  Several experimental techniques have been introduced in recent years in
attempts to measure spin transfer torque in magnetic tunnel junctions (MTJs).
The dependence of spin torque on bias is important for understanding
fundamental spin physics in magnetic devices and for applications. However,
previous techniques have provided only indirect measures of the torque and
their results to date for the bias dependence are qualitatively and
quantitatively inconsistent. Here we demonstrate that spin torque in MTJs can
be measured directly by using time-domain techniques to detect resonant
magnetic precession in response to an oscillating spin torque. The technique is
accurate in the high-bias regime relevant for applications, and because it
detects directly small-angle linear-response magnetic dynamics caused by spin
torque it is relatively immune to artifacts affecting competing techniques. At
high bias we find that the spin torque vector differs markedly from the simple
lowest-order Taylor series approximations commonly assumed.


  While traditionally a labour intensive task, the testing of game content is
progressively becoming more automated. Among the many directions in which this
automation is taking shape, automatic play-testing is one of the most promising
thanks also to advancements of many supervised and reinforcement learning (RL)
algorithms. However these type of algorithms, while extremely powerful, often
suffer in production environments due to issues with reliability and
transparency in their training and usage.
  In this research work we are investigating and evaluating strategies to apply
the popular RL method Proximal Policy Optimization (PPO) in a casual mobile
puzzle game with a specific focus on improving its reliability in training and
generalization during game playing.
  We have implemented and tested a number of different strategies against a
real-world mobile puzzle game (Lily's Garden from Tactile Games). We isolated
the conditions that lead to a failure in either training or generalization
during testing and we identified a few strategies to ensure a more stable
behaviour of the algorithm in this game genre.


  The interaction potential V(Q^2) between static test charges can be used to
define an effective charge $\alpha_V(Q^2)$ and a physically-based
renormalization scheme for quantum chromodynamics and other gauge theories. In
this paper we use recent results for the finite-mass fermionic corrections to
the heavy-quark potential at two-loops to derive the next-to-leading order term
for the Gell Mann-Low function of the V-scheme. The resulting effective number
of flavors $N_F(Q^2/m^2)$ in the $\alpha_V$ scheme is determined as a
gauge-independent and analytic function of the ratio of the momentum transfer
to the quark pole mass. The results give automatic decoupling of heavy quarks
and are independent of the renormalization procedure. Commensurate scale
relations then provide the next-to-leading order connection between all
perturbatively calculable observables to the analytic and gauge-invariant
$\alpha_V$ scheme without any scale ambiguity and a well defined number of
active flavors. The inclusion of the finite quark mass effects in the running
of the coupling is compared with the standard treatment of finite quark mass
effects in the $\bar{MS}$ scheme.


  In this study, the proton is taken as an ensemble of quark-gluon Fock states.
Using the principle of detailed balance, the probabilities of finding every
Fock states of the proton are obtained without any parameter. A new origin of
the light flavor sea quark asymmetry, i.e., $\bar{u} \not= \bar{d}$, is given
as a pure statistical effect. It is found that $\bar{d}-\bar{u} \approx 0.124$,
which is in surprisingly agreement with the experimental observation.


  For ordinary flops, the correspondence defined by the graph closure is shown
to give equivalence of Chow motives and to preserve the Poincar\'e pairing. In
the case of simple ordinary flops, this correspondence preserves the big
quantum cohomology ring after an analytic continuation over the extended
K\"ahler moduli space.
  For Mukai flops, it is shown that the birational map for the local models is
deformation equivalent to isomorphisms. This implies that the birational map
induces isomorphisms on the full quantum rings and all the quantum corrections
attached to the extremal ray vanish.


  We report the first identification of the optical bands of the B-X system of
AlO in the red supergiant VY CMa. In addition to TiO, VO, ScO, and YO, which
were recognized in the optical spectrum of the star long time ago, AlO is
another refractory molecule which displays strong emission bands in this
peculiar star. Simulating the bands of AlO, we derive a rotational temperature
of the circumstellar gas of Trot=700K. By resolving individual rotational
components of the bands, we derive the kinematical characteristics of the gas,
finding that the emission is centered at the stellar radial velocity and its
intrinsic width is 13.5 km/s (full width at half maximum). It is the narrowest
emission among all (thermal) features observed in VY CMa so far. The
temperature and line widths suggest that the emission arises in gas located
within ~20 stellar radii, where the outflow is still being accelerated. This
result contradicts equilibrium-chemistry models which predict substantial AlO
abundances only to within a few stellar radii. We argue that non-equilibrium
models involving propagation of shocks are needed to explain the observations.


  The probe and singular sources methods are two well-known classical direct
reconstruction methods in inverse obstacle problems governed by partial
differential equations. In this paper, by considering an inverse obstacle
problem governed by the Laplace equation in a bounded domain as a prototype
case, an integrated theory of the probe and singular sources methods is
proposed. The theory consists of three parts: (i) introducing the singular
sources method combined with the notion of the probe method; (ii) finding a
third indicator function whose two ways decomposition yields the indicator
functions in the probe and singular sources methods; (iii) finding the
completely integrated version of the probe and singular sources methods.


  While every group is isomorphic to a transitive group of permutations, the
analogous property fails for inverse semigroups: not all inverse semigroups are
isomorphic to transitive inverse semigroups of one-to-one partial
transformations of a set. We describe those inverse semigroups that are.


  We carry out density functional theory calculation to enhance the Rashba spin
splitting (RSS) of BiTeI by modifying the interlayer interaction. It is shown
that RSS increases as the Te layer approaches to adjacent Bi layer or the I
layer recedes from the Bi layer. Our results indicate that the RSS can be
sensitively increased by introducing a vacancy on the Te site to make effective
Bi-Te distance shorter. It is also found that the difference of Te p orbital
character between two spin-split bands increases when the RSS is developed
along crystal momentum, which supports asymmetric interlayer interaction in the
spin-split bands. Our work suggests that the modification of interlayer
interaction is an effective approach in the modeling of the RSS in BiTeI and
other layered materials.


  Time series data are ubiquitous in real-world applications. However, one of
the most common problems is that the time series data could have missing values
by the inherent nature of the data collection process. So imputing missing
values from multivariate (correlated) time series data is imperative to improve
a prediction performance while making an accurate data-driven decision.
Conventional works for imputation simply delete missing values or fill them
based on mean/zero. Although recent works based on deep neural networks have
shown remarkable results, they still have a limitation to capture the complex
generation process of the multivariate time series. In this paper, we propose a
novel imputation method for multivariate time series data, called STING
(Self-attention based Time-series Imputation Networks using GAN). We take
advantage of generative adversarial networks and bidirectional recurrent neural
networks to learn latent representations of the time series. In addition, we
introduce a novel attention mechanism to capture the weighted correlations of
the whole sequence and avoid potential bias brought by unrelated ones.
Experimental results on three real-world datasets demonstrate that STING
outperforms the existing state-of-the-art methods in terms of imputation
accuracy as well as downstream tasks with the imputed values therein.


  In this paper, we are concerned with the global existence and scattering of
small data smooth solutions to a class of quasilinear wave systems on the
product space $\mathbb{R}^2\times\mathbb{T}$. These quasilinear wave systems
include 3D irrotational potential flow equation of Chaplygin gases, 3D
relativistic membrane equation, some 3D quasilinear wave equations which come
from the corresponding Lagrangian functionals as perturbations of the
Lagrangian densities of linear waves, and nonlinear wave maps system. Through
looking for some suitable transformations of unknown functions, the nonlinear
wave system can be reduced into a more tractable form. Subsequently, by
applying the vector-field method together with the ghost weight technique as
well as deriving some kinds of weighted $L^\infty-L^\infty$ and $L^\infty-L^2$
estimates of solution $w$ to the 2D linear wave equation $\Box w=f(t,x)$, the
global existence and scattering of small data solutions are established.


  We compute the memory effect produced at the black hole horizon by a
transient gravitational shockwave. As shown by Hawking, Perry, and Strominger
(HPS) such a gravitational wave produces a deformation of the black hole
geometry which from future null infinity is seen as a Bondi-Metzner-Sachs (BMS)
supertranslation. This results in a diffeomorphic but physically distinct
geometry which differs from the original black hole by their charges at
infinity. Here we give the complementary description of this physical process
in the near-horizon region as seen by an observer hovering just outside the
event horizon. From this perspective, in addition to a supertranslation the
shockwave also induces a horizon superrotation. We compute the associated
superrotation charge and show that its form agrees with the one obtained by HPS
at infinity. In addition, there is a supertranslation contribution to the
horizon charge, which measures the entropy change in the process. We then turn
to electrically and magnetically charged black holes and generalize the
near-horizon asymptotic symmetry analysis to Einstein-Maxwell theory. This
reveals an additional infinite-dimensional current algebra that acts
non-trivially on the horizon superrotations. Finally, we generalize the black
hole memory effect to Reissner-Nordstr\"{o}m black holes.


  With the blasting increase of wireless data traffic, incumbent wireless
service providers (WSPs) face critical challenges in provisioning spectrum
resource. Given the permission of unlicensed access to TV white spaces, WSPs
can alleviate their burden by exploiting the concept of "capacity offload" to
transfer part of their traffic load to unlicensed spectrum. For such use cases,
a central problem is for WSPs to coexist with others, since all of them may
access the unlicensed spectrum without coordination thus interfering each
other. Game theory provides tools for predicting the behavior of WSPs, and we
formulate the coexistence problem under the framework of non-cooperative games
as a capacity offload game (COG). We show that a COG always possesses at least
one pure-strategy Nash equilibrium (NE), and does not have any mixed-strategy
NE. The analysis provides a full characterization of the structure of the NEs
in two-player COGs. When the game is played repeatedly and each WSP
individually updates its strategy based on its best-response function, the
resulting process forms a best-response dynamic. We establish that, for
two-player COGs, alternating-move best-response dynamics always converge to an
NE, while simultaneous-move best-response dynamics does not always converge to
an NE when multiple NEs exist. When there are more than two players in a COG,
if the network configuration satisfies certain conditions so that the resulting
best-response dynamics become linear, both simultaneous-move and
alternating-move best-response dynamics are guaranteed to converge to the
unique NE.


