  We report on a series of experiments in which we study the coevolutionary
"arms-race" dynamics among groups of agents that engage in adaptive automated
trading in an accurate model of contemporary financial markets. At any one
time, every trader in the market is trying to make as much profit as possible
given the current distribution of different other trading strategies that it
finds itself pitched against in the market; but the distribution of trading
strategies and their observable behaviors is constantly changing, and changes
in any one trader are driven to some extent by the changes in all the others.
Prior studies of coevolutionary dynamics in markets have concentrated on
systems where traders can choose one of a small number of fixed pure
strategies, and can change their choice occasionally, thereby giving a market
with a discrete phase-space, made up of a finite set of possible system states.
Here we present first results from two independent sets of experiments, where
we use minimal-intelligence trading-agents but in which the space of possible
strategies is continuous and hence infinite. Our work reveals that by taking
only a small step in the direction of increased realism we move immediately
into high-dimensional phase-spaces, which then present difficulties in
visualising and understanding the coevolutionary dynamics unfolding within the
system. We conclude that further research is required to establish better
analytic tools for monitoring activity and progress in co-adapting markets. We
have released relevant Python code as open-source on GitHub, to enable others
to continue this work.


  Estimating precise metric depth and scene reconstruction from monocular
endoscopy is a fundamental task for surgical navigation in robotic surgery.
However, traditional stereo matching adopts binocular images to perceive the
depth information, which is difficult to transfer to the soft robotics-based
surgical systems due to the use of monocular endoscopy. In this paper, we
present a novel framework that combines robot kinematics and monocular
endoscope images with deep unsupervised learning into a single network for
metric depth estimation and then achieve 3D reconstruction of complex anatomy.
Specifically, we first obtain the relative depth maps of surgical scenes by
leveraging a brightness-aware monocular depth estimation method. Then, the
corresponding endoscope poses are computed based on non-linear optimization of
geometric and photometric reprojection residuals. Afterwards, we develop a
Depth-driven Sliding Optimization (DDSO) algorithm to extract the scaling
coefficient from kinematics and calculated poses offline. By coupling the
metric scale and relative depth data, we form a robust ensemble that represents
the metric and consistent depth. Next, we treat the ensemble as supervisory
labels to train a metric depth estimation network for surgeries (i.e.,
MetricDepthS-Net) that distills the embeddings from the robot kinematics,
endoscopic videos, and poses. With accurate metric depth estimation, we utilize
a dense visual reconstruction method to recover the 3D structure of the whole
surgical site. We have extensively evaluated the proposed framework on public
SCARED and achieved comparable performance with stereo-based depth estimation
methods. Our results demonstrate the feasibility of the proposed approach to
recover the metric depth and 3D structure with monocular inputs.


  We introduce a new method, based on the recently developed random tensor
theory, to study the p-spin glass model with non-Gaussian, correlated disorder.
Using a suitable generalization of Gurau's theorem on the universality of the
large N limit of the p-unitary ensemble of random tensors, we exhibit an
infinite family of such non-Gaussian distributions which leads to same low
temperature phase as the Gaussian distribution. While this result is easy to
show (and well known) for uncorrelated disorder, its robustness with respect to
strong quenched correlations is surprising. We show in detail how the critical
temperature is renormalized by these correlations. We close with a speculation
on possible applications of random tensor theory to finite-range spin glass
models.


  A dynamical symmetry is employed to determine the structure of the quantum
non-Markovian time-local master equation. Such a structure is composed from two
components: scalar kinetic coefficients and the standard quantum Markovian
operator form. The kinetic coefficients are generally time-dependent and
incorporate information on the kinematics and memory effects, while the
operators manifest the dynamical symmetry. Specifically, we focus on
time-translation symmetric dynamics, where the Lindblad jump operators
constitute the eigenoperators of the free dynamics. This symmetry is motivated
by thermodynamic microscopic considerations, where strict energy conservation
between system and environment imposes the time-translation symmetry. The
construction is generalized to other symmetries, and to driven quantum systems.
The formalism is illustrated by three exactly solvable non-Markovian models,
where the exact reduced description exhibits a dynamical symmetric structure.
The formal structure of the master equation leads to a first principle
calculation of the exact kinetic coefficients. This opens the possibility to
simulate in a modular fashion non-Markovian dynamics.


  In this paper, we introduce a general extension of linear sparse component
analysis (SCA) approaches to postnonlinear (PNL) mixtures. In particular, and
contrary to the state-of-art methods, our approaches use a weak sparsity source
assumption: we look for tiny temporal zones where only one source is active. We
investigate two nonlinear single-source confidence measures, using the mutual
information and a local linear tangent space approximation (LTSA). For this
latter measure, we derive two extensions of linear single-source measures,
respectively based on correlation (LTSA-correlation) and eigenvalues
(LTSA-PCA). A second novelty of our approach consists of applying functional
data clustering techniques to the scattered observations in the above
single-source zones, thus allowing us to accurately estimate them.We first
study a classical approach using a B-spline approximation, and then two
approaches which locally approximate the nonlinear functions as lines. Finally,
we extend our PNL methods to more general nonlinear mixtures. Combining
single-source zones and functional data clustering allows us to tackle speech
signals, which has never been performed by other PNL-SCA methods. We
investigate the performance of our approaches with simulated PNL mixtures of
real speech signals. Both the mutual information and the LTSA-correlation
measures are better-suited to detecting single-source zones than the LTSA-PCA
measure. We also find local-linear-approximation-based clustering approaches to
be more flexible and more accurate than the B-spline one.


  This article is in the spirit of our work on the consequences of the Regge
calculus, where some edge length scale arises as an optimal initial point of
the perturbative expansion after functional integration over connection.
  Now consider the perturbative expansion itself. To obtain an algorithmizable
diagram technique, we consider the simplest periodic simplicial structure with
a frozen part of the variables ("hypercubic"). After functional integration
over connection, the system is described by the metric $g_{\lambda \mu}$ at the
sites.
  We parameterize $g_{\lambda \mu}$ so that the functional measure becomes
Lebesgue. The discrete diagrams are free from ultraviolet divergences and
reproduce (for ordinary, non-Planck external momenta) those continuum
counterparts that are finite. We give the parametrization of $g_{\lambda \mu}$
up to terms, providing, in particular, additional three-graviton and
two-graviton-two-matter vertices, which can give additional one-loop
corrections to the Newtonian potential.
  The edge length scale is $\sim \sqrt{ \eta }$, where $\eta$ defines the free
factor $ ( - \det \| g_{\lambda \mu} \| )^{ \eta / 2}$ in the measure and
should be a large parameter to ensure the true action after integration over
connection. We verify the important fact that the perturbative expansion does
not contain increasing powers of $\eta$ if its initial point is chosen close
enough to the maximum point of the measure, thus justifying this choice.
  Discrete propagators depend on the Barbero-Immirzi parameter $\gamma$, which
determines the ratio of timelike and spacelike elementary length scales. The
existing estimates of $\gamma$ allow the propagator poles to have real energy
for any (real) spatial momenta.


  We propose two new methods to address the weak scaling problems of KRR: the
Balanced KRR (BKRR) and K-means KRR (KKRR). These methods consider alternative
ways to partition the input dataset into p different parts, generating p
different models, and then selecting the best model among them. Compared to a
conventional implementation, KKRR2 (optimized version of KKRR) improves the
weak scaling efficiency from 0.32% to 38% and achieves a 591times speedup for
getting the same accuracy by using the same data and the same hardware (1536
processors). BKRR2 (optimized version of BKRR) achieves a higher accuracy than
the current fastest method using less training time for a variety of datasets.
For the applications requiring only approximate solutions, BKRR2 improves the
weak scaling efficiency to 92% and achieves 3505 times speedup (theoretical
speedup: 4096 times).


  The goal of this study is to identify, review, and analyze the published
research works that used network analysis as a tool for understanding the human
collaboration on different levels of software development. This study and its
findings are expected to be of benefit for software engineering practitioners
and researchers who are mining software repositories using tools from network
science field. We conducted a systematic literature review, in which we
analyzed a number of selected papers from different digital libraries based on
inclusion and exclusion criteria. We identified $35$ primary studies (PSs) from
4 digital libraries, then we extracted data from each PS according to a
predefined data extraction sheet. The results of our data analysis showed that
not all of the constructed networks used in the PSs were valid as the edges of
these networks did not reflect a real relationship between the entities of the
network. Additionally, the used measures in the PSs were in many cases not
suitable for the used networks. Also, the reported analysis results by the PSs
were not, in most cases, validated using any statistical model. Finally, many
of the PSs did not provide lessons or guidelines for software practitioners
that can improve the software engineering practices. Although employing network
analysis in mining developers' collaboration showed some satisfactory results
in some of the PSs, the application of network analysis needs to be conducted
more carefully. That is said, the constructed network should be representative
and meaningful, the used measure needs to be suitable for the context, and the
validation of the results should be considered. More and above, we state some
research gaps, in which network science can be applied, with some pointers to
recent advances that can be used to mine collaboration networks.


  For a formal scheme over a complete discrete valuation ring with a good
action of a finite group, we define equivariant motivic integration, and we
prove a change of variable formula for that.To do so, we construct and examine
an induced group action on the Greenberg scheme of such a formal scheme. Using
this equivariant motivic integration, we define an equivariant volume
Poincar\'e series, from which we deduce Denef and Loeser's motivic zeta
function including the action of the profinite group of roots of unity.


  We consider the classical molecular beam epitaxy (MBE) model with logarithmic
type potential known as no-slope-selection. We employ a third order backward
differentiation (BDF3) in time with implicit treatment of the surface diffusion
term. The nonlinear term is approximated by a third order explicit
extrapolation (EP3) formula. We exhibit mild time step constraints under which
the modified energy dissipation law holds. We break the second Dahlquist
barrier and develop a new theoretical framework to prove unconditional uniform
energy boundedness with no size restrictions on the time step. This is the
first unconditional result for third order BDF methods applied to the MBE
models without introducing any stabilization terms or fictitious variables. A
novel theoretical framework is also established for the error analysis of high
order methods.


