  This paper is part of an ongoing project that seeks to address a gap in
disaster information coordination and collaboration in Zimbabwe. There is lack
of coordinated information and knowledge in natural disaster and emergency
situations in Zimbabwe. This results in weak collaboration links among the
various organizations that respond to emergencies, leading to slow decision
making processes and long response times. This negatively affects the affected
communities, exacerbating poverty in Zimbabwe. This has been evidenced in the
recent catastrophic cyclone Idai where many people were left dead,
infrastructure destroyed and some people marooned. To address this, the
research seeks to develop an integrated Knowledge Management and ICT framework
that aid in coordination and collaboration among the various crisis responders.
This will be achieved through a case study approach using Zimbabwe's Civil
Protection Unit. PAR within DSRM will be used to gather data from CPU as well
as with NGO respondents, traditional leaders and disaster response experts.
Findings will be compared and contrasted with secondary data gathered in
literature, this, with collected data will be used in developing a home grown
coordination and collaboration solution. Qualitative approach to data
collection will be adopted using interviews, visioning workshops and document
analysis.


  Extrusion is a widely used process for forming pastes into designed shapes,
and is central to the manufacture of many industrial products. The extrusion
through a square-entry die of a model paste of non-Brownian spheres suspended
in a Newtonian fluid is investigated using discrete element simulations,
capturing individual particle contacts and hydrodynamic interactions. The
simulations reveal inhomogeneous velocity and stress distributions, originating
in the inherent microstructure formed by the constituent particles. Such
features are shown to be relevant to generic paste extrusion behaviour, such as
die swell. The pressure drop across the extruder is correlated with the
extrudate velocity using the Benbow-Bridgwater equation, with the empirical
parameters being linked directly to particle properties such as surface
friction, and processing conditions such as extruder wall roughness. Our model
and results bring recent advances in suspension rheology into an industrial
setting, laying foundations for future model development, paste formulation and
extrusion design.


  We calculate the invariant and helicity amplitudes for the transitions
$\Lambda_b~\to~\Lambda^{(\ast)}(J^P)~+~J/\psi$ where the
$\Lambda^{(\ast)}(J^P)$ are $\Lambda(sud)$-type ground and excited states with
$J^P$ quantum numbers $J^P=\frac12^{\pm},\frac32^{\pm}$. The calculations are
performed in the framework of a covariant confined quark model previously
developed by us. We find that the values of the helicity amplitudes for the
$\Lambda^\ast(1520,\,\frac32^-)$ and the $\Lambda^\ast(1890,\,\frac32^+)$ are
suppressed compared with those for the ground state $\Lambda(1116,\,\frac12^+)$
and the excited state $\Lambda^\ast(1405,\,\frac12^-)$. This analysis is
important for the identification of the hidden charm pentaquark states
$P_c^+(4380)$ and $P_c^+(4450)$ which were discovered in the decay chain
$\Lambda_b^0~\to~P_c^+(~\to~p~J/\psi)~+~K^- $ because the cascade decay chain
$\Lambda_b~\to~\Lambda^\ast(\frac32^\pm)(~\to~pK^-)~+~J/\psi$ involves the same
final state.


  Efficiently estimating fermionic Hamiltonian expectation values is vital for
simulating various physical systems. Classical shadow (CS) algorithms offer a
solution by reducing the number of quantum state copies needed, but noise in
quantum devices poses challenges. We propose an error-mitigated CS algorithm
assuming gate-independent, time-stationary, and Markovian (GTM) noise. For
$n$-qubit systems, our algorithm, which employs the easily prepared initial
state $|0^n\rangle\!\langle 0^n|$ assumed to be noiseless, efficiently
estimates $k$-RDMs with $\widetilde{\mathcal O}(kn^k)$ state copies and
$\widetilde{\mathcal O}(\sqrt{n})$ calibration measurements for GTM noise with
constant fidelities. We show that our algorithm is robust against noise types
like depolarizing, damping, and $X$-rotation noise with constant strengths,
showing scalings akin to prior CS algorithms for fermions but with better noise
resilience. Numerical simulations confirm our algorithm's efficacy in noisy
settings, suggesting its viability for near-term quantum devices.


  Various panel sessions were organized to highlight the activities of the
African Strategy for Fundamental and Applied Physics (ASFAP) Working Groups
during the second African Conference of Fundamental and Applied Physics
(ACP2021) that was held in March 7-11, 2022. A joint session was devoted to
highlight the activities assigned to the Light Sources, Accelerators,
Biophysics, Earth Sciences, Atomic and Molecular Physics, and Condensed Matter
and Materials Physics Working Groups. Major outcomes and recommendations are
demonstrated and deliberated in this contribution.


  Hilbert spaces of states can be constructed in standard quantum field theory
only for infinitely extended spacelike hypersurfaces, precluding a more local
notion of state. In fact, the Reeh-Schlieder Theorem prohibits the localization
of states on pieces of hypersurfaces in the standard formalism. From the point
of view of geometric quantization the problem lies in the non-locality of the
complex structures associated to hypersurfaces in standard quantization. We
show that using a weakened version of the positive formalism puts this problem
into a new perspective. This is a local TQFT type formalism based on
super-operators and mixed state spaces rather than on amplitudes and pure state
spaces as the one of Atiyah-Segal. In particular, we show that in the case of
purely fermionic degrees of freedom the complex structure can be dispensed with
when the notion of state is suitably generalized. These generalized states do
localize on compact hypersurfaces with boundaries. For the simplest case of
free fermionic fields we embed this in a rigorous and functorial quantization
scheme yielding a local description of the quantum theory. Crucially, no
classical data is needed beyond the structures evident from a Lagrangian
setting. When the classical data is augmented with complex structures on
hypersurfaces, the quantum data correspondingly augment to the full positive
formalism. This scheme is applicable to field theory in curved spacetime, but
also to field theories without metric background.


  We study the Excluded Grid Theorem of Robertson and Seymour. This is a
fundamental result in graph theory, that states that there is some function $f:
Z^+\rightarrow Z^+$, such that for all integers $g>0$, every graph of treewidth
at least $f(g)$ contains the $(g\times g)$-grid as a minor. Until recently, the
best known upper bounds on $f$ were super-exponential in $g$. A recent work of
Chekuri and Chuzhoy provided the first polynomial bound, by showing that
treewidth $f(g)=O(g^{98}\operatorname{poly}\log g)$ is sufficient to ensure the
existence of the $(g\times g)$-grid minor in any graph. In this paper we
improve this bound to $f(g)=O(g^{19}\operatorname{poly}\log g)$. We introduce a
number of new techniques, including a conceptually simple and almost entirely
self-contained proof of the theorem that achieves a polynomial bound on $f(g)$.


  Since May 2011 the AMS-02 experiment is installed on the International Space
Station and is observing cosmic radiation. It consists of several
state-of-the-art sub-detectors, which redundantly measure charge and energy of
traversing particles. Due to the long exposure time of AMS-02 of many years the
measurement of momentum for protons and ions is limited systematically by the
spatial resolution and magnetic field strength of the silicon tracker. The
maximum detectable rigidity for protons is about 1.8~TV, for helium about
3.6~TV. We investigate the possibility to extend the range of the energy
measurement for heavy nuclei ($Z\geq2$) with the transition radiation detector
(TRD). The response function of the TRD shows a steep increase in signal from
the level of ionization at a Lorentz factor $\gamma$ of about 500 to
$\gamma\approx20000$, where the transition radiation signal saturates. For
heavy ions the signal fluctuations in the TRD are sufficiently small to allow
an energy measurement with the TRD beyond the limitations of the tracker. The
energy resolution of the TRD is determined and reaches a level of about 20\%
for boron ($Z=5$). After adjusting the operational parameters of the TRD a
measurement of boron and carbon could be possible up to 5~TeV/nucleon.


  The kinematics of particles refer to events and tangent vectors, while that
of waves refer to dual gradient planes. Special relativity [1-3] applies to
both objects alike. Here we show that spacetime exchange symmetry [7] implicit
in the SIdefinition of length based on the universal constant c has profound
consequences at low velocities. Galilean physics, exact in the limit c \to
\infty, is mirrored by a dual so-called Carrollian superluminal kinematics
[4-6] exact in the limit c \to 0. Several new results follow. The Galilean
limit explains mass conservation in Newtonian mechanics, while the dual limit
is a kinematical prerequisite for wavelike tachyonic motion [8, 9]. As an
example, the Land\'e paradox [19, 20] of waveparticle duality has a natural
resolution within special relativity in terms of superluminal, particlelike
waves. It is emphasized that internal particle energy mc^2 can not be ignored,
while kinetic energy leads to an extended Galilei group. We also demonstrate
that Maxwell's equations have magnetic and electric limits covariant under
Galilean and Carrollian symmetry.


  Handwritten automatic character recognition has attracted many researchers
all over the world to contribute automatic character recognition domain. Shape
identification and feature extraction is very important part of any character
recognition system and success of method is highly dependent on selection of
features. However feature extraction is the most important step in defining the
shape of the character as precisely and as uniquely as possible. This is indeed
the most important step and complex task as well and achieved success by using
invariance property, irrespective of position and orientation. Zernike moments
describes shape, identify rotation invariant due to its Orthogonality property.
MODI is an ancient script of India had cursive and complex representation of
characters. The work described in this paper presents efficiency of Zernike
moments over Hus moment for automatic recognition of handwritten MODI numerals.


  We have performed an experimental study on the temperature dependence of
electrical resistivity $\rho$($T$) and heat capacity $C$($T$) of the
Mo$_{1-x}$Re$_x$ $(x = 0.20, 0.25)$ alloy superconductors in different magnetic
fields. In the presence of applied magnetic field, the electrical resistivity
of these alloys go to zero at a temperature well above the bulk superconducting
transition temperature obtained with the help of heat capacity measurements in
the same magnetic field. Our study indicates the presence of surface
superconducting state in these alloys, where the flux lines are pinned in the
surface sheath of the superconductor. The configuration of the flux-lines (2d
pancake-like) in the surface sheath is understood in the realm of the flux-spot
model. Experimental evidence in support of the surface mixed-state state or
"Kulik vortex-state" and the occurrence of a vortex-liquid to vortex-glass
transition is presented.


