  Sentiment analysis on user reviews helps to keep track of user reactions
towards products, and make advices to users about what to buy. State-of-the-art
review-level sentiment classification techniques could give pretty good
precisions of above 90%. However, current phrase-level sentiment analysis
approaches might only give sentiment polarity labelling precisions of around
70%~80%, which is far from satisfaction and restricts its application in many
practical tasks. In this paper, we focus on the problem of phrase-level
sentiment polarity labelling and attempt to bridge the gap between phrase-level
and review-level sentiment analysis. We investigate the inconsistency between
the numerical star ratings and the sentiment orientation of textual user
reviews. Although they have long been treated as identical, which serves as a
basic assumption in previous work, we find that this assumption is not
necessarily true. We further propose to leverage the results of review-level
sentiment classification to boost the performance of phrase-level polarity
labelling using a novel constrained convex optimization framework. Besides, the
framework is capable of integrating various kinds of information sources and
heuristics, while giving the global optimal solution due to its convexity.
Experimental results on both English and Chinese reviews show that our
framework achieves high labelling precisions of up to 89%, which is a
significant improvement from current approaches.


  The growth rate function $r_N$ counts the number of irreducible
representations of simple complex Lie groups of dimension $N$. While no
explicit formula is known for this function, previous works have found bounds
for $R_N=\sum_{i=1}^Nr_i$. In this paper we improve on previous bounds and show
that $R_N=O(N)$.


  We consider the recently estimated corrections \Delta\dot\varpi to the
Newtonian/Einsteinian secular precessions of the longitudes of perihelia \varpi
of several planets of the Solar System in order to evaluate whether they are
compatible with the predicted precessions due to models of long-range modified
gravity put forth to account for certain features of the rotation curves of
galaxies without resorting to dark matter. In particular, we consider a
logarithmic-type correction and a f(R) inspired power-law modification of the
Newtonian gravitational potential. The results obtained by taking the ratio of
the apsidal rates for different pairs of planets show that the modifications of
the Newtonian potentials examined in this paper are not compatible with the
secular extra-precessions of the perihelia of the Solar System's planets
estimated by E.V. Pitjeva as solve-for parameters processing almost one century
of data with the latest EPM ephemerides.


  We investigate geodesics in non-homogeneous vacuum pp-wave solutions and
demonstrate their chaotic behavior by rigorous analytic and numerical methods.
For the particular class of solutions considered, distinct "outcomes" (channels
to infinity) are identified, and it is shown that the boundary between
different outcomes has a fractal structure. This seems to be the first example
of chaos in exact radiative spacetimes.


  We consider quasilinear parabolic equations with measurable coefficients when
the right-hand side is a signed Radon measure with finite total mass, having
$p$-Laplace type: $$u_t - \textrm{div} \, \mathbf{a}(Du,x,t) = \mu \quad
\textrm{in} \ \Omega \times (0,T) \subset \mathbb{R}^n \times \mathbb{R}.$$ In
the singular range $\frac{2n}{n+1} <p \le 2-\frac{1}{n+1}$, we establish
regularity estimates for the spatial gradient of solutions in the Marcinkiewicz
spaces, under a suitable density condition of the right-hand side measure.


  Goldstone and Higgs modes have been detected in various condensed matter,
cold atom and particle physics experiments. Here, we demonstrate that the two
modes can also be observed in optical systems with only a few (artificial)
atoms inside a cavity. We establish this connection by studying the $ U(1)/Z_2
$ Dicke model where $ N $ qubits (atoms) coupled to a single photon mode. We
determine the Goldstone and Higgs modes inside the super-radiant phase and
their corresponding spectral weights by performing both $ 1/J=2/N $ expansion
and exact diagonization (ED) study at a finite $ N $. We find nearly perfect
agreements between the results achieved by the two approaches when $ N $ gets
down even to $ N = 2 $. The quantum finite size effects at a few qubits make
the two modes quite robust against an effectively small counter-rotating wave
term. We present a few schemes to reduce the critical coupling strength, so the
two modes can be observed in several experimental systems of (artificial) atoms
inside a cavity by just conventional optical measurements.


  For large $n$ we determine the maximum number of induced 6-cycles which can
be contained in a planar graph on $n$ vertices, and we classify the graphs
which achieve this maximum. In particular we show that the maximum is achieved
by the graph obtained by blowing up three pairwise non-adjacent vertices in a
6-cycle to sets of as even size as possible, and that every extremal example
closely resembles this graph. This extends previous work by the author which
solves the problem for 4-cycles and 5-cycles. The 5-cycle problem was also
solved independently by Ghosh, Gy\H{o}ri, Janzer, Paulos, Salia, and Zamora.


  This note provides an extension of the constructive loop vertex expansion to
stable interactions of arbitrarily high order, opening the way to many
applications. We treat in detail the example of the $(\bar \phi \phi)^p$ field
theory in zero dimension. We find that the important feature to extend the loop
vertex expansion is not to use an intermediate field representation, but rather
to force integration of exactly one particular field per vertex of the initial
action.


  Many theories for the formation of massive black holes in galactic nuclei
predict that the stellar motions should be anisotropic within the radius of
influence of the black hole. We report tentative evidence for such an effect in
M87.


  We consider the problem of the reconstruction of a Schwarz matrix from
exactly one given eigenvalue. This inverse eigenvalue problem leads to the
Jacobi orthogonal polynomials~$\{P_k^{(-n,n)}\}_{k=0}^{n-1}$ that can be
treated as a discrete finite analogue of Bessel polynomials.


  A century ago, Srinivasa Ramanujan -- the great self-taught Indian genius of
mathematics -- died, shortly after returning from Cambridge, UK, where he had
collaborated with Godfrey Hardy. Ramanujan contributed numerous outstanding
results to different branches of mathematics, like analysis and number theory,
with a focus on special functions and series. Here we refer to apparently weird
values which he assigned to two simple divergent series, $\sum_{n \geq 1} n$
and $\sum_{n \geq 1} n^{3}$. These values are sensible, however, as analytic
continuations, which correspond to Riemann's $\zeta$-function. Moreover, they
have applications in physics: we discuss the vacuum energy of the photon field,
from which one can derive the Casimir force, which has been experimentally
measured. We further discuss its interpretation, which remains controversial.
This is a simple way to illustrate the concept of renormalization, which is
vital in quantum field theory.


  We study transport through a ferromagnetic single-electron transistor. The
resistance is represented as a path integral, so that systems where the tunnel
resistances are smaller than the quantum resistance can be investigated. Beyond
the low order sequential tunneling and co-tunneling regimes, a large
magnetoresistance ratio at sufficiently low temperatures is found. In the
opposite limit, when the thermal energy is larger than the charging energy, the
magnetoresistance ratio is only slightly enhanced.


  Information-Centric Networking (ICN) is a recent paradigm that claims to
mitigate some limitations of the current IP-based Internet architecture. The
centerpiece of ICN is named and addressable content, rather than hosts or
interfaces. Content-Centric Networking (CCN) is a prominent ICN instance that
shares the fundamental architectural design with its equally popular academic
sibling Named-Data Networking (NDN). CCN eschews source addresses and creates
one-time virtual circuits for every content request (called an interest). As an
interest is forwarded it creates state in intervening routers and the requested
content back is delivered over the reverse path using that state.
  Although a stateful forwarding plane might be beneficial in terms of
efficiency, and resilience to certain types of attacks, this has not been
decisively proven via realistic experiments. Since keeping per-interest state
complicates router operations and makes the infrastructure susceptible to
router state exhaustion attacks (e.g., there is currently no effective defense
against interest flooding attacks), the value of the stateful forwarding plane
in CCN should be re-examined.
  In this paper, we explore supposed benefits and various problems of the
stateful forwarding plane. We then argue that its benefits are uncertain at
best and it should not be a mandatory CCN feature. To this end, we propose a
new stateless architecture for CCN that provides nearly all functionality of
the stateful design without its headaches. We analyze performance and resource
requirements of the proposed architecture, via experiments.


  The behavior of photons is controlled by quantum mechanics, not as
deterministic as classical optics shows. To this end, we defined a new
statistic $Z$, which is equal to the variance minus the expectation or mean.
Then, we established a statistical model for imaging systems and obtained three
fundamental imaging formulas. Among them, the first formula is entirely
consistent with the classic convolution equation. The second and third ones
link the $Z$ quantities of the object and noise elegantly with the $Z$ image
and covariance image, revealing new laws. Consequently, besides the flux
density, the $Z$ quantity of an object is also imageable, which opens a new
realm for imaging systems to explore the physical world.


  Here we give a definition of regularity on multiprojective spaces which is
different from the definitions of Hoffmann-Wang and Costa-Mir\'o Roig. By using
this notion we prove some splitting criteria for vector bundles.


  Gamma-ray data from the Fermi-Large Area Telescope reveal an unexplained,
apparently diffuse, signal from the Galactic bulge that peaks near 2 GeV with
an approximately spherical intensity profile $\propto r^{-2.4}$ that extends to
angular radial scales of at least 10 degrees, possibly to 20 degrees. The
origin of this "Galactic Centre Excess" (GCE) has been debated with proposed
sources prominently including self-annihilating dark matter and a hitherto
undetected population of millisecond pulsars (MSPs). However, the conventional
channel for the generation of MSPs has been found to predict too many low mass
X-ray binary (LMXB) systems and, because of the expected large natal kicks, may
not accommodate the close spatial correspondence between the GCE signal and
stars in the bulge. Here we report a binary population synthesis forward model
that demonstrates that an MSP population arising from the accretion induced
collapse (AIC) of O-Ne white dwarfs in Galactic bulge binaries can naturally
reproduce the morphology, spectral shape, and intensity of the GCE signal while
also obeying LMXB constraints. Synchrotron emission from MSP-launched cosmic
ray electrons and positrons may simultaneously explain the mysterious,
microwave "haze" from the inner Galaxy


  We derive a non-BPS linear ansatz using the charged Weyl formalism in string
and M-theory backgrounds. Generic solutions are static and axially-symmetric
with an arbitrary number of non-BPS sources corresponding to various brane,
momentum and KKm charges. Regular sources are either four-charge non-extremal
black holes or smooth non-BPS bubbles. We construct several families such as
chains of non-extremal black holes or smooth non-BPS bubbling geometries and
study their physics. The smooth horizonless geometries can have the same mass
and charges as non-extremal black holes. Furthermore, we find examples that
scale towards the four-charge BPS black hole when the non-BPS parameters are
taken to be small, but the horizon is smoothly resolved by adding a small
amount of non-extremality.


