  A disk-shaped universe (encompassing the observable universe) rotating
globally with an angular speed equal to the Hubble constant is postulated. It
is shown that dark energy and dark matter are cosmic inertial effects resulting
from such a cosmic rotation, corresponding to centrifugal (dark energy), and a
combination of centrifugal and the Coriolis forces (dark matter), respectively.
The physics and the cosmological and galactic parameters obtained from the
model closely match those attributed to dark energy and dark matter in the
standard {\Lambda}-CDM model.


  Spinor fields are written in polar form so as to compute their tensorial
connection, an object that contains the same information of the connection but
which is also proven to be a real tensor. From this, one can still compute the
Riemann curvature, encoding the information about gravity. But even in absence
of gravity, when the Riemann curvature vanishes, it may still be possible that
the tensorial connection remains different from zero, and this can have effects
on matter. This is shown with examples in the two known integrable cases: the
hydrogen atom and the harmonic oscillator. The fact that a spinor can feel
effects due to sourceless actions is already known in electrodynamics as the
Aharonov-Bohm phenomenon. A parallel between the electrodynamics case and the
situation encountered here will be drawn. Some ideas about relativistic effects
and their role for general treatments of quantum field theories are also
underlined.


  In the present paper, we prove that with probability one, the Stratonovich
signatures of a multidimensional diffusion process (possibly degenerate) over
[0,1], which is the collection of all iterated Stratonovich's integrals of the
diffusion process over [0,1], determine the diffusion sample paths.


  SrTiO$_{3}$ is one of the most popular insulating single-crystal substrates
for various complex-oxide thin film growths, because of its good lattice match
with many complex oxide films. Here, we show that a common thin film processing
technique, argon ion-milling, creates highly conducting layer on the surface of
STO, not only at room temperatures but also at cryogenic temperatures at which
thermal diffusion is completely suppressed. Systematic \emph{in situ}
four-point conductance measurements were taken on single-crystal STO substrates
inside vacuum environment. The evolution of metallicity out of insulating STO
follows simple models based on oxygen vacancy doping effect. At cryogenic
temperatures, ion milling created a thin - but much thicker than the
argon-penetration depth - steady-state oxygen-vacant layer, leading to a
highly-concentric metallic state. Near room temperatures, however, significant
thermal diffusion occurred and the metallic state continuously diffused into
the bulk, leaving only low concentraion of electron carriers on the surface.
Analysis of the discrepancy between the experiments and the models also
provided evidence for vacany clustering, which seems to occur during any
vacancy formation process and affects the observed conductance. These
observations suggest that the transport properties of films processed on STO
substrates using energetic methods such as ion milling need to be taken with
caution. On the other hand, if properly controlled, ionic bombardment could be
used as a way to create selective conducting layers on the surface of STO for
device applications.


  In this paper, we introduce
$\mathbb{Z}_{p^r}\mathbb{Z}_{p^r}\mathbb{Z}_{p^s}$-additive cyclic codes for
$r\leq s$. These codes can be identified as $\mathbb{Z}_{p^s}[x]$-submodules of
$\mathbb{Z}_{p^r}[x]/\langle x^{\alpha}-1\rangle \times
\mathbb{Z}_{p^r}[x]/\langle x^{\beta}-1\rangle\times
\mathbb{Z}_{p^s}[x]/\langle x^{\gamma}-1\rangle$. We determine the generator
polynomials and minimal generating sets for this family of codes. Some previous
works has been done for the case $p=2$ with $r=s=1$, $r=s=2$, and $r=1,s=2$.
However, we show that in these previous works the classification of these codes
were incomplete and the statements in this paper complete such classification.
We also discuss the structure of separable
$\mathbb{Z}_{p^r}\mathbb{Z}_{p^r}\mathbb{Z}_{p^s}$-additive cyclic codes and
determine their generator polynomials. Further, we also study the duality of
$\mathbb{Z}_{p^s}[x]$-submodules. As applications, we present some examples and
construct some optimal binary codes.


  To implement useful quantum algorithms which demonstrate quantum advantage,
we must scale currently demonstrated quantum computers up significantly.
Leading platforms such as trapped ions face physical challenges in including
more information carriers. A less explored avenue for scaling up the
computational space involves utilizing the rich energy level structure of a
trapped ion to encode multi-level qudits rather than two-level qubits. Here we
show control and single-shot readout of qudits with up to 13 computational
states, using protocols which can be extended directly to manipulate qudits of
up to 25 levels in our chosen information host, $^{137}\text{Ba}^{+}$. This
represents more than twice as many computational states per qudit compared with
prior work in trapped ions. In addition to the preparation and readout
protocols we demonstrate, universal quantum computation requires other quantum
logic primitives such as entangling gates. These primitives have been
demonstrated for lower qudit dimensions and can be directly generalized to the
higher dimensions we employ. Hence, our advance opens an avenue towards using
high-dimensional qudits for large-scale quantum computation. We anticipate
efficiently utilizing available energy states in a trapped ion to play a
significant and complementary role in tackling the challenge in scaling up the
computational space of a trapped ion quantum computer. A qudit architecture
also offers other practical benefits, which include affording relaxed fault
tolerance thresholds for quantum error correction, providing an avenue for
efficient quantum simulation of higher spin systems, and more efficient qubit
gates.


  Galaxies in the local Universe are thought to require ongoing replenishment
of their gas reservoir in order to maintain the observed star formation rates.
Cosmological simulations predict that such accretion can occur in both a
dynamically hot and cold mode. However, until now observational evidence of the
accretion required to match the observed star formation histories is lacking.
This paper attempts to determine whether galaxies in the local Universe possess
a significant reservoir of HI and what would be the accretion rates derived
from such reservoirs. We search the vicinity of 22 nearby galaxies for isolated
HI clouds or distinct streams in a systematic and automated manner. The HALOGAS
observations represent one of the most sensitive and detailed HI surveys to
date. These observations typically reach column density sensitivities of 10^19
cm^-2 over a 20 km/s width. We find 14 secure HI cloud candidates without an
observed optical counterpart. These cloud candidates appear to be analogues to
the most massive clouds detected around the Milky Way and M31. However, on
average their numbers seem significantly reduced. We constrain upper limits for
HI accretion in the local Universe. The average HI mass currently observed
amounts to a rate of 0.05 Msun/yr with a stringent upper limit of 0.22 Msun/yr,
confirming previous estimates. This is much lower than the average star
formation rate in this sample. Our best estimate, based on GBT detection limits
of several galaxies, suggests that another 0.04 Msun/yr could be accreted from
undetected clouds and streams. These results show that in nearby galaxies HI is
not being accreted at the same rate as stars are currently being formed. Our
study can not exclude that other forms of gas accretion are at work. However,
these observations also do not reveal extended neutral gas reservoirs around
most nearby spiral galaxies.


  We introduce a ultradiscretization with parity variables of the
$q$-difference Painlev\'e VI system of equations. We show that ultradiscrete
limit of Riccati-type solutions of $q$-Painlev\'e VI satisfies the
ultradiscrete Painlev\'e VI system of equations with the parity variables,
which is valid by using the parity variables. We study some solutions of the
ultradiscrete Riccati-type equation and those of ultradiscrete Painlev\'e VI
equation.


  Low-energy dipole excitations in neon isotopes and N=16 isotones are
calculated with a fully consistent axially-symmetric-deformed quasiparticle
random phase approximation (QRPA) approach based on Hartree-Fock-Bogolyubov
(HFB) states. The same Gogny D1S effective force has been used both in HFB and
QRPA calculations. The microscopical structure of these low-lying resonances,
as well as the behavior of proton and neutron transition densities, are
investigated in order to determine the isoscalar or isovector nature of the
excitations. It is found that the N=16 isotones 24O, 26Ne, 28Mg, and 30Si are
characterized by a similar behavior. The occupation of the 2s_1/2 neutron orbit
turns out to be crucial, leading to nontrivial transition densities and to
small but finite collectivity. Some low-lying dipole excitations of 28Ne and
30Ne, characterized by transitions involving the neutron 1d_3/2 state, present
a more collective behavior and isoscalar transition densities. A collective
proton low-lying excitation is identified in the 18Ne nucleus.


  We formulate a multi-band generalisation of the time-dependent Gutzwiller
theory. This approach allows for the calculation of general two-particle
response functions, which are crucial for an understanding of various
experiments in solid-state physics. As a first application, we study the
momentum- and frequency-resolved magnetic susceptibility in a two-band Hubbard
model. Like in the underlying ground-state approaches we find significant
differences between the results of our method and those from a time-dependent
Hartree-Fock approximation.


  Given an equidistributed set in the whole Euclidean space, we have
established in [1] that there exists a constant positive $C$ such that the
observability inequality of diffusion equations holds for all $T\in]0,1[$, with
an observability cost being of the form $Ce^{C/T}$. In this paper, for any
small constant $\varepsilon>0$, we prove that there exists a nontrivial
equidistributed set (in the sense that whose complementary set is unbounded),
so that the above observability cost can be improved to a fast form of
$Ce^{\varepsilon/T}$ for certain constant $C>0$. The proof is based on the
strategy used in [1], as well as an interpolation inequality for gradients of
solutions to elliptic equations obtained recently in [2].


  We use semi-orthogonal decompositions to construct autoequivalences of
Hilbert schemes of points on Enriques surfaces and of Calabi-Yau varieties
which cover them. While doing this, we show that the derived category of a
surface whose irregularity and geometric genus vanish embeds into the derived
category of its Hilbert scheme of points.


  If there are a plethora of axions in nature, they may have a complicated
potential and create an axion landscape. We study a possibility that one of the
axions is so light that it is cosmologically stable, explaining the observed
dark matter density. In particular we focus on a case in which two (or more)
shift-symmetry breaking terms conspire to make the axion sufficiently light at
the potential minimum. In this case the axion has a flat-bottomed potential. In
contrast to the case in which a single cosine term dominates the potential, the
axion abundance as well as its isocurvature perturbations are significantly
suppressed. This allows an axion with a rather large mass to serve as dark
matter without fine-tuning of the initial misalignment, and further makes
higher-scale inflation to be consistent with the scenario.


