  In general, generation of entangled photon pairs and also the random choice
of measurement basis can be implemented with passive optical devices in
entanglement based quantum key distribution (QKD) system. However, auxiliary
random numbers are still mandatory for conducting the privacy amplification
procedure. In this paper, we propose a fully passive entanglement based QKD
scheme in which certified random bits for privacy amplification are extracted
from detection events of measurement-basis-mismatched entangled photon pairs.
The privacy of these random bits can be certified by estimating the phase error
rate in the sifted key. The idea of extracting certified random numbers from
measurement-basis-mismatched photons, can be extended to all practical QKD
schemes.


  Algorithm unrolling has emerged as a learning-based optimization paradigm
that unfolds truncated iterative algorithms in trainable neural-network
optimizers. We introduce Stochastic UnRolled Federated learning (SURF), a
method that expands algorithm unrolling to federated learning in order to
expedite its convergence. Our proposed method tackles two challenges of this
expansion, namely the need to feed whole datasets to the unrolled optimizers to
find a descent direction and the decentralized nature of federated learning. We
circumvent the former challenge by feeding stochastic mini-batches to each
unrolled layer and imposing descent constraints to guarantee its convergence.
We address the latter challenge by unfolding the distributed gradient descent
(DGD) algorithm in a graph neural network (GNN)-based unrolled architecture,
which preserves the decentralized nature of training in federated learning. We
theoretically prove that our proposed unrolled optimizer converges to a
near-optimal region infinitely often. Through extensive numerical experiments,
we also demonstrate the effectiveness of the proposed framework in
collaborative training of image classifiers.


  The scattering of a baryon consisting of three massive quarks is investigated
in the high energy limit of perturbative QCD. A model of a relativistic
proton-like wave function, dependent on valence quark longitudinal and
transverse momenta and on quark helicities, is proposed, and we derive the
baryon impact factors for two, three and four t-channel gluons. We find that
the baryonic impact factor can be written as a sum of three pieces: in the
first one a subsystem consisting of two of the three quarks behaves very much
like the quark-antiquark pair in gamma* scattering, whereas the third quark
acts as a spectator. The second term belongs to the odderon, whereas in the
third (C-even) piece all three quarks participate in the scattering. This term
is new and has no analogue in gamma* scattering. We also study the small x
evolution of gluon radiation for each of these three terms. The first term
follows the same pattern of gluon radiation as the gamma*-initiated
quark-antiquark dipole, and, in particular, it contains the BFKL evolution
followed by the 2-->4 transition vertex (triple Pomeron vertex). The
odderon-term is described by the standard BKP evolution, and the baryon couples
to both known odderon solutions, the Janik-Wosiek solution and the BLV
solution. Finally, the t-channel evolution of the third term starts with a
three reggeized gluon state which then, via a new 3-->4 transition vertex,
couples to the four gluon (two-Pomeron) state. We briefly discuss a few
consequences of these findings, in particular the pattern of unitarization of
high energy baryon scattering amplitudes.


  Let $p$ be a prime and $\mathbb{F}$ a field of characteristic $p$, and let
$\mathcal{H}_n$ denote the Iwahori--Hecke algebra of the symmetric group
$\mathfrak{S}_n$ over $\mathbb{F}$ at $q=-1$. We prove that there are only
finitely many partitions $\lambda$ such that both $\lambda$ and $\lambda'$ are
2-singular and the Specht module $S^\lambda$ for $\mathcal{H}_{|\la|}$ is
irreducible.


  We investigate the possibility that the observed rotation of galaxies can be
accounted for by invoking a massive baryonic disc with no need for non-baryonic
dark matter or a massive halo. There are 5 primary reasons for suggesting this:
1. there are well known disc surface mass density distributions that naturally
produce the observed rotation curves of galaxies. 2. there are a number of
rotation curve `puzzles' that cannot be explained by a massive dark matter halo
i.e. the success of maximum disc fitting, HI gas scaling to the observed
rotation, the disc/halo conspiracy and the interpretation of the Tully-Fisher
relation. 3. recent 21cm observations show an almost constant HI surface
density and a distinct `cut-off' or edge to galactic discs. We explain this
constant surface density in terms of either an optical depth effect or the
onset of molecular gas formation and hence the possibility of considerably more
gas existing in galaxies. We suggest that the HI cut-off does indeed mark the
edge of the galactic disc. 4. there have been an increasing number of recent
observations that imply that X_CO may be ten times higher in the outer Galaxy.
This `dark' gas may provide adequate mass to account for galaxy rotation. 5. we
show that the additional baryonic mass required to account for the rotation of
galaxies is just that required to reconcile observed baryons with those
predicted by big bang nucleosynthesis. Mestel discs can be used to straight
forwardly explain the scaling laws of galaxies, particularly the observed
relation between rotation velocity and radius and the oft used Tully-Fisher
relation. We discuss observations of the baryonic content of galactic discs and
where sufficient `hidden' baryons might be found to account for the rotation.


  In this paper, we define (im, reg)-invariant extension of graphs and propose
a new approach for Nevo and Peeva's conjecture which said that for any gap-free
graph $G$ with $reg(I(G)) = 3$ and for any $k \geq 2$, $I(G)^k$ has a linear
resolution.
  Moreover, we consider new conjectures related to the regularity of powers of
edge ideals of gap-free graphs.


  User interfaces provide an interactive window between physical and virtual
environments. A new concept in the field of human-computer interaction is a
soft user interface; a compliant surface that facilitates touch interaction
through deformation. Despite the potential of these interfaces, they currently
lack a signal processing framework that can efficiently extract information
from their deformation. Here we present OrbTouch, a device that uses
statistical learning algorithms, based on convolutional neural networks, to map
deformations from human touch to categorical labels (i.e., gestures) and touch
location using stretchable capacitor signals as inputs. We demonstrate this
approach by using the device to control the popular game Tetris. OrbTouch
provides a modular, robust framework to interpret deformation in soft media,
laying a foundation for new modes of human computer interaction through shape
changing solids.


  ALICE (A Large Heavy Ion Experiment) is one of the four major experiments at
the Large Hadron Collider (LHC) at CERN. The High Level Trigger (HLT) is an
online compute farm which reconstructs events measured by the ALICE detector in
real-time. The most compute-intensive part is the reconstruction of particle
trajectories called tracking and the most important detector for tracking is
the Time Projection Chamber (TPC). The HLT uses a GPU-accelerated algorithm for
TPC tracking that is based on the Cellular Automaton principle and on the
Kalman filter. The GPU tracking has been running in 24/7 operation since 2012
in LHC Run 1 and 2. In order to better leverage the potential of the GPUs, and
speed up the overall HLT reconstruction, we plan to bring more reconstruction
steps (e.g. the tracking for other detectors) onto the GPUs. There are several
tasks running so far on the CPU that could benefit from cooperation with the
tracking, which is hardly feasible at the moment due to the delay of the PCI
Express transfers. Moving more steps onto the GPU, and processing them on the
GPU at once, will reduce PCI Express transfers and free up CPU resources. On
top of that, modern GPUs and GPU programming APIs provide new features which
are not yet exploited by the TPC tracking. We present our new developments for
GPU reconstruction, both with a focus on the online reconstruction on GPU for
the online offline computing upgrade in ALICE during LHC Run 3, and also taking
into account how the current HLT in Run 2 can profit from these improvements.


  We investigate in a nonperturbative way the dynamics of a correlated quantum
capacitor. We find that the many-body correlations do not disturb the universal
low-frequency relaxation resistance per channel, $R_q(\omega=0) = h/4e^2$
ensured by the Korringa-Shiba rule whereas the interpretation of the quantum
capacitance $C_q$ in terms of the density of states fails when strong
correlations are present. The AC resistance $R_q(\omega)$ shows huge peaks
(with values larger than $h/4e^2$) at $\hbar\omega \approx \pm \Gamma^*$, where
$\Gamma^*$ is the renormalized level broadening. These peaks are merged to a
single one at $\omega=0$ when a finite Zeeman field is applied comparable to
$\Gamma^*$. The observed features of $R_q$, being most evident in the Kondo
regime, are attributed to the generation of particle-hole excitations in the
contacts accomplished by spin-flip processes in the dot.


  Delay-tolerant networks (DTNs) are characterized by a possible absence of
end-to-end communication routes at any instant. Still, connectivity can
generally be established over time and space. The optimality of a temporal path
(journey) in this context can be defined in several terms, including
topological (e.g. {\em shortest} in hops) and temporal (e.g. {\em fastest,
foremost}). The combinatorial problem of computing shortest, foremost, and
fastest journeys {\em given full knowledge} of the network schedule was
addressed a decade ago (Bui-Xuan {\it et al.}, 2003). A recent line of research
has focused on the distributed version of this problem, where foremost,
shortest or fastest {\em broadcast} are performed without knowing the schedule
beforehand. In this paper we show how to build {\em fastest} broadcast trees
(i.e., trees that minimize the global duration of the broadcast, however late
the departure is) in Time-Varying Graphs where intermittent edges are available
periodically (it is known that the problem is infeasible in the general case
even if various parameters of the graph are know). We address the general case
where contacts between nodes can have arbitrary durations and thus fastest
routes may consist of a mixture of {\em continuous} and {\em discontinuous}
segments (a more complex scenario than when contacts are {\em punctual} and
thus routes are only discontinuous). Using the abstraction of \tclocks to
compute the temporal distances, we solve the fastest broadcast problem by first
learning, at the emitter, what is its time of {\em minimum temporal
eccentricity} (i.e. the fastest time to reach all the other nodes), and second
by building a {\em foremost} broadcast tree relative to this particular
emission date.


  We report a time-dependent density functional based tight-binding (TD-DFTB)
scheme for the calculation of UV/Vis spectra, explicitly taking into account
the excitation of nuclear vibrations via the adiabatic Hessian Franck-Condon
(AH|FC) method with a harmonic approximation for the nuclear wavefunction. The
theory of vibrationally resolved UV/Vis spectroscopy is first summarized from
the viewpoint of TD-DFTB. The method is benchmarked against time-dependent
density functional theory (TD-DFT) calculations for strongly dipole allowed
excitations in various aromatic and polar molecules. Using the recent 3ob:freq
parameter set of Elstner's group, very good agreement with TD-DFT calculations
using local functionals was achieved.


  The trigger system of the Surface Detector (SD) of the Pierre Auger
Observatory is described, from the identification of candidate showers ($E>1$
EeV) at the level of a single station, among a huge background (mainly single
muons), up to the selection of real events and the rejection of random
coincidences at a higher central trigger level (including the reconstruction
accuracy). Efficiency of a single station trigger is evaluated using real data
, and the high performance of event selection hierarchy will be demonstrated.


