  Scientists deploy environmental monitoring net-works to discover previously
unobservable phenomena and quantify subtle spatial and temporal differences in
the physical quantities they measure. Our experience, shared by others, has
shown that measurements gathered by such networks are perturbed by sensor
faults. In response, multiple fault detection techniques have been proposed in
the literature. However, in this paper we argue that these techniques may
misclassify events (e.g. rain events for soil moisture measurements) as faults,
potentially discarding the most interesting measurements. We support this
argument by applying two commonly used fault detection techniques on data
collected from a soil monitoring network. Our results show that in this case,
up to 45% of the event measurements are misclassified as faults. Furthermore,
tuning the fault detection algorithms to avoid event misclassification, causes
them to miss the majority of actual faults. In addition to exposing the tension
between fault and event detection, our findings motivate the need to develop
novel fault detection mechanisms which incorporate knowledge of the underlying
events and are customized to the sensing modality they monitor.


  The coincidence problem is studied in the effective Yang-Mills condensate
dark energy model. As the effective YM Lagrangian is completely determined by
quantum field theory, there is no adjustable parameter in this model except the
energy scale, and the cosmic evolution only depends on the initial conditions.
For generic initial conditions with the YM condensate subdominant to the
radiation and matter, the model always has a tracking solution, the Universe
transits from matter-dominated into the dark energy dominated stage only
recently $z\sim 0. 3$, and evolve to the present state with $\Omega_{y}\sim
0.73$ and $\Omega_m\sim 0.27$.


  The divisor theory of graphs views a finite connected graph $G$ as a discrete
version of a Riemann surface. Divisors on $G$ are formal integral combinations
of the vertices of $G$, and linear equivalence of divisors is determined by the
discrete Laplacian operator for $G$. As in the case of Riemann surfaces, we are
interested in the complete linear system $|D|$ of a divisor $D$---the
collection of nonnegative divisors linearly equivalent to $D$. Unlike the case
of Riemann surfaces, the complete linear system of a divisor on a graph is
always finite. We compute generating functions encoding the sizes of all
complete linear systems on $G$ and interpret our results in terms of polyhedra
associated with divisors and in terms of the invariant theory of the (dual of
the) Jacobian group of $G$. If $G$ is a cycle graph, our results lead to a
bijection between complete linear systems and binary necklaces. The final
section generalizes our results to a model based on integral $M$-matrices.


  In this talk, I will discuss the use of harmonic functions to study the
geometry and topology of complete manifolds. In my previous joint work with
Luen-fai Tam, we discovered that the number of infinities of a complete
manifold can be estimated by the dimension of a certain space of harmonic
functions. Applying this to a complete manifold whose Ricci curvature is almost
non-negative, we showed that the manifold must have finitely many ends. In my
recent joint works with Jiaping Wang, we successfully applied this general
method to two other classes of complete manifolds. The first class are
manifolds with the lower bound of the spectrum $\lambda_1(M) >0$ and whose
Ricci curvature is bounded by $$ Ric_M \ge -{m-2 \over m-1} \lambda_1(M). $$
The second class are stable minimal hypersurfaces in a complete manifold with
non-negative sectional curvature. In both cases we proved some splitting type
theorems and also some finiteness theorems.


  A new approach to the finite-gap property for the Heun equation is
constructed. The relationship between the finite-dimensional invariant space
and the spectral curve is clarified. The monodromies are calculated and are
expressed as hyperelliptic integrals. Applications to the spectral problem for
the $BC_1$ Inozemtsev model are obtained.


  Variational quantum algorithms are a class of techniques intended to be used
on near-term quantum computers. The goal of these algorithms is to perform
large quantum computations by breaking the problem down into a large number of
shallow quantum circuits, complemented by classical optimization and feedback
between each circuit execution. One path for improving the performance of these
algorithms is to enhance the classical optimization technique. Given the
relative ease and abundance of classical computing resources, there is ample
opportunity to do so. In this work, we introduce the idea of learning surrogate
models for variational circuits using few experimental measurements, and then
performing parameter optimization using these models as opposed to the original
data. We demonstrate this idea using a surrogate model based on kernel
approximations, through which we reconstruct local patches of variational cost
functions using batches of noisy quantum circuit results. Through application
to the quantum approximate optimization algorithm and preparation of ground
states for molecules, we demonstrate the superiority of surrogate-based
optimization over commonly-used optimization techniques for variational
algorithms.


  In the (3+1)D Hamiltonian Regge calculus (one of the coordinates, $ t$, is
continuous) conjugate variables are (defined on triangles of discrete 3D
section $ t=const$) finite connections and antisymmetric area bivectors. The
latter, however, are not independent, since triangles may have common edges.
This circumstance can be taken into account with the help of the set of
kinematical (that is, required to hold by definition of Regge manifold)
bilinear constraints on bivectors. Some of these contain derivatives over $ t$,
and taking them into account with the help of Lagrange multipliers would result
in the new dynamical variables not having analogs in the continuum theory. It
is shown that kinematical constraints with derivatives are consequences of eqs.
of motion for Regge action supplemented with the rest of these constraints
without derivatives and can be omitted; so the new dynamical variables do not
appear.


  The hybrid-high order (HHO) scheme has many successful applications including
linear elasticity as the first step towards computational solid mechanics. The
striking advantage is the simplicity among other higher-order nonconforming
schemes and its geometric flexibility as a polytopal method on the expanse of a
parameter-free refined stabilization. The classical suggestion of a
locking-free HHO discretization requires a split of the the reconstruction
terms with an additional reconstruction of the divergence operator that might
be motivated by the Stokes equations for the robust approximation in the
incompressible limit, when one Lam\'e parameter $\lambda\to\infty$ becomes very
large. This paper utilizes just one reconstruction operator for the linear
Green strain and therefore does not rely on a split in deviatoric and spherical
behavior. The a priori error analysis provides quasi-best approximation with
$\lambda$-independent equivalence constants. The reliable and (up to data
oscillations) efficient a posteriori error estimates are stabilization-free and
$\lambda$-robust. The error analysis is carried out on simplicial meshes to
allow conforming piecewise polynomials finite elements in the kernel of the
stabilization terms. Numerical benchmarks provide empirical evidence for
optimal convergence rates of the a posteriori error estimator in some
associated adaptive mesh-refining algorithm also in the incompressible limit.


  We estimate the hardness factors and the equivalent 1 MeV neutron fluences
for hadrons fluences expected at the GaAs positions wheels in the ATLAS Inner
Detector. On this basis the degradation of the GaAs particle detectors made
from different substrates as a function of years LHC operation is predicted.


  The advance in laser plasma acceleration techniques pushes the regime of the
resulting accelerated particles to higher energies and intensities. In
particular the upcoming experiments with the FLAME laser at LNF will enter the
GeV regime with almost 1pC of electrons. From the current status of
understanding of the acceleration mechanism, relatively large angular and
energy spreads are expected. There is therefore the need to develop a device
capable to measure the energy of electrons over three orders of magnitude (few
MeV to few GeV) under still unknown angular divergences. Within the PlasmonX
experiment at LNF a spectrometer is being constructed to perform these
measurements. It is made of an electro-magnet and a screen made of
scintillating fibers for the measurement of the trajectories of the particles.
The large range of operation, the huge number of particles and the need to
focus the divergence present unprecedented challenges in the design and
construction of such a device. We will present the design considerations for
this spectrometer and the first results from a prototype.


  Hard scattering processes involving hadrons at small $x$ are described by a
$k_T$-factorization formula driven by a BFKL gluon. We explore the equivalence
of this description to a collinear-factorization approach in which the
anomalous dimensions $\gamma_{gg}$ and $\gamma_{qg}/\alpha_S$ are expressed as
power series in $\alpha_S \log (1/x)$, or to be precise $\alpha_S/\omega$ where
$\omega$ is the moment index. In particular we confront the
collinear-factorization expansion with that extracted from the BFKL approach
with running coupling included.


  Learning the governing equations in dynamical systems from time-varying
measurements is of great interest across different scientific fields. This task
becomes prohibitive when such data is moreover highly corrupted, for example,
due to the recording mechanism failing over unknown intervals of time. When the
underlying system exhibits chaotic behavior, such as sensitivity to initial
conditions, it is crucial to recover the governing equations with high
precision. In this work, we consider continuous time dynamical systems $\dot{x}
= f(x)$ where each component of $f: \mathbb{R}^{d} \rightarrow \mathbb{R}^d$ is
a multivariate polynomial of maximal degree $p$; we aim to identify $f$ exactly
from possibly highly corrupted measurements $x(t_1), x(t_2), \dots, x(t_m)$. As
our main theoretical result, we show that if the system is sufficiently ergodic
that this data satisfies a strong central limit theorem (as is known to hold
for chaotic Lorenz systems), then the governing equations $f$ can be exactly
recovered as the solution to an $\ell_1$ minimization problem -- even if a
large percentage of the data is corrupted by outliers. Numerically, we apply
the alternating minimization method to solve the corresponding constrained
optimization problem. Through several examples of 3D chaotic systems and higher
dimensional hyperchaotic systems, we illustrate the power, generality, and
efficiency of the algorithm for recovering governing equations from noisy and
highly corrupted measurement data.


  Planetary magnetic fields are generated by motions of electrically conducting
fluids in their interiors. The dynamo problem has thus received much attention
in spherical geometries, even though planetary bodies are non-spherical. To go
beyond the spherical assumption, we develop an algorithm that exploits a fully
spectral description of the magnetic field in triaxial ellipsoids to solve the
induction equation with local boundary conditions (i.e. pseudo-vacuum or
perfectly conducting boundaries). We use the method to compute the free-decay
magnetic modes and to solve the kinematic dynamo problem for prescribed flows.
The new method is thoroughly compared with analytical solutions and standard
finite-element computations, which are also used to model an insulating
exterior. We obtain dynamo magnetic fields at low magnetic Reynolds numbers in
ellipsoids, which could be used as simple benchmarks for future dynamo studies
in such geometries. We finally discuss how the magnetic boundary conditions can
modify the dynamo onset, showing that a perfectly conducting boundary can
strongly weaken dynamo action, whereas pseudo-vacuum and insulating boundaries
often give similar results.


  We extend earlier schemes for merging tree-level matrix elements with parton
showers to include also merging with one-loop matrix elements. In this paper we
make a first study on how to include one-loop corrections, not only for events
with a given jet multiplicity, but simultaneously for several different jet
multiplicities. Results are presented for the simplest non-trivial case of
hadronic events at LEP as a proof-of-concept.