  We seek to derive the probability--expressed in terms of the Hilbert-Schmidt
(Euclidean or flat) metric--that a generic (nine-dimensional) real two-qubit
system is separable, by implementing the well-known Peres-Horodecki test on the
partial transposes (PTs) of the associated 4 x 4 density matrices. But the full
implementation of the test--requiring that the determinant of the PT be
nonnegative for separability to hold--appears to be, at least presently,
computationally intractable. So, we have previously implemented--using the
auxiliary concept of a diagonal-entry-parameterized separability function
(DESF)--the weaker implied test of nonnegativity of the six 2 x 2 principal
minors of the PT. This yielded an exact upper bound on the separability
probability of 1024/(135 Pi^2) = 0.76854. Here, we extend this line of work by
requiring that the four 3 x 3 principal minors of the PT be nonnegative, giving
us an improved/reduced upper bound of 22/35 = 0.628571. Numerical
simulations--as opposed to exact symbolic calculations--indicate, on the other
hand, that the true probability is certainly less than 1/2. Our combined
analyses lead us to suggest a possible form for the true DESF, yielding a
separability probability of 29/64 = 0.453125, while the best exact lower bound
established so far is (6928-2205 Pi)/2^(9/2) = 0.0348338.


  We study a class of nonlinear pricing models which involves the feedback
effect from the dynamic hedging strategies on the price of asset introduced by
Sircar and Papanicolaou. We are first to study the case of a nonlinear demand
function involved in the model. Using a Lie group analysis we investigate the
symmetry properties of these nonlinear diffusion equations. We provide the
optimal systems of subalgebras and the complete set of non-equivalent
reductions of studied PDEs to ODEs. In most cases we obtain families of exact
solutions or derive particular solutions to the equations.


  In dynamic malware analysis, programs are classified as malware or benign
based on their execution logs. We propose a concept of applying monotonic
classification models to the analysis process, to make the trained model's
predictions consistent over execution time and provably stable to the injection
of any noise or `benign-looking' activity into the program's behavior. The
predictions of such models change monotonically through the log in the sense
that the addition of new lines into the log may only increase the probability
of the file being found malicious, which make them suitable for real-time
classification on a user's machine. We evaluate monotonic neural network models
based on the work by Chistyakovet al. (2017) and demonstrate that they provide
stable and interpretable results.


  We give two new examples of non-hyperelliptic curves whose Ceresa cycles have
torsion images in the intermediate Jacobian. For one of them, the central value
of the $L$-function of the relevant motive is non-vanishing and the Ceresa
cycle is torsion in the Griffiths group, consistent with the conjectures of
Beilinson and Bloch. We speculate on a possible explanation for the existence
of these torsion Ceresa classes, based on some computations with cyclic Fermat
quotients.


  We prove existence results and lower bounds for the resonances of
Schr\"odinger operators associated to smooth, compactly support potentials on
hyperbolic space. The results are derived from a combination of heat and wave
trace expansions and asymptotics of the scattering phase.


  We describe the problem of Sweedler's duals for bialgebras as essentially
characterizing the domain of the transpose of the multiplication. This domain
is the set of what could be called ``representative linear forms'' which are
the elements of the algebraic dual which are also representative on the
multiplicative semigroup of the algebra. When the algebra is free, this notion
is indeed equivalent to that of rational functions of automata theory. For the
sake of applications, the range of coefficients has been considerably
broadened, i.e. extended to semirings, so that the results could be specialized
to the boolean and multiplicity cases. This requires some caution (use of
``positive formulas'', iteration replacing inversion, stable submodules
replacing finite-rank families for instance). For the theory and its
applications has been created a rational calculus which can, in return, be
applied to harness Sweedler's duals. A new theorem of rational closure and
application to Hopf algebras of use in Physics and Combinatorics is provided.
The concrete use of this ``calculus'' is eventually illustrated on an example.


  Quantum batteries (QBs) are energy storage and transfer microdevices that
open up new possibilities in energy technology. Here, we derive a
resonator-qutrits quantum battery (QB) model consisting of a multi-modes
resonator and $N$ superconducting transmon qutrits. We investigate the charging
and self-discharging performance of the QB and discuss the roles of quantum
coherence and quantum entanglement. The results show that environment noise is
not always detrimental for QB systems. The QB with efficient charging, stable
energy-storage and slow self-discharging processes can be realized by
considering the dephasing noise and manipulating the energy gap. We find that
the charing energy is positively related to coherence and entanglement while
the stable energy and the self-discharing energy are negatively related to
coherence. The phenomenon of the vanishing entanglement corresponds to the
dynamic decoupling behavior of the QB's steady states. Our results provide a
way to realize many-body QBs on superconducting circuits platform.


  We establish a general "affine representability" result in ${\mathbb
A}^1$-homotopy theory over a general base. We apply this result to obtain
representability results for vector bundles in ${\mathbb A}^1$-homotopy theory.
Our results simplify and significantly generalize F. Morel's ${\mathbb
A}^1$-representability theorem for vector bundles.


  Several recent observations suggest that gas-poor (dissipationless) mergers
of elliptical galaxies contribute significantly to the build-up of the massive
end of the red sequence. We perform a series of major merger simulations to
investigate the spatial and velocity structure of the remnants of such mergers.
Regardless of orbital energy or angular momentum, we find that the stellar
remnants lie on the fundamental plane defined by their progenitors, a result of
virial equilibrium with a small tilt due to an increasing central dark matter
fraction. However, the locations of merger remnants in the projections of the
fundamental plane -- the Faber-Jackson and R_e-M_* relations -- depend strongly
on the merger orbit, and the relations steepen significantly from the canonical
scalings (L sigma^4 and R_e M_*^0.6) for mergers on radial orbits. Our results
imply that the projections of the fundamental plane -- but not necessarily the
plane itself -- provide a powerful way of investigating the assembly history of
massive elliptical galaxies, including the brightest cluster galaxies at or
near the centers of galaxy clusters. We argue that most massive ellipticals are
formed by anisotropic merging and that their fundamental plane projections
should thus differ noticeably from those of lower mass ellipticals even though
they should lie on the same fundamental plane. Current observations are
consistent with this conclusion. The steepening in the L-sigma relation for
luminous ellipticals may also be reflected in a corresponding steepening in the
M_BH-sigma relation for massive black holes.


  We point out that time's arrow is naturally induced by quantum mechanical
evolution, whenever the systems have a very large number ${\cal N}$ of
non-degenerate states and a Hamiltonian bounded from below. When ${\cal N}$ is
finite, the arrow is imperfect, since evolution can resurrect past states. In
the limit ${\cal N} \rightarrow \infty$ the arrow is fixed by the "tooth of
time": the decay of excited states induced by {\it spontaneous emission} to the
ground state, mediated by interactions and a large number of decay products
which carry energy and information to infinity. This applies to individual
isolated atoms, and does not require a coupling to a separate large heath bath.


  In this paper, we introduce a new benchmark dataset for the challenging
writing in the air (WiTA) task -- an elaborate task bridging vision and NLP.
WiTA implements an intuitive and natural writing method with finger movement
for human-computer interaction (HCI). Our WiTA dataset will facilitate the
development of data-driven WiTA systems which thus far have displayed
unsatisfactory performance -- due to lack of dataset as well as traditional
statistical models they have adopted. Our dataset consists of five sub-datasets
in two languages (Korean and English) and amounts to 209,926 video instances
from 122 participants. We capture finger movement for WiTA with RGB cameras to
ensure wide accessibility and cost-efficiency. Next, we propose spatio-temporal
residual network architectures inspired by 3D ResNet. These models perform
unconstrained text recognition from finger movement, guarantee a real-time
operation by processing 435 and 697 decoding frames-per-second for Korean and
English, respectively, and will serve as an evaluation standard. Our dataset
and the source codes are available at https://github.com/Uehwan/WiTA.


  Utilizing the Fermi gas microscope, recently the MIT group has measured the
spin transport of the Fermi Hubbard model starting from a spin-density-wave
state, and the Princeton group has measured the charge transport of the Fermi
Hubbard model starting from a charge-density-wave state. Motivated by these two
experiments, we prove a theorem that shows under certain conditions, the spin
and charge transports can be equivalent to each other. The proof makes use of
the particle-hole transformation of the Fermi Hubbard model and a recently
discovered symmetry protected dynamical symmetry. Our results can be directly
verified in future cold atom experiment with the Fermi gas microscope.


  Information-theoretic Bayesian regret bounds of Russo and Van Roy capture the
dependence of regret on prior uncertainty. However, this dependence is through
entropy, which can become arbitrarily large as the number of actions increases.
We establish new bounds that depend instead on a notion of rate-distortion.
Among other things, this allows us to recover through information-theoretic
arguments a near-optimal bound for the linear bandit. We also offer a bound for
the logistic bandit that dramatically improves on the best previously
available, though this bound depends on an information-theoretic statistic that
we have only been able to quantify via computation.


  This paper is devoted to memory of late Professor V. G. Bagrov, who was my
first teacher in theoretical physics. About 45 years later, theoretical physics
has changed and me too. The subject of this paper relates some old ideas in
cosmology with some recent ideas, as is reflected in the title. The current
status of Starobinsky inflation is reviewed and compared to three main
conjectures in the Swampland program. It is argued that the Starobinsky
inflation model is not in conflict with those Swampland conjectures in their
basic versions.


  Attention-based methods and Connectionist Temporal Classification (CTC)
network have been promising research directions for end-to-end (E2E) Automatic
Speech Recognition (ASR). The joint CTC/Attention model has achieved great
success by utilizing both architectures during multi-task training and joint
decoding. In this work, we present a multi-stream framework based on joint
CTC/Attention E2E ASR with parallel streams represented by separate encoders
aiming to capture diverse information. On top of the regular attention
networks, the Hierarchical Attention Network (HAN) is introduced to steer the
decoder toward the most informative encoders. A separate CTC network is
assigned to each stream to force monotonic alignments. Two representative
framework have been proposed and discussed, which are Multi-Encoder
Multi-Resolution (MEM-Res) framework and Multi-Encoder Multi-Array (MEM-Array)
framework, respectively. In MEM-Res framework, two heterogeneous encoders with
different architectures, temporal resolutions and separate CTC networks work in
parallel to extract complimentary information from same acoustics. Experiments
are conducted on Wall Street Journal (WSJ) and CHiME-4, resulting in relative
Word Error Rate (WER) reduction of 18.0-32.1% and the best WER of 3.6% in the
WSJ eval92 test set. The MEM-Array framework aims at improving the far-field
ASR robustness using multiple microphone arrays which are activated by separate
encoders. Compared with the best single-array results, the proposed framework
has achieved relative WER reduction of 3.7% and 9.7% in AMI and DIRHA
multi-array corpora, respectively, which also outperforms conventional fusion
strategies.


