  We report on the experimental study of quadrupole collectivity in the
neutron-deficient nucleus \nuc{104}{Sn} using intermediate-energy Coulomb
excitation. The $B(E2; 0^+_1 \rightarrow 2^+_1)$ value for the excitation of
the first $2^+$ state in \nuc{104}{Sn} has been measured to be
$0.180(37)~e^2$b$^2$ relative to the well-known $B(E2)$ value of \nuc{102}{Cd}.
This result disagrees by more than one sigma with a recently published
measurement \cite{Gua13}. Our result indicates that the most modern many-body
calculations remain unable to describe the enhanced collectivity below
mid-shell in Sn approaching $N=Z=50$. We attribute the enhanced collectivity to
proton particle-hole configurations beyond the necessarily limited shell-model
spaces and suggest the asymmetry of the $B(E2)$-value trend around mid-shell to
originate from enhanced proton excitations across $Z=50$ as $N=Z$ is
approached.


  We show that it is possible to fully determine the neutrino mass spectrum
from two-zero textures of the neutrino mass matrix. As a consequence, definite
predictions can be obtained for the neutrinoless double beta decay.


  With the rapid development of large models, the need for data has become
increasingly crucial. Especially in 3D object detection, costly manual
annotations have hindered further advancements. To reduce the burden of
annotation, we study the problem of achieving 3D object detection solely based
on 2D annotations. Thanks to advanced 3D reconstruction techniques, it is now
feasible to reconstruct the overall static 3D scene. However, extracting
precise object-level annotations from the entire scene and generalizing these
limited annotations to the entire scene remain challenges. In this paper, we
introduce a novel paradigm called BA$^2$-Det, encompassing pseudo label
generation and multi-stage generalization. We devise the DoubleClustering
algorithm to obtain object clusters from reconstructed scene-level points, and
further enhance the model's detection capabilities by developing three stages
of generalization: progressing from complete to partial, static to dynamic, and
close to distant. Experiments conducted on the large-scale Waymo Open Dataset
show that the performance of BA$^2$-Det is on par with the fully-supervised
methods using 10% annotations. Additionally, using large raw videos for
pretraining,BA$^2$-Det can achieve a 20% relative improvement on the KITTI
dataset. The method also has great potential for detecting open-set 3D objects
in complex scenes. Project page: https://ba2det.site.


  Recent results on searches for physics beyond the Standard Model at Large
Hadron Collider are presented, based on early LHC data in proton-proton
collisions at $\sqrt{s} = 7$ TeV collected by the CMS experiment. Prospects of
early SUSY searches at CMS are also outlined.


  We describe the derivation of the InterHourly Variability (IHV) index of
geomagnetic activity. The IHV-index for a geomagnetic element is mechanically
derived from hourly values as the sum of the unsigned differences between
adjacent hours over a seven-hour interval centered on local midnight. The index
is derived separately for stations in both hemispheres within six longitude
sectors using only local night hours. It is intended as a long-term index.
Available data allows derivation of the index back well into the 19th century.
On a time scale of a 27-day Bartels rotation, IHV averages for stations with
corrected geomagnetic latitude less than 55 degrees are strongly correlated
with midlatitude range indices. Assuming a constant calibration of the aa-index
we find that observed yearly values of aa before the year 1957 are 2.9 nT too
small compared to values calculated from IHV using the regression constants
based on 1980-2004. We interpret this discrepancy as an indication that the
calibration of the aa index is in error before 1957. There is no such problem
with the ap index. Rotation averages of IHV are also strongly correlated with
solar wind parameters (BV^2). On a time scale of a year combining the IHV-index
and the recently-developed Inter-Diurnal Variability (IDV) index (giving B)
allows determination of solar wind speed, V, from 1890-present. Over the
~120-year series, the yearly mean solar wind speed varied from a low of 303
km/s in 1902 to a high value of 545 km/s in 2003. The calculated yearly values
of the product BV using B and V separately derived from IDV and IHV agree
quantitatively with (completely independent) BV derived from the amplitude of
the diurnal variation of the H component in the polar caps since 1926 and
sporadically beyond.


  Alkali-metal-vapor magnetometers, using coherent precession of polarized
atomic spins for magnetic field measurement, have become one of the most
sensitive magnetic field detectors. Their application areas range from
practical uses such as detections of NMR signals to fundamental physics
research such as searches for permanent electric dipole moments. One of the
main noise sources of atomic magnetometers comes from the light shift that
depends on the frequency of the pump laser. In this work, we theoretically
study the light shift, taking into account the relaxation due to the optical
pumping and the collision between alkali atoms and between alkali atoms and the
buffer gas. Starting from a full master equation containing both the ground and
excited states, we adiabatically eliminate the excited states and obtain an
effective master equation in the ground-state subspace that shows an intuitive
picture and dramatically accelerates the numerical simulation. Solving this
effective master equation, we find that in the light-narrowing regime, where
the line width is reduced while the coherent precession signal is enhanced, the
frequency-dependence of the light shift is largely reduced, which agrees with
experimental observations in cesium magnetometers. Since this effective master
equation is general and is easily solved, it can be applied to an extensive
parameter regime, and also to study other physical problems in
alkali-metal-vapor magnetometers, such as heading errors.


