  Focusing on four types of correlation plots, $R_{\rm AA}$ vs. $v_2$, $R_{\rm
AA}$ vs. $I_{\rm AA}$, $I_{\rm AA}$ vs. $v_2^{I_{\rm AA}}$ and $v_2$ vs.\
$v_2^{I_{\rm AA}}$, we demonstrate how the centrality dependence of
\emph{correlations} between multiple jet quenching observables provide valuable
insight into the energy loss mechanism in a quark-gluon plasma. In particular
we find that a qualitative energy loss model gives a good description of
$R_{\rm AA}$ vs.\ $v_2$ only when we take $\Delta E\sim l^3$ and a medium
geometry generated by a model of the Color Glass Condensate. This same $\Delta
E\sim l^3$ model also qualitatively describes the trigger $p_T$ dependence of
$R_{\rm AA}$ vs.\ $I_{\rm AA}$ data and makes novel predictions for the
centrality dependence for this $R_{\rm AA}$ vs.\ $I_{\rm AA}$ correlation.
Current data suggests, albeit with extremely large uncertainty, that
$v_2^{I_{\rm AA}}\gg v_2$, a correlation that is difficult to reproduce in
current energy loss models.


  We describe a Bayesian formalism for analyzing individual gravitational-wave
events in light of the rest of an observed population. This analysis reveals
how the idea of a "population-informed prior" arises naturally from a suitable
marginalization of an underlying hierarchical Bayesian model which consistently
accounts for selection effects. Our formalism naturally leads to the presence
of "leave-one-out" distributions which include subsets of events. This differs
from other approximations, also known as empirical Bayes methods, which
effectively double count one or more events. We design a double-reweighting
post-processing strategy that uses only existing data products to reconstruct
the resulting population-informed posterior distributions. Although the
correction we highlight is an important conceptual point, we find it has a
limited impact on the current catalog of gravitational-wave events. Our
approach further allows us to study, for the first time in the
gravitational-wave literature, correlations between the parameters of
individual events and those of the population.


  Orthogonal Generalized Autoregressive Conditional Heteroskedasticity model
(OGARCH) is widely used in finance industry to produce volatility and
correlation forecasts. We show that the classic OGARCH model, nevertheless,
tends to be too slow in reflecting sudden changes in market condition due to
excessive persistence of the integral univariate GARCH processes. To obtain
more flexibility to accommodate abrupt market changes, e.g. financial crisis,
we extend classic OGARCH model by incorporating a two-state Markov
regime-switching GARCH process. This novel construction allows us to capture
recurrent systemic regime shifts. Empirical results show that this
generalization resolves the problem of excessive persistency effectively and
greatly enhances OGARCH's ability to adapt to sudden market breaks while
preserving OGARCH's most attractive features such as dimension reduction and
multi-step ahead forecasting. By constructing a global minimum variance
portfolio (GMVP), we are able to demonstrate significant outperformance of the
extended model over the classic OGARCH model and the commonly used
Exponentially Weighted Moving Average (EWMA) model. In addition, we show that
the extended model is superior to OGARCH and EWMA in terms of predictive
accuracy.


  We determine the quantum automorphism groups of finite spaces and find they
are all compact quantum groups in the sense of Woronowicz. This solves a
problem of Connes for finite spaces.


  While pre-training and fine-tuning, e.g., BERT~\citep{devlin2018bert},
GPT-2~\citep{radford2019language}, have achieved great success in language
understanding and generation tasks, the pre-trained models are usually too big
for online deployment in terms of both memory cost and inference speed, which
hinders them from practical online usage. In this paper, we propose LightPAFF,
a Lightweight Pre-training And Fine-tuning Framework that leverages two-stage
knowledge distillation to transfer knowledge from a big teacher model to a
lightweight student model in both pre-training and fine-tuning stages. In this
way the lightweight model can achieve similar accuracy as the big teacher
model, but with much fewer parameters and thus faster online inference speed.
LightPAFF can support different pre-training methods (such as BERT, GPT-2 and
MASS~\citep{song2019mass}) and be applied to many downstream tasks. Experiments
on three language understanding tasks, three language modeling tasks and three
sequence to sequence generation tasks demonstrate that while achieving similar
accuracy with the big BERT, GPT-2 and MASS models, LightPAFF reduces the model
size by nearly 5x and improves online inference speed by 5x-7x.


  Thueringer Landessternwarte Tautenburg (TLS) has started to operate a small
dedicated telescope - the Tautenburg Exoplanet Search Telescope (TEST) -
searching for transits of extrasolar planets in photometric time series
observations. In a joint effort with the Berlin Exoplanet Search Telescope
(BEST) operated by the Institut fuer Planetenforschung of the "Deutsches
Zentrum fuer Luft- und Raumfahrt (DLR)" at the Observatoire de Haute-Provence
(OHP), France, two observing sites are used to optimise transit search. Here,
we give a short overview of these systems and the data analysis. We describe a
software pipeline that we have set up to identify transit events of extrasolar
planets and variable stars in time series data from these and other telescopes,
and report on some first results.


  We show that if the Gabor system $\{ g(x-t) e^{2\pi i s x}\}$, $t \in T$, $s
\in S$, is an orthonormal basis in $L^2(\mathbb{R})$ and if the window function
$g$ is compactly supported, then both the time shift set $T$ and the frequency
shift set $S$ must be periodic. To prove this we establish a necessary
functional tiling type condition for Gabor orthonormal bases which may be of
independent interest.


  Chiral properties of QCD formulated with the domain-wall fermion (DWQCD) are
studied using the anomalous quark mass m_{5q} and the spectrum of the
4-dimensional Wilson-Dirac operator. Numerical simulations are made with the
standard plaquette gauge action and a renormalization-group improved gauge
action. Results are reported on the density of zero eigenvalue obtained with
the accumulation method, and a comparison is made with the results for m_{5q}.


  This paper establishes a remarkable result regarding Palmdistributions for a
log Gaussian Cox process: the reduced Palmdistribution for a log Gaussian Cox
process is itself a log Gaussian Coxprocess which only differs from the
original log Gaussian Cox processin the intensity function. This new result is
used to study functionalsummaries for log Gaussian Cox processes.


  We study the intermediate quantum groups $H_N\subset G\subset U_N^+$. The
basic examples are $H_N,K_N,O_N,U_N,H_N^+,K_N^+,O_N^+,U_N^+$, which form a
cube. Any other example $G$ sits inside the cube, and by using standard
operations, namely intersection $\cap$ and generation $<\,,>$, can be projected
on the faces and edges. We prove that under the strongest possible axioms,
namely (1) easiness, (2) uniformity, and (3) geometric coherence of the various
projection operations, the 8 basic solutions are the only ones.


  Several fundamental and closely interconnected issues related to factor
models are reviewed and discussed: dynamic versus static loadings, rate-strong
versus rate-weak factors, the concept of weakly common component recently
introduced by Gersing et al. (2023), the irrelevance of cross-sectional
ordering and the assumption of cross-sectional exchangeability, and the problem
of undetected strong factors.


  Exact and approximate expressions for thermodynamic characteristics of heated
matter, which consists of particles with finite mass-widths, are constructed.
They are expressed in terms of Fermi/Bose distributions and spectral functions,
rather than in terms of more complicated combinations between real and
imaginary parts of the self-energies of different particle species. Therefore
thermodynamically consistent approximate treatment of systems of particles with
finite mass-widths can be performed, provided spectral functions of particle
species are known. Approximation of the free resonance gas at low densities is
studied. Simple ansatz for the energy dependence of the spectral function is
suggested that allows to fulfill thermodynamical consistency conditions. On
examples it is shown that a simple description of dense systems of interacting
particle species can be constructed, provided some species can be treated in
the quasiparticle approximation and others as particles with widths. The
interaction affects quasiparticle contributions, whereas particles with widths
can be treated as free. Example is considered of a hot gas of heavy fermions
strongly interacting with light bosons, both species with zero chemical
potentials. The density of blurred fermions is dramatically increased for high
temperatures compared to the standard Boltzmann value. The system consists of
boson quasiparticles (with effective masses) interacting with fermion --
antifermion blurs. In thermodynamical values interaction terms partially
compensate each other. Thereby, in case of a very strong coupling between
species thermodynamical quantities of the system, like the energy, pressure and
entropy, prove to be such as for the quasi-ideal gas mixture of quasi-free
fermion blurs and quasi-free bosons.


  Let $G_1 \times G_2$ be a subgroup of $\mathrm{SO}_3(\mathbb{R})$ such that
the two factors $G_1$ and $G_2$ are non-trivial groups. We show that if $G_1
\times G_2$ is not abelian, then one factor is the (abelian) group of order 2,
and the other factor is non-abelian and contains an element of order 2. There
exist finite and infinite such non-abelian subgroups.


  We consider an M/M/N/K/FCFS system (N>0, K>=N), where the servers operate at
(possibly) heterogeneous service rates. In this situation, the steady state
behavior depends on the routing policy that is used to select which idle server
serves the next job in queue. We define a class of idle-time-order-based
policies (including, for example, Longest Idle Server First (LISF)) and show
that all policies in this class result in the same steady state behavior. In
particular, they are all equivalent to the naive Random routing policy.


  The development of artificial agents able to learn through dialog without
domain restrictions has the potential to allow machines to learn how to perform
tasks in a similar manner to humans and change how we relate to them. However,
research in this area is practically nonexistent. In this paper, we identify
the modifications required for a dialog system to be able to learn from the
dialog and propose generic approaches that can be used to implement those
modifications. More specifically, we discuss how knowledge can be extracted
from the dialog, used to update the agent's semantic network, and grounded in
action and observation. This way, we hope to raise awareness for this subject,
so that it can become a focus of research in the future.


  Quantified Boolean logic results from adding operators to Boolean logic for
existentially and universally quantifying variables. This extends the reach of
Boolean logic by enabling a variety of applications that have been explored
over the decades. The existential quantification of literals (variable states)
and its applications have also been studied in the literature. In this paper,
we complement this by studying universal literal quantification and its
applications, particularly to explainable AI. We also provide a novel semantics
for quantification, discuss the interplay between variable/literal and
existential/universal quantification. We further identify some classes of
Boolean formulas and circuits on which quantification can be done efficiently.
Literal quantification is more fine-grained than variable quantification as the
latter can be defined in terms of the former. This leads to a refinement of
quantified Boolean logic with literal quantification as its primitive.


