  We present an analysis of the gas-phase oxygen abundances of a sample of 28
galaxies in the local Universe (z < 0.02) hosting Type Ia Supernovae (SNe Ia).
The data were obtained with the 4.2m William Herschel Telescope (WHT). We
derive local oxygen abundances for the regions where the SNe Ia exploded by
calculating oxygen gradients through each galaxy (when possible) or assuming
the oxygen abundance of the closest HII region. The sample selection only
considered galaxies for which distances not based on the the SN Ia method are
available. Then, we use a principal component analysis to study the dependence
of the absolute magnitudes on the color of the SN Ia, the oxygen abundances of
the region where they exploded, and the stretch of the SN light curve. We
demonstrate that our previous result suggesting a metallicity-dependence on the
SN Ia luminosity for not-reddened SNe Ia (Moreno-Raya et al. 2016) can be
extended to our whole sample. These results reinforce the need of including a
metallicity proxy, such as the oxygen abundance of the host galaxy, to minimize
the systematic effect induced by the metallicity-dependence of the SN Ia
luminosity in future studies of SNe Ia at cosmological distances.


  In the first part of this paper, the existence of infinitely many
$L^p$-standing wave solutions for the nonlinear Helmholtz equation $$ -\Delta u
-\lambda u=Q(x)|u|^{p-2}u\quad\text{ in }\mathbb{R}^N $$ is proven for $N\geq
2$ and $\lambda>0$, under the assumption that $Q$ be a nonnegative, periodic
and bounded function and the exponent $p$ lies in the Helmholtz subcritical
range. In a second part, the existence of a nontrivial solution is shown in the
case where the coefficient $Q$ is only asymptotically periodic.


  Dendritic cells are antigen presenting cells that provide a vital link
between the innate and adaptive immune system. Research into this family of
cells has revealed that they perform the role of coordinating T-cell based
immune responses, both reactive and for generating tolerance. We have derived
an algorithm based on the functionality of these cells, and have used the
signals and differentiation pathways to build a control mechanism for an
artificial immune system. We present our algorithmic details in addition to
some preliminary results, where the algorithm was applied for the purpose of
anomaly detection. We hope that this algorithm will eventually become the key
component within a large, distributed immune system, based on sound
immunological concepts.


  We measure the conductance of a quantum point contact (QPC) while the biased
tip of a scanning probe microscope induces a depleted region in the electron
gas underneath. At finite magnetic field we find plateaus in the real-space
maps of the conductance as a function of tip position at integer
(\nu=1,2,3,4,6,8) and fractional (\nu=1/3,2/3,5/3,4/5) values of transmission.
They resemble theoretically predicted compressible and incompressible stripes
of quantum Hall edge states. The scanning tip allows us to shift the
constriction limiting the conductance in real space over distances of many
microns. The resulting stripes of integer and fractional filling factors are
rugged on the micron scale, i.e. on a scale much smaller than the zero-field
elastic mean free path of the electrons. Our experiments demonstrate that
microscopic inhomogeneities are relevant even in high-quality samples and lead
to locally strongly fluctuating widths of incompressible regions even down to
their complete suppression for certain tip positions. The macroscopic
quantization of the Hall resistance measured experimentally in a non-local
contact configuration survives in the presence of these inhomogeneities, and
the relevant local energy scale for the \nu=2 state turns out to be independent
of tip position.


  We show via particle-in-cell simulations that small normalized magnetic
fields ($\omega_c/\omega_p \ll 1$) applied perpendicularly to a light wave can
significantly modify the evolution of backward stimulated Raman scattering
(SRS) in the kinetic regime. The presence of the magnetic field increases the
threshold for kinetic inflation and decreases the amount of reflectivity when
SRS is driven significantly above threshold. Analysis indicates this arises
because trapped electrons are accelerated as they surf across the wave, leading
to the continual dissipation of the electron plasma waves over a wider range of
wave amplitudes. The simulation parameters are directly relevant for SRS in
inertial confinement fusion devices and indicate that approximately 30 Tesla
magnetic fields might significantly reduce SRS backscatter.


  Although experience sharing (ES) accelerates multiagent reinforcement
learning (MARL) in an advisor-advisee framework, attempts to apply ES to
decentralized multiagent systems have so far relied on trusted environments and
overlooked the possibility of adversarial manipulation and inference.
Nevertheless, in a real-world setting, some Byzantine attackers, disguised as
advisors, may provide false advice to the advisee and catastrophically degrade
the overall learning performance. Also, an inference attacker, disguised as an
advisee, may conduct several queries to infer the advisors' private information
and make the entire ES process questionable in terms of privacy leakage. To
address and tackle these issues, we propose a novel MARL framework (BRNES) that
heuristically selects a dynamic neighbor zone for each advisee at each learning
step and adopts a weighted experience aggregation technique to reduce Byzantine
attack impact. Furthermore, to keep the agent's private information safe from
adversarial inference attacks, we leverage the local differential privacy
(LDP)-induced noise during the ES process. Our experiments show that our
framework outperforms the state-of-the-art in terms of the steps to goal,
obtained reward, and time to goal metrics. Particularly, our evaluation shows
that the proposed framework is 8.32x faster than the current non-private
frameworks and 1.41x faster than the private frameworks in an adversarial
setting.


  In this paper we revisit the classical problem of polynomial interpolation,
with a slight twist; namely, polynomial evaluations are available up to a group
action of the unit circle on the complex plane. It turns out that this new
setting allows for a phaseless recovery of a polynomial in a polynomial time.


  The study of language emergence aims to understand how human languages are
shaped by perceptual grounding and communicative intent. Computational
approaches to emergent communication (EC) predominantly consider referential
games in limited domains and analyze the learned protocol within the game
framework. As a result, it remains unclear how the emergent languages from
these settings connect to natural languages or provide benefits in real-world
language processing tasks, where statistical models trained on large text
corpora dominate. In this work, we propose a novel way to establish such a link
by corpus transfer, i.e. pretraining on a corpus of emergent language for
downstream natural language tasks, which is in contrast to prior work that
directly transfers speaker and listener parameters. Our approach showcases
non-trivial transfer benefits for two different tasks -- language modeling and
image captioning. For example, in a low-resource setup (modeling 2 million
natural language tokens), pre-training on an emergent language corpus with just
2 million tokens reduces model perplexity by $24.6\%$ on average across ten
natural languages. We also introduce a novel metric to predict the
transferability of an emergent language by translating emergent messages to
natural language captions grounded on the same images. We find that our
translation-based metric highly correlates with the downstream performance on
modeling natural languages (for instance $\rho=0.83$ on Hebrew), while
topographic similarity, a popular metric in previous work, shows surprisingly
low correlation ($\rho=0.003$), hinting that simple properties like attribute
disentanglement from synthetic domains might not capture the full complexities
of natural language. Our findings also indicate potential benefits of moving
language emergence forward with natural language resources and models.


  We consider a multivariable functional errors-in-variables model $AX\approx
B$, where the data matrices $A$ and $B$ are observed with errors, and a matrix
parameter $X$ is to be estimated. A goodness-of-fit test is constructed based
on the total least squares estimator. The proposed test is asymptotically
chi-squared under null hypothesis. The power of the test under local
alternatives is discussed.


  As robots venture into the real world, they are subject to unmodeled dynamics
and disturbances. Traditional model-based control approaches have been proven
successful in relatively static and known operating environments. However, when
an accurate model of the robot is not available, model-based design can lead to
suboptimal and even unsafe behaviour. In this work, we propose a method that
bridges the model-reality gap and enables the application of model-based
approaches even if dynamic uncertainties are present. In particular, we present
a learning-based model reference adaptation approach that makes a robot system,
with possibly uncertain dynamics, behave as a predefined reference model. In
turn, the reference model can be used for model-based controller design. In
contrast to typical model reference adaptation control approaches, we leverage
the representative power of neural networks to capture highly nonlinear
dynamics uncertainties and guarantee stability by encoding a certifying
Lipschitz condition in the architectural design of a special type of neural
network called the Lipschitz network. Our approach applies to a general class
of nonlinear control-affine systems even when our prior knowledge about the
true robot system is limited. We demonstrate our approach in flying inverted
pendulum experiments, where an off-the-shelf quadrotor is challenged to balance
an inverted pendulum while hovering or tracking circular trajectories.


  The large scale reflector array of programmable metasurfaces is capable of
increasing the power efficiency of backscatter communications via passive
beamforming and thus has the potential to revolutionize the low-data-rate
nature of backscatter communications. In this paper, we propose to design the
power-efficient higher-order constellation and reflection pattern under the
amplitude constraint brought by backscatter communications. For the
constellation design, we adopt the amplitude and phase-shift keying (APSK)
constellation and optimize the parameters of APSK such as ring number, ring
radius, and inter-ring phase difference. Specifically, we derive closed-form
solutions to the optimal ring radius and interring phase difference for an
arbitrary modulation order in the decomposed subproblems. For the reflection
pattern design, we propose to optimize the passive beamforming vector by
solving a multi-objective optimization problem that maximizes reflection power
and guarantees beam homogenization within the interested angle range. To solve
the problem, we propose a constant-modulus power iteration method, which is
proven to be monotonically increasing, to maximize the objective function in
each iteration. Numerical results show that the proposed APSK constellation
design and reflection pattern design outperform the existing modulation and
beam pattern designs in programmable metasurface enabled backscatter
communications.


  We study the analytic structure of the heavy-heavy-light-light holographic
correlators in the supergravity approximation of the AdS$_3 \times S^3$/CFT$_2$
duality. As an explicit example, we derive the correlator where the heavy
operator is a classical microstate of the 5D supersymmetric black hole and its
dual geometry interpolates as a function of a continuous parameter between
global AdS$_3$ and the extremal BTZ black hole. The simplest perturbation of
this interpolating geometry by a light field is described by the Heun equation
and we exploit the relation of its connection coefficients to the Liouville CFT
to analytically compute the correlator in the two limits, focusing in
particular on the black hole regime. In this limit we find that the real poles
of the correlator become dense and can be approximated by a cut. We show that,
when the charges of the heavy state are in the black hole regime, the
discontinuity across the cut has complex poles corresponding to the
quasi-normal modes of BTZ. This behaviour is qualitatively similar to what is
expected for the large central charge limit of a typical black hole microstate


  At low temperatures when the phonon modes are effectively frozen, photon
transport is the dominating mechanism of thermal relaxation in metallic
systems. Starting from a microscopic many-body Hamiltonian, we develop a
nonequilibrium Green's function method to study energy transport by photons in
nanostructures. A formally exact expression for the energy current between a
metallic island and a one-dimensional electromagnetic field is obtained. From
this expression we derive the quantized thermal conductance as well as show how
the results can be generalized to nonequilibrium situations. Generally, the
frequency-dependent current noise of the island electrons determines the energy
transfer rate.