  We apply near-threshold laser photodetachment to characterize the rotational
quantum level distribution of OH$^-$ ions stored in the cryogenic ion-beam
storage ring, DESIREE, at Stockholm University. We find that the stored ions
relax to a rotational temperature of 13.4$\pm$0.2 K with 94.9$\pm$0.3 % of the
ions in the rotational ground state. This is consistent with the storage ring
temperature of 13.5$\pm$0.5 K as measured with eight silicon diodes, but in
contrast to all earlier studies in cryogenic traps and rings where the
rotational temperatures were always much higher than those of the storage
devices at their lowest temperatures. Furthermore, we actively modify the
rotational distribution through selective photodetachment to produce an OH$^-$
beam where 99.1$\pm$0.1 % of approximately one million stored ions are in the
$J$=0 rotational ground state.


  Font generation is a challenging problem especially for some writing systems
that consist of a large number of characters and has attracted a lot of
attention in recent years. However, existing methods for font generation are
often in supervised learning. They require a large number of paired data, which
is labor-intensive and expensive to collect. Besides, common image-to-image
translation models often define style as the set of textures and colors, which
cannot be directly applied to font generation. To address these problems, we
propose novel deformable generative networks for unsupervised font generation
(DGFont). We introduce a feature deformation skip connection (FDSC) which
predicts pairs of displacement maps and employs the predicted maps to apply
deformable convolution to the low-level feature maps from the content encoder.
The outputs of FDSC are fed into a mixer to generate the final results. Taking
advantage of FDSC, the mixer outputs a high-quality character with a complete
structure. To further improve the quality of generated images, we use three
deformable convolution layers in the content encoder to learn style-invariant
feature representations. Experiments demonstrate that our model generates
characters in higher quality than state-of-art methods. The source code is
available at https://github.com/ecnuycxie/DG-Font.


  We generalize the application of the functional renormalization group (fRG)
method for the fermionic flow into the symmetry-broken phase to finite
temperatures. We apply the scheme to the case of a broken discrete symmetry:
the charge-density wave (CDW) mean-field model at half filling. We show how an
arbitrarily small initial CDW order parameter starts to grow at the CDW
instability and how it flows to the correct final value, suppressing the
divergence of the effective interaction in the fRG flow. The effective
interaction peaks at the instability and saturates at low energy scales or
temperatures. The relation to the mean-field treatment, differences compared to
the flow for a broken continuous symmetry, and the prospects of the new method
are discussed.


  Disk accretion at high rate onto a white dwarf or a neutron star has been
suggested to result in the formation of a spreading layer (SL) - a belt-like
structure on the object's surface, in which the accreted matter steadily
spreads in the poleward (meridional) direction while spinning down. To assess
its basic characteristics we perform two-dimensional hydrodynamic simulations
of supersonic SLs in the relevant morphology with a simple prescription for
cooling. We demonstrate that supersonic shear naturally present at the base of
the SL inevitably drives sonic instability that gives rise to large scale
acoustic modes governing the evolution of the SL. These modes dominate the
transport of momentum and energy, which is intrinsically global and cannot be
characterized via some form of local effective viscosity (e.g.
$\alpha$-viscosity). The global nature of the wave-driven transport should have
important implications for triggering Type I X-ray bursts in low mass X-ray
binaries. The nonlinear evolution of waves into a system of shocks drives
effective re-arrangement (sensitively depending on thermodynamical properties
of the flow) and deceleration of the SL, which ultimately becomes transonic and
susceptible to regular Kelvin-Helmholtz instability. We interpret this
evolution in terms of the global structure of the SL and suggest that mixing of
the SL material with the underlying stellar fluid should become effective only
at intermediate latitudes on the accreting object's surface, where the flow has
decelerated appreciably. In the near-equatorial regions the transport is
dominated by acoustic waves and mixing is less efficient. We speculate that
this latitudinal non-uniformity of mixing in accreting white dwarfs may be
linked to the observed bipolar morphology of classical novae ejecta.


  Computational models are an essential tool for the design, characterization,
and discovery of novel materials. Hard computational tasks in materials science
stretch the limits of existing high-performance supercomputing centers,
consuming much of their simulation, analysis, and data resources. Quantum
computing, on the other hand, is an emerging technology with the potential to
accelerate many of the computational tasks needed for materials science. In
order to do that, the quantum technology must interact with conventional
high-performance computing in several ways: approximate results validation,
identification of hard problems, and synergies in quantum-centric
supercomputing. In this paper, we provide a perspective on how quantum-centric
supercomputing can help address critical computational problems in materials
science, the challenges to face in order to solve representative use cases, and
new suggested directions.


  The present paper deals with the identification of nonlinear mechanical
vibrations. A grey-box, or semi-physical, nonlinear state-space representation
is introduced, expressing the nonlinear basis functions using a limited number
of measured output variables. This representation assumes that the observed
nonlinearities are localised in physical space, which is a generic case in
mechanics. A two-step identification procedure is derived for the grey-box
model parameters, integrating nonlinear subspace initialisation and weighted
least-squares optimisation. The complete procedure is applied to an electrical
circuit mimicking the behaviour of a single-input, single-output (SISO)
nonlinear mechanical system and to a single-input, multiple-output (SIMO)
geometrically nonlinear beam structure.


  In this paper, we classify the perfect lattices in dimension 8. There are
10916 of them. Our classification heavily relies on exploiting symmetry in
polyhedral computations. Here we describe algorithms making the classification
possible.


  The transport properties and electron states in cylinder nanowires of Dirac
and Weyl semimetals are studied paying special attention to the structure and
properties of the surface Fermi arcs. The latter make the electric charge and
current density distributions in nanowires strongly nonuniform as the majority
of the charge density is accumulated at the surface. It is found that a Weyl
semimetal wire also supports a magnetization current localized mainly at the
surface because of the Fermi arcs contribution. By using the Kubo linear
response approach, the direct current (DC) conductivity is calculated and it is
found that its spatial profile is nontrivial. By explicitly separating the
contributions of the surface and bulk states, it is shown that when the
electric chemical potential and/or the radius of the wire is small, the
electron transport is determined primarily by the Fermi arcs and the electrical
conductivity is much higher at the surface than in the bulk. Due to the rise of
the surface-bulk transition rate, the relative contribution of the surface
states to the total conductivity gradually diminishes as the chemical potential
increases. In addition, the DC conductivity at the surface demonstrates
noticeable peaks when the Fermi level crosses energies of the surface states.


  We compute the decay of the autocorrelation function of the observable
$|v_x|$ in the Sinai billiard and of the observable $v_x$ in the associated
Lorentz gas with an approximation due to Baladi, Eckmann and Ruelle. We
consider the standard configuration where the disks is centered inside a unit
square. The asymptotic decay is found to be $C(t) \sim c(R)/t$. An explicit
expression is given for the prefactor $c(R)$ as a function of the radius of the
scatterer. For the small scatterer case we also present expressions for the
preasymptotic regime. Our findings are supported by numerical computations.


  Image-based localization (IBL) aims to estimate the 6DOF camera pose for a
given query image. The camera pose can be computed from 2D-3D matches between a
query image and Structure-from-Motion (SfM) models. Despite recent advances in
IBL, it remains difficult to simultaneously resolve the memory consumption and
match ambiguity problems of large SfM models. In this work, we propose a
cascaded parallel filtering method that leverages the feature, visibility and
geometry information to filter wrong matches under binary feature
representation. The core idea is that we divide the challenging filtering task
into two parallel tasks before deriving an auxiliary camera pose for final
filtering. One task focuses on preserving potentially correct matches, while
another focuses on obtaining high quality matches to facilitate subsequent more
powerful filtering. Moreover, our proposed method improves the localization
accuracy by introducing a quality-aware spatial reconfiguration method and a
principal focal length enhanced pose estimation method. Experimental results on
real-world datasets demonstrate that our method achieves very competitive
localization performances in a memory-efficient manner.


  The EM ratio for a free Delta electromagnetic transition is discussed within
the frame work of nonrelativistic approach. Such an approach gives a good
account of data for a free Delta but is less important for an intrinsically
relativistic nuclear many body problem.


  Watson-Crick (WK) finite automata are working on a Watson-Crick tape, that
is, on a DNA molecule. A double stranded DNA molecule contains two strands,
each having a 5' and a 3' end, and these two strands together form the molecule
with the following properties. The strands have the same length, their 5' to 3'
directions are opposite, and in each position, the two strands have nucleotides
that are complement of each other (by the Watson-Crick complementary relation).
Consequently, WK automata have two reading heads, one for each strand. In
traditional WK automata both heads read the whole input in the same physical
direction, but in 5'->3' WK automata the heads start from the two extremes and
read the input in opposite direction. In sensing 5'->3' WK automata, the
process on the input is finished when the heads meet, and the model is capable
to accept the class of linear context-free languages. Deterministic variants
are weaker, the class named 2detLIN, a proper subclass of linear languages is
accepted by them. Recently, another specific variants, the state-deterministic
sensing 5'->3' WK automata are investigated in which the graph of the automaton
has the special property that for each node of the graph, all out edges (if
any) go to a sole node, i.e., for each state there is (at most) one state that
can be reached by a direct transition. It was shown that this concept is
somewhat orthogonal to the usual concept of determinism in case of sensing
5'->3' WK automata. In this paper a new concept, the quasi-determinism is
investigated, that is in each configuration of a computation (if it is not
finished yet), the next state is uniquely determined although the next
configuration may not be, in case various transitions are enabled at the same
time. We show that this new concept is a common generalisation of the usual
determinism and the state-determinism, i.e., the class of quasi-deterministic
sensing 5'->3' WK automata is a superclass of both of the mentioned other
classes. There are various usual restrictions on WK automata, e.g., stateless
or 1-limited variants. We also prove some hierarchy results among language
classes accepted by various subclasses of quasi-deterministic sensing 5'->3' WK
automata and also some other already known language classes.


  We study the transport properties of a quantum dot (QD) with highly resistive
gate electrodes, and show that the QD displays a quantum phase transition
analogous to the famous dissipative phase transition first identified by S.
Chakravarty [Phys. Rev. Lett. {\bf 49}, 681 (1982)]; for a review see [A. J.
Leggett {\em et al.}, Rev. Mod. Phys. {\bf 59}, 1 (1987)]. At temperature T=0,
the charge on the central island of a conventional QD changes smoothly as a
function of gate voltage, due to quantum fluctuations. However, for
sufficiently large gate resistance charge fluctuations on the island can freeze
out even at the degeneracy point, causing the charge on the island to change in
sharp steps as a function of gate voltage. For $R_g<R_C$ the steps remain
smeared out by quantum fluctuations. The Coulomb blockade peaks in conductance
display anomalous scaling at intermediate temperatures, and at very low
temperatures a sharp step develops in the QD conductance.