  When is the composition of paraproducts bounded? This is an important, and
difficult question, related to to a question of Sarason on composition of
Hankel matrices, and the two-weight problem for the Hilbert transform. We
consider randomized variants of this question, finding non-classical
characterizations, for dyadic paraproducts.


  A hanging glacier at the east face of Weisshorn broke off in 2005. We were
able to monitor and measure surface motion and icequake activity for 21 days up
to three days prior to the break-off. Results are presented from the analysis
of seismic waves generated by the glacier during the rupture maturation
process. Three types of precursory signals of the imminent catastrophic rupture
were identified: (i) an increasing seismic activity within the glacier, (ii) a
change in the size-frequency distribution of icequake energy, and (iii) a
log-periodic oscillating behavior superimposed on power law acceleration of the
inverse of waiting time between two icequakes. The analysis of the seismic
activity gave indications of the rupture process and led to the identification
of two regimes: a stable one where events are isolated and non correlated which
is characteristic of diffuse damage, and an unstable and dangerous one in which
events become synchronized and large icequakes are triggered.


  We present a dataflow model for modelling parallel Unix shell pipelines. To
accurately capture the semantics of complex Unix pipelines, the dataflow model
is order-aware, i.e., the order in which a node in the dataflow graph consumes
inputs from different edges plays a central role in the semantics of the
computation and therefore in the resulting parallelization. We use this model
to capture the semantics of transformations that exploit data parallelism
available in Unix shell computations and prove their correctness. We
additionally formalize the translations from the Unix shell to the dataflow
model and from the dataflow model back to a parallel shell script. We implement
our model and transformations as the compiler and optimization passes of a
system parallelizing shell pipelines, and use it to evaluate the speedup
achieved on 47 pipelines.


  Neural architecture search enables automation of architecture design. Despite
its success, it is computationally costly and does not provide an insight on
how to design a desirable architecture. Here we propose a new way of searching
neural network where we search neural architecture by rewiring the
corresponding graph and predict the architecture performance by graph
properties. Because we do not perform machine learning over the entire graph
space and use predicted architecture performance to search architecture, the
searching process is remarkably efficient. We find graph based search can give
a reasonably good prediction of desirable architecture. In addition, we find
graph properties that are effective to predict architecture performance. Our
work proposes a new way of searching neural architecture and provides insights
on neural architecture design.


  SETI@home observes a 2.5 MHz bandwidth centered on 1420 MHz near the 21-cm
line using a short line feed at Arecibo which provides a 6' beam. This feed
sits on Carriage House 1. During normal astronomical observations with the new
Gregorian dome the feed scans across the sky at twice the sidereal rate. We are
using the SETI@home receiver to obtain about 4.4x10^6 HI spectra per year with
integration time of 5 seconds per spectrum. We have accumulated 2.6 years of
data covering most of the sky observable from Arecibo. This survey has much
better angular resolution than previous single dish surveys and better
sensitivity than existing or planned interferometric surveys.


  In the previous research by Grassl, Huber and Winter, they proved a theorem
which can make entanglement-assisted quantum error-correcting codes (EAQECC)
from general quantum error-correcting codes (QECC). In this paper, we prove
that the shortened EAQECC is a stabilizer code if the original EAQECC is a
stabilizer code.


  Recent experiments demonstrated that proton transport through graphene
electrodes can be accelerated by over an order of magnitude with low intensity
illumination. Here we show that this photo-effect can be suppressed for a
tuneable fraction of the infrared spectrum by applying a voltage bias. Using
photocurrent measurements and Raman spectroscopy, we show that such fraction
can be selected by tuning the Fermi energy of electrons in graphene with a
bias, a phenomenon controlled by Pauli blocking of photo-excited electrons.
These findings demonstrate a dependence between graphene's electronic and
proton transport properties and provide fundamental insights into molecularly
thin electrode-electrolyte interfaces and their interaction with light.


  Domain Generation Algorithms (DGAs) are used by adversaries to establish
Command and Control (C\&C) server communications during cyber attacks.
Blacklists of known/identified C\&C domains are often used as one of the
defense mechanisms. However, since blacklists are static and generated by
signature-based approaches, they can neither keep up nor detect
never-seen-before malicious domain names. Due to this shortcoming of blacklist
domain checking, machine learning algorithms have been used to address the
problem to some extent. However, when training is performed with limited
datasets, the algorithms are likely to fail in detecting new DGA variants. To
mitigate this weakness, we successfully applied a DGA-based malicious domain
classifier using the Long Short-Term Memory (LSTM) method with a novel feature
engineering technique. Our model's performance shows a higher level of accuracy
compared to a previously reported model from prior research. Additionally, we
propose a new method using adversarial machine learning to generate
never-before-seen malware-related domain families that can be used to
illustrate the shortcomings of machine learning algorithms in this regard.
Next, we augment the training dataset with new samples such that it makes
training of the machine learning models more effective in detecting
never-before-seen malicious domain name variants. Finally, to protect
blacklists of malicious domain names from disclosure and tampering, we devise
secure data containers that store blacklists and guarantee their protection
against adversarial access and modifications.


  The aim of this study is to carry out an abundance determination, to search
for spectral variability and for the presence of a weak magnetic field in the
typical PGa star HD19400. High-resolution, high signal-to-noise HARPS
spectropolarimetric observations of HD19400 were obtained at three different
epochs in 2011 and 2013. For the first time, we present abundances of various
elements determined using an ATLAS12 model, including the abundances of a
number of elements not analysed by previous studies, such as Ne I, Ga II, and
Xe II. Several lines of As II are also present in the spectra of HD19400. To
study the variability, we compared the behaviour of the line profiles of
various elements. We report on the first detection of anomalous shapes of line
profiles belonging to Mn and Hg, and the variability of the line profiles
belonging to the elements Hg, P, Mn, Fe, and Ga. We suggest that the
variability of the line profiles of these elements is caused by their
non-uniform surface distribution, similar to the presence of chemical spots
detected in HgMn stars. The search for the presence of a magnetic field was
carried out using the moment technique and the SVD method. Our measurements of
the magnetic field with the moment technique using 22 Mn II lines indicate the
potential existence of a weak variable longitudinal magnetic field on the first
epoch. The SVD method applied to the Mn II lines indicates <B_z>=-76+-25G on
the first epoch, and at the same epoch the SVD analysis of the observations
using the Fe II lines shows <B_z>=-91+-35G. The calculated false alarm
probability values, 0.008 and 0.003, respectively, are above the value 10^{-3},
indicating no detection.


  Any simulation of the r-process is affected by uncertainties in our present
knowledge of nuclear physics quantities and astrophysical conditions. It is
common to quantify the impact of these uncertainties through a global
sensitivity metric, which is then used to identify specific nuclides that would
be most worthwhile to measure experimentally. Using descriptive statistics, we
assess a set of metrics used in previous sensitivity studies, as well as a new
logarithmic measure. For certain neutron-rich nuclides lying near the r-process
path for the typical hot-wind scenario, we find opposing conclusions on their
relative sensitivity implied by different metrics, although they all generally
agree which ones are the most sensitive nuclei. The underlying reason is that
sensitivity metrics which simply sum over variations in the r-process
distribution depend on the scaling used in the baseline, which often varies
between simulations. We show that normalization of the abundances causes
changes in the reported sensitivity factors and recommend reporting a minimized
F statistic in addition to a scale estimation for rough calibration to be used
when comparing tables of sensitivity factors from different studies.


  We study the phase structure of the two-flavor Nambu--Jona-Lasinio (NJL)
model in the chiral limit, extending a previous study of the competition of an
inhomogeneous chiral phase and a two-flavor color-superconducting (2SC) phase
[1, 2]. There, an analytic expression for the dispersion relations for
quasiparticle excitations in the presence of both a particular inhomogeneous
chiral condensate, the so-called chiral density wave (CDW), and a homogeneous
2SC condensate was found. In this work we show how to determine the dispersion
relations for arbitrary modulations of the chiral condensate in the presence of
a homogeneous 2SC condensate, if the dispersion relations in the absence of
color superconductivity are known. In our calculations, we employ two different
Ans\"atze for the inhomogeneous chiral condensate, the CDW as well as the
real-kink crystal (RKC). Depending on the value of the diquark coupling we find
a region of the phase diagram where the inhomogeneous chiral and the 2SC
condensates coexist, confirming results of Refs. [1, 2]. Decreasing the diquark
coupling favors the inhomogeneous phase over the coexistence phase. On the
other hand, increasing the diquark coupling leads to a larger 2SC phase, while
the inhomogeneous chiral and the coexistence phases become smaller. In
agreement with previous studies the RKC Ansatz is energetically preferred over
the CDW Ansatz. Both Ans\"atze lead to a qualitatively similar phase diagram,
however the coexistence phase is smaller for the RKC Ansatz.


  The linear-quadratic (LQ) model to describe the survival of irradiated cells
may be the most frequently used biomathematical model in radiotherapy. There
has been an intense debate on the mechanistic origin of the LQ model. An
interesting approach is that of obtaining LQ-like behavior from kinetic models,
systems of differential equations that model the induction and repair of
damage. Development of such kinetic models is particularly interesting for
application to continuous dose rate therapies, such as molecular radiotherapy
or brachytherapy. In this work, we present a simple kinetic model that
describes the kinetics of populations of tumor cells, rather than
lethal/sub-lethal lesions, which may be especially useful for application to
continuous dose rate therapies, as in molecular radiotherapy. The
multi-compartment model consists of a set of three differential equations. The
model incorporates in an easy way different cross-interacting compartments of
cells forming a tumor, and may be of especial interest for studying dynamics of
treated tumors. In the fast dose delivery limit, the model can be analytically
solved, obtaining a simple closed-form expression. Fitting of several surviving
curves with both this solution and the LQ model shows that they produce similar
fits, despite being functionally different. We have also investigated the
operation of the model in the continuous dose rate scenario, firstly by fitting
pre-clinical data of tumor response to 131I-CLR1404 therapy, and secondly by
showing how damage repair and proliferation rates can cause a treatment to
achieve control or not. Kinetic models like the one presented in this work may
be of special interest when modeling response to molecular radiotherapy.


  If an active Janus particle is trapped at the interface between a liquid and
a fluid, its self-propelled motion along the interface is affected by a net
torque on the particle due to the viscosity contrast between the two adjacent
fluid phases. For a simple model of an active, spherical Janus colloid we
analyze the conditions under which translation occurs along the interface and
we provide estimates of the corresponding persistence length. We show that
under certain conditions the persistence length of such a particle is
significantly larger than the corresponding one in the bulk liquid, which is in
line with the trends observed in recent experimental studies.


