several ways of estimating the
star formation rates in normal galaxies are discussed and some considerations
concerning the applicability of the models are presented. Criteria have been
also studied for ascertaining the presence of a burst, current or ended not
long ago. Bursts usually hinder the determination of the past star formation
rate.


  A qualitatively different manifestation of the Rayleigh instability is
demonstrated, where, instead of the usual extended undulations and breakup of
the liquid into many droplets, the instability is localized, leading to an
isolated narrowing of the liquid filament. The localized instability, caused by
a nonuniform curvature of the liquid domain, plays a key role in the
evaporation of thin liquid films off solid surfaces.


  The partition function of rational conformal field theories (CFTs) on Riemann
surfaces is expected to satisfy ODEs of Gauss-Manin type. We investigate the
case of hyperelliptic surfaces and derive the ODE system for the $(2,5)$
minimal model.


  This paper proposes a new method for vector quantization by minimizing the
Kullback-Leibler Divergence between the class label distributions over the
quantization inputs, which are original vectors, and the output, which is the
quantization subsets of the vector set. In this way, the vector quantization
output can keep as much information of the class label as possible. An
objective function is constructed and we also developed an iterative algorithm
to minimize it. The new method is evaluated on bag-of-features based image
classification problem.


  Annealing has been extensively used to control crystal growth and physical
properties of materials with unfortunately unclear mechanism and quantitative
correlations. Here we present the "annealing temperature - grain size - band
gap" correlation for ZnO nanocrystals with experimental evidence. Findings
revealed that the annealing condition determines the critical size by equating
the thermal and the cohesive energy of the undercoordinated atoms in the
surface skin, which in turn induce local strain and quantum entrapment,
perturbing the Hamiltonian and hence the band gap. The formulation provides a
general guideline for controlling crystal growth and performance of materials,
and makes predictive design and fabrication of functional nanomaterials into
reality.


  We study the 2D Navier--Stokes solution starting from an initial vorticity
mildly concentrated near $N$ distinct points in the plane. We prove
quantitative estimates on the propagation of concentration near a system of
interacting point vortices introduced by Helmholtz and Kirchhoff. Our work
extends the previous results in the literature in three ways: The initial
vorticity is concentrated in a weak (Wasserstein) sense, it is merely $L^p$
integrable for some $p>2$, and the estimates we derive are uniform with respect
to the viscosity.


  The socialization of the web has undertaken a new dimension after the
emergence of the Online Social Networks (OSN) concept. The fact that each
Internet user becomes a potential content creator entails managing a big amount
of data. This paper explores the most popular professional OSN: LinkedIn. A
scraping technique was implemented to get around 5 Million public profiles. The
application of natural language processing techniques (NLP) to classify the
educational background and to cluster the professional background of the
collected profiles led us to provide some insights about this OSN's users and
to evaluate the relationships between educational degrees and professional
careers.


  The linear response of synchronized time-delayed chaotic systems to small
external perturbations, i.e., the phenomenon of chaos pass filter, is
investigated for iterated maps. The distribution of distances, i.e., the
deviations between two synchronized chaotic units due to external perturbations
on the transfered signal, is used as a measure of the linear response. It is
calculated numerically and, for some special cases, analytically. Depending on
the model parameters this distribution has power law tails in the region of
synchronization leading to diverging moments of distances. This is a
consequence of multiplicative and additive noise in the corresponding linear
equations due to chaos and external perturbations. The linear response can also
be quantified by the bit error rate of a transmitted binary message which
perturbs the synchronized system. The bit error rate is given by an integral
over the distribution of distances and is calculated analytically and
numerically. It displays a complex nonmonotonic behavior in the region of
synchronization. For special cases the distribution of distances has a fractal
structure leading to a devil's staircase for the bit error rate as a function
of coupling strength. The response to small harmonic perturbations shows
resonances related to coupling and feedback delay times. A bi-directionally
coupled chain of three units can completely filtered out the perturbation. Thus
the second moment and the bit error rate become zero.


  We report on the study of many-body interactions in a single high quality
V-shaped quantum wire by means of continuous and time-resolved
microphotoluminescence. The transition from a weakly interacting exciton gas
when the carrier density n is less than 10^5 cm^-1 (i.e. n aX < 0.1, with aX
the exciton Bohr radius), to a dense electron-hole plasma (n > 10^6 cm^-1, i.e.
n aX > 1) is systematically followed in the system as the carrier density is
increased. We show that this transition occurs gradually : the free carriers
first coexist with excitons for n aX > 0.1, then the electron-hole plasma
becomes degenerate at n aX = 0.8. We also show that the non-linear effects are
strongly related to the kind of disorder and localization properties in the
structure especially in the low density regime.


  We discuss the design, implementation and performance of the radiation
monitoring and protection system used by the Silicon Vertex Tracker (SVT) in
the BaBar detector. Using 12 reverse-biased PIN photodiodes mounted around the
beampipe near the IP, we are able to provide instantaneous radiation dose
rates, absorbed dose integrals, and active protection that aborts the
circulating beams in the PEP-II storage ring when radiation levels exceed
user-defined thresholds. The system has reliably protected the SVT from
excessive radiation damage and has also served as a key diagnostic tool in
understanding radiation backgrounds at PEP-II.