  Spin dynamics of a single electron and an exciton confined in CdTe/ZnTe
quantum dot is investigated by polarization-resolved correlation spectroscopy.
Spin memory effects extending over at least a few tens of nanoseconds have been
directly observed in magnetic field and described quantitatively in terms of a
simple rate equation model. We demonstrate an effective (68%) all-optical
read-out of the single carrier spin state through probing the degree of
circular polarization of exciton emission after capture of an oppositely
charged carrier. The perturbation introduced by the pulsed optical excitation
serving to study the spin dynamics has been found to be the main source of the
polarization loss in the read-out process. In the limit of low laser power the
read-out efficiency extrapolates to a value close to 100%. The measurements
allowed us as well to determine neutral exciton spin relaxation time ranging
from 3.4 +/- 0.1 ns at B = 0 T to 16 +/- 3 ns at B = 5 T.


  What is the maximum number of intersections of the boundaries of a simple
$m$-gon and a simple $n$-gon, assuming general position? This is a basic
question in combinatorial geometry, and the answer is easy if at least one of
$m$ and $n$ is even: If both $m$ and $n$ are even, then every pair of sides may
cross and so the answer is $mn$. If exactly one polygon, say the $n$-gon, has
an odd number of sides, it can intersect each side of the $m$-gon at most $n-1$
times; hence there are at most $mn-m$ intersections. It is not hard to
construct examples that meet these bounds. If both $m$ and $n$ are odd, the
best known construction has $mn-(m+n)+3$ intersections, and it is conjectured
that this is the maximum. However, the best known upper bound is only $mn-(m +
\lceil \frac{n}{6} \rceil)$, for $m \ge n$. We prove a new upper bound of
$mn-(m+n)+C$ for some constant $C$, which is optimal apart from the value of
$C$.


  In recent years, thin-film organic field-effect transistors (OFETs) have
begun to be considered as a possible alternative to the hydrogenated amorphous
silicon thin-film transistors (a-Si:H TFT's) used in active matrix flat panel
displays and other large-area electronics applications. Low-temperature
processability, low-cost fabrication and compatibility with arbitrary
substrates are some of the promising advantages of OFETs, among others. Of the
many organic materials available, pentacene, in particular, is one of the
leading candidates for use in current thin-film OFET architectures - this
because of its excellent electrical characteristics and its resistance to
atmospheric oxygen. In the recent literature, pentacene's transport properties,
as well as transistor performance, have already been analyzed from the point of
view of substrate treatments, pentacene evaporation rate and substrate
temperature, electrode chemical nature and channel geometry. The results show
that the morphology, crystal structure and molecular ordering of the first
organic monolayer(s) at the pentacene/dielectric interface are essential
determinants of carrier transport phenomena. To further investigate these
interface effects, we have built a model organic field-effect transistor which
consists essentially of a single layer of pentacene on an oxide substrate.
Four-probe and two-probe transport measurements as a function of temperature
and fields will be presented in relation with structural near-field
observations. The experimental results suggest a simple two-dimensional model
where the equilibrium between free and trapped carriers at the oxide interface
determines the OFET characteristics and performance.


  The optical afterglow of long-duration GRB 071003 is among the brightest yet
to be detected from any GRB, with R ~ 12 mag in KAIT observations starting 42 s
after the GRB trigger, including filtered detections during prompt emission.
However, our high S/N ratio afterglow spectrum displays only extremely weak
absorption lines at what we argue is the host redshift of z = 1.60435 - in
contrast to the three other, much stronger Mg II absorption systems observed at
lower redshifts. Together with Keck adaptive optics observations which fail to
reveal a host galaxy coincident with the burst position, our observations
suggest a halo progenitor and offer a cautionary tale about the use of Mg II
for GRB redshift determination. We present early through late-time observations
spanning the electromagnetic spectrum, constrain the connection between the
prompt emission and early variations in the light curve (we observe no
correlation), and discuss possible origins for an unusual, marked rebrightening
that occurs a few hours after the burst: likely either a late-time refreshed
shock or a wide-angle secondary jet. Analysis of the late-time afterglow is
most consistent with a wind environment, suggesting a massive star progenitor.
Together with GRB 070125, this may indicate that a small but significant
portion of star formation in the early universe occurred far outside what we
consider a normal galactic disk.


  GRB 220627A is a rare burst with two distinct gamma-ray emission episodes
separated by almost 1000 s that triggered the Fermi Gamma-ray Burst Monitor
twice. High-energy GeV emission was detected by the Fermi Large Area Telescope
coincident with the first emission episode but not the second. The discovery of
the optical afterglow with MeerLICHT led to MUSE observations which secured the
burst redshift to z=3.08, making this the most distant ultra-long gamma-ray
burst (GRB) detected to date. The progenitors of some ultra-long GRBs have been
suggested in the literature to be different to those of normal long GRBs. Our
aim is to determine whether the afterglow and host properties of GRB 220627A
agree with this interpretation. We performed empirical and theoretical
modelling of the afterglow data within the external forward shock framework,
and determined the metallicity of the GRB environment through modelling the
absorption lines in the MUSE spectrum. Our optical data show evidence for a jet
break in the light curve at ~1.2 days, while our theoretical modelling shows a
preference for a homogeneous circumburst medium. Our forward shock parameters
are typical for the wider GRB population, and we find that the environment of
the burst is characterised by a sub-solar metallicity. Our observations and
modelling of GRB 220627A do not suggest that a different progenitor compared to
the progenitor of normal long GRBs is required. We find that more observations
of ultra-long GRBs are needed to determine if they form a separate population
with distinct prompt and afterglow features, and possibly distinct progenitors.


  In this work we analyze the sample complexity of classification by
differentially private algorithms. Differential privacy is a strong and
well-studied notion of privacy introduced by Dwork et al. (2006) that ensures
that the output of an algorithm leaks little information about the data point
provided by any of the participating individuals. Sample complexity of private
PAC and agnostic learning was studied in a number of prior works starting with
(Kasiviswanathan et al., 2008) but a number of basic questions still remain
open, most notably whether learning with privacy requires more samples than
learning without privacy.
  We show that the sample complexity of learning with (pure) differential
privacy can be arbitrarily higher than the sample complexity of learning
without the privacy constraint or the sample complexity of learning with
approximate differential privacy. Our second contribution and the main tool is
an equivalence between the sample complexity of (pure) differentially private
learning of a concept class $C$ (or $SCDP(C)$) and the randomized one-way
communication complexity of the evaluation problem for concepts from $C$. Using
this equivalence we prove the following bounds:
  1. $SCDP(C) = \Omega(LDim(C))$, where $LDim(C)$ is the Littlestone's (1987)
dimension characterizing the number of mistakes in the online-mistake-bound
learning model. Known bounds on $LDim(C)$ then imply that $SCDP(C)$ can be much
higher than the VC-dimension of $C$.
  2. For any $t$, there exists a class $C$ such that $LDim(C)=2$ but $SCDP(C)
\geq t$.
  3. For any $t$, there exists a class $C$ such that the sample complexity of
(pure) $\alpha$-differentially private PAC learning is $\Omega(t/\alpha)$ but
the sample complexity of the relaxed $(\alpha,\beta)$-differentially private
PAC learning is $O(\log(1/\beta)/\alpha)$. This resolves an open problem of
Beimel et al. (2013b).


  Let V be a cofibrantly generated monoidal model category and let M be a
monoidal V-model category. Given a cofibrant C-coloured operad P in V, we give
sufficient conditions for the fibrant replacement and cofibrant replacement
functors in M^C to preserve P-algebra structures. In particular, we show how
P-algebra structures can be transferred along derived Quillen adjunctions of
monoidal V-model categories, and we apply this result to the Quillen
adjunctions defined by enriched Bousfield localizations and colocalizations on
M. As an application, we prove that in the category of symmetric spectra the
n-connective cover functor preserves A_{\infty} and E_{\infty} module spectra
over connective ring spectra, for every integer n.


  A standard elasto-plasto-dynamic model at finite strains based on the
Lie-Liu-Kr\"oner multiplicative decomposition, formulated in rates, is here
enhanced to cope with spatially inhomogeneous materials by using the reference
(called also return) mapping. Also an isotropic hardening can be involved.
Consistent thermodynamics is formulated, allowing for both the free and the
dissipation energies temperature dependent. The model complies with the energy
balance and entropy inequality. A multipolar Stokes-like viscosity and plastic
rate gradient are used to allow for a rigorous analysis towards existence of
weak solutions by a semi-Galerkin approximation.


  Along with the growing interest in using the transverse-spatial modes of
light in quantum and classical optics applications, developing an accurate and
efficient measurement method has gained importance. Here, we present a
technique relying on a unitary mode conversion for measuring any full-field
transverse-spatial mode. Our method only requires three consecutive phase
modulations followed by a single mode fiber and is, in principle, error-free
and lossless. We experimentally test the technique using a single spatial light
modulator and achieve an average error of 4.2% for a set of 9 different
full-field Laguerre-Gauss and Hermite-Gauss modes with an efficiency of up to
70%. Moreover, as the method can also be used to measure any complex
superposition state, we demonstrate its potential in a quantum cryptography
protocol and in high-dimensional quantum state tomography.


  The approximate unification of gauge couplings is the best indirect evidence
for low-energy supersymmetry, although it is not perfect in its simplest
realizations. Given the experimental evidence for small non-zero neutrino
masses, it is plausible to extend the MSSM with three right-handed neutrino
chiral multiplets, with large Majorana masses below the unification scale, so
that a see-saw mechanism can be implemented. In this extended MSSM, the
unification prediction for the strong gauge coupling constant at M_Z can be
lowered by up to \sim 5%, bringing it closer to the experimental value at
1\sigma, therefore improving significantly the accuracy of gauge coupling
unification.


  A shell-correction method is applied to nuclei far from the beta stability
line and its suitability to describe effects of the particle continuum is
discussed. The sensitivity of predicted locations of one- and two-particle drip
lines to details of the macroscopic-microscopic model is analyzed.