  We present Monte Carlo calculations of the thermodynamics of the (2+1)
dimensional Thirring model at finite density. We bypass the sign problem by
deforming the domain of integration of the path integral into complex space in
such a way as to maximize the average sign within a parameterized family of
manifolds. We present results for lattice sizes up to $10^3$ and we find that
at high densities and/or temperatures the chiral condensate is abruptly
reduced.


  We calculate the two-point correlation function using the interpolating
current with $J^{PC}=2^{-}$. After performing the Borel sum rule analysis, the
extracted masses of the $2^{--}$ tensor charmonium and bottomonium are
$3.97\pm0.25$ GeV and $10.13\pm0.34$ GeV respectively. For comparison, we also
perform the moment sum rule analysis for the charmonium and bottomonium
systems. We extend the same analysis to study the $\bar qq, \bar qs, \bar ss,
\bar qc, \bar sc, \bar qb, \bar sb$ and $\bar cb$ systems. Their masses are
$1.78\pm 0.12, 1.85\pm 0.14, 2.00\pm 0.16, 2.86\pm 0.14, 3.01\pm 0.21,
5.66\pm0.33, 6.40\pm 0.25$, and $7.08\pm 0.34$ GeV respectively.


  Chemical composition is a good tracer of hydrodynamical processes that occur
in stars as they often lead to mixing and particle transport. By comparing
abundances predicted by models and those observed in stars we can infer some
constraints on those mixing processes. As pulsations in stars are often very
sensitive to chemical composition, we can use asteroseismology to probe the
internal chemical composition of stars where no direct observations are
possible. In this paper I focus on main sequence stars Am, lambda bootis, and
HgMn stars and discuss what we can learn of mixing processes in those stars
from seismology.


  Trapping and cooling techniques have become very important for many
fundamental experiments in atomic physics. When applied to highly charged ions
confined in Penning traps, these procedures are very effective for testing
quantum electrodynamics in extreme electromagnetic fields produced by heavy
highly charged ions such as uranium U$^{91+}$. In addition, fundamental
constants or nuclear ground state properties can be determined with high
accuracy in these simple systems. Finally, by studying a single trapped
radioactive ion, its nuclear decay can be studied in detail by observing the
disappearance of the signal of the mother and the appearance of that of the
daughter isotope. Such experiments on highly charged ions at extremely low
energy will become possible by the HITRAP facility which is currently being
built up at GSI. Also the future Facility for Antiproton and Ion Research
(FAIR) will be briefly described which is expected to be operational by 2014.


  For any sequences $\mathbf{u}=\{u(n)\}_{n\geq0},
\mathbf{v}=\{v(n)\}_{n\geq0},$ we define
$\mathbf{u}\mathbf{v}:=\{u(n)v(n)\}_{n\geq0}$ and
$\mathbf{u}+\mathbf{v}:=\{u(n)+v(n)\}_{n\geq0}$. Let $f_i(x)~(0\leq i< k)$ be
sequence polynomials whose coefficients are integer sequences. We say an
integer sequence $\mathbf{u}=\{u(n)\}_{n\geq0}$ is a polynomial generated
sequence if $$\{u(kn+i)\}_{n\geq0}=f_i(\mathbf{u}),~(0\leq i< k).$$ %Here we
define $\mathbf{u}\mathbf{v}:=\{u(n)v(n)\}_{n\geq0}$ and
$\mathbf{u}+\mathbf{v}:=\{u(n)+v(n)\}_{n\geq0}$ for any two sequences
$\mathbf{u}=\{u(n)\}_{n\geq0}, \mathbf{v}=\{v(n)\}_{n\geq0}.$
  In this paper, we study the polynomial generated sequences. Assume $k\geq2$
and $f_i(x)=\mathbf{a}_ix+\mathbf{b}_i~(0\leq i< k)$. If $\mathbf{a}_i$ are
$k$-automatic and $\mathbf{b}_i$ are $k$-regular for $0\leq i< k$, then we
prove that the corresponding polynomial generated sequences are $k$-regular. As
a application, we prove that the Hankel determinant sequence
$\{\det(p_{i+j})_{i,j=0}^{n-1}\}_{n\geq0}$ is $2$-regular, where
$\{p(n)\}_{n\geq0}=0110100010000\cdots$ is the characteristic sequence of
powers 2. Moreover, we give a answer of Cigler's conjecture about the Hankel
determinants.


  We present a study of the relationship between galactic kinematics, flare
rates, chromospheric activity, and rotation periods for a volume-complete,
nearly all-sky sample of 219 single stars within 15 parsecs and with masses
between 0.1$-$0.3 M$_{odot}l$ observed during the primary mission of TESS. We
find all stars are consistent with a common value of $\alpha$=1.984 $\pm$ 0.019
for the exponent of the flare frequency distribution. Using our measured
stellar radial velocities and Gaia astrometry, we determine galactic UVW space
motions. We find 64% of stars are members of the Galactic thin disk, 5% belong
to the thick disk, and for the remaining 31%, we cannot confidently assign
membership to either component. If we assume star formation has been constant
in the thin disk for the past 8 Gyr, then based on the fraction that we observe
to be active, we estimate the average age at which these stars transition from
the saturated to the unsaturated flaring regime to be 2.4 $\pm$ 0.3 Gyr. This
is consistent with the ages that we assign from galactic kinematics: We find
that stars with Prot $<$ 10 days have an age of 2.0 $\pm$ 1.2 Gyr, stars with
10 $<$ Prot $\leq$ 90 days have an age of 5.6 $\pm$ 2.7 Gyr, and stars with
Prot $>$ 90 days have an age of 12.9 $\pm$ 3.5 Gyr. We find that the average
age of stars with Prot $<$ 10 days increases with decreasing stellar mass from
0.6 $\pm$ 0.3 Gyr (0.2 - 0.3 M$_{odot}$) to 2.3 $\pm$ 1.3 Gyr (0.1--0.2
M$_{odot}l$).


  Clustering is an extensive research area in data science. The aim of
clustering is to discover groups and to identify interesting patterns in
datasets. Crisp (hard) clustering considers that each data point belongs to one
and only one cluster. However, it is inadequate as some data points may belong
to several clusters, as is the case in text categorization. Thus, we need more
flexible clustering. Fuzzy clustering methods, where each data point can belong
to several clusters, are an interesting alternative. Yet, seeding iterative
fuzzy algorithms to achieve high quality clustering is an issue. In this paper,
we propose a new linear and efficient initialization algorithm MaxMin Linear to
deal with this problem. Then, we validate our theoretical results through
extensive experiments on a variety of numerical real-world and artificial
datasets. We also test several validity indices, including a new validity index
that we propose, Transformed Standardized Fuzzy Difference (TSFD).


  Future long-baseline neutrino experiments will measure neutrino oscillation
properties with unprecedented precision and will search for clear signatures of
CP violation in the leptonic sector. Near detectors can measure the
neutrino-electron scattering with high statistics, giving the chance for its
precise measurement. We study, in this work, the expectations for the
measurement of radiative corrections in this process. We focus on the
determination of contributions that are exclusive to the neutrino channels,
particularly on the neutrino charge radius. We illustrate how the perspectives
in a first clear measurement of this effective quantity are encouraging.


  Bosonic boundary states at finite temperature are constructed as solutions of
boundary conditions at $T\neq 0$ for bosonic open strings with a constant gauge
field $F_{ab}$ coupled to the boundary. The construction is done in the
framework of thermo field dynamics where a thermal Bogoliubov transformation
maps states and operators to finite temperature. Boundary states are given in
terms of states from the direct product space between the Fock space of the
closed string and another identical copy of it. By analogy with zero
temperature, the boundary states heve the interpretation of $Dp$-brane at
finite temperature. The boundary conditions admit two different solutions. The
entropy of the closed string in a $Dp$-brane state is computed and analysed. It
is interpreted as the entropy of the $Dp$-brane at finite temperature.


  Inspired by the spin-inversion statistics of Schilling et al. and Haglund et
al., we relate the symmetry of ribbon functions to a result of van Leeuwen, and
also describe the multiplication of a domino function by a Schur function.


  A generalization of the Dirac field equation in three-dimensional Minkowski
space-time to the case of the $\bar{SL}(3,R)$ $\subset$ $\bar{SA}(3,R)$
symmetry is considered. Constraints that ensure a correct physical
interpretation of the corresponding particle states are presented. Dirac-like
equations based on both multiplicity-free and generic infinite-component
$\bar{SL}(3,R)$ representations are outlined.


  In this research paper, structured bi-matrix variate, matrix quadratic
equations are considered. Some lemmas related to determining the eigenvalues of
unknown matrices are proved. Also, a method of determining the diagonalizabe
unknown matrices is provided. The results are generalized to multi-matrix
variate, matrix polynomial equations. Briefly generalization to tensor variate
polynomial equations is discussed. It is hoped that the results lead to
important contributions in "non-commutative algebra".


  B. Green and T. Tao have recently proved that 'the set of primes contains
arbitrary long arithmetic progressions', answering to an old question with a
remarkably simple formulation. The proof does not use any "transcendental"
method and any of the deep theorems of analytic number theory. It is written in
a 'spirit' close to ergodic theory and in particular of Furstenberg's proof of
Szemer\'{e}di's Theorem, but it does not use any result of this theory.
Therefore the method can be considered as elementary, which does not mean easy.
We entend here to present the mains ideas of this proof.


  In this paper, we present VSCAN, a novel approach for generating static video
summaries. This approach is based on a modified DBSCAN clustering algorithm to
summarize the video content utilizing both color and texture features of the
video frames. The paper also introduces an enhanced evaluation method that
depends on color and texture features. Video Summaries generated by VSCAN are
compared with summaries generated by other approaches found in the literature
and those created by users. Experimental results indicate that the video
summaries generated by VSCAN have a higher quality than those generated by
other approaches.


  We present new additive results for the group invertibility in a ring. Then
we apply our results to block operator matrices over Banach spaces and derive
the existence of group inverses of $2\times 2$ block operator matrices. These
generalize many known results, e.g., Benitez, Liu and Zhu(Linear Multilinear
Algebra, {\bf 59}(2011), 279--289) and Zhou, Chen and Zhu(Comm. Algebra, {\bf
48}(2020),676-690).