  A study on the optimization of ambient temperature growth and superconducting
properties of Ti-V alloy thin films grown on SiO2-coated Si substrate is
reported here. These films have been synthesized by co-sputtering of Ti and V
targets, and films having different Ti concentrations were deposited to get the
optimized critical temperature (TC) of thin films close to the bulk value. The
maximum TC of 5.2 K has been obtained in the Ti40V60 composition, which is
further increased to 6.2 K when a 10 nm thick Ti underlayer is added below the
Ti-V film. GIXRD measurements confirm the formation of Ti-V alloys in the
desired crystal structure. The upper critical field (HC2) of the thin films has
been estimated with the help of magnetotransport measurements. The utility of
Ti-V alloy thin films in superconducting radiation detection applications is
ascertained.


  Many video understanding tasks work in the offline setting by assuming that
the input video is given from the start to the end. However, many real-world
problems require the online setting, making a decision immediately using only
the current and the past frames of videos such as in autonomous driving and
surveillance systems. In this paper, we present a novel solution for online
action detection by using a simple yet effective RNN-based networks called the
Future Anticipation and Temporally Smoothing network (FATSnet). The proposed
network consists of a module for anticipating the future that can be trained in
an unsupervised manner with the cycle-consistency loss, and another component
for aggregating the past and the future for temporally smooth frame-by-frame
predictions. We also propose a solution to relieve the performance loss when
running RNN-based models on very long sequences. Evaluations on TVSeries,
THUMOS14, and BBDB show that our method achieve the state-of-the-art
performances compared to the previous works on online action detection.


  We consider both divergence and non-divergence parabolic equations on a half
space in weighted Sobolev spaces. All the leading coefficients are assumed to
be only measurable in the time and one spatial variable except one coefficient,
which is assumed to be only measurable either in the time or the spatial
variable. As functions of the other variables the coefficients have small
bounded mean oscillation (BMO) semi-norms. The lower-order coefficients are
allowed to blow up near the boundary with a certain optimal growth condition.
As a corollary, we also obtain the corresponding results for elliptic
equations.


  In this paper we study a discrete time consensus model on a connected graph
with monotonically increasing peer-pressure and noise perturbed outputs masking
a hidden state. We assume that each agent maintains a constant hidden state and
a presents a dynamic output that is perturbed by random noise drawn from a
mean-zero distribution. We show consensus is ensured in the limit as time goes
to infinity under certain assumptions on the increasing peer-pressure term and
also show that the hidden state cannot be exactly recovered even when model
dynamics and outputs are known. The exact nature of the distribution is
computed for a simple two vertex graph and results found are shown to
generalize (empirically) to more complex graph structures.


  Based on accurate representation of the He+-He angular differential
scattering cross sections consisting of both elastic and charge exchange
collisions, we performed detailed numerical simulations of the ion velocity
distribution functions (IVDF) by Monte Carlo collision method (MCC). The
results of simulations are validated by comparison with the experimental data
of the ion mobility and the transverse diffusion. The IVDF simulation study
shows that due to significant effect of scattering in elastic collisions IVDF
cannot be separated into product of two independent IVDFs in the transverse and
parallel to the electric field directions.


  The most fundamental complexes of free modules over a commutative ring are
the Koszul complex, which is constructed from a vector (i.e., a 1-tensor), and
the Eagon-Northcott and the Buchsbaum-Rim complexes, which are constructed from
a matrix (i.e., a 2-tensor). The subject of this paper is a multilinear
analogue of these complexes, which we construct from an arbitrary higher
tensor. Our construction provides detailed new examples of minimal free
resolutions, as well as a unifying view on a wide variety of complexes
including: the Eagon-Northcott, Buchsbaum-Rim and similar complexes, the
Eisenbud-Schreyer pure resolutions, and the complexes used by
Gelfand-Kapranov-Zelevinsky and Weyman to compute hyperdeterminants. In
addition, we provide applications to the study of pure resolutions and
Boij-Soederberg theory, including the construction of infinitely many new
families of pure resolutions and the first explicit description of the
differentials of the Eisenbud-Schreyer pure resolutions.


  The present work constitutes the second part of a two-paper project that, in
particular, deals with an in-depth study of effective techniques used in
econometrics in order to make accurate forecasts in the concrete framework of
one of the major economies of the most productive Italian area, namely the
province of Verona. It is worth mentioning that this region is indubitably
recognized as the core of the commercial engine of the whole Italian country.
This is why our analysis has a concrete impact; it is based on real data, and
this is also the reason why particular attention has been taken in treating the
relevant economical data and in choosing the right methods to manage them to
obtain good forecasts. In particular, we develop an approach mainly based on
vector autoregression where lagged values of two or more variables are
considered, Granger causality, and the stochastic trend approach useful to work
with the cointegration phenomenon.


  Fast pixelated detectors incorporating direct electron detection (DED)
technology are increasingly being regarded as universal detectors for scanning
transmission electron microscopy (STEM), capable of imaging under multiple
modes of operation. However, several issues remain around the post acquisition
processing and visualisation of the often very large multidimensional STEM
datasets produced by them. We discuss these issues and present open source
software libraries to enable efficient processing and visualisation of such
datasets. Throughout, we provide examples of the analysis methodologies
presented, utilising data from a 256$\times$256 pixel Medipix3 hybrid DED
detector, with a particular focus on the STEM characterisation of the
structural properties of materials. These include the techniques of virtual
detector imaging; higher order Laue zone analysis; nanobeam electron
diffraction; and scanning precession electron diffraction. In the latter, we
demonstrate nanoscale lattice parameter mapping with a fractional precision
$\le 6\times10^{-4}$ (0.06%).


  Recent progress in neural forecasting accelerated improvements in the
performance of large-scale forecasting systems. Yet, long-horizon forecasting
remains a very difficult task. Two common challenges afflicting the task are
the volatility of the predictions and their computational complexity. We
introduce N-HiTS, a model which addresses both challenges by incorporating
novel hierarchical interpolation and multi-rate data sampling techniques. These
techniques enable the proposed method to assemble its predictions sequentially,
emphasizing components with different frequencies and scales while decomposing
the input signal and synthesizing the forecast. We prove that the hierarchical
interpolation technique can efficiently approximate arbitrarily long horizons
in the presence of smoothness. Additionally, we conduct extensive large-scale
dataset experiments from the long-horizon forecasting literature, demonstrating
the advantages of our method over the state-of-the-art methods, where N-HiTS
provides an average accuracy improvement of almost 20% over the latest
Transformer architectures while reducing the computation time by an order of
magnitude (50 times). Our code is available at bit.ly/3VA5DoT


  This work explores the biases in learning processes based on deep neural
network architectures. We analyze how bias affects deep learning processes
through a toy example using the MNIST database and a case study in gender
detection from face images. We employ two gender detection models based on
popular deep neural networks. We present a comprehensive analysis of bias
effects when using an unbalanced training dataset on the features learned by
the models. We show how bias impacts in the activations of gender detection
models based on face images. We finally propose InsideBias, a novel method to
detect biased models. InsideBias is based on how the models represent the
information instead of how they perform, which is the normal practice in other
existing methods for bias detection. Our strategy with InsideBias allows to
detect biased models with very few samples (only 15 images in our case study).
Our experiments include 72K face images from 24K identities and 3 ethnic
groups.


  Usual explanations of spiral galaxy rotation curves assume circular orbits of
stars. The consequences of giving up this assumption are investigated here. In
particular, hyperbolic stellar trajectories are found to be interesting. The
two suggested models for the production of such trajectories will also explain
the observed flat rotation curves without the postulation of dark matter or
MOND. It is suggested that spiral galaxies may have started as compact objects
with significant angular momenta and then disintegrated. The first model
conjectures the existence of a spinning hot disk around a spherical galactic
core. The disk is held together by local gravity and electromagnetic scattering
forces. However, it disintegrates at the edge producing fragments that form
stars. Once separated from the disk, the stars experience only the centrally
directed gravitational force due to the massive core and remaining disk. A
numerical simulation shows that a high enough angular velocity of the disk
produces hyperbolic stellar trajectories that agree with the observed rotation
curves. The second model conjectures a significant initial thermonuclear event
that produces a dust plume along with large stars. This dust plume is made of
ordinary matter. However, it acts like the postulated dark matter in producing
initial circular trajectories. Unlike dark matter, the plume can be shown to
escape the galaxy rapidly causing the star trajectories to evolve to hyperbolic
shapes. This process can be seen to produce the observed rotation curves due to
the initial circular orbits. Also, as the plume dissipates rapidly it does not
obfuscate the stars from view. Both models have weaknesses as do the currently
known models using dark matter or MOND.


  The success of neural summarization models stems from the meticulous
encodings of source articles. To overcome the impediments of limited and
sometimes noisy training data, one promising direction is to make better use of
the available training data by applying filters during summarization. In this
paper, we propose a novel Bi-directional Selective Encoding with Template
(BiSET) model, which leverages template discovered from training data to softly
select key information from each source article to guide its summarization
process. Extensive experiments on a standard summarization dataset were
conducted and the results show that the template-equipped BiSET model manages
to improve the summarization performance significantly with a new state of the
art.


  Large training data and expensive model tweaking are standard features of
deep learning for images. As a result, data owners often utilize cloud
resources to develop large-scale complex models, which raises privacy concerns.
Existing solutions are either too expensive to be practical or do not
sufficiently protect the confidentiality of data and models. In this paper, we
study and compare novel \emph{image disguising} mechanisms, DisguisedNets and
InstaHide, aiming to achieve a better trade-off among the level of protection
for outsourced DNN model training, the expenses, and the utility of data.
DisguisedNets are novel combinations of image blocktization, block-level random
permutation, and two block-level secure transformations: random
multidimensional projection (RMT) and AES pixel-level encryption (AES).
InstaHide is an image mixup and random pixel flipping technique \cite{huang20}.
We have analyzed and evaluated them under a multi-level threat model. RMT
provides a better security guarantee than InstaHide, under the Level-1
adversarial knowledge with well-preserved model quality. In contrast, AES
provides a security guarantee under the Level-2 adversarial knowledge, but it
may affect model quality more. The unique features of image disguising also
help us to protect models from model-targeted attacks. We have done an
extensive experimental evaluation to understand how these methods work in
different settings for different datasets.