  We study estimation of causal effects in staggered rollout designs, i.e.
settings where there is staggered treatment adoption and the timing of
treatment is as-good-as randomly assigned. We derive the most efficient
estimator in a class of estimators that nests several popular generalized
difference-in-differences methods. A feasible plug-in version of the efficient
estimator is asymptotically unbiased with efficiency (weakly) dominating that
of existing approaches. We provide both $t$-based and permutation-test-based
methods for inference. In an application to a training program for police
officers, confidence intervals for the proposed estimator are as much as eight
times shorter than for existing approaches.


  An attempt is made to resolve the controversy related to the low temperature
phase (ground state) of the low-doped ferromagnetic (FM)- insulator(I)
manganite through bulk magnetic measurements on La${_{0.9}}$Sr$_{0.1}$MnO${_3}$
sample. It is shown that the FM phase, formed out of well defined transition in
the low-doped system, becomes inhomogeneous with decrease in temperature. This
inhomogeniety is considered to be an outcome of the formation of orbital domain
state of e$_g$-electrons having hole rich (metallic) walls separating the hole
deficient (insulating) regions. The resulting complexity brings in
metastability and glassy behaviour within the FM phase at low temperature,
however, with no resemblance to spin glass, cluster glass or reentrant phases.
It shows ageing effect without memory but magnetic relaxation shows signatures
of inter-cluster interaction. The energy landscape picture of this glassy phase
is described in terms of hierarchical model. Further, it is shown that this
inhomogeneity disappear in La${_{0.9}}$Sr$_{0.1}$MnO$_{3.08}$ where, the
orbital domain state is destroyed by self doping resulting in reduction of
Mn$^{3+}$ and hence e$_g$-electrons. The ferromagnetic phase of the
non-stoichiometric sample, does not show glassy behaviour. It neither follows
'hierarchical model' nor 'droplet model' generally used to explain glassy or
inhomogeneous systems. Its magnetic response can be explained simply from the
domain wall dynamics of otherwise homogeneous ferromagnet.


  The recursive method for computing the generalized LM-inverse of a constant
rectangular matrix augmented by a column vector is proposed in Udwadia and
Phohomsiri (2007) [16] and [17]. The corresponding algorithm for the sequential
determination of the generalized LM-inverse is established in the present
paper. We prove that the introduced algorithm for computing the generalized
LM-inverse and the algorithm for the computation of the weighted Moore-Penrose
inverse developed by Wang and Chen (1986) in [23] are equivalent algorithms.
Both of the algorithms are implemented in the present paper using the package
MATHEMATICA. Several rational test matrices and randomly generated constant
matrices are tested and the CPU time is compared and discussed.


  The cutoff scheme dependence in the several formulations of the Exact
Renormalization Group (ERG) is investigated. It is shown that the cutoff scheme
dependence of the Wilsonian effective action is regarded as a certain
coordinate transformation on the theory space. From this observation the
Wilsonian effective actions are found to suffer from strong dependence on the
schemes even in the infra-red asymptotic region for massive theories. However
there is no such scheme dependence in the one particle irreducible parts of
them, which is called the effective average actions. We also derive the
explicit form of the Polchinski RG equation in the sharp cutoff limit. Finally
this equation is shown to be identical with the Wegner-Houghton RG equation.


  The scalar mesons in the 1 GeV region constitute the Higgs sector of the
strong interactions. They are responsible for the masses of all light flavour
hadrons. However, the composition of these scalar states is far from clear,
despite decades of experimental effort. The two photon couplings of the
$f_{0}$'s are a guide to their structure. Two photon results from Mark II,
Crystal Ball and CELLO prompt a new Amplitude Analysis of
$\gamma\gamma\to\pi^+\pi^-$, $\pi^0\pi^0$ cross-sections. Despite their
currently limited angular coverage and lack of polarized photons, we use a
methodology that provides the nearest one can presently achieve to a
model-independent partial wave separation. We find two distinct classes of
solutions. Both have very similar two photon couplings for the $f_0(980)$ and
$f_0(400-1200)$. Hopefully these definitive results will be a spur to dynamical
calculations that will bring us a better understanding of these important
states.


  RX J1211+2242 is an optically faint (B = 19.2 mag) but X-ray bright (2 - 10
keV flux fx = 5e-12 erg/cm**2/sec) AGN, which has been shown to be a BL Lac
object at redshift z = 0.455. The ROSAT X-ray, Calar Alto optical, and NVSS
radio data suggest that the peak of the synchrotron emission of this object is
at energies as high as several keV. BeppoSAX observations have been carried out
simultaneously with optical observations in order to extend the coverage to
higher energies. The new data indeed indicate a turn-over in the 2 - 10 keV
energy region. We propose that RX J1211+2242 is the counterpart of the
unidentified EGRET source 3EG J1212+2304, making it a gamma-ray emitter with
properties similar to, for example, Markarian 501 in its bright state, though
being at a much larger distance.


  We study a nonlinear evolutionary partial differential equation that can be
viewed as a generalization of the heat equation where the temperature gradient
is a~priori bounded but the heat flux provides merely \mbox{$L^1$-coercivity}.
Applying higher differentiability techniques in space and time, choosing a
special weighted norm (equivalent to the Euclidean norm in $\mathbb{R}^d$),
incorporating finer properties of integrable functions and using the concept of
renormalized solution, we prove long-time and large-data existence and
uniqueness of weak solution, with an $L^1$-integrable flux, to an initial
spatially-periodic problem for all values of a positive model parameter. If
this parameter is smaller than $2/(d+1)$, where $d$ denotes the spatial
dimension, we obtain higher integrability of the flux. As the developed
approach is not restricted to a scalar equation, we also present an analogous
result for nonlinear parabolic systems in which the nonlinearity, being the
gradient of a strictly convex function, gives an a-priori $L^\infty$-bound on
the gradient of the unknown solution.


  These notes briefly discuss Fourier transforms of finite measures and
extensions of Fourier integrals to points in complex domains.


  We present optical and near-infrared photometry of GRB~140606B ($z=0.384$),
and optical photometry and spectroscopy of its associated supernova (SN). The
results of our modelling indicate that the bolometric properties of the SN
($M_{\rm Ni} = 0.4\pm0.2$~M$_{\odot}$, $M_{\rm ej} = 5\pm2$~M$_{\odot}$, and
$E_{\rm K} = 2\pm1 \times 10^{52}$ erg) are fully consistent with the
statistical averages determined for other GRB-SNe. However, in terms of its
$\gamma$-ray emission, GRB~140606B is an outlier of the Amati relation, and
occupies the same region as low-luminosity ($ll$) and short GRBs. The
$\gamma$-ray emission in $ll$GRBs is thought to arise in some or all events
from a shock-breakout (SBO), rather than from a jet. The measured peak photon
energy ($E_{\rm p}\approx800$ keV) is close to that expected for $\gamma$-rays
created by a SBO ($\gtrsim1$ MeV). Moreover, based on its position in the
$M_{V,\rm p}$--$L_{\rm iso,\gamma}$~plane and the $E_{\rm
K}$--$\Gamma\beta$~plane, GRB~140606B has properties similar to both SBO-GRBs
and jetted-GRBs. Additionally, we searched for correlations between the
isotropic $\gamma$-ray emission and the bolometric properties of a sample of
GRB-SNe, finding that no statistically significant correlation is present. The
average kinetic energy of the sample is $\bar{E}_{\rm K} = 2.1\times10^{52}$
erg. All of the GRB-SNe in our sample, with the exception of SN 2006aj, are
within this range, which has implications for the total energy budget available
to power both the relativistic and non-relativistic components in a GRB-SN
event.


  We consider a recently introduced geometrically nonlinear elastic Cosserat
shell model incorporating effects up to order $O(h^5)$ in the shell thickness
$h$. We develop the corresponding geometrically nonlinear constrained Cosserat
shell model, we show the existence of minimizers for the $O(h^5)$ and $O(h^3)$
case and we draw some connections to existing models and classical shell strain
measures. Notably, the role of the appearing new bending tensor is highlighted
and investigated with respect to an invariance condition of Acharya [Int. J.
Solids and Struct., 2000] which will be further strengthened.


  Background: Nuclear energy-density functional (EDF) approach has been widely
used to describe nuclear-matter equations of state (EoS) and properties of
finite nuclei. Recent advancements in neutron-star (NS) observations have put
constraints on the nuclear EoS. The Korea-IBS-Daegu-SKKU (KIDS) functional has
been then developed to satisfy the NS observations and applied to homogeneous
nuclear matter and spherical nuclei. Purpose: We examine the performance of the
KIDS functional by calculating the masses and charge radii of even-even nuclei
towards the drip lines. Method: The Kohn-Sham-Bogoliubov equation is solved by
taking into account the axial deformation. Results: The root-mean-square
deviation of the binding energy and the charge radius for the KIDS functional
is 4.5--5.1 MeV and 0.03--0.04 fm, which is comparable to that for existing
EDFs. The emergence and development of nuclear deformation in open-shell nuclei
are well described. The location of the neutron drip line is according to the
nuclear-matter parameter characterizing the low-mass NS. Conclusions: The
NS-observation-inspired EDF offers a reasonable reproduction of the structures
of finite nuclei. A future global optimization including more nuclear data will
give better accuracy and high predictive power of neutron-rich nuclei.


  We present a systematic study of entire symmetric solutions $u:R^n\rightarrow
R^m$ of the vector Allen-Cahn equation $\Delta u-W_u(u)=0, x \in R^n$, where
$W:R^m\rightarrow R$ is smooth, symmetric, nonnegative with a finite number of
zeros and $W_u=(\frac{\partial W}{\partial u_1},\ldots,\frac{\partial
W}{\partial u_m})^\top$. We introduce a general notion of equivariance with
respect to a homomorphism $f:G\rightarrow\Gamma$ ($G,\Gamma$ reflection groups)
and prove two abstract results, concerning the cases of $G$ finite and $G$
discrete, for the existence of equivariant solutions. Our approach is
variational and based on a mapping property of the parabolic vector Allen-Cahn
equation and on a pointwise estimate for vector minimizers.


