  We develop a model for the coupling of quasi-normal modes in open photonic
systems consisting of two resonators. By expressing the modes of the coupled
system as a linear combination of the modes of the individual particles, we
obtain a generalized eigenvalue problem involving small size dense matrices. We
apply this technique to dielectric rod dimmer of rectangular cross section for
Transverse Electric (TE) polarization in a two-dimensional (2D) setup. The
results of our model show excellent agreement with full-wave finite element
simulations. We provide a convergence analysis, and a simplified model with a
few modes to study the influence of the relative position of the two
resonators. This model provides interesting physical insights on the coupling
scheme at stake in such systems and pave the way for systematic and efficient
design and optimization of resonances in more complicated systems, for
applications including sensing, antennae and spectral filtering.


  We show that during cosmological inflation the nonsymmetric metric tensor
theory of gravitation develops a spectrum which is potentially observable by
cosmic microwave background observations, and may be the most sensitive probe
of the scale of cosmic inflation.


  We derive line-element's templates of space-time models with Space models
complying with Helmholtz's Free mobility postulate, and discuss some of the
Time models compatible with them.


  In addition to magnetic field and electric charge noise adversely affecting
spin qubit operations, performing single-qubit gates on one of multiple coupled
singlet-triplet qubits presents a new challenge---crosstalk, which is
inevitable (and must be minimized) in any multiqubit quantum computing
architecture. We develop a set of dynamically-corrected pulse sequences that
are designed to cancel the effects of both types of noise (i.e., field and
charge) as well as crosstalk to leading order, and provide parameters for these
corrected sequences for all 24 of the single-qubit Clifford gates. We then
provide an estimate of the error as a function of the noise and capacitive
coupling to compare the fidelity of our corrected gates to their uncorrected
versions. Dynamical error correction protocols presented in the current work
are important for the next generation of singlet-triplet qubit devices where
coupling among many qubits will become relevant.


  Fully resolved simulation of flows with buoyant particles is a challenging
problem since buoyant particles are lighter than the surrounding fluid, and as
a result, the two phases are strongly coupled together. In this work, the
virtual force stabilization technique introduced by Schwarz et al. [Schwarz,
S., Kempe, T., & Fr\"ohlich, J. (2015). A temporal discretization scheme to
compute the motion of light particles in viscous flows by an immersed boundary
method. J. Comput. Phys., 281, 591-613] is extended to simulate buoyant
particle suspensions with high volume fractions (up to $40 \%$). It is
concluded that the dimensionless numerical model constant $C_v$ in the virtual
force technique should increase with volume fraction. The behavior of a single
rising particle, two in-line rising particles, and buoyant particle suspensions
are studied. In each case, results are compared with experimental works on
bubbly flows to highlight the differences and similarities between buoyant
particles and bubbles. Finally, the drag coefficient is extracted from
simulations of buoyant particle suspensions at different volume fractions and
based on that a drag correlation is presented.


  We present a technique for speeding up the convergence of value iteration for
partially observable Markov decisions processes (POMDPs). The underlying idea
is similar to that behind modified policy iteration for fully observable Markov
decision processes (MDPs). The technique can be easily incorporated into any
existing POMDP value iteration algorithms. Experiments have been conducted on
several test problems with one POMDP value iteration algorithm called
incremental pruning. We find that the technique can make incremental pruning
run several orders of magnitude faster.


  Recently, convolutional neural networks (CNNs) have been widely used in sound
event detection (SED). However, traditional convolution is deficient in
learning time-frequency domain representation of different sound events. To
address this issue, we propose multi-dimensional frequency dynamic convolution
(MFDConv), a new design that endows convolutional kernels with
frequency-adaptive dynamic properties along multiple dimensions. MFDConv
utilizes a novel multi-dimensional attention mechanism with a parallel strategy
to learn complementary frequency-adaptive attentions, which substantially
strengthen the feature extraction ability of convolutional kernels. Moreover,
in order to promote the performance of mean teacher, we propose the confident
mean teacher to increase the accuracy of pseudo-labels from the teacher and
train the student with high confidence labels. Experimental results show that
the proposed methods achieve 0.470 and 0.692 of PSDS1 and PSDS2 on the DESED
real validation dataset.


  We discuss prospects for probing Z-prime and non-standard neutrino
interactions using neutrino-nucleus coherent scattering with ultra-low energy
(~ 10 eV) threshold Si and Ge detectors. The analysis is performed in the
context of a specific and contemporary reactor-based experimental proposal,
developed in cooperation with the Nuclear Science Center at Texas A&M
University, and referencing available technology based upon economical and
scalable detector arrays. For expected exposures, we show that sensitivity to
the Z-prime mass is on the order of several TeV, and is complementary to the
LHC search with low mass detectors in the near term. This technology is also
shown to provide sensitivity to the neutrino magnetic moment, at a level that
surpasses terrestrial limits, and is competitive with more stringent
astrophysical bounds. We demonstrate the benefits of combining silicon and
germanium detectors for distinguishing between classes of models of new
physics, and for suppressing correlated systematic uncertainties.


  We consider the regularity of sample paths of Volterra processes. These
processes are defined as stochastic integrals $$ M(t)=\int_{0}^{t}F(t,r)dX(r),
\ \ t \in \mathds{R}_{+}, $$ where $X$ is a semimartingale and $F$ is a
deterministic real-valued function. We derive the information on the modulus of
continuity for these processes under regularity assumptions on the function $F$
and show that $M(t)$ has "worst" regularity properties at times of jumps of
$X(t)$. We apply our results to obtain the optimal H\"older exponent for
fractional L\'{e}vy processes.


  We study the transverse momentum distribution for a $pair$ of heavy quarks
produced in hadron-hadron interactions. Predictions for the large transverse
momentum region are based on exact order $\alpha_s^3$ QCD perturbation theory.
For the small transverse momentum region, we use techniques for all orders
resummation of leading logarithmic contributions associated with initial state
soft gluon radiation. The combination provides the transverse momentum
distribution of heavy quark pairs for all transverse momenta. Explicit results
are presented for $b\bar b$ pair production at the Fermilab Tevatron collider
and for $c\bar c$ pair production at fixed target energies.


  We present a large-scale study of the X-ray properties and near-IR-to-radio
SEDs of submillimetre galaxies (SMGs) detected at 1.1mm with the AzTEC
instrument across a ~1.2 square degree area of the sky. Combining deep 2-4 Ms
Chandra data with Spitzer IRAC/MIPS and VLA data within the GOODS-N/S and
COSMOS fields, we find evidence for AGN activity in ~14 percent of 271 AzTEC
SMGs, ~28 percent considering only the two GOODS fields. Through X-ray spectral
modeling and SED fitting using Monte Carlo Markov Chain techniques to
Siebenmorgen et al. (2004) (AGN) and Efstathiou et al. (2000) (starburst)
templates, we find that while star formation dominates the IR emission, with
SFRs ~100-1000 M_sun/yr, the X-ray emission for most sources is almost
exclusively from obscured AGNs, with column densities in excess of 10^23 cm^-2.
Only for ~6 percent of our sources do we find an X-ray-derived SFR consistent
with NIR-to-radio SED derived SFRs. Inclusion of the X-ray luminosities as a
prior to the NIR-to-radio SED effectively sets the AGN luminosity and SFR,
preventing significant contribution from the AGN template. Our SED modeling
further shows that the AGN and starburst templates typically lack the required
1.1 mm emission necessary to match observations, arguing for an extended, cool
dust component. The cross correlation function between the full samples of
X-ray sources and SMGs in these fields does not indicate a strong correlation
between the two populations at large scales, suggesting that SMGs and AGNs do
not necessarily trace the same underlying large scale structure. Combined with
the remaining X-ray-dim SMGs, this suggests that sub-mm bright sources may
evolve along multiple tracks, with X-ray-detected SMGs representing
transitionary objects between periods of high star formation and AGN activity
while X-ray-faint SMGs represent a brief starburst phase of more normal
galaxies.


  For one-dimensional Jump-Drift and Jump-Diffusion processes converging
towards some steady state, the large deviations of a long dynamical trajectory
are described from two perspectives. Firstly, the joint probability of the
empirical time-averaged density, of the empirical time-averaged current and of
the empirical time-averaged jump-flow are studied via the large deviations at
Level 2.5. Secondly, the joint probability of the empirical jumps and of the
empirical excursions between consecutive jumps are analyzed via the large
deviations at Level 2.5 for the alternate Markov chain that governs the series
of all the jump events of a long trajectory. These two general frameworks are
then applied to three examples of positive jump-drift processes without
diffusion, and to two examples of jump-diffusion processes, in order to
illustrate various simplifications that may occur in rate functions and in
contraction procedures.


  As the largest radio telescope in the world, the Square Kilometre Array (SKA)
will lead the next generation of radio astronomy. The feats of engineering
required to construct the telescope array will be matched only by the
techniques developed to exploit the rich scientific value of the data. To drive
forward the development of efficient and accurate analysis methods, we are
designing a series of data challenges that will provide the scientific
community with high-quality datasets for testing and evaluating new techniques.
In this paper we present a description and results from the first such Science
Data Challenge (SDC1). Based on SKA MID continuum simulated observations and
covering three frequencies (560 MHz, 1400MHz and 9200 MHz) at three depths (8
h, 100 h and 1000 h), SDC1 asked participants to apply source detection,
characterization and classification methods to simulated data. The challenge
opened in November 2018, with nine teams submitting results by the deadline of
April 2019. In this work we analyse the results for 8 of those teams,
showcasing the variety of approaches that can be successfully used to find,
characterise and classify sources in a deep, crowded field. The results also
demonstrate the importance of building domain knowledge and expertise on this
kind of analysis to obtain the best performance. As high-resolution
observations begin revealing the true complexity of the sky, one of the
outstanding challenges emerging from this analysis is the ability to deal with
highly resolved and complex sources as effectively as the unresolved source
population.


  Learning the activities of animals is important for the purpose of monitoring
their welfare vis a vis their behaviour with respect to their environment and
conspecifics. While previous works have largely focused on activity recognition
in a single animal, little or no work has been done in learning the collective
behaviour of animals. In this work, we address the problem of recognising the
collective movement activities of a group of sheep in a flock. We present a
discriminative framework that learns to track the positions and velocities of
all the animals in the flock in an online manner whilst estimating their
collective activity. We investigate the performance of two simple deep network
architectures and show that we can learn the collective activities with good
accuracy even when the distribution of the activities is skewed.


