  Videos are inherently multimodal. This paper studies the problem of how to
fully exploit the abundant multimodal clues for improved video categorization.
We introduce a hybrid deep learning framework that integrates useful clues from
multiple modalities, including static spatial appearance information, motion
patterns within a short time window, audio information as well as long-range
temporal dynamics. More specifically, we utilize three Convolutional Neural
Networks (CNNs) operating on appearance, motion and audio signals to extract
their corresponding features. We then employ a feature fusion network to derive
a unified representation with an aim to capture the relationships among
features. Furthermore, to exploit the long-range temporal dynamics in videos,
we apply two Long Short Term Memory networks with extracted appearance and
motion features as inputs. Finally, we also propose to refine the prediction
scores by leveraging contextual relationships among video semantics. The hybrid
deep learning framework is able to exploit a comprehensive set of multimodal
features for video classification. Through an extensive set of experiments, we
demonstrate that (1) LSTM networks which model sequences in an explicitly
recurrent manner are highly complementary with CNN models; (2) the feature
fusion network which produces a fused representation through modeling feature
relationships outperforms alternative fusion strategies; (3) the semantic
context of video classes can help further refine the predictions for improved
performance. Experimental results on two challenging benchmarks, the UCF-101
and the Columbia Consumer Videos (CCV), provide strong quantitative evidence
that our framework achieves promising results: $93.1\%$ on the UCF-101 and
$84.5\%$ on the CCV, outperforming competing methods with clear margins.


  This study investigates the charging-up effect on the Topmetal-II- chip in
Gas Micro-Pixel Detectors(GMPD). It is found that this effect differs from the
charging-up typically observed in gas detector multiplier devices and increases
the relative gain of the detector. The research indicates that this effect
originates from the accumulation of charges on the insulating layer of the
chip's pixel surface. Iterative simulations using COMSOL and GARFIELD++ are
employed to model the variation of detector relative gain with the charging-up
effect, and a simple yet effective model is proposed, which aligns well with
experimental data. The feasibility of validating the deposition of resistive
materials and adjusting the local voltage distribution on the chip to suppress
charging-up effects and enhance the relative gain is also verified.


  A projection space is a collection of spaces interrelated by the
combinatorics of projection onto tensor factors in a symmetric monoidal
background category. Examples include classical configuration spaces, orbit
configuration spaces, the graphical configuration spaces of Eastwood--Huggett,
the simplicial configuration spaces of Cooper--de Silva--Sazdanovic, the
generalized configuration spaces of Petersen, and Stiefel manifolds. We show
that, under natural assumptions on the background category, the homology of a
projection space is calculated by the Chevalley--Eilenberg complex of a certain
generalized Lie algebra. We identify conditions on this Lie algebra implying
representation stability in the classical setting of finite sets and
injections.


  This work focuses on a class of regime-switching jump diffusion processes
with a countably infinite state space for the discrete component. Such
processes can be used to model complex hybrid systems in which both structural
changes, small fluctuations as well as big spikes coexist and are intertwined.
The paper provides weak sufficient conditions for Feller and strong Feller
properties and irreducibility for such processes. The conditions are presented
in terms of the coefficients of the associated stochastic differential
equations.


  We summarize recent results on QCD corrections to various observables in
semileptonic $b$ quark decays. For massless leptons in the final state we
present effects of such corrections on triple differential distribution of
leptons which are important in studies of polarized $b$ quark decays. Analogous
formulas for distributions of neutrinos are applicable in decays of polarized
$c$ quarks. In the case of decays with a $\tau$ lepton in the final state mass
effect of $\tau$ has to be included. In this case we concentrate on corrections
to the total decay width.


  We conjecture that hidden state vectors corresponding to individual input
tokens encode information sufficient to accurately predict several tokens
ahead. More concretely, in this paper we ask: Given a hidden (internal)
representation of a single token at position $t$ in an input, can we reliably
anticipate the tokens that will appear at positions $\geq t + 2$? To test this,
we measure linear approximation and causal intervention methods in GPT-J-6B to
evaluate the degree to which individual hidden states in the network contain
signal rich enough to predict future hidden states and, ultimately, token
outputs. We find that, at some layers, we can approximate a model's output with
more than 48% accuracy with respect to its prediction of subsequent tokens
through a single hidden state. Finally we present a "Future Lens" visualization
that uses these methods to create a new view of transformer states.


  Shared memory emulation can be used as a fault-tolerant and highly available
distributed storage solution or as a low-level synchronization primitive.
Attiya, Bar-Noy, and Dolev were the first to propose a single-writer,
multi-reader linearizable register emulation where the register is replicated
to all servers. Recently, Cadambe et al. proposed the Coded Atomic Storage
(CAS) algorithm, which uses erasure coding for achieving data redundancy with
much lower communication cost than previous algorithmic solutions.
  Although CAS can tolerate server crashes, it was not designed to recover from
unexpected, transient faults, without the need of external (human)
intervention. In this respect, Dolev, Petig, and Schiller have recently
developed a self-stabilizing version of CAS, which we call CASSS. As one would
expect, self-stabilization does not come as a free lunch; it introduces,
mainly, communication overhead for detecting inconsistencies and stale
information. So, one would wonder whether the overhead introduced by
self-stabilization would nullify the gain of erasure coding.
  To answer this question, we have implemented and experimentally evaluated the
CASSS algorithm on PlanetLab; a planetary scale distributed infrastructure. The
evaluation shows that our implementation of CASSS scales very well in terms of
the number of servers, the number of concurrent clients, as well as the size of
the replicated object. More importantly, it shows (a) to have only a constant
overhead compared to the traditional CAS algorithm (which we also implement)
and (b) the recovery period (after the last occurrence of a transient fault) is
as fast as a few client (read/write) operations. Our results suggest that CASSS
does not significantly impact efficiency while dealing with automatic recovery
from transient faults and bounded size of needed resources.


  Monolayer transition metal dichalcogenides (TMDs) are direct gap
semiconductors that hold great promise for advanced applications in photonics
and optoelectronics. Understanding the interplay between their radiative and
non-radiative recombination pathways is thus of crucial importance not only for
fundamental studies but also for the design of future nanoscale on-chip
devices. Here, we investigate the interplay between doping and exciton-exciton
annihilation (EEA) and their impact on the photoluminescence quantum yield in
different TMD samples and related heterostructures. We demonstrate that the EEA
threshold increases in highly doped samples, where the radiative and
non-radiative recombination of trions dominates.


  We present a study of the inclusive production in $p \overline p $ collisions
of the pentaquark states $P_c(4440)$ and $P_c(4457)$ with the decay to the
$J/\psi p$ final state previously observed by the LHCb experiment. Using a
sample of candidates originating from decays of $b$-flavored hadrons, we find
an enhancement in the $J/\psi p$ invariant mass distribution consistent with a
sum of $P_c(4440)$ and $P_c(4457)$. The significance, with the input parameters
set to the LHCb values, is $3.0\sigma$. This is the first confirmatory evidence
for these pentaquark states. We measure the ratio $N_{\rm prompt}/N_{\rm
nonprompt}=0.05 \pm 0.39$ and set an upper limit of 0.8 at the 95\% credibility
level. The ratio of the yield of the $P_c(4312)$ to the sum of $P_c(4440)$ and
$P_c(4457)$ is less than 0.6 at the 95\% credibility level. The study is based
on $10.4~\rm{fb^{-1}}$ of data collected by the D0 experiment at the Fermilab
Tevatron collider.


  A quantum master equation is obtained for identical fermions by including a
relaxation term in addition to the mean-field Hamiltonian. [Huang C F and Huang
K N 2004 Chinese J. Phys. ${\bf 42}$ 221; Gebauer R and Car R 2004 Phys. Rev. B
${\bf 70}$ 125324] It is proven in this paper that both the positivity and
Pauli's exclusion principle are preserved under this equation when there exists
an upper bound for the transition rate. Such an equation can be generalized to
model BCS-type quasiparticles, and is reduced to a Markoff master equation of
Lindblad form in the low-density limit with respect to particles or holes.


  We strengthen certain known results saying that separately regular functions
are rational and separately Nash functions are semialgebraic. The approach
presented here unifies and highlights the similarities between the two
problems.


  The complexity of droplet microfluidics grows by implementing parallel
processes and multiple functionalities on a single device. This poses a
challenge to the engineer designing the microfluidic networks. In today's
design processes, the engineer relies on calculations, assumptions,
simplifications, as well as his/her experiences and intuitions. In order to
validate the obtained specification of the microfluidic network, usually a
prototype is fabricated and physical experiments are conducted thus far. In
case the design does not implement the desired functionality, this prototyping
iteration is repeated - obviously resulting in an expensive and time-consuming
design process. In order to avoid unnecessary prototyping loops, simulation
methods could help to validate the specification of the microfluidic network
before any prototype is fabricated. However, state-of-the-art simulation tools
come with severe limitations, which prevent their utilization for
practically-relevant applications. More precisely, they are often not dedicated
to droplet microfluidics, cannot handle the required physical phenomena, are
not publicly available, and can hardly be extended. In this work, we present an
advanced simulation approach for droplet microfluidics which addresses these
shortcomings and, eventually, allows to simulate practically-relevant
applications. To this end, we propose a simulation framework which directly
works on the specification of the design, supports essential physical
phenomena, is publicly available, and easy to extend. Evaluations and case
studies demonstrate the benefits of the proposed simulator: While current
state-of-the-art tools were not applicable for practically-relevant
microfluidic networks, the proposed solution allows to reduce the design time
and costs e.g. of a drug screening device from one person month and USD 1200,
respectively, to just a fraction of that.


  Here we present ComPPI, a cellular compartment specific database of proteins
and their interactions enabling an extensive, compartmentalized protein-protein
interaction network analysis (http://ComPPI.LinkGroup.hu). ComPPI enables the
user to filter biologically unlikely interactions, where the two interacting
proteins have no common subcellular localizations and to predict novel
properties, such as compartment-specific biological functions. ComPPI is an
integrated database covering four species (S. cerevisiae, C. elegans, D.
melanogaster and H. sapiens). The compilation of nine protein-protein
interaction and eight subcellular localization data sets had four curation
steps including a manually built, comprehensive hierarchical structure of more
than 1600 subcellular localizations. ComPPI provides confidence scores for
protein subcellular localizations and protein-protein interactions. ComPPI has
user-friendly search options for individual proteins giving their subcellular
localization, their interactions and the likelihood of their interactions
considering the subcellular localization of their interacting partners.
Download options of search results, whole proteomes, organelle-specific
interactomes and subcellular localization data are available on its website.
Due to its novel features, ComPPI is useful for the analysis of experimental
results in biochemistry and molecular biology, as well as for proteome-wide
studies in bioinformatics and network science helping cellular biology,
medicine and drug design.