  This paper proposes a computationally efficient algorithm for distributed
fusion in a sensor network in which multi-Bernoulli (MB) filters are locally
running in every sensor node for multi-target tracking. The generalized
Covariance Intersection (GCI) fusion rule is employed to fuse multiple MB
random finite set densities. The fused density comprises a set of fusion
hypotheses that grow exponentially with the number of Bernoulli components.
Thus, GCI fusion with MB filters can become computationally intractable in
practical applications that involve tracking of even a moderate number of
objects. In order to accelerate the multi-sensor fusion procedure, we derive a
theoretically sound approximation to the fused density. The number of fusion
hypotheses in the resulting density is significantly smaller than the original
fused density. It also has a parallelizable structure that allows multiple
clusters of Bernoulli components to be fused independently. By carefully
clustering Bernoulli components into isolated clusters using the GCI divergence
as the distance metric, we propose an alternative to build exactly the
approximated density without exhaustively computing all the fusion hypotheses.
The combination of the proposed approximation technique and the fast clustering
algorithm can enable a novel and fast GCIMB fusion implementation. Our analysis
shows that the proposed fusion method can dramatically reduce the computational
and memory requirements with small bounded L1-error. The Gaussian mixture
implementation of the proposed method is also presented. In various numerical
experiments, including a challenging scenario with up to forty objects, the
efficacy of the proposed fusion method is demonstrated.


  We introduce non-Hermitian plasmonic waveguide-cavity structures based on the
Aubry-Andre-Harper model to realize switching between right and left
topological edge states (TESs) using the phase-change material
Ge$_2$Sb$_2$Te$_5$ (GST). We show that switching between the crystalline and
amorphous phases of GST leads to a shift of the dispersion relation of the
optimized structure so that a right TES for the crystalline phase, and a left
TES for the amorphous phase occur at the same frequency. Thus, we realize
switching between right and left TESs at that frequency by switching between
the crystalline and amorphous phases of GST. Our results could be potentially
important for developing compact reconfigurable topological photonic devices.


  We explore systematically, in a general two Higgs doublet model, the
possibility, that bound systems of scalar bosons do exist. We find a wide
region of parameter space in the scalar potential for which S-wave bound states
of Higgs bosons do indeed exist. On the contrary we show that the Minimal
Supersimmetric Standard Model does not admit such bound systems.


  Ranking-based loss functions, such as Average Precision Loss and Rank&Sort
Loss, outperform widely used score-based losses in object detection. These loss
functions better align with the evaluation criteria, have fewer
hyperparameters, and offer robustness against the imbalance between positive
and negative classes. However, they require pairwise comparisons among $P$
positive and $N$ negative predictions, introducing a time complexity of
$\mathcal{O}(PN)$, which is prohibitive since $N$ is often large (e.g., $10^8$
in ATSS). Despite their advantages, the widespread adoption of ranking-based
losses has been hindered by their high time and space complexities.
  In this paper, we focus on improving the efficiency of ranking-based loss
functions. To this end, we propose Bucketed Ranking-based Losses which group
negative predictions into $B$ buckets ($B \ll N$) in order to reduce the number
of pairwise comparisons so that time complexity can be reduced. Our method
enhances the time complexity, reducing it to $\mathcal{O}(\max (N \log(N),
P^2))$. To validate our method and show its generality, we conducted
experiments on 2 different tasks, 3 different datasets, 7 different detectors.
We show that Bucketed Ranking-based (BR) Losses yield the same accuracy with
the unbucketed versions and provide $2\times$ faster training on average. We
also train, for the first time, transformer-based object detectors using
ranking-based losses, thanks to the efficiency of our BR. When we train CoDETR,
a state-of-the-art transformer-based object detector, using our BR Loss, we
consistently outperform its original results over several different backbones.
Code is available at https://github.com/blisgard/BucketedRankingBasedLosses


  We present a new class of slowly rotating black hole solutions in
$(n+1)$-dimensional $(n\geq3)$ Einstein-Maxwell-dilaton gravity in the presence
of Liouville-type potential for the dilaton field and an arbitrary value of the
dilaton coupling constant. Because of the presence of the dilaton field, the
asymptotic behaviour of these solutions are neither flat nor (A)dS. In the
absence of a dilaton field, our solution reduces to the $(n+1)$-dimensional
Kerr-Newman modification thereof for small rotation parameter \cite{Aliev2}. We
also compute the angular momentum and the gyromagnetic ratio of these rotating
dilaton black holes.


  In this brief note we describe two devices, a sort of flat and spherical
capacitor, with which one should be able to test the possibility of creating a
macroscopic voltage, and thus exploitable current, out of a single thermal
source at room temperature. The basic idea is trivial and it makes use of a
thermo-emitting cathode with work function as low as 0.7eV. The idea is not
completely new, but our approach is simpler and neat. When implemented, it
should allow to assess if approaches based on thermo-ionic materials at room
temperature really violate the Second Law of Thermodynamics macroscopically.


  We study the self-triggered stabilization of discrete-time linear systems
with quantized state measurements. In the networked control system we consider,
sensors may be spatially distributed and be connected to a self-triggering
mechanism through finite data-rate channels. Each sensor independently encodes
its measurements and sends them to the self-triggering mechanism. The
self-triggering mechanism integrates quantized measurement data and then
computes sampling times. Assuming that the closed-loop system is stable in the
absence of quantization and self-triggered sampling, we propose a joint design
method of an encoding scheme and a self-triggering mechanism for stabilization.
To deal with data inaccuracy due to quantization, the proposed self-triggering
mechanism uses not only quantized data but also an upper bound of quantization
errors, which is shared with a decoder.


  Morpho-evolution (ME) refers to the simultaneous optimisation of a robot's
design and controller to maximise performance given a task and environment.
Many genetic encodings have been proposed which are capable of representing
design and control. Previous research has provided empirical comparisons
between encodings in terms of their performance with respect to an objective
function and the diversity of designs that are evaluated, however there has
been no attempt to explain the observed findings. We address this by applying
Local Optima Network (LON) analysis to investigate the structure of the fitness
landscapes induced by three different encodings when evolving a robot for a
locomotion task, shedding new light on the ease by which different fitness
landscapes can be traversed by a search process. This is the first time LON
analysis has been applied in the field of ME despite its popularity in
combinatorial optimisation domains; the findings will facilitate design of new
algorithms or operators that are customised to ME landscapes in the future.


  A power law is postulated for both site and bond percolation thresholds. The
formula writes $p_c=p_0[(d-1)(q-1)]^{-a}d^{\ b}$, where $d$ is the space
dimension and $q$ the coordination number. All thresholds up to $d\rightarrow
\infty$ are found to belong to only three universality classes. For first two
classes $b=0$ for site dilution while $b=a$ for bond dilution. The last one
associated to high dimensions is characterized by $b=2a-1$ for both sites and
bonds. Classes are defined by a set of value for $\{p_0; \ a\}$. Deviations
from available numerical estimates at $d \leq 7$ are within $\pm 0.008$ and
$\pm 0.0004$ for high dimensional hypercubic expansions at $d \geq 8$. The
formula is found to be also valid for Ising critical temperatures.


  We present a generic framework for parallel coordinate descent (CD)
algorithms that includes, as special cases, the original sequential algorithms
Cyclic CD and Stochastic CD, as well as the recent parallel Shotgun algorithm.
We introduce two novel parallel algorithms that are also special
cases---Thread-Greedy CD and Coloring-Based CD---and give performance
measurements for an OpenMP implementation of these.


  Inspired by recent advances in retrieval augmented methods in
NLP~\citep{khandelwal2019generalization,khandelwal2020nearest,meng2021gnn}, in
this paper, we introduce a $k$ nearest neighbor NER ($k$NN-NER) framework,
which augments the distribution of entity labels by assigning $k$ nearest
neighbors retrieved from the training set. This strategy makes the model more
capable of handling long-tail cases, along with better few-shot learning
abilities. $k$NN-NER requires no additional operation during the training
phase, and by interpolating $k$ nearest neighbors search into the vanilla NER
model, $k$NN-NER consistently outperforms its vanilla counterparts: we achieve
a new state-of-the-art F1-score of 72.03 (+1.25) on the Chinese Weibo dataset
and improved results on a variety of widely used NER benchmarks. Additionally,
we show that $k$NN-NER can achieve comparable results to the vanilla NER model
with 40\% less amount of training data. Code available at
\url{https://github.com/ShannonAI/KNN-NER}.


  In 1959 Aharonov and Bohm suggested that an electron passing around a long
solenoid would pick up a phase shift dependent on the magnetic field of the
solenoid, even though the electrons themselves pass through a region of space
which has a zero magnetic field. It has long been held that this result is
purely quantum and is derived in many well known quantum mechanics text books
using the Schrodinger equation and vector potential. Here the same phase shift
is derived from a purely classical force, but relativistic transformations are
taken into account. The force is in the direction of motion of the electron (or
opposite) leading to a phase advance (or lag) and we obtain precisely the phase
shift thought previously to be purely quantum. The only quantum result used
here is the de Broglie wavelength of the particle, in order to get two slit
like interference and the phase shift. We employ a stack of dipoles as the
solenoid and note the same force on the electron in two different frames of
reference. We shall consider the solenoid stationary and the electron moving,
and then consider the electron rest frame and consider the solenoid moving in
the opposite direction.


  We show that for every spherical category $\C$ with invertible dimension, the
Turaev-Viro TQFT admits a splitting into blocks which come from an HQFT, called
the Turaev-Viro HQFT. The Turaev-Viro HQFT has the classifying space $B\grad$
as target space, where $\grad$ is a group obtained from the category $\C$. This
construction gives a reformulation of the Turaev-Viro TQFT in terms of HQFT.
Furthermore the Turaev-Viro HQFT is an extension of the \emph{homotopical
Turaev-Viro invariant} which splits the Turaev-Viro invariant. An application
of this result is a description of the homological twisted version of the
Turaev-Viro invariant in terms of HQFT.


  Microalgae have been shown as a potential bioresource for food, biofuel, and
pharmaceutical products. During the growth phases with corresponding
environmental conditions, microalgae accumulate different amounts of various
metabolites. We quantified the lipid accumulation and analyzed swimming
signatures (speed and trajectories) of the motile green alga, Dunaliella
primolecta, during the lag-exponential-stationary growth cycle at different
nutrient concentrations. We discovered significant changes in neutral lipid
content and swimming signatures of microalgae across growth phases. The timing
of the maximum swimming speed coincided with the maximum lipid content and both
maxima occurred under nutrient stress at the stationary growth phase.
Furthermore, the swimming trajectories of microalgae signal the growth phase
and corresponding intracellular lipid accumulation. Our results provide the
potential exploitation of microalgal swimming signatures as indicators for the
cultivation conditions and the timing of microalgal harvest to maximize the
lipid yield for biofuel production. The findings can also be implemented to
explore the production of food and antibiotics from other microalgal
metabolites with low energy cost.


