  The rich open cluster M67 is known to have a chemical composition close to
solar, and an age around 4Gyr. It thus offers the opportunity to check our
understanding of the physics and the evolution of solar-type stars in a cluster
environment. We present the first spectroscopic study at high resolution,
R~50,000, of the potentially best solar twin, M67-1194, identified among
solar-like stars in M67. Based on a pre-selection of solar-twin candidates
performed at medium resolution by Pasquini et al. (2008), we explore the
chemical-abundance similarities and differences between M67-1194 and the Sun,
using VLT/FLAMES-UVES. Working with a solar twin in the framework of a
differential analysis, we minimize systematic model errors in the abundance
analysis compared to previous studies which utilized more evolved stars to
determine the metallicity of M67. We find M67-1194 to have stellar parameters
indistinguishable from the solar values, with the exception of the overall
metallicity which is slightly super-solar ([Fe/H]=0.023 +/- 0.015). An age
determination based on evolutionary tracks yields 4.2 +/- 1.6Gyr. Most
surprisingly, we find the chemical abundance pattern to closely resemble the
solar one, in contrast to most known solar twins in the solar neighbourhood. We
confirm the solar-twin nature of M67-1194, the first solar twin known to belong
to a stellar association. This fact allows us to put some constraints on the
physical reasons for the seemingly systematic departure of M67-1194 and the Sun
from most known solar twins regarding chemical composition. We find that
radiative dust cleansing by nearby luminous stars may be the explanation for
the peculiar composition of both the Sun and M67-1194, but alternative
explanations are also possible. The chemical similarity between the Sun and
M67-1194 also suggests that the Sun once formed in a cluster like M67.


  Energy efficiency is the most important issue in all facets of wireless
sensor networks (WSNs) operations because of the limited and non-replenish able
energy supply. Data aggregation mechanism is one of the possible solutions to
prolong the life time of sensor nodes and on the other hand it also helps in
eliminating the data redundancy and improving the accuracy of information
gathering, is essential for WSNs. In this paper we propose a Clustering based
lifetime maximizing aggregation tree (CLMAT) in which we create aggregation
tree which aim to reduce energy consumption, minimizing the distance traversed
and minimizing the cost in terms of energy consumption. In CLMAT the node
having maximum available energy is used as parent node/ aggregator node. We
concluded with the best possible aggregation tree minimizing energy
utilization, minimizing cost and hence maximizing network lifetime.


  Experimental observations on synaptic plasticity at individual glutamatergic
synapses from the CA3 Shaffer collateral pathway onto CA1 pyramidal cells in
the hippocampus suggest that the transitions in synaptic strength occur among
discrete levels at individual synapses (~\cite{Peter} and S. S.-H. Wang,
unpublished data used with the authors' permission). This happens for both long
term potentiation (LTP) and long term depression (LTD) induction protocols.
O'Connor, Wittenberg, and Wang have argued that three states would account for
their observations on individual synapses in the CA3-CA1 pathway. We develop a
quantitative model of this three state system with transitions among the states
determined by a competition between kinases and phosphatases shown by O'Connor
et al. to be determinant of LTP and LTD, respectively. Specific predictions for
various plasticity protocols are given by coupling this description of discrete
synaptic AMPA conductance changes to a model of postsynaptic membrane potential
and associated intracellular calcium fluxes to yield the transition rates among
the states. We then present various LTP and LTD induction protocols to the
model system and report the resulting whole cell changes in AMPA conductance.
We also examine the effect of our discrete state synaptic plasticity model on
the synchronization of realistic oscillating neurons. We show that one-to-one
synchronization is enhanced by the plasticity we discuss here and the
presynaptic and postsynaptic oscillations are in phase. Synaptic strength
saturates naturally in this model and does not require artificial upper or
lower cutoffs, in contrast to earlier models of plasticity.


  We show that there are no vacuum solutions with a purely magnetic Weyl tensor
with respect to an observer submitted to kinematic restrictions involving first
order differential scalars. This result generalizes previous ones for the
vorticity-free and shear-free cases. We use a covariant approach which makes
evident that only the Bianchi identities are used and, consequently, the
results are also valid for non vacuum solutions with vanishing Cotton tensor.


  The kinetics of phase transition processes often governs the resulting
material microstruc-ture. Using optical microscopy, we here investigate the
formation and stabilization of a po-rous crystalline microstructure forming in
low-salt suspensions of charged colloidal spheres containing aggregates
comprising some 5-10 of these colloids. We observe the transformation of an
initially crystalline colloidal solid with homogeneously incorporated
aggregates to indi-vidual, compositionally refined crystallites of perforated
morphology coexisting with an ag-gregate-enriched fluid phase filling the holes
and separating individual crystallites. A prelimi-nary kinetic characterization
suggests that the involved processes follow power laws. We show that this route
to porous materials is neither restricted to nominally single component systems
nor to a particular microstructure to start from. However, it necessitates an
early rapid solidification stage during which the aggregates become trapped in
the bulk of the host-crystals. The thermodynamic stability of the reconstructed
crystalline scaffold against melt-ing under increased salinity was found
comparable to that of pure phase crystallites grown very slowly from a melt.
Future implications of this novel route to porous colloidal crystals are
discussed.


  A two-dimensional Fourier transform of hadron form factors allows to
determine their charge density in transverse space. We show that this method
can be applied to any virtual photon induced transition, such as \gamma *(q)+N
-> \pi N. Only Fock states that are common to the initial and final states
contribute to the amplitudes, which are determined by the overlap of the
corresponding light-front wave functions. Their transverse extent may be
studied as a function of the final state configuration, allowing qualitatively
new insight into strong interaction dynamics. Fourier transforming the cross
section (rather than the amplitude) gives the distribution of the transverse
distance between the virtual photon interaction vertices in the scattering
amplitude and its complex conjugate. While the measurement of parton
distributions in longitudinal momentum depends on the leading twist
approximation (-q^2 -> \infty limit), all q^2<0 values contribute to the
Fourier transform, with the transverse resolution increasing with the available
range in q^2. We illustrate the method using QED amplitudes.


  Designing hierarchical reinforcement learning algorithms that exhibit safe
behaviour is not only vital for practical applications but also, facilitates a
better understanding of an agent's decisions. We tackle this problem in the
options framework, a particular way to specify temporally abstract actions
which allow an agent to use sub-policies with start and end conditions. We
consider a behaviour as safe that avoids regions of state-space with high
uncertainty in the outcomes of actions. We propose an optimization objective
that learns safe options by encouraging the agent to visit states with higher
behavioural consistency. The proposed objective results in a trade-off between
maximizing the standard expected return and minimizing the effect of model
uncertainty in the return. We propose a policy gradient algorithm to optimize
the constrained objective function. We examine the quantitative and qualitative
behaviour of the proposed approach in a tabular grid-world, continuous-state
puddle-world, and three games from the Arcade Learning Environment: Ms.Pacman,
Amidar, and Q*Bert. Our approach achieves a reduction in the variance of
return, boosts performance in environments with intrinsic variability in the
reward structure, and compares favorably both with primitive actions as well as
with risk-neutral options.


  We obtain a prediction for the hadron-collider event-shape variable
transverse thrust in which the terms enhanced in the dijet limit are resummed
to next-to-next-to-leading logarithmic accuracy. Our method exploits
universality properties made manifest in the factorized expression for the
cross section and only requires one-loop calculations. The necessary two-loop
ingredients are extracted using known results and existing numerical codes. Our
technique is general and applicable to other observables as well.


  The response function of domain growth processes, and in particular the
violation of the fluctuation-dissipation theorem, are studied both analytically
and numerically. In the asymptotic limit of large times, the
fluctuation-dissipation ratio $X$, which quantifies this violation, tends to
one if $C>m^2$ and to zero if $C<m^2$, corresponding to the fast (`bulk') and
slow (`domain-wall') responses, respectively. In this paper, we focus on the
pre-asymptotic behavior of the domain-wall response. This response is shown to
scale with the typical domain length $L(t)$ as $1/L(t)$ for dimension $d>2$,
and as $\ln (L(t))/L(t)$ for $d=2$. Numerical results confirming this analysis
are presented.


  In this paper we present a new approach based on the heat equation and
extension problems to some intertwining formulas arising in conformal CR
geometry.


  In archaeological and paleontological demographic temporal frequency analysis
(dTFA), a handful of protocols for generating temporal frequency distributions
(tfds) have emerged based on the aggregation not of single-point timestamps but
instead of constituent temporal distributions, including probability summation,
kernel density estimation, and human occupation index calculation. While these
protocols bear a striking algebraic resemblance to one another, they are
motivated by the desire to contain fundamentally different sources of
uncertainty, leading to detailed differences in procedure as well as
fundamental differences in the interpretation of the resulting tfd. Rather than
assuming that one technique can fulfil dual purposes based on its formal
resemblance with another, the joint containment of multiple sources of
uncertainty therefore warrants the adoption of propagation-of-uncertainty
techniques in tfd construction.


  The development of increasingly realistic experimental stimuli and task
environments is important for understanding behavior outside the laboratory. We
report a process for generating 3D human model stimuli that combines commonly
used graphics software and enables the flexible generation of animated human
models while providing parametric control over individualized identity
features. Our approach creates novel head models using FaceGen Modeller,
attaches them to commercially-purchased 3D avatar bodies in 3D Studio Max, and
generates Cal3D human models that are compatible with many virtual 3D
environments. Stimuli produced by this method can be embedded as animated 3D
avatars in interactive simulations or presented as 2D images embedded in scenes
for use in traditional laboratory experiments. The inherent flexibility in this
method makes the stimuli applicable to a broad range of basic and applied
research questions in the domain of person perception. We describe the steps of
the stimulus generation process, provide an example of their use in a
recognition memory paradigm, and highlight the adaptability of the method for
related avenues of research.


  We study a class of 2D non-equilibrium Ising models based on competing
dynamics induced by contact with heat-baths at two different temperatures. We
make a comparative study of the non-equilibrium versions of Metropolis, heat
bath/Glauber and Swendsen-Wang dynamics and focus on their critical behavior in
order to understand their universality classes. We present strong evidence that
some of these dynamics have the same critical exponents and belong to the same
universality class as the equilibrium 2D Ising model. We show that the bond
version of the Swendsen-Wang update algorithm can be mapped into an equilibrium
model at an effective temperature.