  The iterations of many sparse estimation algorithms are comprised of a fixed
linear filter cascaded with a thresholding nonlinearity, which collectively
resemble a typical neural network layer. Consequently, a lengthy sequence of
algorithm iterations can be viewed as a deep network with shared, hand-crafted
layer weights. It is therefore quite natural to examine the degree to which a
learned network model might act as a viable surrogate for traditional sparse
estimation in domains where ample training data is available. While the
possibility of a reduced computational budget is readily apparent when a
ceiling is imposed on the number of layers, our work primarily focuses on
estimation accuracy. In particular, it is well-known that when a signal
dictionary has coherent columns, as quantified by a large RIP constant, then
most tractable iterative algorithms are unable to find maximally sparse
representations. In contrast, we demonstrate both theoretically and empirically
the potential for a trained deep network to recover minimal $\ell_0$-norm
representations in regimes where existing methods fail. The resulting system is
deployed on a practical photometric stereo estimation problem, where the goal
is to remove sparse outliers that can disrupt the estimation of surface normals
from a 3D scene.


  We prove results towards the equidistribution of certain families of periodic
torus orbits on homogeneous spaces, with particular focus on the case of the
diagonal torus acting on quotients of $\PGL_n(\R)$. After attaching to each
periodic orbit an integral invariant (the discriminant) our results have the
following flavour: certain standard conjectures about the distribution of such
orbits hold up to exceptional sets of at most $O(\Delta ^{\epsilon})$ orbits of
discriminant $\leq \Delta$. The proof relies on the well-separatedness of
periodic orbits together with measure rigidity for torus actions. We also give
examples of sequences of periodic orbits of this action that fail to become
equidistributed, even in higher rank.
  We give an application of our results to sharpen a theorem of Minkowski on
ideal classes in totally real number fields of cubic and higher degrees.


  We employ Random Matrix Theory in order to investigate coherent perfect
absorption (CPA) in lossy systems with complex internal dynamics. The loss
strength $\gamma_{\rm CPA}$ and energy $E_{\rm CPA}$, for which a CPA occurs
are expressed in terms of the eigenmodes of the isolated cavity -- thus
carrying over the information about the chaotic nature of the target -- and
their coupling to a finite number of scattering channels. Our results are
tested against numerical calculations using complex networks of resonators and
chaotic graphs as CPA cavities.


  We consider s-wave pairing in a double layer of two chiral metals due to
Coulomb interaction, and study the Josephson effect near a domain wall, where
the sign of the order parameter jumps. The domain wall creates two zero energy
modes, whose superposition is associated with a current that flows in different
direction in the two layers. Assuming a toroidal geometry, the effective
Josephson currents winds around the domain walls, whose winding number is
determined by the coefficients of the superimposed zero energy modes. This
result can be understood as a competition of the conventional Josephson current
perpendicular and the edge current parallel to a domain wall in a double layer
of two chiral metals. As a realization we suggest the surface of a ring-shaped
topological insulator. The duality between electron-electron and electron-hole
double layers indicates that this effect should also be observable in excitonic
double layers.


  We have fitted the surface brightness of a sample of 79 elliptical galaxies
pertaining to the Coma cluster of galaxies using the Sersic profile. This model
is defined through three primary parameters: scale length (a), intensity
(\Sigma_0), and a shape parameter (\nu); physical and astrophysical quantities
may be computed from these parameters. We show that correlations are stronger
among primary parameters than the classical astrophysical ones. In particular,
the galaxies follow a high correlation in \nu and a parameters. We show that
the \nu and a correlation satisfies a constant specific entropy condition. We
propose to use this entropy relation as distance indicator for clusters.


  The discovery of neutrino oscillations provides a solid evidence for nonzero
neutrino masses and leptonic mixing. The fact that neutrino masses are so tiny
constitutes a puzzling problem in particle physics. From the theoretical
viewpoint, the smallness of neutrino masses can be elegantly explained through
the seesaw mechanism. Another challenging issue for particle physics and
cosmology is the explanation of the matter-antimatter asymmetry observed in
Nature. Among the viable mechanisms, leptogenesis is a simple and
well-motivated framework. In this talk we briefly review these aspects, making
emphasis on the possibility of linking neutrino physics to the cosmological
baryon asymmetry originated from leptogenesis.


