  Using methods previously developed by Kelbg and others for creating effective
potentials for electron-ion plasmas, we investigate quarkonium potentials above
deconfinement. Using results for the internal energy of a static
quark-antiquark pair, a set of effective potentials are constructed that take
into account quantum effects and symmetry conditions. Bound state effects are
explicitly included in order to account for the strongly coupled nature of
plasmas. It is hoped that these effective potentials will be useful in
simulations of heavy quarks or plasma quasiparticles when the dynamics is
treated classically.


  We consider a general class of sharp $L^p$ Hardy inequalities in $\R^N$
involving distance from a surface of general codimension $1\leq k\leq N$. We
show that we can succesively improve them by adding to the right hand side a
lower order term with optimal weight and best constant. This leads to an
infinite series improvement of $L^p$ Hardy inequalities.


  We study the topology of admissible-loop spaces on a step-two Carnot group G.
We use a Morse-Bott theory argument to study the structure and the number of
geodesics on G connecting the origin with a 'vertical' point (geodesics are
critical points of the 'Energy' functional, defined on the loop space). These
geodesics typically appear in families (critical manifolds). Letting the energy
grow, we obtain an upper bound on the number of critical manifolds with energy
bounded by s: this upper bound is polynomial in s of degree l (the corank of
the distribution). Despite this evidence, we show that Morse-Bott inequalities
are far from sharp: the topology (i.e. the sum of the Betti numbers) of the
loop space filtered by the energy grows at most as a polynomial in s of degree
l-1. In the limit for s at infinity, all Betti numbers (except the zeroth) must
actually vanish: the admissible-loop space is contractible. In the case the
corank l=2 we compute exactly the leading coefficient of the sum of the Betti
numbers of the admissible-loop space with energy less than s. This coefficient
is expressed by an integral on the unit circle depending only on the
coordinates of the final point and the structure constants of the Lie algebra
of G.


  The design, accurate preparation and manipulation of quantum states in
quantum circuits are essential operational tasks at the heart of quantum
technologies. Nowadays, circuits can be designed with physical parameters that
can be controlled with unprecedented accuracy and flexibility. However, the
generation of well-controlled current states is still a nagging bottleneck,
especially when different circuit elements are integrated together. In this
work, we show how machine learning can effectively address this challenge and
outperform the current existing methods. To this end, we exploit deep
reinforcement learning to prepare prescribed quantum current states in circuits
composed of lumped elements. To highlight our method, we show how to engineer
bosonic persistent currents as they are relevant in different quantum
technologies as cold atoms and superconducting circuits. We demonstrate the use
of deep reinforcement learning to re-discover established protocols, as well as
solve configurations that are difficult to treat with other methods. With our
approach, quantum current states characterised by a single winding number or
entangled currents of multiple winding numbers can be prepared in a robust
manner, superseding the existing protocols.


  We analyze the role of spatial electronic correlations and, in particular, of
the magnetic fluctuations in Mott insulators. A half-filled Hubbard model is
solved at large strength of the repulsion U on a two-dimensional square lattice
using an advanced diagrammatic non-perturbative approach capable of going
beyond Hartree-Fock and single-site dynamical mean-field theories. We show that
at high temperatures the magnetic fluctuations are weak, and the electronic
self-energy of the system is mainly local and is well reproduced by the atomic
(Hubbard-I) approximation. Lowering the temperature toward the low-temperature
magnetically ordered phase, the non-locality of the self-energy becomes crucial
in determining the momentum-dispersion of the Hubbard bands and the Green's
function zeros. We therefore establish a precise link between Luttinger
surface, non-local correlations and spectral properties of the Hubbard bands.


  Inspired by work of McMullen, we show that any orbit of the diagonal group in
the space of lattices accumulates on the set of stable lattices. As
consequences, we settle a conjecture of Ramharter concerning the asymptotic
behaviour of the Mordell constant, and reduce Minkowski's conjecture on
products of linear forms to a geometric question, yielding two new proofs of
the conjecture in dimensions up to 7.


  We discuss the recent paper by Inan and Ugurlu [Inan I.E., Ugurlu Y.,
Exp-function method for the exact solutions of fifth order KdV equation and
modified Burgers equation, Appl. Math. Comp. 217 (2010) 1294 -- 1299]. We
demonstrate that all exact solutions of fifth order KdV equation and modified
Burgers equation by Inan and Ugurlu are trivial solutions that are reduced to
constants. Moreover, we show exact solutions of the fifth -- order equation
studied by Inan and Ugurlu cannot be found by the Exp-function method.


  In our recent paper [1], we explored a prospect of discovering the heavy
Majorana right-handed neutrinos (RHNs) at the future LHC in the context of the
minimal non-exotic U(1) extended Standard Model (SM), where a pair of RHNs are
created via decay of resonantly produced massive U(1) gauge boson
($Z^{\prime}$). We pointed out that this model can yield a significant
enhancement of the branching ratio of the $Z^\prime$ boson to a pair of RHNs,
which is crucial for discovering the RHNs under the very severe LHC Run-2
constraint from the search for the $Z^\prime$ boson with dilepton final states.
In this paper, we perform a general parameter scan to evaluate the maximum
production rate of the same-sign dilepton final states (smoking gun signature
of Majorana RHNs production) at the LHC, while reproducing the neutrino
oscillation data. We also consider the minimal non-exotic U(1) model with an
alternative charge assignment. In this case, we find a further enhancement of
the branching ratio of the $Z^\prime$ boson to a pair of RHNs compared to the
conventional case, which opens up a possibility of discovering the RHNs even
before the $Z^\prime$ boson at the future LHC experiment.


  We introduce a new deep learning architecture for predicting price movements
from limit order books. This architecture uses a causal convolutional network
for feature extraction in combination with masked self-attention to update
features based on relevant contextual information. This architecture is shown
to significantly outperform existing architectures such as those using
convolutional networks (CNN) and Long-Short Term Memory (LSTM) establishing a
new state-of-the-art benchmark for the FI-2010 dataset.


  Traditional frameworks for dynamic graphs have relied on processing only the
stream of edges added into or deleted from an evolving graph, but not any
additional related information such as the degrees or neighbor lists of nodes
incident to the edges. In this paper, we propose a new edge sampling framework
for big-graph analytics in dynamic graphs which enhances the traditional model
by enabling the use of additional related information. To demonstrate the
advantages of this framework, we present a new sampling algorithm, called Edge
Sample and Discard (ESD). It generates an unbiased estimate of the total number
of triangles, which can be continuously updated in response to both edge
additions and deletions. We provide a comparative analysis of the performance
of ESD against two current state-of-the-art algorithms in terms of accuracy and
complexity. The results of the experiments performed on real graphs show that,
with the help of the neighborhood information of the sampled edges, the
accuracy achieved by our algorithm is substantially better. We also
characterize the impact of properties of the graph on the performance of our
algorithm by testing on several Barabasi-Albert graphs.


  In sensor array beamforming methods, a class of algorithms commonly used to
estimate the position of a radiating source, the diagonal loading of the
beamformer covariance matrix is generally used to improve computational
accuracy and localization robustness. This paper proposes a diagonal unloading
(DU) method which extends the conventional response power beamforming method by
imposing an additional constraint to the covariance matrix of the array output
vector. The regularization is obtained by subtracting a given amount of white
noise from the main diagonal of the covariance matrix. Specifically, the DU
beamformer aims at subtracting the signal subspace from the noisy signal space
and it is computed by constraining the regularized covariance matrix to be
negative definite. It is hence a data-dependent covariance matrix conditioning
method. We show how to calculate precisely the unloading parameter, and we
present an eigenvalue analysis for comparing the proposed DU beamforming, the
minimum variance distortionless response (MVDR) filter and the multiple signal
classification (MUSIC) method. Theoretical analysis and experiments with
acoustic sources demonstrate that the DU beamformer localization performance is
comparable to that of MVDR and MUSIC. Since the DU beamformer computational
cost is comparable to that of a conventional beamformer, the proposed method
can be attractive in array processing due to its simplicity, effectiveness and
computational efficiency.


  We derive upper and lower bounds on the fidelity susceptibility in terms of
macroscopic thermodynamical quantities, like susceptibilities and thermal
average values. The quality of the bounds is checked by the exact expressions
for a single spin in an external magnetic field. Their usefulness is
illustrated by two examples of many-particle models which are exactly solved in
the thermodynamic limit: the Dicke superradiance model and the single impurity
Kondo model. It is shown that as far as divergent behavior is considered, the
fidelity susceptibility and the thermodynamic susceptibility are equivalent for
a large class of models exhibiting critical behavior.


  Let two concentric circles $k$ and $K$ be given on the plane with radii $r$
and $R$, $r<R$. Assume that the disc bounded by $k$ is covered by angular
domains whose vertices are within $K$. Then the sum of the angles of these
angular domains is greater than or equal to the view angle of $k$ from an
arbitrary point of $K$.


  The decay modes $B$ to $\pi\pi$, $\psi K_S$, $K^- D$, $\pi K$ and $\eta K$
are promising channels to study the unitarity triangle of the CP violating CKM
matrix. In this paper I study the consequences of these measurements in the
Weinberg model. I show that using the same set of measurements, the following
different mechanisms for CP violation can be distinguished: 1) CP is violated
in the CKM sector only; 2) CP is violated spontaneously in the Higgs sector
only; And 3) CP is violated in both the CKM and Higgs sectors.


  Dispersal is a well recognized driver of ecological and evolutionary
dynamics, and simultaneously an evolving trait. Dispersal evolution has
traditionally been studied in single-species metapopulations so that it remains
unclear how dispersal evolves in spatially structured communities and food
webs. Since most natural systems are biodiverse and spatially structured, and
thus affected by dispersal and its evolution, this knowledge gap should be
bridged.
  Here we discuss whether knowledge established in single-species systems holds
in spatially structured multispecies systems and highlight generally valid and
fundamental principles. Most biotic interactions form the ecological theatre
for the evolutionary dispersal play because interactions mediate patterns of
fitness expectations in space and time. While this allows for a simple
transposition of certain known drivers to a multispecies context, other drivers
may require more complex transpositions, or might not be transferred. We
discuss an important quantitative modulator of dispersal evolution in the
increased trait dimensionality of biodiverse meta-systems and an additional
driver in co-dispersal.
  We speculate that scale and selection pressure mismatches due to
co-dispersal, together with increased trait dimensionality may lead to slower
and more "diffuse" evolution in biodiverse meta-systems. Open questions and
potential consequences in both ecological and evolutionary terms call for more
investigation.