  We study freely acting orbifolds of type IIB string theory on $T^5$ that
spontaneously break supersymmetry from $\mathcal{N}=8$ to $\mathcal{N}=6,4,2$
or 0 in five dimensions. We focus on orbifolds that are a $\mathbb{Z}_p$
quotient by a T-duality acting on $T^4$ and a shift on the remaining $S^1$.
Modular invariant partition functions are constructed and detailed examples of
both symmetric and asymmetric orbifolds are presented, including new examples
of five-dimensional non-supersymmetric string theories with no tachyons. The
orbifolds we consider arise at special points in the moduli space of string
theory compactifications with a duality twist. The supergravity limit of these
are Scherk-Schwarz reductions which generate gauged supergravities with
positive definite potentials on the moduli space in five dimensions. Both
symmetric and asymmetric freely acting orbifolds give a landscape of Minkowski
vacua. For gauged supergravities to belong to this landscape, we find a number
of constraints and conditions. Firstly, the scalar potential should lead to a
massive spectrum with masses that obey quantization conditions arising from a
string theory orbifold, which we discuss in detail. Secondly, we find
constraints on the massless sector, e.g. in the examples of orbifolds
preserving sixteen supercharges in five dimensions that we consider, only an
odd number of vector multiplets arise. Lastly, we present new examples of
candidate asymmetric orbifolds with modular invariant partition functions, but
with non-integral coefficients in the $q\bar{q}$-expansion in the twisted
sector.


  The cross-entropy softmax loss is the primary loss function used to train
deep neural networks. On the other hand, the focal loss function has been
demonstrated to provide improved performance when there is an imbalance in the
number of training samples in each class, such as in long-tailed datasets. In
this paper, we introduce a novel cyclical focal loss and demonstrate that it is
a more universal loss function than cross-entropy softmax loss or focal loss.
We describe the intuition behind the cyclical focal loss and our experiments
provide evidence that cyclical focal loss provides superior performance for
balanced, imbalanced, or long-tailed datasets. We provide numerous experimental
results for CIFAR-10/CIFAR-100, ImageNet, balanced and imbalanced 4,000
training sample versions of CIFAR-10/CIFAR-100, and ImageNet-LT and Places-LT
from the Open Long-Tailed Recognition (OLTR) challenge. Implementing the
cyclical focal loss function requires only a few lines of code and does not
increase training time. In the spirit of reproducibility, our code is available
at \url{https://github.com/lnsmith54/CFL}.


  Generalised Complex Geometry provides a natural interpretation of the
$\mathcal{N}=1$ supersymmetry conditions for warped solutions of type II
supergravity as differential equations on polyforms on the internal manifold.
Written in this language the supersymmetry conditions correspond to calibration
conditions for probe D-branes: D-string, domain-wall or space-filling branes,
depending on the directions they span in the non-compact four-dimensional
space. The BPS condition corresponding to the calibration of space-filling
D-branes has been reformulated by Tomasiello, eliminating the explicit
dependence on the metric. We generalise this derivation to the case of
non-supersymmetric backgrounds violating the domain-wall and D-string
calibration conditions. We use this reformulation to derive constraints that
the ten-dimensional solutions with BPS space-filling sources must respect in
order to dimensionally reduce to solutions of four-dimensional $\mathcal{N}=1$
supergravity with non-vanishing F-terms and potentially non-vanishing D-terms.
We give the equations of motion for the class of type II vacua satisfying these
constraints in the language of pure spinors. We investigate how restrictive
these constraints are for the class of type IIB SU$(3)$ backgrounds with BPS
space-filling O5-planes.


  Generalized parton distributions (GPDs) enter QCD factorization theorems for
hard exclusive reactions. They encode rich information about hadron partonic
structure. We explore a possibility to constrain GPDs in experiments at LHC
considering two different exclusive processes: the timelike Compton scattering
and the photoproduction of heavy vector mesons.


  We present a new optical spectroscopic survey of 1777 'star-forming' ('SF')
and 366 'non-star-forming' ('non-SF') galaxies at redshifts z < 1 (2143 in
total), 22 AGN and 423 stars, observed by instruments such as DEIMOS, VIMOS and
GMOS, in 3 fields containing 5 quasi-stellar objects (QSOs) with HST UV
spectroscopy. We also present a new spectroscopic survey of 165 'strong' (10^14
< NHI < 10^17 cm^-2), and 489 'weak' (10^13 < NHI < 10^14 cm^-2) intervening HI
absorption line systems at z < 1 (654 in total), observed in the spectra of 8
QSOs by COS and FOS on the HST. Combining these new data with previously
published galaxy catalogs such as VVDS and GDDS, we have gathered a sample of
654 HI absorption systems and 17509 galaxies at transverse scales < 50 Mpc. We
present observational results on the HI-galaxy and galaxy-galaxy correlations
at transverse scales r < 10 Mpc, and the HI-HI auto-correlation at transverse
scales r < 2 Mpc. The two-point correlation functions are measured both along
and transverse to the line-of-sight. We constrain the HI-galaxy statistical
connection, as a function of both HI column density and galaxy star-forming
activity. Our results are consistent with the following conclusions: (1) the
bulk of HI systems on Mpc scales have little velocity dispersion (<120 km/s)
with respect to the bulk of galaxies; (2) the vast majority of strong HI
systems and SF galaxies are distributed in the same locations, together with
75+-15% of non-SF galaxies, all of which typically reside in dark matter haloes
of similar masses; (3) 25+-15% of non-SF galaxies reside in galaxy clusters and
are not correlated with strong HI systems at scales < 2 Mpc; and (4) 50% of
weak HI systems reside within galaxy voids (hence not correlated with
galaxies), and are confined in dark matter haloes of masses smaller than those
hosting... [abridged]


  The Kolmogorov-Johnson-Mehl-Avrami model, which is a nucleation and growth
poissonian process in space, has been implemented by taking into account
spatial correlation among nuclei. This is achieved through a detailed study of
a system of distinguishable and correlated dots (nuclei). The probability that
no dots be in a region of the space has been evaluated in terms of correlation
functions. The theory has been applied to describe nucleation and growth in two
dimensions under constant nucleation rate, where correlation among nuclei
depends upon the size of the nucleus. We propose a simple formula for
describing the phase transition kinetics in the presence of correlation among
nuclei. The theory is applied to the constant nucleation rate process when
correlation depends upon the nucleus-birth time. It is shown that the random
sequential adsorption and Tobin process can be analyzed in the framework of the
simultaneous nucleation case, admitting a common rationale that is apart from
an appropriate re-scaling they represent the same process from the mathematical
point of view.


  We show that the Dirichlet series associated to the Fourier coefficients of a
half-integral weight Hecke eigenform at squarefree integers extends
analytically to a holomorphic function in the half-plane $\re
s\textgreater{}\tfrac{1}{2}$. This exhibits a high fluctuation of the
coefficients at squarefree integers.


  We present a comprehensive ab initio investigation on Mg$_3$Bi$_2$, a
promising Mg-ion battery anode material with high rate capacity. Through
combined DFT (PBE, HSE06) and $G_0W_0$ electronic structure calculations, we
find that Mg$_3$Bi$_2$ is likely to be a small band gap semiconductor.
  DFT-based defect formation energies indicate that Mg vacancies are likely to
form in this material, with relativistic spin-orbit coupling significantly
lowering the defect formation energies. We show that a transition state
searching methodology based on the hybrid eigenvector-following approach can be
used effectively to search for the transition states in cases where full
spin-orbit coupling is included. Mg migration barriers found through this
hybrid eigenvector-following approach indicate that spin-orbit coupling also
lowers the migration barrier, decreasing it to a value of 0.34 eV with
spin-orbit coupling. Finally, recent experimental results on Mg diffusion are
compared to the DFT results and show good agreement. This work demonstrates
that vacancy defects and the inclusion of relativistic spin-orbit coupling in
the calculations have a profound effect in Mg diffusion in this material. It
also sheds light on the importance of relativistic spin-orbit coupling in
studying similar battery systems where heavy elements play a crucial role.


  We test whether the structural properties of the nearby dwarf spheroidal
(dSph) galaxy Draco, a well-studied Milky Way companion, can be reconciled with
the suggestion that dSphs are unbound tidal remnants with a large depth extent
along the line of sight. In order to apply the observational test of this
hypothesis suggested by Klessen & Zhao, we use public photometric data from the
Sloan Digital Sky Survey (SDSS) to explore the width of Draco's blue horizontal
branch over a range of areas covering 0.06 square degrees to 6.25 square
degrees centered on Draco. The SDSS database is the only currently existing
database with sufficient depth and area coverage to permit a stringent test of
the tidal models. We show that blue horizontal branch stars extend beyond the
previously inferred limiting radii of Draco, consistent with the observed
absence of a truncated stellar surface density profile of this dSph. We
calculate new models for a galaxy without dark matter, using Draco's
morphological properties as constraints. The resulting models are unable to
reproduce the narrow observed horizontal branch width of Draco, which stays
roughly constant regardless of the field of view. We conclude that Draco cannot
be the remnant of a tidally disrupted satellite, but is probably strongly
dark-matter dominated. (ABSTRACT ABBREVIATED)


  As noisy intermediate-scale quantum (NISQ) processors increase in size and
complexity, their use as general purpose quantum simulators will rely on
algorithms based on the Trotter-Suzuki expansion. We run quantum simulations on
a small, highly accurate quantum processor, and show how one can optimize
simulation accuracy by balancing algorithmic (Trotter) errors against native
errors specific to the quantum hardware at hand. We further study the interplay
between native errors, Trotter errors, and the emergence of chaos as seen in
measurements of a time averaged fidelity-out-of-time-ordered-correlator


  We give a characterization of modified (in the sense of Zwegers) mock theta
functions, parallel to that of ordinary theta functions. Namely, modified mock
theta functions are characterized by their analyticity properties, elliptic
transformation properties, and by being annihilated by certain second order
differential operators.


  The discovery/exclusion of Supersymmetric models for fundamental interactions
of particles is one of the milestones targeted by the Large Hadron Collider
(LHC), and in particular comprises of a large part of the physics program of
the CMS experiment. Since the initial measurements using the 36\ipb of
integrated luminosity delivered by the LHC in 2010, presently available results
utilize about one fifth of the data delivered in 2011, i.e. in the ballpark of
1\ifb, significantly extending the world limits placed on gluino and squark
production signals. An overview of these analyses is presented, highlighting
four that had been newly made public as of the date of this conference. The
evidence for Supersymmetry (SUSY) is still elusive, and a discussion follows as
to where current searches have not yet probed, also pointing out where they
might have difficulty ever probing without dedicated arrangements.