  ${\rm W}^\pm {\rm W}^\pm {\rm H}$ production at hadron colliders through
vector boson scattering is a so far unconsidered process, which leads to a
clean signature of two same-sign charged leptons and two widely separated jets.
This process is sensitive to the ${\rm HHH}$ and ${\rm WWHH}$ couplings and any
deviation of these couplings from their SM predictions serves as direct
evidence of new physics beyond the SM. In this paper we perform a Monte Carlo
study of this process for the $\sqrt{s}=14$ TeV LHC and a $100$ TeV
pp-collider, and provide projections of the constraints on the triple-Higgs and
${\rm WWHH}$ quartic couplings for these environments. In particular, we
consider the impact of pileup on the expected sensitivity in this channel. Our
analysis demonstrates that although the sensitivity to the ${\rm HHH}$ coupling
is rather low, the ${\rm WWHH}$ coupling can be constrained in this channel
within $\sim 100\%$ and $\sim 20\%$ at 95\% confidence level around the SM
prediction at the HL-LHC and a 100 TeV pp-collider, respectively.


  The precise spectra of Cosmic Ray (CR) electrons and positrons have been
published by the measurement of AMS-02. It is reasonable to regard the
difference between the electrons and positrons spectra ( $\triangle \Phi=
\Phi_{e^-}-\Phi_{e^+}$ ) as being dominated by primary electrons. Noticing that
the resulting electron spectrum shows no sign of spectral softening above 20
GeV, which is in contrast with the prediction of standard model. In this work,
we generalize the analytic one dimensional two-halo model of diffusion to a
three dimensional realistic calculation by implementing a spatial variant
diffusion coefficients in DRAGON package. As a result, we can reproduce the
spectral hardening of protons observed by several experiments, and predict an
excess of high energy primary electrons which agrees with the measurement
reasonably well. Unlike the break spectrum obtained for protons, the model
calculation predicts a smooth electron excess and thus slightly over predicts
the flux from tens of GeV to 100GeV. To understand this issue, further
experimental and theoretical studies are necessary.


  We discuss a new formalism for light propagation which can be used within the
regime of validity of geometric optics, but with no limitation on the scales of
interest: from inside the Galaxy to the ultra-large scales of cosmology. One of
our main results is that within this framework it is possible to calculate all
relevant observables (image magnification, parallax, position drift or proper
motion) by simply differentiating the photon trajectory with respect to the
initial data. We then focus on a new observable, which we name the distance
slip: it is defined as the relative difference between the angular diameter
distance and the parallax distance. Its peculiarity lies in the fact that its
value is independent of the momentary motions of both the source and the
observer and that for short distances it shows a tomographic property, being
proportional to the amount of matter along the line of sight. After describing
further its properties and methods of measurement, we specialize our study of
the distance slip to cosmology. We show that it does not depend on the Hubble
constant H_0 and that its dependence on the other cosmological parameters is
different from other distance indicators. This suggests that the distance slip
may contain new information.


  We consider the problem of verifying deadlock freedom for symmetric cache
coherence protocols. In particular, we focus on a specific form of deadlock
which is useful for the cache coherence protocol domain and consistent with the
internal definition of deadlock in the Murphi model checker: we refer to this
deadlock as a system- wide deadlock (s-deadlock). In s-deadlock, the entire
system gets blocked and is unable to make any transition. Cache coherence
protocols consist of N symmetric cache agents, where N is an unbounded
parameter; thus the verification of s-deadlock freedom is naturally a
parameterized verification problem. Parametrized verification techniques work
by using sound abstractions to reduce the unbounded model to a bounded model.
Efficient abstractions which work well for industrial scale protocols typically
bound the model by replacing the state of most of the agents by an abstract
environment, while keeping just one or two agents as is. However, leveraging
such efficient abstractions becomes a challenge for s-deadlock: a violation of
s-deadlock is a state in which the transitions of all of the unbounded number
of agents cannot occur and so a simple abstraction like the one above will not
preserve this violation. In this work we address this challenge by presenting a
technique which leverages high-level information about the protocols, in the
form of message sequence dia- grams referred to as flows, for constructing
invariants that are collectively stronger than s-deadlock. Efficient
abstractions can be constructed to verify these invariants. We successfully
verify the German and Flash protocols using our technique.


  Spider pulsars are compact binary systems composed of a millisecond pulsar
and a low-mass companion. Their X-ray emission - modulated on the orbital
period - is interpreted as synchrotron radiation from high-energy electrons
accelerated at the intrabinary shock. We perform global two-dimensional
particle-in-cell simulations of the intrabinary shock, assuming that the shock
wraps around the companion star. When the pulsar spin axis is nearly aligned
with the orbital angular momentum, we find that the magnetic energy of the
relativistic pulsar wind - composed of magnetic stripes of alternating field
polarity - efficiently converts to particle energy at the intrabinary shock,
via shock-driven reconnection. The highest energy particles accelerated by
reconnection can stream ahead of the shock and be further accelerated by the
upstream motional electric field. In the downstream, further energization is
governed by stochastic interactions with the plasmoids / magnetic islands
generated by reconnection. We also extend our earlier work (Cort\'es & Sironi
2022) by performing simulations that have a larger (and more realistic)
companion size and a more strongly magnetized pulsar wind. We confirm that our
first-principles synchrotron spectra and lightcurves are in good agreement with
X-ray observations.


  An integer distance digraph is the Cayley graph $\Gamma(\mathbb{Z},S)$ of the
additive group $\mathbb{Z}$ of all integers with respect to a finite subset
$S\subseteq\mathbb{Z}$. The domination ratio of $\Gamma(\mathbb{Z},S)$, defined
as the minimum density of its dominating sets, is related to some number theory
problems, such as tiling the integers and finding the maximum density of a set
of integers with missing differences. We precisely determine the domination
ratio of the integer distance graph $\Gamma(\mathbb{Z},\{1,2,\ldots,d-2,s\})$
for any integers $d$ and $s$ satisfying $d\ge2$ and $s\notin[0,d-2]$. Our
result generalizes a previous result on the domination ratio of the graph
$\Gamma(\mathbb{Z},\{1,s\})$ with $s\in\mathbb{Z}\setminus\{0,1\}$ and also
implies the domination number of certain circulant graphs
$\Gamma(\mathbb{Z}_n,S)$, where $\mathbb{Z}_n$ is the finite cyclic group of
integers modulo $n$ and $S$ is a subset of $\mathbb{Z}_n$.


  Let $\mathcal{C}$ be a finitely bicomplete category and $\mathcal{W}$ a
subcategory. We prove that the existence of a model structure on $\mathcal{C}$
with $\mathcal{W}$ as subcategory of weak equivalence is not first order
expressible. Along the way we characterize all model structures where
$\mathcal{C}$ is a partial order and show that these are determined by the
homotopy categories.


  Visual target navigation in unknown environments is a crucial problem in
robotics. Despite extensive investigation of classical and learning-based
approaches in the past, robots lack common-sense knowledge about household
objects and layouts. Prior state-of-the-art approaches to this task rely on
learning the priors during the training and typically require significant
expensive resources and time for learning. To address this, we propose a new
framework for visual target navigation that leverages Large Language Models
(LLM) to impart common sense for object searching. Specifically, we introduce
two paradigms: (i) zero-shot and (ii) feed-forward approaches that use language
to find the relevant frontier from the semantic map as a long-term goal and
explore the environment efficiently. Our analysis demonstrates the notable
zero-shot generalization and transfer capabilities from the use of language.
Experiments on Gibson and Habitat-Matterport 3D (HM3D) demonstrate that the
proposed framework significantly outperforms existing map-based methods in
terms of success rate and generalization. Ablation analysis also indicates that
the common-sense knowledge from the language model leads to more efficient
semantic exploration. Finally, we provide a real robot experiment to verify the
applicability of our framework in real-world scenarios. The supplementary video
and code can be accessed via the following link:
https://sites.google.com/view/l3mvn.


  The transition to Euclidean space and the discretization of quantum field
theories on spatial or space-time lattices opens up the opportunity to
investigate probabilistic machine learning within quantum field theory. Here,
we will discuss how discretized Euclidean field theories, such as the
$\phi^{4}$ lattice field theory on a square lattice, are mathematically
equivalent to Markov fields, a notable class of probabilistic graphical models
with applications in a variety of research areas, including machine learning.
The results are established based on the Hammersley-Clifford theorem. We will
then derive neural networks from quantum field theories and discuss
applications pertinent to the minimization of the Kullback-Leibler divergence
for the probability distribution of the $\phi^{4}$ machine learning algorithms
and other probability distributions.


  In this paper, we describe a robust algorithm for 2-Manifold generation of
various kinds of ShapeNet Models. The input of our pipeline is a triangle mesh,
with a set of vertices and triangular faces. The output of our pipeline is a
2-Manifold with vertices roughly uniformly distributed on the geometry surface.
Our algorithm uses an octree to represent the original mesh, and construct the
surface by isosurface extraction. Finally, we project the vertices to the
original mesh to achieve high precision. As a result, our method can be adopted
efficiently to all ShapeNet models with the guarantee of correct 2-Manifold
topology.


  We study the Coulomb branch of class $\mathcal{S}_k$ $\mathcal{N} = 1$ SCFTs
by constructing and analyzing their spectral curves.


  In this paper, we study and predict the charged-particle pseudorapidity
multiplicity density ($\frac{dN_{ch}}{d\eta}$), transverse momentum spectra of
identified particles and their ratios in relativistic heavy ion collisions at
the Large Hadron Collider (LHC), using the string-melting version of a
multi-phase transport (AMPT) model with improved quark coalescence method.
Results of the charged-particle pseudorapidity multiplicity density from AMPT
model calculations for Pb+Pb collisions at $\sqrt{s_{NN}}=5.02$ TeV are
compared with the experimental data. Good agreements are generally found
between theoretical calculations and experimental data. We predict
$\frac{dN_{ch}}{d\eta}$ for Xe+Xe collisions at $\sqrt{s_{NN}}=5.44$ TeV at
different centralities, and $p_T$ spectra of charged pions, kaons and protons,
and their ratios $K/\pi$ and $p/\pi$ in Pb+Pb collisions at
$\sqrt{s_{NN}}=5.02$ TeV and Xe+Xe collisions at $\sqrt{s_{NN}}=5.44$ TeV that
are being studied at LHC. The $p_T$ spectra of identified particles in Pb+Pb
collisions from the improved AMPT model are compared and found to be consistent
with results from the iEBE-VISHNU hybrid model with TRENTo initial condition.