  We consider conditioned Galton-Watson trees and show asymptotic normality of
additive functionals that are defined by toll functions that are not too large.
This includes, as a special case, asymptotic normality of the number of fringe
subtrees isomorphic to any given tree, and joint asymptotic normality for
several such subtree counts. Another example is the number of protected nodes.
The offspring distribution defining the random tree is assumed to have
expectation 1 and finite variance; no further moment condition is assumed.


  Transitions to measure synchronization in two coupled $\phi ^{4}$ lattices
are investigated based on numerical simulations. The relationship between
measure synchronization (MS), phase locking and system's total energy is
studied both for periodic and chaotic states. Two different scalings are
discovered during the process to MS according to phase locking. Random walk
like phase synchronization in chaotic measure synchronization is found, and
phase locking interrupted by phase slips irregularly is also investigated.
Meanwhile, related analysis is qualitative given to explain this phenomenon.


  We report a significantly tighter trend between gaseous N/O and $M_*/R_e$ (a
proxy for gravitational potential) than has previously been reported between
gaseous metallicity and $M_*/R_e$, for star-forming galaxies in the MaNGA
survey. We argue this result to be a consequence of deeper potential wells
conferring greater resistance to metal outflows while also being associated
with earlier star-formation histories, combined with N/O being comparatively
unaffected by metal-poor inflows. The potential-N/O relation thus appears to be
both more resistant to short-timescale baryonic processes and also more
reflective of a galaxy's chemical evolution state, when compared to
previously-considered relations.


  A celebrated theorem of M. Heins says that up to post-composition with a
M\"obius transformation, a finite Blaschke product is uniquely determined by
its critical points. K. Dyakonov suggested that it may interesting to extend
this result to infinite degree, however, one needs to be careful since inner
functions may have identical critical sets.
  In this work, we try parametrizing inner functions by 1-generated invariant
subspaces of the weighted Bergman space $A^2_1$. Our technique is based on the
Liouville correspondence which provides a bridge between complex analysis and
non-linear elliptic PDE.


  Graph models have long been used in lieu of real data which can be expensive
and hard to come by. A common class of models constructs a matrix of
probabilities, and samples an adjacency matrix by flipping a weighted coin for
each entry. Examples include the Erd\H{o}s-R\'{e}nyi model, Chung-Lu model, and
the Kronecker model. Here we present the HyperKron Graph model: an extension of
the Kronecker Model, but with a distribution over hyperedges. We prove that we
can efficiently generate graphs from this model in order proportional to the
number of edges times a small log-factor, and find that in practice the runtime
is linear with respect to the number of edges. We illustrate a number of useful
features of the HyperKron model including non-trivial clustering and highly
skewed degree distributions. Finally, we fit the HyperKron model to real-world
networks, and demonstrate the model's flexibility with a complex application of
the HyperKron model to networks with coherent feed-forward loops.


  New formulas for approximation of zeta-constants were derived on the basis of
a number-theoretic approach constructed for the irrationality proof of certain
classical constants. Using these formulas it's possible to approximate certain
zeta-constants and their combinations by rational fractions and construct a
method for their evaluation.


  Coordination-related, two-dimensional (2D) structural phase transitions are a
fascinating and novel facet of two-dimensional materials with structural
degeneracies. Nevertheless, a unified theoretical account of these transitions
remains absent, and the following points are established through {\em
ab-initio} molecular dynamics and 2D discrete clock models here: Group-IV
monochalcogenide (GeSe, SnSe, SnTe, ...) monolayers have four degenerate
structural ground states, and a 2D phase transition from a three-fold
coordinated onto a five-fold coordinated structure takes place at finite
temperature. On unstrained samples, the 2D phase transition requires lattice
parameters to freely evolve. A fundamental energy scale permits understanding
this transition. The transition temperature $T_c$ and the orientation of the
in-plane intrinsic electric dipole can be controlled by moderate uniaxial
tensile strain, and a modified discrete clock model describes the transition on
strained samples. These results establish a general underlying theoretical
background to understand structural phase transitions in 2D materials and their
effects on material properties.


  The effective action describing the long range fluctuations in the high
temperature phase of the electroweak standard theory is a strongly coupled
SU(2)-Higgs-model in three dimensions. We outline in detail a model in which
the spatial correlation scales in this phase are calculated as inverse
relativistic bound state masses. Selection rules for these states are derived.
The correlation masses are calculated by evaluating the bound state Green's
function. The scalar-scalar-potential and its influence on the masses is
investigated. The predictions for the correlation masses agree very well with
the lattice data available now.


  The distribution of monomers along a linear polymer grafted on a hard wall is
modelled by determining the probability distribution of occupied vertices of
Dyck and ballot path models of adsorbing linear polymers. For example, the
probability that a Dyck path passes through the lattice site with coordinates
$(\lfloor \epsilon n \rfloor,\lfloor \delta \sqrt{n}\rfloor)$ in the square
lattice, for $0 < \epsilon < 1$ and $\delta\geq 0$, is determined
asymptotically as $n\to\infty$ and this uncovers the probability density of
vertices along Dyck paths in the limit as the length of the path $n$ approaches
infinity: $$\hbox{P}_r (\epsilon,\delta) =
\frac{4\delta^2}{\sqrt{\pi\,\epsilon^3(1-\epsilon)^3}} \,
e^{-\delta^2/\epsilon(1-\epsilon)}\ .$$ The properties of a polymer coating of
a hard wall and the density or distribution of monomers in the coating is
relevant in applications such as the stabilisation of a colloid dispersion by a
polymer or in a drug delivery system such as a drug-eluding stent covered by a
grafted polymer.


  In this demonstration, we will present the world's first molecular
multiple-input multiple-output (MIMO) communication link to deliver two data
streams in a spatial domain. We show that chemical signals such as
concentration gradients could be used in MIMO fashion to transfer sequential
data. Until now it was unclear whether MIMO techniques, which are used
extensively in modern radio communication, could be applied to molecular
communication. In the demonstration, using our devised MIMO apparatus and
carefully designed detection algorithm, we will show that we can achieve about
1.7 times higher data rate than single input single output (SISO) molecular
communication systems.


  We measure the thermoelectric response of Corbino structures in the quantum
Hall effect regime and compare it with a theoretical analysis. The measured
thermoelectric voltages are qualitatively and quantitatively simulated based
upon the independent measurement of the conductivity indicating that they
originate predominantly from the electron diffusion. Electron-phonon
interaction does not lead to a phonon-drag contribution in contrast to earlier
Hall-bar experiments. This implies a description of the Onsager coefficients on
the basis of a single transmission function, from which both thermovoltage and
conductivity can be predicted with a single fitting parameter. It furthermore
let us predict a figure of merit for the efficiency of thermoelectric cooling
which becomes very large for partially filled Landau levels (LL) and high
magnetic fieldse of merit can be estimated which becomes very large for
partially filled Landau levels and high magnetic fields.


  To investigate the evolution of syntax, we need to ascertain the evolutionary
r\^ole of syntax and, before that, the very nature of syntax. Here, we will
assume that syntax is computing. And then, since we are computationally Turing
complete, we meet an evolutionary anomaly, the anomaly of sytax: we are
syntactically too competent for syntax. Assuming that problem solving is
computing, and realizing that the evolutionary advantage of Turing completeness
is full problem solving and not syntactic proficiency, we explain the anomaly
of syntax by postulating that syntax and problem solving co-evolved in humans
towards Turing completeness. Examining the requirements that full problem
solving impose on language, we find firstly that semantics is not sufficient
and that syntax is necessary to represent problems. Our final conclusion is
that full problem solving requires a functional semantics on an infinite
tree-structured syntax. Besides these results, the introduction of Turing
completeness and problem solving to explain the evolution of syntax should help
us to fit the evolution of language within the evolution of cognition, giving
us some new clues to understand the elusive relation between language and
thinking.


  The Axelrod model is a spatial stochastic model for the dynamics of cultures
which includes two important social factors: social influence, the tendency of
individuals to become more similar when they interact, and homophily, the
tendency of individuals to interact more frequently with individuals who are
more similar. Each vertex of the interaction network is characterized by its
culture, a vector of $F$ cultural features that can each assumes $q$ different
states. Pairs of neighbors interact at a rate proportional to the number of
cultural features they have in common, which results in the interacting pair
having one more cultural feature in common. In this article, we continue the
analysis of the Axelrod model initiated by the first author by proving that the
one-dimensional system fixates when $F\leq cq$ where the slope satisfies the
equation $e^{-c}=c$. In addition, we show that the two-feature model with at
least three states fixates. This last result is sharp since it is known from
previous works that the one-dimensional two-feature two-state Axelrod model
clusters.


  In the allocation of indivisible goods, a prominent fairness notion is
envy-freeness up to one good (EF1). We initiate the study of reachability
problems in fair division by investigating the problem of whether one EF1
allocation can be reached from another EF1 allocation via a sequence of
exchanges such that every intermediate allocation is also EF1. We show that two
EF1 allocations may not be reachable from each other even in the case of two
agents, and deciding their reachability is PSPACE-complete in general. On the
other hand, we prove that reachability is guaranteed for two agents with
identical or binary utilities as well as for any number of agents with
identical binary utilities. We also examine the complexity of deciding whether
there is an EF1 exchange sequence that is optimal in the number of exchanges
required.


  In this article, we consider products of random walks on finite groups with
moderate growth and discuss their cutoffs in the total variation. Based on
several comparison techniques, we are able to identify the total variation
cutoff of discrete time lazy random walks with the Hellinger distance cutoff of
continuous time random walks. Along with the cutoff criterion for Laplace
transforms, we derive a series of equivalent conditions on the existence of
cutoffs, including the existence of pre-cutoffs, Peres' product condition and a
formula generated by the graph diameters. For illustration, we consider
products of Heisenberg groups and randomized products of finite cycles.


  The mathematical model underlying the Neural Engineering Framework (NEF)
expresses neuronal input as a linear combination of synaptic currents. However,
in biology, synapses are not perfect current sources and are thus nonlinear.
Detailed synapse models are based on channel conductances instead of currents,
which require independent handling of excitatory and inhibitory synapses. This,
in particular, significantly affects the influence of inhibitory signals on the
neuronal dynamics. In this technical report we first summarize the relevant
portions of the NEF and conductance-based synapse models. We then discuss a
na\"ive translation between populations of LIF neurons with current- and
conductance-based synapses based on an estimation of an average membrane
potential. Experiments show that this simple approach works relatively well for
feed-forward communication channels, yet performance degrades for NEF networks
describing more complex dynamics, such as integration.