  In this paper, we study pointed rank one Hopf algebras and Hopf-Ore
extensions of group algebras, over an arbitrary field $k$. It is proved that
the rank of a Hopf-Ore extension of a group algebra is one or two or infinite.
It is also shown that an arbitrary (finite or infinite dimensional) pointed
Hopf algebra of rank one is isomorphic to a quotient of a Hopf-Ore extension of
its coradical, a group algebra. We classify the finite dimensional simple
modules and describe a family of indecomposable modules over a Hopf-Ore
extension $H=kG(\chi, a,\delta)$ and its quotient $H'$ of rank one, where
$\chi(a)\neq 1$, $G$ is an abelian group and $k$ is an algebraically closed
field. The decomposition of the tensor products of two finite dimensional
simple modules into a direct sum of indecomposable modules is given too. We
also determine all simple objects and a family of indecomposable projective
objects in the categories of all weight modules over $H$ and $H'$.


  Topological Kondo insulators (TKIs) are new type of symmetry-protected
topological insulators, which develop through the interplay of strong
correlations and spin-orbit interactions. In these materials, the bulk is a
perfect band insulator due to Kondo screening of localized moments via
conduction electrons. Furthermore, strong spin-orbit coupling (SOC) and crystal
field effect (CFE) of the localized moments result in a nonlocal odd-parity,
time-reversal invariant hybridization between the local-moments and conduction
bands, which creates a ground-state with nontrivial topology and gapless
surface excitations (Physical Review Letters 104 (2010) 106408). In the present
work, we develop a self-consistent theory to study topological Kondo insulators
at the mean-field level. To achieve this, we apply slave-boson mean-field
theory for a system with and without periodic boundary conditions, in order to
study the system at bulk and slab geometry configuration. This enables us to
observe a clear signature of protected edge states through band structure and
calculation of spectral functions.


  We study ground states of a hybrid system consisting of a polymer and an
attractive nanowire by means of computer simulations. Depending on structural
and energetic properties of the substrate, we find different adsorbed polymer
conformations, amongst which are spherical droplets attached to the wire and
monolayer tubes surrounding it. We construct the complete conformational phase
diagram and analyze in more detail particularly interesting polymer-tube
conformations.


  Triggered star formation around HII regions could be an important process.
The Galactic HII region RCW 79 is a prototypical object for triggered high-mass
star formation. We take advantage of Herschel data from the surveys HOBYS,
"Evolution of Interstellar Dust", and Hi-Gal to extract compact sources in this
region, complemented with archival 2MASS, Spitzer, and WISE data to determine
the physical parameters of the sources (e.g., envelope mass, dust temperature,
and luminosity) by fitting the spectral energy distribution. We obtained a
sample of 50 compact sources, 96% of which are situated in the
ionization-compressed layer of cold and dense gas that is characterized by the
column density PDF with a double-peaked lognormal distribution. The 50 sources
have sizes of 0.1-0.4 pc with a typical value of 0.2 pc, temperatures of 11-26
K, envelope masses of 6-760 $M_\odot$, densities of 0.1-44 $\times$ $10^5$
cm$^{-3}$, and luminosities of 19-12712 $L_\odot$. The sources are classified
into 16 class 0, 19 intermediate, and 15 class I objects. Their distribution
follows the evolutionary tracks in the diagram of bolometric luminosity versus
envelope mass (Lbol-Menv) well. A mass threshold of 140 $M_\odot$, determined
from the Lbol-Menv diagram, yields 12 candidate massive dense cores that may
form high-mass stars. The core formation efficiency (CFE) for the 8 massive
condensations shows an increasing trend of the CFE with density. This suggests
that the denser the condensation, the higher the fraction of its mass
transformation into dense cores, as previously observed in other high-mass
star-forming regions.


  We provide a detailed analysis of the problems and prospects of superstring
theory c. 1986, anticipating much of the progress of the decades to follow.


  The topological Hochschild homology THH(R) of a commutative S-algebra
(E_infty ring spectrum) R naturally has the structure of a commutative
R-algebra in the strict sense, and of a Hopf algebra over R in the homotopy
category. We show, under a flatness assumption, that this makes the Boekstedt
spectral sequence converging to the mod p homology of THH(R) into a Hopf
algebra spectral sequence. We then apply this additional structure to the study
of some interesting examples, including the commutative S-algebras ku, ko, tmf,
ju and j, and to calculate the homotopy groups of THH(ku) and THH(ko) after
smashing with suitable finite complexes. This is part of a program to make
systematic computations of the algebraic K-theory of S-algebras, by means of
the cyclotomic trace map to topological cyclic homology.


  (Abridged) We discuss the design considerations of the EXPLORE (EXtra-solar
PLanet Occultation REsearch) project, a series of transiting planet searches
using 4-m-class telescopes to continuously monitor a single field of stars in
the Galactic Plane in each ~2 week observing campaign. We discuss the general
factors which determine the efficiency and the number of planets found by a
transit search, including time sampling strategy and field selection. The
primary goal is to select the most promising planet candidates for radial
velocity follow-up observations. We show that with very high photometric
precision light curves that have frequent time sampling and at least two
detected transits, it is possible to uniquely solve for the main parameters of
the eclipsing system (including planet radius) based on several important
assumptions about the central star. Together with a measured spectral type for
the star, this unique solution for orbital parameters provides a powerful
method for ruling out most contaminants to transiting planet candidates. For
the EXPLORE project, radial velocity follow-up observations for companion mass
determination of the best candidates are done on 8-m-class telescopes within
two or three months of the photometric campaigns. This same-season follow-up is
made possible by the use of efficient pipelines to produce high quality light
curves within weeks of the observations. We conclude by presenting early
results from our first search, EXPLORE I, in which we reached <1% rms
photometric precision (measured over a full night) on ~37,000 stars to I <=
18.2.


  The Jagiellonian Positron Emission Tomograph (J-PET) project carried out in
the Institute of Physics of the Jagiellonian University is focused on
construction and tests of the first prototype of PET scanner for medical
diagnostic which allows for the simultaneous 3D imaging of the whole human body
using organic scintillators. The J-PET prototype consists of 192 scintillator
strips forming three cylindrical layers which are optimized for the detection
of photons from the electron-positron annihilation with high time- and high
angular-resolutions. In this article we present time calibration and
synchronization of the whole J-PET detection system by irradiating each single
detection module with a 22Na source and a small detector providing common
reference time for synchronization of all the modules.


  Recovering the Cosmic Microwave Background (CMB) from WMAP data requires
galactic foreground emissions to be accurately separated out. Most component
separation techniques rely on second order statistics such as Internal Linear
Combination (ILC) techniques. In this paper, we present a new WMAP 9-year CMB
map, with 15 arcmin resolution, which is reconstructed using a recently
introduced sparse component separation technique, coined Local Generalized
Morphological Component Analysis (LGMCA). LGMCA emphasizes on the sparsity of
the components to be retrieved in the wavelet domain. We show that although
derived from a radically different separation criterion ({i.e. sparsity), the
LGMCA-WMAP 9 map and its power spectrum are fully consistent with their more
recent estimates from WMAP 9.


  In this paper, we shall give an explicit proof that constacyclic codes over
finite commutative rings can be realized as ideals in some twisted group rings.
Also, we shall study isometries between those codes and, finally, we shall
study k-Galois LCD constacyclic codes over finite fields. In particular, we
shall characterize constacyclic LCD codes with respect to Euclidean inner
product in terms of its idempotent generators and the classical involution
using the twisted group algebras structures and find some good LCD codes.


  We present exact analytical black hole solutions with conformal anomaly in
AdS space and discuss the thermodynamical properties of these black hole
solutions. These black holes can have a positive, zero and negative constant
curvature horizon, respectively. For the black hole with a positive constant
curvature horizon, there exists a minimal horizon determined by the coefficient
of the trace anomaly, the black hole with a smaller horizon is
thermodynamically unstable, while it is stable for the case with a larger
horizon. The Hawking-Page transition happens in this case. For the black hole
with a Ricci flat horizon, the black hole is always thermodynamically stable
and there is no Hawking-Page transition. In the case of the black hole with a
negative constant curvature horizon, there exists a critical value for the
coefficient of the trace anomaly, under this critical value, the black hole is
always thermodynamical stable and the Hawking-Page transition does not happen.
When the coefficient is beyond the critical value, the black hole with a
smaller horizon is thermodynamically unstable, but it becomes stable for the
case with a larger horizon, the Hawking-Page transition always happens in this
case. The latter is a new feature for the black holes with a negative constant
curvature horizon.


  The formal deformation space of a supersingular Barsotti-Tate group over of
dimension two equipped with an action of Z_{p^2} is known to be isomorphic to
the formal spectrum of a power series ring in two variables. If one chooses an
extra Z_{p^2}-linear endomorphism of the p-divisible group then the locus in
the formal deformation space formed by those deformations for which the extra
endomorphism lifts is a closed formal subscheme of codimension two. We give a
complete description of the irreducible components of this formal subscheme,
compute the multiplicities of these components, and compute the intersection
numbers of the components with a distinguished closed formal subscheme of
codimension one. These calculations, which extend the Gross-Keating theory of
quasi-canonical lifts, are used in the companion article "Intersection theory
on Shimura surfaces II" to compute global intersection numbers of special
cycles on the integral model of a Shimura surface.


  Byzantine Fault Tolerant (BFT) consensus exhibits higher throughput in
comparison to Proof of Work (PoW) in blockchains. But BFT-based protocols
suffer from scalability problems with respect to the number of replicas in the
network. The main reason for this limitation is the quadratic message
complexity of BFT protocols. Previously, proposed solutions improve BFT
performance for normal operation, but will fall back to quadratic message
complexity once the protocol observes a certain number of failures. This makes
the protocol performance unpredictable as it is not guaranteed that the network
will face a a certain number of failures.
  As a result, such protocols are only scalable when conditions are favorable
(i.e., the number of failures are less than a given threshold). To address this
issue we propose Proteus, a new BFT-based consensus protocol which elects a
subset of nodes $c$ as a root committee. Proteus guarantees stable performance,
regardless of the number of failures in the network and it improves on the
quadratic message complexity of typical BFT-based protocols to $O(cn)$, where
$c<<n$, for large $n$.
  Thus, message complexity remains small and less than quadratic when $c$ is
asymptotically smaller than $n$, and this helps the protocol to provide stable
performance even during the view change process (change of root committee). Our
view change process is different than typical BFT protocols as it replaces the
whole root committee compared to replacing a single primary in other protocols.
We deployed and tested our protocol on $200$ Amazon $EC2$ instances, with two
different baseline BFT protocols (PBFT and Bchain) for comparison. In these
tests, our protocol outperformed the baselines by more than $2\times$ in terms
of throughput as well as latency.