  This paper discusses the development of trainable statistical models for
extracting content from television and radio news broadcasts. In particular we
concentrate on statistical finite state models for identifying proper names and
other named entities in broadcast speech. Two models are presented: the first
represents name class information as a word attribute; the second represents
both word-word and class-class transitions explicitly. A common n-gram based
formulation is used for both models. The task of named entity identification is
characterized by relatively sparse training data and issues related to
smoothing are discussed. Experiments are reported using the DARPA/NIST Hub-4E
evaluation for North American Broadcast News.


  This paper describes Clebsch-Gordan coefficients (CGCs) for unitary
irreducible representations (UIRs) of the extended quantum mechanical
Poincar\'e group $\pt$. `Extended' refers to the extension of the 10 parameter
Lie group that is the Poincar\'e group by the discrete symmetries $C$, $P$, and
$T$; `quantum mechanical' refers to the fact that we consider projective
representations of the group. The particular set of CGCs presented here are
applicable to the problem of the reduction of the direct product of two
massive, unitary irreducible representations (UIRs) of $\pt$ with positive
energy to irreducible components. Of the sixteen inequivalent representations
of the discrete symmetries, the two standard representations with $U_C U_P =
\pm 1$ are considered. Also included in the analysis are additive internal
quantum numbers specifying the superselection sector. As an example, these CGCs
are applied to the decay process of the $\Upsilon(4S)$ meson.


  We propose a successive one-sided Hodrick-Prescott (SOHP) filter from
multiple time scale decomposition perspective to derive trend estimate for a
time series. The idea is to apply the one-sided HP (OHP) filter recursively on
the updated cyclical component to extract the trend residual on multiple time
scales, thereby to improve the trend estimate. To address the issue of
optimization with a moving horizon as that of the SOHP filter, we present an
incremental HP filtering algorithm, which greatly simplifies the involved
inverse matrix operation and reduces the computational demand of the basic HP
filtering. Actually, the new algorithm also applies effectively to other
HP-type filters, especially for large-size or expanding data scenario.
Numerical examples on real economic data show the better performance of the
SOHP filter in comparison with other known HP-type filters.


  The local gradient points to the direction of the steepest slope in an
infinitesimal neighborhood. An optimizer guided by the local gradient is often
trapped in local optima when the loss landscape is multi-modal. A directional
Gaussian smoothing (DGS) approach was recently proposed in (Zhang et al., 2020)
and used to define a truly nonlocal gradient, referred to as the DGS gradient,
for high-dimensional black-box optimization. Promising results show that
replacing the traditional local gradient with the DGS gradient can
significantly improve the performance of gradient-based methods in optimizing
highly multi-modal loss functions. However, the optimal performance of the DGS
gradient may rely on fine tuning of two important hyper-parameters, i.e., the
smoothing radius and the learning rate. In this paper, we present a simple, yet
ingenious and efficient adaptive approach for optimization with the DGS
gradient, which removes the need of hyper-parameter fine tuning. Since the DGS
gradient generally points to a good search direction, we perform a line search
along the DGS direction to determine the step size at each iteration. The
learned step size in turn will inform us of the scale of function landscape in
the surrounding area, based on which we adjust the smoothing radius accordingly
for the next iteration. We present experimental results on high-dimensional
benchmark functions, an airfoil design problem and a game content generation
problem. The AdaDGS method has shown superior performance over several the
state-of-the-art black-box optimization methods.


  We address the physics of nematic liquid crystalline elastomers randomly
crosslinked in the isotropic state. To do this, we construct a phenomenological
effective replica Hamiltonian in terms of two order-parameter fields: one for
the vulcanization, the other for nematic alignment. Using a Gaussian
variational approach, we analyze both thermal and quenched fluctuations of the
local nematic order, and find that, even for low temperatures, the
macroscopically isotropic polydomain state is stabilized by the network
heterogeneity. For sufficiently strong disorder and low enough temperature, our
theory predicts unusual, short-range oscillatory structure in (i.e.,
anti-alignment of) the local nematic order. The present approach, which
naturally takes into account the compliant, thermally fluctuating and
heterogeneous features of elastomeric networks, can also be applied to other
types of randomly crosslinked solids.


  Character-based neural models have recently proven very useful for many NLP
tasks. However, there is a gap of sophistication between methods for learning
representations of sentences and words. While most character models for
learning representations of sentences are deep and complex, models for learning
representations of words are shallow and simple. Also, in spite of considerable
research on learning character embeddings, it is still not clear which kind of
architecture is the best for capturing character-to-word representations. To
address these questions, we first investigate the gaps between methods for
learning word and sentence representations. We conduct detailed experiments and
comparisons of different state-of-the-art convolutional models, and also
investigate the advantages and disadvantages of their constituents.
Furthermore, we propose IntNet, a funnel-shaped wide convolutional neural
architecture with no down-sampling for learning representations of the internal
structure of words by composing their characters from limited, supervised
training corpora. We evaluate our proposed model on six sequence labeling
datasets, including named entity recognition, part-of-speech tagging, and
syntactic chunking. Our in-depth analysis shows that IntNet significantly
outperforms other character embedding models and obtains new state-of-the-art
performance without relying on any external knowledge or resources.


  We relate character theory of the symmetric groups $S_{2n}$ and $S_{2n+1}$
with that of the hyperoctahedral group $B_n = ({\mathbb Z}/2)^n \rtimes S_n$,
as part of the expectation that the character theory of reductive groups with
diagram automorphism and their Weyl groups, is related to the character theory
of the fixed subgroup of the diagram automorphism.


  An introduction is provided to some current research trends in stability in
geometric invariant theory and the problem of Kaehler metrics of constant
scalar curvature. Besides classical notions such as Chow-Mumford stability, the
emphasis is on several new stability conditions, such as K-stability,
Donaldson's infinite-dimensional GIT, and conditions on the closure of orbits
of almost-complex structures under the diffeomorphism group. Related analytic
methods are also discussed, including estimates for energy functionals,
Tian-Yau-Zelditch approximations, estimates for moment maps, complex
Monge-Ampere equations and pluripotential theory, and the Kaehler-Ricci flow


  A period of rapidly accelerating expansion is expected in the early Universe
implemented by a scalar field slowly rolling down along an asymptotically flat
potential preferred by the current data. In this paper, we point out that this
picture of the cosmic inflation with an asymptotically flat potential could
emerge from the Palatini quadratic gravity by adding the matter field in such a
way to break the local gauged conformal symmetry in both kinetic and potential
terms.


  Since its introduction in 2018, EPIC-KITCHENS has attracted attention as the
largest egocentric video benchmark, offering a unique viewpoint on people's
interaction with objects, their attention, and even intention. In this paper,
we detail how this large-scale dataset was captured by 32 participants in their
native kitchen environments, and densely annotated with actions and object
interactions. Our videos depict nonscripted daily activities, as recording is
started every time a participant entered their kitchen. Recording took place in
4 countries by participants belonging to 10 different nationalities, resulting
in highly diverse kitchen habits and cooking styles. Our dataset features 55
hours of video consisting of 11.5M frames, which we densely labelled for a
total of 39.6K action segments and 454.2K object bounding boxes. Our annotation
is unique in that we had the participants narrate their own videos after
recording, thus reflecting true intention, and we crowd-sourced ground-truths
based on these. We describe our object, action and. anticipation challenges,
and evaluate several baselines over two test splits, seen and unseen kitchens.
We introduce new baselines that highlight the multimodal nature of the dataset
and the importance of explicit temporal modelling to discriminate fine-grained
actions e.g. 'closing a tap' from 'opening' it up.


  We conduct a systematic study of the approximation properties of Transformer
for sequence modeling with long, sparse and complicated memory. We investigate
the mechanisms through which different components of Transformer, such as the
dot-product self-attention, positional encoding and feed-forward layer, affect
its expressive power, and we study their combined effects through establishing
explicit approximation rates. Our study reveals the roles of critical
parameters in the Transformer, such as the number of layers and the number of
attention heads. These theoretical insights are validated experimentally and
offer natural suggestions for alternative architectures.


  We present a new method to translate videos to commands for robotic
manipulation using Deep Recurrent Neural Networks (RNN). Our framework first
extracts deep features from the input video frames with a deep Convolutional
Neural Networks (CNN). Two RNN layers with an encoder-decoder architecture are
then used to encode the visual features and sequentially generate the output
words as the command. We demonstrate that the translation accuracy can be
improved by allowing a smooth transaction between two RNN layers and using the
state-of-the-art feature extractor. The experimental results on our new
challenging dataset show that our approach outperforms recent methods by a fair
margin. Furthermore, we combine the proposed translation module with the vision
and planning system to let a robot perform various manipulation tasks. Finally,
we demonstrate the effectiveness of our framework on a full-size humanoid robot
WALK-MAN.


  The NASA Star and Exoplanet Database (NStED) is a general purpose stellar
archive with the aim of providing support for NASA's planet finding and
characterization goals, stellar astrophysics, and the planning of NASA and
other space missions. There are two principal components of NStED: a database
of (currently) 140,000 nearby stars and exoplanet-hosting stars, and an archive
dedicated to high precision photometric surveys for transiting exoplanets. We
present a summary of the NStED stellar database, functionality, tools, and user
interface. NStED currently serves the following kinds of data for 140,000 stars
(where available): coordinates, multiplicity, proper motion, parallax, spectral
type, multiband photometry, radial velocity, metallicity, chromospheric and
coronal activity index, and rotation velocity/period. Furthermore, the
following derived quantities are given wherever possible: distance, effective
temperature, mass, radius, luminosity, space motions, and physical/angular
dimensions of habitable zone. Queries to NStED can be made using constraints on
any combination of the above parameters. In addition, NStED provides tools to
derive specific inferred quantities for the stars in the database,
cross-referenced with available extra-solar planetary data for those host
stars. NStED can be accessed at http://nsted.ipac.caltech.edu


  [Fe(phen)2(NCS)2] is a prototype transition metal complex material, which
undergoes a phase transition between low-spin (LS) and high-spin (HS) phases,
induced by temperature, pressure or light. Vibrational modes play a key role
for spin-state switching both in thermal and photo-induced cases, by
contributing to vibrational entropy for thermal equilibrium transitions or
driving the fast structural trapping of the photoinduced high spin state. Here
we study the crystal phonon modes of [Fe(phen)2(NCS)2], by combining THz, IR,
and Raman spectroscopies sensitive to modes in different frequency ranges and
different symmetries. We compare the experimental results to DFT calculations
performed in a periodic 3D crystal for understanding the phonon modes in the
crystal, compared to molecular vibrations. Indeed, each vibrational mode of the
isolated molecule combines into several modes of different symmetry and
frequency in the crystal, as the unit cell contains four molecules. We focus
our attention on the HS symmetric and anti-symmetric breathing modes in the
crystal as well as on the N-CS stretching modes.