  Deep spiking neural networks (SNNs) are promising neural networks for their
model capacity from deep neural network architecture and energy efficiency from
SNNs' operations. To train deep SNNs, recently, spatio-temporal backpropagation
(STBP) with surrogate gradient was proposed. Although deep SNNs have been
successfully trained with STBP, they cannot fully utilize spike information. In
this work, we proposed gradient scaling with local spike information, which is
the relation between pre- and post-synaptic spikes. Considering the causality
between spikes, we could enhance the training performance of deep SNNs.
According to our experiments, we could achieve higher accuracy with lower
spikes by adopting the gradient scaling on image classification tasks, such as
CIFAR10 and CIFAR100.


  Querying knowledge graphs (KGs) using deep learning approaches can naturally
leverage the reasoning and generalization ability to learn to infer better
answers. Traditional neural complex query answering (CQA) approaches mostly
work on entity-centric KGs. However, in the real world, we also need to make
logical inferences about events, states, and activities (i.e., eventualities or
situations) to push learning systems from System I to System II, as proposed by
Yoshua Bengio. Querying logically from an EVentuality-centric KG (EVKG) can
naturally provide references to such kind of intuitive and logical inference.
Thus, in this paper, we propose a new framework to leverage neural methods to
answer complex logical queries based on an EVKG, which can satisfy not only
traditional first-order logic constraints but also implicit logical constraints
over eventualities concerning their occurrences and orders. For instance, if we
know that "Food is bad" happens before "PersonX adds soy sauce", then "PersonX
adds soy sauce" is unlikely to be the cause of "Food is bad" due to implicit
temporal constraint. To facilitate consistent reasoning on EVKGs, we propose
Complex Eventuality Query Answering (CEQA), a more rigorous definition of CQA
that considers the implicit logical constraints governing the temporal order
and occurrence of eventualities. In this manner, we propose to leverage theorem
provers for constructing benchmark datasets to ensure the answers satisfy
implicit logical constraints. We also propose a Memory-Enhanced Query Encoding
(MEQE) approach to significantly improve the performance of state-of-the-art
neural query encoders on the CEQA task.


  In this paper we discuss an extension of some results obtained by E. Serra
and P. Tilli, in [Serra&Tilli '12, Serra&Tilli '16], concerning an original
conjecture by E. De Giorgi ([De Giorgi '96, De Giorgi '06]) on a purely
minimization approach to the Cauchy problem for the defocusing nonlinear wave
equation. Precisely, we show how to extend the techniques developed by Serra
and Tilli for homogeneous hyperbolic nonlinear PDEs to the nonhomogeneous case,
thus proving that the idea of De Giorgi yields in fact an effective approach to
investigate general hyperbolic equations.


  Supply chain management (SCM) has been recognized as an important discipline
with applications to many industries, where the two-echelon stochastic
inventory model, involving one downstream retailer and one upstream supplier,
plays a fundamental role for developing firms' SCM strategies. In this work, we
aim at designing online learning algorithms for this problem with an unknown
demand distribution, which brings distinct features as compared to classic
online optimization problems. Specifically, we consider the two-echelon supply
chain model introduced in [Cachon and Zipkin, 1999] under two different
settings: the centralized setting, where a planner decides both agents'
strategy simultaneously, and the decentralized setting, where two agents decide
their strategy independently and selfishly. We design algorithms that achieve
favorable guarantees for both regret and convergence to the optimal inventory
decision in both settings, and additionally for individual regret in the
decentralized setting. Our algorithms are based on Online Gradient Descent and
Online Newton Step, together with several new ingredients specifically designed
for our problem. We also implement our algorithms and show their empirical
effectiveness.


  Prompt tuning is a parameter-efficient tuning (PETuning) method for utilizing
pre-trained models (PTMs) that simply prepends a soft prompt to the input and
only optimizes the prompt to adapt PTMs to downstream tasks. Although it is
parameter- and deployment-efficient, its performance still lags behind other
state-of-the-art PETuning methods. Besides, the training cost of prompt tuning
is not significantly reduced due to the back-propagation through the entire
model. Through empirical analyses, we shed some light on the lagging
performance of prompt tuning and recognize a trade-off between the propagation
distance from label signals to the inserted prompt and the influence of the
prompt on model outputs. Further, we present Late Prompt Tuning (LPT) that
inserts a late prompt into an intermediate layer of the PTM instead of the
input layer or all layers. The late prompt is obtained by a neural prompt
generator conditioned on the hidden states before the prompt insertion layer
and therefore is instance-dependent. Through extensive experimental results
across various tasks and PTMs, we show that LPT can achieve competitive
performance to full model tuning and other PETuning methods under both
full-data and few-shot scenarios while possessing faster training speed and
lower memory cost.


  In this paper we apply the Self-Organized Map (SOM) method for clustering the
DJIA and NASDAQ100 portfolios for determination of non-linear correlations
between stocks. We represent the application of this method as alternative to
ultrametric spaces method. We have found, that SOM method is more relevant and
perspective for clustering ill-structured large databases and, in particular,
NASDAQ100, where nonlinear processing of the large data samples is required.


  This paper tackles the purely unsupervised person re-identification (Re-ID)
problem that requires no annotations. Some previous methods adopt clustering
techniques to generate pseudo labels and use the produced labels to train Re-ID
models progressively. These methods are relatively simple but effective.
However, most clustering-based methods take each cluster as a pseudo identity
class, neglecting the large intra-ID variance caused mainly by the change of
camera views. To address this issue, we propose to split each single cluster
into multiple proxies and each proxy represents the instances coming from the
same camera. These camera-aware proxies enable us to deal with large intra-ID
variance and generate more reliable pseudo labels for learning. Based on the
camera-aware proxies, we design both intra- and inter-camera contrastive
learning components for our Re-ID model to effectively learn the ID
discrimination ability within and across cameras. Meanwhile, a proxy-balanced
sampling strategy is also designed, which facilitates our learning further.
Extensive experiments on three large-scale Re-ID datasets show that our
proposed approach outperforms most unsupervised methods by a significant
margin. Especially, on the challenging MSMT17 dataset, we gain $14.3\%$ Rank-1
and $10.2\%$ mAP improvements when compared to the second place. Code is
available at: \texttt{https://github.com/Terminator8758/CAP-master}.


  The relation between the Seiberg-Witten prepotentials, Nekrasov functions and
matrix models is discussed. We derive quasiclassically the matrix models of
Eguchi-Yang type, describing the instantonic contribution to the deformed
partition functions of supersymmetric gauge theories. The exact quasiclassical
solution for the case of conformal four-dimensional theory is studied in
detail, and some aspects of its relation with the recently proposed logarithmic
beta-ensembles are considered. We discuss also the "quantization" of this
picture in terms of two-dimensional conformal theory with extended symmetry,
and stress its difference from common picture of perturbative expansion a la
matrix models. Instead, the representation for Nekrasov functions in terms of
conformal blocks or Whittaker vector suggests some nontrivial relation with
Teichmueller spaces and quantum integrable systems.


  We perform a detailed study of the dynamics of a nonlinear, one-dimensional
oscillator driven by a periodic force under hysteretic damping, whose linear
version was originally proposed and analyzed by Bishop in [1]. We first add a
small quadratic stiffness term in the constitutive equation and construct the
periodic solution of the problem by a systematic perturbation method,
neglecting transient terms as $t\rightarrow \infty$. We then repeat the
analysis replacing the quadratic by a cubic term, which does not allow the
solutions to escape to infinity. In both cases, we examine the dependence of
the amplitude of the periodic solution on the different parameters of the model
and discuss the differences with the linear model. We point out certain
undesirable features of the solutions, which have also been alluded to in the
literature for the linear Bishop's model, but persist in the nonlinear case as
well. Finally, we discuss an alternative hysteretic damping oscillator model
first proposed by Reid [2], which appears to be free from these difficulties
and exhibits remarkably rich dynamical properties when extended in the
nonlinear regime.


  We present a detailed study of the phase diagram of the Kitaev-Hubbard chain,
that is the Kitaev chain in the presence of a nearest-neighbour density-density
interaction, using both analytical techniques as well as DMRG. In the case of a
moderate attractive interaction, the model has the same phases as the
non-interacting chain, a trivial and a topological phase. For repulsive
interactions, the phase diagram is more interesting. Apart from the previously
observed topological, incommensurate and charge density wave phases, we
identify the `excited state charge density wave' phase. In this phase, the
ground state resembles an excited state of an ordinary charge density phase,
but is lower in energy due to the frustrated nature of the model. We find that
the dynamical critical exponent takes the value $z\simeq 1.8$. Interestingly,
this phase only appears for even system sizes, and is sensitive to the chemical
potential on the edges of the chain. For the topological phase, we present an
argument that excludes the presence of a strong zero mode for a large part of
the topological phase. For the remaining region, we study the time dependence
of the edge magnetization (using the bosonic incarnation of the model). These
results further expand the region where a strong zero mode does not occur.


  Three-dimensional topological insulators are characterized by the presence of
protected gapless spin helical surface states. In realistic samples these
surface states are extended from one surface to another, covering the entire
sample. Generally, on a curved surface of a topological insulator an electron
in a surface state acquires a spin Berry phase as an expression of the
constraint that the effective surface spin must follow the tangential surface
of real space geometry. Such a Berry phase adds up to pi when the electron
encircles, e.g., once around a cylinder. Realistic topological insulators
compounds are also often layered, i.e., are anisotropic. We demonstrate
explicitly the existence of such a pi Berry phase in the presence and absence
(due to crystal anisotropy) of cylindrical symmetry, that is, regardless of
fulfilling the spin-to-surface locking condition. The robustness of the spin
Berry phase pi against cylindrical symmetry breaking is confirmed numerically
using a tight-binding model implementation of a topological insulator nanowire
penetrated by a pi-flux tube.