  We present an algorithm for doing Gibbs sampling on a quantum computer. The
algorithm combines phase estimation for a Szegedy operator, and Grover's
algorithm. For any $\epsilon>0$, the algorithm will sample a probability
distribution in ${\cal O}(\frac{1}{\sqrt{\delta}})$ steps with precision ${\cal
O}(\epsilon)$. Here $\delta$ is the distance between the two largest eigenvalue
magnitudes of the transition matrix of the Gibbs Markov chain used in the
algorithm. It takes ${\cal O}(\frac{1}{\delta})$ steps to achieve the same
precision if one does Gibbs sampling on a classical computer.


  We investigate the proportion of fixed point free permutations (derangements)
in finite transitive permutation groups. This article is the first in a series
where we prove a conjecture of Shalev that the proportion of such elements is
bounded away from zero for a simple finite group. In fact, there are much
stronger results. This article focuses on finite Chevalley groups of bounded
rank. We also discuss derangements in algebraic groups and in more general
primitive groups. These results have applications in questions about
probabilistic generation of finite simple groups and maps between varieties
over finite fields.


  Integrability condition of Hamiltonian perturbations of integrable
Hamiltonian PDEs of hydrodynamic type up to the second order approximation is
considered.


  We propose and study the feasibility of wireless quantum key distribution
(QKD) in indoor environments. Such systems are essential in providing wireless
access to the developing quantum communications networks. We find a practical
regime of operation, where, in the presence of external light sources and loss,
secret keys can be exchanged. Our findings identify the trade-off between the
acceptable amount of background light and the receiver field of view, where the
latter affects the ease of access to the QKD system. In particular, we show
that, using a proper setting, we can provide mobility for the QKD users without
imposing stringent conditions on beam steering.


  Two architectures that generalize convolutional neural networks (CNNs) for
the processing of signals supported on graphs are introduced. We start with the
selection graph neural network (GNN), which replaces linear time invariant
filters with linear shift invariant graph filters to generate convolutional
features and reinterprets pooling as a possibly nonlinear subsampling stage
where nearby nodes pool their information in a set of preselected sample nodes.
A key component of the architecture is to remember the position of sampled
nodes to permit computation of convolutional features at deeper layers. The
second architecture, dubbed aggregation GNN, diffuses the signal through the
graph and stores the sequence of diffused components observed by a designated
node. This procedure effectively aggregates all components into a stream of
information having temporal structure to which the convolution and pooling
stages of regular CNNs can be applied. A multinode version of aggregation GNNs
is further introduced for operation in large scale graphs. An important
property of selection and aggregation GNNs is that they reduce to conventional
CNNs when particularized to time signals reinterpreted as graph signals in a
circulant graph. Comparative numerical analyses are performed in a source
localization application over synthetic and real-world networks. Performance is
also evaluated for an authorship attribution problem and text category
classification. Multinode aggregation GNNs are consistently the best performing
GNN architecture.


  Understanding how visual information is encoded in biological and artificial
systems often requires vision scientists to generate appropriate stimuli to
test specific hypotheses. Although deep neural network models have
revolutionized the field of image generation with methods such as image style
transfer, available methods for video generation are scarce. Here, we introduce
the Spatiotemporal Style Transfer (STST) algorithm, a dynamic visual stimulus
generation framework that allows powerful manipulation and synthesis of video
stimuli for vision research. It is based on a two-stream deep neural network
model that factorizes spatial and temporal features to generate dynamic visual
stimuli whose model layer activations are matched to those of input videos. As
an example, we show that our algorithm enables the generation of model
metamers, dynamic stimuli whose layer activations within our two-stream model
are matched to those of natural videos. We show that these generated stimuli
match the low-level spatiotemporal features of their natural counterparts but
lack their high-level semantic features, making it a powerful paradigm to study
object recognition. Late layer activations in deep vision models exhibited a
lower similarity between natural and metameric stimuli compared to early
layers, confirming the lack of high-level information in the generated stimuli.
Finally, we use our generated stimuli to probe the representational
capabilities of predictive coding deep networks. These results showcase
potential applications of our algorithm as a versatile tool for dynamic
stimulus generation in vision science.


  Graph convolution networks (GCN) have emerged as the leading method to
classify node classes in networks, and have reached the highest accuracy in
multiple node classification tasks. In the absence of available tagged samples,
active learning methods have been developed to obtain the highest accuracy
using the minimal number of queries to an oracle. The current best active
learning methods use the sample class uncertainty as selection criteria.
However, in graph based classification, the class of each node is often related
to the class of its neighbors. As such, the uncertainty in the class of a
node's neighbor may be a more appropriate selection criterion. We here propose
two such criteria, one extending the classical uncertainty measure, and the
other extending the page-rank algorithm. We show that the latter is optimal
when the fraction of tagged nodes is low, and when this fraction grows to one
over the average degree, the regional uncertainty performs better than all
existing methods. While we have tested this methods on graphs, such methods can
be extended to any classification problem, where a distance metrics can be
defined between the input samples.
  All the code used can be accessed at : https://github.com/louzounlab/graph-al
  All the datasets used can be accessed at :
https://github.com/louzounlab/DataSets


  We investigate large wireless networks subject to security constraints. In
contrast to point-to-point, interference-limited communications considered in
prior works, we propose active cooperative relaying based schemes. We consider
a network with $n_l$ legitimate nodes, $n_e$ eavesdroppers, and path loss
exponent $\alpha\geq 2$. As long as $n_e^2(\log(n_e))^{\gamma}=o(n_l)$, for
some positive $\gamma$, we show one can obtain unbounded secure aggregate rate.
This means zero-cost secure communication, given fixed total power constraint
for the entire network. We achieve this result through (i) the source using
Wyner randomized encoder and a serial (multi-stage) block Markov scheme, to
cooperate with the relays and (ii) the relays acting as a virtual multi-antenna
to apply beamforming against the eavesdroppers. Our simpler parallel
(two-stage) relaying scheme can achieve the same unbounded secure aggregate
rate when
$n_e^{\frac{\alpha}{2}+1}(\log(n_e))^{\gamma+\delta(\frac{\alpha}{2}+1)}=o(n_l)$
holds, for some positive $\gamma,\delta$. Finally, we study the improvement (to
the detriment of legitimate nodes) the eavesdroppers achieve in terms of the
information leakage rate in a large cooperative network in case of collusion.
We show that again the zero-cost secure communication is possible, if
$n_e^{(2+\frac{2}{\alpha})}(\log n_e)^{\gamma}=o(n_l)$ holds, for some positive
$\gamma$; i.e., in case of collusion slightly fewer eavesdroppers can be
tolerated compared to the non-colluding case.


  Recently, effective one-dimensional configuration coordinate diagrams have
been utilized to calculate the line shapes of luminescence spectra and
non-radiative carrier capture coefficients via point defects. Their
calculations necessitate accurate total energies as a function of configuration
coordinates. Although supercells under periodic boundary conditions are
commonly employed, the spurious cell size effects have not been previously
considered. In this study, we have proposed a correction energy formalism and
verified its effectiveness by applying it to a nitrogen vacancy in GaN.


  It has long been accepted that a possible mechanism for explaining the
existence of magnetic white dwarfs is the merger of a binary white dwarf
system, as there are viable mechanisms for producing sustainable magnetic
fields within the merger product. However, the lack of rapid rotators in the
magnetic white dwarf population has been always considered a problematic issue
of this scenario. Smoothed Particle Hydrodynamics simulations show that in
mergers in which the two white dwarfs have different masses a disc around the
central compact object is formed. If the central object is magnetized it can
interact with the disc through its magnetosphere. The torque applied by the
disc changes the spin of the star, whereas the transferred angular momentum
from the star to the disc determines the properties of the disc. In this work
we build a model for the disc evolution under the effect of magnetic accretion,
and for the angular momentum evolution of the star, which can be compared with
the observations. Our model predicts that the magnetospheric interaction of
magnetic white dwarfs with their discs results in a significant spin down, and
we show that for magnetic white dwarfs with relatively strong fields (larger
than 10 MG) the observed rotation periods of the magnetic white dwarf
population can be reproduced. We also investigate whether turbulence can be
sustained during the late phases of the evolution of the system. When a
critical temperature below which turbulence is not sustained is introduced into
the model, the periods of the three fast rotating, strongly magnetic, massive
white dwarfs in the solar neighborhood are recovered.


  Let $\Omega_n$ denote the class of $n \times n$ doubly stochastic matrices
(each such matrix is entrywise nonnegative and every row and column sum is 1).
We study the diagonals of matrices in $\Omega_n$. The main question is: which
$A \in \Omega_n$ are such that the diagonals in $A$ that avoid the zeros of $A$
all have the same sum of their entries. We give a characterization of such
matrices, and establish several classes of patterns of such matrices.


  In this paper, we present substantial evidence that a deep neural network
will intrinsically learn the appropriate way to discretize the ideal continuous
reconstruction filter. Currently, the Ram-Lak filter or heuristic filters which
impose different noise assumptions are used for filtered back-projection. All
of these, however, inhibit a fully data-driven reconstruction deep learning
approach. In addition, the heuristic filters are not chosen in an optimal
sense. To tackle this issue, we propose a formulation to directly learn the
reconstruction filter. The filter is initialized with the ideal Ramp filter as
a strong pre-training and learned in frequency domain. We compare the learned
filter with the Ram-Lak and the Ramp filter on a numerical phantom as well as
on a real CT dataset. The results show that the network properly discretizes
the continuous Ramp filter and converges towards the Ram-Lak solution. In our
view these observations are interesting to gain a better understanding of deep
learning techniques and traditional analytic techniques such as Wiener
filtering and discretization theory. Furthermore, this will allow fully
trainable data-driven reconstruction deep learning approaches.