  A recent proposal by Shuler regarding a postulate-based derivation of a
family of metrics describing the gravitational field outside a static
spherically symmetric mass distribution is reviewed. All of Shuler's gravities
agree with the Schwarzschild solution in the weak-field limit, but they differ
in the strong-field domain, i.e., close enough to a sufficiently compact source
of the field. It is found that the evoked postulates of i) momentum
conservation and ii) consistency of field strength measurement are satisfied in
all metric theories of gravity compatible with the Einstein equivalence
principle, no matter what the form of the metric. Therefore, they cannot be
used, within any correct deduction, to derive a particular metric. Shuler's
derivations are based on an inconsistent set of correspondences between local
and distant quantities. Furthermore, it is shown here that out of the family of
possible metrics given by Shuler only one member, the Schwarzschild metric,
satisfies a standard relativistic generalization of Newton's law of
gravitation, suggesting the others to be unphysical.


  A monopolist wishes to maximize her profits by finding an optimal price
policy. After she announces a menu of products and prices, each agent $x$ will
choose to buy that product $y(x)$ which maximizes his own utility, if positive.
The principal's profits are the sum of the net earnings produced by each
product sold. These are determined by the costs of production and the
distribution of products sold, which in turn are based on the distribution of
anonymous agents and the choices they make in response to the principal's price
menu. In this paper, we provide a necessary and sufficient condition for the
convexity or concavity of the principal's (bilevel) optimization problem,
assuming each agent's disutility is a strictly increasing but not necessarily
affine (i.e. quasilinear) function of the price paid. Concavity when present,
makes the problem more amenable to computational and theoretical analysis; it
is key to obtaining uniqueness and stability results for the principal's
strategy in particular. Even in the quasilinear case, our analysis goes beyond
previous work by addressing convexity as well as concavity, by establishing
conditions which are not only sufficient but necessary, and by requiring fewer
hypotheses on the agents' preferences.


  A first measurement of the average polarisation P_tau of tau leptons produced
in e+e- annihilation at energies significantly above the Z resonance is
presented. The polarisation is determined from the kinematic spectra of tau
hadronic decays. The measured value P_tau = -0.164 +/- 0.125 is consistent with
the Standard Model prediction for the mean LEP energy of 197 GeV.


  We study the sensitivity of the processes `e+ e- -> lepton (l) neutrino (v)
quark (u) antiquark (d)' at LEP2 energies on the non-standard trilinear gauge
couplings (TGC), using the optimal observables method. All relevant leading
logarithmic corrections to the tree-order cross section, as well as
experimental resolution effects have been studied. Taking into account
correlations among the different TGC parameters we show that the limits on the
TGC can reach the level of 0.15~(1sd) at 161 GeV with 100 pb$^{-1}$, a
challenge for the first LEP2 phase. At higher energies this can be improved
drastically, reaching the level of 0.02~(1sd).


  A novel computational model (CoDD) utilizing combinatory logic to create
higher-order decision trees is presented. A theoretical analysis of general
intelligence in terms of the formal theory of pattern recognition and pattern
formation is outlined, and shown to take especially natural form in the case
where patterns are expressed in CoDD language. Relationships between logical
entropy and algorithmic information, and Shannon entropy and runtime
complexity, are shown to be elucidated by this approach. Extension to the
quantum computing case is also briefly discussed.


  Let f be a transcendental entire function that omits a complex value a. We
show that for every simply connected region D that does not contain a the full
preimage of D is disconnected. We conjecture that the same holds if one only
assumes that a is omitted locally. We were able to prove this conjecture under
the additional assumption that f is of finite order. We include some auxilliary
results on the singularities of the inverses of entire functions which are of
independent interest.


  We have used measurements by the Fermi Large Area Telescope (LAT) to study
the interstellar gamma-ray emission in a region of the second Galactic
quadrant, at 100 deg < l < 145 deg and -15 deg < b < 30 deg. This region
encompasses the prominent Gould-Belt clouds of Cassiopeia, Cepheus, and the
Polaris flare, as well as large atomic and molecular complexes at larger
distances in several spiral arms. The good kinematic separation in velocity
between the local, Perseus, and outer arms, and the presence of massive
complexes in each, make this region very well suited to probe the gamma-ray
emission from the interstellar medium beyond the solar circle. The
unprecedented sensitivity and angular resolution of the LAT provide improved
constraints on the gradient of the cosmic-ray densities and on the increase of
the CO-to-H2 conversion factor, Xco, in the outer Galaxy.


  In this paper we study the diameter of the random graph $G(n,p)$, i.e., the
the largest finite distance between two vertices, for a wide range of functions
$p=p(n)$. For $p=\la/n$ with $\la>1$ constant, we give a simple proof of an
essentially best possible result, with an $O_p(1)$ additive correction term.
Using similar techniques, we establish 2-point concentration in the case that
$np\to\infty$. For $p=(1+\epsilon)/n$ with $\epsilon\to 0$, we obtain a
corresponding result that applies all the way down to the scaling window of the
phase transition, with an $O_p(1/\epsilon)$ additive correction term whose
(appropriately scaled) limiting distribution we describe. Combined with earlier
results, our new results complete the determination of the diameter of the
random graph $G(n,p)$ to an accuracy of the order of its standard deviation (or
better), for all functions $p=p(n)$. Throughout we use branching process
methods, rather than the more common approach of separate analysis of the
2-core and the trees attached to it.


  In this paper we study a family of operators dependent on a small parameter
$\epsilon > 0$, which arise in a problem in fluid mechanics. We show that the
spectra of these operators converge to N as $\epsilon \to 0$, even though, for
fixed $\epsilon > 0$, the eigenvalue asymptotics are quadratic.


  What is the action sequence aa'a" that was likely responsible for reaching
state s"' (from state s) in 3 steps? Addressing such questions is important in
causal reasoning and in reinforcement learning. Inverse "MDP" models
p(aa'a"|ss"') can be used to answer them. In the traditional "forward" view,
transition "matrix" p(s'|sa) and policy {\pi}(a|s) uniquely determine
"everything": the whole dynamics p(as'a's"a"...|s), and with it, the
action-conditional state process p(s's"...|saa'a"), the multi-step inverse
models p(aa'a"...|ss^i), etc. If the latter is our primary concern, a natural
question, analogous to the forward case is to which extent 1-step inverse model
p(a|ss') plus policy {\pi}(a|s) determine the multi-step inverse models or even
the whole dynamics. In other words, can forward models be inferred from inverse
models or even be side-stepped. This work addresses this question and
variations thereof, and also whether there are efficient decision/inference
algorithms for this.


  We present new time dependent solutions for the dynamics of tubular
D2-branes. We comment on the connection to cosmic string dynamics and
explicitly give a few simple examples of oscillating and rotating brane
configurations.


  We present a calibration of the acquisition data obtained by the Red Peak-Up
(PU) sub-array on the Infrared Spectrograph on Spitzer, based on repeated
observations of three K giants. This calibration is tied directly to the most
current infrared calibration based on data from Multiband Imaging Photometer
for Spitzer. An analysis of the responsivity of the Red PU sub-array reveals no
detectable deviations from linearity in the most recent pipeline version, but
older pipeline versions show evidence suggesting possible small
non-linearities.


  Although the Theta has been listed as a three star resonance in the 2004
PDG,its existence is still not completely established. Now it is still of
interest to see what QCD has to say on the subject, In this paper we review
briefly the pentaquark Theta properties.


  We present a special science case for an intermediate resolution multi-object
IR spectrograph for the VLT. We have constructed new models for massive
Population III stars and metal-free stellar populations (see Schaerer 2001).
The properties of individual stars and integrated populations, including their
ionising fluxes and SEDs are discussed. We also study their dependence on the
poorly known IMF and the star formation history. The synthetic spectra are used
to simulate spectroscopic observations of the expected emission lines of Pop
III galaxies. We show that such an instrument should allow the detection and
efficient observations of the first galaxies with the VLT.


  Background: We study the statistical properties of fragment coverage in
genome sequencing experiments. In an extension of the classic Lander-Waterman
model, we consider the effect of the length distribution of fragments. We also
introduce the notion of the shape of a coverage function, which can be used to
detect abberations in coverage. The probability theory underlying these
problems is essential for constructing models of current high-throughput
sequencing experiments, where both sample preparation protocols and sequencing
technology particulars can affect fragment length distributions.
  Results: We show that regardless of fragment length distribution and under
the mild assumption that fragment start sites are Poisson distributed, the
fragments produced in a sequencing experiment can be viewed as resulting from a
two-dimensional spatial Poisson process. We then study the jump skeleton of the
the coverage function, and show that the induced trees are Galton-Watson trees
whose parameters can be computed.
  Conclusions: Our results extend standard analyses of shotgun sequencing that
focus on coverage statistics at individual sites, and provide a null model for
detecting deviations from random coverage in high-throughput sequence census
based experiments. By focusing on fragments, we are also led to a new approach
for visualizing sequencing data that should be of independent interest.


  We perform high-resolution N-Body+SPH simulations of gas-rich dwarf galaxy
satellites orbiting within a Milky Way-sized halo and study for the first time
the combined effects of tides and ram pressure. The structure of the galaxy
models and the orbital configurations are chosen in accordance to those
expected in a LCDM Universe.While tidal stirring of disky dwarfs produces
objects whose stellar structure and kinematics resembles that of dwarf
spheroidals after a few orbits, ram pressure stripping is needed to entirely
remove their gas component. Gravitational tides can aid ram pressure stripping
by diminishing the overall potential of the dwarf, but tides also induce bar
formation which funnels gas inwards making subsequent stripping more difficult.
This inflow is particularly effective when the gas can cool radiatively.
Assuming a low density of the hot Galactic corona consistent with observational
constraints, dwarfs with V_{peak} < 30 km/s can be completely stripped of their
gas content on orbits with pericenters of 50 kpc or less. Instead, dwarfs with
more massive dark haloes and V_{peak} > 30 km/s lose most or all of their gas
content only if a heating source keeps the gas extended, partially
counteracting the bar-driven inflow. We show that the ionizing radiation from
the cosmic UV background at z > 2 can provide the required heating. In these
objects most of the gas is removed or becomes ionized at the first pericenter
passage,explaining the early truncation of the star formation observed in Draco
and Ursa Minor. The stripped gas breaks up into individual clouds pressure
confined by the outer gaseous medium that have masses, sizes and densities
comparable to the HI clouds recently discovered around M31.(abridged)


  Urban planning, which aims to design feasible land-use configurations for
target areas, has become increasingly essential due to the high-speed
urbanization process in the modern era. However, the traditional urban planning
conducted by human designers can be a complex and onerous task. Thanks to the
advancement of deep learning algorithms, researchers have started to develop
automated planning techniques. While these models have exhibited promising
results, they still grapple with a couple of unresolved limitations: 1)
Ignoring the relationship between urban functional zones and configurations and
failing to capture the relationship among different functional zones. 2) Less
interpretable and stable generation process. To overcome these limitations, we
propose a novel generative framework based on normalizing flows, namely
Dual-stage Urban Flows (DSUF) framework. Specifically, the first stage is to
utilize zone-level urban planning flows to generate urban functional zones
based on given surrounding contexts and human guidance. Then we employ an
Information Fusion Module to capture the relationship among functional zones
and fuse the information of different aspects. The second stage is to use
configuration-level urban planning flows to obtain land-use configurations
derived from fused information. We design several experiments to indicate that
our framework can outperform compared to other generative models for the urban
planning task.