  We analyze the results of a recent experiment with bosonic rubidium atoms
harmonically confined in a quasi-two-dimensional geometry. In this experiment a
well defined critical point was identified, which separates the
high-temperature normal state characterized by a single component density
distribution, and the low-temperature state characterized by a bimodal density
distribution and the emergence of high-contrast interference between
independent two-dimensional clouds. We first show that this transition cannot
be explained in terms of conventional Bose-Einstein condensation of the trapped
ideal Bose gas. Using the local density approximation, we then combine the
mean-field (MF) Hartree-Fock theory with the prediction for the
Berezinskii-Kosterlitz-Thouless transition in an infinite uniform system. If
the gas is treated as a strictly 2D system, the MF predictions for the spatial
density profiles significantly deviate from those of a recent Quantum
Monte-Carlo (QMC) analysis. However when the residual thermal excitation of the
strongly confined degree of freedom is taken into account, an excellent
agreement is reached between the MF and the QMC approaches. For the interaction
strength corresponding to the experiment, we predict a strong correction to the
critical atom number with respect to the ideal gas theory (factor $\sim 2$). A
quantitative agreement between theory and experiment is reached concerning the
critical atom number if the predicted density profiles are used for temperature
calibration.


  The Interface Region Imaging Spectrograph (IRIS) provides spectroscopy and
narrow band slit-jaw (SJI) imaging of the solar chromosphere and transition
region at unprecedented spatial and temporal resolution. Combined with
high-resolution context spectral imaging of the photosphere and chromosphere as
provided by the Swedish 1-m Solar Telescope (SST), we can now effectively trace
dynamic phenomena through large parts of the solar atmosphere in both space and
time. IRIS SJI 1400 images from active regions, which primarily sample the
transition region with the Si IV 1394 and 1403 {\AA} lines, reveal ubiquitous
bright "grains" which are short-lived (2-5 min) bright roundish small patches
of sizes 0.5-1.7" that generally move limbward with velocities up to about 30
km s$^{-1}$. In this paper we show that many bright grains are the result of
chromospheric shocks impacting the transition region. These shocks are
associated with dynamic fibrils (DFs), most commonly observed in H{\alpha}. We
find that the grains show strongest emission in the ascending phase of the DF,
that the emission is strongest towards the top of the DF and that the grains
correspond to a blueshift and broadening of the Si IV lines. We note that the
SJI 1400 grains can also be observed in the SJI 1330 channel which is dominated
by C II lines. Our observations show that a significant part of the active
region transition region dynamics is driven from the chromosphere below rather
than from coronal activity above. We conclude that the shocks that drive DFs
also play an important role in the heating of the upper chromosphere and lower
transition region.


  I review our observational and theoretical knowledge of AM CVn stars,
focusing on recent developments. These include newly discovered systems, the
possibility that two recently discovered extremely short period objects are AM
CVn stars and an update on X-ray, UV an optical studies. Theoretical advances
include the study of the details of both the donor and accretor, and the
physics of the helium accretion discs. I review our (limited) knowledge of the
formation of AM CVn stars and the apparent success of the now more than 25 year
old suggestion that in these objects the mass transfer is driven by
gravitational wave radiation losses. The exciting prospect of directly
detecting these gravitational waves and the possibilities this brings conclude
this contribution.


  In this book, the authors define several new types of soft neutrosophic
algebraic structures over neutrosophic algebraic structures and we study their
generalizations. These soft neutrosophic algebraic structures are basically
parameterized collections of neutrosophic sub-algebraic structures of the
neutrosophic algebraic structure. An important feature of this book is that the
authors introduce the soft neutrosophic group ring, soft neutrosophic semigroup
ring with its generalization, and soft mixed neutrosophic N-algebraic structure
over neutrosophic group ring, then the neutrosophic semigroup ring and mixed
neutrosophic N-algebraic structure respectively.


  It is known that there are four-manifolds which are not algorithmically
recognizable. This implies that there exist triangulations of these manifolds
which are separated by large barriers from the point of view of the computer
algorithm. We have not observed these barriers for triangulations of $S^4$.


  A quantum group of type A is defined as a Hopf algebra associated to a Hecke
symmetry. We show the homology of a Koszul complex associated to the Hecke
symmetry is one dimensional and determines a group-like element in the Hopf
algebra. This group-like element can be interpreted as a homological
determinant as suggested by Yu. Manin.


  A supervised learning framework is proposed to approximate a model predictive
controller (MPC) with reduced computational complexity and guarantees on
stability and constraint satisfaction. The framework can be used for a wide
class of nonlinear systems. Any standard supervised learning technique (e.g.
neural networks) can be employed to approximate the MPC from samples. In order
to obtain closed-loop guarantees for the learned MPC, a robust MPC design is
combined with statistical learning bounds. The MPC design ensures robustness to
inaccurate inputs within given bounds, and Hoeffding's Inequality is used to
validate that the learned MPC satisfies these bounds with high confidence. The
result is a closed-loop statistical guarantee on stability and constraint
satisfaction for the learned MPC. The proposed learning-based MPC framework is
illustrated on a nonlinear benchmark problem, for which we learn a neural
network controller with guarantees.


  For a minimal diffusion process on $ (a,b) $, any possible extension of it to
a standard process on $ [a,b] $ is characterized by the characteristic measures
of excursions away from the boundary points $ a $ and $ b $. The generator of
the extension is proved to be characterized by Feller's boundary condition.


  Recently growing evidence has been accumulated that the NLS1s are viewed from
nearly pole-on viewing angles. However, there has been no theoretical model
which explains the following important correlations; 1) weaker optical Fe II
emitters always have wider emission-line widths but stronger optical Fe II
emitters have either wider or narrower line widths, and 2) S1s with wider line
widths always have flatter soft X-ray spectra but S1s with narrower line widths
have either steeper or flatter soft X-ray spectra.
  Photoionization models predict that the partly-ionized zone in the broad line
region (BLR) with a disk-like configuration, in which the optical Fe II
emission is thought to arise, is very optically thick. If we observe this
disk-like BLR from an inclined viewing angle, the Fe II emitting region located
in the far-side half disk cannot be seen entirely because of the large optical
depth while almost all the Hbeta emission can be seen because the ionized
hydrogen is located in the outer surfaces of BLR clouds. This explains that the
Fe II/Hbeta ratio depends on viewing angle.
  Recent discovery of relativistic outflows in some NLS1s suggests that the
nuclear radio jet interacts with the dense ambient gas very close to the
central engine. The kinetic Doppler effect increases the soft X-ray
luminosities if we observe S1s from a nearly pole-on view given the above range
of beta. These explain why NLS1s tend to have steeper soft X-ray spectra
together with higher soft X-ray luminosities. Furthermore, the extinction of
soft X-ray photons due to dust grain above the dusty tori are expected to more
serious for the BLS1s than for the NLS1s. We thus suggest that these
orientation effects are responsible for the second important correlation.


  Distorted plane waves, sometimes called Eisenstein functions, are a family of
eigenfunctions of a Schr\"odinger operator that are not square integrable. More
precisely, they can be written as the sum of a plane wave and an outgoing wave.
We shall study distorted plane waves in the semiclassical limit, in a general
setting which includes manifolds that are Euclidean near infinity, under the
hypothesis that the classical dynamics is hyperbolic close to the trapped set,
and that some topological pressure is negative.


  Given a subset $S$ of the non-identity elements of the dihedral group of
order $2m$, is it possible to order the elements of $S$ so that the partial
products are distinct? This is equivalent to the sequenceability of the group
when $|S| = 2m-1$ and so it is known that the answer is yes in this case if and
only if $m>4$. We show that the answer is yes when $|S| \leq 9$ and $m$ is an
odd prime other than 3, when $|S| = 2m-2$ and $m$ is even or prime, and when
$|S| = 2m-2$ for many instances of the problem when $m$ is odd and composite.
We also consider the problem in the more general setting of arbitrary
non-abelian groups and discuss connections between this work and the concept of
strong sequenceability.


  In a recent letter [1] with the same title, Farrar and Piran offered an
explanation for the near isotropy of the arrival directions [2] of ultrahigh
energy cosmic rays (UHECRs) and the apparent absence [3] of the so called `GZK
cutoff' in their spectrum around $10^{20}$ eV due to pion photoproduction on
the cosmic background radiation (CMB) that was predicted independently by
Greisen [4] and by Zatsepin and Kuz'min [5]. They suggested that the
extragalactic magnetic fields near the Milky Way are strong enough to deflect
and isotropise the arrival directions of the UHECRs from a few nearby sources
for which their travel time to Earth is shorter than their attenuation time by
pion photoproduction on the CMB. They also estimated that this allows active
galactic nuclei (AGNs) or gamma ray bursts (GRBs) to be the source of the
UHECRs. However, these suggestions are inconsistent with various observations


  Dirac's large number hypothesis is motivated by certain scaling
transformations that relate the parameters of macro and microphysics. We show
that these relations can actually be explained in terms of the holographic $N$
bound conjectured by Bousso and a series of purely cosmological observations,
namely, that our universe is spatially homogeneous, isotropic, and flat to a
high degree of approximation and that the cosmological constant dominates the
energy density at present.


  In this paper we explore the effect of the generalized uncertainty principle
and modified dispersion relation to compute Hawking radiation from a rotating
acoustic black hole in the tunneling formalism by using the
Wentzel-Kramers-Brillouin (WKB) approximation applied to the Hamilton-Jacobi
method. The starting point is to consider the planar acoustic black hole metric
found in a Lorentz-violating Abelian Higgs model. In our analyzes we
investigate quantum corrections for the Hawking temperature and entropy. A
logarithmic correction and an extra term that depends on a conserved charge
were obtained. We also have found that the changing in the Hawking temperature
${\cal T}_H$ for a dispersive medium due to a Lorentz-violating background
accounts for supersonic velocities in the general form $(v_g-v_p)/v_p = \Delta
{\cal T}_H/{\cal T}_H\sim10^{-5}$ in Bose-Einstein-Condensate (BEC) systems.


