  We investigate phase structure of the D (> 4)-dimensional gauged
Nambu-Jona-Lasinio (NJL) model with $\delta(=D-4)$ extra dimensions
compactified on TeV scale, based on the improved ladder Schwinger-Dyson (SD)
equation in the bulk. We assume that the bulk running gauge coupling in the SD
equation for the SU(N_c) gauge theory with N_f massless flavors is given by the
truncated Kaluza-Klein effective theory and hence has a nontrivial ultraviolet
fixed point (UVFP). We find the critical line in the parameter space of two
couplings, the gauge coupling and the four-fermion coupling, which is similar
to that of the gauged NJL model with fixed (walking) gauge coupling in four
dimensions. It is shown that in the presence of such walking gauge interactions
the four-fermion interactions become ``nontrivial'' even in higher dimensions,
similarly to the four-dimensional gauged NJL model. Such a nontriviality holds
only in the restricted region of the critical line (``nontrivial window'') with
the gauge coupling larger than a non-vanishing value (``marginal triviality
(MT)'' point), in contrast to the four-dimensional case where such a
nontriviality holds for all regions of the critical line except for the pure
NJL point. In the nontrivial window the renormalized effective potential yields
a nontrivial interaction which is conformal invariant. The exisitence of the
nontrivial window implies ``cutoff insensitivity'' of the physics prediction in
spite of the ultraviolet dominance of the dynamics. In the formal limit D -> 4,
the nontrivial window coincides with the known condition of the nontriviality
of the four-dimensional gauged NJL model, $9/(2N_c) < N_f - N_c < 9/2 N_c$.


  In this thesis, a multimodal biometric, secure encrypted data and encrypted
biometric encoded into the QR code-based biometric-passport authentication
method is proposed for national security applications. Firstly, using the
Extended Profile - Local Binary Patterns (EP-LBP), a Canny edge detector, and
the Scale Invariant Feature Transform (SIFT) algorithm with Image File
Information (IMFINFO) process, the facial mark size recognition is initially
achieved. Secondly, by using the Active Shape Model (ASM) into Active
Appearance Model (AAM) to follow the hand and infusion the hand geometry
characteristics for verification and identification, hand geometry recognition
is achieved. Thirdly, the encrypted biometric passport information that is
publicly accessible is encoded into the QR code and inserted into the
electronic passport to improve protection. Further, Personal information and
biometric data are encrypted by applying the Advanced Encryption Standard (AES)
and the Secure Hash Algorithm (SHA) 256 algorithm. It will enhance the
biometric passport security system.


  This is a brief sketch of the use of supernovae to measure cosmological
parameters. It traces the early work, the events surrounding the discovery and
verification of cosmic acceleration using SN Ia, and the efforts today to make
sound inferences about the nature of dark energy. The prospects for minimizing
systematics by using near-infrared observations in the supernova restframe are
emphasized. This could be an important point in the design of a JDEM that
employs supernovae to measure the history of cosmic expansion.


  A classical result of topological algebra states that any compact left
topological semigroup has an idempotent. We refine this by showing that any
compact left topological left semiring has a common, i.e. additive and
multiplicative simultaneously, idempotent. As an application, we partially
answer a question related to algebraic properties of ultrafilters over natural
numbers. Finally, we observe that similar arguments establish the existence of
common idempotents in much more general, non-associative universal algebras.


  Asymptotically good sequences of linear ramp secret sharing schemes have been
intensively studied by Cramer et al. in terms of sequences of pairs of nested
algebraic geometric codes. In those works the focus is on full privacy and full
reconstruction. In this paper we analyze additional parameters describing the
asymptotic behavior of partial information leakage and possibly also partial
reconstruction giving a more complete picture of the access structure for
sequences of linear ramp secret sharing schemes. Our study involves a detailed
treatment of the (relative) generalized Hamming weights of the considered
codes.


  Wild animals are commonly fitted with trackers that record their position
through time, to learn about their behaviour. Broadly, statistical models for
tracking data often fall into two categories: local models focus on describing
small-scale movement decisions, and global models capture large-scale spatial
distributions. Due to this dichotomy, it is challenging to describe
mathematically how animals' distributions arise from their short-term movement
patterns, and to combine data sets collected at different scales. We propose a
multiscale model of animal movement and space use based on the underdamped
Langevin process, widely used in statistical physics. The model is convenient
to describe animal movement for three reasons: it is specified in continuous
time (such that its parameters are not dependent on an arbitrary time scale),
its speed and direction are autocorrelated (similarly to real animal
trajectories), and it has a closed form stationary distribution that we can
view as a model of long-term space use. We use the common form of a resource
selection function for the stationary distribution, to model the environmental
drivers behind the animal's movement decisions. We further increase flexibility
by allowing movement parameters to be time-varying, e.g., to account for daily
cycles in an animal's activity. We formulate the model as a state-space model
and present a method of inference based on the Kalman filter. The approach
requires discretising the continuous-time process, and we use simulations to
investigate performance for various time resolutions of observation. The
approach works well at fine resolutions, though the estimated stationary
distribution tends to be too flat when time intervals between observations are
very long.


  We introduce the fully-dynamic conflict-free coloring problem for a set $S$
of intervals in $\mathbb{R}^1$ with respect to points, where the goal is to
maintain a conflict-free coloring for$S$ under insertions and deletions. A
coloring is conflict-free if for each point $p$ contained in some interval, $p$
is contained in an interval whose color is not shared with any other interval
containing $p$. We investigate trade-offs between the number of colors used and
the number of intervals that are recolored upon insertion or deletion of an
interval. Our results include:
  - a lower bound on the number of recolorings as a function of the number of
colors, which implies that with $O(1)$ recolorings per update the worst-case
number of colors is $\Omega(\log n/\log\log n)$, and that any strategy using
$O(1/\varepsilon)$ colors needs $\Omega(\varepsilon n^{\varepsilon})$
recolorings;
  - a coloring strategy that uses $O(\log n)$ colors at the cost of $O(\log n)$
recolorings, and another strategy that uses $O(1/\varepsilon)$ colors at the
cost of $O(n^{\varepsilon}/\varepsilon)$ recolorings;
  - stronger upper and lower bounds for special cases.
  We also consider the kinetic setting where the intervals move continuously
(but there are no insertions or deletions); here we show how to maintain a
coloring with only four colors at the cost of three recolorings per event and
show this is tight.


  Molecular nanomagnets show clear signatures of coherent behavior and have a
wide variety of effective low-energy spin Hamiltonians suitable for encoding
qubits and implementing spin-based quantum information processing. At the
nanoscale, the preferred mechanism for control of quantum systems is through
application of electric fields, which are strong, can be locally applied, and
rapidly switched. In this work, we provide the theoretical tools for the search
for single molecule magnets suitable for electric control. By group-theoretical
symmetry analysis we find that the spin-electric coupling in triangular
molecules is governed by the modification of the exchange interaction, and is
possible even in the absence of spin-orbit coupling. In pentagonal molecules
the spin-electric coupling can exist only in the presence of spin-orbit
interaction. This kind of coupling is allowed for both $s=1/2$ and $s=3/2$
spins at the magnetic centers. Within the Hubbard model, we find a relation
between the spin-electric coupling and the properties of the chemical bonds in
a molecule, suggesting that the best candidates for strong spin-electric
coupling are molecules with nearly degenerate bond orbitals. We also
investigate the possible experimental signatures of spin-electric coupling in
nuclear magnetic resonance and electron spin resonance spectroscopy, as well as
in the thermodynamic measurements of magnetization, electric polarization, and
specific heat of the molecules.


  In this paper we present an in-depth analysis of a recently proposed Standard
Model extension with a complete fourth generation of quarks and leptons, which
are vector-like with respect to the Standard Model gauge group and charged
under a new spontaneously broken vector-like $\mathrm{U(1)^\prime}$ gauge
symmetry. The model is designed to explain the known muon anomalies, i.e. the
observed deviations from Standard Model predictions in the anomalous magnetic
moment of the muon, $\Delta a_\mu$, and in $b \rightarrow s \ell^+ \ell^-$
processes. We perform a global $\chi^2$ analysis of the data with $65$ model
parameters and including $98$ observables. We find many points with $\chi^2$
per degree of freedom $\leq 1$. The vector-like leptons and the new heavy
$Z^\prime$ are typically much lighter than a TeV and would, thus, be eminently
visible at the HL-LHC.


  Contrary to standard coupled cluster doubles (CCD) and Brueckner doubles
(BD), singlet-paired analogues of CCD and BD (denoted here as CCD0 and BD0) do
not break down when static correlation is present, but neglect substantial
amounts of dynamic correlation. In fact, CCD0 and BD0 do not account for any
contributions from multielectron excitations involving only same-spin electrons
at all. We exploit this feature to add---without introducing double counting,
self-interaction, or increase in cost---the missing correlation to these
methods via meta-GGA density functionals (TPSS and SCAN). Furthermore, we
improve upon these CCD0+DFT blends by invoking range separation: the short- and
long-range correlations absent in CCD0/BD0 are evaluated with DFT and the
direct random phase approximation (dRPA), respectively. This corrects the
description of long-range van der Waals forces. Comprehensive benchmarking
shows that the combinations presented here are very accurate for weakly
correlated systems, while also providing a reasonable description of strongly
correlated problems without resorting to symmetry breaking.


  We study the joint estimation of multiple Rabi frequencies in a multilevel
system. By analytically identifying the optimal probe state and the optimal
measurement, we obtain the highest precision limit for the joint estimation of
multiple Rabi frequencies. We show that the joint estimation does not always
outperform the separate estimation. In different regimes the joint estimation
can either outperform or underperform the separate estimation. We further show
that if additional adaptive quantum controls are allowed then the advantage of
the joint estimation over the separate estimation can be reestablished.


  We use the four-dimensional N=2 central charge superspace to give a
geometrical construction of the Abelian vector-tensor multiplet consisting,
under N=1 supersymmetry, of one vector and one linear multiplet. We derive the
component field supersymmetry and central charge transformations, and show that
there is a super-Lagrangian, the higher components of which are all total
derivatives, allowing us to construct superfield and component actions.


