  There is an incompatibility between the symmetries of causal structure in
relativity theory and the signaling abilities of probabilistic devices with
inputs and outputs: while time-reversal in relativity will not introduce the
ability to signal between spacelike separated regions, this is not the case for
probabilistic devices with space-like separated input-output pairs. We
explicitly describe a non-signaling device which becomes a perfect signaling
device under time-reversal, where time-reversal can be conceptualized as
playing backwards a videotape of an agent manipulating the device. This leads
to an arrow of time that is identifiable when studying the correlations of
events for spacelike separated regions. Somewhat surprisingly, although
time-reversal of Popuscu-Roerlich boxes also allows agents to signal, it does
not yield a perfect signaling device. Finally, we realize time-reversal using
post-selection, which could lead experimental implementation.


  This paper considers the reliability problem in energy-only markets.
Following widespread blackouts in 2011, Texas introduced a reliability price
incentive to attract two GW of net additional natural gas-generating capacity.
The incentive is unusual because energy buyers pay the incentive directly to
producers in a real-time spot market. The program has created $13 billion in
direct payments to generators annually since 2015 and is now being implemented
or considered in several major energy markets in the US and abroad. We assess
the incentive's impact on the Texas market from three perspectives: First, we
derive the incentive's equilibrium effect on the electricity price in a
monopolistic market from first principles using a standard partial equilibrium
economic model. We then empirically test whether the incentive encouraged net
entry into the market or the generating applicant pool, controlling for market
and climatic conditions using monthly capacity data. Finally, we look for
direct evidence of an incentive response among active traders using real-time
market trading data. The three approaches suggest buyers and producers cancel
out the incentive, and the price-only program does not encourage new generation
capacity to enter the market.


  Some results on the ordered statistics of eigenvalues for one-dimensional
random Schr\"odinger Hamiltonians are reviewed. In the case of supersymmetric
quantum mechanics with disorder, the existence of low energy delocalized states
induces eigenvalue correlations and makes the ordered statistics problem
nontrivial. The resulting distributions are used to analyze the problem of
classical diffusion in a random force field (Sinai problem) in the presence of
weakly concentrated absorbers. It is shown that the slowly decaying averaged
return probability of the Sinai problem, $\mean{P(x,t|x,0)}\sim \ln^{-2}t$, is
converted into a power law decay, $\mean{P(x,t|x,0)}\sim t^{-\sqrt{2\rho/g}}$,
where $g$ is the strength of the random force field and $\rho$ the density of
absorbers.


  The promise of Additive Manufacturing (AM) includes reduced transportation
and warehousing costs, reduction of source material waste, and reduced
environmental impact. AM is extremely useful for making prototypes and has
demonstrated the ability to manufacture complex parts not possible (or
prohibitively expensive) with conventional machining. Scientists and
manufactures are finding increased uses for AM in creation of all types of
finished products including those built from polymers, biological material, and
metals. Although companies such as GE have been using 3D printing for Additive
Manufacturing for over thirty years to make mandrels for light bulb
manufacturing, application areas of Additive Manufacturing have increased
substantially in recent years, particularly due to the reduction in cost of 3D
printers. Like most emergent technologies, there are bound to be growing pains
with AM. This paper looks at the software that supports AM and 3D printing and
their vulnerability to cyber-attacks, intellectual property theft, defect rates
of AM software (which can cause undesired consequences themselves and also
create vulnerabilities that a hacker may exploit), part reliability and safety
of devices incorporating 3D printed parts (when making mission critical parts),
and security/throughput issues of computer networks. Literature searches,
consulting with technical experts and a relatively new hazard analysis
technique will be used, one especially developed for software intensive systems
called Systemic Theoretic Process Analysis (STPA). The purpose of this white
paper is to identify risks (or hazards for mission critical parts) for AM in
this emergent stage so that mitigations can be applied before accidents occur.
A second purpose of this white paper is to evaluate the effectiveness of STPA
as a hazard analysis technique in a field that is still relatively new.


  We focus on a replanning scenario for quadrotors where considering time
efficiency, non-static initial state and dynamical feasibility is of great
significance. We propose a real-time B-spline based kinodynamic (RBK) search
algorithm, which transforms a position-only shortest path search (such as A*
and Dijkstra) into an efficient kinodynamic search, by exploring the properties
of B-spline parameterization. The RBK search is greedy and produces a
dynamically feasible time-parameterized trajectory efficiently, which
facilitates non-static initial state of the quadrotor. To cope with the
limitation of the greedy search and the discretization induced by a grid
structure, we adopt an elastic optimization (EO) approach as a
post-optimization process, to refine the control point placement provided by
the RBK search. The EO approach finds the optimal control point placement
inside an expanded elastic tube which represents the free space, by solving a
Quadratically Constrained Quadratic Programming (QCQP) problem. We design a
receding horizon replanner based on the local control property of B-spline. A
systematic comparison of our method against two state-of-the-art methods is
provided. We integrate our replanning system with a monocular vision-based
quadrotor and validate our performance onboard.


  The non-perturbative instabilities of hot Kaluza-Klein spacetime are
investigated. In addition to the known instability of hot space (the nucleation
of 4D black holes) and the known instability of KK space (the nucleation of
bubbles of nothing by quantum tunneling), we find two new instabilities: the
nucleation of 5D black holes, and the nucleation of bubbles of nothing by
thermal fluctuation. These four instabilities are controlled by two Euclidean
instantons, with each instanton doing double duty via two inequivalent analytic
continuations; thermodynamic instabilities of one are shown to be related to
mechanical instabilities of the other. I also construct bubbles of nothing that
are formed by a hybrid process involving both thermal fluctuation and quantum
tunneling. There is an exact high-temperature/low-temperature duality that
relates the nucleation of black holes to the nucleation of bubbles of nothing.


  The IceCube experiment has recently released 3 years of data of the first
ever detected high-energy (>30 TeV) neutrinos, which are consistent with an
extraterrestrial origin. In this talk, we compute the compatibility of the
observed track-to-shower ratio with possible combinations of neutrino flavors
with relative proportion (alpha_e:alpha_mu:alpha_tau). Although this
observation is naively favored for the canonical (1:1:1) at Earth, once we
consider the IceCube expectations for the atmospheric muon and neutrino
backgrounds, this flavor combination presents some tension with data. We find
that, for an astrophysical neutrino E_nu^{-2} energy spectrum, (1:1:1) at Earth
is currently disfavored at 92% C.L. We discuss the trend of this result by
comparing the results with the 2-year and 3-year data. We obtain the best-fit
for (1:0:0) at Earth, which cannot be achieved from any flavor ratio at sources
with averaged oscillations during propagation. Although it is not statistically
significant at present, if confirmed, this result would suggest either a
misunderstanding of the expected background events, or a misidentification of
tracks as showers, or even more compellingly, some exotic physics which
deviates from the standard scenario.


  In this paper, the event-triggered resilient filtering problem is
investigated for a class of two-dimensional systems with asynchronous-delay
under binary encoding-decoding schemes with probabilistic bit flips. To reduce
unnecessary communications and computations in complex network systems,
alleviate network energy consumption, and optimize the use of network
resources, a new event-triggered mechanism is proposed, which focuses on
broadcasting necessary measurement information to update innovation only when
the event generator function is satisfied. A binary encoding-decoding scheme is
used in the communication process to quantify the measurement information into
a bit stream, transmit it through a memoryless binary symmetric channel with a
certain probability of bit flipping, and restore it at the receiver. In order
to utilize the delayed decoded measurement information that a measurement
reconstruction approach is proposed. Through generating space equivalence
verification, it is found that the reconstructed delay-free decoded measurement
sequence contains the same information as the original delayed decoded
measurement sequence. In addition, resilient filter is utilized to accommodate
possible estimation gain perturbations. Then, a recursive estimator framework
is presented based on the reconstructed decoded measurement sequence. By means
of the mathematical induction technique, the unbiased property of the proposed
estimator is proved. The estimation gain is obtained by minimizing an upper
bound on the filtering error covariance. Subsequently, through rigorous
mathematical analysis, the monotonicity of filtering performance with respect
to triggering parameters is discussed.


  Denoising Diffusion Probabilistic Models have shown an impressive generation
quality, although their long sampling chain leads to high computational costs.
In this paper, we observe that a long sampling chain also leads to an error
accumulation phenomenon, which is similar to the exposure bias problem in
autoregressive text generation. Specifically, we note that there is a
discrepancy between training and testing, since the former is conditioned on
the ground truth samples, while the latter is conditioned on the previously
generated results. To alleviate this problem, we propose a very simple but
effective training regularization, consisting in perturbing the ground truth
samples to simulate the inference time prediction errors. We empirically show
that, without affecting the recall and precision, the proposed input
perturbation leads to a significant improvement in the sample quality while
reducing both the training and the inference times. For instance, on CelebA
64$\times$64, we achieve a new state-of-the-art FID score of 1.27, while saving
37.5% of the training time. The code is publicly available at
https://github.com/forever208/DDPM-IP


  We present a natural, combinatorial problem whose solution is given by the
meta-Fibonacci recurrence relation $a(n) = \sum_{i=1}^p a(n-i+1 - a(n-i))$,
where $p$ is prime. This combinatorial problem is less general than those given
in [3] (B. Jackson, F. Ruskey, 2006) and [4] (F. Ruskey, C. Deugau, 2009), but
it has the advantage of having a simpler statement.


  Anderson acceleration (AA) is an extrapolation technique designed to speed-up
fixed-point iterations like those arising from the iterative training of DL
models. Training DL models requires large datasets processed in randomly
sampled batches that tend to introduce in the fixed-point iteration stochastic
oscillations of amplitude roughly inversely proportional to the size of the
batch. These oscillations reduce and occasionally eliminate the positive effect
of AA. To restore AA's advantage, we combine it with an adaptive moving average
procedure that smoothes the oscillations and results in a more regular sequence
of gradient descent updates. By monitoring the relative standard deviation
between consecutive iterations, we also introduce a criterion to automatically
assess whether the moving average is needed. We applied the method to the
following DL instantiations: (i) multi-layer perceptrons (MLPs) trained on the
open-source graduate admissions dataset for regression, (ii) physics informed
neural networks (PINNs) trained on source data to solve 2d and 100d Burgers'
partial differential equations (PDEs), and (iii) ResNet50 trained on the
open-source ImageNet1k dataset for image classification. Numerical results
obtained using up to 1,536 NVIDIA V100 GPUs on the OLCF supercomputer Summit
showed the stabilizing effect of the moving average on AA for all the problems
above.