  In this paper, we analyze the approximation quality of a greedy heuristic for
automatic map labeling. As input, we have a set of events, each associated with
a label at a fixed position, a timestamp, and a weight. Let a time-window
labeling be a selection of these labels such that all corresponding timestamps
lie in a queried time window and no two labels overlap. A solution to the
time-window labeling problem consists of a data structure that encodes a
time-window labeling for each possible time window; when a user specifies a
time window of interest using a slider interface, we query the data structure
for the corresponding labeling.
  We define the quality of a time-window labeling solution as the sum of the
weights of the labels in each time-window labeling, integrated over all time
windows. We aim at maximizing the quality under the condition that a label may
never disappear when the user shrinks the time window. In this paper, we
analyze how well a greedy heuristic approximates the maximum quality that can
be realized under this condition.
  On the one hand, we present an instance with square labels of equal size and
equal weight for which the greedy heuristic fails to find a solution of at
least 1/4 of the quality of an optimal solution. On the other hand, we prove
that the greedy heuristic does guarantee a solution with at least 1/8 of the
quality of an optimal solution. In the case of disk-shaped labels of equal size
and equal weight, the greedy heuristic gives a solution with at least 1/10 of
the quality of an optimal solution. If the labels are squares or disks of equal
size and the maximum weight divided by the minimum weight is at most b, then
the greedy heuristic has approximation ratio Theta(log b).


  Quantum Key Distribution~(QKD) is a technology that enables the exchange of
private encryption keys between two legitimate parties, using protocols that
involve quantum mechanics principles. The rate at which secret keys can be
exchanged depends on the attenuation that is experienced. Therefore, it is more
convenient to replace many terrestrial fiber segments (and repeaters) by just
few optical satellite links that would enable flexible global coverage. Then,
the satellite nodes can take the role of trusted-relays, forwarding the secret
keys from source to destination. However, since the rate at which secret keys
can be generated in each quantum link is limited, it is very important to
select the intermediate satellite nodes to inter-connect ground stations
efficiently. This paper studies the most convenient allocation of resources in
a QKD network that combines complementary connectivity services of GEO and LEO
satellites. The aim of the centralized routing algorithm is to select the most
convenient trusted-relays to forward the secret keys between pairs of ground
stations, verifying the constraints that satellite-to-ground and
inter-satellite quantum channels have.


  The automatic speaker verification system is sometimes vulnerable to various
spoofing attacks. The 2-class Gaussian Mixture Model classifier for genuine and
spoofed speech is usually used as the baseline for spoofing detection. However,
the GMM classifier does not separately consider the scores of feature frames on
each Gaussian component. In addition, the GMM accumulates the scores on all
frames independently, and does not consider their correlations. We propose the
two-path GMM-ResNet and GMM-SENet models for spoofing detection, whose input is
the Gaussian probability features based on two GMMs trained on genuine and
spoofed speech respectively. The models consider not only the score
distribution on GMM components, but also the relationship between adjacent
frames. A two-step training scheme is applied to improve the system robustness.
Experiments on the ASVspoof 2019 show that the LFCC+GMM-ResNet system can
relatively reduce min-tDCF and EER by 76.1% and 76.3% on logical access
scenario compared with the GMM, and the LFCC+GMM-SENet system by 94.4% and
95.4% on physical access scenario. After score fusion, the systems give the
second-best results on both scenarios.


  ALICE has performed several measurements aimed at understanding the
collective-like effects observed in small collision systems. New approaches may
be needed to clarify particle-production mechanisms in high-multiplicity pp
collisions. Transverse momentum ($p_{\rm T}$) spectra as a function of
charged-particle multiplicity show intriguing features. For example, data
exhibit a stronger-than-linear increase of the self-normalised high-$p_{\rm T}$
particle yields versus multiplicity. In order to understand the role of
auto-correlations on these effects, it has been proposed to use the underlying
event as a multiplicity estimator to factorise the hardest and the softest
components of the events. This approach can also be used to study collective
effects in events with exceptionally large activity in the underlying-event
region with respect to the event-averaged mean. In these proceedings, $p_{\rm
T}$ spectra as a function of underlying-event activity in pp collisions
measured with the ALICE detector are presented. Results are compared with
PYTHIA 8.2 event generator.


  We use data from the Radial Velocity Experiment (RAVE) and the Tycho-Gaia
astrometric solution catalogue (TGAS) to compute the velocity fields yielded by
the radial (VR), azimuthal (Vphi) and vertical (Vz) components of associated
Galactocentric velocity. We search in particular for variation in all three
velocity components with distance above and below the disc midplane, as well as
how each component of Vz (line-of-sight and tangential velocity projections)
modifies the obtained vertical structure. To study the dependence of velocity
on proper motion and distance we use two main samples: a RAVE sample including
proper motions from the Tycho-2, PPMXL and UCAC4 catalogues, and a RAVE-TGAS
sample with inferred distances and proper motions from the TGAS and UCAC5
catalogues. In both samples, we identify asymmetries in VR and Vz. Below the
plane we find the largest radial gradient to be dVR / dR = -7.01+- 0.61 km\s
kpc, in agreement with recent studies. Above the plane we find a similar
gradient with dVR / dR= -9.42+- 1.77 km\s kpc. By comparing our results with
previous studies, we find that the structure in Vz is strongly dependent on the
adopted proper motions. Using the Galaxia Milky Way model, we demonstrate that
distance uncertainties can create artificial wave-like patterns. In contrast to
previous suggestions of a breathing mode seen in RAVE data, our results support
a combination of bending and breathing modes, likely generated by a combination
of external or internal and external mechanisms.


  In this paper we give an exact relation between the Green's function in a
scattering problem for a wave equation and the correlation of scattered plane
waves. This general relation was proved in a special case by Sanchez-Sesma and
al.


  Nonparametric estimation of a mixing distribution based on data coming from a
mixture model is a challenging problem. Beyond estimation, there is interest in
uncertainty quantification, e.g., confidence intervals for features of the
mixing distribution. This paper focuses on estimation via the predictive
recursion algorithm, and here we take advantage of this estimator's seemingly
undesirable dependence on the data ordering to obtain a permutation-based
approximation of the sampling distribution which can be used to quantify
uncertainty. Theoretical and numerical results confirm that the proposed method
leads to valid confidence intervals, at least approximately.


  Ghost-free bimetric theory can describe gravity in the presence of an extra
spin-2 field. We study certain aspects of dynamics in this theory: (1) It is
shown that if either of the metrics is an Einstein solution then the other is
always forced to be Einstein, too. For a class of bimetric models this
constraint is stronger and as soon as one metric is Einstein, the other metric
is forced to be proportional to it. As a consequence, the models in this class
avoid a branch of pathological solutions that exhibit determinant singularities
or nonlinear ghosts. These constraints persists in a generalized form when
sources are included, but are destroyed in the massive gravity limit of the
theory. (2) For another class of bimetric models, we show the existence of
solutions that do not admit a massive gravity limit. A bimetric model that
could exhibit a nonlinear version of "partially massless" symmetry belongs to
both these classes. It is argued that if such a model exits, its symmetry will
not survive in the massive gravity limit.


  A two-dimensional flow in a 90 degree bent channel is considered. A magnetic
field is uniform and parallel to inlet branch of the channel. A spectral/hp
element method was used for liquid motion calculations. Three types of steady
flows were detected. It was found that magnetic forces can suppress a pressure
gradient and throw out liquid from the inlet, a relatively large reverse flow
appears.


  We present results of optical spectroscopic and BVR_CI_C photometric
observations of 77 pre-main sequence (PMS) stars in the Cepheus flare region. A
total of 64 of these are newly confirmed PMS stars, originally selected from
various published candidate lists. We estimate effective temperatures and
luminosities for the PMS stars, and comparing the results with pre-main
sequence evolutionary models we estimate stellar masses of 0.2-2.4M_sun and
stellar ages of 0.1-15 Myr. Among the PMS stars, we identify 15 visual binaries
with separations of 2-10 arcsec. From archival IRAS, 2MASS, and Spitzer data,
we construct their spectral energy distributions and classify 5% of the stars
as Class I, 10% as Flat SED, 60% as Class II, and 3% as Class III young stellar
objects (YSOs). We identify 12 CTTS and 2 WTTS as members of NGC 7023, with
mean age of 1.6 Myr. The 13 PMS stars associated with L1228 belong to three
small aggregates: RNO 129, L1228A, and L1228S. The age distribution of the 17
PMS stars associated with L1251 suggests that star formation has propagated
with the expansion of the Cepheus flare shell. We detect sparse aggregates of
6-7 Myr old PMS stars around the dark clouds L1177 and L1219, at a distance of
400 pc. Three T Tauri stars appear to be associated with the Herbig Ae star SV
Cep at a distance of 600 pc. Our results confirm that the molecular complex in
the Cepheus flare region contains clouds of various distances and star forming
histories.


  We introduce a new model of spatial random multiple access systems with a
non-standard departure policy: all arriving messages are distributed uniformly
on a finite sphere in the space, and when a successful transmission of a single
message occurs, the transmitted message leaves the system together with all its
neighbours within a ball of a given radius centred at the message's location.
We consider three classes of protocols: centralised protocols and decentralised
protocols with either ternary or binary feedback; and analyse their stability.
Further, we discuss some asymptotic properties of stable protocols.


  We propose a theoretical framework to quantitatively describe Physical
Unclonable Functions (PUFs), including extensions to quantum protocols,
so-called Quantum Readout PUFs (QR-PUFs). (QR-) PUFs are physical systems with
challenge-response behavior intended to be hard to clone or simulate. Their use
has been proposed in several cryptographic protocols, with particular emphasis
on authentication. Here, we provide theoretical assumptions and definitions
behind the intuitive ideas of (QR-) PUFs. This allows to quantitatively
characterize the security of such devices in cryptographic protocols. First, by
generalizing previous ideas, we design a general authentication scheme, which
is applicable to different physical implementations of both classical PUFs and
(QR-) PUFs. Then, we define the robustness and the unclonability, which allows
us to derive security thresholds for (QR-) PUF authentication and paves the way
to develop further new authentication protocols.


  With hundreds, even thousands, of hotels to choose from at every destination,
it's difficult to know which will suit your personal preferences. Expedia wants
to take the proverbial rabbit hole out of hotel search by providing
personalized hotel recommendations to their users. This is no small task for a
site with hundreds of millions of visitors every month! Currently, Expedia uses
search parameters to adjust their hotel recommendations, but there aren't
enough customer specific data to personalize them for each user. In this
project, we have taken up the challenge to contextualize customer data and
predict the likelihood a user will stay at 100 different hotel groups.