  This paper reviews our current understanding of the possible birth
environments of our Solar System. Since most stars form within groups and
clusters, the question becomes one of determining the nature of the birth
aggregate of the Sun. This discussion starts by reviewing Solar System
properties that provide constraints on our environmental history. We then
outline the range of star-forming environments that are available in the
Galaxy, and discuss how they affect star and planet formation. The nature of
the solar birth cluster is constrained by many physical considerations,
including radiation fields provided by the background environment, dynamical
scattering interactions, and by the necessity of producing the short-lived
radioactive nuclear species inferred from meteoritic measurements. Working
scenarios for the solar birth aggregate can be constructed, as discussed
herein, although significant uncertainties remain.


  Predicting and analyzing global behaviour of complex systems is challenging
due to the intricate nature of their component interactions. Recent work has
started modelling complex systems using networks endowed with multiway
interactions among nodes, known as higher-order networks. In this context,
simplicial complexes are a class of higher-order networks that have received
significant attention due to their topological structure and connections to
Hodge theory. Topological signal processing utilizes these connections to
analyze and manipulate signals defined on non-Euclidean domains such as
simplicial complexes. In this work, we present a general quantum algorithm for
implementing filtering processes in TSP and describe its application to
extracting network data based on the Hodge decomposition. We leverage
pre-existing tools introduced in recent quantum algorithms for topological data
analysis and combine them with spectral filtering techniques using the quantum
singular value transformation framework. While this paper serves as a
proof-of-concept, we obtain a super-polynomial improvement over the best known
classical algorithms for TSP filtering processes, modulo some important caveats
about encoding and retrieving the data from a quantum state. The proposed
algorithm generalizes the applicability of tools from quantum topological data
analysis to novel applications in analyzing high-dimensional complex systems.


  In this work we study the relevance of the component separation technique
based on the Independent Component Analysis (ICA) and investigate its
performance in the context of a limited sky coverage observation and from the
viewpoint of our ability to differentiate between cosmological models with
different primordial B-mode content. We focus on the low Galactic emission sky
patch, corresponding to the target of several operating and planned CMB
experiments and which, in many respects, adequately represents a typical
"clean" high latitude sky. We consider two fiducial observations, one operating
at low (40, 90 GHz) and one at high (150, 350 GHz) frequencies and thus
dominated by the synchrotron and thermal dust emission, respectively. We use a
parallel version of the FASTICA code to explore a substantial parameter space
including Gaussian pixel noise level, observed sky area and the amplitude of
the foreground emission and employ large Monte Carlo simulations to quantify
errors and biases pertinent to the reconstruction for different choices of the
parameter values. We identify a large subspace of the parameter space for which
the quality of the CMB reconstruction is excellent. For both the cosmological
models, with and without the primordial gravitational waves, we find that
FASTICA performs extremely well even in the cases when the B mode CMB signal is
up to a few times weaker than the foreground contamination and the noise
amplitude is comparable with the total CMB polarized emission. In addition we
discuss limiting cases of the noise and foreground amplitudes, for which the
ICA approach fails.


  Gravitational wave (GW) standard sirens may resolve the Hubble tension,
provided that standard siren inference of $H_0$ is free from systematic biases.
However, standard sirens from binary neutron star (BNS) mergers suffer from two
sources of systematic bias, one arising from the anisotropy of GW emission, and
the other from the anisotropy of electromagnetic (EM) emission from the
kilonova. For an observed sample of BNS mergers, the traditional Bayesian
approach to debiasing involves the direct computation of the detection
likelihood. This is infeasible for large samples of detected BNS merger due to
the high dimensionality of the parameter space governing merger detection. In
this study, we bypass this computation by fitting the Hubble constant to
forward simulations of the observed GW and EM data under a simulation-based
inference (SBI) framework using marginal neural ratio estimation. A key
innovation of our method is the inclusion of BNS mergers which were only
detected in GW, which allows for estimation of the bias introduced by EM
anisotropy. Our method corrects for $\sim$90$\%$ of the bias in the inferred
value of $H_0$ when telescope follow-up observations of BNS mergers have
extensive tiling of the merger localization region, using known telescope
sensitivities and assuming a model of kilonova emission. Our SBI-based method
thus enables a debiased inference of the Hubble constant of BNS mergers,
including both mergers with detected EM counterparts and those without.


  The low-x behavior of the linearly polarized gluon density h_{g}(x,k_t^2,
Q^2) in nuclei is studied in the rescaling model at small transverse momentum
k_t.


  Programming for today's quantum computers is making significant strides
toward modern workflows compatible with high performance computing (HPC), but
fundamental challenges still remain in the integration of these vastly
different technologies. Quantum computing (QC) programming languages share some
common ground, as well as their emerging runtimes and algorithmic modalities.
In this short paper, we explore avenues of refinement for the quantum
processing unit (QPU) in the context of many-tasks management, asynchronous or
otherwise, in order to understand the value it can play in linking QC with HPC.
Through examples, we illustrate how its potential for scientific discovery
might be realized.


