  Consider a predictor who ranks eventualities on the basis of past cases: for
instance a search engine ranking webpages given past searches. Resampling past
cases leads to different rankings and the extraction of deeper information. Yet
a rich database, with sufficiently diverse rankings, is often beyond reach.
Inexperience demands either "on the fly" learning-by-doing or prudence: the
arrival of a novel case does not force (i) a revision of current rankings, (ii)
dogmatism towards new rankings, or (iii) intransitivity. For this higher-order
framework of inductive inference, we derive a suitably unique numerical
representation of these rankings via a matrix on eventualities x cases and
describe a robust test of prudence. Applications include: the success/failure
of startups; the veracity of fake news; and novel conditions for the existence
of a yield curve that is robustly arbitrage-free.


  Let $\mathcal{O}^{int}_q(m|n)$ be a semisimple tensor category of modules
over a quantum ortho-symplectic superalgebra of type $B, C, D$ introduced in
the author's previous work. It is a natural counterpart of the category of
finitely dominated integrable modules over a quantum group of type $B, C, D$
from a viewpoint of super duality. Continuing the previous work on type $B$ and
$C$, we classify the irreducible modules in $\mathcal{O}^{int}_q(m|n)$, and
prove the existence and uniqueness of their crystal bases in case of type $D$.
A new combinatorial model of classical crystals of type $D$ is introduced,
whose super analogue gives a realization of crystals for the highest weight
modules in $\mathcal{O}^{int}_q(m|n)$.


  A non-perturbative and continuous definition of RG transformations as
stochastic processes is proposed, inspired by the observation that the
functional RG equations for effective Boltzmann factors may be interpreted as
Fokker-Planck equations. The result implies a new approach to Monte Carlo RG
that is amenable to lattice simulation. Long-distance correlations of the
effective theory are shown to approach gradient-flowed correlations, which are
simpler to measure. The Markov property of the stochastic RG transformation
implies an RG scaling formula which allows for the measurement of anomalous
dimensions when transcribed into gradient flow expectation values.


  This submission has been withdrawn by arXiv administrators because it is a
duplicate of 0705.0667.


  This work focuses on the numerical assessment of the accuracy of an
adjoint-based gradient in the perspective of variational data assimilation and
parameter identification in glaciology. Using noisy synthetic data, we quantify
the ability to identify the friction coefficient for such methods with a
non-linear friction law. The exact adjoint problem is solved, based on second
order numerical schemes, and a comparison with the so called "self-adjoint"
approximation, neglecting the viscosity dependency to the velocity (leading to
an incorrect gradient), common in glaciology, is carried out. For data with a
noise of $1\%$, a lower bound of identifiable wavelengths of $10$ ice
thicknesses in the friction coefficient is established, when using the exact
adjoint method, while the "self-adjoint" method is limited, even for lower
noise, to a minimum of $20$ ice thicknesses wavelengths. The second order exact
gradient method therefore provides robustness and reliability for the parameter
identification process. In other respect, the derivation of the adjoint model
using algorithmic differentiation leads to formulate a generalization of the
"self-adjoint" approximation towards an incomplete adjoint method, adjustable
in precision and computational burden.


  Open containers, i.e., containers without covers, are an important and
ubiquitous class of objects in human life. In this letter, we propose a novel
method for robots to "imagine" the open containability affordance of a
previously unseen object via physical simulations. We implement our imagination
method on a UR5 manipulator. The robot autonomously scans the object with an
RGB-D camera. The scanned 3D model is used for open containability imagination
which quantifies the open containability affordance by physically simulating
dropping particles onto the object and counting how many particles are retained
in it. This quantification is used for open-container vs. non-open-container
binary classification (hereafter referred to as open container classification).
If the object is classified as an open container, the robot further imagines
pouring into the object, again using physical simulations, to obtain the
pouring position and orientation for real robot autonomous pouring. We evaluate
our method on open container classification and autonomous pouring of granular
material on a dataset containing 130 previously unseen objects with 57 object
categories. Although our proposed method uses only 11 objects for simulation
calibration (training), its open container classification aligns well with
human judgements. In addition, our method endows the robot with the capability
to autonomously pour into the 55 containers in the dataset with a very high
success rate. We also compare to a deep learning method. Results show that our
method achieves the same performance as the deep learning method on open
container classification and outperforms it on autonomous pouring. Moreover,
our method is fully explainable.


  Brake orbits and homoclinics of autonomous dynamical systems correspond, via
Maupertuis principle, to geodesics in Riemannian manifolds endowed with a
metric which is singular on the boundary (Jacobi metric). Motivated by the
classical, yet still intriguing in many aspects, problem of establishing
multiplicity results for brake orbits and homoclinics, as done in [6, 7, 10],
and by the development of a Morse theory in [8] for geodesics in such kind of
metric, in this paper we study the related normal exponential map from a global
perspective.


  We consider the effect of the magnetic field background in the form of a tube
of the finite transverse size on the vacuum of the quantized charged massive
scalar field which is subject to the Dirichlet boundary condition at the tube.
It is shown that, if the Compton wavelength associated with the scalar field
exceeds considerably the transverse size of the tube, then the vacuum energy
which is finite and periodic in the value of the magnetic flux enclosed in the
tube is induced on a plane transverse to the tube. Some consequences for
generic features of the vacuum polarization in the cosmic-string background are
discussed.


  We present results from model tests to investigate the effect of drafting in
swimming, in particular for the lead swimmer. The drag for scaled-model passive
swimmers was determined accurately at Froude numbers comparable to conditions
for actual human swimmers. Several positions of a draft swimmer at different
separations behind and alongside the lead swimmer were investigated. It was
found that a lead swimmer can experience an advantage from a draft swimmer.
Several other positions of the draft swimmer relative to the frontal wave
generated by the lead swimmer were also considered. These results indicate
favourable and undesirable positions during passing.


  For a compact Riemann surface $X$ of genus $g > 1$, $\Hom(\pi_1(X),
U(p,1))/U(p,1)$ is the moduli space of flat $\U(p,1)$-connections on $X$. There
is an integer invariant, $\tau$, the Toledo invariant associated with each
element in $\Hom(\pi_1(X), U(p,1))/U(p,1)$. If $q = 1$, then $-2(g-1) \le \tau
\le 2(g-1)$. This paper shows that $\Hom(\pi_1(X), U(p,1))/U(p,1)$ has one
connected component corresponding to each $\tau \in 2Z$ with $-2(g-1) \le \tau
\le 2(g-1)$. Therefore the total number of connected components is $2(g-1) +
1$.


  The coupled-cluster wave function factorizes to a very good approximation
into a product of an intrinsic wave function and a Gaussian for the
center-of-mass coordinate. The width of the Gaussian is in general not
identical to the oscillator length of the underlying single-particle basis. The
quality of the separation can be verified by a simple procedure.


  In this paper, we study a new iterative method for a common fixed point of a
finite family of Bregman strongly nonexpansive mappings in the frame work of
reflexive real Banach spaces. Moreover, we prove the strong convergence theorem
for finding common fixed points with the solutions of a mixed equilibrium
problem.


  The extreme intensities obtainable with lasers such as Gemini allow
non-linear QED phenomena to be investigated according to our calculations.
Electron-positron pair production from a pure vacuum target, which has yet to
be observed experimentally, is possibly the most iconic process. Beyond
pair-production our campaign will allow the experimental investigation of
currently unexplored extreme radiation regimes, like the quantum radiation
dominated regime (where quantum and self-field effects become important) and
non-linear Compton scattering. This is the first experiment in a multi-part
campaign proposed by a major international collaboration to investigate
non-linear QED. This proposal is for the first experiment in a series of 3 to
achieve our most high-profile experimental goal of pair production in vacuum,
but each experiment is designed to have its own tangible high-profile outcome.


  The standard $\Lambda$CDM model despite its agreement with observational data
still has some issues unaddressed, lie the problem of initial singularity.
Solving that problem usually requires modifications of general relativity.
However, there appeared the Ho\v{r}ava-Lifshitz (HL) theory of gravity, in
which equations governing cosmological evolution include a new term scaling
similarly as dark radiation term in the Friedmann equations, enabling a bounce
of the universe instead of initial singularity. This review describes past
works on a stability of such a bounce in different formulations of HL theory,
initial detailed balance scenario and further projectable versions containing
higher than quadratic term to the original action.


  We use holographic correspondence to study transport of the conformal plasma
in ${\mathbb R}^{2,1}$ in a phase with a spontaneously broken global $Z_2$
symmetry. The dual black branes in a Poincare patch of asymptotically $AdS_4$
have "hair" -- a condensate of the order parameter for the broken symmetry.
This hair affects both the hydrodynamic and the nonhydrodynamic quasinormal
modes of the black branes. Nonetheless, the shear viscosity of the conformal
order is universal, the bulk viscosity vanishes and the speed of the sound
waves is $c_s^2=\frac 12$. We compute the low-lying spectrum of the
non-hydrodynamic modes. We identify a quasinormal mode associated with the
fluctuations of the $Z_2$ order parameter with the positive imaginary part. The
presence of this mode in the spectrum renders the holographic conformal order
perturbatively unstable. Correspondingly, the dual black branes violate the
correlated stability conjecture.


  We introduce CollisionPro, a pioneering framework designed to estimate
cumulative collision probability distributions using temporal difference
learning, specifically tailored to applications in robotics, with a particular
emphasis on autonomous driving. This approach addresses the demand for
explainable artificial intelligence (XAI) and seeks to overcome limitations
imposed by model-based approaches and conservative constraints. We formulate
our framework within the context of reinforcement learning to pave the way for
safety-aware agents. Nevertheless, we assert that our approach could prove
beneficial in various contexts, including a safety alert system or analytical
purposes. A comprehensive examination of our framework is conducted using a
realistic autonomous driving simulator, illustrating its high sample efficiency
and reliable prediction capabilities for previously unseen collision events.
The source code is publicly available.


