  Coupled mixed convective and stratified systems are common in natural flows.
To study experimentally the associated dynamics, we use a singular property of
water: its non-linear equation of state is characterised by a maximum density
close to $4^{\circ}$C. By heating the top of a tank at $35^{\circ}$C and
cooling the bottom at $0^{\circ}$C, a two-layer configuration spontaneously
appears. The convective motion in the bottom layer consists mostly of a
large-scale circulation and rising cold plumes. This turbulent flow generates
propagating internal gravity waves in the upper stably-stratified layer. PIV
measurements are performed and spectral characteristics of the convection and
internal gravity waves are presented. An horizontal large-scale reversing flow
in the stratified layer is observed which is viscously driven by a third,
intermediate layer. This buffer layer is located between the convective and
stratified layers and is thermally coupled with the convective one, hence
sustaining a strong horizontal shear. Three dimensional direct numerical
simulations with geometry and physical parameters close to the experimental
ones corroborate our experimental results.


  With excellent efficiencies being reported from multiple labs across the
world, device stability and the degradation mechanisms have emerged as the key
aspects that could determine the future prospects of perovskite solar cells.
However, the related experimental efforts remain scattered due to the lack of
any unifying theoretical framework. In this context, here we provide a
comprehensive analysis of ion migration effects in perovskite solar cells.
Specifically, we show, for the first time, that (a) the effect of ionic charges
is almost indistinguishable from that of dopant ions, (b) ion migration could
lead to simultaneous improvement in Voc and degradation in Jsc - a unique
observation which is beyond the realm of mere parametric variation in carrier
mobility and lifetime, (c) champion devices are more resilient towards the ill
effects of ion migration, and finally (d) we propose unique characterization
schemes to determine both magnitude and polarity of ionic species. Our results,
supported by detailed numerical simulations and direct comparison with
experimental data, are of broad interest and provide a much needed predictive
capability towards the research on performance degradation mechanisms in
perovskite solar cells


  In this paper, we propose a taxonomy for 360{\deg} videos that categorizes
videos based on moving objects and camera motion. We gathered and produced 28
videos based on the taxonomy, and recorded viewport traces from 60 participants
watching the videos. In addition to the viewport traces, we provide the
viewers' feedback on their experience watching the videos, and we also analyze
viewport patterns on each category.


  The discovery of a large number of supermassive black holes (SMBH) at
redshifts $z > 6$, when the Universe was only 900 million years old, raises the
question of how such massive compact objects could form in a cosmologically
short time interval. Each of the standard scenarios proposed, involving rapid
accretion of seed black holes or black hole mergers, faces severe theoretical
difficulties in explaining the short-time formation of supermassive objects. In
this work we propose an alternative scenario for the formation of SMBH in the
early Universe, in which energy transfer from superconducting cosmic strings
piercing small seed black holes is the main physical process leading to rapid
mass increase. As a toy model, the accretion rate of a seed black hole pierced
by two antipodal strings carrying constant current is considered. Using an
effective action approach, which phenomenologically incorporates a large class
of superconducting string models, we estimate the minimum current required to
form SMBH with masses of order $M = 2 \times 10^{9}M_{\odot}$ by $z = 7.085$.
This corresponds to the mass of the central black hole powering the quasar ULAS
J112001.48+064124.3 and is taken as a test case scenario for early-epoch SMBH
formation. For GUT scale strings, the required fractional increase in the
string energy density, due to the presence of the current, is of order
$10^{-7}$, so that their existence remains consistent with current
observational bounds on the string tension. In addition, we consider an
"exotic" scenario, in which an SMBH is generated when a small seed black hole
is pierced by a higher-dimensional $F-$string, predicted by string theory. We
find that both topological defect strings and fundamental strings are able to
carry currents large enough to generate early-epoch SMBH via our proposed
mechanism.


  We evaluate the action of Hecke operators on Siegel Eisenstein series of
degree 2, square-free level and arbitrary character, without using knowledge of
their Fourier coefficients. From this we construct a basis of simultaneous
eigenforms for the full Hecke algebra, and we compute their eigenvalues. As
well, we obtain Hecke relations among the Eisenstein series. Using these Hecke
relations in the case that $\stufe$ is square-free and the character is
trivial, we generate a basis for the space of Eisenstein series.


  In this paper we address the problem of matching sets of vectors embedded in
the same input space. We propose an approach which is motivated by canonical
correlation analysis (CCA), a statistical technique which has proven successful
in a wide variety of pattern recognition problems. Like CCA when applied to the
matching of sets, our extended canonical correlation analysis (E-CCA) aims to
extract the most similar modes of variability within two sets. Our first major
contribution is the formulation of a principled framework for robust inference
of such modes from data in the presence of uncertainty associated with noise
and sampling randomness. E-CCA retains the efficiency and closed form
computability of CCA, but unlike it, does not possess free parameters which
cannot be inferred directly from data (inherent data dimensionality, and the
number of canonical correlations used for set similarity computation). Our
second major contribution is to show that in contrast to CCA, E-CCA is readily
adapted to match sets in a discriminative learning scheme which we call
discriminative extended canonical correlation analysis (DE-CCA). Theoretical
contributions of this paper are followed by an empirical evaluation of its
premises on the task of face recognition from sets of rasterized appearance
images. The results demonstrate that our approach, E-CCA, already outperforms
both CCA and its quasi-discriminative counterpart constrained CCA (C-CCA), for
all values of their free parameters. An even greater improvement is achieved
with the discriminative variant, DE-CCA.


  A fraction of brightest cluster galaxies (BCGs) shows bright emission in the
UV and the blue part of the optical spectrum, which has been interpreted as
evidence of recent star formation. Most of these results are based on the
analysis of broadband photometric data. Here, we study the optical spectra of a
sample of 19 BCGs hosted by X-ray luminous galaxy clusters at 0.15 < z < 0.3, a
subset from the Canadian Cluster Comparison Project (CCCP) sample. We identify
plausible star formation histories of the galaxies by fitting Simple Stellar
Populations (SSPs) as well as composite populations, consisting of a young
stellar component superimposed on an intermediate/old stellar component, to
accurately constrain their star formation histories. We detect prominent young
(~200 Myr) stellar populations in 4 of the 19 galaxies. Of the four, the BCG in
Abell 1835 shows remarkable A-type stellar features indicating a relatively
large population of young stars, which is extremely unusual even amongst star
forming BCGs. We constrain the mass contribution of these young components to
the total stellar mass to be typically between 1% to 3%, but rising to 7% in
Abell 1835. We find that the four of the BCGs with strong evidence for recent
star formation (and only these four galaxies) are found within a projected
distance of 5 kpc of their host cluster's X-ray peak, and the diffuse, X-ray
gas surrounding the BCGs exhibit a ratio of the radiative cooling-to-free-fall
time ($t_{c}/t_{ff}$) of < 10. These are also some of the clusters with the
lowest central entropy. Our results are consistent with the predictions of the
precipitation-driven star formation and AGN feedback model, in which the
radiatively cooling diffuse gas is subject to local thermal instabilities once
the instability parameter $t_{c}/t_{ff}$ falls below ~10, leading to the
condensation and precipitation of cold gas. [Abridged]


  I summarize the abilities of LEP-II, the SSC/LHC hadron colliders, and a
future high energy $\epem$ collider (NLC) to detect the Higgs bosons of the
Minimal Supersymmetric Model (MSSM). I then review the unique capabilities of a
back-scattered laser beam facility (BSLBF) at the NLC for detecting the heavier
neutral Higgs bosons (the $\hh$ and $\ha$) of the MSSM. A BSLBF could well
allow $\hh$ and $\ha$ discovery via inclusive $\gam\gam\rta \hh,\ha$ production
out to masses of order $0.8\sqrt s$, \ie\ roughly $400\gev$, at the NLC. In
addition, a BSLBF allows one to check for CP violation in the neutral Higgs
sector; such CP violation is predicted to be absent in the MSSM. (Full
postscript file available upon request. Macropackage phyzzx.tex required. To
appear in Proceedings of 23rd INFN Eloisatron Workshop.)


  We develop Neuron Shapley as a new framework to quantify the contribution of
individual neurons to the prediction and performance of a deep network. By
accounting for interactions across neurons, Neuron Shapley is more effective in
identifying important filters compared to common approaches based on activation
patterns. Interestingly, removing just 30 filters with the highest Shapley
scores effectively destroys the prediction accuracy of Inception-v3 on
ImageNet. Visualization of these few critical filters provides insights into
how the network functions. Neuron Shapley is a flexible framework and can be
applied to identify responsible neurons in many tasks. We illustrate additional
applications of identifying filters that are responsible for biased prediction
in facial recognition and filters that are vulnerable to adversarial attacks.
Removing these filters is a quick way to repair models. Enabling all these
applications is a new multi-arm bandit algorithm that we developed to
efficiently estimate Neuron Shapley values.


  In this work we study the following nonlocal problem
  \begin{equation*}
  \left\{
  \begin{aligned}
  M(\|u\|^2_X)(-\Delta)^s u&= \lambda {f(x)}|u|^{\gamma-2}u+{g(x)}|u|^{p-2}u
&&\mbox{in}\ \ \Omega,
  u&=0 &&\mbox{on}\ \ \mathbb R^N\setminus \Omega,
  \end{aligned}
  \right.
  \end{equation*}
  where $\Omega\subset \mathbb R^N$ is open and bounded with smooth boundary,
$N>2s, s\in (0, 1), M(t)=a+bt^{\theta-1},\;t\geq0$ with $ \theta>1, a\geq 0$
and $b>0$. The exponents satisfy $1<\gamma<2<{2\theta<p<2^*_{s}=2N/(N-2s)}$
(when $a\neq 0$) and $2<\gamma<2\theta<p<2^*_{s}$ (when $a=0$). The parameter
$\lambda$ involved in the problem is real and positive. The problem under
consideration has nonlocal behaviour due to the presence of nonlocal fractional
Laplacian operator as well as the nonlocal Kirchhoff term $M(\|u\|^2_X)$, where
$\|u\|^{2}_{X}=\iint_{\mathbb R^{2N}}
\frac{|u(x)-u(y)|^2}{\left|x-y\right|^{N+2s}}dxdy$. The weight functions $f,
g:\Omega\to \mathbb R$ are continuous, $f$ is positive while $g$ is allowed to
change sign. In this paper an extremal value of the parameter, a threshold to
apply Nehari manifold method, is characterized variationally for both
degenerate and non-degenerate Kirchhoff cases to show an existence of at least
two positive solutions even when $\lambda$ crosses the extremal parameter value
by executing fine analysis based on fibering maps and Nehari manifold.