  Stakeholders constantly make assumptions in the development of deep learning
(DL) frameworks. These assumptions are related to various types of software
artifacts (e.g., requirements, design decisions, and technical debt) and can
turn out to be invalid, leading to system failures. Existing approaches and
tools for assumption management usually depend on manual identification of
assumptions. However, assumptions are scattered in various sources (e.g., code
comments, commits, and issues) of DL framework development, and manually
identifying assumptions has high costs (e.g., time and resources). The
objective of the study is to evaluate different classification models for the
purpose of identification with respect to assumptions from the point of view of
developers and users in the context of DL framework projects (i.e., issues,
pull requests, and commits) on GitHub. We constructed a new and largest dataset
(i.e., AssuEval) of assumptions collected from the TensorFlow and Keras
repositories on GitHub; explored the performance of seven non-transformers
based models (e.g., Support Vector Machine, Classification and Regression
Trees), the ALBERT model, and three large language models (i.e., ChatGPT,
Claude, and Gemini) for identifying assumptions on the AssuEval dataset. The
study results show that ALBERT achieves the best performance (f1-score: 0.9584)
for identifying assumptions on the AssuEval dataset, which is much better than
the other models (the 2nd best f1-score is 0.8858, achieved by the Claude 3.5
Sonnet model). Though ChatGPT, Claude, and Gemini are popular large language
models, we do not recommend using them to identify assumptions in DL framework
development because of their low performance. This study provides researchers
with the largest dataset of assumptions for further research and helps
practitioners better understand assumptions and how to manage them in their
projects.


  MDS self-dual codes have nice algebraic structures, theoretical significance
and practical implications. In this paper, we present three classes of
$q^2$-ary Hermitian self-dual (extended) generalized Reed-Solomon codes with
different code locators. Combining the results in Ball et al. (Designs, Codes
and Cryptography, 89: 811-821, 2021), we show that if the code locators do not
contain zero, $q^2$-ary Hermitian self-dual (extended) GRS codes of length
$\geq 2q\ (q>2)$ does not exist. Under certain conditions, we prove Conjecture
3.7 and Conjecture 3.13 proposed by Guo and Li et al. (IEEE Communications
Letters, 25(4): 1062-1065, 2021).


  We present a multi-stage 3D computer-aided detection and diagnosis (CAD)
model for automated localization of clinically significant prostate cancer
(csPCa) in bi-parametric MR imaging (bpMRI). Deep attention mechanisms drive
its detection network, targeting salient structures and highly discriminative
feature dimensions across multiple resolutions. Its goal is to accurately
identify csPCa lesions from indolent cancer and the wide range of benign
pathology that can afflict the prostate gland. Simultaneously, a decoupled
residual classifier is used to achieve consistent false positive reduction,
without sacrificing high sensitivity or computational efficiency. In order to
guide model generalization with domain-specific clinical knowledge, a
probabilistic anatomical prior is used to encode the spatial prevalence and
zonal distinction of csPCa. Using a large dataset of 1950 prostate bpMRI paired
with radiologically-estimated annotations, we hypothesize that such CNN-based
models can be trained to detect biopsy-confirmed malignancies in an independent
cohort.
  For 486 institutional testing scans, the 3D CAD system achieves
83.69$\pm$5.22% and 93.19$\pm$2.96% detection sensitivity at 0.50 and 1.46
false positive(s) per patient, respectively, with 0.882$\pm$0.030 AUROC in
patient-based diagnosis $-$significantly outperforming four state-of-the-art
baseline architectures (U-SEResNet, UNet++, nnU-Net, Attention U-Net) from
recent literature. For 296 external biopsy-confirmed testing scans, the
ensembled CAD system shares moderate agreement with a consensus of expert
radiologists (76.69%; $kappa$ $=$ 0.51$\pm$0.04) and independent pathologists
(81.08%; $kappa$ $=$ 0.56$\pm$0.06); demonstrating strong generalization to
histologically-confirmed csPCa diagnosis.


  A sender flexibly acquires evidence--which she may pay a third party to
certify--to disclose to a receiver. When evidence acquisition is overt, the
receiver observes the evidence gathering process irrespective of whether its
outcome is certified. When acquisition is covert, the receiver does not. In
contrast to the case with exogenous evidence, the receiver prefers a strictly
positive certification cost. As acquisition costs vanish, equilibria converge
to the Pareto-worst free-learning equilibrium. The receiver always prefers
covert to overt evidence acquisition.


  A new method of controllable injection to generate high quality electron
bunches in the nonlinear blowout regime driven by electron beams is proposed
and demonstrated using particle-in-cell simulations. Injection is facilitated
by decreasing the wake phase velocity through varying the spot size of the
drive beam and can be tuned through the Courant-Snyder (CS) parameters. Two
regimes are examined. In the first, the spot size is focused according to the
vacuum CS beta function, while in the second, it is focused by the plasma ion
column. The effects of the driver intensity and vacuum CS parameters on the
wake velocity and injected beam parameters are examined via theory and
simulations. For plasma densities of $\sim 10^{19} ~\text{cm}^{-3}$,
particle-in-cell (PIC) simulations demonstrate that peak normalized
brightnesses $\gtrsim 10^{20}~\text{A}/\text{m}^2/\text{rad}^2$ can be obtained
with projected energy spreads of $\lesssim 1\%$ within the middle section of
the injected beam, and with normalized slice emittances as low as $\sim 10
~\text{nm}$.