  $M$ is a Riemannian, boundaryless, and compact manifold with $\dim M\geq 2$,
and $f$ is a $C^{1+\beta}$ ($\beta>0$) diffeomorphism of $M$. $\varphi$ is a
H\"older continuous potential on $M$. We construct an invariant and absolutely
continuous family of measures (with transformation relations defined by
$\varphi$), which sit on local unstable leaves. We present two main
applications. First, given an ergodic homoclinic class $H_\chi(p)$, we prove
that $\varphi$ admits a local equilibrium state on $H_\chi(p)$ if and only if
$\varphi$ is "recurrent on $H_\chi(p)$" (a condition tested by counting
periodic points), and one of the leaf measures gives a positive measure to a
set of positively recurrent hyperbolic points; and if an equilibrium measure
exists, the said invariant and absolutely continuous family of measures
constitutes as its conditional measures. An immediate corollary is the local
product structure of hyperbolic equilibrium states.
  Second, we prove a Ledrappier-Young property for hyperbolic equilibrium
states -- if $\varphi$ admits a conformal family of leaf measures, and a
hyperbolic local equilibrium state, then the leaf measures of the invariant
family (respective to $\varphi$) are equivalent to the conformal measures (on a
full measure set). This extends the celebrated result by Ledrappier and Young
for hyperbolic SRB measures, which states that a hyperbolic equilibrium state
of the geometric potential (with pressure 0) has conditional measures on local
unstable leaves which are absolutely continuous w.r.t the Riemannian volume of
these leaves.


  Protein structures are much more conserved than sequences during evolution.
Based on this observation, we investigate the consequences of structural
conservation on protein evolution. We study seven of the most studied protein
folds, finding out that an extended neutral network in sequence space is
associated to each of them. Within our model, neutral evolution leads to a
non-Poissonian substitution process, due to the broad distribution of
connectivities in neutral networks. The observation that the substitution
process has non-Poissonian statistics has been used against the original
Kimura's neutral theory, while our model shows that this is a generic property
of neutral evolution with structural conservation. Our model also predicts that
the substitution rate can strongly fluctuate from one branch to another of the
evolutionary tree. The average sequence similarity within a neutral network is
close to the threshold of randomness, as observed for families of sequences
sharing the same fold. Nevertheless, some positions are more difficult to
mutate than others. We compare such structurally conserved positions to
positions conserved in protein evolution, suggesting that our model can be a
valuable tool to distinguish structural from functional conservation in
databases of protein families. These results indicate that a synergy between
database analysis and structurally-based computational studies can increase our
understanding of protein evolution.


  Given a torus bundle $Y$ over the circle and a cohomology class $[\omega]\in
H^2(Y;\mathbb{Z})$ which evaluates nontrivially on the fiber, we compute the
Heegaard Floer homology of $Y$ with twisted coefficients in the universal
Novikov ring.


  We present Rico, a code designed to compute the ionization fraction of the
Universe during the epoch of hydrogen and helium recombination with an
unprecedented combination of speed and accuracy. This is accomplished by
training the machine learning code Pico on the calculations of a multi-level
cosmological recombination code which self-consistently includes several
physical processes that were neglected previously. After training, Rico is used
to fit the free electron fraction as a function of the cosmological parameters.
While, for example at low redshifts (z<~900), much of the net change in the
ionization fraction can be captured by lowering the hydrogen fudge factor in
Recfast by about 3%, Rico provides a means of effectively using the accurate
ionization history of the full recombination code in the standard cosmological
parameter estimation framework without the need to add new or refined fudge
factors or functions to a simple recombination model. Within the new approach
presented here it is easy to update Rico whenever a more accurate full
recombination code becomes available. Once trained, Rico computes the
cosmological ionization history with negligible fitting error in ~10
milliseconds, a speed-up of at least 10^6 over the full recombination code that
was used here. Also Rico is able to reproduce the ionization history of the
full code to a level well below 0.1%, thereby ensuring that the theoretical
power spectra of CMB fluctuations can be computed to sufficient accuracy and
speed for analysis from upcoming CMB experiments like Planck. Furthermore it
will enable cross-checking different recombination codes across cosmological
parameter space, a comparison that will be very important in order to assure
the accurate interpretation of future cosmic microwave background data.


  A bipartite graph is chordal bipartite if every cycle of length at least six
has a chord in it. M$\ddot{\rm u}$ller \cite {muller1996Hamiltonian} has shown
that the Hamiltonian cycle problem is NP-complete on chordal bipartite graphs
by presenting a polynomial-time reduction from the satisfiability problem. The
microscopic view of the reduction instances reveals that the instances are
$P_9$-free chordal bipartite graphs, and hence the status of Hamiltonicity in
$P_8$-free chordal bipartite graphs is open. In this paper, we identify the
first non-trivial subclass of $P_8$-free chordal bipartite graphs which is
$P_5$-free chordal bipartite graphs, and present structural and algorithmic
results on $P_5$-free chordal bipartite graphs. We investigate the structure of
$P_5$-free chordal bipartite graphs and show that these graphs have a {\em
Nested Neighborhood Ordering (NNO)}, a special ordering among its vertices.
Further, using this ordering, we present polynomial-time algorithms for
classical problems such as the Hamiltonian cycle (path), also the variants and
generalizations of the Hamiltonian cycle (path) problem. We also obtain
polynomial-time algorithms for treewidth (pathwidth), and minimum fill-in in
$P_5$-free chordal bipartite graph. We also present some results on complement
graphs of $P_5$-free chordal bipartite graphs.


  Purpose: Most studies evaluating artificial intelligence (AI) models that
detect abnormalities in neuroimaging are either tested on unrepresentative
patient cohorts or are insufficiently well-validated, leading to poor
generalisability to real-world tasks. The aim was to determine the diagnostic
test accuracy and summarise the evidence supporting the use of AI models
performing first-line, high-volume neuroimaging tasks.
  Methods: Medline, Embase, Cochrane library and Web of Science were searched
until September 2021 for studies that temporally or externally validated AI
capable of detecting abnormalities in first-line CT or MR neuroimaging. A
bivariate random-effects model was used for meta-analysis where appropriate.
PROSPERO: CRD42021269563.
  Results: Only 16 studies were eligible for inclusion. Included studies were
not compromised by unrepresentative datasets or inadequate validation
methodology. Direct comparison with radiologists was available in 4/16 studies.
15/16 had a high risk of bias. Meta-analysis was only suitable for intracranial
haemorrhage detection in CT imaging (10/16 studies), where AI systems had a
pooled sensitivity and specificity 0.90 (95% CI 0.85 - 0.94) and 0.90 (95% CI
0.83 - 0.95) respectively. Other AI studies using CT and MRI detected target
conditions other than haemorrhage (2/16), or multiple target conditions (4/16).
Only 3/16 studies implemented AI in clinical pathways, either for pre-read
triage or as post-read discrepancy identifiers.
  Conclusion: The paucity of eligible studies reflects that most abnormality
detection AI studies were not adequately validated in representative clinical
cohorts. The few studies describing how abnormality detection AI could impact
patients and clinicians did not explore the full ramifications of clinical
implementation.


  We study the effect of resetting on diffusion in a logarithmic potential. In
this model, a particle diffusing in a potential $U(x) = U_0\log|x|$ is reset,
i.e., taken back to its initial position, with a constant rate $r$. We show
that this analytically tractable model system exhibits a series of phase
transitions as a function of a single parameter, $\beta U_0$, the ratio of the
strength of the potential to the thermal energy. For $\beta U_0<-1$ the
potential is strongly repulsive, preventing the particle from reaching the
origin. Resetting then generates a non-equilibrium steady state which is
characterized exactly and thoroughly analyzed. In contrast, for $\beta U_0>-1$
the potential is either weakly repulsive or attractive and the diffusing
particle eventually reaches the origin. In this case, we provide a closed form
expression for the subsequent first-passage time distribution and show that a
resetting transition occurs at $\beta U_0=5$. Namely, we find that resetting
can expedite arrival to the origin when $-1<\beta U_0<5$, but not when $\beta
U_0>5$. The results presented herein generalize results for simple diffusion
with resetting -- a widely applicable model that is obtained from ours by
setting $U_0=0$. Extending to general potential strengths, our work opens the
door to theoretical and experimental investigation of a plethora of problems
that bring together resetting and diffusion in logarithmic potential.


  We present some initial results from a case study in social media data
harvesting and visualization utilizing the tools and analytical features of
NodeXL applied to a degree asymmetric vertex graph set. We consider twitter
graphs harvested for topics related to suicidal ideation, suicide attempts,
self-harm and bullycide. While the twitter-sphere only captures a small and age
biased sample of communications it is a readily available public database for a
wealth of rich topics yielding a large sample set. All these topics gave rise
to highly asymmetric vertex degree graphs and all shared the same general
topological features. We find a strong preference for in degree vertex
information transfer with a 4:25 out degree to in degree vertex ratio with a
power law distribution. Overall there is a low global clustering coefficient
average of 0.038 and a graph clustering density of 0.00034 for
Clauset-Newman-Moore grouping with a maximum geodesic distance of 6.
Eigenvector centrality does not give any large central impact vertices and
betweenness centrality shows many bridging vertices indicating a sparse
community structure. Parts of speech sentiment scores show a strong asymmetry
of predominant negative scores for almost all word and word pairs with salience
greater than one. We used an Hoaxy analysis to check for deliberate
misinformation on these topics by a Twitter-Bot.


  In applications, such as biomedicine and systems/synthetic biology, technical
limitations in actuation complicate implementation of time-varying control
signals. In order to alleviate some of these limitations, it may be desirable
to derive simple control policies, such as step functions with fixed magnitude
and length (or temporal pulses). In this technical note, we further develop a
recently proposed pulse-based solution to the convergence problem, i.e.,
minimizing the convergence time to the target exponentially stable equilibrium,
for monotone systems. In particular, we extend this solution to monotone
systems with parametric uncertainty. Our solutions also provide worst-case
estimates on convergence times. Furthermore, we indicate how our tools can be
used for a class of non-monotone systems, and more importantly how these tools
can be extended to other control problems. We illustrate our approach on
switching under parametric uncertainty and regulation around a saddle point
problems in a genetic toggle switch system.