  We consider connections between similar sublattices and coincidence site
lattices (CSLs), and more generally between similar submodules and coincidence
site modules of general (free) $\mathbb{Z}$-modules in $\mathbb{R}^d$.
  In particular, we generalise results obtained by S. Glied and M. Baake [1,2]
on similarity and coincidence isometries of lattices and certain lattice-like
modules called $\mathcal{S}$-modules. An important result is that the factor
group $\mathrm{OS}(M)/\mathrm{OC}(M)$ is Abelian for arbitrary
$\mathbb{Z}$-modules $M$, where $\mathrm{OS}(M)$ and $\mathrm{OC}(M)$ are the
groups of similar and coincidence isometries, respectively. In addition, we
derive various relations between the indices of CSLs and their corresponding
similar sublattices.
  [1] S. Glied, M. Baake, Similarity versus coincidence rotations of lattices,
Z. Krist. 223, 770--772 (2008). DOI: 10.1524/zkri.2008.1054
  [2] S. Glied, Similarity and coincidence isometries for modules, Can. Math.
Bull. 55, 98--107 (2011). DOI: 10.4153/CMB-2011-076-x


  Detecting a shallowly buried and elongated object and estimating its
orientation using a commonly adopted co-polarized GPR system is challenging due
to the presence of strong ground clutter that masks the target reflection. A
cross-polarized configuration can be used to suppress ground clutter and reveal
the object reflection, but it suffers from inconsistent detection capability
which significantly varies with different object orientations. To address this
issue, we propose a dual-cross-polarized detection (DCPD) method which utilizes
two cross-polarized antennas with a special arrangement to detect the object.
The signals reflected by the object and collected by the two antennas are
combined in a rotationally invariant manner to ensure both effective ground
clutter suppression and consistent detection irrespective of the object
orientation. In addition, we present a dual-cross-polarized orientation
estimation (DCPOE) algorithm to estimate the object orientation from the two
cross-polarized data. The proposed DCPOE algorithm is less affected by
environmental noise and performs robust and accurate azimuth angle estimation.
The effectiveness of the proposed techniques in the detection and orientation
estimation and their advantages over the existing method have been demonstrated
using experimental data. Comparison results show that the maximum and average
errors are 22.3{\deg} and 10.9{\deg} for the Alford rotation algorithm, while
those are 4.9{\deg} and 1.8{\deg} for the proposed DCPOE algorithm in the
demonstrated shallowly buried object cases. The proposed techniques can be
unified in a framework to facilitate the investigation and mapping of shallowly
buried and elongated targets.


  Gait recognition, referring to the identification of individuals based on the
manner in which they walk, can be very challenging due to the variations in the
viewpoint of the camera and the appearance of individuals. Current methods for
gait recognition have been dominated by deep learning models, notably those
based on partial feature representations. In this context, we propose a novel
deep network, learning to transfer multi-scale partial gait representations
using capsules to obtain more discriminative gait features. Our network first
obtains multi-scale partial representations using a state-of-the-art deep
partial feature extractor. It then recurrently learns the correlations and
co-occurrences of the patterns among the partial features in forward and
backward directions using Bi-directional Gated Recurrent Units (BGRU). Finally,
a capsule network is adopted to learn deeper part-whole relationships and
assigns more weights to the more relevant features while ignoring the spurious
dimensions. That way, we obtain final features that are more robust to both
viewing and appearance changes. The performance of our method has been
extensively tested on two gait recognition datasets, CASIA-B and OU-MVLP, using
four challenging test protocols. The results of our method have been compared
to the state-of-the-art gait recognition solutions, showing the superiority of
our model, notably when facing challenging viewing and carrying conditions.


  We introduce the task of scene-aware dialog. Our goal is to generate a
complete and natural response to a question about a scene, given video and
audio of the scene and the history of previous turns in the dialog. To answer
successfully, agents must ground concepts from the question in the video while
leveraging contextual cues from the dialog history. To benchmark this task, we
introduce the Audio Visual Scene-Aware Dialog (AVSD) Dataset. For each of more
than 11,000 videos of human actions from the Charades dataset, our dataset
contains a dialog about the video, plus a final summary of the video by one of
the dialog participants. We train several baseline systems for this task and
evaluate the performance of the trained models using both qualitative and
quantitative metrics. Our results indicate that models must utilize all the
available inputs (video, audio, question, and dialog history) to perform best
on this dataset.


  Dark matter particles with Planck-scale mass ($\simeq10^{19}\text{GeV}/c^2$)
arise in well-motivated theories and could be produced by several cosmological
mechanisms. Using a blind analysis of data collected over a 813 d live time
with DEAP-3600, a 3.3 t single-phase liquid argon-based dark matter experiment
at SNOLAB, a search for supermassive dark matter was performed, looking for
multiple-scatter signals. No candidate signal events were observed, leading to
the first direct detection constraints on Planck-scale mass dark matter.
Leading limits constrain dark matter masses between $8.3\times10^{6}$ and
$1.2\times10^{19} \text{GeV}/c^2$, and cross sections for scattering on
$^{40}$Ar between $1.0\times10^{-23}$ and $2.4\times10^{-18} \text{cm}^2$.
These are used to constrain two composite dark matter models.


  We tackle the problem of unsupervised visual descriptors compression, which
is a key ingredient of large-scale image retrieval systems. While the deep
learning machinery has benefited literally all computer vision pipelines, the
existing state-of-the-art compression methods employ shallow architectures, and
we aim to close this gap by our paper. In more detail, we introduce a DNN
architecture for the unsupervised compressed-domain retrieval, based on
multi-codebook quantization. The proposed architecture is designed to
incorporate both fast data encoding and efficient distances computation via
lookup tables. We demonstrate the exceptional advantage of our scheme over
existing quantization approaches on several datasets of visual descriptors via
outperforming the previous state-of-the-art by a large margin.


  We measure the redshift distribution of a sample of 28 giant arcs discovered
as a part of the Sloan Giant Arcs Survey (SGAS). Gemini/GMOS-North spectroscopy
provides precise redshifts for 24 arcs, and "redshift desert" constraints for
the remaining four. This is a direct measurement of the redshift distribution
of a uniformly selected sample of bright giant arcs, which is an observable
that can be used to inform efforts to predict giant arc statistics. Our primary
giant arc sample has a median redshift z=1.821 and nearly two thirds of the
arcs - 64% - are sources at z \gtrsim 1.4, indicating that the population of
background sources that are strongly lensed into bright giant arcs resides
primarily at high redshift. We also analyze the distribution of redshifts for
19 secondary strongly lensed background sources that are not visually apparent
in SDSS imaging, but were identified in deeper follow-up imaging of the lensing
cluster fields. Our redshift sample for the secondary sources is not
spectroscopically complete, but combining it with our primary giant arc sample
suggests that a large fraction of all background galaxies which are strongly
lensed by foreground clusters reside at z \gtrsim 1.4. Kolmogorov-Smirnov (KS)
tests indicate that our well-selected, spectroscopically complete primary giant
arc redshift sample can be reproduced with a model distribution that is
constructed from a combination of results from studies of strong lensing
clusters in numerical simulations, and observational constraints on the galaxy
luminosity function.


  If the recent observations suggesting a time variation of the fine structure
constant are correct, they imply the existence of an ultra light scalar
particle. This particle inevitably couples to nucleons through the
\alpha-dependence of their masses and thus mediates an isotope-dependent
long-range force. The strength of the coupling is within a couple of orders of
magnitude from the existing experimental bounds for such forces. The new force
can be potentially measured in the precision experimental tests of the
equivalence principle. Due to an interesting coincidence of the required
time-scales, the scalar filed in question can at the same time play the role of
a quintessence field.


  We study the strong vertices $N^*N\pi$, $N^*N^*\pi$ and $NN\pi$ in QCD, where
$N^*$ denotes the negative parity $N (1535)$ state. We use the most general
form of the interpolating currents to calculate the corresponding strong
coupling constants. It is obtained that the coupling associated to $N^*N\pi$
vertex is strongly suppressed compared to those related to two other vertices.
The strong coupling corresponding to $N^*N^*\pi$ is obtained to be roughly half
of that of $NN\pi$ vertex. We compare the obtained results on $N^*N\pi$ and
$NN\pi$ vertices with the existing predictions of other theoretical studies as
well as those extracted from the experimental data.


  This paper describes the architecture and the fundamental methodology of an
anomaly detector, which by continuously monitoring Simple Network Management
Protocol data and by processing it as complex-events, is able to timely
recognize patterns of faults and relevant cyber-attacks. This solution has been
applied in the context of smart grids, and in particular as part of a security
and resilience component of the Information and Communication Technologies
(ICT) Gateway, a middleware-based architecture that correlates and fuses
measurement data from different sources (e.g., Inverters, Smart Meters) to
provide control coordination and to enable grid observability applications. The
detector has been evaluated through experiments, where we selected some
representative anomalies that can occur on the ICT side of the energy
distribution infrastructure: non-malicious faults (indicated by patterns in the
system resources usage), as well as effects of typical cyber-attacks directed
to the smart grid infrastructure. The results show that the detection is
promisingly fast and efficient.


  The symmetry energy for nuclear matter and its relation to the neutron skin
in finite nuclei is discussed. The symmetry energy as a function of density
obtained in a self-consistent Green function approach is presented and compared
to the results of other recent theoretical approaches. A partial explanation of
the linear relation between the symmetry energy and the neutron skin is
proposed. The potential of several experimental methods to extract the neutron
skin is examined.


  Reconstruction and monitoring of displacement and strain fields is an
important problem in engineering. We analyze the remote and non-obtrusive
methods of strain measurement based on photogrammetry and Digital Image
Correlation (DIC). The method is based on covering the photographed surface
with a pattern of speckles and comparing the images taken before and after the
deformation. In this study, a comprehensive literature review and comparative
analysis of photogrammetric solutions is presented. The analysis is based on a
specially developed Digital Image Synthesizer To Reconstruct Strain in Solids
(DISTRESS) Simulator to generate synthetic images of displacement and stress
fields in order to investigate the intrinsic accuracy of the existing variants
of DIC. We investigated the Basic DIC and a commercial software VIC 2D, both
based on displacement field reconstruction with post processing strain
determination based on numerical differentiation. We also investigated what we
call the Extended DIC where the strain field is determined independently of the
displacement field. While the Basic DIC and VIC 2D are faster, the Extended DIC
delivers the best accuracy of strain reconstruction. The speckle pattern is
found to be playing a critical role in achieving high accuracy for DIC.
Increase in subset size for DIC does not significantly improves the accuracy,
while the smallest subset size depends on the speckle pattern and speckle size.
Increase in the overall image size provides more details but does not play
significant role in improving the accuracy, while significantly increasing the
computation cost.