  We give a theoretical framework to obtain a low-energy effective theory of
quantum chromodynamics (QCD) towards a first-principle derivation of
confinement/deconfinement and chiral-symmetry breaking/restoration crossover
transitions. In fact, we demonstrate that an effective theory obtained using
simple but non-trivial approximations within this framework enables us to treat
both transitions simultaneously on equal footing. A resulting effective theory
is regarded as a modified and improved version of nonlocal Polyakov-loop
extended Nambu-Jona-Lasinio (nonlocal PNJL) models proposed recently by Hell,
R\"ossner, Cristoforetti and Weise, and Sasaki, Friman and Redlich, extending
the original (local) PNJL model by Fukushima and others. A novel feature is
that the nonlocal NJL coupling depends explicitly on the temperature and
Polyakov loop, which affects the entanglement between confinement and chiral
symmetry breaking, together with the cross term introduced through the
covariant derivative in the quark sector considered in the conventional PNJL
model. The chiral symmetry breaking/restoration transition is controlled by the
nonlocal NJL interaction, while the confinement/deconfinement transition in the
pure gluon sector is specified by the nonperturbative effective potential for
the Polyakov loop obtained recently by Braun, Gies, Marhauser and Pawlowski.
The basic ingredients are a reformulation of QCD based on new variables and the
flow equation of the Wetterich type in the Wilsonian renormalization group.
This framework can be applied to investigate the QCD phase diagram at finite
temperature and density.


  Extra dimensions (ED) can provide a useful tool for model-building. In this
paper we introduce a single, flat ED extension of the kinetic-mixing/dark
photon (DP) portal for dark matter (DM) interactions with the Standard Model
(SM) assuming a compactification `radius' of order $R^{-1}\sim10-1000$ MeV and
examine the resulting modifications to and augmentation of the usual DP
phenomenology. In the present scenario, both the DP and DM experience the full
5-D while the SM fields are constrained to lie on a 4-D brane at the boundary
of the ED. Such a setup can naturally yield the observed value of the DM relic
density and explain the required rough degeneracy of the DM and DP masses
needed to obtain it. Gauge symmetry breaking can occur via boundary conditions
without the introduction of an additional singlet Higgs scalar thus avoiding
all constraints associated with the coupling of such a field to the usual SM
Higgs field in 5-D. The self-consistency of the field redefinitions that map
the gauge fields into a canonical basis and thus removing the kinetic mixing
terms is found to lead to a strong model building constraint on the ED setup
involving a brane localized kinetic term for the 5-D gauge field on the SM
brane. Multiple variations of this scenario are found to be possible which are
consistent with all current experimental constraints but which predict very
different phenomenologies. In this paper, after setting up the general model
formalism, we discuss in detail the case of a complex scalar 5-D DM field,
consistent with constraints arising from the CMB, which may or may not obtain a
vacuum expectation value (vev). The resulting Kaluza-Klein (KK) towers of both
the DM and DP fields are found to yield interesting and distinctive signatures.


  By computing the completely bounded norm of the flip map on the Haagerup
tensor product $C_0 Y_1\otimes_{C_0 X} C_0 Y_2$ associated to a pair of
continuous mappings of locally compact Hausdorff spaces $Y_1\rightarrow
X\leftarrow Y_2$, we establish a simple characterisation of the Beck-Chevalley
condition for base change of operator modules over commutative $C^*$-algebras,
and a descent theorem for continuous fields of Hilbert spaces.


  We propose and experimentally demonstrate femtosecond direct laser writing
with Bessel beams for the fabrication of photonic crystals with spatial
filtering functionality. Such filters are mechanically stable, of small (of
order of millimeter) size, do not require direct access to the far-field
domain, and therefore are excellent candidates for intracavity spatial
filtering applications in mini- and micro-lasers. The technique allows the
fabrication of efficient photonic crystal spatial filters in glass, with a
narrow angle (~1 degree) nearly 100%-transmission pass-band between broad angle
(up to 10 degrees) nearly 0%-transmission angular stop-bands. We show, that
this technique can not only significantly shorten the fabrication time, but
also allows the fabrication of large-scale defect-free photonic crystal spatial
filters with a wide filtering band.


  Continuing previous work reported in an earlier paper [L.M. Burko, A.I.
Harte, and E. Poisson, Phys. Rev. D 65, 124006 (2002)] we calculate the
self-force acting on a point scalar charge in a wide class of cosmological
spacetimes. The self-force produces two types of effect. The first is a
time-changing inertial mass, and this is calculated exactly for a particle at
rest relative to the cosmological fluid. We show that for certain cosmological
models, the mass decreases and then increases back to its original value. For
all other models except de Sitter spacetime, the mass is restored only to a
fraction of its original value. For de Sitter spacetime the mass steadily
decreases. The second effect is a deviation relative to geodesic motion, and we
calculate this for a charge that moves slowly relative to the dust in a
matter-dominated cosmology. We show that the net effect of the self-force is to
push on the particle. We show that this is not an artifact of the scalar
theory: The electromagnetic self-force acting on an electrically charged
particle also pushes on the particle. The paper concludes with a demonstration
that the pushing effect can also occur in the context of slow-motion
electrodynamics in flat spacetime.


