  Radial superlattices are nanostructured materials obtained by rolling-up thin
solid films into spiral-like tubular structures. The formation of these
"high-order" superlattices from two-dimensional crystals or ultrathin films is
expected to result in a transition of transport characteristics from
two-dimensional to one-dimensional. Here, we show that a transport hallmark of
radial superlattices is the appearance of magnetoconductance modulations in the
presence of externally applied axial magnetic fields. This phenomenon
critically relies on electronic interlayer tunneling processes that activates
an unconventional Aharonov-Bohm-like effect. Using a combination of density
functional theory calculations and low-energy continuum models, we determine
the electronic states of a paradigmatic single-material radial superlattice --
a two-winding carbon nanoscroll -- and indeed show momentum-dependent
oscillations of the magnetic states in axial configuration, which we
demonstrate to be entirely due to hopping between the two windings of the
spiral-shaped scroll.


  Machine learning plays an essential role in preventing financial losses in
the banking industry. Perhaps the most pertinent prediction task that can
result in billions of dollars in losses each year is the assessment of credit
risk (i.e., the risk of default on debt). Today, much of the gains from machine
learning to predict credit risk are driven by gradient boosted decision tree
models. However, these gains begin to plateau without the addition of expensive
new data sources or highly engineered features. In this paper, we present our
attempts to create a novel approach to assessing credit risk using deep
learning that does not rely on new model inputs. We propose a new credit card
transaction sampling technique to use with deep recurrent and causal
convolution-based neural networks that exploits long historical sequences of
financial data without costly resource requirements. We show that our
sequential deep learning approach using a temporal convolutional network
outperformed the benchmark non-sequential tree-based model, achieving
significant financial savings and earlier detection of credit risk. We also
demonstrate the potential for our approach to be used in a production
environment, where our sampling technique allows for sequences to be stored
efficiently in memory and used for fast online learning and inference.


  In this paper we investigate the question of when different surgeries on a
knot can produce identical manifolds. We show that given a knot in a homology
sphere, unless the knot is quite special, there is a bound on the number of
slopes that can produce a fixed manifold that depends only on this fixed
manifold and the homology sphere the knot is in. By finding a different bound
on the number of slopes, we show that non-null-homologous knots in certain
homology $\mathbb{R}P^3$'s are determined by their complements. We also prove
the surgery characterisation of the unknot for null-homologous knots in
$L$-spaces. This leads to showing that all knots in some lens spaces are
determined by their complements. Finally, we establish that knots of genus
greater than $1$ in the Brieskorn sphere $\Sigma(2,3,7)$ are also determined by
their complements.


This paper has been withdrawn by the author.


  We elucidate the close relationship between spontaneous time-reversal
symmetry breaking and the physics of excitonic instabilities in strongly
correlated multiband systems. The underlying mechanism responsible for the
spontaneous breaking of time-reversal symmetry in a many-body system is closely
related to the Cooper-like pairing instability of interband particle-hole pairs
involving higher order symmetries. Studies of such pairing instabilites have,
however, mainly focused on the mean-field aspects of the virtual exciton
condensate, which ignores the presence of the underlying collective Fermi
liquid excitations. We show that this relationship can be exploited to
systematically derive the coupling of the condensate order-parameter to the
intraband Fermi liquid particle-hole excitations. Surprisingly, we find that
the static susceptibility is negative in the ordered phase when the coupling to
the Fermi liquid collective excitations are included, suggesting that a uniform
condensate of virtual excitons, with or without time reversal breaking, is an
unstable phase at T=0.


  Zero forcing is a deterministic iterative graph coloring process in which
vertices are colored either blue or white, and in every round, any blue
vertices that have a single white neighbor force these white vertices to become
blue. Here we study probabilistic zero forcing, where blue vertices have a
non-zero probability of forcing each white neighbor to become blue.
  We explore the propagation time for probabilistic zero forcing on the
Erd\H{o}s-R\'eyni random graph $\Gnp$ when we start with a single vertex
colored blue. We show that when $p=\log^{-o(1)}n$, then with high probability
it takes $(1+o(1))\log_2\log_2n$ rounds for all the vertices in $\Gnp$ to
become blue, and when $\log n/n\ll p\leq \log^{-O(1)}n$, then with high
probability it takes $\Theta(\log(1/p))$ rounds.


  Magnetic Resonance Imaging (MRI) is a kind of medical imaging technology used
for diagnostic imaging of diseases, but its image quality may be suffered by
the long acquisition time. The compressive sensing (CS) based strategy may
decrease the reconstruction time greatly, but it needs efficient reconstruction
algorithms to produce high-quality and reliable images. This paper focuses on
the algorithmic improvement for the sparse reconstruction of CS-MRI, especially
considering a non-smooth convex minimization problem which is composed of the
sum of a total variation regularization term and a $\ell_1$-norm term of the
wavelet transformation. The partly motivation of targeting the dual problem is
that the dual variables are involved in relatively low-dimensional subspace.
Instead of solving the primal model as usual, we turn our attention to its
associated dual model composed of three variable blocks and two separable
non-smooth function blocks. However, the directly extended alternating
direction method of multipliers (ADMM) must be avoided because it may be
divergent, although it usually performs well numerically. In order to solve the
problem, we employ a symmetric Gauss-Seidel (sGS) technique based ADMM.
Compared with the directly extended ADMM, this method only needs one additional
iteration, but its convergence can be guaranteed theoretically. Besides, we
also propose a generalized variant of ADMM because this method has been
illustrated to be efficient for solving semidefinite programming in the past
few years. Finally, we do extensive experiments on MRI reconstruction using
some simulated and real MRI images under different sampling patterns and
ratios. The numerical results demonstrate that the proposed algorithms
significantly achieve high reconstruction accuracies with fast computational
speed.


  Federated learning (FL) is increasingly deployed among multiple clients to
train a shared model over decentralized data. To address privacy concerns, FL
systems need to safeguard the clients' data from disclosure during training and
control data leakage through trained models when exposed to untrusted domains.
Distributed differential privacy (DP) offers an appealing solution in this
regard as it achieves a balanced tradeoff between privacy and utility without a
trusted server. However, existing distributed DP mechanisms are impractical in
the presence of client dropout, resulting in poor privacy guarantees or
degraded training accuracy. In addition, these mechanisms suffer from severe
efficiency issues.
  We present Dordis, a distributed differentially private FL framework that is
highly efficient and resilient to client dropout. Specifically, we develop a
novel `add-then-remove' scheme that enforces a required noise level precisely
in each training round, even if some sampled clients drop out. This ensures
that the privacy budget is utilized prudently, despite unpredictable client
dynamics. To boost performance, Dordis operates as a distributed parallel
architecture via encapsulating the communication and computation operations
into stages. It automatically divides the global model aggregation into several
chunk-aggregation tasks and pipelines them for optimal speedup. Large-scale
deployment evaluations demonstrate that Dordis efficiently handles client
dropout in various realistic FL scenarios, achieving the optimal
privacy-utility tradeoff and accelerating training by up to 2.4$\times$
compared to existing solutions.


  We propose a flexible framework for spectral conversion (SC) that facilitates
training with unaligned corpora. Many SC frameworks require parallel corpora,
phonetic alignments, or explicit frame-wise correspondence for learning
conversion functions or for synthesizing a target spectrum with the aid of
alignments. However, these requirements gravely limit the scope of practical
applications of SC due to scarcity or even unavailability of parallel corpora.
We propose an SC framework based on variational auto-encoder which enables us
to exploit non-parallel corpora. The framework comprises an encoder that learns
speaker-independent phonetic representations and a decoder that learns to
reconstruct the designated speaker. It removes the requirement of parallel
corpora or phonetic alignments to train a spectral conversion system. We report
objective and subjective evaluations to validate our proposed method and
compare it to SC methods that have access to aligned corpora.


  The incorporation of pseudo data in the training of grammatical error
correction models has been one of the main factors in improving the performance
of such models. However, consensus is lacking on experimental configurations,
namely, choosing how the pseudo data should be generated or used. In this
study, these choices are investigated through extensive experiments, and
state-of-the-art performance is achieved on the CoNLL-2014 test set
($F_{0.5}=65.0$) and the official test set of the BEA-2019 shared task
($F_{0.5}=70.2$) without making any modifications to the model architecture.


  Under high pressure, Zr undergoes a transformation from its ambient
equilibrium hexagonal close packed $\alpha$ phase to a simple hexagonal
$\omega$ phase. Subsequent unloading to ambient conditions does not see a full
reversal to the $\alpha$ phase, but rather a retainment of significant
$\omega$. Previously, the thermal stability of the $\omega$ phase was
investigated via in-situ synchrotron X-ray diffraction analysis of the
isothermal annealing of Zr samples shocked to 8 and 10.5 GPa at temperatures
443, 463, 483, and 503 K. The phase volume fractions were tracked
quantitatively and the dislocation densities were tracked semi-quantitatively.
Trends included a rapid initial (transient) transformation rate from
$\omega\to\alpha$ followed by a plateau to a new metastable state with lesser
retained $\omega$ (asymptotic). A significant reduction in dislocation
densities in the $\omega$ phase was observed prior to initiation of an earnest
reverse transformation, leading to the hypothesis that the $\omega\to\alpha$
transformation from is being hindered by defects in the $\omega$ phase. As a
continuation of this work, we present a temperature dependent model that
couples the removal of dislocations in the $\omega$ phase and the reverse
transformation via a barrier energy that is associated with the free energy of
remaining dislocations. The reduction of dislocations in the $\omega$ phase
occur as a sum of glide and climb controlled processes, both of which dictate
the transient and asymptotic behavior of the annealing process respectively.


  We study the specialization of the type A nonsymmetric Macdonald polynomials
at $t=0$ based on the combinatorial formula of Haglund, Haiman, and Loehr. We
prove that this specialization expands nonnegatively into the fundamental slide
polynomials, introduced by the author and Searles. Using this and weak dual
equivalence, we prove combinatorially that this specialization is a positive
graded sum of Demazure characters. We use stability results for fundamental
slide polynomials to show that this specialization stabilizes and to show that
the Demazure character coefficients give a refinement of the Kostka--Foulkes
polynomials.