  We investigate the dynamics of photon echo exhibited by exciton-plasmon
systems under strong coupling conditions. Using a self-consistent model based
on coupled Maxwell-Bloch equations we investigate femtosecond time dynamics of
ensembles of interacting molecules optically coupled to surface plasmon
supporting materials. It is shown that observed photon echoes under two pulse
pump-probe sequence are highly dependent on various material parameters such as
molecular concentration and periodicity. Simulations of photon echoes in
exciton-plasmon materials reveal a unique signature of the strong
exciton-plasmon coupling, namely a double-peak structure in spectra of recorded
echo signals. This phenomenon is shown to be related to hybrid states (upper
and lower polaritons) in exciton-plasmon systems under strong coupling
conditions. It is also demonstrated that the double-peak echo is highly
sensitive to mild deviations of the coupling from resonant conditions making it
a great tool for ultrafast probes.


  We present Reversible Vision Transformers, a memory efficient architecture
design for visual recognition. By decoupling the GPU memory requirement from
the depth of the model, Reversible Vision Transformers enable scaling up
architectures with efficient memory usage. We adapt two popular models, namely
Vision Transformer and Multiscale Vision Transformers, to reversible variants
and benchmark extensively across both model sizes and tasks of image
classification, object detection and video classification. Reversible Vision
Transformers achieve a reduced memory footprint of up to 15.5x at roughly
identical model complexity, parameters and accuracy, demonstrating the promise
of reversible vision transformers as an efficient backbone for hardware
resource limited training regimes. Finally, we find that the additional
computational burden of recomputing activations is more than overcome for
deeper models, where throughput can increase up to 2.3x over their
non-reversible counterparts. Full code and trained models are available at
https://github.com/facebookresearch/slowfast. A simpler, easy to understand and
modify version is also available at https://github.com/karttikeya/minREV


  High-entropy oxides (HEOs) are a new class of materials that are promising
for a wide range of applications. Designing HEOs needs to consider both
geometric compatibility and electrical equilibrium. However, there is currently
no available method to systematically consider these two factors when selecting
constituent materials for making HEOs. Here we propose a two-step strategy,
where a HEO system to be explored is first partitioned into multiple subsystems
based on the valence combinations of substituted cations; the geometric
compatibility is then considered in selecting suitable substituted cations. We
demonstrate this strategy by using A(5B0.2)O3 perovskite as a model system. We
show that the system can be partitioned into 12 subsystems. Ten of the
subsystems have formed a single-phase cubic perovskite, while two have
partially ordering structure. The formation of single phases is correlated to
Goldschmidt's tolerance factor, while the formation of the ordering structure
is mainly correlated to cation-valence difference. We anticipate that this
strategy is applicable to exploring HEOs in other systems.


  J. Willard Gibbs' Elementary Principles in Statistical Mechanics was the
definitive work of one of America's greatest physicists. Gibbs' book on
statistical mechanics establishes the basic principles and fundamental results
that have flowered into the modern field of statistical mechanics. However, at
a number of points, Gibbs' teachings on statistical mechanics diverge from
positions on the canonical ensemble found in more recent works, at points where
seemingly there should be agreement. The objective of this paper is to note
some of these points, so that Gibbs' actual positions are not misrepresented to
future generations of students.


  We present lattice results for the non-perturbative Collins-Soper (CS)
kernel, which describes the energy-dependence of transverse momentum-dependent
parton distributions (TMDs). The CS kernel is extracted from the ratios of
first Mellin moments of quasi-TMDs evaluated at different nucleon momenta.The
analysis is done with dynamical $N_f=2+1$ clover fermions for the CLS ensemble
H101 ($a=0.0854\,\mathrm{fm}$, $m_{\pi}=m_K=422\,\mathrm{MeV}$). The computed
CS kernel is in good agreement with experimental extractions and previous
lattice studies.


  We propose algorithms to create adversarial attacks to assess model
robustness in text classification problems. They can be used to create white
box attacks and black box attacks while at the same time preserving the
semantics and syntax of the original text. The attacks cause significant number
of flips in white-box setting and same rule based can be used in black-box
setting. In a black-box setting, the attacks created are able to reverse
decisions of transformer based architectures.


  We present updated stellar population models appropriate for old ages (>1
Gyr) and covering a wide range in metallicities (-1.5<[Fe/H]<0.3). These models
predict the full spectral variation associated with individual element
abundance variation as a function of metallicity and age. The models span the
optical-NIR wavelength range (0.37-2.4um), include a range of initial mass
functions (IMFs) and contain the flexibility to vary 18 individual elements
including C, N, O, Mg, Si, Ca, Ti, and Fe. To test the fidelity of the models
we fit them to integrated light optical spectra of 41 Galactic globular
clusters (GCs). The value of testing models against GCs is that their ages,
metallicities, and detailed abundance patterns have been derived from the HR
diagram in combination with high resolution spectroscopy of individual stars.
We determine stellar population parameters from fits to all wavelengths
simultaneously ("full spectrum fitting"), and demonstrate explicitly with mock
tests that this approach produces smaller uncertainties at fixed S/N ratio than
fitting a standard set of 14 line indices. Comparison of our integrated-light
results to literature values reveals good agreement in metallicity, [Fe/H].
When restricting to GCs without prominent blue horizontal branch populations we
also find good agreement with literature values for ages, [Mg/Fe], [Si/Fe], and
[Ti/Fe].


  We recast Dirac's Lagrangian in quantum mechanics in the language of vector
bundles and show that the action is an operator-valued connection one-form.
Phases associated with change of frames of reference are seen to be total
differentials in the transformation of the action. The relativistic case is
discussed and we show that it gives the correct phase in the non-relativistic
limit for uniform acceleration.


  Recent observations of fast radio bursts (FRBs) indicate a perplexing,
inconsistent picture. We propose a unified scenario to interpret diverse FRBs
observed. A regular pulsar, otherwise unnoticeable at a cosmological distance,
may produce a bright FRB if its magnetosphere is suddenly "combed" by a nearby,
strong plasma stream towards the anti-stream direction. If the Earth is to the
night side of the stream, the combed magnetic sheath would sweep across the
direction of Earth and make a detectable FRB. The stream could be an AGN flare,
a GRB or supernova blastwave, a tidal disruption event, or even a stellar
flare. Since it is the energy {\em flux} received by the pulsar rather than the
luminosity of the stream origin that defines the properties of the FRB, this
model predicts a variety of counterparts of FRBs, including a possible
connection between FRB 150418 and an AGN flare, a possible connection between
FRB 131104 and a weak GRB, a steady radio nebula associated with the repeating
FRB 121102, and probably no bright counterparts for some FRBs.


  This paper introduces AIVC, an end-to-end neural video codec. It is based on
two conditional autoencoders MNet and CNet, for motion compensation and coding.
AIVC learns to compress videos using any coding configurations through a single
end-to-end rate-distortion optimization. Furthermore, it offers performance
competitive with the recent video coder HEVC under several established test
conditions. A comprehensive ablation study is performed to evaluate the
benefits of the different modules composing AIVC. The implementation is made
available at https://orange-opensource.github.io/AIVC/.


  The concept of data depth leads to a center-outward ordering of multivariate
data, and it has been effectively used for developing various data analytic
tools. While different notions of depth were originally developed for finite
dimensional data, there have been some recent attempts to develop depth
functions for data in infinite dimensional spaces. In this paper, we consider
some notions of depth in infinite dimensional spaces and study their properties
under various stochastic models. Our analysis shows that some of the depth
functions available in the literature have degenerate behaviour for some
commonly used probability distributions in infinite dimensional spaces of
sequences and functions. As a consequence, they are not very useful for the
analysis of data satisfying such infinite dimensional probability models.
However, some modified versions of those depth functions as well as an infinite
dimensional extension of the spatial depth do not suffer from such degeneracy,
and can be conveniently used for analyzing infinite dimensional data.


  Histopathological prognostication of neoplasia including most tumor grading
systems are based upon a number of criteria. Probably the most important is the
number of mitotic figures which are most commonly determined as the mitotic
count (MC), i.e. number of mitotic figures within 10 consecutive high power
fields. Often the area with the highest mitotic activity is to be selected for
the MC. However, since mitotic activity is not known in advance, an arbitrary
choice of this region is considered one important cause for high variability in
the prognostication and grading.
  In this work, we present an algorithmic approach that first calculates a
mitotic cell map based upon a deep convolutional network. This map is in a
second step used to construct a mitotic activity estimate. Lastly, we select
the image segment representing the size of ten high power fields with the
overall highest mitotic activity as a region proposal for an expert MC
determination. We evaluate the approach using a dataset of 32 completely
annotated whole slide images, where 22 were used for training of the network
and 10 for test. We find a correlation of r=0.936 in mitotic count estimate.


  There is a procedure, due to Dani and Levcovitz, for taking a finite
simplicial graph (\Gamma) and a subgraph (\Lambda) of its complement, checking
some conditions, and, if satisfied, producing a graph (\Delta) such that the
right-angled Artin group with presentation graph (\Delta) is a finite index
subgroup of the right-angled Coxeter group with presentation graph (\Gamma).
They do not tell us how to find (\Lambda), given (\Gamma).
  We show, in the 2--dimensional case, that the existence of such a (\Lambda)
is connected to the graph property of satellite-dismantlabilty of (\Gamma), and
we use this to give an algorithm for producing a suitable (\Lambda) or deciding
that one does not exist.


  Floquet's Theorem is a celebrated result in the theory of ordinary
differential equations. Essentially, the theorem states that, when studying a
linear differential system with $T$-periodic coefficients, we can apply a,
possibly complex, $T$-periodic change of variables that transforms it into a
linear system with constant coefficients. In this paper, we explore further the
question of the nature of this change of variables. We state necessary and
sufficient conditions for it to be real and $T$-periodic. Failing those
conditions, we prove that we can still find a real change of variables that is
``partially" $T$-periodic and ``partially" $T$-antiperiodic. We also present
applications of this new form of Floquet's Theorem to the study of the behavior
of solutions of nonlinear differential systems near periodic orbits.