  Object-centric methods have seen significant progress in unsupervised
decomposition of raw perception into rich object-like abstractions. However,
limited ability to ground object semantics of the real world into the learned
abstractions has hindered their adoption in downstream understanding
applications. We present the Neural Slot Interpreter (NSI) that learns to
ground and generate object semantics via slot representations. At the core of
NSI is an XML-like programming language that uses simple syntax rules to
organize the object semantics of a scene into object-centric program
primitives. Then, an alignment model learns to ground program primitives into
slots through a bi-level contrastive learning objective over a shared embedding
space. Finally, we formulate the NSI program generator model to use the dense
associations inferred from the alignment model to generate object-centric
programs from slots. Experiments on bi-modal retrieval tasks demonstrate the
efficacy of the learned alignments, surpassing set-matching-based predictors by
a significant margin. Moreover, learning the program generator from grounded
associations enhances the predictive power of slots. NSI generated programs
demonstrate improved performance of object-centric learners on property
prediction and object detection, and scale with real-world scene complexity.


  Euclidean time windows in the integral representation of the hadronic vacuum
polarization contribution to the muon $g-2$ serve to test the consistency of
lattice calculations and may help in tracing the origins of a potential tension
between lattice and data-driven evaluations. In this paper, we present results
for the intermediate time window observable computed using O($a$) improved
Wilson fermions at six values of the lattice spacings below 0.1\,fm and pion
masses down to the physical value. Using two different sets of improvement
coefficients in the definitions of the local and conserved vector currents, we
perform a detailed scaling study which results in a fully controlled
extrapolation to the continuum limit without any additional treatment of the
data, except for the inclusion of finite-volume corrections. To determine the
latter, we use a combination of the method of Hansen and Patella and the
Meyer-Lellouch-L\"uscher procedure employing the Gounaris-Sakurai
parameterization for the pion form factor. We correct our results for
isospin-breaking effects via the perturbative expansion of QCD+QED around the
isosymmetric theory. Our result at the physical point is
$a_\mu^{\mathrm{win}}=(237.30\pm0.79_{\rm stat}\pm1.22_{\rm
syst})\times10^{-10}$, where the systematic error includes an estimate of the
uncertainty due to the quenched charm quark in our calculation. Our result
displays a tension of 3.9$\sigma$ with a recent evaluation of
$a_\mu^{\mathrm{win}}$ based on the data-driven method.


  We compare the main feature of the measured Raman scattering spectra from
single layer graphene with a bilayer in which the two layers are arbitrarily
misoriented. The profiles of the 2D bands are very similar having only one
component, contrary to the four found for commensurate Bernal bilayers. These
results agree with recent theoretical calculations and point to the similarity
of the electronic structures of single layer graphene and misoriented bilayer
graphene. Another new aspect is that the dependance of the 2D frequency on the
laser excitation energy is different in these two latter systems.


  The Blandford-Znajek theory (1977) is generally studied to understand the
generation of powerful relativistic jets. However, it could also give important
insights about the feedback between a rotating black hole, its ergosphere, and
a surrounding accretion disk. The energy flow between these systems could be
understood by studying the BZ power as a function of a slip factor, which in
turn is defined as a function of the angular velocity of the black hole and the
angular velocity of the magnetic field lines (generally anchored to the disk).
The distinct stages could explain the different types of observed AGN
(with/without jets), but could also help understanding the evolution of the
merging of binary AGN.


  The use of transfer learning (TL) techniques has become common practice in
fields such as computer vision (CV) and natural language processing (NLP).
Leveraging prior knowledge gained from data with different distributions, TL
offers higher performance and reduced training time, but has yet to be fully
utilized in applications of machine learning (ML) and deep learning (DL)
techniques to applications related to wireless communications, a field loosely
termed radio frequency machine learning (RFML). This work begins this
examination by evaluating the how radio frequency (RF) domain changes encourage
or prevent the transfer of features learned by convolutional neural network
(CNN)-based automatic modulation classifiers. Additionally, we examine existing
transferability metrics, Log Expected Empirical Prediction (LEEP) and Logarithm
of Maximum Evidence (LogME), as a means to both select source models for RF
domain adaptation and predict post-transfer accuracy without further training.


  The relationship between on-shell tree level scattering amplitudes of open
and closed strings, discovered some time ago by Kawai, Lewellen and Tye, is
used at field theory level (at $O(\alpha'^3)$) to establish a link between the
general relativity and the non-abelian Yang-Mills effective actions. Insisting
at the effective Lagrangian level that any tree $N$ point gravity on-shell
scattering amplitude is directly factorisable into a sum of $N$ point
left-right products of non-abelian Yang-Mills tree on-shell scattering
amplitudes, non-trivial mappings of the effective general relativity operators
into the effective non-abelian Yang-Mills operators are derived. Implications
of such mapping relations of the field operators are discussed.


  A classical way to construct a Lagrangian in a symplectic manifold $\Sigma$
is to let $\Sigma$ appear as a smooth fiber in a Lefschetz fibration. If this
is possible the singularities of the fibration induce Lagrangian spheres in
$\Sigma$ and these spheres, in turn, are representatives of the corresponding
vanishing cycles in the homology of $\Sigma$. In this paper our aim is twofold:
The first is to describe a generalization of the above mentioned construction
to the "Morse-Bott" case. This leads, whenever such a degeneration exists, to
the existence of Lagrangian sphere bundles rather than just spheres. In the
second part of the paper we study the type of topological restrictions on such
Lagrangian sphere bundles arising from the theory of Floer homology for
Lagrangian intersections and to illustrate the techniques involved.


  For MSSM phenomenology, soft SUSY breaking dimension-three operators are
important, in particular the couplings between Higgs bosons and squarks. In
scattering processes, perturbative unitarity is violated at modest
center-of-mass energy if these couplings are much larger than the masses of the
scalar particles involved. Assuming perturbative unitarity, constraints on the
trilinear couplings can be determined using a computer program that we have
developed.


  Unsuspended phononic integrated circuits have been proposed for on-chip
acoustic information processing. Limited by the operation mechanism of a
conventional interdigital transducer, the excitation of the quasi-Love mode in
GaN-on-Sapphire is inefficient and thus a high-efficiency Rayleigh-to-Love mode
converter is of great significance for future integrated phononic devices.
Here, we propose a high-efficiency and robust phononic mode converter based on
an adiabatic conversion mechanism. Utilizing the anisotropic elastic property
of the substrate, the adiabatic mode converter is realized by a simple tapered
phononic waveguide. A conversion efficiency exceeds $98\%$ with a
$3\,\mathrm{dB}$ bandwidth of $1.7\,\mathrm{GHz}$ can be realized for phononic
waveguides working at GHz frequency band, and excellent tolerance to the
fabrication errors is also numerically validated. The device that we proposed
can be useful in both classical and quantum phononic information processing,
and the adiabatic mechanism could be generalized to other phononic device
designs.


  In this paper, we estimate the Shannon entropy $S(f) = -\E[ \log (f(x))]$ of
a one-sided linear process with probability density function $f(x)$. We employ
the integral estimator $S_n(f)$, which utilizes the standard kernel density
estimator $f_n(x)$ of $f(x)$. We show that $S_n (f)$ converges to $S(f)$ almost
surely and in $\L^2$ under reasonable conditions.


  In 1965 Erd\H{o}s asked, what is the largest size of a family of $k$-element
subsets of an $n$-element set that does not have a matching of size $s+1$? In
this note, we improve upon a recent result of Frankl and resolve this problem
for $s>101k^{3}$ and $(s+1)k\le n<(s+1)(k+\frac{1}{100k})$.


  Recent volumetric 3D reconstruction methods can produce very accurate
results, with plausible geometry even for unobserved surfaces. However, they
face an undesirable trade-off when it comes to multi-view fusion. They can fuse
all available view information by global averaging, thus losing fine detail, or
they can heuristically cluster views for local fusion, thus restricting their
ability to consider all views jointly. Our key insight is that greater detail
can be retained without restricting view diversity by learning a view-fusion
function conditioned on camera pose and image content. We propose to learn this
multi-view fusion using a transformer. To this end, we introduce VoRTX, an
end-to-end volumetric 3D reconstruction network using transformers for
wide-baseline, multi-view feature fusion. Our model is occlusion-aware,
leveraging the transformer architecture to predict an initial, projective scene
geometry estimate. This estimate is used to avoid backprojecting image features
through surfaces into occluded regions. We train our model on ScanNet and show
that it produces better reconstructions than state-of-the-art methods. We also
demonstrate generalization without any fine-tuning, outperforming the same
state-of-the-art methods on two other datasets, TUM-RGBD and ICL-NUIM.


  For classical Lie superalgebras of type I, we provide necessary and
sufficient conditions for a Verma supermodule $\Delta(\lambda)$ to be such that
every non-zero homomorphism from another Verma supermodule to $\Delta(\lambda)$
is injective. This is applied to describe the socle of the cokernel of an
inclusion of Verma supermodules over the periplectic Lie superalgebras
$\mathfrak{pe}(n)$ and, furthermore, to reduce the problem of description of
$\mathrm{Ext}^1_{\mathcal O}(L(\mu),\Delta(\lambda))$ for $\mathfrak{pe}(n)$ to
the similar problem for the Lie algebra $\mathfrak{gl}(n)$.
  Additionally, we study the projective and injective dimensions of structural
supermodules in parabolic category $\mathcal O^{\mathfrak p}$ for classical Lie
superalgebras. In particular, we completely determine these dimensions for
structural supermodules over the periplectic Lie superalgebra
$\mathfrak{pe}(n)$ and the ortho-symplectic Lie superalgebra
$\mathfrak{osp}(2|2n)$.


  We study the Mott phase of three-component bosons, with one particle per
site, in an optical lattice by mapping it onto an SU(3) spin model. In the
simplest case of full SU(3) symmetry, one obtains a ferromagnetic Heisenberg
model. Introducing an SU(3) analog of spin-orbit coupling, additional spin-spin
interactions are generated. We first consider the scenario of spin-dependent
hopping phases, leading to Dzyaloshinskii-Moriya-type interactions. They result
in the formation of spiral spin textures, which in one dimension can be
understood by a local unitary transformation. Applying classical Monte Carlo
simulations, we extend our study to two-dimensional systems, and systems with
"true" spin-orbit coupling, involving spin-changing hoppings.


