  The free expansion of a Gaussian wavepacket is a problem commonly discussed
in undergraduate quantum classes by directly solving the time-dependent
Schrodinger equation as a differential equation. In this work, we provide an
alternative way to calculate the free expansion by recognizing that the
Gaussian wavepacket can be thought of as the ground state of a harmonic
oscillator with its frequency adjusted to give the initial width of the
Gaussian, and the time evolution, given by the free-particle Hamiltonian, being
the same as the application of a time-dependent squeezing operator to the
harmonic oscillator ground state. Operator manipulations alone (including the
Hadamard lemma and the exponential disentangling identity) then allow us to
directly solve the problem. As quantum instruction evolves to include more
quantum information science applications, reworking this well known problem
using a squeezing formalism will help students develop intuition for how
squeezed states are used in quantum sensing.


  Drug overdose is a pressing public health concern in the United States,
resulting in a significant number of fatalities each year. In this study, we
employ the Journey to Crime (JTC) framework borrowed from the field of
environmental criminology to examine the association between drug sales
locations and overdose death locations. In this research, our objective is to
elucidate the trajectory of overdose victims to overdose locations, aiming to
enhance the distribution of overdose services and interventions. To the best of
our knowledge, no previous studies have applied the JTC framework to
investigate drug overdose deaths. By scrutinizing data obtained from the
Hamilton County, OH Coroners, and the Cincinnati Police Department, we endeavor
to explore the plausible correlation between overdose deaths and drug sales
locations. Our findings underscore the necessity of implementing a
comprehensive strategy to curtail overdose deaths. This strategy should
encompass various facets, including targeted efforts to reduce the
accessibility of illicit drugs, the enhancement of responses to overdose
incidents through a collaborative multidisciplinary approach, and the
availability of data to inform evidence-based strategies and facilitate outcome
evaluation. By shedding light on the relationship between drug sales locations
and overdose death locations through the utilization of the JTC framework, this
study contributes valuable insights to the field of drug overdose prevention.
It emphasizes the significance of adopting multifaceted approaches to address
this public health crisis effectively. Ultimately, our research aims to inform
the development of evidence-based interventions and policies that can mitigate
the occurrence and impact of drug overdoses in our communities.


  It is well known that a particle in a periodic potential with an additional
constant force performs Bloch oscillations. Modulating every second period of
the potential, the original Bloch band splits into two subbands. The dynamics
of quantum particles shows a coherent superposition of Bloch oscillations and
Zener tunneling between the subbands, a Bloch-Zener oscillation. Such a system
is modelled by a tight-binding Hamiltonian, a system of two minibands with an
easily controllable gap. The dynamics of the system is investigated by using an
algebraic ansatz leading to a differential equation of Whittaker-Hill type. It
is shown that the parameters of the system can be tuned to generate a periodic
reconstruction of the wave packet and thus of the occupation probability. As an
application, the construction of a matter wave beam splitter and a Mach-Zehnder
interferometer is briefly discussed.


  We present a theoretical and computational framework to compute the symmetry
number of a flexible sphere cluster in $\mathbb{R}^3$, using a definition of
symmetry that arises naturally when calculating the equilibrium probability of
a cluster of spheres in the sticky-sphere limit. We define the sticky symmetry
group of the cluster as the set of permutations and inversions of the spheres
which preserve adjacency and can be realized by continuous deformations of the
cluster that do not change the set of contacts or cause particles to overlap.
The symmetry number is the size of the sticky symmetry group. We introduce a
numerical algorithm to compute the sticky symmetry group and symmetry number,
and show it works well on several test cases. Furthermore we show that once the
sticky symmetry group has been calculated for indistinguishable spheres, the
symmetry group for partially distinguishable spheres (those with non-identical
interactions) can be efficiently obtained without repeating the laborious parts
of the computations. We use our algorithm to calculate the partition functions
of every possible connected cluster of 6 identical sticky spheres, generating
data that may be used to design interactions between spheres so they
self-assemble into a desired structure.


  We analyze monotone difference schemes for strongly degenerate
convection-diffusion equations in one spatial dimension. These nonlinear
equations are well-posed within a class of (discontinuous) entropy solutions.
We prove that the L1 difference between the approximate solutions and the
unique entropy solution is bounded above by a constant times the cube root of
the spatial discretization parameter.


  Urban environments manifest a high level of complexity, and therefore it is
of vital importance for safety systems embedded within autonomous vehicles
(AVs) to be able to accurately predict the short-term future motion of nearby
agents. This problem can be further understood as generating a sequence of
future coordinates for a given agent based on its past motion data e.g.
position, velocity, acceleration etc, and whilst current approaches demonstrate
plausible results they have a propensity to neglect a scene's physical
constrains. In this paper we propose the model based on a combination of the
CNN and LSTM encoder-decoder architecture that learns to extract a relevant
road features from semantic maps as well as general motion of agents and uses
this learned representation to predict their short-term future trajectories. We
train and validate the model on the publicly available dataset that provides
data from urban areas, allowing us to examine it in challenging and uncertain
scenarios. We show that our model is not only capable of anticipating future
motion whilst taking into consideration road boundaries, but can also
effectively and precisely predict trajectories for a longer time horizon than
initially trained for.


  We prove dynamical local limits for the singular numbers of $p$-adic random
matrix products at both the bulk and edge. The limit object which we construct,
the reflecting Poisson sea, may thus be viewed as a $p$-adic analogue of line
ensembles appearing in classical random matrix theory. However, in contrast to
those it is a discrete space Poisson-type particle system with only local
reflection interactions and no obvious determinantal structure. The limits hold
for any $\mathrm{GL}_n(\mathbb{Z}_p)$-invariant matrix distributions under weak
universality hypotheses, with no spatial rescaling.


  Chiral superconductors are a novel class of unconventional superconductors
that host topologically protected chiral Majorana fermions at interfaces and
domain walls, elusive quasiparticles that could serve as a platform for
topological quantum computing. Here we show that, in analogy to a qubit, the
out-of-equilibrium superconducting state in such materials can be described by
a Bloch vector and controlled on ultrafast time scales. The all-optical control
mechanism is universal, permitting arbitrary rotations of the order parameter,
and can induce a dynamical change of handedness of the condensate. It relies on
transient breaking of crystal symmetries via choice of pulse polarization to
enable arbitrary rotations of the Bloch vector. The mechanism extends to
ultrafast time scales, and importantly the engineered state persists after the
pump is switched off. We demonstrate that these phenomena should appear in
graphene or magic-angle twisted bilayer graphene (TBG), as well as
Sr$_2$RuO$_4$, as candidate chiral $d+id$ and $p+ip$ superconductors,
respectively. Furthermore, we show that chiral superconductivity can be
detected in time-resolved pump-probe measurements. This paves the way towards a
robust mechanism for ultrafast control and measurement of chirally-ordered
phases and Majorana modes.


  Feature transformation aims to reconstruct the feature space of raw features
to enhance the performance of downstream models. However, the exponential
growth in the combinations of features and operations poses a challenge, making
it difficult for existing methods to efficiently explore a wide space.
Additionally, their optimization is solely driven by the accuracy of downstream
models in specific domains, neglecting the acquisition of general feature
knowledge. To fill this research gap, we propose an evolutionary LLM framework
for automated feature transformation. This framework consists of two parts: 1)
constructing a multi-population database through an RL data collector while
utilizing evolutionary algorithm strategies for database maintenance, and 2)
utilizing the ability of Large Language Model (LLM) in sequence understanding,
we employ few-shot prompts to guide LLM in generating superior samples based on
feature transformation sequence distinction. Leveraging the multi-population
database initially provides a wide search scope to discover excellent
populations. Through culling and evolution, the high-quality populations are
afforded greater opportunities, thereby furthering the pursuit of optimal
individuals. Through the integration of LLMs with evolutionary algorithms, we
achieve efficient exploration within a vast space, while harnessing feature
knowledge to propel optimization, thus realizing a more adaptable search
paradigm. Finally, we empirically demonstrate the effectiveness and generality
of our proposed method.


  We report controlled ignition of magnetization reversal avalanches by surface
acoustic waves in a single crystal of Mn12 acetate. Our data show that the
speed of the avalanche exhibits maxima on the magnetic field at the tunneling
resonances of Mn12. Combined with the evidence of magnetic deflagration in Mn12
acetate (Suzuki et al., cond-mat/0506569) this suggests a novel physical
phenomenon: deflagration assisted by quantum tunneling.


  Transverse momentum spectra of charged particles are measured by the CMS
experiment at the CERN LHC in pPb collisions at sqrt(s[NN]) = 5.02 TeV, in the
range 0.4 < pt < 120 GeV and pseudorapidity abs(eta[CM]) < 1.8 in the
proton-nucleon center-of-mass frame. For pt < 10 GeV, the charged-particle
production is asymmetric about eta[CM] = 0, with smaller yield observed in the
direction of the proton beam, qualitatively consistent with expectations from
shadowing in nuclear parton distribution functions (nPDF). A pp reference
spectrum at sqrt(s) = 5.02 TeV is obtained by interpolation from previous
measurements at higher and lower center-of-mass energies. The pt distribution
measured in pPb collisions shows an enhancement of charged particles with pt >
20 GeV compared to expectations from the pp reference. The enhancement is
larger than predicted by perturbative quantum chromodynamics calculations that
include antishadowing modifications of nPDFs.


  We give a lower bound for the non-collision probability up to a long time T
in a system of n independent random walks with fixed obstacles on the
two-dimensional lattice. By `collision' we mean collision between the random
walks as well as collision with the fixed obstacles. We give an analogous
result for Brownian particles on the plane. We also explain how this result can
be used to describe in terms of "quasi random walks" a diluted gas evolving
under Kawasaki dynamics or simple exclusion.


  We investigated a suspended bilayer graphene where the bottom (top) layer is
doped by boron (nitrogen) substitutional atoms by using Density Functional
Theory (DFT) calculations. We found that at high dopant concentration (one B-N
pair every 32 C atoms) the electronic structure of the bilayer does not depend
on the B-N distance but on the relative occupation of the bilayer graphene
sub-lattices by B and N. We found that a large built in electric field is
established between layers, giving rise to an energy gap. We further
investigated the transport properties and found that intra-layer electron
current is weakly influenced by the presence of these dopants while the
inter-layer current is significantly enhanced for biases allowing the energy
alignment of N and B states. This effect leads to current rectification in
asymmetric junctions.