  Scintillating bolometers of ZnSe are the baseline choice of the LUCIFER
experiment, whose aim is to observe the neutrinoless double beta decay of 82Se.
The independent read-out of the heat and scintillation signals allows to
identify and reject alpha particle interactions, the dominant background source
for bolometric detectors. In this paper we report the performances of a ZnSe
crystal operated within the LUCIFER R&D. We measured the scintillation yield,
the energy resolution and the background in the energy region where the signal
from neutrinoless double beta decay of 82Se is expected with an exposure of 9.4
kg x days. With a newly developed analysis algorithm we improved the rejection
of alpha events, and we estimated the increase in energy resolution obtained by
the combination of the heat and light signals. For the first time we measured
the light emitted by nuclear recoils, and found it to be compatible with zero.
We conclude that the discrimination of nuclear recoils from beta/gamma
interactions in the WIMPs energy region is possible, but low-noise light
detectors are needed.


  Let $G$ be a Lie group and $H$ be a subgroup of it. We can construct a
bisimplicial manifold $NG(*) \rtimes NH(*)$ and the de Rham complex
$\Omega^*(NG(*) \rtimes NH(*))$ on it. This complex is a triple complex and the
cohomology of its total complex is isomorphic to $H^*(B(G \rtimes H))$. In this
paper, we show that the total complex of the double complex $\Omega^q(NG(*)
\rtimes NH(*))$ is isomorphic to the continuous cohomology $H_c^*(G \rtimes
H;S^q{\mathcal G}^* \otimes S^q{\mathcal H}^*)$ for any fixed $q$.


  In this paper, we study a weak law of large numbers for the total internal
length of the Bolthausen-Szmitman coalescent. As a consequence, we obtain the
weak limit law of the centered and rescaled total external length. The latter
extends results obtained by Dhersin & M\"ohle \cite{DM12}. An application to
population genetics dealing with the total number of mutations in the
genealogical tree is also given.


  In this work we recast parametrized time dependent optimal control problems
governed by partial differential equations in a saddle point formulation and we
propose reduced order methods as an effective strategy to solve them. Indeed,
on one hand parametrized time dependent optimal control is a very powerful
mathematical model which is able to describe several physical phenomena; on the
other hand, it requires a huge computational effort. Reduced order methods are
a suitable approach to have rapid and accurate simulations. We rely on
POD-Galerkin reduction over the physical and geometrical parameters of the
optimality system in a space-time formulation. Our theoretical results and our
methodology are tested on two examples: a boundary time dependent optimal
control for a Graetz flow and a distributed optimal control governed by time
dependent Stokes equations. With these two experiments the convenience of the
reduced order modelling is further extended to the field of time dependent
optimal control.


  The standard asset pricing models (the CCAPM and the Epstein-Zin non-expected
utility model) counterintuitively predict that equilibrium asset prices can
rise if the representative agent's risk aversion increases. If the income
effect, which implies enhanced saving as a result of an increase in risk
aversion, dominates the substitution effect, which causes the representative
agent to reallocate his portfolio in favour of riskless assets, the demand for
securities increases. Thus, asset prices are forced to rise when the
representative agent is more risk adverse. By disentangling risk aversion and
intertemporal substituability, we demonstrate that the risky asset price is an
increasing function of the coefficient of risk aversion only if the elasticity
of intertemporal substitution (EIS) exceeds unity. This result, which was first
proved par Epstein (1988) in a stationary economy setting with a constant risk
aversion, is shown to hold true for non-stationary economies with a variable or
constant risk aversion coefficient. The conclusion is that the EIS probably
exceeds unity.


  We derive data of 4615 star-forming early-type galaxies (ETGs), which come
from cross-match of the $Galaxy~Zoo~1$ and the catalogue of the MPA-JHU
emission-line measurements for the Sloan Digital Sky Survey Data Release 7. Our
sample distributes mainly at $\rm -0.7<log(SFR[M_{\sun}yr^{-1}])<1.2$, and the
median value of our SFRs is slightly higher than that shown in Davis \& Young.
We display a significant trend of lower/higher stellar mass ETGs to have
lower/higher SFR, and obtain our sample best fit of log(SFR)=$
(0.74\pm0.01)$log$(M_{*}/M_{\sun})-(7.64\pm0.10)$, finding the same slope as
that found in Cano-D\'{i}az et al. In our star-forming ETG sample, we
demonstrate clearly the correlation of the stellar mass and metallicity (MZ)
relation. We find that higher metallicity measurements may be introduced by the
diffuse ionized gas, when the D16, Sanch18, and Sander18 indicators are used to
calibrate the metallicity of ETGs. We show the relations between SFR and
12+log(O/H) with different metallicity estimators, and suggest that their
correlations may be a consequence of the SFR-stellar mass and MZ relations in
ETGs.


  We report the results of our theoretical study and analysis of earlier
experimental data for the g-factor tensor components of the ground
$^2\Pi_{1/2}$ state of free PbF radical. The values obtained both within the
relativistic coupled-cluster method combined with the generalized relativistic
effective core potential approach and with our fit of the experimental data
from [R.J. Mawhorter, B.S. Murphy, A.L. Baum, T.J. Sears, T. Yang, P.M.
Rupasinghe, C.P. McRaven, N.E. Shafer-Ray, L.D. Alphei, J.-U. Grabow, Phys.
Rev. A 84, 022508 (2011); A. Baum, B.S. thesis, Pomona College, 2011]. The
obtained results agree very well with each other but contradict the previous
fit performed in the cited works. Our final prediction for g-factors is
$G_{\parallel}= 0.081(5)$, $G_{\perp}=-0.27(1)$.


  Establishing hidden communication is an important subject of discussion that
has gained increasing importance nowadays with the development of the internet.
One of the key methods for establishing hidden communication is steganography.
Modern day steganography mainly deals with hiding information within files like
image, text, html, binary files etc. These file contains small irrelevant
information that can be substituted for small secret data. To store a high
capacity secret data these carrier files are not very supportive. To overcome
the problem of storing the high capacity secret data with the utmost security
fence, we have proposed a novel methodology for concealing a voluminous data
with high levels of security wall by using movie clip as a carrier file.


  Data from the Kepler satellite (Q0-Q11) are used to study HAT-P-7. The
satellite's data are extremely valuable for asteroseismic studies of stars and
for observing planetary transits; in this work we do both. An asteroseismic
study of the host star improves the accuracy of the stellar parameters derived
by Christensen-Dalsgaard et al. (2010), who followed largely the same procedure
but based the analysis on only one month of Kepler data. The stellar
information is combined with transit observations, phase variations and
occultations to derive planetary parameters. In particular, we confirm the
presence of ellipsoidal variations as discovered by Welsh et al. (2010), but
revise their magnitude, and we revise the occultation depth (Borucki et al.
2009), which leads to different planetary temperature estimates. All other
stellar and planetary parameters are now more accurately determined.


  We theoretically investigate the ground states and the spectrum of elementary
excitations across the superfluid to droplet crystallization transition of an
oblate dipolar Bose-Einstein condensate. We systematically identify regimes
where spontaneous rotational symmetry breaking leads to the emergence of a
supersolid phase with characteristic collective excitations, such as the Higgs
amplitude mode. Furthermore, we study the dynamics across the transition and
show how these supersolids can be realized with standard protocols in
state-of-the-art experiments.


  The privacy and security of face data on social media are facing
unprecedented challenges as it is vulnerable to unauthorized access and
identification. A common practice for solving this problem is to modify the
original data so that it could be protected from being recognized by malicious
face recognition (FR) systems. However, such ``adversarial examples'' obtained
by existing methods usually suffer from low transferability and poor image
quality, which severely limits the application of these methods in real-world
scenarios. In this paper, we propose a 3D-Aware Adversarial Makeup Generation
GAN (3DAM-GAN). which aims to improve the quality and transferability of
synthetic makeup for identity information concealing. Specifically, a UV-based
generator consisting of a novel Makeup Adjustment Module (MAM) and Makeup
Transfer Module (MTM) is designed to render realistic and robust makeup with
the aid of symmetric characteristics of human faces. Moreover, a makeup attack
mechanism with an ensemble training strategy is proposed to boost the
transferability of black-box models. Extensive experiment results on several
benchmark datasets demonstrate that 3DAM-GAN could effectively protect faces
against various FR models, including both publicly available state-of-the-art
models and commercial face verification APIs, such as Face++, Baidu and Aliyun.


  Here we report evidence of a large solar filament eruption on 2013, September
29. This smooth eruption, which passed without any previous flare, formed after
a two-ribbon flare and a coronal mass ejection towards Earth. The coronal mass
ejection generated a moderate geomagnetic storm on 2013, October 2 with very
serious localized effects. The whole event passed unnoticed to flare-warning
systems.
  We have conducted multi-wavelength analyses of the Solar Dynamics Observatory
through Atmospheric Imaging Assembly (AIA) and Helioseismic and Magnetic Imager
(HMI) data. The AIA data on 304, 193, 211, and 94 \AA sample the transition
region and the corona, respectively, while HMI provides photospheric
magnetograms, continuum, and linear polarization data, in addition to the fully
inverted data provided by HMI.
  [...]
  We have observed a supergranular-sized emergence close to a large filament in
the boundary of the active region NOAA11850. Filament dynamics and magnetogram
results suggest that the magnetic flux emergence takes place in the
photospheric level below the filament. Reconnection occurs underneath the
filament between the dipped lines that support the filament and the
supergranular emergence. The very smooth ascent is probably caused by this
emergence and torus instability may play a fundamental role, which is helped by
the emergence.


  Recent interest in horizontal symmetry model building has been driven mainly
by the large top mass and hence strong hierarchy in quark masses, and the
possibility of appropriately constrained soft squark mass matrices, in place of
an assumed universality condition, for satisfying the relevant FCNC
constraints. Here we present the first successful SUSY-$SU(5)$ model that has
such a feature. The horizontal symmetry is a gauged $(Q_{12} \times U(1))_H$
($\subset (SU(2) \times U(1))_H$). All nonrenormalizable terms compatible with
the symmetry are allowed in the mass matrix constructions. Charged lepton
masses can also be accommodated.