  Traditional data quality control methods are based on users experience or
previously established business rules, and this limits performance in addition
to being a very time consuming process with lower than desirable accuracy.
Utilizing deep learning, we can leverage computing resources and advanced
techniques to overcome these challenges and provide greater value to users. In
this paper, we, the authors, first review relevant works and discuss machine
learning techniques, tools, and statistical quality models. Second, we offer a
creative data quality framework based on deep learning and statistical model
algorithm for identifying data quality. Third, we use data involving salary
levels from an open dataset published by the state of Arkansas to demonstrate
how to identify outlier data and how to improve data quality via deep learning.
Finally, we discuss future work.


  We use joint observations by the Neil Gehrels Swift X-ray Telescope (XRT) and
the Fermi Large Area Telescope (LAT) of gamma-ray burst (GRB) afterglows to
investigate the nature of the long-lived high-energy emission observed by Fermi
LAT. Joint broadband spectral modeling of XRT and LAT data reveal that LAT
nondetections of bright X-ray afterglows are consistent with a cooling break in
the inferred electron synchrotron spectrum below the LAT and/or XRT energy
ranges. Such a break is sufficient to suppress the high-energy emission so as
to be below the LAT detection threshold. By contrast, LAT-detected bursts are
best fit by a synchrotron spectrum with a cooling break that lies either
between or above the XRT and LAT energy ranges. We speculate that the primary
difference between GRBs with LAT afterglow detections and the non-detected
population may be in the type of circumstellar environment in which these
bursts occur, with late-time LAT detections preferentially selecting GRBs that
occur in low wind-like circumburst density profiles. Furthermore, we find no
evidence of high-energy emission in the LAT-detected population significantly
in excess of the flux expected from the electron synchrotron spectrum fit to
the observed X-ray emission. The lack of excess emission at high energies could
be due to a shocked external medium in which the energy density in the magnetic
field is stronger than or comparable to that of the relativistic electrons
behind the shock, precluding the production of a dominant synchrotron
self-Compton (SSC) component in the LAT energy range. Alternatively, the peak
of the SSC emission could be beyond the 0.1-100 GeV energy range considered for
this analysis.


  Question Answering systems these days typically use template-based language
generation. Though adequate for a domain-specific task, these systems are too
restrictive and predefined for domain-independent systems. This paper proposes
a system that outputs a full-length answer given a question and the extracted
factoid answer (short spans such as named entities) as the input. Our system
uses constituency and dependency parse trees of questions. A transformer-based
Grammar Error Correction model GECToR (2020), is used as a post-processing step
for better fluency. We compare our system with (i) Modified Pointer Generator
(SOTA) and (ii) Fine-tuned DialoGPT for factoid questions. We also test our
approach on existential (yes-no) questions with better results. Our model
generates accurate and fluent answers than the state-of-the-art (SOTA)
approaches. The evaluation is done on NewsQA and SqUAD datasets with an
increment of 0.4 and 0.9 percentage points in ROUGE-1 score respectively. Also
the inference time is reduced by 85\% as compared to the SOTA. The improved
datasets used for our evaluation will be released as part of the research
contribution.


  Patients suffering from multiple diseases (multi-morbid patients) often have
complex clinical pathways. They are diagnosed and treated by different
specialties and undergo other clinical actions related to various diagnoses.
Coordination of care for these patients is often challenging, and it would be
of great benefit to get better insight into how the clinical pathways develop
in reality. Discovering these pathways using traditional process mining
techniques and standard event logs may be difficult because the patient is
involved in several highly independent clinical processes. Our objective is to
explore the potential of analyzing these pathways using an event log
representation reflecting the independent clinical processes. Our main research
question is: How can we identify valuable insights by using a multi-entity
event data representation for clinical pathways of multi-morbid patients? Our
method was built on the idea to represent multiple entities in event logs as
event graphs. The MIMIC-III data-set was used to evaluate the feasibility of
this approach. Several clinical entities were identified and then mapped into
an event graph. Finally, multi-entity directly follows graphs were discovered
by querying the event graph visualizing them. Our result shows that paths
involving multiple entities include traditional process mining concepts not for
one clinical process but all involved processes. In addition, the relationship
between activities of different clinical processes, which was not recognizable
in traditional models, is visible in the event graph representation.


  We assume that the generalized resolvent for a bounded linear operator pencil
mapping one Banach space onto another has an isolated essential singularity at
the origin and is analytic on some annular region of the complex plane centred
at the origin. In such cases the resolvent operator can be represented on the
annulus by a convergent Laurent series and the spectral set has two
components---a bounded component inside the inner boundary of the annulus and
an unbounded component outside the outer boundary. In this paper we prove that
the complementary spectral separation projections on the domain space are
uniquely determined by the respective generating subspaces for the associated
infinite-length generalized Jordan chains of vectors and that the domain space
is the direct sum of these two subspaces. We show that the images of the
generating subspaces under the mapping defined by the pencil provide a
corresponding direct sum decomposition for the range space and that this is
simply the decomposition defined by the complementary spectral separation
projections on the range space. If the domain space has a Schauder basis we
show that the separated systems of fundamental equations are reduced to two
semi-infinite systems of matrix equations which can be solved recursively to
obtain a basic solution and thereby determine the Laurent series coefficients
for the resolvent operator on the given annular region.


  Supermassive black holes have been discovered at the centers of galaxies, and
also in globular clusters. The data shows correlations between the black hole
mass and the elliptical galaxy mass or globular cluster mass. It is shown that
this correlation is accurately predicted by a theory of gravity which includes
the new dynamics of self-interacting space. In spiral galaxies this dynamics is
shown to explain the so-called `dark matter' rotation-curve anomaly, and also
explains the earth based bore-hole g anomaly data. Together these effects imply
that the strength of the self-interaction dynamics is determined by the fine
structure constant. This has major implications for fundamental physics and
cosmology.


  Smoke segmentation is essential to precisely localize wildfire so that it can
be extinguished in an early phase. Although deep neural networks have achieved
promising results on image segmentation tasks, they are prone to be
overconfident for smoke segmentation due to its non-rigid shape and transparent
appearance. This is caused by both knowledge level uncertainty due to limited
training data for accurate smoke segmentation and labeling level uncertainty
representing the difficulty in labeling ground-truth. To effectively model the
two types of uncertainty, we introduce a Bayesian generative model to
simultaneously estimate the posterior distribution of model parameters and its
predictions. Further, smoke images suffer from low contrast and ambiguity,
inspired by physics-based image dehazing methods, we design a
transmission-guided local coherence loss to guide the network to learn
pair-wise relationships based on pixel distance and the transmission feature.
To promote the development of this field, we also contribute a high-quality
smoke segmentation dataset, SMOKE5K, consisting of 1,400 real and 4,000
synthetic images with pixel-wise annotation. Experimental results on benchmark
testing datasets illustrate that our model achieves both accurate predictions
and reliable uncertainty maps representing model ignorance about its
prediction. Our code and dataset are publicly available at:
https://github.com/redlessme/Transmission-BVM.


  For general off-shell N=2 supergravity-matter systems in three spacetime
dimensions, a formalism is developed to reduce the corresponding actions from
superspace to components. The component actions are explicitly computed in the
cases of Type I and Type II minimal supergravity formulations. We describe the
models for topologically massive supergravity which correspond to all the known
off-shell formulations for three-dimensional N=2 supergravity. We also present
a universal setting to construct supersymmetric backgrounds associated with
these off-shell supergravities.


  Reed conjectured that for every epsilon>0 and Delta there exists g such that
the fractional total chromatic number of a graph with maximum degree Delta and
girth at least g is at most Delta+1+epsilon. We prove the conjecture for
Delta=3 and for even Delta>=4 in the following stronger form: For each of these
values of Delta, there exists g such that the fractional total chromatic number
of any graph with maximum degree Delta and girth at least g is equal to
Delta+1.


  Distributed optimization has experienced a significant surge in interest due
to its wide-ranging applications in distributed learning and adaptation. While
various scenarios, such as shared-memory, local-memory, and consensus-based
approaches, have been extensively studied in isolation, there remains a need
for further exploration of their interconnections. This paper specifically
concentrates on a scenario where agents collaborate toward a unified mission
while potentially having distinct tasks. Each agent's actions can potentially
impact other agents through interactions. Within this context, the objective
for the agents is to optimize their local parameters based on the aggregate of
local reward functions, where only local zeroth-order oracles are available.
Notably, the learning process is asynchronous, meaning that agents update and
query their zeroth-order oracles asynchronously while communicating with other
agents subject to bounded but possibly random communication delays. This paper
presents theoretical convergence analyses and establishes a convergence rate
for the proposed approach. Furthermore, it addresses the relevant issue of deep
learning-based resource allocation in communication networks and conducts
numerical experiments in which agents, acting as transmitters, collaboratively
train their individual (possibly unique) policies to maximize a common
performance metric.


  We calculate supernova electron capture and beta decay rates for various
pf-shell nuclei using large-scale shell model techniques. We show that the
centroid of the Gamow-Teller strength distribution has been systematically
misplaced in previous rate estimates. Our total electron capture rates are
significantly smaller than currently adopted in core collapse calculations,
while the total beta decay rates change less. Our calculation shows that for
electron-to-baryon ratios Ye=0.42-0.46 beta decay rates are larger than the
competing electron capture rates.


  Quantum phenomena of interest in connection with applications to computation
and communication almost always involve generating specific transfers between
eigenstates, and their linear superpositions. For some quantum systems, such as
spin systems, the quantum evolution equation (the Schr\"{o}dinger equation) is
finite-dimensional and old results on controllability of systems defined on on
Lie groups and quotient spaces provide most of what is needed insofar as
controllability of non-dissipative systems is concerned. However, in an
infinite-dimensional setting, controlling the evolution of quantum systems
often presents difficulties, both conceptual and technical. In this paper we
present a systematic approach to a class of such problems for which it is
possible to avoid some of the technical issues. In particular, we analyze
controllability for infinite-dimensional bilinear systems under assumptions
that make controllability possible using trajectories lying in a nested family
of pre-defined subspaces. This result, which we call the Finite Controllability
Theorem, provides a set of sufficient conditions for controllability in an
infinite-dimensional setting. We consider specific physical systems that are of
interest for quantum computing, and provide insights into the types of quantum
operations (gates) that may be developed.