  The first detections of cosmic shear signal reported recently by 4
independent groups cover angular scales between one and 10 arcmin. On those
scales, the cosmic shear is a signature of non-linear perturbations, like
groups and clusters of galaxies. We present the results obtained by our team on
CFHT and on the VLT and discuss its impact for the analysis of cluster
abundances and cosmology


  We present the first results from an ongoing survey for Damped Lyman-alpha
systems (DLAs) in the spectra of z>2 quasars observed in the course of the
Baryon Oscillation Spectroscopic Survey (BOSS), which is part of the Sloan
Digital Sky Survey (SDSS) III. Our full (non-statistical) sample, based on Data
Release 9, comprises 12,081 systems with log N(HI)>=20, out of which 6,839 have
log N(HI)>=20.3. This is the largest DLA sample ever compiled, superseding that
from SDSS-II by a factor of seven. Using a statistical sub-sample and
estimating systematics from realistic mock data, we probe the N(HI)
distribution at <z> = 2.5. Contrary to what is generally believed, the
distribution extends beyond 10^22 cm^-2 with a moderate slope of
index\approx-3.5. This result matches surprisingly well the opacity-corrected
distribution observed at z = 0. The cosmological mass density of neutral gas in
DLAs is found to be Omega_g_DLA~10^-3, evolving only mildly over the past 12
billion years.


  In an earlier work [P. J. Bardroff and S. Stenholm], we have derived a fully
quantum mechanical description of excess noise in strongly damped lasers. This
theory is used here to derive the corresponding quantum Langevin equations.
Taking the semi-classical limit of these we are able to regain the starting
point of Siegman's treatment of excess noise [Phys. Rev. A 39, 1253 (1989)].
Our results essentially constitute a quantum derivation of his theory and allow
some generalizations.


  We study divided power structures on finitely generated $k$-algebras, where
$k$ is a field of positive characteristic $p$. As an application we show
examples of $0$-dimensional Gorenstein $k$-schemes that do not lift to a fixed
noetherian local ring of non-equal characteristic. We also show that Frobenius
neighbourhoods of a singular point of a general hypersurface of large dimension
have no liftings to mildly ramified rings of non-equal characteristic.


  Certifying function nonnegativity is a ubiquitous problem in computational
mathematics, with especially notable applications in optimization. We study the
question of certifying nonnegativity of signomials based on the recently
proposed approach of Sums-of-AM/GM-Exponentials (SAGE) decomposition due to the
second author and Shah. The existence of a SAGE decomposition is a sufficient
condition for nonnegativity of a signomial, and it can be verified by solving a
tractable convex relative entropy program. We present new structural properties
of SAGE certificates such as a characterization of the extreme rays of the
cones associated to these decompositions as well as an appealing form of
sparsity preservation. These lead to a number of important consequences such as
conditions under which signomial nonnegativity is equivalent to the existence
of a SAGE decomposition; our results represent the broadest-known class of
nonconvex signomial optimization problems that can be solved efficiently via
convex relaxation. The analysis in this paper proceeds by leveraging the
interaction between the convex duality underlying SAGE certificates and the
face structure of Newton polytopes. While our primary focus is on signomials,
we also discuss how our results provide efficient methods for certifying
polynomial nonnegativity, with complexity independent of the degree of a
polynomial.


  We present a deformable generator model to disentangle the appearance and
geometric information for both image and video data in a purely unsupervised
manner. The appearance generator network models the information related to
appearance, including color, illumination, identity or category, while the
geometric generator performs geometric warping, such as rotation and
stretching, through generating deformation field which is used to warp the
generated appearance to obtain the final image or video sequences. Two
generators take independent latent vectors as input to disentangle the
appearance and geometric information from image or video sequences. For video
data, a nonlinear transition model is introduced to both the appearance and
geometric generators to capture the dynamics over time. The proposed scheme is
general and can be easily integrated into different generative models. An
extensive set of qualitative and quantitative experiments shows that the
appearance and geometric information can be well disentangled, and the learned
geometric generator can be conveniently transferred to other image datasets to
facilitate knowledge transfer tasks.


  Let $\Lambda$ be an artin algebra, and $\mathcal{V}$ a subset of all simple
modules in $\mod\Lambda$. Suppose that $\Lambda/\rad \Lambda$ has finite syzygy
type, then the derived dimension of $\Lambda$ is at most
$\ell\ell^{t_{\mathcal{V}}}(\Lambda_{\Lambda})+\pd\mathcal{V}.$ In particular,
if the global dimension of $\Lambda$ is finite, then the derived dimension of
$\Lambda$ is at most
$\ell\ell^{t_{\mathcal{V}}}(\Lambda_{\Lambda})+\pd\mathcal{V}.$ This
generalized the famous result which state that the derived dimension of
$\Lambda$ is less than or equal to the global dimension of $\Lambda$.


  We begin the study the algebraic topology of semi-coarse spaces, which are
generalizations of coarse spaces that enable one to endow non-trivial
`coarse-like' structures to compact metric spaces, something which is
impossible in coarse geometry. We first study homotopy in this context, and we
then construct homology groups which are invariant under semi-coarse homotopy
equivalence. We further show that any undirected graph $G=(V,E)$ induces a
semi-coarse structure on its set of vertices $V_G$, and that the respective
semi-coarse homology is isomorphic to the Vietoris-Rips homology. This, in
turn, leads to a homotopy invariance theorem for the Vietoris-Rips homology of
undirected graphs.