  Added value can be extracted from event logs generated by business processes
in various ways. However, although complex computations can be performed over
event logs, the result of such computations is often difficult to explain; in
particular, it is hard to determine what parts of an input log actually matters
in the production of that result. This paper describes how an existing log
processing library, called BeepBeep, can be extended in order to provide a form
of provenance: individual output events produced by a query can be precisely
traced back to the data elements of the log that contribute to (i.e. "explain")
the result.


  Neutron stars undergoing r-mode oscillation emit gravitational radiation that
might be detected on earth. For known millisecond pulsars the observed spindown
rate imposes an upper limit on the possible gravitational wave signal of these
sources. Taking into account the physics of r-mode evolution, we show that only
sources spinning at frequencies above a few hundred Hertz can be unstable to
r-modes, and we derive a more stringent universal r-mode spindown limit on
their gravitational wave signal, exploiting the fact that the r-mode saturation
amplitude is insensitive to the structural properties of individual sources. We
find that this refined bound limits the gravitational wave strain from
millisecond pulsars to values below the detection sensitivity of
next-generation detectors. Young sources are therefore a more promising option
for the detection of gravitational waves emitted by r-modes and to probe the
interior composition of compact stars in the near future.


  The current-voltage characteristics of long and narrow superconducting
channels are investigated using the time-dependent Ginzburg-Landau equations
for complex order parameter. We found out that the steps in the current voltage
characteristic can be associated with bifurcations of either steady or
oscillatory solution. We revealed typical instabilities which induced the
singularities in current-voltage characteristics, and analytically estimated
period of oscillations and average voltage in the vicinity of the critical
currents. Our results show that these bifurcations can substantially complicate
dynamics of the order parameter and eventually lead to appearance of such
phenomena as multistability and chaos. The discussed bifurcation phenomena
sheds a light on some recent experimental findings.


  Recent findings suggest that wall-bounded turbulent flow can take different
statistically stationary turbulent states, with different transport properties,
even for the very same values of the control parameters. What state the system
takes depends on the initial conditions. Here we analyze the multiple states in
large-aspect ratio ($\Gamma$) two-dimensional turbulent Rayleigh--B\'enard flow
with no-slip plates and horizontally periodic boundary conditions as model
system. We determine the number $n$ of convection rolls, their mean aspect
ratios $\Gamma_r = \Gamma /n$, and the corresponding transport properties of
the flow (i.e., the Nusselt number $Nu$), as function of the control parameters
Rayleigh ($Ra$) and Prandtl number. The effective scaling exponent $\beta$ in
$Nu \sim Ra^\beta$ is found to depend on the realized state and thus
$\Gamma_r$, with a larger value for the smaller $\Gamma_r$. By making use of a
generalized Friedrichs inequality, we show that the elliptical instability and
viscous damping determine the $\Gamma_r$-window for the realizable turbulent
states. The theoretical results are in excellent agreement with our numerical
finding $2/3 \le \Gamma_r \le 4/3$, where the lower threshold is approached for
the larger $Ra$. Finally, we show that the theoretical approach to frame
$\Gamma_r$ also works for free-slip boundary conditions.


  Mixed-morphology supernova remnants (MMSNRs) are characterized by a
shell-like morphology in the radio and centrally-peaked thermal emission in the
X-ray band. The nature of this peculiar class of supernova remnants (SNRs)
remains a controversial issue. In this work, by pairing the predictions of
stellar evolution theory with two-dimensional hydrodynamic simulations we show
that the mixed morphology properties of a SNR can arise by the interaction of
the SNR with the circumstellar medium shaped by a red supergiant progenitor
star, embedded in a dense environment. As a study case, we model the
circumstellar medium formation and the subsequent interaction of the SNR with
it of a $15~\rm M_{\odot}$ progenitor star. The reflected shock, formed by the
collision of the SNR with the density walls of the surrounding circumstellar
cavity, accumulates and re-shocks the supernova ejecta at the center of the
remnant, increasing its temperature so that the gas becomes X-ray bright. Such
a formation mechanism may naturally explain the nature of MMSNRs resulted from
Type II supernovae without the demand of additional physical mechanisms and/or
ambient medium inhomogeneities. We discuss alternative evolutionary paths that
potentially could be ascribed for the MMSNR formation within the framework of
the reflected shock model.


  In this work we use classical electromagnetism to analyse a three-phase
induction motor. We first cast the motor as a boundary value problem involving
two phenomenological time-constants. These are derived from the widely used
equivalent circuit model of the induction motor. We then use an iterative
procedure to evaluate these constants and obtain the motor performance
equations. Our results depend only on the geometrical parameters of the motor
and can be used to derive precise expressions for the excitation frequency and
applied voltage needed to extract maximum performance from a given motor at any
rotation speed.


  In recent years, talking head generation has become a focal point for
researchers. Considerable effort is being made to refine lip-sync motion,
capture expressive facial expressions, generate natural head poses, and achieve
high video quality. However, no single model has yet achieved equivalence
across all these metrics. This paper aims to animate a 3D face using Jamba, a
hybrid Transformers-Mamba model. Mamba, a pioneering Structured State Space
Model (SSM) architecture, was designed to address the constraints of the
conventional Transformer architecture. Nevertheless, it has several drawbacks.
Jamba merges the advantages of both Transformer and Mamba approaches, providing
a holistic solution. Based on the foundational Jamba block, we present
JambaTalk to enhance motion variety and speed through multimodal integration.
Extensive experiments reveal that our method achieves performance comparable or
superior to state-of-the-art models.


  We present an exactly solvable model of a scalar field in an AdS$_{d+1}$ like
background interpolating between a $Z_2$ preserving and a $Z_2$ breaking minima
of the potential. We define its holographic dual through the AdS/CFT dictionary
and argue that at zero temperature the $d-$dimensional strongly coupled system
on the boundary of AdS$_{d+1}$ exhibits a phase with a spontaneously broken
discrete symmetry. In the presence of a black hole in the bulk ($T\neq 0$) we
find that, although the metastable phase is present, the discrete symmetry gets
restored. We compute exactly the lowest order boundary correlation functions in
the spontaneously broken phase at T=0, finding out a pole of the propagator for
zero momenta that signals the presence of a massless mode.


  We comment on the results of a complete leading-twist next-to-leading order
QCD analysis of the spacelike pion electromagnetic form factor at
large-momentum transfer Q. For the asymptotic distribution amplitude, we have
examined the sensitivity of the predictions to the choice of the
renormalization scale. The results show that reliable perturbative predictions
for the pion electromagnetic form factor can already be made at a momentum
transfer Q below 10 GeV.


  Multi-sensor fusion of multi-modal measurements from commodity inertial,
visual and LiDAR sensors to provide robust and accurate 6DOF pose estimation
holds great potential in robotics and beyond. In this paper, building upon our
prior work (i.e., LIC-Fusion), we develop a sliding-window filter based
LiDAR-Inertial-Camera odometry with online spatiotemporal calibration (i.e.,
LIC-Fusion 2.0), which introduces a novel sliding-window plane-feature tracking
for efficiently processing 3D LiDAR point clouds. In particular, after motion
compensation for LiDAR points by leveraging IMU data, low-curvature planar
points are extracted and tracked across the sliding window. A novel outlier
rejection criterion is proposed in the plane-feature tracking for high-quality
data association. Only the tracked planar points belonging to the same plane
will be used for plane initialization, which makes the plane extraction
efficient and robust. Moreover, we perform the observability analysis for the
LiDAR-IMU subsystem and report the degenerate cases for spatiotemporal
calibration using plane features. While the estimation consistency and
identified degenerate motions are validated in Monte-Carlo simulations,
different real-world experiments are also conducted to show that the proposed
LIC-Fusion 2.0 outperforms its predecessor and other state-of-the-art methods.


  Inspired by the Galerkin and particular method, a new approximation approach
is recalled in the Cartesian case. In this paper, we are interested specially
by constructing this method, when the domain of consideration is a two
dimensional ball, to extend this work to the several dimension. We reduce the
number of iterations to calculate integrals and numerical solution of Poisson
and the Heat problems (elliptic nd parabolic PDEs), in a very fast way.


  The irradiation represents a useful tool for determining the characteristics
of defects in semiconductors as well as a method to evaluate their degradation,
fact with important technological consequences. In this contribution, starting
from available data on the degradation of silicon detector characteristics in
radiation fields, these effects are explained in the frame of a model that
supposes also the production of the SiFFCD defect due to irradiation. The
displacement threshold energies - different for different crystallographic
axes, considered as parameters of the model, are established and the results
obtained could contribute to clarify these controversial aspects. Predictions
of the degradation of electrical parameters (leakage current, effective carrier
concentration and effective trapping probabilities for electrons and holes) of
DOFZ silicon detectors in the hadron background of the LHC accelerator,
supposing operation at -10 grdC are done. The non uniformity of the rate of
production of primary defects and of complexes, as a function of depth, for
incident particles with low kinetic energy was obtained by simulations in some
particular and very simplifying assumptions, suggesting the possible important
contribution of the low energy component of the background spectra to detector
degradation.


  We report equations of motion for the occupation numbers of natural spin
orbitals and show that adiabatic extensions of common functionals employed in
ground-state reduced-density-matrix-functional theory have the shortcoming of
leading always to occupation numbers which are independent of time. We
illustrate the exact time-dependence of the natural spin orbitals and
occupation numbers for the case of electron-ion scattering and for atoms in
strong laser fields. In the latter case, we observe strong variations of the
occupation numbers in time.


  The Cabibbo-Kobayashi-Maskawa matrix element |V_ub| can be extracted from the
rate for the semi-leptonic decay B -> pi + l + antineutrino_l, with little
theoretical uncertainty, provided the hadronic form factor for the B -> pi
transition can be measured from some other B decay. In here, we suggest using
the decay B -> pi J\psi. This is a color suppressed decay, and it cannot be
properly described within the usual factorization approximation; we use instead
a simple and very general phenomenological model for the b d J\psi vertex. In
order to relate the hadronic form factors in the B -> pi J\psi and B -> pi + l
+ antineutrino_l decays, we use form factor relations that hold for
heavy-to-light transitions at large recoil.