  Systematic differences in experimental materials, methods, measurements, and
data handling between labs, over time, and among personnel can sabotage
experimental reproducibility. Uncovering such differences can be difficult and
time consuming. Unfortunately, it is made more so when scientists employ
traditional experimental procedures to explore possible sources of systematic
variability by sequentially changing them one at a time to determine the
magnitude of their effects. We use two simple examples to show how and why well
known methods of factorial experimentation in which multiple potential sources
are simultaneously varied provide a better alternative, can be understood as a
straightforward extension of standard practice, and could be embedded into the
quality control procedures of routine experimental practice. Doing so, we
argue, would help mitigate at least some of the problems fueling the current
"reproducibility crisis" roiling some scientific disciplines.


  We propose that the height-angle ray vector in matrix optics should be
complex, based on a geometric algebra analysis. We also propose that the ray's
2x2 matrix operators should be right-acting, so that the matrix product
succession would go with light's left-to-right propagation. We express the
propagation and refraction operators as a sum of a unit matrix and an imaginary
matrix proportional to the Fermion creation or annihilation matrix. In this
way, we reduce the products of matrix operators into sums of
creation-annihilation product combinations. We classify ABCD optical systems
into four: telescopic, inverse Fourier transforming, Fourier transforming, and
imaging. We show that each of these systems have a corresponding Lagrange
theorem expressed in partial derivatives, and that only the telescopic and
imaging systems have Lagrange invariants.


  A major hurdle in understanding the phase diagram of twisted bilayer graphene
(TBLG) are the roles of lattice relaxation and electronic structure on isolated
band flattening near magic twist angles. In this work, the authors develop an
accurate local environment tight binding model (LETB) fit to tight binding
parameters computed from $ab\ initio$ density functional theory (DFT)
calculations across many atomic configurations. With the accurate
parameterization, it is found that the magic angle shifts to slightly lower
angles than often quoted, from around 1.05$^\circ$ to around 0.99$^\circ$, and
that isolated flat bands appear for rigidly rotated graphene layers, with
enhancement of the flat bands when the layers are allowed to distort. Study of
the orbital localization supports the emergence of fragile topology in the
isolated flat bands without the need for lattice relaxation.


  We prove an extended lifespan result for the full gravity-capillary water
waves system with a $2$ dimensional periodic interface: for initial data of
sufficiently small size $\varepsilon$, smooth solutions exist up to times of
the order of $\varepsilon^{-5/3+}$, for almost all values of the gravity and
surface tension parameters. Besides the quasilinear nature of the equations,
the main difficulty is to handle the weak small divisors bounds for quadratic
and cubic interactions, growing with the size of the largest frequency. To
overcome this difficulty we use (1) the (Hamiltonian) structure of the
equations which gives additional smoothing close to the resonant hypersurfaces,
(2) another structural property, connected to time-reversibility, that allows
us to handle "trivial" cubic resonances, (3) sharp small divisors lower bounds
on three and four-waves modulation functions based on counting arguments, and
(4) partial normal form transformations and symmetrization arguments in the
Fourier space. Our theorem appears to be the first extended lifespan result for
quasilinear equations with non-trivial resonances on a multi-dimensional torus.


  We present high angular resolution (FWHM_beam < 0.2") observations of the
23.1-GHz methanol (CH_3OH) transition toward the massive-star forming region
NGC 7538 IRS 1. The two velocity components previously reported by Wilson et
al. are resolved into distinct spatial features with brightness temperatures
(T_B) greater than 10^4 K, proving their maser nature. Thus, NGC 7538 IRS 1 is
the third region confirmed to show methanol maser emission at this frequency.
The brighter 23.1-GHz spot coincides in position with a rare formaldehyde
(H_2CO) maser, and marginally with a 22.2-GHz water (H_2O) maser, for which we
report archival observations. The weaker CH_3OH spot coincides with an H_2O
maser. The ratio of T_B for the 23.1-GHz masers to that of the well-known
12.2-GHz CH_3OH masers in this region roughly agrees with model predictions.
However, the 23.1-GHz spots are offset in position from the CH_3OH masers at
other frequencies. This is difficult to interpret in terms of models that
assume that all the masers arise from the same clumps, but it may result from
turbulent conditions within the gas or rapid variations in the background
radiation field.


  The purpose of this work is to establish a link between the theory of Chern
classes for singular varieties and the geometry of the varieties in question.
Namely, we show that if $Z$ is a hypersurface in a compact complex manifold,
defined by the zero-scheme of a nonzero holomorphic section of a very ample
line bundle, then its Milnor classes, regarded as elements in the Chow group of
$Z$, determine the global L\^e cycles of $Z$; and viceversa: The L\^e cycles
determine the Milnor classes. Morally this implies, among other things, that
the Milnor classes determine the topology of the local Milnor fibres at each
point of $Z$, and the geometry of the local Milnor fibres determines the
corresponding Milnor classes.


  In this paper, we will talk about the titled elliptic curve defined over
imaginary quadratic fields such as $\mathbb{Q}(\sqrt{-q})$, where $q$ is
congruent to 3 modulo 8 and $(p,q)=1$.


  We present a model atmosphere analysis of cool hydrogen-rich white dwarfs
observed at the Very Large Telescope (VLT) with the X-shooter spectrograph. The
intermediate-dispersion and high signal-to-noise ratio of the spectra allowed
us to conduct a detailed analysis of hydrogen and heavy element line profiles.
In particular, we tested various prescriptions for hydrogen Balmer line
broadening parameters and determined the effective temperature and surface
gravity of each star. Three objects (NLTT 1675, 6390 and 11393) show the
presence of heavy elements (Mg, Al, Ca, or Fe). Our abundance analysis revealed
a relatively high iron to calcium ratio in NLTT 1675 and NLTT 6390. We also
present an analysis of spectropolarimetric data obtained at the VLT using the
focal reducer and low dispersion spectrograph (FORS) and we established strict
upper limits on the magnetic field strengths in three of the DAZ white dwarfs
and determined the longitudinal magnetic field strength in the DAZ NLTT 10480.
The class of DAZ white dwarfs comprises objects that are possibly accreting
material from their immediate circumstellar environment and the present study
contributes in establishing class properties.


  One of the most challenging problems in fingerprint recognition continues to
be establishing the identity of a suspect associated with partial and smudgy
fingerprints left at a crime scene (i.e., latent prints or fingermarks).
Despite the success of fixed-length embeddings for rolled and slap fingerprint
recognition, the features learned for latent fingerprint matching have mostly
been limited to local minutiae-based embeddings and have not directly leveraged
global representations for matching. In this paper, we combine global
embeddings with local embeddings for state-of-the-art latent to rolled matching
accuracy with high throughput. The combination of both local and global
representations leads to improved recognition accuracy across NIST SD 27, NIST
SD 302, MSP, MOLF DB1/DB4, and MOLF DB2/DB4 latent fingerprint datasets for
both closed-set (84.11%, 54.36%, 84.35%, 70.43%, 62.86% rank-1 retrieval rate,
respectively) and open-set (0.50, 0.74, 0.44, 0.60, 0.68 FNIR at FPIR=0.02,
respectively) identification scenarios on a gallery of 100K rolled
fingerprints. Not only do we fuse the complimentary representations, we also
use the local features to guide the global representations to focus on
discriminatory regions in two fingerprint images to be compared. This leads to
a multi-stage matching paradigm in which subsets of the retrieved candidate
lists for each probe image are passed to subsequent stages for further
processing, resulting in a considerable reduction in latency (requiring just
0.068 ms per latent to rolled comparison on a AMD EPYC 7543 32-Core Processor,
roughly 15K comparisons per second). Finally, we show the generalizability of
the fused representations for improving authentication accuracy across several
rolled, plain, and contactless fingerprint datasets.


  In this paper we describe B\"acklund transformations and hierarchies of exact
solutions for the fourth Painlev\'e equation (PIV) $${\d^2 w\over\d
z^2}={1\over2w}\left(\d w\over\d z\right)^2 + {{3\over2}}w^3 + 4zw^2 +
2(z^2-\alpha)w+{\beta\over w},\eqno(1){\hbox to 16pt{\hfill}}$$ with $\alpha$,
$\beta$ constants. Specifically, a nonlinear superposition principle for PIV,
hierarchies of solutions expressible in terms of complementary error or
parabolic cylinder functions as well as rational solutions will be derived.
Included amongst these hierarchies are solutions of (1) for which
$\alpha=\pm\tfr12n$ and $\beta=-\tfr12n^2$, with $n$ an integer. These
particular forms arise in quantum gravity and also satisfy a discrete analogue
of the first Painlev\'e equation. We also obtain a number of exact solutions of
the discrete fourth Painlev\'e equation $$x_{n+1}x_{n-1}+x_n(x_{n+1}+x_{n-1})=
{-2z_nx_n^3+(\eta-3\delta^{-2}-z_n^2)x_n^2+\mu^2\over
(x_n+z_n+\gamma)(x_n+z_n-\gamma)},\eqno(2){\hbox to 16pt{\hfill}}$$}%
{\narrower\noindent\baselineskip=12pt where $z_n=n\delta$ and $\eta$, $\delta$,
$\mu$ and $\gamma$ are constants, which, in an appropriate limit, reduces to
PIV (1). A suitable factorisation of (2) facilitates the identification of a
number of solutions which take the form of ratios of two polynomials in the
variable $z_n$ and the limits of these solutions yield rational solutions of
(1).


  A `forward walking' Green's Function Monte Carlo algorithm is used to obtain
expectation values for SU(3) lattice Yang-Mills theory in (3+1) dimensions. The
ground state energy and Wilson loops are calculated, and the finite-size
scaling behaviour is explored. Crude estimates of the string tension are
derived, which agree with previous results at intermediate couplings; but more
accurate results for larger loops will be required to establish scaling
behaviour at weak coupling.


  We study the effect of filter zero-point uncertainties on future supernova
dark energy missions. Fitting for calibration parameters using simultaneous
analysis of all Type Ia supernova standard candles achieves a significant
improvement over more traditional fit methods. This conclusion is robust under
diverse experimental configurations (number of observed supernovae, maximum
survey redshift, inclusion of additional systematics). This approach to
supernova fitting considerably eases otherwise stringent mission calibration
requirements. As an example we simulate a space-based mission based on the
proposed JDEM satellite; however the method and conclusions are general and
valid for any future supernova dark energy mission, ground or space-based.