  We examine the angular momentum of an electric charge e placed at rest
outside a dilaton black hole with magnetic charge Q. The electromagnetic
angular momentum which is stored in the electromagnetic field outside the black
hole shows several common features regardless of the dilaton coupling strength,
though the dilaton black holes are drastically different in their spacetime
structure depending on it. First, the electromagnetic angular momentum depends
on the separation distance between the two objects and changes monotonically
from eQ to 0 as the charge goes down from infinity to the horizon, if
rotational effects of the black hole are discarded. Next, as the black hole
approaches extremality, however, the electromagnetic angular momentum tends to
be independent of the distance between the two objects. It is then precisely
$eQ$ as in the electric charge and monopole system in flat spacetime. We
discuss why these effects are exhibited and argue that the above features are
to hold in widely generic settings including black hole solutions in theories
with more complicated field contents, by addressing the no hair theorem for
black holes and the phenomenon of field expulsion exhibited by extremal black
holes.


  We study the dual cascade scenario for two-dimensional turbulence driven by a
spectrally localized forcing applied over a finite wavenumber range
$[k_\min,k_\max]$ (with $k_\min > 0$) such that the respective energy and
enstrophy injection rates $\epsilon$ and $\eta$ satisfy
$k_\min^2\epsilon\le\eta\le k_\max^2\epsilon$. The classical
Kraichnan--Leith--Batchelor paradigm, based on the simultaneous conservation of
energy and enstrophy and the scale-selectivity of the molecular viscosity,
requires that the domain be unbounded in both directions. For two-dimensional
turbulence either in a doubly periodic domain or in an unbounded channel with a
periodic boundary condition in the across-channel direction, a direct enstrophy
cascade is not possible. In the usual case where the forcing wavenumber is no
greater than the geometric mean of the integral and dissipation wavenumbers,
constant spectral slopes must satisfy $\beta>5$ and $\alpha+\beta\ge8$, where
$-\alpha$ ($-\beta$) is the asymptotic slope of the range of wavenumbers lower
(higher) than the forcing wavenumber. The influence of a large-scale
dissipation on the realizability of a dual cascade is analyzed. We discuss the
consequences for numerical simulations attempting to mimic the classical
unbounded picture in a bounded domain.


  The fluctuation theorem characterizes the distribution of the dissipation in
nonequilibrium systems and proves that the average dissipation will be
positive. For a large system with no external source of fluctuation,
fluctuations in properties will become unobservable and details of the
fluctuation theorem are unable to be explored. In this letter, we consider such
a situation and show how a fluctuation theorem can be obtained for a small open
subsystem within the large system. We find that a correction term has to be
added to the large system fluctuation theorem due to correlation of the
subsystem with the surroundings. Its analytic expression can be derived
provided some general assumptions are fulfilled, and its relevance it checked
using numerical simulations.


  We present the comprehensive analysis of the high-amplitude $\delta$ Sct star
V2367 Cygni. Firstly, we perform the frequency analysis for the whole available
set of the {\it Kepler} and {\it TESS} photometry. Most of the frequency peaks
are harmonics or combinations of the three known independent frequencies with
the highest amplitudes, i.e., $\nu_1=5.66106$\,d$^{-1}$,
$\nu_2=7.14898$\,d$^{-1}$ and $\nu_3=7.77557$\,d$^{-1}$. The total number of
independent frequencies is 26 and 25 from the {\it Kepler} and {\it TESS} light
curve, respectively. Then, using the $UBVRI$ time-series photometry, we
unambiguously identify the dominant frequency $\nu_1$ as the radial mode,
whereas in the case of frequencies $\nu_2$ and $\nu_3$ the most probable mode
degrees are $\ell=0$ or $\ell=2$. However, only the frequency $\nu_2$ can be
associated with a radial mode, and only if higher order effects of rotation are
taken into account. Including the rotational mode coupling, we constructed
complex seismic models of V2367\,Cyg, which fit $\nu_1$ and $\nu_2$ as radial
modes, and reproduce the amplitude of bolometric flux variations (the parameter
$f$) for the dominant mode. The empirical values of $f$ are derived from the
$UBVRI$ amplitudes and phases. We rely on the Bayesian analysis based on Monte
Carlo simulations to derive constraints on evolutionary stage, mass, rotation,
overshooting from the convective core and efficiency of convective transport in
the envelope. Our seismic analysis clearly indicates that V2367\,Cyg is in a
post-MS phase of evolution. This is the first extensive seismic modelling that
takes into account the effect of rotational coupling between pulsation modes.


  Using noisy crowdsourced labels from multiple annotators, a deep
learning-based end-to-end (E2E) system aims to learn the label correction
mechanism and the neural classifier simultaneously. To this end, many E2E
systems concatenate the neural classifier with multiple annotator-specific
``label confusion'' layers and co-train the two parts in a parameter-coupled
manner. The formulated coupled cross-entropy minimization (CCEM)-type criteria
are intuitive and work well in practice. Nonetheless, theoretical understanding
of the CCEM criterion has been limited. The contribution of this work is
twofold: First, performance guarantees of the CCEM criterion are presented. Our
analysis reveals for the first time that the CCEM can indeed correctly identify
the annotators' confusion characteristics and the desired ``ground-truth''
neural classifier under realistic conditions, e.g., when only incomplete
annotator labeling and finite samples are available. Second, based on the
insights learned from our analysis, two regularized variants of the CCEM are
proposed. The regularization terms provably enhance the identifiability of the
target model parameters in various more challenging cases. A series of
synthetic and real data experiments are presented to showcase the effectiveness
of our approach.


  Given a matrix $M$ (not necessarily nonnegative) and a factorization rank
$r$, semi-nonnegative matrix factorization (semi-NMF) looks for a matrix $U$
with $r$ columns and a nonnegative matrix $V$ with $r$ rows such that $UV$ is
the best possible approximation of $M$ according to some metric. In this paper,
we study the properties of semi-NMF from which we develop exact and heuristic
algorithms. Our contribution is threefold. First, we prove that the error of a
semi-NMF of rank $r$ has to be smaller than the best unconstrained
approximation of rank $r-1$. This leads us to a new initialization procedure
based on the singular value decomposition (SVD) with a guarantee on the quality
of the approximation. Second, we propose an exact algorithm (that is, an
algorithm that finds an optimal solution), also based on the SVD, for a certain
class of matrices (including nonnegative irreducible matrices) from which we
derive an initialization for matrices not belonging to that class. Numerical
experiments illustrate that this second approach performs extremely well, and
allows us to compute optimal semi-NMF decompositions in many situations.
Finally, we analyze the computational complexity of semi-NMF proving its
NP-hardness, already in the rank-one case (that is, for $r = 1$), and we show
that semi-NMF is sometimes ill-posed (that is, an optimal solution does not
exist).


  We identify the algorithm for constructing steady states of the $n$-species
totally asymmetric simple exclusion process (TASEP) on $L$ site periodic chain
by Ferrari and Martin with a composition of combinatorial $R$ for the quantum
affine algebra $U_q(\widehat{sl}_L)$ in crystal base theory. Based on this
connection and the factorized form of the $R$ matrix derived recently from the
tetrahedron equation, we establish a new matrix product formula for the steady
state of the TASEP which is expressed in terms of corner transfer matrices of
the $q$-oscillator valued five-vertex model at $q=0$.


  During the COVID-19 pandemic of 2019/2020, authorities have used temporary
ad-hoc policy measures, such as lockdowns and mass quarantines, to slow its
transmission. However, the consequences of widespread use of these
unprecedented measures are poorly understood. To contribute to the
understanding of the economic and human consequences of such policy measures,
we therefore construct a mathematical model of an economy under the impact of a
pandemic, select parameter values to represent the global economy under the
impact of COVID-19, and perform numerical experiments by simulating a large
number of possible policy responses. By varying the starting date of the policy
intervention in the simulated scenarios, we find that the most effective policy
intervention occurs around the time when the number of active infections is
growing at its highest rate -- that is, the results suggest that the most
severe measures should only be implemented when the disease is sufficiently
spread. The intensity of the intervention, above a certain threshold, does not
appear to have a great impact on the outcomes in our simulations, due to the
strongly concave relationship that we identify between production shortfall and
infection rate reductions. Our experiments further suggest that the
intervention should last until after the peak established by the reduced
infection rate, which implies that stricter policies should last longer. The
model and its implementation, along with the general insights from our policy
experiments, may help policymakers design effective emergency policy responses
in the face of a serious pandemic, and contribute to our understanding of the
relationship between the economic growth and the spread of infectious diseases.


  Objectives: We aim to assess the impact of temperature and relative humidity
on the transmission of COVID-19 across communities after accounting for
community-level factors such as demographics, socioeconomic status, and human
mobility status. Design: A retrospective cross-sectional regression analysis
via the Fama-MacBeth procedure is adopted. Setting: We use the data for
COVID-19 daily symptom-onset cases for 100 Chinese cities and COVID-19 daily
confirmed cases for 1,005 U.S. counties. Participants: A total of 69,498 cases
in China and 740,843 cases in the U.S. are used for calculating the effective
reproductive numbers. Primary outcome measures: Regression analysis of the
impact of temperature and relative humidity on the effective reproductive
number (R value). Results: Statistically significant negative correlations are
found between temperature/relative humidity and the effective reproductive
number (R value) in both China and the U.S. Conclusions: Higher temperature and
higher relative humidity potentially suppress the transmission of COVID-19.
Specifically, an increase in temperature by 1 degree Celsius is associated with
a reduction in the R value of COVID-19 by 0.026 (95% CI [-0.0395,-0.0125]) in
China and by 0.020 (95% CI [-0.0311, -0.0096]) in the U.S.; an increase in
relative humidity by 1% is associated with a reduction in the R value by 0.0076
(95% CI [-0.0108,-0.0045]) in China and by 0.0080 (95% CI [-0.0150,-0.0010]) in
the U.S. Therefore, the potential impact of temperature/relative humidity on
the effective reproductive number alone is not strong enough to stop the
pandemic.