  Difference-phase (or Hanbury Brown - Twiss type) intensity interference of
classical light is considered in higher orders in the intensity. It is shown
that, while the visibility of sum-phase (NOON-type) interference for classical
sources drops with the order of interference, the visibility of
difference-phase interference has opposite behavior. For three-photon and
four-photon interference of two coherent sources, the visibility can be as high
as 81.8% and 94.4%, respectively. High-visibility three-photon and four-photon
interference of space-time and polarization types has been observed in
experiment, for both coherent and pseudo-thermal light.


  In this article, we study conjectures of Sandon on the minimal number of
translated points in the special case of the unit tangent bundle of a
Riemannian manifold. We restrict ourselves to contactomorphisms of $SM$ that
lift diffeomorphisms of $M$ homotopic to identity. We prove that there exist
sequences $(p_n,t_n)$ where $p_n$ is a translated point of time-shift $t_n$
with $t_n\to+\infty$ for a large class of manifolds. We also prove Morse
estimates on the number of translated points in the case of Zoll Riemannian
manifolds.


  In this paper, we study the period map of a certain one-parameter family of
quartic K3 surfaces with an S5-action. We construct automorphic forms on the
period domain as the pull-backs of theta constants of genus 2 by a modular
embedding. Using these automorphic forms, we give an explicit presentation of
the inverse period map.


  We characterize the vanishing of the shifted Courant-Nijenhuis torsion as the
strongest tensorial integrability condition that can be imposed on a
skew-symmetric endomorphism of the generalized tangent bundle.


  The question of whether to attempt deflections during planetary defence
emergencies has been subject to considerable decision-making analysis (Schmidt
2018; SMPAG Ad-Hoc Working Group on Legal Issues 2020). Hypothetical situations
usually involve a newly discovered asteroid with a high impact probability on a
set timescale. This paper addresses two further complexities: (1) limiting
missions to an asteroid due to the risk of a human-caused Earth impact; and (2)
active management of asteroids to place them in "safe harbours", even when
impact risks are otherwise below "decision to act" thresholds. We use Apophis
as a case study, and address the two complexities in turn.


  Jerky elasticity was observed by dynamical mechanical analyzer measurements
in a single crystal of the shape memory alloy Cu74.08Al23.13Be2.79. Jerks
appear as spikes in the dissipation of the elastic response function and relate
to the formation of avalanches during the transformation between the austenite
and the martensite phase. The statistics of the avalanches follows the
predictions of avalanche criticality P(E) proportional to E-epsilon where P(E)
is the probability of finding an avalanche with the energy E. This result
reproduces, within experimental uncertainties, previous findings by acoustic
emission techniques.


  We consider the Ising model on the Bethe lattice with aperiodic modulation of
the couplings, which has been studied numerically in Phys. Rev. E 77, 041113
(2008). Here we present a relevance-irrelevance criterion and solve the
critical behavior exactly for marginal aperiodic sequences. We present
analytical formulae for the continuously varying critical exponents and discuss
a relationship with the (surface) critical behavior of the aperiodic quantum
Ising chain.


  The introduction of the quantum analogue of a Carnot engine based on a bath
comprising of particles with a small amount of coherence initiated an active
line of research on the harnessing of different quantum resources for the
enhancement of thermal machines beyond the standard reversible limit, with an
emphasis on non-thermal baths containing quantum coherence. In our work, we
investigate the impact of coherence on the thermodynamic tasks of a collision
model which is composed of a system interacting, in the continuous time limit,
with a series of coherent ancillas of two baths at different temperatures. Our
results show the advantages of utilising coherence as a resource in the
operation of the machine, and allows it: (i) to exhibit unconventional
behaviour such as the appearance of a hybrid refrigerator, capable of
simultaneous refrigeration and generation of work, and (ii) to function as an
engine or a refrigerator with efficiencies larger than the Carnot bound.
Moreover, we find an effective upper bound to the efficiency of the thermal
machine operating as an engine in the presence of a coherent reservoir.


  Constant cycle curves on a K3 surface $X$ over $\mathbb{C}$ have been
introduced by Huybrechts (2014) as curves whose points all define the same
class in the Chow group. In this paper we study correspondences $Z \subseteq
X\times X$ over $\mathbb{C}$ acting on the group $\mbox{ccc}(X)$ of cycles
generated by irreducible constant cycle curves. We construct for any $n\geq 2$
and any very ample line bundle $L$ a locus $Z_n(L)\subseteq X\times X$ of
expected dimension $2$, which yields a correspondence that acts on
$\mbox{ccc}(X)$, when it has the expected dimension. We provide examples of
$Z_n(L)$ for low $n$ and exhibit one correspondence different from $Z_n(L)$
acting on $\mbox{ccc}(X)$.


  In this note we show how to obtain regularity estimates for the fractional
Laplacian on the multidimensional torus $\mathbb{T}^n$ from the fractional
Laplacian on $\mathbb{R}^n$. Though at first glance this may seem quite
natural, it must be carefully precised. A reason for that is the simple fact
that $L^2$ functions on the torus can not be identified with $L^2$ functions on
$\mathbb{R}^n$. The transference is achieved through a formula that holds in
the distributional sense. Such an identity allows us to transfer Harnack
inequalities, to relate the extension problems, and to obtain pointwise
formulas and H\"older regularity estimates.


  We construct a version of the complex Heisenberg algebra based on the idea of
endless analytic continuation. In particular, we exhibit an integral formula
for the product of resurgent operators with algebraic singularities. This
algebra would be large enough to capture quantum effects that escape ordinary
formal deformation quantisation.


  We discuss the possibility of the quantum Hall effect at half-filled Landau
level in terms of the pairing of the composite fermions. In the absence of
Coulomb energy, we show that the ground state of the system is described by the
{\it p}-wave BCS pairing state of composite fermions. When the ratio $\alpha
\equiv (e^2/\epsilon \ell_B)/\epsilon_F$ ($\ell_B$ : the magnetic length,
$\epsilon_F$ : Fermi energy of the composite fermions) is larger than a
critical value $\alpha_c \sim 8.2$ the gap of the pairing state vanishes.
However, $\alpha$ remains less than $\alpha_c$ if $\hbar \omega_c \gg
e^2/\epsilon \ell_B$ holds. Then in this situation it is possible that the
pairing state which results in the quantum Hall effect occurs. The effect of
the real spin degrees of freedom and the Zeeman energy is also discussed.


  We present a rotating regular black hole whose inner horizon has zero surface
gravity for any value of the spin parameter, and is therefore stable against
mass inflation. Our metric is built by combining two successful strategies for
regularizing singularities, i.e. by replacing the mass parameter with a
function of $r$ and by introducing a conformal factor. The mass function
controls the properties of the inner horizon, whose displacement away from the
Kerr geometry's inner horizon is quantified in terms of a parameter $e$; while
the conformal factor regularizes the singularity in a way that is parametrized
by the dimensionful quantity $b$. The resulting line element not only avoids
the stability issues that are common to regular black hole models endowed with
inner horizons, but is also free of problematic properties of the Kerr
geometry, such as the existence of closed timelike curves. While the proposed
metric has all the phenomenological relevant features of singular rotating
black holes -- such as ergospheres, light ring and innermost stable circular
orbit -- showing a remarkable similarity to a Kerr black hole in its exterior,
it allows nonetheless sizable deviations, especially for large values of the
spin parameter $a$. In this sense, the proposed rotating "inner-degenarate"
regular black hole solution is not only amenable to further theoretical
investigations but most of all can represent a viable geometry to contrast to
the Kerr one in future phenomenological tests.


  This work presents the Video Platform for PyTorch (ViP), a deep
learning-based framework designed to handle and extend to any problem domain
based on videos. ViP supports (1) a single unified interface applicable to all
video problem domains, (2) quick prototyping of video models, (3) executing
large-batch operations with reduced memory consumption, and (4) easy and
reproducible experimental setups. ViP's core functionality is built with
flexibility and modularity in mind to allow for smooth data flow between
different parts of the platform and benchmarking against existing methods. In
providing a software platform that supports multiple video-based problem
domains, we allow for more cross-pollination of models, ideas and stronger
generalization in the video understanding research community.


  We present a new package ZpL for the mathematical software system SM. It
implements a sharp tracking of precision on p-adic numbers, following the
theory of ultrametric precision introduced in [4]. The underlying algorithms
are mostly based on automatic dierentiation techniques. We introduce them,
study their complexity and discuss our design choices. We illustrate the
bene-ts of our package (in comparison with previous implementations) with a
large sample of examples coming from linear algebra, com-mutative algebra and
dierential equations.


  This paper gives an overview of a reconstruction algorithm for muon events in
ATLAS experiment at CERN. After a short introduction on ATLAS Muon
Spectrometer, we will describe the procedure performed by the algorithms
Muonbox and Muonboy (last version) in order to achieve correctly the
reconstruction task. These algorithms have been developed in Fortran language
and are working in the official C++ framework Athena, as well as in stand alone
mode. A description of the interaction between Muonboy and Athena will be
given, together with the reconstruction performances (efficiency and momentum
resolution) obtained with MonteCarlo data.


  We associate to a bimonoidal functor, i.e. a bifunctor which is monoidal in
each variable, a nonabelian version of a biextension. We show that such a
biextension satisfies additional triviality conditions which make it a bilinear
analog of the kind of spans known as butterflies and, conversely, these data
determine a bimonoidal functor. We extend this result to $n$-variables, and
prove that, in a manner analogous to that of butterflies, these
multi-extensions can be composed. This is phrased in terms of a multilinear
functor calculus in a bicategory. As an application, we study a bimonoidal
category or stack, treating the multiplicative structure as a bimonoidal
functor with respect to the additive one. In the context of the multilinear
functor calculus, we view the bimonoidal structure as an instance of the
general notion of pseudo-monoid. We show that when the structure is ring-like,
i.e. the pseudo-monoid is a stack whose fibers are categorical rings, we can
recover the classification by the third Mac Lane cohomology of a ring with
values in a bimodule.


  We derive closed formulae for the first examples of non-algebraic, elliptic
`leading singularities' in planar, maximally supersymmetric Yang-Mills theory
and show that they are Yangian-invariant.