  In the study of surface waves in the presence of a shear current, a useful
and much studied model is that in which the shear flow has constant vorticity.
Recently it was shown by Constantin [Eur. J. Mech. B/Fluids 30 (2011) 12-16]
that a flow of constant vorticity can only permit waves travelling exactly
upstream or downstream, but not at oblique angles to the current, and several
proofs to the same effect have appeared thereafter. Physical waves cannot
possibly adhere to such a restriction, however. We resolve the paradox by
showing that an oblique plane wave propagating atop a current of constant
vorticity according to the linearized Euler equation carries with it an
undulating perturbation of the vorticity field, hence is not prohibited by the
Constantin theorem since vorticity is not constant. The perturbation of the
vorticity field is readily interpreted in a Lagrangian perspective as the wave
motion gently shifting and twisting the vortex lines as the wave passes. In the
special case of upstream or downstream propagation, the wave advection of
vortex lines does not affect the Eulerian vorticity field, in accordance with
the theorem. We conclude that the study of oblique waves on shear currents
requires a formalism allowing undulating perturbations of the vorticity field,
and the constant vorticity model is helpful only in certain 2D systems.


  A study of the modifications of the magnetic properties of
Ho$_{2-x}$Y$_x$Sn$_2$O$_7$ upon varying the concentration of diamagnetic
Y$^{3+}$ ions is presented. Magnetization and specific heat measurements show
that the Spin Ice ground-state is only weakly affected by doping for $x\leq
0.3$, even if non-negligible changes in the crystal field at Ho$^{3+}$ occur.
In this low doping range $\mu$SR relaxation measurements evidence a
modification in the low-temperature dynamics with respect to the one observed
in the pure Spin Ice. For $x\to 2$, or at high temperature, the dynamics
involve fluctuations among Ho$^{3+}$ crystal field levels which give rise to a
characteristic peak in $^{119}$Sn nuclear spin-lattice relaxation rate. In this
doping limit also the changes in Ho$^{3+}$ magnetic moment suggest a variation
of the crystal field parameters.


  We have performed elastic and inelastic neutron scattering experiments on the
solid solutions U(Ru_{1-x}Rh_x)_2Si_2 for the Ru rich concentrations: x=0,
0.01, 0.02, 0.025, 0.03, 0.04 and 0.05. Hidden order is suppressed with
increasing x, and correspondingly the onset temperature T_m (~ 17.5 K at x=0)
of weak antiferromagnetic (AF) Bragg reflection decreases. For x=0.04 and 0.05,
no magnetic order is detected in the investigated temperature range down to 1.4
K. In the middle range, 0.02 <= x <= 0.03, we found that the AF Bragg
reflection is strongly enhanced. At x=0.02, this takes place at ~ 7.7 K (=T_M),
which is significantly lower than T_m (~ 13.7 K). T_M increases with increasing
x, and seems to merge with T_m at x=0.03. If the AF state is assumed to be
homogeneous, the staggered moment \mu_o estimated at 1.4 K increases from
0.02(2) \mu_B/U (x=0) to 0.24(1) \mu_B/U (x=0.02). The behavior is similar to
that observed under hydrostatic pressure (\mu_o increases to ~ 0.25 \mu_B/U at
1.0 GPa), suggesting that the AF evolution induced by Rh doping is due to an
increase in the AF volume fraction. We also found that the magnetic excitation
observed at Q=(1,0,0) below T_m disappears as T is lowered below T_M.


  We described the design and operation principles of a new tunable-filter
photometer developed for the 1-m telescope of the Special Astrophysical
Observatory of the Russian Academy of Sciences and the 2.5-m telescope of the
Sternberg Astronomical Institute of the Moscow State University. The instrument
is mounted on the scanning Fabry-Perot interferometer operating in the
tunable-filter mode in the spectral range of 460-800 nm with a typical spectral
resolution of about 1.3 nm. It allows one to create images of galactic and
extragalactic nebulae in the emission lines having different excitation
conditions and to carry out diagnostics of the gas ionization state. The main
steps of observations, data calibration, and reduction are illustrated by
examples of different emission-line objects: galactic HII regions, planetary
nebulae, active galaxies with extended filaments, starburst galaxies, and
Perseus galaxy cluster.


  This paper studies size-polydisperse Lennard-Jones systems described by
active Ornstein-Uhlenbeck particle dynamics. The focus is on the existence of
isomorphs (curves of invariant structure and dynamics) in the model's
three-dimensional phase diagram. Isomorphs are traced out from a single
steady-state configuration by means of the configurational-temperature method.
Good invariance of the reduced-unit radial distribution function and the
mean-square displacement as a function of time is demonstrated for three
uniform-distribution polydispersities, 12%, 23%, and 29%. Comparing to
active-matter isomorphs generated by the analytical direct-isomorph-check
method, the latter give somewhat poorer invariance of the structure, but better
invariance of the dynamics. We conclude that both methods can be used to
quickly get an overview of the phase diagram of polydisperse AOUP models
involving a potential-energy function obeying the hidden-scale-invariance
property required for isomorph theory to apply.


  Technology-Enhanced Formative Assessment (TEFA) is a pedagogy for teaching
with classroom response technology. Teacher Learning of TEFA is a five-year
research project studying teacher change, in the context of an intensive
professional development program designed to help science and mathematics
teachers learn TEFA. First, we provide an overview of the project's
participating teachers, its intervention (consisting of the technology, the
pedagogy, and the professional development program), and its research design.
Then, we present narratives describing the unfolding change process experienced
by four teachers. Afterward, we present some preliminary findings of the
research, describe a "model for the co-evolution of teacher and pedagogy" that
we are developing, and identify general implications for professional
development.


  We study the impact of three-body physics in quenched unitary Bose gases,
focusing on the role of the Efimov effect. Using a local density model, we
solve the three-body problem and determine three-body decay rates at unitary,
finding density-dependent, log-periodic Efimov oscillations, violating the
expected continuous scale-invariance in the system. We find that the breakdown
of continuous scale-invariance, due to Efimov physics, manifests also in the
earliest stages of evolution after the interaction quench to unitarity, where
we find the growth of a substantial population of Efimov states for densities
in which the interparticle distance is comparable to the size of an Efimov
state. This agrees with the early-time dynamical growth of three-body
correlations at unitarity [Colussi {\em et al}., Phys. Rev. Lett. 120, 100401
(2018)]. By varying the sweep rate away from unitarity, we also find a
departure from the usual Landau-Zener analysis for state transfer when the
system is allowed to evolve at unitarity and develop correlations.


  Two-phase xenon detectors, such as that at the core of the forthcoming LZ
dark matter experiment, use photomultiplier tubes to sense the primary (S1) and
secondary (S2) scintillation signals resulting from particle interactions in
their liquid xenon target. This paper describes a simulation study exploring
two techniques to lower the energy threshold of LZ to gain sensitivity to
low-mass dark matter and astrophysical neutrinos, which will be applicable to
other liquid xenon detectors. The energy threshold is determined by the number
of detected S1 photons; typically, these must be recorded in three or more
photomultiplier channels to avoid dark count coincidences that mimic real
signals. To lower this threshold: a) we take advantage of the double
photoelectron emission effect, whereby a single vacuum ultraviolet photon has a
$\sim20\%$ probability of ejecting two photoelectrons from a photomultiplier
tube photocathode; and b) we drop the requirement of an S1 signal altogether,
and use only the ionization signal, which can be detected more efficiently. For
both techniques we develop signal and background models for the nominal
exposure, and explore accompanying systematic effects, including the dependence
on the free electron lifetime in the liquid xenon. When incorporating double
photoelectron signals, we predict a factor of $\sim 4$ sensitivity improvement
to the dark matter-nucleon scattering cross-section at $2.5$ GeV/c$^2$, and a
factor of $\sim1.6$ increase in the solar $^8$B neutrino detection rate.
Dropping the S1 requirement may allow sensitivity gains of two orders of
magnitude in both cases. Finally, we apply these techniques to even lower
masses by taking into account the atomic Migdal effect; this could lower the
dark matter particle mass threshold to $80$ MeV/c$^2$.


  We review some of the endeavors in trying to connect Petri nets with free
symmetric monoidal categories. We give a list of requirement such connections
should respect if they are meant to be useful for practical/implementation
purposes. We show how previous approaches do not satisfy them, and give
compelling evidence that this depends on trying to make the correspondence
functorial in the direction from nets to free symmetric monoidal categories, in
order to produce an adjunction. We show that dropping this immediately honors
our desiderata, and conclude by introducing an Idris library which implements
them.


  We present deep Hubble Space Telescope (HST) photometry of the ultra-faint
dwarf (UFD) galaxies Pegasus III (Peg III) and Pisces II (Psc II), two of the
most distant satellites in the halo of the Milky Way (MW). We measure the
structure of both galaxies, derive mass-to-light ratios with newly determined
absolute magnitudes, and compare our findings to expectations from UFD-mass
simulations. For Peg III, we find an elliptical half-light radius of
$a_h=1.88^{+0.42}_{-0.33}$ arcminutes ($118^{+31}_{-30}$ pc) and
$M_V{=}{-4.17}^{+0.19}_{-0.22}$; for Psc II, we measure
$a_h{=}1.31^{+0.10}_{-0.09}$ arcminutes ($69\pm8$ pc) and
$M_V{=}{-4.28}^{+0.19}_{-0.16}$. We do not find any morphological features that
indicate a significant interaction between the two has occurred, despite their
close separation of only $\sim$40 kpc. Using proper motions (PMs) from Gaia
early Data Release 3, we investigate the possibility of any past association by
integrating orbits for the two UFDs in a MW-only and a combined MW and Large
Magellanic Cloud (LMC) potential. We find that including the gravitational
influence of the LMC is crucial, even for these outer-halo satellites, and that
a possible orbital history exists where Peg III and Psc II experienced a close
($\sim$10-20 kpc) passage about each other just over $\sim$1 Gyr ago, followed
by a collective passage around the LMC ($\sim$30-60 kpc) just under $\sim$1 Gyr
ago. Considering the large uncertainties on the PMs and the restrictive priors
imposed to derive them, improved PM measurements for Peg III and Psc II will be
necessary to clarify their relationship. This would add to the rare findings of
confirmed pairs of satellites within the Local Group.