  Dust emission, an important diagnostic of star formation and ISM mass
throughout the Universe, can be powered by sources unrelated to ongoing star
formation. In the framework of the DustPedia project we have set out to
disentangle the radiation of the ongoing star formation from that of the older
stellar populations. This is done through detailed, 3D radiative transfer
simulations of face-on spiral galaxies. In this particular study, we focus on
NGC 1068, which contains an active galactic nucleus (AGN). The effect of
diffuse dust heating by AGN (beyond the torus) was so far only investigated for
quasars. This additional dust heating source further contaminates the broadband
fluxes on which classic galaxy modelling tools rely to derive physical
properties. We aim to fit a realistic model to the observations of NGC 1068 and
quantify the contribution of the several dust heating sources. Our model is
able to reproduce the global spectral energy distribution of the galaxy. It
matches the resolved optical and infrared images fairly well, but deviates in
the UV and the submm. We find a strong wavelength dependency of AGN
contamination to the broadband fluxes. It peaks in the MIR, drops in the FIR,
but rises again at submm wavelengths. We quantify the contribution of the dust
heating sources in each 3D dust cell and find a median value of 83% for the
star formation component. The AGN contribution is measurable at the percentage
level in the disc, but quickly increases in the inner few 100 pc, peaking above
90%. This is the first time the phenomenon of an AGN heating the diffuse dust
beyond its torus is quantified in a nearby star-forming galaxy. NGC 1068 only
contains a weak AGN, meaning this effect can be stronger in galaxies with a
more luminous AGN. This could significantly impact the derived star formation
rates and ISM masses for such systems.


  In this paper we show existence of solutions for some elliptic problems with
nonlocal diffusion by means of nonvariational tools. Our proof is based on the
use of topological degree, which requires a priori bounds for the solutions. We
obtain the a priori bounds by adapting the classical scaling method of Gidas
and Spruck. We also deal with problems involving gradient terms.


  Motivated by rate-independent stress-strain hysteresis observed in filled
rubber, this article considers a scalar viscoelastic model in which the
constitutive law is random and varies on a lengthscale which is small relative
to the overall size of the solid. Using stochastic two-scale convergence as
introduced by Bourgeat, Mikelic and Wright, we obtain the homogenized limit of
the evolution, and demonstrate that under certain hypotheses, the homogenized
model exhibits hysteretic behaviour which persists under asymptotically slow
loading. These results are illustrated by means of numerical simulations in a
particular one-dimensional instance of the model.


  Ginzburg-Landau (GL) equations for the coexistent states of superconductivity
and magnetism are derived microscopically from the extended Hubbard model with
on-site repulsive and nearest-neighbor attractive interactions. In the derived
GL free energy a cubic term that couples the spin-singlet and spin-triplet
components of superconducting order parameters (SCOP) with magnetization
exists. This term gives rise to a spin-triplet SCOP near the interface between
a spin-singlet superconductor and a ferromagnet, consistent with previous
theoretical studies based on the Bogoliubov de Gennes method and the
quasiclassical Green's function theory. In coexistent states of singlet
superconductivity and antiferromagnetism it leads to the occurrence of
pi-triplet SCOPs.


  The coexistence of an abnormal rhythm and a normal steady state is often
observed in nature (e.g., epilepsy). Such a system is modeled as a bistable
oscillator that possesses both a limit cycle and a fixed point. Although
bistable oscillators under several perturbations have been addressed in the
literature, the mechanism of oscillation quenching, a transition from a limit
cycle to a fixed point, has not been fully understood. In this study, we
analyze quenching using the extended Stuart-Landau oscillator driven by
periodic forces. Numerical simulations suggest that the entrainment to the
periodic force induces the amplitude change of a limit cycle. By reducing the
system with an averaging method, we investigate the bifurcation structures of
the periodically-driven oscillator. We find that oscillation quenching occurs
by the homoclinic bifurcation when we use a periodic force combined with
quadratic feedback. In conclusion, we develop a state-transition method in a
bistable oscillator using periodic forces, which would have the potential for
practical applications in controlling and annihilating abnormal oscillations.
Moreover, we clarify the rich and diverse bifurcation structures behind
periodically-driven bistable oscillators, which we believe would contribute to
further understanding the complex behaviors in non-autonomous systems.


  The multiplicities of light (anti)nuclei were measured recently by the ALICE
collaboration in Pb+Pb collisions at the center-of-mass collision energy
$\sqrt{s_{NN}} =2.76$ TeV. Surprisingly, the hadron resonance gas model is able
to perfectly describe their multiplicities under various assumptions. For
instance, one can consider the (anti)nuclei with a vanishing hard-core radius
(as the point-like particles) or with the hard-core radius of proton, but the
fit quality is the same for these assumptions. In this paper we assume the
hard-core radius of nuclei consisting of $A$ baryons or antibaryons to follow
the simple law $R(A) = R_b (A)^\frac{1}{3}$, where $R_b$ is the hard-core
radius of nucleon. To implement such a relation into the hadron resonance gas
model we employ the induced surface tension concept and analyze the hadronic
and (anti)nuclei multiplicities measured by the ALICE collaboration. The hadron
resonance gas model with the induced surface tension allows us to verify
different scenarios of chemical freeze-out of (anti)nuclei. It is shown that
the most successful description of hadrons can be achieved at the chemical
freeze-out temperature $T_h=150$ MeV, while the one for all (anti)nuclei is
$T_A=168.5$ MeV. Possible explanations of this high temperature of (anti)nuclei
chemical freeze-out are discussed.


  Two simple kinetic models of Quantum Size Effect-directed nanocluster
self-assembly in circular atomic corrals are discussed. The models correspond
to an adsorption (either a physisorption or a chemisorption) and an
adsorption-diffusion regimes that are typical at low and high temperatures,
respectively. Small magnitudes of a variation of the electronic local density
of states is shown to be the prime factor that impedes self-assembly in the
latter regime.


  Many nonlinear partial differential equations (PDEs) display a coarsening
dynamics, i.e., an emerging pattern whose typical length scale $L$ increases
with time. The so-called coarsening exponent $n$ characterizes the time
dependence of the scale of the pattern, $L(t)\approx t^n$, and coarsening
dynamics can be described by a diffusion equation for the phase of the pattern.
By means of a multiscale analysis we are able to find the analytical expression
of such diffusion equations. Here, we propose a recipe to implement numerically
the determination of $D(\lambda)$, the phase diffusion coefficient, as a
function of the wavelength $\lambda$ of the base steady state $u_0(x)$. $D$
carries all information about coarsening dynamics and, through the relation
$|D(L)| \simeq L^2 /t$, it allows us to determine the coarsening exponent. The
main conceptual message is that the coarsening exponent is determined without
solving a time-dependent equation, but only by inspecting the periodic
steady-state solutions. This provides a much faster strategy than a forward
time-dependent calculation. We discuss our method for several different PDEs,
both conserved and not conserved.


  The flexibility of multi-terminal AC-DC-AC converters connected in
distribution networks can be increased by changing the sizes of the individual
AC-DC converter stages and connecting the AC side of those converters to
electromechanical switches (multiplexers) to allow reconfiguration within the
network. The combinations of real powers that can be transferred by such a
design can be described using a capability chart. In this work, it is proposed
that the area of these capability charts is a meaningful metric for describing
the flexibility of such a device. These capability chart areas are calculated
in closed form for a three-terminal AC-DC-AC device consisting of three AC-DC
converters of arbitrary sizes, allowing the optimal AC-DC converter sizing to
be determined to maximise this area. It is shown that this optimal design
yields a capability chart area that is 64% larger than the equivalent area from
a conventional equally-sized AC-DC-AC converter. Converters which are optimal
in other senses are discussed, such as a design with 10% increased per-feeder
real power transfer, albeit with an 8% area reduction. It is concluded that the
capability chart area is an intuitive and informative approach for describing
the increased flexibility of multiplexed AC-DC-AC converters.


  We present a case study of the tidal interaction between low mass,
star-forming, galaxies initially found exploring the Sloan Digital Sky Survey
(SDSS) images and further analyzed with SDSS spectroscopy and UV GALEX
photometry. With a luminosity of M$_{r}$ = $-$17.7 mag and exhibiting a
prominent tidal filament, UGC 6741 appears as a scale down version of massive
gas--rich interacting systems and mergers.The stellar disk of the smaller
companion, UGC 6741_B, which is three times less massive, has likely been
already destroyed. Both galaxies, which are connected by a 15 kpc long stellar
bridge, have a similar oxygen abundance of 12+log(O/H)$\sim$8.3. Several knots
of star-forming regions are identified along the bridge, some with masses
exceeding $\sim$10$^{7}$ M$_{\sun}$. The most compact of them, which are
unresolved, may evolve into globular clusters or Ultra Compact Dwarf galaxies
(UCDs). This would be the first time progenitors of such objects are detected
in mergers involving dwarf galaxies. UGC 6741 has currently the color and star
formation properties of Blue Compact Dwarf galaxies (BCDs). However the
analysis of its surface photometry suggests that the galaxy lies within the
scaling relations defined by early-type dwarf galaxies (dEs). Thus UGC 6741
appears as a promising system to study the possible transformation of BCDs into
dEs, through possibly a merger episode. The frequency of such dwarf-dwarf
mergers should now be explored.


  In spite of a few attempts in understanding the dynamical robustness of
complex networks, this extremely important subject of research is still in its
dawn as compared to the other dynamical processes on networks. We hereby
consider the concept of long-range interactions among the dynamical units of
complex networks and demonstrate for the first time that such a characteristic
can have noteworthy impacts on the dynamical robustness of networked systems,
regardless of the underlying network topology. We present a comprehensive
analysis of this phenomenon on top of diverse network architectures. Such
dynamical damages being able to substantially affect the network performance,
determining mechanisms that boost the robustness of networks becomes a
fundamental question. In this work, we put forward a prescription based upon
self-feedback that can efficiently resurrect global rhythmicity of complex
networks composed of active and inactive dynamical units, and thus can enhance
the network robustness. We have been able to delineate the whole proposition
analytically while dealing with all d-path adjacency matrices, having an
excellent agreement with the numerical results. For the numerical computations,
we examine scale-free networks, Watts-Strogatz small world model and also
Erd\"os-R\'enyi random network, along with Landau-Stuart oscillators for
casting the local dynamics.