  We study single electron transport through a graphene quantum dot with
magnetic adsorbates. We focus on the relation between the spin order of the
adsorbates and the linear conductance of the device. The electronic structure
of the graphene dot with magnetic adsorbates is modeled through numerical
diagonalization of a tight-binding model with an exchange potential. We
consider several mechanisms by which the adsorbate magnetic state can influence
transport in a single electron transistor: by tuning the addition energy, by
changing the tunneling rate and, in the case of spin polarized electrodes,
through magnetoresistive effects. Whereas the first mechanism is always
present, the others require that the electrode has either an energy or spin
dependent density of states. We find that graphene dots are optimal systems to
detect the spin state of a few magnetic centers.


  We use the geometric structure of the hyperbolic upper half plane to provide
a new proof of the Avalanche Principle introduced by M. Goldstein and W. Schlag
in the context of $\mathrm{SL}_{2}(\mathbb{R})$ matrices. This approach allows
to interpret and extend this result to arbitrary $\mathrm{CAT}(-1)$ metric
spaces. Through the proof, we deduce a polygonal Schur theorem for these
spaces.


  We perform a comprehensive analysis of the spectrum of graphene plasmons
which arise when a pair of sheets are confined between conducting materials.
The associated enhanced local fields may be employed in the manipulation of
light on the nanoscale by adjusting the separation between the graphene layers,
the energy band gap as well as the concentration of charge carriers in the
conducting media surrounding the two-dimensional (2D) layers. We present a
theoretical formalism, based on the calculation of the surface response
function, for determining the plasmon spectrum of an encapsulated pair of 2D
layers and apply it to graphene. We solve the coupled equations involving the
continuity of the electric potential and discontinuity of the electric field at
the interfaces separating the constituents of the hybrid structure. We have
compared the plasmon modes for encapsulated gapped and gapless graphene. The
associated nonlocal graphene plasmon spectrum coupled to the "sandwich" system
show a linear acoustic plasmon mode as well as a low-frequency mode
corresponding to in-phase oscillations of the adjacent 2D charge densities.
These calculations are relevant to the study of energy transfer via plasmon
excitations when graphene is confined by a pair of thick conducting materials.


  A mixed graph $\widetilde{G}$ is obtained by orienting some edges of $G$,
where $G$ is the underlying graph of $\widetilde{G}$. The positive inertia
index, denoted by $p^{+}(G)$, and the negative inertia index, denoted by
$n^{-}(G)$, of a mixed graph $\widetilde{G}$ are the integers specifying the
numbers of positive and negative eigenvalues of the Hermitian adjacent matrix
of $\widetilde{G}$, respectively. In this paper, we study the positive and
negative inertia index of the mixed unicyclic graph. Moreover, we give the
upper and lower bounds of the positive and negative inertia index of the mixed
graph, and characterize the mixed graphs which attain the upper and lower
bounds respectively.


  We construct time-dependent one-dimensional (vertically averaged) models of
accretion disks produced by the tidal disruption of a white dwarf (WD) by a
binary neutron star (NS) companion. Nuclear reactions in the disk midplane burn
the WD matter to increasingly heavier elements at sequentially smaller radii,
releasing substantial energy which can impact the disk dynamics. A model for
disk outflows is employed, by which cooling from the outflow balances other
sources of heating (viscous, nuclear) in regulating the Bernoulli parameter of
the midplane to a fixed value $\lesssim 0$. We perform a comprehensive
parameter study of the compositional yields and velocity distributions of the
disk outflows for WDs of different initial compositions. For C/O WDs, the
radial composition profile of the disk evolves self-similarly in a
quasi-steady-state manner, and is remarkably robust to model parameters. The
nucleosynthesis in helium WD disks does not exhibit this behavior, which
instead depends sensitively on factors controlling the disk midplane density
(e.g. the strength of the viscosity, $\alpha$). By the end of the simulation, a
substantial fraction of the WD mass is unbound in outflows at characteristic
velocities of $\sim 10^9~{\rm cm~s}^{-1}$. The outflows from WD-NS merger disks
contain $10^{-4}-3 \times 10^{-3} M_\odot$ of radioactive $^{56}$Ni, resulting
in fast ($\sim$ week long) dim ($\sim10^{40}~{\rm erg~s}^{-1}$) optical
transients; shock heating of the ejecta by late time outflows may increase the
peak luminosity to $\sim 10^{43}~{\rm erg~s}^{-1}$. The accreted mass onto the
neutron star is probably not sufficient to induce gravitational collapse, but
may be capable of spinning up the NS to periods of $\sim 10~{\rm ms}$. This is
a new possible channel for forming isolated recycled pulsars.


  In this paper we consider a network scenario in which agents can evaluate
each other according to a score graph that models some physical or social
interaction. The goal is to design a distributed protocol, run by the agents,
allowing them to learn their unknown state among a finite set of possible
values. We propose a Bayesian framework in which scores and states are
associated to probabilistic events with unknown parameters and hyperparameters
respectively. We prove that each agent can learn its state by means of a local
Bayesian classifier and a (centralized) Maximum-Likelihood (ML) estimator of
the parameter-hyperparameter that combines plain ML and Empirical Bayes
approaches. By using tools from graphical models, which allow us to gain
insight on conditional dependences of scores and states, we provide two relaxed
probabilistic models that ultimately lead to ML parameter-hyperparameter
estimators amenable to distributed computation. In order to highlight the
appropriateness of the proposed relaxations, we demonstrate the distributed
estimators on a machine-to-machine testing set-up for anomaly detection and on
a social interaction set-up for user profiling.


  Linear system solving is one of the main workhorses in applied mathematics.
Recently, theoretical computer scientists have contributed sophisticated
algorithms for solving linear systems with symmetric diagonally dominant
matrices (a class to which Laplacian matrices belong) in provably nearly-linear
time. While these algorithms are highly interesting from a theoretical
perspective, there are no published results how they perform in practice.
  With this paper we address this gap. We provide the first implementation of
the combinatorial solver by [Kelner et al., STOC 2013], which is particularly
appealing for implementation due to its conceptual simplicity. The algorithm
exploits that a Laplacian matrix corresponds to a graph; solving Laplacian
linear systems amounts to finding an electrical flow in this graph with the
help of cycles induced by a spanning tree with the low-stretch property.
  The results of our comprehensive experimental study are ambivalent. They
confirm a nearly-linear running time, but for reasonable inputs the constant
factors make the solver much slower than methods with higher asymptotic
complexity. One other aspect predicted by theory is confirmed by our findings,
though: Spanning trees with lower stretch indeed reduce the solver's running
time. Yet, simple spanning tree algorithms perform in practice better than
those with a guaranteed low stretch.


  Silicon Carbide (SiC) ceramic matrix composite (CMC) cladding is currently
being pursued as one of the leading candidates for accident-tolerant fuels. To
enable an improved understanding of SiC-SiC composite performance, the
development of non-destructive evaluation techniques to assess critical defects
is needed. Three-dimensional (3D) X-ray imaging, also referred to as X-ray
computed tomography (CT), is a non-destructive, data-rich characterization
technique that can provide surface and subsurface spatial information. This
paper discusses the design and implementation of a fully automatic workflow to
detect and analyze SiC-SiC defects using image processing techniques on 3D
X-ray images. The workflow consists of four processing blocks, including data
preparation, void/crack detection, visualization, and analysis. In this work,
three SiC samples (two irradiated and one unirradiated) provided by General
Atomics are investigated. The irradiated samples were exposed in a way that was
expected to induce cracking, and indeed, the automated workflow developed in
this work was able to successfully identify and characterize the crack
formation in the irradiated samples while detecting no observed cracking in the
unirradiated sample. These results demonstrate the value of automated XCT tools
to better understand the damage and damage propagation in SiC-SiC structures
for nuclear applications.


  In Int. Journ. Mod. Phys. D 14, 181 (2005), the author Khriplovich verbatim
claims that "the correspondence principle does not dictate any relation between
the asymptotics of quasinormal modes and the spectrum of quantized black holes"
and that "this belief is in conflict with simple physical arguments". In this
paper we analyze Khriplovich's criticisms and realize that they work only for
the original proposal by Hod, while they do not work for the improvements
suggested by Maggiore and recently finalized by the author and collaborators
through a connection between Hawking radiation and black hole (BH) quasi-normal
modes (QNMs). This is a model of quantum BH somewhat similar to the historical
semi-classical model of the structure of a hydrogen atom introduced by Bohr in
1913. Thus, QNMs can be really interpreted as BH quantum levels (the
"electrons" of the "Bohr-like BH model"). Our results have also important
implications on the BH information puzzle.


  We present disc wind models aimed at reproducing the main features of the
strong Na I resonance line P-Cygni profiles in the rapidly-accreting pre-main
sequence FU Ori objects. We conducted Monte Carlo radiative transfer
simulations for a standard magnetocentrifugally driven wind (MHD) model and our
own "Genwind" models, which allows for a more flexible wind parameterisation.
We find that the fiducial MHD wind and similar Genwind models, which have flows
emerging outward from the inner disc edge, and thus have polar cavities with no
absorbing gas, cannot reproduce the deep, wide Na I absorption lines in FU Ori
objects viewed at low inclination. We find that it is necessary to include an
"inner wind" to fill this polar cavity to reproduce observations. In addition,
our models assuming pure scattering source functions in the Sobolev
approximation at intermediate viewing angles ($30^{\circ} \lesssim i \lesssim
60^{\circ}$) do not yield sufficiently deep line profiles. Assuming complete
absorption yields better agreement with observations, but simple estimates
strongly suggest that pure scattering should be a much better approximation.
The discrepancy may indicate that the Sobolev approximation is not applicable,
possibly due to turbulence or non-monotonic velocity fields; there is some
observational evidence for the latter. Our results provide guidance for future
attempts to constrain FU Ori wind properties using full MHD wind simulations,
by pointing to the importance of the boundary conditions necessary to give rise
to an inner wind, and by suggesting that the winds must be turbulent to produce
sufficiently deep line profiles.


  We present the measurement of the D+s production in pp collisions at sqrt{s}
= 7 TeV and in Pb Pb collisions at sqrt{s_NN} =2.76 TeV performed with the
ALICE detector at central rapidity through the reconstruction of the hadronic
decay channel D+s-> K+K-pi+. The preliminary results of the D+s nuclear
modification factor will be presented.