  The magnets are typically classified into Stoner and Heisenberg type,
depending on the itinerant or localized nature of the constituent magnetic
moments. In this work, we investigate theoretically the behaviour of the
magnetic moments of iron and cobalt in their B2-ordered alloy. The results
based on local spin density approximation (LSDA) for the density functional
theory (DFT) suggest that the Co magnetic moment strongly depends on the
directions of the surrounding magnetic moments, which usually indicates the
Stoner-type mechanism of magnetism. This is consistent with the disordered
local moment (DLM) picture of the paramagnetic state, where the magnetic moment
of cobalt gets substantially suppressed. We argue that this is due to the lack
of strong on-site electron correlations, which we take into account by
employing a combination of DFT and dynamical mean-field theory (DMFT). Within
LDA+DMFT, we find a substantial quasiparticle mass renormalization and a non
Fermi-liquid behaviour of Fe-$3d$ orbitals. The resulting spectral functions
are in very good agreement with measured spin-resolved photoemission spectra.
Our results suggest that local correlations play an essential role in
stabilizing a robust local moment on Co in the absence of magnetic order at
high temperatures.


  While perturbative QCD is sufficient for understanding the color, mass and
energy dependences of parton energy loss and jet quenching at large transverse
momentum in heavy-ion collisions, a simultaneous description of heavy flavor
nuclear modification factor $R_\mathrm{AA}$ and elliptic flow coefficient $v_2$
at low and intermediate $p_\mathrm{T}$ still remains a challenge due to the
effects from non-perturbative interactions. In this work, we extend the linear
Boltzmann transport model by implementing a generalized Cornell-type potential
that incorporates both short-range Yukawa interaction and long-range color
confining interaction between heavy quarks and the QGP medium. Combining our
new approach for heavy-quark-QGP interaction with a (3+1)-dimensional
hydrodynamic model CLVisc for the QGP evolution and a hybrid
fragmentation-coalescence model for heavy quark hadronization, we obtain a
satisfactory description of heavy meson $R_\mathrm{AA}$ and $v_2$ from low to
intermediate to high $p_\mathrm{T}$ observed at both RHIC and the LHC. By
model-data-comparison, we extract for the first time the in-medium heavy quark
potential from open heavy flavor measurements; the result is in agreement with
the lattice QCD calculation. Our study indicates that while jet quenching at
high $p_\mathrm{T}$ is dominated by perturbative QCD interactions,
non-perturbative interactions are indispensible for understanding heavy flavor
quenching and flow at low and intermediate $p_\mathrm{T}$.


  The efficiency of light coupling to surface plasmon polariton (SPP)
represents a very important issue in plasmonics and laser fabrication of
topographies in various solids. To illustrate the role of pre-patterrned
surfaces and impact of laser polsarisation in the excitation of electromagnetic
modes and periodic pattern formation, Nickel surfaces are irradiated with
femtosecond laser pulses of polarisation perpendicular or parallel to the
orientation of the pre-pattern ridges. Experimental results indicate that for
polarisation parallel to the ridges, laser induced periodic surface structures
(LIPSS) are formed perpendicularly to the pre-pattern with a frequency that is
independent of the distance between the ridges and periodicities close to the
wavelength of the excited SPP. By contrast, for polarisation perpendicular to
the pre-pattern, the periodicities of the LIPSS are closely correlated to the
distance between the ridges for pre-pattern distance larger than the laser
wavelength. The experimental observations are interpreted through a multi-scale
physical model in which the impact of the interference of the electromagnetic
modes is revealed.


  Negative sampling is essential for implicit-feedback-based collaborative
filtering, which is used to constitute negative signals from massive unlabeled
data to guide supervised learning. The state-of-the-art idea is to utilize hard
negative samples that carry more useful information to form a better decision
boundary. To balance efficiency and effectiveness, the vast majority of
existing methods follow the two-pass approach, in which the first pass samples
a fixed number of unobserved items by a simple static distribution and then the
second pass selects the final negative items using a more sophisticated
negative sampling strategy. However, selecting negative samples from the
original items is inherently restricted, and thus may not be able to contrast
positive samples well. In this paper, we confirm this observation via
experiments and introduce two limitations of existing solutions: ambiguous trap
and information discrimination. Our response to such limitations is to
introduce augmented negative samples. This direction renders a substantial
technical challenge because constructing unconstrained negative samples may
introduce excessive noise that distorts the decision boundary. To this end, we
introduce a novel generic augmented negative sampling paradigm and provide a
concrete instantiation. First, we disentangle hard and easy factors of negative
items. Next, we generate new candidate negative samples by augmenting only the
easy factors in a regulated manner: the direction and magnitude of the
augmentation are carefully calibrated. Finally, we design an advanced negative
sampling strategy to identify the final augmented negative samples, which
considers not only the score function used in existing methods but also a new
metric called augmentation gain. Extensive experiments on real-world datasets
demonstrate that our method significantly outperforms state-of-the-art
baselines.


  In this paper, we consider the inventory management (IM) problem where we
need to make replenishment decisions for a large number of stock keeping units
(SKUs) to balance their supply and demand. In our setting, the constraint on
the shared resources (such as the inventory capacity) couples the otherwise
independent control for each SKU. We formulate the problem with this structure
as Shared-Resource Stochastic Game (SRSG)and propose an efficient algorithm
called Context-aware Decentralized PPO (CD-PPO). Through extensive experiments,
we demonstrate that CD-PPO can accelerate the learning procedure compared with
standard MARL algorithms.


  We conjecture the existence of four independent gradings in the colored
HOMFLY homology. We describe these gradings explicitly for the rectangular
colored homology of torus knots and make qualitative predictions of various
interesting structures and symmetries in the colored homology of general knots.
We also give a simple representation-theoretic model for the HOMFLY homology of
the unknot colored by any representation. While some of these structures have a
natural interpretation in the physical realization of knot homologies based on
counting supersymmetric configurations (BPS states, instantons, and vortices),
others are completely new. They suggest new geometric and physical realizations
of colored HOMFLY homology as the Hochschild homology of the category of branes
in a Landau-Ginzburg B-model or, equivalently, in the mirror A-model.
Supergroups and supermanifolds are surprisingly ubiquitous in all aspects of
this work.


  We study extremal functions for a family of Poincar\'e-Sobolev-type
inequalities. These functions minimize, for subcritical or critical $p\geq 2$,
the quotient ${\|\nabla u\|_2}/{\|u\|_p}$ among all $u \in
H^1(B)\setminus\{0\}$ with $\int_{B}u=0$. Here $B$ is the unit ball in
$\mathbb{R}^N$. We show that the minimizers are axially symmetric with respect
to a line passing through the origin. We also show that they are strictly
monotone in the direction of this line. In particular, they take their maximum
and minimum precisely at two antipodal points on the boundary of $B$. We also
prove that, for $p$ close to $2$, minimizers are antisymmetric with respect to
the hyperplane through the origin perpendicular to the symmetry axis, and that,
once the symmetry axis is fixed, they are unique (up to multiplication by a
constant). In space dimension two, we prove that minimizers are not
antisymmetric for large $p$.


  We consider issues related to the conformal mapping between the Einstein and
Jordan frames in f(R) cosmology. We consider the impact of the conformal
transformation on the gauge of a perturbed system and show that unless the
system is written in a restricted set of gauges the mapping could produce an
inconsistent result in the target frame. Newtonian gauge lies within the
restricted group but synchronous gauge does not. If this is not treated
carefully it could in principle contaminate numerical calculations.


  Star cluster formation is unlikely to be a sudden event: instead, matter will
flow to a cluster's formation site over an extended period, even as stars form
and inject energy to the region. A cluster's gaseous precursor must persist
under the competing influences of accretion and feedback for several crossing
times, insofar as star formation is a slow process. The new-born stellar
cluster should therefore preserve a memory of this competition. Using
analytical approximations we assess the dynamical state of the gas, mapping
regimes in which various types of feedback are weak or strong. Protostellar
outflows, radiation pressure, and ionized gas pressure are accounted for.
Comparison to observations shows that feedback is often incapable of expelling
gas in the more massive, rapidly-accreting clusters, but feedback may
nevertheless starve accretion by acting on larger scales.


  The Solar System includes two planets --- Mercury and Mars --- significantly
less massive than Earth, and all evidence indicates that planets of similar
size orbit many stars. In fact, one of the first exoplanets to be discovered is
a lunar-mass planet around a millisecond pulsar. Novel classes of exoplanets
have inspired new ideas about planet formation and evolution, and these
"sub-Earths" should be no exception: they include planets with masses between
Mars and Venus for which there are no Solar System analogs. Advances in
astronomical instrumentation and recent space missions have opened the
sub-Earth frontier for exploration: the Kepler mission has discovered dozens of
confirmed or candidate sub-Earths transiting their host stars. It can detect
Mars-size planets around its smallest stellar targets, as well as exomoons of
comparable size. Although the application of the Doppler method is currently
limited by instrument stability, future spectrographs may detect equivalent
planets orbiting close to nearby bright stars. Future space-based microlensing
missions should be able to probe the sub-Earth population on much wider orbits.
A census of sub-Earths will complete the reconnaissance of the exoplanet mass
spectrum and test predictions of planet formation models, including whether
low-mass M dwarf stars preferentially host the smallest planets. The properties
of sub-Earths may reflect their low gravity, diverse origins, and environment,
but they will be elusive: Observations of eclipsing systems by the James Webb
Space Telescope may give us our first clues to the properties of these small
worlds.


  X-ray emission by sparks implies bremsstrahlung from a population of
energetic electrons, but the details of this process remain a mystery. We
present detailed statistical analysis of X-ray spectra detected by multiple
detectors during sparks produced by 1 MV negative high-voltage pulses with 1
$\mu$s risetime. With over 900 shots, we statistically analyze the signals,
assuming that the distribution of spark X-ray fluence behaves as a power law
and that the energy spectrum of X-rays detectable after traversing $\sim$2 m of
air and a thin aluminum shield is exponential. We then determine the parameters
of those distributions by fitting cumulative distribution functions to the
observations. The fit results match the observations very well if the mean of
the exponential X-ray energy distribution is 86 $\pm$ 7 keV and the spark X-ray
fluence power law distribution has index -1.29 $\pm$ 0.04 and spans at least 3
orders of magnitude in fluence.


  In this talk, we present the results of the complete one-loop matching of the
seesaw model onto its low-energy effective theory by integrating out three
right-handed neutrinos at the one-loop level. We find that there are 31
independent dimension-6 (dim-6) operators (barring flavor structures and
Hermitian conjugates) in the Warsaw basis, and the standard-model couplings and
the Wilson coefficient of the Weinberg operator acquire threshold corrections
at the one-loop level. The complete Lagrangian up to dim-6 at the one-loop
level is derived, which is indispensable for consistent explorations of the
impact of heavy right-handed neutrinos at low energies.