  The dipole blockade between Rydberg atoms has been proposed as a basic tool
in quantum information processing with neutral atoms. Here we demonstrate
experimentally the Rydberg blockade of two individual atoms separated by 4
$\mu$m. Moreover, we show that, in this regime, the single atom excitation is
enhanced by a collective two-atom behavior associated with the excitation of an
entangled state. This observation is a crucial step towards the deterministic
manipulation of entanglement of two or more atoms using the Rydberg dipole
interaction.


  A review of some recent results on the dynamical theory of the Yang-Baxter
maps (also known as set-theoretical solutions to the quantum Yang-Baxter
equation) is given. The central question is the integrability of the transfer
dynamics. The relations with matrix factorisations, matrix KdV solitons,
Poisson Lie groups, geometric crystals and tropical combinatorics are discussed
and demonstrated on several concrete examples.


  The CM chondrites are characterized as primary accretionary rocks which
originate from primitive water-rich asteroids formed during the early Solar
System. Here, we study the mineralogy and organic characteristics of right CM
and one ungrouped chondrite to better understand their alteration history;
Queen Alexandra Range 93005 (QUE 93005), Murchison, LaPaz Icefield 02333 (LAP
02333), Miller Range (MIL 13005), Mackay Glacier 05231 (MCY 05231), Northwest
Africa 8534 (NWA 8534), Northwest Africa 3340 (NWA 3340), Yamato 86695
(Y-86695), and the ungrouped carbonaceous chondrite Belgica 7904 (B-7904).
Raman spectroscopy has been employed to detect the presence of organic carbon
in the samples, specifically through the G band at approximately 1580 cm-1 and
D band at around 1350 cm-1. The properties of organic matter in meteorites
serve as valuable indicators for characterizing the structure and crystallinity
of carbonaceous materials and estimating their thermal metamorphism degree. The
R1 parameter, defined as the peak height ratio of the D and G bands, provides a
quantifiable measure of this structural organization. Raman spectra are used to
show the general mineralogy, thermal history and heating stage of CM and
ungrouped chondrites. X-ray diffraction patterns further indicate the
mineralogical compositions of the samples. Visible to near-infrared (VNIR) and
attenuated total reflection (ATR) reflectance spectra illustrate the trends
related to their mineralogy and furthermore infer aqueous alteration, thermal
history of CM carbonaceous chondrites, formation and evolution of their parent
bodies.


  Galaxy formation models within cosmological hydrodynamical simulations
contain numerous parameters with non-trivial influences over the resulting
properties of simulated cosmic structures and galaxy populations. It is
computationally challenging to sample these high dimensional parameter spaces
with simulations, particularly for halos in the high-mass end of the mass
function. In this work, we develop a novel sampling and reduced variance
regression method, CARPoolGP, which leverages built-in correlations between
samples in different locations of high dimensional parameter spaces to provide
an efficient way to explore parameter space and generate low variance
emulations of summary statistics. We use this method to extend the Cosmology
and Astrophysics with MachinE Learning Simulations (CAMELS) to include a set of
768 zoom-in simulations of halos in the mass range of $10^{13} - 10^{14.5}
M_\odot\,h^{-1}$ that span a 28-dimensional parameter space in the IllustrisTNG
model. With these simulations and the CARPoolGP emulation method, we explore
parameter trends in the Compton $Y-M$, black hole mass-halo mass, and
metallicity-mass relations, as well as thermodynamic profiles and quenched
fractions of satellite galaxies. We use these emulations to provide a physical
picture of the complex interplay between supernova and active galactic nuclei
feedback. We then use emulations of the $Y-M$ relation of massive halos to
perform Fisher forecasts on astrophysical parameters for future
Sunyaev-Zeldovich observations and find a significant improvement in forecasted
constraints. We publicly release both the simulation suite and CARPoolGP
software package.


  Even though tens of directly imaged companions have been discovered in the
past decades, the number of directly confirmed multiplanet systems is still
small. Dynamical analysis of these systems imposes important constraints on
formation mechanisms of these wide-orbit companions. As part of the Young Suns
Exoplanet Survey (YSES) we report the detection of a second planetary-mass
companion around the 17 Myr-old, solar-type star TYC 8998-760-1 that is located
in the Lower Centaurus Crux subgroup of the Scorpius-Centaurus association. The
companion has a projected physical separation of 320 au and several individual
photometric measurements from 1.1 to 3.8 microns constrain a companion mass of
$6\pm1\,M_\mathrm{Jup}$, which is equivalent to a mass ratio of
$q=0.57\pm0.10\%$ with respect to the primary. With the previously detected
$14\pm3\,M_\mathrm{Jup}$ companion that is orbiting the primary at 160 au, TYC
8998-760-1 is the first directly imaged multiplanet system that is detected
around a young, solar analog. We show that circular orbits are stable, but that
mildly eccentric orbits for either/both components ($e > 0.1$) are chaotic on
Gyr timescales, implying in-situ formation or a very specific ejection by an
unseen third companion. Due to the wide separations of the companions TYC
8998-760-1 is an excellent system for spectroscopic and photometric follow-up
with space-based observatories such as the James Webb Space Telescope.


  We report the detection of super-hard (>10 keV) X-ray emission extending up
to 70 keV from the classical nova V2491 Cygni using the Suzaku observatory. We
conducted two ~20 ks target-of-opportunity observations 9 and 29 days after the
outburst on 2008 April 11, yielding wide energy range spectra by combining the
X-ray Imaging Spectrometer and the Hard X-ray Detector. On day 9, a spectrum
was obtained at 1.0-70 keV with the Fe XXV K\alpha line feature and a very flat
continuum, which is explained by thermal plasma with a 3 keV temperature and
power-law emission with a photon index of 0.1 attenuated by a heavy extinction
of 1.4x10^{23} cm^{-2}. The 15-70 keV luminosity at 10.5 kpc is 6x10^{35} ergs
s^{-1}. The super-hard emission was not present on day 29. This is the highest
energy at which X-rays have been detected from a classical nova. We argue a
non-thermal origin for the emission, which suggests the presence of accelerated
charged particles in the nova explosion.


  Topology based analysis of time-series data from dynamical systems is
powerful: it potentially allows for computer-based proofs of the existence of
various classes of regular and chaotic invariant sets for high-dimensional
dynamics. Standard methods are based on a cubical discretization of the
dynamics and use the time series to construct an outer approximation of the
underlying dynamical system. The resulting multivalued map can be used to
compute the Conley index of isolated invariant sets of cubes. In this paper we
introduce a discretization that uses instead a simplicial complex constructed
from a witness-landmark relationship. The goal is to obtain a natural
discretization that is more tightly connected with the invariant density of the
time series itself. The time-ordering of the data also directly leads to a map
on this simplicial complex that we call the witness map. We obtain conditions
under which this witness map gives an outer approximation of the dynamics, and
thus can be used to compute the Conley index of isolated invariant sets. The
method is illustrated by a simple example using data from the classical H\'enon
map.


  We consider a homoclinic orbit to a saddle fixed point of an arbitrary
$C^\infty$ map $f$ on $\mathbb{R}^2$ and study the phenomenon that $f$ has an
infinite family of asymptotically stable, single-round periodic solutions. From
classical theory, this requires $f$ to have a homoclinic tangency. We show it
also necessary for $f$ to satisfy a `global resonance' condition and for the
eigenvalues associated with the fixed point, $\lambda$ and $\sigma$, to satisfy
$|\lambda \sigma| = 1$. The phenomenon is codimension-three in the case
$\lambda \sigma = -1$, but codimension-four in the case $\lambda \sigma = 1$
because here the coefficients of the leading-order resonance terms associated
with $f$ at the fixed point must add to zero. We also identify conditions
sufficient for the phenomenon to occur, illustrate the results for an abstract
family of maps, and show numerically computed basins of attraction.


  Quasi-spherical accretion in wind-fed X-ray pulsars is discussed. At X-ray
luminosities <4 10^{36} erg/s, a hot convective shell is formed around the
neutron star magnetosphere, and subsonic settling accretion regime sets in. In
this regime, accretion rate onto neutron star is determined by the ability of
plasma to enter magnetosphere via Rayleigh-Taylor instability. A gas-dynamic
theory of settling accretion is constructed taking into account anisotropic
turbulence. The angular momentum can be transferred through the quasi-static
shell via large-scale convective motions initiating turbulence cascade. The
angular velocity distribution in the shell is found depending on the turbulent
viscosity prescription. Comparison with observations of long-period X-ray
wind-fed pulsars shows that an almost iso-angular-momentum distribution is most
likely realized in their shells. The theory explains long-term spin-down in
wind- fed accreting pulsars (e.g. GX 1+4) and properties of short-term
torque-luminosity correlations. The theory can be applied to slowly rotating
low-luminosity X-ray pulsars and non-stationary accretion phenomena observed in
some SFXTs.


  A recent thrust in turbulence closure modeling research is to incorporate
machine learning (ML) elements, such as neural networks, for the purpose of
enhancing the predictive capability to a broader class of flows. Such a
turbulence closure framework entails solving a system of equations comprised of
ML functionals coupled with traditional (physics-based - PB) elements. While
combining closure elements from fundamentally different ideologies can lead to
unprecedented progress, there are many critical challenges that must be
overcome. This study examines three such challenges: (i) Physical compatibility
(or lack thereof) between ML and PB constituents of the modeling system of
equations; (ii) Internal (self) consistency of the ML training process; and
(iii) Formulation of an optimal objective (or loss) function for training.
These issues are critically important for generalization of the ML-enhanced
methods to predictive computations of complex engineering flows. Training and
implementation strategies in current practice that may lead to significant
incompatibilities and inconsistencies are identified. Using the simple test
case of turbulent channel flow, key deficiencies are highlighted and proposals
for mitigating them are investigated. Compatibility constraints are evaluated
and it is demonstrated that an iterative training procedure can help ensure
certain degree of consistency. In summary, this work develops foundational
tenets to guide development of ML-enhanced turbulence closure models.