  A formula for the laser linewidth of arbitrary cavities in the multimode
non-linear regime is derived from a scattering analysis of the solutions to
semiclassical laser theory. The theory generalizes previous treatments of the
effects of gain and openness described by the Petermann factor. The linewidth
is expressed using quantities based on the non-linear scattering matrix, which
can be computed from steady-state ab initio laser theory; unlike previous
treatments, no passive cavity or phenomenological parameters are involved. We
find that low cavity quality factor, combined with significant dielectric
dispersion, can cause substantial deviations from the Schawlow-Townes-Petermann
theory.


  We work out the non-equilibrium steady state properties of a harmonic lattice
which is connected to heat reservoirs at different temperatures. The heat
reservoirs are themselves modeled as harmonic systems. Our approach is to write
quantum Langevin equations for the system and solve these to obtain steady
state properties such as currents and other second moments involving the
position and momentum operators. The resulting expressions will be seen to be
similar in form to results obtained for electronic transport using the
non-equilibrium Green's function formalism. As an application of the formalism
we discuss heat conduction in a harmonic chain connected to self-consistent
reservoirs. We obtain a temperature dependent thermal conductivity which, in
the high-temperature classical limit, reproduces the exact result on this model
obtained recently by Bonetto, Lebowitz and Lukkarinen.


  The quadratic Mandelbrot set has been referred to as the most complex and
beautiful object in mathematics and the Riemann Zeta function takes the prize
for the most complicated and enigmatic function. Here we elucidate the spectrum
of Mandelbrot and Julia sets of Zeta, to unearth the geography of its chaotic
and fractal diversities, combining these two extremes into one intrepid journey
into the deepest abyss of complex function space.


  Cell alignment often forms nematic order, which can lead to anomalous
collective cell flow due to the so-called active force. Although it is
appreciated that cell migration is driven by traction force, a quantitative
evaluation of the relationships between the traction force, the nematic
patterning, and the cell flow velocity is still elusive. Here we have found
that cellular traction force aligns almost perfectly and is proportional in
amplitude to the gradient of the nematic order tensor, not only near the
topological defects but also globally. Furthermore, the flow in the monolayer
was best described by adding nonlinear forces and a diffusion term derived from
symmetry considerations. These nonlinear active forces enhance density
instability but suppress bending instability, explaining why cell accumulation
and dispersion can occur in neural progenitor cell culture while their ordering
pattern is stable.


  The Penning trap mass spectrometer JYFLTRAP was used to measure the atomic
masses of radioactive nuclei with an uncertainty better than 10 keV. The atomic
masses of the neutron-deficient nuclei around the N = Z line were measured to
improve the understanding of the rp-process path and the SbSnTe cycle.
Furthermore, the masses of the neutron-rich gallium (Z = 31) to palladium (Z =
46) nuclei have been measured. The physics impacts on the nuclear structure and
the r-process paths are reviewed. A better understanding of the nuclear
deformation is presented by studying the pairing energy around A = 100.


  We have performed 1-dimensional calculations for explosive nucleosynthesis in
collapse-driven supernova and investigated its sensitivity to the initial form
of the shock wave. We have found the tendency that the peak temperature becomes
higher around the mass cut if the input energy is injected more in the form of
kinetic energy rather than internal energy. Then, the mass cut becomes larger,
and, as a result, neutron-rich matter is less included in the ejecta; this is
favorable for producing the observational data compared with a previous model.
Our results imply that the standard method to treat various processes for
stellar evolution, such as convection and electron capture during the silicon
burning stage, are still compatible with the calculation of explosive
nucleosynthesis.


  In this work, we present a joint channel estimation, activity detection and
data decoding scheme for massive machine-type communications. By including the
channel and the a priori activity factor in the factor graph, we present the
bilinear message-scheduling GAMP (BiMSGAMP), a message-passing solution that
uses the channel decoder beliefs to refine the activity detection and data
decoding. We include two message-scheduling strategies based on the residual
belief propagation and the activity user detection in which messages are
evaluated and scheduled in every new iteration. An analysis of the convergence
of BiMSGAMP along with a study of its computational complexity is carried out.
Numerical results show that BiMSGAMP outperforms state-of-the-art algorithms,
highlighting the gains achieved by using the dynamic scheduling strategies and
the effects of the channel decoding part in the system.


  This short paper reviews some of the results obtained from ISO observations
(ISOCAM and ISOPHOT) on galaxy clusters: Chap.1: "Intracluster dust": new
evidence for the presence of dust outside galaxies. Chap.2:"Mid-Infrared
Emission of Galaxies" origin of the mid-IR emission. Chap.3:"Star Formation in
Nearby Clusters" correlation of the 7 and 15 microns fluxes with the SFR.
Chap.4:"Star Formation in z=0.2 Galaxy clusters" Study of the mid-IR emission
of A1732 and A1689. Chap.5:"Star Formation in z>0.4 Galaxy clusters"
Preliminary.


  We consider the class of convex minimization problems, composed of a
self-concordant function, such as the $\log\det$ metric, a convex data fidelity
term $h(\cdot)$ and, a regularizing -- possibly non-smooth -- function
$g(\cdot)$. This type of problems have recently attracted a great deal of
interest, mainly due to their omnipresence in top-notch applications. Under
this \emph{locally} Lipschitz continuous gradient setting, we analyze the
convergence behavior of proximal Newton schemes with the added twist of a
probable presence of inexact evaluations. We prove attractive convergence rate
guarantees and enhance state-of-the-art optimization schemes to accommodate
such developments. Experimental results on sparse covariance estimation show
the merits of our algorithm, both in terms of recovery efficiency and
complexity.


  We calculate the zero point energy of a massive scalar field in the
background of an infinitely thin spherical shell given by a potential of the
delta function type. We use zeta functional regularization and express the
regularized ground state energy in terms of the Jost function of the related
scattering problem. Then we find the corresponding heat kernel coefficients and
perform the renormalization, imposing the normalization condition that the
ground state energy vanishes when the mass of the quantum field becomes large.
Finally the ground state energy is calculated numerically. Corresponding plots
are given for different values of the strength of the background potential, for
both attractive and repulsive potentials.


  Search for azimuthal asymmetries in semi-inclusive production of charged
hadrons by 160 GeV muons on the longitudinally polarized deuterium target, has
been performed using the 2002- 2004 COMPASS data. The observed asymmetries
integrated over the kinematical variables do not depend on the azimuthal angle
of produced hadrons and are consistent with the ratio $g_1^d(x)/f_1^d(x)$. The
asymmetries are parameterized taking into account possible contributions from
different parton distribution functions and parton fragmentation functions
depending on the transverse spin of quarks.They can be modulated
(either/or/and) with $\sin(\phi), \sin(2\phi), \sin(3\phi)$ and $\cos(\phi)$.
The $x$-, $z$- and $p_h^T$-dependencies of these amplitudes are studied.


  We consider massive higher-spin multiplets coupled to quantum gravity and
compute their contributions to the gravitational beta functions at one loop.
Such theories, if quantized with the Feynman prescription, would contain
ghosts. Instead, those degrees of freedom are turned into purely virtual
particles by means of the fakeon prescription and the resulting theories are
both renormalizable and unitary. We extract the necessary number of fields to
obtain asymptotic freedom by solving the relevant renormalization-group
equations in the ultraviolet limit. We show that in the case of irreducible
rank-$s$ bosons with minimal kinetic term only a certain number of fields with
$0\leq s \leq 3$ is compatible with asymptotic freedom. No solution involving
fermionic rank-$s$ fields are found. We also consider the cases of rank-$1$ and
symmetric rank-$2$ tensor fields with nonminimal kinetic terms and repeat the
analysis, finding that the allowed number of fields is enlarged. Possible
implications for metric affine theories of gravity are pointed out.


  We examine the relic density of the light mass dark matter region in the
inert doublet model (IDM) when the dominant process is due to co-annihilation
between the lightest neutral scalars of the model. The full one-loop
electroweak corrections are computed in an on-shell scheme and are found to be
well approximated as an effective cross-section expressed in terms of
$Z$-observables. The electroweak corrections to the subdominant process which
consists of an annihilation into an on-shell $W$ and an off-shell $W$, that is
calculated as a annihilation into a 3-body final state, is also performed. The
latter reveals an important dependence on a parameter that describes the
self-interaction of the new scalars (solely within the dark sector), a
parameter which is not accessible in tree-level calculations of standard model
(SM)-IDM interactions.


  The gauge boson production at forward rapidities in single diffractive events
at the LHC is investigated considering $pp$ collisions at $\sqrt{s} =$ 8 and 13
TeV. The impact of gap survival effects is analysed using two different models
for the soft rescattering contributions. We demonstrate that using the Forward
Shower Counter Project at LHCb -- HERSCHEL, together with the Vertex Locator --
VELO, it is possible to discriminate diffractive production of the gauge bosons
$W$ and $Z$ from the non-diffractive processes and studies of the Pomeron
structure and diffraction phenomenology are feasible. Moreover, we show that
the analysis of this process can be useful to constrain the modelling of the
gap survival effects.