  The growing demand for ride-hailing services has led to an increasing need
for accurate taxi demand prediction. Existing systems are limited to specific
regions, lacking generalizability to unseen areas. This paper presents a novel
taxi demand forecasting system that leverages a graph neural network to capture
spatial dependencies and patterns in urban environments. Additionally, the
proposed system employs a region-neutral approach, enabling it to train a model
that can be applied to any region, including unseen regions. To achieve this,
the framework incorporates the power of Variational Autoencoder to disentangle
the input features into region-specific and region-neutral components. The
region-neutral features facilitate cross-region taxi demand predictions,
allowing the model to generalize well across different urban areas.
Experimental results demonstrate the effectiveness of the proposed system in
accurately forecasting taxi demand, even in previously unobserved regions, thus
showcasing its potential for optimizing taxi services and improving
transportation efficiency on a broader scale.


  Imitation learning algorithms provide state-of-the-art results on many
structured prediction tasks by learning near-optimal search policies. Such
algorithms assume training-time access to an expert that can provide the
optimal action at any queried state; unfortunately, the number of such queries
is often prohibitive, frequently rendering these approaches impractical. To
combat this query complexity, we consider an active learning setting in which
the learning algorithm has additional access to a much cheaper noisy heuristic
that provides noisy guidance. Our algorithm, LEAQI, learns a difference
classifier that predicts when the expert is likely to disagree with the
heuristic, and queries the expert only when necessary. We apply LEAQI to three
sequence labeling tasks, demonstrating significantly fewer queries to the
expert and comparable (or better) accuracies over a passive approach.


  This paper presents a technique which exploits the occurrence of certain
events as observed by different sensors, to detect and classify objects. This
technique explores the extent of dependence between features being observed by
the sensors, and generates more informed probability distributions over the
events. Provided some additional information about the features of the object,
this fusion technique can outperform other existing decision level fusion
approaches that may not take into account the relationship between different
features. Furthermore, this paper addresses the issue of coping with damaged
sensors when using the model, by learning a hidden space between sensor
modalities which can be exploited to safeguard detection performance.


  We introduce SCAL, an algorithm designed to perform efficient
exploration-exploitation in any unknown weakly-communicating Markov decision
process (MDP) for which an upper bound $c$ on the span of the optimal bias
function is known. For an MDP with $S$ states, $A$ actions and $\Gamma \leq S$
possible next states, we prove a regret bound of $\widetilde{O}(c\sqrt{\Gamma
SAT})$, which significantly improves over existing algorithms (e.g., UCRL and
PSRL), whose regret scales linearly with the MDP diameter $D$. In fact, the
optimal bias span is finite and often much smaller than $D$ (e.g., $D=\infty$
in non-communicating MDPs). A similar result was originally derived by Bartlett
and Tewari (2009) for REGAL.C, for which no tractable algorithm is available.
In this paper, we relax the optimization problem at the core of REGAL.C, we
carefully analyze its properties, and we provide the first computationally
efficient algorithm to solve it. Finally, we report numerical simulations
supporting our theoretical findings and showing how SCAL significantly
outperforms UCRL in MDPs with large diameter and small span.


  We propose a new search strategy for heavy top partners at the early stages
of the LHC run-II, based on lepton-jet final states. Our results show that
final states containing a boosted massive jet and a hard lepton, in addition to
a top quark and possibly a forward jet, offer a new window to both detecting
and measuring top partners of mass $\sim 2$ TeV. Our resulting signal
significance is comparable or superior to the same sign di-lepton channels for
top partner masses heavier than roughly 1 TeV. Unlike the di-lepton channel,
the selection criteria we propose are sensitive both to $5/3$ and $1/3$ charge
top partners and allow for full reconstruction of the resonance mass peak.
  Our search strategy utilizes a simplified $b$-tagging procedure and the
Template Overlap Method to tag the massive boosted objects and reject the
corresponding backgrounds. In addition, we propose a new, pileup insensitive
method, to tag forward jets which characterize our signal events.
  We consider full effects of pileup contamination at 50 interactions per bunch
crossing. We demonstrate that even in the most pessimistic pileup scenarios,
the significance we obtain is sufficient to claim a discovery over a wide range
of top partner parameters. While we focus on the minimal natural composite
Higgs model, the results of this paper can be easily translated into bounds on
any heavy partner with a $t\bar{t}Wj$ final state topology.


  This paper is devoted to the parametric estimation of a shift together with
the nonparametric estimation of a regression function in a semiparametric
regression model. We implement a very efficient and easy to handle
Robbins-Monro procedure. On the one hand, we propose a stochastic algorithm
similar to that of Robbins-Monro in order to estimate the shift parameter. A
preliminary evaluation of the regression function is not necessary to estimate
the shift parameter. On the other hand, we make use of a recursive
Nadaraya-Watson estimator for the estimation of the regression function. This
kernel estimator takes into account the previous estimation of the shift
parameter. We establish the almost sure convergence for both Robbins-Monro and
Nadaraya--Watson estimators. The asymptotic normality of our estimates is also
provided. Finally, we illustrate our semiparametric estimation procedure on
simulated and real data.


  The COVID-19 pandemic and the implementation of social distancing policies
have rapidly changed people's visiting patterns, as reflected in mobility data
that tracks mobility traffic using location trackers on cell phones. However,
the frequency and duration of concurrent occupancy at specific locations govern
the transmission rather than the number of customers visiting. Therefore,
understanding how people interact in different locations is crucial to target
policies, inform contact tracing, and prevention strategies. This study
proposes an efficient way to reduce the spread of the virus among on-campus
university students by developing a self-developed Google History Location
Extractor and Indicator software based on real-world human mobility data. The
platform enables policymakers and researchers to explore the possibility of
future developments in the epidemic's spread and simulate the outcomes of human
mobility and epidemic state under different epidemic control policies. It
offers functions for determining potential contacts, assessing individual
infection risks, and evaluating the effectiveness of on-campus policies. The
proposed multi-functional platform facilitates the screening process by more
accurately targeting potential virus carriers and aids in making informed
decisions on epidemic control policies, ultimately contributing to preventing
and managing future outbreaks.


  We define a conformal reference frame, i.e., a special projection of the
six-dimensional sky bundle of a Lorentzian manifold (or the five-dimensional
twistor space) to a three-dimensional manifold. We construct an example, a
conformal compactification, for Minkowski space. Based on the complex structure
on the skies, we define the celestial transform of Lorentzian vectors, a kind
of spinor correspondence. We express a 1-form generating the contact structure
explicitly as a (line bundle)-valued form. We prove a theorem on the projection
of this 1-form to the fiberwise normal bundle of a reference frame; its
corollary is an equation for the flow of time.
  The Appendix is less mathematical than the main body and discusses the causal
relation in context of the FLRW cosmology and its natural conformal reference
frame.


  Rabi oscillations have long been thought to be out of reach in simulations
using time-dependent density functional theory (TDDFT), a prominent symptom of
the failure of the adiabatic approximation for non-perturbative dynamics. We
present a reformulation of TDDFT which requires response quantities only, thus
enabling an adiabatic approximation to predict such dynamics accurately because
the functional is evaluated on a density close to the ground-state, instead of
on the fully non-perturbative density. Our reformulation applies to it any
real-time dynamics, redeeming TDDFT far from equilibrium. Examples of a
resonantly-driven local excitation in a model He atom, and charge-transfer in
the LiCN molecule are given.


  This paper is a review of recent results on integrable nonholonomic geodesic
flows of left--invariant metrics and left- and right--invariant constraint
distributions on compact Lie groups.


  Laser-solid interaction can lead to the acceleration of protons to tens of
MeV. Here, we show that a strong enhancement of this acceleration can be
achieved by splitting the laser pulse to two parts of equal energy and opposite
incidence angles. Through the use of two- and three-dimensional
Particle-In-Cell simulations, we find that the multi-pulse interaction leads to
a standing wave pattern at the front side of the target, with an enhanced
electric field and a substantial modification of the hot electron generation
process. This in turn leads to significant improvement of the proton spectra,
with an almost doubling of the accelerated proton energy and five-fold
enhancement of the number of protons. The proposed scheme is robust with
respect to incidence angles for the laser pulses, providing flexibility to the
scheme, which should facilitate its experimental implementation.


  Defects in liquid crystals are of great practical importance and theoretical
interest. Despite tremendous efforts, predicting the location and transition of
defects under various topological constraint and external field remains to be a
challenge. We investigate defect patterns of nematic liquid crystals confined
in three-dimensional spherical droplet and two-dimensional disk under different
boundary conditions, within the Landau-de Gennes model. We implement a spectral
method that numerically solves the Landau-de Gennes model with high accuracy,
which allows us to study the detailed static structure of defects. We observe
five types of defect structures. Among them the 1/2-disclination lines are the
most stable structure at low temperature. Inspired by numerical results, we
obtain the profile of disclination lines analytically. Moreover, the connection
and difference between defect patterns under the Landau-de Gennes model and the
Oseen-Frank model are discussed. Finally, four conjectures are made to
summarize some important characteristics of defects in the Landau-de Gennes
theory. This work is a continuing effort to deepen our understanding on defect
patterns in nematic liquid crystals.


  Brezis and Mironescu have announced several years ago that for a compact
manifold $N^n \subset \mathbb{R}^\nu$ and for real numbers $0 < s < 1$ and $1
\le p < \infty$ the class $C^\infty(\overline{Q}^m; N^n)$ of smooth maps on the
cube with values into $N^n$ is dense with respect to the strong topology in the
Sobolev space $W^{s, p}(Q^m; N^n)$ when the homotopy group $\pi_{\lfloor sp
\rfloor}(N^n)$ of order $\lfloor sp \rfloor$ is trivial. The proof of this
beautiful result is long and rather involved. Under the additional assumption
that $N^n$ is $\lfloor sp \rfloor$ simply connected, we give a shorter proof of
their result. Our proof for $sp \ge 1$ is based on the existence of a
retraction of $\mathbb{R}^\nu$ onto $N^n$ except for a small subset in the
complement of $N^n$ and on the Gagliardo-Nirenberg interpolation inequality for
maps in $W^{1, q} \cap L^\infty$. In contrast, the case $sp < 1$ relies on the
density of step functions on cubes in $W^{s, p}$.