  Ion hydrations are ubiquitous in natural and fundamental processes. A
quantitative analysis of a novel CO2 sorbent driven by ion hydrations was
presented by molecular dynamics (MD). We explored the humidity effect on the
diffusion and structure of ion hydrations in CO2 sorbent, as well as the
working mechanism of the moisture-swing CO2 sorbent. The discovery of the
diffusion coefficients of ions at different humidity levels can be applied to
design a new CO2 sorbent with superior performance. The molecular structure
analysis shows a higher precipitation rate of HCO3- ions than CO32- ions in a
dry surrounding, which leads to a more alkaline surrounding on CO2 sorbent that
may promote the absorption of CO2.


  Magneli phase Ti5O9 ceramics with 200-nm grain-size were fabricated by
hot-pressing nanopowders of titanium and anatase TiO2 at 1223 K. The
thermoelectric properties of these ceramics were investigated from room
temperature to 1076 K. We show that the experimental variation of the
electrical conductivity with temperature follows a small-polaron model and that
the Seebeck coefficient can be explained by a temperature-dependent
Heikes-Chaikin-Beni model. The thermoelectric figure-of-merit ZT of this
nanoceramic material reaches 0.3 at 1076 K.


  We look at observational constraints on the thawing class of scalar field
models proposed to explain the late time acceleration of the universe. Using
the recently introduced `Statefinder Hierarchy', we compare these thawing class
of models with other widely studied dark energy (and modified gravity) models
to check the underlying parameter degeneracies. We put constraints on the
deviations of these thawing models from the canonical \Lambda CDM model using a
large class of observational data, e.g, the Supernova Type Ia data, the BAO
data, the CMB data and data from the measurements of the Hubble parameter using
red-envelope galaxies. We also forecast constraints using a simulated dataset
for the future JDEM SNe survey. Our study shows that, although with current
data it is difficult to distinguish different thawing models from \Lambda CDM,
a future JDEM like mission would be able tell apart thawing models from \Lambda
CDM for currently acceptable values of \Omega_{m0}


  Change detection in multivariate time series has applications in many
domains, including health care and network monitoring. A common approach to
detect changes is to compare the divergence between the distributions of a
reference window and a test window. When the number of dimensions is very
large, however, the naive approach has both quality and efficiency issues: to
ensure robustness the window size needs to be large, which not only leads to
missed alarms but also increases runtime.
  To this end, we propose LIGHT, a linear-time algorithm for robustly detecting
non-linear changes in massively high dimensional time series. Importantly,
LIGHT provides high flexibility in choosing the window size, allowing the
domain expert to fit the level of details required. To do such, we 1) perform
scalable PCA to reduce dimensionality, 2) perform scalable factorization of the
joint distribution, and 3) scalably compute divergences between these lower
dimensional distributions. Extensive empirical evaluation on both synthetic and
real-world data show that LIGHT outperforms state of the art with up to 100%
improvement in both quality and efficiency.


  The global missing baryon problem - that the sum of observed baryons falls
short of the number expected form BBN - is well known. In addition to this,
there is also a local missing baryon problem that applies to individual dark
matter halos. This halo by halo missing baryon problem is such that the
observed mass fraction of baryons in individual galaxies falls short of the
cosmic baryon fraction. This deficit is a strong function of circular velocity.
I give an empirical estimate of this function, and note the presence of a
critical scale of ~900 km/s therein. I also briefly review Omega_b from BBN,
highlighting the persistent tension between lithium and the CMB, and discuss
some pros and cons of individual galaxies and clusters of galaxies as potential
reservoirs of dark baryons.


  Recently proposed tailpipe emissions standards aim to significant increases
in electric vehicle (EV) sales in the United States. Our work examines whether
this increase is achievable given potential constraints in EV mineral supply
chains. We estimate a model that reflects international sourcing rules,
heterogeneity in the mineral intensity of predominant battery chemistries, and
long-run grid decarbonization efforts. Our efforts yield five key findings.
First, compliance with the proposed standard necessitates replacing at least
10.21 million new ICEVs with EVs between 2027 and 2032. Second, based on
economically viable and geologically available mineral reserves, manufacturing
sufficient EVs is plausible across most battery chemistries and could, subject
to the chemistry leveraged, reduce up to 457.3 million total tons of CO2e.
Third, mineral production capacities of the US and its allies constrain battery
production to a total of 5.09 million EV batteries between 2027 and 2032, well
short of deployment requirements to meet EPA standards even if battery
manufacturing is optimized to exclusively manufacture materials efficient NMC
811 batteries. Fourth, disequilibrium between mineral supply and demand results
in at least 59.54 million tons of CO2e in total lost lifecycle emissions
benefits. Fifth, limited present-day production of battery-grade graphite and
to a lesser extent, cobalt, constrain US electric vehicle battery pack
manufacturing under strict sourcing rules. We demonstrate that should mineral
supply bottlenecks persist, hybrid electric vehicles may offer equivalent
lifecycle emissions benefits as EVs while relaxing mineral production demands,
though this represents a tradeoff of long-term momentum in electric vehicle
deployment in favor of near-term carbon dioxide emissions reductions.


  Resonant laser scattering along with photon correlation measurements have
established the atom-like character of quantum dots. Here, we present
measurements which challenge this identification for a wide range of
experimental parameters: the absorption lineshapes that we measure at magnetic
fields exceeding 1 Tesla indicate that the nuclear spins polarize by an amount
that ensures locking of the quantum dot resonances to the incident laser
frequency. In contrast to earlier experiments, this nuclear spin polarization
is bi-directional, allowing the electron+nuclear spin system to track the
changes in laser frequency dynamically on both sides of the quantum dot
resonance. Our measurements reveal that the confluence of the laser excitation
and nuclear spin polarization suppresses the fluctuations in the resonant
absorption signal. A master equation analysis shows narrowing of the nuclear
Overhauser field variance, pointing to potential applications in quantum
information processing.


  Neural networks are seeing increased use in diverse Internet of Things (IoT)
applications such as healthcare, smart homes and industrial monitoring. Their
widespread use makes neural networks a lucrative target for theft. An attacker
can obtain a model without having access to the training data or incurring the
cost of training. Also, networks trained using private data (e.g., medical
records) can reveal information about this data. Networks can be stolen by
leveraging side channels such as power traces of the IoT device when it is
running the network. Existing attacks require operations to occur in the same
order each time; an attacker must collect and analyze several traces of the
device to steal the network. Therefore, to prevent this type of attack, we
randomly shuffle the order of operations each time. With shuffling, each
operation can now happen at many different points in each execution, making the
attack intractable. However, we show that shuffling in software can leak
information which can be used to subvert this solution. Therefore, to perform
secure shuffling and reduce latency, we present BlackJack, hardware added as a
functional unit within the CPU. BlackJack secures neural networks on IoT
devices by increasing the time needed for an attack to centuries, while adding
just 2.46% area, 3.28% power and 0.56% latency overhead on an ARM M0+ SoC.


  We present exact calculations of the Potts model partition function
$Z(G,q,v)$ for arbitrary $q$ and temperature-like variable $v$ on $n$-vertex
square-lattice strip graphs $G$ for a variety of transverse widths $L_t$ and
for arbitrarily great length $L_\ell$, with free longitudinal boundary
conditions and free and periodic transverse boundary conditions. These have the
form $Z(G,q,v)=\sum_{j=1}^{N_{Z,G,\lambda}}
c_{Z,G,j}(\lambda_{Z,G,j})^{L_\ell}$. We give general formulas for $N_{Z,G,j}$
and its specialization to $v=-1$ for arbitrary $L_t$ for both types of boundary
conditions, as well as other general structural results on $Z$. The free energy
is calculated exactly for the infinite-length limit of the graphs, and the
thermodynamics is discussed. It is shown how the internal energy calculated for
the case of cylindrical boundary conditions is connected with critical
quantities for the Potts model on the infinite square lattice. Considering the
full generalization to arbitrary complex $q$ and $v$, we determine the singular
locus ${\cal B}$, arising as the accumulation set of partition function zeros
as $L_\ell \to \infty$, in the $q$ plane for fixed $v$ and in the $v$ plane for
fixed $q$.


  This paper presents a novel data-driven approach for predicting the number of
vegetation-related outages that occur in power distribution systems on a
monthly basis. In order to develop an approach that is able to successfully
fulfill this objective, there are two main challenges that ought to be
addressed. The first challenge is to define the extent of the target area. An
unsupervised machine learning approach is proposed to overcome this difficulty.
The second challenge is to correctly identify the main causes of
vegetation-related outages and to thoroughly investigate their nature. In this
paper, these outages are categorized into two main groups: growth-related and
weather-related outages, and two types of models, namely time series and
non-linear machine learning regression models are proposed to conduct the
prediction tasks, respectively. Moreover, various features that can explain the
variability in vegetation-related outages are engineered and employed. Actual
outage data, obtained from a major utility in the U.S., in addition to
different types of weather and geographical data are utilized to build the
proposed approach. Finally, by utilizing various time series models and machine
learning methods, a comprehensive case study is carried out to demonstrate how
the proposed approach can be used to successfully predict the number of
vegetation-related outages and to help decision-makers to detect vulnerable
zones in their systems.


  The Fermi Lab Liquid ARgon experiment, FLARE, a huge neutrino argon-liquid
project detector of 50 kt mass, might in a near future enlarge the neutrino
telescope accuracy revealing in detail solar, supernova, atmospheric as well as
largest solar flares neutrino. Indeed the solar energetic (E_p > 100 MeVs)
flare particles (protons, alpha) while scattering among themselves or hitting
the solar atmosphere must produce on sun prompt charged pions, whose decay (as
well as their sequent muon decays) into secondaries is source of a copious
solar neutrino "flare" (at tens or hundreds MeV energy). These brief (minutes)
neutrino "burst" at largest flare peak may overcome by three to five order of
magnitude the steady atmospheric neutrino noise on the Earth, possibly leading
to their emergence and detection above the thresholds. The largest prompt
"burst" solar neutrino flare may be detected in future FLARE neutrino detectors
both in electron and positron and possibly in its muon pair neutrino component.
Our estimate for the recent and exceptional October - November 2003 solar
flares and last January 20th 2005 exceptional flare might lead to a few events
for future FLARE or near unity for present Super-KamiokandeII. The neutrino
spectra may reflect the neutrino flavor oscillations and mixing in flight. In
neutrino detectors a surprising (correlated) muon appearance may occur while a
rarer tau appearance may even marginally take place. A comparison of the solar
neutrino flare signal with other neutrino foreground is estimated: it offer the
first opportunity for an independent road map to disentangle the neutrino
flavor puzzles, as well a prompt alarm system for dangerous solar flare
eruptions.