  In this paper, we establish an equivariant version of Dai-Zhang's Toeplitz
index theorem for compact odd-dimensional spin manifolds with even-dimensional
boundary.


  The mechanical properties of tissues play an essential role for all tissue
properties such as cell division, and differentiation or morphogenesis. Here,
we study theoretically the rheology of 2-dimensional epithelial tissues
described by a discrete vertex-like model, using an analytical coarsegrained
continuum formulation. We show that epithelial tissues are most often
shear-thinning under constant shear rate, and in certain circumstances cross
over from shear thickening at low shear rates to shear thinning at high shear
rates. We give an analytical expression of the tissue response in an
oscillating strain experiment in the linear regime, and calculate it
numerically in the non-linear regime. When the tissue is supported by an
oscillating substrate, it reorients depending on frequency and substrate's
Poisson's ratio. Reorientation could be gradual or abrupt, depending on tissue
and substrate parameters, and the configuration phase space exhibits a
tricritical point.


  This is the second part of a three-part overview, in which we derive the
category-theoretic backbone of quantum theory from a process ontology, treating
quantum theory as a theory of systems, processes and their interactions. In
this part we focus on classical-quantum interaction.
  Classical and quantum systems are treated as distinct types, of which the
respective behavioural properties are specified in terms of processes and their
compositions. In particular, classicality is witnessed by 'spiders' which fuse
together whenever they connect. We define mixedness and show that pure
processes are extremal in the space of all processes, and we define
entanglement and show that quantum theory indeed exhibits entanglement. We
discuss the classification of tripartite qubit entanglement and show that both
the GHZ-state and the W-state come from spider-like families of processes,
which differ only in how they behave when they are connected by two or more
wires. We define measurements and provide fully-comprehensive descriptions of
several quantum protocols involving classical data flow. Finally, we give a
notion of 'genuine quantumness', from which special processes called 'phase
spiders' arise, and get a first glimpse of quantum non-locality.


  One considers the quantum dynamics of a charged spin-1/2 particle in an
extended external eletromagnetic field that arises from the reduction of a
5-dimensional Abelian gauge theory. The non-relativistic regime of the reduced
4D-dynamics is worked out and one identifies the system as a sector of an
N=2-supersymmetric quantum-mechanical dynamics. The full supersymmetric model
is studied and one checks the algebra of the fermionic charges; the conclusion
is that no central charge drops out. The possible r\^ole of the extra external
fields, a scalar and a magnetic-like field, is discussed.


  We prove that an open set $D$ in $\C^n$ is pseudoconvex if and only if for
any $z\in D$ the largest balanced domain centered at $z$ and contained in $D$
is pseudoconvex, and consider analogues of that characterization in the
linearly convex case.


  We present the results from the OGLE-II survey (1996-2000) towards the Large
Magellanic Cloud (LMC), which has the aim of detecting the microlensing
phenomena caused by dark matter compact objects in the Galactic Halo (Machos).
  We use high resolution HST images of the OGLE fields and derive the
correction for the number of monitored stars in each field. This also yield
blending distributions which we use in 'catalogue level' Monte Carlo
simulations of the microlensing events in order to calculate the detection
efficiency of the events.
  We detect two candidates for microlensing events in the All Stars Sample,
which translates into an optical depth of 0.43+-0.33x 10e-7. If both events
were due to Macho the fraction of mass of compact dark matter objects in the
Galactic halo would be 8+-6 per cent. This optical depth, however, along with
the characteristics of the events, seems to be consistent with the self-lensing
scenario, i.e., self-lensing alone is sufficient to explain the observed
microlensing signal. Our results indicate a non-detection of Machos lensing
towards the LMC with an upper limit on their abundance in the Galactic halo of
19 per cent for M=0.4 Msun and 10 per cent for masses between 0.01 and 0.2
Msun.


  The Kundt conjecture states that a Lorentzian manifold of arbitrary dimension
which is not characterized by its scalar polynomial curvature invariants (SPIs)
allows for a non-twisting, non-shearing and non-expanding (in short, Kundt)
null congruence of geodesics. The conjecture has been proven for dimensions 3
and 4. A necessary condition for a spacetime not to be characterized by SPIs is
that all covariant derivatives of the Riemann tensor are of aligned type II or
more special in the null alignment classification. In arbitrary dimensions, we
prove that this property indeed requires the presence of a Kundt null
congruence when a certain genericity condition holds, or when the trac-free
Ricci orWeyl tensor is of genuine type III or N, thus confirming the validity
of the Kundt conjecture in these cases. We also strenghten the results for
dimensions 3 and 4 by removing regularity assumptions and showing that only the
third covariant derivative is needed to obtain the results. A key tool in our
proofs is a new bilinear map acting on tensors of related boost orders relative
to a null direction.


  We show how a charge current through a single antiferromagnetic layer can
excite and control self-oscillations. Sustained oscillations with tunable
amplitudes and frequencies are possible in a variety of geometries using
certain classes of non-centrosymmetric materials that exhibit finite
dissipative spin-orbit torque. We compute the steady-state phase diagram as a
function of the current and spin-orbit torque magnitude. The anisotropic
magnetoresistance causes the conversion of the resulting AF oscillations to a
terahertz AC output voltage. These findings provide an attractive and novel
route to design terahertz antiferromagnetic spin-orbit torque oscillators in
simple single-layer structures.


  This article presents an agent architecture for controlling an autonomous
agent in stochastic environments. The architecture combines the partially
observable Markov decision process (POMDP) model with the
belief-desire-intention (BDI) framework. The Hybrid POMDP-BDI agent
architecture takes the best features from the two approaches, that is, the
online generation of reward-maximizing courses of action from POMDP theory, and
sophisticated multiple goal management from BDI theory. We introduce the
advances made since the introduction of the basic architecture, including (i)
the ability to pursue multiple goals simultaneously and (ii) a plan library for
storing pre-written plans and for storing recently generated plans for future
reuse. A version of the architecture without the plan library is implemented
and is evaluated using simulations. The results of the simulation experiments
indicate that the approach is feasible.


  We identify and quantify systematic effects not accounted for in two previous
measurements of the alpha-alpha relative-energy distribution in the beta decay
of 8B, which can explain the apparent disagreement with respect to two newer
measurements. This settles a current dispute concerning the shape of the 8B
neutrino spectrum of importance to solar-neutrino studies.


  Traffic flow forecasting is a highly challenging task due to the dynamic
spatial-temporal road conditions. Graph neural networks (GNN) has been widely
applied in this task. However, most of these GNNs ignore the effects of
time-varying road conditions due to the fixed range of the convolution
receptive field. In this paper, we propose a novel Adaptive Graph Convolution
Networks (AGC-net) to address this issue in GNN. The AGC-net is constructed by
the Adaptive Graph Convolution (AGC) based on a novel context attention
mechanism, which consists of a set of graph wavelets with various learnable
scales. The AGC transforms the spatial graph representations into
time-sensitive features considering the temporal context. Moreover, a shifted
graph convolution kernel is designed to enhance the AGC, which attempts to
correct the deviations caused by inaccurate topology. Experimental results on
two public traffic datasets demonstrate the effectiveness of the
AGC-net\footnote{Code is available at: https://github.com/zhengdaoli/AGC-net}
which outperforms other baseline models significantly.


  We discuss some statistical results on the evolution of magnetic CP stars in
the framework of the supposition about their binary nature.


  We give a quantum version of the Jarzynski relation between the distribution
of work done over a certain time-interval on a system and the difference of
equilibrium free energies. The main new ingredient is the identification of
work depending on the quantum history of the system and the proper definition
of various quantum ensembles over which the averages should be made. We also
discuss a number of different regimes that have been considered by other
authors and which are unified in the present set-up. In all cases, and quantum
or classical, it is a general relation between heat and time-reversal that
makes the Jarzynski relation so universally valid.


  Observations of quantum turbulence in pure superfluid 4He in a rotating
container are reported. New techniques of large-scale forcing (rotational
oscillations of the cubic container) and detecting (monitoring ion transport
along the axis of rotation) turbulence were implemented. Near the axial walls,
with increasing forcing the vortex tangle grows without an observable
threshold. This tangle gradually develops into bulk turbulence at a
characteristic amplitude of forcing that depends on forcing frequency and
rotation rate. At higher amplitudes, the total vortex line length increases
rapidly. Resonances of inertial waves are observed in both laminar and
turbulent bulk states. On such resonances, the turbulence appears at smaller
amplitudes of forcing.


  The difference between the strange and antistrange quark distributions,
$\delta s(x)=s(x)-\sbar(x)$, and the combination of light quark sea and strange
quark sea, $\Delta (x)=\dbar(x)+\ubar(x)-s(x)-\sbar(x)$, are originated from
non-perturbative processes, and can be calculated using non-perturbative models
of the nucleon. We report calculations of $\delta s(x)$ and $\Delta(x)$ using
the meson cloud model. Combining our calculations of $\Delta(x)$ with
relatively well known light antiquark distributions obtained from global
analysis of available experimental data, we estimate the total strange sea
distributions of the nucleon.


  This work is dedicated to a new completely algebraic approach to Arakelov
geometry, which doesn't require the variety under consideration to be
generically smooth or projective. In order to construct such an approach we
develop a theory of generalized rings and schemes, which include classical
rings and schemes together with "exotic" objects such as F_1 ("field with one
element"), Z_\infty ("real integers"), T (tropical numbers) etc., thus
providing a systematic way of studying such objects.
  This theory of generalized rings and schemes is developed up to construction
of algebraic K-theory, intersection theory and Chern classes. Then existence of
Arakelov models of algebraic varieties over Q is shown, and our general results
are applied to such models.