  We reexamine the improved effective vector boson approximation which is based
on two-vector-boson luminosities $\mathrm{\mathbf{L}}_{\rm pol}$ for the
computation of weak gauge-boson hard scattering subprocesses $V_1 V_2\to {\cal
W}$ in high-energy hadron-hadron or $e^-e^+$ collisions. We calculate these
luminosities for the nine combinations of the transverse and longitudinal
polarizations of $V_1$ and $V_2$ in the unitary and axial gauge. For these two
gauge choices the quality of this approach is investigated for the reactions
$e^-e^+ \to W^- W^+ \nu_e {\bar\nu}_e$ and $e^-e^+ \to t {\bar t} \nu_e
{\bar\nu}_e$ using appropriate phase-space cuts.


  The predictions of Standard Model Higgs inflation are in excellent agreement
with the Planck data, without the need for new fields. However, consistency of
the theory requires the presence of (unknown) threshold corrections. These
modify the running of the couplings, and thereby change the shape of the
inflationary potential. This raises the question how sensitive the CMB
parameters are to the UV completion. We show that, due to a precise
cancellation, the inflationary predictions are almost unaffected. This implies
in general that one cannot relate the spectral index and tensor-to-scalar ratio
to the precise top and Higgs mass measurements at the LHC, nor can one probe
effects of UV physics on the running.


  We calculate the effective potential of the 2SC/g2SC phases including vector
condensates ($<gA_z^6>$ and $<gA_z^8>$) and study the gluonic phase and the
single plane-wave Larkin-Ovchinnikov-Fulde-Ferrell state at nonzero
temperature. Our analysis is performed within the framework of the gauged
Nambu--Jona-Lasinio model. We compute potential curvatures with respect to the
vector condensates and investigate the temperature dependence of the Meissner
masses squared of gluons of color 4--7 and 8 in the neutral 2SC/g2SC phases.
The phase diagram is presented in the plane of temperature and coupling
strength. The unstable regions for gluons 4--7 and 8 are mapped out on the
phase diagram. We find that, apart from the case of strong coupling, the
2SC/g2SC phases at low temperatures are unstable against the vector
condensation until the temperature reaches tens of MeV.


  We discuss how the vector nature of magnetic fields, and the geometrical
interpretation of gravity introduced by general relativity, lead to a special
coupling between magnetism and spacetime curvature. This magneto-geometrical
interaction effectively transfers the tension properties of the field into the
spacetime fabric, triggering a variety of effects with potentially far-reaching
implications.


  Measurements are reported of electromagnetic emission close to the cyclotron
frequency of energetic ions in JET plasmas heated by waves in the ion cyclotron
range of frequencies (ICRF). Hydrogen was the majority ion species in all of
these plasmas. The measurements were obtained using a sub-harmonic arc
detection (SHAD) system in the transmission lines of one of the ICRF antennas.
The measured ion cyclotron emission (ICE) spectra were strongly filtered by the
antenna system, and typically contained sub-structure, consisting of sets of
peaks with a separation of a few kHz, suggesting the excitation of
compressional Alfven eigenmodes (CAEs) closely spaced in frequency. In most
cases the energetic ions can be clearly identified as ICRF-accelerated He-3
minority ions, although in two pulses the emission may have been produced by
energetic He-4 ions, originating from third harmonic ICRF wave acceleration. It
is proposed that the emission close to the He-3 cyclotron frequency was
produced by energetic ions of this species undergoing drift orbit excursions to
the outer midplane plasma edge. Particle-in-cell and hybrid (kinetic ion, fluid
electron) simulations using plasma parameters corresponding to edge plasma
conditions in these JET pulses, and energetic particle parameters inferred from
the cyclotron resonance location, indicate strong excitation of waves at He-3
cyclotron harmonics, including the fundamental, which is identified with the
observed emission. These results underline the potential importance of ICE
measurements as a method of studying confined fast particles that are strongly
suprathermal but have insufficient energies or are not present in sufficient
numbers to excite detectable levels of gamma-ray emission or other collective
instabilities.


  A study is made of the power-law tail effect in the quantum particle
distribution over momentum on the nuclear fusion reactions. Our results do not
support the idea of averaging the fusion reaction cross-section over the
momentum distribution postulated and used in many publications.


  Momentum diffusion of the energetic charged particles is an important
mechanism of the transport process in astrophysics, physics of the fusion
devices, and laboratory plasmas. In addition to the uniform field momentum
diffusion, we obtain the modifying term due to the focusing effect of the
large-scale magnetic field. After evaluating the modifying term, we find that
it is determined by the sign of the focusing characteristic length and the
Fokker-Planck coefficients $D_{\mu\mu}$, $D_{\mu p}$, $D_{p\mu}$, and $D_{pp}$.
It is shown that we get a new second order acceleration mechanism in this work.


  Self-supervised learning (SSL) has gained widespread attention in the remote
sensing (RS) and earth observation (EO) communities owing to its ability to
learn task-agnostic representations without human-annotated labels.
Nevertheless, most existing RS SSL methods are limited to learning either
global semantic separable or local spatial perceptible representations. We
argue that this learning strategy is suboptimal in the realm of RS, since the
required representations for different RS downstream tasks are often varied and
complex. In this study, we proposed a unified SSL framework that is better
suited for RS images representation learning. The proposed SSL framework,
Contrastive Mask Image Distillation (CMID), is capable of learning
representations with both global semantic separability and local spatial
perceptibility by combining contrastive learning (CL) with masked image
modeling (MIM) in a self-distillation way. Furthermore, our CMID learning
framework is architecture-agnostic, which is compatible with both convolutional
neural networks (CNN) and vision transformers (ViT), allowing CMID to be easily
adapted to a variety of deep learning (DL) applications for RS understanding.
Comprehensive experiments have been carried out on four downstream tasks (i.e.
scene classification, semantic segmentation, object-detection, and change
detection) and the results show that models pre-trained using CMID achieve
better performance than other state-of-the-art SSL methods on multiple
downstream tasks. The code and pre-trained models will be made available at
https://github.com/NJU-LHRS/official-CMID to facilitate SSL research and speed
up the development of RS images DL applications.


  This paper introduces a new corpus of Mandarin-English code-switching speech
recognition--TALCS corpus, suitable for training and evaluating code-switching
speech recognition systems. TALCS corpus is derived from real online one-to-one
English teaching scenes in TAL education group, which contains roughly 587
hours of speech sampled at 16 kHz. To our best knowledge, TALCS corpus is the
largest well labeled Mandarin-English code-switching open source automatic
speech recognition (ASR) dataset in the world. In this paper, we will introduce
the recording procedure in detail, including audio capturing devices and corpus
environments. And the TALCS corpus is freely available for download under the
permissive license1. Using TALCS corpus, we conduct ASR experiments in two
popular speech recognition toolkits to make a baseline system, including ESPnet
and Wenet. The Mixture Error Rate (MER) performance in the two speech
recognition toolkits is compared in TALCS corpus. The experimental results
implies that the quality of audio recordings and transcriptions are promising
and the baseline system is workable.


  This paper compares the performance of a NN taking the output of a DCT
(Discrete Cosine Transform) of an image patch with leNet for classifying MNIST
hand written digits. The basis functions underlying the DCT bear a passing
resemblance to some of the learned basis function of the Visual Transformer but
are an order of magnitude faster to apply.


  We use the AdS/CFT correspondence to argue that large dyonic black holes in
anti-de Sitter spacetime are dual to stationary solutions of the equations of
relativistic magnetohydrodynamics on the conformal boundary of AdS. The dyonic
Kerr-Newman-AdS_4 solution corresponds to a charged diamagnetic fluid not
subject to any net Lorentz force, due to orthogonal magnetic and electric
fields compensating each other. The conserved charges, stress tensor and
R-current of the fluid are shown to be in exact agreement with the
corresponding quantities of the black hole. Furthermore, we obtain stationary
solutions of the Navier-Stokes equations in four dimensions, which yield
predictions for (yet to be constructed) charged rotating black strings in AdS_5
carrying nonvanishing momentum along the string. Finally, we consider
Scherk-Schwarz reduced AdS gravity on a circle. In this theory, large black
holes and black strings are dual to lumps of deconfined plasma of the
associated CFT. We analyze the effects that a magnetic field introduces in the
Rayleigh-Plateau instability of a plasma tube, which is holographically dual to
the Gregory-Laflamme instability of a magnetically charged black string.


  NeMo (Neural Modules) is a Python framework-agnostic toolkit for creating AI
applications through re-usability, abstraction, and composition. NeMo is built
around neural modules, conceptual blocks of neural networks that take typed
inputs and produce typed outputs. Such modules typically represent data layers,
encoders, decoders, language models, loss functions, or methods of combining
activations. NeMo makes it easy to combine and re-use these building blocks
while providing a level of semantic correctness checking via its neural type
system. The toolkit comes with extendable collections of pre-built modules for
automatic speech recognition and natural language processing. Furthermore, NeMo
provides built-in support for distributed training and mixed precision on
latest NVIDIA GPUs. NeMo is open-source https://github.com/NVIDIA/NeMo


  We study differentially private distributed optimization under communication
constraints. A server using SGD for optimization aggregates the client-side
local gradients for model updates using distributed mean estimation (DME). We
develop a communication-efficient private DME, using the recently developed
multi-message shuffled (MMS) privacy framework. We analyze our proposed DME
scheme to show that it achieves the order-optimal
privacy-communication-performance tradeoff resolving an open question in [1],
whether the shuffled models can improve the tradeoff obtained in Secure
Aggregation. This also resolves an open question on the optimal trade-off for
private vector sum in the MMS model. We achieve it through a novel privacy
mechanism that non-uniformly allocates privacy at different resolutions of the
local gradient vectors. These results are directly applied to give guarantees
on private distributed learning algorithms using this for private gradient
aggregation iteratively. We also numerically evaluate the private DME
algorithms.