  Let $A$ be a set and $V$ a real Hilbert space. Let $H$ be a real Hilbert
space of functions $f:A\to V$ and assume $H$ is continuously embedded in the
Banach space of bounded functions. For $i=1,\cdots,n$, let $(x_i,y_i)\in
A\times V$ comprise our dataset. Let $0<q<1$ and $f^*\in H$ be the unique
global minimizer of the functional \begin{equation*} u(f) = \frac{q}{2}\Vert
f\Vert_{H}^{2} + \frac{1-q}{2n}\sum_{i=1}^{n}\Vert f(x_i)-y_i\Vert_{V}^{2}.
\end{equation*}
  For $x\in A$ and $v\in V$ let $\Phi(x,v)\in H$ be the unique element such
that $(\Phi(x,v),f)_{H}=(f(x),v)_{V}$ for all $f\in H$. In this paper we show
that for each $k\in\mathbb{N}$, $k\geq 2$ one has a random function $F_{k}\in
H$ with the structure \begin{equation*} F_{k} = \sum_{h=1}^{N_k} \Lambda_{k, h}
\Phi(x_{I_h}, \mathcal{E}_{h}) \end{equation*} (where $0\leq N_k\leq k-1$ are
Binomially distributed with success probability $1-q$, $\Lambda_{k,
h}\in\mathbb{R}$ are random coefficients, $1\leq I_{h}\leq n$ are independent
and uniformly distributed and $\mathcal{E}_{h}\in V$ are random vectors) such
that asymptotically for large $k$ we have \begin{equation*} E\left[ \Vert
F_{k}-f^*\Vert_{H}^{2} \right] = O(\frac{1}{k}). \end{equation*} Thus we
achieve the Monte Carlo type error estimate with no metric or measurability
structure on $A$, possibly infinite dimensional $V$ and the ingredients of
approximating functions are just the Riesz representatives $\Phi(x,v)\in H$. We
obtain this result by considering the stochastic gradient descent sequence in
the Hilbert space $H$ to minimize the functional $u$.


  The relation between quark masses and CKM mixing is studied based on an
approximate chiral $SO(2)_L\times SO(2)_R$ flavor symmetry of quark mass
matrix. In mass hierarchy limit, the mass ratio effect to CKM mixing is
suppressed, which separates mass hierarchy and quark flavor mixing into two
independent problems. We show that CKM mixing is dominated by two left-handed
$SO(2)_L^{u,d}$ symmetry while mass hierarchy only provides slight corrections.
The same mixing structure is generalized to lepton sector with extended Dirac
neutrinos. The common flavor mixing provides a novel comprehension on the
relation between quark CKM mixing and lepton PMNS mixing.


  We study both the spin-average and spin-dependent structure functions of the
lithium isotopes, $^{6-11}$Li, which could be measured at RIKEN and other
nuclear facilities in the future. It is found that the light-cone momentum
distribution of the valence neutron in the halo of $^{11}$Li is very sharp and
symmetric around y = 1, because of the weak binding. The EMC ratios for Li
isotopes are then calculated. We study the possibility of extracting the
neutron structure function from data for the nuclear structure functions of the
Li isotopes. Next we calculate the spin-dependent structure functions of
$^{7,9,11}$Li isotopes, which have spin of 3/2. The effect of the nuclear
binding and Fermi motion on the multipole spin structure function,
$^{3/2}_{~1}g_1$, is about 10% in the region x < 0.7, but it becomes quite
important at large x. The spin structure function of $^{3/2}_{~3}g_1$ is also
investigated. Finally, we discuss the modification of the Gottfried and Bjorken
integrals in a nuclear medium and point out several candidates for a pair of
mirror nuclei to study the flavor-nonsinglet quark distributions in nuclei.


  Despite recent success of self-supervised based contrastive learning model
for 3D point clouds representation, the adversarial robustness of such
pre-trained models raised concerns. Adversarial contrastive learning (ACL) is
considered an effective way to improve the robustness of pre-trained models. In
contrastive learning, the projector is considered an effective component for
removing unnecessary feature information during contrastive pretraining and
most ACL works also use contrastive loss with projected feature representations
to generate adversarial examples in pretraining, while "unprojected " feature
representations are used in generating adversarial inputs during
inference.Because of the distribution gap between projected and "unprojected"
features, their models are constrained of obtaining robust feature
representations for downstream tasks. We introduce a new method to generate
high-quality 3D adversarial examples for adversarial training by utilizing
virtual adversarial loss with "unprojected" feature representations in
contrastive learning framework. We present our robust aware loss function to
train self-supervised contrastive learning framework adversarially.
Furthermore, we find selecting high difference points with the Difference of
Normal (DoN) operator as additional input for adversarial self-supervised
contrastive learning can significantly improve the adversarial robustness of
the pre-trained model. We validate our method, PointACL on downstream tasks,
including 3D classification and 3D segmentation with multiple datasets. It
obtains comparable robust accuracy over state-of-the-art contrastive
adversarial learning methods.


  A common numerical task is to represent functions which are highly spatially
anisotropic, and to solve differential equations related to these functions.
One way such anisotropy arises is that information transfer along one spatial
direction is much faster than in others. In this situation, the derivative of
the function is small in the local direction of a vector field $\mathbf{b}$. In
order to define a discrete representation, a set of surfaces $M_i$ indexed by
an integer $i$ are chosen such that mapping along the field $\mathbf{b}$
induces a one-to-one relation between the points on surface $M_i$ to those on
$M_{i+1}$. For simple cases $M_i$ may be surfaces of constant coordinate value.
On each surface $M_i$, a function description is constructed using basis
functions defined on a regular structured mesh. The definition of each basis
function is extended from the surface $M$ along the lines of the field
$\mathbf{b}$ by multiplying it by a smooth compact support function whose
argument increases with distance along $\mathbf{b}$. Function values are
evaluated by summing contributions associated with each surface $M_i$. This
does not require any special connectivity of the meshes used in the
neighbouring surfaces $M$, which substantially simplifies the meshing problem
compared to attempting to find a space filling anisotropic mesh. We explore the
numerical properties of the scheme, and show that it can be used to efficiently
solve differential equations for certain anisotropic problems.


  The $\rho\omega$--mixing generated by the isospin breaking of the current
quark masses $m_{u} \neq m_{d}$ is studied within the bosonized NJL model in
the gradient expansion. The resulting effective meson lagrangian naturally
incorperates vector meson dominance. By including pion loops an excellent
description of both the pion electromagnetic form factor and of the
$\pi^+\pi^-$ phase shifts in the vector--isovector channel is obtained. The
$\rho\omega$--mixing can be treated in the static approximation but is
absolutely necessary to reproduce the fine structure of the electromagnetic
form factor, while the pion loops are necessary to obtain the correct energy
dependence of the phase shifts.


  The fabrication of luminescent defects in single-crystal diamond upon Sn
implantation and annealing is reported. The relevant spectral features of the
optical centers (emission peaks at 593.5 nm, 620.3 nm, 630.7 nm and 646.7 nm)
are attributed to Sn-related defects through the correlation of their
photoluminescence (PL) intensity with the implantation fluence. Single
Sn-related defects were identified and characterized through the acquisition of
their second-order auto-correlation emission functions, by means of
Hanbury-Brown-Twiss interferometry. The investigation of their single-photon
emission regime as a function of excitation laser power revealed that
Sn-related defects are based on three-level systems with a 6 ns radiative decay
lifetime. In a fraction of the studied centers, the observation of a blinking
PL emission is indicative of the existence of a dark state. Furthermore,
absorption dependence from the polarization of the excitation radiation with
about 45 percent contrast was measured. This work shed light on the existence
of a new optical center associated with a group-IV impurity in diamond, with
similar photo-physical properties to the already well-known Si-V and Ge-V
emitters, thus providing results of interest from both the fundamental and
applicative points of view.


  These proceedings summarize the latest measurements on top production, top
properties and searches using the ATLAS detector at the LHC. The measurements
are performed on $pp$ collision data with a center of mass energy $\sqrt{s} =
7, 8$ and $13$ TeV.


  Deepfakes are computer manipulated videos where the face of an individual has
been replaced with that of another. Software for creating such forgeries is
easy to use and ever more popular, causing serious threats to personal
reputation and public security. The quality of classifiers for detecting
deepfakes has improved with the releasing of ever larger datasets, but the
understanding of why a particular video has been labelled as fake has not kept
pace.
  In this work we develop, extend and compare white-box, black-box and
model-specific techniques for explaining the labelling of real and fake videos.
In particular, we adapt SHAP, GradCAM and self-attention models to the task of
explaining the predictions of state-of-the-art detectors based on EfficientNet,
trained on the Deepfake Detection Challenge (DFDC) dataset. We compare the
obtained explanations, proposing metrics to quantify their visual features and
desirable characteristics, and also perform a user survey collecting users'
opinions regarding the usefulness of the explainers.


  The local maximal inequality for the Schr\"{o}dinger operators of order
$\a>1$ is shown to be bounded from $H^s(\R^2)$ to $L^2$ for any $s>\frac38$.
This improves the previous result of Sj\"{o}lin on the regularity of solutions
to fractional order Schr\"{o}dinger equations. Our method is inspired by
Bourgain's argument in case of $\a=2$. The extension from $\a=2$ to general
$\a>1$ confronts three essential obstacles: the lack of Lee's reduction lemma,
the absence of the algebraic structure of the symbol and the inapplicable
Galilean transformation in the deduction of the main theorem. We get around
these difficulties by establishing a new reduction lemma at our disposal and
analyzing all the possibilities in using the separateness of the segments to
obtain the analogous bilinear $L^2-$estimates. To compensate the absence of
Galilean invariance, we resort to Taylor's expansion for the phase function.
The Bourgain-Guth inequality in \cite{ref Bourgain Guth} is also rebuilt to
dominate the solution of fractional order Schr\"{o}dinger equations.


  An overview of pseudo-Dirac neutrino framework is given starting from general
spinor phenomenology. The framework is then tested by simulation of
oscillations for T2K experiment parameters. Two possible derivations of
oscillation parameters are indicated to have the same result.


  Electric field induced magnetization switching in single-phase multiferroic
materials is intriguing for both fundamental studies and potential
technological applications. Here we develop a framework to study the switching
dynamics of coupled polarization and magnetization in such multiferroic
materials. With the coupling term between the polarization and magnetization as
an invariant dictated by the Dzyaloshinsky-Moriya vector, the dynamical systems
study reveals switching failures and oscillatory mode of magnetization if the
polarization and magnetization relax slowly during switching.


  Inverse protein folding is challenging due to its inherent one-to-many
mapping characteristic, where numerous possible amino acid sequences can fold
into a single, identical protein backbone. This task involves not only
identifying viable sequences but also representing the sheer diversity of
potential solutions. However, existing discriminative models, such as
transformer-based auto-regressive models, struggle to encapsulate the diverse
range of plausible solutions. In contrast, diffusion probabilistic models, as
an emerging genre of generative approaches, offer the potential to generate a
diverse set of sequence candidates for determined protein backbones. We propose
a novel graph denoising diffusion model for inverse protein folding, where a
given protein backbone guides the diffusion process on the corresponding amino
acid residue types. The model infers the joint distribution of amino acids
conditioned on the nodes' physiochemical properties and local environment.
Moreover, we utilize amino acid replacement matrices for the diffusion forward
process, encoding the biologically-meaningful prior knowledge of amino acids
from their spatial and sequential neighbors as well as themselves, which
reduces the sampling space of the generative process. Our model achieves
state-of-the-art performance over a set of popular baseline methods in sequence
recovery and exhibits great potential in generating diverse protein sequences
for a determined protein backbone structure.