  The Hungaria asteroid group is located interior to the main asteroid belt,
with semimajor axes between 1.8 and 2 AU, low eccentricities and inclinations
of 16-35 degrees. Recently, it has been proposed that Hungaria asteroids are a
secularly declining population that may be related to the Late Heavy
Bombardment (LHB) impactors (\'Cuk et al. 2012, Bottke et al. 2012). While
\'Cuk et al. (2012) and Bottke et al. (2012) have reproduced a Hungaria-like
population that declined exponentially, the real Hungarias were never confirmed
to be unstable to the same degree. Here we find that the stability of Hungarias
is strongly dependent on the evolution of the eccentricity of Mars, which is
chaotic and unpredictable on Gyr timescales. We find that the high Martian
eccentricity chiefly affects Hungarias through close approaches with Mars,
rather than planetary secular modes. However, current minimum perihelia of
Hungarias (over Myr timescales) are not diagnostic of their long-term stability
due to a number of secular and mean motion resonances affecting the Hungaria
region (Milani et al. 2010). We conclude that planetary chaos makes it
impossible to determine the effective lifetimes of observed Hungarias.
Furthermore, long-term changes of Martian eccentricity could lead to variable
Hungaria loss over time. We speculate that some of the most stable Hungarias
may have been placed in their present orbit when the eccentricity of Mars was
significantly higher than today.


  In this paper, we study the upper bounds for discrete Steklov eigenvalues on
trees via geometric quantities. For a finite tree, we prove sharp upper bounds
for the first nonzero Steklov eigenvalue by the reciprocal of the size of the
boundary and the diameter respectively. We also prove similar estimates for
higher order Steklov eigenvalues.


  Graph neural networks (GNNs) have exhibited exceptional efficacy in a diverse
array of applications. However, the sheer size of large-scale graphs presents a
significant challenge to real-time inference with GNNs. Although existing
Scalable GNNs leverage linear propagation to preprocess the features and
accelerate the training and inference procedure, these methods still suffer
from scalability issues when making inferences on unseen nodes, as the feature
preprocessing requires the graph to be known and fixed. To further accelerate
Scalable GNNs inference in this inductive setting, we propose an online
propagation framework and two novel node-adaptive propagation methods that can
customize the optimal propagation depth for each node based on its topological
information and thereby avoid redundant feature propagation. The trade-off
between accuracy and latency can be flexibly managed through simple
hyper-parameters to accommodate various latency constraints. Moreover, to
compensate for the inference accuracy loss caused by the potential early
termination of propagation, we further propose Inception Distillation to
exploit the multi-scale receptive field information within graphs. The rigorous
and comprehensive experimental study on public datasets with varying scales and
characteristics demonstrates that the proposed inference acceleration framework
outperforms existing state-of-the-art graph inference acceleration methods in
terms of accuracy and efficiency. Particularly, the superiority of our approach
is notable on datasets with larger scales, yielding a 75x inference speedup on
the largest Ogbn-products dataset.


  This paper presents vertical (001) oriented $\beta$-Ga$_2$O$_3$ field plated
(FP) Schottky barrier diode (SBD) with a novel extreme permittivity dielectric
field oxide. A thin drift layer of 1.7 $\mu m$ was used to enable a
punch-through (PT) field profile and very low differential specific
on-resistance (R$_{on-sp}$) of 0.32 m$\Omega$-cm$^{2}$. The extreme
permittivity field plate oxide facilitated the lateral spread of the electric
field profile beyond the field plate edge and enabled a breakdown voltage
($V_{br}$) of 687 V. The edge termination efficiency increases from 13.5 $\%$
for non-field plated structure to 63 $\%$ for high permittivity field plate
structure. The surface breakdown electric field was extracted to be 5.45 MV/cm
at the center of the anode region using TCAD simulations. The high permittivity
field plated SBD demonstrated a record high Baliga figure of merit (BFOM) of
1.47 GW/cm$^{2}$ showing the potential of Ga$_2$O$_3$ power devices for
multi-kilovolt class applications.


  Potential energy curves for excited leptonic states of the
helium-antihydrogen system are calculated within Ritz' variational approach. An
explicitly correlated ansatz for the leptonic wave function is employed
describing accurately the motion of the leptons (two electrons and positron) in
the field of the helium nucleus and of the antiproton with arbitrary orbital
angular momentum projection $\Lambda$ onto the internuclear axis. Results for
$\Lambda$=0, 1 and 30 are presented. For quasibound states with large values of
$\Lambda$ and rotational quantum numbers $J>\Lambda$ no annihilation and
rearrangement decay channels occur, i. e. they are metastable.


  The effects of low dimensionality on the thermodynamics of a Fermi gas
trapped by isotropic power law potentials are analyzed. Particular attention is
given to different characteristic temperatures that emerge, at low
dimensionality, in the thermodynamic functions of state and in the
thermodynamic susceptibilities (isothermal compressibility and specific heat).
An energy-entropy argument that physically favors the relevance of one of these
characteristic temperatures, namely, the non vanishing temperature at which the
chemical potential reaches the Fermi energy value, is presented. Such an
argument allows to interpret the nonmonotonic dependence of the chemical
potential on temperature, as an indicator of the appearance of a thermodynamic
regime, where the equilibrium states of a trapped Fermi gas are characterized
by larger fluctuations in energy and particle density as is revealed in the
corresponding thermodynamics susceptibilities.


  We consider properties of the operators D(r,M)=a^r(a^\dag a)^M (which we call
generalized Laguerre-type derivatives), with r=1,2,..., M=0,1,..., where a and
a^\dag are boson annihilation and creation operators respectively, satisfying
[a,a^\dag]=1. We obtain explicit formulas for the normally ordered form of
arbitrary Taylor-expandable functions of D(r,M) with the help of an operator
relation which generalizes the Dobinski formula. Coherent state expectation
values of certain operator functions of D(r,M) turn out to be generating
functions of combinatorial numbers. In many cases the corresponding
combinatorial structures can be explicitly identified.


  We will show that the complex shapes of snow crystals can be explained from a
simple basic mechanism that is also responsible for the appearance of many
others structures in nature. We expect that this new physical mechanism, that
follows from minimizing the total stored energy, will permit to explain most of
the features of snow crystal growth.


  In this paper, polar codes for the $m$-user multiple access channel (MAC)
with binary inputs are constructed. It is shown that Ar{\i}kan's polarization
technique applied individually to each user transforms independent uses of a
$m$-user binary input MAC into successive uses of extremal MACs. This
transformation has a number of desirable properties: (i) the `uniform sum rate'
of the original MAC is preserved, (ii) the extremal MACs have uniform rate
regions that are not only polymatroids but matroids and thus (iii) their
uniform sum rate can be reached by each user transmitting either uncoded or
fixed bits; in this sense they are easy to communicate over. A polar code can
then be constructed with an encoding and decoding complexity of $O(n \log n)$
(where $n$ is the block length), a block error probability of $o(\exp(- n^{1/2
- \e}))$, and capable of achieving the uniform sum rate of any binary input MAC
with arbitrary many users. An application of this polar code construction to
communicating on the AWGN channel is also discussed.


  This paper has been removed by arXiv administrators because it plagiarizes
gr-qc/0603075 and others.
  This paper has excessive overlap with the following papers also written by
the authors or their collaborators: gr-qc/0606080, gr-qc/0607126,
gr-qc/0607109, gr-qc/0607110, and others.


  In this paper we develop a formalism to describe a superfluid in a
gravitational background. This formalism is based on a covariant generalization
of the field description for a superconductor in terms of a U(1) spontaneous
symmetry breaking. We study the stability of the solutions for a vortexless
fluid and the force acting on vortices in the fluid, which is a generalization
of the well-known flat space-time Magnus force. To clarify the development we
include the explicit discussion of two particular cases, one of them of
astrophysical interest.


  We report optical and infrared observations of the massive X-ray binary
system 4U1145-619 (V801 Cen) which show that the circumstellar disc of the Be
star component is in decline. Infrared J,H,K,L magnitudes of V801Cen have been
monitored from 1993 March to 1996 April. H alpha spectra have been obtained
throughout the same period. We find that both the infrared excess and the
Balmer emission have been in decline throughout the period of observations. A
13 year optical and X-ray history of the source has been collated, revealing a
possible correlation between the optical and X-ray activity. In addition, we
have used u,v,b,y,beta indices, corrected for both circumstellar and
interstellar effects, to calculate the physical parameters of the underlying B
star.


  We analyze how the thermal history of the universe is influenced by the
statistical description, assuming a deviation from the usual Bose-Einstein,
Fermi-Dirac and Boltzmann-Gibbs distribution functions. These deviations
represent the possible appearance of non-extensive effects related with the
existence of long range forces, memory effects, or evolution in fractal or
multi-fractal space. In the early universe, it is usually assumed that the
distribution functions are the standard ones. Then, considering the evolution
in a larger theoretical framework will allow to test this assumption and to
place limits to the range of its validity. The corrections obtained will change
with temperature, and consequently, the bounds on the possible amount of
non-extensivity will also change with time. We generalize results which can be
used in other contexts as well, as the Boltzmann equation and the Saha law, and
provide an estimate on how known cosmological bounds on the masses of neutrinos
are modified by a change in the statistics. We particularly analyze here the
recombination epoch, making explicit use of the chemical potentials involved in
order to attain the necessary corrections. All these results constitute the
basic tools needed for placing bounds on the amount of non-extensivity that
could be present at different eras and will be later used to study primordial
nucleosynthesis.