  Hole doped transition metal oxides are famous due to their extraordinary
charge transport properties, such as high temperature superconductivity
(cuprates) and colossal magnetoresistance (manganites). Astonishing, the mother
system of these compounds is a Mott insulator, whereas important role in the
establishment of the metallic or superconducting state is played by the way
that holes are self-organized with doping. Experiments have shown that by
adding holes the insulating phase breaks into antiferromagnetic (AFM) regions,
which are separated by hole rich clumps (stripes) with a rapid change of the
phase of the background spins and orbitals. However, recent experiments in
overdoped manganites of the La(1-x)Ca(x)MnO(3) (LCMO) family have shown that
instead of charge stripes, charge in these systems is organized in a uniform
charge density wave (CDW). Besides, recent theoretical works predicted that the
ground state is inhomogeneously modulated by orbital and charge solitons, i.e.
narrow regions carrying charge (+/-)e/2, where the orbital arrangement varies
very rapidly. So far, this has been only a theoretical prediction. Here, by
using 139La Nuclear Magnetic Resonance (NMR) we provide direct evidence that
the ground state of overdoped LCMO is indeed solitonic. By lowering temperature
the narrow NMR spectra observed in the AFM phase are shown to wipe out, while
for T<30K a very broad spectrum reappears, characteristic of an incommensurate
(IC) charge and spin modulation. Remarkably, by further decreasing temperature,
a relatively narrow feature emerges from the broad IC NMR signal, manifesting
the formation of a solitonic modulation as T->0.


  S. Hansen and E. Zuazua [SIAM J. Cont. Optim., 1995] studied the problem of
exact controllability of two strings connected by a point mass with constant
physical coefficients. In this paper we study the same problem with variable
physical coefficients. This system is generated by the following equations
$$\rho(x) u_{tt}=(\sigma(x) u_{x})_{x}-q(x)u,~~~~x\in (-1,0)\cup (0,1),~t>0,$$
$$Mu_{tt}(0,t)+\sigma_{1}(0)u_{x}(0^{-},t)-\sigma_{2}(0)u_{x}(0^{+},t)=0,~~~t>0,$$
with Dirichlet boundary condition on the left end and a control acts on the
right end. We prove that this system is exactly controllable in an asymmetric
space for the control time $T>
2\int_{-1}^{1}(\frac{\rho(x)}{\sigma(x)})^{\frac{1}{2}}dx$. We establish the
equivalence between a suitable asymmetric norm of the initial data and the
$L^{2}(0,T)$-norm of $u_{x}(1,t)$. Our approach is mainly based on a detailed
spectral analysis and the theory of divided differences. More precisely, we
prove that the spectral gap tends to zero with a precise asymptotic estimate.


  The temporal signals from a large gas detector may show dynamical scaling due
to many correlated space points created by the charged particles while passing
through the tracking medium. This has been demonstrated through simulation
using realistic parameters of a Time Projection Chamber (TPC) being fabricated
to be used in ALICE collider experiment at CERN. An interesting aspect of this
dynamical behavior is the existence of an universal scaling which does not
depend on the multiplicity of the collision. This aspect can be utilised
further to study physics at the device level and also for the online monitoring
of certain physical observables including electronics noise which are a few
crucial parameters for the optimal TPC performance.


  While clusters of galaxies are considered one of the most important
cosmological probes, the standard spherical modelling of the dark matter and
the intracluster medium is only a rough approximation. Indeed, it is well
established both theoretically and observationally that galaxy clusters are
much better approximated as triaxial objects. However, investigating the
asphericity of galaxy clusters is still in its infancy. We review here this
topic which is currently gathering a growing interest from the cluster
community. We begin by introducing the triaxial geometry. Then we discuss the
topic of deprojection and demonstrate the need for combining different probes
of the cluster's potential. We discuss the different works that have been
addressing these issues. We present a general parametric framework intended to
simultaneously fit complementary data sets (X-ray, Sunyaev Zel'dovich and
lensing data). We discuss in details the case of Abell 1689 to show how
different models/data sets lead to different haloe parameters. We present the
results obtained from fitting a 3D NFW model to X-ray, SZ, and lensing data for
4 strong lensing clusters. We argue that a triaxial model generally allows to
lower the inferred value of the concentration parameter compared to a spherical
analysis. This may alleviate tensions regarding, e.g. the over-concentration
problem. However, we stress that predictions from numerical simulations rely on
a spherical analysis of triaxial halos. Given that triaxial analysis will have
a growing importance in the observational side, we advocate the need for
simulations to be analysed in the very same way, allowing reliable and
meaningful comparisons. Besides, methods intended to derive the three
dimensional shape of galaxy clusters should be extensively tested on simulated
multi-wavelength observations.


  One of the main difficulties to efficiently generating high-order harmonics
in long neutral-gas targets is to reach the phase-matching conditions. One
issue is that the medium cannot be sufficiently ionized by the driving laser
due to plasma defocusing. We propose a method to improve the phase-matching by
pre-ionizing the gas using a weak capillary discharge. We have demonstrated
this mechanism, for the first time, in absorption-limited XUV generation by an
800 nm femtosecond laser in argon and krypton. The phase-mismatch control
ability of our method is confirmed by an analytical model and numerical
simulation of the complete generation process. Our method allows increasing the
efficiency of the harmonic generation significantly, paving the way towards
photon-hungry applications of these short-wavelength compact sources.


  This article provides a method for constructing invariants and
semi-invariants of a binary $N$-ic form over a field $k$ characteristics $0$ or
$p > N$. A practical and broadly applicable sufficient condition for ensuring
nontriviality of the symmetrization of a graph-monomial is established. This
allows construction of infinite families of invariants (especially,
skew-invariants) and families of $k$-linearly independent semi-invariants.
These constructions are very useful in the quantum physics of Fermions.
Additionally, they permit us to establish a new polynomial-type lower bound on
the coefficient of $q^{w}$ in $(q - 1) {N + d \choose d}_{q}$ for all
sufficiently large integers $d$ and $w \leq N d / 2$.


  Recent results on jet and inclusive charged particle production in hadronic
e+e- interactions are reviewed.


  Distributed-Multiple Input Multiple Output (DMIMO) networks is a promising
enabler to address the challenges of high traffic demand in future wireless
networks. A limiting factor that is directly related to the performance of
these systems is the overhead signaling required for distributing data and
control information among the network elements. In this paper, the concept of
orthogonal partitioning is extended to D-MIMO networks employing joint
multi-user beamforming, aiming to maximize the effective sum-rate, i.e., the
actual transmitted information data. Furthermore, in order to comply with
practical requirements, the overhead subframe size is considered to be
constrained. In this context, a novel formulation of constrained orthogonal
partitioning is introduced as an elegant Knapsack optimization problem, which
allows the derivation of quick and accurate solutions. Several numerical
results give insight into the capabilities of D-MIMO networks and the actual
sum-rate scaling under overhead constraints.


  Individual-qubit readout is a key ingredient for quantum simulation and
quantum computation. Furthermore, this readout must take place in real-time to
enable the application of quantum error-correction protocols. In this paper the
capability of an EMCCD camera with a real-time processing capable output is
demonstrated to determine the quantum state of a single $^9$Be$^+$ ion and the
required timing sequences are explored. The results are comparable to a PMT
based detection. Experiments on the individual detection of $^9$Be$^+$ qubit
states undergoing coherent excitation are reported. Sources of error and the
amount of crosstalk in the detection system are discussed. Error rates due to
known problems in the state preparation and measurement processes were
determined to be approximately 0.5 %.


  The past years have seen widening efforts at increasing Prolog's
declarativeness and expressiveness. Tabling has proved to be a viable technique
to efficiently overcome SLD's susceptibility to infinite loops and redundant
subcomputations. Our research demonstrates that implicit or-parallelism is a
natural fit for logic programs with tabling. To substantiate this belief, we
have designed and implemented an or-parallel tabling engine -- OPTYap -- and we
used a shared-memory parallel machine to evaluate its performance. To the best
of our knowledge, OPTYap is the first implementation of a parallel tabling
engine for logic programming systems. OPTYap builds on Yap's efficient
sequential Prolog engine. Its execution model is based on the SLG-WAM for
tabling, and on the environment copying for or-parallelism.
  Preliminary results indicate that the mechanisms proposed to parallelize
search in the context of SLD resolution can indeed be effectively and naturally
generalized to parallelize tabled computations, and that the resulting systems
can achieve good performance on shared-memory parallel machines. More
importantly, it emphasizes our belief that through applying or-parallelism and
tabling to logic programs the range of applications for Logic Programming can
be increased.


  Einstein's traceless 1919 gravitational theory is analyzed from a variational
viewpoint. It is shown to be equivalent to a transverse (invariant only under
diffeomorphisms that preserve the Lebesgue measure) theory, with an additional
Weyl symmetry, in which the gauge is partially fixed so that the metric becomes
unimodular. In spite of the fact that this symmetry forbids direct coupling of
the potential energy with the gravitational sector, the equivalence principle
is recovered in the unimodular gauge owing to Bianchi's identities.


  We construct the higher-spin massive fermionic fields in 2+1 dimensions.
Their field equations and propagators are derived from first principle. For
fields with j>1/2, complications arise from the non-linear behaviour of the
boost operators. We find that for a spin-three-half field, the non-linearity
have an underlying structure that guarantees the locality of the fields and the
existence of covariant propagators. We conjecture that this structure exists
for fields of all spin.


  We report thermal conductivity measurements on single crystals of
herbertsmithite, over a wide range of temperatures (0.05-120 K) in magnetic
fields up to 15 T. We also report measurements of the thermal Hall effect,
found to be vanishingly small. At high temperatures, in the paramagnetic
regime, the thermal conductivity has a negligible field dependence. Upon
cooling and the development of correlations, the onset of a clear monotonic
field dependence below about 20 K signals a new characteristic temperature
scale that may reflect the subtle crossover towards the quantum spin liquid
regime. Deconfined spinons, if present, are not detected and phonons, as the
main carriers of heat, are strongly scattered by the intrinsic spin excitations
and the magnetic defects. In view of the colossal fields required to affect the
intrinsic spins, most of the field-induced evolution is attributed to the
progressive polarization of some magnetic defects. By elaborating a
phenomenological model, we extract the magnetization of these main scattering
centers which does not resemble the Brillouin function for free spins 1/2,
requiring to go beyond the paradigm of isolated paramagnetic spins. Besides,
the onset of a nonmonotonic field dependence below about 2 K underlines the
existence of another characteristic temperature scale, previously highlighted
with other measurements, and sheds new light on the phase diagram of
herbertsmithite down to the lowest temperatures.