  We investigate the effect of disorder in the laser intensity on the dynamics
of dark-state polaritons in an array of 20 cavities, each containing an
ensemble of four-level atoms that is described by a Bose-Hubbard Hamiltonian.
We examine the evolution of the polariton number in the cavities starting from
a state with either one or two polaritons in one of the cavities. For the case
of a single polariton without disorder in the laser intensity, we calculate the
wavefunction of the polariton and find that it disperses away from the initial
cavity with time. The addition of disorder results in minimal suppression of
the dispersal of the wavefunction. In the case of two polaritons with an
on-site repulsion to hopping strength ratio of 20, we find that the polaritons
form a repulsively bound state or dimer. Without disorder the dimer
wavefunction disperses similarly to the single polariton wavefunction but over
a longer time period. The addition of sufficiently strong disorder results in
localization of the polariton dimer. The localization length is found to be
described by a power law with exponent -1.31. We also find that we can localise
the dimer at any given time by switching on the disorder.


  We consider the problem of data-driven stochastic optimal control of an
unknown LTI dynamical system. Assuming the process noise is normally
distributed, we pose the problem of steering the state's mean and covariance to
a target normal distribution, under noisy data collected from the underlying
system, a problem commonly referred to as covariance steering (CS). A novel
framework for Data-driven Uncertainty quantification and density STeering
(DUST) is presented that simultaneously characterizes the noise affecting the
measured data and designs an optimal affine-feedback controller to steer the
density of the state to a prescribed terminal value. We use both indirect and
direct data-driven design approaches based on the notions of persistency of
excitation and subspace predictors to exactly represent the mean and covariance
dynamics of the state in terms of the data and noise realizations. Since both
the mean and the covariance steering sub-problems are plagued with
distributional uncertainty arising from noisy data collection, we first
estimate the noise realization from this dataset and subsequently compute
tractable upper bounds on the estimation errors. The moment steering problems
are then solved to optimality using techniques from robust control and robust
optimization. Lastly, we present an alternative control design approach based
on the certainty equivalence principle and interpret the problem as one of CS
under multiplicative uncertainties. We analyze the performance and efficacy of
each of these data-driven approaches using a case study and compare them with
their model-based counterparts.


  The moduli space of K3 surfaces $X$ with a purely non-symplectic automorphism
$\sigma$ of order $n\geq 2$ is one dimensional exactly when $\varphi(n)=8$ or
$10$. In this paper we classify and give explicit equations for the very
general members $(X,\sigma)$ of the irreducible components of maximal dimension
of such moduli spaces. In particular we show that there is a unique
one-dimensional component for $n=20,22, 24$, three irreducible components for
$n=15$ and two components in the remaining cases.


  In this brief review we study the discovery potential of heavy Higgs induced
single-top, same-sign top and triple-top quark productions at the Large Hadron
Collider (LHC). The context is general two Higgs doublet model where such
processes can be induced by additional Yukawa couplings and sub-Tev Higgs
bosons. We show that these processes can be discovered at the ongoing or future
high luminosity LHC run. Discovery of these multi-top productions may shed
light on the mechanism behind baryogenesis or cosmic inflation.


  A parameter of the P,T-odd Hamiltonian characterizing interaction of the
nuclear Schiff moment with the gradient of electronic density on the Xe nucleus
is calculated for an isolated Xe atom and for liquid xenon. We use more
realistic model of liquid medium than the spherical cell model used in
[B.Ravaine and A.Derevianko Phys. Rev. A, 69, 050101(R)(2004)]. Qualitatively
different results for enhancement of the P,T-odd effect in liquid xenon are
obtained when polarization of the medium is taken into account. Thus, proper
choice of the liquid phase model is crucially important even for calculation of
the properties dependent mostly on the electronic density near a nucleus.


  This paper is devoted to discussing affine Hirsch foliations on
$3$-manifolds. First, we prove that up to isotopic leaf-conjugacy, every closed
orientable $3$-manifold $M$ admits $0$, $1$ or $2$ affine Hirsch foliations.
Furthermore, every case is possible.
  Then, we analyze the $3$-manifolds admitting two affine Hirsch foliations
(abbreviated as Hirsch manifolds). On the one hand, we construct Hirsch
manifolds by using exchangeable braided links (abbreviated as DEBL Hirsch
manifolds); on the other hand, we show that every Hirsch manifold virtually is
a DEBL Hirsch manifold.
  Finally, we show that for every $n\in \mathbb{N}$, there are only finitely
many Hirsch manifolds with strand number $n$. Here the strand number of a
Hirsch manifold $M$ is a positive integer defined by using strand numbers of
braids.


  In this paper we propose the Structured Deep Neural Network (structured DNN)
as a structured and deep learning framework. This approach can learn to find
the best structured object (such as a label sequence) given a structured input
(such as a vector sequence) by globally considering the mapping relationships
between the structures rather than item by item.
  When automatic speech recognition is viewed as a special case of such a
structured learning problem, where we have the acoustic vector sequence as the
input and the phoneme label sequence as the output, it becomes possible to
comprehensively learn utterance by utterance as a whole, rather than frame by
frame.
  Structured Support Vector Machine (structured SVM) was proposed to perform
ASR with structured learning previously, but limited by the linear nature of
SVM. Here we propose structured DNN to use nonlinear transformations in
multi-layers as a structured and deep learning approach. This approach was
shown to beat structured SVM in preliminary experiments on TIMIT.


  A class of parabolic cross-diffusion systems modeling the interaction of an
arbitrary number of population species is analyzed in a bounded domain with
no-flux boundary conditions. The equations are formally derived from a
random-walk lattice model in the diffusion limit. Compared to previous results
in the literature, the novelty is the combination of general degenerate
diffusion and volume-filling effects. Conditions on the nonlinear diffusion
coefficients are identified, which yield a formal gradient-flow or entropy
structure. This structure allows for the proof of global-in-time existence of
bounded weak solutions and the exponential convergence of the solutions to the
constant steady state. The existence proof is based on an approximation
argument, the entropy inequality, and new nonlinear Aubin-Lions compactness
lemmas. The proof of the large-time behavior employs the entropy estimate and
convex Sobolev inequalities. Moreover, under simplifiying assumptions on the
nonlinearities, the uniqueness of weak solutions is shown by using the $H^{-1}$
method, the $E$-monotonicity technique of Gajewski, and the subadditivity of
the Fisher information.


  We have studied 14 southern infrared dark clouds (IRDCs) using the data taken
from the Millimetre Astronomy Legacy Team 90 GHz (MALT90) survey and the
GLIMPSE and MIPSGAL mid-infrared survey of the inner Galaxy. The physical and
chemical characteristics of the 14 IRDCs are investigated using N2H+(1-0),
HNC(1-0), HCO+(1-0), and HCN(1-0) molecular lines. We find that the 14 IRDCs
are in different evolutionary stages from the "starless" to the sources with an
UCHII region. Three IRDCs are detected to have the star forming activities. The
integrated intensity ratios I(HCO+)/I(HCN), I(N2H+)/I(HCN), and I(HNC)/I(HCN)
are all about 1.5, which is different from the previous measurements,
suggesting that the integrated intensity ratios may be affected by the cloud
environments. The integrated intensities of HNC, HCO+ and HCN show a tight
correlation for the 14 IRDCs, implying a close link to the chemical evolution
of these three species in the IRDCs. The derived excitation temperature for
each IRDC is less than 25 K. We estimate the abundances of the four molecules
from 10^(-11) to 10^(-9), and the average abundance ratios N(HNC)/N(HCN) = 1.4+
-0.50, N(HNC)/N(HCO+) = 1.74 + - 0.22, N(HCN)/N(HCO+)= 1.21 + - 0.41.


  Bird, et. al. and Sasaki, et. al. have recently proposed the intriguing
possibility that the black holes detected by LIGO could be all or part of the
cosmological dark matter. This offers an alternative to WIMPs and axions, where
dark matter could be comprised solely of Standard Model particles. The mass
range lies within an observationally viable window and the predicted merger
rate can be tested by future LIGO observations. In this paper, we argue that
non-thermal histories favor production of black holes near this mass range --
with heavier ones unlikely to form in the early universe and lighter black
holes being diluted through late-time entropy production. We discuss how this
prediction depends on the primordial power spectrum, the likelihood of black
hole formation, and the underlying model parameters. We find the prediction for
the preferred mass range to be rather robust assuming a blue spectral index
less than two. We consider the resulting relic density in black holes, and
using recent observational constraints, establish whether they could account
for all of the dark matter today.


  Particle motion in the fields of Aharonov-Bohm and Aharonov-Casher is
considered in framework of the classical theory to reveal conditions admitting
duality of the two configurations. Important role of orientation of the
magnetic dipole moment is demonstrated. Duality becomes totally destroyed by
addition of electric dipole and/or higher multipole moments. Correspondence
between quantum and classical considerations is also discussed.


  This article investigates the properties of a scalar fifth force that arises
in a scalar tensor-theory with a chameleon screening mechanism in the context
of gravity space missions like the MICROSCOPE experiment. In such an
experiment, the propagation of the chameleon field inside the nested cylinders
of the experiment causes a fifth force when the cylinders are not perfectly
co-axial. We propose a semi-analytic method to compute the field distribution
and the induced fifth force and compare it to a full numerical simulation, in
settings where the cylindrical symmetry is broken. The scaling of the fifth
force with both the parameters of the model and the geometry of the experiment
is discussed. We show that the fifth force is repulsive, hence adds a
destabilizing stiffness that should be included in the force budget acting on
the detector. This opens the way to a new method to constrain a scalar fifth
force in screened models.


  We consider high-energy proton-heavy nucleus scattering within the framework
of the Glauber-Gribov approximation and taking into account cross section
fluctuations. Fixing parameters of the model for cross section fluctuations by
the available data, we make predictions for the total, elastic and coherent
diffractive dissociation proton-nucleus cross sections for the RHIC and LHC
energy range. We predict a strong change of the A-dependence of diffraction
dissociation from A^{0.42} at RHIC energies to A^{0.27} at LHC energies.
  Based on the obtained results, we discuss the approach of the interactions to
the black body (unitarity) limit. We estimate the electromagnetic contribution
to coherent pA diffraction and find that it dominates the coherent diffractive
cross section on heavy nuclear targets in the RHIC and LHC kinematics.


  We demonstrate that the transport characteristics of deep optical lattices
with one or multiple off-resonant external energy offsets can be
greatly-enhanced by modulating the lattice depth in an exotic way. We derive
effective stationary models for our proposed modulation schemes in the strongly
interacting limit, where only one particle can occupy any given site.
Afterwards we discuss the modifications necessary to recover transport when
more than one particle may occupy the lattice sites. For the specific five-site
lattices discussed, we numerically predict transport gains for ranging from
$4.7\times 10^6$ to $9.8\times 10^{8}$.