  In this paper we derive an explicit expression for the normal zeta function
of class two nilpotent groups whose associated Pfaffian hypersurface is smooth.
In particular, we show how the local zeta function depends on counting mod p
rational points on related varieties, and we describe the varieties that can
appear in such a decomposition. As a corollary, we also establish explicit
results on the degree of polynomial subgroup growth in these groups, and we
study the behaviour of poles of this zeta function. Under certain geometric
conditions, we also confirm that these functions satisfy a functional equation.


  (Abridged) Objects with radii of 10 to 100 pc and masses in the range from
10^6 to 10^8 M_sun have been discovered during the past decade. These so-called
ultra compact dwarf galaxies (UCDs) constitute a transition between classical
star clusters and elliptical galaxies in terms of radii, relaxation times and
V-band mass-to-light (M/L_V) ratios. Using new data, we find that the mass
interval from 10^6 to 10^7 M_sun is of special interest, because within this
range typical half-light radii and dynamical mass-to-light ratios begin to
increase compared to globular clusters, the highest stellar densities are
reached and typical median two-body relaxation times surpass a Hubble time. The
M/L_V ratios of the UCDs turn out to be incompatible with the predictions from
simple stellar population (SSP) models when using the canonical stellar initial
mass function (IMF), although SSPs probably are good approximations to the real
stellar populations in UCDs and the SSP models allow to account for metallicity
effects on the M/L_V ratio. This provides evidence for the UCDs either having
formed with an IMF different from the canonical one or containing dark matter.
We emphasise that almost all pressure-supported stellar systems ranging from
star clusters to massive elliptical galaxies have M/L_V ratios less than 10
M_sun/L_sun, and that only dSph satellite galaxies have M/L_V ratios greater
than 100 M_sun/L_sun and therewith form exceptional systems.


  Call a colouring of a graph distinguishing if the only automorphism which
preserves it is the identity. We investigate the role of the Axiom of Choice in
the existence of certain proper or distinguishing colourings in both vertex and
edge variants with special emphasis on locally finite connected graphs. We show
that every locally finite connected graph has a distinguishing colouring with
at most countable number of colours or every locally finite connected graph has
a proper colouring with at most countable number of colours if and only if
K\H{o}nig's Lemma holds. This statement holds for both vertex and edge
colourings. Furthermore, we show that it is not provable in ZF that such
colourings exist even for every connected graph with maximum degree 3. We also
formulate a few conditions about distinguishing and proper colourings which are
equivalent to the Axiom of Choice.


  We give a new, simple construction of the $\alpha$-stable tree for $\alpha
\in (1,2]$. We obtain it as the closure of an increasing sequence of
$\mathbb{R}$-trees inductively built by gluing together line-segments one by
one. The lengths of these line-segments are related to the the increments of an
increasing $\mathbb{R}_+$-valued Markov chain. For $\alpha = 2$, we recover
Aldous' line-breaking construction of the Brownian continuum random tree based
on an inhomogeneous Poisson process.


  We seek signatures of the current experimental
$^{12}$C$(\alpha,\gamma)^{16}$O reaction rate probability distribution function
in the pulsation periods of carbon-oxygen white dwarf models. We find that
adiabatic g-modes trapped by the interior carbon-rich layer offer potentially
useful signatures of this reaction rate probability distribution function.
Probing the carbon-rich region is relevant because it forms during the
evolution of low-mass stars under radiative helium burning conditions,
mitigating the impact of convective mixing processes. We make direct
quantitative connections between the pulsation periods of the identified
trapped g-modes in variable WD models and the current experimental
$^{12}$C$(\alpha,\gamma)^{16}$O reaction rate probability distribution
function. We find an average spread in relative period shifts of $\Delta P/P
\simeq \pm$ 2\% for the identified trapped g-modes over the $\pm$ 3$\sigma$
uncertainty in the $^{12}$C$(\alpha,\gamma)^{16}$O reaction rate probability
distribution function -- across the effective temperature range of observed DAV
and DBV white dwarfs and for different white dwarf masses, helium shell masses,
and hydrogen shell masses. The g-mode pulsation periods of observed white
dwarfs are typically given to 6-7 significant figures of precision. This
suggests that an astrophysical constraint on the
$^{12}$C$(\alpha,\gamma)^{16}$O reaction rate could, in principle, be
extractable from the period spectrum of observed variable white dwarfs.


  In order to utilize network resources and provide a more reliable delivery of
information, multipath routing algorithms are used with a higher priority than
single path routing. But providing the quality of service (QoS) requirements
while load balancing is done among multiple paths is still a challenge. In this
paper a new load balancing algorithm is proposed by using an explicit endpoint
admission control (EEAC) to achieve a dynamic load balancing algorithm, with
the ability to guarantee the end-to-end QoS for a variety of service classes.
The simulation results for non deterministic network conditions show that the
proposed algorithm increases the utilization of network resources and also
decreases the end-to-end delay.


  We construct a family of balanced signature pseudo-Riemannian manifolds,
which arise as hypersurfaces in flat space, that are curvature homogeneous,
that are modeled on a symmetric space, and that are not locally homogeneous.


  Automated representation learning is behind many recent success stories in
machine learning. It is often used to transfer knowledge learned from a large
dataset (e.g., raw text) to tasks for which only a small number of training
examples are available. In this paper, we review recent advance in learning to
represent social media users in low-dimensional embeddings. The technology is
critical for creating high performance social media-based human traits and
behavior models since the ground truth for assessing latent human traits and
behavior is often expensive to acquire at a large scale. In this survey, we
review typical methods for learning a unified user embeddings from
heterogeneous user data (e.g., combines social media texts with images to learn
a unified user representation). Finally we point out some current issues and
future directions.


  We investigate velocity probability distribution functions (PDF) of sheared
hard-sphere suspensions. As observed in our Stokes flow simulations and
explained by our single-particle theory, these PDFs can show pronounced
deviations from a Maxwell-Boltzmann distribution. The PDFs are symmetric around
zero velocity and show a Gaussian core and exponential tails over more than six
orders of magnitude of probability. Following the excellent agreement of our
theory and simulation data, we demonstrate that the distribution functions
scale with the shear rate, the particle volume concentration, as well as the
fluid viscosity.


  We study how well the complex gas velocity fields induced by massive spiral
arms are modelled by the hydrodynamical simulations we used to constrain the
dark matter fraction in nearby spiral galaxies (Kranz et al. 2001, 2003). More
specifically, we explore the dependence of the positions and amplitudes of
features in the gas flow on the temperature of the interstellar medium (assumed
to behave as a one-component isothermal fluid), the non-axisymmetric disk
contribution to the galactic potential, the pattern speed, Omega_p, and finally
the numerical resolution of the simulation. We argue that, after constraining
the pattern speed reasonably well by matching the simulations to the observed
spiral arm morphology, the amplitude of the non-axisymmetric perturbation (the
disk fraction) is left as the primary parameter determining the gas dynamics.
However, due to the sensitivity of the positions of the shocks to modeling
parameters, one has to be cautious when quantitatively comparing the
simulations to observations. In particular, we show that a global least squares
analysis is not the optimal method for distinguishing different models as it
tends to slightly favor low disk fraction models. Nevertheless, we conclude
that, given observational data of reasonably high spatial resolution and an
accurate shock-resolving hydro-code this method tightly constrains the dark
matter content within spiral galaxies. We further argue that even if the
perturbations induced by spiral arms are weaker than those of strong bars, they
are better suited for this kind of analysis because the spiral arms extend to
larger radii where effects like inflows due to numerical viscosity and
morphological dependence on gas sound speed are less of a concern than they are
in the centers of disks.


  We revisit the work of \cite{raphael2011existence} on the minimal mass blow
up solution for $iu_{t}+\Delta u=-k(x)|u|^{2}u$, and extend the construction of
such a solution to the $k\in C^{2}$ case.


  In this paper, it is proved that the teleparallel energy-momentum generalizes
that of the ADM formalism. In doing so, it is shown that the teleparallel
$4$-momentum can be made to coincide with that of the ADM approach whenever the
ADM $4$-momentum is applicable. The only assumptions are the time gauge for the
teleparallel frame and the well-known restrictions for the coordinate system
used in the calculation of the ADM $4$-momentum. Then, examples where the ADM
formalism fails to give consist results, but the teleparallel approach does
not, are given. The advantages of the teleparallel stress-energy tensor
(density) over the pseudo-tensor of Landau-Lifshitz are exhibited. Finally, the
difficulties in identifying the gravitational angular momentum density is
discussed; it is shown that the spatial part of the proposed angular momentum
density $M^{ab}$ vanishes when the teleparallel frame satisfies the time gauge
condition.


  We prove that the energy equality holds for weak solutions of the 3D
Navier-Stokes equations in the functional class $L^3([0,T);V^{5/6})$, where
$V^{5/6}$ is the domain of the fractional power of the Stokes operator
$A^{5/12}$.


  In this paper we consider a special kind of three-point functions of HHL type
at weak coupling in N=4 SYM theory and analyze its volume dependence. At strong
coupling this kind of three-point functions were studied recently by Bajnok,
Janik and Wereszczynski [1]. The authors considered some cases of HHL
correlator in the su(2) sector and, relying on their explicit results,
formulated a conjecture about the form of the volume dependence of the
symmetric HHL structure constant to be valid at any coupling up to wrapping
corrections. In order to test this hypothesis we considered the HHL correlator
in su(2) sector at weak coupling and directly showed that, up to one loop, the
finite volume dependence has exactly the form proposed in [1]. Another side of
the conjecture suggests that computation of the symmetric structure constant is
equivalent to computing the corresponding set of infinite volume form factors,
which can be extracted as the coefficients of finite volume expansion. In this
sense, extracting appropriate coefficients from our result gives a prediction
for the corresponding infinite volume form factors.