  We present the largest survey of spectrally resolved mid-infrared water
emission to date, with spectra for 11 disks obtained with the Michelle and
TEXES spectrographs on Gemini North. Water emission is detected in 6 of 8 disks
around classical T Tauri stars. Water emission is not detected in the
transitional disks SR 24 N and SR 24 S, in spite of SR 24 S having
pre-transitional disk properties like DoAr 44, which does show water emission
(Salyk et al. 2015). With R~100,000, the TEXES water spectra have the highest
spectral resolution possible at this time, and allow for detailed lineshape
analysis. We find that the mid-IR water emission lines are similar to the
"narrow component" in CO rovibrational emission (Banzatti & Pontoppidan 2015),
consistent with disk radii of a few AU. The emission lines are either single
peaked, or consistent with a double peak. Single-peaked emission lines cannot
be produced with a Keplerian disk model, and may suggest that water
participates in the disk winds proposed to explain single-peaked CO emission
lines (Bast et al. 2011, Pontoppidan et al. 2011). Double-peaked emission lines
can be used to determine the radius at which the line emission luminosity drops
off. For HL Tau, the lower limit on this measured dropoff radius is consistent
with the 13 AU dark ring (ALMA partnership et al. 2015). We also report
variable line/continuum ratios from the disks around DR Tau and RW Aur, which
we attribute to continuum changes and line flux changes, respectively. The
reduction in RW Aur line flux corresponds with an observed dimming at visible
wavelengths (Rodriguez et al. 2013).


  We study a connection between two topics: Decoding of Goppa codes arising
from an algebraic curve, and rank two extensions of certain line bundles on the
curve.


  We consider estimating an unknown signal, both blocky and sparse, which is
corrupted by additive noise. We study three interrelated least squares
procedures and their asymptotic properties. The first procedure is the fused
lasso, put forward by Friedman et al. [Ann. Appl. Statist. 1 (2007) 302--332],
which we modify into a different estimator, called the fused adaptive lasso,
with better properties. The other two estimators we discuss solve least squares
problems on sieves; one constrains the maximal $\ell_1$ norm and the maximal
total variation seminorm, and the other restricts the number of blocks and the
number of nonzero coordinates of the signal. We derive conditions for the
recovery of the true block partition and the true sparsity patterns by the
fused lasso and the fused adaptive lasso, and we derive convergence rates for
the sieve estimators, explicitly in terms of the constraining parameters.


  In this paper, pelage pattern matching is considered to solve the individual
re-identification of the Saimaa ringed seals. Animal re-identification together
with the access to large amount of image material through camera traps and
crowd-sourcing provide novel possibilities for animal monitoring and
conservation. We propose a novel feature pooling approach that allow
aggregating the local pattern features to get a fixed size embedding vector
that incorporate global features by taking into account the spatial
distribution of features. This is obtained by eigen decomposition of
covariances computed for probability mass functions representing feature maps.
Embedding vectors can then be used to find the best match in the database of
known individuals allowing animal re-identification. The results show that the
proposed pooling method outperforms the existing methods on the challenging
Saimaa ringed seal image data.


  We demonstrate a high frequency phase-sensitive heterodyne vibrometer,
operating up to 10 GHz. Using this heterodyne vibrometer, the amplitude and
phase fields of the fundamental thickness mode, the radial fundamental and the
2nd-order modes of an AlN optomechanical microdisk resonator are mapped with a
displacement sensitivity of around 0.36 picometer at 1 Hz resolution bandwidth.
The simultaneous amplitude and phase measurement allows precise mode
identification and characterization. The recorded modal frequencies and proles
are consistent with numerical simulations. This vibrometer will be of great
significance for the development of high frequency mechanical devices.


  A graph $G$ is Ramsey for a graph $H$ if every 2-colouring of the edges of
$G$ contains a monochromatic copy of $H$. We consider the following question:
if $H$ has bounded treewidth, is there a `sparse' graph $G$ that is Ramsey for
$H$? Two notions of sparsity are considered. Firstly, we show that if the
maximum degree and treewidth of $H$ are bounded, then there is a graph $G$ with
$O(|V(H)|)$ edges that is Ramsey for $H$. This was previously only known for
the smaller class of graphs $H$ with bounded bandwidth. On the other hand, we
prove that the treewidth of a graph $G$ that is Ramsey for $H$ cannot be
bounded in terms of the treewidth of $H$ alone. In fact, the latter statement
is true even if the treewidth is replaced by the degeneracy and $H$ is a tree.


  Lithium (Li) metal anodes are essential for developing next-generation
high-energy-density batteries. Numerous concerns on the potential safety
hazards of the Li metal have been brought up before its massive application in
commercialized battery packs. However, few investigations have been performed
to systematically evaluate the reactivity of Li metal anode in full cell level.
Here, differential scanning calorimetry (DSC) with in situ Fourier-transform
infrared spectroscopy (FTIR) are used to quantitatively investigate the Li
metal reactivity. Lithiated graphite (Li-Gr) and lithiated silicon (Li-Si) are
also studied as the comparison samples. The reactivity of the plated Li when
coupled with different electrolyte composition, morphology, and atmosphere is
systematically studied. More importantly, the reactivity of Li metal full cell
with different cathode materials (NMC622, LFP and LNMO) has been compared. It
was found that all cell components, including electrolyte composition, Li
morphology, the control of inactive Li accumulation and cathode stability, are
essential in controlling the reactivity of the plated Li. After optimizing
these conditions, the Li metal full cell shows no significant thermal reaction
up to 400C. This work identifies the key parameters in controlling the
reactivity of the plated Li and may facilitate lithium metal battery design and
manufacturing in the coming future.


  Let $S^2$ be the 2-dimensional unit sphere and let $J_\alpha $ denote the
nonlinear functional on the Sobolev space $H^{1,2}(S^2)$ defined by $$
J_\alpha(u) = \frac{\alpha}{4}\int_{S^2}|\nabla u|^2 d\omega + \int_{S^2} u
d\omega -\ln \int_{S^2} e^{u} d\omega, $$ where $d\omega$ denotes Lebesgue
measure on $S^2$, normalized so that $\int_{S^2} d\omega = 1$. Onofri had
established that $J_\alpha$ is non-negative on $H^1(S^2)$ provided $\alpha \geq
1$. In this note, we show that if $J_\alpha$ is restricted to those $u\in
H^1(S^2)$ that satisfy the Aubin condition: \int_{S^2}e^u x_j
dw=0\quad\text{for all}1\leq j\leq 3, then the same inequality continues to
hold (i.e., $J_\alpha (u)\geq0$) whenever $\alpha \geq {2/3}-\epsilon_0$ for
some $\epsilon_0>0$. The question of Chang-Yang on whether this remains true
for all $\alpha \geq {1/2}$ remains open.


  We prove a conjecture of J. Carlson, N. Mazza and J. Th\'evenaz; namely, we
will prove that if $G$ is a finite $p$-nilpotent group which contains a
non-cyclic elementary Abelian $p$-subgroup and $k$ is an algebraically closed
field of characteristic $p$, then all simple endo-trivial $kG$-modules are
$1$-dimensional.


  Many beyond the standard model theories introduce light paraphotons, a
hypothetical spin-1 field that kinetically mixes with photons. Microwave cavity
experiments have traditionally searched for paraphotons via transmission of
power from an actively driven cavity to a passive receiver cavity, with the two
cavities separated by a barrier that is impenetrable to photons. We extend this
measurement technique to account for two-way coupling between the cavities and
show that the presence of a paraphoton field can alter the resonant frequencies
of the coupled cavity pair. We propose an experiment that exploits this effect
and uses measurements of a cavities resonant frequency to constrain the
paraphoton-photon mixing parameter, chi. We show that such an experiment can
improve sensitivity to chi over existing experiments for paraphoton masses less
than the resonant frequency of the cavity, and eliminate some of the most
common systematics for resonant cavity experiments.


  The order and the nature of the finite-temperature phase transition of QCD
with two flavors of dynamical quarks is investigated. An analysis of the
critical exponent of the specific heat is performed through finite-size and
finite-mass scaling of various susceptibilities. Dual superconductivity of QCD
vacuum is investigated using a disorder parameter, namely the v.e.v. of a
monopole creation operator. Hybrid R simulations were run at lattice spatial
sizes of $12^3$, $16^3$, $20^3$ and $32^3$ and temporal size $N_t=4$, with
quark masses in the range $am_q = 0.3 - 0.01$.


  As part of the NASA-CNES agreement, the NASA Star and Exoplanet Database
(NStED) serves as the official US portal for the public CoRoT data products.
NStED is a general purpose archive with the aim of providing support for NASA's
planet finding and characterization goals. Consequently, the NASA Exoplanet
Science Institute (NExScI) developed, and NStED adapted, a periodogram service
for CoRoT data to determine periods of variability phenomena and create phased
photometric light curves. Through the NStED periodogram interface, the user may
choose three different period detection algorithms to use on any photometric
time series product, or even upload and analyze their own data. Additionally,
the NStED periodogram is remotely accessed by the CoRoT archive as part of its
interface. NStED is available at {\bf http://nsted.ipac.caltech.edu}.


  In this paper, we investigate whether robust hashing has a possibility to
robustly detect fake-images even when multiple manipulation techniques such as
JPEG compression are applied to images for the first time. In an experiment,
the proposed fake detection with robust hashing is demonstrated to outperform
state-of-the-art one under the use of various datasets including fake images
generated with GANs.


  Diffusion has been widely used to describe a random walk of particles or
waves, and it requires only one parameter -- the diffusion constant. For waves,
however, diffusion is an approximation that disregards the possibility of
interference. Anderson localization, which manifests itself through a vanishing
diffusion coefficient in an infinite system, originates from constructive
interference of waves traveling in loop trajectories -- pairs of time-reversed
paths returning to the same point. In an open system of finite size, the return
probability through such paths is reduced, particularly near the boundary where
waves may escape. Based on this argument, the self-consistent theory of
localization and the supersymmetric field theory predict that the diffusion
coefficient varies spatially inside the system. A direct experimental
observation of this effect is a challenge because it requires monitoring wave
transport inside the system. Here, we fabricate two-dimensional photonic random
media and probe position-dependent diffusion inside the sample from the third
dimension. By varying the geometry of the system or the dissipation which also
limits the size of loop trajectories, we are able to control the
renormalization of the diffusion coefficient. This work shows the possibility
of manipulating diffusion via the interplay of localization and dissipation.