  The main contribution of this paper is a generalization of several previous
localization theories in equivariant symplectic geometry, including the
classical Atiyah-Bott/Berline-Vergne localization theorem, as well as many
cases of the localization via the norm-square of the momentum map as initiated
and developed by Witten, Paradan, and Woodward. Our version unifies and
generalizes these theories by using noncompact cobordisms as in previous work
of Guillemin, Ginzburg, and Karshon, and by introducing a more flexible notion
of `polarization' than in previous theories. Our localization formulas are also
valid for closed 2-forms that may be degenerate. As a corollary, we are able to
answer a question posed some time ago by Shlomo Sternberg concerning the
classical Brianchon-Gram polytope decomposition,. We illustrate our theory
using concrete examples motivated by our answer to Sternberg's question.


  This paper considers multiple regression procedures for analyzing the
relationship between a response variable and a vector of covariates in a
nonparametric setting where both tuning parameters and the number of covariates
need to be selected. We introduce an approach which handles the dilemma that
with high dimensional data the sparsity of data in regions of the sample space
makes estimation of nonparametric curves and surfaces virtually impossible.
This is accomplished by abandoning the goal of trying to estimate true
underlying curves and instead estimating measures of dependence that can
determine important relationships between variables.


  In this paper we provide the final steps in the proof, announced by
Eskin-Fisher-Whyte, of quasi-isometric rigidity of a class of non-nilpotent
polycyclic groups. To this end, we prove a rigidity theorem on the boundaries
of certain negatively curved homogeneous spaces and combine it with work of
Eskin-Fisher-Whyte and Peng on the structure of quasi-isometries of certain
solvable Lie groups.


  Although deep RL models have shown a great potential for solving various
types of tasks with minimal supervision, several key challenges remain in terms
of learning from limited experience, adapting to environmental changes, and
generalizing learning from a single task. Recent evidence in decision
neuroscience has shown that the human brain has an innate capacity to resolve
these issues, leading to optimism regarding the development of
neuroscience-inspired solutions toward sample-efficient, and generalizable RL
algorithms. We show that the computational model combining model-based and
model-free control, which we term the prefrontal RL, reliably encodes the
information of high-level policy that humans learned, and this model can
generalize the learned policy to a wide range of tasks. First, we trained the
prefrontal RL, and deep RL algorithms on 82 subjects' data, collected while
human participants were performing two-stage Markov decision tasks, in which we
manipulated the goal, state-transition uncertainty and state-space complexity.
In the reliability test, which includes the latent behavior profile and the
parameter recoverability test, we showed that the prefrontal RL reliably
learned the latent policies of the humans, while all the other models failed.
Second, to test the ability to generalize what these models learned from the
original task, we situated them in the context of environmental volatility.
Specifically, we ran large-scale simulations with 10 Markov decision tasks, in
which latent context variables change over time. Our information-theoretic
analysis showed that the prefrontal RL showed the highest level of adaptability
and episodic encoding efficacy. This is the first attempt to formally test the
possibility that computational models mimicking the way the brain solves
general problems can lead to practical solutions to key challenges in machine
learning.


  Daily monitoring of stress is a critical component of maintaining optimal
physical and mental health. Physiological signals and contextual information
have recently emerged as promising indicators for detecting instances of
heightened stress. Nonetheless, developing a real-time monitoring system that
utilizes both physiological and contextual data to anticipate stress levels in
everyday settings while also gathering stress labels from participants
represents a significant challenge. We present a monitoring system that
objectively tracks daily stress levels by utilizing both physiological and
contextual data in a daily-life environment. Additionally, we have integrated a
smart labeling approach to optimize the ecological momentary assessment (EMA)
collection, which is required for building machine learning models for stress
detection. We propose a three-tier Internet-of-Things-based system architecture
to address the challenges. We utilized a cross-validation technique to
accurately estimate the performance of our stress models. We achieved the
F1-score of 70\% with a Random Forest classifier using both PPG and contextual
data, which is considered an acceptable score in models built for everyday
settings. Whereas using PPG data alone, the highest F1-score achieved is
approximately 56\%, emphasizing the significance of incorporating both PPG and
contextual data in stress detection tasks.


  Resonant field enhancement in optical cavities is provided over only narrow
linewidths and for specific spatial modes. Consequently, spectrally restrictive
planar Fabry-P{\'e}rot cavities have not contributed to date to white-light
imaging, which necessitates a highly multimoded broadband field to satisfy the
resonance condition. Here we show that introducing judicious angular-dispersion
circumvents the fundamental trade-off between cavity linewidth and finesse in a
Fabry-P{\'e}rot cavity by exciting a 130-nm-bandwidth achromatic resonance
across the visible spectrum, which far exceeds the finesse-limited linewidth
(0.5~nm), and even exceeds the free spectral range (45~nm). This omni-resonant
configuration enables broadband color-imaging over a 100-nm-bandwidth in the
visible with minimal spherical and chromatic aberrations. We demonstrate
omni-resonant imaging using coherent and incoherent light, and spatially
extended and localized fields comprising stationary and moving objects. This
work paves the way to harnessing broadband resonant enhancements for spatially
structured fields, as needed for example in solar windows.


  We fully characterize those von Neumann algebras having the ball-covering
property. We also study the ball-covering property of noncommutative symmetric
spaces. In particular, we provide a number of new examples of non-separable
(commutative and noncommutative) Banach spaces having the ball-covering
property.


  Introduction: Wrist instability remains a common health concern. The
potential of dynamic Magnetic Resonance Imaging (MRI) in assessing carpal
dynamics associated with this condition is a field of ongoing research. This
study contributes to this line of inquiry by developing MRI-derived carpal
kinematic metrics and investigating their stability. Methods: A previously
described 4D MRI approach for tracking the movements of carpal bones in the
wrist was deployed in this study. A panel of 120 metrics characterizing
radial/ulnar deviation and flexion extension movements was constructed by
fitting low order polynomial models of scaphoid and lunate degrees of freedom
against that of the capitate. Intraclass Correlation Coefficients were utilized
to analyze intra- and inter-subject stability within a mixed cohort of 49
subjects, including 20 with and 29 without a history of wrist injury. Results:
A comparable degree of stability across the two different wrist movements. Out
of the total 120 derived metrics, distinct subsets demonstrated high stability
within each type of movement. Among asymptomatic subjects, 16 out of 17 metrics
with high intra-subject stability also showed high inter-subject stability.
Interestingly, some quadratic term metrics, although relatively unstable within
asymptomatic subjects, showed increased stability within this group, hinting at
potential differentiation in their behavior across different cohorts.
Conclusion: This study showed the developing potential of dynamic MRI to
characterize complex carpal bone dynamics. Stability analyses of the derived
kinematic metrics showed encouraging differences between cohorts with and
without a history of wrist injury. Although these broad metric stability
variations highlight the potential utility of this approach for analysis of
carpal instability, further studies are necessary to better characterize these
observations.


  We show how shape transitions in the neutron-rich exotic Si and S isotopes
occur in terms of shell-model calculations with a newly constructed Hamiltonian
based on V_MU interaction. We first compare the calculated
spectroscopic-strength distributions for the proton 0d_5/2,3/2 and 1s_1/2
orbitals with results extracted from a 48Ca(e,e'p) experiment to show the
importance of the tensor-force component of the Hamiltonian. Detailed
calculations for the excitation energies, B(E2) and two-neutron separation
energies for the Si and S isotopes show excellent agreement with experimental
data. The potential energy surface exhibits rapid shape transitions along the
isotopic chains towards N=28 that are different for Si and S. We explain the
results in terms of an intuitive picture involving a Jahn-Teller-type effect
that is sensitive to the tensor-force-driven shell evolution. The closed
sub-shell nucleus 42Si is a particularly good example of how the
tensor-force-driven Jahn-Teller mechanism leads to a strong oblate rather than
spherical shape.


  We prove several singular value inequalities for sum and product of compact
operators in Hilbert space. Some of our results generalize the previous
inequalities for operators. Also, applications of some inequalities are given.


  An algebraic system from a finite set $\Sigma$ of cardinality $k$ and an
$n$-ary operation $f$ invertible in each argument is called an $n$-ary
quasigroup of order $k$. An autotopy of an $n$-ary quasigroup $(\Sigma,f)$ is a
collection $(\theta_0,\theta_1,...,\theta_n)$ of $n+1$ permutations of $\Sigma$
such that $f(\theta_1(x_1),...,\theta_n(x_n))\equiv
\theta_0(f(x_1,\ldots,x_n))$. We show that every $n$-ary quasigroup of order
$4$ has at least $2^{[n/2]+2}$ and not more than $6\cdot 4^n$ autotopies. We
characterize the $n$-ary quasigroups of order $4$ with $2^{(n+3)/2}$, $2\cdot
4^n$, and $6\cdot 4^n$ autotopies.


  Low-energy background through Compton scattering from the ambient $\gamma$
rays can be contaminated in direct dark matter search experiments. In this
paper, we report comparable measurements on low-energy spectra via Compton
scattering from several $\gamma$-ray sources with a p-type point-contact
germanium detector. The spectra between 500 eV and 18 keV have been measured
and analyzed. Moreover, the features of the electron binding effect,
particularly at the edges of the K- and L-shells in the germanium atom, were
observed with different gamma sources and were consistent with the models in
the Geant4 simulation. An empirical background model is proposed that provides
insights into understanding the low-energy background in germanium for direct
dark matter experiments.


  Here we discuss the ultraviolet and infrared aspects of the noncommutative
counterpart of QED, which is called as noncommutative QED, as well as some
infrared dynamics of noncommutative Yang-Mills (NCYM) theory. First we
demonstrate that the divergence in the theory can be subtracted by the similar
counterterms as in ordinary theory at one loop level. Then the anomalous
magnetic moment is calculated to see the infrared aspect of the theory which
reflects the violation of Lorentz symmetry. The evaluation of the finite part
of the photon vacuum polarization shows that the logarithmically singular term
in the infrared limit appears with the same weight as UV logarithmic
divergence, showing the correlation between the UV and infrared dynamics in
NCYM theory. NC-QED theory does not show such a property. We also consider the
extension to chiral gauge theory in the present context, but the requirement of
anomaly cancellation allows only noncommutative QED.