  Wave-mechanical effects in gravitational lensing have long been predicted,
and with the discovery of populations of compact transients such as
gravitational wave events and fast radio bursts, may soon be observed. We
present an observer's review of the relevant theory underlying wave-mechanical
effects in gravitational lensing. Starting from the curved-spacetime scalar
wave equation, we derive the Fresnel-Kirchoff diffraction integral, and analyze
it in the eikonal and wave optics regimes. We answer the question of what makes
interference effects observable in some systems but not in others, and how
interference effects allow for complementary information to be extracted from
lensing systems as compared to traditional measurements. We end by discussing
how diffraction effects affect optical depth forecasts and lensing near
caustics, and how compact, low-frequency transients like gravitational waves
and fast radio bursts provide promising paths to open up the frontier of
interferometric gravitational lensing.


  Spiking neural networks (SNNs) are receiving increased attention because they
mimic synaptic connections in biological systems and produce spike trains,
which can be approximated by binary values for computational efficiency.
Recently, the addition of convolutional layers to combine the feature
extraction power of convolutional networks with the computational efficiency of
SNNs has been introduced. This paper studies the feasibility of using a
convolutional spiking neural network (CSNN) to detect anticipatory slow
cortical potentials (SCPs) related to braking intention in human participants
using an electroencephalogram (EEG). Data was collected during an experiment
wherein participants operated a remote-controlled vehicle on a testbed designed
to simulate an urban environment. Participants were alerted to an incoming
braking event via an audio countdown to elicit anticipatory potentials that
were measured using an EEG. The CSNN's performance was compared to a standard
CNN, EEGNet and three graph neural networks via 10-fold cross-validation. The
CSNN outperformed all the other neural networks, and had a predictive accuracy
of 99.06 percent with a true positive rate of 98.50 percent, a true negative
rate of 99.20 percent and an F1-score of 0.98. Performance of the CSNN was
comparable to the CNN in an ablation study using a subset of EEG channels that
localized SCPs. Classification performance of the CSNN degraded only slightly
when the floating-point EEG data were converted into spike trains via delta
modulation to mimic synaptic connections.


  Electrons in an expanding ultracold plasma are expected to be in
quasi-equilibrium, since the collision times are short compared to the plasma
lifetime, yet we observe electrons evaporating out as the ion density decreases
during expansion. We observe that a small electric field that shifts the
electron cloud with respect to the ions increases the evaporation rate. We have
calculated the spatial distribution of a zero-temperature electron cloud as a
function of applied field and ion density, which is assumed to be Gaussian at
all times. This calculation allows us to predict the flux of cold electrons
from the plasma at all times, and is in good agreement with our observed
electron signal.


  Strong light-matter coupling manifested by vacuum Rabi splitting has
attracted tremendous attention due to its fundamental importance in cavity
quantum-electrodynamics research and great potentials in quantum information
applications. A prerequisite for practical applications of the strong coupling
in future quantum information processing and coherent manipulation is an
all-solid-state system exhibiting room-temperature vacuum Rabi splitting with
active control. Here we realized such a system in heterostructure consisting of
monolayer WS2 and an individual plasmonic gold nanorod. By taking advantage of
both of the small mode volume of the nanorod and large binding energy of the
WS2 exciton, giant vacuum Rabi splitting energies of 91 meV ~ 133 meV can be
obtained at ambient conditions, which only involve 5 ~ 18 excitons. The vacuum
Rabi splitting can be dynamically tuned either by electrostatic gating or
temperature scanning. These findings could pave the way towards active quantum
optic devices operating at room temperature.


  A method for non-destructive characterization of a dipole trapped atomic
sample is presented. It relies on a measurement of the phase-shift imposed by
cold atoms on an optical pulse that propagates through a free space
Mach-Zehnder interferometer. Using this technique we are able to determine,
with very good accuracy, relevant trap parameters such as the atomic sample
temperature, trap oscillation frequencies and loss rates. Another important
feature is that our method is faster than conventional absorption or
fluorescence techniques, allowing the combination of high-dynamical range
measurements and a reduced number of spontaneous emission events per atom.


  Vector algebra is a powerful and needful tool for Physics but unfortunately,
due to lack of mathematical skills, it becomes misleading for first
undergraduate courses of science and engineering studies. Standard vector
identities are usually proved using Cartesian components or geometrical
arguments, accordingly. Instead, this work presents a new teaching strategy in
order to derive symbolically vector identities without analytical expansions in
components, either explicitly or using indicial notation. This strategy is
mainly based on the correspondence between three-dimensional vectors and
skew-symmetric second-rank tensors. Hence, the derivations are performed from
skew tensors and dyadic products, rather than cross products. Some examples of
skew-symmetric tensors in Physics are illustrated.


  We construct $p$-adic triple product $L$-functions that interpolate (square
roots of) central critical $L$-values in the balanced region. Thus, our
construction complements that of M. Harris and J. Tilouine.
  There are four central critical regions for the triple product $L$-functions
and two opposite settings, according to the sign of the functional equation. In
the first case, three of these regions are of interpolation, having positive
sign; they are called the unbalanced regions and one gets three $p$% -adic
$L$-functions, one for each region of interpolation (this is the
Harris-Tilouine setting). In the other setting there is only one region of
interpolation, called the balanced region. An especially interesting feature of
our construction is that we get three different $p$-adic triple product $% L
$-functions with the same (balanced) region of interpolation. To the best of
the authors' knowledge, this is the first case where an interpolation problem
is solved on a single critical region by different $p$-adic $L$% -functions at
the same time. This is possible due to the structure of the Euler-like factors
at $p$ arising in the interpolation formulas, the vanishing of which are
related to the dimensions of certain Nekovar period spaces. Our triple product
$p$-adic $L$-functions arise as specializations of $p$-adic period integrals
interpolating normalizations of the local archimedean period integrals. The
latter encode information about classical representation theoretic branching
laws. The main step in our construction of $p$-adic period integrals is showing
that these branching laws vary in a $% p$-adic analytic fashion. This relies
crucially on the Ash-Stevens theory of highest weight representations over
affinoid algebras.


  Poincar\'e maps and suspension flows are examples of fundamental
constructions in the study of dynamical systems. This study aimed to show that
these constructions define an adjoint pair of functors if categories of
dynamical systems are suitably set. First, we consider the construction of
Poincar\'e maps in the category of flows on topological manifolds, which are
not necessarily smooth. We show that well-known results can be generalized and
the construction of Poincar\'e maps is functorial, if a category of flows with
global Poincar\'e sections is adequately defined. Next, we consider the
construction of suspension flows and its functoriality. Finally, we consider
the adjointness of the constructions of Poincar\'e maps and suspension flows.
By considering the naturality, we can conclude that the concepts of topological
equivalence or topological conjugacy of flows are not sufficient to describe
the correspondence between map dynamical systems and flows with global
Poincar\'e sections. We define another category of flows with global Poincar\'e
sections and show that the suspension functor and the Poincar\'e map functor
form an adjoint equivalence if these categories are considered. Hence, a
categorical correspondence between map dynamical systems and flows with global
Poincar\'e sections is obtained. This will enable us to better understand the
connection between map dynamical systems and flows.


  Recently it has been shown that the peak of the quarkonium entropy at the
deconfinement transition is related to the emergent entropic force which
destructs the quarkonium. Using the AdS/CFT correspondence, we consider
dissociation of a moving heavy quarkonium by entropic force. We find that the
entropic force destructs the moving quarkonium easier than the static case
which is expected from perturbative weakly coupled plasma. By considering the
Maxwell charge, we study the effect of medium on the destruction of heavy
quarkonium. It is shown that the quarkonium dissociates easier in the medium.


  We examine millisecond magnetars as central engines of Gamma Ray Bursts'
(GRB) prompt emission. Using the proto-magnetar wind model of Metzger et al.
2011, we estimate the temporal evolution of the magnetization and power
injection at the base of the GRB jet and apply these to different prompt
emission models to make predictions for the GRB energetics, spectra and
lightcurves. We investigate both shock and magnetic reconnection models for the
particle acceleration, as well as the effects of energy dissipation across
optically thick and thin regions of the jet. The magnetization at the base of
the jet, $\sigma_0$, is the main parameter driving the GRB evolution in the
magnetar model and the emission is typically released for $100\lesssim \sigma_0
\lesssim 3000$. Given the rapid increase in $\sigma_0$ as the proto-magnetar
cools and its neutrino-driven mass loss subsides, the GRB duration is typically
limited to $\lesssim 100$ s. This low baryon loading at late times challenges
magnetar models for ultra-long GRBs, though black hole models likely run into
similar difficulties without substantial entrainment from the jet walls. The
maximum radiated gamma-ray energy is $\lesssim 5 \times 10^{51}$erg,
significantly less than the magnetar's total initial rotational energy and in
strong tension with the high end of the observed GRB energy distribution.
However, the gradual magnetic dissipation model (Beniamini & Giannios 2017)
applied to a magnetar central engine, naturally explains several key
observables of typical GRBs, including energetics, durations, stable peak
energies, spectral slopes and a hard to soft evolution during the burst.


  In this paper, over imaginary quadratic fields, we consider the family of
$L$-functions $L (s, f)$ for an orthonormal basis of spherical Hecke--Maass
forms $f$ with Archimedean parameter $t_f$. We establish asymptotic formulae
for the twisted first and second moments of the central values $L\big(\frac 1
2, f\big)$, which can be applied to prove that at least $33 \%$ of $L\big(\frac
1 2, f\big)$ with $t_f \leqslant T$ are non-vanishing as $T \rightarrow
\infty$. Our main tools are the spherical Kuznetsov trace formula and the
Vorono\"i summation formula over imaginary quadratic fields.


  The energy of arbitrary graphene edge is derived in analytical form. It
contains a "chemical phase shift", determined by the chemical conditions at the
edge. Direct atomistic computations support the universal nature of the
relationship. Definitive for graphene formation, shapes of the voids or
ribbons, this has further important implications for nanotube chirality
selection and control by chemical means, at the nucleation stage.