  In recent years, Transformer-based language models have become the standard
approach for natural language processing tasks. However, stringent throughput
and latency requirements in industrial applications are limiting their
adoption. To mitigate the gap, model compression techniques such as structured
pruning are being used to improve inference efficiency. However, most existing
neural network inference runtimes lack adequate support for structured
sparsity. In this paper, we propose an efficient sparse deep learning inference
software stack for Transformer-based language models where the weights are
pruned with constant block size. Our sparse software accelerator leverages
Intel Deep Learning Boost to maximize the performance of sparse matrix - dense
matrix multiplication (commonly abbreviated as SpMM) on CPUs. Our SpMM kernel
outperforms the existing sparse libraries (oneMKL, TVM, and LIBXSMM) by an
order of magnitude on a wide range of GEMM shapes under 5 representative
sparsity ratios (70%, 75%, 80%, 85%, 90%). Moreover, our SpMM kernel shows up
to 5x speedup over dense GEMM kernel of oneDNN, a well-optimized dense library
widely used in industry. We apply our sparse accelerator on widely-used
Transformer-based language models including Bert-Mini, DistilBERT, Bert-Base,
and BERT-Large. Our sparse inference software shows up to 1.5x speedup over
Neural Magic's Deepsparse under same configurations on Xeon on Amazon Web
Services under proxy production latency constraints. We also compare our
solution with two framework-based inference solutions, ONNX Runtime and
PyTorch, and demonstrate up to 37x speedup over ONNX Runtime and 345x over
PyTorch on Xeon under the latency constraints. All the source code is publicly
available on Github: https://github.com/intel/intel-extension-for-transformers.


  At present, designing convolutional neural network (CNN) architectures
requires both human expertise and labor. New architectures are handcrafted by
careful experimentation or modified from a handful of existing networks. We
introduce MetaQNN, a meta-modeling algorithm based on reinforcement learning to
automatically generate high-performing CNN architectures for a given learning
task. The learning agent is trained to sequentially choose CNN layers using
$Q$-learning with an $\epsilon$-greedy exploration strategy and experience
replay. The agent explores a large but finite space of possible architectures
and iteratively discovers designs with improved performance on the learning
task. On image classification benchmarks, the agent-designed networks
(consisting of only standard convolution, pooling, and fully-connected layers)
beat existing networks designed with the same layer types and are competitive
against the state-of-the-art methods that use more complex layer types. We also
outperform existing meta-modeling approaches for network design on image
classification tasks.


  Using evolutionary algorithm for crystal structure prediction, we present a
new stable two-dimensional (2D) carbon allotrope composed of polymerized
as-indacenes (PAI) in a zigzag pattern, namely PAI-graphene whose energy is
lower than most of the reported 2D allotropes of graphene. Crucially, the
crystal structure realizes a nonsymmorphic layer group that enforces a
nontrivial global topology of the band structure with two Dirac cones lying
perfectly at the Fermi level. The absence of electron/hole pockets makes
PAI-graphene a pristine crystalline topological semimetal having anisotropic
Fermi velocities with a high value of $7.0 \times 10^{5}$ m/s. We show that
while the semimetallic property of the allotrope is robust against the
application of strain, the positions of the Dirac cone and the Fermi velocities
can be modified significantly with strain. Moreover, by combining strain along
both the x- and y-directions, two band inversions take place at $\Gamma$
leading to the annihilation of the Dirac nodes demonstrating the possibility of
strain-controlled conversion of a topological semimetal into a semiconductor.
Finally we formulate the bulk-boundary correspondence of the topological nodal
phase in the form of a generalized Zak-phase argument finding a perfect
agreement with the topological edge states computed for different
edge-terminations.


  Nowaday, in study of effective interactions, more attention is devoted to
single-particle properties of near-magic nuclei and bulk properties of deformed
ones but quasiparticle states of the latter are rarely used so far because of
theoretical difficulties. In particular, the angular momentum projection
remains too time-consuming for such calculations and the methods, which are
based on the transformation to an intrinsic frame have some unsolved problems
such, e. g., as quantum fluctuations of rotational recoil in the description of
quasiparticle-rotation coupling. To remove a part of these difficulties, the
method of the optimal intrinsic. frame-of-reference is developed. After
applying the Mikhajlov transformation to obtain the nuclear Hamiltonian in the
intrinsic frame, approximate constraints on nucleon's variables are
substantiated, and the quasiparticle structure of the nucleus orientation angle
operators is investigated. That gives possibility to use the variational
principle to derive equations for matrix elements of these operators. An
approximation similar to the cranking model (CM), but with the quantum
rotational recoil, is formulated, which may be considered as a generalization
of the usual self-consistent CM. Simplified model calculations for rotational
bands in $^{163}$Er show that taking into account the recoil operator.
considerably improves the agreement with experimental data


  Bandwidth Allocation Models (BAMs) configure and handle resource allocation
(bandwidth, LSPs, fiber) in networks in general (IP/MPLS/DS-TE, optical domain,
other). BAMs currently available for IP/MPLS/DS-TE networks (MAM, RDM, G-RDM
and AllocTC-Sharing) basically define resource restrictions (bandwidth) by
class (traffic class, application class, user class or other grouping criteria)
and allocate on demand this resource. There is a BAM allocation policy inherent
for each existing model which behaves differently under distinct network state,
such as heavy traffic loads and dynamic traffic and/or application scenarios. A
generalized Bandwidth Allocation Model (G-BAM) is proposed in this paper.
G-BAM, firstly, incorporates the inherent behavior of currently used BAMs such
as MAM, RDM, G-RDM and AllocTC-Sharing in IP/MPLS/DS-TE context. G-BAM,
secondly, proposes a new policy/ behavior allocation in addition to existing
ones in which additional private resources are incorporated. G-BAM, thirdly,
allows a smoother BAM policy transition among existing policy alternatives
resulting from MAM, RDM and AllocTC-Sharing adoption independently. The paper
focuses on the first characteristics of G-BAM which is to reproduce MAM, RDM
and AllocTC-Sharing behaviors. As such, the required configuration to achieve
MAM, RDM and AllocTC-Sharing behaviors is presented followed by a proof of
concept. Authors argue that the G-BAM reproducibility characteristics may
improve overall network resource utilization under distinct traffic profiles.


  Rod packings in the 3-torus encode information of some crystal structures in
crystallography. They can be viewed as links in the 3-torus, and tools from
3-manifold geometry and topology can be used to study their complements. In
this paper, we initiate the use of geometrisation to study such packings. We
analyse the geometric structures of the complements of simple rod packings, and
find families that are hyperbolic and Seifert fibred.


  We study coherent photoassociation, phenomena analogous to coherent optical
transients in few-level systems, which may take place in photoassociation of an
atomic Bose-Einstein condensate but not in a nondegenerate gas. We develop a
second-quantized Hamiltonian to describe photoassociation, and apply the
Hamiltonian both in the momentum representation and in the position
representation (field theory). Solution of the two-mode problem including only
one mode each for the atomic and molecular condensates displays analogs of Rabi
oscillations and rapid adiabatic passage. A classical version of the field
theory for atoms and molecules is used to demonstrate that, in the presence of
photoassociating light, a joint-atom molecule is unstable against growth of
density fluctuations. Experimental complications, including spontaneous
emission and unwanted "rogue" photodissociation from a photoassociated molecule
are analyzed. A two-color Raman scheme is studied as a method to set up an
effective two-mode scheme with reduced spontaneous emission losses. We discuss
photoassociation rates and photoassociation Rabi frequencies for high-lying
vibrational states in alkalis both on the basis of molecular-structure
calculations, and by comparing with an experiment [Wynar et al., Science 287,
1016 (2000)].


  The ability to control the motion of mechanical systems through its
interaction with light has opened the door to a plethora of applications in
fundamental and applied physics. With experiments routinely reaching the
quantum regime, the focus has now turned towards creating and exploiting
interesting non-classical states of motion and entanglement in optomechanical
systems. Quantumness has also shifted from being the very reason why
experiments are constructed to becoming a resource for the investigation of
fundamental physics and the creation of quantum technologies. Here, by focusing
on opto- and electromechanical platforms we review recent progress in quantum
state preparation and entanglement of mechanical systems, together with
applications to signal processing and transduction, quantum sensing,
topological physics, as well as small-scale thermodynamics.


  The NPDGamma experiment aims to measure the parity-odd correlation between
the neutron spin and the direction of the emitted photon in neutron-proton
capture. A parity violating asymmetry (to be measured to 10$^{-8}$) from this
process can be directly related to the strength of the hadronic weak
interaction between nucleons, specifically the $\Delta$I=1 contribution. As
part of the commissioning runs on the Fundamental Neutron Physics beamline at
the Spallation Neutron Source (SNS) at ORNL, the gamma-ray asymmetries from the
parity-violating capture of cold neutrons on $^{35}$Cl and $^{27}$Al were
measured, to check for systematic effects, false asymmetries, and backgrounds.
Early this year, the parahydrogen target for the production run of NPDGamma was
commissioned. Preliminary results for the commissioning measurements with
$^{35}$Cl and $^{27}$Al will be presented as well as first results of the
hydrogen run.


  At this summer school, I have tried to describe a general approach to quantum
transport problems based on the Non-equilibrium Green Function (NEGF) method .
I will not repeat this treatment here. Instead I will use this article to draw
attention to a core issue in quantum transport and how it is modeled within the
NEGF method. Specifically, I will discuss what constitutes a dephasing process
and how the standard descriptions may need to be extended to include what I
will call hot spin effects. These involve a number of subtle issues that tend
to get hidden in a purely formal description. So I have chosen instead to
illustrate the concepts using a concrete device, which is specially engineered
to enhance its sensitivity to spin dephasing and hot spin effects.


  Quasielastic scattering excitation function at large backward angle has been
measured for the weakly bound system, $^{7}$Li+$^{159}$Tb at energies around
the Coulomb barrier. The corresponding quasielastic barrier distribution has
been derived from the excitation function, both including and excluding the
$\alpha$-particles produced in the reaction. The centroid of the barrier
distribution obtained after inclusion of $\alpha$-particles was found to be
shifted higher in energy, compared to the distribution excluding the $\alpha
$-particles. The quasielastic data, excluding the $\alpha$-particles, have been
analyzed in the framework of continuum discretized coupled channel
calculations. The quasielastic barrier distribution for $^{7}$Li+$^{159}$Tb,
has also been compared with the fusion barrier distribution for the system.