  We consider the models Y_{i,n}=\int_0^{i/n}
\sigma(s)dW_s+\tau(i/n)\epsilon_{i,n}, and \tilde
Y_{i,n}=\sigma(i/n)W_{i/n}+\tau(i/n)\epsilon_{i,n}, i=1,...,n, where W_t
denotes a standard Brownian motion and \epsilon_{i,n} are centered i.i.d.
random variables with E(\epsilon_{i,n}^2)=1 and finite fourth moment.
Furthermore, \sigma and \tau are unknown deterministic functions and W_t and
(\epsilon_{1,n},...,\epsilon_{n,n}) are assumed to be independent processes.
Based on a spectral decomposition of the covariance structures we derive series
estimators for \sigma^2 and \tau^2 and investigate their rate of convergence of
the MISE in dependence of their smoothness. To this end specific basis
functions and their corresponding Sobolev ellipsoids are introduced and we show
that our estimators are optimal in minimax sense. Our work is motivated by
microstructure noise models. Our major finding is that the microstructure noise
\epsilon_{i,n} introduces an additionally degree of ill-posedness of 1/2;
irrespectively of the tail behavior of \epsilon_{i,n}. The method is
illustrated by a small numerical study.


  The ANTARES group at the University of Erlangen is working towards the
integration of a set of acoustic sensors into the ANTARES Neutrino Telescope.
With this setup, tests of acoustic particle detection methods and background
studies shall be performed. The ANTARES Neutrino Telescope, which is currently
being constructed in the Mediterranean Sea, will be equipped with the
infrastructure to accommodate a 3-dimensional array of photomultipliers for the
detection of Cherenkov light. Within this infrastructure, the required
resources for acoustic sensors are available: Bandwidth for the transmission of
the acoustic data to the shore, electrical power for the off-shore electronics
and physical space to install the acoustic sensors and to route the connecting
cables (transmitting signals and power) into the electronics containers. It
will be explained how the integration will be performed with minimal
modifications of the existing ANTARES design and which setup is foreseen for
the acquisition of the acoustic data.


  The prevalent use of large language models (LLMs) in various domains has
drawn attention to the issue of "hallucination," which refers to instances
where LLMs generate factually inaccurate or ungrounded information. Existing
techniques for hallucination detection in language assistants rely on intricate
fuzzy, specific free-language-based chain of thought (CoT) techniques or
parameter-based methods that suffer from interpretability issues. Additionally,
the methods that identify hallucinations post-generation could not prevent
their occurrence and suffer from inconsistent performance due to the influence
of the instruction format and model style. In this paper, we introduce a novel
pre-detection self-evaluation technique, referred to as SELF-FAMILIARITY, which
focuses on evaluating the model's familiarity with the concepts present in the
input instruction and withholding the generation of response in case of
unfamiliar concepts. This approach emulates the human ability to refrain from
responding to unfamiliar topics, thus reducing hallucinations. We validate
SELF-FAMILIARITY across four different large language models, demonstrating
consistently superior performance compared to existing techniques. Our findings
propose a significant shift towards preemptive strategies for hallucination
mitigation in LLM assistants, promising improvements in reliability,
applicability, and interpretability.


  Xenophobia is one of the key drivers of marginalisation, discrimination, and
conflict, yet many prominent machine learning (ML) fairness frameworks fail to
comprehensively measure or mitigate the resulting xenophobic harms. Here we aim
to bridge this conceptual gap and help facilitate safe and ethical design of
artificial intelligence (AI) solutions. We ground our analysis of the impact of
xenophobia by first identifying distinct types of xenophobic harms, and then
applying this framework across a number of prominent AI application domains,
reviewing the potential interplay between AI and xenophobia on social media and
recommendation systems, healthcare, immigration, employment, as well as biases
in large pre-trained models. These help inform our recommendations towards an
inclusive, xenophilic design of future AI systems.


  Supernova-driven outflows from early galaxies may have had a large impact on
the kinetic and chemical structure of the intergalactic medium (IGM). We use
three-dimensional Monte Carlo cosmological realizations of a simple linear
peaks model to track the time evolution of such metal-enriched outflows and
their feedback on galaxy formation. We find that at most 30% of the IGM by
volume is enriched to values above 10^-3 solar in models that only include
objects that cool by atomic transitions. The majority of enrichment occurs
relatively early (5 < z < 12) and resulting in a mass-averaged cosmological
metallicity between 10^-3 and 10^-1.5 solar. The inclusion of Population III
objects that cool through H2 line emission has only a minor impact on these
results: increasing the mean metallicity and filling factor by at most a factor
of 1.4, and moving the dawn of the enrichment epoch to a redshift of
approximately 14 at the earliest. Thus enrichment by outflowing galaxies is
likely to have been incomplete and inhomogeneous, biased to the areas near the
starbursting galaxies themselves. Models with a 10% star formation efficiency
can satisfactorily reproduce the nearly constant (2 < z < 5, Z approximately
3.5 x 10^-4 solar) metallicity of the low column density Ly-alpha forest
derived by Songaila (2001), an effect of the decreasing efficiency of metal
loss from larger galaxies. Finally, we show that IGM enrichment is intimately
tied to the ram-pressure stripping of baryons from neighboring perturbations.
This results in the suppression of at least 20% of the dwarf galaxies in the
mass range 10^8.5 to 10^9.5 solar, in all models with filling factors greater
than 2%, and an overall suppression of approximately 50% of dwarf galaxies in
the most observationally-favored model.


  In this letter we have considered the eigenvalues and eigenfunctions of
relativistic massless scalar particle which conformally coupled to the
background of Einstein universe. We found the eigenvalues and eigenfunctions
exactly.


  On 1977 August 15, the Ohio State University Radio Observatory detected a
strong narrowband signal northwest of the globular star cluster M55 in the
constellation Sagittarius. The frequency of the signal, which closely matched
the hydrogen line (1420.40575177 MHz), peaked at approximately 2316 EDT. Since
then, several investigations into the Wow signal have ruled out the source as
terrestrial in origin or other objects such as satellites, planets and
asteroids. From 1977 July 27 to 1977 August 15, comets 266P Christensen and
P2008 Y2 (Gibbs) were transiting in the neighborhood of the Chi Sagittarii star
group. Because the frequency for the Wow! signal fell close to the hydrogen
line, and the hydrogen clouds of 266P/Christensen and P/2008 Y2 (Gibbs) were in
the proximity of the right ascension and declination values of the Wow signal,
the comet(s) and or their hydrogen clouds are strong candidates for the source
of the 1977 Wow signal.


  We prove an upper bound for the (differentiated) density of states of the
Anderson model at the bottom of the spectrum. The density of states is shown to
exhibit the same Lifshitz tails upper bound as the integrated density of
states.


  We propose a method to simultaneously determine the magnetic centers of
multiple quadrupoles in a transport line or a storage ring. The method finds
the magnet centers by correcting the orbit shift due to a change of the
quadrupole gradient strengths with orbit correctors. The quadrupoles are
selected with orbit corrector magnets and beam position monitors in between to
ensure that orbit correction at the quadrupole locations can be achieved. The
correction of the induced orbit shift is done by steering the orbit toward the
quadrupole centers with correctors, using its response matrix with respect to
the correctors. The response matrix can be measured or calculated. Simulations
with a section of the Linac Coherent Light Source (LCLS) II and the SPEAR3
storage ring are done to demonstrate the feasibility and performance of the
method. It is also experimentally tested on SPEAR3. The method can be extended
for beam based alignment measurement of nonlinear magnets.


  We demonstrate how boson sampling with photons of partial distinguishability
can be expressed in terms of interference of fewer photons. We use this
observation to propose a classical algorithm to simulate the output of a boson
sampler fed with photons of partial distinguishability. We find conditions for
which this algorithm is efficient, which gives a lower limit on the required
indistinguishability to demonstrate a quantum advantage. Under these
conditions, adding more photons only polynomially increases the computational
cost to simulate a boson sampling experiment.


  Action recognition and human pose estimation are closely related but both
problems are generally handled as distinct tasks in the literature. In this
work, we propose a multitask framework for jointly 2D and 3D pose estimation
from still images and human action recognition from video sequences. We show
that a single architecture can be used to solve the two problems in an
efficient way and still achieves state-of-the-art results. Additionally, we
demonstrate that optimization from end-to-end leads to significantly higher
accuracy than separated learning. The proposed architecture can be trained with
data from different categories simultaneously in a seamlessly way. The reported
results on four datasets (MPII, Human3.6M, Penn Action and NTU) demonstrate the
effectiveness of our method on the targeted tasks.


  We place perturbative unitarity constraints on both the dimensionful and
dimensionless couplings in the Next-to-Minimal Supersymmetric Standard Model
Higgs Sector. These constraints, plus the requirement that the singlino and/or
Higgsino constitutes at least part of the observed dark matter relic abundance,
generate upper bounds on the Higgs and neutralino/chargino mass spectrum. We
obtain an upper bound of 12 TeV for the charginos and neutralinos and 20 TeV
for the heavy Higgses outside defined fine-tuned regions. By using the NMSSM as
a template, we describe a method which replaces naturalness arguments with more
rigorous perturbative unitarity arguments to get a better understanding of when
new physics will appear.


  We study the series of complex nonassociative algebras On and real
nonassociative algebras $O_{p,q}$ introduced in [10]. These algebras generalize
the classical algebras of octonions and Clifford algebras. The algebras $O_{n}$
and $O_{p,q}$ with $p + q = n$ have a natural $Z_n^2$-grading, and they are
characterized by cubic forms over the field $Z_2$. We establish a periodicity
for the algebras $O_{n}$ and $O_{p,q}$ similar to that of the Clifford algebras
Cln and $Cl_{p,q}$.


  In Weyl semimetals the application of parallel electric and magnetic fields
leads to valley polarization -- an occupation disbalance of valleys of opposite
chirality -- a direct consequence of the chiral anomaly. In this work, we
present numerical tools to explore such nonequilibrium effects in spatially
confined three-dimensional systems with a variable disorder potential, giving
exact solutions to leading order in the disorder potential and the applied
electric field. Application to a Weyl-metal slab shows that valley polarization
also occurs without an external magnetic field as an effect of chiral anomaly
"trapping": Spatial confinement produces chiral bulk states, which enable the
valley polarization in a similar way as the chiral states induced by a magnetic
field. Despite its finite-size origin, the valley polarization can persist up
to macroscopic length scales if the disorder potential is sufficiently long
ranged, so that direct inter-valley scattering is suppressed and the relaxation
then goes via the Fermi-arc surface states.