  In this work we consider the existence and uniqueness of the ground state of
the regularized Hamiltonian of the Supermembrane in dimensions $D= 4,\,5,\,7$
and 11, or equivalently the $SU(N)$ Matrix Model. That is, the 0+1 reduction of
the 10-dimensional $SU(N)$ Super Yang-Mills Hamiltonian. This ground state
problem is associated with the solutions of the inner and outer Dirichlet
problems for this operator, and their subsequent smooth patching (glueing) into
a single state. We have discussed properties of the inner problem in a previous
work, therefore we now investigate the outer Dirichlet problem for the
Hamiltonian operator. We establish existence and uniqueness on unbounded
valleys defined in terms of the bosonic potential. These are precisely those
regions where the bosonic part of the potential is less than a given value
$V_0$, which we set to be arbitrary. The problem is well posed, since these
valleys are preserved by the action of the $SU(N)$ constraint. We first show
that their Lebesgue measure is finite, subject to restrictions on $D$ in terms
of $N$. We then use this analysis to determine a bound on the fermionic
potential which yields the coercive property of the energy form. It is from
this, that we derive the existence and uniqueness of the solution. As a
by-product of our argumentation, we show that the Hamiltonian, restricted to
the valleys, has spectrum purely discrete with finite multiplicity. Remarkably,
this is in contrast to the case of the unrestricted space, where it is well
known that the spectrum comprises a continuous segment. We discuss the relation
of our work with the general ground state problem and the question of
confinement in models with strong interactions.


  Results on two-particle angular correlations in jet cones and on multiplicity
fluctuations in one- and two- dimensional angular intervals, delivered by three
experiments (DELPHI, L3 and ZEUS, at $\sqrt{s}$ from few to 183 GeV) are
compared to present existing analytical QCD calculations, using the LPHD
hypothesis. Two different types of functions have been tested. While the
differentially normalized correlation functions show substantial deviations
from the predictions, a globally normalized correlation function agrees
surprisingly well. The role of the QCD parameters $\alpha_s$, $\Lambda$ and
$n_f$ is discussed. The necessity to include full energy-momentum conservation
into the analytical calculations is stressed.


  In this work, we have adopted gravitational decoupling by Minimal Geometric
Deformation (MGD) approach and have developed an anisotropic version of
well-known Tolman VII isotropic solution in the framework of $f(R, T)$ gravity,
where $R$ is Ricci scalar and $T$ is trace of energy momentum tensor. The set
of field equations has been developed with respect to total energy momentum
tensor, which combines effective energy momentum tensor in $f(R,T)$ gravity and
additional source $\phi_{ij}$. Following MGD approach, the set of field
equations has been separated into two sections. One section represents $f(R,
T)$ field equations, while the other is related to the source $\phi_{ij}$. The
matching conditions for inner and outer geometry have also been discussed and
an anisotropic solution has been developed using mimic constraint for radial
pressure. In order to check viability of the solution, we have considered
observation data of three different compact star models, named PSR J1614-2230,
PSR 1937+21 and SAX J1808.4-3658 and have discussed thermodynamical properties
analytically and graphically.
  The energy conditions are found to be satisfied for the three compact stars.
The stability analysis has been presented through causality condition and
Herrera's cracking concept, which ensures physical acceptability of the
solution.


  In Intelligence Analysis it is of vital importance to manage uncertainty.
Intelligence data is almost always uncertain and incomplete, making it
necessary to reason and taking decisions under uncertainty. One way to manage
the uncertainty in Intelligence Analysis is Dempster-Shafer Theory. This thesis
contains five results regarding multiple target tracks and intelligence
specification.


  We calculate the full spectrum, as observed today, of the cosmological
gravitational waves generated within a model based on loop quantum cosmology.
It is assumed that the universe, after the transition to the classical regime,
undergoes a period of inflation driven by a scalar field with a chaotic-type
potential. Our analysis shows that, for certain conditions, loop quantum
effects leave a clear signature on the spectrum, namely, an over-production of
low-frequency gravitational waves. One of the aims of our work is to show that
loop quantum cosmology models can be tested and that, more generally,
pre-inflationary physical processes, contrary to what is usually assumed, leave
their imprint in those spectra and can also be tested.


  This paper collects heuristics of Go Game and employs them to achieve
coverage of dense wireless sensor networks. In this paper, we propose an
algorithm based on Go heuristics and validate it. Investigations show that it
is very promising and could be seen as a good optimization. Keywords: Go
Heuristics, Wireless Sensor Networks, Coverage, Density


  Finding the common structural features of two molecules is a fundamental task
in cheminformatics. Most drugs are small molecules, which can naturally be
interpreted as graphs. Hence, the task is formalized as maximum common subgraph
problem. Albeit the vast majority of molecules yields outerplanar graphs this
problem remains NP-hard.
  We consider a variation of the problem of high practical relevance, where the
rings of molecules must not be broken, i.e., the block and bridge structure of
the input graphs must be retained by the common subgraph. We present an
algorithm for finding a maximum common connected induced subgraph of two given
outerplanar graphs subject to this constraint. Our approach runs in time
$\mathcal{O}(\Delta n^2)$ in outerplanar graphs on $n$ vertices with maximum
degree $\Delta$. This leads to a quadratic time complexity in molecular graphs,
which have bounded degree. The experimental comparison on synthetic and
real-world datasets shows that our approach is highly efficient in practice and
outperforms comparable state-of-the-art algorithms.


  We discuss the space $VPS(Q,H)$ of ideals with Hilbert function $H=(1,n,n,
\ldots)$ that are apolar to a full rank quadric $Q$. We prove that its
components of saturated ideals are closely related to the locus of Gorenstein
algebras and to the Slip component in border apolarity. We also point out an
important error in~[RS] and provide the necessary corrections.


  In this paper we study a nonlinear size-structured population model with
distributed delay in the recruitment. The delayed problem is reduced into an
abstract initial value problem of an ordinary differential equation in the
Banach space by using the delay semigroup techniques. The local existence and
uniqueness of solution as well as the continuous dependence on initial
conditions are obtained by using the general theory of quasi-linear evolution
equations in nonreflexive Banach spaces, while the global existence of solution
is obtained by the estimates of the solution and the extension theorem.


  Thomas Schelling developed an influential demographic model that illustrated
how, even with relatively mild assumptions on each individual's nearest
neighbor preferences, an integrated city would likely unravel to a segregated
city, even if all individuals prefer integration. Individuals in Schelling's
model cities are divided into two groups of equal number and each individual is
'happy' or 'unhappy' when the number of similar neighbors cross a simple
threshold. In this manuscript we consider natural extensions of Schelling's
original model to allow the two groups have different sizes and to allow
different notions of happiness of an individual. We observe that differences in
aggregation patterns of majority and minority groups are highly sensitive to
the happiness threshold; for low threshold, the differences are small, and when
the threshold is raised, striking new patterns emerge. We also observe that
when individuals strongly prefer to live integrated neighborhoods, the final
states exhibit a new tessellated-like structure.


  We recover the Tutte polynomial of a matroid, up to change of coordinates,
from an Ehrhart-style polynomial counting lattice points in the Minkowski sum
of its base polytope and scalings of simplices. Our polynomial has coefficients
of alternating sign with a combinatorial interpretation closely tied to the
Dawson partition. Our definition extends in a straightforward way to
polymatroids, and in this setting our polynomial has K\'alm\'an's internal and
external activity polynomials as its univariate specialisations.


  We present a study of the decays B+ -> rho+ gamma, B0 -> rho0 gamma, and B0
-> omega gamma. The analysis is based on data containing 347 million BBbar
events recorded with the BaBar detector at the PEP-II asymmetric B factory. We
measure the branching fractions BR(B+ -> rho+ gamma) = (1.10 +0.37/-0.33 +/-
0.09) x 10-6 and BR(B0 -> rho0 gamma) = (0.79 +0.22/-0.20 +/- 0.06) x 10-6, and
set a 90% C.L. upper limit BR(B0 -> omega gamma) < 0.78 x 10-6. We also measure
the isospin-averaged branching fraction BR(B->rho/omega gamma) = (1.25
+0.25/-0.24 +/- 0.09) x 10-6, from which we determine |Vtd/Vts| = 0.200
+0.021/-0.020 +/- 0.015, where the first uncertainty is experimental and the
second is theoretical.


  We report the discovery of a new class of low frequency quasi--periodic
variations of the X-ray flux in the X-ray bursters 4U1608-52 and 4U1636-536. We
also report an occasional detection of a similar QPO in Aql X-1. The QPOs,
associated with flux variations at the level of percents, are observed at a
frequency of 7-9 mHz. While usually the relative amplitude of flux variations
increases with energy, the newly discovered QPOs are limited to the softest
energies (1-5 keV). The observations of 4U1608-52 suggest that these QPOs are
present only when the source X-ray luminosity is within a rather narrow range
and they disappear after X-ray bursts. Approximately at the same level of the
source luminosity, type I X-ray bursts cease to exist.
  Judging from this complex of properties, we speculate that a special mode of
nuclear burning at the neutron star surface is responsible for the observed
flux variations. Alternatively, some instabilities in the accretion disk may be
responsible for these QPOs.


  While decentralized training is attractive in multi-agent reinforcement
learning (MARL) for its excellent scalability and robustness, its inherent
coordination challenges in collaborative tasks result in numerous interactions
for agents to learn good policies. To alleviate this problem, action advising
methods make experienced agents share their knowledge about what to do, while
less experienced agents strictly follow the received advice. However, this
method of sharing and utilizing knowledge may hinder the team's exploration of
better states, as agents can be unduly influenced by suboptimal or even adverse
advice, especially in the early stages of learning. Inspired by the fact that
humans can learn not only from the success but also from the failure of others,
this paper proposes a novel knowledge sharing framework called
Cautiously-Optimistic kNowledge Sharing (CONS). CONS enables each agent to
share both positive and negative knowledge and cautiously assimilate knowledge
from others, thereby enhancing the efficiency of early-stage exploration and
the agents' robustness to adverse advice. Moreover, considering the continuous
improvement of policies, agents value negative knowledge more in the early
stages of learning and shift their focus to positive knowledge in the later
stages. Our framework can be easily integrated into existing Q-learning based
methods without introducing additional training costs. We evaluate CONS in
several challenging multi-agent tasks and find it excels in environments where
optimal behavioral patterns are difficult to discover, surpassing the baselines
in terms of convergence rate and final performance.


  We report our investigation of the electronic and magnetic excitations of
Sr$_3$NiIrO$_6$ by resonant inelastic x-ray scattering at the Ir L$_3$ edge.
The intra-$t_{2g}$ electronic transitions are analyzed using an atomic model,
including spin-orbit coupling and trigonal distortion of the IrO$_6$
octahedron, confronted to {\it ab initio} quantum chemistry calculations. The
Ir spin-orbital entanglement is quantified and its implication on the magnetic
properties, in particular in inducing highly anisotropic magnetic interactions,
is highlighted. These are included in the spin-wave model proposed to account
for the dispersionless magnetic excitation that we observe at 90 meV. By
counterbalancing the strong Ni$^{2+}$ easy-plane anisotropy that manifests
itself at high temperature, the anisotropy of the interactions finally leads to
the remarkable easy-axis magnetism reported in this material at low
temperature.