  The objective of the work summarised here has been to exploit and extend
ideas from plasma physics and accelerator dynamics to formulate a unified
description of collisionless relaxation that views violent relaxation, Landau
damping, and phase mixing as (manifestations of) a single phenomenon. This
approach embraces the fact that the collisionless Boltzmann equation (CBE), the
basic object of the theory, is an infinite-dimensional Hamiltonian system, with
the distribution function f playing the role of the fundamental dynamical
variable, and that, interpreted appropriately, an evolution described by the
{\it CBE} is no different fundamentally from an evolution described by any
other Hamiltonian system. Equilibrium solutions correspond to extremal points
of the Hamiltonian subject to the constraints associated with Liouville's
Theorem. Stable equilibria correspond to energy minima. The evolution of a
system out of equilibrium involves (in general nonlinear) phase space
oscillations which may -- or may not -- interfere destructively so as to damp
away.


  We present a half-life formalism for describing the disruption of
gravitationally-bound few-body systems, with a focus on binary-binary
scattering. For negative total encounter energies, the four-body problem has
three possible decay products in the point particle limit. For each decay
product and a given set of initial conditions, we obtain directly from
numerical scattering simulations the half-life for the distribution of
disruption times. As in radioactive decay, the half-lives should provide a
direct prediction for the relative fractions of each decay product. We test
this prediction with simulated data and find good agreement with our
hypothesis. We briefly discuss applications of this feature of the
gravitational four-body problem to populations of black holes in globular
clusters. This paper, the second in the series, builds on extending the
remarkable similarity between gravitational chaos at the macroscopic scale and
radioactive decay at the microscopic scale to larger-N systems.


  We report the discovery of a statistically significant hardening in the
Fermi-LAT $\gamma$-ray spectrum of Centaurus A's core, with the spectral index
hardening from $\Gamma_{1}=2.73 \pm 0.02$ to $\Gamma_{1}=2.29 \pm 0.07$ at a
break energy of ($2.6 \pm 0.3$) GeV. Using a likelihood analysis, we find no
evidence for flux variability in Cen A's core lightcurve above or below the
spectral break when considering the entire 8 year period. Interestingly,
however, the first $\sim3.5$ years of the low energy lightcurve shows evidence
of flux variability at the $\sim3.5 \sigma$ confidence level. To understand the
origin of this spectral break, we assume that the low energy component below
the break feature originates from leptons in Centaurus A's radio jet and we
investigate the possibility that the high energy component above the spectral
break is due to an additional source of very high energy particles near the
core of Cen A. We show for the first time that the observed $\gamma$-ray
spectrum of an Active Galactic Nucleus is compatible with either a very large
localized enhancement (referred to as a spike) in the dark matter halo profile
or a population of millisecond pulsars. Our work constitutes the first robust
indication that new $\gamma$-ray production mechanisms can explain the emission
from active galaxies and could provide tantalizing first evidence for the
clustering of heavy dark matter particles around black holes.


  By now it is known that in a singlet superconductor/ferromagnet (S/F)
structure the superconducting correlations carried by opposite-spin pairs
penetrate into the ferromagnet over a short distance of the order of magnetic
coherence length. The long-range proximity effect (LRPE), taking place on the
length scale of the normal metal coherence length, can only be maintained by
equal-spin pairs, which can be generated by magnetic inhomogeneities in the
system. In this work we have predicted a new type of LRPE, which can take place
in S/F heterostructures under non-equilibrium conditions. The superconducting
correlations in the F region are generated by opposite-spin Cooper pairs and
equal-spin pairs are not involved. The possibility for an opposite-spin pair to
penetrate into the ferromagnet over a large distance is provided by creation of
the proper non-equilibrium quasiparticle distribution there. This leads to a
sharp increase (up to a few orders of magnitude) of the critical Josephson
current through a S/F/S junction at some values of the voltage controlling the
nonequilibrium distribution in the F interlayer.


  Catalyzing capping layers on top of metal hydrides are often employed to
enhance the hydrogenation kinetics of metal-hydride based systems such as
hydrogen sensors. Here, we experimentally study the hydrogenation kinetics of
capping layers composed of several alloys of Pd and Au as well as Pt, Ni and
Ru, all with and without an additional PTFE protection layer using a novel
method and under the same set of experimental conditions. Our results
demonstrate that doping Pd with Au results in significantly faster
hydrogenation kinetics, with response times up to five times shorter than Pd
through enhanced diffusion and a reduction of the activation energy. The
kinetics of non-Pd based materials turns out to be significantly slower and
mainly limited by the diffusion through the capping layer itself. Surprisingly,
the additional PTFE layer was only found to improve the kinetics of Pd-based
capping materials and has no significant effect on the kinetics of Pt, Ni and
Ru. Taken together, the experimental results aid in rationally choosing a
suitable capping material for the application of metal hydrides and other
materials in a green economy. In addition, the developed method can be used to
simultaneously study the hydrogenation kinetics and determine diffusion
constants in thin film materials for a wide set of experimental conditions.


  We propose to employ a multilevel detection (MLDT) technique to allow
multiple users which respectively transmit messages over independent fading
channels to share the same resource, e.g., the same signature sequence in the
CDMA (code division multiple access) system. The users are separated by the
different channel gains including amplitudes and phases resultant from the
independent fading channels. In a CDMA system with a fixed amount of available
signature sequences, the number of users can be doubled or tripled by using
MLDT although there is the cost of some BER performance degradation.


  Recently, layered copper chalcogenides Cu2X family (X=S, Se, Te) has
attracted tremendous research interests due to their high thermoelectric (TE)
performance, which is partly due to the superionic behavior of mobile Cu ions,
making these compounds phonon liquids. Here, we systematically investigate the
electronic structure and its temperature evolution of the less studied single
crystal Cu2-xTe by the combination of angle resolved photoemission spectroscopy
(ARPES) and scanning tunneling microscope/spectroscopy (STM/STS) experiments.
While the band structure of the Cu2-xTe shows agreement with the calculations,
we clearly observe a 2 * 2 surface reconstruction from both our low temperature
ARPES and STM/STS experiments which survives up to room temperature.
Interestingly, our low temperature STM experiments further reveal multiple
types of reconstruction patterns, which suggests the origin of the surface
reconstruction being the distributed deficiency of liquid-like Cu ions. Our
findings reveal the electronic structure and impurity level of Cu2Te, which
provides knowledge about its thermoelectric properties from the electronic
degree of freedom.


  As machine learning becomes more widespread throughout society, aspects
including data privacy and fairness must be carefully considered, and are
crucial for deployment in highly regulated industries. Unfortunately, the
application of privacy enhancing technologies can worsen unfair tendencies in
models. In particular, one of the most widely used techniques for private model
training, differentially private stochastic gradient descent (DPSGD),
frequently intensifies disparate impact on groups within data. In this work we
study the fine-grained causes of unfairness in DPSGD and identify gradient
misalignment due to inequitable gradient clipping as the most significant
source. This observation leads us to a new method for reducing unfairness by
preventing gradient misalignment in DPSGD.


  We propose a novel prediction interval (PI) method for uncertainty
quantification, which addresses three major issues with the state-of-the-art PI
methods. First, existing PI methods require retraining of neural networks (NNs)
for every given confidence level and suffer from the crossing issue in
calculating multiple PIs. Second, they usually rely on customized loss
functions with extra sensitive hyperparameters for which fine tuning is
required to achieve a well-calibrated PI. Third, they usually underestimate
uncertainties of out-of-distribution (OOD) samples leading to over-confident
PIs. Our PI3NN method calculates PIs from linear combinations of three NNs,
each of which is independently trained using the standard mean squared error
loss. The coefficients of the linear combinations are computed using
root-finding algorithms to ensure tight PIs for a given confidence level. We
theoretically prove that PI3NN can calculate PIs for a series of confidence
levels without retraining NNs and it completely avoids the crossing issue.
Additionally, PI3NN does not introduce any unusual hyperparameters resulting in
a stable performance. Furthermore, we address OOD identification challenge by
introducing an initialization scheme which provides reasonably larger PIs of
the OOD samples than those of the in-distribution samples. Benchmark and
real-world experiments show that our method outperforms several
state-of-the-art approaches with respect to predictive uncertainty quality,
robustness, and OOD samples identification.


  This paper presents how photonics associated with new arising detection
technologies is able to provide fully integrated instrument for coherent beam
combination applied to astrophysical interferometry. The feasibility and
operation of on-chip coherent beam combiners has been already demonstrated
using various interferometric combination schemes. More recently we proposed a
new detection principle aimed at directly sampling and extracting the spectral
information of an input signal together with its flux level measurement. The
so-called SWIFTS demonstrated concept that stands for Stationary-Wave
Integrated Fourier Transform Spectrometer, provides full spectral and spatial
information recorded simultaneously thanks to a motionless detecting device.
  Due to some newly available detection principles considered for the
implementation of the SWIFTS concept, some technologies can even provide
photo-counting operation that brought a significant extension of the
interferometry domain of investigation in astrophysics . The proposed concept
is applicable to most of the interferometric instrumental modes including
fringe tracking, fast and sensitive detection, Fourier spectral reconstruction
and also to manage a large number of incoming beams. The paper presents three
practical implementations, two dealing with pair-wise integrated optics beam
combinations and the third one with an all-in-one 8 beam combination. In all
cases the principles turned into a pair wise baseline coding after proper data
processing.


  Some roaming users need services to manipulate autonomous processes. Trading
agents running on agent trade servers are used as a case in point. We present a
solution that provides the agent owners with means to upkeeping their desktop
environment, and maintaining their agent trade server processes, via a
briefcase service.


  We find universal scaling relations of the pinning effect on the Hall
resistivity $\rho_{xy}$ and Hall angle $\theta_{H}$. Considering the extended
power law form of $\rho_{xx}$ and the microscopic analysis of $\sigma_{xy}$, we
obtain unified $\rho_{xy}$ equations for superconductors with and without
double sign reversal. These equations reasonably explain the striking
universality in doping dependence found by Nagoaka et al., which contradicts
the prediction of the time dependent Ginzburg-Landau equation based on s-wave
coupling theory [PRL {\bf{80}},3594 (1998)]. A full comparison of experiment
with prediction from theoretical models is proposed.


  We study the scattering of solitons in the nonlinear Schroedinger equation on
local inhomogeneities which may give rise to resonant transmission and
reflection. In both cases, we derive resonance conditions for the soliton's
velocity. The analytical predictions are tested numerically in regimes
characterized by various time scales. Special attention is paid to intermode
interactions and their effect on coherence, decoherence and dephasing of
plane-wave modes which build up the soliton.