  We build a systematic calculational method for the covariant expansion of the
two-point heat kernel $\hat K(\tau|x,x')$ for generic minimal and non-minimal
differential operators of any order. This is the expansion in powers of
dimensional background field objects -- the coefficients of the operator and
the corresponding spacetime and vector bundle curvatures, suitable in
renormalization and effective field theory applications. For minimal operators
whose principal symbol is given by an arbitrary power of the covariant
Laplacian $(-\Box)^M$, $M>1$, this result generalizes the well-known
Schwinger--DeWitt (or Seeley--Gilkey) expansion to the infinite series of
positive and negative fractional powers of the proper time $\tau^{1/M}$,
weighted by the generalized exponential functions of the dimensionless argument
$-\sigma(x,x')/2\tau^{1/M}$ depending on the Synge world function
$\sigma(x,x')$. The coefficients of this series are determined by the chain of
auxiliary differential operators acting on the two-point parallel transport
tensor, which in their turn follow from the solution of special recursive
equations. The derivation of these operators and their recursive equations are
based on the covariant Fourier transform in curved spacetime. The series of
negative fractional powers of $\tau$ vanishes in the coincidence limit $x'=x$,
which makes the proposed method consistent with the heat kernel theory of
Seeley--Gilkey and generalizes it beyond the heat kernel diagonal in the form
of the asymptotic expansion in the domain $\sigma(x,x')\ll\tau^{1/M}$, $\tau\to
0$.$\nabla^a\sigma(x,x')\ll\tau^{1/2M}$, $\tau\to 0$.


  We study a production-inventory system with two customer classes with
different priorities which are admitted to the system following a flexible
admission control scheme. The inventory management is according to a base stock
policy and arriving demand which finds the inventory depleted is lost (lost
sales). We analyse the global balance equations of the associated Markov
process and derive structural properties of the steady state distribution which
provide insights into the equilibrium behaviour of the system. We derive a
sufficient condition for ergodicity using the Foster-Lyapunov stability
criterion. For a special case we show that the condition is necessary as well.


  Several new accelerated methods in minimax optimization and fixed-point
iterations have recently been discovered, and, interestingly, they rely on a
mechanism distinct from Nesterov's momentum-based acceleration. In this work,
we show that these accelerated algorithms exhibit what we call the merging path
(MP) property; the trajectories of these algorithms merge quickly. Using this
novel MP property, we establish point convergence of existing accelerated
minimax algorithms and derive new state-of-the-art algorithms for the
strongly-convex-strongly-concave setup and for the prox-grad setup.


  The integration of a scanning tunneling microscope chamber with a sample
growth facility using non-custom, commercially available parts is described.
The facility also features a newly-designed magnetic wobble stick to increase
the reliability of sample transfer in a cost-effective manner.


  We develop the basic constructions of homological algebra in the
(appropriately defined) unbounded derived categories of modules over algebras
over coalgebras over noncommutative rings (which we call semialgebras over
corings). We define double-sided derived functors SemiTor and SemiExt of the
functors of semitensor product and semihomomorphisms, and construct an
equivalence between the exotic derived categories of semimodules and
semicontramodules.
  Certain (co)flatness and/or (co)projectivity conditions have to be imposed on
the coring and semialgebra to make the module categories abelian (and the
cotensor product associative). Besides, for a number of technical reasons we
mostly have to assume that the basic ring has a finite homological dimension
(no such assumptions about the coring and semialgebra are made).
  In the final sections we construct model category structures on the
categories of complexes of semi(contra)modules, and develop relative
nonhomogeneous Koszul duality theory for filtered semialgebras and
quasi-differential corings.
  Our motivating examples come from the semi-infinite cohomology theory.
Comparison with the semi-infinite (co)homology of Tate Lie algebras and graded
associative algebras is established in appendices, and the semi-infinite
homology of a locally compact topological group relative to an open profinite
subgroup is defined. An application to the correspondence between complexes of
representations of an infinite-dimensional Lie algebra on the complementary
central charge levels ($c$ and $26-c$ for the Virasoro) is worked out.


  It is known that a binary neutron star merger produces a hypermassive neutron
star. The lifetime of this compact remnant depends on the total mass and the
equation of state. The collapse of this compact remnant to a black- hole-torus
system is expected to give rise to a powerful jet and a short gamma-ray burst.
Nevertheless, if the collapse is delayed half a second or so, the surrounding
matter would be already accreted and/or expelled and hence no torus will be
formed. However, the collapse itself will give rise to a quasi-isotropic
magnetized fireball. This magnetic bomb will dissipate much of its energy due
to magnetic re-connection and will produce the prompt emission, when the
fireball will become transparent to gamma-rays. The energy range of such an
explosion depends on the initial magnetic field strength of the two neutron
stars and the amplification of the magnetic energy during merger. We discuss
the production of a quasi-isotropic magnetized fireball and its subsequent
interaction with the ejected matter during merger, as the outcome of the
coalescence of a binary neutron star system. We further discuss a possible
origin for the duration of the burst and the radial stratification of the flow
following the quasi-normal modes of the black hole.