  Given a power-bounded operator $T$, the theorem of Katznelson and Tzafriri
states that $\|T^n(I-T)\|\to0$ as $n\to\infty$ if and only if the spectrum
$\sigma(T)$ of $T$ intersects the unit circle $\mathbb{T}$ in at most the point
1. This paper investigates the rate at which decay takes place when
$\sigma(T)\cap\mathbb{T}=\{1\}$. The results obtained lead in particular to
both upper and lower bounds on this rate of decay in terms of the growth of the
resolvent operator $R(\mathrm{e}^{\mathrm{i}\theta},T)$ as $\theta\to0$. In the
special case of polynomial resolvent growth, these bounds are then shown to be
optimal for general Banach spaces but not in the Hilbert space case.


  This work investigates the vulnerability of Gaussian Mixture Model (GMM)
i-vector based speaker verification systems to adversarial attacks, and the
transferability of adversarial samples crafted from GMM i-vector based systems
to x-vector based systems. In detail, we formulate the GMM i-vector system as a
scoring function of enrollment and testing utterance pairs. Then we leverage
the fast gradient sign method (FGSM) to optimize testing utterances for
adversarial samples generation. These adversarial samples are used to attack
both GMM i-vector and x-vector systems. We measure the system vulnerability by
the degradation of equal error rate and false acceptance rate. Experiment
results show that GMM i-vector systems are seriously vulnerable to adversarial
attacks, and the crafted adversarial samples prove to be transferable and pose
threats to neuralnetwork speaker embedding based systems (e.g. x-vector
systems).


  A historical overview is given on the basic results which appeared by the
year 1926 concerning Einstein's fluctuation formula of black-body radiation, in
the context of light-quanta and wave-particle duality. On the basis of the
original publications (from Planck's derivation of the black-body spectrum and
Einstein's introduction of the photons up to the results of Born, Heisenberg
and Jordan on the quantization of a continuum) a comparative study is presented
on the first line of thoughts that led to the concept of quanta. The nature of
the particle-like fluctuations and the wave-like fluctuations are analysed by
using several approaches. With the help of the classical probability theory, it
is shown that the infinite divisibility of the Bose distribution leads to the
new concept of classical poissonian photo-multiplets or to the binary
photo-multiplets of fermionic character. As an application, Einstein's
fluctuation formula is derived as a sum of fermion type fluctuations of the
binary photo-multiplets.


  Generalised Nambu-Jona-Lasinio model for QCD is considered at finite
temperatures in the framework of a real-time formalism. The proposed approach
allows one to study various properties of the model at T>0, such as chiral
symmetry breaking and restoration, properties of the bound-state spectrum, and
so on.


  We propose a differentiable imaging framework to address uncertainty in
measurement coordinates such as sensor locations and projection angles. We
formulate the problem as measurement interpolation at unknown nodes supervised
through the forward operator. To solve it we apply implicit neural networks,
also known as neural fields, which are naturally differentiable with respect to
the input coordinates. We also develop differentiable spline interpolators
which perform as well as neural networks, require less time to optimize and
have well-understood properties. Differentiability is key as it allows us to
jointly fit a measurement representation, optimize over the uncertain
measurement coordinates, and perform image reconstruction which in turn ensures
consistent calibration. We apply our approach to 2D and 3D computed tomography,
and show that it produces improved reconstructions compared to baselines that
do not account for the lack of calibration. The flexibility of the proposed
framework makes it easy to extend to almost arbitrary imaging problems.


  we can establish an entanglement criteria from skew information. our
criterion is independent of Local Uncertainty Relations.


  For a character of the absolute Galois group of a complete discrete valuation
field, we define a lifting of the refined Swan conductor, using higher
dimensional class field theory.


  Transformer structures have demonstrated outstanding skills in the deep
learning space recently, significantly increasing the accuracy of models across
a variety of domains. Researchers have started to question whether such a
sophisticated network structure is actually necessary and whether equally
outstanding results can be reached with reduced inference cost due to its
complicated network topology and high inference cost. In order to prove the
Mixer's efficacy on three datasets Speech Commands, UrbanSound8k, and CASIA
Chinese Sentiment Corpus this paper applies amore condensed version of the
Mixer to an audio classification task and conducts comparative experiments with
the Transformer-based Audio Spectrogram Transformer (AST)model. In addition,
this paper conducts comparative experiments on the application of several
activation functions in Mixer, namely GeLU, Mish, Swish and Acon-C.
Further-more, the use of various activation functions in Mixer, including GeLU,
Mish, Swish, and Acon-C, is compared in this research through comparison
experiments. Additionally, some AST model flaws are highlighted, and the model
suggested in this study is improved as a result. In conclusion, a model called
the Audio Spectrogram Mixer, which is the first model for audio classification
with Mixer, is suggested in this study and the model's future directions for
improvement are examined.


  Statistical agencies and other institutions collect data under the promise to
protect the confidentiality of respondents. When releasing microdata samples,
the risk that records can be identified must be assessed. To this aim, a widely
adopted approach is to isolate categorical variables key to the identification
and analyze multi-way contingency tables of such variables. Common disclosure
risk measures focus on sample unique cells in these tables and adopt parametric
log-linear models as the standard statistical tools for the problem. Such
models often have to deal with large and extremely sparse tables that pose a
number of challenges to risk estimation. This paper proposes to overcome these
problems by studying nonparametric alternatives based on Dirichlet process
random effects. The main finding is that the inclusion of such random effects
allows us to reduce considerably the number of fixed effects required to
achieve reliable risk estimates. This is studied on applications to real data,
suggesting, in particular, that our mixed models with main effects only produce
roughly equivalent estimates compared to the all two-way interactions models,
and are effective in defusing potential shortcomings of traditional log-linear
models. This paper adopts a fully Bayesian approach that accounts for all
sources of uncertainty, including that about the population frequencies, and
supplies unconditional (posterior) variances and credible intervals.


  The standard method of "measuring" quantum wavefunction is the technique of
{\it indirect} quantum state tomography. Owing to conceptual novelty and
possible advantages, an alternative {\it direct} scheme was proposed and
demonstrated recently in quantum optics system. In this work we present a study
on the direct scheme of measuring qubit state in the circuit QED system, based
on weak measurement and weak value concepts. To be applied to generic parameter
conditions, our formulation and analysis are carried out for finite strength
weak measurement, and in particular beyond the bad-cavity and weak-response
limits. The proposed study is accessible to the present state-of-the-art
circuit-QED experiments.


  The formation of shocks within the solar atmosphere remains one of the few
observable signatures of energy dissipation arising from the plethora of
magnetohydrodynamic waves generated close to the solar surface. Active region
observations offer exceptional views of wave behavior and its impact on the
surrounding atmosphere. The stratified plasma gradients present in the lower
solar atmosphere allow for the potential formation of many theorized shock
phenomena. In this study, using chromospheric Ca II 854.2nm spectropolarimetric
data of a large sunspot, we examine fluctuations in the plasma parameters in
the aftermath of powerful shock events that demonstrate polarimetric reversals
during their evolution. Modern inversion techniques are employed to uncover
perturbations in the temperatures, line-of-sight velocities, and vector
magnetic fields occurring across a range of optical depths synonymous with the
shock formation. Classification of these non-linear signatures is carried out
by comparing the observationally-derived slow, fast, and Alfv\'en shock
solutions to the theoretical Rankine-Hugoniot relations. Employing over 200,000
independent measurements, we reveal that the Alfv\'en (intermediate) shock
solution provides the closest match between theory and observations at optical
depths of log(tau) = -4, consistent with a geometric height at the boundary
between the upper photosphere and lower chromosphere. This work uncovers
first-time evidence of the manifestation of chromospheric intermediate shocks
in sunspot umbrae, providing a new method for the potential thermalization of
wave energy in a range of magnetic structures, including pores, magnetic flux
ropes, and magnetic bright points.


  In the light of growing evidence that blazars are responsible for part of the
astrophysical very-high-energy neutrino flux detected by IceCube, models for
neutrino production through photo-pion interactions in blazar jets have been
developed. Evidence is also mounting that photon fields originating external to
the jet are strongly favored over the co-moving primary electron synchrotron
photon field as target for photo-pion interactions. Even though those external
photon fields appear highly anisotropic in the co-moving frame of the emission
region, current models usually consider neutrino production to occur
isotropically in the co-moving frame, resulting in a beaming pattern that is
identical to intrinsically isotropic synchrotron and synchrotron self-Compton
emission. In this paper, we derive the resulting beaming patterns of neutrinos
produced by interactions wich external photon fields, taking into account all
relevant anisotropy effects. It is shown that neutrino emission resulting from
photo-pion production on a stationary and isotropic (in the AGN rest frame)
external photon field is significantly more strongly beamed along the jet
direction than intrinsically isotropic emission. For the most highly beamed
sources, this implies that expected neutrino fluxes are grossly under-estimated
or jet-power requirements for the production of a given neutrino flux grossly
over-estimated when not accounting for the proper Doppler boosting and beaming
characteristics.


  The neutrino mass experiment KATRIN uses conversion electrons from the 32.2
keV transition of the nuclear isomer $^{\mathrm{83m}}$Kr for calibration.
Comparing the measured energies to the appropriate literature values allows for
an independent evaluation of the energy scale, but the uncertainties in some of
the literature values obtained by gamma spectroscopy are a limiting factor.
Building upon the already excellent linearity of KATRIN's energy scale, this
paper proposes a novel method for determining the $^{\mathrm{83m}}$Kr
transition energies via high-precision electron spectroscopy. Notably, the
method makes use of conversion electrons from the 41.6-keV direct transition of
$^{\mathrm{83m}}$Kr to its ground state in addition to conversion electrons
from the much more frequent cascade of a 32.2-keV and a 9.4-keV transition. By
implementing this method, KATRIN may be able to deliver order-of-magnitude
improvements in precision over current $^{\mathrm{83m}}$Kr transition energy
literature values.


  In this paper, for the first time a method is proposed to compute
electromagnetic effects in hadronic processes using lattice simulations. The
method can be applied, for example, to the leptonic and semileptonic decays of
light or heavy pseudoscalar mesons. For these quantities the presence of
infrared divergences in intermediate stages of the calculation makes the
procedure much more complicated than is the case for the hadronic spectrum, for
which calculations already exist. In order to compute the physical widths,
diagrams with virtual photons must be combined with those corresponding to the
emission of real photons. Only in this way do the infrared divergences cancel
as first understood by Bloch and Nordsieck in 1937. We present a detailed
analysis of the method for the leptonic decays of a pseudoscalar meson. The
implementation of our method, although challenging, is within reach of the
present lattice technology.