  We introduce $k$NN-LMs, which extend a pre-trained neural language model (LM)
by linearly interpolating it with a $k$-nearest neighbors ($k$NN) model. The
nearest neighbors are computed according to distance in the pre-trained LM
embedding space, and can be drawn from any text collection, including the
original LM training data. Applying this augmentation to a strong Wikitext-103
LM, with neighbors drawn from the original training set, our $k$NN-LM achieves
a new state-of-the-art perplexity of 15.79 - a 2.9 point improvement with no
additional training. We also show that this approach has implications for
efficiently scaling up to larger training sets and allows for effective domain
adaptation, by simply varying the nearest neighbor datastore, again without
further training. Qualitatively, the model is particularly helpful in
predicting rare patterns, such as factual knowledge. Together, these results
strongly suggest that learning similarity between sequences of text is easier
than predicting the next word, and that nearest neighbor search is an effective
approach for language modeling in the long tail.


  For E/k an elliptic curve with CM by O, we determine a formula for (a
generalization of) the arithmetic local constant of [4] at almost all primes of
good reduction. We apply this formula to the CM curves defined over Q and are
able to describe extensions F/Q over which the O-rank of E grows.


  The Grundy domination number of a simple graph $G = (V,E)$ is the length of
the longest sequence of unique vertices $S = (v_1, \ldots, v_k)$, $v_i \in V$,
that satisfies the property $N[v_i] \setminus \cup_{j=1}^{i-1}N[v_j] \neq
\emptyset$ for each $i \in [k]$. Here, $N(v) = \{u : uv \in E\}$ and $N[v] =
N(v) \cup \{v\}$. In this note, we prove a recent conjecture about the Grundy
domination number of the strong product of two graphs. We then discuss how this
result relates to the zero forcing number of the strong product of graphs.


  We study the renormalization of the Wilson loop with a path corresponding to
the Drell-Yan lepton pair production in two-loop approximation of perturbation
theory. We establish the renormalization group equation in next-to-leading
order and find a process specific anomalous dimension Gamma_DY in the
corresponding approximation.


  We present a systematic study of an extension of the Standard Model (SM) with
two Higgs doublets and one complex singlet (2HDM+S). In order to gain
analytical understanding of the parameter space, we re-parameterize the 27
parameters in the Lagrangian by quantities more closely related to physical
observables: physical masses, mixing angles, trilinear and quadratic couplings,
and vacuum expectation values. Embedding the 125\,GeV SM-like Higgs boson
observed at the LHC places stringent constraints on the parameter space. In
particular, the mixing of the SM-like interaction state with the remaining
states is severely constrained, requiring approximate alignment without
decoupling in the region of parameter space where the additional Higgs bosons
are light enough to be accessible at the LHC. In contrast to 2HDM models, large
branching ratios of the heavy Higgs bosons into two lighter Higgs bosons or a
light Higgs and a $Z$ boson, so-called Higgs cascade decays, are ubiquitous in
the 2HDM+S. Using currently available limits, future projections, and our own
collider simulations, we show that combining different final states arising
from Higgs cascades would allow to probe most of the interesting region of
parameter space with Higgs boson masses up to 1\,TeV at the LHC with
$L=3000\,{\rm fb}^{-1}$ of data.


  The use of xenon-doped liquid argon is a promising alternative for large pure
liquid-argon TPCs. Not only xenon-doped liquid argon enhances the light
production, mitigating the possible suppression due to impurities, but also it
increases the wavelength of the scintillation light, enlarging the effective
Rayleigh scattering length and improving the detection uniformity. ProtoDUNE
Dual-Phase is a 300-ton active volume LAr TPC, a prototype for the Deep
Underground Neutrino Experiment (DUNE), a dual-site experiment for
long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon
decay searches. ProtoDUNE Dual-Phase took cosmic muon data at CERN with pure
liquid argon and with xenon-doped liquid argon for over a year. The impact of
the presence of xenon in the scintillation light and its comparison with the
pure liquid argon data will be presented. These results are of interest to any
future large LAr TPCs.


  In order to solve the problem of the difficult direct measurement of
temperature field in fluid machinery under high-speed compressible conditions,
this study combines high-order finite difference numerical format, Weighted
Essentially Non-Oscillatory (WENO) discontinuity detection, and traditional
Physics-Informed Neural Network (PINN) to develop a high-order discontinuity
detection PINN (Hodd-PINN) that can achieve temperature field inversion with a
small number of measurement points. When dealing with pure convection problems,
Hodd-PINN introduces a 7th-order discretization for the convection term,
reducing an additional 9.7% error compared to traditional low-order
discretization methods. When dealing with pure diffusion problems, Hodd-PINN
introduces an 8th-order discretization for the diffusion term, reducing an
additional 12.8% error compared to traditional low-order discretization
methods. In addition, this paper develops a loss function based on WENO
discontinuity detection technology, which helps eliminate false
discontinuities, allowing Hodd-PINN to successfully identify sparse waves that
are easily overlooked in PINN's predicted results, reducing the error by 24.2%.
Through extensive testing, this paper points out that the Hodd-PINN, which
incorporates high-order discretization and discontinuity detection technology,
can further reduce the prediction error of PINN, effectively reducing the data
requirement, and can effectively solve the problem of false discontinuities.
This method has important value for the inversion of temperature and velocity
fields in fluid machinery under high-speed compressible conditions.


  It is known that chaotic systems have widely been used in cryptography.
Generally, floating point simulations are used to generate pseudo-random
sequence of numbers. Although, it is possible to find some works on the
degradation of chaotic systems due to finite precision of digital computers,
little attention has been paid to exploit this limitation to formulate
efficient process for image encode. This article proposes a novel image
encryption method using natural interval extensions. The sequence of arithmetic
operations is different in each natural interval extension. This is what we
need to produce two different sequences; the difference between these sequences
is used to generate the lower bound error, which has been shown to present
satisfactory pseudo-random properties. The approach has been successfully
tested using the Chua's circuit as the chaotic system. The secret key has
presented good properties for encrypting the Lena image.


  The coupling of geometrical and electronic properties is a promising venue to
engineer conduction properties in graphene. Confinement added to strain allows
for interplay of different transport mechanisms with potential device
applications. To investigate strain signatures on transport in confined
geometries, we focus on graphene nanoribbons (GNR) with circularly symmetric
deformations. In particular, we study GNR with an inhomogeneous, out of plane
Gaussian deformation, connected to reservoirs. We observe an enhancement of the
density of states in the deformed region, accompanied with a decrease in the
conductance, signaling the presence of confined states. The local density of
states exhibits a six-fold symmetric structure with an oscillating sub-lattice
occupation asymmetry, that persist for a wide range of energy and model
parameters.


  We study the Iitaka-Kodaira dimension of nef relative anti-canonical
divisors. As a consequence, we prove that given a complex projective variety
with klt singularities, if the anti-canonical divisor is nef, then the
dimension of a general fibre of the maximal rationally connected fibration is
at least the Iitaka-Kodaira dimension of the anti-canonical divisor.


  Sensor-based human activity segmentation and recognition are two important
and challenging problems in many real-world applications and they have drawn
increasing attention from the deep learning community in recent years. Most of
the existing deep learning works were designed based on pre-segmented sensor
streams and they have treated activity segmentation and recognition as two
separate tasks. In practice, performing data stream segmentation is very
challenging. We believe that both activity segmentation and recognition may
convey unique information which can complement each other to improve the
performance of the two tasks. In this paper, we firstly proposes a new
multitask deep neural network to solve the two tasks simultaneously. The
proposed neural network adopts selective convolution and features multiscale
windows to segment activities of long or short time durations. First, multiple
windows of different scales are generated to center on each unit of the feature
sequence. Then, the model is trained to predict, for each window, the activity
class and the offset to the true activity boundaries. Finally, overlapping
windows are filtered out by non-maximum suppression, and adjacent windows of
the same activity are concatenated to complete the segmentation task. Extensive
experiments were conducted on eight popular benchmarking datasets, and the
results show that our proposed method outperforms the state-of-the-art methods
both for activity recognition and segmentation.


  Shear-induced vertical mixing in a stratified flow is a key ingredient of
thermohaline circulation. We experimentally determine the vertical flux of
momentum and density of a forced gravity current using high-resolution velocity
and density measurements. A constant eddy viscosity model provides a poor
description of the physics of mixing, but a Prandtl mixing length model
relating momentum and density fluxes to mean velocity and density gradients
works well. For $<Ri_g > \approx 0.08$ and $Re_\lambda \approx 100$, the mixing
lengths are fairly constant, about the same magnitude, comparable to the
turbulent shear length.


  Grain growth by accretion of gas-phase metals is a common assumption in
models of dust evolution, but in dense gas, where the timescale is short enough
for accretion to be effective, material is accreted in the form of ice mantles
rather than adding to the refractory grain mass. It has been suggested that
negatively-charged small grains in the diffuse interstellar medium (ISM) can
accrete efficiently due to the Coulomb attraction of positively-charged ions,
avoiding this issue. We show that this inevitably results in the growth of the
small-grain radii until they become positively charged, at which point further
growth is effectively halted. The resulting gas-phase depletions under diffuse
ISM conditions are significantly overestimated when a constant grain size
distribution is assumed. While observed depletions can be reproduced by
changing the initial size distribution or assuming highly efficient grain
shattering, both options result in unrealistic levels of far-ultraviolet
extinction. We suggest that the observed elemental depletions in the diffuse
ISM are better explained by higher initial depletions, combined with
inefficient dust destruction by supernovae at moderate ($n_{\rm H} \sim 30 {\rm
\, cm^{-3}}$) densities, rather than by higher accretion efficiences.