  A kernelization algorithm for a computational problem is a procedure which
compresses an instance into an equivalent instance whose size is bounded with
respect to a complexity parameter. For the Boolean satisfiability problem
(SAT), and the constraint satisfaction problem (CSP), there exist many results
concerning upper and lower bounds for kernelizability of specific problems, but
it is safe to say that we lack general methods to determine whether a given SAT
problem admits a kernel of a particular size. This could be contrasted to the
currently flourishing research program of determining the classical complexity
of finite-domain CSP problems, where almost all non-trivial tractable classes
have been identified with the help of algebraic properties. In this paper, we
take an algebraic approach to the problem of characterizing the kernelization
limits of NP-hard SAT and CSP problems, parameterized by the number of
variables. Our main focus is on problems admitting linear kernels, as has,
somewhat surprisingly, previously been shown to exist. We show that a CSP
problem has a kernel with O(n) constraints if it can be embedded (via a domain
extension) into a CSP problem which is preserved by a Maltsev operation. We
also study extensions of this towards SAT and CSP problems with kernels with
O(n^c) constraints, c>1, based on embeddings into CSP problems preserved by a
k-edge operation, k > c. These results follow via a variant of the celebrated
few subpowers algorithm. In the complementary direction, we give indication
that the Maltsev condition might be a complete characterization of SAT problems
with linear kernels, by showing that an algebraic condition that is shared by
all problems with a Maltsev embedding is also necessary for the existence of a
linear kernel unless NP is included in co-NP/poly.


  We consider the estimation of an integer vector $\hbx\in \mathbb{Z}^n$ from
the linear observation $\y=\A\hbx+\v$, where $\A\in\mathbb{R}^{m\times n}$ is a
random matrix with independent and identically distributed (i.i.d.) standard
Gaussian $\mathcal{N}(0,1)$ entries, and $\v\in \mathbb{R}^m$ is a noise vector
with i.i.d. $\mathcal{N}(0,\sigma^2 )$ entries with given $\sigma$. In digital
communications, $\hbx$ is typically uniformly distributed over an
$n$-dimensional box $\mathcal{B}$. For this estimation problem, successive
interference cancellation (SIC) decoders are popular due to their low
complexity, and a detailed analysis of their word error rates (WERs) is highly
useful. In this paper, we derive closed-form WER expressions for two cases: (1)
$\hbx\in \mathbb{Z}^n$ is fixed and (2) $\hbx$ is uniformly distributed over
$\mathcal{B}$. We also investigate some of their properties in detail and show
that they agree closely with simulated word error probabilities.


  In order to characterize flux flow through disordered type-II
superconductors, we investigate the effects of columnar and point defects on
the vortex velocity / voltage power spectrum in the driven non-equilibrium
steady state. We employ three-dimensional Metropolis Monte Carlo simulations to
measure relevant physical observables including the force-velocity /
current-voltage (I-V) characteristics, vortex spatial arrangement and structure
factor, and mean flux line radius of gyration. Our simulation results compare
well to earlier findings and physical intuition. We focus specifically on the
voltage noise power spectra in conjunction with the vortex structure factor in
the presence of weak columnar and point pinning centers. We investigate the
vortex washboard noise peak and associated higher harmonics, and show that the
intensity ratios of the washboard harmonics are determined by the strength of
the material defects rather than the type of pins present. Through varying
columnar defect lengths and pinning strengths as well as magnetic flux density
we further explore the effect of the material defects on vortex transport. It
is demonstrated that the radius of gyration displays quantitatively unique
features that depend characteristically on the type of material defects present
in the sample.


  Scalable quantum photonics relies on interfacing many optical components
under mutually compatible operating conditions. To that end, we demonstrate
that spontaneous parametric down-conversion (SPDC) in nonlinear waveguides, a
standard technology for generating entangled photon pairs, squeezed states, and
heralded single photons, is fully compatible with cryogenic operating
conditions required for superconducting detectors. This is necessary for the
proliferation of integrated quantum photonics in integration platforms
exploiting quasi-phase-matched second-order nonlinear interactions. We
investigate how cryogenic operation at 4 K affects the SPDC process by
comparing the heralding efficiency, second-order correlation function and
spectral properties with operation at room temperature.


  We show that the fidelity of the standard quantum teleportation protocol,
which utilizes an impure resource state, applied successively, can be
significantly improved, when used in conjunction with a quantum switch. In
particular, we find that for two such teleportation channels conjugated with
the superposition of causal order, teleportation fidelity beyond the classical
threshold is achieved for significantly larger noise than would be possible
conventionally. One can even make the effective teleportation channel perfectly
faithful for very large noise. We also discuss the generalization of our scheme
for more than two pathways, and define a figure of merit in that context.


  Maxwell's equation, Dirac's equation and the equation of
gravito-electromagnetism are shown to be particular instances of the extended
Maxwell system. The equations are discussed in the framework of the theory of
evolutionary equations. Their formal relationship are systematically analyzed.
Applications to coupled systems such as the Maxwell-Dirac system are also
discussed.


  Aims. We investigate statistical equilibrium of Cr in the atmospheres of
late-type stars to show whether the systematic abundance discrepancy between Cr
I and Cr II lines, as often encountered in the literature, is due to deviations
from LTE. Furthermore, we attempt to interpret the NLTE trend of [Cr/Fe] with
[Fe/H] using chemical evolution models for the solar neighborhood. Methods.
NLTE calculations are performed for the model of Cr atom, comprising 340 levels
and 6806 transitions in total. We make use of the quantum-mechanical
photoionization cross-sections of Nahar (2009) and investigate sensitivity of
the model to uncertain cross-sections for H I collisions. NLTE line formation
is performed for the MAFAGS-ODF model atmospheres of the Sun and 10 metal-poor
stars with -3.2 < [Fe/H] < -0.5, and abundances of Cr are derived by comparison
of the synthetic and observed flux spectra. Results. We achieve good ionization
equilibrium of Cr for the models with different stellar parameters, if
inelastic collisions with H I atoms are neglected. The solar NLTE abundance
based on Cr I lines is 5.74 dex with {\sigma} = 0.05 dex; it is \sim 0.1 higher
than the LTE abundance. For the metal-poor stars, the NLTE abundance
corrections to Cr I lines range from +0.3 to +0.5 dex. The resulting [Cr/Fe]
ratio is roughly solar for the range of metallicities analyzed here, which is
consistent with current views on production of these iron peak elements in
supernovae. Conclusions. The tendency of Cr to become deficient with respect to
Fe in metal-poor stars is an artifact due to neglect of NLTE effects in the
line formation of Cr I, and it has no relation to peculiar physical conditions
in the Galactic ISM or deficiencies of nucleosynthesis theory.


  The random coefficients model $Y_i={\beta_0}_i+{\beta_1}_i
{X_1}_i+{\beta_2}_i {X_2}_i+\ldots+{\beta_d}_i {X_d}_i$, with $\mathbf{X}_i$,
$Y_i$, $\mathbf{\beta}_i$ i.i.d, and $\mathbf{\beta}_i$ independent of $X_i$ is
often used to capture unobserved heterogeneity in a population. We propose a
quasi-maximum likelihood method to estimate the joint density distribution of
the random coefficient model. This method implicitly involves the inversion of
the Radon transformation in order to reconstruct the joint distribution, and
hence is an inverse problem. Nonparametric estimation for the joint density of
$\mathbf{\beta}_i=({\beta_0}_i,\ldots, {\beta_d}_i)$ based on kernel methods or
Fourier inversion have been proposed in recent years. Most of these methods
assume a heavy tailed design density $f_\mathbf{X}$. To add stability to the
solution, we apply regularization methods. We analyze the convergence of the
method without assuming heavy tails for $f_\mathbf{X}$ and illustrate
performance by applying the method on simulated and real data. To add stability
to the solution, we apply a Tikhonov-type regularization method.


  Time-frequency audio source separation is usually achieved by estimating the
short-time Fourier transform (STFT) magnitude of each source, and then applying
a phase recovery algorithm to retrieve time-domain signals. In particular, the
multiple input spectrogram inversion (MISI) algorithm has shown good
performance in several recent works. This algorithm minimizes a quadratic
reconstruction error between magnitude spectrograms. However, this loss does
not properly account for some perceptual properties of audio, and alternative
discrepancy measures such as beta-divergences have been preferred in many
settings. In this paper, we propose to reformulate phase recovery in audio
source separation as a minimization problem involving Bregman divergences. To
optimize the resulting objective, we derive a projected gradient descent
algorithm. Experiments conducted on a speech enhancement task show that this
approach outperforms MISI for several alternative losses, which highlights
their relevance for audio source separation applications.


  In the present paper I show how it is possible to derive the Hilbert space
formulation of Quantum Mechanics from a comprehensive definition of "physical
experiment" and assuming "experimental accessibility and simplicity" as
specified by five simple Postulates. This accomplishes the program presented in
form of conjectures in the previous paper quant-ph/0506034. Pivotal roles are
played by the "local observability principle", which reconciles the holism of
nonlocality with the reductionism of local observation, and by the postulated
existence of "informationally complete observables" and of a "symmetric
faithful state". This last notion allows one to introduce an operational
definition for the real version of the "adjoint"--i. e. the transposition--from
which one can derive a real Hilbert-space structure via either the
Mackey-Kakutani or the Gelfand-Naimark-Segal constructions. Here I analyze in
detail only the Gelfand-Naimark-Segal construction, which leads to a real
Hilbert space structure analogous to that of (classes of generally unbounded)
selfadjoint operators in Quantum Mechanics. For finite dimensions, general
dimensionality theorems that can be derived from a local observability
principle, allow us to represent the elements of the real Hilbert space as
operators over an underlying complex Hilbert space (see, however, a still open
problem at the end of the paper). The route for the present operational
axiomatization was suggested by novel ideas originated from Quantum Tomography.


  The elementary geometric properties of the Jacob's ladders \cite{7} lead to a
class of new formulae for short parts of the Hardy-Littlewood integral. This
class of formulae cannot be obtained by methods of Balasubramanian, Heath-Brown
and Ivic.