  In this study, we present a deep learning-based approach for time-series
respiration data classification. The dataset contains regular breathing
patterns as well as various forms of abnormal breathing, obtained through
non-contact incoherent light-wave sensing (LWS) technology. Given the
one-dimensional (1D) nature of the data, we employed a 1D convolutional neural
network (1D-CNN) for classification purposes. Genetic algorithm was employed to
optimize the 1D-CNN architecture to maximize classification accuracy.
Addressing the computational complexity associated with training the 1D-CNN
across multiple generations, we implemented transfer learning from a
pre-trained model. This approach significantly reduced the computational time
required for training, thereby enhancing the efficiency of the optimization
process. This study contributes valuable insights into the potential
applications of deep learning methodologies for enhancing respiratory anomaly
detection through precise and efficient respiration classification.


  Data from angle resolved photo-emission spectroscopy (ARPES) often serves as
a smoking-gun evidence for the existence of topological materials. It provides
the energy dispersion curves of the topological boundary modes which
characterize these phases. Unfortunately this method requires a sufficiently
regular boundary such that these boundary modes remain sharp in momentum space.
Here the seemingly random data obtained from performing ARPES on strongly
disordered topological insulators and Weyl semimetals is analyzed theoretically
and numerically. Expectedly the disorder averaged ARPES spectra appear
featureless. Surprisingly however, correlations in these spectra between
different energies and momenta reveal delta-sharp features in momentum space.
Measuring such correlations using nano-ARPES may verify the topological nature
of the suggested weak topological insulator ($Bi_{14} Rh_3 I_9$) which thus far
was not studied using ARPES due to the rough nature of its metallic surfaces.


  If $i:A\subset B$ is a commutative ring extension, we show that the group
$\mathcal I(A,B)$ of invertible $A$-submodules of $B$ is contracted in the
sense of Bass, with $L\mathcal I(A,B)=H^0_{et}(A,i_*\mathbb Z/\mathbb Z)$. This
gives a canonical decomposition for $\mathcal I(A[t,\frac1t],B[t,\frac1t])$.


  This research paper studies about the role of social media use and increase
the risk factor of mental health during covid 19 or lockdown. Although few
studies have been conducted on the role about the effect of social media use on
mental health during lockdown and impact on human reactive nature during
lockdown. As a rapidly spreading pandemic, a biomedical disease has serious
physical and tremendous mental health implications. An occupational community
of internal migrant workers is one of the most vulnerable, but neglected, and
is likely to develop psychological ill-effects due to COVID-19's double whammy
impact. Mental health is a crucial aspect that needs to be addressed during
this lock-down as all modes of communication revolve around the virus. There
are many difficulties with the unprecedented changes that have occurred so
quickly due to the pandemic and stay-at - home confinement to achieve social
distance and mitigate the risk of infection. These include impaired health,
well-being, and sleep as a result of daily routine disruption, anxiety, worry,
isolation, greater stress on family and work, and excessive screen time. An
essential part of our overall health and well-being is mental and emotional
health. An important skill is managing emotions and maintaining emotional
balance. It helps you face challenges and stress when you manage your emotional
health. Lack of skills in emotional regulation may lead to poor mental health
and relationship difficulties. It is as important to look after our mental
health as it is to look after our physical health. For mental health
professionals, the pandemic has also brought many ethical challenges.


  In the eighties Goldman discovered a Lie algebra structure on the vector
space generated by the free homotopy classes of oriented curves on an oriented
surface. The Lie bracket [a,b] is defined as the signed sum over the
intersection points of a and b of the loop product of at the intersection
points.
  If one of the classes has a simple representative we give a combinatorial
group theory description of the terms of the Lie bracket and prove that this
bracket has as many terms, counted with multiplicity, as the minimal number of
intersection points of a and b. In other words the bracket with a simple
element has no cancellation and determines minimal intersection numbers. We
show that analogous results hold for the Lie bracket (also discovered by
Goldman) of unoriented curves. We give three applications: a factorization of
Thurston's map defining the boundary of Teichmuller space, various
decompositions of the underlying vector space of conjugacy classes into ad
invariant subspaces and a connection between bijections of the set of conjugacy
classes of curves on a surface preserving the Goldman bracket and the mapping
class group.


  In this paper, employing the exponential corrected entropy (Chatterjee and
Ghosh in Phys Rev Lett 125:041302, 2020), we derive the modified Friedmann
equations from the first law of thermodynamics at apparent horizon and
Verlinde's entropic gravity scenario. First, we derive the modified Friedmann
equations from the first law of thermodynamics. We investigate the validity of
generalised second law (GSL) of thermodynamics and find that it is always
satisfied for the all eras of universe. Moreover, we investigate the
deceleration parameter for the case $k=0$ in two frameworks. Finally, we
numerically study the bouncing behaviour for the modified Friedmann equations
obtained from entropic gravity. The results indicate that the bouncing
behaviour is possible for the cases $k=1$ and $k=-1$.


  We present ab initio results at the density functional theory level for the
energetics and kinetics of H_2 and CH_4 in the SI clathrate hydrate. Our
results complement a recent article by some of the authors [G. Roman-Perez et
al., Phys. Rev. Lett. 105, 145901 (2010)] in that we show additional results of
the energy landscape of H_2 and CH_4 in the various cages of the host material,
as well as further results for energy barriers for all possible diffusion paths
of H_2 and CH_4 through the water framework. We also report structural data of
the low-pressure phase SI and the higher-pressure phases SII and SH.


  By combining genetic algorithm optimizations, first-principles calculations
and the double-exchange model studies, we have unveiled that the exotic
insulating ferromagnetism in LaMnO3 thin film originates from the previously
unreported G-type d_{3z^2-r^2}/d_{x^2-y^2} orbital ordering. An insulating gap
opens as a result of both the orbital ordering and the strong electron-phonon
coupling. Therefore, there exist two strain induced phase transitions in the
LaMnO3 thin film, from the insulating A-type antiferromagnetic phase to the
insulating ferromagnetic phase and then to the metallic ferromagnetic phase.
These phase transitions may be exploited in tunneling magnetoresistance and
tunneling electroresistance related devices.


  This is a correction to our article in the Journal of Differential Equations,
Volume 76(1988).


  With their prominent scene understanding and reasoning capabilities,
pre-trained visual-language models (VLMs) such as GPT-4V have attracted
increasing attention in robotic task planning. Compared with traditional task
planning strategies, VLMs are strong in multimodal information parsing and code
generation and show remarkable efficiency. Although VLMs demonstrate great
potential in robotic task planning, they suffer from challenges like
hallucination, semantic complexity, and limited context. To handle such issues,
this paper proposes a multi-agent framework, i.e., GameVLM, to enhance the
decision-making process in robotic task planning. In this study, VLM-based
decision and expert agents are presented to conduct the task planning.
Specifically, decision agents are used to plan the task, and the expert agent
is employed to evaluate these task plans. Zero-sum game theory is introduced to
resolve inconsistencies among different agents and determine the optimal
solution. Experimental results on real robots demonstrate the efficacy of the
proposed framework, with an average success rate of 83.3%.


  A search is presented for particle dark matter produced in association with a
pair of top quarks in pp collisions at a centre-of-mass energy of sqrt(s) = 8
TeV. The data were collected with the CMS detector at the LHC and correspond to
an integrated luminosity of 19.7 inverse femtobarns. This search requires the
presence of one lepton, multiple jets, and large missing transverse energy. No
excess of events is found above the SM expectation, and upper limits are
derived on the production cross section. Interpreting the findings in the
context of a scalar contact interaction between fermionic dark matter particles
and top quarks, lower limits on the interaction scale are set. These limits are
also interpreted in terms of the dark matter-nucleon scattering cross sections
for the spin-independent scalar operator and they complement direct searches
for dark matter particles in the low mass region.


  This paper investigates the dynamic properties of one, two and
three-dimensional tensegrity-based periodic structures introduced in Rimoli and
Pal, Comp. B, 2017, which are here termed as tensegrity beams, plates and
solids, respectively. We study their linear wave propagation properties and
show that in each case, these properties can be significantly altered by the
prestrain in the cables. As the prestrain is varied, we observe jumps in the
wave velocities at two critical prestrain values, which define transitions
between the three distinct phases of these structural assemblies. At low cable
prestrains, the wave speeds are zero as the lattices have zero effective
stiffness. At moderate prestrains, the wave speed is nonzero and finally, at
prestrain levels where the bars buckle, the wave speed decreases to a lower
value. Dispersion analysis on these beams, plates and solids reveal unique
properties such as very low wave velocities compared to their constituent
material and the existence of flat bands at low frequencies. Furthermore, we
find that shear waves travel faster than longitudinal waves in tensegrity
solids in a range of cable prestrains. Finally, we verify the key observations
through detailed numerical simulations on finite tensegrity solids.


  We present and test a new method for simulating dynamical fermions with fat
links. Our construction is based on the introduction of auxiliary but dynamical
gauge fields and works with any fermionic action and can be combined with any
fermionic updating. In our simulation we use an over-relaxation step which
makes it effective. For four flavors of staggered fermions first results
indicate that flavor symmetry at a lattice spacing a~0.2 fm is restored to a
few percent. With the standard action this amount of flavor symmetry
restoration is achieved at a~0.07 fm. We estimate that the overall
computational cost is reduced by at least a factor 10.


  We study a two-dimensional model of an isolated narrow topological band at
partial filling with local attractive interactions. Numerically exact quantum
Monte Carlo calculations show that the ground state is a superconductor with a
critical temperature that scales nearly linearly with the interaction strength.
We also find a broad pseudogap regime at temperatures above the superconducting
phase that exhibits strong pairing fluctuations and a tendency towards
electronic phase separation; introducing a small nearest neighbor attraction
suppresses superconductivity entirely and results in phase separation. We
discuss the possible relevance of superconductivity in this unusual regime to
the physics of flat band moir\'{e} materials, and as a route to designing
higher temperature superconductors.


  We review some experimental and theoretical results on the metal-to-insulator
transition (MIT) observed at zero magnetic field (B=0) in several
two-dimensional electron systems (2DES). Scaling of the conductance and
magnetic field dependence of the conductance provide convincing evidence that
the MIT is driven by Coulomb interactions among the carriers and is
dramatically sensitive to spin polarization of the carriers.