  An important goal in reinforcement learning is to create agents that can
quickly adapt to new goals while avoiding situations that might cause damage to
themselves or their environments. One way agents learn is through exploration
mechanisms, which are needed to discover new policies. However, in deep
reinforcement learning, exploration is normally done by injecting noise in the
action space. While performing well in many domains, this setup has the
inherent risk that the noisy actions performed by the agent lead to unsafe
states in the environment. Here we introduce a novel approach called
Meta-Learned Instinctual Networks (MLIN) that allows agents to safely learn
during their lifetime while avoiding potentially hazardous states. At the core
of the approach is a plastic network trained through reinforcement learning and
an evolved "instinctual" network, which does not change during the agent's
lifetime but can modulate the noisy output of the plastic network. We test our
idea on a simple 2D navigation task with no-go zones, in which the agent has to
learn to approach new targets during deployment. MLIN outperforms standard
meta-trained networks and allows agents to learn to navigate to new targets
without colliding with any of the no-go zones. These results suggest that
meta-learning augmented with an instinctual network is a promising new approach
for safe AI, which may enable progress in this area on a variety of different
domains.


  We study the Hilbert space of the Class 5 model described in
arXiv:1904.12005. Despite being integrable, neither its transfer matrix nor its
Hamiltonian are diagonalisable, meaning that the usual Algebraic Bethe Ansatz
does not provide the full Hilbert space. Instead, we make use of the symmetries
of the model to construct the Jordan blocks of the transfer matrix. We also
show that the Hamiltonian and the transfer matrix, despite commuting, do not
have the same Jordan block structure.


  A lift-and-permute scheme of alternating direction method of multipliers
(ADMM) is proposed for linearly constrained convex programming. It contains not
only the newly developed balanced augmented Lagrangian method and its
dual-primal variation, but also the proximal ADMM and Douglas-Rachford
splitting algorithm. It helps to propose accelerated algorithms with worst-case
$O(1/k^2)$ convergence rates in the case that the objective function to be
minimized is strongly convex.


  The method for quantization of constrained theories that was suggested
originally by Faddeev and Jackiw along with later modifications is discussed.
The particular emphasis of this paper is to show how it is simple to implement
their method within the path integral framework using the natural geometric
structure that their method utilizes. The procedure is exemplified with the
analysis of two models: a quantum mechanical particle constrained to a surface
(of which the hypersphere is a special case), and a quantized Schr\"odinger
field interacting with a quantized vector field for both the massive and the
massless cases. The results are shown to agree with what is found using the
Dirac method for constrained path integrals. We comment on a previous path
integral analysis of the Faddeev-Jackiw method. We also discuss why a previous
criticism of the Faddeev-Jackiw method is unfounded and why suggested
modifications of their method are unnecessary.


  We study the characteristics of galaxy protoclusters using the latest
L-galaxies semi-analytic model. Searching for protoclusters on a scale of $\sim
10 \, \mathrm{cMpc}$ gives an excellent compromise between the completeness and
purity of their galaxy populations, leads to high distinction from the field in
overdensity space, and allows accurate determination of the descendant cluster
mass. This scale is valid over a range of redshifts and selection criteria. We
present a procedure for estimating, given a measured galaxy overdensity, the
protocluster probability and its descendant cluster mass for a range of
modelling assumptions, particularly taking into account the shape of the
measurement aperture. This procedure produces lower protocluster probabilities
compared to previous estimates using fixed size apertures. The relationship
between AGN and protoclusters is also investigated, and shows significant
evolution with redshift; at $z \sim 2$ the fraction of protoclusters traced by
AGN is high, but the fraction of all AGN in protoclusters is low, whereas at $z
\geqslant 5$ the fraction of protoclusters containing AGN is low, but most AGN
are in protoclusters. We also find indirect evidence for the emergence of a
passive sequence in protoclusters at $z \sim 2$, and note that a significant
fraction of all galaxies reside in protoclusters at $z \geqslant 2$,
particularly the most massive.


  In this paper we study the complexity of the problems: given a loop,
described by linear constraints over a finite set of variables, is there a
linear or lexicographical-linear ranking function for this loop? While
existence of such functions implies termination, these problems are not
equivalent to termination. When the variables range over the rationals (or
reals), it is known that both problems are PTIME decidable. However, when they
range over the integers, whether for single-path or multipath loops, the
complexity has not yet been determined. We show that both problems are
coNP-complete. However, we point out some special cases of importance of PTIME
complexity. We also present complete algorithms for synthesizing linear and
lexicographical-linear ranking functions, both for the general case and the
special PTIME cases. Moreover, in the rational setting, our algorithm for
synthesizing lexicographical-linear ranking functions extends existing ones,
because our class of ranking functions is more general, yet it has polynomial
time complexity.


  Object navigation tasks require agents to locate specific objects in unknown
environments based on visual information. Previously, graph convolutions were
used to implicitly explore the relationships between objects. However, due to
differences in visibility among objects, it is easy to generate biases in
object attention. Thus, in this paper, we propose a directed object attention
(DOA) graph to guide the agent in explicitly learning the attention
relationships between objects, thereby reducing the object attention bias. In
particular, we use the DOA graph to perform unbiased adaptive object attention
(UAOA) on the object features and unbiased adaptive image attention (UAIA) on
the raw images, respectively. To distinguish features in different branches, a
concise adaptive branch energy distribution (ABED) method is proposed. We
assess our methods on the AI2-Thor dataset. Compared with the state-of-the-art
(SOTA) method, our method reports 7.4%, 8.1% and 17.6% increase in success rate
(SR), success weighted by path length (SPL) and success weighted by action
efficiency (SAE), respectively.


  OptControl.jl(OptControl) implements that modeling optimal control problems
with symbolic algebra system based on Julia language, and generates the
corresponding numerical optimization codes to solve them with packages from
Julia. OptControl does not define a data type, but generates a solution script
by handling Julia strings and runs the script automatically. It also provides
an interface to save script files. Meanwhile, OptControl supports
component-based modeling, which makes it easy to build the optimal control
problem of complex systems. All of OptControl's dependency packages come from
ecosystem of Julia.


  If a closed 3-manifold M supports a closed, nonsingular, irrational 1-form
which linearly deforms into contact forms, then M supports a K-contact form. On
the 3-torus, a closed nonsingular 1-form deforms linearly into contact forms if
and only if it is a fibration 1-form. on any other 2-torus bundle over the
circle, every closed, nonsingular 1-form deforms linearly into contact forms.


  We study the emergence of information integration in cellular automata (CA)
with respect to states in the long run. Information integration is in this case
quantified by applying the information-theoretic measure known as total
correlation to the long-run distribution of CA states. Total correlation is the
amount by which the total uncertainty associated with cell states surpasses the
uncertainty of the CA state taken as a whole. It is an emergent property, in
the sense that it can only be ascribed to how the cells interact with one
another, and has been linked to the rise of consciousness in the brain. We
investigate total correlation in the evolution of elementary CA for all update
rules that are unique with respect to negation or reflection. For each rule we
consider the usual, deterministic CA behavior, assuming that the initial state
is chosen uniformly at random, and also the probabilistic variant in which
every cell, at all time steps and independently of all others, disobeys the
rule's prescription with a fixed probability. We have found rules that generate
as much total correlation as possible, or nearly so, particularly in Wolfram
classes 2 and 3. We conjecture that some of these rules can be used as CA
models of information integration.


  Parkinson disease is a very common neurodegenerative disorder. Patients
usually undergo destruction of substantia nigra to develop typical symptoms
such as resting tremor, hypokinesia, and rigidity. However, the exact mechanism
of Parkinson disease is still unknown, so it is called idiopathic Parkinsonism.
According to my microarray analysis of peripheral blood leukocytes and
substantia nigra brain tissue, I propose that Parkinson disease is actually a
TH17 dominant autoimmune disease. Based on the microarray data in substantia
nigra, HSP40, HSP70, HSP90, HSP27, HSP105, TLR5, TLR7, CEBPB, CEBPG, FOS, and
caspase1 are significantly up-regulated. In peripheral leukocytes, NFKB1A,
CEBPD, FOS, retinoic receptor alpha, suppressor of IKK epsilon, S100A11, G-CSF,
MMP9, IL-1 receptor, IL-8 receptor, TNF receptor, caspase8, c1q receptor,
cathepsin Z, HLA-G, complement receptor1, and complement 5a receptor. General
immune related genes are also up-regulated including ILF2, CD22, CD3E, BLNK,
ILF3, TCR alpha, TCR zeta, TCR delta, LAT, ITK, Ly9, and BANK1. The autoantigen
is mainly alpha-synuclein. After knowing the exact disease pathophysiology, we
can develop better drugs to prevent or control the detrimental disorder.


  We present a scheduler that improves cluster utilization and job completion
times by packing tasks having multi-resource requirements and
inter-dependencies. While the problem is algorithmically very hard, we achieve
near-optimality on the job DAGs that appear in production clusters at a large
enterprise and in benchmarks such as TPC-DS. A key insight is that carefully
handling the long-running tasks and those with tough-to-pack resource needs
will produce good-enough schedules. However, which subset of tasks to treat
carefully is not clear (and intractable to discover). Hence, we offer a search
procedure that evaluates various possibilities and outputs a preferred schedule
order over tasks. An online component enforces the schedule orders desired by
the various jobs running on the cluster. In addition, it packs tasks, overbooks
the fungible resources and guarantees bounded unfairness for a variety of
desirable fairness schemes. Relative to the state-of-the art schedulers, we
speed up 50% of the jobs by over 30% each.


  A balanced ratio of ocean to land is believed to be essential for an
Earth-like biosphere and one may conjecture that plate-tectonics planets should
be similar in geological properties. After all, the volume of continental crust
evolves towards an equilibrium between production and erosion. If the interior
thermal states of Earth-sized exoplanets are similar to the Earth's, one might
expect a similar equilibrium between continental production and erosion to
establish and, hence, a similar land fraction. We will show that this
conjecture is not likely to be true. Positive feedback associated with the
coupled mantle water - continental crust cycle may rather lead to a manifold of
three possible planets, depending on their early history: a land planet, an
ocean planet and a balanced Earth-like planet. In addition, thermal blanketing
of the interior by the continents enhances the sensitivity of continental
growth to its history and, eventually, to initial conditions. Much of the
blanketing effect is however compensated by mantle depletion in radioactive
elements. A model of the long-term carbonate-silicate cycle shows the land and
the ocean planet to differ by about 5 K in average surface temperature. A
larger continental surface fraction results both in higher weathering rates and
enhanced outgassing, partly compensating each other. Still, the land planet is
expected to have a substantially dryer, colder and harsher climate possibly
with extended cold deserts in comparison with the ocean planet and with the
present-day Earth. Using a model of balancing water availability and nutrients
from continental crust weathering, we find the bioproductivity and the biomass
of both the land and ocean planet to be reduced by a third to half of Earth's.
The biosphere on these planets might not be substantial enough to produce a
supply of free oxygen.