  The effect of sintering temperatures (Ts) on the structural and magnetic
properties of Ni0.6Zn0.4Fe2O4 (NZFO) ferrites synthesized by conventional
double sintering method has been reported. The samples are sintered at 1200,
1250 and 1300 {\deg}C. The X-ray diffraction (XRD) analysis reveals the
formation of a single phase cubic spinel structure of the sample. The magnetic
parameters such as saturation magnetization, Ms; coercive field, Hc; remanent
magnetization, Mr and Bohr magneton, {\mu}B are determined and well compared
with reported values. The obtained values are found to be 71.94 emu/gm and 1.2
Oe for Ms and Hc, respectively at Ts=1300 oC. Curie temperature (Tc) at various
Ts has also been calculated. It is noteworthy to note that the sample with a
very low Hc could be used in transformer core and inductor applications.


  Liouville theory describes the dynamics of surfaces with constant negative
curvature and can be used to study the Weil-Petersson geometry of the moduli
space of Riemann surfaces. This leads to an efficient algorithm to compute the
Weil--Petersson metric to arbitrary accuracy using Zamolodchikov's recursion
relation for conformal blocks. For example, we compute the metric on $\mathcal
M_{0,4}$ numerically to high accuracy by considering Liouville theory on a
sphere with four punctures. We numerically compute the eigenvalues of the
Weil-Petersson Laplacian, and find evidence that the obey the statistics of a
random matrix in the Gaussian Orthogonal Ensemble.


  We are investigating if the Jeans instability criteria mandading a low
entropy,low temperature initial pre inflation state configuration can be
recociled with thermal conditions of temperature at or above ten to the 12
power Kelvin, or higher,when cosmic inflation physics takes over. We justify
this by pointing to the Akshenkar, Pawlowski, and Singh (2006) article about a
prior universe being modeled via their quantum bounce which states that this
prior universe geometrically can be modeled via a discretized Wheeler - De Witt
equation. This allows a way of getting around the fact that conventional
cosmological CMB is limited by a barrier as of a red shift limit of about z =
1000,as to photons, and to come up with a working model of quintessence scalar
fields which permits relic generation of dark matter/dark energy as well as
relic gravitons.


  The latest search for the rare kaon decay $K^+\to\pi^+\nu\bar\nu$ by the NA62
experiment has produced evidence for it with a branching fraction consistent
with the prediction of the standard model. The new result implies that in this
decay, with the $\nu\bar\nu$ pair appearing as missing energy ($\not\!\!E$),
the room for possible new physics is no longer sizable and that therefore its
contributions to underlying four-particle $s\to d\!\not\!\!E$ operators with
parity-even $ds$ quark bilinears have become significantly constrained.
Nevertheless, we point out that appreciable manifestations from beyond the
standard model induced by the corresponding operators with mainly parity-odd
$ds$ quark bilinears could still occur in $K\to\pi\pi\!\not\!\!E$ modes, on
which there are only minimal empirical details at present. We find in
particular that new physics of this kind may enhance the branching fraction of
$K_L\to\pi^0\pi^0\!\not\!\!E$ to values reaching its current experimental upper
limit and the branching fractions of $K^+\to\pi^+\pi^0\!\not\!\!E$ and
$K_L\to\pi^+\pi^-\!\not\!\!E$ to the levels of $10^{-7}$ and $10^{-6}$,
respectively. Thus, quests for these decays in existing kaon facilities such as
KOTO and NA62 or future ones could provide valuable information complementary
to that gained from $K\to\pi\!\not\!\!E$.


  Let $\mathbb{F}_p$ be a finite field and $u$ be an indeterminate. This
article studies $(1-2u^k)$-constacyclic codes over the ring
$\mathcal{R}=\mathbb{F}_p+u\mathbb{F}_p+u^2\mathbb{F}_p+u^{3}\mathbb{F}_{p}+\cdots+u^{k}\mathbb{F}_{p}$
where $u^{k+1}=u$. We illustrate the generator polynomials and investigate the
structural properties of these codes via decomposition theorem.


  We show theoretically and numerically that dichromatic pumping of a nonlinear
microresonator by two continuous wave coherent optical pumps creates an optical
lattice trap that results in the localization of intra-cavity Kerr solitons
with soliton positions defined by the beat frequency of the pumps. This
phenomenon corresponds to the stabilization of the Kerr frequency comb
repetition rate. The locking of the second pump, through adiabatic tuning of
its frequency, to the comb generated by the first pump allows transitioning to
single-soliton states, manipulating the position of Kerr solitons in the
cavity, and tuning the frequency comb repetition rate within the locking range.
It also explains soliton crystal formation in resonators supporting a
dispersive wave emitted as a result of higher-order group velocity dispersion
or avoided mode crossing. We show that dichromatic pumping by externally
stabilized pumps can be utilized for stabilization of microresonator-based
optical frequency combs when the comb span does not cover an octave or a
significant fraction thereof and standard self-referencing techniques cannot be
employed. Our findings have significant ramifications for high-precision
applications of optical frequency combs in spectrally pure signal generation,
metrology, and timekeeping.


  Energies of four-quark systems have been extracted in a quenched SU(2)
lattice Monte Carlo calculation for two different geometries, rectangular and
colinear, with $\beta=2.4$ and lattice size $16^3\times 32$. Also, by going to
a lattice $24^3\times 32$ and to $\beta=2.5$, the effect of the finite lattice
size and scaling are checked. An attempt is made to understand these results in
terms of a model based on interquark two-body potentials but modified very
significantly by a phenomenological gluon-field overlap factor.


  The Darboux transformation applied recurrently on a Schroedinger operator
generates what is called a {\em dressing chain}, or from a different point of
view, a set of supersymmetric shape invariant potentials. The finite-gap
potential theory is a special case of the chain. For the finite-gap case, the
equations of the chain can be expressed as a time evolution of a Hamiltonian
system. We apply Sklyanin's method of separation of variables to the chain. We
show that the classical equation of the separation of variables is the Baxter
T-Q relation after quantization.


  A target-oriented sequential pattern is a sequential pattern with a concerned
itemset in the end of pattern. A time-interval sequential pattern is a
sequential pattern with time-intervals between every pair of successive
itemsets. In this paper we present an algorithm to discover target-oriented
sequential pattern with time-intervals. To this end, the original sequences are
reversed so that the last itemsets can be arranged in front of the sequences.
The contrasts between reversed sequences and the concerned itemset are then
used to exclude the irrelevant sequences. Clustering analysis is used with
typical sequential pattern mining algorithm to extract the sequential patterns
with time-intervals between successive itemsets. Finally, the discovered
time-interval sequential patterns are reversed again to the original order for
searching the target patterns.


  Large area surveys will dominate the forthcoming decades of astronomy and
their success requires characterizing thousands of discoveries through
additional observations at higher spatial or spectral resolution, and at
complementary cadences or periods. Only the full automation of adaptive optics
systems will enable high-acuity, high-sensitivity follow-up observations of
several tens of thousands of these objects per year, maximizing on-sky time.
Automation will also enable rapid response to target-of-opportunity events
within minutes, minimizing the time between discovery and characterization.
  In June 2012, we demonstrated the first fully automated operation of an
astronomical adaptive optics system by observing 125 objects in succession with
the Robo-AO system. Efficiency has increased ever since, with a typical night
comprising 200-250 automated observations at the visible diffraction limit. By
observing tens of thousands of targets in the largest-ever adaptive-optics
surveys, Robo-AO has demonstrated the ability to address the follow-up needs of
current and future large astronomical surveys.


  A simple explanation of the dynamic properties of vector mesons is given in
the framework of extended Nambu - Jona-Lasinio quark model. New mass relations
among the hadron vector resonances are derived. The results of this approach
are in good accordance with the QCD sum rules, the lattice calculations and the
experimental data.


  Neutrino oscillations are discussed from the point of view of the time-energy
uncertainty relation.


  Assume that $X_{1}, \ldots, X_{N}$ is an $\varepsilon$-contaminated sample of
$N$ independent Gaussian vectors in $\mathbb{R}^d$ with mean $\mu$ and
covariance $\Sigma$. In the strong $\varepsilon$-contamination model we assume
that the adversary replaced an $\varepsilon$ fraction of vectors in the
original Gaussian sample by any other vectors. We show that there is an
estimator $\widehat \mu$ of the mean satisfying, with probability at least $1 -
\delta$, a bound of the form \[ \|\widehat{\mu} - \mu\|_2 \le
c\left(\sqrt{\frac{\operatorname{Tr}(\Sigma)}{N}} +
\sqrt{\frac{\|\Sigma\|\log(1/\delta)}{N}} +
\varepsilon\sqrt{\|\Sigma\|}\right), \] where $c > 0$ is an absolute constant
and $\|\Sigma\|$ denotes the operator norm of $\Sigma$. In the same
contaminated Gaussian setup, we construct an estimator $\widehat \Sigma$ of the
covariance matrix $\Sigma$ that satisfies, with probability at least $1 -
\delta$, \[ \left\|\widehat{\Sigma} - \Sigma\right\| \le
c\left(\sqrt{\frac{\|\Sigma\|\operatorname{Tr}(\Sigma)}{N}} +
\|\Sigma\|\sqrt{\frac{\log(1/\delta)}{N}} + \varepsilon\|\Sigma\|\right). \]
Both results are optimal up to multiplicative constant factors. Despite the
recent significant interest in robust statistics, achieving both dimension-free
bounds in the canonical Gaussian case remained open. In fact, several
previously known results were either dimension-dependent and required $\Sigma$
to be close to identity, or had a sub-optimal dependence on the contamination
level $\varepsilon$.
  As a part of the analysis, we derive sharp concentration inequalities for
central order statistics of Gaussian, folded normal, and chi-squared
distributions.


  The appearance of microcracks in CeO$_2$ buffer layers, as used in buffer
layer architectures for coated superconductors, indicates the presence of
stress between this buffer layer and the substrate. This stress can originate
from the differences in thermal expansion or differences in lattice parameters
between the CeO$_2$ buffer layer and the substrate. In this article, we study,
by means of \textit{ab initio} density functional theory calculations, the
influence of group IV doping elements on the lattice parameter and bulk modulus
of CeO$_2$. Vegard's law behavior is found for the lattice parameter in systems
without oxygen vacancies, and the Shannon crystal radii for the doping elements
are retrieved from the lattice expansions. We show that the lattice parameter
of the doped CeO$_2$ can be matched to that of the La$_2$Zr$_2$O$_7$ coated NiW
substrate substrate for dopant concentrations of about $5\%$, and that bulk
modulus matching is either not possible or would require extreme doping
concentrations.