  Photoexcitation and ionization of partially ionized heavy atoms in highly
relativistic flows by interstellar photons, followed by their reemission in
radiative recombination and decay, boost star-light into beamed $\gamma$ rays
along the flow direction. Repeated excitation/decay of highly relativistic
baryonic ejecta from merger or accretion induced collapse of neutron stars in
dense stellar regions (DSRs), like galactic cores, globular clusters and super
star-clusters, can convert enough kinetic energy in such events in distant
galaxies into cosmological gamma ray bursts (GRBs). The model predicts
remarkably well all the main observed temporal and spectral properties of GRBs.
Its success strongly suggests that GRBs are $\gamma$ ray tomography pictures of
DSRs in galaxies at cosmological distances with unprecedented resolution: A
time resolution of $dt\sim 1~ms$ in a GRB can resolve stars at a Hubble
distance which are separated by only $D\sim 10^{10}cm$. This is equivalent to
the resolving power of an optical telescope with a diameter larger than one
Astronomical Unit!


  We show that contrary to first expectations realistic three generation
supersymmetric intersecting brane world models give rise to phenomenologically
interesting predictions about gauge coupling unification. Assuming the most
economical way of realizing the matter content of the MSSM via intersecting
branes we obtain a model independent relation among the three gauge coupling
constants at the string scale. In order to correctly reproduce the
experimentally known values of sin^2[theta_W(M_z)] and alpha_s(M_z) this
relation leads to natural gauge coupling unification at a string scale close to
the standard GUT scale 2 x 10^16 GeV. Additional vector-like matter can push
the unification scale up to the Planck scale.


  An alternative perturbative expansion in quantum mechanics which allows a
full expression of the scaling arbitrariness is introduced. This expansion is
examined in the case of the anharmonic oscillator and is conveniently resummed
using a method which consists in introducing an energy cut-off that is
carefully removed as the order of the expansion is increased. We illustrate
this technique numerically by computing the asymptotic behavior of the ground
state energy of the anharmonic oscillator for large couplings, and show how the
exploitation of the scaling arbitrariness substantially improves the
convergence of this perturbative expansion.


  We present a study of spinning black hole binaries focusing on the spin
dynamics of the individual black holes as well as on the gravitational recoil
acquired by the black hole produced by the merger. We consider two series of
initial spin orientations away from the binary orbital plane. In one of the
series, the spins are anti-aligned; for the second series, one of the spins
points away from the binary along the line separating the black holes. We find
a remarkable agreement between the spin dynamics predicted at 2nd
post-Newtonian order and those from numerical relativity. For each
configuration, we compute the kick of the final black hole. We use the kick
estimates from the series with anti-aligned spins to fit the parameters in the
\KKF{,} and verify that the recoil along the direction of the orbital angular
momentum is $\propto \sin\theta$ and on the orbital plane $\propto \cos\theta$,
with $\theta$ the angle between the spin directions and the orbital angular
momentum. We also find that the black hole spins can be well estimated by
evaluating the isolated horizon spin on spheres of constant coordinate radius.


  We revisit dark-matter production through freeze-in and freeze-out by solving
the Boltzmann equations at the level of the phase-space distribution $f(p,t)$.
Using the $2\to2$ annihilation and the $1\to2$ decay processes for
illustration, we compare the resulting dark-matter relic abundance with that
from the number-density approach. In the transition regime between freeze-in
and freeze-out, we find the difference can be quite significant, or even by
orders of magnitude if the annihilation of dark-matter particles or the
decaying mediator is neglected. The freeze-in production in the $2\to2$ and the
$1\to 2$ processes can also result in non-thermal phase-space distributions, or
even multi-modal ones with out-of-equilibrium decay, which can potentially
affect structure formation at late times. We also investigate how elastic
scatterings can distort such non-thermal distributions.


  In this paper, we propose a varying coefficient panel data model with
unobservable multiple interactive fixed effects that are correlated with the
regressors. We approximate each coefficient function by B-spline, and propose a
robust nonlinear iteration scheme based on the least squares method to estimate
the coefficient functions of interest. We also establish the asymptotic theory
of the resulting estimators under certain regularity assumptions, including the
consistency, the convergence rate and the asymptotic distribution. Furthermore,
we develop a least squares dummy variable method to study an important special
case of the proposed model: the varying coefficient panel data model with
additive fixed effects. To construct the pointwise confidence intervals for the
coefficient functions, a residual-based block bootstrap method is proposed to
reduce the computational burden as well as to avoid the accumulative errors.
Simulation studies and a real data analysis are also carried out to assess the
performance of our proposed methods.


  In this article, we prove that every finite abelian group $G$ of odd order
occurs as a subgroup of the class group of infinitely many real cyclotomic
fields.


  In this investigation oscillation periods in Mg II k line intensity,
brightness temperature, and Doppler velocity obtained above Magnetic Bright
Points (MBPs) are investigated. For that purpose, data from the Interface
Region Imaging Spectrometer (IRIS) observing the higher chromosphere and
transition region (TR) were analysed together with imaging and magnetogram data
obtained by Solar Dynamics Observatory (SDO). The MBPs were identified in
combining Si IV 1403 A Slit Jaw Images (SJIs) with the magnetogram information
from the Heliospheric and Magnetic Imager (HMI). A time-slice analysis followed
by a wavelet inspection were carried out on the Mg II k (2796 A and 10,000 K)
resonance lines for the detection of the oscillation period. Finally, a power
spectrum analysis was performed to characterise the oscillations with the
result that network points feature a typical intensity, temperature, and
velocity oscillation period of about 300 seconds; The internetwork points have
a mean intensity oscillation period of about 180 seconds, mean temperature
oscillation period of about 202, and mean velocity oscillation period of about
202 seconds. In addition, one BP was analysed in detail, which demonstrates
intensity oscillation periods with a value of 500 seconds, obviously not
related to the common 3- or 5-minute oscillations found typically elsewhere in
chromospheric/photospheric structures.


  We study a system of two coupled kicked rotors, both classically and quantum
mechanically, for a wide range of coupling parameters. This was motivated by
two published reports, one of which reported quantum localization, while the
other reported diffusion. The classical systems are chaotic, and exhibit normal
diffusive behavior. In the quantum systems, we found different regimes,
depending on the strength of the coupling. For weak coupling, we found quantum
localization similar to that exhibited by single kicked rotors. For strong
coupling, we found a quasi-diffusive growth of the width of the momentum
distribution, in which the apparent diffusion coefficient decreased as time
increased. The behavior in this regime can be described by the scaling theory
of weak localization for two-dimensional disordered lattices. The weak and
strong coupling regimes are separated by a regime of complex intermediate
behavior. Thus we explain the apparent contradiction in the literature as being
due to qualitatively different regimes of behavior, which we call strong and
weak quantum localization.


  For a finite group $G$ and a conjugation-invariant subset $Q\subseteq G$, we
consider the Hurwitz space $\mathrm{Hur}_n(Q)$ parametrising branched covers of
the plane with $n$ branch points, monodromies in $G$ and local monodromies in
$Q$. For $i\ge0$ we prove that $\bigoplus_n H_i(\mathrm{Hur}_n(Q))$ is a
finitely generated module over the ring $\bigoplus_n H_0(\mathrm{Hur}_n(Q))$.
As a consequence, we obtain polynomial stability of homology of Hurwitz spaces:
taking homology coefficients in a field, the dimension of
$H_i(\mathrm{Hur}_n(Q))$ agrees for $n$ large enough with a quasi-polynomial in
$n$, whose degree is easily bounded in terms of $G$ and $Q$. Under suitable
hypotheses on $G$ and $Q$, we prove classical homological stability for certain
sequences of components of Hurwitz spaces. Our results generalise previous work
of Ellenberg-Venkatesh-Westerland, and rely on techniques introduced by them
and by Hatcher-Wahl.


  We establish a generalized Ihara zeta function formula for simple graphs with
bounded degree. This is a generalization of the formula obtained by G. Chinta,
J. Jorgenson and A. Karlsson from a vertex-transitive graph.


  Adaptive Random Testing (ART) enhances the testing effectiveness (including
fault-detection capability) of Random Testing (RT) by increasing the diversity
of the random test cases throughout the input domain. Many ART algorithms have
been investigated such as Fixed-Size-Candidate-Set ART (FSCS) and Restricted
Random Testing (RRT), and have been widely used in many practical applications.
Despite its popularity, ART suffers from the problem of high computational
costs during test-case generation, especially as the number of test cases
increases. Although several strategies have been proposed to enhance the ART
testing efficiency, such as the forgetting strategy and the k-dimensional tree
strategy, these algorithms still face some challenges, including: (1) Although
these algorithms can reduce the computation time, their execution costs are
still very high, especially when the number of test cases is large; and (2) To
achieve low computational costs, they may sacrifice some fault-detection
capability. In this paper, we propose an approach based on Approximate Nearest
Neighbors (ANNs), called Locality-Sensitive Hashing ART (LSH-ART). When
calculating distances among different test inputs, LSH-ART identifies the
approximate (not necessarily exact) nearest neighbors for candidates in an
efficient way. LSH-ART attempts to balance ART testing effectiveness and
efficiency.


  We study a radiative inverse seesaw model with local B-L symmetry, in which
we extend the neutrino mass structure that is generated through a kind of
inverse seesaw framework to the more generic one than our previous work. We
focus on a real part of bosonic particle as a dark matter and investigate the
features in O(1-80) GeV mass range, reported by the experiments such as CoGeNT
and XENON (2012).


  We have developed a correction tool to improve the quality of RXTE HEXTE
spectra by employing the same method we used earlier to improve the quality of
RXTE PCA spectra. We fit all of the hundreds of HEXTE spectra of the Crab
individually to a simple power-law model, some 37 million counts in total for
Cluster A and 39 million counts for Cluster B, and we create for each cluster a
combined spectrum of residuals. We find that the residual spectrum of Cluster A
is free of instrumental artifacts while that of Cluster B contains significant
features with amplitudes ~1%; the most prominent is in the energy range 30-50
keV, which coincides with the iodine K edge. Starting with the residual
spectrum for Cluster B, via an iterative procedure we created the calibration
tool hexBcorr for correcting any Cluster B spectrum of interest. We demonstrate
the efficacy of the tool by applying it to Cluster B spectra of two bright
black holes, which contain several million counts apiece. For these spectra,
application of the tool significantly improves the goodness of fit, while
affecting only slightly the broadband fit parameters. The tool may be important
for the study of spectral features, such as cyclotron lines, a topic that is
beyond the scope of this paper.


  We point out that lepton number violation is possible even if neutrinos are
Dirac particles. We illustrate this by constructing a simple model that allows
for lepton number violation by four units only. As a consequence, neutrinoless
double beta decay is forbidden, but neutrinoless quadruple beta decay is
possible: $(A,Z) \to (A,Z+4) + 4 e^-$. We identify three candidate isotopes for
this decay, the most promising one being Nd-150 due to its high $Q_{0\nu
4\beta}$-value of 2 MeV. Analogous processes, such as neutrinoless quadruple
electron capture, are also possible. The expected lifetimes are extremely long,
and experimental searches are challenging.