  We report a comprehensive experimental investigation on the magnetic
anisotropy in bulk single crystals of Cr$_2$Ge$_2$Te$_6$, a
quasi-two-dimensional ferromagnet belonging to the family of magnetic layered
transition metal trichalcogenides that have attracted recently a big deal of
interest with regard to the fundamental and applied aspects of two-dimensional
magnetism. For this purpose electron spin resonance (ESR) and ferromagnetic
resonance (FMR) measurements have been carried out over a wide frequency and
temperature range. A gradual change in the angular dependence of the ESR
linewidth at temperatures above the ferromagnetic transition temperature
$T_{\rm c}$ reveals the development of two-dimensional spin correlations in the
vicinity of $T_{\rm c}$ thereby proving the intrinsically low-dimensional
character of spin dynamics in Cr$_2$Ge$_2$Te$_6$. Angular and frequency
dependent measurements in the ferromagnetic phase clearly show an easy-axis
type anisotropy of this compound. Furthermore, these experiments are compared
with simulations based on a phenomenological approach, which takes into account
results of static magnetization measurements as well as high temperature $g$
factors obtained from ESR spectroscopy in the paramagnetic phase. As a result
the determined magnetocrystalline anisotropy energy density (MAE) $K_U$ is
$(0.48 \pm 0.02) \times10^6$ erg/cm$^3$. This analysis is complemented by
density functional calculations which yield the experimental MAE value for a
particular value of the electronic correlation strength $U$. The analysis of
the electronic structure reveals that the low-lying conduction band carries
almost completely spin-polarized, quasi-homogeneous, two-dimensional states.


  We present a realization of astronomical relativistic reference frames in the
solar system and its application to the GRAIL mission. We model the necessary
spacetime coordinate transformations for light-trip time computations and
address some practical aspects of the implementation of the resulting model. We
develop all the relevant relativistic coordinate transformations that are
needed to describe the motion of the GRAIL spacecraft and to compute all
observable quantities. We take into account major relativistic effects
contributing to the dual one-way range observable, which is derived from
one-way signal travel times between the two GRAIL spacecraft. We develop a
general relativistic model for this fundamental observable of GRAIL, accurate
to 1 $\mu$m. We develop and present a relativistic model for another key
observable of this experiment, the dual one-way range-rate, accurate to 1
$\mu$m/s. The presented formulation justifies the basic assumptions behind the
design of the GRAIL mission. It may also be used to further improve the already
impressive results of this lunar gravity recovery experiment after the mission
is complete. Finally, we present transformation rules for frequencies and
gravitational potentials and their application to GRAIL.


  Objective: To propose novel SSVEP classification methodologies using deep
neural networks (DNNs) and improve performances in single-channel and
user-independent brain-computer interfaces (BCIs) with small data lengths.
Approach: We propose the utilization of filter banks (creating sub-band
components of the EEG signal) in conjunction with DNNs. In this context, we
created three different models: a recurrent neural network (FBRNN) analyzing
the time domain, a 2D convolutional neural network (FBCNN-2D) processing
complex spectrum features and a 3D convolutional neural network (FBCNN-3D)
analyzing complex spectrograms, which we introduce in this study as possible
input for SSVEP classification. We tested our neural networks on three open
datasets and conceived them so as not to require calibration from the final
user, simulating a user-independent BCI. Results: The DNNs with the filter
banks surpassed the accuracy of similar networks without this preprocessing
step by considerable margins, and they outperformed common SSVEP classification
methods (SVM and FBCCA) by even higher margins. Conclusion and significance:
Filter banks allow different types of deep neural networks to more efficiently
analyze the harmonic components of SSVEP. Complex spectrograms carry more
information than complex spectrum features and the magnitude spectrum, allowing
the FBCNN-3D to surpass the other CNNs. The performances obtained in the
challenging classification problems indicates a strong potential for the
construction of portable, economical, fast and low-latency BCIs.


  Transient or partial synchronization can be used to do computations, although
a fully synchronized network is frequently related to epileptic seizures. Here,
we propose a homeostatic mechanism that is capable of maintaining a neuronal
network at the edge of a synchronization transition, thereby avoiding the
harmful consequences of a fully synchronized network. We model neurons by maps
since they are dynamically richer than integrate-and-fire models and more
computationally efficient than conductance-based approaches. We first describe
the synchronization phase transition of a dense network of neurons with
different tonic spiking frequencies coupled by gap junctions. We show that at
the transition critical point, inputs optimally reverberate through the network
activity through transient synchronization. Then, we introduce a local
homeostatic dynamic in the synaptic coupling and show that it produces a robust
self-organization toward the edge of this phase transition. We discuss the
potential biological consequences of this self-organization process, such as
its relation to the Brain Criticality hypothesis, its input processing
capacity, and how its malfunction could lead to pathological synchronization.


  In this paper, we investigate the recovery of the sparse representation of
data in general infinite-dimensional optimization problems regularized by
convex functionals. We show that it is possible to define a suitable
non-degeneracy condition on the minimal-norm dual certificate, extending the
well-established non-degeneracy source condition (NDSC) associated with total
variation regularized problems in the space of measures, as introduced in
(Duval and Peyr\'e, FoCM, 15:1315-1355, 2015). In our general setting, we need
to study how the dual certificate is acting, through the duality product, on
the set of extreme points of the ball of the regularizer, seen as a metric
space. This justifies the name Metric Non-Degenerate Source Condition (MNDSC).
More precisely, we impose a second-order condition on the dual certificate,
evaluated on curves with values in small neighbourhoods of a given collection
of n extreme points. By assuming the validity of the MNDSC, together with the
linear independence of the measurements on these extreme points, we establish
that, for a suitable choice of regularization parameters and noise levels, the
minimizer of the minimization problem is unique and is uniquely represented as
a linear combination of n extreme points. The paper concludes by obtaining
explicit formulations of the MNDSC for three problems of interest. First, we
examine total variation regularized deconvolution problems, showing that the
classical NDSC implies our MNDSC, and recovering a result similar to (Duval and
Peyr\'e, FoCM, 15:1315-1355, 2015). Then, we consider 1-dimensional BV
functions regularized with their BV-seminorm and pairs of measures regularized
with their mutual 1-Wasserstein distance. In each case, we provide explicit
versions of the MNDSC and formulate specific sparse representation recovery
results.


  We explore the spectral properties of a capillary dye laser in the highly
multimode regime. Our experiments indicate that the spectral behavior of the
laser does not conform with a simple Fabry-Perot analysis; rather, it is
strongly dictated by a Vernier resonant mechanism involving multiple modes,
which propagate with different group velocities. The laser operates over a very
broad spectral range and the Vernier effect gives rise to a free spectral range
which is orders of magnitude larger than that expected from a simple
Fabry-Perot mechanism. The presented theoretical calculations confirm the
experimental results. Propagating modes of the capillary fiber are calculated
using the finite element method (FEM) and it is shown that the optical
pathlengths resulting from simultaneous beatings of these modes are in close
agreement with the optical pathlengths directly extracted from the Fourier
Transform of the experimentally measured laser emission spectra.


  Coherent small-amplitude unsteadiness of the shock wave and the separation
region over a canonical double cone flow, termed in literature as
oscillation-type unsteadiness, is experimentally studied at Mach 6. The double
cone model is defined by three non-dimensional geometric parameters: fore- and
aft-cone angles ($\theta_1$ and $\theta_2$), and ratio of the conical slant
lengths ($\Lambda$). Previous studies of oscillations have been qualitative in
nature, and mostly restricted to a special case of the cone model with fixed
$\theta_1 = 0^\circ$ and $\theta_2 = 90^\circ$ (referred to as the
spike-cylinder model), where $\Lambda$ becomes the sole governing parameter. In
the present effort we investigate the self-sustained flow oscillations in the
$\theta_1$-$\Lambda$ parameter space for fixed $\theta_2 = 90^\circ$ using
time-resolved schlieren visualization. The experiments reveal two distinct
sub-types of oscillations, characterized by the motion (or lack thereof) of the
separation point on the fore-cone surface. The global time scale associated
with flow oscillation is extracted using spectral proper orthogonal
decomposition. The non-dimensional frequency (Strouhal number) of oscillation
is seen to exhibit distinct scaling for the two oscillation sub-types. The
relationship observed between the local flow properties, instability of the
shear layer, and geometric constraints on the flow suggests that an
aeroacoustic feedback mechanism sustains the oscillations. Based on this
insight, a simple model with no empiricism is developed for the Strouhal
number. The model predictions are found to match well with experimental
measurements. The model provides helpful physical insight into the nature of
the self-sustained flow oscillations over a double cone at high-speeds.


  We formulate a generic three-dimensional higher-derivative superfield theory
for self-interacting scalar superfield action. We consider the cases of real
and complex scalar superfields. For these theories, we explicitly calculate the
one-loop effective potential.


  In this note I will present a subtle interplay between density matrices and
the knowledge about their preparation, and I will argue that there is a need to
consider a new type of quantum state, in between pure states and density
matrices.


  Bursty star formation in dwarf galaxies can slowly transform a steep dark
matter cusp into a constant density core. We explore the possibility that
globular clusters (GCs) retain a dynamical memory of this transformation. To
test this, we use the nbody6df code to simulate the dynamical evolution of GCs,
including stellar evolution, orbiting in static and time-varying potentials for
a Hubble time. We find that GCs orbiting within a cored dark matter halo, or
within a halo that has undergone a cusp-core transformation, grow to a size
that is substantially larger ($R_{\rm eff} > 10$ pc) than those in a static
cusped dark matter halo. They also produce much less tidal debris. We find that
the cleanest signal of an historic cusp-core transformation is the presence of
large GCs with tidal debris. However, the effect is small and will be
challenging to observe in real galaxies. Finally, we qualitatively compare our
simulated GCs with the observed GC populations in the Fornax, NGC 6822, IKN and
Sagittarius dwarf galaxies. We find that the GCs in these dwarf galaxies are
systematically larger ($\langle R_{\rm eff}\rangle \simeq 7.8$ pc), and have
substantially more scatter in their sizes, than in-situ metal rich GCs in the
Milky Way and young massive star clusters forming in M83 ($\langle R_{\rm eff}
\rangle \simeq 2.5$ pc). We show that the size, scatter and survival of GCs in
dwarf galaxies are all consistent with them having evolved in a constant
density core, or a potential that has undergone a cusp-core transformation, but
not in a dark matter cusp.