  A collision between two molecular clouds is one possible candidate for
high-mass star formation. The HII region RCW 36, located in the Vela molecular
ridge, contains a young star cluster with two O-type stars. We present new CO
observations of RCW 36 with NANTEN2, Mopra, and ASTE using $^{12}$CO($J$ = 1-0,
2-1, 3-2) and $^{13}$CO($J$ = 2-1) line emissions. We have discovered two
molecular clouds lying at the velocities $V_\mathrm{LSR} \sim$5.5 and 9 km
s$^{-1}$. Both clouds are likely to be physically associated with the star
cluster, as verified by the good spatial correspondence among the two clouds,
infrared filaments, and the star cluster. We also found a high intensity ratio
of $\sim$0.6-1.2 for CO $J$ = 3-2 / 1-0 toward both clouds, indicating that the
gas temperature has been increased due to heating by the O-type stars. We
propose that the O-type stars in RCW 36 were formed by a collision between the
two clouds, with a relative velocity separation of 5 km s$^{-1}$. The
complementary spatial distributions and the velocity separation of the two
clouds are in good agreement with observational signatures expected for O-type
star formation triggered by a cloud-cloud collision. We also found a
displacement between the complementary spatial distributions of the two clouds,
which we estimate to be 0.3 pc assuming the collision angle to be 45$^{\circ}$
relative to the line-of-sight. We estimate the collision timescale to be
$\sim$10$^5$ yr. It is probable that the cluster age by Ellerbroek et al.
(2013b) is dominated by the low-mass members which were not formed under the
triggering by cloud-cloud collision, and that the O-type stars in the center of
the cluster are explained by the collisional triggering independently from the
low-mass star formation.


  Modern convolutional networks are not shift-invariant, as small input shifts
or translations can cause drastic changes in the output. Commonly used
downsampling methods, such as max-pooling, strided-convolution, and
average-pooling, ignore the sampling theorem. The well-known signal processing
fix is anti-aliasing by low-pass filtering before downsampling. However, simply
inserting this module into deep networks degrades performance; as a result, it
is seldomly used today. We show that when integrated correctly, it is
compatible with existing architectural components, such as max-pooling and
strided-convolution. We observe \textit{increased accuracy} in ImageNet
classification, across several commonly-used architectures, such as ResNet,
DenseNet, and MobileNet, indicating effective regularization. Furthermore, we
observe \textit{better generalization}, in terms of stability and robustness to
input corruptions. Our results demonstrate that this classical signal
processing technique has been undeservingly overlooked in modern deep networks.
Code and anti-aliased versions of popular networks are available at
https://richzhang.github.io/antialiased-cnns/ .


  Heart failure is typically diagnosed with a global function assessment, such
as ejection fraction. However, these metrics have low discriminate power,
failing to distinguish different types of this disease. Quantifying local
deformations in the form of cardiac strain can provide helpful information, but
it remains a challenge. In this work, we introduce WarpPINN, a physics-informed
neural network to perform image registration to obtain local metrics of the
heart deformation. We apply this method to cine magnetic resonance images to
estimate the motion during the cardiac cycle. We inform our neural network of
near-incompressibility of cardiac tissue by penalizing the jacobian of the
deformation field. The loss function has two components: an intensity-based
similarity term between the reference and the warped template images, and a
regularizer that represents the hyperelastic behavior of the tissue. The
architecture of the neural network allows us to easily compute the strain via
automatic differentiation to assess cardiac activity. We use Fourier feature
mappings to overcome the spectral bias of neural networks, allowing us to
capture discontinuities in the strain field. We test our algorithm on a
synthetic example and on a cine-MRI benchmark of 15 healthy volunteers. We
outperform current methodologies both landmark tracking and strain estimation.
We expect that WarpPINN will enable more precise diagnostics of heart failure
based on local deformation information. Source code is available at
https://github.com/fsahli/WarpPINN.


  A coherent seeded SU(1,1) interferometer provides a prominent technique in
the field of precision measurement. We theoretically study the phase
sensitivity of SU(1,1) interferometer with Kerr state seeding under single
intensity and homodyne detection schemes. To find the lower bound in this case
we calculate the quantum Cram\'er-Rao bound using the quantum Fisher
information technique. We found that, under some conditions, the Kerr seeding
performs better in phase sensitivity compared to the well-known vacuum and
coherent seeded case. We expect that the Kerr state might act as an alternative
non-classical state in the field of quantum information and sensing
technologies.


  We introduce the concept of a heterodimensional cycle of hyperbolic ergodic
measures and a special type of them that we call rich. Within a partially
hyperbolic context, we prove that if two measures are related by a rich
heterodimensional cycle, then the entire segment of probability measures
linking them lies within the closure of measures supported on periodic orbits.
Motivated by the occurrence of robust heterodimensional cycles of hyperbolic
basic sets, we study robust rich heterodimensional cycles of measures providing
a framework for this phenomenon for diffeomorphisms. In the setting of skew
products, we construct an open set of maps having uncountably many measures
related by rich heterodimensional cycles.


  We discuss a recent work by J.~Lawrence et al.[arxiv.org/abs/2208.11793]
criticizing relational quantum mechanics (RQM) and based on a famous
nonlocality theorem Going back to Greenberger Horne and Zeilinger (GHZ). Here,
we show that the claims presented in this recent work are unjustified and we
debunk the analysis.


  A closed subgroup of a semisimple algebraic group is called irreducible if it
lies in no proper parabolic subgroup. In this paper we classify all irreducible
$A_1$ subgroups of exceptional algebraic groups $G$. Consequences are given
concerning the representations of such subgroups on various $G$-modules: for
example, the conjugacy classes of irreducible $A_1$ subgroups are determined by
their composition factors on the adjoint module of $G$.


  In this paper we argue that the Sasaki adjunction, which formally encodes the
logicality that different authors tried to attach to the Sasaki hook as a
`quantum implicative connective', has a fundamental dynamic nature and encodes
the so-called `causal duality' (Coecke, Moore and Stubbe 2001;
quant-ph/0009100) for the particular case of a quantum measurement with a
projector as corresponding self-adjoint operator. In particular: The action of
the Sasaki hook $(a\stackrel{S}{\to}-)$ for fixed antecedent $a$ assigns to
some property ``the weakest cause before the measurement of actuality of that
property after the measurement'', i.e. ${(a\stackrel{S}{\to}b)}$ is the weakest
property that guarantees actuality of $b$ after performing the measurement
represented by the projector that has the `subspace $a$' as eigenstates for
eigenvalue 1, say, the measurement that `tests' $a$ . From this we conclude
that the logicality attributable to quantum systems contains a fundamentally
dynamic ingredient: Causal duality actually provides a new dynamic
interpretation of orthomodularity. We also reconsider the status of the Sasaki
hook within `dynamic (operational) quantum logic' (DOQL). We can derive two
labeled dynamic hooks (forwardly and backwardly) that encode how quantum
measurements act on properties. In an even more radical perspective one could
say that the transition from either classical or constructive/intuitionistic
logic to quantum logic entails besides the introduction of an additional unary
connective `operational resolution' (Coecke 2001a; math.LO/0011208) the shift
from a binary connective implication to a ternary connective where two of the
arguments refer to qualities of the system and the third, the new one, to an
obtained outcome (in a measurement).


  We review some results on the complete coupling between tensor and vector
multiplets in six-dimensional $(1,0)$ supergravity.


We present an explicit formula for Witten-Kontsevich tau-function.


  Winds of AGB stars are thought to be driven by a combination of
pulsation-induced shock waves and radiation pressure on dust. In dynamic
atmosphere and wind models, the stellar pulsation is often simulated by
prescribing a simple sinusoidal variation in velocity and luminosity at the
inner boundary of the model atmosphere. We experiment with different forms of
the luminosity variation in order to assess the effects on the wind velocity
and mass-loss rate, when progressing from the simple sinusoidal recipe towards
more realistic descriptions. Using state-of-the-art dynamical models of C-rich
AGB stars, a range of different asymmetric shapes of the luminosity variation
and a range of phase shifts of the luminosity variation relative to the radial
variation are tested. These tests are performed on two stellar atmosphere
models. The first model has dust condensation and, as a consequence, a stellar
wind is triggered, while the second model lacks both dust and wind. The first
model with dust and stellar wind is very sensitive to moderate changes in the
luminosity variation. There is a complex relationship between the luminosity
minimum, and dust condensation: changing the phase corresponding to minimum
luminosity can either increase or decrease mass-loss rate and wind velocity.
The luminosity maximum dominates the radiative pressure on the dust, which in
turn, is important for driving the wind. These effects of changed luminosity
variation are coupled with the dust formation. In contrast there is very little
change to the structure of the model without dust. Changing the luminosity
variation, both by introducing a phase shift and by modifying the shape,
influences wind velocity and the mass-loss rate. To improve wind models it
would probably be desirable to extract boundary conditions from 3D dynamical
interior models or stellar pulsation models.


  In this announcement we present a general and new approach to analyzing the
asymptotics of oscillatory Riemann-Hilbert problems. Such problems arise, in
particular, in evaluating the long-time behavior of nonlinear wave equations
solvable by the inverse scattering method. We will restrict ourselves here
exclusively to the modified Korteweg de Vries (MKdV) equation,
  $$y_t-6y^2y_x+y_{xxx}=0,\qquad -\infty<x<\infty,\ t\ge0, y(x,t=0)=y_0(x),$$
  but it will be clear immediately to the reader with some experience in the
field, that the method extends naturally and easily to the general class of
wave equations solvable by the inverse scattering method, such as the KdV,
nonlinear Schr\"odinger (NLS), and Boussinesq equations, etc., and also to
``integrable'' ordinary differential equations such as the Painlev\'e
transcendents.


  Reversible computing has emerged as a possible low cost alternative to
conventional computing in terms of speed, power consumption and computing
capability. In order to achieve reliable circuits in reversible computing,
provision for fault tolerance is necessary. A number of fault models, fault
tolerant techniques (such as parity-preserving) and testing approaches have
proposed in literature. This dissertation exploits parity-preserving
characteristics of two reversible gates which provide low cost
parity-preserving based fault tolerance. In order to extend online testability
of reversible circuits, the substitution of Peres gate has been presented. The
online testing capabilities of MCF including Swap and Fredkin gates were also
identifies. Finally a tool was developed to implement all above substitutions
and converting any reversible circuit to parity-preserving based fault tolerant
circuit.


  We develop a model of the nonlinear response to a DC electrical current of a
two dimensional electron system(2DES) placed on a magnetic field. Based on the
exact solution of the Schroedinger equation in arbitrarily strong electric and
magnetic fields, and separating the relative and guiding center coordinates, a
Kubo-like formula for the current is worked out as a response to the impurity
scattering. Self-consistent expressions determine the longitudinal and Hall
components of the electric field in terms of the DC current. The differential
resistivity displays strong Hall field-induced oscillations, in agreement with
the main features of the phenomenon observed in recent experiments.