  We show that the traces of $U_q(\widehat{\mathfrak{sl}}_2)$-intertwiners of
Etingof-Schiffmann-Varchenko valued in the three-dimensional evaluation
representation converge in a certain region of parameters and give a
representation-theoretic construction of Felder-Varchenko's hypergeometric
solutions to the $q$-KZB heat equation. This gives the first proof that such a
trace function converges and resolves the first case of the Etingof-Varchenko
conjecture.
  As applications, we prove a symmetry property for traces of intertwiners and
prove Felder-Varchenko's conjecture that their elliptic Macdonald polynomials
are related to the affine Macdonald polynomials defined as traces over
irreducible integrable $U_q(\widehat{\mathfrak{sl}}_2)$-modules by
Etingof-Kirillov Jr. In the trigonometric and classical limits, we recover
results of Etingof-Kirillov Jr. and Etingof-Varchenko. Our method relies on an
interplay between the method of coherent states applied to the free field
realization of the $q$-Wakimoto module of Matsuo, convergence properties given
by the theta hypergeometric integrals of Felder-Varchenko, and rationality
properties originating from the representation-theoretic definition of the
trace function.


  Estimates of population characteristics such as domain means are often
expected to follow monotonicity assumptions. Recently, a method to adaptively
pool neighboring domains was proposed, which ensures that the resulting domain
mean estimates follow monotone constraints. The method leads to asymptotically
valid estimation and inference, and can lead to substantial improvements in
efficiency, in comparison with unconstrained domain estimators. However,
assuming incorrect shape constraints could lead to biased estimators. Here, we
develop the Cone Information Criterion for Survey Data (CICs) as a diagnostic
method to measure monotonicity departures on population domain means. We show
that the criterion leads to a consistent methodology that makes an
asymptotically correct decision choosing between unconstrained and constrained
domain mean estimators.


  The basic ingredients of the Spontaneous Symmetry Breaking Phenomenon and of
the Higgs Mechanism are reviewed in these lectures of pedagogical character.
Some relevant topics related with the breaking $\gs \rightarrow U(1)_{\rm em}$
are selected and discussed here. A brief survey of the experimental Higgs
particle searches and the theoretical limits on $\mh$ are also presented. The
main features of the most popular models of symmetry breaking beyond the
Standard Model are briefly considered. It includes a short summary of the Higgs
Sector in the Minimal SUSY Model, the basic ideas of Technicolor models and a
brief introduction to Strongly Interacting Scalar sectors and to the Effective
Chiral Lagrangian Approach to the Electroweak Theory.


  The tunable properties of molecular materials place them among the favorites
for a variety of future generation devices. In addition, to maintain the
current trend of miniaturization of those devices, a departure from the present
top-down production methods may soon be required and self-assembly appears
among the most promising alternatives. On-surface synthesis unites the promises
of molecular materials and of self-assembly, with the sturdiness of covalently
bonded structures: an ideal scenario for future applications. Following this
idea, we report the synthesis of functional extended nanowires by
self-assembly. In particular, the products correspond to one-dimensional
organic semiconductors. The uniaxial alignment provided by our substrate
templates allows us to access with exquisite detail their electronic
properties, including the full valence band dispersion, by combining local
probes with spatial averaging techniques. We show how, by selectively doping
the molecular precursors, the product's energy level alignment can be tuned
without compromising the charge carrier's mobility.


  The penetration depth is calculated over the entire doping range of the
cuprate phase diagram with emphasis on the underdoped regime. Pseudogap
formation on approaching the Mott transition, for doping below a quantum
critical point, is described within a model based on the resonating valence
bond spin liquid which provides an ansatz for the coherent piece of the Green's
function. Fermi surface reconstruction, which is an essential element of the
model, has a strong effect on the superfluid density at T=0 producing a sharp
drop in magnitude, but does not change the slope of the linear low temperature
variation. Comparison with recent data on Bi-based cuprates provides validation
of the theory and shows that the effects of correlations, captured by
Gutzwiller factors, are essential for a qualitative understanding of the data.
We find that the Ferrell-Glover-Tinkham sum rule still holds and we compare our
results with those for the Fermi arc and the nodal liquid models.


  We study the upper bounds for $A(n,d)$, the maximum size of codewords with
length $n$ and Hamming distance at least $d$. Schrijver studied the Terwilliger
algebra of the Hamming scheme and proposed a semidefinite program to bound
$A(n, d)$. We derive more sophisticated matrix inequalities based on a split
Terwilliger algebra to improve Schrijver's semidefinite programming bounds on
$A(n, d)$. In particular, we improve the semidefinite programming bounds on
$A(18,4)$ to $6551$.


  In this paper we propose a Sequential Representation Quantization AutoEncoder
(SeqRQ-AE) to learn from primarily unpaired audio data and produce sequences of
representations very close to phoneme sequences of speech utterances. This is
achieved by proper temporal segmentation to make the representations
phoneme-synchronized, and proper phonetic clustering to have total number of
distinct representations close to the number of phonemes. Mapping between the
distinct representations and phonemes is learned from a small amount of
annotated paired data. Preliminary experiments on LJSpeech demonstrated the
learned representations for vowels have relative locations in latent space in
good parallel to that shown in the IPA vowel chart defined by linguistics
experts. With less than 20 minutes of annotated speech, our method outperformed
existing methods on phoneme recognition and is able to synthesize intelligible
speech that beats our baseline model.