  We have synthesized Gd$_{2}$FeCrO$_{6}$ (GFCO) double perovskite which is
crystallized in a monoclinic structure with P2$_{1}/$n space group. The
UV-visible and photoluminescence spectroscopic analyses confirmed its direct
bandgap semiconducting nature. Employing experimentally obtained structural
parameters in first-principles calculation, we report the spin-polarized
electronic band structure, charge carrier effective mass, density of states,
electronic charge density distribution and optical absorption property of the
GFCO double perovskite. The effects of on-site d-d Coulomb interaction energy
(U$_{eff}$) on the electronic and optical properties were investigated by
applying a range of Hubbard U$_{eff}$ parameters from 0 to 6 eV to the Fe-3d
and Cr-3d orbitals within the generalized gradient approximation (GGA) and
GGA+U methods. When we applied U$_{eff}$ in the range of 1 to 5 eV, both the
up-spin and down-spin band structures were observed to be direct. The charge
carrier effective masses were also found to enhance gradually from U$_{eff} =$
1 eV to 5 eV, but, these values were anomalous for U$_{eff} =$ 0 and 6 eV.
These results suggest that U$_{eff}$ should be limited within the range of 1 to
5 eV to calculate the structural, electronic and optical properties of GFCO
double perovskite. We observed that considering U$_{eff} =$ 3 eV, the
theoretically calculated optical band gap 1.99 eV matched well with the
experimentally obtained value 2.0 eV. The outcomes of our finding imply that
the U$_{eff}$ value of 3 eV most accurately localized the Fe-3d and Cr-3d
orbitals of GFCO keeping the effect of self-interaction error from the other
orbitals almost negligible. Therefore, we may recommend U$_{eff} =$ 3 eV for
first-principles calculation of the electronic and optical properties of GFCO
double perovskite that might have potential in photocatalytic and related solar
energy applications.


  DNA-coated colloids can crystallize into a multitude of lattices, ranging
from face-centered cubic to diamond and thereby contribute to our understanding
of crystallization and open avenues to producing structures with useful
photonic properties. Despite the broad potential design space of DNA-coated
colloids, the design cycle for synthesizing DNA-coated particles is slow:
preparing a particle with a new type of DNA sequence takes more than one day
and requires custom-made and chemically modified DNA that typically takes the
supplier over a month to synthesize. Here, we introduce a method to generate
particles with custom sequences from a single feed stock in under an hour at
ambient conditions. Our method appends new DNA domains onto the DNA grafted to
colloidal particles based on a template that takes the supplier less than a
week to produce. The resultant particles crystallize as readily and at the same
temperature as those produced via direct chemical synthesis. Moreover, we show
that particles coated with a single sequence can be converted into a variety of
building blocks with differing specificities by appending different DNA
sequences to them. This approach to DNA-coated particle preparation will make
it practical to identify optimal and complex particle sequence designs and to
expand the use of DNA-coated colloids to a much broader range of investigators
and commercial entities.


  We study ensembles of 1/2-BPS bound states of fundamental strings and
NS-fivebranes (NS5-F1 states) in the AdS decoupling limit. We revisit a
solution corresponding to an ensemble average of these bound states, and find
that the appropriate duality frame for describing the near-source structure is
the T-dual NS5-P frame, where the bound state is a collection of momentum waves
on the fivebranes. We find that the fivebranes are generically well-separated;
this property results in the applicability of perturbative string theory. The
geometry sourced by the typical microstate is not close to that of an extremal
non-rotating black hole; instead the fivebranes occupy a ball whose radius is
parametrically much larger than the "stretched horizon" scale of the
corresponding black hole. These microstates are thus better characterized as
BPS fivebrane stars than as small black holes.
  When members of the ensemble spin with two fixed angular potentials about two
orthogonal planes, we find that the spherical ball of the non-rotating ensemble
average geometry deforms into an ellipsoid. This contrasts with ring structures
obtained when fixing the angular momenta instead of the angular potentials; we
trace this difference of ensembles to large fluctuations of the angular
momentum in the ensemble of fixed angular potential.


  Laboratory experimental results are presented for nonlinear Internal Solitary
Waves (ISW) propagation in deep water configuration with miscible fluids. The
results are validated against direct numerical simulations and traveling wave
exact solutions where the effect of the diffused interface is taken into
account. The waves are generated by means of a dam break and their evolution is
recorded with Laser Induced Fluorescence (LIF) and Particle Image Velocimetry
(PIV). In particular, data collected in a frame moving with the waves are
presented here for the first time. Our results are representative of
geophysical applications in the deep ocean where weakly nonlinear theories fail
to capture the characteristics of large amplitude ISWs from field observations.


  We investigate consensus dynamics on temporal hypergraphs that encode network
systems with time-dependent, multi-way interactions. We compare this dynamics
with that on appropriate projections of this higher-order network
representation that flatten the temporal, the multi-way component, or both. For
linear average consensus dynamics, we find that the convergence of a randomly
switching time-varying system with multi-way interactions is slower than the
convergence of the corresponding system with pairwise interactions, which in
turn exhibits a slower convergence rate than a consensus dynamics on the
corresponding static network. We then consider a nonlinear consensus dynamics
model in the temporal setting. Here we find that in addition to an effect on
the convergence speed, the final consensus value of the temporal system can
differ strongly from the consensus on the aggregated, static hypergraph. In
particular we observe a first-mover advantage in the consensus formation
process: If there is a local majority opinion in the hyperedges that are active
early on, the majority in these first-mover groups has a higher influence on
the final consensus value - a behaviour that is not observable in this form in
projections of the temporal hypergraph.


  The temperature evolution of icosahedral medium-range order formed by
interpenetrating icosahedra in CuZr metallic glass-forming liquids was
investigated via molecular dynamics simulations. Scaling analysis based on
percolation theory was employed, and it is found that the size distribution of
clusters formed by the central atoms of icosahedra at various temperatures
follows a very good scaling law with the cluster number density scaled by
$S^{-\tau}$ and the cluster size $S$ scaled by $|1-T_c/T|^{-1/\sigma}$,
respectively. Here $T_c$ is scaling crossover-temperature. $\tau$ and $\sigma$
are scaling exponents. The critical scaling behaviour suggests that there would
be a structural phase transition manifested by percolation of locally favoured
structures underlying the glass transition, if the liquid could be cooled
slowly enough but without crystallization intervening. Furthermore, it is
revealed that when icosahedral short-range order (ISRO) extends to medium-range
length scale by connection, the atomic configurations of ISROs will be
optimized from distorted ones towards more regular ones gradually, which
significantly lowers the energies of ISROs and introduces geometric frustration
simultaneously. Both factors make key impacts on the drastic dynamic slowdown
of supercooled liquids. Our findings provide direct structure-property
relationship for understanding the nature of glass transition.


  We propose "Conceptual Coverage Across Languages" (CoCo-CroLa), a technique
for benchmarking the degree to which any generative text-to-image system
provides multilingual parity to its training language in terms of tangible
nouns. For each model we can assess "conceptual coverage" of a given target
language relative to a source language by comparing the population of images
generated for a series of tangible nouns in the source language to the
population of images generated for each noun under translation in the target
language. This technique allows us to estimate how well-suited a model is to a
target language as well as identify model-specific weaknesses, spurious
correlations, and biases without a-priori assumptions. We demonstrate how it
can be used to benchmark T2I models in terms of multilinguality, and how
despite its simplicity it is a good proxy for impressive generalization.


  We present a study of the effect of biaxial strain on the electrical and
magnetic properties of thin films of manganites. We observe that manganite
films grown under biaxial compressive strain exhibit island growth morphology
which leads to a non-uniform distribution of the strain. Transport and magnetic
properties of these films suggest the coexistence of two different phases, a
metallic ferromagnet and an insulating antiferromagnet. We suggest that the
high strain regions are insulating while the low strain regions are metallic.
In such non-uniformly strained samples, we observe a large magnetoresistance
and a field-induced insulator to metal transition.


  In the recent years, due to the economic and environmental requirements, the
use of distributed generations (DGs) has increased. If DGs have the optimal
size and are located at the optimal locations, they are capable of enhancing
the voltage profile and reducing the power loss. This paper proposes a new
approach to obtain the optimal location and size of DGs. To this end, exchange
market algorithm (EMA) is offered to find the optimal size and location of DGs
subject to minimizing loss, increasing voltage profile, and improving voltage
stability in the distribution systems. The effectiveness of the proposed
approach is verified on both 33- and 69-bus IEEE standard systems.


  Variable Elimination is a fundamental algorithm for probabilistic inference
over Bayesian networks. In this paper, we propose a novel materialization
method for Variable Elimination, which can lead to significant efficiency gains
when answering inference queries. We evaluate our technique using real-world
Bayesian networks. Our results show that a modest amount of materialization can
lead to significant improvements in the running time of queries. Furthermore,
in comparison with junction tree methods that also rely on materialization, our
approach achieves comparable efficiency during inference using significantly
lighter materialization.


  Many neutrino mixing scenarios that have \mu-\tau symmetry with \theta_{13}=0
are in disagreement with recent experimental results that indicate a nonzero
value for \theta_{13}. We investigate the effect of small perturbations on
Majorana mass matrices with \mu-\tau symmetry and derive analytic formulae for
the corrections to the mixing angles. We find that since m_1 and m_2 are nearly
degenerate, \mu-\tau symmetry mixing scenarios are able to explain the
experimental data with about the same size perturbation for most values of
\theta_{12}. This suggests that the underlying unperturbed mixing need not have
\theta_{12} close to the experimentally preferred value. One consequence of
this is that a new class of models with \mu-\tau symmetry is possible, with
unperturbed \theta_{12} equal to zero or 90 degrees for arbitrary unperturbed
\theta_{13}.


  The influence of nonperturbative fields on instantons in quantum
chromodynamics is studied. Nonperturbative vacuum is described in terms of
nonlocal gauge invariant vacuum averages of gluon field strength. Effective
action for instanton is derived in bilocal approximation and it is demonstrated
that stochastic background gluon fields are responsible for infra-red
(IR)stabilization of instantons. Comparison of obtained instanton size
distribution with lattice data is made.


  The tuning of fused filament fabrication parameters is notoriously
challenging. We propose an autonomous data-driven method to select parameters
based on in situ measurements. We use a laser sensor to evaluate the surface
roughness of a printed part. We then correlate the roughness to the mechanical
properties of the part, and show how print quality affects mechanical
performance. Finally, we use Bayesian optimization to search for optimal print
parameters. We demonstrate our method by printing liquid crystal polymer
samples, and successfully find parameters that produce high-performance prints
and maximize the manufacturing process efficiency.