  This technical report considers worst-case robustness analysis of a network
of locally controlled uncertain systems with uncertain parameter vectors
belonging to the ellipsoid sets found by identification procedures. In order to
deal with computational complexity of large-scale systems, an hierarchical
robustness analysis approach is adapted to these uncertain parameter vectors
thus addressing the trade-off between the computation time and the conservatism
of the obtained result.


  Starting from the divergence pattern of perturbation expansions in Quantum
Field Theory and the (assumed) asymptotic character of the series, we address
the problem of ambiguity of a function determined by the perturbation
expansion. We consider functions represented by an integral of the
Laplace-Borel type along a general contour in the Borel complex plane. Proving
a modified form of the Watson lemma, we obtain a large class of functions
having the same asymptotic perturbation expansion. Some remarks on perturbative
QCD are made, using the particular case of the Adler function.


  We study the dynamics of the space debris in the 1:1 and 2:1 resonances,
where geosynchronous and GPS satellites are located. By using Hamiltonian
formalism, we consider a model including the geopotential contribution for
which we compute the secular and resonant expansions of the Hamiltonian.
  Within such model we are able to detect the equilibria and to study the main
features of the resonances in a very effective way. In particular, we analyze
the regular and chaotic behavior of the 1:1 and 2:1 resonant regions by
analytical methods and by computing the Fast Lyapunov Indicators, which provide
a cartography of the resonances. This approach allows us to detect easily the
location of the equilibria, the amplitudes of the libration islands and the
main dynamical stability features of the resonances, thus providing an overview
of the 1:1 and 2:1 resonant domains under the effect of Earth's oblateness.
  The results are validated by a comparison with a model developed in Cartesian
coordinates, including the geopotential, the gravitational attraction of Sun
and Moon and the solar radiation pressure.


  We consider the critical problem of distributed learning over data while
keeping it private from the computational servers. The state-of-the-art
approaches to this problem rely on quantizing the data into a finite field, so
that the cryptographic approaches for secure multiparty computing can then be
employed. These approaches, however, can result in substantial accuracy losses
due to fixed-point representation of the data and computation overflows. To
address these critical issues, we propose a novel algorithm to solve the
problem when data is in the analog domain, e.g., the field of real/complex
numbers. We characterize the privacy of the data from both
information-theoretic and cryptographic perspectives, while establishing a
connection between the two notions in the analog domain. More specifically, the
well-known connection between the distinguishing security (DS) and the mutual
information security (MIS) metrics is extended from the discrete domain to the
continues domain. This is then utilized to bound the amount of information
about the data leaked to the servers in our protocol, in terms of the DS
metric, using well-known results on the capacity of single-input
multiple-output (SIMO) channel with correlated noise. It is shown how the
proposed framework can be adopted to do computation tasks when data is
represented using floating-point numbers. We then show that this leads to a
fundamental trade-off between the privacy level of data and accuracy of the
result. As an application, we also show how to train a machine learning model
while keeping the data as well as the trained model private. Then numerical
results are shown for experiments on the MNIST dataset. Furthermore,
experimental advantages are shown comparing to fixed-point implementations over
finite fields.


  We apply Laplace method for the tree diagrams to calculate the interference
terms arising as a result of summation of particles permutations in the final
state of scattering. These terms significantly influence the values of
experimentally observed quantities. We show that the tree diagram with a single
input line and an arbitrary number of output lines has a maximum value for the
equal four-momenta of secondary particles. It means the tree diagrams of
inelastic scattering describe the formation of parton and hadron showers. We
also demonstrate the need to take into account the contributions from
interference between different showers.


  The abundance and ease of utilizing sound, along with the fact that auditory
clues reveal so much about what happens in the scene, make the audio-visual
space a perfectly intuitive choice for self-supervised representation learning.
However, the current literature suggests that training on \textit{uncurated}
data yields considerably poorer representations compared to the
\textit{curated} alternatives collected in supervised manner, and the gap only
narrows when the volume of data significantly increases. Furthermore, the
quality of learned representations is known to be heavily influenced by the
size and taxonomy of the curated datasets used for self-supervised training.
This begs the question of whether we are celebrating too early on catching up
with supervised learning when our self-supervised efforts still rely almost
exclusively on curated data. In this paper, we study the efficacy of learning
from Movies and TV Shows as forms of uncurated data for audio-visual
self-supervised learning. We demonstrate that a simple model based on
contrastive learning, trained on a collection of movies and TV shows, not only
dramatically outperforms more complex methods which are trained on orders of
magnitude larger uncurated datasets, but also performs very competitively with
the state-of-the-art that learns from large-scale curated data. We identify
that audiovisual patterns like the appearance of the main character or
prominent scenes and mise-en-sc\`ene which frequently occur through the whole
duration of a movie, lead to an overabundance of easy negative instances in the
contrastive learning formulation. Capitalizing on such observation, we propose
a hierarchical sampling policy, which despite its simplicity, effectively
improves the performance, particularly when learning from TV shows which
naturally face less semantic diversity.


  For all $1\leq m\leq n-1$, we investigate the interaction of locally finite
measures in $\mathbb{R}^n$ with the family of $m$-dimensional Lipschitz graphs.
For instance, we characterize Radon measures $\mu$, which are carried by
Lipschitz graphs in the sense that there exist graphs $\Gamma_1,\Gamma_2,\dots$
such that $\mu(\mathbb{R}^n\setminus\bigcup_1^\infty\Gamma_i)=0$, using only
countably many evaluations of the measure. This problem in geometric measure
theory was classically studied within smaller classes of measures, e.g.~for the
restrictions of $m$-dimensional Hausdorff measure $\mathcal{H}^m$ to
$E\subseteq \mathbb{R}^n$ with $0<\mathcal{H}^m(E)<\infty$. However, an example
of Cs\"{o}rnyei, K\"{a}enm\"{a}ki, Rajala, and Suomala shows that classical
methods are insufficient to detect when a general measure charges a Lipschitz
graph. To develop a characterization of Lipschitz graph rectifiability for
arbitrary Radon measures, we look at the behavior of coarse doubling ratios of
the measure on dyadic cubes that intersect conical annuli. This extends a
characterization of graph rectifiability for pointwise doubling measures by
Naples by mimicking the approach used in the characterization of Radon measures
carried by rectifiable curves by Badger and Schul.


  We present an investigation regarding the challenges faced by student teams
across four consecutive iterations of a team-focused, project-based course in
software engineering. The studied period includes the switch to fully online
activities in the spring of 2020, and covers the return to face-to-face
teaching two years later. We cover the feedback provided by over 1,500
students, collected in a free-text form on the basis of a survey. A qualitative
research method was utilized to discern and examine the challenges and
perceived benefits of a course that was conducted entirely online. We show that
technical challenges remain a constant in project-based courses, with time
management being the most affected by the move to online. Students reported
that the effective use of collaborative tools eased team organization and
communication while online. We conclude by providing a number of action points
regarding the integration of online activities in face-to-face course unfolding
related to project management, communication tools, the importance of teamwork,
and of active mentor participation.


  We consider a mortal random walker on a family of hierarchical graphs in the
presence of some trap sites. The configuration comprising the graph, the
starting point of the walk, and the locations of the trap sites is taken to be
exactly self-similar as one goes from one generation of the family to the next.
Under these circumstances, the total probability that the walker hits a trap is
determined exactly as a function of the single-step survival probability $q$ of
the mortal walker. On the $n^{\rm th}$ generation graph of the family, this
probability is shown to be given by the $n^{\rm th}$ iterate of a certain
scaling function or map $q \rightarrow f(q)$. The properties of the map then
determine, in each case, the behavior of the trapping probability, the mean
time to trapping, the temporal scaling factor governing the random walk
dimension on the graph, and other related properties. The formalism is
illustrated for the cases of a linear hierarchical lattice and the Sierpinski
graphs in $2$ and $3$ Euclidean dimensions. We find an effective reduction of
the random walk dimensionality due to the ballistic behavior of the surviving
particles induced by the mortality constraint. The relevance of this finding
for experiments involving travel times of particles in diffusion-decay systems
is discussed.


  We have developed a proper path integral formalism consistent with the
deformed version of the quantum mechanics which contains a maximum observable
length scale at the order of the Cosmological particle horizon, existing in
cosmology. First, we have presented the modifications to the classical
mechanics which shows non-minimal effects on the equation of motion of a
particle. Next, we have provided representation of the deformed quantum
mechanical algebra. With this algebra in hand, we have calculated the general
form of the path integral propagator in this deformed background. Finally, as a
most simple case, we have built up the explicit form of the free particle
propagator. The modifications to the free particle propagator shows some
non-trivial effects in this case, which can have some important significance.


  This paper proposes a sequence-to-sequence learning approach for Arabic
pronoun resolution, which explores the effectiveness of using advanced natural
language processing (NLP) techniques, specifically Bi-LSTM and the BERT
pre-trained Language Model, in solving the pronoun resolution problem in
Arabic. The proposed approach is evaluated on the AnATAr dataset, and its
performance is compared to several baseline models, including traditional
machine learning models and handcrafted feature-based models. Our results
demonstrate that the proposed model outperforms the baseline models, which
include KNN, logistic regression, and SVM, across all metrics. In addition, we
explore the effectiveness of various modifications to the model, including
concatenating the anaphor text beside the paragraph text as input, adding a
mask to focus on candidate scores, and filtering candidates based on gender and
number agreement with the anaphor. Our results show that these modifications
significantly improve the model's performance, achieving up to 81% on MRR and
71% for F1 score while also demonstrating higher precision, recall, and
accuracy. These findings suggest that the proposed model is an effective
approach to Arabic pronoun resolution and highlights the potential benefits of
leveraging advanced NLP neural models.