  Many-body techniques for the calculation of quasielastic nuclear matter
response functions in the fully antisymmetrized random phase approximation on a
Hartree-Fock basis are discussed in detail. The methods presented here allow
for an accurate evaluation of the response functions with little numerical
effort. Formulae are given for a generic non-relativistic potential
parameterized in terms of meson exchanges; on the other hand, relativistic
kinematical effects have been accounted for.


  We compare three different notions of concurrence to measure the polarization
entanglement of two-photon states generated by the biexciton cascade in a
quantum dot embedded in a microcavity. We focus on the often-discussed
situation of a dot with finite biexciton binding energy in a cavity tuned to
the two-photon resonance. Apart from the time-dependent concurrence, which can
be assigned to the two-photon density matrix at any point in time, we study
single- and double-time integrated concurrences commonly used in the literature
that are based on different quantum state reconstruction schemes. We argue that
the single-time integrated concurrence can be thought of as the concurrence of
photons simultaneously emitted from the cavity without resolving the common
emission time, while the more widely studied double-time integrated concurrence
refers to photons that are neither filtered with respect to the emission time
of the first photon nor with respect to the delay time between the two emitted
photons. Analytic and numerical calculations reveal that the single-time
integrated concurrence indeed agrees well with the typical value of the
time-dependent concurrence at long times, even in the presence of phonons.
Thus, the more easily measurable single-time integrated concurrence gives
access to the physical information represented by the time-dependent
concurrence. However, the double-time integrated concurrence shows a different
behavior with respect to changes in the exciton fine structure splitting and
even displays a completely different trend when the ratio between the cavity
loss rate and the fine structure splitting is varied while keeping their
product constant. This implies the non-equivalence of the physical information
contained in the time-dependent and single-time integrated concurrence on the
one hand and the double-time integrated concurrence on the other hand.


  Spontaneous scalarization is a mechanism that endows relativistic stars and
black holes with a nontrivial configuration only when their spacetime curvature
exceeds some threshold. The standard way to trigger spontaneous scalarization
is via a tachyonic instability at the linear level, which is eventually
quenched due to the effect of non-linear terms. In this paper, we identify all
of the terms in the Horndeski action that contribute to the (effective) mass
term in the linearized equations and, hence, can cause or contribute to the
tachyonic instability that triggers scalarization.


  We derive analytic expressions for the critical temperatures of the
superconducting (SC) and pseudogap (PG) phases of the high-Tc cuprates, which
are in excellent agreement with the experimental data for single-layered
materials such as LSCO, Bi2201 and Hg1201. Our effective Hamiltonian, defined
in the oxygen square sub-lattices formed by the alternate hybridization of
$p_x$ and $p_y$ orbitals with the $3d$ copper orbitals, provides an unified
explanation for the $d_{x^2-y^2}$ symmetry of both the SC and PG order
parameters. Attractive and repulsive interactions involve holes of the two
different sublattices and can be derived from the spin-fermion model. Optimal
doping occurs when the chemical potential vanishes. For $N$-layered cuprates,
the growth of the optimal temperature with $N$, as well as the trend of the SC
and AF domes to superimpose, can be simply understood. Our results for the
optimal SC transition temperature are in excellent agreement with the
experiments for $N=2$ materials of the $Bi$ and $Hg$ families. For $N=3$ the
agreement is still satisfactory, while for $N>3$, it becomes poor. The
explanation for these facts allows us to suggest a method for increasing the
critical SC temperature in cuprates.


  Translation ambiguity, out of vocabulary words and missing some translations
in bilingual dictionaries make dictionary-based Cross-language Information
Retrieval (CLIR) a challenging task. Moreover, in agglutinative languages which
do not have reliable stemmers, missing various lexical formations in bilingual
dictionaries degrades CLIR performance. This paper aims to introduce a
probabilistic translation model to solve the ambiguity problem, and also to
provide most likely formations of a dictionary candidate. We propose Minimum
Edit Support Candidates (MESC) method that exploits a monolingual corpus and a
bilingual dictionary to translate users' native language queries to documents'
language. Our experiments show that the proposed method outperforms
state-of-the-art dictionary-based English-Persian CLIR.


  Ultrafaint dwarf galaxies (UFDs) are typically assumed to have simple,
stellar populations with star formation ending at reionization. Yet as the
observations of these galaxies continue to improve, their star formation
histories (SFHs) are revealed to be more complicated than previously thought.
In this paper, we study how star formation, chemical enrichment, and mixing
proceed in small, dark matter halos at early times using a high-resolution,
cosmological, hydrodynamical simulation. The goals are to inform the future use
of analytic models and to explore observable properties of the simulated halos
in the context of UFD data. Specifically, we look at analytic approaches that
might inform metal enrichment within and beyond small galaxies in the early
Universe. We find that simple assumptions for modeling the extent of
supernova-driven winds agree with the simulation on average whereas
inhomogeneous mixing and gas flows have a large effect on the spread in
simulated stellar metallicities. In the context of the UFDs, this work
demonstrates that simulations can form halos with a complex SFH and a large
spread in the metallicity distribution function within a few hundred Myr in the
early Universe. In particular, bursty and continuous star formation are seen in
the simulation and both scenarios have been argued from the data. Spreads in
the simulated metallicities, however remain too narrow and too metal-rich when
compared to the UFDs. Future work is needed to help reduce these discrepancies
and advance our interpretation of the data.


  We describe a method using the integrated Sachs-Wolfe (ISW) effect caused by
individual inhomogeneities to determine the cosmological parameters, $H_0$,
$\Omega_{\rm m}$, and $\Omega_\Lambda$, etc. This ISW-redshift test requires
detailed knowledge of the internal kinematics of a set of individual density
perturbations, e.g., galaxy clusters and/or cosmic voids, in particular their
density and velocity profiles, and their mass accretion rates. It assumes the
density perturbations are isolated and imbedded (equivalently compensated) and
makes use of the newly found relation between the ISW temperature perturbation
of the CMB and the Fermat potential of the lens. Given measurements of the
amplitudes of the temperature variations in the CMB caused by such clusters or
voids at various redshifts and estimates of their angular sizes or masses, one
can constrain the cosmological parameters. More realistically, the converse is
more likely, i.e., if the background cosmology is sufficiently constrained,
measurement of ISW profiles of clusters and voids (e.g., hot and cold spots and
rings) can constrain dynamical properties of the dark matter, including
accretion, associated with such lenses and thus constrain the evolution of
these objects with redshift.


  The complexities involved in modelling the transmission dynamics of COVID-19
has been a roadblock in achieving predictability in the spread and containment
of the disease. In addition to understanding the modes of transmission, the
effectiveness of the mitigation methods also needs to be built into any
effective model for making such predictions. We show that such complexities can
be circumvented by appealing to scaling principles which lead to the emergence
of universality in the transmission dynamics of the disease. The ensuing data
collapse renders the transmission dynamics largely independent of geopolitical
variations, the effectiveness of various mitigation strategies, population
demographics, etc. We propose a simple two-parameter model -- the Blue Sky
model -- and show that one class of transmission dynamics can be explained by a
solution that lives at the edge of a blue sky bifurcation. In addition, the
data collapse leads to an enhanced degree of predictability in the disease
spread for several geographical scales which can also be realized in a
model-independent manner as we show using a deep neural network. The
methodology adopted in this work can potentially be applied to the transmission
of other infectious diseases and new universality classes may be found. The
predictability in transmission dynamics and the simplicity of our methodology
can help in building policies for exit strategies and mitigation methods during
a pandemic.


  We present the current status of the comparisons with the respective data of
the predictions of our approach of exact amplitude-based resummation in quantum
field theory as applied to precision QCD calculations as needed for LHC
physics, using the MC Herwiri1.031. The agreement between the theoretical
predictions and the data exhibited continues to be encouraging.


  In this paper we present a pipeline using stereo images in order to
automatically identify, track in 3D fish, and measure fish population.


  Recall that a group is called large if it has a finite index subgroup which
surjects onto a non-abelian free group. By work of Agol and Cooper-Long-Reid,
most 3-manifold groups are large; in particular, the fundamental groups of
hyperbolic 3-manifolds are large. In previous work, the first author gave
examples of closed, hyperbolic 3-manifolds with arbitrarily large first
homology rank but whose fundamental groups do not surject onto a non-abelian
free group. We call a group very large if it surjects onto a non-abelian free
group. In this paper, we consider the question of whether the groups of
homology handlebodies - which are very close to being free - are very large. We
show that the fundamental group of W. Thurston's tripus manifold, is not very
large; it is known to be weakly parafree by Stallings' Theorem and large by the
work of Cooper-Long-Reid since the tripus is a hyperbolic manifold with totally
geodesic boundary. It is still unknown if a 3-manifold group that is weakly
parafree of rank at least 3 must be very large. However, we more generally
consider the co-rank of the fundamental group, also known as the cut number of
the manifold. For each positive integer g we construct a homology handlebody
Y_g of genus g whose group has co-rank equal to r(g), where r(g)=g/2 for g even
and r(g)=(g+1)/2 for g odd. That is, these groups are weakly parafree of rank g
and surject onto a free group of rank roughly half of g but no larger.


  In this report, we experimented with several concepts regarding text streams
analysis.
  We tested an implementation of Incremental Sparse TF-IDF (IS-TFIDF) and
Incremental Cosine Similarity (ICS) with the use of bipartite graphs.
  We are using bipartite graphs - one type of node are documents, and the other
type of nodes are words - to know what documents are affected with a word
arrival at the stream (the neighbors of the word in the graph). Thus, with this
information, we leverage optimized algorithms used for graph-based
applications. The concept is similar to, for example, the use of hash tables or
other computer science concepts used for fast access to information in memory.


  Simulations show that sliding bilayers of colloidal particles can exhibit a
new phase, the ``melt-freeze'' phase, where the layers stochastically alternate
between solidlike and liquidlike states. We introduce a mean field
phenomenological model with two order parameters to understand the interplay of
two adjacent layers while the system is in this remarkable phase. Predictions
from our numerical simulations of a system in the melt-freeze phase include the
tendency of two adjacent layers to be in opposite states (solid and liquid) and
the difference between the fluctuation of the order parameter in one layer
while the other layer is in the same phase compared to the fluctuation while
the other layer is in the opposite phase. We expect this behavior to be seen in
future simulations and experiments.