  This paper aims to improve privacy-preserving visual recognition, an
increasingly demanded feature in smart camera applications, by formulating a
unique adversarial training framework. The proposed framework explicitly learns
a degradation transform for the original video inputs, in order to optimize the
trade-off between target task performance and the associated privacy budgets on
the degraded video. A notable challenge is that the privacy budget, often
defined and measured in task-driven contexts, cannot be reliably indicated
using any single model performance, because a strong protection of privacy has
to sustain against any possible model that tries to hack privacy information.
Such an uncommon situation has motivated us to propose two strategies, i.e.,
budget model restarting and ensemble, to enhance the generalization of the
learned degradation on protecting privacy against unseen hacker models. Novel
training strategies, evaluation protocols, and result visualization methods
have been designed accordingly. Two experiments on privacy-preserving action
recognition, with privacy budgets defined in various ways, manifest the
compelling effectiveness of the proposed framework in simultaneously
maintaining high target task (action recognition) performance while suppressing
the privacy breach risk.


  Milli-arcsecond astrometry provided by Hipparcos and by radio observations
makes it possible to retrace the orbits of some of the nearest runaway stars
and pulsars to determine their site of origin. The orbits of the runaways AE
Aurigae and mu Columbae and of the eccentric binary iota Orionis intersect each
other about 2.5 Myr ago in the nascent Trapezium cluster, confirming that these
runaways were formed in a binary-binary encounter. The path of the runaway star
zeta Ophiuchi intersects that of the nearby pulsar PSR J1932+1059, about 1 Myr
ago, in the young stellar group Upper Scorpius. We propose that this neutron
star is the remnant of a supernova that occurred in a binary system which also
contained zeta Oph, and deduce that the pulsar received a kick velocity of
about 350 km/s in the explosion. These two cases provide the first specific
kinematic evidence that both mechanisms proposed for the production of runaway
stars, the dynamical ejection scenario and the binary-supernova scenario,
operate in nature.


  Adaptive Cluster Sampling (ACS) is introduced as a technique to use when
"natural" groupings are evident in a spatially distributed population,
especially sparsely distributed populations. An ACS sampling design will allow
efficient allocation of survey manpower with more effective decision rules for
where/when to allocate those resources. In particular, given a clustered
distribution, ACS would result in a lower variance of the mean estimator than
Simple Random Sampling (SRS). This paper derives a linear inequality based on a
ratio of variances and the SRS sample size to determine the conditions under
which ACS would be a more appropriate sampling strategy. This inequality could
be used to make preliminary decisions on the potential benefits of pursuing an
ACS design over an SRS design. The relationship between relative efficiency of
ACS over SRS is discussed for (1) variable conditions for neighborhood
expansion (Conditions to Adpat) (2) the degree of clustering and (3) the
percent of hits in a particular neighborhood. Simulation results demonstrate
how 'rare' clusters should be for ACS to be a better design than SRS. The
relationships that emerge from the simulation provide insights that were not
apparent in the analysis. The results are important in the estimation of
thresher shark landings along the California coast.


  As an extension of the so-called BMN conjecture, we investigate the
plane-wave limit for possible holographic connection between bulk string
theories in non-conformal backgrounds of D$p$-branes and the corresponding
supersymmetric gauge theories for $p<5$. Our work is based on the tunneling
picture for dominant null trajectories of strings in the limit of large angular
momentum. The tunneling null trajectories start from the near-horizon boundary
and return to the boundary, and the resulting backgrounds are time-dependent
for general D$p$-branes except for $p=3$. We develop a general method for
extracting diagonalized two-point functions for boundary theories as Euclidean
(bulk) S-matrix in the time-dependent backgrounds. For the case of D0-brane,
two-point functions of supergravity modes are shown to agree with the results
derived previously by the perturbative analysis of supergravity. We then
discuss the implications of the holography for general cases of D$p$-branes
including the stringy excitations. All the cases ($p\ne 3, p<5$) exhibit
interesting infra-red behaviors, which are different from free-field theories,
suggesting the existence of quite nontrivial fixed-points in dual gauge
theories.


  We have reported previously on the conditioning of the high-gradient
accelerating cavities in the Fermilab Linac. Automated measurements of the
sparking rate have been recorded since 1994 and are reported here. The sparking
rate has declined since the beginning, but there are indications that this rate
may have leveled off now. The X-rays emitted by the cavities are continuing to
decrease.


  In this paper the definitions and the properties of a newle dedicated set of
high-frequency filters based on smoothing-and-clipping are briefly described.
New applications for reduction of wide--field 2048x2048 CCD spectral and direct
images of a new deep survey KISS (KPNO International Spectral Survey) are also
presented. The developed software is available both as a C subroutine and as an
installed MIDAS environment command.


  We calculate the first vertex correction $\delta\Lambda_{\bf k}$ to the bare
vertex $\Lambda_\circ$ in the nearly antiferromagnetic spin fluctuation Fermi
liquid theory of the cuprate superconductor ${\rm YBa_2Cu_3O_7}$. It is
calculated for $\bf k$ on the Fermi surface, and ${\bf Q}=(\pm {\pi\over a},
\pm {\pi\over a})$. We find that the dimensionless ratio $|\delta\Lambda_{\bf
k}|/\Lambda_\circ$, which parametrizes the vertex correction, is not small. It
is a maximum for ${\bf k=k_h}$, where ${\bf k_h}$ is a ``hot spot'' on the
Fermi surface. This makes large quantitative corrections to the theory.


  Strain engineering is a very effective method to continuously tune the
electronic, topological, optical and thermoelectric properties of materials. In
this work, strain-dependent phonon transport of recently-fabricated antimonene
(Sb monolayer) under biaxial strain is investigated from a combination of
first-principles calculations and the linearized phonon Boltzmann equation. It
is found that the ZA dispersion of antimonene with strain less than -1\% gives
imaginary frequencies, which suggests that compressive strain can induce
structural instability. Experimentally, it is possible to enhance structural
stability by tensile strain. Calculated results show that lattice thermal
conductivity increases with strain changing from -1\% to 6\%, and lattice
thermal conductivity at 6\% strain is 5.6 times larger than that at -1\% strain
at room temperature. It is interesting that lattice thermal conductivity is in
inverse proportion to buckling parameter $h$ in considered strain range. Such a
strain dependence of lattice thermal conductivity is attributed to enhanced
phonon lifetimes caused by increased strain, while group velocities have a
decreased effect on lattice thermal conductivity with increasing strain. It is
found that acoustic branches dominate the lattice thermal conductivity over the
full strain range. The cumulative room-temperature lattice thermal conductivity
at -1\% strain converges to maximum with phonon mean free path (MFP) at 50 nm,
while one at 6\% strain becomes as large as 44 $\mathrm{\mu m}$, which suggests
that strain can give rise to very strong size effects on lattice thermal
conductivity in antimonene. These results may provide guidance on fabrication
techniques of antimonene, and offer perspectives on tuning lattice thermal
conductivity by size and strain for applications of thermal management and
thermoelectricity.


  The bosonic nature of light leads to counter-intuitive bunching effects. We
describe an experimentally testable effect in which a single photon is induced
through a highly reflecting beamsplitter by a large amplitude coherent state,
with probability 1/e in the limit of large coherent state amplitude. We use
this effect to construct a viable implementation of the bare raising operator
on coherent states via conditional measurement, which succeeds with high
probability and fidelity even in the high amplitude limit.


  We report on numerical results from an independent formalism to describe the
quasi-equilibrium structure of nonsynchronous binary neutron stars in general
relativity. This is an important independent test of controversial numerical
hydrodynamic simulations which suggested that nonsynchronous neutron stars in a
close binary can experience compression prior to the last stable circular
orbit. We show that, for compact enough stars the interior density increases
slightly as irrotational binary neutron stars approach their last orbits. The
magnitude of the effect, however, is much smaller than that reported in
previous hydrodynamic simulations.


  In 2012 M. Soki\'c proved that the class of all finite permutations has the
Ramsey property. Using different strategies the same result was then reproved
in 2013 by J. B\"ottcher and J. Foniok, in 2014 by M. Bodirsky and in 2015 yet
another proof was provided by M. Soki\'c. Using the categorical
reinterpretation of the Ramsey property in this paper we prove that the class
of all finite permutations has the dual Ramsey property as well. It was Leeb
who pointed out in 1970 that the use of category theory can be quite helpful
both in the formulation and in the proofs of results pertaining to structural
Ramsey theory. In this paper we argue that this is even more the case when
dealing with the dual Ramsey property.


  In this paper, we study the influence of an Allee effect on the spreading
rate in a local reaction-diffusion-mutation equation modelling the invasion of
cane toads in Australia. We are, in particular, concerned with the case when
the diffusivity can take unbounded values. We show that the acceleration
feature that arises in this model with a Fisher-KPP, or monostable,
non-linearity still occurs when this non-linearity is instead bistable, despite
the fact that this kills the small populations. This is in stark contrast to
the work of Alfaro, Gui-Huan, and Mellet-Roquejoffre-Sire in related models,
where the change to a bistable non-linearity prevents acceleration.


  We explore in this paper the ability to constrain the Galactic magnetic field
intensity and spatial distribution with the incoming data from the Planck
satellite experiment. We perform realistic simulations of the Planck
observations at the polarized frequency bands from 30 to 353 GHz for two
all-sky surveys as expected for the nominal mission. These simulations include
CMB, synchrotron and thermal dust Galactic emissions and instrumental noise.
(Note that systematic effects are not considered in this paper). For the
synchrotron and thermal dust Galactic emissions we use a coherent 3D model of
the Galaxy describing its mater density and the magnetic field direction and
intensity. We first simulate the synchrotron and dust emissions at 408 MHz and
545 GHz, respectively, and then we extrapolate them to the Planck frequency
bands. We perform a likelihood analysis to compare the simulated data to a set
of models obtained by varying the pitch angle of the regular magnetic field
spatial distribution, the relative amplitude of the turbulent magnetic field,
the radial scale of the electron and dust grain distributions, and the
extrapolation spectral indices for the synchrotron and thermal dust emissions.
We are able to set tight constraints on all the parameters considered. We have
also found that the observed spatial variations of the synchrotron and thermal
dust spectral indices should not affect our ability to recover the other
parameters of the model. From this, we conclude that the Planck satellite
experiment can precisely measure the main properties of the Galactic magnetic
field. An accurate reconstruction of the matter distribution would require on
the one hand an improved modelling of the ISM and on the other hand to use
extra data sets like rotation measurements of pulsars.