  Magnetic early B-type stars are rare. To identify them, we use the strongest
indirect indicator of a magnetic field in B stars, which is periodic
variability of UV stellar wind lines occurring symmetric about the approximate
rest wavelength. Probable magnetic candidates are targets for follow-up
spectropolarimetry to search for a magnetic field. From the UV wind line
variability the B1/B2V star sigma Lupi emerged as a new magnetic candidate
star. AAT spectropolarimetric measurements with SEMPOL were obtained. The
longitudinal component of the magnetic field integrated over the visible
surface of the star was determined with the Least-Squares Deconvolution method.
The UV line variations of sigma Lupi are similar to what is known in magnetic B
stars, but no periodicity could be determined. We detected a varying
longitudinal magnetic field with amplitude of about 100 G with error bars of
typically 20 G, which supports an oblique magnetic-rotator configuration. The
EW variations of the UV lines, the magnetic and the optical-line variations are
consistent with the photometric period of 3.02 d, which we identify with the
rotation period of the star. Additional observations with ESPaDOnS attached to
the CFHT confirmed this discovery, and allowed the determination of a precise
magnetic period. Analysis revealed that sigma Lupi is a He-strong star, with an
enhanced N abundance and an underabundance of C, and has a chemically spotted
surface. Like in other magnetic B stars the UV wind emission appears to
originate close to the magnetic equatorial plane, with maximum emission when a
magnetic pole points towards the Earth. The 3.01972(43) d magnetic rotation
period is consistent with the photometric period, with maximum light
corresponding to maximum magnetic field.


  Just as classical information systems require buffers and memory, the same is
true for quantum information systems. The potential that optical quantum
information processing holds for revolutionising computation and communication
is therefore driving significant research into developing optical quantum
memory. A practical optical quantum memory must be able to store and recall
quantum states on demand with high efficiency and low noise. Ideally, the
platform for the memory would also be simple and inexpensive. Here, we present
a complete tomographic reconstruction of quantum states that have been stored
in the ground states of rubidium in a vapour cell operating at around 80$^o$C.
Without conditional measurements, we show recall fidelity up to 98% for
coherent pulses containing around one photon. In order to unambiguously verify
that our memory beats the quantum no-cloning limit we employ state independent
verification using conditional variance and signal transfer coefficients.


  By exploiting the fact that conservation laws form the kernel of a discrete
Euler operator, we use a recently introduced symbolic-numeric approach to
construct a new class of finite difference methods for the modified Korteweg-de
Vries (mKdV) equation, that preserve the local conservation laws of mass and
energy.


  We present a nanoparticle size-separation device based on a nanofluidic
rocking Brownian motor. It features a ratchet-shaped electrostatic particle
potential with increasing barrier heights along the particle transport
direction. The sharp drop of the particle current with barrier height is
exploited to separate a particle suspension into multiple sub-populations. By
solving the Fokker--Planck equation, we show that the physics of the separation
mechanism is governed by the energy landscape under forward tilt of the
ratchet. For a given device geometry and sorting duration, the applied force is
thus the only tunable parameter to increase the separation resolution. For the
experimental conditions of 3.5 V applied voltage and 20 s sorting, we predict a
separation resolution of $\sim 2$ nm, supported by experimental data for
separating spherical gold particles of nominal 80 and 100 nm diameters.


  The Ly-alpha emission line has been proven a powerful tool by which to study
evolving galaxies at the highest redshifts. However, in order to use Lya as a
physical probe of galaxies, it becomes vital to know the Lya escape fraction
(fescLya). Unfortunately, due to the resonant nature of Lya, fescLya may vary
unpredictably and requires empirical measurement. Here we compile Lya
luminosity functions between redshift z=0 and 8 and, combined with H-alpha and
ultraviolet data, assess how fescLya evolves with redshift. We find a strong
upwards evolution in fescLya over the range z=0.3-6, which is well-fit by the
power-law fescLya \propto (1+z)^\xi, with \xi =(2.57_-0.12^+0.19). This
predicts that fescLya should reach unity at z=11.1. By comparing fescLya and
E(B-V) in individual galaxies we derive an empirical relationship between
fescLya and E(B-V), which includes resonance scattering and can explain the
redshift evolution of fescLya between z=0 and 6 purely as a function of the
evolution in the dust content of galaxies. Beyond z~6.5, fescLya drops more
substantially; an effect attributed to either ionizing photon leakage, or an
increase in the neutral gas fraction of the intergalactic medium. While
distinguishing between those two scenarios may be extremely challenging, by
framing the problem this way we remove the uncertainty of the halo mass from
Lya-based tests of reionization. We finally derive a new method by which to
estimate the dust content of galaxies based purely upon the observed Lya and UV
LFs. These data are characterized by an exponential with an e-folding redshift
of ~3.5.


  A class of sufficient conditions of local regularity for suitable weak
solutions to the nonstationary three-dimensional Navier-Stokes equations are
discussed. The corresponding results are formulated in terms of functionals
which are invariant with respect to the Navier-Stokes equations scaling. The
famous Caffarelli-Kohn-Nirenberg condition is contained in that class as a
particular case.


  We study ${\cal N}=2$ compactifications of $E_8\times E_8$ heterotic string
theory on orbifolds of $K3 \times T^2$ by $g'$ which acts as an $\mathbb{Z}_N$
automorphism of $K3$ together with a$1/N$ shift on a circle of $T^2$. The
orbifold action $g'$ corresponds to the $26$ conjugacy classes of the Mathieu
group $M_{24}$. We show that for the standard embedding the new supersymmetric
index for these compactifications can always be decomposed into the elliptic
genus of $K3$ twisted by $g'$. The difference in one-loop corrections to the
gauge couplings are captured by automorphic forms obtained by the theta lifts
of the elliptic genus of $K3$ twisted by $g'$. We work out in detail the case
for which $g'$ belongs to the equivalence class $2B$. We then investigate all
the non-standard embeddings for$K3$ realized as a $T^4/\mathbb{Z}_\nu$ orbifold
with $\nu = 2, 4$ and $g'$ the $2A$ involution. We show that for non-standard
embeddings the new supersymmetric index as well as the difference in one-loop
corrections to the gauge couplings are completely characterized by the
instanton numbers of the embeddings together with the difference in number of
hypermultiplets and vector multiplets in the spectrum.


  Bayes linear analysis and approximate Bayesian computation (ABC) are
techniques commonly used in the Bayesian analysis of complex models. In this
article we connect these ideas by demonstrating that regression-adjustment ABC
algorithms produce samples for which first and second order moment summaries
approximate adjusted expectation and variance for a Bayes linear analysis. This
gives regression-adjustment methods a useful interpretation and role in
exploratory analysis in high-dimensional problems. As a result, we propose a
new method for combining high-dimensional, regression-adjustment ABC with
lower-dimensional approaches (such as using MCMC for ABC). This method first
obtains a rough estimate of the joint posterior via regression-adjustment ABC,
and then estimates each univariate marginal posterior distribution separately
in a lower-dimensional analysis. The marginal distributions of the initial
estimate are then modified to equal the separately estimated marginals, thereby
providing an improved estimate of the joint posterior. We illustrate this
method with several examples. Supplementary materials for this article are
available online.


  Black Phosphorus (bP) has emerged as an interesting addition to the category
of two-dimensional materials. Surface-science studies on this material are of
great interest, but they are hampered by bP's high reactivity to oxygen and
water, a major challenge to scanning tunneling microscopy (STM) experiments. As
a consequence, the large majority of these studies were performed by cleaving a
bulk crystal in situ. Here we present a study of surface modifications on
exfoliated bP flakes upon consecutive annealing steps, up to 550 C, well above
the sublimation temperature of bP. In particular, our attention is focused on
the temperature range 375 C - 400 C, when sublimation starts, and a controlled
desorption from the surface occurs alongside with the formation of
characteristic well-aligned craters. There is an open debate in the literature
about the crystallographic orientation of these craters, whether they align
along the zigzag or the armchair direction. Thanks to the atomic resolution
provided by STM, we are able to identify the orientation of the craters with
respect to the bP crystal: the long axis of the craters is aligned along the
zigzag direction of bP. This allows us to solve the controversy, and, moreover,
to provide insight in the underlying desorption mechanism leading to crater
formation.


  Symmetric functions, which take as input an unordered, fixed-size set, are
known to be universally representable by neural networks that enforce
permutation invariance. These architectures only give guarantees for fixed
input sizes, yet in many practical applications, including point clouds and
particle physics, a relevant notion of generalization should include varying
the input size. In this work we treat symmetric functions (of any size) as
functions over probability measures, and study the learning and representation
of neural networks defined on measures. By focusing on shallow architectures,
we establish approximation and generalization bounds under different choices of
regularization (such as RKHS and variation norms), that capture a hierarchy of
functional spaces with increasing degree of non-linear learning. The resulting
models can be learned efficiently and enjoy generalization guarantees that
extend across input sizes, as we verify empirically.


  Massive stars end their lives in spectacular supernova explosions.
Identifying the progenitor star is a test of stellar evolution and explosion
models. Here we show that the progenitor star of the supernova SN 2008bk has
now disappeared, which provides conclusive evidence that this was the death of
a red supergiant star.


  Investigating the implications of interlayer coupling on superconductivity is
essential for comprehending the intrinsic mechanisms of high temperature
superconductors. Van der Waals heterojunctions have attracted extensive
research due to their exotic interlayer coupling. Here, we present a natural
heterojunction superconductor of 6R-TaS2 that demonstrates a double-dome of
superconductivity, in addition to, the reemergence of superconducting under
high pressures. Our first principles calculation shows that the first dome of
superconductivity in 6R-TaS2 can be attributed to changes in interlayer
coupling and charge transfer. The second superconducting dome and the
reemergence of superconductivity can be ascribed to changes in the density of
states resulting from Fermi surface reconstruction, in which the DOS of T-layer
and S p-orbitals play a crucial role. We have reported the first observation in
TMDs that non-metallic atoms playing a dominant role in the reemergence of
superconducting and the influence of two Lifshitz transitions on
superconducting properties.


  An exact formula for partition functions in 3d field theories was recently
suggested by Jafferis, and Hama, Hosomichi, and Lee. These functions are
expressed in terms of specific $q$-hypergeometric integrals whose key building
block is the double sine function (or the hyperbolic gamma function). Elliptic
hypergeometric integrals, discovered by the second author, define 4d
superconformal indices. Using their reduction to the hyperbolic level, we
describe a general scheme of reducing 4d superconformal indices to 3d partition
functions which imply an efficient way of getting 3d $\mathcal{N}=2$
supersymmetric dualities for both SYM and CS theories from the "parent" 4d
$\mathcal{N}=1$ dualities for SYM theories. As an example, we consider
explicitly the duality pattern for 3d $\mathcal{N}=2$ SYM and CS theories with
SP(2N) gauge group with the antisymmetric tensor matter.