  Assuming the existence of a local vacuum rest frame (LVRF), and using
suitable algebraic tranformations, the internal structure of ultra-high energy
particles (UHEPs) is studied in the presence of Lorentz symmetry violation
(LSV) at the Planck scale. Violations of the standard Lorentz contraction and
time dilation formulae are made explicit. Dynamics in the rest frame of a UHEP
is worked out and discussed. Phenomenological implications for ultra-high
energy cosmic rays (UHECR), including possible violations of the
Greisen-Zatsepin-Kuzmin GZK) cutoff, are studied for several LSV models.


  We present an evaluation of the running coupling constant for Nf=2+1 QCD. The
Schroedinger functional scheme is used as the intermediate scheme to carry out
non-perturbative running from the low energy region, where physical scale is
introduced, to deep in the high energy perturbative region, where conversion to
the MS-bar scheme is safely performed. Possible systematic errors due to the
use of perturbation theory occur only in the conversion from three-flavor to
four-flavor running coupling constant near the charm mass threshold, where
higher order terms beyond 5th order in the $\beta$ function may not be
negligible.
  For numerical simulations we adopted Iwasaki gauge action and
non-perturbatively improved Wilson fermion action with the clover term. Seven
renormalization scales are used to cover from low to high energy region and
three lattice spacings to take the continuum limit at each scale.
  A physical scale is introduced from the previous Nf=2+1 simulation of the
CP-PACS/JL-QCD collaboration, which covered the up-down quark mass range
heavier than $m_\pi\sim 500$ MeV.


  We investigate the non-linear response and energy absorption in bulk silicon
irradiated by intense 12-fs near-infrared laser pulses. Depending on the laser
intensity, we distinguish two regimes of non-linear absorption of the laser
energy: for low intensities, energy deposition and photoionization involve
perturbative three-photon transition through the direct bandgap of silicon. For
laser intensities near and above 10$^{14}$ W/cm$^2$, corresponding to
photocarrier density of order 10$^{22}$ cm$^{-3}$, we find that absorption at
near-infrared wavelengths is greatly enhanced due to excitation of bulk plasmon
resonance. In this regime, the energy transfer to electrons exceeds a few times
the thermal melting threshold of Si. The optical reflectivity of the
photoexcited solid is found in good qualitative agreement with existing
experimental data. In particular, the model predicts that the main features of
the reflectivity curve of photoexcited Si as a function of the laser fluence
are determined by the competition between state and band filling associated
with Pauli exclusion principle and Drude free-carrier response. The non-linear
response of the photoexcited solid is also investigated for irradiation of
silicon with a sequence of two strong and temporary non-overlapping pulses. The
cumulative effect of the two pulses is non-additive in terms of deposited
energy. Photoionization and energy absorption on the leading edge of the second
pulse is greatly enhanced due to free carrier absorption.


  Superconformal Ward identities are revisited in the context of superconformal
line defects. Multipoint correlators of topological operators inserted on
superconformal lines are studied. In particular, it is known that protected
operators preserving enough of the supersymmetry become topological after
performing a topological twist. By definition, such a correlator is constant in
the topological limit. By analysing the topological constraint on the OPE of
such operators, the correlator is further constrained away from this limit. The
constraints on multipoint correlators match the known superconformal Ward
identities in the case of 4-point functions. This allows for an simple and
universal derivation of the superconformal Ward identities governing the
multipoint correlation functions of such operators. This concept is illustrated
by 1/2-BPS operators with an $su(2)$ R-symmetry and further explored in the
case of the displacement multiplet on the 1/2-BPS Wilson line in 4d
$\mathcal{N}=4$ super Yang-Mills theory supporting the conjectured multipoint
Ward identities in the literature.


  Nearly 30% increase of the ferromagnetic phase transition temperature has
been achieved in strained MnAs nanocrystals embedded in a wurtzite GaAs matrix.
Wurtzite GaAs exerts tensile stress on hexagonal MnAs nanocrystals, preventing
a hexagonal to orthorhombic structural phase transition, which in the bulk MnAs
is combined with the magnetic one. This effect results in a remarkable shift of
the magneto-structural phase transition temperature from 313 K in the bulk MnAs
to above 400 K in the tensely strained MnAs nanocrystals. This finding is
corroborated by the state of the art transmission electron microscopy,
sensitive magnetometry and the first-principles calculations. The effect relies
in defining a nanotube geometry of molecular beam epitaxy grown core-multishell
wurtzite (Ga,In)As/(Ga,Al)As/(Ga,Mn)As/GaAs nanowires where the MnAs
nanocrystals are formed during the thermal-treatment-induced phase separation
of wurtzite (Ga,Mn)As into the GaAs:MnAs granular system. Such a unique
combination of two types of hexagonal lattices provides possibility of
attaining quasi-hydrostatic tensile strain in MnAs (impossible otherwise),
leading to the substantial ferromagnetic phase transition temperature increase
in this compound.


  Recently, quantum classifiers have been found to be vulnerable to adversarial
attacks, in which quantum classifiers are deceived by imperceptible noises,
leading to misclassification. In this paper, we propose the first theoretical
study demonstrating that adding quantum random rotation noise can improve
robustness in quantum classifiers against adversarial attacks. We link the
definition of differential privacy and show that the quantum classifier trained
with the natural presence of additive noise is differentially private. Finally,
we derive a certified robustness bound to enable quantum classifiers to defend
against adversarial examples, supported by experimental results simulated with
noises from IBM's 7-qubits device.


  The non-conservative, azimuthal forces associated with inhomogeneous
optical-spin angular momentum play a critical role in optical trapping.
Intriguingly, birefringent microspheres can be stably levitated and rapidly
rotated in circularly polarized optical traps in ultra-high vacuum whereas
isotropic spheres are typically destabilized and expelled, even at relatively
modest pressures. Here we show that the resolution of this apparent key paradox
rests in the form of the orientationally averaged, effective forces acting on
the spinning birefringent particle. In particular, the effective azimuthal
component is heavily suppressed and highly non-linear. As a consequence,
non-conservative effects are strongly, if imperfectly, inhibited. Their
influence is apparent only at very low pressures where we observe the formation
of noisy, nano-scale limit cycles or orbits. Finally, we show how parametric
feedback can synthesize a form of dissipation, necessary to preserve limit
cycle oscillation, without introducing additional thermal fluctuations. This
allows the preparation of highly coherent, self-sustained oscillations with
effective temperatures on the order of a milliKelvin. The tailoring of
azimuthal spin forces through the material structure of a spinning,
non-spherical particle opens up new opportunities for the design of ultra
stable optical rotors. In addition, we have shown that the unique profile of
the azimuthal force, featured in this work, allows for the formation of
nano-scale limit cycles that can be stabilized and cooled. In principle, this
approach could enable the cooling of limit cycles into the quantum regime,
allowing for experimental realisation of quantum synchronization, or
alternative ways of entangling mesoscopic bodies.


  Microarcsecond resolutions afforded by an optical-NIR array with
kilometer-baselines would enable breakthrough science. However significant
technology barriers exist in transporting weakly coherent photon states over
these distances: primarily photon loss and phase errors. Quantum telescopy,
using entangled states to link spatially separated apertures, offers a possible
solution to the loss of photons. We report on an initiative launched by NSF
NOIRLab in collaboration with the Center for Quantum Networks and Arizona
Quantum Initiative at the University of Arizona, Tucson, to explore these
concepts further. A brief description of the quantum concepts and a possible
technology roadmap towards a quantum-enhanced very long baseline optical-NIR
interferometric array is presented. An on-sky demonstration of measuring
spatial coherence of photons with apertures linked through the simplest
Gottesman protocol over short baselines and with limited phase fluctuations is
envisaged as the first step.


  In a number of widely-studied materials, such as Si, AlAs, Bi, graphene,
MoS2, and many transition metal dichalcogenide monolayers, electrons acquire an
additional, spin-like degree of freedom at the degenerate conduction band
minima, also known as "valleys". External symmetry breaking fields such as
mechanical strain, or electric or magnetic fields, can tune the
valley-polarization of these materials making them suitable candidates for
"valleytronics". Here we study a quantum well of AlAs, where the
two-dimensional electrons reside in two energetically degenerate valleys. By
fabricating a strain-inducing grating on the sample surface, we engineer a
spatial modulation of the electron population in different valleys, i.e., a
"valley superlattice" in the quantum well plane. Our results establish a novel
manipulation technique of the valley degree of freedom, paving the way to
realizing a valley-selective layered structure in multi-valley materials, with
potential application in valleytronics.


  This paper introduces a new derivative parsing algorithm for recognition of
parsing expression grammars. Derivative parsing is shown to have a polynomial
worst-case time bound, an improvement on the exponential bound of the recursive
descent algorithm. This work also introduces asymptotic analysis based on
inputs with a constant bound on both grammar nesting depth and number of
backtracking choices; derivative and recursive descent parsing are shown to run
in linear time and constant space on this useful class of inputs, with both the
theoretical bounds and the reasonability of the input class validated
empirically. This common-case constant memory usage of derivative parsing is an
improvement on the linear space required by the packrat algorithm.


  A search engine's ability to retrieve desirable datasets is important for
data sharing and reuse. Existing dataset search engines typically rely on
matching queries to dataset descriptions. However, a user may not have enough
prior knowledge to write a query using terms that match with description
text.We propose a novel schema label generation model which generates possible
schema labels based on dataset table content. We incorporate the generated
schema labels into a mixed ranking model which not only considers the relevance
between the query and dataset metadata but also the similarity between the
query and generated schema labels. To evaluate our method on real-world
datasets, we create a new benchmark specifically for the dataset retrieval
task. Experiments show that our approach can effectively improve the precision
and NDCG scores of the dataset retrieval task compared with baseline methods.
We also test on a collection of Wikipedia tables to show that the features
generated from schema labels can improve the unsupervised and supervised web
table retrieval task as well.