  A two Higgs doublet model with flavorful Yukawa structure, in which the two
doublets give mass to the third and the first two generations respectively, is
combined with the twin Higgs mechanism to stabilize the Higgs mass against
radiative corrections. We consider both a mirror twin and fraternal twin setup.
We identify Higgs signal strength measurements and the decay $B_s \to \mu\mu$
as the most important indirect constraints on the parameter space of the model.
We explore the collider phenomenology of the model and find that the heavy
Higgs in the visible sector can give a sizable number of displaced decays into
$b$-jets in regions of parameter space where the SM-like Higgs and the twin
Higgs do not provide any striking signatures.


  An approach to the description of kinetics which taking into account the
large-scale hydrodynamic transport processes for quantum Bose system is
proposed. The nonequilibrium statistical operator which consistently describes
both the kinetic and nonlinear hydrodynamic fluctuations in quantum liquid is
calculated. Using this operator the coupled equations for quantum one-particle
distribution function and functional of hydrodynamic variables: densities of
momentum, energies and number of particles are obtained.


  We study the 2-flavor Nambu--Jona-Lasinio (NJL) model at finite temperature,
$T$, and chemical potential, $\mu$, in the dimensional regularization. The pion
and sigma meson masses are calculated at finite $T$ and $\mu$. The color
superconductivity is also discussed in the extended NJL model. We obtain the
phase structure of the chiral and color symmetry in the dimensional
regularization and compare the results with ones obtained in the cut-off
regularization.


  We discuss how magnetic screening can be systematically included in a
self-consistent way for Chromodynamics at high temperatures. The resulting gap
equation, which gives the summation of self-energy iterations, is calculated to
one-loop order and leads to a nonzero value for the magnetic mass.


  Large datasets of sub-meter aerial imagery represented as orthophoto mosaics
are widely available today, and these data sets may hold a great deal of
untapped information. This imagery has a potential to locate several types of
features; for example, forests, parking lots, airports, residential areas, or
freeways in the imagery. However, the appearances of these things vary based on
many things including the time that the image is captured, the sensor settings,
processing done to rectify the image, and the geographical and cultural context
of the region captured by the image. This thesis explores the use of deep
convolutional neural networks to classify land use from very high spatial
resolution (VHR), orthorectified, visible band multispectral imagery. Recent
technological and commercial applications have driven the collection a massive
amount of VHR images in the visible red, green, blue (RGB) spectral bands, this
work explores the potential for deep learning algorithms to exploit this
imagery for automatic land use/ land cover (LULC) classification.


  Polynomial Systems, or at least their algorithms, have the reputation of
being doubly-exponential in the number of variables [Mayr and Mayer, 1982],
[Davenport and Heintz, 1988]. Nevertheless, the Bezout bound tells us that that
number of zeros of a zero-dimensional system is singly-exponential in the
number of variables. How should this contradiction be reconciled?
  We first note that [Mayr and Ritscher, 2013] shows that the doubly
exponential nature of Gr\"{o}bner bases is with respect to the dimension of the
ideal, not the number of variables. This inspires us to consider what can be
done for Cylindrical Algebraic Decomposition which produces a
doubly-exponential number of polynomials of doubly-exponential degree.
  We review work from ISSAC 2015 which showed the number of polynomials could
be restricted to doubly-exponential in the (complex) dimension using McCallum's
theory of reduced projection in the presence of equational constraints. We then
discuss preliminary results showing the same for the degree of those
polynomials. The results are under primitivity assumptions whose importance we
illustrate.


  We use diagrammatic perturbation theory to construct an effective shell-model
operator for the neutrinoless double-beta decay of 82Se. The starting point is
the same Bonn-C nucleon-nucleon interaction that is used to generate the
Hamiltonian for recent shell-model calculations of double-beta decay. After
first summing high-energy ladder diagrams that account for short-range
correlations and then adding diagrams of low order in the G matrix to account
for longer-range correlations, we fold the two-body matrix elements of the
resulting effective operator with transition densities from the recent
shell-model calculation to obtain the overall nuclear matrix element that
governs the decay. Although the high-energy ladder diagrams suppress this
matrix element at very short distances as expected, they enhance it at
distances between one and two fermis, so that their overall effect is small.
The corrections due to longer-range physics are large, but cancel one another
so that the fully corrected matrix element is comparable to that produced by
the bare operator. This cancellation between large and physically distinct
low-order terms indicates the importance of a reliable nonperturbative
calculation.


  We apply the fusion procedure to a quantum Yang-Baxter algebra associated
with time-discrete integrable systems, notably integrable quantum mappings. We
present a general construction of higher-order quantum invariants for these
systems. As an important class of examples, we present the Yang-Baxter
structure of the Gel'fand-Dikii mapping hierarchy, that we have introduced in
previous papers, together with the corresponding explicit commuting family of
quantum invariants.


  Visual localization for planar moving robot is important to various indoor
service robotic applications. To handle the textureless areas and frequent
human activities in indoor environments, a novel robust visual localization
algorithm which leverages dense correspondence and sparse depth for planar
moving robot is proposed. The key component is a minimal solution which
computes the absolute camera pose with one 3D-2D correspondence and one 2D-2D
correspondence. The advantages are obvious in two aspects. First, the
robustness is enhanced as the sample set for pose estimation is maximal by
utilizing all correspondences with or without depth. Second, no extra effort
for dense map construction is required to exploit dense correspondences for
handling textureless and repetitive texture scenes. That is meaningful as
building a dense map is computational expensive especially in large scale.
Moreover, a probabilistic analysis among different solutions is presented and
an automatic solution selection mechanism is designed to maximize the success
rate by selecting appropriate solutions in different environmental
characteristics. Finally, a complete visual localization pipeline considering
situations from the perspective of correspondence and depth density is
summarized and validated on both simulation and public real-world indoor
localization dataset. The code is released on github.


  It is shown that under certain boundary conditions the virial theorem has to
be modified. We analyze the origin of the extra term and compute it in
particular examples. The Coulomb and harmonic oscillator with point interaction
have been studied in the light of this generalization of the virial theorem.


  Security and stability challenges in future power systems with high
penetration Inverter-Based Resources (IBR) have been anticipated as the main
barrier to decolonization. Grid-following IBRs may become unstable under small
disturbances in weak grids, while, during transient processes, system stability
and protection may be jeopardized due to the lack of sufficient Short-Circuit
Current (SCC). To solve these challenges and achieve decarbonization, the
future system has to be carefully planned. However, it remains unclear how both
small-signal and transient processes can be considered during the system
planning stage. In this context, this paper proposes a coordinated planning
model of different resources to enhance system-level stability. The system
strength and SCC constraints are analytically derived by considering the
different characteristics of synchronous units and IBRs, which are further
effectively linearized through a novel data-driven approach, where an active
sampling method is proposed to generate a representative data set. The
significant economic value of the proposed coordinated planning framework in
both system asset investment and system operation is demonstrated through
detailed case studies.


  We consider offsets of a union of convex objects. We aim for a filtration, a
sequence of nested cell complexes, that captures the topological evolution of
the offsets for increasing radii. We describe methods to compute a filtration
based on the Voronoi partition with respect to the given convex objects. We
prove that, in two and three dimensions, the size of the filtration is
proportional to the size of the Voronoi diagram. Our algorithm runs in
$\Theta(n \log{n})$ in the $2$-dimensional case and in expected time $O(n^{3 +
\epsilon})$, for any $\epsilon > 0$, in the $3$-dimensional case. Our approach
is inspired by alpha-complexes for point sets, but requires more involved
machinery and analysis primarily since Voronoi regions of general convex
objects do not form a good cover. We show by experiments that our approach
results in a similarly fast and topologically more stable method for computing
a filtration compared to approximating the input by point samples.


  In this article the Gordan theorem is applied to the thermodynamics of a
chemical reaction network at steady state. From a theoretical viewpoint it is
equivalent to the Clausius formulation of the second law for the out of
equilibrium steady states of chemical networks, i.e. it states that the
exclusion (presence) of closed reactions loops makes possible (impossible) the
definition of a thermodynamic potential and vice versa. On the computational
side, it reveals that calculating reactions free energy and searching
infeasible loops in flux states are dual problems whose solutions are
alternatively inconsistent. The relevance of this result for applications is
discussed with an example in the field of constraints-based modeling of
cellular metabolism where it leads to efficient and scalable methods to afford
the energy balance analysis.


  We compare the performance of a convolutional neural network (CNN) trained on
jet images with dense neural networks (DNNs) trained on n-subjettiness
variables to study the distinguishing power of these two separate techniques
applied to top quark decays. We find that they perform almost identically and
are highly correlated once jet mass information is included, which suggests
they are accessing the same underlying information which can be intuitively
understood as being contained in 4-, 5-, 6-, and 8-body kinematic phase spaces
depending on the sample. This suggests both of these methods are highly useful
for heavy object tagging and provides a tentative answer to the question of
what the image network is actually learning.


  We apply effective field theory techniques to study several heavy quark
systems. The topics analysed include the singlet static QCD potential,
anomalous dimensions in SCET and a comprehensive study of semi-inclusive
radiative heavy quarkonium decays.


  Recent studies have shown that neural models can achieve high performance on
several sequence labelling/tagging problems without the explicit use of
linguistic features such as part-of-speech (POS) tags. These models are trained
only using the character-level and the word embedding vectors as inputs. Others
have shown that linguistic features can improve the performance of neural
models on tasks such as chunking and named entity recognition (NER). However,
the change in performance depends on the degree of semantic relatedness between
the linguistic features and the target task; in some instances, linguistic
features can have a negative impact on performance. This paper presents an
approach to jointly learn these linguistic features along with the target
sequence labelling tasks with a new multi-task learning (MTL) framework called
Gated Tasks Interaction (GTI) network for solving multiple sequence tagging
tasks. The GTI network exploits the relations between the multiple tasks via
neural gate modules. These gate modules control the flow of information between
the different tasks. Experiments on benchmark datasets for chunking and NER
show that our framework outperforms other competitive baselines trained with
and without external training resources.