  Human body actions are an important form of non-verbal communication in
social interactions. This paper focuses on a specific subset of body actions
known as micro-actions, which are subtle, low-intensity body movements that
provide a deeper understanding of inner human feelings. In real-world
scenarios, human micro-actions often co-occur, with multiple micro-actions
overlapping in time, such as simultaneous head and hand movements. However,
current research primarily focuses on recognizing individual micro-actions
while overlooking their co-occurring nature. To narrow this gap, we propose a
new task named Multi-label Micro-Action Detection (MMAD), which involves
identifying all micro-actions in a given short video, determining their start
and end times, and categorizing them. Achieving this requires a model capable
of accurately capturing both long-term and short-term action relationships to
locate and classify multiple micro-actions. To support the MMAD task, we
introduce a new dataset named Multi-label Micro-Action-52 (MMA-52),
specifically designed to facilitate the detailed analysis and exploration of
complex human micro-actions. The proposed MMA-52 dataset is available at:
https://github.com/VUT-HFUT/Micro-Action.


  Fair clustering under the disparate impact doctrine requires that population
of each protected group should be approximately equal in every cluster.
Previous work investigated a difficult-to-scale pre-processing step for
$k$-center and $k$-median style algorithms for the special case of this problem
when the number of protected groups is two. In this work, we consider a more
general and practical setting where there can be many protected groups. To this
end, we propose Deep Fair Clustering, which learns a discriminative but fair
cluster assignment function. The experimental results on three public datasets
with different types of protected attribute show that our approach can steadily
improve the degree of fairness while only having minor loss in terms of
clustering quality.


  We present a framework for studying circuit complexity that is inspired by
techniques that are used for analyzing the complexity of CSPs. We prove that
the circuit complexity of a Boolean function $f$ is characterized by the
partial polymorphisms of $f$'s truth table. Moreover, the non-deterministic
circuit complexity of $f$ is characterized by the polymorphisms of $f$'s truth
table.


  In this paper, we study the unitarizations in the spaces of holomorphic
sections of equivariant holomorphic line bundles over a bounded homogeneous
domain under the action of a connected algebraic group acting transitively on
the domain. We give a complete classification of unitary representations
arising from such unitarizations. As an application, we classify all such
unitary representations for a specific five-dimensional non-symmetric bounded
homogeneous domain.


  We consider two elementary (max-flow and uniform-flow) and two realistic
(max-min fairness and proportional fairness) congestion control schemes, and
analyse how the algorithms and network structure affect throughput, the
fairness of flow allocation, and the location of bottleneck edges. The more
realistic proportional fairness and max-min fairness algorithms have similar
throughput, but path flow allocations are more unequal in scale-free than in
random regular networks. Scale-free networks have lower throughput than their
random regular counterparts in the uniform-flow algorithm, which is favoured in
the complex networks literature. We show, however, that this relation is
reversed on all other congestion control algorithms for a region of the
parameter space given by the degree exponent $\gamma$ and average degree ${k}$.
Moreover, the uniform-flow algorithm severely underestimates the network
throughput of congested networks, and a rich phenomenology of path flow
allocations is only present in the more realistic $\alpha$-fair family of
algorithms. Finally, we show that the number of paths passing through an edge
characterises the location of a wide range of bottleneck edges in these
algorithms. Such identification of bottlenecks could provide a bridge between
the two fields of complex networks and congestion control.


  We present a photometric analysis of a large sample of early-type galaxies in
16 nearby groups, imaged with the Wide-Field Camera on the Isaac Newton
Telescope. Using a two-dimensional surface brightness decomposition routine, we
fit Sersic (r^{1/n}) and exponential models to their bulge and disk components
respectively. Dividing the galaxies into three subsamples according to the
X-ray luminosities of their parent groups, we compare their photometric
properties. Galaxies in X-ray luminous groups tend to be larger and more
luminous than those in groups with undetected or low X-ray luminosities, but no
significant differences in n are seen. Both normal and dwarf elliptical
galaxies in the central regions of groups are found to have cuspier profiles
than their counterparts in group outskirts.
  Structural differences between dwarf and normal elliptical galaxies are
apparent in terms of an offset between their ``Photometric Planes'' in the
space of n, r_e and mu_0. Dwarf ellipticals are found to populate a surface,
with remarkably low scatter, in this space with significant curvature, somewhat
similar to the surfaces of constant entropy proposed by Marquez etal (2001).
Normal ellipticals are offset from this distribution in a direction of higher
specific entropy. This may indicate that the two populations are distinguished
by the action of galaxy merging on larger galaxies.


  We formulate a QCD-based effective theory approach to heavy quarkonia-like
systems as $\bar{c} c$ and $\bar{b} b$ resonances and $B_c$ states. We apply
the method to inclusive decays, working out a few examples in detail.


  We study the vortex formation in optical lattices submitted to artificial
gauge potentials. We compute the superfluid density for Abelian and non-Abelian
gauge potentials with a mean-field approach of the Bose-Hubbard model and we
determine the rule describing the number of vortices as a function of the
effective magnetic flux. This simple rule is represented by a remarkably rich
figure that represents the superfluid density as a function of the flux. The
phenomena which emanate from this work should be observed experimentally in
optical lattices within which atom tunneling is laser-assisted and described by
commutative or non-commutative tunneling operators.


  We derive an alternative expression for a delayed logistic equation in which
the rate of change in the population involves a growth rate that depends on the
population density during an earlier time period. In our formulation, the delay
in the growth term is consistent with the rate of instantaneous decline in the
population given by the model. Our formulation is a modification of [Arino et
al., J.~Theoret.~Biol.~241(1):109--119, 2006] by taking the intraspecific
competition between the adults and juveniles into account. We provide a
complete global analysis showing that no sustained oscillations are possible. A
threshold giving the interface between extinction and survival is determined in
terms of the parameters in the model. The theory of chain transitive sets and
the comparison theorem for cooperative delay differential equations are used to
determine the global dynamics of the model.
  We extend our delayed logistic equation to a system modeling the competition
of two species. For the competition model, we provide results on local
stability, bifurcation diagrams, and adaptive dynamics. Assuming that the
species with shorter delay produces fewer offspring at a time than the species
with longer delay, we show that there is a critical value, $\tau^*$, such that
the evolutionary trend is for the delay to approach $\tau^*$.


  One of Aesop's (La Fontain's) famous fables `The Ant and the Grasshopper' is
widely known to give a moral lesson through comparison between the hard working
ant and the party-loving grasshopper. Here we show a slightly different version
of this fable, namely, "The Ant and the Metrohopper," which describes human
mobility patterns in modern urban life. Numerous real transportation networks
and the trajectory data have been studied in order to understand mobility
patterns. We study trajectories of commuters on the public transportation of
Metropolitan Seoul, Korea. Smart cards (Integrated Circuit Cards; ICCs) are
used in the public transportation system, which allow collection of transit
transaction data, including departure and arrival stations and time. This
empirical analysis provides human mobility patterns, which impact traffic
forecasting and transportation optimization, as well as urban planning.


  The coupling of an isolated quantum state to a continuum is typically
associated with decoherence and decreased lifetime. Here, we demonstrate that
Rydberg macrodimers, weakly bound pairs of Rydberg atoms, can overcome this
dissipative mechanism and instead form bound states with the continuum of free
motional states. This is enabled by the unique combination of extraordinarily
slow vibrational motion in the molecular state and the optical coupling to a
non-interacting continuum. Under conditions of strong coupling, we observe the
emergence of distinct resonances and explain them within a Fano model. For
atoms arranged on a lattice, we predict the strong continuum coupling to even
stabilize molecules consisting of more than two atoms and find first signatures
of these by observing atom loss correlations using a quantum gas microscope.
Our results present an intriguing mechanism to control decoherence and bind
multiatomic molecules using strong light-matter interactions.


  We survey recent work on local well-posedness results for parabolic equations
and systems with rough initial data.


  Recent data of lattice measurements of the gauge-invariant nonlocal scalar
quark condensates are analyzed to extract the short--distance correlation
length, 1/\lambda_q, and to construct an admissible Ansatz for the condensate
behaviour in a coordinate space. The correlation length values for both the
quenched and full-QCD cases appear in a good agreement with the well-known QCD
SR estimates of the mixed quark-gluon condensate,
  2 \lambda_q^2 = <\bar{q}(ig\sigma^{\mu\nu}G_{\mu\nu})q>/<\bar{q}q>
  = 0.8 - 1.1 GeV^2. We test two different Ansatzes for a nonlocal quark
condensate and trace their influence on the twist-2 pion distribution amplitude
by means of QCD SRs. The main features of the pion distribution amplitude are
confirmed by the CLEO experimental results.


  The $\mu\nu$SSM is a highly predictive alternative model to the MSSM. In
particular, the electroweak sector of the model can explain the longstanding
discrepancy between the experimental result for the anomalous magnetic moment
of the muon, $(g-2)_\mu$, and its Standard Model prediction, while being in
agreement with all other theoretical and experimental constraints. The recently
published MUON G-2 result is within $0.8\,\sigma$ in agreement with the older
BNL result on $(g-2)_\mu$. The combined result was announced as $a_\mu^{\rm
exp} = (11659206.1 \pm 4.1) \times 10^{-10}$, yielding a new deviation from the
Standard Model prediction of $\Delta a_\mu = (25.1 \pm 5.9) \times 10^{-10}$,
corresponding to $4.2\,\sigma$. Using this improved bound we update the
analysis in the $\mu\nu$SSM as presented in Ref. [1] and set new limits on the
allowed parameters space of the electroweak sector of the model. We conclude
that significant regions of the model can explain the new $(g-2)_\mu$ data.


  This is a credit mini-course in French prepared for a Summer School at the
University of Sherbrooke. The course consists of three one-and-half hour
lectures and three credit exercises for a class of advanced graduate students.


  Searching for similar logos in the registered logo database is a very
important and tedious task at the trademark office. Speed and accuracy are two
aspects that one must attend to while developing a system for retrieval of
logos. In this paper, we propose a rough-set based method to quantify the
structural information in a logo image that can be used to efficiently index an
image. A logo is split into a number of polygons, and for each polygon, we
compute the tight upper and lower approximations based on the principles of a
rough set. This representation is used for forming feature vectors for
retrieval of logos. Experimentation on a standard data set shows the usefulness
of the proposed technique. It is computationally efficient and also provides
retrieval results at high accuracy.