  We describe the structure of the tensor product of the basic Fock
representation of sl(\infty) with its shifted dual. More precisely we prove
that this tensor product has a unique decreasing filtration with simple
quotients. We use the categorification of this representation via translation
functors in the abelain envelope of the Deligne category GL(t) for integral t.
We also compute dimensions of standard and tilting objects in this abelian
envelope.


  We introduce a simple autoencoder based on hyperbolic geometry for solving
standard collaborative filtering problem. In contrast to many modern deep
learning techniques, we build our solution using only a single hidden layer.
Remarkably, even with such a minimalistic approach, we not only outperform the
Euclidean counterpart but also achieve a competitive performance with respect
to the current state-of-the-art. We additionally explore the effects of space
curvature on the quality of hyperbolic models and propose an efficient
data-driven method for estimating its optimal value.


  The shift of density of Bose gas due to the mean field potential (MFP) and
the Casimir effect is systematically investigated in the $d$-dimensional
configuration space from the point of thermodynamic consideration. We show
that, for $d=3$, the shift of density arises completely due to the Casimir
effect and, the MFP remains totally ineffective regardless of the state,
condensate or non-condensate. But for dimension $d>3$ the MFP plays an active
role in shifting the density of Bose gas along with the Casimir interaction.
The sign of density shift becomes positive in the present case. So, the
corresponding critical temperature shift would be negative, because these two
shifts are related as $\Delta n_{c}$/$n_{c}$ $\approx$ -$\Delta T_{c}$/$T_{c}$.
It is important to note that, the MFP causes a shift of density for $d>3$ even
when the Casimir effect is not there, and the sign of shift becomes negative
then; consequently, the critical temperature shift would be positive with MFP
alone in this particular situation.


  We present a description of the new complex installation for the study of
extensive air showers which was created at the Tien Shan mountain cosmic ray
station, as well as the results of the test measurements made there in
2014-2016. At present, the system for registration of electromagnetic shower
component consists of $\sim$100 detector points built on the basis of plastic
scintillator plates with the sensitive area of 0.25m$^2$ and 1m$^2$, spread
equidistantly over $\sim$10$^4$m$^2$ space. The dynamic range of scintillation
amplitude measurements is currently about $(3-7)\cdot 10^4$, and there is a
prospect of it being extended up to $\sim$10$^6$. The direction of shower
arrival is defined by signal delays from a number of the scintillators placed
cross-wise at the periphery of the detector system. For the investigation of
nuclear active shower components there was created a multi-tier 55m$^2$
ionization-neutron calorimeter with a sum absorber thickness of
$\sim$1000g/cm$^2$, typical spatial resolution of the order of 10cm, and
dynamic range of ionization measurement channel about $\sim$10$^5$. Also, the
use of saturation-free neutron detectors is anticipated for registration of the
high- and low-energy hadron components in the region of shower core. A complex
of underground detectors is designed for the study of muonic and penetrative
nuclear-active components of the shower.
  The full stack of data acquisition, detector calibration, and shower
parameters restoration procedures are now completed, and the newly obtained
shower size spectrum and lateral distribution of shower particles occur in
agreement with conventional data. Future studies in the field of
$10^{14}-10^{17}$eV cosmic ray physics to be held at the new shower
installation are discussed.


  The projected entangled pair state (PEPS) ansatz can represent a thermal
state in a strongly correlated system. We introduce a novel variational
algorithm to optimize this tensor network. Since full tensor environment is
taken into account, then with increasing bond dimension the optimized PEPS
becomes the exact Gibbs state. Our presentation opens with a 1D version for a
matrix product state (MPS) and then generalizes to PEPS in 2D. Benchmark
results in the quantum Ising model are presented.


  This paper is devoted to the study of the stability of limit cycles of a
nonlinear delay differential equation with a distributed delay. The equation
arises from a model of population dynamics describing the evolution of a
pluripotent stem cells population. We study the local asymptotic stability of
the unique nontrivial equilibrium of the delay equation and we show that its
stability can be lost through a Hopf bifurcation. We then investigate the
stability of the limit cycles yielded by the bifurcation using the normal form
theory and the center manifold theorem. We illustrate our results with some
numerics.


  A trapped polariton condensate with continuous pumping and decay is analyzed
using a generalized Gross-Pitaevskii model. Whereas an equilibrium condensate
is characterized by a macroscopic occupation of a ground state, here the
steady-states take more general forms. Some are characterized by a large
population in an excited state, and others by large populations in several
states. In the latter case, the highly-populated states synchronize to a common
frequency above a critical density. Estimates for the critical density of this
synchronization transition are consistent with experiments.


  The LL(finite) parsing strategy for parsing of LL(k) grammars where k needs
not to be known is presented. The strategy parses input in linear time, uses
arbitrary but always minimal lookahead necessary to disambiguate between
alternatives of nonterminals, and it is optimal in the number of lookahead
terminal scans performed. Modifications to the algorithm are shown that allow
for resolution of grammar ambiguities by precedence -- effectively interpreting
the input as a parsing expression grammar -- as well as for the use of
predicates, and a proof of concept, the open-source parser generator Astir,
employs the LL(finite) strategy in the output it generates.


  The recent 3D Gaussian splatting (3D-GS) has shown remarkable rendering
fidelity and efficiency compared to NeRF-based neural scene representations.
While demonstrating the potential for real-time rendering, 3D-GS encounters
rendering bottlenecks in large scenes with complex details due to an excessive
number of Gaussian primitives located within the viewing frustum. This
limitation is particularly noticeable in zoom-out views and can lead to
inconsistent rendering speeds in scenes with varying details. Moreover, it
often struggles to capture the corresponding level of details at different
scales with its heuristic density control operation. Inspired by the
Level-of-Detail (LOD) techniques, we introduce Octree-GS, featuring an
LOD-structured 3D Gaussian approach supporting level-of-detail decomposition
for scene representation that contributes to the final rendering results. Our
model dynamically selects the appropriate level from the set of
multi-resolution anchor points, ensuring consistent rendering performance with
adaptive LOD adjustments while maintaining high-fidelity rendering results.


  Omnidirectional applications are immersive and highly interactive, which can
improve the efficiency of remote collaborative work among factory workers. The
transmission of omnidirectional video (OV) is the most important step in
implementing virtual remote collaboration. Compared with the ordinary video
transmission, OV transmission requires more bandwidth, which is still a huge
burden even under 5G networks. The tile-based scheme can reduce bandwidth
consumption. However, it neither accurately obtain the field of view(FOV) area,
nor difficult to support real-time OV streaming. In this paper, we propose an
edge-assisted viewport adaptive scheme (EVAS-OV) to reduce bandwidth
consumption during real-time OV transmission. First, EVAS-OV uses a Gated
Recurrent Unit(GRU) model to predict users' viewport. Then, users were divided
into multicast clusters thereby further reducing the consumption of computing
resources. EVAS-OV reprojects OV frames to accurately obtain users' FOV area
from pixel level and adopt a redundant strategy to reduce the impact of
viewport prediction errors. All computing tasks were offloaded to edge servers
to reduce the transmission delay and improve bandwidth utilization.
Experimental results show that EVAS-OV can save more than 60\% of bandwidth
compared with the non-viewport adaptive scheme. Compared to a two-layer scheme
with viewport adaptive, EVAS-OV still saves 30\% of bandwidth.


  Class-agnostic counting (CAC) aims to count objects of interest from a query
image given few exemplars. This task is typically addressed by extracting the
features of query image and exemplars respectively and then matching their
feature similarity, leading to an extract-then-match paradigm. In this work, we
show that CAC can be simplified in an extract-and-match manner, particularly
using a vision transformer (ViT) where feature extraction and similarity
matching are executed simultaneously within the self-attention. We reveal the
rationale of such simplification from a decoupled view of the self-attention.
The resulting model, termed CACViT, simplifies the CAC pipeline into a single
pretrained plain ViT. Further, to compensate the loss of the scale and the
order-of-magnitude information due to resizing and normalization in plain ViT,
we present two effective strategies for scale and magnitude embedding.
Extensive experiments on the FSC147 and the CARPK datasets show that CACViT
significantly outperforms state-of-the art CAC approaches in both effectiveness
(23.60% error reduction) and generalization, which suggests CACViT provides a
concise and strong baseline for CAC. Code will be available.


  We report on a search for artificial narrowband signals of 20 stars within
the restricted Earth Transit Zone as a part of the ten-year Breakthrough Listen
(BL) search for extraterrestrial intelligence. The restricted Earth Transit
Zone is the region of the sky from which an observer would see the Earth
transit the Sun with an impact parameter of less than 0.5. This region of the
sky is geometrically unique, providing a potential way for an extraterrestrial
intelligence to discover the Solar System. The targets were nearby (7-143 pc)
and the search covered an electromagnetic frequency range of 3.95-8.00 GHz. We
used the Robert C. Byrd Green Bank Telescope to perform these observations with
the standard BL data recorder. We searched these data for artificial narrowband
($\sim$Hz) signals with Doppler drift rates of $\pm 20$ Hz s$^{-1}$. We found
one set of potential candidate signals on the target HIP 109656 which was then
found to be consistent with known properties of anthropogenic radio frequency
interference. We find no evidence for radio technosignatures from
extraterrestrial intelligence in our observations. The observing campaign
achieved a minimum detectable flux which would have allowed detections of
emissions that were $10^{-3}$ to $0.88$ times as powerful as the signaling
capability of the Arecibo radar transmitter, for the nearest and furthest stars
respectively. We conclude that at least $8\%$ of the systems in the restricted
Earth Transit Zone within 150 pc do not possess the type of transmitters
searched in this survey. To our knowledge, this is the first targeted search
for extraterrestrial intelligence of the restricted Earth Transit Zone. All
data used in this paper are publicly available via the Breakthrough Listen
Public Data Archive (http://seti.berkeley.edu/bldr2).


  We use the Ginzburg-Landau theory near the transition temperature in order to
examine the behavior of an inhomogeneous superconductor in the presence of a
magnetic field. We find that a transition from type I to type II
superconductivity occurs. Furthermore we calculate the critical value of the
mismatch and estimate the contributions of the fluctuations of the condensate
and the higher order terms in the Ginzburg-Landau framework.