  We report on the serendipitous discovery of the first central star of a
planetary nebula (PN) that mimics the helium- and nitrogen-rich WN sequence of
massive Wolf-Rayet (WR) stars. The central star of IC 4663 (PN G346.2-08.2) is
dominated by broad He II and N V emission lines which correspond to a [WN3]
spectral type. Unlike previous [WN] candidates, the surrounding nebula is
unambiguously a PN. At an assumed distance of 3.5 kpc, corresponding to a
stellar luminosity of 4000 Lsun, the V=16.9 mag central star remains 4-6 mag
fainter than the average luminosity of massive WN3 stars even out to an
improbable d=8 kpc. The nebula is typical of PNe with an elliptical morphology,
a newly discovered Asymptotic Giant Branch (AGB) halo, a relatively low
expansion velocity (v_exp=30 km/s) and a highly ionised spectrum with an
approximately Solar chemical abundance pattern. The [WN3] star is hot enough to
show Ne VII emission (T_*=140+/-20 kK) and exhibits a fast wind (v_infty=1900
km/s), which at d=3.5 kpc would yield a clumped mass loss rate of Mdot = 1.8 x
10^-8 Msun/yr with a small stellar radius (R_*=0.11 Rsun). Its atmosphere
consists of helium (95%), hydrogen (<2%), nitrogen (0.8%), neon (0.2%) and
oxygen (0.05%) by mass. Such an unusual helium-dominated composition cannot be
produced by any extant scenario used to explain the H-deficiency of post-AGB
stars. The O(He) central stars share a similar composition and the discovery of
IC 4663 provides the first evidence for a second He-rich/H-deficient post-AGB
evolutionary sequence [WN]->O(He). This suggests there is an alternative
mechanism responsible for producing the majority of H-deficient post-AGB stars
that may possibly be expanded to include other He-rich/H-deficient stars such
as R Coronae Borealis stars and AM Canum Venaticorum stars. The origin of the
unusual composition of [WN] and O(He) central stars remains unexplained.


  In the past few years, several attacks against the vulnerabilities of EOSIO
smart contracts have caused severe financial losses to this prevalent
blockchain platform. As a lightweight test-generation approach, grey-box
fuzzing can open up the possibility of improving the security of EOSIO smart
contracts. However, developing a practical grey-box fuzzer for EOSIO smart
contracts from scratch is time-consuming and requires a deep understanding of
EOSIO internals. In this work, we proposed AntFuzzer, the first highly
extensible grey-box fuzzing framework for EOSIO smart contracts. AntFuzzer
implements a novel approach that interfaces AFL to conduct AFL-style grey-box
fuzzing on EOSIO smart contracts. Compared to black-box fuzzing tools,
AntFuzzer can effectively trigger those hard-to-cover branches. It achieved an
improvement in code coverage on 37.5% of smart contracts in our benchmark
dataset. AntFuzzer provides unified interfaces for users to easily develop new
detection plugins for continually emerging vulnerabilities. We have implemented
6 detection plugins on AntFuzzer to detect major vulnerabilities of EOSIO smart
contracts. In our large-scale fuzzing experiments on 4,616 real-world smart
contracts, AntFuzzer successfully detected 741 vulnerabilities. The results
demonstrate the effectiveness and efficiency of AntFuzzer and our detection pl


  Neural Ordinary Differential Equations (NODEs) use a neural network to model
the instantaneous rate of change in the state of a system. However, despite
their apparent suitability for dynamics-governed time-series, NODEs present a
few disadvantages. First, they are unable to adapt to incoming data points, a
fundamental requirement for real-time applications imposed by the natural
direction of time. Second, time series are often composed of a sparse set of
measurements that could be explained by many possible underlying dynamics.
NODEs do not capture this uncertainty. In contrast, Neural Processes (NPs) are
a family of models providing uncertainty estimation and fast data adaptation
but lack an explicit treatment of the flow of time. To address these problems,
we introduce Neural ODE Processes (NDPs), a new class of stochastic processes
determined by a distribution over Neural ODEs. By maintaining an adaptive
data-dependent distribution over the underlying ODE, we show that our model can
successfully capture the dynamics of low-dimensional systems from just a few
data points. At the same time, we demonstrate that NDPs scale up to challenging
high-dimensional time-series with unknown latent dynamics such as rotating
MNIST digits.


  The availability of data in expressive styles across languages is limited,
and recording sessions are costly and time consuming. To overcome these issues,
we demonstrate how to build low-resource, neural text-to-speech (TTS) voices
with only 1 hour of conversational speech, when no other conversational data
are available in the same language. Assuming the availability of non-expressive
speech data in that language, we propose a 3-step technology: 1) we train an
F0-conditioned voice conversion (VC) model as data augmentation technique; 2)
we train an F0 predictor to control the conversational flavour of the
voice-converted synthetic data; 3) we train a TTS system that consumes the
augmented data. We prove that our technology enables F0 controllability, is
scalable across speakers and languages and is competitive in terms of
naturalness over a state-of-the-art baseline model, another augmented method
which does not make use of F0 information.


  Fast convolutions via transforms, either Winograd or FFT, had emerged as a
preferred way of performing the computation of convolutional layers, as it
greatly reduces the number of required operations. Recent work shows that, for
many layer structures, a well--designed implementation of fast convolutions can
greatly utilize modern CPUs, significantly reducing the compute time. However,
the generous amount of shared L3 cache present on modern CPUs is often
neglected, and the algorithms are optimized solely for the private L2 cache. In
this paper we propose an efficient `L3 Fusion` algorithm that is specifically
designed for CPUs with significant amount of shared L3 cache. Using the
hierarchical roofline model, we show that in many cases, especially for layers
with fewer channels, the `L3 fused` approach can greatly outperform standard 3
stage one provided by big vendors such as Intel. We validate our theoretical
findings, by benchmarking our `L3 fused` implementation against publicly
available state of the art.


  While consolidation strategies form the backbone of many supply chain
optimisation problems, exploitation of multi-tier material relationships
through consolidation remains an understudied area, despite being a prominent
feature of industries that produce complex made-to-order products. In this
paper, we propose an optimisation framework for exploiting multi-to-multi
relationship between tiers of a supply chain. The resulting formulation is
flexible such that quantity discounts, inventory holding, and transport costs
can be included. The framework introduces a new trade-off between tiers,
leading to cost reductions in one tier but increased costs in the other, which
helps to reduce the overall procurement cost in the supply chain. A mixed
integer linear programming model is developed and tested with a range of small
to large-scale test problems from aerospace manufacturing. Our comparison to
benchmark results shows that there is indeed a cost trade-off between two
tiers, and that its reduction can be achieved using a holistic approach to
reconfiguration. Costs are decreased when second tier fixed ordering costs and
the number of machining options increase. Consolidation results in reduced
inventory holding costs in all scenarios. Several secondary effects such as
simplified supplier selection may also be observed.


  B\"uchi Automata on infinite words present many interesting problems and are
used frequently in program verification and model checking. A lot of these
problems on B\"uchi automata are computationally hard, raising the question if
a learning-based data-driven analysis might be more efficient than using
traditional algorithms. Since B\"uchi automata can be represented by graphs,
graph neural networks are a natural choice for such a learning-based analysis.
In this paper, we demonstrate how graph neural networks can be used to reliably
predict basic properties of B\"uchi automata when trained on automatically
generated random automata datasets.


  We use the score-based transport modeling method to solve the mean-field
Fokker-Planck equations, which we call MSBTM. We establish an upper bound on
the time derivative of the Kullback-Leibler (KL) divergence to MSBTM numerical
estimation from the exact solution, thus validates the MSBTM approach. Besides,
we provide an error analysis for the algorithm. In numerical experiments, we
study two types of mean-field Fokker-Planck equation and their corresponding
dynamics of particles in interacting systems. The MSBTM algorithm is
numerically validated through qualitative and quantitative comparison between
the MSBTM solutions, the results of integrating the associated stochastic
differential equation and the analytical solutions if available.


  We have imaged two normal, non-coronal, infrared-bright K giants, Alpha Tau
and Alpha Boo, in the 1.4-mm and 2.8-mm continuum using the Berkeley Illinois
Maryland Association millimeter array. These stars have been used as important
absolute calibrators for several infrared infrared satellites. Our goals are:
(1) to establish whether these stars radiate as simple photospheres or possess
long-wavelength chromospheres; and (2) to make a connection between millimeter
wave and far-infrared absolute flux calibrations. To accomplish these goals we
also present Infrared Space Observatory Long Wavelength Spectrometer
measurements of both these K giants. The far-infrared and millimeter continuum
radiation is produced in the vicinity of the temperature minimum in Alpha Tau
and Alpha Boo. We find that current photospheric models predict fluxes in
reasonable agreement with those observed for wavelengths which sample the upper
photosphere, namely <=125 microns in Alpha Tau and Alpha Boo. We clearly detect
chromospheric radiation from both stars by 2.8mm (by 1.4mm in the case of Alpha
Boo). Only additional observations can determine precisely where beyond 125
microns the purely radiative models fail. Until then, purely radiative models
for these stars can only be used with confidence for calibration purposes below
125 microns.


  We study the gravitational influence of very large scale structures, as
traced by clusters of galaxies, on the Local Group [LG] motion and the large
scale flows. We derive from the distribution of Abell clusters within
$300~$Mpc/h the overdensity field on a 3--D grid of spacing $5~$Mpc/h, then we
solve the Poisson equation for the peculiar potential and finally obtain the
peculiar velocity field. Quite interestingly, from this global solution we: i)
recover within $\sim 10^o$ the direction of the LG motion in the Cosmic
Microwave Background [CMB] frame, ii find that the Great Attractor itself moves
wrt to the CMB frame, iii) derive $\beta_c^{-1} \equiv b_c \Omega_0^{-0.6} =
5.3 \pm 0.20$ from a preliminary comparison with the Mark~II catalog of
peculiar velocities, iv) derive estimates for the bulk flow in spheres which
fairly agree with the level derived from POTENT and the Spiral samples, v) find
that the Lauer \& Postman [L\&P] bulk flow has too a large amplitude to be in
agreement with our results.


  In this paper we obtain the Fourier Transform of a continuous gravitational
wave. We have analysed the data set for (i) one year observation time and (ii)
arbitrary observation time, for arbitrary location of detector and source
taking into account the effects arising due to rotational as well as orbital
motion of the earth. As an application of the transform we considered spin down
and N-component signal analysis.