  Slow kinetic processes of molecular systems can be analyzed by computing
dominant eigenpairs of the Koopman operator or its generator. In this context,
the Variational Approach to Markov Processes (VAMP) provides a rigorous way of
discerning the quality of different approximate models. Kernel methods have
been shown to provide accurate and robust estimates for slow kinetic processes,
but are sensitive to hyper-parameter selection, and require the solution of
large-scale generalized eigenvalue problems, which can easily become
computationally demanding for large data sizes. In this contribution, we employ
a stochastic approximation of the kernel based on random Fourier features
(RFFs), to derive a small-scale dual eigenvalue problem which can easily be
solved. We provide an interpretation of this procedure in terms of a finite
randomly generated basis set. By combining the RFF approach and model selection
by means of the VAMP score, we show that kernel parameters can be efficiently
tuned, and accurate estimates of slow molecular kinetics can be obtained for
several benchmarking systems, such as deca alanine and the NTL9 protein.


  We propose two protocols for distributed priority queues (for simplicity
denoted 'heap') called SKEAP and SEAP. SKEAP realizes a distributed heap for a
constant amount of priorities and SEAP one for an arbitrary amount. Both
protocols build on an overlay, which induces an aggregation tree on top of
which heap operations are aggregated in batches, ensuring that our protocols
scale even for a high rate of incoming requests. As part of SEAP we provide a
novel distributed protocol for the $k$-selection problem that runs in $O(\log
n)$ rounds w.h.p. SKEAP guarantees sequential consistency for its heap
operations, while SEAP guarantees serializability. SKEAP and SEAP provide
logarithmic runtimes w.h.p. on all their operations with SEAP having to use
only $O(\log n)$ bit messages.


  Following earlier work by Aldo de Luca and others, we study trapezoidal words
and their prefixes, with respect to their characteristic parameters $K$ and $R$
(length of shortest unrepeated suffix, and shortest length without right
special factors, respectively), as well as their symmetric versions $H$ and
$L$. We consider the distinction between closed (i.e., periodic-like) and open
prefixes, and between Sturmian and non-Sturmian ones. Our main results
characterize right special and strictly bispecial trapezoidal words, as done by
de Luca and Mignosi for Sturmian words.


  Few-shot learning (FSL) enables adaptation to new tasks with only limited
training data. In wireless communications, channel environments can vary
drastically; therefore, FSL techniques can quickly adjust transceiver
accordingly. In this paper, we develop two FSL frameworks that fit in wireless
transceiver design. Both frameworks are base on optimization programs that can
be solved by well-known algorithms like the inexact alternating direction
method of multipliers (iADMM) and the inexact alternating direction method
(iADM). As examples, we demonstrate how the proposed two FSL frameworks are
used for the OFDM receiver and beamforming (BF) for the millimeter wave
(mmWave) system. The numerical experiments confirm their desirable performance
in both applications compared to other popular approaches, such as transfer
learning (TL) and model-agnostic meta-learning.


  We prove the conjecture of Pollack and Weston on the quantitative analysis of
the level lowering congruence \`{a} la Ribet for modular forms of higher
weight. It was formulated and studied in the context of the integral
Jacquet-Langlands correspondence and anticyclotomic Iwasawa theory for modular
forms of weight two and square-free level for the first time. We use a
completely different method based on the $R=\mathbb{T}$ theorem established by
Diamond-Flach-Guo and Dimitrov and an explicit comparison of adjoint
$L$-values. We briefly discuss arithmetic applications of our main result at
the end.


  This article summarizes the various ways one may use to construct the Skew
Brownian motion, and shows their connections. Recent applications of this
process in modelling and numerical simulation motivates this survey. This
article ends with a brief account of related results, extensions and
applications of the Skew Brownian motion.


  The pulsational properties of the Cepheid models along the evolutionary
tracks from the Padova group (Girardi et al.), as calculated with our turbulent
convective pulsation code, are in good agreement with the resonance constraints
imposed by the observational OGLE-2 data of the Small and Large Magellanic
Clouds. Our study suggests that the P_4/P_1=1/2 resonance for the overtone
Cepheids occurs for periods clustering around 4.2 d, in disagreement with the
suggestion of Antonello & Poretti based on the observations of light curves,
but in agreement with Kienzle et al. and Feuchtinger et al. For the fundamental
Cepheids the lowest order Fourier decomposition coefficients from the light
curves, \viz R_21 and phi_21 can be used to locate the resonance region, but
not so for the first overtone Cepheids. Here, the radial velocity curves can be
used to locate the overtone resonance region, or in their absence, one needs to
resort to numerical hydrodynamic modelling.


  It is conjectured since long that for any convex body $P\subset \mathbb{R}^n$
there exists a point in its interior which belongs to at least $2n$ normals
from different points on the boundary of $P$. The conjecture is known to be
true for $n=2,3,4$.
  We treat the same problem for convex polytopes in $\mathbb{R}^3$. It turns
out that the PL concurrent normals problem differs a lot from the smooth one.
One almost immediately proves that a convex polytope in $\mathbb{R}^3$ has $8$
normals to its boundary emanating from some point in its interior. Moreover, we
conjecture that each simple polytope in $\mathbb{R}^3$ has a point in its
interior with $10$ normals to the boundary. We confirm the conjecture for all
tetrahedra and triangular prisms and give a sufficient condition for a simple
polytope to have a point with $10$ normals.
  Other related topics (average number of normals, minimal number of normals
from an interior point, other dimensions) are discussed.


  Solutions to most nonlinear ordinary differential equations (ODEs) rely on
numerical solvers, but this gives little insight into the nature of the
trajectories and is relatively expensive to compute. In this paper, we derive
analytic solutions to a class of nonlinear, homogeneous ODEs with linear and
quadratic terms on the right-hand side. We formulate a power series expansion
of each state variable, whose function depends on the eigenvalues of the
linearized system, and solve for the coefficients using some linear algebra and
combinatorics. Various experiments exhibit quickly decaying coefficients, such
that a good approximation to the true solution consists of just a few terms.


  We study the simultaneous message passing model of communication complexity.
Building on the quantum fingerprinting protocol of Buhrman et al., Yao recently
showed that a large class of efficient classical public-coin protocols can be
turned into efficient quantum protocols without public coin. This raises the
question whether this can be done always, i.e. whether quantum communication
can always replace a public coin in the SMP model. We answer this question in
the negative, exhibiting a communication problem where classical communication
with public coin is exponentially more efficient than quantum communication.
Together with a separation in the other direction due to Bar-Yossef et al.,
this shows that the quantum SMP model is incomparable with the classical
public-coin SMP model.
  In addition we give a characterization of the power of quantum fingerprinting
by means of a connection to geometrical tools from machine learning, a
quadratic improvement of Yao's simulation, and a nearly tight analysis of the
Hamming distance problem from Yao's paper.


  We revisit supersymmetric nonlinear sigma models on the target manifold
$CP^{N-1}$ and $SO(N)/SO(N-2)\times U(1)$ in four dimensions. These models are
formulated as gauged linear models, but it is indicated that the Wess-Zumino
term should be added to the linear model since the hidden local symmetry is
anomalous. Applying a procedure used for quantization of anomalous gauge
theories to the nonlinear models, we determine the form of the Wess-Zumino
term, by which a global symmetry in the linear model becomes smaller in the
action than the conventional one. Moreover, we analyze the resulting linear
model in the $1/N$ leading order. Consequently, we find that the model has a
critical coupling constant similar to bosonic models. In the weak coupling
regime, the $U(1)$ local symmetry is broken but supersymmetry is never broken.
In contrast to the bosonic case, it is impossible to find stable vacua in the
strong coupling regime as far as in the $1/N$ leading order. These results are
straightforwardly generalized to the case of the hermitian symmetric space.


  In this paper we establish a complete local theory for the energy-critical
nonlinear wave equation (NLW) in high dimensions ${\mathbb R} \times {\mathbb
R}^d$ with $d \geq 6$. We prove the stability of solutions under the weak
condition that the perturbation of the linear flow is small in certain
space-time norms. As a by-product of our stability analysis, we also prove
local well-posedness of solutions for which we only assume the smallness of the
linear evolution. These results provide essential technical tools that can be
applied towards obtaining the extension to high dimensions of the analysis of
Kenig and Merle \cite{keme06} of the dynamics of the focusing (NLW) below the
energy threshold. By employing refined paraproduct estimates we also prove
unconditional uniqueness of solutions for $d\ge 5$ in the natural energy class.
This extends an earlier result by Furioli, Planchon and Terraneo \cite{FPT03}
in dimension $d=4$.


  Computer vision is playing an increasingly important role in automated
malware detection with the rise of the image-based binary representation. These
binary images are fast to generate, require no feature engineering, and are
resilient to popular obfuscation methods. Significant research has been
conducted in this area, however, it has been restricted to small-scale or
private datasets that only a few industry labs and research teams have access
to. This lack of availability hinders examination of existing work, development
of new research, and dissemination of ideas. We release MalNet-Image, the
largest public cybersecurity image database, offering 24x more images and 70x
more classes than existing databases (available at https://mal-net.org).
MalNet-Image contains over 1.2 million malware images -- across 47 types and
696 families -- democratizing image-based malware capabilities by enabling
researchers and practitioners to evaluate techniques that were previously
reported in propriety settings. We report the first million-scale malware
detection results on binary images. MalNet-Image unlocks new and unique
opportunities to advance the frontiers of machine learning, enabling new
research directions into vision-based cyber defenses, multi-class imbalanced
classification, and interpretable security.


  We review works on the asymptotic stability of the Couette flow. The majority
of the paper is aimed towards a wide range of applied mathematicians with an
additional section aimed towards experts in the mathematical analysis of PDEs.


  We report on a dispersion relation formalism for the virtual Compton
scattering (VCS) reaction on the proton, which for the first time allows a
dispersive evaluation of 4 generalized polarizabilities. The dispersion
formalism provides a new tool to analyze VCS experiments above pion threshold,
thus increasing the sensitivity to the generalized polarizabilities of the
nucleon.


  The 1-loop corrections to the seesaw mechanism in the noncommutative standard
model are computed. Other consequences of the Lorentzian signature in the inner
space are summarised.