  Mass estimates of galaxy clusters from X-ray and Sunyeav-Zel'dovich
observations assume the intracluster gas is in hydrostatic equilibrium with
their gravitational potential. However, since galaxy clusters are dynamically
active objects whose dynamical states can deviate significantly from the
equilibrium configuration, the departure from the hydrostatic equilibrium
assumption is one of the largest sources of systematic uncertainties in cluster
cosmology. In the literature there has been two methods for computing the
hydrostatic mass bias based on the Euler and the modified Jeans equations,
respectively, and there has been some confusion about the validity of these two
methods. The word "Jeans" was a misnomer, which incorrectly implies that the
gas is collisionless. To avoid further confusion, we instead refer these
methods as "summation" and "averaging" methods respectively. In this work, we
show that these two methods for computing the hydrostatic mass bias are
equivalent by demonstrating that the equation used in the second method can be
derived from taking spatial averages of the Euler equation. Specifically, we
identify the correspondences of individual terms in these two methods
mathematically and show that these correspondences are valid to within a few
percent level using hydrodynamical simulations of galaxy cluster formation. In
addition, we compute the mass bias associated with the acceleration of gas and
show that its contribution is small in the virialized regions in the interior
of galaxy cluster, but becomes non-negligible in the cluster outskirts of
massive clusters where materials are being actively accreted. We discuss
implications for understanding the origin of hydrostatic mass biases and for
characterizing them using hydrodynamical simulations as well as observations.


  Tidal Disruption Events (TDEs) can be perfect probes of dormant SMBHs in
normal galaxies. During the rising phase, the accretion luminosity can increase
by orders of magnitude in several weeks and the emergent ionizing radiation
illuminates the fresh accretion flow. In this paper, we simulated the evolution
of the expected spectral line profile of iron due to such a flare by using a
ray-tracing code with effects of general relativity (GR) taken into account. We
found that the time-dependent profile changes significantly with black hole
spin, inclination angle with respect to the black-hole equatorial plane, and
the expansion velocity of the ionization front. At low values of spin, a "loop"
feature appears in the line profile vs. time plot when the inclination is no
less than $30^\circ$ and the expansion velocity $v_{\rm exp}$ is no less than
half speed of light, due to a shadow in the emission of the truncated disk. In
the light curve two peaks occur depending on the inclination angle. At large
$v_{\rm exp}$, a shallow "nose" feature may develop ahead of the loop, its
duration depends on the expansion velocity and the inclination angle. We
explore the entire interval of black hole spin parameter ranging from extreme
prograde to extreme retrograde rotation, $-1<a<1$. In the prograde case, a
low-energy tail appears to be more pronounced in the evolving centroid energy
of the line. Our results demonstrate the importance to search for X-ray
spectral lines in the early phase of TDE flares in order to constrain black
hole mass and spin, as well as properties of the innermost accretion flow.


  We discuss some key issues associated with duality-violating and
non-perturbative OPE contributions to the theoretical representations of light
quark current-current two-point functions and relevant to precision
determinations of alpha_s from hadronic tau decay and electroproduction
cross-section data. We demonstrate that analyses with an explicit
representation of duality-violating effects are required to bring theoretical
errors in such extractions under control, motivating the accompanying paper in
these proceedings, which presents the results of such an analysis.


  DNA double-strand breaks (DSBs) represent a serious source of damage for all
living things and thus there have been many quantitative studies of DSBs both
in vivo and in vitro. Despite this fact, the processes that lead to their
production have not yet been clearly understood, and there is no established
theory that can account for the statistics of their production, in particular,
the number of DSBs per base pair per unit Gy, here denoted by P1, which is the
most important parameter for evaluating the degree of risk posed by DSBs. Here,
using the single-molecule observation method with giant DNA molecules (166
kbp), we evaluate the number of DSBs caused by gamma-ray irradiation. We find
that P1 is nearly inversely proportional to the DNA concentration above a
certain threshold DNA concentration. A simple model that accounts for the
marked decrease of P1 shows that it is necessary to consider the
characteristics of giant DNA molecules as semiflexible polymers to interpret
the intrinsic mechanism of DSBs.


  Computer Aided Diagnosis (CAD) system has been developed for the early
detection of breast cancer, one of the most deadly cancer for women. The benign
of mammogram has different texture from malignant. There are fifty mammogram
images used in this work which are divided for training and testing. Therefore,
the selection of the right texture to determine the level of accuracy of CAD
system is important. The first and second order statistics are the texture
feature extraction methods which can be used on a mammogram. This work
classifies texture descriptor into nine groups where the extraction of features
is classified using backpropagation learning with two types of multi-layer
perceptron (MLP). The best texture descriptor as selected when the value of
regression 1 appears in both the MLP-1 and the MLP-2 with the number of epoches
less than 1000. The results of testing show that the best selected texture
descriptor is the second order (combination) using all direction (0, 45, 90 and
135) that have twenty four descriptors.