  This paper systematically decomposes a quadrupedal robot into bipeds to
rapidly generate walking gaits and then recomposes these gaits to obtain
quadrupedal locomotion. We begin by decomposing the full-order, nonlinear and
hybrid dynamics of a three-dimensional quadrupedal robot, including its
continuous and discrete dynamics, into two bipedal systems that are subject to
external forces. Using the hybrid zero dynamics (HZD) framework, gaits for
these bipedal robots can be rapidly generated (on the order of seconds) along
with corresponding controllers. The decomposition is achieved in such a way
that the bipedal walking gaits and controllers can be composed to yield dynamic
walking gaits for the original quadrupedal robot --- the result is the rapid
generation of dynamic quadruped gaits utilizing the full-order dynamics. This
methodology is demonstrated through the rapid generation (3.96 seconds on
average) of four stepping-in-place gaits and one diagonally symmetric ambling
gait at 0.35 m/s on a quadrupedal robot --- the Vision 60, with 36 state
variables and 12 control inputs --- both in simulation and through outdoor
experiments. This suggested a new approach for fast quadrupedal trajectory
planning using full-body dynamics, without the need for empirical model
simplification, wherein methods from dynamic bipedal walking can be directly
applied to quadrupeds.


  In the $3$-gauge theory, a $3$-connection is given by a $1$-form $A$ valued
in the Lie algebra $ \mathfrak g$, a $2$-form $B$ valued in the Lie algebra
$\mathfrak h $ and a $3$-form $C$ valued in the Lie algebra $ \mathfrak l $,
where $(\mathfrak g,\mathfrak h, \mathfrak l)$ constitutes a differential $
2$-crossed module. We give the $3$-gauge transformations from a $3$-connection
to another, and show the transformation formulae of the $1$-curvature $2$-form,
the $2$-curvature $3$-form and the $3$-curvature $4$-form. The gauge
configurations can be interpreted as smooth $\mathbf{Gray}$-functors between
two $\mathbf{Gray}$ $3$-groupoids: the path $3$-groupoid $\mathcal{P}_3(X)$ and
the $3$-gauge group $ \mathcal{G}^{\mathscr L}$ associated to the $ 2$-crossed
module $\mathscr L$, whose differential is $(\mathfrak g,\mathfrak h, \mathfrak
l)$. The derivatives of $\mathbf{Gray}$-functors are $3$-connections, and the
derivatives of lax-natural transformations between two such
$\mathbf{Gray}$-functors are $3$-gauge transformations. We give the
$3$-dimensional holonomy, the lattice version of the $3$-curvature, whose
derivative gives the $3$-curvature $4$-form. The covariance of $3$-curvatures
easily follows from this construction. This $\mathbf{ Gray}$-categorical
construction explains why $3$-gauge transformations and $3$-curvatures have the
given forms. The interchanging $3$-arrows are responsible for the appearance of
terms concerning the Peiffer commutator $\{,\}$.


  Many recent studies have highlighted certain failures of the standard
Eulerian-space cosmological perturbation theory (SPT). Its problems include (1)
not capturing large-scale bulk flows [leading to an O(1) error in the 1-loop
SPT prediction for the baryon acoustic peak in the correlation function], (2)
assuming that the Universe behaves as a pressureless, inviscid fluid, and (3)
treating fluctuations on scales that are non-perturbative as if they were.
Recent studies have highlighted the successes of perturbation theory in
Lagrangian space or theories that solve equations for the effective dynamics of
smoothed fields. Both approaches mitigate some or all of the aforementioned
issues with SPT. We discuss these physical developments by specializing to the
simplified 1D case of gravitationally interacting sheets, which allows us to
substantially reduces the analytic overhead and still (as we show) maintain
many of the same behaviors as in 3D. In 1D, linear-order Lagrangian
perturbation theory ("the Zeldovich approximation") is exact up to shell
crossing, and we prove that n^{th}-order Eulerian perturbation theory converges
to the Zeldovich approximation as n goes to infinity. In no 1D cosmology that
we consider (including a CDM-like case and power-law models) do these theories
describe accurately the matter power spectrum on any mildly nonlinear scale. We
find that theories based on effective equations are much more successful at
describing the dynamics. Finally, we discuss many topics that have recently
appeared in the perturbation theory literature such as beat coupling, the shift
and smearing of the baryon acoustic oscillation feature, and the advantages of
Fourier versus configuration space. Our simplified 1D case serves as an
intuitive review of these perturbation theory results.


  The masses of galaxy clusters can be measured using data obtained exclusively
from wide photometric surveys in one of two ways: directly from the amplitude
of the weak lensing signal or, indirectly, through the use of scaling relations
calibrated using binned lensing measurements. In this paper, we build on a
recently proposed idea and implement an alternative method based on the radial
profile of the satellite distribution. This technique relies on splashback, a
feature associated with the apocenter of recently accreted galaxies that offers
a clear window into the phase-space structure of clusters without the use of
velocity information. We carry out this dynamical measurement using the stacked
satellite distribution around a sample of luminous red galaxies in the fourth
data release of the Kilo-Degree Survey and validate our results using
abundance-matching and lensing masses. To illustrate the power of this
measurement, we combine dynamical and lensing mass estimates to robustly
constrain scalar-tensor theories of gravity at cluster scales. Our results
exclude departures from General Relativity of order unity. We conclude the
paper by discussing the implications for future data sets. Because splashback
mass measurements scale only with the survey volume, stage-IV photometric
surveys are well-positioned to use splashback to provide high-redshift cluster
masses.


  We demonstrate that a simple model successfully describing experimental data
for the process $\epm\to 4\pi$ can also qualitatively account for the data of
CLEOII and ALEPH obtained recently for the decay $\tau\to 4\pi\nu_{\tau}$. The
model is based on the assumption of the $a_1(1260)\pi$ and $\omega\pi$
dominance as intermediate states. Our observation is in contrast with the claim
by ARGUS that the $\rho$-meson signal in the $\tau\to 4\pi\nu_\tau$ decay can
not be explained by the $a_1\pi$ intermediate state.


  Let $\rho_\ell$ be a semisimple $\ell$-adic representation of a number field
$K$ that is unramified almost everywhere. We introduce a new notion called weak
abelian direct summands of $\rho_\ell$ and completely characterize them, for
example, if the algebraic monodromy of $\rho_\ell$ is connected. If $\rho_\ell$
is in addition $E$-rational for some number field $E$, we prove that the weak
abelian direct summands are locally algebraic (and thus de Rham). We also show
that the weak abelian parts of a connected semisimple Serre compatible system
form again such a system.
  Using our results on weak abelian direct summands, when $K$ is totally real
and $\rho_\ell$ is the three-dimensional $\ell$-adic representation attached to
a regular algebraic cuspidal automorphic, not necessarily polarizable
representation $\pi$ of $\mathrm{GL}_3(\mathbb{A}_K)$ together with an
isomorphism $\mathbb{C}\simeq \overline{\mathbb{Q}}_\ell$, we prove that
$\rho_\ell$ is irreducible. We deduce in this case also some $\ell$-adic Hodge
theoretic properties of $\rho_\ell$ if $\ell$ belongs to a Dirichlet density
one set of primes.


  We study the possibility of using dark soliton in quasi one dimensional Bose
Einstein condensates to produce two level system (qubits) by exploiting the
intrinsic nonlinear and the coherent nature of the matter waves. We calculate
the soliton spectrum and the conditions for a qubit to exist. We also compute
the coupling between the phonons and the soliton and investigate the emission
rate of the qubits in that case. Remarkably, the qubit lifetime is estimated to
be of the order of a few seconds, being by the dark soliton "death" due to
quantum evaporation.


  5G is the next-generation cellular network technology, with the goal of
meeting the critical demand for bandwidth required to accommodate a high
density of users. It employs flexible architectures to accommodate the high
density. 5G is enabled by mmWave communication, which operates at frequencies
ranging from 30 to 300 GHz. This paper describes the design of the 5G Routing
Interfered Environment (5GRIE), a python-based environment based on Gym's
methods. The environment can run different algorithms to route packets with
source and destination pairs using a formulated interference model. Deep
Reinforcement Learning algorithms that use Stable-Baselines 3, as well as
heuristic-based algorithms like random or greedy, can be run on it. Profitable
is an algorithm that is provided.


  For a compact convex set $K$ and a Poisson point process $\eta$, the union of
all Voronoi cells with a nucleus in $K$ is the Poisson-Voronoi approximation of
$K$. Lower and upper bounds for the variance and a central limit theorem for
the volume of the Poisson-Voronoi approximation are shown. The proofs make use
of so called Wiener-It\^o chaos expansions and the central limit theorem is
based on a more abstract central limit theorem for Poisson functionals, which
is also derived.


  Let G be a finite subgroup of SL(2,C). Let S_N#G^N be the wreath product of G
by the symmetric group of degree N, acting symplectically on a complex vector
space V of dimension 2N, with symplectic basis {x_i, y_i} i=1,...,N. In this
paper we classify all the irreducible representations of S_N#G^N that can be
extended to a representation of the associated symplectic reflection algebra
H(k,c,N,G) (where k is a complex number and c a class function on the
non-trivial elements of G) for non-zero values of k and with trivial action of
the generators x_i,y_i\in H(k,c,N,G).


  Information Geometry has been used to inspire efficient algorithms for
stochastic optimization, both in the combinatorial and the continuous case. We
give an overview of the authors' research program and some specific
contributions to the underlying theory.


  Heavy quark production in $\gamma\gamma$ collisions is reanalyzed. It is
argued that evaluating the cross section $\sigma(\gamma\gamma\to
Q\overline{Q})$ in a well-defined renormalization scheme requires the inclusion
of direct photon contributions up to the order $\alpha^2\alpha_s^2$. The order
$\alpha^2\alpha_s^2$ direct photon contributions are furthermore needed for
factorization scale invariance of the sum of direct and resolved photon
contributions. The importance of quantitative analysis of renormalization and
factorization scale dependence of the approximation currently used for the
evaluation of $\sigma(\gamma\gamma\to Q\overline{Q})$ is emphasized as the only
way of estimating the theoretical uncertainty related to the ambiguity in
choosing these scales.