  Femtolensing of gamma ray bursts (GRBs) has been put forward as an exciting
possibility to probe exotic astrophysical objects with masses below $10^{-13}$
solar masses such as small primordial black holes or ultra-compact dark matter
minihalos, made up for instance of QCD axions. In this paper we critically
review this idea, properly taking into account the extended nature of the
source as well as wave optics effects. We demonstrate that most GRBs are
inappropriate for femtolensing searches due to their large sizes. This removes
the previous femtolensing bounds on primordial black holes, implying that vast
regions of parameter space for primordial black hole dark matter are not
robustly constrained. Still, we entertain the possibility that a small fraction
of GRBs, characterized by fast variability can have smaller sizes and be
useful. However, a large number of such bursts would need to be observed to
achieve meaningful constraints. We study the sensitivity of future observations
as a function of the number of detected GRBs and of the size of the emission
region.


  We determine the first homology group with coefficients in
$H_1(N;\mathbb{Z})$ for various mapping class groups of a non--orientable
surface $N$ with punctures and/or boundary.


  Timing systems based on Analog-to-Digital Converters are widely used in the
design of previous high energy physics detectors. In this paper, we propose a
new method based on deep learning to extract the time information from a finite
set of ADC samples. Firstly, a quantitative analysis of the traditional curve
fitting method regarding three kinds of variations (long-term drift, short-term
change and random noise) is presented with simulation illustrations. Next, a
comparative study between curve fitting and the neural networks is made to
demonstrate the potential of deep learning in this problem. Simulations show
that the dedicated network architecture can greatly suppress the noise RMS and
improve timing resolution in non-ideal conditions. Finally, experiments are
performed with the ALICE PHOS FEE card. The performance of our method is more
than 20% better than curve fitting in the experimental condition.


  The structure of the Fe3O4(110)-(1x3) surface was studied with scanning
tunneling microscopy (STM), low-energy electron diffraction (LEED), and
reflection high energy electron diffraction (RHEED). The so-called
one-dimensional reconstruction is characterised by bright rows that extend
hundreds of nanometers in the [1-10] direction and have a periodicity of 2.52
nm in [001] in STM. It is concluded that this reconstruction is the result of a
periodic faceting to expose {111}-type planes with a lower surface energy.


  We study active run-and-tumble particles with an additional two-state
internal variable characterizing their motile or non-motile state. Motile
particles change irreversibly into non-motile ones upon collision with a
non-motile particle. The system evolves towards an absorbing state where all
particles are non-motile. We initialize the system with one non-motile
particles in a bath of motile ones and study numerically the kinetics of
relaxation to absorbing state and its structure as function of the density of
the initial bath of motile particles and of their tumbling rate. We find a
crossover from fractal aggregates at low density to homogeneous ones at high
density. The persistence of single-particle dynamics as quantified by the
tumbling rate pushes this crossover to higher density and can be used to tune
the porosity of the aggregate. At the lowest density the fractal dimension of
the aggregate approaches that obtained in single-particle diffusion limited
aggregation. Our results could be exploited for the design of structures of
desired porosity. The model is a first step towards the study of the collective
dynamics of active particles that can exchange biological information.


  The temperature dependence of the hydrodynamic boundary condition between a
PDMS melt and two different non-attractive surfaces made of either an OTS
(octadecyltrichlorosilane) self-assembled monolayer (SAM) or a grafted layer of
short PDMS chains has been characterized. A slip length proportional to the
fluid viscosity is observed on both surfaces. The slip temperature dependence
is deeply influenced by the surfaces. The viscous stress exerted by the polymer
liquid on the surface is observed to follow exactly the same temperature
dependences as the friction stress of a cross-linked elastomer sliding on the
same surfaces. Far above the glass transition temperature, these observations
are rationalized in the framework of a molecular model based on activation
energies: increase or decrease of the slip length with increasing temperatures
can be observed depending on how the activation energy of the bulk viscosity
compares to that of the interfacial Navier's friction coefficient.


  Signatures of photon localization are observed in a constellation of
transport phenomena which reflect the transition from diffusive to localized
waves. The dimensionless conductance, g, and the ratio of the typical spectral
width and spacing of quasimodes, \delta, are key indicators of electronic and
classical wave localization when inelastic processes are absent. However, these
can no longer serve as localization parameters in absorbing samples since the
affect of absorption depends upon the length of the trajectories of partial
waves traversing the sample, which are superposed to create the scattered
field. A robust determination of localization in the presence of absorption is
found, however, in steady-state measurements of the statistics of radiation
transmitted through random samples. This is captured in a single parameter, the
variance of the total transmission normalized to its ensemble average value,
which is equal to the degree of intensity correlation of the transmitted wave,
\kappa. The intertwined effects of localization and absorption can also be
disentangled in the time domain since all waves emerging from the sample at a
fixed time delay from an exciting pulse, t, are suppressed equally by
absorption. As a result, the relative weights of partial waves emerging from
the sample, and hence the statistics of intensity fluctuations and correlation,
and the suppression of propagation by weak localization are not changed by
absorption, and manifest the growing impact of weak localization with t.


  We compared the efficiency of the FlyHash model, an insect-inspired sparse
neural network (Dasgupta et al., 2017), to similar but non-sparse models in an
embodied navigation task. This requires a model to control steering by
comparing current visual inputs to memories stored along a training route. We
concluded the FlyHash model is more efficient than others, especially in terms
of data encoding.


  Let N > n, and denote by K the convex hull of N independent standard gaussian
random vectors in an n-dimensional Euclidean space. We prove that with high
probability, the isotropic constant of K is bounded by a universal constant.
Thus we verify the hyperplane conjecture for the class of gaussian random
polytopes.


  Remote code disclosure attacks threaten embedded systems as they allow
attackers to steal intellectual property or to find reusable code for use in
control-flow hijacking attacks. Execute-only memory (XOM) prevents remote code
disclosures, but existing XOM solutions either require a memory management unit
that is not available on ARM embedded systems or incur significant overhead.
  We present PicoXOM: a fast and novel XOM system for ARMv7-M and ARMv8-M
devices which leverages ARM's Data Watchpoint and Tracing unit along with the
processor's simplified memory protection hardware. On average, PicoXOM incurs
0.33% performance overhead and 5.89% code size overhead on two benchmark suites
and five real-world applications.


  Spectacular advances in heterodyne astronomy with both the Herschel Space
Observatory and Stratospheric Observatory for Far Infrared Astronomy (SOFIA)
have been largely due to breakthroughs in detector technology. In order to
exploit the full capacity of future THz telescope space missions (e.g. Origins
Space Telescope), new concepts of THz coherent receivers are needed, providing
larger bandwidths and imaging capabilities with multi-pixel focal plane
heterodyne arrays. Here we show that graphene, uniformly doped to the Dirac
point, enables highly sensitive and wideband coherent detection of THz signals.
With material resistance dominated by quantum localization, and thermal
relaxation governed by electron diffusion, proof-of-concept graphene bolometers
demonstrate a gain bandwidth of 8 GHz and a mixer noise temperature of 475 K,
limited by residual thermal background in our setup. An optimized device will
result in a mixer noise temperature as low as 36 K, with the gain bandwidth
exceeding 20 GHz, and a Local Oscillator power lower than 100 pW. In
conjunction with the emerging quantum-limited amplifiers at the intermediate
frequency, our approach promises quantum-limited sensing in the THz domain,
potentially surpassing superconducting technologies, particularly for large
heterodyne arrays.


  A new model to investigate environmental effects of genetically
distinguishable predators is presented. The Holling type II response function,
modelling feeding satiation, leads to persistent system's oscillations, as in
classical population models. An almost complete classification of the cases
arising in the Routh-Hurwitz stability conditions mathematically characterizes
the paper. It is instrumental as a guideline in the numerical experiments
leading to the findings on the limit cycles. This result extends what found in
an earlier parallel investigation containing a standard bilinear response
function.


  Szilard's one-molecule engine is operated by a Maxwell's demon attempting to
convert heat to work. It is argued here that when using the demon to relate
information to work (Landauer's principle), the demon's goal must be regarded
as an implicit assumption that should not be taken for granted. Other demons
than the standard one can be constructed depending on their assumed goal. When
the demon is purely mechanical, the goal is instilled in it by its design. When
the demon is regarded as "intelligent" (Maxwell) and "endowed with free will"
(Thomson), it is not so clear whence he could acquire a specific goal. A
solution is to subject the demon to evolution by natural selection, which in an
extended form can provide the demon with a genuine goal for which work is
necessary. This implies that the information the demon acquires and uses for
operating the engine becomes functional for the demon, and thereby acquires a
real physical status. Such information, called functional information, applies
to all life and technology. It should be distinguished from the formal,
causally ineffective information that can be defined, more arbitrarily, for any
system. Information in general is not physical, only functional information is.
A similar functional/formal distinction applies to close associates of
information, in particular entropy, probability, and the second law of
thermodynamics.


  We investigate here a generalized construction of spherical wavelets/needlets
which admits extra-flexibility in the harmonic domain, i.e., it allows the
corresponding support in multipole (frequency) space to vary in more general
forms than in the standard constructions. We study the analytic properties of
this system and we investigate its behaviour when applied to isotropic random
fields: more precisely, we establish asymptotic localization and uncorrelation
properties (in the high-frequency sense) under broader assumptions than
typically considered in the literature.


  Reciprocity is an important characteristic of directed networks and has been
widely used in the modeling of World Wide Web, email, social, and other complex
networks. In this paper, we take a statistical physics point of view and study
the limiting entropy and free energy densities from the microcanonical
ensemble, the canonical ensemble, and the grand canonical ensemble whose
sufficient statistics are given by edge and reciprocal densities. The sparse
case is also studied for the grand canonical ensemble. Extensions to more
general reciprocal models including reciprocal triangle and star densities will
likewise be discussed.