  The recent excitement about Dirac and Weyl fermion systems has renewed
interest in magnetotransport properties of multi-carrier systems. However, the
complexity of their analysis, even in the simplest two-carrier case, has
hampered a good understanding of the underlying phenomena. Here we propose a
new analysis scheme for two independent conduction channels, that strongly
reduces previous ambiguities and allows to draw robust conclusions. This is
demonstrated explicitly for the example of three-dimensional topological
insulators. Their temperature and gate voltage-dependent Hall coefficient and
transverse magnetoresistance behavior, including the phenomenon of huge linear
transverse magnetoresistance, can be traced back to two conduction channels,
with fully determined carrier concentrations and mobilities. We further derive
an upper limit for the transverse magnetoresistance. Its violation implies
field dependences in the electronic band structure or scattering processes, or
the presence of more than two effective carrier types. Remarkably, none of the
three-dimensional topological insulators or semimetals with particularly large
transverse magnetoresistance violates this limit.


  In certain situations the state of a quantum system, after transmission
through a quantum channel, can be perfectly restored. This can be done by
'coding' the state space of the system before transmission into a 'protected'
part of a larger state space, and by applying a proper 'decoding' map
afterwards. We investigate two kinds of protected subspaces: the error
correction subspaces and the dark subspaces. In neither case information leaks
out of the system, but in the second it is more difficult to restore the state.
Recent results on higher rank numerical ranges of operators are used to
construct examples. In particular, dark spaces are constructed for any map of
rank 2, for a biased permutations channel and for certain separable maps acting
on multipartite systems. Furthermore, error correction subspaces are provided
for a class of three unitary noise models.


  Recent empirical work has shown that human children are adept at learning and
reasoning with probabilities. Here, we model a recent experiment investigating
the development of school-age children's non-symbolic probability reasoning
ability using the Neural Probability Learner and Sampler (NPLS) system. We
demonstrate that NPLS can accurately simulate children's probability judgments
at different ages, tasks and difficulty levels to discriminate two
probabilistic choices through accurate probability learning and sampling. An
extension of NPLS using a skewed heuristic distribution can also model
children's tendency to wrongly select the outcome with more favorable items but
less likely to draw the favorable ones when the probabilistic choices are
similar. We discuss the roles of two model parameters that can be adjusted to
simulate the probability matching versus probability maximization phenomena in
children, and why frequency biases children's probabilistic judgments.


  In order to benchmark the 3-dimensional calculation of the atmospheric
neutrino flux based on the FLUKA Monte Carlo code, muon fluxes in the
atmosphere have been computed and compared with data taken by the CAPRICE94
experiment at ground level and at different altitudes in the atmosphere. For
this purpose only two additions have been introduced with respect to the
neutrino flux calculation: the specific solar modulation corresponding to the
period of data taking and the bending of charged particles in the atmosphere.
Results are in good agreement with experimental data, although improvements in
the model are possible. At this level, however, it is not possible to
disentangle the interplay between the primary flux and the interaction model.


  We introduce the notion of two-dimensional Coxeter system and show that
parabolic subgroups of GL_n(F_2) can be described by an appropriate
two-dimensional Coxeter system.


  We offer a method for one-shot mask-guided image synthesis that allows
controlling manipulations of a single image by inverting a quasi-robust
classifier equipped with strong regularizers. Our proposed method, entitled
MAGIC, leverages structured gradients from a pre-trained quasi-robust
classifier to better preserve the input semantics while preserving its
classification accuracy, thereby guaranteeing credibility in the synthesis.
Unlike current methods that use complex primitives to supervise the process or
use attention maps as a weak supervisory signal, MAGIC aggregates gradients
over the input, driven by a guide binary mask that enforces a strong, spatial
prior. MAGIC implements a series of manipulations with a single framework
achieving shape and location control, intense non-rigid shape deformations, and
copy/move operations in the presence of repeating objects and gives users firm
control over the synthesis by requiring to simply specify binary guide masks.
Our study and findings are supported by various qualitative comparisons with
the state-of-the-art on the same images sampled from ImageNet and quantitative
analysis using machine perception along with a user survey of 100+ participants
that endorse our synthesis quality. Project page at
https://mozhdehrouhsedaghat.github.io/magic.html. Code is available at
https://github.com/mozhdehrouhsedaghat/magic


  The Glauber model is reconsidered based on a quantum formulation of the
Master equation. Unlike the conventional approach the temperature and the Ising
energy are included from the beginning by introducing a Heisenberg-like picture
of the second quantized operators. This method enables us to get an exact
expression for the transition rate of a single flip-process $w_i(\sigma_i)$
which is in accordance with the principle of detailed balance. The transition
rate differs significantly from the conventional one due to Glauber in the low
temperature regime. Here the behavior is controlled by the Ising energy and not
by the microscopic time scale.


  We compare the two-year COBE DMR sky maps with the predictions of
cosmological-constant cold dark matter models. Using a Bayesian analysis, we
find that the most likely value of the cosmological constant in such a model is
Lambda = 0. The data set an upper limit on Lambda of 0.78 (0.85) at 90%
confidence, and 0.86 (0.92) at 95% confidence with (without) the quadrupole
anisotropy.


  We present a differential calculus on the extension of the quantum plane
obtained considering that the (bosonic) generator $x$ is invertible and
furthermore working polynomials in $\ln x$ instead of polynomials in $x$. We
call quantum Lie algebra to this extension and we obtain its Hopf algebra
structure and its dual Hopf algebra. Differential geometry of the quantum Lie
algebra of the extended quantum plane and its Hopf algebra structure is
obtained. Its dual Hopf algebra is also given.


  We develop a rigorous theoretical approach for analyzing inelastic scattering
of photon pairs in arrays of two-level qubits embedded in a waveguide. Our
analysis reveals strong enhancement of the scattering when the energy of
incoming photons resonates with the double-excited subradiant states. We
identify the role of different double-excited states in the scattering such as
superradiant, subradiant, and twilight states, being a product of
single-excitation bright and subradiant states. Importantly, the N-excitation
subradiant states can be engineered only if the number of qubits exceeds 2N.
Both the subradiant and twilight states can generate long-lived photon-photon
correlations, paving the way to a storage and processing of quantum
information.


  In this paper, we propose a novel joint caching and non-orthogonal multiple
access (NOMA) scheme to facilitate advanced downlink transmission for next
generation cellular networks. In addition to reaping the conventional
advantages of caching and NOMA transmission, the proposed cache-aided NOMA
scheme also exploits cached data for interference cancellation which is not
possible with separate caching and NOMA transmission designs. Furthermore, as
caching can help to reduce the residual interference power, several decoding
orders are feasible at the receivers, and these decoding orders can be flexibly
selected for performance optimization. We characterize the achievable rate
region of cache-aided NOMA and investigate its benefits for minimizing the time
required to complete video file delivery. Our simulation results reveal that,
compared to several baseline schemes, the proposed cache-aided NOMA scheme
significantly expands the achievable rate region for downlink transmission,
which translates into substantially reduced file delivery times.


  We present optical spectroscopy of several (candidate) ultra-compact X-ray
binaries (UCXBs) obtained with the ESO VLT and Gemini-North telescopes. In only
one of five observed UCXB candidates did we find evidence for H in its spectrum
(4U 1556-60). For XB 1905+00 the optical counterpart is not detected. For the
known UCXBs 4U 1626-67 and XB 1916-05 we find spectra consistent with a C/O and
a He/N accretion disc respectively, the latter is the first optical spectrum of
a He-rich donor in an UCXB. Interestingly, the C/O spectrum of 4U 1626-67 shows
both similarities as well as marked differences from the optical C/O spectrum
of 4U 0614+09. We obtained phase resolved spectroscopy of 4U 0614+09 and the 44
min transient XTE J0929-314. In neither object were we able to detect clear
orbital periodicities, highlighting the difficulties of period determinations
in UCXBs. We reanalysed the spectra of XTE J0929-314 that were taken close to
the peak of its 2003 X-ray outburst and do not confirm the detection of Halpha
emission as was claimed in the literature. The peak spectra do show strong C or
N emission around 4640A, as has also been detected in other UCXBs. We discuss
the implications of our findings for our understanding of the formation of
UCXBs and the Galactic population of UCXBs. At the moment all studied systems
are consistent with having white dwarf donors, the majority being C/O rich.


  The relativistic phase-space representation by means of the usual position
and momentum operators for a class of observables with Weyl symbols independent
of charge variable (i.e. with any combination of position and momentum) is
proposed. The dynamical equation coincides with its analogue in the non-local
theory (generalization of the Newton-Wigner position operator approach) under
conditions when particles creation is impossible. Differences reveal themselves
in specific constraints on possible initial conditions.


  An increasing number of works have devoted to the application of Transition
Adjacency Relation (TAR) as a means to capture behavioral features of business
process models. In this paper, we systematically study the efficient TAR
derivation from process models using unfolding technique which previously has
been used to address the state space explosion when dealing with concurrent
behaviors of a Petri net. We reveal and formally describe the equivalence
between TAR and Event Adjacency Relation (EAR), the manifestation of TAR in the
Complete Prefix Unfolding (CPU) of a Petri net. By computing TARs from CPU
using this equivalence, we can alleviate the concurrency caused state-explosion
issues. Furthermore, structural boosting rules are categorized, proved and
added to the TAR computing algorithm. Formal proofs of correctness and
generality of CPU-based TAR computation are provided for the first time by this
work, and they significantly expand the range of Petri nets from which TARs can
be efficiently derived. Experiments on both industrial and synthesized process
models show the effectiveness of proposed CPU-based algorithms as well as the
observation that they scale well with the increase in size and concurrency of
business process models.


  Multi-object spectroscopy (MOS) instruments, such as the Two-degree Field
(2dF) facility of the Anglo-Australian Observatory (AAO), have facilitated
large-scale redshift surveys. Yet despite their acclaim, instrument design has
been suspected of introducing subtle selection effects into surveys.
Investigation into these selection effects has been overshadowed by instrument
complexity. We identify the field configuration algorithm (FCA) used to select
targets for observation as mainly responsible for such effects. A FCA can
imprint artificial structure on observed target distributions, which may accrue
over large angular scales, potentially to the detriment of statistical analyses
applied to such surveys. We present here a new FCA developed for 2dF that is
based on simulated annealing (SA), a generic method commonly used to solve
constrained optimisation problems. We generate synthetic fields and utilise
mock 2dF volumes to contrast the behaviour of previous strategies with the SA
FCA. The angular two-point correlation function and other sensitive techniques
reveal that the new FCA achieves unprecedented sampling uniformity and target
yield with improved target priority handling and observational flexibility over
current FCAs. The SA FCA is generic enough to be used by current 2dF-like and
potentially next-generation MOS instruments with little modification.