  The use of known analytic results for the continuum fermion determinants in
QCD and QED as benchmarks for zero lattice spacing extrapolations of lattice
fermion determinants is proposed. Specifically, they can be used as a check on
the universality hypothesis relating the continuum limits of the na\"{\i}ve,
staggered and Wilson fermion determinants.


  We present a slight generalization of the notion of completely integrable
systems to get them being integrable by quadratures. We use this generalization
to integrate dynamical systems on double Lie groups.


  In this article we introduce a theory of integration for deterministic,
operator-valued integrands with respect to cylindrical L\'evy processes in
separable Banach spaces. Here, a cylindrical L\'evy process is understood in
the classical framework of cylindrical random variables and cylindrical
measures, and thus, it can be considered as a natural generalisation of
cylindrical Wiener processes or white noises. Depending on the underlying
Banach space, we provide necessary and/or sufficient conditions for a function
to be integrable. In the last part, the developed theory is applied to define
Ornstein-Uhlenbeck processes driven by cylindrical L\'evy processes and several
examples are considered.


  Dark photons in the MeV to GeV mass range are important targets for
experimental searches. We consider the case where dark photons $A'$ decay
invisibly to hidden dark matter $X$ through $A' \to XX$. For generic masses,
proposed accelerator searches are projected to probe the thermal target region
of parameter space, where the $X$ particles annihilate through $XX \to A' \to
\text{SM}$ in the early universe and freeze out with the correct relic density.
However, if $m_{A'} \approx 2m_X$, dark matter annihilation is resonantly
enhanced, shifting the thermal target region to weaker couplings. For $\sim
10\%$ degeneracies, we find that the annihilation cross section is generically
enhanced by four (two) orders of magnitude for scalar (pseudo-Dirac) dark
matter. For such moderate degeneracies, the thermal target region drops to weak
couplings beyond the reach of all proposed accelerator experiments in the
scalar case and becomes extremely challenging in the pseudo-Dirac case.
Proposed direct detection experiments can probe moderate degeneracies in the
scalar case. For greater degeneracies, the effect of the resonance can be even
more significant, and both scalar and pseudo-Dirac cases are beyond the reach
of all proposed accelerator and direct detection experiments. For scalar dark
matter, we find an absolute minimum that sets the ultimate experimental
sensitivity required to probe the entire thermal target parameter space, but
for pseudo-Dirac fermions, we find no such thermal target floor.


  This work introduced a novel GAN architecture for unsupervised image
translation on the task of face style transform. A spectral attention-based
mechanism is embedded into the design along with spatial attention on the image
contents. We proved that neural network has the potential of learning complex
transformations such as Fourier transform, within considerable computational
cost. The model is trained and tested in comparison to the baseline model,
which only uses spatial attention. The performance improvement of our approach
is significant especially when the source and target domain include different
complexity (reduced FID to 49.18 from 142.84). In the translation process, a
spectra filling effect was introduced due to the implementation of FFT and
spectral attention. Another style transfer task and real-world object
translation are also studied in this paper.


  It is proved that tight closure commutes with localization in any domain
which has a module finite extension in which tight closure is known to commute
with localization. It follows that tight closure commutes with localization in
binomial rings, in particular in semigroup or toric rings.


  We present an atomic cluster expansion (ACE) for carbon that improves over
available classical and machine learning potentials. The ACE is parameterized
from an exhaustive set of important carbon structures at extended volume and
energy range, computed using density functional theory (DFT). Rigorous
validation reveals that ACE predicts accurately a broad range of properties of
both crystalline and amorphous carbon phases while being several orders of
magnitude more computationally efficient than available machine learning
models. We demonstrate the predictive power of ACE on three distinct
applications, brittle crack propagation in diamond, evolution of amorphous
carbon structures at different densities and quench rates and nucleation and
growth of fullerene clusters under high pressure and temperature conditions.


  A broad class of higher dimensional instanton solutions are found for a
theory which contains gravity, a scalar field and antisymmetric tensor fields
of arbitrary rank. The metric used, a warp product of an arbitrary number of
any compact Einstein manifolds, includes many of great interest in particle
physics and cosmology. For example 4D FRW universes with additional dimensions
compactified on a Calabi-Yau three fold, a torus, a compact hyperbolic manifold
or a sphere are all included. It is shown that the solution of this form which
dominates the Hartle Hawking path integral is always a higher dimensional
generalisation of a Hawking Turok instanton when the potential of the scalar
field is such that these instantons can exist. On continuation to Lorentzian
signature such instantons give rise to a spacetime in which all of the spatial
dimensions are of equal size and where the spatial topology is that of a
sphere. The extra dimensions are thus not hidden. In the case where the
potential for the scalar field is generated solely by a dilatonic coupling to
the form fields we find no integrable instantons at all. In particular we find
no integrable solutions of the type under consideration for the supergravity
theories which are the low energy effective field theories of superstrings.


  Based on the study of temporal asymmetry of 631 gamma ray bursts from the
BATSE 3B catalog by Link and Epstein [Ap J 466, 764 (1996)], we identify the
population of bursts whose rising times are longer than their decays, thus
showing atypical profiles. We analyse their sky distribution, morphology,
time-space clustering and other average properties and compare them with those
associated with the bulk of the bursts. We show how most of the peculiar bursts
analysed are consistent with recent fireball models, but a fraction of bursts
($\sim 4$% of the total sample) appear to be inconsistent.


  Bug fixing holds significant importance in software development and
maintenance. Recent research has made notable progress in exploring the
potential of large language models (LLMs) for automatic bug fixing. However,
existing studies often overlook the collaborative nature of bug resolution,
treating it as a single-stage process. To overcome this limitation, we
introduce a novel stage-wise framework named STEAM in this paper. The objective
of STEAM is to simulate the interactive behavior of multiple programmers
involved in various stages across the bug's life cycle. Taking inspiration from
bug management practices, we decompose the bug fixing task into four distinct
stages: bug reporting, bug diagnosis, patch generation, and patch verification.
These stages are performed interactively by LLMs, aiming to imitate the
collaborative abilities of programmers during the resolution of software bugs.
By harnessing the collective contribution, STEAM effectively enhances the
bug-fixing capabilities of LLMs. We implement STEAM by employing the powerful
dialogue-based LLM -- ChatGPT. Our evaluation on the widely adopted bug-fixing
benchmark demonstrates that STEAM has achieved a new state-of-the-art level of
bug-fixing performance.


  Deep learning has significantly improved the precision of instance
segmentation with abundant labeled data. However, in many areas like medical
and manufacturing, collecting sufficient data is extremely hard and labeling
this data requires high professional skills. We follow this motivation and
propose a new task set named zero-shot instance segmentation (ZSI). In the
training phase of ZSI, the model is trained with seen data, while in the
testing phase, it is used to segment all seen and unseen instances. We first
formulate the ZSI task and propose a method to tackle the challenge, which
consists of Zero-shot Detector, Semantic Mask Head, Background Aware RPN and
Synchronized Background Strategy. We present a new benchmark for zero-shot
instance segmentation based on the MS-COCO dataset. The extensive empirical
results in this benchmark show that our method not only surpasses the
state-of-the-art results in zero-shot object detection task but also achieves
promising performance on ZSI. Our approach will serve as a solid baseline and
facilitate future research in zero-shot instance segmentation.


  Heat capacity measurements on the prototypical three-dimensional random-field
Ising model compound Fe0.58Zn0.42F2 have been performed in both of the
field-cooling (FC) and zero-field-cooling (ZFC) procedures. There is no
evidence of hysteresis between the FC and ZFC protocols within the experimental
accuracy. The absence of hysteresis is interpreted based on a magnetic field
(H)-temperature (T) phase diagram in which a metastability region exists
between the Neel temperature line Tn(H) and Hc1(T), the latter being the lowest
critical field line for the local spin flips.


  We investigate the connections between max-weight approaches and dual
subgradient methods for convex optimisation. We find that strong connections
exist and we establish a clean, unifying theoretical framework that includes
both max-weight and dual subgradient approaches as special cases. Our analysis
uses only elementary methods, and is not asymptotic in nature. It also allows
us to establish an explicit and direct connection between discrete queue
occupancies and Lagrange multipliers.


  Blood feeding represents a critical event in the life cycle of female
mosquitoes. In addition to providing nutrients to the mosquito, blood feeding
facilitates the transmission of parasites and viruses to hosts, potentially
having devastating health consequences. Despite this, our understanding of
these short, yet important bouts of behaviour is incomplete. How and where a
mosquito decides to feed and the success of feeding can influence the
transmission of pathogens, while a more thorough understanding may allow
interventions to reduce or prevent infections. Recent advances in machine
vision and automated tracking presents the opportunity to observe and
understand blood feeding behaviour of mosquitoes at unprecedented spatial and
temporal resolution. Here, we combine these technologies with novel designs for
behavioural arenas and controllable artificial host cues to enable detailed
observations of biting behaviour using relatively inexpensive and readily
available materials. Combined with a workflow for quantitative image analysis,
we are able to describe nuanced, high resolution biting behaviour under tightly
controlled conditions.


  Homogeneous continued fraction algorithms are multidimensional
generalizations of the classical Euclidean algorithm, the dissipative map $$
(x_1,x_2) \in \mathbb{R}_+^2 \longmapsto \left\{\begin{array}{ll}
  (x_1 - x_2, x_2), & \mbox{if $x_1 \geq x_2$}
  (x_1, x_2 - x_1), & \mbox{otherwise.} \end{array} \right. $$ We focus on
those which act piecewise linearly on finitely many copies of positive cones
which we call Rauzy induction type algorithms.
  In particular, a variation Selmer algorithm belongs to this class. We prove
that Rauzy induction type algorithms, as well as Selmer algorithms, are ergodic
with respect to Lebesgue measure.


  Starlight corrupted by atmospheric turbulence cannot couple efficiently into
astronomical instruments based on integrated optics as they require light of
high spatial coherence to couple into their single-mode waveguides. Low-order
adaptive optics in combination with photonic lanterns offer a practical
approach to achieve efficient coupling into multiplexed astrophotonic devices.
We investigate, aided by simulations and an experimental testbed, the trade-off
between the degrees of freedom of the adaptive optics system and those of the
input waveguide of an integrated optic component leading to a cost-effective
hybrid system that achieves a signal-to-noise ratio higher than a standalone
device fed by a single-mode fiber.