  For generic systems exhibiting power law behaviors, and hence multiscale
dependencies, we propose a new, and yet simple, tool to analyze multifractality
and intermittency, after noticing that these concepts are directly related to
the deformation of a probability density function from Gaussian at large scales
to non-Gaussian at smaller scales. Our framework is based on information
theory, and uses Shannon entropy and Kullback-Leibler divergence. We propose an
extensive application to three-dimensional fully developed turbulence, seen
here as a paradigmatic complex system where intermittency was historically
defined. Moreover, the concepts of scale invariance and multifractality were
extensively studied in this field and, most importantly, benchmarked. We
compute our measure on experimental Eulerian velocity measurements, as well as
on synthetic processes and a phenomenological model of fluid turbulence.Our
approach is very general and does not require any underlying model of the
system, although it can probe the relevance of such a model.


  The $g$-vector fans play an important role in studying cluster algebras and
silting theory. We survey cluster algebras with dense $g$-vector fans and show
that a connected acyclic cluster algebra has a dense $g$-vector fan if and only
if it is either finite type or affine type. As an application, we classify
finite dimensional hereditary algebras with dense $g$-vector fans.


  Decentralized learning has shown great promise for cooperative multi-agent
reinforcement learning (MARL). However, non-stationarity remains a significant
challenge in fully decentralized learning. In the paper, we tackle the
non-stationarity problem in the simplest and fundamental way and propose
multi-agent alternate Q-learning (MA2QL), where agents take turns updating
their Q-functions by Q-learning. MA2QL is a minimalist approach to fully
decentralized cooperative MARL but is theoretically grounded. We prove that
when each agent guarantees $\varepsilon$-convergence at each turn, their joint
policy converges to a Nash equilibrium. In practice, MA2QL only requires
minimal changes to independent Q-learning (IQL). We empirically evaluate MA2QL
on a variety of cooperative multi-agent tasks. Results show MA2QL consistently
outperforms IQL, which verifies the effectiveness of MA2QL, despite such
minimal changes.


  In this article we present coherent control of above-threshold photoemission
from a tungsten nanotip achieving nearly perfect modulation. Depending on the
pulse delay between fundamental (1560 nm) and second harmonic (780 nm) pulses
of a femtosecond fiber laser at the nanotip, electron emission is significantly
enhanced or depressed during temporal overlap. Electron emission is studied as
a function of pulse delay, optical near-field intensities, DC bias field, and
final photoelectron energy. Under optimized conditions modulation amplitudes of
the electron emission of 97.5% are achieved. Experimental observations are
discussed in the framework of quantum- pathway interference supported by local
density of states (LDOS) simulations.


  In a quantum-mechanical system, particle-hole duality implies that instead of
studying particles, we can get equivalent information by studying the missing
particles, the so-called holes. Using this duality picture for rotating fermion
condensates the vortices appear as holes in the Fermi see. Here we predict that
the formation of vortices in quantum dots at high magnetic fields causes
oscillations in the energy spectrum which can be experimentally observed using
accurate tunnelling spectroscopy. We use the duality picture to show that these
oscillations are caused by the localisation of vortices in rings.


  We consider the second order Cauchy problem $$u''+\m{u}Au=0, u(0)=u_{0},
u'(0)=u_{1},$$ where $m:[0,+\infty)\to[0,+\infty)$ is a continuous function,
and $A$ is a self-adjoint nonnegative operator with dense domain on a Hilbert
space.
  It is well known that this problem admits local-in-time solutions provided
that $u_{0}$ and $u_{1}$ are regular enough, depending on the continuity
modulus of $m$. It is also well known that the solution is unique when $m$ is
locally Lipschitz continuous.
  In this paper we prove that if either $<Au_{0},u_{1}>\neq 0$, or
$|A^{1/2}u_{1}|^{2}\neq\m{u_{0}}|Au_{0}|^{2}$, then the local solution is
unique even if $m$ is not Lipschitz continuous.


  We present a set of six general relativistic, multi-frequency, radiation
magnetohydrodynamic simulations of thin accretion disks with different target
mass accretion rates around black holes with spins ranging from non-rotating to
rapidly spinning. The simulations use the $\mathbf{M}_1$ closure scheme with
twelve, independent frequency (or energy) bins ranging logarithmically from
$5\times 10^{-3}$ to $5\times 10^3$ keV. The multi-frequency capability allows
us to generate crude spectra and energy-dependent light curves directly from
the simulations without a need for special post-processing. While we generally
find roughly thermal spectra with peaks around 1 to 4 keV, our high-spin cases
showed harder than expected tails for the soft or thermally dominant state.
This leads to radiative efficiencies that are up to five times higher than
expected for a Novikov-Thorne disk at the same spin. We attribute these high
efficiencies to the high-energy, coronal emission. These coronae mostly occupy
the effectively optically thin regions near the inner edges of the disks and
also cover or sandwich the inner $\sim 15 GM/c^2$ of the disks.


  We study soliton solutions to the DKP equation which is defined by the Hirota
bilinear form, \[ {\begin{array}{llll} (-4D_xD_t+D_x^4+3D_y^2)
\tau_n\cdot\tau_n=24\tau_{n-1}\tau_{n+1}, (2D_t+D_x^3\mp 3D_xD_y) \tau_{n\pm
1}\cdot\tau_n=0 \end{array} \quad n=1,2,.... \] where $\tau_0=1$. The
$\tau$-functions $\tau_n$ are given by the pfaffians of certain skew-symmetric
matrix. We identify one-soliton solution as an element of the Weyl group of
D-type, and discuss a general structure of the interaction patterns among the
solitons. Soliton solutions are characterized by $4N\times 4N$ skew-symmetric
constant matrix which we call the $B$-matrices. We then find that one can have
$M$-soliton solutions with $M$ being any number from $N$ to $2N-1$ for some of
the $4N\times 4N$ $B$-matrices having only $2N$ nonzero entries in the upper
triangular part (the number of solitons obtained from those $B$-matrices was
previously expected to be just $N$).


  We give a mathematically precise statement of SYZ conjecture between mirror
space pairs and prove it for any toric Calabi-Yau manifold with Gross's special
Lagrangian fibration. To date, it is the first time we realize the SYZ proposal
with singular fibers beyond the topological level. The dual singular fibration
is explicitly written and proved to be compatible with the family Floer mirror
construction. We use both ideas of Kontsevich-Soibelman and
Gross-Hacking-Keel-Siebert. Moreover, we discover that the Maurer-Cartan set of
a singular Lagrangian is only a strict subset of the corresponding dual
singular fiber. This responds negatively to the previous expectation and leads
to new perspectives of SYZ singularities. As extra evidence, we also check some
computations for a well-known folklore conjecture for the Landau-Ginzburg
model.


  The detection of cause-effect relationships from the analysis of
paleoclimatic records is a crucial step to disentangle the main mechanisms at
work in the climate system. Here, we show that the approach based on the
generalized Fluctuation-Dissipation Relation, complemented by the analysis of
the Transfer Entropy, allows the causal links to be identified between
temperature, CO2 concentration and astronomical forcing during the glacial
cycles of the last 800 kyr based on Antarctic ice core records. When
considering the whole spectrum of time scales, the results of the analysis
suggest that temperature drives CO2 concentration, or that are both driven by
the common astronomical forcing. However, considering only millennial-scale
fluctuations, the results reveal the presence of more complex causal links,
indicating that CO2 variations contribute to driving the changes of temperature
on such time scales. The results also evidence a slow temporal variability in
the strength of the millennial-scale causal links between temperature and CO2
concentration.


  Detailed chemistry-based computational fluid dynamics (CFD) simulations are
computationally expensive due to the solution of the underlying chemical
kinetics system of ordinary differential equations (ODEs). Here, we introduce a
novel open-source library aiming at speeding up such reactive flow simulations
using OpenFOAM, an open-source C++ software for CFD. First, our dynamic load
balancing model DLBFoam (Tekg\"ul et al., 2021) is utilized to mitigate the
computational imbalance due to chemistry solution in multiprocessor reactive
flow simulations. Then, the individual (cell-based) chemistry solutions are
optimized by implementing an analytical Jacobian formulation using the
open-source library pyJac, and by increasing the efficiency of the ODE solvers
by utilizing the linear algebra package LAPACK. We demonstrate the speed-up
capabilities of this new library on various combustion problems. These test
problems include a 2D turbulent reacting shear layer and 3D stratified
combustion to highlight the favorable scaling aspects of the library on
ignition/flame front initiation setups for dual-fuel combustion. Furthermore,
two fundamental 3D demonstrations are provided on non-premixed and partially
premixed flames, namely the ECN Spray A and the Sandia flame D experimental
configurations. The novel model offers up to two orders of magnitude speed-up
for most of the investigated cases. The openly shared code along with the test
case setups represent a radically new enabler for reactive flow simulations in
the OpenFOAM framework.


  For a finite group $G$, we consider the problem of counting simultaneous
conjugacy classes of $n$-tuples and simultaneous conjugacy classes of commuting
$n$-tuples in $G$. Let $\alpha_{G,n}$ denote the number of simultaneous
conjugacy classes of $n$-tuples, and $\beta_{G,n}$ the number of simultaneous
conjugacy classes of commuting $n$-tuples in $G$. The generating functions
$A_G(t) = \sum_{n\geq 0} \alpha_{G,n}t^n,$ and $B_G(t) = \sum_{n\geq 0}
\beta_{G,n}t^n$ are rational functions of $t$. This paper concern studied of
normalized functions $A_G(t/|G|)$ and $B_G(t/|G|)$ for finite $p$-groups of
rank at most $5$.


  The Ag ion in the recently synthesized novel material Ag2NiO2 adopts an
extremely unusual valency of 1/2, leaving the Ni ion as 3+, rather than the
expected 2+. Using first principles calculations, we show that this mysterious
subvalent state emerges due to a strong bonding-antibonding interaction between
the two Ag layers which drives the lower band beneath the O p complex,
eliminating the possibility of a conventional Ag 1+ valence state. The strong
renormalization of the specific heat coefficient, gamma, is likely due to
strong spin fluctuations that stem from nearly complete compensation of the
ferro- (metallic double exchange and the 90 degree superexchange) and
antiferromagnetic (conventional superexchange via Ni-O-Ag-O-Ni path)
interactions.


  We demonstrate that silicon-vacancy (SiV) centers in diamond can be used to
efficiently generate coherent optical photons with excellent spectral
properties. We show that these features are due to the inversion symmetry
associated with SiV centers, and demonstrate generation of indistinguishable
single photons from separate emitters in a Hong-Ou-Mandel (HOM) interference
experiment.Prospects for realizing efficient quantum network nodes using SiV
centers are discussed.