  In this paper, we provide two different resolutions of structural sheaves of
projectivized tangent bundles of smooth complete intersections. These
resolutions allow in particular to obtain convenient (and completely explicit)
descriptions of cohomology of twisted symmetric powers of cotangent bundles of
complete intersections, which are easily implemented on computer. We then
provide several applications. First, we recover the known vanishing theorems on
the subject, and show that they are optimal via some non-vanishing theorems.
Then, we study the symmetric algebra of global sections of symmetric powers of
$\Omega_X(1)$, where $X$ is a smooth complete intersection of codimension $c <
N/2$, improving the known results in the literature. We also study partial
ampleness of cotangent bundles of general hypersurfaces. Finally, we illustrate
how the explicit descriptions of cohomology can be implemented on computer. In
particular, this allows to exhibit new and simple examples of family of
surfaces along which the canonically twisted pluri-genera do not remain
constant.


  In this paper, we characterize and study the concept of controlled continuous
$g$-frame which is an extension of continuous $g$-frame in Hilbert spaces. We
introduce the concept of controlled continuous dual $g$-frame and observe some
interesting properties of it. Finally, we characterize all controlled
continuous dual $g$-frames of a controlled continuous $g$-frame.


  Click-through rate (CTR) prediction becomes indispensable in ubiquitous web
recommendation applications. Nevertheless, the current methods are struggling
under the cold-start scenarios where the user interactions are extremely
sparse. We consider this problem as an automatic identification about whether
the user behaviors are rich enough to capture the interests for prediction, and
propose an Auto-Quantized Contrastive Learning (AQCL) loss to regularize the
model. Different from previous methods, AQCL explores both the
instance-instance and the instance-cluster similarity to robustify the latent
representation, and automatically reduces the information loss to the active
users due to the quantization. The proposed framework is agnostic to different
model architectures and can be trained in an end-to-end fashion. Extensive
results show that it consistently improves the current state-of-the-art CTR
models.


  As of 2014, 54% of the earth's population resides in urban areas, and it is
steadily increasing, expecting to reach 66% by 2050. Urban areas range from
small cities with tens of thousands of people to megacities with greater than
10 million people. Roughly 12% of the global population today lives in 28
megacities, and at least 40 are projected by 2030. At these scales, the urban
infrastructure such as roads, buildings, and utility networks will cover areas
as large as New England. This steady urbanization and the resulting expansion
of infrastructure, combined with renewal of aging urban infrastructure,
represent tens of trillion of dollars in new urban infrastructure investment
over the coming decades. These investments must balance factors including
impact on clean air and water, energy and maintenance costs, and the
productivity and health of city dwellers. Moreover, cost-effective management
and sustainability of these growing urban areas will be one of the most
critical challenges to our society, motivating the concept of science- and
data-driven urban design, retrofit, and operation-that is, "Smart Cities".


  The need for recognition/approximation of functions in terms of elementary
functions/operations emerges in many areas of experimental mathematics,
numerical analysis, computer algebra systems, model building, machine learning,
approximation and data compression. One of the most underestimated methods is
the symbolic regression. In the article, reductionist approach is applied,
reducing full problem to constant functions, i.e, pure numbers (decimal,
floating-point). However, existing solutions are plagued by lack of solid
criteria distinguishing between random formula, matching approximately or
literally decimal expansion and probable ''exact'' (the best) expression match
in the sense of Occam's razor. In particular, convincing STOP criteria for
search were never developed. In the article, such a criteria, working in
statistical sense, are provided. Recognition process can be viewed as (1)
enumeration of all formulas in order of increasing Kolmogorov complexity K (2)
random process with appropriate statistical distribution (3) compression of a
decimal string. All three approaches are remarkably consistent, and provide
essentially the same limit for practical depth of search. Tested unique
formulas count must not exceed 1/sigma, where sigma is relative numerical error
of the target constant. Beyond that, further search is pointless, because, in
the view of approach (1), number of equivalent expressions within error bounds
grows exponentially; in view of (2), probability of random match approaches 1;
in view of (3) compression ratio much smaller than 1.


  The purpose of this paper is to introduce a new family of semigroups - the
free projection-generated regular $*$-semigroups - and initiate their
systematic study. Such a semigroup $PG(P)$ is constructed from a projection
algebra $P$, using the recent groupoid approach to regular $*$-semigroups. The
assignment $P\mapsto PG(P)$ is a left adjoint to the forgetful functor that
maps a regular $*$-semigroup $S$ to its projection algebra $P(S)$. In fact, the
category of projection algebras is coreflective in the category of regular
$*$-semigroups. The algebra $P(S)$ uniquely determines the biordered structure
of the idempotents $E(S)$, up to isomorphism, and this leads to a category
equivalence between projection algebras and regular $*$-biordered sets. As a
consequence, $PG(P)$ can be viewed as a quotient of the classical free
idempotent-generated (regular) semigroups $IG(E)$ and $RIG(E)$, where
$E=E(PG(P))$; this is witnessed by a number of presentations in terms of
generators and defining relations. The semigroup $PG(P)$ can also be viewed as
the fundamental groupoid of a simplicial complex explicitly constructed from
$P$. The theory is then illustrated on a number of examples. In one direction,
the free construction applied to the projection algebras of adjacency
semigroups yields a new family of graph-based path semigroups. In another, it
turns out that, remarkably, the Temperley-Lieb monoid $TL_n$ is the free
regular $*$-semigroup over its own projection algebra $P(TL_n)$.


  In this work we present a performance exploration on Eager K-truss, a
linear-algebraic formulation of the K-truss graph algorithm. We address
performance issues related to load imbalance of parallel tasks in symmetric,
triangular graphs by presenting a fine-grained parallel approach to executing
the support computation. This approach also increases available parallelism,
making it amenable to GPU execution. We demonstrate our fine-grained parallel
approach using implementations in Kokkos and evaluate them on an Intel Skylake
CPU and an Nvidia Tesla V100 GPU. Overall, we observe between a 1.261. 48x
improvement on the CPU and a 9.97-16.92x improvement on the GPU due to our
fine-grained parallel formulation.


  Backdoor attacks have been one of the emerging security threats to deep
neural networks (DNNs), leading to serious consequences. One of the mainstream
backdoor defenses is model reconstruction-based. Such defenses adopt model
unlearning or pruning to eliminate backdoors. However, little attention has
been paid to survive from such defenses. To bridge the gap, we propose Venom,
the first generic backdoor attack enhancer to improve the survivability of
existing backdoor attacks against model reconstruction-based defenses. We
formalize Venom as a binary-task optimization problem. The first is the
original backdoor attack task to preserve the original attack capability, while
the second is the attack enhancement task to improve the attack survivability.
To realize the second task, we propose attention imitation loss to force the
decision path of poisoned samples in backdoored models to couple with the
crucial decision path of benign samples, which makes backdoors difficult to
eliminate. Our extensive evaluation on two DNNs and three datasets has
demonstrated that Venom significantly improves the survivability of eight
state-of-the-art attacks against eight state-of-the-art defenses without
impacting the capability of the original attacks.


  Aims. We aim to expand our understanding of radio wave emission and
propagation in the pulsar magnetosphere by studying the polarization of
drifting sub-pulses in highly sensitive observations of PSR~B1919+21 recorded
at the Arecibo Observatory.
  Methods. We apply and compare several methods of analysis and visualization,
including eigenvalue analysis of the longitude-resolved covariances between the
Stokes parameters; longitude-resolved scatter plots of the normalised Stokes
vectors in the Poincar\'e sphere; auto- and cross-correlations between the
Stokes parameters as a function of offset in pulse longitude and lag in pulse
number; and mean drift bands of polarization state, formed by averaging the
Stokes parameters and quantities derived from them synchronously with the
drifting sub-pulse modulation period.
  Results. We observe regions of pulse longitude where the superposition of
orthogonally polarised modes is best described as incoherent and regions where
the superposition appears to be at least partially coherent. Within the region
of coherent superposition, over a range of pulse longitudes spanning $\sim
2\circ$, the distribution of the Stokes polarization vectors forms a torus
centered near the origin of the Poincar\'e sphere. Furthermore, the
polarization vectors rotate about the axis of revolution of the torus
synchronously with the drifting sub-pulse modulation of the total intensity.
  Conclusions. The nearly uniform circular modulation of polarization state,
clearly evident in both the toroidal distribution of the Stokes polarization
vectors and the mean drift bands of the Stokes parameters, is not predicted by
current theoretical models of pulsar emission. We propose different scenarios
to explain the generation of the torus, based on either incoherent or
phase-coherent superposition of orthogonally polarised modes.


  Images of the CO 2-1 line emission, and the radio continuum emission, from
the redshift 4.12 gravitationally lensed quasi-stellar object (QSO) PSS
J2322+1944 reveal an Einstein ring with a diameter of 1.5". These observations
are modeled as a star forming disk surrounding the QSO nucleus with a radius of
2 kpc. The implied massive star formation rate is 900 M_sun/year. At this rate
a substantial fraction of the stars in a large elliptical galaxy could form on
a dynamical time scale of 10^8 years. The observation of active star formation
in the host galaxy of a high-redshift QSO supports the hypothesis of coeval
formation of supermassive black holes and stars in spheroidal galaxies.


  Solid state spectroscopy continues to be an important source of information
on the mineralogical composition and physical properties of dust grains both in
space and on planetary surfaces. With only a few exceptions, artificially
produced or natural terrestrial analog materials, rather than 'real' cosmic
dust grains, are the subject of solid state astrophysics. The Jena laboratory
has provided a large number of data sets characterizing the UV, optical and
infrared properties of such cosmic dust analogs. The present paper highlights
recent developments and results achieved in this context, focussing on
'non-standard conditions' such as very low temperatures, very high temperatures
and very long wavelengths.