  This work reports the first observation of azimuthal asymmetries around the
thrust axis in $e^+e^-$ annihilation of pairs of back-to-back charged pions in
one hemisphere, and $\pi^0$ and $\eta$ mesons in the opposite hemisphere. These
results are complemented by a new analysis of pairs of back-to-back charged
pions. The $\pi^0$ and $\eta$ asymmetries rise with the relative momentum $z$
of the detected hadrons as well as with the transverse momentum with respect to
the thrust axis. These asymmetries are sensitive to the Collins fragmentation
function $H_1^{\perp}$ and provide complementary information to previous
measurements with charged pions and kaons in the final state. In particular,
the $\eta$ final states will provide additional information on the flavor
structure of $H_1^{\perp}$. This is the first measurement of the explicit
transverse-momentum dependence of the Collins fragmentation function from Belle
data. It uses a dataset of 980.4~fb$^{-1}$ collected by the Belle experiment at
or near a center-of-mass energy of 10.58 GeV.


  The conventional slow-roll approximation is broken in the so-called "ultra
slow-roll" models of inflation, for which the inflaton potential is exactly (or
extremely) flat. The interesting nature of (canonical) ultra slow-roll
inflation is that the curvature perturbation grows on superhorizon scales, but
has a scale-invariant power spectrum. We study the ultra slow-roll inflationary
dynamics in the presence of non-canonical kinetic terms of the scalar field,
namely ultra slow-roll G-inflation. We compute the evolution of the curvature
perturbation and show that the primordial power spectrum follows a broken power
law with an oscillation feature. It is demonstrated that this could explain the
lack of large-scale power in the cosmic microwave background temperature
anisotropies. We also point out that the violation of the null energy condition
is prohibited in ultra slow-roll G-inflation and hence a blue tensor tilt is
impossible as long as inflation is driven by the potential. This statement is,
however, not true if the energy density is dominated by the kinetic energy of
the scalar field.


  For a Banach left module action, we will extend some propositions from Lau
and $\ddot{U}$lger and others into general situations and we establish the
relationships between topological centers of the left module action with the
multiplier and factorization properties of left module actions. We have some
applications in the dual groups.


  We study a class of elliptic operators $A$ with unbounded coefficients
defined in $I\times\CR^d$ for some unbounded interval $I\subset\CR$. We prove
that, for any $s\in I$, the Cauchy problem $u(s,\cdot)=f\in C_b(\CR^d)$ for the
parabolic equation $D_tu=Au$ admits a unique bounded classical solution $u$.
This allows to associate an evolution family $\{G(t,s)\}$ with $A$, in a
natural way. We study the main properties of this evolution family and prove
gradient estimates for the function $G(t,s)f$. Under suitable assumptions, we
show that there exists an evolution system of measures for $\{G(t,s)\}$ and we
study the first properties of the extension of $G(t,s)$ to the $L^p$-spaces
with respect to such measures.


  We consider the problem of causal discovery (structure learning) from
heterogeneous observational data. Most existing methods assume a homogeneous
sampling scheme, which leads to misleading conclusions when violated in many
applications. To this end, we propose a novel approach that exploits data
heterogeneity to infer possibly cyclic causal structures from causally
insufficient systems. The core idea is to model the direct causal effects as
functions of exogenous covariates that properly explain data heterogeneity. We
investigate structure identifiability properties of the proposed model.
Structure learning is carried out in a fully Bayesian fashion, which provides
natural uncertainty quantification. We demonstrate its utility through
extensive simulations and a real-world application.


  In one of his papers, using arguments about l-adic representations, Taniyama
expresses the zeta function of an abelian variety over a number field as an
infinite product of modified Artin L-functions. The latter can be further
decomposed as products of modified Dedekind zeta functions. After recalling
Taniyama's work, we give a simple geometric proof of the resulting product
formula for abelian and more general group schemes.


  We study the transport properties of an impurity in a sheared granular gas,
in the framework of the Boltzmann equation for inelastic Maxwell models. We
investigate here the impact of a nonequilibrium phase transition found in such
systems, where the tracer species carries a finite fraction of the total
kinetic energy (ordered phase). To this end, the diffusion coefficients are
first obtained for a granular binary mixture in spatially inhomogeneous states
close to the simple shear flow. In this situation, the set of coupled Boltzmann
equations are solved by means of a Chapman-Enskog-like expansion around the
(local) shear flow distributions for each species, thereby retaining all the
hydrodynamic orders in the shear rate $a$. Due to the anisotropy induced by the
shear flow, three tensorial quantities $D_{ij}$, $D_{p,ij}$, and $D_{T,ij}$ are
required to describe the mass transport process instead of the conventional
scalar coefficients. These tensors are given in terms of the solutions of a set
of coupled algebraic equations, which can be \emph{exactly} solved as functions
of the shear rate $a$, the coefficients of restitution $\alpha_{sr}$ and the
parameters of the mixture (masses and composition). Once the forms of $D_{ij}$,
$D_{p,ij}$, and $D_{T,ij}$ are obtained for arbitrary mole fraction
$x_1=n_1/(n_1+n_2)$ (where $n_r$ is the number density of species $r$), the
tracer limit ($x_1\to 0$) is carefully considered for the above three diffusion
tensors. Explicit forms for these coefficients are derived showing that their
shear rate dependence is significantly affected by the order-disorder
transition.


  While studying the motion of a heavy symmetric top, in general, constants of
motion are used. Some students may want to understand the motion in terms of
torque, which can lie on their routine based on the usage of Newton's second
law. However, this is not easy, and examples of this work will illustrate this
situation.
  In this work, first, we will show the equivalence of torque-angular momentum
relation and Euler equations for a heavy symmetric top which give the
description of the motion in terms of torque. Then, we will study some simple
motions of a heavy symmetric top in terms of torque, angular momentum, angular
velocities and accelerations, which can help students in understanding rigid
body rotations and the necessity of considering the motion of a heavy symmetric
top in terms of constants. We will also study Perry's historical observational
principle on the relation between precession and the rise of the top.


  It has been shown in earlier works that for Q=0 and L a multiple of N, the
ground state sector eigenspace of the superintegrable tau_2(t_q) model is
highly degenerate and is generated by a quantum loop algebra L(sl_2).
Furthermore, this loop algebra can be decomposed into r=(N-1)L/N simple sl_2
algebras. For Q not equal 0, we shall show here that the corresponding
eigenspace of tau_2(t_q) is still highly degenerate, but splits into two
spaces, each containing 2^{r-1} independent eigenvectors. The generators for
the sl_2 subalgebras, and also for the quantum loop subalgebra, are given
generalizing those in the Q=0 case. However, the Serre relations for the
generators of the loop subalgebra are only proven for some states, tested on
small systems and conjectured otherwise. Assuming their validity we construct
the eigenvectors of the Q not equal 0 ground state sectors for the transfer
matrix of the superintegrable chiral Potts model.


  Graph embedding methods aim at finding useful graph representations by
mapping nodes to a low-dimensional vector space. It is a task with important
downstream applications, such as link prediction, graph reconstruction, data
visualization, node classification, and language modeling. In recent years, the
field of graph embedding has witnessed a shift from linear algebraic approaches
towards local, gradient-based optimization methods combined with random walks
and deep neural networks to tackle the problem of embedding large graphs.
However, despite this improvement in the optimization tools, graph embedding
methods are still generically designed in a way that is oblivious to the
particularities of real-life networks. Indeed, there has been significant
progress in understanding and modeling complex real-life networks in recent
years. However, the obtained results have had a minor influence on the
development of graph embedding algorithms. This paper aims to remedy this by
designing a graph embedding method that takes advantage of recent valuable
insights from the field of network science. More precisely, we present a novel
graph embedding approach based on the popularity-similarity and local
attraction paradigms. We evaluate the performance of the proposed approach on
the link prediction task on a large number of real-life networks. We show,
using extensive experimental analysis, that the proposed method outperforms
state-of-the-art graph embedding algorithms. We also demonstrate its robustness
to data scarcity and the choice of embedding dimensionality.


  We obtain exact results for correlation functions of primary operators in the
two-dimensional conformal field theory of a scalar field interacting with a
critical periodic boundary potential. Amplitudes involving arbitrary bulk
discrete primary fields are given in terms of SU(2) rotation coefficients while
boundary amplitudes involving discrete boundary fields are independent of the
boundary interaction. Mixed amplitudes involving both bulk and boundary
discrete fields can also be obtained explicitly. Two- and three-point boundary
amplitudes involving fields at generic momentum are determined, up to
multiplicative constants, by the band spectrum in the open-string sector of the
theory.


  Cylindrical Algebraic Decomposition (CAD) is a key tool in computational
algebraic geometry, best known as a procedure to enable Quantifier Elimination
over real-closed fields. However, it has a worst case complexity doubly
exponential in the size of the input, which is often encountered in practice.
It has been observed that for many problems a change in algorithm settings or
problem formulation can cause huge differences in runtime costs, changing
problem instances from intractable to easy. A number of heuristics have been
developed to help with such choices, but the complicated nature of the
geometric relationships involved means these are imperfect and can sometimes
make poor choices. We investigate the use of machine learning (specifically
support vector machines) to make such choices instead.
  Machine learning is the process of fitting a computer model to a complex
function based on properties learned from measured data. In this paper we apply
it in two case studies: the first to select between heuristics for choosing a
CAD variable ordering; the second to identify when a CAD problem instance would
benefit from Groebner Basis preconditioning. These appear to be the first such
applications of machine learning to Symbolic Computation. We demonstrate in
both cases that the machine learned choice outperforms human developed
heuristics.


  This paper investigates the asymptotic theory of the quasi-maximum
exponential likelihood estimators (QMELE) for ARMA--GARCH models. Under only a
fractional moment condition, the strong consistency and the asymptotic
normality of the global self-weighted QMELE are obtained. Based on this
self-weighted QMELE, the local QMELE is showed to be asymptotically normal for
the ARMA model with GARCH (finite variance) and IGARCH errors. A formal
comparison of two estimators is given for some cases. A simulation study is
carried out to assess the performance of these estimators, and a real example
on the world crude oil price is given.


  We examine the magnetic susceptibility of topological insulators
microscopically and find that the orbital-Zeeman (OZ) cross term, the cross
term between the orbital effect and the spin Zeeman effect, is directly related
to the Berry curvature when the $z$-component of spin is conserved. In
particular, the OZ cross term reflects the spin Chern number, which results in
the quantization of the magnetic susceptibility jump at the topological phase
transition. The magnitude of the jump is in units of the universal value
$4|e|\mu_{\rm B}/h$. The physical origin of this quantization is clarified. We
also apply the obtained formula to an explicit model and demonstrate the
quantization.