  We generalize the local surface counterterm prescription suggested in
Einstein gravity for higher derivative (HD) and Weyl gravities. Explicitly, the
surface counterterm is found for three- and five-dimensional HD gravities. As a
result, the gravitational action for asymptotically AdS spaces is finite and
gravitational energy-momentum tensor is well-defined. The holographic trace
anomaly for d2 and d4 boundary (gauge) QFT dual to above HD gravity is
calculated from gravitational energy-momentum tensor. The calculation of AdS
black hole mass in HD gravity is presented within above prescrition. The
comparison with the standard prescription (using reference spacetime) is done.


  In this paper, the impact of energy constraints on a two-hop network with a
source, a relay and a destination under random medium access is studied. A
collision channel with erasures is considered, and the source and the relay
nodes have energy harvesting capabilities and an unlimited battery to store the
harvested energy. Additionally, the source and the relay node have external
traffic arrivals and the relay forwards a fraction of the source node's traffic
to the destination; the cooperation is performed at the network level. An inner
and an outer bound of the stability region for a given transmission probability
vector are obtained. Then, the closure of the inner and the outer bound is
obtained separately and they turn out to be identical. This work is not only a
step in connecting information theory and networking, by studying the maximum
stable throughput region metric but also it taps the relatively unexplored and
important domain of energy harvesting and assesses the effect of that on this
important measure.


  We propose and demonstrate a method for the reduction of testing effort in
safety-critical software development using DO-178 guidance. We achieve this
through the application of Bounded Model Checking (BMC) to formal low-level
requirements, in order to generate tests automatically that are good enough to
replace existing labor-intensive test writing procedures while maintaining
independence from implementation artefacts. Given that existing manual
processes are often empirical and subjective, we begin by formally defining a
metric, which extends recognized best practice from code coverage analysis
strategies to generate tests that adequately cover the requirements. We then
formulate the automated test generation procedure and apply its prototype in
case studies with industrial partners. In review, the method developed here is
demonstrated to significantly reduce the human effort for the qualification of
software products under DO-178 guidance.


  In this paper, we explore the challenges associated with biomarker
identification for diagnosis purpose in biomedical experiments, and propose a
novel approach to handle the above challenging scenario via the generalization
of the Dantzig selector. To improve the efficiency of the regularization
method, we introduce a transformation from an inherent nonlinear programming
due to its nonlinear link function into a linear programming framework. We
illustrate the use of of our method on an experiment with binary response,
showing superior performance on biomarker identification studies when compared
to their conventional analysis. Our proposed method does not merely serve as a
variable/biomarker selection tool, its ranking of variable importance provides
valuable reference information for practitioners to reach informed decisions
regarding the prioritization of factors for further investigations.


  Google Earth Engine (GEE) provides a convenient platform for applications
based on optical satellite imagery of large areas. With such data sets, the
detection of cloud is often a necessary prerequisite step. Recently, deep
learning-based cloud detection methods have shown their potential for cloud
detection but they can only be applied locally, leading to inefficient data
downloading time and storage problems. This letter proposes a method to
directly perform cloud detection in Landsat-8 imagery in GEE based on deep
learning (DeepGEE-CD). A deep neural network (DNN) was first trained locally,
and then the trained DNN was deployed in the JavaScript client of GEE. An
experiment was undertaken to validate the proposed method with a set of
Landsat-8 images and the results show that DeepGEE-CD outperformed the widely
used function of mask (Fmask) algorithm. The proposed DeepGEE-CD approach can
accurately detect cloud in Landsat-8 imagery without downloading it, making it
a promising method for routine cloud detection of Landsat-8 imagery in GEE.


  This is a short exposition--mostly by way of the toy models ``double
logarithm'' and ``triple logarithm''--which should serve as an introduction to
a forthcoming article in which we establish a connection between multiple
polylogarithms, polygons, trees and algebraic cycles.


  We show that the long-established concept of a linewidth-enhancement factor
\alpha to describe carrier-induced refractive index changes in semiconductor
lasers breaks down in quantum dot (QD) lasers when describing complex dynamic
scenarios, found for example under high-excitation or optical injection. By
comparing laser simulations using a constant \alpha-factor with results from a
more complex non-equilibrium model that separately treats gain and refractive
index dynamics, we examine the conditions under which an approximation of the
amplitude-phase coupling by an \alpha-factor becomes invalid. The
investigations show that while a quasi-equilibrium approach for conventional
quantum well lasers is valid over a reasonable parameter range, allowing one to
introduce an \alpha-factor as a constant parameter, the concept is in general
not applicable to predict QD laser dynamics due to the different timescales of
the involved scattering processes.


  We show how the "finite Quot scheme method" applied to Le Potier's strange
duality on del Pezzo surfaces leads to conjectures (valid for all smooth
complex projective surfaces) relating two sets of universal power series on
Hilbert schemes of points on surfaces: those for top chern classes of
tautological sheaves, and those for Euler characteristics of line bundles. We
have verified these predictions computationally for low order. We then give an
analysis of these conjectures in small ranks. We also give a combinatorial
proof of a formula predicted by our conjectures: the top chern class of the
tautological sheaf on $S^{[n]}$ associated to the structure sheaf of a point is
equal to $(-1)^n$ times the $n$th Catalan number.


  We show explicitly that traversable wormholes requiring exotic matter in
4-dimensions nevertheless have acceptable stress-tensors obeying reasonable
energy conditions in higher dimensions if the wormholes are regarded as being
embedded in higher dimensional space-times satisfying Einstein's field
equations. From the 4-dimensional perspective, the existence of higher
dimensions may thus facilitate wormhole and time-machine constructions through
access to "exotic matter".


  The Long Term Evolution (LTE) standard enables, besides cellular
connectivity, basic automotive services to promote road safety through
vehicle-to-infrastructure (V2I) communications. Nevertheless, stakeholders and
research institutions, driven by the ambitious technological advances expected
from fully autonomous and intelligent transportation systems, have recently
investigated new radio technologies as a means to support vehicular
applications. In particular, the millimeter wave (mmWave) spectrum holds great
promise because of the large available bandwidth that may provide the required
link capacity. Communications at high frequencies, however, suffer from severe
propagation and absorption loss, which may cause communication disconnections
especially considering high mobility scenarios. It is therefore important to
validate, through simulations, the actual feasibility of establishing V2I
communications in the above-6 GHz bands. Following this rationale, in this
paper we provide the first comparative end-to-end evaluation of the performance
of the LTE and mmWave technologies in a vehicular scenario. The simulation
framework includes detailed measurement-based channel models as well as the
full details of MAC, RLC and transport protocols. Our results show that,
although LTE still represents a promising access solution to guarantee robust
and fair connections, mmWaves satisfy the foreseen extreme throughput demands
of most emerging automotive applications.


  High-precision measurements of the electron affinities (EA) of the three
stable isotopes of silicon, $^{28}$Si, $^{29}$Si and $^{30}$Si, have been
performed at the cryogenic electrostatic ion-beam storage ring DESIREE. The
quantum states of the ions were manipulated using laser depletion, and the ions
were photodetached by laser photodetachment threshold spectroscopy. These EA
values are the first reported for $^{29}$Si$^-$ and $^{30}$Si$^-$ and provide a
reduced uncertainty for $^{28}$Si$^-$. The resulting EAs are $EA(^{28}$Si$) =
1.38952201(17)$ eV, $EA(^{29}$Si$) = 1.38952172(12)$ eV and $EA(^{29}$Si$) =
1.38952078(12)$ eV, with the corresponding isotope shifts $IS(^{29-28}$Si$) =
0.29(16)$ micro eV and $IS(^{30-28}$Si$) = 1.23(16) $ micro eV. In addition to
these measurements, the resolution and signal-to-background level was
sufficient to reveal the hyperfine structure splitting in the $^{29}$Si$^-$
isotope, which we report to be $1.8(4) micro eV.


  To understand the crystal structure of n-diamond, a hydrogen-doped (H-doped)
diamond model has been investigated using first principles calculations. In
particular, hydrogen concentration dependent elastic constants and lattice
parameters for the H-doped diamond have been analyzed. Our results indicate
that when the hydrogen concentration is less than 19 at.%, the H-doped diamond
is mechanically stable. When the hydrogen concentration is about 4 at.%, the
optimized lattice parameter, simulated XRD pattern and electronic properties
for the H-doped diamond all agree well with the corresponding experimental
values of n-diamond. The results imply that the n-diamond is likely to be an
H-doped diamond.


  We calculate the dispersion equations for magnetoplasmons in a single layer,
a pair of parallel layers, a graphite bilayer and a superlattice of graphene
layers in a perpendicular magnetic field. We demonstrate the feasibility of a
drift-induced instability of magnetoplasmons. The magnetoplasmon instability in
a superlattice is enhanced compared to a single graphene layer. The energies of
the unstable magnetoplasmons could be in the terahertz (THz) part of the
electromagnetic spectrum. The enhanced instability makes superlattice graphene
a potential source of THz radiation.


  We have investigated the 2-D stellar distribution in the outer parts of three
nearby open clusters: NGC 2287 (=M41), NGC 2516, and NGC 2548 (=M48).
Wide-field star counts have been performed in two colours on pairs of digitized
ESO and SRC Schmidt plates, allowing us to select likely cluster members in the
colour-magnitude diagrams. Cluster tidal extensions were emphasized using a
wavelet transform. Taking into account observational biases, namely the galaxy
clustering and differential extinction in the Galaxy, we have associated these
stellar overdensities with real open cluster structures stretched by the
galactic gravitational field. As predicted by theory and simulations, and
despite observational limitations, we detected a general elongated (prolate)
shape in a direction parallel to the galactic Plane, combined with tidal tails
extended perpendicularly to it. This geometry is due both to the static
galactic tidal field and the heating up of the stellar system when crossing the
Disk. The time varying tidal field will deeply affect the cluster dynamical
evolution, and we emphasize the importance of adiabatic heating during the
Disk-shocking. In the case of NGC 2548, our dating of the last shocking with
the Plane (based on a tidal clump) is consistent with its velocity. During the
10-20 Z-oscillations experienced by a cluster before its dissolution in the
Galaxy, crossings through the galactic Disk contribute to at least 15% of the
total mass loss. Using recent age estimations published for open clusters, we
find a destruction time-scale of about 600 Myr for clusters in the solar
neighbourhood.