  The paper describes a number of simple but quite effective methods for
constructing exact solutions of PDEs, that involve a relatively small amount of
intermediate calculations. The methods employ two main ideas: (i) simple exact
solutions can serve to construct more complex solutions of the equations under
consideration and (ii) exact solutions of some equations can serve to construct
solutions of other, more complex equations. In particular, we propose a method
for constructing complex solutions from simple solutions using translation and
scaling. We show that in some cases, rather complex solutions can be obtained
by adding one or more terms to simpler solutions. There are situations where
nonlinear superposition allows us to construct a complex composite solution
using similar simple solutions. We also propose a few methods for constructing
complex exact solutions to linear and nonlinear PDEs by introducing
complex-valued parameters into simpler solutions. The effectiveness of the
methods is illustrated by a large number of specific examples (over 30 in
total). These include nonlinear heat/diffusion equations, wave type equations,
Klein--Gordon type equations, hydrodynamic boundary layer equations,
Navier--Stokes equations, and some other PDEs. Apart from exact solutions to
`ordinary' PDEs, we also describe some exact solutions to more complex
nonlinear delay PDEs. Along with the unknown function at the current time,
$u=u(x,t)$, these equations contain the same function at a past time,
$w=u(x,t-\tau)$, where $\tau>0$ is the delay time. Furthermore, we look at
nonlinear partial functional-differential equations of the pantograph type,
which in addition to the unknown $u=u(x,t)$, also contain the same functions
with dilated or contracted arguments, $w=u(px,qt)$, where $p$ and $q$ are
scaling parameters.


  In this work, we present a dense tracking and mapping system named
Vox-Fusion, which seamlessly fuses neural implicit representations with
traditional volumetric fusion methods. Our approach is inspired by the recently
developed implicit mapping and positioning system and further extends the idea
so that it can be freely applied to practical scenarios. Specifically, we
leverage a voxel-based neural implicit surface representation to encode and
optimize the scene inside each voxel. Furthermore, we adopt an octree-based
structure to divide the scene and support dynamic expansion, enabling our
system to track and map arbitrary scenes without knowing the environment like
in previous works. Moreover, we proposed a high-performance multi-process
framework to speed up the method, thus supporting some applications that
require real-time performance. The evaluation results show that our methods can
achieve better accuracy and completeness than previous methods. We also show
that our Vox-Fusion can be used in augmented reality and virtual reality
applications. Our source code is publicly available at
https://github.com/zju3dv/Vox-Fusion.


  In this paper we consider a probabilistic signal-to-interference and-noise
ratio (SINR) constrained problem for transmit beamforming design in the
presence of imperfect channel state information (CSI), under a multiuser
multiple-input single-output (MISO) downlink scenario. In particular, we deal
with outage-based quality-of-service constraints, where the probability of each
user's SINR not satisfying a service requirement must not fall below a given
outage probability specification. The study of solution approaches to the
probabilistic SINR constrained problem is important because CSI errors are
often present in practical systems and they may cause substantial SINR outages
if not handled properly. However, a major technical challenge is how to process
the probabilistic SINR constraints. To tackle this, we propose a novel
relaxation- restriction (RAR) approach, which consists of two key
ingredients-semidefinite relaxation (SDR), and analytic tools for
conservatively approximating probabilistic constraints. The underlying goal is
to establish approximate probabilistic SINR constrained formulations in the
form of convex conic optimization problems, so that they can be readily
implemented by available solvers. Using either an intuitive worst-case argument
or specialized probabilistic results, we develop various conservative
approximation schemes for processing probabilistic constraints with quadratic
uncertainties. Consequently, we obtain several RAR alternatives for handling
the probabilistic SINR constrained problem. Our techniques apply to both
complex Gaussian CSI errors and i.i.d. bounded CSI errors with unknown
distribution. Moreover, results obtained from our extensive simulations show
that the proposed RAR methods significantly improve upon existing ones, both in
terms of solution quality and computational complexity.


  Prediction models can perform poorly when deployed to target distributions
different from the training distribution. To understand these operational
failure modes, we develop a method, called DIstribution Shift DEcomposition
(DISDE), to attribute a drop in performance to different types of distribution
shifts. Our approach decomposes the performance drop into terms for 1) an
increase in harder but frequently seen examples from training, 2) changes in
the relationship between features and outcomes, and 3) poor performance on
examples infrequent or unseen during training. These terms are defined by
fixing a distribution on $X$ while varying the conditional distribution of $Y
\mid X$ between training and target, or by fixing the conditional distribution
of $Y \mid X$ while varying the distribution on $X$. In order to do this, we
define a hypothetical distribution on $X$ consisting of values common in both
training and target, over which it is easy to compare $Y \mid X$ and thus
predictive performance. We estimate performance on this hypothetical
distribution via reweighting methods. Empirically, we show how our method can
1) inform potential modeling improvements across distribution shifts for
employment prediction on tabular census data, and 2) help to explain why
certain domain adaptation methods fail to improve model performance for
satellite image classification.


  The engineering design of robotic grippers presents an ample design space for
optimization towards robust grasping. In this paper, we adopt the
reconfigurable design of the robotic gripper using a novel soft finger
structure with omni-directional adaptation, which generates a large number of
possible gripper configurations by rearranging these fingers. Such
reconfigurable design with these omni-adaptive fingers enables us to
systematically investigate the optimal arrangement of the fingers towards
robust grasping. Furthermore, we adopt a learning-based method as the baseline
to benchmark the effectiveness of each design configuration. As a result, we
found that a 3-finger and 4-finger radial configuration is the most effective
one achieving an average 96\% grasp success rate on seen and novel objects
selected from the YCB dataset. We also discussed the influence of the
frictional surface on the finger to improve the grasp robustness.


  We find a new rotating black hole in three-dimensional anti-de Sitter space
using an anisotropic perfect fluid inspired by the noncommutative black hole.
We deduce the thermodynamical quantities of this black hole and compare them
with those of a rotating BTZ solution.


  Grammatical inference consists in learning a formal grammar (as a set of
rewrite rules or a finite state machine). We are concerned with learning
Nondeterministic Finite Automata (NFA) of a given size from samples of positive
and negative words. NFA can naturally be modeled in SAT. The standard model [1]
being enormous, we also try a model based on prefixes [2] which generates
smaller instances. We also propose a new model based on suffixes and a hybrid
model based on prefixes and suffixes. We then focus on optimizing the size of
generated SAT instances issued from the hybrid models. We present two
techniques to optimize this combination, one based on Iterated Local Search
(ILS), the second one based on Genetic Algorithm (GA). Optimizing the
combination significantly reduces the SAT instances and their solving time, but
at the cost of longer generation time. We, therefore, study the balance between
generation time and solving time thanks to some experimental comparisons, and
we analyze our various model improvements.


  Functoinal polymers can be used as electrolyte and binder materials in
solid-state batteries. This often requires performance targets in terms of both
transport and mechanical properties. In this work, a model ionic conductive
polymer system, i.e., poly(ethylene oxide)-LiTFSI, was used to study the impact
of salt concentrations on mechanical properties, including different types of
elastic moduli and the visoelasticity with both non-equilibrium and equilibrium
molecular dynamics simulations. We found an encouragingly good agreement
between experiments and simulations regarding the Young's modulus, bulk modulus
and viscosity. In addition, we identified an intermediate salt concentration at
which the system shows high ionic conductivity, high Young's modulus and short
elastic restoration time. Therefore, this study laid down the groundwork for
investigating ionic conductive polymer binders with self-healing functionality
from molecular dynamics simulations.


  We test the operator form of the Fourier transform of the Argonne V18
potential by computing selected scattering observables and all Wolfenstein
parameters for a variety of energies. These are compared to the GW-DAC database
and to partial wave calculations. We represent the interaction and transition
operators as expansions in a spin-momentum basis. In this representation the
Lippmann-Schwinger equation becomes a six channel integral equation in two
variables. Our calculations use different numbers of spin-momentum basis
elements to represent the on- and off-shell transition operators. This is
because different numbers of independent spin-momentum basis elements are
required to expand the on- and off-shell transition operators. The choice of on
and off-shell spin-momentum basis elements is made so that the coefficients of
the on-shell spin-momentum basis vectors are simply related to the
corresponding off-shell coefficients.


  I explore computer simulations of the dynamics of small multi-fermion lattice
systems. The method is more general, but I concentrate on Hubbard type models
where the fermions hop between a small number of connected sites. I use the
natural mapping of fermion occupation numbers onto computer bits. Signs from
fermion interchange are reduced to bit counting. The technique inherently
requires computer resources growing exponentially with the system volume; so,
it restricted to modestly small systems. Large volume results would require
combining these techniques with further approximations, perhaps in a recursive
renormalization group manner.


  How can we learn a classifier that is "fair" for a protected or sensitive
group, when we do not know if the input to the classifier belongs to the
protected group? How can we train such a classifier when data on the protected
group is difficult to attain? In many settings, finding out the sensitive input
attribute can be prohibitively expensive even during model training, and
sometimes impossible during model serving. For example, in recommender systems,
if we want to predict if a user will click on a given recommendation, we often
do not know many attributes of the user, e.g., race or age, and many attributes
of the content are hard to determine, e.g., the language or topic. Thus, it is
not feasible to use a different classifier calibrated based on knowledge of the
sensitive attribute.
  Here, we use an adversarial training procedure to remove information about
the sensitive attribute from the latent representation learned by a neural
network. In particular, we study how the choice of data for the adversarial
training effects the resulting fairness properties. We find two interesting
results: a small amount of data is needed to train these adversarial models,
and the data distribution empirically drives the adversary's notion of
fairness.


  The representation theory of a 3-dimensional Sklyanin algebra $S$ depends on
its (noncommutative projective algebro-) geometric data: an elliptic curve $E$
in $\mathbb{P}^2$, and an automorphism $\sigma$ of $E$ given by translation by
a point. Indeed, by a result of Artin-Tate-van den Bergh, we have that $S$ is
module-finite over its center if and only if $\sigma$ has finite order. In this
case, all irreducible representations of $S$ are finite-dimensional and of at
most dimension $|\sigma|$.
  In this work, we provide an algorithm in Maple to directly compute all
irreducible representations of $S$ associated to $\sigma$ of order 2, up to
equivalence. Using this algorithm, we compute and list these representations.
To illustrate how the algorithm developed in this paper can be applied to other
algebras, we use it to recover well-known results about irreducible
representations of the skew polynomial ring $\mathbb{C}_{-1}[x,y]$.


  We solve the dilaton field equation in the background of a spherically
symmetric black hole in bosonic or heterotic string theory with
curvature-squared corrections in arbitrary d spacetime dimensions. We then
apply this result to obtain a spherically symmetric black hole solution with
dilatonic charge and curvature-squared corrections in bosonic or heterotic
string theory compactified on a torus. For this black hole we obtain its free
energy, entropy, temperature, specific heat and mass.