  To achieve the ambitious aims of the Paris climate agreement, the majority of
fossil-fuel reserves needs to remain underground. As current national
government commitments to mitigate greenhouse gas emissions are insufficient by
far, actors such as institutional and private investors and the social movement
on divestment from fossil fuels could play an important role in putting
pressure on national governments on the road to decarbonization. Using a
stochastic agent-based model of co-evolving financial market and investors'
beliefs about future climate policy on an adaptive social network, here we find
that the dynamics of divestment from fossil fuels shows potential for social
tipping away from a fossil-fuel based economy. Our results further suggest that
socially responsible investors have leverage: a small share of 10--20\,\% of
such moral investors is sufficient to initiate the burst of the carbon bubble,
consistent with the Pareto Principle. These findings demonstrate that
divestment has potential for contributing to decarbonization alongside other
social movements and policy instruments, particularly given the credible
imminence of strong international climate policy. Our analysis also indicates
the possible existence of a carbon bubble with potentially destabilizing
effects to the economy.


  [abridged] We report four years of radial velocity monitoring observations of
SDSS J080531.84+481233.0 that reveal significant and periodic variability,
confirming the binary nature of the source. We infer an orbital period of
2.02$\pm$0.03 yr, a semi-major axis of 0.76$^{+0.05}_{-0.06}$ AU, and an
eccentricity of 0.46$\pm$0.05, consistent with the amplitude of astrometric
variability and prior attempts to resolve the system. Folding in constraints
based on the spectral types of the components (L4$\pm$0.7 and T5.5$\pm$1.1),
corresponding effective temperatures, and brown dwarf evolutionary models, we
further constrain the orbital inclination of this system to be nearly edge-on
(90$^o\pm$19$^o$), and deduce a large system mass ratio (M$_2$/M$_1$ =
0.86$^{+0.10}_{-0.12}$), substellar components (M$_1$ =
0.057$^{+0.016}_{-0.014}$ M$_{\odot}$, M$_2$ = 0.048$^{+0.008}_{-0.010}$
M$_{\odot}$), and a relatively old system age (minimum age =
4.0$^{+1.9}_{-1.2}$ Gyr). The measured projected rotational velocity of the
primary ($v\sin{i}$ = 34.1$\pm$0.7 km/s) implies that this inactive source is a
rapid rotator (period $\lesssim$ 3 hr) and a viable system for testing
spin-orbit alignment in very-low-mass multiples. The combination of
well-determined component atmospheric properties and masses near and/or below
the hydrogen minimum mass make SDSS J0805+4812AB an important system for future
tests of brown dwarf evolutionary models.


  An almost Fuchsian manifold is a quasi-Fuchsian hyperbolic three-manifold
that contains a closed incompressible minimal surface with principal curvatures
everywhere in the range of (-1,1). In such a hyperbolic three-manifold, the
minimal surface is unique and embedded, hence one can parametrize these
three-manifolds by their minimal surfaces. We prove that any closed surface
which is a graph over any fixed surface of small principal curvatures can be
deformed into the minimal surface via the mean curvature flow. We also obtain
an upper bound for the hyperbolic volume of the convex core of M, as well as
estimates of the Hausdorff dimension of the limit set for $M$.


  Most energy and commodity markets exhibit mean-reversion and occasional
distinctive price spikes, which results in demand for derivative products which
protect the holder against high prices. To this end, in this paper we present
exact and fast methodologies for the simulation of the spot price dynamics
modeled as the exponential of the sum of an Ornstein-Uhlenbeck and an
independent pure jump process, where the latter one is driven by a compound
Poisson process with (bilateral) exponentially distributed jumps. These
methodologies are finally applied to the pricing of Asian options, gas storages
and swings under different combinations of jump-diffusion market models, and
the apparent computational advantages of the proposed procedures are
emphasized.


  The Parrondo game, devised by Parrondo, means that winning strategy is
constructed a combination of losing strategy. This situation is called the
Parrondo paradox. The Parrondo game based on quantum walk and the search
algorithm via quantum walk have been widely studied, respectively. This paper
newly presents a Parrondo game of quantum search based on quantum walk by
combining both models. Moreover we confirm that Parrondo's paradox exists for
our model on the one- and two-dimensional torus by numerical simulations.
Afterwards we show the range in which the paradox occurs is symmetric about the
origin on the $d$-dimensional torus $(d \geq 1)$ with even vertices and one
marked vertex.


  Future high luminosity polarized deep--inelastic scattering experiments will
improve both the knowledge of the spin sub--structure of the nucleons and
contribute further to the precision determination of the strong coupling
constant, as well as, reveal currently yet unknown higher twist contributions
in the polarized sector. For all these tasks to be performed, it is necessary
to know the QCD leading twist scaling violations of the measured structure
functions. Here an important ingredient consists in the polarized singlet
anomalous dimensions and splitting functions in QCD. We recalculate these
quantities to three--loop order in the M--scheme by using the traditional
method of space--like off--shell massless operator matrix elements, being a
gauge--dependent framework. Here one obtains the anomalous dimensions without
referring to gravitational currents, needed when calculating them using the
forward Compton amplitude. We also calculate the non--singlet splitting
function $\Delta P_{\rm qq}^{(2), \rm s, NS}$ and compare the final results to
the literature, also including predictions for the region of small values of
Bjorken $x$.


  Although they are only minor constituents of the interstellar medium,
halogen-containing molecules are of special interest because of their unique
thermochemistry. Here, we present a theoretical study of the chemistry of
interstellar molecules containing the halogen elements chlorine and fluorine.
We have modeled both diffuse and dense molecular clouds, making use of updated
estimates for the rates of several key chemical processes. We present
predictions for the abundances of the three halogen molecules that have been
detected to date in the interstellar medium: HF, CF+ and HCl. As in our
previous study of fluorine-bearing interstellar molecules, we predict HF to be
the dominant gas-phase reservoir of fluorine within both diffuse and dense
molecular clouds; we expect the Herschel Space Observatory to detect widespread
absorption in the HF J=1-0 transition. Our updated model now overpredicts the
CF+ abundance by a factor ~10 relative to observations of the Orion Bar; this
discrepancy has widened because we now adopt a laboratory measurement of the
CF+ dissociative recombination rate that is smaller than the estimate we
adopted previously. This disagreement suggests that the reaction of C+ with HF
proceeds more slowly than the capture rate assumed in our model; a laboratory
measurement of this reaction rate would be very desirable. Our model predicts
diffuse cloud HCl abundances that are similar to those predicted previously and
detected tentatively toward zeta Oph. Two additional species are potentially
detectable from photodissociation regions: the H2Cl+ and HCl+ molecular ions.
Ortho-H2Cl+ has its lowest-lying transition in the millimeter spectral region
observable from the ground, and the lowest rotational transition of HCl+ is
observable with Herschel's HIFI instrument.


  Spin-dependent scattering from magnetic impurities inside a superconductor
gives rise to Yu-Shiba-Rusinov (YSR) states within the superconducting gap. As
such, YSR states have been very successfully modeled with an effective
scattering potential (Kondo impurity model). Using a scanning tunneling
microscope, we exploit the proximity of the tip to a surface impurity and its
influence on the YSR state to make a quantitative connection between the YSR
state energy and the impurity-substrate hybridization. We corroborate the
coupling between impurity and substrate as a key energy scale for surface
derived YSR states using the Anderson impurity model in the mean field
approximation, which accurately explains our observations. The model allows to
decide on which side of the quantum phase transition the system resides based
on additional conductance measurements. We propose that the Anderson impurity
model is much more appropriate to describe YSR states from impurities on a
superconducting surface than the Kondo impurity model, which is more
appropriate for impurities inside a superconductor. We thus provide a first
step towards a more quantitative comparison of experimental data with fully
correlated calculations based on the Anderson impurity model.


  We persist in our investigation of the sup-completion of a Dedekind complete
Riesz space, extending to the broader context of Riesz spaces. some results
initially obtained by Feng, Li, Shen, and also by Erd\"os, and R\'enyi.


  The F' center in an alkali halide forms when an anion vacancy traps two
electrons which is the prerequisite of a diatomic molecule. Indeed, the center
may displace left or right along <110> in a (110) plane, due to its coupling to
the B_{1u} vibrational mode of <110> polarization respectively. On jumping from
the initial position to the final position the F' center passes through a
saddle point which configuration is molecule-like being conformed by two
neighboring semi-vacancies along <110>. Each semi-vacancy traps one electron to
change its effective charge from +1/2 to -1/2 formin a semi-F' center. We
ouline the basic theory so as to perform calculations on the F' eigenenergies
in the two configurations to see which one of them is more favorable.


  We study the relation between elliptic flow, $v_2$ and the initial
eccentricity, $\varepsilon_2$, in heavy-ion collisions, using hydrodynamic
simulations. Significant deviations from linear eccentricity scaling are seen
in more peripheral collisions. We identify the mechanism responsible for these
deviations as a cubic response, which we argue is a generic property of the
hydrodynamic response to the initial density profile. The cubic response
increases elliptic flow fluctuations, thereby improving agreement of initial
condition models with experimental data.


  We have been developing event-driven SOI Pixel Detectors, named `XRPIX'
(X-Ray soiPIXel) based on the silicon-on-insulator (SOI) pixel technology, for
the future X-ray astronomical satellite with wide band coverage from 0.5 keV to
40 keV. XRPIX has event trigger output function at each pixel to acquire a good
time resolution of a few $\mu \rm s$ and has Correlated Double Sampling
function to reduce electric noises. The good time resolution enables the XRPIX
to reduce Non X-ray Background in the high energy band above 10\,keV
drastically by using anti-coincidence technique with active shield counters
surrounding XRPIX. In order to increase the soft X-ray sensitivity, it is
necessary to make the dead layer on the X-ray incident surface as thin as
possible. Since XRPIX1b, which is a device at the initial stage of development,
is a front-illuminated (FI) type of XRPIX, low energy X-ray photons are
absorbed in the 8 $\rm \mu$m thick circuit layer, lowering the sensitivity in
the soft X-ray band. Therefore, we developed a back-illuminated (BI) device
XRPIX2b, and confirmed high detection efficiency down to 2.6 keV, below which
the efficiency is affected by the readout noise. In order to further improve
the detection efficiency in the soft X-ray band, we developed a
back-illuminated device XRPIX3b with lower readout noise. In this work, we
irradiated 2--5 keV X-ray beam collimated to 4 $\rm \mu m \phi$ to the sensor
layer side of the XRPIX3b at 6 $\rm \mu m$ pitch. In this paper, we reported
the uniformity of the relative detection efficiency, gain and energy resolution
in the subpixel level for the first time. We also confirmed that the variation
in the relative detection efficiency at the subpixel level reported by
Matsumura et al. has improved.