  The COVID-19 outbreak has admittedly caused a major disruption worldwide. The
interruptions to production, transportation, and mobility have clearly had a
significant impact on the well-functioning of the global supply and demand
chain. But what happened to the companies developing digital services, such as
software. Were they interrupted as much or at all? And how has the enforced
Working-From-Home mode impacted their ability to continue to deliver software?
We hear that some managers are concerned that their engineers are not working
effectively from home, or even lack the motivation to work in general, that
teams lose touch and that managers do not notice when things go wrong. In this
article, we share our findings from monitoring the situation in an
international software company with engineers located in Sweden, USA, and the
UK. We analyzed different aspects of productivity, such as developer
satisfaction and well-being, activity, communication and collaboration,
efficiency and flow based on the archives of commit data, calendar invites, and
Slack communication, as well as the internal reports of WFH experiences and 18
interviews. We find that company engineers continue committing code and carry
out their daily duties without significant disruptions, while their routines
have gradually adjusted to the new norm with new emerging practices and various
changes to the old ones. In a way, our message is that there is no news, which
is good news. Yet, the experiences gained with the WFH of such scale have
already made significant changes in the software industry's future, work from
anywhere being an example of major importance.


  We present a hybrid-mixed finite element method for
  a novel hybrid-dimensional model of single-phase Darcy flow in a fractured
porous media. In this model, the fracture is treated as an $(d-1)$-dimensional
interface within the $d$-dimensional fractured porous domain, for $d=2, 3$. Two
classes of fracture are distinguished based on the permeability magnitude ratio
between the fracture and its surrounding medium: when the permeability in the
fracture is (significantly) larger than in its surrounding medium, it is
considered as a {\it conductive} fracture; when the permeability in the
fracture is (significantly) smaller than in its surrounding medium, it is
considered as a {\it blocking} fracture. The conductive fractures are treated
using the classical hybrid-dimensional approach of the interface model where
pressure is assumed to be continuous across the fracture interfaces, while the
blocking fractures are treated using the recent Dirac-$\delta$ function
approach where normal component of Darcy velocity is assumed to be continuous
across the interface. Due to the use of Dirac-$\delta$ function approach for
the blocking fractures, our numerical scheme allows for nonconforming meshes
with respect to the blocking fractures. This is the major novelty of our model
and numerical discretization. Moreover, our numerical scheme produces locally
conservative velocity approximations and leads to a symmetric positive definite
linear system involving pressure degrees of freedom on the mesh skeleton only.
The performance of the proposed method is demonstrated by various benchmark
test cases in both two- and three-dimensions. Numerical results indicate that
the proposed scheme is highly competitive with existing methods in the
literature.


  Interfacial Dzyaloshinskii-Moriya interaction (DMI) has long been observed in
normal metal/ferromagnetic multilayers, enabling the formation of chiral domain
walls, skyrmions and other 2D antisymmetric spin textures confined within a
single ferromagnetic layer, while more recent works on interlayer DMI reveal
new pathways in realizing novel chiral 3D spin textures between two separate
layers.Here, we report on interlayer DMI between two orthogonally magnetized
ferromagnetic layers (CoFeB/Co) mediated by a Pt layer, and confirm the chiral
nature of the observed effective field of up to 37 Oe through asymmetric
hysteresis loops under in-plane field.We highlight the importance of
growth-induced in-plane symmetry breaking, resulting in a sizable interlayer
DMI and a universal characteristic vector through wedge deposition of the
samples.We further perform deterministic current-driven magnetization switching
in the perpendicularly magnetized Co layer utilizing solely the effective field
from the interlayer DMI.These results demonstrate the potential of interlayer
DMI in facilitating deterministic field-free switching in spin memory
applications.


  The prevalence of quantum crosstalk in current quantum devices poses
challenges for achieving high-fidelity quantum logic operations and reliable
quantum processing. Through quantum control theory, we develop an analytical
condition for achieving crosstalk-robust single-qubit control of multi-qubit
systems. We examine the effects of quantum crosstalk via a cumulant expansion
and develop a condition to suppress the leading order contributions to the
dynamics. The efficacy of the condition is illustrated in the domains of
quantum state preservation and noise characterization through the development
of crosstalk-robust dynamical decoupling and quantum noise spectroscopy (QNS)
protocols. Using the IBM Quantum Experience, crosstalk-robust state
preservation is demonstrated on 27 qubits, where a $3\times$ improvement in
coherence decay is observed for single-qubit product and multipartite entangled
states. Through the use of noise injection, we experimentally demonstrate
crosstalk-robust dephasing QNS on a seven qubit processor, where a $10^4$
improvement in reconstruction accuracy over ``cross-susceptible" alternatives
is found. Together, these experiments highlight the significant impact the
crosstalk mitigation condition can have on improving multi-qubit
characterization and control on current quantum devices.


  Dimensionality reduction and clustering techniques are frequently used to
analyze complex data sets, but their results are often not easy to interpret.
We consider how to support users in interpreting apparent cluster structure on
scatter plots where the axes are not directly interpretable, such as when the
data is projected onto a two-dimensional space using a dimensionality-reduction
method. Specifically, we propose a new method to compute an interpretable
clustering automatically, where the explanation is in the original
high-dimensional space and the clustering is coherent in the low-dimensional
projection. It provides a tunable balance between the complexity and the amount
of information provided, through the use of information theory. We study the
computational complexity of this problem and introduce restrictions on the
search space of solutions to arrive at an efficient, tunable, greedy
optimization algorithm. This algorithm is furthermore implemented in an
interactive tool called ExClus. Experiments on several data sets highlight that
ExClus can provide informative and easy-to-understand patterns, and they expose
where the algorithm is efficient and where there is room for improvement
considering tunability and scalability.


  While the deflection of light is achromatic in General Relativity, it is not
always so in several new-physics models (e.g. certain quantum-gravity and
string-inspired models, models with nonminimal photon-gravity coupling or with
massive photon etc.). We discuss how parameters of these models may be
constrained by precise astrometry at different wavelenghts. From published
observations of the gravitational lens MG J2016+112, we obtain world-best
limits on chromatic gravitational deflection of light (and the unique limit on
the photon mass relevant for distance scales >Mpc). We also outline prospects
for further improvement of these limits.


  Optical coherence tomography (OCT) has proven to be a powerful technique for
studying tissue morphology in ophthalmology, cardiology, and endomicroscopy.
Its performance is limited by the fundamental trade-off between the imaging
sensitivity and acquisition speed -- a predicament common in virtually all
imaging systems. In this paper, we circumvent this limit by using distributed
Raman post-amplification of the reflection from the sample. We combine the
amplification with simultaneously performed dispersive Fourier transformation,
a process that maps the optical spectrum into an easily measured time-domain
waveform. The Raman amplification enables measurement of weak signals which are
otherwise buried in noise. It extends the depth range without sacrificing the
acquisition speed or causing damage to the sample. As proof of concept,
single-shot imaging with 15 dB improvement in sensitivity at an axial scan rate
of 36.6 MHz is demonstrated.


  Distributionally robust stochastic optimization (DRSO) is a framework for
decision-making problems under certainty, which finds solutions that perform
well for a chosen set of probability distributions. Many different approaches
for specifying a set of distributions have been proposed. The choice matters,
because it affects the results, and the relative performance of different
choices depend on the characteristics of the problems. In this paper, we
consider problems in which different random variables exhibit some form of
dependence, but the exact values of the parameters that represent the
dependence are not known. We consider various sets of distributions that
incorporate the dependence structure, and we study the corresponding DRSO
problems.
  In the first part of the paper, we consider problems with linear dependence
between random variables. We consider sets of distributions that are within a
specified Wasserstein distance of a nominal distribution, and that satisfy a
second-order moment constraint. We obtain a tractable dual reformulation of the
corresponding DRSO problem. This approach is compared with the traditional
moment-based DRSO and Wasserstein-based DRSO with no moment constraints.
Numerical experiments suggest that our new formulation has superior
out-of-sample performance.
  In the second part of the paper, we consider problems with various types of
rank dependence between random variables, including rank dependence measured by
Spearman's footrule distance between empirical rankings, comonotonic
distributions, box uncertainty for individual observations, and Wasserstein
distance between copulas associated with continuous distributions. We also
obtain a dual reformulation of the DRSO problem. A desirable byproduct of the
formulation is that it also avoids an issue associated with the one-sided
moment constraints in moment-based DRSO problems.


  In open quantum systems, the precision of metrology inevitably suffers from
the noise. {In Markovian open quantum dynamics, the precision can not be
improved by using entangled probes although the measurement time is effectively
shortened.} However, it was predicted over one decade ago that in a
non-Markovian one, the error can be significantly reduced by the quantum Zeno
effect (QZE) [Chin, Huelga, and Plenio, Phys. Rev. Lett. \textbf{109}, 233601
(2012)]. In this work, we apply a recently-developed quantum simulation
approach to experimentally verify that entangled probes can improve the
precision of metrology by the QZE. Up to $n=7$ qubits, we demonstrate that the
precision has been improved by a factor of $n^{1/4}$, which is consistent with
the theoretical prediction. Our quantum simulation approach may provide an
intriguing platform for experimental verification of various quantum metrology
schemes.


  Due to the high complexity of geometry-deterministic wireless channel
modeling and the difficulty in its implementation, geometry-based stochastic
channel modeling (GBSM) approaches have been used to evaluate wireless systems.
This paper introduces a new method to model any GBSM by training a generative
neural network using images formed by channel parameters. In this work, we
obtain channel parameters from the ray-tracing simulation in a specific area
and process them in the form of images to train any generative model. Through a
case study, we confirm that the use of channel images completes the training of
the generative model within 10 epochs. In addition, we show that the trained
generative model based on channel images faithfully represents the
distributions of the original data under the assigned conditions. Therefore, we
argue that the proposed data-to-image methods will facilitate the modeling of
GBSM using any generative neural network under general wireless conditions.