  Internet Banking System refers to systems that enable bank customers to
access accounts and general information on bank products and services through a
personal computer or other intelligent device. Internet banking products and
services can include detailed account information for corporate customers as
well as account summery and transfer money. Ultimately, the products and
services obtained through Internet Banking may mirror products and services
offered through other bank delivery channels. In this paper, Internet Banking
System Prototype has been proposed in order to illustrate the services which is
provided by the Bank online services.


  We use a simple cosmological model with two parameters $(A_s, n_s)$ to
illustrate the impact of using Halofit on error forecast based on Fisher
information matrix for a $h^{-3} Gpc^3$ volume survey. We show that Halofit
fails to reproduce well the derivatives of the power spectrum with respect to
the cosmological parameters despite the good fit produced for its amplitude. We
argue that the poor performance on the derivatives prediction is a general
feature of this model and we exhibit the response function for the Halofit to
show how it compares with the same quantity measured on simulations. The
analytic structure of the Halofit response function points towards the origin
of its weak performance at reproducing the derivatives of the non-linear power
spectrum, which translates into unreliable Fisher information matrices.


  The rotational invariance under the usual physical angular momentum of the
SUq(2) Hamiltonian for the description of rotational molecular spectra is
explicitly proved and a connection of this Hamiltonian to the formalism of
Amal'sky is provided. In addition, a new Hamiltonian for rotational spectra is
introduced, based on the construction of irreducible tensor operators (ITOs)
under SUq(2) and use of q-deformed tensor products and q-deformed
Clebsch-Gordan coefficients. The rotational invariance of this SUq(2) ITO
Hamiltonian under the usual physical angular momentum is explicitly proved and
a simple closed expression for its energy spectrum (the ``hyperbolic tangent
formula'') is introduced. Numerical tests against an experimental rotational
band of HF are provided.


  A novel hybrid deep neural network architecture is designed to capture the
spatial-temporal features of unsteady flows around moving boundaries directly
from high-dimensional unsteady flow fields data. The hybrid deep neural network
is constituted by the convolutional neural network (CNN), improved
convolutional Long-Short Term Memory neural network (ConvLSTM) and
deconvolutional neural network (DeCNN). Flow fields at future time step can be
predicted through flow fields by previous time steps and boundary positions at
those steps by the novel hybrid deep neural network. Unsteady wake flows around
a forced oscillation cylinder with various amplitudes are calculated to
establish the datasets as training samples for training the hybrid deep neural
networks. The trained hybrid deep neural networks are then tested by predicting
the unsteady flow fields around a forced oscillation cylinder with new
amplitude. The effect of neural network structure parameters on prediction
accuracy was analyzed. The hybrid deep neural network, constituted by the best
parameter combination, is used to predict the flow fields in the future time.
The predicted flow fields are in good agreement with those calculated directly
by computational fluid dynamic solver, which means that this kind of deep
neural network can capture accurate spatial-temporal information from the
spatial-temporal series of unsteady flows around moving boundaries. The result
shows the potential capability of this kind novel hybrid deep neural network in
flow control for vibrating cylinder, where the fast calculation of
high-dimensional nonlinear unsteady flow around moving boundaries is needed.


  We use astrometry, broad-band photometry and variability information from the
Data Release 2 of ESA's Gaia mission (GDR2) to identify members of the Orphan
Stream (OS) across the whole sky. The stream is traced above and below the
celestial equator and in both Galactic hemispheres, thus increasing its visible
length to ~ 210 degrees equivalent to ~150 kpc in physical extent. Taking
advantage of the large number of RR Lyrae stars in the OS, we extract accurate
distances and proper motions across the entire stretch of the tidal debris
studied. As delineated by the GDR2 RR Lyrae, the stream exhibits two prominent
twists in its shape on the sky which are accompanied by changes in the
tangential motion. We complement the RR Lyrae maps with those created using
GDR2 Red Giants and the DECam Legacy Survey Main Sequence Turn-Off stars. The
behavior of the OS track on the sky is consistent across all three tracers
employed. We detect a strong non-zero motion in the across-stream direction for
a substantial portion of the stream. Such a misalignment between the debris
track and the streaming velocity cannot be reproduced in a static gravitational
potential and signals an interaction with a massive perturber.


  Providing fault-tolerance for long-running GPU-intensive jobs requires
application-specific solutions, and often involves saving the state of complex
data structures spread among many graphics libraries. This work describes a
mechanism for transparent GPU-independent checkpoint-restart of 3D graphics.
The approach is based on a record-prune-replay paradigm: all OpenGL calls
relevant to the graphics driver state are recorded; calls not relevant to the
internal driver state as of the last graphics frame prior to checkpoint are
discarded; and the remaining calls are replayed on restart. A previous approach
for OpenGL 1.5, based on a shadow device driver, required more than 78,000
lines of OpenGL-specific code. In contrast, the new approach, based on
record-prune-replay, is used to implement the same case in just 4,500 lines of
code. The speed of this approach varies between 80 per cent and nearly 100 per
cent of the speed of the native hardware acceleration for OpenGL 1.5, as
measured when running the ioquake3 game under Linux. This approach has also
been extended to demonstrate checkpointing of OpenGL 3.0 for the first time,
with a demonstration for PyMol, for molecular visualization.