  In this note, we study invertible sheaves on group homogeneous spaces and
their ampleness, especially when the bases are Prufer schemes, namely, the
schemes whose all local rings are valuation rings. First, we give several
conditions for Hartogs's phenomenon of invertible sheaves to hold on
non-Noetherian schemes through parafactorial pairs in EGAIV4, thus describe
relatively effective Cartier divisors on smooth schemes over valuation rings as
flat closed subschemes of pure codimension one. Subsequently, we obtain
criteria for ampleness in the non-Noetherian case, and from this, construct
ample invertible sheaves explicitly in terms of the flat cycles of pure
codimension one. Finally, we establish extension properties of (semi)ample
invertible sheaves on group homogeneous spaces smooth over Pr\"uferian bases.


  We present high statistics results for the structure of the nucleon from a
mixed-action calculation using 2+1 flavors of asqtad sea and domain wall
valence fermions. We perform extrapolations of our data based on different
chiral effective field theory schemes and compare our results with available
information from phenomenology. We discuss vector and axial form factors of the
nucleon, moments of generalized parton distributions, including moments of
forward parton distributions, and implications for the decomposition of the
nucleon spin.


  We combine near-ultraviolet (NUV; 2250 {\AA}) and optical (U, B, V, I)
imaging from the Wide Field Camera 3 (WFC3), on board the Hubble Space
Telescope (HST), to study the globular cluster (GC) population in NGC 4150, a
sub-L* (M_B ~ -18.48 mag) early-type minor-merger remnant in the Coma I cloud.
We use broadband NUV-optical photometry from the WFC3 to estimate individual
ages, metallicities, masses and line-of-sight extinctions [E_(B-V)] for 63
bright (M_V < -5 mag) GCs in this galaxy. In addition to a small GC population
with ages greater than 10 Gyr, we find a dominant population of clusters with
ages centred around 6 Gyr, consistent with the expected peak of stellar mass
assembly in faint early-types residing in low-density environments. The old and
intermediate-age GCs in NGC 4150 are metal-poor, with metallicities less than
0.1 ZSun, and reside in regions of low extinction (E_(B-V) < 0.05 mag). We also
find a population of young, metal-rich (Z > 0.3 ZSun) clusters that have formed
within the last Gyr and reside in relatively dusty (E_(B-V) > 0.3 mag) regions
that are coincident with the part of the galaxy core that hosts significant
recent star formation. Cluster disruption models (in which ~80-90% of objects
younger than a few 10^8 yr dissolve every dex in time) suggest that the bulk of
these young clusters are a transient population.


  Sources of entanglement are an enabling resource in quantum technology, and
pushing the limits of generation rate and quality of entanglement is a
necessary pre-requisite towards practical applications. Here, we present an
ultra-bright source of polarization-entangled photon pairs based on
time-reversed Hong-Ou-Mandel interference. By superimposing four pair-creation
possibilities on a polarization beam splitter, pairs of identical photons are
separated into two spatial modes without the usual requirement for wavelength
distinguishability or non-collinear emission angles. Our source yields
high-fidelity polarization entanglement and high pair-generation rates without
any requirement for active interferometric stabilization, which makes it an
ideal candidate for a variety of applications, in particular those requiring
indistinguishable photons.


  We study concentration in spectral norm of nonparametric estimates of
correlation matrices. We work within the confine of a Gaussian copula model.
Two nonparametric estimators of the correlation matrix, the sine
transformations of the Kendall's tau and Spearman's rho correlation
coefficient, are studied. Expected spectrum error bound is obtained for both
the estimators. A general large deviation bound for the maximum spectral error
of a collection of submatrices of a given dimension is also established. These
results prove that when both the number of variables and sample size are large,
the spectral error of the nonparametric estimators is of no greater order than
that of the latent sample covariance matrix, at least when compared with some
of the sharpest known error bounds for the later. As an application, we
establish the minimax optimal convergence rate in the estimation of
high-dimensional bandable correlation matrices via tapering off of these
nonparametric estimators. An optimal convergence rate for sparse principal
component analysis is also established as another example of possible
applications of the main results.


  Commercial wearables from Fitbit, Garmin, and Whoop have recently introduced
real-time notifications based on detecting changes in physiological responses
indicating potential stress. In this paper, we investigate how these new
capabilities can be leveraged to improve stress management. We developed a
smartwatch app, a smartphone app, and a cloud service, and conducted a 100-day
field study with 122 participants who received prompts triggered by
physiological responses several times a day. They were asked whether they were
stressed, and if so, to log the most likely stressor. Each week, participants
received new visualizations of their data to self-reflect on patterns and
trends. Participants reported better awareness of their stressors, and
self-initiating fourteen kinds of behavioral changes to reduce stress in their
daily lives. Repeated self-reports over 14 weeks showed reductions in both
stress intensity (in 26,521 momentary ratings) and stress frequency (in 1,057
weekly surveys).


  Margin has played an important role on the design and analysis of learning
algorithms during the past years, mostly working with the maximization of the
minimum margin. Recent years have witnessed the increasing empirical studies on
the optimization of margin distribution according to different statistics such
as medium margin, average margin, margin variance, etc., whereas there is a
relative paucity of theoretical understanding. In this work, we take one step
on this direction by providing a new generalization error bound, which is
heavily relevant to margin distribution by incorporating ingredients such as
average margin and semi-variance, a new margin statistics for the
characterization of margin distribution. Inspired by the theoretical findings,
we propose the MSVMAv, an efficient approach to achieve better performance by
optimizing margin distribution in terms of its empirical average margin and
semi-variance. We finally conduct extensive experiments to show the superiority
of the proposed MSVMAv approach.


  In this note we complete a study of globally homogeneous Riemannian quotients
$\Gamma\backslash (M,ds^2)$ in positive curvature. Specifically, $M$ is a
homogeneous space $G/H$ that admits a $G$-invariant Riemannian metric of
strictly positive sectional curvature, and $ds^2$ is a $G$--invariant
Riemannian metric on $M$, not necessarily normal and not necessarily positively
curved. The Homogeneity Conjecture is that $\Gamma\backslash (M,ds^2)$ is
(globally) homogeneous if and only if $(M,ds^2)$ is homogeneous and every
$\gamma \in \Gamma$ is of constant displacement on $(M,ds^2)$. In an earlier
paper we verified that conjecture for all homogeneous spaces that admit an
invariant Riemannian metric of positive curvature -- with three exceptions, all
odd dimensional spheres, which surprisingly did not yield to the earlier
approaches. Here we develop some methods that let us verify the Homogeneity
Conjecture for those three obstinate spheres. That completes verification of
the Homogeneity Conjecture in positive curvature.


  We give a new framework for proving the existence of low-degree, polynomial
approximators for Boolean functions with respect to broad classes of
non-product distributions. Our proofs use techniques related to the classical
moment problem and deviate significantly from known Fourier-based methods,
which require the underlying distribution to have some product structure.
  Our main application is the first polynomial-time algorithm for agnostically
learning any function of a constant number of halfspaces with respect to any
log-concave distribution (for any constant accuracy parameter). This result was
not known even for the case of learning the intersection of two halfspaces
without noise. Additionally, we show that in the "smoothed-analysis" setting,
the above results hold with respect to distributions that have sub-exponential
tails, a property satisfied by many natural and well-studied distributions in
machine learning.
  Given that our algorithms can be implemented using Support Vector Machines
(SVMs) with a polynomial kernel, these results give a rigorous theoretical
explanation as to why many kernel methods work so well in practice.


  On the basis of the pseudopotential plane-wave(PP-PW) method and the
local-density-functional theory(LDFT), this paper studies energetics,
stress-strain relation, stability and ideal strength of $\beta $-SiC under
various loading modes, where uniform uniaxial extension and tension, biaxial
proportional extension are considered along directions [001] and [111]. The
lattice constant, elastic constants and moduli of equilibrium state are
calculated, and the results agree well with the experimental data. As the four
Si-C bonds along directions [111], [$\bar{1}$11], [11$\bar{1}$] and
[1$\bar{1}$1] are not the same under the loading along [111], internal
relaxation and the corresponding internal displacements must be considered. We
find that, at the beginning of loading, the effect of internal displacement
through shuffle and glide plane diminishes the difference among the four Si-C
bonds length, but will increase the difference at the subsequent loading, which
will result in a crack nucleated on \{111\} shuffle plane and a subsequently
cleavage fracture. Thus the corresponding theoretical strength is 50.8 GPa,
which agrees well with the recent experiment value, 53.4 GPa. However, with the
loading along [001], internal relaxation is not important for tetragonal
symmetry. Elastic constants during the uniaxial tension along [001] are
calculated. Based on the stability analysis with stiffness coefficients, we
find that the spinodal and Born instabilities are triggered almost at the same
strain, which agrees with the previous molecular dynamics simulation. During
biaxial proportional extension, stress and strength vary proportionally with
the biaxial loading ratio at the same longitudinal strain.


  This are the cumulated reports of the SoNDe detector Project as of July 2017.
The contained reports are: - Report on the 1x1 module technical demonstrator -
Report on used materials - Report on radiation hardness of components - Report
on potential additional applications - Report on the 2x2 module technical
demonstrator - Report on test results of the 2x2 technical demonstrator


  Vector-boson pair production ranks among the most important Standard-Model
benchmark processes at the LHC, not only in view of on-going Higgs analyses.
These processes may also help to gain a deeper understanding of the electroweak
interaction in general, and to test the validity of the Standard Model at
highest energies. In this work, the first calculation of the full one-loop
electroweak corrections to on-shell W-boson pair production at hadron colliders
is presented. We discuss the impact of the corrections on the total cross
section as well as on relevant differential distributions. We observe that
corrections due to photon-induced channels can be amazingly large at energies
accessible at the LHC, while radiation of additional massive vector bosons does
not influence the results significantly.


  The so called "globalization" process (i.e. the inexorable integration of
markets, currencies, nation-states, technologies and the intensification of
consciousness of the world as a whole) has a behavior exactly equivalent to a
system that is tending to a maximum entropy state. This globalization process
obeys a collective welfare principle in where the maximum payoff is given by
the equilibrium of the system and its stability by the maximization of the
welfare of the collective besides the individual welfare. This let us predict
the apparition of big common markets and strong common currencies. They will
reach the "equilibrium" by decreasing its number until they reach a state
characterized by only one common currency and only one big common community
around the world.