  Existing machine learning methods for causal inference usually estimate
quantities expressed via the mean of potential outcomes (e.g., average
treatment effect). However, such quantities do not capture the full information
about the distribution of potential outcomes. In this work, we estimate the
density of potential outcomes after interventions from observational data. For
this, we propose a novel, fully-parametric deep learning method called
Interventional Normalizing Flows. Specifically, we combine two normalizing
flows, namely (i) a nuisance flow for estimating nuisance parameters and (ii) a
target flow for parametric estimation of the density of potential outcomes. We
further develop a tractable optimization objective based on a one-step bias
correction for efficient and doubly robust estimation of the target flow
parameters. As a result, our Interventional Normalizing Flows offer a properly
normalized density estimator. Across various experiments, we demonstrate that
our Interventional Normalizing Flows are expressive and highly effective, and
scale well with both sample size and high-dimensional confounding. To the best
of our knowledge, our Interventional Normalizing Flows are the first proper
fully-parametric, deep learning method for density estimation of potential
outcomes.


  Cost optimization is a common goal of workflow schedulers operating in cloud
computing environments. The use of spot instances is a potential means of
achieving this goal, as they are offered by cloud providers at discounted
prices compared to their on-demand counterparts in exchange for reduced
reliability. This is due to the fact that spot instances are subjected to
interruptions when spare computing capacity used for provisioning them is
needed back owing to demand variations. Also, the prices of spot instances are
not fixed as pricing is dependent on long term supply and demand. The
possibility of interruptions and pricing variations associated with spot
instances adds a layer of uncertainty to the general problem of workflow
scheduling across cloud computing environments. These challenges need to be
efficiently addressed for enjoying the cost savings achievable with the use of
spot instances without compromising the underlying business requirements. To
this end, in this paper we use Deep Reinforcement Learning for developing an
autonomous agent capable of scheduling workflows in a cost efficient manner by
using an intelligent mix of spot and on-demand instances. The proposed solution
is implemented in the open source container native Argo workflow engine that is
widely used for executing industrial workflows. The results of the experiments
demonstrate that the proposed scheduling method is capable of outperforming the
current benchmarks.


  In practical terms, controlling a network requires manipulating a large
number of nodes with a comparatively small number of external inputs, a process
that is facilitated by paths that broadcast the influence of the
(directly-controlled) driver nodes to the rest of the network. Recent work has
shown that surprisingly, temporal networks can enjoy tremendous control
advantages over their static counterparts despite the fact that in temporal
networks such paths are seldom instantaneously available. To understand the
underlying reasons, here we systematically analyze the scaling behavior of a
key control cost for temporal networks--the control energy. We show that the
energy costs of controlling temporal networks are determined solely by the
spectral properties of an "effective" Gramian matrix, analogous to the static
network case. Surprisingly, we find that this scaling is largely dictated by
the first and the last network snapshot in the temporal sequence, independent
of the number of intervening snapshots, the initial and final states, and the
number of driver nodes. Our results uncover the intrinsic laws governing why
and when temporal networks save considerable control energy over their static
counterparts.


  Calculations of transverse polarization of leptons in the decay $W\rightarrow
l\nu$ with polarized $W$'s are presented. Planned accelerators will produce
enough $W$'s for observation of the Standard Model contributions to this
polarization. One loop corrections to the polarization are given; these are too
small to be seen at presently available $W$ sources. The exchange of Majorons
will contribute to these polarizations; these may provide limits on the
couplings of these particles to leptons.


  An analytical expression is obtained for the mass of an isolated magnetic
skyrmion and its linearized equation of motion. The magnetic skyrmion is viewed
as a topologically protected spin-wave soliton in the magnetic ultrathin films
stabilized by the interfacial-Dzyaloshinskii-Moriya interaction. The equations
of motion are derived from the Landau-Lifshitz-Gilbert equation for both the
skyrmion charge and magnetization centers. They are generalized Thiele
equations, including the gyro-term, dissipation term, external force,
acceleration term with the tensorial mass, and time derivatives of the external
forces. The equation of motion of the center of the skyrmion charge essentially
shows the massless nature of the skyrmion. In contrast, the equation of motion
for the magnetization center results in a finite mass that is in the same order
as the Doring mass density for the linear domain wall. Furthermore, the time
derivative of the external force predominantly contributes to the immediate
response of the skyrmion motion, i.e., the mass-less property remains even
after the skyrmion acquires its kinetic mass.
  A micromagnetic simulation based on the LLG equation was performed for
various magnetic parameters. Obtained trajectories at 0 K are compared with the
theoretical predictions.


  This paper describes the operation of the Coherent CAPTAIN-Mills (CCM)
detector located at the Lujan Neutron Science Center (LANSCE) at Los Alamos
National Laboratory (LANL). CCM is a 10-ton liquid argon (LAr) detector located
20 meters from a high flux neutron/neutrino source and is designed to search
for sterile neutrinos ($\nu_s$) and light dark matter (LDM). An engineering run
was performed in Fall 2019 to study the characteristics of the CCM120 detector
by searching for coherent scattering signals consistent with $\nu_s$'s and LDM
resulting from $\pi^+$ and $\pi^0$ decays in the tungsten target. New parameter
space in a leptophobic dark matter model was excluded for DM masses between
$\sim2.0$ and 30 MeV. The lessons learned from this run have guided the
development and construction of the new CCM200 detector that will begin
operations in 2021 and significantly improve on these searches.


  Many exoplanetary systems containing hot Jupiters are observed to have highly
misaligned orbital axes relative to the stellar spin axes. Kozai-Lidov
oscillations of orbital eccentricity/inclination induced by a binary companion,
in conjunction with tidal dissipation, is a major channel for the production of
hot Jupiters. We demonstrate that gravitational interaction between the planet
and its oblate host star can lead to chaotic evolution of the stellar spin axis
during Kozai cycles. As parameters such as the planet mass and stellar rotation
period vary, periodic islands can appear in an ocean of chaos, in a manner
reminiscent of other dynamical systems. In the presence of tidal dissipation,
the complex spin evolution can leave an imprint on the final spin-orbit
misalignment angles.


  UV/IR mixing is one of the most important features of noncommutative field
theories. As a consequence of this coupling of the UV and IR sectors, the
configuration of fields at the zero momentum limit in these theories is a very
singular configuration. We show that the renormalization conditions set at a
particular momentum configuration with a fixed number of zero momenta,
renormalizes the Green's functions for any general momenta only when this
configuration has same set of zero momenta. Therefore only when renormalization
conditions are set at a point where all the external momenta are nonzero, the
quantum theory is renormalizable for all values of nonzero momentum. This
arises as a result of different scaling behaviors of Green's functions with
respect to the UV cutoff ($\Lambda$) for configurations containing different
set of zero momenta. We study this in the noncommutative $\phi^4$ theory and
analyse similar results for the Gross-Neveu model at one loop level. We next
show this general feature using Wilsonian RG of Polchinski in the globally O(N)
symmetric scalar theory and prove the renormalizability of the theory to all
orders with an infrared cutoff. In the context of spontaneous symmetry breaking
(SSB) in noncommutative scalar theory, it is essential to note the different
scaling behaviors of Green's functions with respect to $\Lambda$ for different
set of zero momenta configurations. We show that in the broken phase of the
theory the Ward identities are satisfied to all orders only when one keeps an
infrared regulator by shifting to a nonconstant vacuum.


  We consider the isometric deformation problem for oriented non simply
connected immersed minimal surfaces $f:M \to S^{4}$. We prove that the space of
all isometric minimal immersions of $M$ into $S^{4}$ with the same normal
curvature function is, within congruences, either finite or a circle.
  Furthermore, we show that for any compact immersed minimal surface in $S^{4}$
with nontrivial normal bundle there are at most finitely many noncongruent
immersed minimal surfaces in $S^{4}$ isometric to it with the same normal
curvature function.


  The detection of gravitational waves from mergers of tens of Solar mass black
hole binaries has led to a surge in interest in Primordial Black Holes (PBHs)
as a dark matter candidate. We aim to provide a (relatively) concise overview
of the status of PBHs as a dark matter candidate, circa Summer 2020. First we
review the formation of PBHs in the early Universe, focusing mainly on PBHs
formed via the collapse of large density perturbations generated by inflation.
Then we review the various current and future constraints on the present day
abundance of PBHs. We conclude with a discussion of the key open questions in
this field.


  We report on the first simultaneous observations that cover the optical,
X-ray, and high energy gamma-ray bands of the BL Lac object PKS 2155-304. The
gamma-ray bands were observed for 11 days, between 25 August and 6 September
2008, jointly with the Fermi Gamma-ray Space Telescope and the H.E.S.S.
atmospheric Cherenkov array, providing the first simultaneous MeV-TeV spectral
energy distribution with the new generation of gamma-ray telescopes. The ATOM
telescope and the RXTE and Swift observatories provided optical and X-ray
coverage of the low-energy component over the same time period. The object was
close to the lowest archival X-ray and Very High Energy state, whereas the
optical flux was much higher. The light curves show relatively little (~30%$)
variability overall when compared to past flaring episodes, but we find a clear
optical/VHE correlation and evidence for a correlation of the X-rays with the
high energy spectral index. Contrary to previous observations in the flaring
state, we do not find any correlation between the X-ray and VHE components.
Although synchrotron self-Compton models are often invoked to explain the SEDs
of BL Lac objects, the most common versions of these models are at odds with
the correlated variability we find in the various bands for PKS 2155-304.


  Consider an insurance company for which the reserve process follows the
Sparre Anderson model. In this paper, we study the optimal dividend problem for
such a company as Bai, Ma and Xing [9] do. However, we remove the constant
restriction on the dividend rates, i.e. the optimization problem is of singular
type. In this case, the value function is no longer bounded and the associated
HJB equation is a variational inequality involving a first order
integro-differential operator and a gradient constraint. We use other
techniques to prove the regularity properties for the value function and show
that the value function is a constrained viscosity solution of the associated
HJB equation. In addition, we show that the value function is the upper
semi-continuous envelop of the supremum for a class of subsolutions.


  The integration of wireless communication and radar sensing is gaining the
interest of researchers from wireless communication and radar societies.
Sensing in Integrated Communication and Sensing (ICAS) systems differs from the
traditional radar system in the configuration of transmitter-target-receiver,
the operating frequency bands, and the transmitting waveform. It is necessary
to understand how target electromagnetic signatures behave in this context.
Therefore, this paper presents measurements and analysis of two important
target signatures, reflectivity and micro-Doppler, for sensing in ICAS. These
target signatures are measured in the state-of-the-art measurement system,
Bistatische-Radar-Messeinrichtung (BiRa).