  To learn (statistical) dependencies among random variables requires
exponentially large sample size in the number of observed random variables if
any arbitrary joint probability distribution can occur.
  We consider the case that sparse data strongly suggest that the probabilities
can be described by a simple Bayesian network, i.e., by a graph with small
in-degree \Delta. Then this simple law will also explain further data with high
confidence. This is shown by calculating bounds on the VC dimension of the set
of those probability measures that correspond to simple graphs. This allows to
select networks by structural risk minimization and gives reliability bounds on
the error of the estimated joint measure without (in contrast to a previous
paper) any prior assumptions on the set of possible joint measures.
  The complexity for searching the optimal Bayesian networks of in-degree
\Delta increases only polynomially in the number of random varibales for
constant \Delta and the optimal joint measure associated with a given graph can
be found by convex optimization.


  Phase interfaces in melting and solidification processes are strongly
affected by the presence of convection in the liquid. One way of modeling their
transient evolution is to couple an incompressible flow model to an energy
balance in enthalpy formulation. Two strong nonlinearities arise, which account
for the viscosity variation between phases and the latent heat of fusion at the
phase interface.
  The resulting coupled system of PDE's can be solved by a single-domain
semi-phase-field, variable viscosity, finite element method with monolithic
system coupling and global Newton linearization. A robust computational model
for realistic phase-change regimes furthermore requires a flexible
implementation based on sophisticated mesh adaptivity. In this article, we
present first steps towards implementing such a computational model into a
simulation tool which we call Phaseflow.
  Phaseflow utilizes the finite element software FEniCS, which includes a
dual-weighted residual method for goal-oriented adaptive mesh refinement.
Phaseflow is an open-source, dimension-independent implementation that, upon an
appropriate parameter choice, reduces to classical benchmark situations
including the lid-driven cavity and the Stefan problem. We present and discuss
numerical results for these, an octadecane PCM convection-coupled melting
benchmark, and a preliminary 3D convection-coupled melting example,
demonstrating the flexible implementation. Though being preliminary, the latter
is, to our knowledge, the first published 3D result for this method. In our
work, we especially emphasize reproducibility and provide an easy-to-use
portable software container using Docker.


  We introduce and completely describe the analogues of the Riemann curvature
tensor for the curved supergrassmannian of the passing through the origin
(0|2)-dimensional subsupermanifolds in the (0|4)-dimensional supermanifold with
the preserved volume form. The underlying manifold of this supergrassmannian is
the conventional Penrose's complexified and compactified version of the
Minkowski space, i.e., the Grassmannian of 2-dimensional subspaces in the
4-dimensional space. The result provides with yet another counterexample to
Coleman-Mandula's theorem.


  We consider a problem which may be viewed as an inverse one to the Schwinger
realization of Lie algebra, and suggest a procedure of deforming the
so-obtained algebra. We illustrate the method through a few simple examples
extending Schwinger's $su(1,1)$ construction. As results, various q-deformed
algebras are (re-)produced as well as their undeformed counterparts. Some
extensions of the method are pointed out briefly.


  We develop a stochastic approach to time-dependent DFT with optimally-tuned
range-separated hybrids containing non-local exchange, for calculating optical
spectra. The attractive electron-hole interaction, which leads to the formation
of excitons, is included through a time-dependent linear-response technique
with a non-local exchange interaction which is computed very efficiently
through a stochastic scheme. The method is inexpensive and scales quadratically
with the number of electrons, at almost the same (low) cost of time dependent
Kohn-Sham (TDKS) with local functionals. Our results are in excellent agreement
with experimental data and the efficiency of the approach is demonstrated on
large finite phosphorene sheets containing up to 1958 valence electrons.


  In this talk I will review the recent experimental status of $\sigma(e^+ e^-
\to hadrons)$ at $\sqrt{s}<10 GeV$ and the prospects for the future. The
influence on $\alpha_{QED}(M^2_{Z})$ and $(g-2)_{\mu}$ is also discussed.


  These are the very unpretentious lecture notes for the minicourse
"Introduction to evolution equations in Geometry," a part of the Brazilian
Colloquium of Mathematics held at IMPA, in July of 2009.


  This paper presents a new measure of entanglement which can be employed for
multipartite entangled systems. The classification of multipartite entangled
systems based on this measure is considered. Two approaches to applying this
measure to mixed quantum states are discussed.


  GNNs have been proven to perform highly effective in various node-level,
edge-level, and graph-level prediction tasks in several domains. Existing
approaches mainly focus on static graphs. However, many graphs change over time
with their edge may disappear, or node/edge attribute may alter from one time
to the other. It is essential to consider such evolution in representation
learning of nodes in time varying graphs. In this paper, we propose a Temporal
Multi-layered Position-aware Graph Neural Network (TMP-GNN), a node embedding
approach for dynamic graph that incorporates the interdependence of temporal
relations into embedding computation. We evaluate the performance of TMP-GNN on
two different representations of temporal multilayered graphs. The performance
is assessed against the most popular GNNs on node-level prediction tasks. Then,
we incorporate TMP-GNN into a deep learning framework to estimate missing data
and compare the performance with their corresponding competent GNNs from our
former experiment, and a baseline method. Experimental results on four
real-world datasets yield up to 58% of lower ROC AUC for pairwise node
classification task, and 96% of lower MAE in missing feature estimation,
particularly for graphs with a relatively high number of nodes and lower mean
degree of connectivity.


  The world's leading directional dark matter experiments currently all utilize
low-pressure gas Time Projection Chamber (TPC) technologies. We discuss some of
the challenges for this technology, for which balancing the goal of achieving
the best sensitivity with that of cost effective scale-up requires optimization
over a large parameter space. Critical for this are the precision measurements
of the fundamental properties of both electron and nuclear recoil tracks down
to the lowest detectable energies. Such measurements are necessary to provide a
benchmark for background discrimination and directional sensitivity that could
be used for future optimization studies for directional dark matter
experiments. In this paper we describe a small, high resolution, high signal-
to-noise GEM-based TPC with a 2D CCD readout designed for this goal. The
performance of the detector was characterized using alpha particles, X-rays,
gamma-rays, and neutrons, enabling detailed measurements of electron and
nuclear recoil tracks. Stable effective gas gains of greater than $1 \times
10^5$ were obtained in 100 Torr of pure CF$_4$ by a cascade of three standard
CERN GEMs each with a 140 $\mu$m pitch. The high signal-to-noise and
sub-millimeter spatial resolution of the GEM amplification and CCD readout,
together with low diffusion, allow for excellent background discrimination
between electron and nuclear recoils down below $\sim$10 keVee ($\sim$23 keVr
fluorine recoil). Even lower thresholds, necessary for the detection of low
mass WIMPs for example, might be achieved by lowering the pressure and
utilizing full 3D track reconstruction. These and other paths for improvements
are discussed, as are possible fundamental limitations imposed by the physics
of energy loss.


  In this work we consider non-zero circular polarization for the CMB radiation
as a result of new interactions. We then rewrite the Boltzmann equations for
the Stokes parameters $Q$, $U$ and $V$ and show that the circular polarization
can generate the B-mode polarization even if no tensor perturbations are
present.


  Let $\theta, \theta'$ be irrational numbers and $A, B$ be matrices in
$SL_2(\mathbb{Z})$ of infinite order. We compute the $K$-theory of the crossed
product $\mathcal{A}_{\theta}\rtimes_A \mathbb{Z}$ and show that
$\mathcal{A}_{\theta} \rtimes_A\mathbb{Z}$ and $\mathcal{A}_{\theta'} \rtimes_B
\mathbb{Z}$ are $*$-isomorphic if and only if $\theta = \pm\theta'
\pmod{\mathbb{Z}}$ and $I-A^{-1}$ is matrix equivalent to $I-B^{-1}$. Combining
this result and an explicit construction of equivariant bimodules, we show that
$\mathcal{A}_{\theta} \rtimes_A\mathbb{Z}$ and $\mathcal{A}_{\theta'} \rtimes_B
\mathbb{Z}$ are Morita equivalent if and only if $\theta$ and $\theta'$ are in
the same $GL_2(\mathbb{Z})$ orbit and $I-A^{-1}$ is matrix equivalent to
$I-B^{-1}$. Finally, we determine the Morita equivalence class of
$\mathcal{A}_{\theta} \rtimes F$ for any finite subgroup $F$ of
$SL_2(\mathbb{Z})$.


  We report the initial results of a survey for intracluster planetary nebulae
in the Virgo Cluster. In two 16' x 16' fields, we identify 69 and 16
intracluster planetary nebula candidates, respectively. In a third 16' x 16'
field near the central elliptical galaxy M87, we detect 75 planetary nebula
candidates, of which a substantial fraction are intracluster in nature. By
examining the number of the planetaries detected in each field and the shape of
the planetary nebula luminosity function, we show that 1) the intracluster
starlight of Virgo is distributed non-uniformly, and varies between subclumps A
and B, 2) the Virgo Cluster core extends ~3 Mpc in front of M87, and thus is
elongated along the line-of-sight, and 3) a minimum of 22% of Virgo's stellar
luminosity resides between the galaxies in our fields, and that the true number
may be considerably larger. We also use our planetary nebula data to argue that
the intracluster stars in Virgo are likely derived from a population that is of
moderate age and metallicity.