  We consider an M/M/1 update-and-decide system where Poisson distributed
decisions are made based on the received updates. We propose to characterize
the freshness of the received updates at decision epochs with Age upon
Decisions (AuD). Under the first-come-first-served policy (FCFS), the closed
form average AuD is derived. We show that the average AuD of the system is
determined by the arrival rate and the service rate, and is independent of the
decision rate. Thus, merely increasing the decision rate does not improve the
timeliness of decisions. Nevertheless, increasing the arrival rate and the
service rate simultaneously can decrease the average AuD efficiently.


  Random binning features, introduced in the seminal paper of Rahimi and Recht
(2007), are an efficient method for approximating a kernel matrix using
locality sensitive hashing. Random binning features provide a very simple and
efficient way of approximating the Laplace kernel but unfortunately do not
apply to many important classes of kernels, notably ones that generate smooth
Gaussian processes, such as the Gaussian kernel and Matern kernel. In this
paper, we introduce a simple weighted version of random binning features and
show that the corresponding kernel function generates Gaussian processes of any
desired smoothness. We show that our weighted random binning features provide a
spectral approximation to the corresponding kernel matrix, leading to efficient
algorithms for kernel ridge regression. Experiments on large scale regression
datasets show that our method outperforms the accuracy of random Fourier
features method.


  Let $\mu$ be a positive Borel measure and $T_\mu$ be the bounded Toeplitz
operator induced by $\mu$ on the Bergman or Fock space. In this paper, we
mainly investigate the invertibility of the Toeplitz operator $T_\mu$ and the
Douglas question on the Bergman and Fock spaces. In the Bergman-space setting,
we obtain several necessary and sufficient conditions for the invertibility of
$T_\mu$ in terms of the Berezin transform of $\mu$ and the reverse Carleson
condition in two classical cases: (1) $\mu$ is absolutely continuous with
respect to the normalized area measure on the open unit disk $\mathbb D$; (2)
$\mu$ is the pull-back measure of the normalized area measure under an analytic
self-mapping of $\mathbb D$. Nonetheless, we show that there exists a Carleson
measure for the Bergman space such that its Berezin transform is bounded below
but the corresponding Toeplitz operator is not invertible. On the Fock space,
we show that $T_\mu$ is invertible if and only if $\mu$ is a reverse Carleson
measure, but the invertibility of $T_\mu$ is not completely determined by the
invertibility of the Berezin transform of $\mu$. These suggest that the answers
to the Douglas question for Toeplitz operators induced by positive measures on
the Bergman and Fock spaces are both negative in general cases.


  In this paper we consider introducing careful regularization in the
quantization of Maxwell theory in the asymptotic null infinity. This allows
systematic discussions of the commutators in various boundary conditions, and
application of Dirac brackets accordingly in a controlled manner. This method
is most useful when we consider asymptotic charges that are not localized at
the boundary $u\to \pm \infty$ like large gauge transformations. We show that
our method reproduces the operator algebra in known cases, and it can be
applied to other space-time symmetry charges such as the BMS transformations.
We also obtain the asymptotic form of the U(1) charge following from the
electromagnetic duality in an explicitly EM symmetric Schwarz-Sen type action.
Using our regularization method, we demonstrate that the charge generates the
expected transformation of a helicity operator. Our method promises
applications in more generic theories.


  We study the statistical mechanics of a class of problems whose phase space
is the set of permutations of an ensemble of quenched random positions.
Specific examples analyzed are the finite temperature traveling salesman
problem on several different domains and various problems in one dimension such
as the so called descent problem. We first motivate our method by analyzing
these problems using the annealed approximation, then the limit of a large
number of points we develop a formalism to carry out the quenched calculation.
This formalism does not require the replica method and its predictions are
found to agree with Monte Carlo simulations. In addition our method reproduces
an exact mathematical result for the Maximum traveling salesman problem in two
dimensions and suggests its generalization to higher dimensions. The general
approach may provide an alternative method to study certain systems with
quenched disorder.


  In this work, we consider the use of a model-based decoder in combination
with an unsupervised learning strategy for direction-of-arrival (DoA)
estimation. Relying only on unlabeled training data we show in our analysis
that we can outperform existing unsupervised machine learning methods and
classical methods. The proposed approach consists of introducing a model-based
decoder in an autoencoder architecture which leads to a meaningful
representation of the statistical model in the latent space of the autoencoder.
Our numerical simulations show that the performance of the presented approach
is not affected by correlated signals and performs well for both, uncorrelated
and correlated, scenarios. This is a result of the fact, that, in the proposed
framework, the signal covariance matrix and the DOAs are estimated
simultaneously.


  We have made radio- and millimeter-wavelength interferometric observations of
a variety of molecular absorption lines toward the gravitational lens systems
B0218+357 and PKS1830-211. The absorption occurs in the lensing galaxies at
redshifts of 0.685 and 0.89, respectively. The high spatial resolution of our
VLA and VLBA observations allows imaging of the background continuum emission
and the absorption distribution. Our multi-transition studies yield estimates
of the cosmic microwave background temperature at z = 0.89 and determinations
of molecular and isotopic abundance ratios, which allow meaningful comparisons
with Galactic molecular clouds.


  For a graph $G$ and integers $a_i\ge 1$, the expression $G \rightarrow
(a_1,\dots,a_r)^v$ means that for any $r$-coloring of the vertices of $G$ there
exists a monochromatic $a_i$-clique in $G$ for some color $i \in
\{1,\cdots,r\}$. The vertex Folkman numbers are defined as
$F_v(a_1,\dots,a_r;H) = \min\{|V(G)| : G$ is $H$-free and $G \rightarrow
(a_1,\dots,a_r)^v\}$, where $H$ is a graph. Such vertex Folkman numbers have
been extensively studied for $H=K_s$ with $s>\max\{a_i\}_{1\le i \le r}$. If
$a_i=a$ for all $i$, then we use notation $F_v(a^r;H)=F_v(a_1,\dots,a_r;H)$.
  Let $J_k$ be the complete graph $K_k$ missing one edge, i.e. $J_k=K_k-e$. In
this work we focus on vertex Folkman numbers with $H=J_k$, in particular for
$k=4$ and $a_i\le 3$. A result by Ne\v{s}et\v{r}il and R\"{o}dl from 1976
implies that $F_v(3^r;J_4)$ is well defined for any $r\ge 2$. We present a new
and more direct proof of this fact. The simplest but already intriguing case is
that of $F_v(3,3;J_4)$, for which we establish the upper bound of 135 by using
the $J_4$-free process. We obtain the exact values and bounds for a few other
small cases of $F_v(a_1,\dots,a_r;J_4)$ when $a_i \le 3$ for all $1 \le i \le
r$, including $F_v(2,3;J_4)=14$, $F_v(2^4;J_4)=15$, and $22 \le F_v(2^5;J_4)
\le 25$. Note that $F_v(2^r;J_4)$ is the smallest number of vertices in any
$J_4$-free graph with chromatic number $r+1$. Most of the results were obtained
with the help of computations, but some of the upper bound graphs we found are
interesting by themselves.


  This paper describes a new parallel kinematic architecture for machining
applications: the orthoglide. This machine features three fixed parallel linear
joints which are mounted orthogonally and a mobile platform which moves in the
Cartesian x-y-z space with fixed orientation. The main interest of the
orthoglide is that it takes benefit from the advantages of the popular PPP
serial machines (regular Cartesian workspace shape and uniform performances) as
well as from the parallel kinematic arrangement of the links (less inertia and
better dynamic performances), which makes the orthoglide well suited to
high-speed machining applications. Possible extension of the orthoglide to
5-axis machining is also investigated.


  The multiresolution diffusion entropy analysis is used to evaluate the
stochastic information left in a time series after systematic removal of
certain non-stationarities. This method allows us to establish whether the
identified patterns are sufficient to capture all relevant information
contained in a time series. If they do not, the method suggests the need for
further interpretation to explain the residual memory in the signal. We apply
the multiresolution diffusion entropy analysis to the daily count of births to
teens in Texas from 1964 through 2000 because it is a typical example of a
non-stationary time series, having an anomalous trend, an annual variation, as
well as short time fluctuations. The analysis is repeated for the three main
racial/ethnic groups in Texas (White, Hispanic and African American), as well
as, to married and unmarried teens during the years from 1994 to 2000 and we
study the differences that emerge among the groups.


  This review summarizes recent attempts to reconstruct the expansion history
of the Universe and to probe the nature of dark energy. Reconstruction methods
can be broadly classified into parametric and non-parametric approaches. It is
encouraging that, even with the limited observational data currently available,
different approaches give consistent results for the reconstruction of the
Hubble parameter $H(z)$ and the effective equation of state $w(z)$ of dark
energy. Model independent reconstruction using current data allows for modest
evolution of dark energy density with redshift. However, a cosmological
constant (= dark energy with a constant energy density) remains an excellent
fit to the data. Some pitfalls to be guarded against during cosmological
reconstruction are summarized and future directions for the model independent
reconstruction of dark energy are explored.


  In this paper, we explore existing synergies between private and public
transportation as provided by taxi and bus services on the level of individual
trips. While these modes are typically separated for economic reasons, in a
future with shared Autonomous Vehicles (AVs) providing cheap and efficient
transportation services, such distinctions will blur. Consequently,
optimization based on real-time data will allow exploiting parallels in demand
in a dynamic way, such as the proposed approach of the current work. New
operational and pricing strategies will then evolve, providing service in a
more efficient way and utilizing a dynamic landscape of urban transportation.
In the current work, we evaluate existing parallels between individual bus and
taxi trips in two Asian cities and show how exploiting these synergies could
lead to an increase in transportation service quality.