  In the ground state of the doped two-leg Hubbard ladder there are power-law
decaying d_{x^2-y^2}-type pairing correlations. It is important to know the
strength and the temperature scale of these correlations. For this purpose, we
have performed determinantal Quantum Monte Carlo (QMC) calculations of the
reducible particle-particle interaction in the Hubbard ladder. In this paper,
we report on these calculations and show that, at sufficiently low
temperatures, resonant particle-particle scattering takes place in the
d_{x^2-y^2} pairing channel for certain values of the model parameters. The QMC
data presented here indicate that the d_{x^2-y^2} pairing correlations are
strong in the Hubbard ladder.


  Respiratory motion during radiotherapy causes uncertainty in the tumor's
location, which is typically addressed by an increased radiation area and a
decreased dose. As a result, the treatments' efficacy is reduced. The recently
proposed hybrid MR-linac scanner holds the promise to efficiently deal with
such respiratory motion through real-time adaptive MR-guided radiotherapy
(MRgRT). For MRgRT, motion-fields should be estimated from MR-data and the
radiotherapy plan should be adapted in real-time according to the estimated
motion-fields. All of this should be performed with a total latency of
maximally 200 ms, including data acquisition and reconstruction. A measure of
confidence in such estimated motion-fields is highly desirable, for instance to
ensure the patient's safety in case of unexpected and undesirable motion. In
this work, we propose a framework based on Gaussian Processes to infer 3D
motion-fields and uncertainty maps in real-time from only three readouts of
MR-data. We demonstrated an inference frame rate up to 69 Hz including data
acquisition and reconstruction, thereby exploiting the limited amount of
required MR-data. Additionally, we designed a rejection criterion based on the
motion-field uncertainty maps to demonstrate the framework's potential for
quality assurance. The framework was validated in silico and in vivo on healthy
volunteer data (n=5) acquired using an MR-linac, thereby taking into account
different breathing patterns and controlled bulk motion. Results indicate
end-point-errors with a 75th percentile below 1mm in silico, and a correct
detection of erroneous motion estimates with the rejection criterion.
Altogether, the results show the potential of the framework for application in
real-time MR-guided radiotherapy with an MR-linac.


  App store-inspired elicitation is the practice of exploring competitors'
apps, to get inspiration for requirements. This activity is common among
developers, but little insight is available on its practical use, advantages,
and possible issues. This paper aims to study strategies, benefits, and
challenges of app store-inspired elicitation, and to compare this technique
with the more traditional requirements elicitation interviews. We conduct an
experimental simulation with 58 analysts and collect qualitative data. Our
results show that: (1) specific guidelines and procedures are required to
better conduct app store-inspired elicitation; (2) current search features made
available by app stores are not suitable for this practice, and more tool
support is required to help analysts in the retrieval and evaluation of
competing products; (3) while interviews focus on the why dimension of
requirements engineering (i.e., goals), app store-inspired elicitation focuses
on how (i.e., solutions), offering indications for implementation and improved
usability. Our study provides a framework for researchers to address existing
challenges and suggests possible benefits to foster app store-inspired
elicitation among practitioners.


  Convolutional Neural Networks (CNNs) trained on large scale RGB databases
have become the secret sauce in the majority of recent approaches for object
categorization from RGB-D data. Thanks to colorization techniques, these
methods exploit the filters learned from 2D images to extract meaningful
representations in 2.5D. Still, the perceptual signature of these two kind of
images is very different, with the first usually strongly characterized by
textures, and the second mostly by silhouettes of objects. Ideally, one would
like to have two CNNs, one for RGB and one for depth, each trained on a
suitable data collection, able to capture the perceptual properties of each
channel for the task at hand. This has not been possible so far, due to the
lack of a suitable depth database. This paper addresses this issue, proposing
to opt for synthetically generated images rather than collecting by hand a 2.5D
large scale database. While being clearly a proxy for real data, synthetic
images allow to trade quality for quantity, making it possible to generate a
virtually infinite amount of data. We show that the filters learned from such
data collection, using the very same architecture typically used on visual
data, learns very different filters, resulting in depth features (a) able to
better characterize the different facets of depth images, and (b) complementary
with respect to those derived from CNNs pre-trained on 2D datasets. Experiments
on two publicly available databases show the power of our approach.


  \citet{Shmuel2016JMPS} discovered that all infinite band structures of waves
at normal incidence in two-phase laminates are encapsulated in a compact
universal manifold. We show that manifolds of higher dimensionality encapsulate
the band structures of all multiphase laminates. We use these manifolds to
determine the density of gaps in the spectrum, and prove it is invariant with
respect to certain properties. We further demonstrate that these manifolds are
useful for formulating optimization problems on the gaps width, for which we
develop a simple bound. Using our theory, we numerically study the dependency
of the gaps density and width on the impedance and number of phases. Finally,
we show that in certain settings, our analysis applies to non-linear multiphase
laminates, whose band diagram is tunable by finite pre-deformations. Through
simple examples, we demonstrate how the universality of our representation is
useful for characterizing this tunability in multiphase laminates.


  We present several aspects of the "topology of meromorphic functions", which
we conceive as a general theory which includes the topology of holomorphic
functions, the topology of pencils on quasi-projective spaces and the topology
of polynomial functions.


  The field of weak gravitational lensing, which measures the basic properties
of the Universe by studying the way that light from distant galaxies is
perturbed as it travels towards us, is a very active field in astronomy. This
short article presents a broad overview of the field, including some of the
important questions that cosmologists are trying to address, such as
understanding the nature of dark energy and dark matter. To do this, there is
an increasing feeling within the weak lensing community that other disciplines,
such as computer science, machine learning, signal processing and image
processing, have the expertise that would bring enormous advantage if
channelled into lensing studies. To illustrate this point, the article below
outlines some of the key steps in a weak lensing analysis chain. The challenges
are distinct at each step, but each could benefit from ideas developed in the
signal processing domain. This article also gives a brief overview of current
and planned lensing experiments that will soon bring about an influx of data
sets that are substantially larger than those analysed to date. It is,
therefore, inevitable that current techniques are likely to be insufficient,
thus leading to an exciting era where new methods will become crucial for the
continued success of the field.


  We develop a numerical method to estimate the average speed of the free
boundary in a Hele-Shaw problem with periodic coefficients in both space and
time. We test the accuracy of the method and present a few examples. We show
numerical evidence of flat parts (facets) on the free boundary in the
homogenization limit.


  Motivated by the interaction between cells, the recently introduced concept
of Neural Cellular Automata shows promising results in a variety of tasks. So
far, this concept was mostly used to generate images for a single scenario. As
each scenario requires a new model, this type of generation seems contradictory
to the adaptability of cells in nature. To address this contradiction, we
introduce a concept using different initial environments as input while using a
single Neural Cellular Automata to produce several outputs. Additionally, we
introduce GANCA, a novel algorithm that combines Neural Cellular Automata with
Generative Adversarial Networks, allowing for more generalization through
adversarial training. The experiments show that a single model is capable of
learning several images when presented with different inputs, and that the
adversarially trained model improves drastically on out-of-distribution data
compared to a supervised trained model.


  This article focuses on properties and structures of trees with maximum mean
subtree order in a given family; such trees are called optimal in the family.
Our main goal is to describe the structure of optimal trees in $\mathcal{T}_n$
and $\mathcal{C}_n$, the families of all trees and caterpillars, respectively,
of order $n$. We begin by establishing a powerful tool called the Gluing Lemma,
which is used to prove several of our main results. In particular, we show that
if $T$ is an optimal tree in $\mathcal{T}_n$ or $\mathcal{C}_n$ for $n\geq 4$,
then every leaf of $T$ is adjacent to a vertex of degree at least $3$. We also
use the Gluing Lemma to answer an open question of Jamison, and to provide a
conceptually simple proof of Jamison's result that the path $P_n$ has minimum
mean subtree order among all trees of order $n$. We prove that if $T$ is
optimal in $\mathcal{T}_n$, then the number of leaves in $T$ is
$\mathrm{O}(\log_2 n)$, and that if $T$ is optimal in $\mathcal{C}_n$, then the
number of leaves in $T$ is $\mathrm{\Theta}(\log_2 n)$. Along the way, we
describe the asymptotic structure of optimal trees in several narrower families
of trees.


  We investigate magnetic properties of strongly interacting four component
spin-3/2 ultracold fermionic atoms in the Mott insulator limit with one
particle per site in an optical lattice with honeycomb symmetry. In this limit,
atomic tunneling is virtual, and only the atomic spins can exchange. We find a
competition between symmetry breaking and liquid like disordered phases.
Particularly interesting are valence bond states with bond centered
magnetizations, situated between the ferromagnetic and conventional valence
bond phases. In the framework of a mean-field theory, we calculate the phase
diagram and identify an experimentally relevant parameter region where a
homogeneous SU(4) symmetric Affleck-Kennedy-Lieb-Tasaki-like valence bond state
is present.


  The {\it string theory} seems to be a mathematically consistent way for
explaining so far observed fermion and boson second quantized fields, with
gravity included, by offering the renormalizability of the theory by extending
the point fermions and bosons into strings and by offering the supersymmetry
among fermions and bosons. In a long series of works one of the authors in
collaboration with another author and other collaborators, has found the
phenomenological success with the model named the {\it spin-charge-family}
theory with the properties: The creation and annihilation operators for
fermions and bosons fields are described as tensor products of the Clifford odd
(for fermions) and the Clifford even (for bosons) ``basis vectors'' and basis
in ordinary space, explaining the second quantization postulates. The theory
offers the explanation for the observed properties of fermion and bosons and
for several cosmological observations. Since the number of creation and
annihilation operators for fermions and bosons is in this theory the same,
manifesting correspondingly a kind of supersymmetry, the authors start to study
in this contribution the properties of the creation and annihilation operators
if extending the point fermions and bosons into strings, expecting that this
theory offers the low energy limit for the {\it string theory}.