  Solving the stationary nonlinear Fokker-Planck equations is important in
applications and examples include the Poisson-Boltzmann equation and the two
layer neural networks. Making use of the connection between the interacting
particle systems and the nonlinear Fokker-Planck equations, we propose to solve
the stationary solution by sampling from the $N$-body Gibbs distribution. This
avoids simulation of the $N$-body system for long time and more importantly
such a method can avoid the requirement of uniform propagation of chaos from
direct simulation of the particle systems. We establish the convergence of the
Gibbs measure to the stationary solution when the interaction kernel is bounded
(not necessarily continuous) and the temperature is not very small. Numerical
experiments are performed for the Poisson-Boltzmann equations and the two-layer
neural networks to validate the method and the theory.


  Faces play a magnificent role in human robot interaction, as they do in our
daily life. The inherent ability of the human mind facilitates us to recognize
a person by exploiting various challenges such as bad illumination, occlusions,
pose variation etc. which are involved in face recognition. But it is a very
complex task in nature to identify a human face by humanoid robots. The recent
literatures on face biometric recognition are extremely rich in its application
on structured environment for solving human identification problem. But the
application of face biometric on mobile robotics is limited for its inability
to produce accurate identification in uneven circumstances. The existing face
recognition problem has been tackled with our proposed component based
fragmented face recognition framework. The proposed framework uses only a
subset of the full face such as eyes, nose and mouth to recognize a person.
It's less searching cost, encouraging accuracy and ability to handle various
challenges of face recognition offers its applicability on humanoid robots. The
second problem in face recognition is the face spoofing, in which a face
recognition system is not able to distinguish between a person and an imposter
(photo/video of the genuine user). The problem will become more detrimental
when robots are used as an authenticator. A depth analysis method has been
investigated in our research work to test the liveness of imposters to
discriminate them from the legitimate users. The implication of the previous
earned techniques has been used with respect to criminal identification with
NAO robot. An eyewitness can interact with NAO through a user interface. NAO
asks several questions about the suspect, such as age, height, her/his facial
shape and size etc., and then making a guess about her/his face.


  The bar pattern speed ($\Omega_{\rm b}$) is defined as the rotational
frequency of the bar, and it determines the bar dynamics. Several methods have
been proposed for measuring $\Omega_{\rm b}$. The non-parametric method
proposed by Tremaine \& Weinberg (1984; TW) and based on stellar kinematics is
the most accurate. This method has been applied so far to 17 galaxies, most of
them SB0 and SBa types. We have applied the TW method to a new sample of 15
strong and bright barred galaxies, spanning a wide range of morphological types
from SB0 to SBbc. Combining our analysis with previous studies, we investigate
32 barred galaxies with their pattern speed measured by the TW method. The
resulting total sample of barred galaxies allows us to study the dependence of
$\Omega_{\rm b}$ on galaxy properties, such as the Hubble type. We measured
$\Omega_{\rm b}$ using the TW method on the stellar velocity maps provided by
the integral-field spectroscopy data from the CALIFA survey. Integral-field
data solve the problems that long-slit data present when applying the TW
method, resulting in the determination of more accurate $\Omega_{\rm b}$. In
addition, we have also derived the ratio $\cal{R}$ of the corotation radius to
the bar length of the galaxies. According to this parameter, bars can be
classified as fast ($\cal{R}$ $< 1.4$) and slow ($\cal{R}$>1.4). For all the
galaxies, $\cal{R}$ is compatible within the errors with fast bars. We cannot
rule out (at 95$\%$ level) the fast bar solution for any galaxy. We have not
observed any significant trend between $\cal{R}$ and the galaxy morphological
type. Our results indicate that independent of the Hubble type, bars have been
formed and then evolve as fast rotators. This observational result will
constrain the scenarios of formation and evolution of bars proposed by
numerical simulations.


  We present the discovery of a new type of explosive X-ray flash in Chandra
images of the old elliptical galaxy M86. This unique event is characterised by
the peak luminosity of 6x10^42 erg/s for the distance of M86, the presence of
precursor events, the timescale between the precursors and the main event
(~4,000 s), the absence of detectable hard X-ray and gamma-ray emission, the
total duration of the event and the detection of a faint associated optical
signal. The transient is located close to M86 in the Virgo cluster at the
location where gas and stars are seen protruding from the galaxy probably due
to an ongoing wet minor merger. We discuss the possible mechanisms for the
transient and we conclude that the X-ray flash could have been caused by the
disruption of a compact white dwarf star by a ~10^4 Msun black hole.
Alternative scenarios such that of a foreground neutron star accreting an
asteroid or the detection of an off-axis (short) gamma-ray burst cannot be
excluded at present.


  Statistical mechanics underlies our understanding of macroscopic quantum
systems. It is based on the assumption that out-of-equilibrium systems rapidly
approach their equilibrium states, forgetting any information about their
microscopic initial conditions. This fundamental paradigm is challenged by
disordered systems, in which a slowdown or even absence of thermalization is
expected. We report the observation of critical thermalization in a three
dimensional ensemble of $\sim 10^6$ electronic spins coupled via dipolar
interactions. By controlling the spin states of nitrogen vacancy color centers
in diamond, we observe slow, sub-exponential relaxation dynamics and identify a
regime of power-law decay with disorder-dependent exponents; this behavior is
modified at late times owing to many-body interactions. These observations are
quantitatively explained by a resonance counting theory that incorporates the
effects of both disorder and interactions.


  We use the P&L on a particular class of swaps, representing variance and
higher moments for log returns, as estimators in our empirical study on the
S&P500 that investigates the factors determining variance and higher-moment
risk premia. This class is the discretisation invariant sub-class of swaps with
Neuberger's aggregating characteristics. Besides the market excess return,
momentum is the dominant driver for both skewness and kurtosis risk premia,
which exhibit a highly significant negative correlation. By contrast, the
variance risk premium responds positively to size and negatively to growth, and
the correlation between variance and tail risk premia is relatively low
compared with previous research, particularly at high sampling frequencies.
These findings extend prior research on determinants of these risk premia.
Furthermore, our meticulous data-construction methodology avoids unwanted
artefacts which distort results.


  Bialek, Callan and Strong have recently given a solution of the problem of
determining a continuous probability distribution from a finite set of
experimental measurements by formulating it as a one-dimensional quantum field
theory. This report applies an extension of their formalism to the inference of
functional parton distributions from scattering data.


  There has been considerable recent interest, primarily motivated by problems
in applied algebraic topology, in the homology of random simplicial complexes.
We consider the scenario in which the vertices of the simplices are the points
of a random point process in $\mathbb {R}^d$, and the edges and faces are
determined according to some deterministic rule, typically leading to \v{C}ech
and Vietoris-Rips complexes. In particular, we obtain results about homology,
as measured via the growth of Betti numbers, when the vertices are the points
of a general stationary point process. This significantly extends earlier
results in which the points were either i.i.d. observations or the points of a
Poisson process. In dealing with general point processes, in which the points
exhibit dependence such as attraction or repulsion, we find phenomena
quantitatively different from those observed in the i.i.d. and Poisson cases.
From the point of view of topological data analysis, our results seriously
impact considerations of model (non)robustness for statistical inference. Our
proofs rely on analysis of subgraph and component counts of stationary point
processes, which are of independent interest in stochastic geometry.


  Given a graph $H$, let $g(n,H)$ denote the smallest $k$ for which the
following holds. We can assign a $k$-colouring $f_v$ of the edge set of $K_n$
to each vertex $v$ in $K_n$ with the property that for any copy $T$ of $H$ in
$K_n$, there is some $u\in V(T)$ such that every edge in $T$ has a different
colour in $f_u$.
  The study of this function was initiated by Alon and Ben-Eliezer. They
characterized the family of graphs $H$ for which $g(n,H)$ is bounded and asked
whether it is true that for every other graph $g(n,H)$ is polynomial. We show
that this is not the case and characterize the family of connected graphs $H$
for which $g(n,H)$ grows polynomially. Answering another question of theirs, we
also prove that for every $\varepsilon>0$, there is some $r=r(\varepsilon)$
such that $g(n,K_r)\geq n^{1-\varepsilon}$ for all sufficiently large $n$.
  Finally, we show that the above problem is connected to the
Erd\H{o}s-Gy\'arf\'as function in Ramsey Theory, and prove a family of special
cases of a conjecture of Conlon, Fox, Lee and Sudakov by showing that for each
fixed $r$ the complete $r$-uniform hypergraph $K_n^{(r)}$ can be edge-coloured
using a subpolynomial number of colours in such a way that at least $r$ colours
appear among any $r+1$ vertices.


  Galaxies in dense environments are subject to interactions and mechanisms
which directly affect their evolution by lowering their gas fractions and
reducing their star-forming capacity earlier than their isolated counterparts.
The aim of our project is to get new insights about the role of environment on
the stellar and baryonic content of galaxies using a kinematic approach,
through the study of the Tully-Fisher relation (TFR). We study a sample of
galaxies in 8 groups spanning a redshift range of $0.5<z<0.8$ and located in 10
pointings of the MAGIC MUSE Guaranteed Time Observations program. We perform a
morpho-kinematics analysis of this sample and set up a selection based on
galaxy size, [OII] emission line doublet signal-to-noise ratio, bulge-to-disk
ratio and nuclear activity to construct a robust kinematic sample of 67
star-forming galaxies. This selection considerably reduces the number of
outliers in the TFR, which are predominantly dispersion-dominated galaxies. Our
results suggest a significant offset of the TFR zero-point between galaxies in
low- and high-density environments, whatever kinematics estimator is used. This
can be interpreted as a decrease of either stellar mass by $\sim 0.05 - 0.3$
dex or an increase of rotation velocity by $\sim 0.02 - 0.06$ dex for galaxies
in groups, depending on the samples used for comparison. We also studied the
stellar and baryon mass fractions within stellar disks and found they both
increase with stellar mass, the trend being more pronounced for the stellar
component alone. These fractions do not exceed 50%. We show that this evolution
of the TFR is consistent either with a decrease of star formation or with a
contraction of the mass distribution due to the environment. These two effects
probably act together with their relative contribution depending on the mass
regime.