  Leakage of information in power line communication networks is a threat to
privacy and security both in smart grids and in-home applications. A way to
enhance security is to encode the transmitted information with a secret key.
Relying on the channel properties, it is possible to generate a common key at
the two communication ends without transmitting it through the broadcast
channel. Since the key is generated locally, it is intrinsically secure from a
possible eavesdropper. Most of the existing physical layer key generation
techniques have been developed for symmetric channels. However, the power line
channel is in general not symmetric, but just reciprocal. Therefore, in this
paper, we propose two novel methods that exploit the reciprocity of the power
line channel to generate common information at the two intended users. This
information is processed through different quantization techniques to generate
secret keys. To assess the security of the generated keys, we analyze the
spatial correlation of the power line channels and verify the low correlation
of the possible eavesdropping channels. The two proposed methods are tested on
a measurement dataset. The results show that the information leaked to possible
eavesdroppers has very low correlation to any secret key.


  In accreting neutron star X-ray transients, the neutron star crust can be
substantially heated out of thermal equilibrium with the core during an
accretion outburst. The observed subsequent cooling in quiescence (when
accretion has halted) offers a unique opportunity to study the structure and
thermal properties of the crust. Initially crust cooling modelling studies
focussed on transient X-ray binaries with prolonged accretion outbursts (> 1
year) such that the crust would be significantly heated for the cooling to be
detectable. Here we present the results of applying a theoretical model to the
observed cooling curve after a short accretion outburst of only ~10 weeks. In
our study we use the 2010 outburst of the transiently accreting 11 Hz X-ray
pulsar in the globular cluster Terzan 5. Observationally it was found that the
crust in this source was still hot more than 4 years after the end of its short
accretion outburst. From our modelling we found that such a long-lived hot
crust implies some unusual crustal properties such as a very low thermal
conductivity (> 10 times lower than determined for the other crust cooling
sources). In addition, we present our preliminary results of the modelling of
the ongoing cooling of the neutron star in MXB 1659-298. This transient X-ray
source went back into quiescence in March 2017 after an accretion phase of ~1.8
years. We compare our predictions for the cooling curve after this outburst
with the cooling curve of the same source obtained after its previous outburst
which ended in 2001.


  We study asymptotically minimax predictive distributions in an infinite
sequence model. First, we discuss the connection between the prediction in the
infinite sequence model and the prediction in the function model. Second, we
construct an asymptotically minimax predictive distribution when the parameter
space is a known ellipsoid. We show that the Bayesian predictive distribution
based on the Gaussian prior distribution is asymptotically minimax in the
ellipsoid. Third, we construct an asymptotically minimax predictive
distribution for any Sobolev ellipsoid. We show that the Bayesian predictive
distribution based on the product of Stein's priors is asymptotically minimax
for any Sobolev ellipsoid. Finally, we present an efficient sampling method
from the proposed Bayesian predictive distribution.


  In this paper, we consider an unconventional overdetermined problem through a
property of concavity, which provides some characterizations of balls via
Brunn-Minkowski inequalities. In this setting, our rsults can be viewed as the
generalization of $p$-capacity in [14], which have its own interest.


  A Gallai coloring is a coloring of the edges of a complete graph without
rainbow triangles, and a Gallai $k$-coloring is a Gallai coloring that uses at
most $k$ colors. For an integer $k\geq 1$, the Gallai-Ramsey number $GR_k(H)$
of a given graph $H$ is the least positive integer $N$ such that every Gallai
$k$-coloring of the complete graph $K_N$ contains a monochromatic copy of $H$.
Let $C_m$ denote the cycle on $m\ge4$ vertices and let $\Theta_m$ denote the
family of graphs obtained from $C_m$ by adding an additional edge joining two
non-consecutive vertices. We prove that $GR_k(\Theta_{2n+1})=n\cdot 2^k+1$ for
all $k\geq 1$ and $n\geq 3$. This implies that $GR_k(C_{2n+1})=n\cdot 2^k+1$
all $k\geq 1$ and $n\geq 3$. Our result yields a unified proof for the
Gallai-Ramsey number of all odd cycles on at least five vertices.


  Instruction-tuning is a widely adopted method of finetuning that enables
large language models (LLMs) to generate output that more closely resembles
human responses to natural language queries, in many cases leading to
human-level performance on diverse testbeds. However, it remains unclear
whether instruction-tuning truly makes LLMs more similar to how humans process
language. We investigate the effect of instruction-tuning on LLM-human
similarity in two ways: (1) brain alignment, the similarity of LLM internal
representations to neural activity in the human language system, and (2)
behavioral alignment, the similarity of LLM and human behavior on a reading
task. We assess 25 vanilla and instruction-tuned LLMs across three datasets
involving humans reading naturalistic stories and sentences. We discover that
instruction-tuning generally enhances brain alignment by an average of 6%, but
does not have a similar effect on behavioral alignment. To identify the factors
underlying LLM-brain alignment, we compute correlations between the brain
alignment of LLMs and various model properties, such as model size, various
problem-solving abilities, and performance on tasks requiring world knowledge
spanning various domains. Notably, we find a strong positive correlation
between brain alignment and model size (r = 0.95), as well as performance on
tasks requiring world knowledge (r = 0.81). Our results demonstrate that
instruction-tuning LLMs improves both world knowledge representations and brain
alignment, suggesting that mechanisms that encode world knowledge in LLMs also
improve representational alignment to the human brain.


  We present new low-resolution HI spectral line imaging, obtained with the
Karl G. Jansky Very Large Array (JVLA), of the star-forming Magellanic
irregular galaxy UGCA 105. This nearby (D = 3.39+/-0.25 Mpc), low mass
[M_HI=(4.3+/-0.5)x10^8 Solar masses] system harbors a large neutral gas disk
(HI radius ~7.2 kpc at the N_HI=10^20 cm^-2 level) that is roughly twice as
large as the stellar disk at the B-band R_25 isophote. We explore the neutral
gas dynamics of this system, fitting tilted ring models in order to extract a
well-sampled rotation curve. The rotation velocity rises in the inner disk,
flattens at 72+/-3 km/s, and remains flat to the last measured point of the
disk (~7.5 kpc). The dynamical mass of UGCA 105 at this outermost point,
(9+/-2)x10^9 Solar masses, is ~10 times as large as the luminous baryonic
components (neutral atomic gas and stars). The proximity and favorable
inclination (55 degrees) of UGCA 105 make it a promising target for
high-resolution studies of both star formation and rotational dynamics in a
nearby low-mass galaxy.


  This review is made of two parts which are related to Poincar\'e in different
ways. The first part reviews the work of Poincar\'e on the Theory of (Special)
Relativity. One emphasizes both the remarkable achievements of Poincar\'e, and
the fact that he never came close to what is the essential conceptual
achievement of Einstein: changing the concept of time. The second part reviews
a topic which probably would have appealed to Poincar\'e because it involves
several mathematical structures he worked on: chaotic dynamics, discrete
reflection groups, and Lobachevskii space. This topic is the hidden role of
Kac-Moody algebras in the billiard description of the asymptotic behaviour of
certain Einstein-matter systems near a cosmological singularity. Of particular
interest are the Einstein-matter systems arising in the low-energy limit of
superstring theory. These systems seem to exhibit the highest-rank hyperbolic
Kac-Moody algebras, and notably E(10), as hidden symmetries.


  We propose a novel methodology to define, analyze and forecast market states.
In our approach market states are identified by a reference sparse precision
matrix and a vector of expectation values. In our procedure, each multivariate
observation is associated with a given market state accordingly to a
minimization of a penalized Mahalanobis distance. The procedure is made
computationally very efficient and can be used with a large number of assets.
We demonstrate that this procedure is successful at clustering different states
of the markets in an unsupervised manner. In particular, we describe an
experiment with one hundred log-returns and two states in which the methodology
automatically associates states prevalently to pre- and post- crisis periods
with one state gathering periods with average positive returns and the other
state periods with average negative returns, therefore discovering
spontaneously the common classification of `bull' and `bear' markets. In
another experiment, with again one hundred log-returns and two states, we
demonstrate that this procedure can be efficiently used to forecast off-sample
future market states with significant prediction accuracy. This methodology
opens the way to a range of applications in risk management and trading
strategies in the context where the correlation structure plays a central role.


  The mounting evidence for violent nuclear star formation in Seyfert galaxies
has led us to consider the hydrodynamics of the matter reinserted by massive
stars through strong stellar winds and supernovae, under the presence of a
central massive BH. We show that in all cases there is a bimodal solution
strongly weighted by the location of the stagnation radius (Rst), which splits
the star cluster into two different zones. Matter reinserted within the
stagnation volume is to be accreted by the BH while its outer counterpart would
composed a star cluster wind. The mechanical power of the latter, ensures that
there is no accretion of the ISM into the BH and thus the BH accretion and its
luminosity is regulated by the star formation feedback. The location of the
stagnation radius is a function of three parameters: the BH mass, the
mechanical power (or mass) of the star formation event and the size of the star
forming region. Here we present our self-consistent, stationary solution,
discuss the accretion rates and BH luminosities and show that our model
predicts the intrinsic link between the BH activity and the starburst
parameters.


  We present results of the study of the non-monotonous behavior of the
Lifshitz line as a function of temperature in ternary
homopolymer/diblock-copolymer mixtures. The non-monotonous behavior of the
Lifshitz line is due to the wave vector dependence of fluctuational
corrections, which we treat in the framework of the renormalization group
method. Our results are in agreement with the experimental findings of Schwahn
et al.[1,2]


  We collect some isomorphisms of categories and bijections of structures using
the Kleisli and Eilenberg-Moore 2-adjunctions.


  In this paper the tachyonic resonance preheating generated from the bosonic
trilinear $\phi\chi^2$ interactions in an expanding Universe is studied. In
$\lambda\phi^4/4$ inflationary model the trilinear interaction, in contrast to
the four-legs $\phi^2\chi^2$, breaks the conformal symmetry explicitly and the
resonant source term becomes non-periodic, making the Floquet theorem
inapplicable. We find that the occupation number of the produced
$\chi$-particles has a non-linear exponential growth with exponent $\sim
x^{3/2}$, where $x$ is the conformal time. This should be contrasted with
preheating from a periodic resonant source, arising for example from the
four-legs $\phi^2\chi^2$ interaction, where the occupation number has a linear
exponential growth. We present an analytic method to compute the interference
term coming from phases accumulated in non-tachyonic scattering regions and
show that the effects of the interference term causes ripples on $x^{3/2}$
curve, a result which is confirmed by numerical analysis. Studying the effects
of back-reaction of the $\chi$-particles, we show that tachyonic resonance
preheating in our model can last long enough to transfer most of the energy
from the background inflation field $\phi$, providing an efficient model for
preheating in the chaotic inflation models.