  Recently, superconductivity was discovered at very low densities in slightly
misaligned graphene multilayers. Surprisingly, despite extremely low electronic
density (about $10^{-4}$ electrons per unit cell), these systems realize
strong-coupling superconductivity, with the transition temperature being a
large fraction of the Fermi energy ($T_c\sim 0.1 \epsilon_F$). Here we propose
a qualitative explanation for this remarkable phenomenon, highlighting
similarities and qualitative differences with the conventional uniform
high-density superconductivity. Most importantly, we find that periodic
superimposed potential generically enhances local interactions relative to
nonlocal (for instance, Coulomb) interactions. In addition, the density of
states is enhanced as well, exponentially in modulation strength for low lying
bands in some cases. Combination of these two effects makes moir\'e systems
natural intermediate or strong-coupled superconductors, with potential for very
high transition temperatures.


  A scenario for the origin of the system PSR B1757-24/supernova remnant (SNR)
G5.4-1.2 is proposed. It is suggested that both objects are the remnants of a
supernova (SN) that exploded within a pre-existing bubble blown-up by a runaway
massive star (the SN progenitor) during the final (Wolf-Rayet) phase of its
evolution. This suggestion implies that (a) the SN blast centre was
significantly offset from the geometric centre of the wind-blown bubble (i.e.
from the centre of the future SNR), (b) the bubble was surrounded by a massive
wind-driven shell, and (c) the SN blast wave was drastically decelerated by the
interaction with the shell. Therefore, one can understand how the relatively
young and low-velocity pulsar PSR B1757-24 was able to escape from the
associated SNR G5.4-1.2 and why the inferred vector of pulsar transverse
velocity does not point away from the geometric centre of the SNR. A possible
origin of the radio source G5.27-0.9 (located between PSR B1757-24 and the SNR
G5.4-1.2) is proposed. It is suggested that G5.27-0.9 is a lobe of a low Mach
number (\simeq 1.7) jet of gas outflowing from the interior of G5.4-1.2 through
the hole bored in the SNR's shell by the escaping pulsar. It is also suggested
that the non-thermal emission of the comet-shaped pulsar wind nebula originates
in the vicinity of the termination shock and in the cylindric region of
subsonically moving shocked pulsar wind. The role of magnetized wind-driven
shells (swept-up during the Wolf-Rayet phase from the ambient interstellar
medium with the regular magnetic field) in formation of elongated axisymmetric
SNRs is discussed.


  We report the quasi-simultaneous INTEGRAL, SWIFT, and NuSTAR observations
showing spectral state transitions in the neutron star low mass X-ray binary
1RXS J180408.9-342058 during its 2015 outburst. We present results of the
analysis of high-quality broad energy band (0.8-200 keV) data in three
different spectral states: high/soft, low/very-hard, and transitional state.
The broad band spectra can be described in general as the sum of thermal
Comptonization and reflection due to illumination of an optically-thick
accretion disc. During the high/soft state, blackbody emission is generated
from the accretion disc and the surface of the neutron star. This emission,
measured at a temperature of kTbb ~1.2 keV, is then Comptonized by a thick
corona with an electron temperature of ~2.5 keV. For the transitional and
low/very-hard state, the spectra are successfully explained with emission from
a double Comptonizing corona. The first component is described by thermal
Comptonization of seed disc/neutron-star photons (kTbb ~1.2 keV) by a cold
corona cloud with kT e ~8-10 keV, while the second one originates from lower
temperature blackbody photons (kTbb~0.1 keV) Comptonized by a hot corona
(kTe~35 keV). Finally, from NuSTAR observations, there is evidence that the
source is a new clocked burster. The average time between two successive X-ray
bursts corresponds to ~7.9 ks and ~4.0 ks when the persistent emission
decreases by a factor ~2, moving from very hard to transitional state. The
accretion rate and the decay time of the X-ray bursts longer than ~30 s suggest
that the thermonuclear emission is due to mixed H/He burning triggered by
thermally unstable He ignition.


  Lagrangian multiforms provide a variational framework to describe integrable
hierarchies. The case of Lagrangian $1$-forms covers finite-dimensional
integrable systems. We use the theory of Lie dialgebras introduced by
Semenov-Tian-Shansky to construct a Lagrangian $1$-form. Given a Lie dialgebra
associated with a Lie algebra $\mathfrak{g}$ and a collection $H_k$,
$k=1,\dots,N$, of invariant functions on $\mathfrak{g}^*$, we give a formula
for a Lagrangian multiform describing the commuting flows for $H_k$ on a
coadjoint orbit in $\mathfrak{g}^*$. We show that the Euler-Lagrange equations
for our multiform produce the set of compatible equations in Lax form
associated with the underlying $r$-matrix of the Lie dialgebra. We establish a
structural result which relates the closure relation for our multiform to the
Poisson involutivity of the Hamiltonians $H_k$ and the so-called ``double
zero'' on the Euler-Lagrange equations. The construction is extended to a
general coadjoint orbit by using reduction from the free motion of the
cotangent bundle of a Lie group. We illustrate the dialgebra construction of a
Lagrangian multiform with the open Toda chain and the rational Gaudin model.
The open Toda chain is built using two different Lie dialgebra structures on
$\mathfrak{sl}(N+1)$. The first one possesses a non-skew-symmetric $r$-matrix
and falls within the Adler-Kostant-Symes scheme. The second one possesses a
skew-symmetric $r$-matrix. In both cases, the connection with the well-known
descriptions of the chain in Flaschka and canonical coordinates is provided.


  A self-consistent, non-perturbative scheme of approximation is proposed for
arbitrary interacting quantum systems by generalization of the Hartree
method.The scheme consists in approximating the original interaction term
$\lambda H_I$ by a suitable 'potential' $\lambda V(\phi)$ which satisfies the
following two requirements: (i) the 'Hartree Hamiltonian' $H_o$ generated by
$V(\phi)$ is exactly solvable i.e, the eigen states $|n>$ and the eigenvalues
$E_n$ are known and (ii) the 'quantum averages' of the two are equal, i.e. $<
n|H_I|n>$ = $<n|V(\phi)|n>$ for arbitrary $'n '$. The leading-order results for
$|n>$ and $E_n$, which are already accurate, can be systematically improved
further by the development of a 'Hartree-improved perturbation theory' (HIPT)
with $H_o$ as the unperturbed part and the modified interaction:$\lambda
H^{\prime} \equiv \lambda (H_I-V)$ as the perturbation. The HIPT is assured of
rapid convergence because of the 'Hartree condtion' : $<n| H'| n> = 0$. This is
in contrast to the naive perturbation theory developed with the original
interaction term $\lambda H_I$ chosen as the perturbation, which diverges even
for infinitesimal $\lambda$ ! The structure of the Hartree vacuum is shown to
be highly non-trivial. Application of the method to the anharmonic-and
double-well quartic-oscillators, anharmonic- sextic and octic- oscillators
leads to very accurate results for the energy levels. In case of $\lambda
\phi^{4}$ quantum field theory, the method reproduces, in the leading order,
the results of Gaussian approximation, which can be improved further by the
HIPT. We study the vacuum structure, renormalisation and stability of the
theory in GHA.


  The paper shows an analysis of the large-scale distribution of galaxy spin
directions of 739,286 galaxies imaged by DES. The distribution of the spin
directions of the galaxies exhibits a large-scale dipole axis. Comparison of
the location of the dipole axis to a similar analysis with data from SDSS,
Pan-STARRS, and DESI Legacy Survey shows that all sky surveys exhibit dipole
axes within 52$^o$ or less from each other, well within 1$\sigma$ error. While
non-random distribution is unexpected, the findings are consistent across all
sky surveys, regardless of the telescope or whether the data were annotated
manually or automatically. Possible errors that can lead to the observation are
discussed. The paper also discusses previous studies showing opposite
conclusions,and analyzes the decisions that led to these results. Although the
observation is provocative, and further research will be required, the existing
evidence justifies to consider the contention that galaxy spin directions as
observed from Earth are not necessarily randomly distributed. Possible
explanations can be related to mature cosmological theories, but also to the
internal structure of galaxies.


  The optical color distributions of globular clusters (GCs) in most large
elliptical galaxies are bimodal. Based on the assumed linear relationship
between GC colors and their metallicities, the bimodality has been taken as
evidence of two GC subsystems with different metallicities in each galaxy and
led to a number of theories in the context of galaxy formation. More recent
observations and modeling of GCs, however, suggest that the color-metallicity
relations (CMRs) are inflected, and thus colors likely trace metallicities in a
nonlinear manner. The nonlinearity could produce bimodal color distributions
from a broad underlying metallicity spread, even if it is unimodal. Despite the
far-reaching implications, whether CMRs are nonlinear and whether the
nonlinearity indeed causes the color bimodality are still open questions. Given
that the spectroscopic refinement of CMRs is still very challenging, we here
propose a new photometric technique to probe the possible nonlinear nature of
CMRs. In essence, a color distribution of GCs is a "projected" distribution of
their metallicities. Since the form of CMRs hinges on which color is used, the
shape of color distributions varies depending significantly on the colors.
Among other optical colors, the u-band related colors (e.g., u - g and u - z)
are theoretically predicted to exhibit significantly less inflected CMRs than
other preferred CMRs (e.g., for g - z). As a case study, we performed the
HST/WFPC2 archival u-band photometry for the M87 (NGC 4486) GC system with
confirmed color bimodality. We show that the u-band color distributions are
significantly different from that of g - z, and consistent with our model
predictions. With more u-band measurements, this method will support or rule
out the nonlinear-CMR scenario for the origin of GC color bimodality with high
confidence. [Abridged]


  Decision making is a human process that is a fundamental part of competition.
As a realisation of decision making, Command and Control, or C2, has been
studied in the literature for adversarial populations, yet these models do not
explicitly capture competition. Our work here seeks to enrich such competition
models by extending ecologically inspired population models to include decision
dynamics through coupling with a nonlinear system of oscillators (the Kuramoto
equation) to model the action-perception cycle in decision making. Through
asymmetric competition models of increasing complexity, we highlight the
importance of competitive agility and decision making processes necessary for a
population to be successful.


  We investigate the electron addition spectrum in a class of Hubbard-like
models which describe arrays of coupled quantum dots. Interdot tunneling leads
to a sequence of two phase transitions separating a region of collective
Coulomb blockade from a region where the Coulomb blockade of individual dots is
maintained and a region where the Coulomb blockade is destroyed altogether.
Observable experimental consequences of our theory are discussed.