  Pedestrian behavior has much more complicated characteristics in a dense
crowd and thus attracts the widespread interest of scientists and engineers.
However, even successful modeling approaches such as pedestrian models based on
particle systems are still not fully considered the perceptive mechanism
underlying collective pedestrian behavior. This paper extends a behavioral
heuristics-based pedestrian model to an adaptive agent-based model, which
explicitly considers the crowding effect of neighboring individuals and
perception anisotropy on the representation of a pedestrians visual
information. The adaptive agents with crowding perception are constructed to
investigate complex, selforganized collective dynamics of pedestrian motion.
The proposed model simulates selforganized pedestrian flows in good
quantitative agreement with empirical data. The selforganized phenomena include
lane formation in bidirectional flow and fundamental diagrams of unidirectional
flow. Simulation results show that the emergence of lane formation in
bidirectional flow can be well reproduced. To investigate this further,
increasing view distance has a significant effect on reducing the number of
lanes, increasing lane width, and stabilizing the self-organized lanes. The
paper also discusses phase transitions of fundamental diagrams of pedestrian
crowds with unidirectional flow. It is found that the heterogeneity of how
pedestrians perceive crowding in the population has a remarkable impact on the
flow quality, which results in the buildup of congestion and rapidly decreases
the efficiency of pedestrian flows. It also indicates that the concept of
heterogeneity may be used to explain the instability of phase transitions.


  The parity and time-reversal invariant effective lagrangian for a heavy
fermion interacting with an abelian gauge field, i.e., NRQED, is constructed
through order $1/M^4$. The implementation of Lorentz invariance in the
effective theory becomes nontrivial at this order, and a complete solution for
Wilson coefficient constraints is obtained. Matching conditions in the
one-fermion sector are presented in terms of form factors and two-photon matrix
elements of the nucleon. The extension of NRQED to describe interactions of the
heavy fermion with a light fermion is introduced. Sample applications are
discussed; these include the computation of nuclear structure effects in atomic
bound states, the model-independent analysis of radiative corrections to
low-energy lepton-nucleon scattering, and the study of static electromagnetic
properties of nucleons.


  Casimir energies on space-times having the fundamental domains of
semi-regular spherical tesselations of the three-sphere as their spatial
sections are computed for scalar and Maxwell fields. The spectral theory of
p-forms on the fundamental domains is also developed and degeneracy generating
functions computed. Absolute and relative boundary conditions are encountered
naturally. Some aspects of the heat-kernel expansion are explored. The
expansion is shown to terminate with the constant term which is computed to be
1/2 on all tesselations for a coexact 1-form and shown to be so by topological
arguments. Some practical points concerning generalised Bernoulli numbers are
given.


  We live in a time when billions of IoT devices are being deployed and
increasingly relied upon. This makes ensuring their availability and
recoverability in case of a compromise a paramount goal. The large and rapidly
growing number of deployed IoT devices make manual recovery impractical,
especially if the devices are dispersed over a large area. Thus, there is a
need for a reliable and scalable remote recovery mechanism that works even
after attackers have taken full control over devices, possibly misusing them or
trying to render them useless.
  To tackle this problem, we present Lazarus, a system that enables the remote
recovery of compromised IoT devices. With Lazarus, an IoT administrator can
remotely control the code running on IoT devices unconditionally and within a
guaranteed time bound. This makes recovery possible even in case of severe
corruption of the devices' software stack. We impose only minimal hardware
requirements, making Lazarus applicable even for low-end constrained
off-the-shelf IoT devices. We isolate Lazarus's minimal recovery trusted
computing base from untrusted software both in time and by using a trusted
execution environment. The temporal isolation prevents secrets from being
leaked through side-channels to untrusted software. Inside the trusted
execution environment, we place minimal functionality that constrains untrusted
software at runtime.
  We implement Lazarus on an ARM Cortex-M33-based microcontroller in a full
setup with an IoT hub, device provisioning and secure update functionality. Our
prototype can recover compromised embedded OSs and bare-metal applications and
prevents attackers from bricking devices, for example, through flash wear out.
We show this at the example of FreeRTOS, which requires no modifications but
only a single additional task. Our evaluation shows negligible runtime
performance impact and moderate memory requirements.


  A common task in physics, information theory, and other fields is the
analysis of properties of subsystems of a given system. Given the covariance
matrix $M$ of a system of $n$ coupled variables, the covariance matrices of the
subsystems are principal submatrices of $M$. The rapid growth with $n$ of the
set of principal submatrices makes it impractical to exhaustively study each
submatrix for even modestly-sized systems. It is therefore of great interest to
derive methods for approximating the distributions of important submatrix
properties for a given matrix.
  Motivated by the importance of differential entropy as a systemic measure of
disorder, we study the distribution of log-determinants of principal $k\times
k$ submatrices when the covariance matrix has bounded condition number. We
derive upper bounds for the right tail and the variance of the distribution of
minors, and we use these in turn to derive upper bounds on the standard error
of the sample mean of subsystem entropy. Our results demonstrate that, despite
the rapid growth of the set of subsystems with $n$, the number of samples that
are needed to bound the sampling error is asymptotically independent of $n$.
Instead, it is sufficient to increase the number of samples in linear
proportion to $k$ to achieve a desired sampling accuracy.


  A small fraction of GRBs with available data down to soft X-rays ($\sim0.5$
keV) have been shown to feature a spectral break in the low-energy part
($\sim1-10$ keV) of their prompt emission spectrum. The overall spectral shape
is consistent with optically thin synchrotron emission from a population of
particles that have cooled on a timescale comparable to the dynamic time to
energies that are still much higher than their rest mass energy (marginally
fast cooling regime). We consider a hadronic scenario and investigate if the
prompt emission of these GRBs can originate from relativistic protons that
radiate synchrotron in the marginally fast cooling regime. Using
semi-analytical methods, we derive the source parameters, such as magnetic
field strength and proton luminosity, and calculate the high-energy neutrino
emission expected in this scenario. We also investigate how the emission of
secondary pairs produced by photopion interactions and $\gamma\gamma$ pair
production affect the broadband photon spectrum. We support our findings with
detailed numerical calculations. Strong modification of the photon spectrum
below the break energy due to the synchrotron emission of secondary pairs is
found, unless the bulk Lorentz factor is very large ($\Gamma \gtrsim 10^3$).
Moreover, this scenario predicts unreasonably high Poynting luminosities
because of the strong magnetic fields ($10^6-10^7$ G) that are necessary for
the incomplete proton cooling. Our results strongly disfavour marginally fast
cooling protons as an explanation of the low-energy spectral break in the
prompt GRB spectra.


  We show that an arbitrary Anosov Gaussian thermostat on a surface is
dissipative unless the external field has a global potential.


  The finite sample properties of estimators are usually understood or
approximated using asymptotic theories. Two main asymptotic constructions have
been used to characterize the presence of many instruments. The first assumes
that the number of instruments increases with the sample size. I demonstrate
that in this case, one of the key assumptions used in the asymptotic
construction may imply that the number of ``effective" instruments should be
finite, resulting in an internal contradiction. The second asymptotic
representation considers that the number of instrumental variables (IVs) may be
finite, infinite, or even a continuum. The number does not change with the
sample size. In this scenario, the regularized estimator obtained depends on
the topology imposed on the set of instruments as well as on a regularization
parameter. These restrictions may induce a bias or restrict the set of
admissible instruments. However, the assumptions are internally coherent. The
limitations of many IVs asymptotic assumptions provide support for finite
sample distributional studies to better understand the behavior of many IV
estimators.


  We explore the design space for the static visualization of datasets with
quantitative attributes that vary over multiple orders of magnitude-we call
these attributes Orders of Magnitude Values (OMVs)-and provide design
guidelines and recommendations on effective visual encodings for OMVs. Current
charts rely on linear or logarithmic scales to visualize values, leading to
limitations in performing simple tasks for OMVs. In particular, linear scales
prevent the reading of smaller magnitudes and their comparisons, while
logarithmic scales are challenging for the general public to understand. Our
design space leverages the approach of dividing OMVs into two different parts:
mantissa and exponent, in a way similar to scientific notation. This separation
allows for a visual encoding of both parts. For our exploration, we use four
datasets, each with two attributes: an OMV, divided into mantissa and exponent,
and a second attribute that is nominal, ordinal, time, or quantitative. We
start from the original design space described by the Grammar of Graphics and
systematically generate all possible visualizations for these datasets,
employing different marks and visual channels. We refine this design space by
enforcing integrity constraints from visualization and graphical perception
literature. Through a qualitative assessment of all viable combinations, we
discuss the most effective visualizations for OMVs, focusing on channel and
task effectiveness. The article's main contributions are 1) the presentation of
the design space of OMVs, 2) the generation of a large number of OMV
visualizations, among which some are novel and effective, 3) the refined
definition of a scale that we call E+M for OMVs, and 4) guidelines and
recommendations for designing effective OMV visualizations. These efforts aim
to enrich visualization systems to better support data with OMVs and guide
future research.


  An unusual solar burst was observed simultaneously by two decameter radio
telescopes UTR-2 (Kharkov, Ukraine) and URAN-2 (Poltava, Ukraine) on 3 June
2011 in the frequency range 16-28 MHz. The observed radio burst has some
unusual properties, which are not typical for the other types of solar radio
bursts. The frequency drift rate of it was positive (about 500 kHz s$^{-1}$) at
frequencies higher than 22 MHz and negative (100 kHz s$^{-1}$) at lower
frequencies. The full duration of this event varies from 50 s up to 80 s,
depending on the frequency. The maximum radio flux of the unusual burst reaches
$\approx 10^3$ s.f.u and its polarization does not exceed 10%. This burst has a
fine frequency-time structure of unusual appearance. It consists of stripes
with the frequency bandwidth 300-400 kHz. We consider that several accompanied
radio and optical events observed by SOHO and STEREO spacecraft are possibly
associated with the reported radio burst. A model that may interpret the
observed unusual solar radio burst is proposed.


  The task of out-of-distribution (OOD) detection is notoriously ill-defined.
Earlier works focused on new-class detection, aiming to identify label-altering
data distribution shifts, also known as "semantic shift." However, recent works
argue for a focus on failure detection, expanding the OOD evaluation framework
to account for label-preserving data distribution shifts, also known as
"covariate shift." Intriguingly, under this new framework, complex OOD
detectors that were previously considered state-of-the-art now perform
similarly to, or even worse than the simple maximum softmax probability
baseline. This raises the question: what are the latest OOD detectors actually
detecting? Deciphering the behavior of OOD detection algorithms requires
evaluation datasets that decouples semantic shift and covariate shift. To aid
our investigations, we present ImageNet-OOD, a clean semantic shift dataset
that minimizes the interference of covariate shift. Through comprehensive
experiments, we show that OOD detectors are more sensitive to covariate shift
than to semantic shift, and the benefits of recent OOD detection algorithms on
semantic shift detection is minimal. Our dataset and analyses provide important
insights for guiding the design of future OOD detectors.