  Interactions between people are often governed by their relationships. On the
flip side, social relationships are built upon several interactions. Two
strangers are more likely to greet and introduce themselves while becoming
friends over time. We are fascinated by this interplay between interactions and
relationships, and believe that it is an important aspect of understanding
social situations. In this work, we propose neural models to learn and jointly
predict interactions, relationships, and the pair of characters that are
involved. We note that interactions are informed by a mixture of visual and
dialog cues, and present a multimodal architecture to extract meaningful
information from them. Localizing the pair of interacting characters in video
is a time-consuming process, instead, we train our model to learn from
clip-level weak labels. We evaluate our models on the MovieGraphs dataset and
show the impact of modalities, use of longer temporal context for predicting
relationships, and achieve encouraging performance using weak labels as
compared with ground-truth labels. Code is online.


  Time--distance inversions usually provide tomographic maps of the interesting
plasma properties (we will focus on flows) at various depths. These maps
however do not correspond directly to the flow field, but rather to the true
flow field smoothed by the averaging kernels. We introduce a method to derive a
regularly gridded estimate of the true velocity field from the set of
tomographic maps. We aim mainly to reconstruct the flow on a uniform grid in
the vertical domain. We derive the algorithm, implement it and validate using
synthetic data. The use of the synthetic data allows us to investigate the
influence of random noise and to develop the methodology to deal with it
properly.


  We assess the possibility to detect the warm-hot intergalactic medium (WHIM)
in emission and to characterize its physical conditions and spatial
distribution through spatially resolved X-ray spectroscopy, in the framework of
the recently proposed DIOS, EDGE, Xenia, and ORIGIN missions, all of which are
equipped with microcalorimeter-based detectors. For this purpose we analyze a
large set of mock emission spectra, extracted from a cosmological
hydrodynamical simulation. These mock X-ray spectra are searched for emission
features showing both the OVII K alpha triplet and OVIII Ly alpha line, which
constitute a typical signature of the warm hot gas. Our analysis shows that 1
Ms long exposures and energy resolution of 2.5 eV will allow us to detect about
400 such features per deg^2 with a significance >5 sigma and reveals that these
emission systems are typically associated with density ~100 above the mean. The
temperature can be estimated from the line ratio with a precision of ~20%. The
combined effect of contamination from other lines, variation in the level of
the continuum, and degradation of the energy resolution reduces these
estimates. Yet, with an energy resolution of 7 eV and all these effects taken
into account, one still expects about 160 detections per deg^2. These line
systems are sufficient to trace the spatial distribution of the line-emitting
gas, which constitute an additional information, independent from line
statistics, to constrain the poorly known cosmic chemical enrichment history
and the stellar feedback processes.


  By using Symanzik's improvement program, we study on-shell improved lattice
QCD with staggered fermions. We find that there are as many as 15 independent
lattice operators of dimension of six~(including both gauge and fermion
operators) which must be added to the unimproved action to form an $O(a^2)$
improved action. Among them, the total number of dimension-6 gauge operators
and fermion bilinears is 5. The other 10 terms are four-fermion operators. At
the tree-level and tadpole-improved tree-level, all the 10 four fermion
operators are absent.


  Emotion elicitation using emotional film clips is one of the most common and
ecologically valid methods in Affective Computing. However, selecting and
validating appropriate materials that evoke a range of emotions is challenging.
Here we present EmoStim: A Database of Emotional Film Clips as a film library
with a rich and varied content. EmoStim is designed for researchers interested
in studying emotions in relation to either discrete or componential models of
emotion. To create the database, 139 film clips were selected from literature
and then annotated by 638 participants through the CrowdFlower platform. We
selected 99 film clips based on the distribution of subjective ratings that
effectively distinguished between emotions defined by the discrete model. We
show that the selected film clips reliably induce a range of specific emotions
according to the discrete model. Further, we describe relationships between
emotions, emotion organization in the componential space, and underlying
dimensions representing emotional experience. The EmoStim database and
participant annotations are freely available for research purposes. The
database can be used to enrich our understanding of emotions further and serve
as a guide to select or create additional materials.


  Betweenness centrality is a fundamental centrality measure in social network
analysis. Given a large-scale network, how can we find the most central nodes?
This question is of key importance to numerous important applications that rely
on betweenness centrality, including community detection and understanding
graph vulnerability. Despite the large amount of work on designing scalable
approximation algorithms for betweenness centrality, estimating it on
large-scale networks remains a computational challenge.
  In this paper, we study the Betweenness Centrality Maximization problem:
given a graph $G=(V,E)$ and a positive integer $k$, find a set $S^* \subseteq
V$ that maximizes betweenness centrality subject to the cardinality constraint
$|S^*| \leq k$. We present an efficient randomized algorithm that provides a
$(1-1/e-\epsilon)$-approximation with high probability, where $\epsilon>0$. Our
results improve the current state-of-the-art result by
Yoshida~\cite{yoshida2014almost}. Furthermore, we provide theoretical evidence
for the validity of a crucial assumption in the literature of betweenness
centrality estimation, namely that in real-world networks $O(|V|^2)$ shortest
paths pass through the top-$k$ central nodes, where $k$ is a constant. On the
experimental side, we perform an extensive experimental analysis of our method
on real-world networks, demonstrate its accuracy and scalability, and study
different properties of central nodes. Finally, we provide three graph mining
applications of our method.


  The influence of the Hall effect on the global stability of cool Kepler disks
under the influence of an axial magnetic field is considered. For sufficiently
large magnetic Reynolds numbers Rm the magnetorotational instability (MRI)
exists in a finite interval of magnetic field amplitudes, $B$_{min} < $B$ <
$B$_{max}. For Kepler disks the pure MRI needs both rather high Rm
(representing the needed electrical conductivity) as well as $B$_{min} of order
0.1 G. The magnetic field pattern resulting from our global and linear
calculations is of quadrupolar parity. For magnetic fields $antiparallel$ to
the rotation axis the Hall effect reduces the minimum magnetic Reynolds number
by about one order of magnitude. The $B$_{min}, however, is even (sightly)
increased (see Fig. 6). For magnetic fields $parallel$ to the rotation axis the
Hall effect drives its own instability without the action of the Lorentz force.
The corresponding critical magnetic Reynolds number proves to be larger with
Hall effect (Rm ~ 10) than without Hall effect (Rm ~ 7) so that the Hall effect
for parallel fields even disturbs the formation of MHD-instability in cool
protoplanetary disks. If the disk is supercritical then the main result of the
Hall effect for positive fields is the strong reduction of the minimum magnetic
field amplitude which is necessary to start the instability. Observations must
show whether in star-forming regions the rotation axis and the magnetic field
orientation are correlated or are anticorrelated. If the magnetic fields are
high enough then our model predicts the dominance of fields antiparallel to the
rotation axis.


  The black hole X-ray binary source 4U 1543--47 experienced a super-Eddington
outburst in 2021, reaching a peak flux of up to $\sim1.96\times10^{-7}\rm erg\
\rm cm^{-2}\ \rm s^{-1}$ ($\sim 8.2$ Crab) in the 2--10\,keV band. Soon after
the outburst began, it rapidly transitioned into the soft state. Our goal is to
understand how the accretion disk structure deviates from a standard thin disk
when the accretion rate is near Eddington. To do so, we analyzed spectra
obtained from quasi-simultaneous observations conducted by the Hard X-ray
Modulation Telescope (Insight-HXMT), the Nuclear Spectroscopic Telescope Array
(NuSTAR), and the Neil Gehrels Swift Observatory (Swift). These spectra are
well-fitted by a model comprising a disk, a weak corona, and a reflection
component. We suggest that the reflection component is caused by disk
self-irradiation, that is by photons emitted from the inner disk which return
to the accretion disk surface, as their trajectories are bent by the strong
gravity field. In this scenario, the best-fitting parameters imply that the
reflected flux represents more than half of the total flux. Using general
relativistic ray-tracing simulations, we show that this scenario is viable when
the disk becomes geometrically thick, with a funnel-like shape, as the
accretion rate is near or above the Eddington limit. In the specific case of 4U
1543--47, an angle $\gtrsim$ 45 deg between the disk surface and the equatorial
plane can explain the required amount of self-irradiation.


  We consider an online binary prediction setting where a forecaster observes a
sequence of $T$ bits one by one. Before each bit is revealed, the forecaster
predicts the probability that the bit is $1$. The forecaster is called
well-calibrated if for each $p \in [0, 1]$, among the $n_p$ bits for which the
forecaster predicts probability $p$, the actual number of ones, $m_p$, is
indeed equal to $p \cdot n_p$. The calibration error, defined as $\sum_p |m_p -
p n_p|$, quantifies the extent to which the forecaster deviates from being
well-calibrated. It has long been known that an $O(T^{2/3})$ calibration error
is achievable even when the bits are chosen adversarially, and possibly based
on the previous predictions. However, little is known on the lower bound side,
except an $\Omega(\sqrt{T})$ bound that follows from the trivial example of
independent fair coin flips.
  In this paper, we prove an $\Omega(T^{0.528})$ bound on the calibration
error, which is the first super-$\sqrt{T}$ lower bound for this setting to the
best of our knowledge. The technical contributions of our work include two
lower bound techniques, early stopping and sidestepping, which circumvent the
obstacles that have previously hindered strong calibration lower bounds. We
also propose an abstraction of the prediction setting, termed the
Sign-Preservation game, which may be of independent interest. This game has a
much smaller state space than the full prediction setting and allows simpler
analyses. The $\Omega(T^{0.528})$ lower bound follows from a general reduction
theorem that translates lower bounds on the game value of Sign-Preservation
into lower bounds on the calibration error.


  In this paper, we study the question of classifying self-similar sets under
bi-Lipschitz mappings and obtain an important bi-Lipschitz invariant, which is
an ideal of a ring related to IFS. Roughly speaking, different Lipschitz
equivalence classes of self-similar sets correspond to different ideal classes
of a related ring. This result reveals an interesting relationship between the
Lipschitz classification problem in fractal geometry and the Gauss class number
problem in algebraic number theory.


  We introduce DeepProbLog, a neural probabilistic logic programming language
that incorporates deep learning by means of neural predicates. We show how
existing inference and learning techniques of the underlying probabilistic
logic programming language ProbLog can be adapted for the new language. We
theoretically and experimentally demonstrate that DeepProbLog supports (i) both
symbolic and subsymbolic representations and inference, (ii) program induction,
(iii) probabilistic (logic) programming, and (iv) (deep) learning from
examples. To the best of our knowledge, this work is the first to propose a
framework where general-purpose neural networks and expressive
probabilistic-logical modeling and reasoning are integrated in a way that
exploits the full expressiveness and strengths of both worlds and can be
trained end-to-end based on examples.