  In this article we study high-dimensional approximation capacities of shallow
and deep artificial neural networks (ANNs) with the rectified linear unit
(ReLU) activation. In particular, it is a key contribution of this work to
reveal that for all $a,b\in\mathbb{R}$ with $b-a\geq 7$ we have that the
functions $[a,b]^d\ni x=(x_1,\dots,x_d)\mapsto\prod_{i=1}^d x_i\in\mathbb{R}$
for $d\in\mathbb{N}$ as well as the functions $[a,b]^d\ni x =(x_1,\dots,
x_d)\mapsto\sin(\prod_{i=1}^d x_i) \in \mathbb{R} $ for $ d \in \mathbb{N} $
can neither be approximated without the curse of dimensionality by means of
shallow ANNs nor insufficiently deep ANNs with ReLU activation but can be
approximated without the curse of dimensionality by sufficiently deep ANNs with
ReLU activation. We show that the product functions and the sine of the product
functions are polynomially tractable approximation problems among the
approximating class of deep ReLU ANNs with the number of hidden layers being
allowed to grow in the dimension $ d \in \mathbb{N} $. We establish the above
outlined statements not only for the product functions and the sine of the
product functions but also for other classes of target functions, in
particular, for classes of uniformly globally bounded $ C^{ \infty }
$-functions with compact support on any $[a,b]^d$ with $a\in\mathbb{R}$,
$b\in(a,\infty)$. Roughly speaking, in this work we lay open that simple
approximation problems such as approximating the sine or cosine of products
cannot be solved in standard implementation frameworks by shallow or
insufficiently deep ANNs with ReLU activation in polynomial time, but can be
approximated by sufficiently deep ReLU ANNs with the number of parameters
growing at most polynomially.


  Formation of low-resistance metal contacts is the biggest challenge that
masks the intrinsic exceptional electronic properties of 2D WSe2 devices. We
present the first comparative study of the interfacial properties between ML/BL
WSe2 and Sc, Al, Ag, Au, Pd, and Pt contacts by using ab initio energy band
calculations with inclusion of the spin-orbital coupling (SOC) effects and
quantum transport simulations. The interlayer coupling tends to reduce both the
electron and hole Schottky barrier heights (SBHs) and alters the polarity for
WSe2-Au contact, while the SOC chiefly reduces the hole SBH. In the absence of
the SOC, Pd contact has the smallest hole SBH with a value no less than 0.22
eV. Dramatically, Pt contact surpasses Pd contact and becomes p-type Ohmic or
quasi-Ohmic contact with inclusion of the SOC. Our study provides a theoretical
foundation for the selection of favorable metal electrodes in ML/BL WSe2
devices.


  The Assouad dimension of a metric space determines its extremal scaling
properties. The derived notion of the Assouad spectrum fixes relative scales by
a scaling function to obtain interpolation behaviour between the quasi-Assouad
and box-counting dimensions. While the quasi-Assouad and Assouad dimensions
often coincide, they generally differ in random constructions. In this paper we
consider a generalised Assouad spectrum that interpolates between the
quasi-Assouad to the Assouad dimension. For common models of random fractal
sets we obtain a dichotomy of its behaviour by finding a threshold function
where the quasi-Assouad behaviour transitions to the Assouad dimension. This
threshold can be considered a phase transition and we compute the threshold for
the Gromov boundary of Galton-Watson trees and one-variable random self-similar
and self-affine constructions. We describe how the stochastically self-similar
model can be derived from the Galton-Watson tree result.


  We give explicit uniform bounds for several quantities relevant to the study
of Galois representations attached to elliptic curves $E/\mathbb Q$. We
consider in particular the subgroup of scalars in the image of Galois, the
first Galois cohomology group with values in the torsion of $E$, and the Kummer
extensions generated by points of infinite order in $E(\mathbb Q)$.


  We study zoom-whirl behaviour of equal mass, non-spinning black hole binaries
in full general relativity. The magnitude of the linear momentum of the initial
data is fixed to that of a quasi-circular orbit, and its direction is varied.
We find a global maximum in radiated energy for a configuration which completes
roughly one orbit. The radiated energy in this case exceeds the value of a
quasi-circular binary with the same momentum by 15%. The direction parameter
only requires minor tuning for the localization of the maximum. There is
non-trivial dependence of the energy radiated on eccentricity (several local
maxima and minima). Correlations with orbital dynamics shortly before merger
are discussed. While being strongly gauge dependent, these findings are
intuitive from a physical point of view and support basic ideas about the
efficiency of gravitational radiation from a binary system.


  Active learning is a machine learning paradigm that aims to improve the
performance of a model by strategically selecting and querying unlabeled data.
One effective selection strategy is to base it on the model's predictive
uncertainty, which can be interpreted as a measure of how informative a sample
is. The sample's distance to the decision boundary is a natural measure of
predictive uncertainty, but it is often intractable to compute, especially for
complex decision boundaries formed in multiclass classification tasks. To
address this issue, this paper proposes the {\it least disagree metric} (LDM),
defined as the smallest probability of disagreement of the predicted label, and
an estimator for LDM proven to be asymptotically consistent under mild
assumptions. The estimator is computationally efficient and can be easily
implemented for deep learning models using parameter perturbation. The
LDM-based active learning is performed by querying unlabeled data with the
smallest LDM. Experimental results show that our LDM-based active learning
algorithm obtains state-of-the-art overall performance on all considered
datasets and deep architectures.


  The first version of a computer program "eett6f" for calculating cross
sections of e+e- -> 6 fermions processes relevant for a t\bar{t}-pair
production and decay at centre of mass energies typical for linear colliders is
presented. "eett6f v.~1.0" allows for calculating both the total and
differential cross sections at tree level of the Standard Model. The program
can be used as the Monte Carlo generator of unweighted events as well.


  We present a novel boundary-aware face alignment algorithm by utilising
boundary lines as the geometric structure of a human face to help facial
landmark localisation. Unlike the conventional heatmap based method and
regression based method, our approach derives face landmarks from boundary
lines which remove the ambiguities in the landmark definition. Three questions
are explored and answered by this work: 1. Why using boundary? 2. How to use
boundary? 3. What is the relationship between boundary estimation and landmarks
localisation? Our boundary- aware face alignment algorithm achieves 3.49% mean
error on 300-W Fullset, which outperforms state-of-the-art methods by a large
margin. Our method can also easily integrate information from other datasets.
By utilising boundary information of 300-W dataset, our method achieves 3.92%
mean error with 0.39% failure rate on COFW dataset, and 1.25% mean error on
AFLW-Full dataset. Moreover, we propose a new dataset WFLW to unify training
and testing across different factors, including poses, expressions,
illuminations, makeups, occlusions, and blurriness. Dataset and model will be
publicly available at https://wywu.github.io/projects/LAB/LAB.html


  We study scalar, fermionic and gauge fields coupled nonminimally to gravity
in the Einstein-Cartan formulation. We construct a wide class of models with
nondynamical torsion whose gravitational spectra comprise only the massless
graviton. Eliminating non-propagating degrees of freedom, we derive an
equivalent theory in the metric formulation of gravity. It features contact
interactions of a certain form between and among the matter and gauge currents.
We also discuss briefly the inclusion of curvature-squared terms.


  Capelli's and Turnbull's classical identities are given elegant combinatorial
proofs.


  Interest and problems in the studies of diffraction at LHC are highlighted.
Predictions for the global characteristics of proton-proton interactions at the
LHC energy are given. Potential discoveries of the antishadow scattering mode
and diffractive scattering conjugated with high--$E_T$ jets are discussed.


  The construction and first operation of the slow positron beam built at the
Hebrew University is reported here. The beam follows a traditional design,
using a 22Na source, a Tungsten moderator, and a target cell equipped with a
load-lock system for easy sample insertion. The beam energy varies between 0.03
keV and 30 keV. The detection system consists of two high purity Germanium
detectors, facing each other, allowing low-background Doppler-Broadening (DB)
measurements. Event readout is done using a state-of-the-art compact desktop
system. The target cell is designed to allow a combined measurement of DB and
sample conductivity, with the flexibility to add more detection options in the
future. The beam has been successfully tested by using it to charecterize
Titanium (Ti) films. Two 1.2 {\mu}m Ti films -- as produced, and after
annealing, were measured at various energies (2 keV - 25 keV), and the results
show consistent behavior with previous measurements.


  We investigate the harmonically trapped interacting Bose gas in a quasi-2D
geometry using the classical field method. The system exhibits quasi-long-range
order and non-classical rotational inertia at temperatures below the
Berezinskii-Kosterlitz-Thouless cross-over to the superfluid state. In
particular, we compute the scissors-mode oscillation frequencies and find that
the irrotational mode changes its frequency as the temperature is sweeped
across the cross-over thus providing microscopic evidence for the emergence of
superfluidity.


  We determined the bulk electronic structure in the prototypical Heusler
compound Cu$_2$MnAl by measuring the Angular Correlation of Annihilation
Radiation (2D-ACAR) using spin-polarized positrons. To this end, a new
algorithm for reconstructing 3D densities from projections is introduced that
allows us to corroborate the excellent agreement between our electronic
structure calculations and the experimental data. The contribution of each
individual Fermi surface sheet to the magnetization was identified, and summed
to a total spin magnetic moment of $3.6\,\pm\,0.5\,\mu_B/\mathrm{f.u.}$.


  We study Compton upscattering of low-frequency photons in a converging flow
of thermal plasma. The photons escape diffusively and electron scattering is
the dominant source of opacity. We solve numerically and approximately
analytically the equation of radiative transfer in the case of spherical,
steady state accretion into black holes. Unlike previous work on this subject,
we consider the inner boundary at a finite radius and this has a significant
effect on the emergent spectrum. It is shown that the bulk motion of the
converging flow is more efficient in upscattering photons than thermal
Comptonization, provided that the electron temperature in the flow is of order
a few keV or less. In this case, the spectrum observed at infinity consists of
a soft component coming from those input photons which escaped after a few
scatterings without any significant energy change and of a power law which
extends to high energies and is made of those photons which underwent
significant upscattering. The luminosity of the power law is relatively small
compared to that of the soft component. The more reflective the inner boundary
is, the flatter the power-law spectrum becomes. The spectral energy power-law
index for black-hole accretion is always higher than 1 and it is approximately
1.5 for high accretion rates. This result tempts us to say that bulk motion
Comptonization might be the mechanism behind the power-law spectra seen in
black-hole X-ray sources.