  Several reduced order models have been developed for nonlinear dynamical
systems. To achieve a considerable speed-up, a hyper-reduction step is needed
to reduce the computational complexity due to nonlinear terms. Many
hyper-reduction techniques require the construction of nonlinear term basis,
which introduces a computationally expensive offline phase. A novel way of
constructing nonlinear term basis within the hyper-reduction process is
introduced. In contrast to the traditional hyper-reduction techniques where the
collection of nonlinear term snapshots is required, the SNS method avoids
collecting the nonlinear term snapshots. Instead, it uses the solution
snapshots that are used for building a solution basis, which enables avoiding
an extra data compression of nonlinear term snapshots. As a result, the SNS
method provides a more efficient offline strategy than the traditional model
order reduction techniques, such as the DEIM, GNAT, and ST-GNAT methods. The
SNS method is theoretically justified by the conforming subspace condition and
the subspace inclusion relation. It is useful for model order reduction of
large-scale nonlinear dynamical problems to reduce the offline cost. It is
especially useful for ST-GNAT that has shown promising results, such as a good
accuracy with a considerable online speed-up for hyperbolic problems in a
recent paper by Choi and Carlberg in SISC 2019, because ST-GNAT involves an
expensive offline cost related to collecting nonlinear term snapshots.
Numerical results support that the accuracy of the solution from the SNS method
is comparable to the traditional methods and a considerable speed-up (i.e., a
factor of two to a hundred) is achieved in the offline phase.


  Pathologists diagnose and grade prostate cancer by examining tissue from
needle biopsies on glass slides. The cancer's severity and risk of metastasis
are determined by the Gleason grade, a score based on the organization and
morphology of prostate cancer glands. For diagnostic work-up, pathologists
first locate glands in the whole biopsy core, and -- if they detect cancer --
they assign a Gleason grade. This time-consuming process is subject to errors
and significant inter-observer variability, despite strict diagnostic criteria.
This paper proposes an automated workflow that follows pathologists'
\textit{modus operandi}, isolating and classifying multi-scale patches of
individual glands in whole slide images (WSI) of biopsy tissues using distinct
steps: (1) two fully convolutional networks segment epithelium versus stroma
and gland boundaries, respectively; (2) a classifier network separates benign
from cancer glands at high magnification; and (3) an additional classifier
predicts the grade of each cancer gland at low magnification. Altogether, this
process provides a gland-specific approach for prostate cancer grading that we
compare against other machine-learning-based grading methods.


  Distributed software development is more difficult than co-located software
development. One of the main reasons is that communication is more difficult in
distributed settings. Defined processes and artifacts help, but cannot cover
all information needs. Not communicating important project information,
decisions and rationales can result in duplicate or extra work, delays or even
project failure. Planning and managing a distributed project from an
information flow perspective helps to facilitate available communication
channels right from the start - beyond the documents and artifacts which are
defined for a given development process. In this paper we propose FLOW Mapping,
a systematic approach for planning and managing information flows in
distributed projects. We demonstrate the feasibility of our approach with a
case study in a distributed agile class room project. FLOW Mapping is
sufficient to plan communication and to measure conformance to the
communication strategy. We also discuss cost and impact of our approach.


  We develop an approach to the theory nonholonomic relativistic stochastic
processes on curved spaces. The Ito and Stratonovich calculus are formulated
for spaces with conventional horizontal (holonomic) and vertical (nonholonomic)
splitting defined by nonlinear connection structures. Geometric models of
relativistic diffusion theory are elaborated for nonholonomic (pseudo)
Riemannian manifolds and phase velocity spaces. Applying the anholonomic
deformation method, the field equations in Einstein gravity and various
modifications are formally integrated in general forms, with generic
off-diagonal metrics depending on some classes of generating and integration
functions. Choosing random generating functions we can construct various
classes of stochastic Einstein manifolds. We show how various types of
stochastic gravitational interactions with mixed holonomic/ nonholonomic and
random variables can be modelled in explicit form and study their main
geometric and stochastic properties. Finally, there are analyzed the conditions
when non-random classical gravitational processes transform into stochastic
ones and inversely.


  Both sigma and kappa are well established from E791 data on D->3pi and
D->K-pi-pi$ and BES II data on J/Psi->omega-pi-pi and KKpipi. Fits to these
data are accurately consistent with pi-pi and Kpi elastic scattering when one
allows for the Adler zero which arises from Chiral Symmetry Breaking. The phase
variation with mass is also consistent between elastic scattering and
production data.


  In observational studies, unmeasured confounders present a crucial challenge
in accurately estimating desired causal effects. To calculate the hazard ratio
(HR) in Cox proportional hazard models for time-to-event outcomes, two-stage
residual inclusion and limited information maximum likelihood are typically
employed. However, these methods are known to entail difficulty in terms of
potential bias of HR estimates and parameter identification. This study
introduces a novel nonparametric Bayesian method designed to estimate an
unbiased HR, addressing concerns that previous research methods have had. Our
proposed method consists of two phases: 1) detecting clusters based on the
likelihood of the exposure and outcome variables, and 2) estimating the hazard
ratio within each cluster. Although it is implicitly assumed that unmeasured
confounders affect outcomes through cluster effects, our algorithm is
well-suited for such data structures. The proposed Bayesian estimator has good
performance compared with some competitors.


  We have developed a prototype time-resolved neutron imaging detector
employing a micro-pattern gaseous detector known as the micro-pixel chamber
({\mu}PIC) coupled with a field-programmable-gate-array-based data acquisition
system. Our detector system combines 100{\mu}m-level spatial and sub-{\mu}s
time resolutions with a low gamma sensitivity of less than 10^-12 and high data
rates, making it well suited for applications in neutron radiography at
high-intensity, pulsed neutron sources. In the present paper, we introduce the
detector system and present several test measurements performed at NOBORU
(BL10), J-PARC to demonstrate the capabilities of our prototype. We also
discuss future improvements to the spatial resolution and rate performance.


  We present early laboratory simulations and extensive on-sky tests validating
of the performance of a shaped pupil coronagraph (SPC) behind an extreme-AO
corrected beam of the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO)
system. In tests with the SCExAO internal source/wavefront error simulator, the
normalized intensity profile for the SPC degrades more slowly than for the Lyot
coronagraph as low-order aberrations reduce the Strehl ratio from extremely
high values (S.R. $\sim$ 0.93--0.99) to those characteristic of current
ground-based extreme AO systems (S.R. $\sim$ 0.74--0.93) and then slightly
lower values down to S.R. $\sim$ 0.57. On-sky SCExAO data taken with the SPC
and other coronagraphs for brown dwarf/planet-hosting stars HD 1160 and HR 8799
provide further evidence for the SPC's robustness to low-order aberrations.
From H-band Strehl ratios of 80% to 70%, the Lyot coronagraph's performance vs.
that of the SPC may degrade even faster on sky than is seen in our internal
source simulations. The 5-$\sigma$ contrast also degrades faster (by a factor
of two) for the Lyot than the SPC. The SPC we use was designed as a technology
demonstrator only, with a contrast floor, throughput, and outer working angle
poorly matched for SCExAO's current AO performance and poorly tuned for imaging
the HR 8799 planets. Nevertheless, we detect HR 8799 cde with SCExAO/CHARIS
using the SPC in broadband mode, where the S/N for planet e is within 30% of
that obtained using the vortex coronagraph. The shaped-pupil coronagraph is a
promising design demonstrated to be robust in the presence of low-order
aberrations and may be well-suited for future ground and space-based direct
imaging observations, especially those focused on follow-up exoplanet
characterization and technology demonstration of deep contrast within
well-defined regions of the image plane.


  One of the state-of-the-art strategies for predicting crack propagation,
nucleation, and interaction is the phase-field approach. Despite its
reliability and robustness, the phase-field approach suffers from burdensome
computational cost, caused by the non-convexity of the underlying energy
functional and a large number of unknowns required to resolve the damage
gradients. In this work, we propose to solve such nonlinear systems in a
monolithic manner using the Schwarz preconditioned inexact Newton's (SPIN)
method. The proposed SPIN method leverages the field split approach and
minimizes the energy functional separately with respect to displacement and the
phase-field, in an additive and multiplicative manner. In contrast to the
standard alternate minimization, the result of this decoupled minimization
process is used to construct a preconditioner for a coupled linear system,
arising at each Newton's iteration. The overall performance and the convergence
properties of the proposed additive and multiplicative SPIN methods are
investigated by means of several numerical examples. Comparison with
widely-used alternate minimization is also performed and we show a reduction in
the execution time up to a factor of 50. Moreover, we also demonstrate that
this reduction grows even further with increasing problem size and larger
loading increments.


  Critical properties in the dynamical charge correlation function for the
one-dimensional Mott insulator are studied. By properly taking into account
{\it the final-state interaction} between the charge and spin degrees of
freedom, we find that the edge singularity in the charge correlation function
is governed by massless spinon excitations, although it is naively expected
that spinons do not directly contribute to the charge excitation over the
Hubbard gap. We obtain the momentum-dependent anomalous critical exponent by
applying the finite-size scaling analysis to the Bethe ansatz solution of the
half-filled Hubbard model.


  1D stellar evolution calculations produce uncertain predictions for
quantities like the age, core mass, core compactness, and nucleo-synthetic
yields; a key source of uncertainty is the modeling of interfaces between
regions that are convectively stable and those that are not. Theoretical and
numerical work has demonstrated that there should be numerous processes
adjacent to the convective boundary that induce chemical and angular momentum
transport, as well as modify the thermal structure of the star. One such
process is called convective penetration, wherein vigorous convection extends
beyond the nominal convective boundary and alters both the composition and
thermal structure. In this work, we incorporate the process of convective
penetration in stellar evolution calculations using the stellar evolution
software instrument mesa. We implement convective penetration according to the
description presented by Anders et al. (2022a) to calculate a grid of models
from the pre main sequence to He core depletion. The extent of the convective
penetration zone is self-consistently calculated at each time step without
introducing new free parameters. We find both a substantial penetration zone in
all models with a convective core and observable differences to global stellar
properties such as the luminosity and radius. We preset how the predicted
radial extent of the penetration zone scales with the total stellar mass, age
and the metallicity of the star. We discuss our results in the context of
existing numerical and observational studies.