  Long term X-ray monitoring data from the RXTE ASM and CGRO BATSE reveal that
the third (superorbital) period in SMC X-1 is not constant, but varies between
40-60 days. A dynamic power spectrum analysis indicates that the third period
has been present continuously throughout the five years of ASM observations.
This period changed smoothly from 60 days to 45 days and then returned to its
former value, on a timescale of approximately 1600 days. During the nearly 4
years of overlap between the CGRO & RXTE missions, the simultaneous BATSE hard
X-ray data confirm and extend this variation in SMC X-1. Our discovery of such
an instability in the superorbital period of SMC X-1 is interpreted in the
context of recent theoretical studies of warped, precessing accretion disks. We
find that the behaviour of SMC X-1 is consistent with a radiation-driven
warping model.


  We consider a one-dimensional classical many-body system with interaction
potential of Lennard-Jones type in the thermodynamic limit at low temperature
$1/\beta\in(0,\infty)$. The ground state is a periodic lattice. We show that
when the density is strictly smaller than the density of the ground state
lattice, the system with $N$ particles fills space by alternating approximately
crystalline domains (clusters) with empty domains (voids) due to cracked bonds.
The number of domains is of the order of $N\exp(- \beta e_\mathrm{surf}/2)$
with $e_\mathrm{surf}>0$ a surface energy.
  For the proof, the system is mapped to an effective model, which is a
low-density lattice gas of defects. The results require conditions on the
interactions between defects. We succeed in verifying these conditions for
next-nearest neighbor interactions, applying recently derived uniform estimates
of correlations.


  Motivated by a question on the maximal number of vertex disjoint Schrijver
graphs in the Kneser graph, we investigate the following function, denoted by
$f(n,k)$: the maximal number of Hamiltonian cycles on an $n$ element set, such
that no two cycles share a common independent set of size more than $k$. We
shall mainly be interested in the behavior of $f(n,k)$ when $k$ is a linear
function of $n$, namely $k=cn$. We show a threshold phenomenon: there exists a
constant $c_t$ such that for $c<c_t$, $f(n,cn)$ is bounded by a constant
depending only on $c$ and not on $n$, and for $c_t <c$, $f(n,cn)$ is
exponentially large in $n ~(n \to \infty)$. We prove that $0.26 < c_t < 0.36$,
but the exact value of $c_t$ is not determined. For the lower bound we prove a
technical lemma, which for graphs that are the union of two Hamiltonian cycles
establishes a relation between the independence number and the number of $K_4$
subgraphs. A corollary of this lemma is that if a graph $G$ on $n>12$ vertices
is the union of two Hamiltonian cycles and $\alpha(G)=n/4$, then $V(G)$ can be
covered by vertex-disjoint $K_4$ subgraphs.


  The Monte Carlo simulation of $N$ point vortices with square periodic
boundary conditions is performed where $N$ is order of 100. The clustering
property is examined by computing the $L$ function familiar in the field of
spatial ecology. The case of a positive value of $L$ corresponds to the state
of clustering and the Onsager's negative temperature.


  The non-forward eikonal scattering matrix for dipole-proton scattering at
high energy obtains an imaginary part due to a $C$-odd three gluon exchange. We
present numerical estimates for the perturbative Odderon amplitude as a
function of dipole size, impact parameter, their relative azimuthal angle, and
light-cone momentum cutoff $x$. The proton is approximated as
$\psi_\mathrm{qqq}|qqq\rangle + \psi_\mathrm{qqqg}|qqqg\rangle$, where
$\psi_\mathrm{qqq}$ is a non-perturbative three quark model wave function while
the gluon emission is computed in light-cone perturbation theory. We find that
the Odderon amplitude increases as $x$ decreases from 0.1 to 0.01. At yet lower
$x$, the reversal of this energy dependence would reflect the onset of
universal small-$x$ renormalization group evolution.


  We construct the chiral gravitational waves from the $z=2$
Ho\v{r}ava-Lifshitz gravity with gravitational Chern-Simons term in the de
Sitter and Minkowski backgrounds. These gravitational waves which show a
feature of the Ho\v{r}ava-Lifshitz gravity may be related to the generalized
uncertainty principle. In addition, we find the classical and quantum IR-UV
transition rules in the $z=2$ Ho\v{r}ava-Lifshitz gravity.


  We study a realization of the topology of the Zee model for the generation of
neutrino masses at one-loop with a minimal set of vector-like fermions. After
imposing an exact $Z_2$ symmetry to avoid tree-level Higgs-mediated flavor
changing neutral currents, one dark matter candidate is obtained from the
subjacent inert doublet model, but with the presence of new co-annihilating
particles. We show that the model is consistent with the constraints coming
from lepton flavor violation processes, oblique parameters, dark matter and
neutrino oscillation data.


  We revisit long-standing controversies regarding relationships among the
all-India rainfall index (AIRI), sub-India summer rainfall variations, El
Ni\~no-Southern Oscillation (ENSO), and the Indian Ocean Dipole (IOD) using
120-year sea surface temperature and high-resolution rainfall datasets. AIRI
closely tracks with the spatial extent of wet anomalies and with the average
across gridpoints in rainy day count. The leading rainfall variability mode is
a monopole associated primarily with rainy day count and ENSO. The second mode
is a tripole with same-signed loadings in the high-rainfall Western Ghats and
Central Monsoon Zone regions and opposite-signed loadings in Southeastern India
between. The IOD projects onto this tripole and, as such, is weakly correlated
with AIRI. However, when the linear influence of ENSO is removed, the IOD
rainfall regressions become quasi-homogeneously more positive, making the
ENSO-residual IOD and AIRI timeseries significantly correlated.


  This paper introduces a new mathematical formulation and numerical approach
for the computation of distances and geodesics between immersed planar curves.
Our approach combines the general simplifying transform for first-order elastic
metrics that was recently introduced by Kurtek and Needham, together with a
relaxation of the matching constraint using parametrization-invariant fidelity
metrics. The main advantages of this formulation are that it leads to a simple
optimization problem for discretized curves, and that it provides a flexible
approach to deal with noisy, inconsistent or corrupted data. These benefits are
illustrated via a few preliminary numerical results.


  In contrast to wave functions in nonrelativistic quantum mechanics
interpreted as probability amplitudes, wave functions in relativistic quantum
mechanics have generalized meanings such as charge-density amplitudes,
energy-density amplitudes as well as particle-number density amplitudes, etc.
Applying electromagnetic field intensities we construct a photon wave function,
it corresponds to the (1,0)+(0,1) spinor representation of the electromagnetic
field, and can be interpreted as the energy-density amplitude of photons
outside a source. In terms of photon wave functions we develop photon wave
mechanics, which provides us with a new quantum-mechanical description for
photons outside a source.


  The ultimate aim of quantum key distribution (QKD) is improving the
performance of transmission distance and key generation speed. Unfortunately,
it is believed to be limited by the secret-key capacity of quantum channel
without quantum repeater. Recently, a novel twin-field QKD (TFQKD) [Nature 557,
400 (2018)] is proposed to break through the limit, where the key rate is
proportional to the square-root of channel transmittance. Here, by using the
vacuum and one-photon state as a qubit, we show that the TF-QKD can be regarded
as a measurement-device-independent QKD (MDI-QKD) with single-photon Bell state
measurement. Therefore, the MDI property of TF-QKD can be understood clearly.
Importantly, the universal security proof theories can be directly used for the
TF-QKD, such as BB84, six-state and reference-frame-independent schemes.
Furthermore, we propose a feasible experimental scheme for the
proof-of-principle experimental demonstration.


  Machine learning plays an increasingly significant role in many aspects of
our lives (including medicine, transportation, security, justice and other
domains), making the potential consequences of false predictions increasingly
devastating. These consequences may be mitigated if we can automatically flag
such false predictions and potentially assign them to alternative, more
reliable mechanisms, that are possibly more costly and involve human attention.
This suggests the task of detecting errors, which we tackle in this paper for
the case of visual classification. To this end, we propose a novel approach for
classification confidence estimation. We apply a set of semantics-preserving
image transformations to the input image, and show how the resulting image sets
can be used to estimate confidence in the classifier's prediction. We
demonstrate the potential of our approach by extensively evaluating it on a
wide variety of classifier architectures and datasets, including
ResNext/ImageNet, achieving state of the art performance. This paper
constitutes a significant revision of our earlier work in this direction (Bahat
& Shakhnarovich, 2018).


  We provide a quantitative evaluation of non-Markovianity (NM) for an XX chain
of interacting qubits with one end coupled to a reservoir. The NM of several
non-Markovian spectral densities is assessed in terms of various quantum state
distance (QSD) measures. Our approach is based on the construction of the
density matrix of the open chain, without the necessity of a master equation.
For the quantification of NM we calculate the dynamics of the QSD measures
between the Markovian-damped and various types of non-Markovian-damped cases.
Since in the literature several QSD measures, appear in forms that imply trace
preserving density matrices, we introduced appropriate modifications so as to
render them applicable to the case of decaying traces. The results produce
remarkable consistency between the various QSD measures. They also reveal a
subtle and potentially useful interplay between qubit-qubit interaction and
non-Markovian damping. Our calculations have also uncovered a surprisingly
dramatic slowing-down of dissipation by the squared Lorentzian reservoir.


  Whereas classical multi-agent systems have the agent in center, there have
recently been a development towards focusing more on the organization of the
system. This allows the designer to focus on what the system goals are, without
considering how the goals should be fulfilled. This paper investigates whether
taking this approach has any clear advantages to the classical way of
implementing multi-agent systems. The investigation is done by implementing
each type of system in the same environment in order to realize what advantages
and disadvantages each approach has.


  Bad metal properties have motivated a description of the parent iron
pnictides as correlated metals on the verge of Mott localization. What has been
unclear is whether interactions can push these and related compounds to the
Mott insulating side of the phase diagram. Here we consider the iron
oxychalcogenides La2O2Fe2O(Se,S)2, which contain an Fe square lattice with an
expanded unit cell. We show theoretically that they contain enhanced
correlation effects through band narrowing compared to LaOFeAs, and we provide
experimental evidence that they are Mott insulators with moderate charge gaps.
We also discuss the magnetic properties in terms of a Heisenberg model with
frustrating J1-J2-J2' exchange interactions on a "doubled" checkerboard
lattice.