  These notes are for the proceedings of the NATO Advanced Study Insitutue on
"Scale Invariance, Interfaces, and Non--Equilibrium Dynamics", held at the
Isaac Newton Institute, 20--30 June 1994. The four lectures address a number of
issues related to dynamic fluctuations of lines in non-equilibrium
circumstances. The first two are devoted to the critical behavior of contact
lines and flux lines depinning from impurities. It is emphasized that
anisotropies in the medium lead to different universality classes. The
importance of nonlinearities for moving lines are discussed in the context of
flux lines and polymers in the last two lectures. A dynamic form birefringence
is predicted for drifting polymers.


  Modern scientific instruments produce vast amounts of data, which can
overwhelm the processing ability of computer systems. Lossy compression of data
is an intriguing solution, but comes with its own drawbacks, such as potential
signal loss, and the need for careful optimization of the compression ratio. In
this work, we focus on a setting where this problem is especially acute:
compressive sensing frameworks for interferometry and medical imaging. We ask
the following question: can the precision of the data representation be lowered
for all inputs, with recovery guarantees and practical performance? Our first
contribution is a theoretical analysis of the normalized Iterative Hard
Thresholding (IHT) algorithm when all input data, meaning both the measurement
matrix and the observation vector are quantized aggressively. We present a
variant of low precision normalized {IHT} that, under mild conditions, can
still provide recovery guarantees. The second contribution is the application
of our quantization framework to radio astronomy and magnetic resonance
imaging. We show that lowering the precision of the data can significantly
accelerate image recovery. We evaluate our approach on telescope data and
samples of brain images using CPU and FPGA implementations achieving up to a 9x
speed-up with negligible loss of recovery quality.


  The spatial resolution of direct-modulation Brillouin optical
correlation-domain reflectometry is studied with respect to modulation
amplitude and frequency. Results suggest that optimal resolution improvement is
achieved by increasing modulation amplitude first, followed by frequency.


  Network-based epidemic models have been extensively employed to understand
the spread of infectious diseases, but have generally overlooked the fact that
most realistic networks are dynamical rather than static. In this paper, we
study a susceptible-infected-susceptible epidemic model with vaccination in a
dynamical contact network of moving individuals, where we regard mobile
individuals as random walkers that are allowed to perform long-range jumps.
Different from previous studies of epidemics in a random walk network with a
constant interaction radius, we consider the scenario where the individuals
have a heterogeneous distribution of interaction radius $r$ and infected
individuals are vaccinated with a probability depending on the interaction
radius distribution. We derive the basic reproduction number $\mathcal{R}_0$
and explore the stability of disease-free and endemic equilibria of the model.
Both theoretical and simulation results reveal that the distribution of
individual interaction radius has significant effects on the basic reproduction
number and the epidemic prevalence. In general, the disease will break out more
readily in the population with a more heterogeneous radius distribution;
however resulting in a lower epidemic prevalence. Interestingly, the results
suggest that an optimal vaccination intervention for disease prevention and
control is achievable regardless of the radius distribution. Furthermore, some
interesting results on the structure of the underlying contact network are
shown to have strong correlation with the epidemic dynamics. This study
provides potential implications for developing efficient containment measures
against infectious disease while considering the spatial constraints of moving
individuals.


  The polarization of $\Lambda$ hyperons from relativistic flow vorticity is
studied in peripheral heavy ion reactions at FAIR and NICA energies, just above
the threshold of the transition to the Quark-Gluon Plasma. Previous
calculations at higher energies with larger initial angular momentum, predicted
significant $\Lambda$ polarization based on the classical vorticity term in the
polarization, while relativistic modifications decreased the polarization and
changed its structure in the momentum space. At the lower energies studied
here, we see the same effect namely that the relativistic modifications
decrease the polarization arising from the initial shear flow vorticity.


  Searching for extrasolar planets by direct detection is extremely challenging
for current instrumentation. Indirect methods, that measure the effect of a
planet on its host star, are much more promising and have indeed led to the
discovery of nearly all extrasolar systems known today. While the most
successful method thus far is the radial velocity technique, new
interferometric instruments like PRIMA at the VLTI will enable us to carry out
astrometric measurements accurate enough to detect extrasolar planets and to
determine all orbital parameters, including their orbit inclination and true
mass. In this article I describe the narrow-angle astrometry technique, how it
will be realized with PRIMA, what kind of planets we can find, and what kind of
preparatory observations are required.


  Let f: X \to Z be a surjective morphism of smooth complex projective
varieties with connected fibers. Suppose that L is a pseudo-effective divisor
on X that is f-numerically trivial. We show that there is a divisor D on Z such
that L is numerically equivalent to f^*D.


  Classical monetary systems regularly subject the most vulnerable majority of
the world's population to debilitating financial shocks, and have manifestly
allowed uncontrolled global inequality over the long term. Given these basic
failures, how can we avoid asking whether mainstream macroeconomic principles
are actually compatible with democratic principles such as equality or the
protection of human rights and dignity? This idea paper takes a constructive
look at this question, by exploring how alternate monetary principles might
result in a form of money more compatible with democratic principles -- dare we
call it "democratic money"? In this alternative macroeconomic philosophy, both
the supply of and the demand for money must be rooted in people, so as to give
all people both equal opportunities for economic participation. Money must be
designed around equality, not only across all people alive at a given moment,
but also across past and future generations of people, guaranteeing that our
descendants cannot be enslaved by their ancestors' economic luck or misfortune.
Democratic money must reliably give all people a means to enable everyday
commerce, investment, and value creation in good times and bad, and must impose
hard limits on financial inequality. Democratic money must itself be governed
democratically, and must economically facilitate the needs of citizens in a
democracy for trustworthy and unbiased information with which to make wise
collective decisions. An intriguing approach to implementing and deploying
democratic money is via a cryptocurrency built on a proof-of-personhood
foundation, giving each opt-in human participant one equal unit of stake. Such
a cryptocurrency would have both interesting similarities to, and important
differences from, a Universal Basic Income (UBI) denominated in an existing
currency.


  Both the dynamics and the observational properties of relativistic jets are
determined by their interaction with the ambient medium. A crucial role is
played by the contact discontinuity at the jet boundary, which in the presence
of jet collimation may become subject to Rayleigh-Taylor instability (RTI) and
Richtmyer-Meshkov instability (RMI). Here, we study the evolution of these
instabilities in non-magnetized relativistic jets using special relativistic
three-dimensional hydrodynamic simulations. We show that the growth of initial
perturbations is consistent with relativistic RTI operating in the jet
collimation region. The contribution of RMI becomes important downstream from
the collimation shock in agreement with theoretical expectations. Both
instabilities reach non-linear scales above the shock convergence point and
trigger strong turbulence, mixing jet with ambient matter. We devise an
analytic solution for the mixing rate and show that it is sensitive to the
external density gradients. Our results may be applied to different types of
astrophysical objects. In particular, different contribution of interface
instabilities is a natural explanation for the observed dichotomy between FR-I
and FR-II radiogalaxies. The rapid slow-down in the jet of M87 is consistent
with baryon entrainment from the circumnuclear matter with the observed density
distribution. In microquasars, baryon loading triggered by interface
instabilities is a probable reason for the low observed Lorentz factors. We
show that the observed variability in gamma-ray bursts cannot come from mixing
driven by interface instabilities and likely originates from the engine,
suggesting the presence of magnetic fields in the jet.


  The standard conformal compactification of Euclidean space is the round
sphere. We use conformal geodesics to give an elementary proof that this is the
only possible conformal compactification.


  The study aimed to examine the effect of MLIS degree on graduates in Iran
from different dimensions. The study examined the effects of MLIS on scientific
progress, the development of subject expertise, employment, individual
characteristics, skills and capabilities, and scientific activities of Iran's
graduates. The study was a descriptive-survey and researcher-made questionnaire
is used for data collection. The overall effect average of degree of MLIS on
Iranian graduates was equal to 3/25. The findings showed that the average
effect of MLIS degree associated with each studied factors on the graduates in
the country were: Scientific progress (3/13), development of subject expertise
(3/27), employment (3/27), individual characteristics (2/75), skills and
capabilities (3/48), scientific activities (3/57(. Discussion: Based on the
results, the effect of MLIS degree on Iranian graduates was more than moderate.
Generally, it can be concluded that MLIS courses at universities in the
country, can increase the value of a master's degree of graduates at an
acceptable level, but is not perfect; it seems that the authorities should
increase their efforts to promote the value of a master's degree in graduates.


  Adaptive optic (AO) systems delivering high levels of wavefront correction
are now common at observatories. One of the main limitations to image quality
after wavefront correction comes from atmospheric refraction. An Atmospheric
dispersion compensator (ADC) is employed to correct for atmospheric refraction.
The correction is applied based on a look-up table consisting of dispersion
values as a function of telescope elevation angle. The look-up table based
correction of atmospheric dispersion results in imperfect compensation leading
to the presence of residual dispersion in the point-spread function (PSF) and
is insufficient when sub-milliarcsecond precision is required. The presence of
residual dispersion can limit the achievable contrast while employing
high-performance coronagraphs or can compromise high-precision astrometric
measurements. In this paper, we present the first on-sky closed-loop correction
of atmospheric dispersion by directly using science path images. The concept
behind the measurement of dispersion utilizes the chromatic scaling of focal
plane speckles. An adaptive speckle grid generated with a deformable mirror
(DM) that has a sufficiently large number of actuators is used to accurately
measure the residual dispersion and subsequently correct it by driving the ADC.
We have demonstrated with the Subaru Coronagraphic Extreme AO (SCExAO) system
on-sky closed-loop correction of residual dispersion to < 1 mas across H-band.
This work will aid in the direct detection of habitable exoplanets with
upcoming extremely large telescopes (ELTs) and also provide a diagnostic tool
to test the performance of instruments which require sub-milliarcsecond
correction.