  In 2013 A.A. Borovkov and A.A. Mogulskii proved a weaker-than-standard
"metric" large deviations principle (LDP) for trajectories of random walks in
$R^d$ whose increments have the Laplace transform finite in a neighbourhood of
zero. We prove that general metric LDPs are preserved under uniformly
continuous mappings. This allows us to transform the result of Borovkov and
Mogulskii into standard LDPs. We also give an explicit integral representation
of the rate function they found. As an application, we extend the classical
Cram'er theorem by proving an LPD for kernel-weighted sums of i.i.d. random
vectors in $R^d$.


  In both molecular physics and condensed matter theory, deeper understanding
of the correlation energy density epsilon_c (r) remains a high priority. By
adopting Loewdin's definition of correlation energy as the difference between
the exact and the Hartree-Fock values, here we propose two alternative routes
to define this. One of these involves both exact and Hartree-Fock (HF)
wavefunctions, while the second requires a coupling constant integration. As an
exact analytical example of the first route, we treat the two-electron model
atom of Moshinsky, for which both confinement potential and interactions are
harmonic. Though the correlation energy density epsilon_c (r) is known
analytically, we also investigate numerically its relation to the exact
ground-state density in this example.


  We propose and demonstrate a novel method to reduce the pulse width and
timing jitter of a relativistic electron beam through THz-driven beam
compression. In this method the longitudinal phase space of a relativistic
electron beam is manipulated by a linearly polarized THz pulse in a dielectric
tube such that the bunch tail has a higher velocity than the bunch head, which
allows simultaneous reduction of both pulse width and timing jitter after
passing through a drift. In this experiment, the beam is compressed by more
than a factor of four from 130 fs to 28 fs with the arrival time jitter also
reduced from 97 fs to 36 fs, opening up new opportunities in using pulsed
electron beams for studies of ultrafast dynamics. This technique extends the
well known rf buncher to the THz frequency and may have a strong impact in
accelerator and ultrafast science facilities that require femtosecond electron
beams with tight synchronization to external lasers.


  In this paper we present KiT-RT (Kinetic Transport Solver for Radiation
Therapy), an open-source C++ based framework for solving kinetic equations in
radiation therapy applications. The aim of this code framework is to provide a
collection of classical deterministic solvers for unstructured meshes that
allow for easy extendability. Therefore, KiT-RT is a convenient base to test
new numerical methods in various applications and compare them against
conventional solvers. The implementation includes spherical-harmonics, minimal
entropy, neural minimal entropy and discrete ordinates methods. Solution
characteristics and efficiency are presented through several test cases ranging
from radiation transport to electron radiation therapy. Due to the variety of
included numerical methods and easy extendability, the presented open source
code is attractive for both developers, who want a basis to build their own
numerical solvers and users or application engineers, who want to gain
experimental insights without directly interfering with the codebase.


  We consider the orbital evolution of satellites in galaxy mergers, focusing
on the evolution of eccentricity. Using a large suite of N-body simulations, we
study the phenomenon of satellite orbital radialization -- a profound increase
in the eccentricity of its orbit as it decays under dynamical friction. While
radialization is detected in a variety of different setups, it is most
efficient in the cases of high satellite mass, not very steep host density
profiles, and high initial eccentricity. To understand the origin of this
phenomenon, we run additional simulations with various physical factors
selectively turned off: satellite mass loss, reflex motion and distortion of
the host, etc. We find that all these factors are important for radialization,
since it does not occur for point-mass satellites or when the host potential is
replaced with an unperturbed initial profile. The analysis of forces and
torques acting on both galaxies confirms the major role of self-gravity of both
host and satellite in the reduction of orbital angular momentum. The classical
Chandrasekhar dynamical friction formula, which accounts only for the forces
between the host and the satellite, but not for internal distortions of both
galaxies, does not match the evolution of eccentricity observed in N-body
simulations.


  We consider the problem of inserting one item into a list of N-1 ordered
items. We previously showed that no quantum algorithm could solve this problem
in fewer than log N/(2 log log N) queries, for N large. We transform the
problem into a "translationally invariant" problem and restrict attention to
invariant algorithms. We construct the "greedy" invariant algorithm and show
numerically that it outperforms the best classical algorithm for various N. We
also find invariant algorithms that succeed exactly in fewer queries than is
classically possible, and iterating one of them shows that the insertion
problem can be solved in fewer than 0.53 log N quantum queries for large N
(where log N is the classical lower bound). We don't know whether a o(log N)
algorithm exists.


  With sintered needles aligned and a magnetic field applied transverse to its
easy axis, the rare-earth ferromagnet Nd$_2$Fe$_{14}$B becomes a
room-temperature realization of the Random Field Ising Model. The transverse
field tunes the pinning potential of the magnetic domains in a continuous
fashion. We study the magnetic domain reversal and avalanche dynamics between
liquid helium and room temperatures at a series of transverse fields using a
Barkhausen noise technique. The avalanche size and energy distributions follow
power-law behavior with a cutoff dependent on the pinning strength dialed in by
the transverse field, consistent with theoretical predictions for Barkhausen
avalanches in disordered materials. A scaling analysis reveals two regimes of
behavior: one at low temperature and high transverse field, where the dynamics
are governed by the randomness, and the second at high temperature and low
transverse field where thermal fluctuations dominate the dynamics.