  In an informal way some kind of Ising Lattice QCD is introduced which allows
to interprete and discuss the well-known theory of quantum chromodynamics
(confinement, quarks and gluons, etc.) from simple phenomena of magnetism and
polymer physics. Also the viewpoint of duality is stressed. Moreover, the
non-abelian character of the Lie group SU(3) is important. The essential
arguments for confinement and asymptotic freedom are given at the very end of
the manuscript, after an appendix.


  The analyses of hadron production in the framework of the statistical
hadronisation model are reviewed. The analysis of average multiplicities in
collisions at relatively low centre-of-mass energy confirms previous findings,
namely the universality of hadronisation temperature and of strange to
non-strange quark production rate. The study of transverse momentum spectra of
identified hadrons allows a further determination of the hadronisation
temperature which is found to be compatible with that obtained from fits to
average multiplicities.


  We present the results of X-ray spectral analysis of the superbubble around
the OB association LH9 in the H II complex N11 in the Large Magellanic Cloud.
Using observations from Suzaku, we have modeled the X-ray emission over the
energy range 0.2-7.5 keV. We constrained the thermal spectrum below 2 keV using
a thermal plasma model found in a previous XMM-Newton study of the N11 region.
We find that the hard X-ray emission (> 2 keV) requires a nonthermal power-law
component. The photon index of this component was found to be $\Gamma=1.72\pm
0.15$. We performed an energy budget analysis for N11 using the known stellar
content of LH9. We found that the observed thermal and kinetic energy in the
superbubble is only half of the expected mechanical energy injected by stars.


  Understanding the protein folding process is an outstanding issue in
biophysics; recent developments in molecular dynamics simulation have provided
insights into this phenomenon. However, the large freedom of atomic motion
hinders the understanding of this process. In this study, we applied persistent
homology, an emerging methods to analyze topological features in a dataset, to
reveal protein folding dynamics. We developed a new method to characterize
protein structure based on persistent homology and applied this method to
molecular dynamics simulations of chignolin. Using principle component analysis
or non-negative matrix factorization, our analysis method revealed two stable
states and one saddle state, corresponding to the native, misfolded, and
transition states, respectively. We also identified an unfolded state with slow
dynamics in the reduced space. Our method serves as a promising tool to
understand the protein folding process.


  In quantum algorithms discovered so far for simulating scattering processes
in quantum field theories, state preparation is the slowest step. We present a
new algorithm for preparing particle states to use in simulation of Fermionic
Quantum Field Theory (QFT) on a quantum computer, which is based on the matrix
product state ansatz. We apply this to the massive Gross-Neveu model in one
spatial dimension to illustrate the algorithm, but we believe the same
algorithm with slight modifications can be used to simulate any one-dimensional
massive Fermionic QFT. In the case where the number of particle species is one,
our algorithm can prepare particle states using $O\left(
\epsilon^{-3.23\ldots}\right)$ gates, which is much faster than previous known
results, namely $O\left(\epsilon^{-8-o\left(1\right)}\right)$. Furthermore,
unlike previous methods which were based on adiabatic state preparation, the
method given here should be able to simulate quantum phases unconnected to the
free theory.


  We have measured the optically injected excess carrier lifetime in silicon
using photoexcited muon spin spectroscopy. Positive muons implanted deep in a
wafer can interact with the excess carriers and directly probe the bulk carrier
lifetime whilst minimizing the effect from surface recombination. The method is
based on the relaxation rate of muon spin asymmetry, which depends on the
excess carrier concentration. The underlying microscopic mechanism has been
understood by simulating the four-state muonium model in Si under illumination.
We apply the technique to different injection levels and temperatures, and
demonstrate its ability for injection- and temperature-dependent lifetime
spectroscopy.


  We prove that, given a function $f$ in the Nevanlinna class $N$ and a
positive integer $n$, there exist $g\in N$ and $h\in BMOA$ such that
$f^{(n)}=gh^{(n)}$. We may choose $g$ to be zero-free, so it follows that the
zero sets for the class $N^{(n)}:=\{f^{(n)}: f\in N\}$ are the same as those
for $BMOA^{(n)}$. Furthermore, while the set of all products $gh^{(n)}$ (with
$g$ and $h$ as above) is strictly larger than $N^{(n)}$, we show that the gap
is not too large, at least when $n=1$. Precisely speaking, the class $\{gh':
g\in N, h\in BMOA\}$ turns out to be the smallest ideal space containing $\{f':
f\in N\}$, where "ideal" means invariant under multiplication by $H^\infty$
functions. Similar results are established for the Smirnov class $N^+$.


  We demonstrate aluminum-on-silicon planar transmon qubits with time-averaged
${T_1}$ energy relaxation times of up to ${270\,\mu s}$, corresponding to Q = 5
million, and a highest observed value of ${501\,\mu s}$. We use materials
analysis techniques and numerical simulations to investigate the dominant
sources of energy loss, and devise and demonstrate a strategy towards
mitigating them. The mitigation of loss is achieved by reducing the presence of
oxide, a known host of defects, near the substrate-metal interface, by growing
aluminum films thicker than 300 nm. A loss analysis of coplanar-waveguide
resonators shows that the improvement is owing to a reduction of dielectric
loss due to two-level system defects. We perform time-of-flight secondary ion
mass spectrometry and observe a reduced presence of oxygen at the
substrate-metal interface for the thicker films. The correlation between the
enhanced performance and the film thickness is due to the tendency of aluminum
to grow in columnar structures of parallel grain boundaries, where the size of
the grain depends on the film thickness: transmission electron microscopy
imaging shows that the thicker film has larger grains and consequently fewer
grain boundaries containing oxide near this interface. These conclusions are
supported by numerical simulations of the different loss contributions in the
device.


  We investigate the task of learning to follow natural language instructions
by jointly reasoning with visual observations and language inputs. In contrast
to existing methods which start with learning from demonstrations (LfD) and
then use reinforcement learning (RL) to fine-tune the model parameters, we
propose a novel policy optimization algorithm which dynamically schedules
demonstration learning and RL. The proposed training paradigm provides
efficient exploration and better generalization beyond existing methods.
Comparing to existing ensemble models, the best single model based on our
proposed method tremendously decreases the execution error by over 50% on a
block-world environment. To further illustrate the exploration strategy of our
RL algorithm, We also include systematic studies on the evolution of policy
entropy during training.


  In this paper, we investigate relay selection for cooperative
multiple-antenna systems that are equipped with buffers, which increase the
reliability of wireless links. In particular, we present a novel relay
selection technique based on switching and the selection of the best link, that
is named Switched Max-Link. We also introduce a novel relay selection criterion
based on the Maximum Likelihood (ML) principle and the Pairwise Error
Probability (PEP) denoted Maximum Minimum Distance (MMD) that is incorporated
into the proposed Switched Max-Link protocol. We compare the proposed MMD to
the existing Quadratic Norm (QN), in terms of PEP and computational complexity.
Simulations are then employed to evaluate the performance of the proposed and
existing techniques.


  Higher-form symmetries have proved useful in constraining the dynamics of a
number of quantum field theories. In the context of the Argyres-Douglas (AD)
theories of the $(G,G')$ type, we find that the 1-form symmetries are invariant
under the Higgs branch flow, and that they are captured by the non-Higgsable
sector at a generic point on the Higgs branch of the AD theory in question. As
a consequence, dimensional reduction of an AD theory with a non-trivial 1-form
symmetry to 3d leads to a free sector. We utilize these observations, along
with other results, to propose systematically the mirror theories for the AD
theories of the $(A_n, E_m)$ type. As a by-product of these findings, we
discover many important results: the Flip-Flip duality for all $T[G]$ theories
with simply-laced group $G$, including the exceptional ones; the class
$\mathcal{S}$ descriptions of exceptional affine Dynkin diagram such that all
gauge groups are special unitary; the universality of the mirror theories for
$D_{h^\vee_G}(G)$ with $h^\vee_G$ the dual Coxeter number of $G$; and the
triviality of the 2-group structure in the $(A_n, E_m)$ theories.


  Using a chemical evolution model we investigate the intriguing suggestion
that there are populations of stars in some globular clusters (e.g. NGC 2808,
omega Centauri) with enhanced levels of helium (Y from about 0.28 to 0.40)
compared to the majority of the population that presumably have a primordial
helium abundance. We assume that a previous generation of massive
low-metallicity Asymptotic Giant Branch (AGB) stars has polluted the cluster
gas via a slow stellar wind. We use two independent sets of AGB yields computed
from detailed models to follow the evolution of helium, carbon, nitrogen and
oxygen in the cluster gas using a Salpeter initial mass function (IMF) and a
number of top-heavy IMFs. In no case were we able to fit the observational
constraints, Y > 0.30 and C+N+O approximately constant. Depending on the shape
of the IMF and the yields, we either obtained Y approximately greater than 0.30
and large increases in C+N+O or Y < 0.30 and C+N+O approximately constant.
These results suggest that either AGB stars alone are not responsible for the
large helium enrichment or that any dredge-up from this generation of stars was
less than predicted by standard models.


  The evolving algorithms for 2D facial landmark detection empower people to
recognize faces, analyze facial expressions, etc. However, existing methods
still encounter problems of unstable facial landmarks when applied to videos.
Because previous research shows that the instability of facial landmarks is
caused by the inconsistency of labeling quality among the public datasets, we
want to have a better understanding of the influence of annotation noise in
them. In this paper, we make the following contributions: 1) we propose two
metrics that quantitatively measure the stability of detected facial landmarks,
2) we model the annotation noise in an existing public dataset, 3) we
investigate the influence of different types of noise in training face
alignment neural networks, and propose corresponding solutions. Our results
demonstrate improvements in both accuracy and stability of detected facial
landmarks.


  Self-supervised learning (SSL) has emerged as a key technique for training
networks that can generalize well to diverse tasks without task-specific
supervision. This property makes SSL desirable for computational pathology, the
study of digitized images of tissues, as there are many target applications and
often limited labeled training samples. However, SSL algorithms and models have
been primarily developed in the field of natural images and whether their
performance can be improved by adaptation to particular domains remains an open
question. In this work, we present an investigation of modifications to SSL for
pathology data, specifically focusing on the DINOv2 algorithm. We propose
alternative augmentations, regularization functions, and position encodings
motivated by the characteristics of pathology images. We evaluate the impact of
these changes on several benchmarks to demonstrate the value of tailored
approaches.