  Competing scenarios for quantum critical points (QCPs) of strongly
interacting Fermi systems signaled by a divergent density of states at zero
temperature are contrasted. The conventional scenario, which enlists critical
fluctuations of a collective mode and attributes the divergence to a coincident
vanishing of the quasiparticle strength $z$, is shown to be incompatible with
identities arising from conservation laws prevailing in the fermionic medium.
An alternative scenario, in which the topology of the Fermi surface is altered
at the QCP, is found to explain the non-Fermi-liquid thermodynamic behavior
observed experimentally in Yb-based compounds close to the QCP. It is suggested
that combination of the topological scenario with the theory of quantum phase
transitions will provide a proper foundation for analysis of the extended QCP
region.


  Application of Karhunen-Loeve decomposition (KLD, or singular value
decomposition) is presented for analysis of the spatio-temporal dynamics of
wide-aperture vertical cavity surface emitting laser (VCSEL), considered as a
thin-layer system. KLD technique enables to extract a set of dominant
components from complex dynamics of system under study and separate them from
noise and inessential underlying dynamical behavior. Properties of KLD spectrum
and structure of its main components are studied for different regimes of
VCSEL. Along with the analysis of VCSEL, a brief survey of KLD method and its
usage for theoretical and experimental description of nonlinear dynamical
systems is presented.


  We consider the focusing energy-critical nonlinear wave equation for radially
symmetric initial data in space dimensions $D \ge 4$. This equation has a
unique (up to sign and scale) nontrivial, finite energy stationary solution
$W$, called the ground state. We prove that every finite energy solution with
bounded energy norm resolves, continuously in time, into a finite superposition
of asymptotically decoupled copies of the ground state and free radiation.


  We explore how local, cosmology-independent measurements of the Hubble
constant and the age of the Universe help to provide a powerful consistency
check of the currently favored cosmological model (flat LambdaCDM) and
model-independent constraints on cosmology. We use cosmic microwave background
(CMB) data to define the model-dependent cosmological parameters, and add local
measurements to assess consistency and determine whether extensions to the
model are justified. At current precision, there is no significant tension
between the locally measured Hubble constant and age of the Universe (with
errors of 3% and 5% respectively) and the corresponding parameters derived from
the CMB. However, if errors on the local measurements could be decreased by a
factor of two, one could decisively conclude if there is tension or not. We
also compare the local and CMB data assuming simple extensions of the flat,
$\Lambda$CDM model (including curvature, dark energy with a constant equation
of state parameter not equal to -1, non-zero neutrino masses and a non-standard
number of neutrino families) and find no need for these extra parameters; in
particular, we constrain the effective number of neutrino species to be Neff <
4 at 95% confidence. We show that local measurements provide constraints on the
curvature and equation of state of dark energy nearly orthogonal to those of
the CMB. We argue that cosmology-independent measurements of local quantities
at the percent level would be very useful to explore cosmology in a
model-independent way.


  We derive and calculate the space-time translational gauge identities in
quantum Yang-Mills gravity with a general class of gauge conditions involving
two arbitrary parameters. These identities of the Abelian group of translation
are a generalization of Ward-Takahasi-Fradkin identities and important for
general discussions of possible renormalization of Yang-Mills gravity with
translational gauge symmetry. The gauge identities in Yang-Mills gravity with a
general class of gauge conditions are substantiated by explicit calculations.


  A 1-2 model configuration is a subset of edges of a hexagonal lattice
satisfying the constraint that each vertex is incident to 1 or 2 edges. We
introduce Markov chains to sample the 1-2 model configurations on 2D hexagonal
lattice and prove that the mixing time of these chains is polynomial in the
sizes of the graphs for a large class of probability measures.


  Adiabatic quantum programming defines the time-dependent mapping of a quantum
algorithm into an underlying hardware or logical fabric. An essential step is
embedding problem-specific information into the quantum logical fabric. We
present algorithms for embedding arbitrary instances of the adiabatic quantum
optimization algorithm into a square lattice of specialized unit cells. These
methods extend with fabric growth while scaling linearly in time and
quadratically in footprint. We also provide methods for handling hard faults in
the logical fabric without invoking approximations to the original problem, and
illustrate their versatility through numerical studies of embeddabilty versus
fault rates in square lattices of complete bipartite unit cells. The studies
show these algorithms are more resilient to faulty fabrics than naive embedding
approaches, a feature which should prove useful in benchmarking the adiabatic
quantum optimization algorithm on existing faulty hardware.


  The strong correlation between neurons or filters can significantly weaken
the generalization ability of neural networks. Inspired by the well-known
Tammes problem, we propose a novel diversity regularization method to address
this issue, which makes the normalized weight vectors of neurons or filters
distributed on a hypersphere as uniformly as possible, through maximizing the
minimal pairwise angles (MMA). This method can easily exert its effect by
plugging the MMA regularization term into the loss function with negligible
computational overhead. The MMA regularization is simple, efficient, and
effective. Therefore, it can be used as a basic regularization method in neural
network training. Extensive experiments demonstrate that MMA regularization is
able to enhance the generalization ability of various modern models and
achieves considerable performance improvements on CIFAR100 and TinyImageNet
datasets. In addition, experiments on face verification show that MMA
regularization is also effective for feature learning. Code is available at:
https://github.com/wznpub/MMA_Regularization.


  The impact of different linearisation and iterative solution strategies for
fully-coupled pressure-based algorithms for compressible flows at all speeds is
studied, with the aim of elucidating their impact on the performance of the
numerical algorithm. A fixed-coefficient linearisation and a Newton
linearisation of the transient and advection terms of the governing nonlinear
equations are compared, focusing on test-cases that feature acoustic, shock and
expansion waves. The linearisation and iterative solution strategy applied to
discretise and solve the nonlinear governing equations is found to have a
significant influence on the performance and stability of the numerical
algorithm. The Newton linearisation of the transient terms of the momentum and
energy equations is shown to yield a significantly improved convergence of the
iterative solution algorithm compared to a fixed-coefficient linearisation,
while the linearisation of the advection terms leads to substantial differences
in performance and stability at large Mach numbers and large Courant numbers.
It is further shown that the consistent Newton linearisation of all transient
and advection terms of the governing equations allows, in the context of
coupled pressure-based algorithms, to eliminate all forms of underrelaxation
and provides a clear performance benefit for flows in all Mach number regimes.


  In this paper, we obtain some sufficient conditions for a 3-dimensional
compact trans-Sasakian manifold of type $(\alpha ,\beta)$ to be homothetic to a
Sasakian manifold. A characterization of a 3-dimensional cosymplectic manifold
is also obtained.


  We review clustering as an analysis tool and the underlying concepts from an
introductory perspective. What is clustering and how can clusterings be
realised programmatically? How can data be represented and prepared for a
clustering task? And how can clustering results be validated?
Connectivity-based versus prototype-based approaches are reflected in the
context of several popular methods: single-linkage, spectral embedding,
k-means, and Gaussian mixtures are discussed as well as the density-based
protocols (H)DBSCAN, Jarvis-Patrick, CommonNN, and density-peaks.


  Commensurable groups are bi-interpretable, under suitable definability
conditions.


  Monte Carlo investigations of magnetization versus field, $M_c(H)$, at the
critical temperature provide direct accurate results on the critical exponent
$\delta^{-1}$ for one, two, three and four-dimensional lattices:
$\delta_{1D}^{-1}$=0, $\delta_{2D}^{-1}$=0.0666(2)$\simeq$1/15,
$\delta_{3D}^{-1}$=0.1997(4)$\simeq$1/5,
$\delta_{4D}^{-1}$=0.332(5)$\simeq$1/3. This type of Monte Carlo data on
$\delta$, which is not easily found in studies of Ising lattices in the current
literature, as far as we know, defines extremely well the numerical value of
this exponent within very stringent limits.


  Because the propagators of flavor-singlet states incorporate disconnected
diagrams, they are uniquely sensitive to any differences in the actions
governing sea and valence fermions on the lattice. As such, they present an
important test of the validity of the ``fourth-root trick'' in the staggered
fermion formulation. The pseudoscalar's relationship to topological charge also
makes it of theoretical interest. We present preliminary results from our
measurements of flavor-singlet pseudoscalar mesons on 2+1 flavor Asqtad
lattices, and discuss some strategies for improving the signal-to-error ratio
of disconnected singlet correlators.


  We investigate bounds on the strength of the primordial magnetic field (PMF)
from the cosmic microwave background (CMB) bispectra of the intensity
(temperature) modes induced from the auto- and cross-correlated bispectra of
the scalar and tensor components of the PMF anisotropic stress. At first, we
construct a general formula for the CMB intensity and polarization bispectra
from PMFs composed of any type of perturbation. Then we derive an approximate
expression which traces the exact shape of the CMB bispectrum in order to
reduce the computation time with respect to a large number of the multipole
configurations, and also show that the non-Gaussian structure coming from PMFs
is classified as the local-type configuration. Computing the signal-to-noise
ratio on the basis of the approximate formula with the information of the
instrumental noises and resolutions, we find expected upper bounds on the
magnetic field strength, when the magnetic spectrum is nearly scale invariant
($n_B = -2.9$), smoothed on $1 {\rm Mpc}$ scale at 95% confidence level from
the WMAP and PLANCK experiments as $B_{1 \rm Mpc} < 4.0 - 6.7 {\rm nG}$ and
$3.8 - 6.5 {\rm nG}$, respectively, depending on the energy scale of the
magnetic field production from $10^{14} {\rm GeV}$ to $10^3 {\rm GeV}$. Our new
consequences imply slight overestimations by the previous rough discussions.


  We use the quaternion Kahler reduction technique to study old and new
self-dual Einstein metrics of negative scalar curvature with at least a
two-dimensional isometry group, and relate the quotient construction to the
hyperbolic eigenfunction Ansatz. We focus in particular on the
(semi-)quaternion Kahler quotients of (semi-)quaternion Kahler hyperboloids,
analysing the completeness and topology, and relating them to the self-dual
Einstein Hermitian metrics of Apostolov-Gauduchon and Bryant.