  We investigate black hole production in pp collisions at the Large Hadron
Collider by employing the horizon quantum mechanics for models of gravity with
extra spatial dimensions. This approach can be applied to processes around the
fundamental gravitational scale and naturally yields a suppression below the
fundamental gravitational scale and for increasing number of extra dimensions.
The results of numerical simulations performed with the black hole event
generator BLACKMAX are here reported in order to illustrate the main
differences in the number of expected black hole events and mass distributions.


  Eigenvalue analysis is widely used for linear instability analysis in both
external and internal aerodynamics. It typically involves finding the steady
state, linearizing around it to obtain the Jacobian, and then solving for its
eigenvalues and eigenvectors. When the flow is modelled with Reynolds-averaged
Navier--Stokes equations with a large boundary-layer-resolving mesh, the
resulting eigenvalue problem can be of very high dimensions, and is thus
computationally very challenging. To reduce the computational cost, a
simplified approach is proposed to compute the eigenvalues and eigenvectors, by
exploiting the cyclic symmetric nature of annular fluid domain for typical
compressors. It is shown that via a rotational transformation, the Jacobian can
be reduced to a block circulant matrix, whose eigenvalues and eigenvectors then
can be computed using only one sector of the entire domain. This simplified
approach significantly lowers the memory overhead and the CPU time of the
eigenvalue analysis without compromising on the accuracy. The proposed method
is applied to the eigenvalue analysis of an annular compressor cascade with 22
repeated sectors and it is shown the spectrum of the whole annulus can be
obtained by using the information of 1 sector only, demonstrating the
effectiveness of the proposed method.


  We comment on the paper by E. B. Sonin, PRB v 85, 104516 (2012)
[arXiv:1201.3188], with which we find ourselves in serious disagreement. We use
this option to shed light on some important issues of a theory of Kelvin wave
turbulence, touched in E. B. Sonin's paper, in particular, on the relation
between the Vinen spectrum of strong- and the L'vov-Nazarenko spectrum of
weak-turbulence of Kelvin waves. We also discuss the role of our explicit
calculation of the Kelvin wave interaction Hamiltonian and of the "symmetry
arguments" that are supposed to resolve a contradiction between the
Kozik-Svistunov and L'vov-Nazarenko spectrum of weak turbulence of Kelvin
waves.


  We prove that the Landau-Lifshitz-Gilbert equation in three space dimensions
with homogeneous Neumann boundary conditions admits arbitrarily smooth
solutions, given that the initial data is sufficiently close to a constant
function.


  Real-time video surveillance has become a crucial technology for smart
cities, made possible through the large-scale deployment of mobile and fixed
video cameras. In this paper, we propose situation-aware streaming, for
real-time identification of important events from live-feeds at the source
rather than a cloud based analysis. For this, we first identify the frames
containing a specific situation and assign them a high scale-of-importance
(SI). The identification is made at the source using a tiny neural network
(having a small number of hidden layers), which incurs a small computational
resource, albeit at the cost of accuracy. The frames with a high SI value are
then streamed with a certain required Signal-to-Noise-Ratio (SNR) to retain the
frame quality, while the remaining ones are transmitted with a small SNR. The
received frames are then analyzed using a deep neural network (with many hidden
layers) to extract the situation accurately. We show that the proposed scheme
is able to reduce the required power consumption of the transmitter by 38.5%
for 2160p (UHD) video, while achieving a classification accuracy of 97.5%, for
the given situation.


  Chandra deep fields represent the deepest look at the X-ray sky. We analyzed
the Chandra Deep Field South (CDFS) with the aid of a dedicated wavelet-based
algorithm. Here we present a detailed description of the procedures used to
analyze this field, tested and verified by means of extensive simulations. We
show that we can safely reconstruct the LogN-Log S source distribution of the
CDFS down to limiting fluxes of 2.4x10^-17 and 2.1x10^-16 erg s^-1 cm^-2 in the
soft (0.5-2 keV) and hard (2-10 keV) bands, respectively, fainter by a factor ~
2 than current estimates. At these levels we can account for ~ 90% of the 1-2
keV and 2-10 keV X-ray background.


  The Frequency Response Functions (FRFs) are the most widely used functions to
characterise the dynamic behaviour of structures. The natural frequencies and
damping behaviour can be easily and quickly detected from a Bode diagram. The
modal properties of FRFs can be evaluated using modal analysis methods, and as
the last step, frequency response models can synthesise response functions to
verify the robustness of the modal parameters identified by the analysis. The
circularity between 1) measurement, 2) identification, 3) regeneration and 4)
comparison is ensured on the assumption that transfer functions are measured
under linear vibrations, even though mechanical systems are intrinsically
non-linear. Some sources of nonlinearity might be excited and revealed, and
others not for various reasons. Anyhow, it is unavoidable to measure non-linear
vibrations when vibration tests are executed at various levels of excitation
forces. Eventually, linear and non-linear vibrations are processed to obtain
linear and non-linear FRFs. The linear FRFs are processed using the existing
identification methods. The non-linear FRFs are archived or blandly processed
to evaluate the level and the type of nonlinearity, such as hardening or
softening behaviour. This research aims to (i) formulate a new analysis method
to generate nonlinear frequency responses and (ii) formulate a new
identification method for extracting amplitude-dependent modal parameters. The
first objective will demonstrate that a nonlinear frequency response surface
generated by linear FRFs is the solution space of nonlinear FRFs. The second
objective will demonstrate that a linear modal analysis method called line-fit,
based on the Dobson formulation, allows extracting amplitude-dependent modal
parameters from non-linear FRFs.


  In this paper we considered the most general form of non conformally flat
cylindrically symmetric non-static space-times to study proper conformal
motions using direct integration technique. We have shown that very special
classes for cylindrically symmetric space-times admit proper conformal motions.
This classification also covers non-static and static plane symmetric
space-times. In [9] it was claimed that non conformally flat plane symmetric
static space-times do not admit proper conformal motion. Here it is also shown
that static and non static plane symmetric space-times admit proper conformal
motions. We also discuss the Lie algebra in each case.


  Two-dimensional (2D) van der Waals ferromagnetic materials are emerging as
promising candidates for applications in ultra-compact spintronic nanodevices,
nanosensors, and information storage. Our recent discovery of the strong room
temperature ferromagnetism in single layers of VSe2 grown on graphite or MoS2
substrate has opened new opportunities to explore these ultrathin magnets for
such applications. In this paper, we present a new type of magnetic sensor that
utilizes the single layer VSe2 film as a highly sensitive magnetic core. The
sensor relies in changes in resonance frequency of the LC circuit composed of a
soft ferromagnetic microwire coil that contains the ferromagnetic VSe2 film
subject to applied DC magnetic fields. The sensitivity of the sensor reaches an
extremely high value of 16x10^6 Hz/Oe, making it an excellent candidate for a
wide range of magnetic sensing applications.


  The gauge invariance of cubic open superstring field theory is considered in
a framework of level truncation, and applications to the tachyon condensation
problem are discussed. As it is known, in the bosonic case the Feynman-Siegel
gauge is not universal within the level truncation method. We explore another
gauge that is more suitable for calculation of the tachyon potential for
fermionic string at level (2,6). We show that this new gauge has no
restrictions on the region of its validity at least at this level.


  A public database system archiving a direct numerical simulation (DNS) data
set of isotropic, forced turbulence is described in this paper. The data set
consists of the DNS output on $1024^3$ spatial points and 1024 time-samples
spanning about one large-scale turn-over timescale. This complete $1024^4$
space-time history of turbulence is accessible to users remotely through an
interface that is based on the Web-services model. Users may write and execute
analysis programs on their host computers, while the programs make
subroutine-like calls that request desired parts of the data over the network.
The users are thus able to perform numerical experiments by accessing the 27
Terabytes of DNS data using regular platforms such as laptops. The architecture
of the database is explained, as are some of the locally defined functions,
such as differentiation and interpolation. Test calculations are performed to
illustrate the usage of the system and to verify the accuracy of the methods.
The database is then used to analyze a dynamical model for small-scale
intermittency in turbulence. Specifically, the dynamical effects of pressure
and viscous terms on the Lagrangian evolution of velocity increments are
evaluated using conditional averages calculated from the DNS data in the
database. It is shown that these effects differ considerably among themselves
and thus require different modeling strategies in Lagrangian models of velocity
increments and intermittency.


  We propose a Lorentzian derivation of the generalized entropy associated with
the island formula for black holes as a Wald-like entropy without reference to
the exterior non-gravitating region or field-theoretic von Neumann entropy of
Hawking radiation in a fixed curved spacetime background. We illustrate this
idea by studying two-dimensional black holes in the Jackiw-Teitelboim gravity
and the Russo-Susskind-Thorlacius model in which Hawking radiation is
represented by conformal scalars. With some prescriptions assumed, we show that
the generalized entropy for the island formula can be reproduced as the
Wald-like entropy of the two-dimensional dilaton-gravity theories upon the
inclusion of the backreaction from Hawking radiation described by conformal
anomaly. We give a discussion on how a similar idea can be applied to
higher-dimensional black holes. It is emphasized that the generalized entropy
is obtained in a fully gravitational fashion, yet it yields the same Page curve
as that of the half-gravitational set-up. We argue that the results in this
paper exacerbate the issues raised in the work of massive islands and
inconsistency of islands in theories of long-range gravity.


  In a recent multiwavelength study of galaxies at redshift ~ 2 by Daddi et al.
(2007a,b) it is shown that galaxies with a Mid-IR excess most likely harbor a
Compton-thick AGN, thus bringing to about 1/3 the fraction of z ~ 2 galaxies
hosting an AGN. This finding opens a number of intriguing issues concerning the
concomitant growth of galaxies and supermassive black holes, AGN feedback, and
downsizing, at the cosmic epoch of most intense star formation and nuclear
activity.


  A variety of natural language tasks require processing of textual data which
contains a mix of natural language and formal languages such as mathematical
expressions. In this paper, we take unit conversions as an example and propose
a data augmentation technique which leads to models learning both translation
and conversion tasks as well as how to adequately switch between them for
end-to-end localization.