  The SM prediction for the ratio $\varepsilon^\prime/\varepsilon$ appears to
be significantly below the experimental data. Also $\varepsilon_K$ in the SM
tends to be below the data. Any NP removing these anomalies will first of all
have impact on flavour observables in the $K$ meson system, in particular on
rare $K$ decays and $\Delta M_K$. Restricting the operators contributing to
$\varepsilon^\prime/\varepsilon$ to the SM ones and to the corresponding primed
operators, NP contributions are quite generally dominated either by QCD penguin
(QCDP) operators $Q_6(Q_6^\prime)$ or electroweak penguin (EWP) operators
$Q_8(Q_8^\prime)$ with rather different implications for other flavour
observables. We discuss general models with tree-level $Z$ and $Z^\prime$
flavour violating exchanges and few specific models. We find that simultaneous
enhancements of $\varepsilon^\prime/\varepsilon$, $\varepsilon_K$,
$\mathcal{B}(K_L\to\pi^0\nu\bar\nu)$ and $\mathcal{B}(K^+\to\pi^+\nu\bar\nu)$
in $Z$ scenarios are only possible in the presence of both LH and RH
flavour-violating couplings. In $Z^\prime$ scenarios this is not required but
the size of NP effects and the correlation between
$\mathcal{B}(K_L\to\pi^0\nu\bar\nu)$ and $\mathcal{B}(K^+\to\pi^+\nu\bar\nu)$
depends strongly on whether QCDP or EWP dominate NP contributions to
$\varepsilon^\prime/\varepsilon$. In the QCDP case possible enhancements of
both branching ratios are much larger than for EWP scenario and take place only
on the branch parallel to the Grossman-Nir bound, which is in the case of EWP
dominance only possible in the absence of NP in $\varepsilon_K$. QCDP and EWP
scenarios of NP in $\varepsilon^\prime/\varepsilon$ can also be uniquely
distinguished by the size and the sign of NP contribution to $\Delta M_K$,
elevating the importance of the precise calculation of $\Delta M_K$ in the SM.


  The article considers minimization of the expectation of convex function.
Problems of this type often arise in machine learning and a number of other
applications. In practice, stochastic gradient descent (SGD) and similar
procedures are often used to solve such problems. We propose to use the
ellipsoid method with minibatching, which converges linearly and hence requires
significantly less iterations than SGD. This is verified by our experiments,
which are publicly available. The algorithm does not require neither smoothness
nor strong convexity of target function to achieve linear convergence. We prove
that the method arrives at approximate solution with given probability when
using minibatches of size proportional to the desired precision to the power
-2. This enables efficient parallel execution of the algorithm, whereas
possibilities for batch parallelization of SGD are rather limited. Despite fast
convergence, ellipsoid method can result in a greater total number of calls to
oracle than SGD, which works decently with small batches. Complexity is
quadratic in dimension of the problem, hence the method is suitable for
relatively small dimensionalities.


  Partitioning and grouping of similar objects plays a fundamental role in
image segmentation and in clustering problems. In such problems a typical goal
is to group together similar objects, or pixels in the case of image
processing. At the same time another goal is to have each group distinctly
dissimilar from the rest and possibly to have the group size fairly large.
These goals are often combined as a ratio optimization problem. One example of
such problem is the normalized cut problem, another is the ratio regions
problem. We devise here the first polynomial time algorithms solving these
problems optimally. The algorithms are efficient and combinatorial. This
contrasts with the heuristic approaches used in the image segmentation
literature that formulate those problems as nonlinear optimization problems,
which are then relaxed and solved with spectral techniques in real numbers.
These approaches not only fail to deliver an optimal solution, but they are
also computationally expensive. The algorithms presented here use as a
subroutine a minimum $s,t-cut procedure on a related graph which is of
polynomial size. The output consists of the optimal solution to the respective
ratio problem, as well as a sequence of nested solution with respect to any
relative weighting of the objectives of the numerator and denominator.
  An extension of the results here to bi-criteria and multi-criteria objective
functions is presented in part II.


  Some geometric properties of a normalized hyper-Bessel functions are
investigated. Especially we focus on the radii of starlikeness, convexity, and
uniform convexity of hyper-Bessel functions and we show that the obtained radii
satisfy some transcendental equations. In addition, we give some bounds for the
first positive zero of normalized hyper-Bessel functions, Redheffer-type
inequalities, and bounds for this function. In this study we take advantage of
Euler-Rayleigh inequalities and Laguerre-P\'{o}lya class of real entire
functions, intensively.


  We introduce methods for clock synchronization that make use of the adiabatic
exchange of nondegenerate two-level quantum systems: ticking qubits. Schemes
involving the exchange of N independent qubits with frequency $\omega$ give a
synchronization accuracy that scales as $(\omega\sqrt{N})^{-1}$, i.e., as the
standard quantum limit. We introduce a protocol that makes use of N coherent
exchanges of a single qubit at frequency $\omega$, leading to an accuracy that
scales as $(\omega N)^{-1}\log N$. This protocol beats the standard quantum
limit without the use of entanglement, and we argue that this scaling is the
fundamental limit for clock synchronization allowed by quantum mechanics. We
analyse the performance of these protocols when used with a lossy channel.


  Nonlinear dynamical systems can be made easier to control by lifting them
into the space of observable functions, where their evolution is described by
the linear Koopman operator. This paper describes how the Koopman operator can
be used to generate approximate linear, bilinear, and nonlinear model
realizations from data, and argues in favor of bilinear realizations for
characterizing systems with unknown dynamics. Necessary and sufficient
conditions for a dynamical system to have a valid linear or bilinear
realization over a given set of observable functions are presented and used to
show that every control-affine system admits an infinite-dimensional bilinear
realization, but does not necessarily admit a linear one. Therefore,
approximate bilinear realizations constructed from generic sets of basis
functions tend to improve as the number of basis functions increases, whereas
approximate linear realizations may not. To demonstrate the advantages of
bilinear Koopman realizations for control, a linear, bilinear, and nonlinear
Koopman model realization of a simulated robot arm are constructed from data.
In a trajectory following task, the bilinear realization exceeds the prediction
accuracy of the linear realization and the computational efficiency of the
nonlinear realization when incorporated into a model predictive control
framework.


  We investigate the role of relativistic and magnetic corrections in photo
ionization of hydrogen-like ions. For hydrogen, the wavelengths of the laser
resides in the weakly ultra violet region. For higher nuclear charges, the
laser parameters are scaled in a manner which renders the time-dependent
Schr{\"o}dinger equation in the dipole approximation independent of nuclear
charge. By comparing with numerical solutions of both the relativistic
time-dependent Dirac equation and the non-relativistic Schr{\"o}dinger equation
-- with and without magnetic interactions, the influence of these interactions
are revealed. Moreover, we investigate to what extent relativistic effects are
induced by the relativistic shift in the structure of the ions or by the strong
external field. In agreement with a recent work, Ivanova et al., Phys. Rev. A
{\bf 98}, 063402 (2018), we find that the dominant relativistic correction is
the former, i.e., the relativistic shift in the binding energy of the ions.
However, dynamical relativistic corrections induced by the laser field are also
seen -- in addition to a significant influence of the magnetic field for the
longer wavelengths.


  Recently, the BESIII experiment renewed the interest on baryon form factors
by measuring the modulus and phase of the ratio $G_E^\Lambda/G_M^\Lambda$
between the electric and the magnetic $\Lambda$ form factors with unprecedented
accuracy. The BESIII measurement together with older, less precise data, can be
analyzed by means of a dispersive procedure based on analyticity and a set of
first-principle constraints. Such a dispersive procedure shows the unique
ability to determine for the first time the complex structure of the ratio
knowing its modulus and phase measured by the BESIII collaboration at only one
energy point. Different classes of solutions are obtained, and in all cases,
the time-like and space-like behaviors show interesting properties: space-like
zeros or unexpected large determinations for the phase. More data at different
energies would be crucial to enhance the predictive power of the dispersive
procedure and to unravel further remarkable features of the $\Lambda$ baryon.


  We study the magnetic properties of topological insulators doped with
isoelectronic magnetic impurities. We obtain that at zero temperature the
impurities order ferromagnetically, but when raising the temperature the
topological insulator undergoes a first order phase transition to a spin
density wave phase before the system reaches the paramagnetic phase. The origin
of this phase is the non-trivial dependence of the topological insulator spin
susceptibility on the momentum. We analyze the coupling of the non-uniform
magnetic phase with the Dirac electronic system that occurs at the surfaces of
the topological insulators.


  We analyse the dynamics of a hard-sphere lattice gas on generalised Bethe
lattices using a projective approximation scheme (PAS). The latter consists in
mapping the system's dynamics to a finite set of global observables, closure of
the resulting equations is obtained by approximating the true non-equilibrium
state by a pseudo-equilibrium based only on the value of the observables under
consideration. We study the liquid--crystal as well as the liquid--spin-glass
transitions, special attention is given to the prediction of equilibration
times and their divergence close to the phase transitions. Analytical results
are corroborated by Monte-Carlo simulations.


  The Yeo-Johnson (YJ) transformation is a standard parametrized per-feature
unidimensional transformation often used to Gaussianize features in machine
learning. In this paper, we investigate the problem of applying the YJ
transformation in a cross-silo Federated Learning setting under privacy
constraints. For the first time, we prove that the YJ negative log-likelihood
is in fact convex, which allows us to optimize it with exponential search. We
numerically show that the resulting algorithm is more stable than the
state-of-the-art approach based on the Brent minimization method. Building on
this simple algorithm and Secure Multiparty Computation routines, we propose
SecureFedYJ, a federated algorithm that performs a pooled-equivalent YJ
transformation without leaking more information than the final fitted
parameters do. Quantitative experiments on real data demonstrate that, in
addition to being secure, our approach reliably normalizes features across
silos as well as if data were pooled, making it a viable approach for safe
federated feature Gaussianization.


  It is often of interest to decompose a total effect of an exposure into the
component that acts on the outcome through some mediator and the component that
acts independently through other pathways. Said another way, we are interested
in the direct and indirect effects of the exposure on the outcome. Even if the
exposure is randomly assigned, it is often infeasible to randomize the
mediator, leaving the mediator-outcome confounding not fully controlled. We
develop a sensitivity analysis technique that can bound the direct and indirect
effects without parametric assumptions about the unmeasured mediator-outcome
confounding.


  In the minimal left-right symmetric model, there are only two intrinsic CP
violating phases to account for all CP violation in both the quark and lepton
sectors, if CP is broken spontaneously by the complex phases in the VEV's of
the scalar fields. In addition, the left- and right-handed Majorana mass terms
for the neutrinos are proportional to each other due to the parity in the
model. This is thus a very constrained framework, making the existence of
correlations among the CP violation in leptogenesis, neutrino oscillation and
neutrinoless double beta decay possible. In these models, CP violation in the
leptonic sector and CP violation in the quark sector are also related. We find,
however, that such connection is rather weak due to the large hierarchy in the
bi-doublet VEV required by a realistic quark sector.