  We show that the Thurston norm of any irreducible 3-manifold can be detected
using twisted Reidemeister torsions corresponding to integral representations
and also corresponding to representations over finite fields. In particular our
result holds for all graph manifolds, these are not covered by the earlier work
of the first author and Vidussi.


  Menon's identity is $\sum_{a \in A}^m (a-1,m) = d(m) \varphi(m)$, where $A$
is a reduced set of residues modulo $m$. This paper contains elementary proofs
of some generalizations of this result.


  A search is performed for the rare decay W$^\pm\to\pi^\pm\gamma$ in
proton-proton collisions at $\sqrt{s} =$ 13 TeV. Data corresponding to an on W
integrated luminosity of 137 fb$^{-1}$ were collected during 2016 to 2018 with
the CMS detector. This analysis exploits a novel search strategy based on W
boson production in top quark pair events. An inclusive search for the
W$^\pm\to\pi^\pm\gamma$ decay is not optimal at the LHC because of the high
trigger thresholds. Instead, a trigger selection is exploited in which the W
boson originating from one of the top quarks is used to tag the event in a
leptonic decay. The W boson emerging from the other top quark is used to search
for the W$^\pm\to\pi^\pm\gamma$ signature. Such decays are characterized by an
isolated track pointing to a large energy deposit, and by an isolated photon of
large transverse momentum. The presence of b quark jets reduces the background
from the hadronization of light-flavor quarks and gluons. The
W$^\pm\to\pi^\pm\gamma$ decay is not observed. An upper exclusion limit is set
to this branching fraction, corresponding to 1.50 $\times$ 10$^{-5}$ at 95%
confidence level, whereas the expected upper limit exclusion limit is 0.85
$^{+0.52}_{-0.29}$ $\times$ 10$^{-5}$.


  In this paper, a method is presented to synthesize neural network controllers
such that the feedback system of plant and controller is dissipative,
certifying performance requirements such as L2 gain bounds. The class of plants
considered is that of linear time-invariant (LTI) systems interconnected with
an uncertainty, including nonlinearities treated as an uncertainty for
convenience of analysis. The uncertainty of the plant and the nonlinearities of
the neural network are both described using integral quadratic constraints
(IQCs). First, a dissipativity condition is derived for uncertain LTI systems.
Second, this condition is used to construct a linear matrix inequality (LMI)
which can be used to synthesize neural network controllers. Finally, this
convex condition is used in a projection-based training method to synthesize
neural network controllers with dissipativity guarantees. Numerical examples on
an inverted pendulum and a flexible rod on a cart are provided to demonstrate
the effectiveness of this approach.


  In this paper, we study the Orienteering Aisle-graphs Single-access Problem
(OASP), a variant of the orienteering problem for a robot moving in a so-called
single-access aisle-graph, i.e., a graph consisting of a set of rows that can
be accessed from one side only. Aisle-graphs model, among others, vineyards or
warehouses. Each aisle-graph vertex is associated with a reward that a robot
obtains when visits the vertex itself. As the robot's energy is limited, only a
subset of vertices can be visited with a fully charged battery. The objective
is to maximize the total reward collected by the robot with a battery charge.
We first propose an optimal algorithm that solves OASP in O(m^2 n^2) time for
aisle-graphs with a single access consisting of m rows, each with n vertices.
With the goal of designing faster solutions, we propose four greedy sub-optimal
algorithms that run in at most O(mn (m+n)) time. For two of them, we guarantee
an approximation ratio of 1/2(1-1/e), where e is the base of the natural
logarithm, on the total reward by exploiting the well-known submodularity
property. Experimentally, we show that these algorithms collect more than 80%
of the optimal reward.


  We study the zero temperature BCS gaps for the triplet channel in pure
neutron matter using Similarity Renormalization Group (SRG) evolved
interactions. We use the dependence of the results on the SRG resolution scale,
as a tool to analyze medium and many-body corrections. In particular, we study
the effects of including the three-body interactions at leading order, which
appear at N2LO in the Chiral EFT, as well as that of the first-order
self-energy corrections on the zero temperature gap. In addition we also
extract the transition temperature as a function of densities and verify the
BCS scaling of the zero temperature gaps to the transition temperature. We
observe that the self-energy effects are very crucial in order to reduce the
SRG resolution scale dependence of the results, while the three-body effects at
the leading order do not change the two-body resolution scale dependence. On
the other hand, the results depend strongly on the three-body cut-off,
emphasizing the importance of the missing higher-order three-body effects. We
also observe that self-energy effects reduce the overall gap as well as shift
the gap closure to lower densities.


  As quantum technologies transition out of the research lab and into
commercial applications, it becomes important to better prepare students to
enter this new and evolving workforce. To work towards this goal of preparing
physics students for a career in the quantum industry, a senior capstone course
called "Quantum Forge" was created at the University of Colorado Boulder. This
course aims to provide students a hands-on quantum experience and prepare them
to enter the quantum workforce directly after their undergraduate studies. Some
of the course's goals are to have students understand what comprises the
quantum industry and have them feel confident they could enter the industry if
desired. To understand to what extent these goals are achieved, we followed the
first cohort of Quantum Forge students through their year in the course in
order to understand their perceptions of the quantum industry including what it
is, whether they feel that they could be successful in it, and whether or not
they want to participate in it. The results of this work can assist educators
in optimizing the design of future quantum-industry-focused courses and
programs to better prepare students to be a part of this burgeoning industry.


  The softening of a Gamma Ray Burst (GRB) afterglow bears remarkable
similarities to the frequency evolution in a sonic boom. At the front end of
the sonic boom cone, the frequency is infinite, much like a GRB. Inside the
cone, the frequency rapidly decreases to infrasonic ranges and the sound source
appears at two places at the same time, mimicking the double-lobed radio
sources. Although a "luminal" boom violates the Lorentz invariance and is
therefore forbidden, it is tempting to work out the details and compare them
with existing data. This temptation is further enhanced by the observed
superluminality in the celestial objects associated with radio sources and some
GRBs. In this article, we calculate the temporal and spatial variation of
observed frequencies from a hypothetical luminal boom and show remarkable
similarity between our calculations and current observations.


  We present a universal mechanism that, acting on any target qubit, propagates
it to the state it had T time units before the experiment started. This
protocol works by setting the target on a superposition of flight paths, where
it is acted on by uncharacterized, but repeatable, quantum operations.
Independently of the effect of each of these individual operations on the
target, the successful interference of the paths causes it to leap to its past
state. We prove that, for generic interaction effects, the system will reach
the desired state with probability 1 after some finite number of steps.


  Driven classical self-sustained oscillators have been studied extensively in
the context of synchronization. Using the master equation, this work considers
the classically driven generalized quantum Rayleigh-van der Pol oscillator,
which is characterized by linear dissipative gain and loss terms as well as
three non-linear dissipative terms. Since two of the non-linear terms break the
rotational phase space symmetry, the Wigner distribution of the quantum
mechanical limit cycle state of the undriven system is, in general, not
rotationally symmetric. The impact of the symmetry-breaking dissipators on the
long-time dynamics of the driven system are analyzed as functions of the drive
strength and detuning, covering the deep quantum to near-classical regimes.
Phase localization and frequency entrainment, which are required for
synchronization, are discussed in detail. We identify a large parameter space
where the oscillators exhibit appreciable phase localization but only weak or
no entrainment, indicating the absence of synchronization. Several observables
are found to exhibit the analog of the celebrated classical Arnold tongue; in
some cases, the Arnold tongue is found to be asymmetric with respect to
vanishing detuning between the external drive and the natural oscillator
frequency.


  A series of accurate ab initio calculations on Cu_pO-q finite clusters,
properly embedded on the Madelung potential of the infinite lattice, have been
performed in order to determine the local effective interactions in the CuO_2
planes of La_{2-x}Sr_xCuO_4 compounds. The values of the first-neighbor
interactions, magnetic coupling (J_{NN}=125 meV) and hopping integral
(t_{NN}=-555 meV), have been confirmed. Important additional effects are
evidenced, concerning essentially the second-neighbor hopping integral
t_{NNN}=+110meV, the displacement of a singlet toward an adjacent colinear
hole, h_{SD}^{abc}=-80 meV, a non-negligible hole-hole repulsion
V_{NN}-V_{NNN}=0.8 eV and a strong anisotropic effect of the presence of an
adjacent hole on the values of the first-neighbor interactions. The dependence
of J_{NN} and t_{NN} on the position of neighbor hole(s) has been rationalized
from the two-band model and checked from a series of additional ab initio
calculations. An extended t-J model Hamiltonian has been proposed on the basis
of these results. It is argued that the here-proposed three-body effects may
play a role in the charge/spin separation observed in these compounds, that is,
in the formation and dynamic of stripes.


  We propose a junction of metal and rare-earth compound semiconductor as the
basis for a possible efficient low-temperature thermoelectric device. If an
overlayer of rare earth atoms differing from the bulk is placed at the
interface, very high values of the figure of merit ZT can be reached at low
temperature. This is due to sharp variation of the transmission coefficient of
carriers across the junction at a narrow energy range, which is intrinsically
linked to the localized character of the overlayer f-orbital.


  Convolutional layers are the core building blocks of Convolutional Neural
Networks (CNNs). In this paper, we propose to augment a convolutional layer
with an additional depthwise convolution, where each input channel is convolved
with a different 2D kernel. The composition of the two convolutions constitutes
an over-parameterization, since it adds learnable parameters, while the
resulting linear operation can be expressed by a single convolution layer. We
refer to this depthwise over-parameterized convolutional layer as DO-Conv. We
show with extensive experiments that the mere replacement of conventional
convolutional layers with DO-Conv layers boosts the performance of CNNs on many
classical vision tasks, such as image classification, detection, and
segmentation. Moreover, in the inference phase, the depthwise convolution is
folded into the conventional convolution, reducing the computation to be
exactly equivalent to that of a convolutional layer without
over-parameterization. As DO-Conv introduces performance gains without
incurring any computational complexity increase for inference, we advocate it
as an alternative to the conventional convolutional layer. We open-source a
reference implementation of DO-Conv in Tensorflow, PyTorch and GluonCV at
https://github.com/yangyanli/DO-Conv.