  Quantum information transfer necessary to reconcile black hole evaporation
with quantum mechanics, while approximately preserving regular near-horizon
geometry, can be simply parameterized in terms of couplings of the black hole
internal state to quantum fields of the black hole atmosphere. The necessity of
transferring sufficient information for unitarization sets the strengths of
these couplings. Such couplings via the stress tensor offer apparently
significant advantages, and behave like quantum fluctuations of the effective
metric near the horizon. At the requisite strength, these fluctuations, while
soft (low energy/momentum), have significant magnitude, and so can deflect
near-horizon geodesics that span distances of order the black hole radius.
Thus, the presence of such couplings can result in effects that could be
detected or constrained by observation: disruption of near-horizon accretion
flows, scintillation of light passing close to the black hole, and alteration
of gravitational wave emission from inspirals. These effects could in
particular distort features of Sgr A* expected to be observed, e.g., by the
Event Horizon Telescope, such as the black hole shadow and photon ring.


  Methanol lines observations of a sample of low mass Class 0 protostars are
presented. Using a 1D radiative transfer model, I show that several protostars
have large abundance jumps in the inner hot and dense region of envelopes,
probably because of thermal grain mantle evaporation. These abundances are
compared with a grain surface chemistry model.


  A gas of interacting fermions confined in a quasi one-dimensional geometry
shows a BEC to BCS crossover upon slowly driving its coupling constant through
a confinement-induced resonance. On one side of the crossover the fermions form
tightly-bound bosonic molecules behaving as a repulsive Bose gas, while on the
other they form Cooper pairs, whose size is much larger than the average
inter-particle distance. Here we consider the situation arising when the
coupling constant is varied suddenly from the BEC to the BCS value. Namely, we
study a BEC-to-BCS quench. By exploiting a suitable continuum limit of recently
discovered solvable quenches in the Hubbard model, we show that the local
stationary state reached at large times after the quench can be determined
exactly by means of the Quench Action approach. We provide an
experimentally-accessible characterisation of the stationary state by computing
local pair correlation function as well as the quasi-particle distribution
functions. We find that the steady state is increasingly dominated by two
particle spin singlet bound states for stronger interaction strength but that
bound state formation is inhibited at larger BEC density. The bound state
rapidity distribution displays quartic power law decay suggesting a violation
of Tan's contact relations.


  Within the framework of on-line learning, we study the generalization error
of an ensemble learning machine learning from a linear teacher perceptron. The
generalization error achieved by an ensemble of linear perceptrons having
homogeneous or inhomogeneous initial weight vectors is precisely calculated at
the thermodynamic limit of a large number of input elements and shows rich
behavior. Our main findings are as follows. For learning with homogeneous
initial weight vectors, the generalization error using an infinite number of
linear student perceptrons is equal to only half that of a single linear
perceptron, and converges with that of the infinite case with O(1/K) for a
finite number of K linear perceptrons. For learning with inhomogeneous initial
weight vectors, it is advantageous to use an approach of weighted averaging
over the output of the linear perceptrons, and we show the conditions under
which the optimal weights are constant during the learning process. The optimal
weights depend on only correlation of the initial weight vectors.


  For the Srzednicki-W\'ojcik equation, the planar nonautonomous ODE
parameterized by $\kappa \in \mathbb{R}$, $$ z'=\overline{z}(1+ |z|^2 \exp(i
\kappa t)), \qquad z(t) \in \mathbb{C} $$ using averaging we show how the
region of hyperbolicty grows with $|\kappa|$. Based on this we give bounds on
the sizes of bounded orbits.


  Using the spherically symmetric self-consistent Green's function method, we
consider thermodynamic properties of the $S=1/2$ $J_1$-$J_2$ Heisenberg model
on the 2D square lattice. We calculate the temperature dependence of the
spin-spin correlation functions $c_{\mathbf{r}}=\langle
S_{\mathbf{0}}^{z}S_{\mathbf{r}}^{z}\rangle $, the gaps in the spin excitation
spectrum, the energy $E$ and the heat capacity $C_{V}$ for the whole
$J_{1}$--$J_{2}$-circle, i.e. for arbitrary $\varphi$, $J_1=cos(\varphi)$,
$J_2=sin(\varphi)$. Due to low dimension there is no long-range order at $T\neq
0$, but the short-range holds the memory of the parent zero-temperature ordered
phase (antiferromagnetic, stripe or ferromagnetic). $E(\varphi)$ and
$C_{V}(\varphi)$ demonstrate extrema "above" the long-range ordered phases and
in the regions of rapid short-range rearranging. Tracts of
$c_{\mathbf{r}}(\varphi)$ lines have several nodes leading to nonmonotonic
$c_{\mathbf{r}}(T)$ dependence. For any fixed $\varphi$ the heat capacity
$C_{V}(T)$ always has maximum, tending to zero at $T\rightarrow 0$, in the
narrow vicinity of $\varphi = 155^{\circ}$ it exhibits an additional
frustration-induced low-temperature maximum. We have also found the
nonmonotonic behaviour of the spin gaps at $\varphi=270^{\circ}\pm 0$ and
exponentially small antiferromagnetic gap up to ($T\lesssim 0.5$) for $\varphi
\gtrsim 270^{\circ}$.


  We propose a new mixing scheme for neutrinos which eventually can be linked
to a neutrino mass matrix texture bearing a suitable correlation ($m_{22} +
2\,m_{13} = 0$) among its elements. The texture predicts three mass eigenvalues
in the light of normal ordering, in addition to the Majorana phases. The
texture is realized from $A_4 \times Z_{10} \times Z_2$ group in the framework
of general type-I+II seesaw mechanism.


  Long memory or long range dependency is an important phenomenon that may
arise in the analysis of time series or spatial data. Most of the definitions
of long memory of a stationary process $X=\{X_1, X_2,\cdots,\}$ are based on
the second-order properties of the process. The excess entropy of a stationary
process is the summation of redundancies which relates to the rate of
convergence of the conditional entropy $H(X_n|X_{n-1},\cdots, X_1)$ to the
entropy rate. It is proved that the excess entropy is identical to the mutual
information between the past and the future when the entropy $H(X_1)$ is
finite. We suggest the definition that a stationary process is long memory if
the excess entropy is infinite. Since the definition of excess entropy of a
stationary process requires very weak moment condition on the distribution of
the process, it can be applied to processes whose distributions without bounded
second moment. A significant property of excess entropy is that it is invariant
under invertible transformation, which enables us to know the excess entropy of
a stationary process from the excess entropy of other process. For stationary
Guassian process, the excess entropy characterization of long memory relates to
popular characterization well. It is proved that the excess entropy of
fractional Gaussian noise is infinite if the Hurst parameter $H \in (1/2, 1)$.


  Superionic hydrogen was previously thought to be an exotic state predicted
and confirmed only in pure H2O ice. In Earth's deep interior, H2O exists in the
form of O-H groups in ultra-dense hydrous minerals, which have been proved to
be stable even at the conditions of the core-mantle boundary (CMB). However,
the superionic states of these hydrous minerals at high P-T have not been
investigated. Using first-principles calculations, we found that pyrite
structured FeO2Hx (0 <= x <= 1) and d-AlOOH, which have been proposed to be
major hydrogen-bearing phases in the deep lower mantle (DLM), contain
superionic hydrogen at high P-T conditions. Our observations indicate a
universal pathway of the hydroxyl O-H at low pressure transforming to
symmetrical O-H-O bonding at high-P low-T, and a superionic state at high-P
high-T. The superionicity of hydrous minerals has a major impact on the
electrical conductivity and hydrogen transportation behaviors of Earth's lower
mantle as well as the CMB.


  Creating functions is at the center of writing computer programs. But there
has been little empirical research on how this is done and what are the
considerations that developers use. We design an experiment in which we can
compare the decisions made by multiple developers under exactly the same
conditions. The experiment is based on taking existing production code,
"flattening" it into a single monolithic function, and then charging developers
with the task of refactoring it to achieve a better design by extracting
functions. The results indicate that developers tend to extract functions based
on structural cues, such as 'if' or 'try' blocks. And while there are
significant correlations between the refactorings performed by different
developers, there are also significant differences in the magnitude of
refactoring done. For example, the number of functions that were extracted was
between 3 and 10, and the amount of code extracted into functions ranged from
37% to 95%.


  We determine the full $1/\sqrt{\lambda}$ correction to the flat-space Wilson
coefficients which enter the AdS Virasoro-Shapiro amplitude in $\mathcal{N}=4$
SYM theory at strong coupling. The assumption that the Wilson coefficients are
in the ring of single-valued multiple zeta values, as expected for closed
string amplitudes, is surprisingly powerful and leads to a unique solution to
the dispersive sum rules relating Wilson coefficients and OPE data obtained in
[1]. The corresponding OPE data fully agrees with and extends the results from
integrability. The Wilson coefficients to order $1/\sqrt{\lambda}$ can be
summed into an expression whose structure of poles and residues generalises
that of the Virasoro-Shapiro amplitude in flat space.


  Traditional neural networks assume vectorial inputs as the network is
arranged as layers of single line of computing units called neurons. This
special structure requires the non-vectorial inputs such as matrices to be
converted into vectors. This process can be problematic. Firstly, the spatial
information among elements of the data may be lost during vectorisation.
Secondly, the solution space becomes very large which demands very special
treatments to the network parameters and high computational cost. To address
these issues, we propose matrix neural networks (MatNet), which takes matrices
directly as inputs. Each neuron senses summarised information through bilinear
mapping from lower layer units in exactly the same way as the classic feed
forward neural networks. Under this structure, back prorogation and gradient
descent combination can be utilised to obtain network parameters efficiently.
Furthermore, it can be conveniently extended for multimodal inputs. We apply
MatNet to MNIST handwritten digits classification and image super resolution
tasks to show its effectiveness. Without too much tweaking MatNet achieves
comparable performance as the state-of-the-art methods in both tasks with
considerably reduced complexity.


  Fiber Distributed Data Interface (FDDI) is a 100 megabits per second fiber
optic local area network (LAN) standard being developed by the American
National Standard Institute (ANSI).
  We analyze the impact of various design decisions on the error detection
capability of the protocol. In particular, we quantify frame error rate, token
loss rate, and undetected error rate. Several characteristics of the 32-bit
frame check sequence (FCS) polynomial, which is also used in IEEE 802 LAN
protocols, are discussed.