  In order for clarifying what are the essential thermal effects that govern
the chiral phase transition at finite temperature, we investigate, in the
real-time thermal QED, the consequences of the Hard-Thermal-Loop (HTL) resummed
Dyson-Schwinger equation for the physical fermion mass function $\Sigma_R$.
Since $\Sigma_R$ is the mass function of an ``unstable'' quasi-particle in
thermal field theories, it necessarily has non-trivial imaginary parts together
with non-trivial wave function renormalization constants. In the present
analysis we correctly respect this fact, and study, in the ladder
approximation, the effect of HTL resummed gauge boson propagator. Our results
with the use of numerical analysis, show the two facts; i) The chiral phase
transition is of second order, since the fermion mass is dynamically generated
at a critical value of the temperature $T_c$, or at the critical coupling
constant $\alpha_c$, without any discontinuity, and ii) the critical
temperature $T_c$ at fixed value of $\alpha$ is significantly lower than the
previous results, namely the restoration of chiral symmetry occurs at lower
temperature than previously expected. The second fact shows the importance of
correctly taking the essential thermal effect into the analysis of chiral phase
transition, which are, in the previous analyses, neglected due to the
inappropriate approximations. The procedure how to maximally respect the gauge
invariance in the present approximation, is also discussed.


  Both local geometry and collective, extended excitations drive the moves of a
particle in the cage of its neighbours in dense liquids. The strength of their
influence is investigated by Molecular Dynamics simulations of a supercooled
liquid of fully-flexible trimers with semirigid or rigid bonds. The rattling in
the cage is investigated on different length scales. First, the rattling
anisotropy due to local order is characterized by two order parameters sensing
the monomers succeeding or failing to escape from the cage. Then, the
collective response of the surroundings excited by the monomer-monomer
collisions is considered. The collective response is initially restricted to
the nearest neighbours of the colliding particle by a Voronoi analysis
revealing elastic contributions. Then, the long-range excitation of the
farthest neighbours is scrutinised by searching spatially-extended correlations
between the simultaneous fast displacements of the caged particle and the
surroundings. It is found that the longitudinal component has stronger spatial
modulation than the transverse one with wavelength of about one particle
diameter, in close resemblance with experimental findings on colloids. It is
concluded that the cage rattling is largely affected by solid-like extended
modes.


  Addressing uncertainty in Deep Learning (DL) is essential, as it enables the
development of models that can make reliable predictions and informed decisions
in complex, real-world environments where data may be incomplete or ambiguous.
This paper introduces a novel algorithm leveraging Dempster-Shafer Theory (DST)
to integrate multiple pre-trained models to form an ensemble capable of
providing more reliable and enhanced classifications. The main steps of the
proposed method include feature extraction, mass function calculation, fusion,
and expected utility calculation. Several experiments have been conducted on
CIFAR-10 and CIFAR-100 datasets, demonstrating superior classification accuracy
of the proposed DST-based method, achieving improvements of 5.4% and 8.4%,
respectively, compared to the best individual pre-trained models. Results
highlight the potential of DST as a robust framework for managing uncertainties
related to data when applying DL in real-world scenarios.


  We describe a versatile pipeline for processing the data collected by the
Ultra-Violet Imaging Telescope (UVIT) on board Indian Multi-wavelength
astronomical satellite AstroSat.The UVIT instrument carries out simultaneous
astronomical imaging through selected filters / gratings in Far-Ultra-Violet
(FUV), Near-Ultra-Violet & visible (VIS) bands of the targeted circular sky
field (~ 0.5 deg dia). This pipeline converts the data (Level-1) emanating from
UVIT in their raw primitive format supplemented by inputs from the spacecraft
sub-systems into UV sky images (& slitless grating spectra) and associated
products readily usable by astronomers (Level-2). The primary products include
maps of Intensity (rate of photon arrival), error on Intensity and effective
Exposure. The pipeline is open source, extensively user configurable with many
selectable parameters and its execution is fully automated. The key ingredients
of the pipeline includes - extraction of drift in pointing of the spacecraft,
and disturbances in pointing due to internal movements; application of various
corrections to measured position in the detector for each photon - e.g.
differential pointing with respect to a reference frame for shift and add
operation, systematic effects and artifacts in the optics of the telescopes and
detectors, exposure tracking on the sky, alignment of sky products from
multi-episode exposures to generate a consolidated set and astrometry. Detailed
logs of operations and intermediate products for every processing stage are
accessible via user selectable options. While large number of selectable
parameters are available for the user, a well characterized standard default
set is used for executing this pipeline at the Payload Operation Centre (POC)
for UVIT and selected products are archived and disseminated by the Indian
Space Research Organization (ISRO) through its ISSDC portal.


  The Abstraction and Reasoning Corpus (ARC) is a challenging program induction
dataset that was recently proposed by Chollet (2019). Here, we report the first
set of results collected from a behavioral study of humans solving a subset of
tasks from ARC (40 out of 1000). Although this subset of tasks contains
considerable variation, our results showed that humans were able to infer the
underlying program and generate the correct test output for a novel test input
example, with an average of 80% of tasks solved per participant, and with 65%
of tasks being solved by more than 80% of participants. Additionally, we find
interesting patterns of behavioral consistency and variability within the
action sequences during the generation process, the natural language
descriptions to describe the transformations for each task, and the errors
people made. Our findings suggest that people can quickly and reliably
determine the relevant features and properties of a task to compose a correct
solution. Future modeling work could incorporate these findings, potentially by
connecting the natural language descriptions we collected here to the
underlying semantics of ARC.


  This paper has been removed from arXiv as the submitter did not have
ownership of the data presented in this work.


  We demonstrate that amplification of arbitrarily weak randomness is possible
using quantum resources. We present a randomness amplification protocol that
involves Bell experiments. We find a Bell inequality which can amplify
arbitrarily weak randomness and give a detailed analysis of the protocol
involving it. Our analysis includes finding a sufficient violation of Bell
inequality as a function of the initial quality of randomness. It has a very
important property that for any quality the required violation is strictly
lower than possible to obtain using quantum resources. Among other things, it
means that the protocol takes a finite amount of time to amplify arbitrarily
weak randomness.


  This analysis proposes a new topic model to study the yearly trends in Marvel
Cinematic Universe fanfictions on three levels: character popularity, character
images/topics, and vocabulary pattern of topics. It is found that character
appearances in fanfictions have become more diverse over the years thanks to
constant introduction of new characters in feature films, and in the case of
Captain America, multi-dimensional character development is well-received by
the fanfiction world.


  The purpose of this article is to study conservativity in the context of
triangulated categories equipped with a weight structure. As application, we
establish (weight) conservativity for the restriction of the (generic) l-adic
realization to the category of motives of Abelian type of characteristic zero.


  It is common to use Galilean rotational transformation to investigate the
Unruh effect for uniformly rotating observers. However, the rotating observer
in this subject is an eccentric observer while Galilean rotational
transformation is only valid for centrally rotating observers. Thus, the
reliability of the results of applying Galilean rotational transformation to
the study of the Unruh effect might be considered as questionable. In this work
the rotational analog of the Unruh effect is investigated by employing two
relativistic rotational transformations corresponding to the eccentric rotating
observer, and it is shown that in both cases the detector response function is
non-zero. It is also shown that although consecutive Lorentz transformations
can not give a frame within which the canonical construction can be carried
out, the expectation value of particle number operator in canonical approach
will be zero if we use modified Franklin transformation. These conclusions
reinforce the claim that correspondence between vacuum states defined via
canonical field theory and a detector is broken for rotating observers. Some
previous conclusions are commented on and some controversies are also
discussed.


  It is widely believed that most of the cosmic X-ray background (XRB) is
produced by a vast, hitherto undetected population of obscured AGN. Deep X-ray
surveys with Chandra and XMM will soon test this hypothesis. Similarly, recent
sub-mm surveys with SCUBA have revealed an analogous population of
exceptionally luminous, dust-enshrouded {\em star-forming} galaxies at high
redshift. There is now growing evidence for an intimate link between these
obscured populations. There are currently large uncertainties in the models,
but several independent arguments lead to the conclusion that a significant
fraction of the SCUBA sources ($10-30% $) will contain quasars. Recent
observational studies of SCUBA survey sources appear to confirm these
predictions, although the relative roles of AGN and star-forming activity in
heating the dust are unclear. Forthcoming surveys combining X-ray and sub-mm
observations will provide a very powerful tool for disentangling these
processes.


  As the Fano effect is an interference phenomenon where tunneling paths
compete for the electronic transport, it becomes a probe to catch fingerprints
of Majorana fermions lying on condensed matter systems. In this work we benefit
of this mechanism by proposing as a route for that an Aharonov-Bohm-like
interferometer composed by two quantum dots, being one of them coupled to a
Majorana bound state, which is attached to one of the edges of a semi-infinite
Kitaev wire within the topological phase. By changing the Fermi energy of the
leads and the symmetric detuning of the levels for the dots, we show that
opposing Fano regimes result in a transmittance characterized by distinct
conducting and insulating regions, which are fingerprints of an isolated
Majorana quasiparticle. Furthermore, we show that the maximum fluctuation of
the transmittance as a function of the detuning is half for a semi-infinite
wire, while it corresponds to the unity for a finite system. The setup proposed
here constitutes an alternative experimental tool to detect Majorana
excitations.


  We describe a simple model of fermions in quasi-one dimension that features
interaction induced deconfinement (a phase transition where the effective
dimensionality of the system increases as interactions are turned on) and which
can be realised using dipolar fermions in an optical lattice. The model
provides a relisation of a "soft quantum matter" phase diagram of
strongly-correlated fermions, featuring meta-nematic, smectic and crystalline
states, in addition to the normal Fermi liquid. In this paper we review the
model and discuss in detail the mechanism behind each of these transitions on
the basis of bosonization and detailed analysis of the RPA susceptibility.


  Retrosynthesis, of which the goal is to find a set of reactants for
synthesizing a target product, is an emerging research area of deep learning.
While the existing approaches have shown promising results, they currently lack
the ability to consider availability (e.g., stability or purchasability) of the
reactants or generalize to unseen reaction templates (i.e., chemical reaction
rules). In this paper, we propose a new approach that mitigates the issues by
reformulating retrosynthesis into a selection problem of reactants from a
candidate set of commercially available molecules. To this end, we design an
efficient reactant selection framework, named RetCL (retrosynthesis via
contrastive learning), for enumerating all of the candidate molecules based on
selection scores computed by graph neural networks. For learning the score
functions, we also propose a novel contrastive training scheme with hard
negative mining. Extensive experiments demonstrate the benefits of the proposed
selection-based approach. For example, when all 671k reactants in the USPTO
{database} are given as candidates, our RetCL achieves top-1 exact match
accuracy of $71.3\%$ for the USPTO-50k benchmark, while a recent
transformer-based approach achieves $59.6\%$. We also demonstrate that RetCL
generalizes well to unseen templates in various settings in contrast to
template-based approaches.