  Complex Event Processing (CEP) is an event processing paradigm to perform
real-time analytics over streaming data and match high-level event patterns.
Presently, CEP is limited to process structured data stream. Video streams are
complicated due to their unstructured data model and limit CEP systems to
perform matching over them. This work introduces a graph-based structure for
continuous evolving video streams, which enables the CEP system to query
complex video event patterns. We propose the Video Event Knowledge Graph
(VEKG), a graph driven representation of video data. VEKG models video objects
as nodes and their relationship interaction as edges over time and space. It
creates a semantic knowledge representation of video data derived from the
detection of high-level semantic concepts from the video using an ensemble of
deep learning models. A CEP-based state optimization - VEKG-Time Aggregated
Graph (VEKG-TAG) is proposed over VEKG representation for faster event
detection. VEKG-TAG is a spatiotemporal graph aggregation method that provides
a summarized view of the VEKG graph over a given time length. We defined a set
of nine event pattern rules for two domains (Activity Recognition and Traffic
Management), which act as a query and applied over VEKG graphs to discover
complex event patterns. To show the efficacy of our approach, we performed
extensive experiments over 801 video clips across 10 datasets. The proposed
VEKG approach was compared with other state-of-the-art methods and was able to
detect complex event patterns over videos with F-Score ranging from 0.44 to
0.90. In the given experiments, the optimized VEKG-TAG was able to reduce 99%
and 93% of VEKG nodes and edges, respectively, with 5.19X faster search time,
achieving sub-second median latency of 4-20 milliseconds.


  The set of solutions to the AdS$_3$ Einstein gravity with Brown-Henneaux
boundary conditions is known to be a family of metrics labeled by two arbitrary
periodic functions, respectively left and right-moving. It turns out that there
exists an appropriate presymplectic form which vanishes on-shell. This promotes
this set of metrics to a phase space in which the Brown-Henneaux asymptotic
symmetries become symplectic symmetries in the bulk of spacetime. Moreover, any
element in the phase space admits two global Killing vectors. We show that the
conserved charges associated with these Killing vectors commute with the
Virasoro symplectic symmetry algebra, extending the Virasoro symmetry algebra
with two $U(1)$ generators. We discuss that any element in the phase space
falls into the coadjoint orbits of the Virasoro algebras and that each orbit is
labeled by the $U(1)$ Killing charges. Upon setting the right-moving function
to zero and restricting the choice of orbits, one can take a near-horizon
decoupling limit which preserves a chiral half of the symplectic symmetries.
Here we show two distinct but equivalent ways in which the chiral Virasoro
symplectic symmetries in the near-horizon geometry can be obtained as a limit
of the bulk symplectic symmetries.


  Using Krichever-Phong's universal formula, we show that a multiplicative
representation linearizes Sklyanin quadratic brackets for a multi-pole Lax
function with a spectral parameter. The spectral parameter can be either
rational or elliptic. As a by-product, we obtain an extension of a Sklyanin
algebra in the elliptic case. Krichever-Phong's formula provides a hierarchy of
symplectic structures, and we show that there exists a non-trivial cubic
bracket in Sklyanin's case.


  While a bit is the fundamental unit of binary classical information, a qubit
is the fundamental unit of quantum information. In quantum information
processing (QIP), it is customary to call the qubits under study as system
qubits, and the additional qubits as ancillary qubits. In this thesis, I
describe various schemes to exploit the ancillary qubits to efficiently perform
many QIP tasks and their experimental demonstrations in nuclear magnetic
resonance (NMR) systems. Particularly, we have showed that, in the presence of
sufficient ancillary qubits, it is possible to completely characterize a
general quantum state as well as a general quantum dynamics in a single
measurement. In addition, it is also possible to exploit ancillary qubits for
realizing noninvasive quantum measurements required for several experiments
related to quantum physics. I will also illustrate some interesting
applications of ancillary qubits in spectroscopy. At last, I describe an
experimental study of the efficiency of various dynamical decoupling sequences
for suppressing decoherence of single as well as multiple quantum coherences on
large spin-clusters. The experiments reveal the superior performance of the
recently introduced RUDD sequences in suppressing decoherence.


  Nuclear matrix elements (NMEs) for two-neutrino double-beta decay
($2\nu\beta\beta$) are studied in the framework of relativistic nuclear energy
density functional (REDF). The properties of nuclei involved in the decay are
obtained using the relativistic Hartree-Bardeen-Cooper-Schrieffer theory and
relevant nuclear transitions are described using the relativistic
proton-neutron quasiparticle random phase approximation based on relativistic
energy density functional (REDF-QRPA). Three effective interactions have been
employed, including density-dependent meson-exchange (DD-ME2) and point
coupling interactions (DD-PC1 and DD-PCX), and pairing correlations are
described consistently both in $T=1$ and $T=0$ channels using a separable
pairing interaction. The optimal values of $T=0$ pairing strength parameter
$V_{0pp}$ are constrained by the experimental data on $\beta$-decay half lives.
The $2\nu\beta\beta$ matrix elements and half-lives are calculated for several
nuclides experimentally known to undergo this kind of decay: $^{48}$Ca,
$^{76}$Ge, $^{82}$Se, $^{96}$Zr, $^{100}$Mo, $^{116}$Cd, $^{124}$Xe,
$^{128}$Te, $^{130}$Te, $^{136}$Xe and $^{150}$Nd. The model dependence of the
NMEs and their sensitivity on $V_{0pp}$ is investigated, and the NMEs obtained
using optimal values of $V_{0pp}$ are discussed in comparison to previous
studies. The results of the present work represent an important benchmark for
the future applications of the relativistic framework in studies of
neutrinoless double-beta decay.


  The generic changes of the electronic compressibility in systems which show
magnetic instabilities is studied. It is shown that, when going into the
ordered phase, the compressibility is reduced by an amount comparable to the
its original value, making charge instabilities also possible. We discuss,
within this framework, the tendency towards phase separation of the double
exchange systems, the pyrochlores, and other magnetic materials.


  Let $a\in\mathbb{R}$ denote an unknown stationary target with a known
distribution $\mu\in\mathcal{P(\mathbb{R}})$, the space of probability measures
on $\mathbb{R}$. A diffusive searcher $X(\cdot)$ sets out from the origin to
locate the target. The time to locate the target is $T_a=\inf\{t\ge0:
X(t)=a\}$. The searcher has a given constant diffusion rate $D>0$, but its
drift $b$ can be set by the search designer from a natural admissible class
$\mathcal{D}_\mu$ of drifts. Thus, the diffusive searcher is a Markov process
generated by the operator $L=\frac D2\frac{d^2}{dx^2}+b(x)\frac d{dx}$. %
equivalently, $X(\cdot)$ satisfies the stochastic differential equation
%$X(t)=W(t)+\int_0^tb(X(s))ds$, where $W(\cdot)$ is a standard Brownian motion.
For a given drift $b$, the expected time of the search is \begin{equation}
\int_{\mathbb{R}} (E^{(b)}_0T_a)\thinspace\mu(da). \end{equation} Our aim is to
minimize this expected search time over all admissible drifts
$b\in\mathcal{D}_\mu$. For measures $\mu$ that satisfy a certain balance
condition between their restriction to the positive axis and their restriction
to the negative axis, a condition satisfied, in particular, by all symmetric
measures, we can give a complete answer to the problem. We calculate the above
infimum explicitly, we classify the measures for which the infimum is attained,
and in the case that it is attained, we calculate the minimizing drift
explicitly. For measures that do not satisfy the balance condition, we obtain
partial results.


  The Kitaev model, which hosts a quantum spin liquid (QSL) in the ground
state, was originally defined on a two-dimensional honeycomb lattice, but can
be straightforwardly extended to any tricoordinate lattices in any spatial
dimensions. In particular, the three-dimensional (3D) extensions are of
interest as a realization of 3D QSLs, and some materials like
$\beta$-Li$_{2}$IrO$_{3}$, $\gamma$-Li$_2$IrO$_3$, and $\beta$-ZnIrO$_{3}$ were
proposed for the candidates. However, the phase diagrams of the models for
those candidates have not been fully elucidated, mainly due to the limitation
of numerical methods for 3D frustrated quantum spin systems. Here we study the
Kitaev-Heisenberg model defined on a 3D hyperhoneycomb lattice, by using the
pseudofermion functional renormalization group method. We show that the
ground-state phase diagram contains the QSL phases in the vicinities of the
pristine ferromagnetic and antiferromagnetic Kitaev models, in addition to four
magnetically ordered phases, similar to the two-dimensional honeycomb case. Our
results respect the four-sublattice symmetry inherent in the model, which was
violated in the previous study. Moreover, we also show how the phase diagram
changes with the anisotropy in the interactions. The results provide a
reference for the search of the hyperhoneycomb Kitaev materials.


  We show that F-manifolds with compatible connection $(\nabla,\circ,e)$ are
the geometric counterpart of integrable systems of quasilinear first order
evolutionary PDEs. We consider F-manifolds equipped with an Euler vector field
and assume that the operator $L=E\circ$ is regular. This generalises previous
results in the semisimple context. As an example we study regular F-manifolds
with compatible connection $(\nabla,\circ,e,E)$ associated with integrable
hierarchies obtained from the solutions of the equation $d\cdot d_L \,a_0=0$ by
applying the construction of [27]. We show that $n$-dimensional F-manifolds
associated to operators $L$ with $r\le n$ Jordan blocks $L_\alpha$ of size
$m_\alpha$ are classified by $n$ arbitrary functions of a single variable,
where each block $L_\alpha$ contributes with $m_\alpha$ functions of the
variable appearing in the diagonal of the block. In the case of a single Jordan
block of arbitrary size we show that flat connections $\nabla$ correspond to
linear solutions $a_0$. This generalises part of the construction of [31] where
special linear solutions were considered. We illustrate the construction in
dimensions $2,3,$ and $4$ for any choice of Jordan canonical form and any
choice of the corresponding solution $a_0$. In these dimensions we have that
linear solutions define bi-flat F-manifolds, and that the special linear
solutions studied in [31] are related to Riemannian F-manifolds with Killing
unit vector field. We conjecture that this is true in general.


  We combine a limited number of accurately measured transition frequencies in
hydrogen and deuterium, recent quantum electrodynamics (QED) calculations, and,
as an essential additional ingredient, a generalized least-squares analysis, to
obtain precise and optimal predictions for hydrogen and deuterium transition
frequencies. Some of the predicted transition frequencies have relative
uncertainties more than an order of magnitude smaller than that of the g-factor
of the electron, which was previously the most accurate prediction of QED.