  We consider a class of particle systems which appear in various applications
such as approximation theory, plasticity, potential theory and space-filling
designs. The positions of the particles on the real line are described as a
global minimum of an interaction energy, which consists of a nonlocal,
repulsive interaction part and a confining part. Motivated by the applications,
we cover non-standard scenarios in which the confining potential weakens as the
number of particles increases. This results in a large area over which the
particles spread out. Our aim is to approximate the particle interaction energy
by a corresponding continuum interacting energy. Our main results are bounds on
the corresponding energy difference and on the difference between the related
potential values. We demonstrate that these bounds are useful to problems in
approximation theory and plasticity. The proof of these bounds relies on
convexity assumptions on the interaction and confining potentials. It combines
recent advances in the literature with a new upper bound on the minimizer of
the continuum interaction energy.


  Mobile medical imaging devices are invaluable for clinical diagnostic
purposes both in and outside healthcare institutions. Among the various imaging
modalities, only a few are readily portable. Magnetic resonance imaging (MRI),
the gold standard for numerous healthcare conditions, does not traditionally
belong to this group. Recently, low-field MRI start-up companies have
demonstrated the first decisive steps towards portability within medical
facilities, but these are so far incompatible with more demanding use cases
such as in remote and developing regions, sports facilities and events, medical
and military camps, or home healthcare. Here we present in vivo images taken
with a light, home-made, low-field extremity MRI scanner outside the controlled
environment provided by medical facilities. To demonstrate the true portability
of the system and benchmark its performance in various relevant scenarios, we
have acquired images of a volunteer's knee in: i) an MRI physics laboratory;
ii) an office room; iii) outside a campus building, connected to a nearby power
outlet; iv) in open air, powered from a small fuel-based generator; and v) at
the volunteer's home. All images have been acquired within clinically viable
times, and signal-to-noise ratios (SNR) and tissue contrast suffice for 2D and
3D reconstructions with diagnostic value, with comparable overall image quality
across all five situations. Furthermore, the volunteer carries a fixation
metallic implant screwed to the femur, which leads to strong artifacts in
standard clinical systems but appears sharp in our low-field acquisitions.
Altogether, this work opens a path towards highly accessible MRI under
circumstances previously unrealistic.


This paper has been replaced by hep-ph/9908225.


  With a combination of simple analytical arguments and extensive numerical
simulations, we theoretically propose a Josephson junction with $n+1$
superconductors where the current-phase relation can be toggled in situ between
a $\sin(\delta\varphi)$ and $\sin(\delta\varphi/n)$ shape using an applied
magnetic field. Focusing in particular on the case $n=2$, we show that by using
realistic system parameters such as unequal interface transparencies, the
$\sin(\delta\varphi/2)$-shaped solution retains its $2\pi$-periodicity due to
discontinuities at $\delta\varphi = \pm \pi$. Moreover, we demonstrate that as
one toggles between the $\sin(\delta\varphi)$- and
$\sin(\delta\varphi/2)$-shaped solutions, the system acts as an on--off switch,
and can acheive more than two orders of magnitude difference between the
supercurrent in the on and off states. Finally, we argue that the same approach
can be generalized to switchable $\sin(\delta\varphi/n)$ junctions for
arbitrary integers~$n$, which we motivate by analytically solving the Josephson
equations for double- and triple-barrier junctions.


  The Lyman-alpha (Lya) emission has played an important role in detecting
high-redshift galaxies, including recently distant ones at redshift z > 7. It
may also contain important information on the origin of these galaxies. Here,
we investigate the formation of a typical L* galaxy and its observational
signatures at the earliest stage, by combining a cosmological hydrodynamic
simulation with three-dimensional radiative transfer calculations using the
newly improved ART^2 code. Our cosmological simulation uses the Aquila initial
condition which zooms in onto a Milky Way-like halo with high resolutions, and
our radiative transfer couples multi-wavelength continuum, Lya line, and
ionization of hydrogen. We find that the modeled galaxy starts to form at
redshift z ~ 24 through efficient accretion of cold gas, which produces a
strong Lya line with a luminosity of L(Lya) ~ 10^42 erg/s as early as z ~ 14.
The Lya emission appears to trace the cold, dense gas. The lines exhibit
asymmetric, single-peak profiles, and are shifted to the blue wing, a
characteristic feature of gas inflow. Moreover, the contribution to the total
Lya luminosity by excitation cooling increases with redshift, and it becomes
dominant at z >~ 6. We predict that L* galaxies such as the modeled one may be
detected at z <~ 8 by JWST and ALMA with a reasonable integration time. Beyond
redshift 12, however, only Lya line may be observable by spectroscopic surveys.
Our results suggest that Lya line is one of the most powerful tools to detect
the first generation of galaxies, and to decipher their formation mechanism.


  The \CP-violating charge asymmetry in $B^{\pm}\rightarrow \phi K^{\pm}$
decays is measured in a sample of $pp$ collisions at 7 TeV centre-of-mass
energy, corresponding to an integrated luminosity of 1.0 fb$^{-1}$ collected by
the LHCb experiment. The result is $\mathcal{A}_{CP}(B^{\pm}\rightarrow \phi
K^{\pm}) = \rm 0.022\pm 0.021 \pm 0.009$, where the first uncertainty is
statistical and the second systematic. In addition, a search for the
$B^{\pm}\rightarrow \phi \pi^{\pm}$ decay mode is performed, using the
$B^{\pm}\rightarrow \phi K^{\pm}$ decay rate for normalization. An upper limit
on the branching fraction $\mathcal{B}(B^{\pm}\rightarrow \phi \pi^{\pm})<
1.5\times 10^{-7}$ is set at 90% confidence level.