  The sum degrees of freedom (DoF) of the two-user MIMO X-channel is
characterized in the presence of output feedback and delayed channel state
information (CSI). The number of antennas at each transmitters is assumed to be
M and the number of antennas at each of the receivers is assumed to be N. It is
shown that the sum DoF of the two-user MIMO X-channel is the same as the sum
DoF of a two-user MIMO broadcast channel with 2M transmit antennas, and N
antennas at each receiver. Hence, for this symmetric antenna configuration,
there is no performance loss in the sum degrees of freedom due to the
distributed nature of the transmitters. This result highlights the usefulness
of feedback and delayed CSI for the MIMO X-channel.
  The K-user X-channel with single antenna at each transmitter and each
receiver is also studied. In this network, each transmitter has a message
intended for each receiver. For this network, it is shown that the sum DoF with
partial output feedback alone is at least 2K/(K+1). This lower bound is
strictly better than the best lower bound known for the case of delayed CSI
assumption for all values of K.


  We propose an online heuristic algorithm for the problem of network slice
placement optimization. The solution is adapted to support placement on large
scale networks and integrates Edge-specific and URLLC constraints. We rely on
an approach called the Power of Two Choices to build the heuristic. The
evaluation results show the good performance of the heuristic that solves the
problem in few seconds under a large scale scenario. The heuristic also
improves the acceptance ratio of network slice placement requests when compared
against a deterministic online Integer Linear Programming (ILP) solution.


  Previous work identifying depth-optimal $n$-channel sorting networks for
$9\leq n \leq 16$ is based on exploiting symmetries of the first two layers.
However, the naive generate-and-test approach typically applied does not scale.
This paper revisits the problem of generating two-layer prefixes modulo
symmetries. An improved notion of symmetry is provided and a novel technique
based on regular languages and graph isomorphism is shown to generate the set
of non-symmetric representations. An empirical evaluation demonstrates that the
new method outperforms the generate-and-test approach by orders of magnitude
and easily scales until $n=40$.


  Semi-invertible multiplicative ergodic theorems establish the existence of an
Oseledets splitting for cocycles of non-invertible linear operators (such as
transfer operators) over an invertible base. Using a constructive approach, we
establish a semi-invertible multiplicative ergodic theorem that for the first
time can be applied to the study of transfer operators associated to the
composition of piecewise expanding interval maps randomly chosen from a set of
cardinality of the continuum.


  We use radio-frequency reflectometry to measure quasiparticle tunneling rates
in the single-Cooper-pair-transistor. Devices with and without quasiparticle
traps in proximity to the island are studied. A $10^2$ to $10^3$-fold reduction
in the quasiparticle tunneling rate onto the island is observed in the case of
quasiparticle traps. In the quasiparticle trap samples we also measure a
commensurate decrease in quasiparticle tunneling rate off the island.


  We investigate the problem of nodes clustering under privacy constraints when
representing a dataset as a graph. Our contribution is threefold. First we
formally define the concept of differential privacy for structured databases
such as graphs, and give an alternative definition based on a new neighborhood
notion between graphs. This definition is adapted to particular frameworks that
can be met in various application fields such as genomics, world wide web,
population survey, etc. Second, we introduce a new algorithm to tackle the
issue of privately releasing an approximated minimum spanning tree topology for
a simple-undirected-weighted graph. It provides a simple way of producing the
topology of a private almost minimum spanning tree which outperforms, in most
cases, the state of the art "Laplace mechanism" in terms of
weight-approximation error.
  Finally, we propose a theoretically motivated method combining a sanitizing
mechanism (such as Laplace or our new algorithm) with a Minimum Spanning Tree
(MST)-based clustering algorithm. It provides an accurate method for nodes
clustering in a graph while keeping the sensitive information contained in the
edges weights of the private graph. We provide some theoretical results on the
robustness of an almost minimum spanning tree construction for Laplace
sanitizing mechanisms. These results exhibit which conditions the graph weights
should respect in order to consider that the nodes form well separated clusters
both for Laplace and our algorithm as sanitizing mechanism. The method has been
experimentally evaluated on simulated data, and preliminary results show the
good behavior of the algorithm while identifying well separated clusters.


  This Letter reports on the first measurements of transverse momentum
dependent flow angle $\Psi_n$ and flow magnitude $v_n$ fluctuations, determined
using new four-particle correlators. The measurements are performed for various
centralities in Pb-Pb collisions at a centre-of-mass energy per nucleon pair of
$\sqrt{s_{\rm NN}}$ = 5.02 TeV with ALICE at the CERN Large Hadron Collider.
Both flow angle and flow magnitude fluctuations are observed in the presented
centrality ranges and are strongest in the most central collisions and for a
transverse momentum $p_{\rm T}>2$ GeV/$c$. Comparison with theoretical models,
including iEBE-VISHNU, MUSIC, and AMPT, show that the measurements exhibit
unique sensitivities to the initial state of heavy-ion collisions.


  Some time ago Ranada (1989) obtained new nontrivial solutions of the
Maxwellian gauge fields without sources. These were reinterpreted in Kholodenko
(2015a) (part I) as particle-like (monopoles, dyons, etc.). They were obtained
by the method of Abelian reduction of the non-Abelian Yang-Mills functional.
The developed method uses instanton-type calculations normally employed for the
non-Abelian gauge fields. By invoking the electric-magnetic duality it then
becomes possible to replace all known charges/masses by the particle -like
solutions of the source-free Abelian gauge fields. To employ these results in
high energy physics, it is essential to to extend Ranada's results by carefully
analysing and classifying all dynamically generated knoted/linked structures in
gauge fields, including those discovered by Ranada. This task is completed in
this work. The study is facilitated by the recent progress made in solving the
Moffatt conjecture. Its essence is stated as follows: in steady incompressible
Euler-type fluids the streamlines could have knots/links of all types. By
employing the correspondence between the ideal hydrodynamics and
electrodynamics discussed in part I and by superimposing it with the already
mentioned method of Abelian reduction, it is demonstrated that in the absence
of boundaries only the iterated torus knots and links could be dynamically
generated. Obtained results allow to develop further particle-knot/link
correspondence studied in Kholodenko (2015b)


  It was shown by A. Beauville that if the canonical map $\varphi_{|K_M|}$ of a
complex smooth projective surface $M$ is generically finite, then ${\rm
deg}(\varphi_{|K_M|})\leq 36$. The first example of a surface with canonical
degree 36 was found by the second author. In this article, we show that for any
surface which is a degree four Galois \'etale cover of a fake projective plane
$X$ with the largest possible automorphism group ${\rm Aut}(X)=C_7:C_3$ (the
unique non-abelian group of order 21), the base locus of the canonical map is
finite, and we verify that 35 of these surfaces have maximal canonical degree
36. We also classify all smooth degree four Galois \'etale covers of fake
projective planes, which give possible candidates for surfaces of canonical
degree $36$. Finally, we also confirm in this paper the optimal upper bound of
the canonical degree of smooth threefolds of general type with sufficiently
large geometric genus, related to earlier work of C. Hacon and J.-X. Cai.


  This paper builds on recent developments of adaptive methods for linear
transport equations based on certain stable variational formulations of
Petrov-Galerkin type. The variational formulations allow us to employ meshes
with cells of arbitrary aspect ratios. We develop a refinement scheme
generating highly anisotropic partitions that is inspired by shearlet systems.
We establish approximation rates for N-term approximations from corresponding
piecewise polynomials for certain compact cartoon classes of functions. In
contrast to earlier results in a curvelet or shearlet context the cartoon
classes are concisely defined through certain characteristic parameters and the
dependence of the approximation rates on these parameters is made explicit
here. The approximation rate results serve then as a benchmark for subsequent
applications to adaptive Galerkin solvers for transport equations. In numerical
experiments, the new algorithms track C^2-curved shear layers and
discontinuities stably and accurately, and realize essentially optimal rates.
Finally, we treat parameter dependent transport problems, which arise in
kinetic models as well as in radiative transfer. In heterogeneous media these
problems feature propagation of singularities along curved characteristics
precluding, in particular, fast marching methods based on ray-tracing. Since
now the solutions are functions of spatial variables and parameters one has to
address the curse of dimensionality. We show computationally, for a model
parametric transport problem in heterogeneous media in 2 + 1 dimension, that
sparse tensorization of the presently proposed spatial directionally adaptive
scheme with hierarchic collocation in ordinate space based on a stable
variational formulation high-dimensional phase space, the curse of
dimensionality can be removed when approximating averaged bulk quantities.


  In this letter, we report on lepton flavor violating Higgs decay into mu+tau
in the framework of the generic supersymmetric standard model without R parity
and list interesting combinations of R-parity violating parameters. We impose
other known experimental constraints on the parameters of the model and show
our results from the R-parity violating parameters. In our analysis, the
branching ratio of Higgs to mu+tau can exceed 10^{-5} within admissible
parameter space.


  Network function virtualization (NFV) is referred to the technology in which
softwarized network functions virtually run on commodity servers. Such
functions are called virtual network functions (VNFs). A specific service is
composed of a set of VNFs. This is a paradigm shift for service provisioning in
telecom networks which introduces new design and implementation challenges. One
of these challenges is to meet the reliability requirement of the requested
services considering the reliability of the commodity servers. VNF placement
which is the problem of assigning commodity servers to the VNFs becomes crucial
under such circumstances. To address such an issue, in this paper, we employ
Deep Q-Network (DQN) to model NFV placement problem considering the reliability
requirement of the services. The output of the introduced model determines what
placement will be optimal in each state. Numerical evaluations show that the
introduced model can significantly improve the performance of the network
operator.


  For a simple algebraic group $G$ over an algebraically closed field, we study
products of normal subsets. For this we mark the nodes of the Dynkin diagram of
$G$. We use two types of labels, a binary marking and a labeling with
non-negative integers. The first is used to recognize large conjugacy classes
which appear in a product of two conjugacy classes while the second is used to
keep track of multiplicities of regular diagrams. In particular, we formulate
sufficient conditions in terms of marked diagrams, for a product of normal
subsets in $G$ to contain regular semisimple elements.


  Audio classification is an active research area with a wide range of
applications. Over the past decade, convolutional neural networks (CNNs) have
been the de-facto standard building block for end-to-end audio classification
models. Recently, neural networks based solely on self-attention mechanisms
such as the Audio Spectrogram Transformer (AST) have been shown to outperform
CNNs. In this paper, we find an intriguing interaction between the two very
different models - CNN and AST models are good teachers for each other. When we
use either of them as the teacher and train the other model as the student via
knowledge distillation (KD), the performance of the student model noticeably
improves, and in many cases, is better than the teacher model. In our
experiments with this CNN/Transformer Cross-Model Knowledge Distillation (CMKD)
method we achieve new state-of-the-art performance on FSD50K, AudioSet, and
ESC-50.