  Recent times have witnessed sharp improvements in reinforcement learning
tasks using deep reinforcement learning techniques like Deep Q Networks, Policy
Gradients, Actor Critic methods which are based on deep learning based models
and back-propagation of gradients to train such models. An active area of
research in reinforcement learning is about training agents to play complex
video games, which so far has been something accomplished only by human
intelligence. Some state of the art performances in video game playing using
deep reinforcement learning are obtained by processing the sequence of frames
from video games, passing them through a convolutional network to obtain
features and then using recurrent neural networks to figure out the action
leading to optimal rewards. The recurrent neural network will learn to extract
the meaningful signal out of the sequence of such features. In this work, we
propose a method utilizing a transformer network which have recently replaced
RNNs in Natural Language Processing (NLP), and perform experiments to compare
with existing methods.


  The Northern European Enclosure Dam (NEED) is a hypothetical project to
prevent flooding in European countries following the rising ocean level due to
melting arctic glaciers. This project involves the construction of two large
dams between Scotland and Norway, as well as England and France. The
anticipated cost of this project is 250 to 500 billion euros. In this paper, we
present the simulation of the aftermath of flooding on the European coastline
caused by a catastrophic break of this hypothetical dam. From our simulation
results, we can observe that there is a traveling wave after the accident, with
a velocity of around 10 kilometers per hour, raising the sea level permanently
inside the dammed region. This observation implies a need to construct
additional dams or barriers protecting the northern coastline of the
Netherlands and the interior of the Baltic Sea. Our simulations have been
obtained using the following building blocks. First, a graph transformation
model was applied to generate an adaptive mesh approximating the topography of
the Earth. We employ the composition graph grammar model for breaking
triangular elements in the mesh without the generation of hanging nodes.
Second, the wave equation is formulated in a spherical latitude-longitude
system of coordinates and solved by a high-order time integration scheme using
the generalized $\alpha$ method.


  We give a probabilistic construction of a $3$-uniform hypergraph on $N$
vertices with independence number $O(\log N / \log \log N)$ in which there are
at most two edges among any four vertices. This bound is tight and solves a
longstanding open problem of Erd\H{o}s and Hajnal in Ramsey theory. We further
extend this result to prove tight bounds on various other hypergraph Ramsey
numbers.


  Given a graph property $\Phi$, we consider the problem
$\mathtt{EdgeSub}(\Phi)$, where the input is a pair of a graph $G$ and a
positive integer $k$, and the task is to decide whether $G$ contains a $k$-edge
subgraph that satisfies $\Phi$. Specifically, we study the parameterized
complexity of $\mathtt{EdgeSub}(\Phi)$ and of its counting problem
$\#\mathtt{EdgeSub}(\Phi)$ with respect to both approximate and exact counting.
We obtain a complete picture for minor-closed properties $\Phi$: the decision
problem $\mathtt{EdgeSub}(\Phi)$ always admits an FPT algorithm and the
counting problem $\#\mathtt{EdgeSub}(\Phi)$ always admits an FPTRAS. For exact
counting, we present an exhaustive and explicit criterion on the property
$\Phi$ which, if satisfied, yields fixed-parameter tractability and otherwise
$\#\mathsf{W[1]}$-hardness. Additionally, most of our hardness results come
with an almost tight conditional lower bound under the so-called Exponential
Time Hypothesis, ruling out algorithms for $\#\mathtt{EdgeSub}(\Phi)$ that run
in time $f(k)\cdot|G|^{o(k/\log k)}$ for any computable function $f$.
  As a main technical result, we gain a complete understanding of the
coefficients of toroidal grids and selected Cayley graph expanders in the
homomorphism basis of $\#\mathtt{EdgeSub}(\Phi)$. This allows us to establish
hardness of exact counting using the Complexity Monotonicity framework due to
Curticapean, Dell and Marx (STOC'17). Our methods can also be applied to a
parameterized variant of the Tutte Polynomial $T^k_G$ of a graph $G$, to which
many known combinatorial interpretations of values of the (classical) Tutte
Polynomial can be extended. As an example, $T^k_G(2,1)$ corresponds to the
number of $k$-forests in the graph $G$. Our techniques allow us to completely
understand the parametrized complexity of computing the evaluation of $T^k_G$
at every pair of rational coordinates $(x,y)$.


  A simple recipe is given for constructing a maximally sparse regular lattice
of spin-free post-1PN gravitational wave chirp templates subject to a given
minimal match constraint, using Tanaka-Tagoshi coordinates.


  The Parton-Hadron-String-Dynamics (PHSD) transport model is employed for p-Pb
collisions at $\sqrt{s_{NN}}=$ 5.02 TeV and compared to recent experimental
data from the LHC as well as to alternative models. We focus on the question of
initial state dynamics, i.e. if the initial state might be approximated by a
superposition of independent nucleon-nucleon collisions or should be considered
as a coherent gluon field as predicted within the color glass condensate (CGC)
framework. We find that the PHSD approach provides correlations between the
charged particle multiplicity at midrapidity and the number of participant
nucleons close to results from the CGC and differs substantially from results
calculated with independent Glauber initial conditions. However, a sizeable
difference is found between the PHSD approach and CGC models with respect to
the rapidity dependence of the average transverse momentum. Accordingly,
related measurements at LHC should allow to prove or disprove the presence of
coherent colour fields in the initial phase of the collisions.


  In this work, we are developing the theoretical prototype and improving the
technique for installing the Thermoelectric Generator (TEG) set up in
automobiles. We have considered a linear curve fit from a zigzag curve of
reported mass flow rate and temperature variation at the hot gas inlet.
Accordingly, the temperature of the coolant is also varied linearly at the
inlet from 300 K to 320 K and corresponding the mass flow rate of coolant.
Circular fin is installed around each circular layer of Thermoelectric
Materials (TEM) after the water jacket. The heat loss through each fin is
calculated as 24 W. Energy balance is done at each and every TEM and
correspondingly calculated the amount of power transferred through each segment
of TEG as 32 W. We have calculated the length of TEM sample for attaining the
respective temperature range for the hybrid of $Bi_2Te_3$ and $TiO_{1.1}$. This
calculation is done by considering the compatibility factor derived as $s
=\frac{\sqrt{1+ ZT}-1}{\alpha T}$ which is a ratio of current density to
conduction heat flux. The length obtained for this particular combination is
$\sim$8 mm. To this end, we have reported the efficiency with respect to mass
flow rate of hot flue gas from the automobile for different layers of TEG for
the above-mentioned combination. Here, we have explored the possibility of
installing a number of different layers TEG module which can be installed
throughout the lateral surface area of exhaust chamber. Thermal mismatching
criteria are also discussed at the adjoining surface of TEM because of high
temperature. To maintain the thermal expansion or contraction of TEM, spring
and bolt arrangement is provided, which is fixed over the aluminium oxide
ceramic substrate. For automobile, if temperature of source is considered as
800 K, so for the temperature range of 300 K to 800 K the ideal power output is
obtained as 58 W.


  A multiband CuO Hubbard model is studied which incorporates long-range (LR)
repulsive Coulomb interactions. In the atomic limit, it is shown that a
charge-transfer from copper to oxygen ions occurs as the strength of the LR
interaction is increased. The regime of phase separation becomes unstable, and
is replaced by a uniform state with doubly occupied oxygens. As the holes
become mobile a superfluid condensate is formed, as suggested by a numerical
analysis of pairing correlation functions and flux quantization. Although most
of the calculations are carried out on one dimensional chains, it is


  The presence of frozen-in or quenched disorder in a system can often modify
the nature of its phase transition. A particular instance of this phenomenon is
the so-called rounding effect: it has been shown in many cases that the
free-energy curve of the disordered system at its critical point is smoother
than that of the homogenous one. In particular some disordered systems do not
allow first-order transitions. We study this phenomenon for the pinning of a
renewal with stretched-exponential tails on a defect line (the distribution $K$
of the renewal increments satisfies $K(n) \sim c_K\exp(-n^{\alpha}),$
$\alpha\in (0,1)$) which has a first order transition when disorder is not
present. We show that the critical behavior of the disordered system depends on
the value of $\alpha$: when $\alpha>1/2$ the transition remains first order,
whereas the free-energy diagram is smoothed for $\alpha\le 1/2$. Furthermore we
show that the rounding effect is getting stronger when $\alpha$ diminishes.


  The paper studies the initial boundary value problem related to the dynamic
evolution of an elastic beam interacting with a substrate through an
elastic-breakable forcing term. This discontinuous interaction is aimed to
model the phenomenon of attachement-detachement of the beam occurring in
adhesion phenomena. We prove existence of solutions in energy space and exhibit
various counterexamples to uniqueness. Furthermore we characterize some
relavant features of the solutions, ruling the main effectes of the
nonlinearity due to the elasic-breakable term on the dynamical evolution, by
proving the linearization property according to \cite{G96} and an asymtotic
result pertaining the long time behavior.


  Distributed Space-Time Block Codes (DSTBCs) from Complex Orthogonal Designs
(CODs) (both square and non-square CODs other than the Alamouti design) are
known to lose their single-symbol ML decodable (SSD) property when used in
two-hop wireless relay networks using amplify and forward protocol. For such a
network, in this paper, a new class of high rate, training-embedded (TE) SSD
DSTBCs are constructed from TE-CODs. The proposed codes include the training
symbols in the structure of the code which is shown to be the key point to
obtain high rate as well as the SSD property. TE-CODs are shown to offer
full-diversity for arbitrary complex constellations. Non-square TE-CODs are
shown to provide higher rates (in symbols per channel use) compared to the
known SSD DSTBCs for relay networks with number of relays less than $10.$


  In this paper, I develop the Soldering formalism in a new domain - the
noncommutative planar field theories. The Soldering mechanism fuses two
distinct theories showing opposite or complimentary properties of some
symmetry, taking into account the interference effects. The above mentioned
symmetry is hidden in the composite (or soldered) theory. In the present work
it is shown that a pair of noncommutative Maxwell-Chern-Simons theories, having
opposite signs in their respective topological terms, can be consistently
soldered to yield the Proca model (Maxwell theory with a mass term) with
corrections that are at least quadratic in the noncommutativity parameter. We
further argue that this model can be thought of as the noncommutative
generalization of the Proca theory of ordinary spacetime. It is well-known that
abelian noncommutative gauge theory bears a close structural similarity with
non-abelian gauge theory. This fact is manifested in a non-trivial way if the
present work is compared with existing literature, where soldering of
non-abelian models are discussed. Thus the present work further establishes the
robustness of the soldering programme. The subtle role played by gauge
invariance, (or the lack of it), in the above soldering process, is revealed in
an interesting way.