  We engineered an interactive music system that influences a user's breathing
rate to induce a relaxation response. This system generates ambient music
containing periodic shifts in loudness that are determined by the user's own
breathing patterns. We evaluated the efficacy of this music intervention for
participants who were engaged in an attention-demanding task, and thus
explicitly not focusing on their breathing or on listening to the music. We
measured breathing patterns in addition to multiple peripheral and cortical
indicators of physiological arousal while users experienced three different
interaction designs: (1) a "Fixed Tempo" amplitude modulation rate at six beats
per minute; (2) a "Personalized Tempo" modulation rate fixed at 75\% of each
individual's breathing rate baseline, and (3) a "Personalized Envelope" design
in which the amplitude modulation matches each individual's breathing pattern
in real-time. Our results revealed that each interactive music design slowed
down breathing rates, with the "Personalized Tempo" design having the largest
effect, one that was more significant than the non-personalized design. The
physiological arousal indicators (electrodermal activity, heart rate, and slow
cortical potentials measured in EEG) showed concomitant reductions, suggesting
that slowing users' breathing rates shifted them towards a more calmed state.
These results suggest that interactive music incorporating biometric data may
have greater effects on physiology than traditional recorded music.


  One of the recent attempts to address the Hubble and $S_8$ tensions is to
consider the Universe started out not as a de Sitter-like spacetime, but rather
anti-de Sitter-like. That is, the Universe underwent an "AdS-to-dS" transition
at some point. We study the possibility that there are two dark energy fluids,
one of which gave rise to the anti-de Sitter-like early Universe. The
interaction is modeled by the Lotka-Volterra equations, commonly used in
population biology. We consider "competition" models that are further
classified as "unfair competition" and "fair competition". The former involves
a quintessence in competition with a phantom, and the second involves two
phantom fluids. Surprisingly, even in the latter scenario it is possible for
the overall dark energy to cross the phantom divide. The latter model also
allows a constant $w$ "AdS-to-dS" transition, thus evading the theorem that
such a dark energy must possess a singular equation of state. We also consider
a "conversion" model in which a phantom fluid still manages to achieve
"AdS-to-dS" transition even if it is being converted into a negative energy
density quintessence. In these models, the energy density of the late time
effective dark energy is related to the coefficient of the quadratic
self-interaction term of the fluids, which is analogous to the resource
capacity in population biology.


  In this paper, we prove that a link which has an almost positive diagram with
a certain condition is Lagrangian fillable.


  In light of the emergence of big data, I have advocated and argued for a
paradigm shift from Tobler's law to scaling law, from Euclidean geometry to
fractal geometry, from Gaussian statistics to Paretian statistics, and - more
importantly - from Descartes' mechanistic thinking to Alexander's organic
thinking. Fractal geometry falls under the third definition of fractal - that
is, a set or pattern is fractal if the scaling of far more small things than
large ones recurs multiple times (Jiang and Yin 2014) - rather than under the
second definition of fractal, which requires a power law between scales and
details (Mandelbrot 1982). The new fractal geometry is more towards living
geometry that "follows the rules, constraints, and contingent conditions that
are, inevitably, encountered in the real world" (Alexander et al. 2012, p.
395), not only for understanding complexity, but also for creating complex or
living structure (Alexander 2002-2005). This editorial attempts to clarify why
the paradigm shift is essential and to elaborate on several concepts, including
spatial heterogeneity (scaling law), scale (or the fourth meaning of scale),
data character (in contrast to data quality), and sustainable transport in the
big data era.


  Let $\D$ be the finite difference Laplacian associated to the lattice
$\bZ^{d}$. For dimension $d\ge 3$, $a\ge 0$ and $L$ a sufficiently large
positive dyadic integer, we prove that the integral kernel of the resolvent
$G^{a}:=(a-\D)^{-1}$ can be decomposed as an infinite sum of positive
semi-definite functions $ V_{n} $ of finite range, $ V_{n} (x-y) = 0$ for
$|x-y|\ge O(L)^{n}$. Equivalently, the Gaussian process on the lattice with
covariance $G^{a}$ admits a decomposition into independent Gaussian processes
with finite range covariances. For $a=0$, $ V_{n} $ has a limiting scaling form
$L^{-n(d-2)}\Gamma_{c,\ast}{\bigl (\frac{x-y}{L^{n}}\bigr)}$ as $n\to \infty$.
As a corollary, such decompositions also exist for fractional powers
$(-\D)^{-\alpha/2}$, $0<\alpha \leq 2$. The results of this paper give an
alternative to the block spin renormalization group on the lattice.


  We study transitive step skew-product maps modeled over a complete shift of
$k$, $k\ge2$, symbols whose fiber maps are defined on the circle and have
intermingled contracting and expanding regions. These dynamics are genuinely
nonhyperbolic and exhibit simultaneously ergodic measures with positive,
negative, and zero exponents.
  We introduce a set of axioms for the fiber maps and study the dynamics of the
resulting skew-product. These axioms turn out to capture the key mechanisms of
the dynamics of nonhyperbolic robustly transitive maps with compact central
leaves.
  Focusing on the nonhyperbolic ergodic measures (with zero fiber exponent) of
these systems, we prove that such measures are approximated in the weak$\ast$
topology and in entropy by hyperbolic ones. We also prove that they are in the
intersection of the convex hulls of the measures with positive fiber exponent
and with negative fiber exponent. Our methods also allow us to perturb
hyperbolic measures. We can perturb a measure with negative exponent directly
to a measure with positive exponent (and vice-versa), however we lose some
amount of entropy in this process. The loss of entropy is determined by the
difference between the Lyapunov exponents of the measures.


  Recent demonstrations of optically pumped lasers based on GeSn alloys put
forward the prospect of efficient laser sources monolithically integrated on a
Si photonic platform. For instance, GeSn layers with 12.5% of Sn were reported
to lase at 2.5 um wavelength up to 130 K. In this work, we report a longer
emitted wavelength and a significant improvement in lasing temperature. The
improvements resulted from the use of higher Sn content GeSn layers of
optimized crystalline quality, grown on graded Sn content buffers using Reduced
Pressure CVD. The fabricated GeSn micro-disks with 13% and 16% of Sn showed
lasing operation at 2.6 um and 3.1 um wavelengths, respectively. For the
longest wavelength (i.e 3.1 um), lasing was demonstrated up to 180 K, with a
threshold of 377 kW/cm2 at 25 K.


  We show that the Kapitza stabilization can occur in the context of nonlinear
quantum fields. Through this phenomenon, an amplitude-modulated lattice can
stabilize a Bose-Einstein condensate with repulsive interactions and prevent
the spreading for long times. We present a classical and quantum analysis in
the framework of Gross-Pitaevskii equation, specifying the parameter region
where stabilization occurs. Effects of nonlinearity lead to a significant
increase of the stability domain compared with the classical case. Our proposal
can be experimentally implemented with current cold atom settings.


  The Gaze Interaction Markup Language (GIML) is presented, which is new
language for designing the gaze-controlled application and psychological
experiments (also by non-programmers).


  This is a short review of methods and results of calculations of fission
barriers and fission half-lives of even-even superheavy nuclei. An approvable
agreement of the following approaches is shown and discussed: The
macroscopic-microscopic approach based on the stratagem of the shell correction
to the liquid drop model and a vantage point of microscopic energy density
functionals of Skyrme and Gogny type selfconsistently calculated within
Hartree-Fock-Bogoliubov method. Mass parameters are calculated in the
Hartree-Fock-Bogoliubov cranking approximation. A short part of the paper is
devoted to the nuclear fission dynamics. We also discuss the predictive power
of Skyrme functionals applied to key properties of the fission path of
$^{266}$Hs. It applies the standard techniques of error estimates in the
framework of a $\chi^2$ analysis.


  We develop a learning-based control algorithm for unknown dynamical systems
under very severe data limitations. Specifically, the algorithm has access to
streaming and noisy data only from a single and ongoing trial. It accomplishes
such performance by effectively leveraging various forms of side information on
the dynamics to reduce the sample complexity. Such side information typically
comes from elementary laws of physics and qualitative properties of the system.
More precisely, the algorithm approximately solves an optimal control problem
encoding the system's desired behavior. To this end, it constructs and
iteratively refines a data-driven differential inclusion that contains the
unknown vector field of the dynamics. The differential inclusion, used in an
interval Taylor-based method, enables to over-approximate the set of states the
system may reach. Theoretically, we establish a bound on the suboptimality of
the approximate solution with respect to the optimal control with known
dynamics. We show that the longer the trial or the more side information is
available, the tighter the bound. Empirically, experiments in a high-fidelity
F-16 aircraft simulator and MuJoCo's environments illustrate that, despite the
scarcity of data, the algorithm can provide performance comparable to
reinforcement learning algorithms trained over millions of environment
interactions. Besides, we show that the algorithm outperforms existing
techniques combining system identification and model predictive control.


  Two all-spherical catadioptric optical systems with a Mangin mirror are
described. The design A (aperture 500 mm, f/2.0) has flat field of view of 7
deg in diameter; the design B (aperture 1000 mm, f/1.7) has 10-deg flat field.
Both designs show near-diffraction-limited images. The D_80 diameter for the
design A in the integral waveband 0.45-0.85 mcm varies from 1''.3 on the
optical axis up to 2''.2 at the edge of the field (6.2-10.7 mcm); the
corresponding range of the D_80 diameter for the design B is 1''.5-1''.9
(12.4-16.2 mcm). The designs include simple glass types, mainly Schott N-BK7
and fused silica. In case of need, better images could be attained by a choice
of other glass, aspherisation of some surfaces, etc.


  We study several subseries of the space of second order theta functions on
the Jacobian of a non-hyperelliptic curve. In particular, we are interested in
the subseries P\Gamma_{00} consisting of 2theta-divisors having multiplicity at
least 4 at the origin, or, equivalently, containing the surface C-C, and in its
analogues consisting of 2theta-divisors having higher multiplicities at the
origin, containing the four-fold Sym^2C-Sym^2C, or singular along the surface
C-C. We use rank 2 vector bundles with a given number of global sections to
prove canonical isomorphisms between quotients of the above introduced
subseries and vector spaces defined by the canonical divisor.