  In ABJM theory, enriched RG flows between circular 1/6 BPS bosonic and 1/2
BPS fermionic Wilson loops have been introduced in arXiv:2211.16501. These
flows are triggered by deformations corresponding to parametric 1/6 BPS
fermionic loops. In this paper we revisit the study of these operators, but
instead of circular contours we consider an interpolating cusped line and a
latitude and study their RG flow in perturbation theory. This allows for the
definition of a Bremsstrahlung function away from fixed points. We generalize
to this case the known cusp/latitude correspondence that relates the
Bremsstrahlung function to a latitude Wilson loop. We find that away from the
conformal fixed points the ordinary identity is broken by the conformal anomaly
in a controlled way. From a defect perspective, the breaking of the
correspondence can be traced back to the appearance of an anomalous dimension
for fermionic operators localized on the defect. As a by-product, we provide a
brand new result for the two-loop cusp anomalous dimension of the 1/6 BPS
fermionic and the 1/6 BPS bosonic Wilson lines.


  Artificial Intelligence (AI) incorporating genetic and medical information
have been applied in disease risk prediction, unveiling disease mechanism, and
advancing therapeutics. However, AI training relies on highly sensitive and
private data which significantly limit their applications and robustness
evaluation. Moreover, the data access management after sharing across
organization heavily relies on legal restriction, and there is no guarantee in
preventing data leaking after sharing. Here, we present Genie, a secure AI
platform which allows AI models to be trained on medical data securely. The
platform combines the security of Intel Software Guarded eXtensions (SGX),
transparency of blockchain technology, and verifiability of open algorithms and
source codes. Genie shares insights of genetic and medical data without
exposing anyone's raw data. All data is instantly encrypted upon upload and
contributed to the models that the user chooses. The usage of the model and the
value generated from the genetic and health data will be tracked via a
blockchain, giving the data transparent and immutable ownership.


  We prove that there exist uncountably many separable II$_1$ factors whose
ultrapowers (with respect to arbitrary ultrafilters) are non-isomorphic. In
fact, we prove that the families of non-isomorphic II$_1$ factors originally
introduced by McDuff \cite{MD69a,MD69b} are such examples. This entails the
existence of a continuum of non-elementarily equivalent II$_1$ factors, thus
settling a well-known open problem in the continuous model theory of operator
algebras.


  We investigate the generation of steady-state entanglement between two atoms
resulting from the fluctuation-mediated Casimir-Polder (CP) interactions near a
surface. Starting with an initially separable state of the atoms, we analyze
the atom-atom entanglement dynamics for atoms placed at distances in the range
of $\sim25$ nm away from a planar medium, examining the effect of medium
properties and geometrical configuration of the atomic dipoles. We show that
perfectly conducting and superconducting surfaces yield an optimal steady-state
concurrence value of approximately 0.5. Furthermore, although the generated
entanglement decreases with medium losses for a metal surface, we identify an
optimal distance from the metal surface that assists in entanglement generation
by the surface. While fluctuation-mediated interactions are typically
considered detrimental to the coherence of quantum systems at nanoscales, our
results demonstrate a mechanism for leveraging such interactions for
entanglement generation.


  In the first part of the talk I report on surprising relations between higher
spin (HS) theory and nonlinear realizations of the supergroup OSp(1|8), a
minimal superconformal extension of N=1, 4D supersymmetry with tensorial
charges. The second part is a review of the ``master'' model of HS particle
which makes manifest the classical equivalence of two previously known HS
particle formulations and gives rise to new massless HS multiplets.


  For a wide class of Hamiltonians, a novel method to obtain lower and upper
bounds for the lowest energy is presented. Unlike perturbative or variational
techniques, this method does not involve the computation of any integral (a
normalisation factor or a matrix element). It just requires the determination
of the absolute minimum and maximum in the whole configuration space of the
local energy associated with a normalisable trial function (the calculation of
the norm is not needed). After a general introduction, the method is applied to
three non-integrable systems: the asymmetric annular billiard, the many-body
spinless Coulombian problem, the hydrogen atom in a constant and uniform
magnetic field. Being more sensitive than the variational methods to any local
perturbation of the trial function, this method can used to systematically
improve the energy bounds with a local skilled analysis; an algorithm relying
on this method can therefore be constructed and an explicit example for a
one-dimensional problem is given.


  Current class-incremental learning research mainly focuses on single-label
classification tasks while multi-label class-incremental learning (MLCIL) with
more practical application scenarios is rarely studied. Although there have
been many anti-forgetting methods to solve the problem of catastrophic
forgetting in class-incremental learning, these methods have difficulty in
solving the MLCIL problem due to label absence and information dilution. In
this paper, we propose a knowledge restore and transfer (KRT) framework for
MLCIL, which includes a dynamic pseudo-label (DPL) module to restore the old
class knowledge and an incremental cross-attention(ICA) module to save
session-specific knowledge and transfer old class knowledge to the new model
sufficiently. Besides, we propose a token loss to jointly optimize the
incremental cross-attention module. Experimental results on MS-COCO and PASCAL
VOC datasets demonstrate the effectiveness of our method for improving
recognition performance and mitigating forgetting on multi-label
class-incremental learning tasks.


  We consider a countable discrete group $G$ acting ergodicaly and a.e. freely,
by measure-preserving transformations, on an infinite measure space $(\mathcal
X,\nu)$ with $\sigma$-finite measure $\nu$. Let $\Gamma \subseteq G$ be an
almost normal subgroup with fundamental domain $F\subseteq \mathcal X $ of
finite measure. Let $\mathcal R_G$ be the countable measurable equivalence
relation on $\mathcal X$ determined by the orbits of $G$. Let $\mathcal R_G| F$
be its restriction to $F$.
  We find an explicit presentation, by generators and relations, for the von
Neumann algebra associated, by the Feldman-Moore (\cite{FM}) construction, to
the relation $\mathcal R_G|_F$. The generators of the relation $\mathcal
R_G|_F$ are a set of transformations of the quotient space $F\cong \mathcal X/
\Gamma$, in a one to one correspondence with the cosets of $\Gamma$ in $G$. We
prove that the composition formula for these transformations is an averaged
version, with coefficients in $L^\infty(F,\nu)$, of the Hecke algebra product
formula (\cite{BC}).
  In the situation $G = PGL_2(\mathbb Z[\frac1p])$, $\Gamma=PSL_2(\mathbb Z)$,
$p\geq 3$ prime number, the relation $\mathcal R_G|_F$ is the equivalence
relation associated to a free, measure-preserving action of a free group on
$(p+1)/2$ generators on $F$ (\cite{Ad},\cite {Hj}). We use the coset
representations of the transformations generating $\mathcal R_G|_F$ to find a
canonical treeing (\cite{Ga}).


  Within the framework of the gauge-invariant, but path-dependent, variables
formalism, we study the manifestations of vacuum electromagnetic nonlinearities
in $D=3$ models. For this we consider both generalized Born-Infeld and
Pagels-Tomboulis-like electrodynamics, as well as, an Euler-Heisenberg-like
electrodynamics. We explicitly show that generalized Born-Infeld and
Pagels-Tomboulis-like electrodynamics are equivalent, where the static
potential profile contains a long-range (${\raise0.5ex\hbox{$\scriptstyle
1$}\kern-0.1em/\kern-0.15em\lower0.25ex\hbox{$\scriptstyle {{r^2}}$}}$-type)
correction to the Coulomb potential. Interestingly enough, for an
Euler-Heisenberg-like electrodynamics the interaction energy contains a linear
potential, leading to the confinement of static charges.


  In this paper we define the notion of pullback lifting of a lifting crossed
module over a crossed module morphism and interpret this notion in the category
of group-groupoid actions as pullback action. Moreover, we give a criterion for
the lifting of homotopic crossed module morphisms to be homotopic, which will
be called homotopy lifting property for crossed module morphisms. Finally, we
investigate some properties of derivations of lifting crossed modules according
to base crossed module derivations.


  Mobile robots rely on odometry to navigate through areas where localization
fails. Visual odometry (VO) is a common solution for obtaining robust and
consistent relative motion estimates of the vehicle frame. Contrarily, Global
Positioning System (GPS) measurements are typically used for absolute
positioning and localization. However, when the constraint on absolute accuracy
is relaxed, time-differenced carrier phase (TDCP) measurements can be used to
find accurate relative position estimates with one single-frequency GPS
receiver. This suggests practitioners may want to consider GPS odometry as an
alternative or in combination with VO. We describe a robust method for
single-receiver GPS odometry on an unmanned ground vehicle (UGV). We then
present an experimental comparison of the two strategies on the same test
trajectories. After 1.8km of testing, the results show our GPS odometry method
has a 75% lower drift rate than a proven stereo VO method while maintaining a
smooth error signal despite varying satellite availability.


  We present an approach to Morse theory on symmetric products of surfaces
using the notion of folded ribbon trees. We introduce an $A_\infty$-category
with objects defined as $\kappa$-tuples of Morse functions, where the
differential of the tuple has no self-intersection. We show that when the graph
of the differential of the $\kappa$-tuple of Morse functions on
$T^*\mathbb{R}^2$ is the wrapped $\kappa$ disjoint cotangent fibers, its
endormorphism is the Hecke algebra associated to the symmetric group
$\mathfrak{S}_\kappa$.


  We discuss electronic transport through a lateral quantum dot close to the
singlet-triplet degeneracy in the case of a single conduction channel per lead.
By applying the Numerical Renormalization Group, we obtain rigorous results for
the linear conductance and the density of states. A new quantum phase
transition of the Kosterlitz-Thouless type is found, with an exponentially
small energy scale $T^*$ close to the degeneracy point. Below $T^*$, the
conductance is strongly suppressed, corresponding to a universal dip in the
density of states. This explains recent transport measurements.


  We study Whittaker--Fourier coefficients of automorphic forms on a
quasi-split unitary group. We reduce the analogue of the Ichino--Ikeda
conjectures to a conjectural local statement using the descent method of
Ginzburg--Rallis--Soudry.