  We consider a renormalization group study of the problem of coupled stripes
of holes in cuprates. We use a model of a mesh of horizontal and vertical
stripes and study the problemof superconductivity via the Josephson coupling.
We discuss the evolution of the Fermi surface with doping and temperature, the
existence of Luttinger and/or Fermi liquid behavior, the presence of pre-formed
Cooper pairs and the symmetry and magnitude of the superconducting order
parameter.


  We give explicit formul{\ae} for Noether invariants associated to Killing
vector fields for the variational problem of minimal and constant mean
curvature surfaces in 3-manifolds. In the case of homogeneous spaces, such
invariants are the flux (associated to translations) and the torque (associated
to rotations). Then we focus on homogeneous spaces with isometry groups of
dimensions 3 or 4 and study the behavior of these invariants under the action
of isometries. Finally, we give examples of actual computations and of
interpretations of these invariants in different situations.


  Pionic excitations are analyzed in isospin-asymmetric Fermi gas of
constituent quarks. It is found that in addition to the usual pionic
excitations, there exists a very low collective mode with quantum numbers of
the charged pion (spin-isospin sound). In the chiral limit the excitation
energy of one of the modes scales as the current quark mass, and the mode
saturates current-algebraic sum rules. This is in agreement with predictions of
current algebra for isospin-asymmetric medium.


  We update the Big Bang Nucleosynthesis (BBN) calculations on the basis of the
recent NACRE compilation of reaction rates. In particular, we calculate the
uncertainties related to the nuclear reaction rates on the abundances of 7Li
and compare our results with an other recent analysis.


  In the foundations of quantum mechanics, the Kolmogorovian Censorship (KC)
stipulates that quantum probabilities can be identified with classical,
Kolmogorovian probabilities when considering a specified measurement context.
Then in any given measurement context it is possible to build a Kolmogorovian
probability distribution, or equivalently a hidden variable theory; however
this distribution must be matched to the chosen context. In a loophole-free
Bell test, the remote random choices of measurements (polarizers orientations)
have the purpose to prevent that this matching can be obtained from any
relativistically causal transmission between the source and the detectors. Then
the matching (required to violate Bell's inequalities) may be obtained either
by an instantaneous influence at a distance between the source and the
detectors (explicit nonlocality), or by assuming that it is pre-established
before the actual experiment takes place (super-determinism). If both influence
at a distance and super-determinism are not accepted on physical grounds, a
third way is still available, called "predictive incompleteness": it tells that
the usual quantum state $\psi$ is incomplete, as long as the measurement
context has not been specified. In agreement with the general quantum framework
called CSM (Contexts, Systems and Modalities) we argue that predictive
incompleteness is the correct quantum way to understand the violation of Bell's
inequalities.


  Recently, Yang et al. (Quantum Inf Process:17:129, 2018) proposed a secure
multi-party quantum summation protocol allowing the involved participants to
sum their secrets privately. They claimed that the proposed protocol can
prevent each participant's secret from being known by others. However, this
study shows that the participant who prepares the initial quantum states can
obtain other participants' secrets with an inverse quantum Fourier transform
attack. A modification is then proposed here to solve this problem.


  Using high-statistics datasets generated in (2+1)-flavor QCD calculations at
finite temperature we construct estimators for the radius of convergence from
an eighth order series expansion of the pressure as well as the number density.
We show that the estimator for pressure and number density will be identical in
the asymptotic limit. In the vicinity of the pseudo-critical temperature,
$T_{pc}\simeq 156.5$~MeV, we find the estimator of the radius of convergence to
be $\mu_B/T \gtrsim\ 3$ for strangeness-neutral matter. We also present results
for the pole structure of the Pad\'e approximants for the pressure at non-zero
values of the baryon chemical potential and show that the pole structure of the
[4,4] Pad\'e is consistent with not having a critical point at temperatures
larger than $135~$MeV and a baryon chemical potential smaller than $\mu_B/T
\sim \ 2.5$.


  Restart has the potential of expediting or impeding the completion times of
general random processes. Consequently, the issue of mean-performance takes
center stage: quantifying how the application of restart on a process of
interest impacts its completion-time's mean. Going beyond the mean, little is
known on how restart affects stochasticity measures of the completion time.
This paper is the first in a duo of studies that address this knowledge gap
via: a comprehensive analysis that quantifies how sharp restart -- a keystone
restart protocol -- impacts the completion-time's Boltzmann-Gibbs-Shannon
entropy. The analysis establishes closed-form results for sharp restart with
general timers, with fast timers (high-frequency resetting), and with slow
timers (low-frequency resetting). These results share a common structure:
comparing the completion-time's hazard rate to a flat benchmark -- the constant
hazard rate of an exponential distribution whose entropy is equal to the
completion-time's entropy. In addition, using an information-geometric approach
based on Kullback-Leibler distances, the analysis establishes results that
determine the very existence of timers with which the application of sharp
restart decreases or increases the completion-time's entropy. Our work sheds
first light on the intricate interplay between restart and randomness -- as
gauged by the Boltzmann-Gibbs-Shannon entropy.


  We analyse the constraints on scalar leptoquarks coming from radiative
corrections to $Z$ physics. We perform a global fitting to the LEP data
including the contributions of the most general effective Lagrangian for scalar
leptoquarks, which exhibits the $SU(2)_L \times U(1)_Y$ gauge invariance. We
show that the bounds on leptoquarks that couple to the top quark are much
stronger than the ones obtained from low energy experiments.


  The goal of supervised representation learning is to construct effective data
representations for prediction. Among all the characteristics of an ideal
nonparametric representation of high-dimensional complex data, sufficiency, low
dimensionality and disentanglement are some of the most essential ones. We
propose a deep dimension reduction approach to learning representations with
these characteristics. The proposed approach is a nonparametric generalization
of the sufficient dimension reduction method. We formulate the ideal
representation learning task as that of finding a nonparametric representation
that minimizes an objective function characterizing conditional independence
and promoting disentanglement at the population level. We then estimate the
target representation at the sample level nonparametrically using deep neural
networks. We show that the estimated deep nonparametric representation is
consistent in the sense that its excess risk converges to zero. Our extensive
numerical experiments using simulated and real benchmark data demonstrate that
the proposed methods have better performance than several existing dimension
reduction methods and the standard deep learning models in the context of
classification and regression.


  We have observed a linear pressure dependence of longitudinal relaxation time
($T_1$) at 4.2 K and 295 K in gaseous $^3$He cells made of either bare pyrex
glass or Cs/Rb-coated pyrex due to paramagnetic sites in the cell wall. The
paramagnetic wall relaxation is previously thought to be independent of $^3$He
pressure. We develop a model to interpret the observed wall relaxation by
taking into account the diffusion process, and our model gives a good
description of the data.


  For a quantum system with Hilbert space ${\cal H}$ of dimension $N$ and a set
$S$ of $n$ Hermitian operators ${\cal O}_i$, a basic question is to understand
the set $E_S \subset \mathbb{R}^n$ of points $\vec{e}$ where $e_i = {\rm
tr}(\rho {\cal O}_i)$ for an allowed state $\rho$. A related question is to
determine whether a given set of expectation values $\vec{e}$ lies in $E_S$ and
in this case to describe the most general state with these expectation values.
In this paper, we describe various ways to characterize $E_S$, reviewing basic
results that are perhaps not widely known and adding new ones. One important
result (originally due to E. Wichmann) is that for a set $S$ of linearly
independent traceless operators, every set of expectation values $\vec{e}$ in
the interior of $E_S$ is achieved uniquely by a state of the form
$\rho({\vec{\beta}}) = e^{-\sum_i \beta_i {\cal O}_i}/{\rm tr}(e^{-\sum_i
\beta_i {\cal O}_i})$ for ${\cal O}_i \in S$. In fact, the map $\vec{\beta} \to
\vec{E}(\vec{\beta}) = {\rm tr}(\vec{\cal O} \rho({\vec{\beta}}))$ is a
diffeomorphism from $\mathbb{R}^n$ to the interior of $E_S$ with symmetric,
positive Jacobian; using this fact, we provide an algorithm to invert
$\vec{E}(\vec{\beta})$ and thus determine a state
$\rho({\vec{\beta}(\vec{e})})$ with specified expectation values $\vec{e}$
provided that these lie in $E_S$. The algorithm is based on defining a first
order differential equation in the space of parameters $\vec{\beta}$ that is
guaranteed to converge to $\vec{\beta}(\vec{e})$ in a precise way, with
$|\vec{E}(\vec{\beta}(t)) - \vec{e}| = C e^{-t}$.


  The relative strength between forward and reverse shock emission in early
gamma-ray burst afterglow reflects that of magnetic energy densities in the two
shock regions. We numerically show that with the current standard treatment,
the fireball magnetization is underestimated by up to two orders of magnitude.
This discrepancy is especially large in the sub-relativistic reverse shock
regime (i.e. the thin shell and intermediate regime) where most optical flashes
were detected. We provide new analytic estimates of the reverse shock emission
based on a better shock approximation, which well describe numerical results in
the intermediate regime. We show that the reverse shock temperature at the
onset of afterglow is constant, $(\bar{\Gamma}_d-1)\sim 8\times10^{-2}$, when
the dimensionless parameter $\xi_{0}$ is more than several. Our approach is
applied to case studies of GRB 990123 and 090102, and we find that magnetic
fields in the fireballs are even stronger than previously believed.


  We investigate variations of the Zitterbewegung frequency of electron due to
an external static and uniform magnetic field employing the expectation value
quantum approach, and compare our results with the classical model of spinning
particles. We demonstrate that these two so far compatible approaches are not
in agreement in the presence of an external uniform static magnetic field, in
which the classical approach breaks the usual symmetry of free particles and
antiparticles states, i.e. it leads to CP violation. Hence, regarding the
Zitterbewegung frequency of electron, the classical approach in the presence of
an external magnetic field is unlikely to correctly describe the spin of
electron, while the quantum approach does, as expected. We also show that the
results obtained via the expectation value are in close agreement with the
quantum approach of the Heisenberg picture derived in the literature. However,
the method we use is capable of being compared with the classical approach
regarding the spin aspects. The classical interpretation of spin produced by
the altered Zitterbewegung frequency, in the presence of an external magnetic
field, are discussed.