  The datasets presented in this article are related to materials research on
hard ferromagnet in TM-Fe-Si (TM=Ti, Zr, Hf, V, Nb, and Ta) ternary systems.
The motivation for data collection is based on the research paper entitled
"Novel hard magnetic phase with Zr$_{11.5}$Fe$_{53}$Si$_{35.5}$ composition".
The datasets are composed of scanning electron microscope images, X-ray
diffraction (XRD) patterns, and magnetization data for
TM$_{7}$Fe$_{52}$Si$_{41}$ annealed at 1050 $^{\circ}$C. The chemical
compositions of constituent phases were determined by an energy dispersive
X-ray spectrometer (EDS). The phase analysis was performed using XRD and EDS
results. The Curie temperature of each sample was obtained using magnetization
data, and the coercive field was determined for hard ferromagnet samples
Zr$_{7}$Fe$_{52}$Si$_{41}$ and Hf$_{7}$Fe$_{52}$Si$_{41}$. The datasets would
be useful for developing an Fe-based rare-earth-free permanent magnet, which is
one of the central issues of materials science.


  We develop a theory of generalist predation showing how alternative prey
species are affected by changes in both mean abundance and variability
(coefficient of variation) of their predator's primary prey. The theory is
motivated by the indirect effects of cyclic rodent populations on
ground-breeding birds, and developed through progressive analytic
simplifications of an empirically-based model. It applies nonetheless to many
other systems where primary prey have fast life-histories and can become
locally superabundant, which facilitates impact on alternative prey species. In
contrast to classic apparent competition theory based on symmetric
interactions, our results suggest that predator effects on alternative prey
should generally decrease with mean primary prey abundance, and increase with
primary prey variability (low to high CV) - unless predators have strong
aggregative responses, in which case these results can be reversed.
Approximations of models including predator dynamics (general numerical
response with possible delays) confirm these results but further suggest that
negative temporal correlation between predator and primary prey is harmful to
alternative prey. We find in general that predator numerical responses are
crucial to predict the response of ecosystems to changes in key prey species
exhibiting outbreaks, and extend the apparent competition/mutualism theory to
asymmetric interactions.


  Motivation: Site directed mutagenesis is widely used to understand the
structure and function of biomolecules. Computational prediction of protein
mutation impacts offers a fast, economical and potentially accurate alternative
to laboratory mutagenesis. Most existing methods rely on geometric
descriptions, this work introduces a topology based approach to provide an
entirely new representation of protein mutation impacts that could not be
obtained from conventional techniques. Results: Topology based mutation
predictor (T-MP) is introduced to dramatically reduce the geometric complexity
and number of degrees of freedom of proteins, while element specific persistent
homology is proposed to retain essential biological information. The present
approach is found to outperform other existing methods in globular protein
mutation impact predictions. A Pearson correlation coefficient of 0.82 with an
RMSE of 0.92 kcal/mol is obtained on a test set of 350 mutation samples. For
the prediction of membrane protein stability changes upon mutation, the
proposed topological approach has a 84% higher Pearson correlation coefficient
than the current state-of-the-art empirical methods, achieving a Pearson
correlation of 0.57 and an RMSE of 1.09 kcal/mol in a 5-fold cross validation
on a set of 223 membrane protein mutation samples.


  We present the first systematic comparison of the charged-particle
pseudorapidity densities for three widely different collision systems, pp,
p-Pb, and Pb-Pb, at the top energy of the Large Hadron Collider ($\sqrt{s_{\rm
NN}} = 5.02$ TeV) measured over a wide pseudorapidity range (${-3.5 <\eta
<5}$), the widest possible among the four experiments at that facility. The
systematic uncertainties are minimised since the measurements are recorded by
the same experimental apparatus (ALICE). The distributions for p-Pb and Pb-Pb
collisions are determined as a function of the centrality of the collisions,
while results from pp collisions are reported for inelastic events with at
least one charged particle at midrapidity. The charged-particle pseudorapidity
densities are, under simple and robust assumptions, transformed to
charged-particle rapidity densities. This allows for the calculation and the
presentation of the evolution of the width of the rapidity distributions and of
a lower bound on the Bjorken energy density, as a function of the number of
participants in all three collision systems. We find a decreasing width of the
particle production, and roughly a smooth ten fold increase in the energy
density, as the system size grows, which is consistent with a gradually higher
dense phase of matter.


  The bound on the proton lifetime is one of a small handful of observations
that constrains physics not far from the Planck scale. This calls for a
calculation of the proton lifetime in quantum gravity. Here, we calculate how
quantum fluctuations of the metric impact four-fermion interactions which
mediate proton decay. We find that quantum gravity lowers the scaling dimension
of the four-fermion interaction, suppressing proton decay and raising the
proton lifetime significantly. As a special case, we analyze asymptotically
safe quantum gravity, in which we discover that proton-decay-mediating
four-fermion interactions are strictly zero.


  We describe the inter-dependence of four properties of classical double radio
sources - spectral index, linear size, luminosity and redshift - from an
extensive study based on spectroscopically-identified complete samples. We use
these relationships to discuss aspects of strategies for searching for radio
galaxies at extreme redshifts, in the context of possible capabilities of the
new generation of proposed radio telescopes.


  In this paper, a sorting technique is presented that takes as input a data
set whose primary key domain is known to the sorting algorithm, and works with
an time efficiency of O(n+k), where k is the primary key domain. It is shown
that the algorithm has applicability over a wide range of data sets. Later, a
parallel formulation of the same is proposed and its effectiveness is argued.
Though this algorithm is applicable over a wide range of general data sets, it
finds special application (much superior to others) in places where sorting
information that arrives in parts and in cases where input data is huge in
size.


  We establish a generalized Perron-Frobenius theorem, based on a combinatorial
criterion which entails the existence of an eigenvector for any nonlinear
order-preserving and positively homogeneous map $f$ acting on the open orthant
$\mathbb{R}_{\scriptscriptstyle >0}^n$. This criterion involves dominions,
i.e., sets of states that can be made invariant by one player in a two-person
game that only depends on the behavior of $f$ "at infinity". In this way, we
characterize the situation in which for all $\alpha, \beta > 0$, the "slice
space" $\mathcal{S}_\alpha^\beta := \{ x \in \mathbb{R}_{\scriptscriptstyle
>0}^n \mid \alpha x \leq f(x) \leq \beta x \}$ is bounded in Hilbert's
projective metric, or, equivalently, for all uniform perturbations $g$ of $f$,
all the orbits of $g$ are bounded in Hilbert's projective metric. This solves a
problem raised by Gaubert and Gunawardena (Trans. AMS, 2004). We also show that
the uniqueness of an eigenvector is characterized by a dominion condition,
involving a different game depending now on the local behavior of $f$ near an
eigenvector. We show that the dominion conditions can be verified by directed
hypergraph methods. We finally illustrate these results by considering specific
classes of nonlinear maps, including Shapley operators, generalized means and
nonnegative tensors.


  Our previous theoretical study of the impact of an accreting envelope on the
thermal state of an underlying white dwarf (WD) has yielded equilibrium core
temperatures, classical nova ignition masses and thermal luminosities for WDs
accreting at time averaged rates of <Mdot> = 10^-11 - 10^-8 Msun/yr. These
<Mdot>'s are appropriate to WDs in cataclysmic variables (CVs) of P_orb <~ 7
hr, many of which accrete sporadically as Dwarf Novae. Approximately thirty
nonmagnetic Dwarf Novae have been observed in quiescence, when the accretion
rate is low enough for spectral detection of the WD photosphere, and a
measurement of T_eff. We use our theoretical work to translate the measured
T_eff's into local time-averaged accretion rates, confirming the factor of ten
drop in <Mdot> predicted for CV's as they transit the period gap. For DN below
the period gap, we show that if <Mdot> is that given by gravitational radiation
losses alone, then the WD masses are > 0.8 Msun. An alternative conclusion is
that the masses are closer to 0.6 Msun and <Mdot> is 3-4 times larger than that
expected from gravitational radiation losses. In either case, it is very
plausible that a subset of CVs with P_orb < 2 hours will have T_eff's low
enough for them to become non-radial pulsators, as discovered by van Zyl and
collaborators in GW Lib.


  Multimodal sentiment analysis aims to identify the emotions expressed by
individuals through visual, language, and acoustic cues. However, most of the
existing research efforts assume that all modalities are available during both
training and testing, making their algorithms susceptible to the missing
modality scenario. In this paper, we propose a novel knowledge-transfer network
to translate between different modalities to reconstruct the missing audio
modalities. Moreover, we develop a cross-modality attention mechanism to retain
the maximal information of the reconstructed and observed modalities for
sentiment prediction. Extensive experiments on three publicly available
datasets demonstrate significant improvements over baselines and achieve
comparable results to the previous methods with complete multi-modality
supervision.


  We suggest measuring the one-particle density matrix of a trapped ultracold
atomic cloud by scattering fast atoms in a pure momentum state off the cloud.
The lowest-order probability for the process, resulting in a pair of outcoming
fast atoms for each incoming one, as well as of its time reversed counterpart,
turns out to be given by the Fourier transform of the density matrix.
Accordingly, important information about quantum correlations can be deduced
directly from the differential scattering cross-section of these processes.
Several most interesting cases of scattering - from a single condensate
containing a vortex, and from a split condensate characterized by some phase
difference - are discussed.


  Reliable systems require effective monitoring techniques for fault
identification. System-level diagnosis was originally proposed in the 1960s as
a test-based approach to monitor and identify faulty components of a general
system. Over the last decades, several diagnosis models and strategies have
been proposed, based on different fault models, and applied to the most diverse
types of computer systems. In the 1990s, unreliable failure detectors emerged
as an abstraction to enable consensus in asynchronous systems subject to crash
faults. Since then, failure detectors have become the \textit{de facto}
standard for monitoring distributed systems. The purpose of the present work is
to fill a conceptual gap by presenting a distributed diagnosis model that is
consistent with unreliable failure detectors. Results are presented for the
number of tests/monitoring messages required, latency for event detection, as
well as completeness and accuracy. Three different failure detectors compliant
with the proposed model are presented, including vRing and vCube which provide
scalable alternatives to the traditional all-monitor-all strategy adopted by
most existing failure detectors.


  According to a result due to B.T. Polyak, a mapping between Hilbert spaces,
which is $C^{1,1}$ around a regular point, carries a ball centered at that
point to a convex set, provided that the radius of the ball is small enough.
The present paper considers the extension of such result to mappings defined on
a certain subclass of uniformly convex Banach spaces. This enables one to
extend to such setting a variational principle for constrained optimization
problems, already observed in finite dimension, that establishes a convex
behaviour for proper localizations of them. Further variational consequences
are explored.