  Stochastic gradient Markov chain Monte Carlo (SGMCMC) is a popular class of
algorithms for scalable Bayesian inference. However, these algorithms include
hyperparameters such as step size or batch size that influence the accuracy of
estimators based on the obtained posterior samples. As a result, these
hyperparameters must be tuned by the practitioner and currently no principled
and automated way to tune them exists. Standard MCMC tuning methods based on
acceptance rates cannot be used for SGMCMC, thus requiring alternative tools
and diagnostics. We propose a novel bandit-based algorithm that tunes the
SGMCMC hyperparameters by minimizing the Stein discrepancy between the true
posterior and its Monte Carlo approximation. We provide theoretical results
supporting this approach and assess various Stein-based discrepancies. We
support our results with experiments on both simulated and real datasets, and
find that this method is practical for a wide range of applications.


  The relation between free carrier absorption and intersubband transitions in
semiconductor heterostructures is resolved by comparing a sequence of
structures. Our numerical and analytical results show how free carrier
absorption evolves from the intersubband transitions in the limit of an
infinite number of wells with vanishing barrier width. It is explicitly shown
that the integral of the absorption over frequency matches the value obtained
by the f-sum rule. This shows that a proper treatment of intersubband
transitions is fully sufficient to simulate the entire electronic absorption in
heterostructure THz devices.


  One challenge for applying current weak lensing analysis tools to the Nancy
Grace Roman Space Telescope is that individual images will be undersampled. Our
companion paper presented an initial application of Imcom - an algorithm that
builds an optimal mapping from input to output pixels to reconstruct a fully
sampled combined image - on the Roman image simulations. In this paper, we
measure the output noise power spectra, identify the sources of the major
features in the power spectra, and show that simple analytic models that ignore
sampling effects underestimate the power spectra of the coadded noise images.
We compute the moments of both idealized injected stars and fully simulated
stars in the coadded images, and their 1- and 2-point statistics. We show that
the idealized injected stars have root-mean-square ellipticity errors (1 - 6) x
10-4 per component depending on the band; the correlation functions are >= 2
orders of magnitude below requirements, indicating that the image combination
step itself is using a small fraction of the overall Roman 2nd moment error
budget, although the 4th moments are larger and warrant further investigation.
The stars in the simulated sky images, which include blending and chromaticity
effects, have correlation functions near the requirement level (and below the
requirement level in a wide-band image constructed by stacking all 4 filters).
We evaluate the noise-induced biases in the ellipticities of injected stars,
and explain the resulting trends with an analytical model. We conclude by
enumerating the next steps in developing an image coaddition pipeline for
Roman.


  This paper seeks to establish a framework for directing a society of simple,
specialized, self-interested agents to solve what traditionally are posed as
monolithic single-agent sequential decision problems. What makes it challenging
to use a decentralized approach to collectively optimize a central objective is
the difficulty in characterizing the equilibrium strategy profile of
non-cooperative games. To overcome this challenge, we design a mechanism for
defining the learning environment of each agent for which we know that the
optimal solution for the global objective coincides with a Nash equilibrium
strategy profile of the agents optimizing their own local objectives. The
society functions as an economy of agents that learn the credit assignment
process itself by buying and selling to each other the right to operate on the
environment state. We derive a class of decentralized reinforcement learning
algorithms that are broadly applicable not only to standard reinforcement
learning but also for selecting options in semi-MDPs and dynamically composing
computation graphs. Lastly, we demonstrate the potential advantages of a
society's inherent modular structure for more efficient transfer learning.


  In this paper, we consider an adaptive approach to address optimization
problems with uncertain cost parameters. Here, the decision maker selects an
initial decision, observes the realization of the uncertain cost parameters,
and then is permitted to modify the initial decision. We treat the uncertainty
using the framework of robust optimization in which uncertain parameters lie
within a given set. The decision maker optimizes so as to develop the best cost
guarantee in terms of the worst-case analysis. The recourse decision is
``incremental"; that is, the decision maker is permitted to change the initial
solution by a small fixed amount. We refer to the resulting problem as the
robust incremental problem. We study robust incremental variants of several
optimization problems. We show that the robust incremental counterpart of a
linear program is itself a linear program if the uncertainty set is polyhedral.
Hence, it is solvable in polynomial time. We establish the NP-hardness for
robust incremental linear programming for the case of a discrete uncertainty
set. We show that the robust incremental shortest path problem is NP-complete
when costs are chosen from a polyhedral uncertainty set, even in the case that
only one new arc may be added to the initial path. We also address the
complexity of several special cases of the robust incremental shortest path
problem and the robust incremental minimum spanning tree problem.


  Gauge theories admit a generalisation in which the gauge group is replaced by
a finer algebraic structure, known as a 2-group. The first model of this type
is a Topological Quantum Field Theory introduced by Yetter. We discuss a common
generalisation of both the Yetter's model and Yang-Mills theory and in
particular we focus on the lattice formulation of such model for finite
2-groups. In the second part we present a particular realization based on a
2-group constructed from $\mathbb Z_4$ groups. In the selected model,
independent degrees of freedom are associated to both links and faces of a
four-dimensional lattice and are subject to a certain constraint. We present
the details of this construction, discuss the expected dynamics in different
regions of phase space and show numerical results from Monte Carlo simulations
corroborating these expectations.


  SAR (Synthetic Aperture Radar) tomography reconstructs 3-D volumes from
stacks of SAR images. High-resolution satellites such as TerraSAR-X provide
images that can be combined to produce 3-D models. In urban areas, sparsity
priors are generally enforced during the tomographic inversion process in order
to retrieve the location of scatterers seen within a given radar resolution
cell. However, such priors often miss parts of the urban surfaces. Those
missing parts are typically regions of flat areas such as ground or rooftops.
This paper introduces a surface segmentation algorithm based on the computation
of the optimal cut in a flow network. This segmentation process can be included
within the 3-D reconstruction framework in order to improve the recovery of
urban surfaces. Illustrations on a TerraSAR-X tomographic dataset demonstrate
the potential of the approach to produce a 3-D model of urban surfaces such as
ground, fa\c{c}ades and rooftops.


  (abridged) Deep long-slit optical spectrophotometric observations are
presented for 25 Galactic bulge planetary nebulae (GBPNe) and 6 Galactic disk
planetary nebulae (GDPNe). The spectra, combined with archival ultraviolet
spectra obtained with the International Ultraviolet Explorer (IUE) and infrared
spectra obtained with the Infrared Space Observatory (ISO), have been used to
carry out a detailed plasma diagnostic and element abundance analysis utilizing
both collisional excited lines (CELs) and optical recombination lines (ORLs).
  Comparisons of plasma diagnostic and abundance analysis results obtained from
CELs and from ORLs reproduce many of the patterns previously found for GDPNe.
In particular we show that the large discrepancies between electron
temperatures (Te's) derived from CELs and from ORLs appear to be mainly caused
by abnormally low values yielded by recombination lines and/or continua.
Similarly, the large discrepancies between heavy element abundances deduced
from ORLs and from CELs are largely caused by abnormally high values obtained
from ORLs, up to tens of solar in extreme cases. It appears that whatever
mechanisms are causing the ubiquitous dichotomy between CELs and ORLs, their
main effects are to enhance the emission of ORLs, but hardly affect that of
CELs. It seems that heavy element abundances deduced from ORLs may not reflect
the bulk composition of the nebula. Rather, our analysis suggests that ORLs of
heavy element ions mainly originate from a previously unseen component of
plasma of Te's of just a few hundred Kelvin, which is too cool to excite any
optical and UV CELs.


  We consider non-self-adjoint operators in Hilbert spaces of the form
$H=H_0+CWC$, where $H_0$ is self-adjoint, $W$ is bounded and $C$ is a metric
operator, $C$ bounded and relatively compact with respect to $H_0$. We suppose
that $C(H_0-z)^{-1}C$ is uniformly bounded in
$z\in\mathbb{C}\setminus\mathbb{R}$. We define the spectral singularities of
$H$ as the points of the essential spectrum
$\lambda\in\sigma_{\mathrm{ess}}(H)$ such that $C(H\pm i\varepsilon)^{-1}CW$
does not have a limit as $\varepsilon\to0^+$. We prove that the spectral
singularities of $H$ are in one-to-one correspondence with the eigenvalues,
associated to resonant states, of an extension of $H$ to a larger Hilbert
space. Next, we show that the asymptotically disappearing states for $H$, i.e.
the set of vectors $\varphi$ such that $e^{\pm itH}\varphi\to0$ as
$t\to\infty$, coincide with the generalized eigenstates of $H$ corresponding to
eigenvalues $\lambda\in\mathbb{C}$, $\mp\mathrm{Im}(\lambda)>0$. Finally, we
define the absolutely continuous spectral subspace of $H$ and show that it
satisfies $\mathcal{H}_{\mathrm{ac}}(H)=\mathcal{H}_{\mathrm{p}}(H^*)^\perp$,
where $\mathcal{H}_{\mathrm{p}}(H^*)$ stands for the point spectrum of $H^*$.
We thus obtain a direct sum decomposition of the Hilbert spaces in terms of
spectral subspaces of $H$. One of the main ingredients of our proofs is a
spectral resolution formula for a bounded operator $r(H)$ regularizing the
identity at spectral singularities. Our results apply to Schr\"odinger
operators with complex potentials.


  We present a study of the magnetic susceptibility of La_2-xSr_xCoO_4 single
crystals in a doping range 0.3<=x<=0.8. Our data shows a pronounced magnetic
anisotropy for all compounds. This anisotropy is in agreement with a low-spin
ground state (S=0) of Co^3+ for x>=0.4 and a high-spin ground state (S=3/2) of
Co^2+. We compare our data with a crystal-field model calculation assuming
local moments and find a good description of the magnetic behavior for x>=0.5.
This includes the pronounced kinks observed in the inverse magnetic
susceptibility, which result from the anisotropy and low-energy excited states
of Co^2+ and are not related to magnetic ordering or temperature-dependent
spin-state transitions.


  We compute by Bethe Ansatz both bulk and boundary hole scattering matrices
for the critical A_{N-1}^(1) quantum spin chain. The bulk S matrix coincides
with the soliton S matrix for the A_{N-1}^(1) Toda field theory with imaginary
coupling. We verify our result for the boundary S matrix using a generalization
of the Ghoshal-Zamolodchikov boundary crossing relation.