  The dependence of the sequence of red galaxies (RS) with the environment is
investigated using field, group, and cluster galaxies drawn from the SDSS. Our
work focuses in studying the mean colour ($\mu_R$) and the scatter ($\sigma_R$)
of the RS as a function absolute magnitude in different environments
characterised either by the mass of the system in which the galaxies are
located or by the distance to the system's centre. The same analysis is carried
out using red early type galaxies. For a given luminosity, $\mu_R$ of field
galaxies is bluer and $\sigma_R$ is larger than their group and cluster
counterparts irrespective of mass and position within the systems. Among
systems of galaxies, high mass groups and clusters have the reddest $\mu_R$ and
the smallest $\sigma_R$. These differences almost disappear when red early type
galaxies alone are considered. Galaxies in the core and in the outskirts of
groups have similar $\mu_R$, whereas galaxies in clusters show a strong
dependence on cluster centric distance. Red early type galaxies in the
outskirts of clusters have $\sigma_R$ values as large as field galaxies', while
galaxies in the inner regions of clusters have lower values. We find that
bright red early type galaxies have reached nearly the same evolutionary stage
in all environments. Our results suggest that the cluster environment is not
necessary to populate the RS. We propose a scenario in which the RS in massive
systems is populated by two different star formation history galaxies: red
early type galaxies that formed the bulk of their stars during the early stages
of massive halo assembly, and red galaxies that passed most of their lives
inhabiting poor groups or the field and fell into massive systems at lower
redshifts.


  The noncooperative Nash equilibrium solution of classical games corresponds
to a rational expectations attitude on the part of the players. However, in
many cases, games played by human players have outcomes very different from
Nash equilibria. A restricted version of quantum games is proposed to
implement, in mathematical games, the interplay of self-interest and
internalized social norms that rules human behavior.


  Incorrect operations of a Multi-Robot System (MRS) may not only lead to
unsatisfactory results, but can also cause economic losses and threats to
safety. These threats may not always be apparent, since they may arise as
unforeseen consequences of the interactions between elements of the system.
This call for tools and techniques that can help in providing guarantees about
MRSs behaviour. We think that, whenever possible, these guarantees should be
backed up by formal proofs to complement traditional approaches based on
testing and simulation.
  We believe that tailored linguistic support to specify MRSs is a major step
towards this goal. In particular, reducing the gap between typical features of
an MRS and the level of abstraction of the linguistic primitives would simplify
both the specification of these systems and the verification of their
properties. In this work, we review different agent-oriented languages and
their features; we then consider a selection of case studies of interest and
implement them useing the surveyed languages. We also evaluate and compare
effectiveness of the proposed solution, considering, in particular, easiness of
expressing non-trivial behaviour.


  More and more software practitioners are tackling towards industrial
applications of artificial intelligence (AI) systems, especially those based on
machine learning (ML). However, many of existing principles and approaches to
traditional systems do not work effectively for the system behavior obtained by
training not by logical design. In addition, unique kinds of requirements are
emerging such as fairness and explainability. To provide clear guidance to
understand and tackle these difficulties, we present an analysis on what
quality concepts we should evaluate for AI systems. We base our discussion on
ISO/IEC 25000 series, known as SQuaRE, and identify how it should be adapted
for the unique nature of ML and $\textit{Ethics guidelines for trustworthy AI}$
from European Commission. We thus provide holistic insights for quality of AI
systems by incorporating the ML nature and AI ethics to the traditional
software quality concepts.


  When does a holographic CFT with a boundary added to it (a BCFT) also have a
`good' holographic dual with a localized gravitating end-of-the-world brane? We
argue that the answer to this question is almost never. By studying Lorentzian
BCFT correlators, we characterize constraints imposed on a BCFT by the
existence of a bulk causal structure. We argue that approximate `bulk brane'
singularities place restrictive constraints on the spectrum of a BCFT that are
not expected to be true generically. We discuss how similar constraints implied
by bulk causality might apply in higher-dimensional holographic descriptions of
BCFTs involving a degenerating internal space. We suggest (although do not
prove) that even these higher-dimensional holographic duals are not generic.


  We give the bridge indices for 11-crossing prime knots and give a minimal
bridge projection for each of these knots. The results on the indices may be
easily summarized: all of these knots that are not rational knots or Montesinos
knots have bridge index three.


  Applying neural networks as controllers in dynamical systems has shown great
promises. However, it is critical yet challenging to verify the safety of such
control systems with neural-network controllers in the loop. Previous methods
for verifying neural network controlled systems are limited to a few specific
activation functions. In this work, we propose a new reachability analysis
approach based on Bernstein polynomials that can verify neural-network
controlled systems with a more general form of activation functions, i.e., as
long as they ensure that the neural networks are Lipschitz continuous.
Specifically, we consider abstracting feedforward neural networks with
Bernstein polynomials for a small subset of inputs. To quantify the error
introduced by abstraction, we provide both theoretical error bound estimation
based on the theory of Bernstein polynomials and more practical sampling based
error bound estimation, following a tight Lipschitz constant estimation
approach based on forward reachability analysis. Compared with previous
methods, our approach addresses a much broader set of neural networks,
including heterogeneous neural networks that contain multiple types of
activation functions. Experiment results on a variety of benchmarks show the
effectiveness of our approach.


  This paper presents a linear complexity iterative rake detector for the
recently proposed orthogonal time frequency space (OTFS) modulation scheme. The
basic idea is to extract and combine the received multipath components of the
transmitted symbols in the delay-Doppler grid using linear diversity combining
schemes like maximal ratio combining (MRC), equal gain combining and selection
combining to improve the SNR of the combined signal. We reformulate the OTFS
input-output relation in the vector form by placing some null symbols in the
delay-Doppler grid thereby exploiting the block circulant property of the
channel matrix. Using the new input-output relation we propose a low complexity
iterative detector based on the MRC scheme. The bit error rate (BER)
performance of the proposed detector will be compared with the state of the art
message passing detector and orthogonal frequency division multiplexing (OFDM)
scheme employing a single tap minimum mean square error (MMSE) equalizer. We
also show that the frame error rate (FER) performance of the MRC detector can
be improved by employing error correcting codes operating in the form of a
turbo decision feedback equalizer (DFE).


  We consider the problem of uplink timing synchronization for Orthogonal Time
Frequency Space (OTFS) modulation based systems where information is embedded
in the delay-Doppler (DD) domain. For this, we propose a novel Random Access
(RA) preamble waveform based on OTFS modulation. We also propose a method to
estimate the round-trip propagation delay between a user terminal (UT) and the
base station (BS) based on the received RA preambles in the DD domain. This
estimate (known as the timing advance estimate) is fed back to the respective
UTs so that they can advance their uplink timing in order that the signal from
all UTs in a cell is received at the BS in a time-synchronized manner. Through
analysis and simulations we study the impact of OTFS modulation parameters of
the RA preamble on the probability of timing error, which gives valuable
insights on how to choose these parameters. Exhaustive numerical simulations of
high mobility scenarios suggests that the timing error probability (TEP)
performance of the proposed OTFS based RA is much more robust to channel
induced multi-path Doppler shift when compared to the RA method in Fourth
Generation (4G) systems.


  We present a preliminary study on an end-to-end variational autoencoder (VAE)
for sound morphing. Two VAE variants are compared: VAE with dilation layers
(DC-VAE) and VAE only with regular convolutional layers (CC-VAE). We combine
the following loss functions: 1) the time-domain mean-squared error for
reconstructing the input signal, 2) the Kullback-Leibler divergence to the
standard normal distribution in the bottleneck layer, and 3) the classification
loss calculated from the bottleneck representation. On a database of spoken
digits, we use 1-nearest neighbor classification to show that the sound classes
separate in the bottleneck layer. We introduce the Mel-frequency cepstrum
coefficient dynamic time warping (MFCC-DTW) deviation as a measure of how well
the VAE decoder projects the class center in the latent (bottleneck) layer to
the center of the sounds of that class in the audio domain. In terms of
MFCC-DTW deviation and 1-NN classification, DC-VAE outperforms CC-VAE. These
results for our parametrization and our dataset indicate that DC-VAE is more
suitable for sound morphing than CC-VAE, since the DC-VAE decoder better
preserves the topology when mapping from the audio domain to the latent space.
Examples are given both for morphing spoken digits and drum sounds.


  In the high-dimensional sparse modeling literature, it has been crucially
assumed that the sparsity structure of the model is homogeneous over the entire
population. That is, the identities of important regressors are invariant
across the population and across the individuals in the collected sample. In
practice, however, the sparsity structure may not always be invariant in the
population, due to heterogeneity across different sub-populations. We consider
a general, possibly non-smooth M-estimation framework, allowing a possible
structural change regarding the identities of important regressors in the
population. Our penalized M-estimator not only selects covariates but also
discriminates between a model with homogeneous sparsity and a model with a
structural change in sparsity. As a result, it is not necessary to know or
pretest whether the structural change is present, or where it occurs. We derive
asymptotic bounds on the estimation loss of the penalized M-estimators, and
achieve the oracle properties. We also show that when there is a structural
change, the estimator of the threshold parameter is super-consistent. If the
signal is relatively strong, the rates of convergence can be further improved
and asymptotic distributional properties of the estimators including the
threshold estimator can be established using an adaptive penalization. The
proposed methods are then applied to quantile regression and logistic
regression models and are illustrated via Monte Carlo experiments.


  The Spitzer Space Telescope has three science instruments (IRAC, MIPS, and
IRS) that can take images at 3.6, 4.5, 5.8, 8.0, 24, 70, and 160 microns,
spectra over 5--38 microns, and spectral energy distribution over 52--100
microns. The Spitzer archive contains targeted imaging observations for more
than 100 PNe. Spitzer legacy surveys, particularly the GLIMPSE survey of the
Galactic plane, contain additional serendipitous imaging observations of PNe.
Spitzer imaging and spectroscopic observations of PNe allow us to investigate
atomic/molecular line emission and dust continuum from the nebulae as well as
circumstellar dust disks around the central stars. Highlights of Spitzer
observations of PNe are reviewed in this paper.


  This article proposes and evaluates a technique to predict the level of
interference in wireless networks. We design a recursive predictor that
estimates future interference values by filtering measured interference at a
given location. The predictor's parameterization is done offline by translating
the autocorrelation of interference into an autoregressive moving average
(ARMA) representation. This ARMA model is inserted into a steady-state Kalman
filter enabling nodes to predict with low computational effort. Results show a
good accuracy of predicted values versus true values for relevant time
horizons. Although the predictor is parameterized for Poisson-distributed
nodes, Rayleigh fading, and fixed message lengths, a sensitivity analysis shows
that it also tends to work well in more general network scenarios. Numerical
examples for underlay device-to-device communications, a common wireless sensor
technology, and coexistence scenarios of Wi-Fi and LTE illustrate its broad
applicability. The predictor can be applied as part of interference management
to improve medium access, scheduling, and radio resource allocation.