  Eye gaze analysis is an important research problem in the field of Computer
Vision and Human-Computer Interaction. Even with notable progress in the last
10 years, automatic gaze analysis still remains challenging due to the
uniqueness of eye appearance, eye-head interplay, occlusion, image quality, and
illumination conditions. There are several open questions, including what are
the important cues to interpret gaze direction in an unconstrained environment
without prior knowledge and how to encode them in real-time. We review the
progress across a range of gaze analysis tasks and applications to elucidate
these fundamental questions, identify effective methods in gaze analysis, and
provide possible future directions. We analyze recent gaze estimation and
segmentation methods, especially in the unsupervised and weakly supervised
domain, based on their advantages and reported evaluation metrics. Our analysis
shows that the development of a robust and generic gaze analysis method still
needs to address real-world challenges such as unconstrained setup and learning
with less supervision. We conclude by discussing future research directions for
designing a real-world gaze analysis system that can propagate to other domains
including Computer Vision, Augmented Reality (AR), Virtual Reality (VR), and
Human Computer Interaction (HCI). Project Page:
https://github.com/i-am-shreya/EyeGazeSurvey}{https://github.com/i-am-shreya/EyeGazeSurvey


  The Segment Anything Model (SAM) stands as a foundational framework for image
segmentation. While it exhibits remarkable zero-shot generalization in typical
scenarios, its advantage diminishes when applied to specialized domains like
medical imagery and remote sensing. To address this limitation, this paper
introduces Conv-LoRA, a simple yet effective parameter-efficient fine-tuning
approach. By integrating ultra-lightweight convolutional parameters into
Low-Rank Adaptation (LoRA), Conv-LoRA can inject image-related inductive biases
into the plain ViT encoder, further reinforcing SAM's local prior assumption.
Notably, Conv-LoRA not only preserves SAM's extensive segmentation knowledge
but also revives its capacity of learning high-level image semantics, which is
constrained by SAM's foreground-background segmentation pretraining.
Comprehensive experimentation across diverse benchmarks spanning multiple
domains underscores Conv-LoRA's superiority in adapting SAM to real-world
semantic segmentation tasks.


  Task-oriented parsing (TOP) aims to convert natural language into
machine-readable representations of specific tasks, such as setting an alarm. A
popular approach to TOP is to apply seq2seq models to generate linearized parse
trees. A more recent line of work argues that pretrained seq2seq models are
better at generating outputs that are themselves natural language, so they
replace linearized parse trees with canonical natural-language paraphrases that
can then be easily translated into parse trees, resulting in so-called
naturalized parsers. In this work we continue to explore naturalized semantic
parsing by presenting a general reduction of TOP to abstractive question
answering that overcomes some limitations of canonical paraphrasing.
Experimental results show that our QA-based technique outperforms
state-of-the-art methods in full-data settings while achieving dramatic
improvements in few-shot settings.


  Image search is an essential and user-friendly method to explore vast
galleries of digital images. However, existing image search methods heavily
rely on proximity measurements like tag matching or image similarity, requiring
precise user inputs for satisfactory results. To meet the growing demand for a
contemporary image search engine that enables accurate comprehension of users'
search intentions, we introduce an innovative user intent expansion framework.
Our framework leverages visual-language models to parse and compose multi-modal
user inputs to provide more accurate and satisfying results. It comprises
two-stage processes: 1) a parsing stage that incorporates a language parsing
module with large language models to enhance the comprehension of textual
inputs, along with a visual parsing module that integrates an interactive
segmentation module to swiftly identify detailed visual elements within images;
and 2) a logic composition stage that combines multiple user search intents
into a unified logic expression for more sophisticated operations in complex
searching scenarios. Moreover, the intent expansion framework enables users to
perform flexible contextualized interactions with the search results to further
specify or adjust their detailed search intents iteratively. We implemented the
framework into an image search system for NFT (non-fungible token) search and
conducted a user study to evaluate its usability and novel properties. The
results indicate that the proposed framework significantly improves users'
image search experience. Particularly the parsing and contextualized
interactions prove useful in allowing users to express their search intents
more accurately and engage in a more enjoyable iterative search experience.


  We have studied the evolution with temperature of the local as well as the
average crystal structure of MgB$_2$ using the real-space atomic pair
distribution function (PDF) measured by high resolution neutron powder
diffraction. We have investigated the correlations of the B-B and B-Mg nearest
neighbor pair motion by comparing, in the wide temperature range from T=10 K up
to T=600 K, the mean-square displacements (MSD) of single atoms with the
mean-square relative displacements (MSRD) obtained from the PDF peak
linewidths. The results show that the single atom B and Mg vibrations are
mostly decoupled from each other, with a small predominance of positive (in
phase) correlation factor for both the B-B and B-Mg pairs. The small positive
correlation is almost temperature independent, in contrast with our theoretical
calculations; this can be a direct consequence of the strong decay processes of
the $E_{2g}$ anharmonic phonons.


  We consider the thermal response of a (3+1)-dimensional theory with a chiral
anomaly on a curved space motivated by the chiral magnetic effect. We find a
new phenomenon, called the chiral heat effect, such that the thermal current is
induced transverse to a gradient of the temperature even on a flat space. This
effect is expected to be observed in QCD experiment as well as the chiral
magnetic effect. We study a similar topological effect on the spacetime with a
torsion. A holographic construction is also discussed with the D3/D7 and the
Sakai-Sugimoto models.


  The selective adsorption of a corrosive gas, SO$_2$, into two microporous
pillared paddle-wheel frameworks M(bdc)(ted)0.5 [M = Ni, Zn; bdc =
1,4-benzenedicarboxylate; ted = triethylenediamine] is studied by volumetric
adsorption measurements and a combination of in-situ infrared spectroscopy and
ab initio density functional theory (DFT) calculations. The uptake of SO$_2$ in
M(bdc)(ted)0.5 at room temperature is quite significant, 9.97 mol/kg at 1.13
bar. The major adsorbed SO$_2$ molecules contributing to the isotherm
measurements are characterized by stretching bands at 1326 and 1144 cm$^{-1}$.
Theoretical calculations including van der Waals interactions (based on vdW-DF)
suggest that two adsorption configurations are possible for these SO$_2$
molecules. One geometry involves an SO$_2$ molecule bonded through its sulfur
atom to the oxygen atom of the paddle-wheel building unit and its two oxygen
atoms to the C-H groups of the organic linkers by formation of hydrogen bonds.
Such a configuration results in a distortion of the benzene rings, which is
consistent with the experimentally observed shift of the ring deformation mode.
In the other geometry, SO$_2$ establishes hydrogen bonding with -CH$_2$ group
of the ted linker through its two oxygen atoms simultaneously. The
vdW-DF-simulated frequency shifts of the SO$_2$ stretching bands in these two
configurations are similar and in good agreement with spectroscopically
measured values of physisorbed SO$_2$.In addition, the IR spectra reveal the
presence of another minor species, characterized by stretching modes at 1242
and 1105 cm$^{-1}$ and causing significant perturbations of MOFs vibrational
modes (CH$_x$ and carboxylate groups). This species is more strongly bound,
requiring a higher temperature ($\sim$150 $^\circ$C) to remove it than for the
main physisorbed species.


  The effects of core polarization and tensor coupling on the magnetic moments
in $^{13}_\Lambda$C, $^{17}_\Lambda$O, and $^{41}_\Lambda$Ca
$\Lambda$-hypernuclei are studied in the Dirac equation with scalar, vector and
tensor potentials. It is found that the effect of core polarization on the
magnetic moments is suppressed by $\Lambda$ tensor coupling. The $\Lambda$
tensor potential reduces the spin-orbit splitting of $p_\Lambda$ states
considerably. However, almost the same magnetic moments are obtained using the
hyperon wave function obtained via the Dirac equation either with or without
the $\Lambda$ tensor potential in the electromagnetic current vertex. The
deviations of magnetic moments for $p_\Lambda$ states from the Schmidt values
are found to increase with nuclear mass number.


  We prove the asymptotic formulae for several moments of derivatives of GL(2)
L-functions over quadratic twists. The family of L-functions we consider has
root number fixed to -1 and odd orthogonal symmetry. Assuming GRH we prove the
asymptotic formulae for (1) the second moment with one secondary term, (2) the
moment of two distinct modular forms f and g and (3) the first moment with
controlled weight and level dependence. We also include some immediate
corollaries to elliptic curves via the modularity theorem and the work of Gross
and Zagier.


  Nonlinearity continuation method, applied to boundary value problems for
steady-state Richards equation, gradually approaches the solution through a
series of intermediate problems. Originally, the Newton method with simple line
search algorithm was used to solve the intermediate problems. In this paper,
other solvers such as Picard and mixed Picard-Newton methods are considered,
combined with slightly modified line search approach. Numerical experiments are
performed with advanced finite volume discretizations on model and real-life
problems.


  This is a review aimed at a physics audience on the relation between Poisson
sigma models on surfaces with boundary and deformation quantization. These
models are topological open string theories. In the classical Hamiltonian
approach, we describe the reduced phase space and its structures (symplectic
groupoid), explaining in particular the classical origin of the
non-commutativity of the string end-point coordinates. We also review the
perturbative Lagrangian approach and its connection with Kontsevich's star
product. Finally we comment on the relation between the two approaches.


  The Kaon physics program at CERN will be shortly presented, addressing the
most recent results from the NA48/2 and NA62 experiments at the CERN SPS and
future prospects.


  Frozen percolation on the binary tree was introduced by Aldous around fifteen
years ago, inspired by sol-gel transitions. We investigate a version of the
model on the triangular lattice, where connected components stop growing
("freeze") as soon as they contain at least $N$ vertices, for some parameter $N
\geq 1$.
  This process has a substantially different behavior from the diameter-frozen
process, studied in previous works: in particular, we show that many (more and
more as $N \to \infty$) frozen clusters surrounding the origin appear
successively, each new cluster having a diameter much smaller than the previous
one. This separation of scales is instrumental, and it helps to approximate the
process in sufficiently large (but not too large), as a function of $N$, finite
domains by a Markov chain. This allows us to establish a deconcentration
property for the sizes of the holes of the frozen clusters around the origin.
  For the full-plane process, we then show that it can be compared to the
process in large finite domains, so that the deconcentration property also
holds in this case. In particular, we obtain that with high probability (as $N
\to \infty$), the origin does not belong to a frozen cluster in the final
configuration.
  This work requires new properties for near-critical percolation, which we
develop along the way, and which are interesting in their own right: in
particular, an asymptotic formula involving the percolation probability
$\theta(p)$ as $p \searrow p_c$, and regularity properties for large holes in
the infinite cluster. Volume-frozen percolation also gives insight into
forest-fire processes, where lightning hits independently each tree with a
small rate, and burns its entire connected component immediately.


  Polar codes based on $2\times2$ non-binary kernels are discussed in this
work. The kernel over $\text{GF}(q)$ is selected by maximizing the polarization
effect and using Monte-Carlo simulation. Belief propagation (BP) and successive
cancellation (SC) based decoding algorithms are extended to non-binary codes.
Additionally, a successive cancellation list (SCL) decoding with a pruned tree
is proposed. Simulation results show that the proposed decoder performs very
close to a conventional SCL decoder with significantly lower complexity.