  Network control theory (NCT) offers a robust analytical framework for
understanding the influence of network topology on dynamic behaviors, enabling
researchers to decipher how certain patterns of external control measures can
steer system dynamics towards desired states. Distinguished from other
structure-function methodologies, NCT's predictive capabilities can be coupled
with deploying Graph Neural Networks (GNNs), which have demonstrated
exceptional utility in various network-based learning tasks. However, the
performance of GNNs heavily relies on the expressiveness of node features, and
the lack of node features can greatly degrade their performance. Furthermore,
many real-world systems may lack node-level information, posing a challenge for
GNNs.To tackle this challenge, we introduce a novel approach, NCT-based
Enhanced Feature Augmentation (NCT-EFA), that assimilates average
controllability, along with other centrality indices, into the feature
augmentation pipeline to enhance GNNs performance. Our evaluation of NCT-EFA,
on six benchmark GNN models across two experimental setting. solely employing
average controllability and in combination with additional centrality metrics.
showcases an improved performance reaching as high as 11%. Our results
demonstrate that incorporating NCT into feature enrichment can substantively
extend the applicability and heighten the performance of GNNs in scenarios
where node-level information is unavailable.


  A search for long-lived particles decaying into hadrons and at least one muon
is presented. The analysis selects events that pass a muon or
missing-transverse-momentum trigger and contain a displaced muon track and a
displaced vertex. The analyzed dataset of proton-proton collisions at $\sqrt{s}
= 13$ TeV was collected with the ATLAS detector and corresponds to 136
fb$^{-1}$. The search employs dedicated reconstruction techniques that
significantly increase the sensitivity to long-lived particle decays that occur
in the ATLAS inner detector. Background estimates for Standard Model processes
and instrumental effects are extracted from data. The observed event yields are
compatible with those expected from background processes. The results are
presented as limits at 95% confidence level on model-independent cross sections
for processes beyond the Standard Model, and interpreted as exclusion limits in
scenarios with pair-production of long-lived top squarks that decay via a small
$R$-parity-violating coupling into a quark and a muon. Top squarks with masses
up to 1.7 TeV are excluded for a lifetime of 0.1 ns, and masses below 1.3 TeV
are excluded for lifetimes between 0.01 ns and 30 ns.


  Unmanned Aerial Vehicles (UAVs) have emerged as adequate platforms to carry
communications nodes, including Wi-Fi Access Points and cellular Base Stations.
This has led to the concept of flying networks composed of UAVs as a flexible
and agile solution to provide on-demand wireless connectivity anytime,
anywhere. However, state of the art works have been focused on optimizing the
placement of the access network providing connectivity to ground users,
overlooking the backhaul network design. In order to improve the overall
Quality of Service (QoS) offered to ground users, the placement of Flying
Gateways (FGWs) and the size of the queues configured in the UAVs need to be
carefully defined to meet strict performance requirements. The main
contribution of this article is a traffic-aware gateway placement and queue
management (GPQM) algorithm for flying networks. GPQM takes advantage of
knowing in advance the positions of the UAVs and their traffic demand to
determine the FGW position and the queue size of the UAVs, in order to maximize
the aggregate throughput and provide stochastic delay guarantees. GPQM is
evaluated by means of ns-3 simulations, considering a realistic wireless
channel model. The results demonstrate significant gains in the QoS offered
when GPQM is used.


  Quantum key distribution (QKD) permits information-theoretically secure
transmission of digital encryption keys, assuming that the behaviour of the
devices employed for the key exchange can be reliably modelled and predicted.
Remarkably, no assumptions have to be made on the capabilities of an
eavesdropper other than that she is bounded by the laws of Nature, thus making
the security of QKD "unconditional". However, unconditional security is hard to
achieve in practice. For example, any experimental realisation can only collect
finite data samples, leading to vulnerabilities against coherent attacks, the
most general class of attacks, and for some protocols the theoretical proof of
robustness against these attacks is still missing. For these reasons, in the
past many QKD experiments have fallen short of implementing an unconditionally
secure protocol and have instead considered limited attacking capabilities by
the eavesdropper. Here, we explore the security of QKD against coherent attacks
in the most challenging environment: the long-distance transmission of keys. We
demonstrate that the BB84 protocol can provide positive key rates for distances
up to 240 km without multiplexing of conventional signals, and up to 200 km
with multiplexing. Useful key rates can be achieved even for the longest
distances, using practical thermo-electrically cooled single-photon detectors.


  Topological magnetic insulators host chiral gapless edge modes. In the
presence of strong interaction effects, the spin of these modes may
fractionalize. Studying a 2D array of coupled insulating spin-1/2 chains, we
show how spatially modulated magnetic fields and Dzyaloshinskii-Moriya
interactions can be exploited to realize chiral spin liquids or integer and
fractional spin quantum Hall effect phases. These are characterized by a gapped
bulk spectrum and gapless chiral edge modes with fractional spin. The spin
fractionalization is manifested in the quantized spin conductance, which can be
used to probe the fractional spin quantum Hall effect. We analyze the system
via bosonization and perturbative renormalization group techniques that allow
us to identify the most relevant terms induced by the spin-spin interactions
that open gaps and render the system topological under well-specified resonance
conditions. We show explicitly that the emerging phase is a genuine chiral spin
liquid. We suggest that the phases can be realized experimentally in synthetic
spin chains and ultracold atom systems.


  We investigate how the properties of spiral arms relate to other fundamental
galaxy properties. To this end, we use previously published measurements of
those properties, and our own measurements of arm-interarm luminosity contrasts
for a large sample of galaxies, using 3.6$\mu$m images from the Spitzer Survey
of Stellar Structure in Galaxies. Flocculent galaxies are clearly distinguished
from other spiral arm classes, especially by their lower stellar mass and
surface density. Multi-armed and grand-design galaxies are similar in most of
their fundamental parameters, excluding some bar properties and the
bulge-to-total luminosity ratio. Based on these results, we discuss dense,
classical bulges as a necessary condition for standing spiral wave modes in
grand-design galaxies. We further find a strong correlation between
bulge-to-total ratio and bar contrast, and a weaker correlation between arm and
bar contrasts.


  Magnetic graphene-ribbon is a candidate for realizing future ultra high
density 100 tera bit/inch2 class data storage media. In order to increase the
saturation magnetization, first principles DFT analysis was done for Fe, Co,
Ni-modified zigzag edge graphene-ribbon. Typical unit cell is [C32H2Fe1],
[C32H2Co1] and [C32H2Ni1] respectively. Most stable spin state was Sz=4/2 for
Fe-modified case, whereas Sz=3/2 for Co-case and Sz=2/2 for Ni-case. Magnetic
moment of Fe,Co, and Ni were 3.63, 2.49 and 1.26 {\mu}B, which can be explained
by the Hund-rule considering charge donation to neighboring carbons. Band
calculation shows half-metal like structure with a large band gap (in Co-case,
0.55eV) for up-spin, whereas very small gap (0.05eV) for down-spin, which will
be useful for many featured application like information storage, spin filter
and magneto-resistance devices. Dual layer Fe-modified ribbon shows a tube like
curved structure, which may suggest a carbon nanotube creation by Fe catalyst.


  We present multifrequency observations with the Giant Metrewave Radio
Telescope (GMRT) and the Very Large Array (VLA) of a sample of seventeen
largely giant radio sources (GRSs). These observations have either helped
clarify the radio structures or provided new information at a different
frequency. The broad line radio galaxy, J0313+413, has an asymmetric, curved
radio jet and a variable radio core, consistent with a moderate angle of
inclination to the line of sight. We attempt to identify steep spectrum radio
cores (SSCs), which may be a sign of recurrent activity, and find four
candidates. If confirmed, this would indicate a trend for SSCs to occur
preferentially in GRSs. From the structure and integrated spectra of the
sources we suggest that the lobes of emission in J0139+399 and J0200+408 may be
due to an earlier cycle of nuclear activity. We find that inverse-Compton
losses with the cosmic microwave background radiation dominate over synchrotron
radiative losses in the lobes of all the sources, consistent with earlier
studies. We also show that prominence of the bridge emission decreases with
increasing redshift, possibly due to inverse-Compton losses. This could affect
the appearance and identification of GRSs at large redshifts.


  For cyclic totally real number fields $K$ with odd prime degree $n$, odd
class number, $2$ inert, and the property that every totally positive unit is a
square, the density of rational primes $p$ that satisfy the spin relation
spin$(\mathfrak{p},\sigma)$spin$(\mathfrak{p},\sigma^{-1})=1$ for all
$\sigma\neq 1 \in$ Gal$(K/\mathbb{Q})$ where $\mathfrak{p}$ is a prime of $K$
above $p$ is given by the formula \[ D_K=\frac{m_Kn+1}{n2^n} \] where $m_K$ is
a computable and bounded invariant of the number field $K$. This formula is
modified in the erratum from the original version due to an error in the inert
case. As the inert case is insubstantial, the strength of the results is not
significantly changed.


  We tested the validity of the three Larson relations in a sample of 213
massive clumps selected from the Herschel Hi-GAL survey and combined with data
from the MALT90 survey of 3mm emission lines. The clumps have been divided in 5
evolutionary stages to discuss the Larson relations also as function of
evolution. We show that this ensemble does not follow the three Larson
relations, regardless of clump evolutionary phase. A consequence of this
breakdown is that the virial parameter $\alpha_{vir}$ dependence with mass (and
radius) is only a function of the gravitational energy, independent of the
kinetic energy of the system, and $\alpha_{vir}$ is not a good descriptor of
clump dynamics. Our results suggest that clumps with clear signatures of infall
motions are statistically indistinguishable from clumps with no such
signatures. The observed non-thermal motions are not necessarily ascribed to
turbulence acting to sustain the gravity, but they may be due to the
gravitational collapse at the clump scales. This seems particularly true for
the most massive (M$\geq$1000 M$_{\odot}$) clumps in the sample, where also
exceptionally high magnetic fields may not be enough to stabilize the collapse.


  In this paper, we consider the diffractive photoproduction of quark-antiquark
pairs in peripheral heavy ion collisions. The color field of the nuclei is
treated within the Colored Glass Condensate model. The cross-section turns out
to be very sensitive to the value of the saturation scale.


  A combined statistical analysis of the experimental results of the LSND and
KARMEN numubar->nuebar oscillation search is presented. LSND has evidence for
neutrino oscillations that is not confirmed by the KARMEN experiment. However,
there is a region in the (sin^2(2theta),Dm^2) parameter space where the results
of both experiments are statistically compatible. This joint analysis is based
on likelihood functions for both data sets. A frequentist approach creating
Monte Carlo samples analogous to the experimental outcome is applied to deduce
correct confidence limits. Different schemes of combination can be chosen to
provide correct coverage which lead to slightly different confidence regions in
(sin^2(2theta),Dm^2).