  In pursuit of a noncommutative spectrum functor, we argue that the
Heyneman-Sweedler finite dual coalgebra can be viewed as a quantization of the
maximal spectrum of a commutative affine algebra, integrating prior
perspectives of Takeuchi, Batchelor, Kontsevich-Soibelman, and Le Bruyn. We
introduce fully residually finite-dimensional algebras $A$ as those with enough
finite-dimensional representations to let $A^\circ$ act as an appropriate
depiction of the noncommutative maximal spectrum of $A$; importantly, this
class includes affine noetherian PI algebras. In the case of prime affine
algebras that are module-finite over their center, we describe how the Azumaya
locus is represented in the finite dual. This is used to describe the finite
dual of quantum planes at roots of unity as an endeavor to visualize the
noncommutative space on which these algebras act as functions. Finally, we
discuss how a similar analysis can be carried out for other maximal orders over
surfaces.


  In this paper, we have proved four theorems on the degree of approximation of
continuous functions by matrix means of their Fourier series which is expressed
in terms of the modulus of continuity and a non-negative mediate function.


  In this paper we propose to associate a temporal two-component wave-function
to the decay process of meson particles. This simple quantum model provides a
good estimation of the CP symmetry violation parameter. This result is based on
our previous paper ("Two-Level Friedrichs model and Kaonic phenomenology",
Physics Letters A 362, 100-104 (2007)) where we have shown that the two-level
Friedrichs Hamiltonian model makes it possible to provide a qualitatively
correct phenomenological model of kaons physics. In this previous paper, we
derived a violation parameter that is 14 times larger than the measured
quantity. In the present paper we improve our estimation of the violation and
obtain the right order of magnitude. The improvement results from a
renormalized superposition of the probability amplitudes describing short and
long exponential decays. The renormalization occurs because the amplitudes that
we are dealing with are associated to the decay rate, and not to the integrated
decay rate or survival probability as is usually the case in standard
approaches to CP-violation. We also compare with recent experimental data for
the mesons D and B and also there the agreement between our model and
experimental data is quite satisfying.


  We investigate the dynamics of bright matter wave solitons in spin-1
Bose-Einstein condensates with time modulated nonlinearities. We obtain soliton
solutions of an integrable autonomous three-coupled Gross-Pitaevskii (3-GP)
equations using Hirota's method involving a non-standard bilinearization. The
similarity transformations are developed to construct the soliton solutions of
non-autonomous 3-GP system. The non-autonomous solitons admit different density
profiles. An interesting phenomenon of soliton compression is identified for
kink-like nonlinearity coefficient with Hermite-Gaussian-like potential
strength. Our study shows that these non-autonomous solitons undergo
non-trivial collisions involving condensate switching.


  Optical transition-edge sensors have shown energy resolution for resolving
the number of incident photons at the telecommunication wavelength. Higher
energy resolution is required for biological imaging and microscope
spectroscopy. In this paper, we report on a Au/Ti (10/20 nm) bilayer TES that
showed high energy resolution. This was achieved by lowering the critical
temperature Tc to 115 mK and the resultant energy resolution was 67 meV full
width at half maximum (FWHM) at 0.8 eV. When Tc was lowered to 115 mK, the
theoretical resolution would scaled up to 30 meV FWHM, considering that the
typical energy resolution of optical TESs is 150 meV and Tc is 300 mK. To
investigate the gap between the theoretical expectation (30 meV) and the
measured value (67 meV), we measured its complex impedance and current noise.
We found excess Johnson noise in the TES and an excess Johnson term M was 1.5
at a bias point where the resistance was 10% of normal resistance. For
reference, the TES was compared with a TES showing typical energy resolution
(156 meV FWHM). We will discuss what improved the energy resolution and what
might have been the limiting factor on it.


  We present a general approach to isolate chemical reaction mechanism as an
independently controllable variable across chemically distinct systems. Modern
approaches to reduce the computational expense of molecular dynamics
simulations often group multiple atoms into a single "coarse-grained"
interaction site, which leads to a loss of chemical resolution. In this work we
convert this shortcoming into a feature and use identical coarse-grained models
to represent molecules that share non-reactive characteristics but react by
different mechanisms. As a proof of concept we use this approach to simulate
and investigate distinct, yet similar, trifunctional isocyanurate resin
formulations that polymerize by either chain- or step-growth. Since the
underlying molecular mechanics of these models are identical, all emergent
differences are a function of the reaction mechanism only. We find that the
microscopic morphologies resemble related all-atom simulations and that
simulated mechanical testing reasonably agrees with experiment.


  Enhancing the light-matter interaction in two-dimensional (2D) materials with
high-$Q$ resonances in photonic structures has boosted the development of
optical and photonic devices. Herein, we intend to build a bridge between the
radiation engineering and the bound states in the continuum (BIC), and present
a general method to control light absorption at critical coupling through the
quasi-BIC resonance. In a single-mode two-port system composed of graphene
coupled with silicon nanodisk metasurfaces, the maximum absorption of 0.5 can
be achieved when the radiation rate of the magnetic dipole resonance equals to
the dissipate loss rate of graphene. Furthermore, the absorption bandwidth can
be adjusted more than two orders of magnitude from 0.9 nm to 94 nm by
simultaneously changing the asymmetric parameter of metasurfaces, the Fermi
level and the layer number of graphene. This work reveals out the essential
role of BIC in radiation engineering and provides promising strategies in
controlling light absorption of 2D materials for the next-generation optical
and photonic devices, e.g., light emitters, detectors, modulators, and sensors.


  The electronic structure of Ba$_2$Ti$_2$Fe$_2$As$_4$O, a newly discovered
superconductor, is investigated using first-principles calculations based on
local density approximations. Multiple Fermi surface sheets originating from
Ti-3$d$ and Fe-3$d$ states are present corresponding to the conducting
Ti$_2$As$_2$O and Fe$_2$As$_2$ layers respectively. Compared with
BaFe$_2$As$_2$, sizeable changes in the related Fermi surface sheets indicate
significant electron transfer (about 0.12$e$) from Ti to Fe, which suppresses
the stripe-like antiferromagnetism at the Fe sites and simultaneously induces
superconductivity. Our calculations also suggest that an additional
N\'{e}el-type antiferromagnetic instability at the Ti sites is relatively
robust against the electron transfer, which accounts for the anomaly at 125 K
in the superconducting Ba$_2$Ti$_2$Fe$_2$As$_4$O.


  MINOS will measure the composition of a neutrino beam at two locations, 735km
apart, in an effort confirm the (atmospheric) neutrino oscillation hypothesis
and measure the associated mixing parameters. Oscillations will be manifested
as a difference in the rate and energy spectrum of muon neutrino CC
interactions measured in the two detectors. Because most interactions observed
in MINOS are inelastic, the neutrino energy is reconstructed as the sum of the
energy carried by the muon and that seen in the hadronic shower emanating from
the struck nucleus. The latter is sensitive to uncertainties in the
hadronisation process, chief among them those due to intranuclear re-scattering
(i.e., final state interactions). We discuss the simulation of intranuclear
re-scattering currently used by MINOS and its effect on quantities observable
in the experiment.


  We use our Clifford algebra technique, that is nilpotents and projectors
which are binomials of the Clifford algebra objects $\gamma^a$ with the
property $\{\gamma^a,\gamma^b\}_+ = 2 \eta^{ab}$, for representing quantum
gates and quantum algorithms needed in quantum computers in an elegant way. We
identify $n$-qubits with spinor representations of the group SO(1,3) for a
system of $n$ spinors. Representations are expressed in terms of products of
projectors and nilpotents. An algorithm for extracting a particular information
out of a general superposition of $2^n$ qubit states is presented. It
reproduces for a particular choice of the initial state the Grover's algorithm.


  Noether's 2nd theorem applied to a total system states that a global symmetry
which is a part of local symmetries does not provide a physically meaningful
conserved charge but it instead leads to off-shell constraints as a form of
conserved currents. In this paper, we propose a general method to derive a
matter conserved current associated with a special global symmetry in the
presence of local symmetries. While currents derived from local symmetries of a
matter sector with a covariant background gauge field are not conserved in
general, we show that the current associated with a special type of a global
symmetry, called a hidden matter symmetry, is on-shell conserved. We apply this
derivation to a $U(1)$ gauge theory, general relativity and a non-abelian gauge
theory. In general relativity, the associated conserved charge agrees with the
one recently proposed from a different point of view.


  The model of congestion games is widely used to analyze games related to
traffic and communication. A central property of these games is that they are
potential games and hence posses a pure Nash equilibrium. In reality it is
often the case that some players cooperatively decide on their joint action in
order to maximize the coalition's total utility. This is by modeled by
Coalitional Congestion Games. Typical settings include truck drivers who work
for the same shipping company, or routers that belong to the same ISP. The
formation of coalitions will typically imply that the resulting coalitional
congestion game will no longer posses a pure Nash equilibrium. In this paper we
provide conditions under which such games are potential games and posses a pure
Nash equilibrium.


  We extend the geometric approach to vertex algebras developed by the first
author to twisted modules, allowing us to treat orbifold models in conformal
field theory. Let $V$ be a vertex algebra, $H$ a finite group of automorphisms
of $V$, and $C$ an algebraic curve such that $H \subset \on{Aut}(C)$. We show
that a suitable collection of twisted $V$--modules gives rise to a section of a
certain sheaf on the quotient $X=C/H$. We introduce the notion of conformal
blocks for twisted modules, and analyze them in the case of the Heisenberg and
affine Kac-Moody vertex algebras. We also give a chiral algebra interpretation
of twisted modules.


  The Dark UNiverse Explorer (DUNE) is a wide-field space imager whose primary
goal is the study of dark energy and dark matter with unprecedented precision.
For this purpose, DUNE is optimised for the measurement of weak gravitational
lensing but will also provide complementary measurements of baryonic accoustic
oscillations, cluster counts and the Integrated Sachs Wolfe effect. Immediate
auxiliary goals concern the evolution of galaxies, to be studied with
unequalled statistical power, the detailed structure of the Milky Way and
nearby galaxies, and the demographics of Earth-mass planets. DUNE is an
Medium-class mission which makes use of readily available components, heritage
from other missions, and synergy with ground based facilities to minimise cost
and risks. The payload consists of a 1.2m telescope with a combined visible/NIR
field-of-view of 1 deg^2. DUNE will carry out an all-sky survey, ranging from
550 to 1600nm, in one visible and three NIR bands which will form a unique
legacy for astronomy. DUNE will yield major advances in a broad range of fields
in astrophysics including fundamental cosmology, galaxy evolution, and
extrasolar planet search. DUNE was recently selected by ESA as one of the
mission concepts to be studied in its Cosmic Vision programme.