  Heller et. Al. (Science 311, 508 (2006)) demonstrated the first DNA-CN
optical sensor by wrapping a piece of double-stranded DNA around the surface of
single-walled carbon nanotubes (CN). This new type of optical device can be
placed inside living cells and detect trace amounts of harmful contaminants by
means of near infrared light. Using a simple exciton theory in nanostructures
and the phenomena of B-Z structural phase transition of DNA, we investigate the
working principle of this new class of optical biosensor from DNA by using the
nanostructure surface as a sensor to detect the property change of DNA as it
responds to the presence of target ions. We also propose some new design models
by replacing carbon nanotubes with graphene ribbon semiconductors.


  The Multimodal Video Search by Examples (MVSE) project investigates using
video clips as the query term for information retrieval, rather than the more
traditional text query. This enables far richer search modalities such as
images, speaker, content, topic, and emotion. A key element for this process is
highly rapid, flexible, search to support large archives, which in MVSE is
facilitated by representing video attributes by embeddings. This work aims to
mitigate any performance loss from this rapid archive search by examining
reranking approaches. In particular, zero-shot reranking methods using large
language models are investigated as these are applicable to any video archive
audio content. Performance is evaluated for topic-based retrieval on a publicly
available video archive, the BBC Rewind corpus. Results demonstrate that
reranking can achieve improved retrieval ranking without the need for any
task-specific training data.


  It is demonstrated that very general nonlinear dynamical systems covering all
cases arising in practice can be brought down to rate equations of chemical
kinetics


  This paper introduces a new Windowed Green Function (WGF) method for the
numerical integral-equation solution of problems of electromagnetic scattering
by obstacles in presence of dielectric or conducting half-planes. The WGF
method, which is based on use of smooth windowing functions and integral
kernels that can be expressed directly in terms of the free-space Green
function, does not require evaluation of expensive Sommerfeld integrals. The
proposed approach is fast, accurate, flexible and easy to implement. In
particular, straightforward modifications of existing (accelerated or
unaccelerated) solvers suffice to incorporate the WGF capability. The
mathematical basis of the method is simple: the method relies on a certain
integral equation posed on the union of the boundary of the obstacle and a
small flat section of the interface between the penetrable media. Numerical
experiments demonstrate that both the near- and far-field errors resulting from
the proposed approach decrease faster than any negative power of the window
size. In the examples considered in this paper the proposed method is up to
thousands of times faster, for a given accuracy, than a corresponding method
based on the layer-Green-function.


  We propose a simple modification to existing neural machine translation (NMT)
models that enables using a single universal model to translate between
multiple languages while allowing for language specific parameterization, and
that can also be used for domain adaptation. Our approach requires no changes
to the model architecture of a standard NMT system, but instead introduces a
new component, the contextual parameter generator (CPG), that generates the
parameters of the system (e.g., weights in a neural network). This parameter
generator accepts source and target language embeddings as input, and generates
the parameters for the encoder and the decoder, respectively. The rest of the
model remains unchanged and is shared across all languages. We show how this
simple modification enables the system to use monolingual data for training and
also perform zero-shot translation. We further show it is able to surpass
state-of-the-art performance for both the IWSLT-15 and IWSLT-17 datasets and
that the learned language embeddings are able to uncover interesting
relationships between languages.


  We searched for z=7.3 Lya emitters (LAEs) behind two lensing clusters, Abell
2390 and CL 0024, with the Subaru Telescope Suprime-Cam and a narrowband NB1006
(FWHM ~ 21 nm centered at 1005 nm). We investigated if there exist objects
consistent with the color of z=7.3 LAEs behind the clusters but could not
detect any LAEs to the unlensed line limit F(Lya) ~ 6.9 x 10^{-18} erg/s/cm^2.
Using several z=7 Lya luminosity functions (LFs) from the literature, we
estimated and compared the expected detection numbers of z ~ 7 LAEs in lensing
and blank field surveys in the case of using an 8m class ground based
telescope. Given the steep bright-end slope of the LFs, when the detector
field-of view (FOV) is comparable to the angular extent of a massive lensing
cluster, imaging cluster(s) is more efficient in detecting z ~ 7 LAEs than
imaging a blank field. However, the gain is expected to be modest, a factor of
two at most and likely much less depending on the adopted LFs. The main
advantage of lensing-cluster survey, therefore, remains to be the gain in depth
and not necessarily in detection efficiency. For much larger detectors, the
lensing effect becomes negligible and the efficiency of LAE detection is
proportional to the instrumental FOV. We also inspected NB1006 images of three
z ~ 7 z-dropouts previously detected in Abell 2390 and found that none of them
are detected in NB1006. Two of them are consistent with predictions from the
previous studies that they would be at lower redshifts. The other one has a
photometric redshift of z ~ 7.3, and if it is at z=7.3, its unlensed Lya line
flux would be very faint: F(Lya) < 4.4 x 10^{-18} erg/s/cm^2 (1 sigma upper
limit) or rest frame equivalent width of W(Lya) < 26A. Its Lya emission might
be attenuated by neutral hydrogen, as recent studies show that the fraction of
Lyman break galaxies displaying strong Lya emission is lower at z ~ 7 than at z
<~ 6.


  Consider a set $X\subseteq \mathbb{R}^d$ which is 1-dense, namely, it
intersects every unit ball. We show that we can get from any point to any other
point in $\mathbb{R}^d$ in $n$ steps so that the intermediate points are in
$X$, and the discrepancy of the step vectors is at most $2\sqrt{2}$, or
formally, $$\sup\limits_{\substack{n\in \mathbb{Z}^+,\ t\in \mathbb{R}^d\\
X\text{ is 1-dense}}}\,\, \inf\limits_{\substack{p_1,\ldots, p_{n-1}\in X\\
p_0=\underline{0},\ p_n=t}}\,\, \max\limits_{0\leq i<j<n}
\big\|(p_{i+1}-p_i)-(p_{j+1}-p_j)\big\|\leq 2\sqrt{2}.$$


  The Extragalactic Background Light (EBL) stands for the mean surface
brightness of the sky as we would see it from a representative vantage point in
the intergalactic space outside of our Milky Way Galaxy. Averaged over the
whole 4 pi solid angle it represents the collective light from all luminous
matter radiated throughout the cosmic history. Part of the EBL is resolved into
galaxies that, with the increasing detecting power of giant telescopes and
sensitive detectors, are seen to deeper and deeper limiting magnitudes. This
resolved part is now known to contribute a substantial or even the major part
of the EBL. There still remains, however, the challenge of finding out to what
extent galaxies too faint or too diffuse to be discerned individually,
individual stars or emission by gas outside the galaxies, or more
speculatively, some hitherto unknown light sources such as decaying elementary
particles are accounting for the remaining EBL. We review the recent progress
that has been made in the measurement of EBL. The current photometric results
suggest that there is, beyond the resolved galaxies, an EBL component that
cannot be explained by diffuse galaxy halos or intergalactic stars.


  For the Bd meson system, CP, T and CPT indirect violation can be described
using two physical parameters, epsilon and delta. The traditional observables
based on flavour tag and used in the kaon system, are not helpful in the Bd
case, and new asymmetries have to be introduced. Here such alternative
observables, based on CP tag, are presented, together with the first estimation
on the sensitivity that current asymmetric B-factories can achieve on their
measurement.


  Deep learning can achieve outstanding results in various fields. However, it
requires so significant computational power that graphics processing units
(GPUs) and/or numerous computers are often required for the practical
application. We have developed a new distributed calculation framework called
"Sashimi" that allows any computer to be used as a distribution node only by
accessing a website. We have also developed a new JavaScript neural network
framework called "Sukiyaki" that uses general purpose GPUs with web browsers.
Sukiyaki performs 30 times faster than a conventional JavaScript library for
deep convolutional neural networks (deep CNNs) learning. The combination of
Sashimi and Sukiyaki, as well as new distribution algorithms, demonstrates the
distributed deep learning of deep CNNs only with web browsers on various
devices. The libraries that comprise the proposed methods are available under
MIT license at http://mil-tokyo.github.io/.


  Recently we initiated the study of spherical T-duality for spacetimes that
are principal SU(2)-bundles. In this paper, we extend spherical T-duality to
spacetimes that are oriented non-principal SU(2)-bundles. There are several
interesting new examples in this case and a new phenomenon appearing in the
non-principal case is the existence of infinitely many spherical T-duals.


  We employ a single-charge counting technique to measure the full counting
statistics (FCS) of Andreev events in which Cooper pairs are either produced
from electrons that are reflected as holes at a superconductor/normal-metal
interface or annihilated in the reverse process. The FCS consists of quiet
periods with no Andreev processes, interrupted by the tunneling of a single
electron that triggers an avalanche of Andreev events giving rise to strongly
super-Poissonian distributions.


  We construct an example of a spherically symmetric black hole interior in
which there is NO (spherically symmetric) marginally trapped tube asymptotic to
the event horizon. The construction uses a self-gravitating massive scalar
field matter model, and the key condition we impose is that the scalar field
$\phi$ be bounded below by a positive constant along the event horizon.


  Geometric predicates are at the core of many algorithms, such as the
construction of Delaunay triangulations, mesh processing and spatial relation
tests. These algorithms have applications in scientific computing, geographic
information systems and computer-aided design. With floating-point arithmetic,
these geometric predicates can incur round-off errors that may lead to
incorrect results and inconsistencies, causing computations to fail. This issue
has been addressed using a combination of exact arithmetic for robustness and
floating-point filters to mitigate the computational cost of exact
computations. The implementation of exact computations and floating-point
filters can be a difficult task, and code generation tools have been proposed
to address this. We present a new C++ meta-programming framework for the
generation of fast, robust predicates for arbitrary geometric predicates based
on polynomial expressions. We combine and extend different approaches to
filtering, branch reduction, and overflow avoidance that have previously been
proposed. We show examples of how this approach produces correct results for
data sets that could lead to incorrect predicate results with naive
implementations. Our benchmark results demonstrate that our implementation
surpasses state-of-the-art implementations.