  In unimodular-like theories, the constants of nature are demoted from
pre-given parameters to phase space variables. Their canonical duals provide
physical time variables. We investigate how this interacts with an alternative
approach to varying constants, where they are replaced by dynamical scalar
fields. Specifically we investigate the Brans-Dicke theory of gravity and its
interaction with clocks dual to the cosmological constant, the Planck mass,
etc. We crucially distinguish between the different role of Newton's G in this
process, leading to the possibility of local Lorentz invariance violation. A
large number of possible theories emerge, for example where the Brans-Dicke
coupling, omega, depends on unimodular-like times (in a generalization of
scalar-tensor theories), or even become the dual variable to unimodular-like
clocks ticking variations in other demoted constants, such as the cosmological
constant. We scan the space of possible theories and select those most
interesting regarding the joint variations of the Brans-Dicke omega and other
parameters, (such as the cosmological constant); and also regarding their
energy conservation violation properties. This ground work is meant to provide
the formalism for further developments, namely regarding cosmology, black holes
and the cosmological constant problem.


  The author seeks to develop a model to alter the bid-offer spread, currently
quoted by market makers, that varies with the market and trading conditions.
The dynamic nature of financial markets and trading, as with the rest of social
sciences, where changes can be observed and decisions can be made by
participants to influence the system, means that this model has to be adaptive
and include a feedback loop that alters the bid-offer adjustment based on the
modifications observed in the market and trading conditions, without a
significant time delay.
  The factors used to adjust the spread are price volatility, which is publicly
observable, and trade count and volume, which are generally known only to the
market maker, in various instruments over different historical durations in
time. The contributions of each factor to the bid-offer adjustment are computed
separately and then consolidated to produce a very adaptive bid-offer
quotation. The author uses the currency markets to build the sample model
because they are extremely liquid and trading in them is not as transparent as
other financial instruments, such as equities. Simulating the number of trades
and the average size of trades from a lognormal distribution, the parameters of
the lognormal distributions are chosen such that the total volume in a certain
interval matches the volume publicly mentioned by currency trading firms. This
methodology can easily be extended to other financial instruments and possibly
to any product with the ability to make electronic price quotations, or can
even be used to periodically perform manual price updates on products that are
traded non-electronically.


  The Phasor measurement unit (PMU) measurements are mandatory to monitor the
power system's voltage stability margin in an online manner. Monitoring is key
to the secure operation of the grid. Traditionally, online monitoring of
voltage stability using synchrophasors required a centralized communication
architecture, which leads to high investment cost and cyber-security concerns.
The increasing importance of cyber-security and low investment cost have
recently led to the development of distributed algorithms for online monitoring
of the grid that are inherently less prone to malicious attacks. In this work,
a novel distributed non-iterative voltage stability index (VSI) is proposed by
recasting the power flow equations as circles. The online computations of VSI
are simultaneously performed by the processors embedded at each bus in the
smart grid with the help of PMUs and communication of voltage phasors between
neighboring buses. The distributed nature of the index enables the real-time
identification of the critical bus of the system with minimal communication
infrastructure. The effectiveness of the proposed distributed index is
demonstrated on IEEE test systems and contrasted with existing methods to show
the benefits of the proposed method in speed, interpretability, identification
of outage location, and low sensitivity to noisy measurements.


  Neural Architecture Search (NAS) has become a widely used tool for automating
neural network design. While one-shot NAS methods have successfully reduced
computational requirements, they often require extensive training. On the other
hand, zero-shot NAS utilizes training-free proxies to evaluate a candidate
architecture's test performance but has two limitations: (1) inability to use
the information gained as a network improves with training and (2) unreliable
performance, particularly in complex domains like RecSys, due to the
multi-modal data inputs and complex architecture configurations. To synthesize
the benefits of both methods, we introduce a "sub-one-shot" paradigm that
serves as a bridge between zero-shot and one-shot NAS. In sub-one-shot NAS, the
supernet is trained using only a small subset of the training data, a phase we
refer to as "warm-up." Within this framework, we present SiGeo, a proxy founded
on a novel theoretical framework that connects the supernet warm-up with the
efficacy of the proxy. Extensive experiments have shown that SiGeo, with the
benefit of warm-up, consistently outperforms state-of-the-art NAS proxies on
various established NAS benchmarks. When a supernet is warmed up, it can
achieve comparable performance to weight-sharing one-shot NAS methods, but with
a significant reduction ($\sim 60$\%) in computational costs.


  Mapping blood microflows of the whole brain is crucial for early diagnosis of
cerebral diseases. Ultrasound localization microscopy (ULM) was recently
applied to map and quantify blood microflows in 2D in the brain of adult
patients down to the micron scale. Whole brain 3D clinical ULM remains
challenging due to the transcranial energy loss which significantly reduces the
imaging sensitivity. Large aperture probes with a large surface can increase
both resolution and sensitivity. However, a large active surface implies
thousands of acoustic elements, with limited clinical translation. In this
study, we investigate via simulations a new high-sensitive 3D imaging approach
based on large diverging elements, combined with an adapted beamforming with
corrected delay laws, to increase sensitivity. First, pressure fields from
single elements with different sizes and shapes were simulated. High
directivity was measured for curved element while maintaining high transmit
pressure. Matrix arrays of 256 elements with a dimension of 10x10 cm with small
( $\lambda$ /2), large (4 $\lambda$ ), and curved elements (4 $\lambda$ ) were
compared through point spread functions analysis. A large synthetic microvessel
phantom filled with 100 microbubbles per frame was imaged using the matrix
arrays in a transcranial configuration. 93% of the bubbles were detected with
the proposed approach demonstrating that the multi-lens diffracting layer has a
strong potential to enable 3D ULM over a large field of view through the bones.


  On September 21, 2006, an intense (~10^39 erg/s) and short (20 ms) burst was
detected by Swift BAT at a position consistent with that of the candidate
Anomalous X-ray Pulsar, CXOU J164710.2-455216, discovered by Chandra in 2005.
Swift follow-up observations began about 13 hours after the event and found the
source at a 1-10keV flux level of about 4.5 x 10^-11 erg/s/cm^2, i.e. ~300
times brighter than measured 5 days earlier by XMM. We report the results
obtained from Swift BAT observations of the burst and subsequent Swift XRT
observations carried out during the first four months after the burst. These
data are complemented with those from two XMM observations (carried out just
before and after the BAT event) and four archival Chandra observations carried
out between 2005 and 2007. We find a phase coherent solution for the source
pulsations after the burst. The evolution of the pulse phase comprises an
exponential component decaying with timescale of 1.4d which we interpret as the
recovery stage following a large glitch (Delta nu / nu about 6 x 10^-5). We
also detect a quadratic component corresponding to a spin-down rate of Pdot ~ 9
x 10^-13, implying a magnetic field strength of 10^14 Gauss.
  During the first Swift XRT observation taken 0.6 days after the burst, the
spectrum showed a kT = 0.65keV blackbody (R_BB = 1.5km) plus a Gamma=2.3
power-law accounting for about 60% of the 1-10 keV observed flux. Analysis of
Chandra archival data, taken during 2005 when the source was in quiescence,
reveal that the modulation in quiescence is 100% pulsed at energies above 4 keV
and consistent with the (unusually small-sized) blackbody component being
occulted by the neutron star as it rotates.


  The second-order nonlinear optical susceptibility $\Pi^{(2)}$ for second
harmonic generation is calculated for gapped graphene. The linear and
second-order nonlinear plasmon excitations are investigated in context of
second harmonic generation (SHG). We report a red shift and an order of
magnitude enhancement of the SHG resonance with growing gap, or alternatively,
reduced electro-chemical potential.


  We investigate the stability of a uniform elliptical vortex in a
two-dimensional incompressible Euler fluid. It's demonstrated that for small
eccentricities, the vortex relaxes to a core-halo structure that undergoes
rigid rotation with the central core remaining elliptical. For large
eccentricities, the vortex splits into two quasi-circular vortices that revolve
around the center of mass. Independent of the aspect ratio, the steady-state
displays a low-density halo. We present a theory that qualitatively explains
the transition between the two states. All theoretical results are compared
with extensive molecular dynamics simulations based on the vortex-in-cell
algorithm.


  Surface photovoltage (SPV) spectroscopy, which is a versatile method to
analyze the energetic distribution of electronic defect states at surfaces and
interfaces of wide-bandgap semiconductor (hetero-)structures, is applied to
comparatively investigate heterostructures made of 5-unit-cell-thick LaAlO$_3$
films grown either on TiO$_2$- or on SrO-terminated SrTiO$_3$. As shown in a
number of experimental and theoretical investigations in the past, these two
interfaces exhibit dramatically different properties with the first being
conducting and the second insulating.
  Our present SPV investigation reveals clearly distinguishable interface
defect state distributions for both configurations when interpreted within the
framework of a classical semiconductor band scheme. Furthermore, bare SrTiO$_3$
crystals with TiO$_2$ or mixed SrO/TiO$_2$ terminations show similar SPV
spectra and transients as do LaAlO$_3$-covered samples with the respective
termination of the SrTiO$_3$ substrate. This is in accordance with a number of
recent works that stress the decisive role of SrTiO$_3$ and the minor role of
LaAlO$_3$ with respect to the electronic interface properties.


  We study the topology of the punctured disc defined over a non-archimedean
field of characteristic zero. Chapter two includes a new proof of the so-called
p-adic Riemann existence theorem. This release completes the study of breaks
and break decompositions of the monodromy representation of a sheaf around the
origin of the punctured disc.


  We measure the cross section of $e^+e^-\rightarrow\eta_c J/\psi$ at the
$\Upsilon(nS) (n=1$ -- $5)$ on-resonance and 10.52 GeV off-resonance energy
points using the full data sample collected by the Belle detector with an
integrated luminosity of $955~\rm fb^{-1}$. We also search for double
charmonium production in $e^+e^-\rightarrow\eta_c J/\psi$ via initial state
radiation near the $\eta_c J/\psi$ threshold. No evident signal of the double
charmonium state is found, but evidence for the $e^+e^-\rightarrow\eta_c
J/\psi$ process is found with a statistical significance greater than
$3.3\sigma$ near the $\eta_c J/\psi$ threshold. The average cross section near
the threshold is measured and upper limits of cross sections are set for other
regions.


  We introduce a method to define $C^*$-algebras from $C^*$-correspondences.
Our construction generalizes Cuntz-Pimsner algebras, crossed products by
Hilbert $C^*$-modules, and graph algebras.