  We investigate a vertically-stacked hybrid photodiode consisting of a thin
n-type molybdenum disulfide (MoS$_{2}$) layer transferred onto p-type silicon.
The fabrication is scalable as the MoS$_{2}$ is grown by a controlled and
tunable vapor phase sulfurization process. The obtained large-scale p-n
heterojunction diodes exhibit notable photoconductivity which can be tuned by
modifying the thickness of the MoS$_{2}$ layer. The diodes have a broad
spectral response due to direct and indirect band transitions of the nanoscale
MoS$_{2}$. Further, we observe a blue-shift of the spectral response into the
visible range. The results are a significant step towards scalable fabrication
of vertical devices from two-dimensional materials and constitute a new
paradigm for materials engineering.


  Metasurface has witnessed an urgent need for reconfigurable chiral
manipulation recently, while the graphene-based devices attracted significant
attention from researchers due to their inherent tunable properties. Here, an
L-shaped metasurface composed of three hollow monolayer graphene resonant rings
is proposed. A huge dual-frequency asymmetric transmission (AT) in the
mid-infrared band (7800 nm-9000 nm) with transmission efficiency peaks of 0.14
and 0.26 is revealed, which is optimal of its similar monolayer counterparts in
the current band. By changing the Fermi level of graphene and the relaxation
time of its carriers, the AT spectrum including the positions and widths of the
peaks can be effectively modulated. More importantly, the structure designed
here gives priority to the machinability of the metasurface configuration,
ensuring its practicality and promising applications in chiral applications in
the future.


  A Banach space $X$ is said to have the Daugavet property if every operator
$T: X\to X$ of rank~$1$ satisfies $\|Id+T\| = 1+\|T\|$. We show that then every
weakly compact operator satisfies this equation as well and that $X$ contains a
copy of $\ell_{1}$. However, $X$ need not contain a copy of $L_{1}$. We also
study pairs of spaces $X\subset Y$ and operators $T: X\to Y$ satisfying
$\|J+T\|=1+\|T\|$, where $J: X\to Y$ is the natural embedding. This leads to
the result that a Banach space with the Daugavet property does not embed into a
space with an unconditional basis. In another direction, we investigate spaces
where the set of operators with $\|Id+T\|=1+\|T\|$ is as small as possible and
give characterisations in terms of a smoothness condition.


  Classification of planar unit-distance graphs with up to 9 edges, by
homeomorphism and isomorphism classes. With exactly nine edges, there are 633
nonisomorphic connected matchstick graphs, of which 196 are topologically
distinct from each other. Increasing edges' number, their quantities rise more
than exponentially, in a still unclear way.


  Machine learning, particularly deep learning, is being increasing utilised in
space applications, mirroring the groundbreaking success in many earthbound
problems. Deploying a space device, e.g. a satellite, is becoming more
accessible to small actors due to the development of modular satellites and
commercial space launches, which fuels further growth of this area. Deep
learning's ability to deliver sophisticated computational intelligence makes it
an attractive option to facilitate various tasks on space devices and reduce
operational costs. In this work, we identify deep learning in space as one of
development directions for mobile and embedded machine learning. We collate
various applications of machine learning to space data, such as satellite
imaging, and describe how on-device deep learning can meaningfully improve the
operation of a spacecraft, such as by reducing communication costs or
facilitating navigation. We detail and contextualise compute platform of
satellites and draw parallels with embedded systems and current research in
deep learning for resource-constrained environments.


  Summarization systems are ultimately evaluated by human annotators and
raters. Usually, annotators and raters do not reflect the demographics of end
users, but are recruited through student populations or crowdsourcing platforms
with skewed demographics. For two different evaluation scenarios -- evaluation
against gold summaries and system output ratings -- we show that summary
evaluation is sensitive to protected attributes. This can severely bias system
development and evaluation, leading us to build models that cater for some
groups rather than others.


  The paper defines and studies manifold (M) convolutional filters and neural
networks (NNs). \emph{Manifold} filters and MNNs are defined in terms of the
Laplace-Beltrami operator exponential and are such that \emph{graph} (G)
filters and neural networks (NNs) are recovered as discrete approximations when
the manifold is sampled. These filters admit a spectral representation which is
a generalization of both the spectral representation of graph filters and the
frequency response of standard convolutional filters in continuous time. The
main technical contribution of the paper is to analyze the stability of
manifold filters and MNNs to smooth deformations of the manifold. This analysis
generalizes known stability properties of graph filters and GNNs and it is also
a generalization of known stability properties of standard convolutional
filters and neural networks in continuous time. The most important observation
that follows from this analysis is that manifold filters, same as graph filters
and standard continuous time filters, have difficulty discriminating high
frequency components in the presence of deformations. This is a challenge that
can be ameliorated with the use of manifold, graph, or continuous time neural
networks. The most important practical consequence of this analysis is to shed
light on the behavior of graph filters and GNNs in large-scale graphs.