  Explicit high-order feature interactions efficiently capture essential
structural knowledge about the data of interest and have been used for
constructing generative models. We present a supervised discriminative
High-Order Parametric Embedding (HOPE) approach to data visualization and
compression. Compared to deep embedding models with complicated deep
architectures, HOPE generates more effective high-order feature mapping through
an embarrassingly simple shallow model. Furthermore, two approaches to
generating a small number of exemplars conveying high-order interactions to
represent large-scale data sets are proposed. These exemplars in combination
with the feature mapping learned by HOPE effectively capture essential data
variations. Moreover, through HOPE, these exemplars are employed to increase
the computational efficiency of kNN classification for fast information
retrieval by thousands of times. For classification in two-dimensional
embedding space on MNIST and USPS datasets, our shallow method HOPE with simple
Sigmoid transformations significantly outperforms state-of-the-art supervised
deep embedding models based on deep neural networks, and even achieved
historically low test error rate of 0.65% in two-dimensional space on MNIST,
which demonstrates the representational efficiency and power of supervised
shallow models with high-order feature interactions.


  The ground state of the quantum spin ice candidate magnet Yb2Ti2O7 is known
to be sensitive to weak disorder at the 1 percent level which occurs in single
crystals grown from the melt. Powders produced by solid state synthesis tend to
be stoichiometric and display large and sharp heat capacity anomalies at
relatively high temperatures, with Tc about 0.26 K. We have carried out neutron
elastic and inelastic measurements on well characterized and equilibrated
stoichiometric powder samples of Yb2Ti2O7 which show resolution-limited Bragg
peaks to appear at low temperatures, but whose onset correlates with
temperatures much higher than Tc. The corresponding magnetic structure is best
described as an ice-like splayed ferromagnet. The spin dynamics in Yb2Ti2O7 are
shown to be gapless on an energy scale smaller than 0.09 meV at all
temperatures, and organized into a continuum of scattering with vestiges of
highly overdamped ferromagnetic spin waves present. These excitations differ
greatly from conventional spin waves predicted for Yb2Ti2O7 s mean field
ordered state, but appear robust to weak disorder as they are largely
consistent with those displayed by non stoichiometric crushed single crystals
and single crystals, as well as by powder samples of Yb2Ti2O7 s sister quantum
magnet Yb2Sn2O7.


  We study the problem of finding approximate first-order stationary points in
optimization problems of the form $\min_{x \in X} \max_{y \in Y} f(x,y)$, where
the sets $X,Y$ are convex and $Y$ is compact. The objective function $f$ is
smooth, but assumed neither convex in $x$ nor concave in $y$. Our approach
relies upon replacing the function $f(x,\cdot)$ with its $k$th order Taylor
approximation (in $y$) and finding a near-stationary point in the resulting
surrogate problem. To guarantee its success, we establish the following result:
let the Euclidean diameter of $Y$ be small in terms of the target accuracy
$\varepsilon$, namely $O(\varepsilon^{\frac{2}{k+1}})$ for $k \in \mathbb{N}$
and $O(\varepsilon)$ for $k = 0$, with the constant factors controlled by
certain regularity parameters of $f$; then any $\varepsilon$-stationary point
in the surrogate problem remains $O(\varepsilon)$-stationary for the initial
problem. Moreover, we show that these upper bounds are nearly optimal: the
aforementioned reduction provably fails when the diameter of $Y$ is larger. For
$0 \le k \le 2$ the surrogate function can be efficiently maximized in $y$; our
general approximation result then leads to efficient algorithms for finding a
near-stationary point in nonconvex-nonconcave min-max problems, for which we
also provide convergence guarantees.


  The massless Dirac fermions and the ease to introduce spatial and magnetic
confinement in graphene provide us unprecedented opportunity to explore
confined relativistic matter in this condensed-matter system. Here we report
the interplay between the confinement induced by external electric fields and
magnetic fields of the massless Dirac fermions in graphene. When the magnetic
length lB is larger than the characteristic length of the confined electric
potential lV, the spatial confinement dominates and a relatively small critical
magnetic field splits the spatial-confinement-induced atomic-like shell states
by switching on a pi Berry phase of the quasiparticles. When the lB becomes
smaller than the lV, the transition from spatial confinement to magnetic
confinement occurs and the atomic-like shell states condense into Landau levels
(LLs) of the Fock-Darwin states in graphene. Our experiment demonstrates that
the spatial confinement dramatically changes the energy spacing between the LLs
and generates large electron-hole asymmetry of the energy spacing between the
LLs. These results shed light on puzzling observations in previous experiments,
which hitherto remained unaddressed.


  A dressing scheme applicable to Dunajski equation is developed. Simple
example of constructing solutions in terms of implicit functions is considered.
Dunajski equation hierarchy is described, its Lax-Sato form is presented.
Dunajsky equation hierarchy is characterised by conservation of
three-dimensional volume form, in which a spectral variable is taken into
account. Some reductions of Dunajsky equation hierarchy, including
waterbag-type reduction, are studied.


  We present extensive experiments training and testing hidden units in deep
networks that emit only a predefined, static, number of discretized values.
These units provide benefits in real-world deployment in systems in which
memory and/or computation may be limited. Additionally, they are particularly
well suited for use in large recurrent network models that require the
maintenance of large amounts of internal state in memory. Surprisingly, we find
that despite reducing the number of values that can be represented in the
output activations from $2^{32}-2^{64}$ to between 64 and 256, there is little
to no degradation in network performance across a variety of different
settings. We investigate simple classification and regression tasks, as well as
memorization and compression problems. We compare the results with more
standard activations, such as tanh and relu. Unlike previous discretization
studies which often concentrate only on binary units, we examine the effects of
varying the number of allowed activation levels. Compared to existing
approaches for discretization, the approach presented here is both conceptually
and programatically simple, has no stochastic component, and allows the
training, testing, and usage phases to be treated in exactly the same manner.


  This paper reports ballistic magnetoresistance values over 4000% measured in
electrodeposited Ni-Ni nanocontacts with T geometry previously developed . Over
the time, after several magnetic field cycles, the ballistic magnetoresistance
relaxed to a 400%. While that the magnetoreistance of a contact could rise
indefinitely; relaxtion and reproducibility are, however, the main issue. We
find that the tip ending radius conforming the contacts appears not to play the
main role.


  We compute the number of massive vacua of N=4 supersymmetric Yang-Mills
theory mass-deformed to preserve N=1 supersymmetry, for any gauge group G. We
use semi-classical techniques and efficiently reproduce the known counting for
A,B and C-type gauge groups, present the generating function for both O(2n) and
SO(2n), and compute the supersymmetric index for gauge groups of exceptional
type. A crucial role is played by the classification of nilpotent orbits, as
well as global properties of their centralizers. We give illustrative examples
of new features of our analysis for the D-type algebras.


  The false discovery proportion (FDP) is a convenient way to account for false
positives when a large number $m$ of tests are performed simultaneously. Romano
and Wolf [Ann. Statist. 35 (2007) 1378-1408] have proposed a general principle
that builds FDP controlling procedures from $k$-family-wise error rate
controlling procedures while incorporating dependencies in an appropriate
manner; see Korn et al. [J. Statist. Plann. Inference 124 (2004) 379-398];
Romano and Wolf (2007). However, the theoretical validity of the latter is
still largely unknown. This paper provides a careful study of this heuristic:
first, we extend this approach by using a notion of "bounding device" that
allows us to cover a wide range of critical values, including those that adapt
to $m\_0$, the number of true null hypotheses. Second, the theoretical validity
of the latter is investigated both nonasymptotically and asymptotically. Third,
we introduce suitable modifications of this heuristic that provide new methods,
overcoming the existing procedures with a proven FDP control.


  We discuss compactifications of higher dimensional supergravities which are
induced by scalars. In particular, we consider vector multiplets coupled to the
supergravity multiplet in the case of D=9, 8 and D=7 minimal supergravities.
These vector multiplets contain scalars, which parametrize coset spaces of the
general form SO(10-D,n)/SO(10-D)xSO(n), where n is the number of vector
multiplets. We discuss the compactification of the supergravity theory to D-2
dimensons, which is induced by non-trivial vacuum scalar field configurations.
There are singular and non-singular solutions, which preserve half of the
supersymmetries.


  We propose a base-station (BS) cooperation model for broadcasting a discrete
memoryless source in a cellular or heterogeneous network. The model allows the
receivers to use helper BSs to improve network performance, and it permits the
receivers to have prior side information about the source. We establish the
model's information-theoretic limits in two operational modes: In Mode 1, the
helper BSs are given information about the channel codeword transmitted by the
main BS, and in Mode 2 they are provided correlated side information about the
source. Optimal codes for Mode 1 use \emph{hash-and-forward coding} at the
helper BSs; while, in Mode 2, optimal codes use source codes from Wyner's
\emph{helper source-coding problem} at the helper BSs. We prove the optimality
of both approaches by way of a new list-decoding generalisation of [8, Thm. 6],
and, in doing so, show an operational duality between Modes 1 and 2.


  We theoretically investigate the use of fast pulsed two-qubit gates for
trapped ion quantum computing in a two-dimensional microtrap architecture. In
one dimension, such fast gates are optimal when employed between nearest
neighbours, and we examine the generalisation to a two-dimensional geometry. We
demonstrate that fast pulsed gates are capable of implementing high-fidelity
entangling operations between ions in neighbouring traps faster than the
trapping period, with experimentally demonstrated laser repetition rates.
Notably, we find that without increasing the gate duration, high-fidelity gates
are achievable even in large arrays with hundreds of ions. To demonstrate the
usefulness of this proposal, we investigate the application of these gates to
the digital simulation of a 40-mode Fermi-Hubbard model. This also demonstrates
why shorter chains of gates required to connect arbitrary pairs of ions makes
this geometry well suited for large-scale computation.


  We study uncertainty principles for orthonormal bases and sequences in
$L^2(\R^d)$. As in the classical Heisenberg inequality we focus on the product
of the dispersions of a function and its Fourier transform. In particular we
prove that there is no orthonormal basis for $L^2(\R)$ for which the time and
frequency means as well as the product of dispersions are uniformly bounded.
The problem is related to recent results of J. Benedetto, A. Powell, and Ph.
Jaming.
  Our main tool is a time frequency localization inequality for orthonormal
sequences in $L^2(\R^d)$. It has various other applications.