  We initiate the study of what we refer to as random walk labelings of graphs.
These are graph labelings that are obtainable by performing a random walk on
the graph, such that the labeling occurs increasingly whenever an unlabeled
vertex is encountered. Some of the results we obtain involve sums of inverses
of binomial coefficients, for which we obtain new identities. In particular, we
prove that
$\sum_{k=0}^{n-1}2^{k}(2k+1)^{-1}\binom{2k}{k}^{-1}\binom{n+k}{k}=\binom{2n}{n}2^{-n}\sum_{k=0}^{n-1}2^{k}(2k+1)^{-1}\binom{2k}{k}^{-1}$,
thus confirming a conjecture of Bala.


  In this work, we study the reaction of a nucleon and a doubly charmed state
$T_{cc}$. Under the assumption of the $T_{cc}$ as a molecular state of
$D^{*}D$, the reaction of the nucleon and $T_{cc}$ is mediated by exchanges of
$\pi$, $\eta$, $\rho$, and $\omega$ meson, which results in split of $T_{cc}$
state with two $D$ mesons in final state. With the help of the effective
Lagrangians, the cross section of $p+T^+_{cc}\to p+D^++D^0$ process is
calculated, and a very large cross section can be obtained with very small
incoming momentum of proton. It decrease rapidly with the increase of the
momentum to about 10 mb at momenta of order of GeV. Such large cross section
suggests that induced by a proton the $T_{cc}^+$ state is very easy to decay
and transit to two $D$ mesons. In the rest frame of the $T_{cc}^+$ state, an
obvious accumulation of final $D$ meson at small momentum region can be
observed in predicted Dalitz plot, which is due to the molecular state
interpretation of $T_{cc}$ state. This novel quasi-fission phenomenon of double
charm molecular $T_{cc}^+$ state induced by a proton can be accessible at the
forthcoming PANDA experiment.


  Hermann Feshbach predicted fifty years ago that when two atomic nuclei are
scattered within an open entrance channel-- the state observable at infinity,
they may enter an intermediate closed channel -- the locally bounded state of
the nuclei. If the energy of a bound state of in the closed channel is
fine-tuned to match the relative kinetic energy, then the open channel and the
closed channel "resonate", so that the scattering length becomes divergent. We
find that this so-called Feshbach resonance phenomenon not only exists during
the collisions of massive particles, but also emerges during the coherent
transport of massless particles, that is, photons confined in the coupled
resonator arrays \cite{lzhou08}. We implement the open and the closed channels
inside a pair of such arrays, linked by a separated cavity or a tunable qubit.
When a single photon is bounded inside the closed channel by setting the
relevant physical parameters appropriately, the vanishing transmission appears
to display this photonic Feshbach resonance. The general construction can be
implemented through various experimentally feasible solid state systems, such
as the couple defected cavities in photonic crystals. The numerical simulation
based on finite-different time-domain(FDTD) method confirms our conceive about
physical implementation.


  We prove a strengthened version of the inhomogeneous Sprindzhuk conjecture in
metric Diophantine approximation, over a local field of positive
characteristic. The main tool is the transference principle of Beresnevich and
Velani coupled with earlier work of the second named author who proved the
standard, i.e. homogeneous version.


  Vorticity in turbulent flows is often organized into complex geometries that
influence the dynamics. We use a relatively novel approach to describe these
geometries: that of obtaining segments of vortex lines embedded in the flow.
This enables us to quantify the geometric features of these objects. Vortex
lines differ widely in their behaviour but we find some unifying features. The
decay from high levels of vorticity is shown to happen over a short fraction of
the vortex length. The local curvature is inversely related with the vorticity
magnitude. Strong parts of vortex lines bundle together. It is hoped that this
first work will generate interest in such quantification and the physics of
vortex dynamics in turbulence.


  Inspired by the discussion in the community on possible hidden systematic
errors in late universe cosmological probes and non-trivial physical models
developed to reduce the Hubble tension, we investigate the Pantheon and
Pantheon+ SNe samples for possible deviations from the original $\Lambda$CDM
analysis. To simultaneously account for possible systematics or deviations from
$\Lambda$CDM, we adopt Gaussian processes to model additional covariance while
making no further assumptions on their origin. We explore both stationary and
non-stationarity corrections to the covariance. While small changes in the
inferred cosmological parameters $H_0$ and $\Omega_{m}$ can occur, we find no
statistically significant evidence for missing covariance. We find an upper
limit for the Gaussian processes amplitude $\sigma < 0.031$ mag with $95\%$
confidence, which corresponds to $20\%$ of the average statistical error in the
Pantheon+ sample. The strongest effect we find on the inferred cosmological
parameter posterior can reduce the statistical significance of the Hubble
tension between Pantheon+ and Planck estimates from 5.3$\sigma$ to 4.5$\sigma$.
Therefore, we conclude that the SN cosmological parameter inference is robust
against the analysis modifications studied in this work.


  A stochastic model of the chemical enrichment of metal-poor systems by
core-collapse supernovae is used to study the scatter in stellar abundance
ratios. The resulting scatter in abundance ratios, e.g. as functions of the
overall metallicity, is demonstrated to be crucially dependent on the as yet
uncertain supernovae yields. The observed abundance ratios and their scatters
therefore have diagnostic power as regards the yields. The relatively small
star-to-star scatter observed in many chemical abundance ratios, e.g. by Cayrel
et al. (2004) for stars down to [Fe/H] = -4, is tentatively explained by the
averaging of a large number of contributing supernovae and by the cosmic
selection effects favoring contributions from supernovae in a certain mass
range for the most metal-poor stars. The scatter in observed abundances of
alpha-elements is understood in terms of observational errors only, while
additional spread in yields or sites of nucleosynthesis may affect the odd-even
elements Na and Al. For the iron-group elements we find systematically too high
predicted Cr/Fe and Cr/Mg ratios, as well as differences between the different
sets of yields, both in terms of predicted abundance ratios and scatter. The
semi-empirical yields recently suggested by Francois et al. (2004) are found to
lead to scatter in abundance ratios significantly greater than observed, when
applied in the inhomogeneous models. "Spurs", very narrow sequences in
abundance-ratio diagrams, may disclose a single-supernova origin of the
elements of the stars on the sequence. Verification of the existence of such
features, called single supernova sequences (SSSs), is challenging. This will
require samples of several hundred stars with abundance ratios observed to
accuracies of 0.05 dex or better.


  We construct a wavefunction, generalizing the well known Moore-Read Pfaffian,
that describes spinless electrons at filling fraction nu=2/5 (or bosons at
filling fraction nu=2/3) as the ground state of a very simple three body
potential. We find, analogous to the Pfaffian, that when quasiholes are added
there is a ground state degeneracy which can be identified as zero-modes of the
quasiholes. The zero-modes are identified as having semionic statistics. We
write this wavefunction as a correlator of the Virasoro minimal model conformal
field theory M(5,3). Since this model is non-unitary, we conclude that this
wavefunction is a quantum critical state. Nonetheless, we find that the
overlaps of this wavefunction with exact diagonalizations in the lowest and
first excited Landau level are very high, suggesting that this wavefunction may
have experimental relevance for some transition that may occur in that regime.


  The field of eXplainable Artificial Intelligence faces challenges due to the
absence of a widely accepted taxonomy that facilitates the quantitative
evaluation of explainability in Machine Learning algorithms. In this paper, we
propose a novel taxonomy that addresses the current gap in the literature by
providing a clear and unambiguous understanding of the key concepts and
relationships in XAI. Our approach is rooted in a systematic analysis of
existing definitions and frameworks, with a focus on transparency,
interpretability, completeness, complexity and understandability as essential
dimensions of explainability. This comprehensive taxonomy aims to establish a
shared vocabulary for future research. To demonstrate the utility of our
proposed taxonomy, we examine a case study of a Recommender System designed to
curate and recommend the most suitable online resources from MERLOT. By
employing the SHAP package, we quantify and enhance the explainability of the
RS within the context of our newly developed taxonomy.


  If the Galactic rotation speed at the Solar circle is $\sim 200$ km s$^{-1}$
or smaller, which is supported by several recent studies, the rotation curve of
the Galaxy could be declining in the outermost region. Motivated by this, we
investigate the effect of such declining rotation curve on the estimate of the
MACHO mass and the fractional contribution of the MACHOs to the Galactic dark
halo. Using Hernquist and Plummer halo models instead of the standard halo
model, we find that the MACHO mass could be significantly smaller than that for
the standard halo case. In particular, there exists a certain set of halo
parameters for which the MACHO mass is 0.1$M_\odot$ or less and at the same
time the MACHO contribution to the total mass of the halo is almost 100 %. This
result indicates that a halo which consists solely of brown dwarfs can be
consistent with both of the observed microlensing properties and the
constraints from the rotation curve, provided the outer rotation curve is
indeed declining.


  We study the connection between topological order and degeneracy of the
singular value spectrum by explicitly solving the two-dimensional dimerized
quantum Heisenberg model in the form of tensor product state ansatz. Based on
the ground state solution, we find non-zero topological entanglement entropy at
the frustrated regime. It indicates a possible topological phase. Furthermore,
we find that the singular value spectrum associated with each link in tensor
product state is doubly degenerate only in this phase. Degeneracy of the
singular value spectrum is robust against various types of perturbations, in
accordance with our expectation for topological order. Our results support the
connection among topological order, long range entanglement and the dominant
degenerate singular values. In the context of tensor product state ansatz, the
numerical evaluation of singular value spectrum costs far less computation
power than the one for topological entanglement entropy. Our results provide a
more viable way to numerically identify the topological order for the generic
frustrated systems.