  WFPC-2 images are used to study the central structure of M31, M32, and M33.
The dimmer peak, P2, of the M31 double nucleus is centered on the bulge to
0.1", implying that it is the dynamical center of M31. P2 contains a compact
source discovered by King et al. (1995) at 1700 A. This source is resolved,
with r_{1/2} approx0.2 pc. It dominates the nucleus at 3000 A, and is
consistent with late B-early A stars. This probable cluster may consist of
young stars and be an older version of the cluster of hot stars at the center
of the Milky Way, or it may consist of heavier stars built up from collisions
in a possible cold disk of stars orbiting P2. In M32, the central cusp rises
into the HST limit with gamma approx0.5, and the central density
rho_0>10^7M_sol pc^-3. The V-I and U-V color profiles are flat, and there is no
sign of an inner disk, dust, or any other structure. This total lack of
features seems at variance with a nominal stellar collision time of 2 X 10^10
yr, which implies that a significant fraction of the light in the central pixel
should come from blue stragglers. InM33, the nucleus has an extremely steep
gamma=1.49 power-law profile for 0.05"<r<0.2" that becomes shallower as the HST
resolution limit is approached. The profile for r<0.04" has either a gamma
approx 0.8 cusp or a small core with r_c ~<0.13 pc. The central density is
rho_0 > 2 10^6M_sol pc^-3, and the implied relaxation time is only ~3 X 10^6
yr, indicating that the nucleus is highly relaxed. The accompanying short
collision time of 7 X 10^9 yr predicts a central blue straggler component
quantitatively consistent with the strong V-I and B-R color gradients seen with
HST and from the ground.


  We investigated the structural and dynamical properties of a tetrahedrally
coordinated crystalline ice from first principles based on density functional
theory within the generalized gradient approximation with the projected
augmented wave method. First, we report the structural behaviour of ice at
finite temperatures based on the analysis of radial distribution functions
obtained by molecular dynamics simulations. The results show how the ordering
of the hydrogen bonding breaks down in the tetrahedral network of ice with
entropy increase in agreement with the neutron diffraction data. We also
calculated the phonon spectra of ice in a 3x1x1 supercell by using the direct
method. So far, due to the direct method used in this calculation, the phonon
spectra is obtained without taking into account the effect of polarization
arising from dipole-dipole interactions of water molecules which is expected to
yield the splitting of longitudinal and transverse optic modes at the
Gamma-point. The calculated longitudinal acoustic velocities from the initial
slopes of the acoustic mode is in a reasonable agreement with the neutron
scatering data. The analysis of the vibrational density of states shows the
existence of a boson peak at low energy of translational region a
characteristic common to amorphous systems.


  One way to improve the relationship between humans and anthropomorphic agents
is to have humans empathize with the agents. In this study, we focused on a
task between agents and humans. We experimentally investigated hypotheses
stating that task difficulty and task content facilitate human empathy. The
experiment was a two-way analysis of variance (ANOVA) with four conditions:
task difficulty (high, low) and task content (competitive, cooperative). The
results showed no main effect for the task content factor and a significant
main effect for the task difficulty factor. In addition, pre-task empathy
toward the agent decreased after the task. The ANOVA showed that one category
of empathy toward the agent increased when the task difficulty was higher than
when it was lower.This indicated that this category of empathy was more likely
to be affected by the task. The task itself used can be an important factor
when manipulating each category of empathy.


  Preliminary constraints are placed on a cluster of YSOs (J2000 02:54:31.4
+69:20:32.5) discovered in the field of the classical Cepheid SU Cas. WISE 3.4,
4.6, 12, and 22 um images reveal that the cluster deviates from spherical
symmetry and exhibits an apparent diameter of 3x6'. SEDs constructed using
2MASS Ks (2.2 um) and WISE photometry indicate that 19 (36%) class I, 21 (40%)
class f, and 13 (25%) class II objects lie r<3' from the cluster center.
Conversely, 11 (18%) class I, 13 (21%) class f, and 37 (61%) class II objects
were detected for r>3'. Approximately 50% of the class I sources within r<3'
were classified solely using WISE photometry owing to the absence of detections
by 2MASS.


  A four-dimensional ${\rm SU}(4)$ confining Yang-Mills field, coupled to a
fundamental fermion field and a bi-fundamental scalar field, has excitations
with spin-2, but no other quantum numbers. These spin-2 excitations can be
light or can condense, depending upon the scalar coupling. If condensation
occurs, there is a massless spin-2 Goldstone boson with (possibly weakly)
broken Lorentz invariance in the effective theory. The low-lying spectrum
contains additional spin-0 and spin-1 particles. We discuss how to couple these
new fields to other matter fields. To our knowledge, this is the only explicit
proposal for a unitary and perturbatively-renormalizable local field theory of
gravity.


  Ions of the isomer $^{229m}$Th are a topic of high interest for the
construction of a "nuclear clock" and in the field of fundamental physics for
testing symmetries of nature. They can be efficiently captured in Paul traps
which are ideal for performing high precision quantum logic spectroscopy.
Trapping and identification of long-lived $^{232}$Th$^{+}$ ions from a laser
ablation source was already demonstrated by the TACTICa collaboration on
Trapping And Cooling of Thorium Ions with Calcium. The $^{229m}$Th is most
easily accessible as $\alpha$-decay daughter of the decay of $^{233}$U. We
report on the development of a source for slow Th ions, including $^{229(m)}$Th
for the TACTICa experiment. The $^{229(m)}$Th source is currently under
construction and comprises a $^{233}$U monolayer, from which $^{229(m)}$Th ions
recoil. These are decelerated in an electric field. Conservation of the full
initial charge state distribution of the $^{229(m)}$Th recoil ions is one of
the unique features of this source. We present ion-flight simulations for our
adopted layout and give a final design. This source will provide Th ions in
their original charge state at energies suitable for capture in a linear Paul
trap for spectroscopy investigations.


  We study the stability of circular orbits of the electromagnetic two-body
problem in an electromagnetic setting that includes retarded and advanced
interactions. We give a method to derive the equations of tangent dynamics
about circular orbits up to nonlinear terms and we derive the linearized
equations explicitly. In particular we study the normal modes of the linearized
dynamics that have an arbitrarily large imaginary eigenvalue. These large
imaginary eigenvalues define fast frequencies that introduce a fast (stiff)
timescale into the dynamics. As an application of Dirac's electrodynamics of
point charges with retarded-only interactions, we study the conditions for the
two charges to perform a fast gyrating motion of small radius about a circular
orbit. The fast gyration defines an angular momentum of the order of the
orbital angular momentum, a vector that rotates in the orbital plane at a
frequency of the order of the orbital frequency and causes a gyroscopic torque.
We explore a consequence of this multiscale solution, i.e; the resonance
condition that the angular momentum of the stiff spinning should rotate exactly
at the orbital frequency. The resonant orbits turn out to have angular momenta
that are integer multiples of Planck's constant to a good approximation. Among
the many qualitative agreements with quantum electrodynamics (QED), the orbital
frequency of the resonant orbits are given by a difference of two eigenvalues
of a linear operator and the emission lines of QED agree with our predictions
within a few percent.


  The notion that the electromagnetic field is quantised is usually inferred
from observations such as the photoelectric effect and the black-body spectrum.
However accounts of the quantisation of this field are usually mathematically
motivated and begin by introducing a vector potential, followed by the
imposition of a gauge that allows the manipulation of the solutions of
Maxwell's equations into a form that is amenable for the machinery of canonical
quantisation. By contrast, here we quantise the electromagnetic field in a less
mathematically and more physically-motivated way. Starting from a direct
description of what one sees in experiments, we show that the usual expressions
of the electric and magnetic field observables follow from Heisenberg's
equation of motion. In our treatment, there is no need to invoke the vector
potential in a specific gauge and we avoid the commonly-used notion of a
fictitious cavity that applies boundary conditions to the field.


  We investigate the reviews of a Comptes rendus note by Andr\'e Weil in 1940
in the three journals Jahrbuch \"uber die Fortschritte der Mathematik,
Zentralblatt f\"ur Mathematik und ihre Grenzgebiete and Mathematical Reviews,
together with the context of the publication of these reviews.


  Three-dimensional conformal theories with six supersymmetries and SU(4)
R-symmetry describing stacks of M2-branes are here proposed to be related to
generalized Jordan triple systems. Writing the four-index structure constants
in an appropriate form, the Chern-Simons part of the action immediately
suggests a connection to such triple systems. In contrast to the previously
considered three-algebras, the additional structure of a generalized Jordan
triple system is associated to a graded Lie algebra, which corresponds to an
extension of the gauge group. In this note we show that the whole theory with
six manifest supersymmetries can be naturally expressed in terms of such a
graded Lie algebra. Also the BLG theory with eight supersymmetries is included
as a special case.


  This paper studies input-to-state stability for hybrid systems with memory,
which models hybrid dynamics affected by time delays. Using both
Lyapunov-Razumikhin functions and Lyapunov-Krasovskii functionals,
Lyapunov-based sufficient conditions are established for input-to-state
stability. In addition, further extensions and relaxations are proposed for
special cases, such as the stable flow/jump cases and the cases that Lyapunov
functions do not decrease strictly during flow/jumps. Finally, two examples are
used to illustrate the developed results.


  In this paper, we prove that there is a strongly universal cellular automaton
on the pentagrid with six states. For each cell c, Moore neighbourhood consists
of the cells which share a vertex with c. Moreover, the rules are rotation
invariant. There are 1072 of them. The result is different from
arXiv:2306.06728. The present paper deals with the pentagrid and not with the
heptagrid, it is not at all the same context although the implementated model
is basically the same. The implementation of that model is different from the
quoted arXiv paper.


  A general quantum mechanical theory is developed for the isomeric excitation
of $^{229}$Th in strong femtosecond laser pulses. The theory describes the
tripartite interaction between the nucleus, the atomic electrons, and the laser
field. The nucleus can be excited both by the laser field and by laser-driven
electronic transitions. Numerical results show that strong femtosecond laser
pulses are very efficient in exciting the $^{229}$Th nucleus, yielding nuclear
excitation probabilities on the order of $10^{-11}$ per nucleus per pulse.
Laser-driven electronic excitations are found to be more efficient than direct
optical excitations.