  We obtain the reduced CMB data $\{l_A, R, z_*\}$ from WMAP9, WMAP9+BICEP2,
Planck+WP and Planck+WP+BICEP2 for the $\Lambda$CDM and $w$CDM models with or
without spatial curvature. We then use these reduced CMB data in combination
with low-redshift observations to put constraints on cosmological parameters.
We find that including BICEP2 results in a higher value of the Hubble constant
especially when the equation of state of dark energy and curvature are allowed
to vary. For the $\Lambda$CDM model with curvature, the estimate of the Hubble
constant with Planck+WP+Lensing is inconsistent with the one derived from
Planck+WP+BICEP at about 1.3 $\sigma$ confidence level.


  We demonstrate that the dark soliton trains in optical fibers with a zero of
the group velocity dispersion can generate broad spectral distribution
(continuum) associated with the resonant dispersive radiation emitted by
solitons. This radiation is either enhanced or suppressed by the Raman
scattering depending on the sign of the third order dispersion.


  Predictive coding is an influential model of cortical neural activity. It
proposes that perceptual beliefs are furnished by sequentially minimising
"prediction errors" - the differences between predicted and observed data.
Implicit in this proposal is the idea that perception requires multiple cycles
of neural activity. This is at odds with evidence that several aspects of
visual perception - including complex forms of object recognition - arise from
an initial "feedforward sweep" that occurs on fast timescales which preclude
substantial recurrent activity. Here, we propose that the feedforward sweep can
be understood as performing amortized inference and recurrent processing can be
understood as performing iterative inference. We propose a hybrid predictive
coding network that combines both iterative and amortized inference in a
principled manner by describing both in terms of a dual optimization of a
single objective function. We show that the resulting scheme can be implemented
in a biologically plausible neural architecture that approximates Bayesian
inference utilising local Hebbian update rules. We demonstrate that our hybrid
predictive coding model combines the benefits of both amortized and iterative
inference -- obtaining rapid and computationally cheap perceptual inference for
familiar data while maintaining the context-sensitivity, precision, and sample
efficiency of iterative inference schemes. Moreover, we show how our model is
inherently sensitive to its uncertainty and adaptively balances iterative and
amortized inference to obtain accurate beliefs using minimum computational
expense. Hybrid predictive coding offers a new perspective on the functional
relevance of the feedforward and recurrent activity observed during visual
perception and offers novel insights into distinct aspects of visual
phenomenology.


  Equipping an experiment at FCC-ee with particle identification (PID)
capabilities, in particular the ability to distinguish between hadron species,
would bring great benefits to the physics programme. Good PID is essential for
precise studies in quark flavour physics, and is also a great asset for many
measurements in tau, top and Higgs physics. The requirements placed by flavour
physics and these other applications are surveyed, with an emphasis on the
momentum range over which PID is necessary. Possible solutions are discussed,
including classical RICH counters, time-of-flight systems, and d$E$/d$x$ and
cluster counting. Attention is paid to the impact on the global detector design
that including PID capabilities would imply.


  In this note we prove that if a closed monotone symplectic manifold admits a
Hamiltonian pseudo-rotation, which may be degenerate, then the quantum Steenrod
square of the cohomology class Poincar\'{e} dual to the point must be deformed.
This result gives restrictions on the existence of pseudo-rotations, implying a
form of uniruledness by pseudo-holomorphic spheres, and generalizes a recent
result of the author. The new component in the proof consists in an elementary
calculation with capped periodic orbits.


  When faced with a limited budget of function evaluations, state-of-the-art
black-box optimization (BBO) solvers struggle to obtain globally, or sometimes
even locally, optimal solutions. In such cases, one may pursue solution
polishing, i.e., a computational method to improve (or ``polish'') an incumbent
solution, typically via some sort of evolutionary algorithm involving two or
more solutions. While solution polishing in ``white-box'' optimization has
existed for years, relatively little has been published regarding its
application in costly-to-evaluate BBO. To fill this void, we explore two novel
methods for performing solution polishing along one-dimensional curves rather
than along straight lines. We introduce a convex quadratic program that can
generate promising curves through multiple elite solutions, i.e., via path
relinking, or around a single elite solution. In comparing four solution
polishing techniques for continuous BBO, we show that solution polishing along
a curve is competitive with solution polishing using a state-of-the-art BBO
solver.


  Techniques for data-mining, latent semantic analysis, contextual search of
databases, etc. have long ago been developed by computer scientists working on
information retrieval (IR). Experimental scientists, from all disciplines,
having to analyse large collections of raw experimental data (astronomical,
physical, biological, etc.) have developed powerful methods for their
statistical analysis and for clustering, categorising, and classifying objects.
Finally, physicists have developed a theory of quantum measurement, unifying
the logical, algebraic, and probabilistic aspects of queries into a single
formalism. The purpose of this paper is twofold: first to show that when
formulated at an abstract level, problems from IR, from statistical data
analysis, and from physical measurement theories are very similar and hence can
profitably be cross-fertilised, and, secondly, to propose a novel method of
fuzzy hierarchical clustering, termed \textit{semantic distillation} --
strongly inspired from the theory of quantum measurement --, we developed to
analyse raw data coming from various types of experiments on DNA arrays. We
illustrate the method by analysing DNA arrays experiments and clustering the
genes of the array according to their specificity.


  We present the first results of a systematic search for the rare
extragalactic radio sources showing an inverted (integrated) spectrum, with
spectral index $\alpha \ge +2.0$, a previously unexplored spectral domain. The
search is expected to yield strong candidates for $\alpha \ge +2.5$, for which
the standard synchrotron self-absorption (characterized by a single power-law
energy distribution of relativistic electron population) would not be a
plausible explanation, even in an ideal case of a perfectly homogeneous source
of incoherent synchrotron radiation. Such sharply inverted spectra, if found,
would require alternative explanations, e.g., free-free absorption, or
non-standard energy distribution of relativistic electrons which differs from a
power-law (e.g., Maxwellian).
  The search was carried out by comparing two sensitive low-frequency radio
surveys made with sub-arcminute resolution, namely, the WISH survey at 352 MHz
and TGSS/DR5 at 150 MHz. The overlap region between these two surveys contains
7056 WISH sources classified as `single' and brighter than 100 mJy at 352 MHz.
We focus here on the seven of these sources for which we find $\alpha > +2.0$.
Two of these are undetected at 150 MHz and are particularly good candidates for
$\alpha > +2.5$. Five of the seven sources exhibit a
`Gigahertz-Peaked-Spectrum' (GPS).


  The thermodynamic Bethe ansatz equations for the Coqblin-Schrieffer model
have been solved for the first time to obtain the magnetic susceptibility in
the presence of crystal fields for non-zero temperatures. For the case of N = 4
effective ionic states an analytic expression for the limiting values of the
pseudo-energies has been found facilitating the numerical solution for various
crystal and magnetic field configurations. The single-impurity model applies to
a wide range of dense Kondo systems and has been used before to explain
apparent non-Fermi-liquid behavior. The flattening off of the susceptibility
curves at a substantially higher temperature than the specific heat is shown to
be a general feature of the Coqblin-Schrieffer thermodynamics.


  Kilometer-sized moonlets in Saturn's A ring create S-shaped wakes called
"propellers" in surrounding material. The Cassini spacecraft has tracked the
motions of propellers for several years and finds that they deviate from
Keplerian orbits having constant semimajor axes. The inferred orbital migration
is known to switch sign. We show using a statistical test that the time series
of orbital longitudes of the propeller Bl\'eriot is consistent with that of a
time-integrated Gaussian random walk. That is, Bl\'eriot's observed migration
pattern is consistent with being stochastic. We further show, using a
combination of analytic estimates and collisional N-body simulations, that
stochastic migration of the right magnitude to explain the Cassini observations
can be driven by encounters with ring particles 10-20 m in radius. That the
local ring mass is concentrated in decameter-sized particles is supported on
independent grounds by occultation analyses.


  Theoretical framework for power dissipation in low temperature plasmas in
corona equilibrium is developed. The framework is based on fundamental
conservation laws and reaction cross sections and is only weakly sensitive to
plasma parameters, e.g. electron temperature and density. The theory is applied
to low temperature atomic and molecular hydrogen laboratory plasmas for which
the plasma heating power dissipation to photon emission, ionization and
chemical potential is calculated. The calculated photon emission is compared to
recent experimental results.


  Adaptive video streaming is a key enabler for optimising the delivery of
offline encoded video content. The research focus to date has been on
optimisation, based solely on rate-quality curves. This paper adds an
additional dimension, the energy expenditure, and explores construction of
bitrate ladders based on decoding energy-quality curves rather than the
conventional rate-quality curves. Pareto fronts are extracted from the
rate-quality and energy-quality spaces to select optimal points. Bitrate
ladders are constructed from these points using conventional rate-based rules
together with a novel quality-based approach. Evaluation on a subset of
YouTube-UGC videos encoded with x.265 shows that the energy-quality ladders
reduce energy requirements by 28-31% on average at the cost of slightly higher
bitrates. The results indicate that optimising based on energy-quality curves
rather than rate-quality curves and using quality levels to create the rungs
could potentially improve energy efficiency for a comparable quality of
experience.


  We discuss a possibility that the parameter space of the two Higgs doublet
model is significantly narrowed down by considering the synergy between direct
searches for additional Higgs bosons at the LHC and its luminosity upgraded
operation and precision measurements of the Higgs boson properties at future
electron-positron colliders such as the International Linear Collider. We show
that, in the case where the coupling constants of the discovered Higgs boson
are slightly different from the predicted values in the standard model, most of
the parameter space is explored by the direct searches of extra Higgs bosons,
in particular for the decays of the extra Higgs bosons into the discovered
Higgs boson, and also by the theoretical arguments such as perturbative
unitarity and vacuum stability. This can be done because there appears an upper
limit on the mass of the extra Higgs bosons as long as the deviation exists in
the Higgs boson coupling. We also show that in the alignment limit where all
the Higgs boson couplings take the standard model like values most of the
parameter space cannot be excluded because most of the Higgs to Higgs decays
are suppressed and also there is no upper limit on the masses from the
theoretical arguments.