  We study torsors under finite group schemes over the punctured spectrum of a
singularity $x\in X$ in positive characteristic. We show that the Dieudonn\'e
module of the (loc,loc)-part
$\mathrm{Picloc}^{\mathrm{loc},\mathrm{loc}}_{X/k}$ of the local Picard sheaf
can be described in terms of local Witt vector cohomology, making
$\mathrm{Picloc}^{\mathrm{loc},\mathrm{loc}}_{X/k}$ computable. Together with
the class group and the abelianised local \'etale fundamental group,
$\mathrm{Picloc}^{\mathrm{loc},\mathrm{loc}}_{X/k}$ completely describes the
finite abelian torsors over $X\setminus\{x\}$. We compute
$\mathrm{Picloc}^{\mathrm{loc},\mathrm{loc}}_{X/k}$ for every rational double
point singularity, which complements results of Artin and Lipman, who
determined ${\pi_{\mathrm{loc}}^{\mathrm{et}}}(X)$ and ${\rm Cl}(X)$. All three
objects turn out to be finite. We extend the Flenner--Mumford criterion for
smoothness of a normal surface germ $x \in X$ to perfect fields of positive
characteristic, generalising work of Esnault and Viehweg: If $k$ is
algebraically closed, then $X$ is smooth if and only if
$\mathrm{Picloc}^{\mathrm{loc},\mathrm{loc}}_{X/k}$,
${\pi_{\mathrm{loc}}^{\mathrm{et}}}(X)$, and ${\rm Cl}(X)$ are trivial.
Finally, we study the question whether rational double point singularities are
quotient singularities by group schemes and if so, whether the group scheme is
uniquely determined by the singularity. We give complete answers to both
questions, except for some $D_n^r$-singularities in characteristic $2$. In
particular, we will give examples of (F-injective) rational double points that
are not quotient singularities.


  We investigate BPS soliton solutions of U(N) Chern-Simons gauge theory
coupled to a scalar field in noncommutative plane. With a scalar field in the
fundamental representation, we show that the BPS equation becomes that of
abelian Chern-Simons theory in the unitary gauge. We also find a class of
particular solutions for the BPS equation with scalar field in the adjoint
representation.


  Semiconductor devices are notoriously difficult to simulate at deep-cryogenic
temperatures. The lowest temperature that can be simulated today in commercial
TCAD is around 4.2 K, possibly 100 mK, while most experimental quantum science
is performed at 10 mK or lower. Besides the challenges in transport solvers,
one of the main bottlenecks is the non-convergence in the electrostatics due to
the extreme sensitivity to small variations in the potential. This article
proposes to reformulate Poisson's equation to take out this extreme sensitivity
and improve convergence. We solve the reformulated Poisson equation for a p-n
diode using an iterative Newton-Raphson scheme, demonstrating convergence for
the first time down to a record low temperature of one microkelvin using the
standard IEEE-754 arithmetic with double precision. We plot the potential
diagrams and resolve the rapid variation of the carrier densities near the
edges of the depletion layer. The main Python functions are presented in the
Appendix.


  The Dzyaloshinskii-Moriya Interaction (DMI) between spins is induced by
spin-orbit coupling in magnetic materials lacking inversion symmetry. DMI is
recognized to play a crucial role at the interface between ferromagnetic (FM)
and heavy nonmagnetic (NM) metals to create topological textures called
magnetic skyrmions which are very attractive for ultra-dense information
storage and spintronic devices. DMI also plays an essential role for fast
domain wall (DW) dynamics driven by spin-orbit torques. Here, we present first
principles calculations which clarify the main features and microscopic
mechanisms of DMI in Co/Pt bilayers. DMI is found to be predominantly located
at the interfacial Co layer, originating from spin-orbit energy provided by the
adjacent NM layer. Furthermore, no direct correlation is found between DMI and
proximity induced magnetism in Pt. These results clarify underlying mechanisms
of DMI at FM/NM bilayers and should help optimizing material combinations for
skyrmion- and DW-based storage and memory devices.


  The one-loop contribution to the superpotential, in particular the
Veneziano-Yankielowicz potential in N=1 supersymmetric Yang-Mills model is
discussed from an elementary field theory method and the matrix model point of
view. Both approaches are based on the Renormalization Group variation of the
superconformal N=4 supersymmetric Yang-Mills model.


  The most recent results of Standard Model physics using 8 and 13 TeV
proton-proton collision data recorded by the CMS detector during the LHC Runs I
and II are reviewed. This overview includes studies of several results of
vector boson production in association with jets. The outlined results are
compared to the corresponding theoretical predictions and no significant
deviation is observed.


  We consider returns of two Korean stock market indices, KOSPI and KOSDAQ
index. Central parts of the probability distribution function of returns are
well fitted by the Lorentzian distribution function. However, tail parts of the
probability distribution function follow a power law behavior well. We found
that the probability distribution function of returns for both KOSPI and
KOSDAQ, is outside the L\'{e}vy stable distribution.


  Interacting particles on graphs are routinely used to study magnetic
behaviour in physics, disease spread in epidemiology, and opinion dynamics in
social sciences. The literature on mean-field approximations of such systems
for large graphs is limited to cluster-free graphs for which standard
approximations based on degrees and pairs are often reasonably accurate. Here,
we propose a motif-based mean-field approximation that considers higher-order
subgraph structures in large clustered graphs. Numerically, our equations agree
with stochastic simulations where existing methods fail.


  Fine-grained image recognition is a longstanding computer vision challenge
that focuses on differentiating objects belonging to multiple subordinate
categories within the same meta-category. Since images belonging to the same
meta-category usually share similar visual appearances, mining discriminative
visual cues is the key to distinguishing fine-grained categories. Although
commonly used image-level data augmentation techniques have achieved great
success in generic image classification problems, they are rarely applied in
fine-grained scenarios, because their random editing-region behavior is prone
to destroy the discriminative visual cues residing in the subtle regions. In
this paper, we propose diversifying the training data at the feature-level to
alleviate the discriminative region loss problem. Specifically, we produce
diversified augmented samples by translating image features along semantically
meaningful directions. The semantic directions are estimated with a covariance
prediction network, which predicts a sample-wise covariance matrix to adapt to
the large intra-class variation inherent in fine-grained images. Furthermore,
the covariance prediction network is jointly optimized with the classification
network in a meta-learning manner to alleviate the degenerate solution problem.
Experiments on four competitive fine-grained recognition benchmarks
(CUB-200-2011, Stanford Cars, FGVC Aircrafts, NABirds) demonstrate that our
method significantly improves the generalization performance on several popular
classification networks (e.g., ResNets, DenseNets, EfficientNets, RegNets and
ViT). Combined with a recently proposed method, our semantic data augmentation
approach achieves state-of-the-art performance on the CUB-200-2011 dataset. The
source code will be released.


  A model of a superlattice consisting of alternating strips of single-layer
and bilayer graphene is proposed, whose parameters of the energy spectrum can
be controlled by changing the external electric field perpendicular to the
surface of the sample. Using the Kronig-Penney model, the dispersion equation
is obtained, based on the analysis of which the energy spectrum of a graphene
superlattice is studied depending on the ratio of the strip widths of
single-layer and bilayer graphene. The results of the analytical solution are
compared with the results of modeling by methods of the theory of the density
functional. It is shown that the low-energy approximation used to derive the
dispersion equation is valid when considering a superlattice with narrow strips
of bilayer graphene and wide strips of single-layer graphene.


  We investigate families of Legendrian submanifolds of 1-jet spaces by
developing and applying a theory of families of generating family homologies.
This theory allows us to detect an infinite family of loops of Legendrian
n-spheres embedded in the standard contact (2n+1)-space (for n>1) that are
contractible in the smooth, but not Legendrian, categories.


  The survey is concerned with the issue of information transmission from
experts to non-experts. Two main approaches to the use of experts can be
traced. According to the game-theoretic approach expertise is a case of
asymmetric information between the expert, who is the better informed agent,
and the non-expert, who is either a decision-maker or an evaluator of the
expert's performance. According to the Bayesian decision-theoretic approach the
expert is the agent who announces his probabilistic opinion, and the non-expert
has to incorporate that opinion into his beliefs in a consistent way, despite
his poor understanding of the expert's substantive knowledge. The two
approaches ground the relationships between experts and non-experts on so
different premises that their results are very poorly connected.


  The use of optical fiber as sensor as well as transmission medium for sensing
data is discussed, enabling the use of optically active sensors without power
supply at distances of tens of kilometers. Depending on the interrogation
system, a spatial resolution of less than a millimeter can be achieved. The
basic sensing principle is optical time-domain reflectometry (OTDR) with direct
detection or coherent detection of the Rayleigh back-scattered or Fresnel
reflected signal. Spatial resolution is improved by a cross-correlation between
the transmitted sequence and the received signals.


  We investigate the dynamics of two models of biological networks with purely
suppressive interactions between the units; species interacting via niche
competition and neurons via inhibitory synaptic coupling. In both of these
cases, power-law scaling of the density of states with probability arises
without any fine-tuning of the model parameters. These results argue against
the increasingly popular notion that non-equilibrium living systems operate at
special critical points, driven by there by evolution so as to enable adaptive
processing of input data.


  Chern insulators exhibit fascinating properties which originate from the
topologically nontrivial state characterized by the Chern number. How these
properties change if the system is quenched between topologically distinct
phases has however not been systematically explored. In this work, we
investigate the quench dynamics of the prototypical massive Dirac model for
topological insu- lators in two dimensions. We consider both dissipation-less
dynamics and the effect of electron- phonon interactions, and ask how the
transient dynamics and nonequilibrium steady states affect simple observables.
Specifically, we discuss a time-dependent generalization of the Hall effect and
the dichroism of the photoexcitation probability between left and right
circularly polarized light. We present optimized schemes based on these
observables, which can reveal the evolution of the topological state of the
quenched system.


  In this paper, we describe how we transformed our large-enrollment
introductory physics sequence for life-science students to a Lecture/Studio
format and aligned the physics concepts with authentic biological applications.
We have reformed the pedagogy to include research-validated practices in
interactive engagement, and accomplished our goals of enhanced learning gains,
sustainability, and adoptability of our course reforms. The active engagement
at the heart of the Lecture/Studio format results in comparable or enhanced
learning gains (as measured by validated concept surveys) when compared to
traditional instruction. When coupled with appropriate instructor preparation
the format is sustainable, requiring no greater financial or human resources
than does the traditional mode of teaching such courses. We have developed a
complete suite of active-engagement instructional materials and made them
available to the physics education community for adoption outside our
institution.


  In this paper we use tools from set theory and the uncountable categoricity
of Zilber's pseudo-exponential field to show that Zilber's field is isomorphic
to the complex field with (standard) exponentiation and hence Schanuel's
conjecture holds for that field.


  The electron--electron scattering does not affect the electrical current in
Galilean--invariant systems. We show that nevertheless electron--electron
collisions may contribute to the electric resistivity of systems with parabolic
spectrum provided that they have multiply connected Fermi surface and there is
an additional mechanism of scattering. To this end, we calculate the
resistivity of a two-dimensional electron gas with two filled transverse
subbands in a presence of electron--electron and impurity scattering. Though
the collisions between the electrons do not directly affect the current in such
systems, they cause a redistribution of the electrons between the Fermi
contours, which results in a noticeable change of resistivity for realistic
mechanisms of impurity scattering.