  Understanding ultrafast coherent electron dynamics is necessary for
application of a single-electron source to metrological standards, quantum
information processing, including electron quantum optics, and quantum sensing.
While the dynamics of an electron emitted from the source has been extensively
studied, there is as yet no study of the dynamics inside the source. This is
because the speed of the internal dynamics is typically higher than 100 GHz,
beyond state-of-the-art experimental bandwidth. Here, we theoretically and
experimentally demonstrate that the internal dynamics in a silicon
singleelectron source comprising a dynamic quantum dot can be detected,
utilising a resonant level with which the dynamics is read out as
gate-dependent current oscillations. Our experimental observation and
simulation with realistic parameters show that an electron wave packet
spatially oscillates quantum-coherently at $\sim$ 200 GHz inside the source.
Our results will lead to a protocol for detecting such fast dynamics in a
cavity and offer a means of engineering electron wave packets. This could allow
high-accuracy current sources, high-resolution and high-speed
electromagnetic-field sensing, and high-fidelity initialisation of flying
qubits.


  We consider the electron-vibron coupling in suspended nanotube quantum dots.
Modelling the tube as an elastic medium, we study the possible coupling
mechanism for exciting the stretching mode in a single-electron-transistor
setup. Both the forces due to the longitudinal and the transverse fields are
included. The effect of the longitudinal field is found to be too small to be
seen in experiment. In contrast, the transverse field which couple to the
stretching mode via the bending of the tube can in some cases give sizeable
Franck-Condon factors. However, the length dependence is not compatible with
recent experiments [Sapmaz et al. cond-mat/0508270].


  A combination of a priority queueing model and mean field theory shows the
emergence of traders' swarm behavior, even when each has a subjective
prediction of the market driven by a limit order book. Using a nonlinear Markov
model, we analyze the dynamics of traders who select a favorable order price
taking into account the waiting cost incurred by others. We find swarm behavior
emerges because of the delay in trader reactions to the market, and the
direction of the swarm is decided by the current market position and the
intensity of zero-intelligent random behavior, rather than subjective trader
predictions.


  When aggregating information from conflicting sources, one's goal is to find
the truth. Most real-value \emph{truth discovery} (TD) algorithms try to
achieve this goal by estimating the competence of each source and then
aggregating the conflicting information by weighing each source's answer
proportionally to her competence. However, each of those algorithms requires
more than a single source for such estimation and usually does not consider
different estimation methods other than a weighted mean. Therefore, in this
work we formulate, prove, and empirically test the conditions for an Empirical
Bayes Estimator (EBE) to dominate the weighted mean aggregation. Our main
result demonstrates that EBE, under mild conditions, can be used as a second
step of any TD algorithm in order to reduce the expected error.


  Associated to an embedded surface in the $3$-sphere, we construct a diagram
of fundamental groups, and prove that it is a complete invariant, wherefrom we
deduce complete invariants of handlebody links, tunnels of handlebody links,
and spatial graphs.The main ingredients in the proof of the completeness are a
generalization of the Kneser conjecture for $3$-manifolds with boundary proved
also here, and extensions of Waldhausen's theorem by Evans, Tucker and Swarup.
Computable invariants of handlebody links derived therefrom are calculated.


  The way of reduction of metal oxyde semiconductor (MOS) structures is going
to reach limitations and new devices have to be explored as an alternative to
MOS technology. Molecular electronic and more particularly
self-assembly-molecular technique on silicon substrate gives interesting
results as seen in the literature. We are going to study n-alkyltrichlorosilane
grafting on oxidised silicon, characterise it macroscopically with ellipsometer
and goniometry measurements, and down to microscopic scale with atomic force
microscopy. Once the uniformity of the monolayer is verified (roughness of few
Angstr\"oms) we have tested a sputtering method deposition to form aluminium
dots onto the surface. Also metal-insulator-semiconductor diodes are tested
measuring both leakage current between gate and substrate and
capacitance-voltage. The sputtering method deposition can be improved in order
to decrease the gate leakage current and we would like to test another
evaporation method. Further application we want to study is gas sensors using
conjugated organic films or synthetic polymers and concerns the drift current
with gas absorption.


  Modeling time series is a research focus in cryospheric sciences because of
the complexity and multiscale nature of events of interest. Highly non-uniform
sampling of measurements from different sensors with different levels of
accuracy, as is typical for measurements of ice sheet elevations, makes the
problem even more challenging. In this paper, we propose a spline-based
approximation framework (ALPS - Approximation by Localized Penalized Splines)
for modeling time series of land ice changes. The localized support of the
B-spline basis functions enable robustness to non-uniform sampling, a
considerable improvement over other global and piecewise local models. With
features like, discrete-coordinate-difference-based penalization and two-level
outlier detection, ALPS further guarantees the stability and quality of
approximations. ALPS incorporates rigorous model uncertainty estimates with all
approximations. As demonstrated by examples, ALPS performs well for a variety
of data sets, including time series of ice sheet thickness, elevation,
velocity, and terminus locations. The robust estimation of time series and
their derivatives facilitates new applications, such as the reconstruction of
high-resolution elevation change records by fusing sparsely sampled time series
of ice sheet thickness changes with modeled firn thickness changes, and the
analysis of the relationship between different outlet glacier observations to
gain new insight into processes and forcing.


  We describe a method for recovering of the substructure, internal dynamics
and geometrical shapes of clusters of galaxies. Applying the method to the
Virgo cluster, we, first, reveal the substructure of the central 4 arc degree
field of the Virgo cluster by means of S-tree technique. The existence of three
main subgroups of galaxies is revealed and their dynamical characteristics are
estimated. Then, using the previously suggested technique (Gurzadyan and Rauzy
1997), the bulk flow velocities of the subgroups are evaluated based on the
distribution of the redshifts of the galaxies. The results enable us also to
obtain a secure indication of the elongation of the Virgo cluster and its
positional inclination.


  Recently, a novel model for a regular black hole was advocated which
possesses an asymptotically Minkowski core implemented via an exponential
suppression (in the core region) of the Misner-Sharp quasi-local mass. Using
this regular black hole as a template, we shall construct a spherically
symmetric thin-shell traversable wormhole using the "cut-and-paste" technique,
thereby constructing yet another black hole mimicker. The surface stress-energy
at the wormhole throat is calculated, and the stability of the wormhole is
analyzed. An important result is that, (as compared to their Schwarzschild
thin-shell counterparts), increasing the exponential suppression of the
Misner-Sharp quasi-local mass by increasing the suppression parameter "a", also
considerably increases the stability regions for these thin-shell wormholes,
and furthermore minimizes the amount of energy condition violating exotic
matter required to keep the wormhole throat open.


  We study the phase transition of the coalitional manipulation problem for
generalized scoring rules. Previously it has been shown that, under some
conditions on the distribution of votes, if the number of manipulators is
$o(\sqrt{n})$, where $n$ is the number of voters, then the probability that a
random profile is manipulable by the coalition goes to zero as the number of
voters goes to infinity, whereas if the number of manipulators is
$\omega(\sqrt{n})$, then the probability that a random profile is manipulable
goes to one. Here we consider the critical window, where a coalition has size
$c\sqrt{n}$, and we show that as $c$ goes from zero to infinity, the limiting
probability that a random profile is manipulable goes from zero to one in a
smooth fashion, i.e., there is a smooth phase transition between the two
regimes. This result analytically validates recent empirical results, and
suggests that deciding the coalitional manipulation problem may be of limited
computational hardness in practice.


  We describe the design and x-ray emission properties (temporal, spatial, and
spectral) of Dry Pinch I, a portable X-pinch driver developed at Imperial
College London. Dry Pinch I is a direct capacitor discharge device, 300x300x700
mm3 in size and approximately 50 kg in mass, that can be used as an external
driver for x-ray diagnostics in high-energy-density physics experiments. Among
key findings, the device is shown to reliably produce 1.1 +- 0.3 ns long x-ray
bursts that couple approximately 50 mJ of energy into photon energies from 1 to
10 keV. The average shot-to-shot jitter of these bursts is found to be 10 +-
4.6 ns using a combination of x-ray and current diagnostics. The spatial extent
of the x-ray hot spot from which the radiation emanates agrees with previously
published results for X-pinches suggesting a spot size of 10 +- 6 um in the
soft energy region (1-10 keV) and 190 +- 100 um in the hard energy region (>10
keV). These characteristics mean that Dry Pinch I is ideally suited for use as
a probe in experiments driven in the laboratory or at external facilities when
more conventional sources of probing radiation are not available. At the same
time, this is also the first detailed investigation of an X-pinch operating
reliably at current rise rates of less than 1 kA/ns.


  We present new multi-band (UBVI) time-series data of helium burning variables
in the Carina dwarf spheroidal galaxy. The current sample includes 92 RR
Lyrae-six of them are new identifications-and 20 Anomalous Cepheids, one of
which is new identification. The analysis of the Bailey diagram shows that the
luminosity amplitude of the first overtone component in double-mode variables
is located along the long-period tail of regular first overtone variables,
while the fundamental component is located along the short-period tale of
regular fundamental variables. This evidence further supports the transitional
nature of these objects. Moreover, the distribution of Carina double-mode
variables in the Petersen diagram (P_1/P_0 vs P_0) is similar to metal-poor
globulars (M15, M68), to the dwarf spheroidal Draco and to the Galactic Halo.
This suggests that the Carina old stellar population is metal-poor and affected
by a small spread in metallicity. We use trigonometric parallaxes for five
field RR Lyrae stars to provide an independent estimate of the Carina distance
using the observed reddening free Period--Wesenheit [PW, (BV)] relation. Theory
and observations indicate that this diagnostic is independent of metallicity.
We found a true distance modulus of \mu=20.01\pm0.02 (standard error of the
mean) \pm0.05 (standard deviation) mag. We also provided independent estimates
of the Carina true distance modulus using four predicted PW relations (BV, BI,
VI, BVI) and we found: \mu=(20.08\pm0.007\pm0.07) mag,
\mu=(20.06\pm0.006\pm0.06) mag, \mu=(20.07\pm0.008\pm0.08) mag and
\mu=(20.06\pm0.006\pm0.06) mag. Finally, we identified more than 100 new SX
Phoenicis stars that together with those already known in the literature (340)
make Carina a fundamental laboratory to constrain the evolutionary and
pulsation properties of these transitional variables.