  Rapid visualization of large-scale spatial vector data is a long-standing
challenge in Geographic Information Science. In existing methods, the
computation overheads grow rapidly with data volumes, leading to the
incapability of providing real-time visualization for large-scale spatial
vector data, even with parallel acceleration technologies. To fill the gap, we
present HiVision, a display-driven visualization model for large-scale spatial
vector data. Different from traditional data-driven methods, the computing
units in HiVision are pixels rather than spatial objects to achieve real-time
performance, and efficient spatial-index-based strategies are introduced to
estimate the topological relationships between pixels and spatial objects.
HiVision can maintain exceedingly good performance regardless of the data
volume due to the stable pixel number for display. In addition, an optimized
parallel computing architecture is proposed in HiVision to ensure the ability
of real-time visualization. Experiments show that our approach outperforms
traditional methods in rendering speed and visual effects while dealing with
large-scale spatial vector data, and can provide interactive visualization of
datasets with billion-scale points/segments/edges in real-time with flexible
rendering styles. The HiVision code is open-sourced at
https://github.com/MemoryMmy/HiVision with an online demonstration.


  In this paper we study the inverse problem of identifying the diffusion
matrix in an elliptic PDE from measurements. The convex energy functional
method with Tikhonov regularization is applied to tackle this problem. For the
discretization we use the variational discretization concept, where the PDE is
discretized with piecewise linear, continuous finite elements. We show the
convergence of approximations. Using a suitable source condition, we prove an
error bound for discrete solutions. For the numerical solution we propose a
gradient-projection algorithm and prove the strong convergence of its iterates
to a solution of the identification problem. Finally, we present a numerical
experiment which illustrates our theoretical results.


  Pervasive computing allows the provision of services in many important areas,
including the relevant and dynamic field of health and well-being. In this
domain, Human Activity Recognition (HAR) has gained a lot of attention in
recent years. Current solutions rely on Machine Learning (ML) models and
achieve impressive results. However, the evolution of these models remains
difficult, as long as a complete retraining is not performed. To overcome this
problem, the concept of Continual Learning is very promising today and, more
particularly, the techniques based on regularization. These techniques are
particularly interesting for their simplicity and their low cost. Initial
studies have been conducted and have shown promising outcomes. However, they
remain very specific and difficult to compare. In this paper, we provide a
comprehensive comparison of three regularization-based methods that we adapted
to the HAR domain, highlighting their strengths and limitations. Our
experiments were conducted on the UCI HAR dataset and the results showed that
no single technique outperformed all others in all scenarios considered.


  Two fundamental research tasks in science and engineering are forward
predictions and data inversion. This article introduces a recent R package
RobustCalibration for Bayesian data inversion and model calibration by
experiments and field observations. Mathematical models for forward predictions
are often written in computer code, and they can be computationally expensive
slow to run. To overcome the computational bottleneck from the simulator, we
implemented a statistical emulator from the RobustGaSP package for emulating
both scalar-valued or vector-valued computer model outputs. Both posterior
sampling and maximum likelihood approach are implemented in the
RobustCalibration package for parameter estimation. For imperfect computer
models, we implement Gaussian stochastic process and the scaled Gaussian
stochastic process for modeling the discrepancy function between the reality
and mathematical model. This package is applicable to various types of field
observations, such as repeated experiments and multiple sources of
measurements. We discuss numerical examples of calibrating mathematical models
that have closed-form expressions, and differential equations solved by
numerical methods.


  The new CARMENES instrument comprises two high-resolution and high-stability
spectrographs that are used to search for habitable planets around M dwarfs in
the visible and near-infrared regime via the Doppler technique. Characterising
our target sample is important for constraining the physical properties of any
planetary systems that are detected. The aim of this paper is to determine the
fundamental stellar parameters of the CARMENES M-dwarf target sample from
high-resolution spectra observed with CARMENES. We also include several M-dwarf
spectra observed with other high-resolution spectrographs, that is CAFE, FEROS,
and HRS, for completeness. We used a {chi}^2 method to derive the stellar
parameters effective temperature T_eff, surface gravity log g, and metallicity
[Fe/H] of the target stars by fitting the most recent version of the
PHOENIX-ACES models to high-resolution spectroscopic data. These stellar
atmosphere models incorporate a new equation of state to describe spectral
features of low-temperature stellar atmospheres. Since T_eff, log g, and [Fe/H]
show degeneracies, the surface gravity is determined independently using
stellar evolutionary models. We derive the stellar parameters for a total of
300 stars. The fits achieve very good agreement between the PHOENIX models and
observed spectra. We estimate that our method provides parameters with
uncertainties of {sigma} T_eff = 51 K, {sigma} log g = 0.07, and {sigma} [Fe/H]
= 0.16, and show that atmosphere models for low-mass stars have significantly
improved in the last years. Our work also provides an independent test of the
new PHOENIX-ACES models, and a comparison for other methods using
low-resolution spectra. In particular, our effective temperatures agree well
with literature values, while metallicities determined with our method exhibit
a larger spread when compared to literature results.