  This paper describes an experimental comparison of seven different learning
algorithms on the problem of learning to disambiguate the meaning of a word
from context. The algorithms tested include statistical, neural-network,
decision-tree, rule-based, and case-based classification techniques. The
specific problem tested involves disambiguating six senses of the word ``line''
using the words in the current and proceeding sentence as context. The
statistical and neural-network methods perform the best on this particular
problem and we discuss a potential reason for this observed difference. We also
discuss the role of bias in machine learning and its importance in explaining
performance differences observed on specific problems.


  This paper aims at studying how finitely many generalized polarization
tensors of an algebraic domain can be used to determine its shape. Precisely,
given a planar set with real algebraic boundary, it is shown that the minimal
polynomial with real coefficients vanishing on the boundary can be identified
as the generator of a one dimensional kernel of a matrix whose entries are
obtained from a finite number of generalized polarization tensors. The size of
the matrix depends polynomially on the degree of the boundary of the algebraic
domain. The density with respect to Hausdorff distance of algebraic domains
among all bounded domains invites to extend via approximation our
reconstruction procedure beyond its natural context. Based on this, a new
algorithm for shape recognition/classification is proposed with some strong
hints about its efficiency.


  A major coronal heating theory based on magnetic reconnection relies on the
existence of braided magnetic field structures in the corona. In this
small-angle reconnection scenario, numerical simulations indicate that the
reconnected magnetic field lines are driven sideways by magnetic tension and
can overshoot from their new rest position, thereby leading to low-amplitude
transverse MHD waves. This provides an efficient mechanism for transverse MHD
wave generation, and the direct causality also constitutes substantial evidence
of reconnection from braiding. However, this wave-generation mechanism has
never been directly observed. Recently, the telltale signature of small-angle
reconnection in a sheared coronal structure has been identified through
nanojets, which are small, short-lived, and fast jet-like bursts in the
nanoflare range transverse to the guide-field. We present for the first time
IRIS and SDO observations of transverse MHD waves in a coronal loop that
directly result from braiding-induced reconnection. The reconnection is
identified by the presence of nanojets at the loop apex which release
nanoflare-range energy. We find that the oscillations have an energy flux on
the order of $10^6 - 10^8$~erg~cm$^{-2}$~s$^{-1}$, which is within the budget
to power active region loops. The estimated kinetic and thermal energy from the
nanojets is also sufficient to power the transverse waves and sustain the
observed heating at the loop apex. This discovery provides major support to (a)
existing theories that transverse MHD waves can be a signature of reconnection,
(b) the existence of braiding in coronal structures and (c) the coronal
reconnection scenario identified by nanojets.


  We investigate a non-interacting many-particle bosonic system, placed in an
asymmetric double-well potential. We first consider the dynamics of a single
particle and determine its time-dependent probabilities to be in the left or
the right well of the potential. These probabilities obey the standard
Josephson equations, which in their many-particle interpretation also describe
a globally coherent system, such as a Bose-Einstein condensate. This system
exhibits the widely studied Josephson oscillations of the population imbalance
between the wells. In our study we go beyond the regime of global coherence by
developing a formalism based on an effective density matrix. This formalism
gives rise to a generalization of Josephson equations, which differ from the
standard ones by an additional parameter, that has the meaning of the degree of
fragmentation. We first consider the solution of the generalized Josephson
equations in the particular case of thermal equilibrium at finite temperatures,
and extend our discussion to the non-equilibrium regime afterwards. Our model
leads to a constraint on the maximum amplitude of Josephson oscillations for a
given temperature and the total number of particles. A detailed analysis of
this constraint for typical experimental scenarios is given.


  Context : Dynamical studies of prestellar cores search for small velocity
differences between different tracers. The highest radiation frequency
precision is therefore required for each of these species. Aims : We want to
adjust the frequency of the first three rotational transitions of N2H+ and N2D+
and extrapolate to the next three transitions. Methods : N2H+ and N2D+ are
compared to NH3 the frequency of which is more accurately known and which has
the advantage to be spatially coexistent with N2H+ and N2D+ in dark cloud
cores. With lines among the narrowests, and N2H+ and NH3 emitting region among
the largests, L183 is a good candidate to compare these species. Results : A
correction of ~10 kHz for the N2H+ (J:1-0) transition has been found (~0.03
km/s) and similar corrections, from a few m/s up to ~0.05 km/s are reported for
the other transitions (N2H+ J:3-2 and N2D+ J:1-0, J:2-1, and J:3-2) compared to
previous astronomical determinations. Einstein spontaneous decay coefficients
(Aul) are included.


  In this paper we introduce a technique and a tool for formal verification of
various quantum information processing protocols. The tool uses stabilizer
formalism and is capable of representing concurrent quantum protocol, thus is
more expressive than quantum circuits. We also report on experimental results
of using our Quantum Equivalence Checker (QEC) to analyse a range of quantum
information processing protocols.


  The dynamics of a cascaded system that consists of two atom-cavity subsystems
is studied by using the quantum trajectory method. Considering the two
atom-cavity subsystems driven by a Raman interaction, analytical solutions are
obtained. Subsequently, the entanglement evolution between the two atoms is
studied, and it is shown that the entanglement can be stored by switching off
the Raman coupling. By monitoring the radiation field, the entanglement between
the two atoms can be enhanced.


  In this note we generalize the Ball-James rigidity theorem for gradient
differential inclusions to the setting of a general linear differential
constraint. In particular, we prove the rigidity for approximate solutions to
the two-state inclusion with incompatible states for merely
$\mathrm{L}^1$-bounded sequences. In this way, our theorem can be seen as a
result of compensated compactness in the linear-growth setting.


  We report numerical simulation results for free-vortex lifetimes in the
critical region of classical two-dimensional easy-plane ferro- and
antiferromagnets having three-component order parameters. The fluctuations in
the vortex number density in a spin dynamics simulation were used to estimate
the lifetimes. The observed lifetimes are of the same order of magnitude but
smaller than the characteristic time-scale above which a phenomenological ideal
vortex-gas theory that has been used to account for the central peak in the
dynamic structure factor $S^{\alpha\alpha}({\bf q},\omega)$ is expected to be
valid. % For strong anisotropy, where the vortices are in-plane, the free
vortex lifetimes for ferromagnets and antiferromagnets are the same, while for
weak anisotropy, where the vortices have nonzero out-of-easy-plane components,
the lifetimes in antiferromagnets are smaller than in ferromagnets. The
dependence of the free-vortex and total vortex densities on the size dependent
correlation length in the critical region is examined. We also determined the
lifetimes of vortex-antivortex pairs for $T = T_{{\scriptsize KT}}$ and well
below $T_{{\scriptsize KT}}$. The observed time-scales are very short, and the
observed pair densities are extremely small. These results suggest that pair
creation and annihilation are unlikely to play any role in the central peak in
$S^{xx}({\bf q},\omega)$ observed in computer simulations for the ferromagnetic
model for $T \leq T_{{\scriptsize KT}}$.


  In this paper, we review how to obtain the central charge of a critical
entanglement Hamiltonian through the nested entanglement entropy which was
first introduced in [J. Lou et al. PRB 84, 245128 (2011)]. The critical
phenomena of the entanglement Hamiltonian can be identified by the central
charge obtained by the nested entanglement entropy. We review our previous
studies[J. Lou et al. PRB 84, 245128 (2011), S. Tanaka et al. PRA 87, 214401
(2013)] in which we investigated certain entanglement nature of two-dimensional
valence-bond-solid (VBS) state and quantum hard-square models on square and
triangle ladders using the nested entanglement entropy.


  We analyze the trajectories for multifield DBI inflation, which can arise in
brane inflation models, and show that the trajectories are the same as in
typical slow roll inflation. We calculate the power spectrum and find that the
higher derivative terms of the DBI action lead to a suppression of the
contribution from the isocurvature perturbations. We also calculate the
bispectrum generated by the isocurvature perturbation, and find that it leads
to distinctive features.


  Linear stability analysis of speckle pattern resulting from multiple, diffuse
scattering of coherent light waves in random media with intensity-dependent
refractive index (noninstantaneous Kerr nonlinearity) is performed. The speckle
pattern is shown to become unstable with respect to dynamic perturbations
within a certain frequency band, provided that nonlinearity exceeds some
frequency-dependent threshold. Although the absolute instability threshold is
independent of the response time of nonlinearity, the latter significantly
affects speckle dynamics (in particular, its spectral content) beyond the
threshold. Our results suggest that speckle dynamics becomes chaotic
immediately beyond the threshold.


  We give an explicit formula for the $RO(C_{2^n})$-graded homotopy of
$H\underline{\mathbb{F}_2}$.


  In a one-way analysis-of-variance (ANOVA) model, the number of all pairwise
comparisons can be large even when there are only a moderate number of groups.
Motivated by this, we consider a regime with a growing number of groups, and
prove that for testing pairwise comparisons the BH procedure can offer
asymptotic control on false discoveries, despite that the t-statistics involved
do not exhibit the well-known positive dependence structure called the PRDS to
guarantee exact false discovery rate (FDR) control. Sharing Tukey's viewpoint
that the difference in the means of any two groups cannot be exactly zero, our
main result is stated in terms of the control on the directional false
discovery rate and directional false discovery proportion. A key technical
contribution is that we have shown the dependence among the t-statistics to be
weak enough to induce a convergence result typically needed for establishing
asymptotic FDR control. Our analysis does not adhere to stylized assumptions
such as normality, variance homogeneity and a balanced design, and thus
provides a theoretical grounding for applications in more general situations.


  A mass-energy scale for neutrinos was calculated from the null cone curvature
using geometric concepts. The scale is variable depending on the gravitational
potential and the trajectory inclination with respect to the field direction.
The proposed neutrino covariant equation provides the adequate curvature. The
mass-energy at the Earth surface varies from a horizontal value 0.402 eV to a
vertical value 0.569 eV. Earth spinor waves with winding numbers n show squared
energy differences within ranges from 2.05 x 10*(-3) to 4.10 x 10*(-3) eV*2 for
n=0,1 neutrinos and from 3.89 x 10*(-5) to 7.79 x 10*(-5) eV*2 for n=1,2
neutrinos. These waves interfere and the different phase velocities produce
neutrino-like oscillations. The experimental results for atmospheric and solar
neutrino oscillation mass parameters respectivelly fall within these
theoretical ranges. Neutrinos in outer space, where interactions may be
neglected, appear as particles travelling with zero mass on null geodesics.
These gravitational curvature energies are consistent with neutrino
oscillations, zero neutrino rest masses and Einstein's General Relativity and
energy mass equivalence principle. When analyzing or averaging experimental
neutrino mass-energy results of different experiments on the Earth it is of
interest to consider the possible influence of the trajectory inclination
angle.