  Intrinsic microphysical irreversibility is the time asymmetry observed in
exponentially decaying states. It is described by the semigroup generated by
the Hamiltonian $\QTR{it}{H}$ of the quantum physical system, not by the
semigroup generated by a Liouvillian $\QTR{it}{L}$ which describes the
irreversibility due to the influence of an external reservoir or measurement
apparatus. The semigroup time evolution generated by $\QTR{it}{H}$ is
impossible in the Hilbert Space (HS) theory, which allows only time symmetric
boundary conditions and an unitary group time evolution. This leads to problems
with decay probabilities in the HS theory. To overcome these and other problems
(non-existence of Dirac kets) caused by the Lebesgue integrals of the HS, one
extends the HS to a Gel'fand triplet, which contains not only Dirac kets, but
also generalized eigenvectors of the self-adjoint $\QTR{it}{H}$ with complex
eigenvalues ($E_R-i\Gamma /2$) and a Breit-Wigner energy distribution. These
Gamow states $\psi ^G$ have a time asymmetric exponential evolution. One can
derive the decay probability of the Gamow state into the decay products
described by $\Lambda $ from the basic formula of quantum mechanics
$\QTR{cal}{P}(t)=Tr(|\psi ^G> < \psi ^G|\Lambda)$, which in HS quantum
mechanics is identically zero. From this result one derives the decay rate
$\QTR{group}{\dot c}(t)$ and all the standard relations between
$\QTR{group}{\dot c}(0)$, $\Gamma $ and the lifetime $\tau_R$ used in the
phenomenology of resonance scattering and decay. In the Born approximation one
obtains Dirac's Golden Rule.


  Quantum chemistry methods exploiting density-functional approximations for
short-range electron-electron interactions and second-order M{{\o}}ller-Plesset
(MP2) perturbation theory for long-range electron-electron interactions have
been implemented for periodic systems using Gaussian-type basis functions and
the local correlation framework. The performance of these range-separated
double hybrids has been benchmarked on a significant set of systems including
rare-gas, molecular, ionic, and covalent crystals. The use of
spin-component-scaled MP2 for the long-range part has been tested as well. The
results show that the value of $\mu$ = 0.5 bohr^{--1} for the range-separation
parameter usually used for molecular systems is also a reasonable choice for
solids. Overall, these range-separated double hybrids provide a good accuracy
for binding energies using basis sets of moderate sizes such as cc-pVDZ and
aug-cc-pVDZ.


  Experimental results, supported by precise modelling, demonstrate
optimisation of a plasma-based injector with intermediate laser pulse energy
($<1$ J), corresponding to a normalised vector potential $a_0 = 2.15$, using
ionisation injection in a tailored plasma density profile. An increase in
electron bunch quality and energy is achieved experimentally with the extension
of the density downramp at the plasma exit. Optimisation of the focal position
of the laser pulse in the tailored plasma density profile is shown to
efficiently reduce electron bunch angular deviation, leading to a better
alignment of the electron bunch with the laser axis. Single peak electron
spectra are produced in a previously unexplored regime by combining an early
focal position and adaptive optic control of the laser wavefront through
optimising the symmetry of the pre-focal laser energy distribution.
Experimental results have been validated through particle-in-cell simulations
using realistic laser energy, phase distribution, and temporal envelope,
allowing for accurate predictions of difficult to model parameters, such as
total charge and spatial properties of the electron bunches, opening the way
for more accurate modelling for the design of plasma-based accelerators.


  We describe solutions of the Klein-Gordon equation which are spherically
symmetric and localized, and may be regarded as massive particles without
charge or spin. The proposed model, which is based on the action for a complex
scalar field minimally coupled to the electromagnetic and gravitational fields,
contains no adjustable parameters and predicts five particle species with
masses of the order of the Planck mass. These particles appear to be candidates
for dark matter.


  Probes perform local measurements by interacting with the surrounding system.
This often occurs in a dilute system whose effective macroscopic dynamics are
diffusive. It is analytically shown here that, for dimensions two or less, the
relative uncertainty of any such measurement converges to an explicit universal
power law in the long-time limit. The dynamical exponent depends on the
dimension, and the prefactor depends solely on the bulk density and the
effective mass diffusivity. Simulations of four distinct microscopic models
support the results. The results imply that saturation of thermodynamic
uncertainty relations cannot be approached for local measurements.


  Based on maximally entangled states, we explore the constructions of mutually
unbiased bases in bipartite quantum systems. We present a new way to construct
mutually unbiased bases by difference matrices in the theory of combinatorial
designs. In particular, we establish $q$ mutually unbiased bases with $q-1$
maximally entangled bases and one product basis in $\mathbb{C}^q\otimes
\mathbb{C}^q$ for arbitrary prime power $q$. In addition, we construct
maximally entangled bases for dimension of composite numbers of non-prime
power, such as five maximally entangled bases in $\mathbb{C}^{12}\otimes
\mathbb{C}^{12}$ and $\mathbb{C}^{21}\otimes\mathbb{C}^{21}$, which improve the
known lower bounds for $d=3m$, with $(3,m)=1$ in $\mathbb{C}^{d}\otimes
\mathbb{C}^{d}$. Furthermore, we construct $p+1$ mutually unbiased bases with
$p$ maximally entangled bases and one product basis in $\mathbb{C}^p\otimes
\mathbb{C}^{p^2}$ for arbitrary prime number $p$.


  We present evidence for a highly obscured X-ray source in one of two giant
Ly-alpha emission nebulae in the z=3.09 proto-cluster region SSA22. Neither
Ly-alpha nebula is associated with significant radio emission. While one has a
significant submillimeter detection and is undetected in the X-ray, the other
is a factor of 2-10 times less submillimeter bright and appears to contain a
hard-band X-ray source. We discuss our analysis and techniques for assessing
the X-ray properties of this source and suggest that we have detected an
embedded AGN source in one of these nebulae which may be at least partially
responsible for exciting the Ly-alpha emission through a mechanism that is
essentially decoupled from the radio, submillimeter, or optical luminosities.
We also present an upper limit on the mean X-ray emission from 10 other
extended Ly-alpha objects in the SSA22 region.


  We report the first operation of a rotating odd-parity Lorentz Invariance
test in electrodynamics using a microwave Mach-Zehnder interferometer with
permeable material in one arm. The experiment sets a direct bound to $
\kappa_{tr}$ of $-0.3\pm 3\times10^{-7}$. Using new power recycled waveguide
interferometer techniques (with the highest spectral resolution ever achieved
of $2\times10^{-11} rad/\sqrt{Hz}$) we show an improvement of several orders of
magnitude is attainable in the future.


  Estimating Click-Through Rate (CTR) is a vital yet challenging task in
personalized product search. However, existing CTR methods still struggle in
the product search settings due to the following three challenges including how
to more effectively extract users' short-term interests with respect to
multiple aspects, how to extract and fuse users' long-term interest with
short-term interests, how to address the entangling characteristic of long and
short-term interests. To resolve these challenges, in this paper, we propose a
new approach named Hierarchical Interests Fusing Network (HIFN), which consists
of four basic modules namely Short-term Interests Extractor (SIE), Long-term
Interests Extractor (LIE), Interests Fusion Module (IFM) and Interests
Disentanglement Module (IDM). Specifically, SIE is proposed to extract user's
short-term interests by integrating three fundamental interests encoders within
it namely query-dependent, target-dependent and causal-dependent interest
encoder, respectively, followed by delivering the resultant representation to
the module LIE, where it can effectively capture user long-term interests by
devising an attention mechanism with respect to the short-term interests from
SIE module. In IFM, the achieved long and short-term interests are further
fused in an adaptive manner, followed by concatenating it with original raw
context features for the final prediction result. Last but not least,
considering the entangling characteristic of long and short-term interests, IDM
further devises a self-supervised framework to disentangle long and short-term
interests. Extensive offline and online evaluations on a real-world e-commerce
platform demonstrate the superiority of HIFN over state-of-the-art methods.


  Deep learning has made significant applications in the field of data science
and natural science. Some studies have linked deep neural networks to dynamic
systems, but the network structure is restricted to the residual network. It is
known that residual networks can be regarded as a numerical discretization of
dynamic systems. In this paper, we back to the classical network structure and
prove that the vanilla feedforward networks could also be a numerical
discretization of dynamic systems, where the width of the network is equal to
the dimension of the input and output. Our proof is based on the properties of
the leaky-ReLU function and the numerical technique of splitting method to
solve differential equations. Our results could provide a new perspective for
understanding the approximation properties of feedforward neural networks.


  We discuss models that attempt to provide an explanation for the violation of
Bell inequalities at a distance in terms of hidden influences. These models
reproduce the quantum correlations in most situations, but are restricted to
produce local correlations in some configurations. The argument presented in
[Bancal et al. Nature Physics 8, 867 (2012)] applies to all of these models,
which can thus be proved to allow for faster-than-light communication. In other
words, the signalling character of these models cannot remain hidden.


  This note summarizes a pedagogical tutorial on CalcHEP and PYTHIA that was
given at TASI 2011 program.


  Coded caching scheme provides us an effective framework to realize additional
coded multicasting gain by exploiting coding into multiple transmitted signals.
The goal of coded caching design is to jointly optimize the placement and
delivery scheme so as to minimize the amount of transmitted coded signals.
However, few research efforts consider multiple-round coded caching design
problem, in which fixed and mobile users may coexist in one network different
number of active users present in successive rounds. Obviously, such dynamic
network configurations may lead to undesired frequent placement caching content
updating at user sides, if we assume coded caching scheme for each round
separately. Thus how to tailor the coded caching design, such that the frequent
caching content updating in the placement phase can be avoided, and
simultaneously retaining full caching gain in delivery phase in multiple rounds
will become highly desirable. In this paper, by carefully examining the
bipartite graph representation of the coded caching scheme, a dynamic
centralized coded caching design is proposed on the basis of the
concatenating-based placement and the saturating matching based delivery
scheme. Our analysis unveils that, the proposed dynamic coded caching scheme
can realize the flexible coded multicast, and is order optimal.


  Let B_n be the braid group on n strands, with n at least 4, and let Mod(S) be
the extended mapping class group of the sphere with n+1 punctures. We show that
the abstract commensurator of B_n is isomorphic to a semidirect product of
Mod(S) with a group we refer to as the transvection subgroup, Tv(B_n). We also
show that Tv(B_n) is itself isomorphic to a semidirect product of an infinite
dimensional rational vector space with the multiplicative group of nonzero
rational numbers.