  Modelling spatio-temporal processes has become an important issue in current
research. Since Gaussian processes are essentially determined by their second
order structure, broad classes of covariance functions are of interest. Here, a
new class is described that merges and generalizes various models presented in
the literature, in particular models in Gneiting (J. Amer. Statist. Assoc. 97
(2002) 590--600) and Stein (Nonstationary spatial covariance functions (2005)
Univ. Chicago). Furthermore, new models and a multivariate extension are
introduced.


  We present wide-field near-infrared (JHK) images of the young, 2 Myr IC 348
cluster taken with FLAMINGOS. We use these new data to construct an infrared
census of sources, which is sensitive enough to detect a 10 Mjup brown dwarf
seen through an extinction of Av=7mag. We examine the cluster's structure and
relationship to the molecular cloud and construct the cluster's K band
luminosity function. Using our model luminosity function algorithm, we derive
the cluster's initial mass function throughout the stellar and substellar
regimes and find that the IC 348 IMF is very similar to that found for the
Trapezium Cluster with both cluster IMFs having a mode between 0.2 - 0.08 Msun.
In particular we find that, similar to our results for the Trapezium, brown
dwarfs constitute only 1 in 4 of the sources in the IC 348 cluster. We show
that a modest secondary peak forms in the substellar IC 348 KLF, corresponding
to the same mass range responsible for a similar KLF peak found in the
Trapezium. We interpret this KLF peak as either evidence for a corresponding
secondary IMF peak at the deuterium burning limit, or as arising from a feature
in the substellar mass-luminosity relation that is not predicted by current
theoretical models. Lastly, we find that IC 348 displays radial variations of
its sub-solar (0.5 - 0.08 Msun) IMF on a parsec scale. Whatever mechanism that
is breaking the universality of the IMF on small spatial scales in IC 348 does
not appear to be acting upon the brown dwarf population, whose relative size
does not vary with distance from the cluster center.


  A report to the Fermilab Director from the Study Group on Future Neutrino
Experiments at Fermilab


  We report experimental realization of a quantum time quasicrystal, and its
transformation to a quantum time crystal. We study Bose-Einstein condensation
of magnons, associated with coherent spin precession, created in a flexible
trap in superfluid $^3$He-B. Under a periodic drive with an oscillating
magnetic field, the coherent spin precession is stabilized at a frequency
smaller than that of the drive, demonstrating spontaneous breaking of discrete
time translation symmetry. The induced precession frequency is incommensurate
with the drive, and hence the obtained state is a time quasicrystal. When the
drive is turned off, the self-sustained coherent precession lives a
macroscopically-long time, now representing a time crystal with broken symmetry
with respect to continuous time translations. Additionally, the magnon
condensate manifests spin superfluidity, justifying calling the obtained state
a time supersolid or a time super-crystal.


  In this paper, we investigate properties of modules introduced by
Kra\'skiewicz and Pragacz which realize Schubert polynomials as their
characters. In particular, we give some characterizations of modules having a
filtration by Kra\'skiewicz-Pragacz modules. In finding criteria for
filtrations, we calculate generating sets for the annihilator ideals of the
lowest vectors in Kra\'skiewicz-Pragacz modules, and derive a projectivity
result concerning Kra\'skiewicz-Pragacz modules.


  We propose an improved parametric form for the equation of state of
three-dimensional O(N) spin systems. The proposed form is a series expansion
with two sets of terms, which contribute (mainly) separately to the description
of the high- and low-temperature regions of the phase diagram. Our goal is a
better description of the low-temperature phase at zero magnetic field (i.e.
the coexistence line), characterized by singularities induced by Goldstone
modes. We test our proposed form by comparison with existing Monte Carlo data
for the N=4 case, which is of interest in studies of the QCD phase transition
and for which the Goldstone-mode effects are quite pronounced. We find that the
description of the numerical equation of state is indeed improved with respect
to other fitting forms. In all cases considered we determine the coefficients
nonperturbatively, from fits to the data. As a consequence, we are able to
obtain a very precise characterization of the pseudo-critical line for the
model.


  We study polarisation of W-bosons produced in association with one jet at the
LHC. In particular, we provide all necessary theoretical ingredients for the
precise extraction of polarisation fractions. To that end, we present new
polarised predictions up to NNLO QCD accuracy employing the narrow-width
approximation, in two phase spaces: inclusive and fiducial. We compare results
in the fiducial phase space to a full off-shell computation as well as
experimental data. Finally, we fit the polarisation fractions using shape
templates and show that NNLO corrections significantly improve their
determination.


  Training machine learning algorithms is a computationally intensive process,
which is frequently memory-bound due to repeatedly accessing large training
datasets. As a result, processor-centric systems (e.g., CPU, GPU) suffer from
costly data movement between memory units and processing units, which consumes
large amounts of energy and execution cycles. Memory-centric computing systems,
i.e., computing systems with processing-in-memory (PIM) capabilities, can
alleviate this data movement bottleneck.
  Our goal is to understand the potential of modern general-purpose PIM
architectures to accelerate machine learning training. To do so, we (1)
implement several representative classic machine learning algorithms (namely,
linear regression, logistic regression, decision tree, K-means clustering) on a
real-world general-purpose PIM architecture, (2) characterize them in terms of
accuracy, performance and scaling, and (3) compare to their counterpart
implementations on CPU and GPU. Our experimental evaluation on a memory-centric
computing system with more than 2500 PIM cores shows that general-purpose PIM
architectures can greatly accelerate memory-bound machine learning workloads,
when the necessary operations and datatypes are natively supported by PIM
hardware.
  To our knowledge, our work is the first one to evaluate training of machine
learning algorithms on a real-world general-purpose PIM architecture.


  In this paper we discuss some spectral invariance results for non-smooth
pseudodifferential operators with coefficients in H\"older spaces. In analogy
to the proof in the smooth case of Beals and Ueberberg, we use the
characterization of non-smooth pseudodifferential operators to get such a
result. The main new difficulties are the limited mapping properties of
pseudodifferential operators with non-smooth symbols and the fact, that in
general the composition of two non-smooth pseudodifferential operators is not a
pseudodifferential operator.
  In order to improve these spectral invariance results for certain subsets of
non-smooth pseudodifferential operators with coefficients in H\"older spaces,
we improve the characterization of non-smooth pseudodifferential operators in a
previous work by the authors.


  Supercritical string theories in D>10 dimensions with no moduli are
described, generalizing the asymmetric orientifold construction of one of the
authors. By taking the number of dimensions to be large and turning on fluxes,
dilaton potentials are generated with nontrivial minima at arbitrarily small
cosmological constant and D-dimensional string coupling, separated by a barrier
from a flat-space linear dilaton region, but possibly suffering from strong
coupling problems. The general issue of the decay of a de Sitter vacuum to flat
space is discussed. For relatively small barriers, such decays are described by
gravitational instantons. It is shown that for a sufficiently large potential
barrier, the bubble wall crosses the horizon. At the same time the instanton
decay time exceeds the Poincare recurrence time. It is argued that the
inclusion of such instantons is neither physically meaningful nor consistent
with basic principles such as causality. This raises the possibility that such
de Sitter vacua are effectively stable. In the case of the supercritical flux
models, decays to the linear dilaton region can be forbidden by such large
barriers, but decays to lower flux vacua including AdS minima nevertheless
proceed consistently with this criterion. These models provide concrete
examples in which cosmological constant reduction by flux relaxation can be
explored.


  The emission of a charged light lepton pair by a superluminal neutrino has
been identified as a major factor in the energy loss of highly energetic
neutrinos. The observation of PeV neutrinos by IceCube implies their stability
against lepton pair Cerenkov radiation. Under the assumption of a
Lorentz-violating dispersion relation for highly energetic superluminal
neutrinos, one may thus constrain the Lorentz-violating parameters. A
kinematically different situation arises when one assumes a Lorentz-covariant,
space-like dispersion relation for hypothetical tachyonic neutrinos, as an
alternative to Lorentz-violating theories. We here discuss a hitherto neglected
decay process, where a highly energetic tachyonic neutrinos may emit other
(space-like, tachyonic) neutrino pairs. We find that the space-like dispersion
relation implies the absence of a q^2 threshold for the production of a
tachyonic neutrino-antineutrino pair, thus leading to the dominant additional
energy loss mechanism for an oncoming tachyonic neutrino in the medium-energy
domain. Surprisingly, the small absolute value of the decay rate and energy
loss rate in the tachyonic model imply that these models, in contrast to the
Lorentz-violating theories, are not pressured by the cosmic PeV neutrinos
registered by the IceCube collaboration.


  We combine perturbation theory with analytic and numerical bootstrap
techniques to study the critical point of the long-range Ising (LRI) model in
two and three dimensions. This model interpolates between short-range Ising
(SRI) and mean-field behaviour. We use the Lorentzian inversion formula to
compute infinitely many three-loop corrections in the two-dimensional LRI near
the mean-field end. We further exploit the exact OPE relations that follow from
bulk locality of the LRI to compute infinitely many two-loop corrections near
the mean-field end, as well as some one-loop corrections near SRI. By including
such exact OPE relations in the crossing equations for LRI we set up a very
constrained bootstrap problem, which we solve numerically using SDPB. We find a
family of sharp kinks for two- and three-dimensional theories which compare
favourably to perturbative predictions, as well as some Monte Carlo simulations
for the two-dimensional LRI.


  In this supplemental document we explain the details of our ab initio density
functional theory calculations and crystal structure searches performed in CaF2
under pressure. Also we report the computed P-dependence of the formation
energy of Frenkel pair defects in the cubic fluorite phase, and the vibrational
phonon spectra and structural data of the predicted high-T monoclinic P2_1/c
phase. Calculated enthalpy energies in compressed SrF2 and BaF2 are also
presented.


  Improving model robustness in case of corrupted images is among the key
challenges to enable robust vision systems on smart devices, such as robotic
agents. Particularly, robust test-time performance is imperative for most of
the applications. This paper presents a novel approach to improve robustness of
any classification model, especially on severely corrupted images. Our method
(FROST) employs high-frequency features to detect input image corruption type,
and select layer-wise feature normalization statistics. FROST provides the
state-of-the-art results for different models and datasets, outperforming
competitors on ImageNet-C by up to 37.1% relative gain, improving baseline of
40.9% mCE on severe corruptions.