  By now it is known that in an s-wave
superconductor-ferromagnet-superconductor ($SFS$) structure the supercurrent
induced by spin singlet pairs can only transmit a short distance of the order
of magnetic coherence length. The long-range supercurrent, taking place on the
length scale of the normal metal coherence length, will be maintained by
equal-spin triplet pairs, which can be generated by magnetic inhomogeneities in
the system. In this paper, we show an unusual long-range supercurrent, which
can take place in clean $SF_1F_2S$ junction with non-parallel orientation of
magnetic moments. The mechanism behind the enhancement of Josephson current is
provided by the interference of the opposite-spin triplet states derived from
$S/F_1$ and $F_2/S$ interfaces when both ferromagnetic layers have the same
values of the length and exchange field. This finds can provide a natural
explanation for recent experiment [Robinson et al., Phys. Rev. Lett. 104,
207001 (2010)].


  A remarkable connection between perturbative scattering amplitudes of
four-dimensional planar SYM, and the stratification of the positive
grassmannian, was revealed in the seminal work of Arkani-Hamed et. al. Similar
extension for three-dimensional ABJM theory was proposed. Here we establish a
direct connection between planar scattering amplitudes of ABJM theory, and
singularities there of, to the stratification of the positive orthogonal
grassmannian. In particular, scattering processes are constructed through
on-shell diagrams, which are simply iterative gluing of the fundamental
four-point amplitude. Each diagram is then equivalent to the merging of
fundamental OG_2 orthogonal grassmannian to form a larger OG_k, where 2k is the
number of external particles. The invariant information that is encoded in each
diagram is precisely this stratification. This information can be easily read
off via permutation paths of the on-shell diagram, which also can be used to
derive a canonical representation of OG_k that manifests the vanishing of
consecutive minors as the singularity of all on-shell diagrams. Quite
remarkably, for the BCFW recursion representation of the tree-level amplitudes,
the on-shell diagram manifests the presence of all physical factorization
poles, as well as the cancellation of the spurious poles. After analytically
continuing the orthogonal grassmannian to split signature, we reveal that each
on-shell diagram in fact resides in the positive cell of the orthogonal
grassmannian, where all minors are positive. In this language, the amplitudes
of ABJM theory is simply an integral of a product of dlog forms, over the
positive orthogonal grassmannian.


  We present the first photometric study of the globular cluster system (GCS)
of the E galaxy NGC 3613 (Mv = -21.5, d = 30.1 Mpc), as well as the surface
photometry of the host galaxy, based on Gemini/GMOS images. Being considered
the central galaxy of a group, NGC 3613 inhabits a low-density environment
although its intrinsic brightness is similar to the expected one for galaxies
in the centre of clusters. The following characteristics are obtained for this
GCS. The colour distribution is bimodal, with metal-poor globular clusters
(GCs) getting slightly bluer with increasing radius. The radial and azimuthal
projected distributions show that metal-rich GCs are more concentrated towards
the host galaxy and trace its light distribution very precisely, while
metal-poor GCs present a more extended and uniform distribution. The GC
luminosity function helps validate the adopted distance. The estimated total GC
population of Ntot= 2075 +/- 130 leads to a specific frequency Sn=5.2 +/- 0.7,
a value within the expected range for GCSs with host galaxies of similar
luminosity. The surface photometry of NGC 3613 reveals a three-component
profile and a noticeable substructure. Finally, a small sample of ultra-compact
dwarf (UCD) candidates are identified in the surroundings of the host galaxy.


  Diabetic retinopathy (DR) is a leading cause of blindness among diabetic
patients. Deep learning models have shown promising results in automating the
detection of DR. In the present work, we propose a new methodology that
integrates a feature attention module with a pretrained VGG19 convolutional
neural network (CNN) for more accurate DR detection. Here, the pretrained net
is fine-tuned with the proposed feature attention block. The proposed module
aims to leverage the complementary information from various regions of fundus
images to enhance the discriminative power of the CNN. The said feature
attention module incorporates an attention mechanism which selectively
highlights salient features from images and fuses them with the original input.
The simultaneous learning of attention weights for the features and thereupon
the combination of attention-modulated features within the feature attention
block facilitates the network's ability to focus on relevant information while
reducing the impact of noisy or irrelevant features. Performance of the
proposed method has been evaluated on a widely used dataset for diabetic
retinopathy classification e.g., the APTOS (Asia Pacific Tele-Ophthalmology
Society) DR Dataset. Results are compared with/without attention module, as
well as with other state-of-the-art approaches. Results confirm that the
introduction of the fusion module (fusing of feature attention module with CNN)
improves the accuracy of DR detection achieving an accuracy of 95.70%.


  Traffic analysis attacks can counteract end-to-end encryption and use leaked
communication metadata to reveal information about communicating parties. With
an ever-increasing amount of traffic by an ever-increasing number of networked
devices, communication privacy is undermined. Therefore, Anonymous
Communication Systems (ACSs) are proposed to hide the relationship between
transmitted messages and their senders and receivers, providing privacy
properties known as anonymity, unlinkability, and unobservability. This article
aims to review research in the ACSs field, focusing on Dining Cryptographers
Networks (DCNs). The DCN-based methods are information-theoretically secure and
thus provide unconditional unobservability guarantees. Their adoption for
anonymous communications was initially hindered because their computational and
communication overhead was deemed significant at that time, and scalability
problems occurred. However, more recent contributions, such as the possibility
to transmit messages of arbitrary length, efficient disruption handling and
overhead improvements, have made the integration of modern DCN-based methods
more realistic. In addition, the literature does not follow a common definition
for privacy properties, making it hard to compare the approaches' gains.
Therefore, this survey contributes to introducing a harmonized terminology for
ACS privacy properties, then presents an overview of the underlying principles
of ACSs, in particular, DCN-based methods, and finally, investigates their
alignment with the new harmonized privacy terminologies. Previous surveys did
not cover the most recent research advances in the ACS area or focus on
DCN-based methods. Our comprehensive investigation closes this gap by providing
visual maps to highlight privacy properties and discussing the most promising
ideas for making DCNs applicable in resource-constrained environments.


  Group sequential designs in clinical trials allow for interim efficacy and
futility monitoring. Adjustment for baseline covariates can increase power and
precision of estimated effects. However, inconsistently applying covariate
adjustment throughout the stages of a group sequential trial can result in
inflation of type I error, biased point estimates, and anti-conservative
confidence intervals. We propose methods for performing correct interim
monitoring, estimation, and inference in this setting that avoid these issues.
We focus on two-arm trials with simple, balanced randomization and continuous
outcomes. We study the performance of our boundary, estimation, and inference
adjustments in simulation studies. We end with recommendations about the
application of covariate adjustment in group sequential designs.


  We present an analysis of the X-ray data of a magnetic cataclysmic variable,
BG CMi, obtained with ROSAT in March 1992 and with ASCA in April 1996. We show
that four peaks clearly exist in the X-ray pulse profile, unlike a single peak
found in the optical profile. The fluxes of two major pulses are $\sim 2 - 5$
times larger than those of two minor pulses. The fraction of the total pulsed
flux increases from 51% to 85% with increasing energy in 0.1 $-$ 2.0 keV,
whereas it decreases from 96% to 22% in 0.8 $-$ 10 keV. We discuss the
implications of our findings for the origin of the pulse profile and its energy
dependence.


  Context: Across different domains, Artificial Neural Networks (ANNs) are used
more and more in safety-critical applications in which erroneous outputs of
such ANN can have catastrophic consequences. However, the development of such
neural networks is still immature and good engineering practices are missing.
With that, ANNs are in the same position as software was several decades ago.
Today, standards for functional safety, such as ISO 26262 in the automotive
domain, require the application of a collection of proven engineering
principles and methods in the creation of software to increase its quality and
reduce failure rates to an acceptable level. Objective: In the future, such a
set of proven engineering methods needs to be established for the development
of Artificial Neural Networks to allow their use in safety-critical
applications. Method: This work takes a step in this direction by conducting a
mapping study to extract challenges faced in the development of ANNs for
safety-critical applications and to identify methods that have been used for
the hardening of ANNs in such settings. Results: We extracted ten different
challenges found to be repeatedly reported in the literature regarding the use
of ANNs in critical contexts. All of these challenges are addressed by
engineering methods, of which we identified 54 in our study that can be used
for the hardening of networks. Conclusions: Various methods have been proposed
to overcome the specific challenges of using ANNs in safety-critical
applications. On the path towards defining best practices, we envision that
future software engineering will need to focus on further investigating these
methods and increasing the maturity and understanding of existing approaches,
with the goal to develop clear guidance for proper engineering of high-quality
ANNs.


  We probed the pole structure of the $P_\psi^{N}(4312)^{+}$ using a trained
deep neural network. The training dataset was generated using uniformized
independent S-matrix poles to ensure that the obtained interpretation is as
model-independent as possible. To prevent possible ambiguity in the
interpretation of the pole structure, we included the contribution from the
off-diagonal element of the S-matrix. Five out of the six neural networks we
trained favor $P_\psi^{N}(4312)^{+}$ as possibly having a three-pole structure,
with one pole on each of the unphysical sheets - a first in its report. The two
poles can be associated to a pole-shadow pair which is a characteristic of a
true resonance. On the other hand, the last pole is most likely associated with
the coupled-channel effect. The combined effect of these poles produced a peak
below the $\Sigma^{+}_C\bar{D}^0$ which mimic the line shape of a hadronic
molecule.


  We constrain tilted spatially-flat and untilted nonflat XCDM dynamical dark
energy inflation parameterizations using Planck 2015 cosmic microwave
background (CMB) anisotropy data and recent baryonic acoustic oscillations
distance measurements, Type Ia supernovae data, Hubble parameter observations,
and growth rate measurements. Inclusion of the four non-CMB data sets results
in a significant strengthening of the evidence for nonflatness in the nonflat
XCDM model from 1.1$\sigma$ for the CMB data alone to 3.4$\sigma$ for the full
data combination. In this untilted nonflat XCDM case the data favor a
spatially-closed model in which spatial curvature contributes a little less
than a percent of the current cosmological energy budget; they also mildly
favor dynamical dark energy over a cosmological constant at 1.2$\sigma$. These
data are also better fit by the flat-XCDM parameterization than by the standard
$\Lambda$CDM model, but only at 0.3$\sigma$ significance. Current data is
unable to rule out dark energy dynamics. The nonflat XCDM parameterization is
compatible with the Dark Energy Survey limits on the present value of the rms
mass fluctuations amplitude ($\sigma_8$) as a function of the present value of
the nonrelativistic matter density parameter ($\Omega_m$), however it does not
provide as good a fit to the higher multipole CMB temperature anisotropy data
as does the standard tilted flat-$\Lambda$CDM model. A number of measured
cosmological parameter values differ significantly when determined using the
tilted flat-XCDM and the nonflat XCDM parameterizations, including the baryonic
matter density parameter and the reionization optical depth.