  Janus phoretic particles exploit chemical energy stored in their environment
to self-propel. These active particles modify and respond to their hydrodynamic
and chemical environments, thus giving them a sensibility to external flows and
other particles. Furthermore, experimental observations and analysis on
biological or synthetic active suspensions indicate that hydro-chemical
interparticle interactions lead to non-trivial collective behaviour (e.g.,
cluster formation of phoretic particles or bacterial swarming) and that the
response of the suspensions to shear flows is non-trivial. In fact, it can lead
to significant reductions in viscosity due to the energy conversion at
microscopic scales. In this work, using simulations of a continuum kinetic
model, we analyse the dynamics and response to shear and confinement of dilute
suspensions of chemotactic phoretic particles that reorient and drift toward
the chemical solutes released by their neighbours. We show that a 1D transient
steady distribution driven by the effect of confinement is a common feature
considered and analyse its stability for varying confinement strength and shear
rate. In the second step, we consider and discuss, more specifically, the
feedback effect on the flow by the particle and the resulting effective
viscosity of the suspension.


  In this paper, we obtain a classification theorem of $2$-dimensional complete
Lagrangian self-expanders with constant squared norm of the second fundamental
form in $\mathbb C^{2}$.


  We present preliminary results from our analysis of the form factors for the
$\overline{B}\rightarrow D^\ast\ell\overline{\nu}$ decay at non-zero recoil.
Our analysis includes 15 MILC asqtad ensembles with $N_f=2+1$ flavors of sea
quarks and lattice spacings ranging from $a\approx 0.15$ fm down to $0.045$ fm.
The valence light quarks employ the asqtad action, whereas the heavy quarks are
treated using the Fermilab action. We conclude with a discussion of future
plans and phenomenological implications. When combined with experimental
measurements of the decay rate, our calculation will enable a determination of
the CKM matrix element $|V_{cb}|$.


  We present analytical five-loop results for the quark mass and quark field
anomalous dimensions, for a general gauge group and in the MSbar scheme. We
confirm the values known for the gauge group SU(3) from an independent
calculation, and find full agreement with results available from large-Nf
studies.


  Curriculum learning (CL) aims to increase the performance of a learner on a
given task by applying a specialized learning strategy. This strategy focuses
on either the dataset, the task, or the model. There is little to no work
analysing the possibilities to apply CL on the model capacity in natural
language processing. To close this gap, we propose the cup curriculum. In a
first phase of training we use a variation of iterative magnitude pruning to
reduce model capacity. These weights are reintroduced in a second phase,
resulting in the model capacity to show a cup-shaped curve over the training
iterations. We empirically evaluate different strategies of the cup curriculum
and show that it outperforms early stopping reliably while exhibiting a high
resilience to overfitting.


  Let $K\backslash G$ be an irreducible Hermitian symmetric space of noncompact
type and $\Gamma \,\subset\, G$ a closed torsionfree discrete subgroup. Let $X$
be a compact K\"ahler manifold and $\rho\, :\, \pi_1(X, x_0)\,\longrightarrow\,
\Gamma$ a homomorphism such that the adjoint action of $\rho(\pi_1(X, x_0))$ on
$\text{Lie}(G)$ is completely reducible. A theorem of Corlette associates to
$\rho$ a harmonic map $X\, \longrightarrow\, K\backslash G/\Gamma$. We give a
criterion for this harmonic map to be holomorphic. We also give a criterion for
it to be anti--holomorphic.


  The eta-mesic nuclei in which the eta meson is bound with nucleus via strong
interaction was postulated already in 1986, however till now no experiment
confirmed empirically its existence. The discovery of this new kind of an
exotic nuclear matter would be very important for better understanding of the
eta meson structure and its interaction with nucleons. The search for eta-mesic
helium is carried out with high statistic and high acceptance with the
WASA-at-COSY detection setup in the Forschungszentrum Julich. The search is
conducted via the measurement of the excitation function for the chosen decay
channels of the 4He-eta system. Untill now two reactions dd->(4He-eta)bs->3He p
pi- and dd->(4He-eta)bs->3He n pi0 have been measured with the beam momentum
ramped around the eta production threshold. This report includes the
description of experimental method and status of the analysis.


  In this paper, we construct protograph-based spatially coupled low-density
parity-check (SC-LDPC) codes by coupling together a series of L disjoint, or
uncoupled, LDPC code Tanner graphs into a single coupled chain. By varying L,
we obtain a flexible family of code ensembles with varying rates and frame
lengths that can share the same encoding and decoding architecture for
arbitrary L. We demonstrate that the resulting codes combine the best features
of optimized irregular and regular codes in one design: capacity approaching
iterative belief propagation (BP) decoding thresholds and linear growth of
minimum distance with block length. In particular, we show that, for
sufficiently large L, the BP thresholds on both the binary erasure channel
(BEC) and the binary-input additive white Gaussian noise channel (AWGNC)
saturate to a particular value significantly better than the BP decoding
threshold and numerically indistinguishable from the optimal maximum
a-posteriori (MAP) decoding threshold of the uncoupled LDPC code. When all
variable nodes in the coupled chain have degree greater than two,
asymptotically the error probability converges at least doubly exponentially
with decoding iterations and we obtain sequences of asymptotically good LDPC
codes with fast convergence rates and BP thresholds close to the Shannon limit.
Further, the gap to capacity decreases as the density of the graph increases,
opening up a new way to construct capacity achieving codes on memoryless
binary-input symmetric-output (MBS) channels with low-complexity BP decoding.


  The topological non-triviality of insulating phases of matter is by now well
understood through topological K-theory where the indices of the Dirac
operators are assembled into topological classes. We consider in the context of
the Kitaev chain a notion of a generalized Dirac operator where the associated
Clifford algebra is centrally extended. We demonstrate that the central
extension is achieved via taking rational operator powers of Pauli matrices
that appear in the corresponding BdG Hamiltonian. Doing so introduces a
pseudo-metallic component to the topological phase diagram within which the
winding number is valued in $\mathbb Q$. We find that this phase hosts a mode
that remains extended in the presence of weak disorder, motivating a
topological interpretation of a non-integral winding number. We remark that
this is in correspondence with Ref.[J. Differential Geom. 74(2):265-292]
demonstrating that projective Dirac operators defined in the absence of
spin$^\mathbb C$ structure have rational indices.


  This paper examines the question whether information is contained in
forecasts from DSGE models beyond that contained in lagged values, which are
extensively used in the models. Four sets of forecasts are examined. The
results are encouraging for DSGE forecasts of real GDP. The results suggest
that there is information in the DSGE forecasts not contained in forecasts
based only on lagged values and that there is no information in the
lagged-value forecasts not contained in the DSGE forecasts. The opposite is
true for forecasts of the GDP deflator.
  Keywords: DSGE forecasts, Lagged values
  JEL Classification Codes: E10, E17, C53


  We study the anomalous $W^+W^-V$ ($V=\gamma,Z$) couplings in $e^+e^-\to
W^+W^-$ using the complete set of polarization observables of $W$ boson with
longitudinally polarized beams. We use most general Lorentz invariant form
factors parametrization as well as $SU(2)\times U(1)$ invariant dimension $6$
effective operators for the effective $W^+W^-V$ couplings. We estimate
simultaneous limits on the anomalous couplings in both the parametrizations
using cross section, forward backward asymmetry and polarization observables of
$W$ boson with different kinematical cuts using Markov-Chain--Monte-Carlo
(MCMC) method for an $e^+e^-$ collider running at centre of mass energy of
$\sqrt{s}=500$ GeV and ${\cal L}=100$ fb$^{-1}$. The best limits on form
factors are obtained to be $1 \sim 5 \times 10^{-2}$ for $e^-$ and $e^+$
polarization being $(+0.4,-0.4)$. For operator's coefficients, the best limits
are obtained to be $1\sim 16$ TeV$^{-2}$.


  Signature of phase coherence on the electric and magnetic response of non
connected Aharonov-Bohm rings is measured by a resonant method at 350 MHz
between 20 mK and 500 mK. The rings are etched in a GaAs-AlGaAs heterojunction.
Both quantities exhibit a oscillating behaviour with a periodicity consistent
with half a flux quantum $\Phi_0/2=h/2e$ in a ring. Electric screening is shown
to be enhanced when time reversal symmetry is broken by magnetic field, leading
to a positive magnetopolarisability, in agreement with theoretical predictions
for isolated rings at finite frequency. Temperature and electronic density
dependence are investigated. The dissipative part of the electric response, the
electric absorption, is also measured and leads to a negative
magnetoconductance. The magnetic orbital response of the very same rings is
also investigated. It is consistent with diamagnetic persistent currents of
0.25 nA. This magnetic response is an order of magnitude smaller than the
electric one, in qualitative agreement with theoretical expectations.


  In the Hurwitz space of rational functions on CP^1 with poles of given
orders, we study the loci of multisingularities, that is, the loci of functions
with a given ramification profile over 0. We prove a recursion relation on the
Poincare dual cohomology classes of these loci and deduce a differential
equation on Hurwitz numbers.


  The concept of uniform convexity of a Banach space was generalized to linear
operators between Banach spaces and studied by Beauzamy [1976]. Under this
generalization, a Banach space X is uniformly convex if and only if its
identity map I_X is. Pisier showed that uniformly convex Banach spaces have
martingale type p for some p>1. We show that this fact is in general not true
for linear operators. To remedy the situation, we introduce the new concept of
martingale subtype and show, that it is equivalent, also in the operator case,
to the existence of an equivalent uniformly convex norm on X. In the case of
identity maps it is also equivalent to having martingale type p for some p>1.
  Our main method is to use sequences of ideal norms defined on the class of
all linear operators and to study the factorization of the finite summation
operators. There is a certain analogy with the theory of Rademacher type.


  The photon induced reactions which are named as photonuclear reactions have a
great importance in many field of nuclear, radiation physics and related
fields. Since we have planned to perform photonuclear reaction on gallium
target with bremmstrahlung photons from clinical linear accelerator in the
future, the cross-sections of neutron (photo-neutron ({\gamma},xn)) and proton
(photo-proton ({\gamma},xn)) productions after photon activation have been
calculated by using TALYS 1.2 computer code in this study. The target nucleus
has been considered gallium which has two stable isotopes, 69Ga and 71Ga.
According to the results, we have seen that the calculations are in harmony in
the limited literature values. Furthermore, the pre-equilibrium and compound
process contributions to the total cross-section have been investigated.