  In this paper, Problem 4.17 on R. Kirby's problem list is solved by
constructing infinitely many aspherical 4-manifolds that are homology 4-spheres


  This paper discerns the invariant manifold of a class of ill-posed stochastic
evolution equations driven by a nonlinear multiplicative noise. To be more
precise, we establish the existence of mean-square random unstable invariant
manifold and only mean-square stable invariant set. Due to the lack of the
Hille-Yosida condition, we construct a modified variation of constants formula
by the resolvent operator. With the price of imposing an unusual condition
involving a non-decreasing map, we set up the Lyapunov-Perron method and derive
the required estimates. We also emphasize that the Lyapunov-Perron map in the
forward time loses the invariant due to the adaptedness, we alternatively
establish the existence of mean-square random stable sets.


  Possibility of kaon-condensed phase in hyperon-mixed matter is considered on
the basis of chiral symmetry for kaon-baryon and kaon-kaon interactions, being
combined with the relativistic mean-field theory for two-body baryon
interaction. In addition, universal three-baryon repulsive force in the
string-junction model and phenomenological three-nucleon attractive force are
introduced. It is shown that softening of the equation of state stemming from
both kaon condensation and mixing of hyperons is compensated with the repulsive
effect of the three-baryon force and the relativistic effect for two-body
baryon-baryon interaction. The latter effect reflects the density-dependence of
scalar and vector meson mean-fields, which is constrained by the contribution
of the attractive three-nucleon force to the binding energy at saturation
density. The kaon-condensed phase in hyperon-mixed matter becomes stiff enough
to be consistent with recent observations of massive neutron stars.


  Double detonations in double white dwarf (WD) binaries undergoing unstable
mass transfer have emerged in recent years as one of the most promising Type Ia
supernova (SN Ia) progenitor scenarios. One potential outcome of this
"dynamically driven double-degenerate double-detonation" (D^6) scenario is that
the companion WD survives the explosion and is flung away with a velocity equal
to its > 1000 km/s pre-SN orbital velocity. We perform a search for these
hypervelocity runaway WDs using Gaia's second data release. In this paper, we
discuss seven candidates followed up with ground-based instruments. Three
sources are likely to be some of the fastest known stars in the Milky Way, with
total Galactocentric velocities between 1000 and 3000 km/s, and are consistent
with having previously been companion WDs in pre-SN Ia systems. However,
although the radial velocity of one of the stars is > 1000 km/s, the radial
velocities of the other two stars are puzzlingly consistent with 0. The
combined five-parameter astrometric solutions from Gaia and radial velocities
from follow-up spectra yield tentative 6D confirmation of the D^6 scenario. The
past position of one of these stars places it within a faint, old SN remnant,
further strengthening the interpretation of these candidates as hypervelocity
runaways from binary systems that underwent SNe Ia.


  In this paper, we focus on $(n+3)$-dimensional metric $n$-Lie algebras. To
begin with, we give some properties on $(n+3)$-dimensional $n$-Lie algebras.
Then based on the properties, we obtain the classification of
$(n+3)$-dimensional metric $n$-Lie algebras.


  Far ultraviolet observations of comets yield information about the energetic
processes that dissociate the sublimated gases from their primitive surfaces.
Understanding which emission processes are dominant, their effects on the
observed cometary spectrum, and how to properly invert the spectrum back to
composition of the presumably pristine surface ices of a comet nuclei are all
critical components for proper interpretation and analysis of comets. The close
approach of comet 46P/Wirtanen in 2018-2019 provided a unique opportunity to
study the inner most parts of a cometary coma with the Hubble Space Telescope
Cosmic Origins Spectrograph, rarely accessible with remote observations, at
length scales (100's of km) and wavelengths (900-1430 Angstroms) previously
probed only by the European Space Agency's Rosetta spacecraft. Our observations
show a complex picture for the inner coma; atomic production rates for H and O
that show water is the dominant source of both, an abundance of atomic sulfur
that is difficult to explain with the lifetimes of common sulfur parent
molecules, and a density distribution that is poorly fit with both Haser and
vectorial models.


  Sensitive detection of magnetic field is one of the open problem in
metrology. Here, we propose an Mach-Zehnder atomic interferometry to
sensitively detect the very weak local magnetic field, which is expelled by the
superconductor (as the "testing magnet") due to the Meissner effect. The
induced magnetic field gradient near the superconductor provides a centripetal
acceleration of the atomic motion in the interferometry and thus can be
detected by using the atomic interferences. Given gravity acceleration of the
atoms have been measured at the accuracy of $10^{-12}$ g, the measured
sensitivity of the expelled local field could reach $10^{-14}$ T.


  We study viscous fingering during drainage experiments in linear Hele-Shaw
cells filled with a random porous medium. The central zone of the cell is found
to be statistically more occupied than the average, and to have a lateral width
of 40% of the system width, irrespectively of the capillary number $Ca$. A
crossover length $w_f \propto Ca^{-1}$ separates lower scales where the
invader's fractal dimension $D\simeq1.83$ is identical to capillary fingering,
and larger scales where the dimension is found to be $D\simeq1.53$. The lateral
width and the large scale dimension are lower than the results for Diffusion
Limited Aggregation, but can be explained in terms of Dielectric Breakdown
Model. Indeed, we show that when averaging over the quenched disorder in
capillary thresholds, an effective law $v\propto (\nabla P)^2$ relates the
average interface growth rate and the local pressure gradient.


  The detection of Interstellar Objects passing through the Solar System offers
the promise of constraining the physical and chemical processes involved in
planetary formation in other extrasolar systems. While the effect of outgassing
by 1I/2017 U1 ('Oumuamua) was dynamically observed, no direct detection of the
ejected material was made. The discovery of the active interstellar comet
2I/Borisov means spectroscopic investigations of the sublimated ices is
possible for this object. We report the first detection of gas emitted by an
interstellar comet via the near-UV emission of CN from 2I/Borisov at a
heliocentric distance of $r$ = 2.7 au on 2019 September 20. The production rate
was found to be Q(CN) = $(3.7\pm0.4)\times10^{24}$ s$^{-1}$, using a simple
Haser model with an outflow velocity of 0.5 km s$^{-1}$. No other emission was
detected, with an upper limit to the production rate of C$_2$ of
$4\times10^{24}$ s$^{-1}$. The spectral reflectance slope of the dust coma over
$3900$ \AA\ $< \lambda< 6000$ \AA \ is steeper than at longer wavelengths, as
found for other comets. Broad band $R_c$ photometry on 2019 September 19 gave a
dust production rate of $Af\rho=143\pm10$ cm. Modelling of the observed gas and
dust production rates constrains the nuclear radius to $0.7-3.3$ km assuming
reasonable nuclear properties. Overall, we find the gas, dust and nuclear
properties for the first active Interstellar Object are similar to normal Solar
System comets.


  The accurate (or even approximate) solution of the equations that govern the
dynamics of dissipative quantum systems remains a challenging task for quantum
science. While several algorithms have been designed to solve those equations
with different degrees of flexibility, they rely mainly on highly expensive
iterative schemes. Most recently, deep neural networks have been used for
quantum dynamics but current architectures are highly dependent on the physics
of the particular system and usually limited to population dynamics. Here we
introduce an artificial-intelligence-based surrogate model that solves
dissipative quantum dynamics by parameterizing quantum propagators as Fourier
neural operators, which we train using both dataset and physics-informed loss
functions. Compared with conventional algorithms, our quantum neural propagator
avoids time-consuming iterations and provides a universal super-operator that
can be used to evolve any initial quantum state for arbitrarily long times. To
illustrate the wide applicability of the approach, we employ our quantum neural
propagator to compute population dynamics and time-correlation functions of the
Fenna-Matthews-Olson complex.


  In this article, we introduce an instruction set architecture (ISA) for
processing-in-memory (PIM) based deep neural network (DNN) accelerators. The
proposed ISA is for DNN inference on PIM-based architectures. It is assumed
that the weights have been trained and programmed into PIM-based DNN
accelerators before inference, and they are fixed during inference. We do not
restrict the devices of PIM-based DNN accelerators. Popular devices used to
build PIM-based DNN accelerators include resistive random-access memory (RRAM),
flash, ferroelectric field-effect transistor (FeFET), static random-access
memory (SRAM), etc. The target DNNs include convolutional neural networks
(CNNs) and multi-layer perceptrons (MLPs). The proposed ISA is transparent to
both applications and hardware implementations. It enables to develop unified
toolchains for PIM-based DNN accelerators and software stacks. For practical
hardware that uses a different ISA, the generated instructions by unified
toolchains can easily converted to the target ISA. The proposed ISA has been
used in the open-source DNN compiler PIMCOMP-NN
(https://github.com/sunxt99/PIMCOMP-NN) and the associated open-source
simulator PIMSIM-NN (https://github.com/wangxy-2000/pimsim-nn).


  We investigated the electronic properties of epitaxially stabilized
perovskite SrIrO3 and demonstrated the effective strain-control on its
electronic structure. Comprehensive transport measurements showed that the
strong spin-orbit coupling renders a novel semimetallic phase for the J_eff=1/2
electrons rather than an ordinary correlated metal, elucidating the nontrivial
mechanism underlying the dimensionality-controlled metal-insulator transition
in iridates. The electron-hole symmetry of this correlated semimetal was found
to exhibit drastic variation when subject to bi-axial strain. Under compressive
strain, substantial electron-hole asymmetry is observed in contrast to the
tensile side, where the electron and hole effective masses are comparable,
illustrating the susceptivity of the J_eff=1/2 to structural distortion.
Tensile strain also shrinks the Fermi surface, indicative of an increasing
degree of correlation which is consistent with optical measurements. These
results pave a pathway to investigate and manipulate the electronic states in
spin-orbit-coupled correlated oxides, and lay the foundation for constructing
5d transition metal heterostructures.


  We have made the first direct measurement of the parity-violating coupling of
the Z^0 boson to the strange quark, A_s, using ~550,000 e^+e^- ->Z^0->hadrons
events produced with a polarized electron beam and recorded by the SLD
experiment. Z^0 -> s-sbar events were tagged by the absence of B or D hadrons
and the presence in each hemisphere of a high-momentum K^+- or K^0_s. From the
polar angle distributions of the strangeness-signed thrust axis, we obtained
A_s=0.895+-0.066(stat.)+-0.062(syst.). The analyzing power and u-ubar plus
d-dbar background were constrained using the data.