  We prove a conjecture by Van Dam and Sotirov on the smallest eigenvalue of
(distance-$j$) Hamming graphs and a conjecture by Karloff on the smallest
eigenvalue of (distance-$j$) Johnson graphs. More generally, we study the
smallest eigenvalue and the second largest eigenvalue in absolute value of the
graphs of the relations of classical $P$- and $Q$-polynomial association
schemes.


  A major issue in the association of genes to neuroimaging phenotypes is the
high dimension of both genetic data and neuroimaging data. In this article, we
tackle the latter problem with an eye toward developing solutions that are
relevant for disease prediction. Supported by a vast literature on the
predictive power of neural networks, our proposed solution uses neural networks
to extract from neuroimaging data features that are relevant for predicting
Alzheimer's Disease (AD) for subsequent relation to genetics. Our
neuroimaging-genetic pipeline is comprised of image processing, neuroimaging
feature extraction and genetic association steps. We propose a neural network
classifier for extracting neuroimaging features that are related with disease
and a multivariate Bayesian group sparse regression model for genetic
association. We compare the predictive power of these features to expert
selected features and take a closer look at the SNPs identified with the new
neuroimaging features.


  Orthogonal frequency-division multiplexing (OFDM) with subcarrier number
modulation (OFDM-SNM) manifests its superior nature of high spectral efficiency
(SE) and low complexity for signal estimation. To exploit the spatial gain of
OFDM-SNM, we propose a relay assisted OFDM-SNM scheme for multi-hop cooperative
systems in this letter. It is stipulated that a relay operated by
decode-and-forward (DF) and half-duplex (HD) protocols exists in each hop. We
analyze the outage performance of the relay assisted OFDM-SNM system. The
average outage probability is approximated in closed form. Moreover, to reveal
the diversity and coding gains of relay assisted OFDM-SNM, we explore the
asymptotic outage performance at high signal-to-noise ratio (SNR) by power
series expansion. To verify the improvement on outage performance and energy
efficiency, we carry out the comparison among different multi-hops systems with
traditional OFDM-SNM fixing a certain distance from source to destination.
Simulation results corroborate the derived outage probabilities and provide
insight into the proposed system in this letter.


  This paper uses typed linear algebra (LA) to represent data and perform
analytical querying in a single, unified framework. The typed approach offers
strong type checking (as in modern programming languages) and a diagrammatic
way of expressing queries (paths in LA diagrams). A kernel of LA operators has
been implemented so that paths extracted from LA diagrams can be executed. The
approach is validated and evaluated taking TPC-H benchmark queries as
reference. The performance of the LA-based approach is compared with popular
database competitors (PostgreSQL and MySQL).


  By strongly driving a transmon-resonator system, the transmon qubit may
eventually escape from its cosine-shaped potential. This process is called
transmon ionization (TI) and known to be detrimental to the qubit coherence and
operation. In this work, we investigate the onset of TI in an irreversible,
parametrically-driven, frequency conversion process in a system consisting of a
superconducting 3D-cavity coupled to a fixed-frequency transmon qubit. Above a
critical pump power we find a sudden increase in the transmon population. Using
Renyi entropy, Floquet modes, and Husimi Q functions, we infer that this abrupt
change can be attributed to a quantum-to-classical phase transition.
Furthermore, in the context of the single-photon detection, we measure a
TI-uncorrected detection efficiency of up to 86% and estimate a TI-corrected
value of up to 78% by exploiting the irreversible frequency conversion. Our
numerical simulations suggest that increasing the detuning between the pump and
qubit frequencies and increasing the qubit anharmonicity can suppress the TI
impact. Our findings highlight the general importance of the TI process when
operating coupled qubit-cavity systems.


  A new amplification method, weaving the three basic compression techniques,
Chirped Pulse Amplification (CPA), Optical Parametric Chirped Pulse
Amplification (OPCPA) and Plasma Compression by Backward Raman Amplification
(BRA) in plasma, is proposed. It is called C3 for Cascaded Conversion
Compression. It has the capability to compress with good efficiency kilojoule
to megajoule, nanosecond laser pulses into femtosecond pulses, to produce
exawatt and beyond peak power. In the future, C3 could be used at large-scale
facilities such as the National Ignition Facility (NIF) or the Laser Megajoule
(LMJ) and open the way to zettawatt level pulses. The beam will be focused to a
wavelength spot size with a f#1. The very small beam size, i.e. few
centimeters, along with the low laser repetition rate laser system will make
possible the use of inexpensive, precision, disposable optics. The resulting
intensity will approach the Schwinger value, thus opening up new possibilities
in fundamental physics.


  Maximum likelihood is one of the most widely used techniques to infer
evolutionary histories. Although it is thought to be intractable, a proof of
its hardness has been lacking. Here, we give a short proof that computing the
maximum likelihood tree is NP-hard by exploiting a connection between
likelihood and parsimony observed by Tuffley and Steel.


  We simulate the growth of large-scale structure in the universe using a
N-body code. By combining these simulations with a Monte-Carlo method, we
generate galaxy distributions at present that reproduces the observed
morphology-density relation, with most ellipticals concentrated in the densest
regions. By "tying" each galaxy to its nearest particle, we trace the
trajectory of that galaxy back in time. This enables us to reconstruct the
distribution of galaxies at high redshift, and the trajectory of each galaxy
from its formation epoch to the present. Our goal is to determine whether the
morphological type of galaxies is primarily determined by the initial
conditions in which these galaxies form, or by evolutionary processes occurring
later. We compare the environment in which galaxies are at the epoch of galaxy
formation (z=3) and at the present. Making the null hypothesis that
morphological types do not evolve, we compare the galaxies that form in low
density environments but end up later in high density environments to the ones
that form also in low density environment but remain in low density
environment. The first group contains a larger proportion of E and S0 galaxies
than the second group. We assume that the galaxy formation process cannot
distinguish a low density environment that will always remain low density from
one that will eventually become high density. Hence, these results force us to
discard the null hypothesis of no morphological evolution. Our study suggests
that 75% of the E and S0 galaxies observed at present formed as such, while the
remaining 25% formed as spirals, and underwent morphological evolution. We
conclude that most galaxies did not undergo morphological evolution, but a
non-negligible fraction did.


  Nielsen \cite{Nielsen05} recently asked the following question: "What is the
minimal size quantum circuit required to exactly implement a specified $%
\mathit{n}$-qubit unitary operation $U$, without the use of ancilla qubits?"
Nielsen was able to prove that a lower bound on the minimal size circuit is
provided by the length of the geodesic between the identity $I$ and $U$, where
the length is defined by a suitable Finsler metric on $SU(2^{n})$. We prove
that the minimum circuit size that simulates $U$ is in linear relation with the
geodesic length and simulation parameters, for the given Finsler structure $F$.
As a corollary we prove the highest lower bound of $O(\frac{%
n^{4}}{p}d_{F_{p}}^{2}(I,U)L_{F_{p}}(I,\tilde{U})) $and the lowest upper bound
of $\Omega (n^{4}d_{F_{p}}^{3}(I,U))$, for the standard simulation technique.
Therefore, our results show that by standard simulation one can not expect a
better then $n^{2}$ times improvement in the upper bound over the result from
Nielsen, Dowling, Gu and Doherty \cite{Nielsen06}. Moreover, our equivalence
result can be applied to the arbitrary path on the manifold including the one
that is generated adiabatically.


  Using full-potential density functional calculations we have investigated the
structural and electronic properties of graphene and some of its structural
analogues, viz., monolayer (ML) of SiC, GeC, BN, AlN, GaN, ZnO, ZnS and ZnSe.
While our calculations corroborate some of the reported results based on
different methods, our results on ZnSe, the two dimensional bulk modulus of
ML-GeC, ML-AlN, ML-GaN, ML-ZnO and ML-ZnS and the effective masses of the
charge carriers in these binary mono-layers are something new. With the current
progress in synthesis techniques, some of these new materials may be
synthesized in near future for applications in nano-devices.


  Firstly, we consider Yang-Mills theory on ${\mathbb R}^{3,1}$ with an adjoint
Higgs field spontaneously breaking a compact gauge group $G$ to a subgroup $H$,
so that the Higgs vacuum manifold forms the coset $G/H$. It is shown that in
the low-energy limit, when the Higgs vacuum value is large, the 4d
Yang-Mills-Higgs theory reduces to the Faddeev sigma model on ${\mathbb
R}^{3,1}$ with $G/H$ as target. Its action contains the standard two-derivative
sigma-model term as well as the four-derivative Skyrme-type term, which
stabilizes solutions against scaling. Secondly, we put the Higgs field in the
bi-fundamental representation of $G=\textrm{U}_+(N)\times\textrm{U}_-(N)$,
realizing the simplest $A_2$-type quiver gauge theory. Breaking $G$ to
$H{=}\,\textrm{diag}(G)$, the vacuum manifold $G/H\cong\textrm{U}(N)$ is a
group. In this case, when the Higgs vacuum value is large, the 4d $A_2$-quiver
gauge theory reduces to the Skyrme sigma model on ${\mathbb R}^{3,1}$ with
U$(N)$ as target. Thus, both the Skyrme and the Faddeev model arise as
effective field theories in the infrared of Yang-Mills-Higgs models.


  Intermolecular interactions are pivotal for aggregation, solvation, and
crystallization. We demonstrate that the collective strong coupling of several
molecules to a single optical mode results in notable changes in the molecular
excitations around an impurity, e.g., in the first aggregation or solvation
shell. A competition between short-range Coulombic and long-range photonic
correlation inverts the local transition density in a polaritonic state,
suggesting notable changes in the polarizability of the solvation shell. Our
results provide an alternative perspective on recent work in polaritonic
chemistry and pave the way for the rigorous treatment of cooperative effects in
aggregation, solvation, and crystallization.


  We present a calculation of the total cross section for top quark production
based on a new perturbative resummation of gluon radiative corrections to the
basic QCD subprocesses. We use Principal Value Resummation to calculate all
relevant large threshold corrections. Advantages of this method include its
independence from arbitrary infrared cutoffs and specification of the
perturbative regime of applicability. For $p\bar{p}$ collisions at
center-of-mass energy $\sqrt{s}=1.8$TeV and a top mass of 175 GeV, we compute
$\sigma(t\bar{t})=5.52^{+0.07}_{-0.45}pb$.