  We study the prediction of the Effective Field Theory of Large Scale
Structures (EFTofLSS) for the matter power spectrum at different redshifts. In
previous work, we found that the two-loop prediction can match the nonlinear
power spectrum measured from $N$-body simulations at redshift zero within
approximately 2% up to $k\sim 0.6\,h\, {\rm Mpc}^{-1}$ after fixing a single
free parameter, the so-called "speed of sound". We determine the time evolution
of this parameter by matching the EFTofLSS prediction to simulation output at
different redshifts, and find that it is well-described by a fitting function
that only includes one additional parameter. After the two free parameters are
fixed, the prediction agrees with nonlinear data within approximately 2% up to
at least $k\sim 1\,h\, {\rm Mpc}^{-1}$ at $z\geq 1$, and also within
approximately 5% up to $k\sim 1.2\,h\, {\rm Mpc}^{-1}$ at $z=1$ and $k\sim
2.3\,h\, {\rm Mpc}^{-1}$ at $z=3$, a major improvement with respect to other
perturbative techniques. We also develop an accurate way to estimate where the
EFTofLSS predictions at different loop orders should fail, based on the sizes
of the next-order terms that are neglected, and find agreement with the actual
comparisons to data. Finally, we use our matter power spectrum results to
perform analytical calculations of lensing potential power spectra
corresponding to both CMB and galaxy lensing. This opens the door to future
direct applications of the EFTofLSS to observations of gravitational clustering
on cosmic scales.


  We introduce a method for assigning photorealistic relightable materials to
3D shapes in an automatic manner. Our method takes as input a photo exemplar of
a real object and a 3D object with segmentation, and uses the exemplar to guide
the assignment of materials to the parts of the shape, so that the appearance
of the resulting shape is as similar as possible to the exemplar. To accomplish
this goal, our method combines an image translation neural network with a
material assignment neural network. The image translation network translates
the color from the exemplar to a projection of the 3D shape and the part
segmentation from the projection to the exemplar. Then, the material prediction
network assigns materials from a collection of realistic materials to the
projected parts, based on the translated images and perceptual similarity of
the materials. One key idea of our method is to use the translation network to
establish a correspondence between the exemplar and shape projection, which
allows us to transfer materials between objects with diverse structures.
Another key idea of our method is to use the two pairs of (color, segmentation)
images provided by the image translation to guide the material assignment,
which enables us to ensure the consistency in the assignment. We demonstrate
that our method allows us to assign materials to shapes so that their
appearances better resemble the input exemplars, improving the quality of the
results over the state-of-the-art method, and allowing us to automatically
create thousands of shapes with high-quality photorealistic materials. Code and
data for this paper are available at https://github.com/XiangyuSu611/TMT.


  We show that the formation/evaporation of Black Holes (BH) unitarizes quantum
gravity at all the orders of the perturbation theory. Non-perturbative quantum
effects save the scattering amplitudes from any polynomial divergences. Such a
phenomena is intimately related to the dynamical emergence of an effective
non-locality as well as emergent modifications of the Heisenberg's uncertainty
principle. The BH production de-localizes quantum gravity vertices and
propagators as a consequence of its holographically stored entropy. In this
sense, quantum gravity is a superrenormalizable theory, although non-locality
is hidden in its action.


  We study Mellin pseudodifferential operators (shortly, Mellin PDO's) with
symbols in the algebra $\widetilde{\mathcal{E}}(\mathbb{R}_+,V(\mathbb{R}))$ of
slowly oscillating functions of limited smoothness introduced in \cite{K09}. We
show that if
$\mathfrak{a}\in\widetilde{\mathcal{E}}(\mathbb{R}_+,V(\mathbb{R}))$ does not
degenerate on the "boundary" of $\mathbb{R}_+\times\mathbb{R}$ in a certain
sense, then the Mellin PDO ${\rm Op}(\mathfrak{a})$ is Fredholm on the space
$L^p$ for $p\in(1,\infty)$ and each its regularizer is of the form ${\rm
Op}(\mathfrak{b})+K$ where $K$ is a compact operator on $L^p$ and
$\mathfrak{b}$ is a certain explicitly constructed function in the same algebra
$\widetilde{\mathcal{E}}(\mathbb{R}_+,V(\mathbb{R}))$ such that
$\mathfrak{b}=1/\mathfrak{a}$ on the "boundary" of
$\mathbb{R}_+\times\mathbb{R}$. This result complements a known Fredholm
criterion from \cite{K09} for Mellin PDO's with symbols in the closure of
$\widetilde{\mathcal{E}}(\mathbb{R}_+,V(\mathbb{R}))$.


  Technology and the fruition of cultural heritage are becoming increasingly
more entwined, especially with the advent of smart audio guides, virtual and
augmented reality, and interactive installations. Machine learning and computer
vision are important components of this ongoing integration, enabling new
interaction modalities between user and museum. Nonetheless, the most frequent
way of interacting with paintings and statues still remains taking pictures.
Yet images alone can only convey the aesthetics of the artwork, lacking is
information which is often required to fully understand and appreciate it.
Usually this additional knowledge comes both from the artwork itself (and
therefore the image depicting it) and from an external source of knowledge,
such as an information sheet. While the former can be inferred by computer
vision algorithms, the latter needs more structured data to pair visual content
with relevant information. Regardless of its source, this information still
must be be effectively transmitted to the user. A popular emerging trend in
computer vision is Visual Question Answering (VQA), in which users can interact
with a neural network by posing questions in natural language and receiving
answers about the visual content. We believe that this will be the evolution of
smart audio guides for museum visits and simple image browsing on personal
smartphones. This will turn the classic audio guide into a smart personal
instructor with which the visitor can interact by asking for explanations
focused on specific interests. The advantages are twofold: on the one hand the
cognitive burden of the visitor will decrease, limiting the flow of information
to what the user actually wants to hear; and on the other hand it proposes the
most natural way of interacting with a guide, favoring engagement.


  We present Spitzer 3.6, 4.5, 5.8, 8.0, and 24 micron images of the Mon OB1
East giant molecular cloud, which contains the young star forming region NGC
2264, as well as more extended star formation. With Spitzer data and 2MASS
photometry, we identify and classify young stellar objects (YSOs) with dusty
circumstellar disks and/or envelopes in Mon OB1 East by their infrared-excess
emission and study their distribution with respect to cloud material. We find a
correlation between the local surface density of YSOs and column density of
molecular gas as traced by dust extinction that is roughly described as a power
law in these quantities. NGC 2264 follows a power law index of ~2.7, exhibiting
a large YSO surface density for a given gas column density. Outside of NGC 2264
where the surface density of YSOs is lower, the power law is shallower and the
region exhibits a larger gas column density for a YSO surface density,
suggesting the star formation is more recent. In order to measure the fraction
of cloud members with circumstellar disks/envelopes, we estimate the number of
diskless pre-main sequence stars by statistical removal of background star
detections. We find that the disk fraction of the NGC 2264 region is 45%, while
the surrounding more distributed regions show a disk fraction of 19%. This may
be explained by the presence an older, more dispersed population of stars. In
total, the Spitzer observations provide evidence for heterogenous, non-coeval
star formation throughout the Mon OB1 cloud.


  The galaxy Luminosity Function (LF) has been estimated in the rest frame B
luminosity at 0<z<1.25 and at 1700 {\AA} for 2.5<z<4.5 from deep multicolor
surveys in the HDF-N, HDF-S, NTT-DF. The results have been compared with a
recent version of galaxy formation models in the framework of hierarchical
clustering in a flat Cold Dark Matter Universe with cosmological constant. The
results show a general agreement for z<= 1, although the model LF has a steeper
average slope at the faint end; at z~3 such feature results in an
overprediction of the number of faint (I_{AB}~ 27) galaxies, while the
agreement at the bright end becomes critically sensitive to the details of dust
absorption at such redshifts. The discrepancies at the faint end show that a
refined treatement of the physical processes involving smaller galaxies is to
be pursued in the models, in terms of aggregation processes and/or stellar
feedback heavily affecting the luminosity of the low luminosity objects. The
implications of our results on the evolution of the cosmological star formation
rate are discussed.


  I report recent results on hidden charm spectroscopy from Belle. These
include: observation of a near-threshold enhancement in the omega-J/psi
invariant mass distribution for exclusive B-->K omega J/psi decays; evidence
for the decay X(3872)-->pi+pi-pi0 J/psi, where the pi+pi-pi0 invariant mass
distribution has a strong peak between 750 MeV and the kinematic limit of 775
MeV, suggesting that the process is dominated by the sub-threshold decay
X-->omega J/psi; and the observation of a peak near 3940 MeV in the J/psi
recoil mass spectrum for the inclusive continuum process e+e- --> J/psi X. The
results are based on a study of a 287 fb-1 sample of e+e- annihilation data
collected at center- of-mass energies around the Upsilon(4S) in the Belle
detector at the KEKB collider.


  First galaxies formed within halos of mass M=E7.5-E9 Msun at z=30-40 in the
standard cold dark matter (CDM) universe may each display an extended hydrogen
21-cm absorption halo against the cosmic microwave background with a brightness
temperature decrement of del T=-(100-150)mK at a radius 0.3 < r < 3.0 comoving
Mpc, corresponding to an angular size of 10-100 arcseconds. A 21-cm tomographic
survey in the redshift shell z=30-40 (at 35-45MHz), which could be carried out
by the next generation of radio telescopes, is expected to be able to detect
millions of first galaxies and may prove exceedingly profitable in enabling (at
least) four fundamental applications for cosmology and galaxy formation. First,
it may yield direct information on star formation physics in first galaxies.
Second, it could provide a unique and sensitive probe of small-scale power in
the standard cosmological model hence physics of dark matter and inflation.
Third, it would allow for an independent, perhaps "cleaner" characterization of
interesting features on large scales in the power spectrum such as the baryonic
oscillations. Finally, possibly the most secure, each 21-cm absorption halo is
expected to be highly spherical and faithfully follow the Hubble flow. By
applying the Alcock-Paczynski test to a significant sample of first galaxies,
one may be able to determine the dark energy equation of state with an accuracy
likely only limited by the accuracy with which the matter density can be
determined independently.