  We investigate numerically the time dependence of "window" overlaps in a
three-dimensional Ising spin glass below its transition temperature after a
rapid quench. Using an efficient GPU implementation, we are able to study large
systems up to lateral length $L=128$ and up to long times of $t=10^8$ sweeps.
We find that the data scales according to the ratio of the window size $W$ to
the non-equilibrium coherence length $\xi(t)$. We also show a substantial
change in behavior if the system is run for long enough that it globally
equilibrates, i.e. $\xi(t) \approx L/2$, where $L$ is the lattice size. This
indicates that the local behavior of a spin glass depends on the spin
configurations (and presumably also the bonds) far away. We compare with
similar simulations for the Ising ferromagnet. Based on these results, we
speculate on a connection between the non-equilibrium dynamics discussed here
and averages computed theoretically using the "metastate".


  In recent years, large-scale pre-trained diffusion models have demonstrated
their outstanding capabilities in image and video generation tasks. However,
existing models tend to produce visual objects commonly found in the training
dataset, which diverges from user input prompts. The underlying reason behind
the inaccurate generated results lies in the model's difficulty in sampling
from specific intervals of the initial noise distribution corresponding to the
prompt. Moreover, it is challenging to directly optimize the initial
distribution, given that the diffusion process involves multiple denoising
steps. In this paper, we introduce a Fine-tuning Initial Noise Distribution
(FIND) framework with policy optimization, which unleashes the powerful
potential of pre-trained diffusion networks by directly optimizing the initial
distribution to align the generated contents with user-input prompts. To this
end, we first reformulate the diffusion denoising procedure as a one-step
Markov decision process and employ policy optimization to directly optimize the
initial distribution. In addition, a dynamic reward calibration module is
proposed to ensure training stability during optimization. Furthermore, we
introduce a ratio clipping algorithm to utilize historical data for network
training and prevent the optimized distribution from deviating too far from the
original policy to restrain excessive optimization magnitudes. Extensive
experiments demonstrate the effectiveness of our method in both text-to-image
and text-to-video tasks, surpassing SOTA methods in achieving consistency
between prompts and the generated content. Our method achieves 10 times faster
than the SOTA approach. Our homepage is available at
\url{https://github.com/vpx-ecnu/FIND-website}.


  The interaction between the electromagnetic field inside a cavity and natural
or artificial atoms has played a crucial role in developing our understanding
of light-matter interaction, and is central to various quantum technologies.
Recently, new regimes beyond the weak and strong light-matter coupling have
been explored in several settings. These regimes, where the interaction
strength is comparable (ultrastrong) or even higher (deep-strong) than the
transition frequencies in the system, can give rise to new physical effects and
applications. At the same time, they challenge our understanding of cavity QED.
When the interaction strength is so high, fundamental issues like the proper
definition of subsystems and of their quantum measurements, the structure of
light-matter ground states, or the analysis of time-dependent interactions are
subject to ambiguities leading to even qualitatively distinct predictions. The
resolution of these ambiguities is also important for understanding and
designing next-generation quantum devices that will exploit the ultrastrong
coupling regime. Here we discuss and provide solutions to these issues.


  We study the loss surface of DNNs with $L_{2}$ regularization. We show that
the loss in terms of the parameters can be reformulated into a loss in terms of
the layerwise activations $Z_{\ell}$ of the training set. This reformulation
reveals the dynamics behind feature learning: each hidden representations
$Z_{\ell}$ are optimal w.r.t. to an attraction/repulsion problem and
interpolate between the input and output representations, keeping as little
information from the input as necessary to construct the activation of the next
layer. For positively homogeneous non-linearities, the loss can be further
reformulated in terms of the covariances of the hidden representations, which
takes the form of a partially convex optimization over a convex cone.
  This second reformulation allows us to prove a sparsity result for
homogeneous DNNs: any local minimum of the $L_{2}$-regularized loss can be
achieved with at most $N(N+1)$ neurons in each hidden layer (where $N$ is the
size of the training set). We show that this bound is tight by giving an
example of a local minimum that requires $N^{2}/4$ hidden neurons. But we also
observe numerically that in more traditional settings much less than $N^{2}$
neurons are required to reach the minima.


  Two of the dominant channels for galaxy mass assembly are cold flows (cold
gas supplied via the filaments of the cosmic web) and mergers. How these
processes combine in a cosmological setting, at both low and high redshift, to
produce the whole zoo of galaxies we observe is largely unknown. Indeed there
is still much to understand about the detailed physics of each process in
isolation. While these formation channels have been studied using
hydrodynamical simulations, here we study their impact on gas properties and
star formation (SF) with some of the first simulations that capture the
multiphase, cloudy nature of the interstellar medium (ISM), by virtue of their
high spatial resolution (and corresponding low temperature threshold). In this
regime, we examine the competition between cold flows and a
supernovae(SNe)-driven outflow in a very high-redshift galaxy (z {\approx} 9)
and study the evolution of equal-mass galaxy mergers at low and high redshift,
focusing on the induced SF. We find that SNe-driven outflows cannot reduce the
cold accretion at z {\approx} 9 and that SF is actually enhanced due to the
ensuing metal enrichment. We demonstrate how several recent observational
results on galaxy populations (e.g. enhanced HCN/CO ratios in ULIRGs, a
separate Kennicutt Schmidt (KS) sequence for starbursts and the population of
compact early type galaxies (ETGs) at high redshift) can be explained with
mechanisms captured in galaxy merger simulations, provided that the multiphase
nature of the ISM is resolved.


  KK-theory is a bivariant and homotopy-invariant functor on $C^*$-algebras
that combines K-theory and K-homology. KK-groups form the morphisms in a
triangulated category. Spanier-Whitehead K-Duality intertwines the homological
with the cohomological side of KK-theory. Any extension of a unital
$C^*$-algebra by the compacts has two natural exact triangles associated to it
(the extension sequence itself and a mapping cone sequence). We find a duality
(based on Spanier-Whitehead K-duality) that interchanges the roles of these two
triangles together with their six-term exact sequences. This allows us to give
a categorical picture for the duality of Cuntz-Krieger-Toeplitz extensions
discovered by K. Matsumoto.


  Density functional theory augmented with Hubbard-$U$ corrections (DFT+$U$) is
currently one of the widely used methods for first-principles electronic
structure modeling of insulating transition metal oxides (TMOs). Since $U$ is
relatively large compared to band widths, the magnetic excitations in TMOs are
expected to be well described by a Heisenberg model. However, in practice the
calculated exchange parameters $J_{ij}$ depend on the magnetic configuration
from which they are extracted and on the functional used to compute them. In
this work we investigate how the spin polarization dependence of the underlying
exchange-correlation functional influences the calculated magnetic exchange
constants of TMOs. We perform a systematic study of the predictions of
calculations based on the local density approximation plus $U$ (LDA+$U$) and
the local spin density approximation plus $U$ (LSDA+$U$) for the electronic
structures, total energies and magnetic exchange interactions $J_{ij}$'s
extracted from ferromagnetic (FM) and antiferromagnetic (AFM) configurations of
several transition metal oxide materials. We report that, for realistic choices
of Hubbard $U$ and Hund's $J$ parameters, LSDA+$U$ and LDA+$U$ calculations
result in different values of the magnetic exchange constants and band gap. The
dependence of the band gap on the magnetic configuration is stronger in LDA+$U$
than in LSDA+$U$ and we argue that this is the main reason why the
configuration dependence of the $J_{ij}$'s is found to be systematically more
pronounced in LDA+$U$ than in LSDA+$U$ calculations. We report a very good
correspondence between the computed total energies and the parameterized
Heisenberg model for LDA+$U$ calculations, but not for LSDA+$U$, suggesting
that LDA+$U$ is a more appropriate method for estimating exchange interactions.


  Mosaic crystals, with their high integrated reflectivities, are
widely-employed in spectrometers used to diagnose high energy density systems.
X-ray Thomson scattering (XRTS) has emerged as a powerful diagnostic tool of
these systems, providing in principle direct access to important properties
such as the temperature via detailed balance. However, the measured XRTS
spectrum is broadened by the spectrometer instrument function (IF), and without
careful consideration of the IF one risks misdiagnosing system conditions.
Here, we consider in detail the IF of mosaic crystals and how the broadening
varies across the spectrometer. Notably, we find a strong asymmetry in the
shape of the IF towards higher energies. As an example, we consider the effect
on the inferred temperature, and find that it can be overestimated if an
approximate symmetric IF is used. We therefore expect a detailed consideration
of the full IF will have an important impact on system properties inferred via
XRTS in both forward modelling and model-free approaches.


  We discuss systematically the fermion mass and mixing matrices in a generic
\linebreak field-theoretical flipped $SU(5)$ model, with particular
applications to neutrino and baryon number-changing physics. We demonstrate
that the different quark flavour branching ratios in proton decay are related
to the Cabibbo-Kobayashi-Maskawa angles, whereas the lepton flavour branching
ratios are undetermined. The light neutrino mixing angles observable via
oscillation effects are related to the heavy conjugate (right-handed) neutrino
mass matrix, which also plays a key role in cosmological baryogenesis. The
ratios of neutrino and charged lepton decay modes in baryon decay may also be
related to neutrino oscillation parameters. Plausible Ans\"atze for the
generation structure of coupling matrices motivate additional relations between
physical observables, and yield a satisfactory baryon asymmetry.


  The problem of distributed optimization requires a group of networked agents
to compute a parameter that minimizes the average of their local cost
functions. While there are a variety of distributed optimization algorithms
that can solve this problem, they are typically vulnerable to "Byzantine"
agents that do not follow the algorithm. Recent attempts to address this issue
focus on single dimensional functions, or assume certain statistical properties
of the functions at the agents. In this paper, we provide two resilient,
scalable, distributed optimization algorithms for multi-dimensional functions.
Our schemes involve two filters, (1) a distance-based filter and (2) a min-max
filter, which each remove neighborhood states that are extreme (defined
precisely in our algorithms) at each iteration. We show that these algorithms
can mitigate the impact of up to $F$ (unknown) Byzantine agents in the
neighborhood of each regular agent. In particular, we show that if the network
topology satisfies certain conditions, all of the regular agents' states are
guaranteed to converge to a bounded region that contains the minimizer of the
average of the regular agents' functions.