  We prove the connection between the Nekrasov partition function of N=2
super-symmetric U(2) gauge theory with adjoint matter and conformal blocks for
the Virasoro algebra, as predicted by the Alday-Gaiotto-Tachikawa relations.
Mathematically, this is achieved by relating the Carlsson-Okounkov Ext vector
bundle on the moduli space of rank 2 sheaves with Liouville vertex
operators.Our approach is geometric in nature, and uses a new method for
intersection-theoretic computations of the Ext operator.


  This paper describes, in detail, techniques for measuring the Hurst
parameter. Measurements are given on artificial data both in a raw form and
corrupted in various ways to check the robustness of the tools in question.
Measurements are also given on real data, both new data sets and well-studied
data sets. All data and tools used are freely available for download along with
simple ``recipes'' which any researcher can follow to replicate these
measurements.


  The optical conductivity for the surface excitations for a Topological
Insulator as a function of the chemical potential and disorder is considered.
Due to the time reversal symmetry the chiral metallic surface states are
protected against disorder. This allow to use the averaged single particle
Green's function to compute the optical conductivity. We compute the
conductivity in the limit of a finite disorder. We find that the conductivity
as a function of the chemical potential $\mu $ and frequency $\Omega$ is given
by the universal value $\sigma(\Omega>2\mu)= \frac{e^2 \pi}{8h}$. For
frequencies $\Omega< \mu$ and elastic mean free path $l_{el}=v\tau$ which obey
$k_{F}l>1$ we obtain the conductivity is given by
$\sigma(\Omega<2|\mu|)=\frac{e^2}{2h}\frac{k_{F}l_{el}}{(\Omega \tau)^2+1}$. In
the limit of zero disorder we find $\sigma(\mu\neq0,\Omega, k_{F}l\rightarrow
\infty)=\frac{e^2 \pi}{2h}|\mu|\delta(\Omega)$.


  Through seven publications this dissertation shows how anonymized mobile
phone data can contribute to the social good and provide insights into human
behaviour on a large scale. The size of the datasets analysed ranges from 500
million to 300 billion phone records, covering millions of people. The key
contributions are two-fold:
  1. Big Data for Social Good: Through prediction algorithms the results show
how mobile phone data can be useful to predict important socio-economic
indicators, such as income, illiteracy and poverty in developing countries.
Such knowledge can be used to identify where vulnerable groups in society are,
reduce economic shocks and is a critical component for monitoring poverty rates
over time. Further, the dissertation demonstrates how mobile phone data can be
used to better understand human behaviour during large shocks in society,
exemplified by an analysis of data from the terror attack in Norway and a
natural disaster on the south-coast in Bangladesh. This work leads to an
increased understanding of how information spreads, and how millions of people
move around. The intention is to identify displaced people faster, cheaper and
more accurately than existing survey-based methods.
  2. Big Data for efficient marketing: Finally, the dissertation offers an
insight into how anonymised mobile phone data can be used to map out large
social networks, covering millions of people, to understand how products spread
inside these networks. Results show that by including social patterns and
machine learning techniques in a large-scale marketing experiment in Asia, the
adoption rate is increased by 13 times compared to the approach used by
experienced marketers. A data-driven and scientific approach to marketing,
through more tailored campaigns, contributes to less irrelevant offers for the
customers, and better cost efficiency for the companies.


  Covariant density functional theory and the tilted axis cranking method are
used to investigate antimagnetic rotation (AMR) in nuclei for the first time in
a fully self-consistent and microscopic way. The experimental spectrum as well
as the B(E2) values of the recently observed AMR band in 105Cd are reproduced
very well. This gives a further strong hint that AMR is realized in specific
bands in nuclei.


  The need to help people choose among large numbers of items and to filter
through large amounts of information has led to a flood of research in
construction of personal recommendation agents. One of the central issues in
constructing such agents is the representation and elicitation of user
preferences or interests. This topic has long been studied in Decision Theory,
but surprisingly little work in the area of recommender systems has made use of
formal decision-theoretic techniques. This paper describes DIVA, a
decision-theoretic agent for recommending movies that contains a number of
novel features. DIVA represents user preferences using pairwise comparisons
among items, rather than numeric ratings. It uses a novel similarity measure
based on the concept of the probability of conflict between two orderings of
items. The system has a rich representation of preference, distinguishing
between a user's general taste in movies and his immediate interests. It takes
an incremental approach to preference elicitation in which the user can provide
feedback if not satisfied with the recommendation list. We empirically evaluate
the performance of the system using the EachMovie collaborative filtering
database.


  We consider the first LHC data for elastic pp scattering in the framework of
Regge theory with multiple Pomeron exchanges. The simplest eikonal approach
allows one to describe differential elastic cross sections at LHC, as well as
pp and $\bar{p}p$ scattering at lower collider energies, on a reasonable level.


  Denote $\mathcal{A}$ as the set of all doubly substochastic $m \times n$
matrices and let $k$ be a positive integer. Let $\mathcal{A}_k$ be the set of
all $1/k$-bounded doubly substochastic $m \times n$ matrices, i.e.,
$\mathcal{A}_k \triangleq \{E \in \mathcal{A}: e_{i,j} \in [0, 1/k], \forall
i=1,2,\cdots,m, j = 1,2,\cdots, n\}$. Denote $\mathcal{B}_k$ as the set of all
matrices in $\mathcal{A}_k$ whose entries are either $0$ or $1/k$. We prove
that $\mathcal{A}_k$ is the convex hull of all matrices in $\mathcal{B}_k$.


  The translation of ambiguous text presents a challenge for translation
systems, as it requires using the surrounding context to disambiguate the
intended meaning as much as possible. While prior work has studied ambiguities
that result from different grammatical features of the source and target
language, we study semantic ambiguities that exist in the source (English in
this work) itself. In particular, we focus on idioms that are open to both
literal and figurative interpretations (e.g., goose egg), and collect TIDE, a
dataset of 512 pairs of English sentences containing idioms with disambiguating
context such that one is literal (it laid a goose egg) and another is
figurative (they scored a goose egg, as in a score of zero). In experiments, we
compare MT-specific models and language models for (i) their preference when
given an ambiguous subsentence, (ii) their sensitivity to disambiguating
context, and (iii) the performance disparity between figurative and literal
source sentences. We find that current MT models consistently translate English
idioms literally, even when the context suggests a figurative interpretation.
On the other hand, LMs are far more context-aware, although there remain
disparities across target languages. Our findings underline the potential of
LMs as a strong backbone for context-aware translation.


  Enlarging on Parts I and II we write more equations in the desired format of
the extended abstract theory of composites. We focus on a multitude of full
dynamic equations, including equations where the medium is moving or otherwise
changing in time. The motivation is that results and methods in the theory of
composites then extend to these equations.


  This paper introduces a very challenging dataset of historic German documents
and evaluates Fully Convolutional Neural Network (FCNN) based methods to locate
handwritten annotations of any kind in these documents. The handwritten
annotations can appear in form of underlines and text by using various writing
instruments, e.g., the use of pencils makes the data more challenging. We train
and evaluate various end-to-end semantic segmentation approaches and report the
results. The task is to classify the pixels of documents into two classes:
background and handwritten annotation. The best model achieves a mean
Intersection over Union (IoU) score of 95.6% on the test documents of the
presented dataset. We also present a comparison of different strategies used
for data augmentation and training on our presented dataset. For evaluation, we
use the Layout Analysis Evaluator for the ICDAR 2017 Competition on Layout
Analysis for Challenging Medieval Manuscripts.


  The local magnetic moment of an interacting quantum dot occupied by a single
electron can be screened by binding a Bogoliubov quasiparticle from a nearby
superconductor. This gives rise to a long-lived discrete spin-singlet state
inside the superconducting gap, known as the Yu-Shiba-Rusinov (YSR) state. We
study the nature of the subgap states induced by a quantum dot embedded between
two small superconducting islands. We show that this system has two
spin-singlet subgap states with different spatial charge distributions. These
states can be put in a linear superposition and coherently manipulated using
electric-field pulses applied on the gate electrode. Such YSR qubit could be
implemented using present-day technology.


  In this paper we formulate combinatorial identities that give representation
of positive integers as linear combination of even powers of 2 with binomial
coefficients. We present side by side combinatorial as well as computer
generated proofs using the Wilf-Zeilberger(WZ) method.


  The response of a many body system to a time dependent coupling which passes
through or approaches a critical point displays universal scaling behavior. In
some regimes, scaling laws have been known since the 1970's. Recently
holographic techniques have been used to understand the origins of such
scaling. Along the way, new scaling behaviors in other regimes have been found
in holographic models, which have later been shown to hold in a generic field
theory regardless of holography. This contribution summarizes recent work on
these various scaling regimes.


  We construct two families of free resolutions that resolve the ideals of
certain opposite Schubert varieties restricted to the big open cell. We
conjecture that these examples have genericity properties translating to
structure theorems for perfect ideals with given Betti numbers, extending the
well-known theorem of Buchsbaum and Eisenbud on Gorenstein ideals of
codimension three.


  We examine the Cerenkov-like emission of $e^+ e^-$ from muon super-luminal
muon neutrinos assuming a quadratic energy dependence of the neutrino velocity
arising from Lorentz violating interactions. We find that with the OPERA result
for the neutrino-photon velocity difference, the decay length for the process
$\nu_\mu\rightarrow \nu_\mu e^+ e^-$ is 17,039 km which is much larger than the
OPERA neutrinos path length of 730 km. We also calculate the pion rate for
super-luminal outgoing neutrinos, and we find that the deviation of the pion
decay length from the standard Lorentz conserving case at the OPERA neutrino
energy is 2%. We conclude that if the muon-neutrino velocity has a quadratic
energy dependence, then OPERA result is consistent with non-observation of
forbidden neutrino decays and large deviations from the standard pion decay
lifetime.