  Consider a monopolist selling $n$ items to an additive buyer whose item
values are drawn from independent distributions $F_1,F_2,\ldots,F_n$ possibly
having unbounded support. Unlike in the single-item case, it is well known that
the revenue-optimal selling mechanism (a pricing scheme) may be complex,
sometimes requiring a continuum of menu entries. Also known is that simple
mechanisms with a bounded number of menu entries can extract a constant
fraction of the optimal revenue. Nonetheless, whether an arbitrarily high
fraction of the optimal revenue can be extracted via a bounded menu size
remained open.
  We give an affirmative answer: for every $n$ and $\varepsilon>0$, there
exists $C=C(n,\varepsilon)$ s.t. mechanisms of menu size at most $C$ suffice
for obtaining $(1-\varepsilon)$ of the optimal revenue from any
$F_1,\ldots,F_n$. We prove upper and lower bounds on the revenue-approximation
complexity $C(n,\varepsilon)$ and on the deterministic communication complexity
required to run a mechanism achieving such an approximation.


  We describe a method for computing the highest degree coefficients of a
weighted Ehrhart quasi-polynomial for a rational simple polytope.


  We study the choice of the regularisation parameter for linear ill-posed
problems in the presence of data noise and operator perturbations, for which a
bound on the operator error is known but the data noise-level is unknown. We
introduce a new family of semi-heuristic parameter choice rules that can be
used in the stated scenario. We prove convergence of the new rules and provide
numerical experiments that indicate an improvement compared to standard
heuristic rules.


  We have combined observations of the Antennae galaxies from the radio
interferometer ALMA (Atacama Large Millimeter/submillimeter Array) and from the
optical interferometer GH$\alpha$FaS (Galaxy H$\alpha$ Fabry-Perot System). The
two sets of observations have comparable angular and spectral resolutions,
enabling us to identify 142 giant molecular clouds (GMCs) and 303 HII regions.
We have measured, and compared, their basic physical properties (radius,
velocity dispersion, luminosity). For the HII regions, we find two physical
regimes, one for masses $>10^{5.4} \mathrm{M_{\odot}}$ of ionized gas, where
the gas density increases with gas mass, the other for masses $<10^{5.4}
\mathrm{M_{\odot}}$ of ionized gas, where the gas density decreases with gas
mass. For the GMCs, we find, in contrast to previous studies in other galaxies
over a generally lower mass range of clouds, that the gas surface density
increases with the radius, hinting at two regimes for these clouds if we
consider both sources of data. We also find that the GMC mass function has a
break at $10^{6.7}\mathrm{M_{\odot}}$. Using the velocity dispersion
measurements, we claim that the difference between the regimes is the nature of
the dominant binding force. For the regions in the lower mass range, the
dominant force is the external pressure, while in the higher mass range it is
the internal gravity of the clouds. In the regime where gravity is dominant,
the star formation rate, derived from the dust-corrected H$\alpha$ luminosity,
increases super-linearly with the velocity dispersion, and the gas density
increases with the gas mass.


  In a multi-input multi-output (MIMO) setup, where one side of the link
comprises a linear antenna array, data can be transmitted over the direction of
incident rays. Channel capacity for this setup is studied in this paper. We
define two different setups; one when the energy is constant and equal over all
rays, and one when available energy is evenly distributed over rays. For the
latter, we show that there is an upper bound for channel capacity, regardless
of the number of rays and antennas. Also, we have compared this setup with the
legacy single-input single-output (SISO) AWGN channel.


  The time development of equal-time correlation functions in quantum mechanics
and quantum field theory is described by an exact evolution equation for
generating functionals. This permits a comparison between classical and quantum
evolution in non-equilibrium systems.


  Quantum billiards provide an excellent forum for the analysis of quantum
chaos. Toward this end, we consider quantum billiards with time-varying
surfaces, which provide an important example of quantum chaos that does not
require the semiclassical ($\hbar \longrightarrow 0$) or high quantum-number
limits. We analyze vibrating quantum billiards using the framework of
Riemannian geometry. First, we derive a theorem detailing necessary conditions
for the existence of chaos in vibrating quantum billiards on Riemannian
manifolds. Numerical observations suggest that these conditions are also
sufficient. We prove the aforementioned theorem in full generality for one
degree-of-freedom boundary vibrations and briefly discuss a generalization to
billiards with two or more degrees-of-vibrations. The requisite conditions are
direct consequences of the separability of the Helmholtz equation in a given
orthogonal coordinate frame, and they arise from orthogonality relations
satisfied by solutions of the Helmholtz equation. We then state and prove a
second theorem that provides a general form for the coupled ordinary
differential equations that describe quantum billiards with one
degree-of-vibration boundaries. This set of equations may be used to illustrate
KAM theory and also provides a simple example of semiquantum chaos. Moreover,
vibrating quantum billiards may be used as models for quantum-well
nanostructures, so this study has both theoretical and practical applications.


  Using density functional calculations, we investigate the structural and
magnetic properties of ultrathin Gd and Gd-carbide nanowires (NWs) encapsulated
in narrow carbon nanotubes (CNTs). The equilibrium geometry of an encapsulated
(2 \times 2) Gd-NW is markedly different from that of bulk Gd crystals. The
charge-density analysis shows pronounced spin-dependent electron transfer in
the encapsulated Gd-NW in comparison with that of Gd-carbide NWs. We conclude
that Gd-CNT hybridization is primarily responsible for both the structural
difference and electron transfer in the encapsulated Gd-NW.


  In the present paper we prove, that if the geodesic flow of a metric G on the
torus T is quadratically integrable, then the torus T isometrically covers a
torus with a Liouville metric on it, and describe the set of quadratically
integrable geodesic flows on the Klein bottle.


  We investigate the usage of highly efficient error correcting codes of
multilevel systems to protect encoded quantum information from erasure errors
and implementation to repetitively correct these errors. Our scheme makes use
of quantum polynomial codes to encode quantum information and generalizes
teleportation based error correction for multilevel systems to correct photon
losses and operation errors in a fault-tolerant manner. We discuss the
application of quantum polynomial codes to one-way quantum repeaters. For
various types of operation errors, we identify different parameter regions
where quantum polynomial codes can achieve a superior performance compared to
qubit based quantum parity codes.


  A typical form of mass formula is re-explained in terms of nuclear structure.
  For $ N \approx Z $ nuclei, we propose to start with the shell model picture
and to consider the T=0 $2n-2p$ ($\alpha$-like) correlations as the fundamental
concept, instead of the symmetry energy.
  Subsequently, the symmetry energy is described on the basis of the
$\alpha$-like superfluidity caused by the T=0 $2n-2p$ correlations, in parallel
with the pairing energy described on the basis of the pairing superfluidity.
This re-explanation gives useful insight for understanding the nuclear mass
formula. The origin of the Wigner energy is also explained in an interacting
boson model for the Cooper pairs in the $\alpha$-like superfluid vacuum. Adding
a correction term due to the T=0 $2n-2p$ correlations, which determines the T=0
base level for nuclear masses, can improve the mass formulas in practice.


  We compile X-ray data of clusters of galaxies at a wide range of redshift
$z=0.0\sim1.0$ and compare X-ray luminosities, gas masses, iron abundances and
iron masses of nearby clusters and those of distant clusters as a function of
plasma temperature. All the date presented in this paper have been obtained
only with \ASCA and/or \ROSAT. No evidence for a change in the \KT -\LX\
relationship or \KT - iron abundance at $z<0.6$ is found. No significant change
in \KT -\LX relationship at $z>0.6$ is seen, either. However, the gas masses of
very distant clusters at $z\sim0.8-1.0$ and some clusters around $z\sim0.6$ are
significantly lower than those of nearby clusters, which indicates a hint of
evolution. The iron masses of the two very distant clusters at $z\sim0.8-1.0$
are significantly different from each other, which suggests that the epoch of
the metal injection into ICM is different from cluster to cluster.


  We present the results of wide-band (720-2400 MHz) study of PSR B1821-24A
(J1824-2452A, M28A), an energetic millisecond pulsar visible in radio, X-rays
and gamma-rays. In radio, the pulsar has a complex average profile which spans
>85% of the spin period and exhibits strong evolution with observing frequency.
For the first time we measure phase-resolved polarization properties and
spectral indices of radio emission throughout almost all of the on-pulse
window. We combine this knowledge with the high-energy information to compare
M28A to other known gamma-ray millisecond pulsars and to speculate that M28A's
radio emission originates in multiple regions within its magnetosphere (i.e.
both in the slot or outer gaps near the light cylinder and at lower altitudes
above the polar cap). M28A is one of the handful of pulsars which are known to
emit Giant Pulses (GPs) -- short, bright radio pulses of unknown nature. We
report a drop in the linear polarization of the average profile in both windows
of GP generation and also a `W'-shaped absorption feature (resembling a double
notch), partly overlapping with one of the GP windows. The GPs themselves have
broadband spectra consisting of multiple patches with fractional spectral width
($\Delta\nu/\nu$) of about 0.07. Although our time resolution was not
sufficient to resolve the GP structure on the microsecond scale, we argue that
GPs from this pulsar most closely resemble the GPs from the main pulse of the
Crab pulsar, which consist of a series of narrowband nanoshots.


  Suspended resonant optical cavities are basic building blocks for several
experimental devices. An important issue is the control strategy required to
bring them in the resonant or slightly detuned configuration needed for their
operation, the so-called \textit{ locking} procedure. This can be obtained with
a feedback strategy, but the error signal needed is tipically available only
when the cavity is near the resonance with a precision of the order $\Delta
L\simeq\lambda_{\ell}{\cal F}^{-1}$, where ${\cal F}$ is the cavity finesse and
$\lambda_{\ell}$ is the laser's wavelength. When the mirrors are freely
swinging the locking can be attempted only in the short time windows when this
condition is verifyed. Tipically this means that the procedure must be repeated
several times, and that large forces must be applied. In this paper we describe
a different strategy, which tries to take advantage by the fact that the
dynamics of the mirrors is known at least in an approximate way. We argue that
the locking procedure considered can be more efficient compared with the naive
one, with a reduced needed maximal feedback. Finally we discuss possible
generalizations and we point to future investigations.