  Let $G$ be a non-compact connected semisimple real Lie group with finite
center. Suppose $L$ is a non-compact connected closed subgroup of $G$ acting
transitively on a symmetric space $G/H$ such that $L\cap H$ is compact. We
study the action on $L/L\cap H$ of a Dirac operator $D_{G/H}(E)$ acting on
sections of an $E$-twist of the spin bundle over $G/H$. As a byproduct, in the
case of $(G,H,L)=(SL(2,{\mathbb R})\times SL(2,{\mathbb
R}),\Delta(SL(2,{\mathbb R})\times SL(2,{\mathbb R})),SL(2,{\mathbb R})\times
SO(2))$, we identify certain representations of $L$ which lie in the kernel of
$D_{G/H}(E)$.


  Near infrared color centers in silicon are emerging candidates for on-chip
integrated quantum emitters, optical access quantum memories and sensing. We
access ensemble G color center formation dynamics and radiation-induced atomic
disorder in silicon for a series of MeV proton flux conditions.
Photoluminescence results reveal that the G-centers are formed more efficiently
by pulsed proton irradiation than continuous wave proton irradiation. The
enhanced transient excitations and dynamic annealing within nanoseconds allows
optimizing the ratio of G-center formation to nonradiative defect accumulation.
The G-centers preserve narrow linewidths of about 0.1 nm when they are
generated by moderate pulsed proton fluences, while the linewidth broadens
significantly as the pulsed proton fluence increases. This implies
vacancy/interstitial clustering by overlapping collision cascades. Tracking
G-center properties for a series of irradiation conditions enables sensitive
probing of atomic disorder, serving as a complimentary analytical method for
sensing damage accumulation. Aided by ${\it ab}$ ${\it initio}$ electronic
structure calculations, we provide insight into the atomic disorder-induced
inhomogeneous broadening by introducing vacancies and silicon interstitials in
the vicinity of a G-center. A vacancy leads to a tensile strain and can result
in either a redshift or blueshift of the G-center emission, depending on its
position relative to the G-center. Meanwhile, Si interstitials lead to
compressive strain, which results in a monotonic redshift. High flux and
tunable ion pulses enable the exploration of fundamental dynamics of
radiation-induced defects as well as methods for defect engineering and qubit
synthesis for quantum information processing.


  In this paper we review some old and new results about the enlargement of
filtrations problem, as well as their applications to credit risk and insider
trading problems. The enlargement of filtrations problem consists in the study
of conditions under which a semimartingale remains a semimartingale when the
filtration is enlarged, and, in such a case, how to find the Doob-Meyer
decomposition. Filtrations may be enlarged in different ways. In this paper we
consider initial and progressive filtration enlargements made by random
variables and processes.
  Keywords: Credit Risk, Insider Trading, Enlargement of Filtrations


  In this paper we prove new constructive coercivity estimates for the
Boltzmann collision operator without cutoff, that is for long-range
interactions. In particular we give a generalized sufficient condition for the
existence of a spectral gap which involves both the growth behavior of the
collision kernel at large relative velocities and its singular behavior at
grazing and frontal collisions. It provides in particular existence of a
spectral gap and estimates on it for interactions deriving from the hard
potentials $\phi(r) = r^{-(s−1)}$, $s \ge 5$ or the so-called moderately
soft potentials $\phi(r) = r^{−(s−1)}$, $3 < s < 5$, (without
angular cutoff). In particular this paper recovers (by constructive means),
improves and extends previous results of Pao [46]. We also obtain constructive
coercivity estimates for the Landau collision operator for the optimal
coercivity norm pointed out in [34] and we formulate a conjecture about a
unified necessary and sufficient condition for the existence of a spectral gap
for Boltzmann and Landau linearized collision operators.


  Learning a world model for model-free Reinforcement Learning (RL) agents can
significantly improve the sample efficiency by learning policies in
imagination. However, building a world model for Multi-Agent RL (MARL) can be
particularly challenging due to the scalability issue in a centralized
architecture arising from a large number of agents, and also the
non-stationarity issue in a decentralized architecture stemming from the
inter-dependency among agents. To address both challenges, we propose a novel
world model for MARL that learns decentralized local dynamics for scalability,
combined with a centralized representation aggregation from all agents. We cast
the dynamics learning as an auto-regressive sequence modeling problem over
discrete tokens by leveraging the expressive Transformer architecture, in order
to model complex local dynamics across different agents and provide accurate
and consistent long-term imaginations. As the first pioneering
Transformer-based world model for multi-agent systems, we introduce a Perceiver
Transformer as an effective solution to enable centralized representation
aggregation within this context. Results on Starcraft Multi-Agent Challenge
(SMAC) show that it outperforms strong model-free approaches and existing
model-based methods in both sample efficiency and overall performance.


  Loss functions are error metrics that quantify the difference between a
prediction and its corresponding ground truth. Fundamentally, they define a
functional landscape for traversal by gradient descent. Although numerous loss
functions have been proposed to date in order to handle various machine
learning problems, little attention has been given to enhancing these functions
to better traverse the loss landscape. In this paper, we simultaneously and
significantly mitigate two prominent problems in medical image segmentation
namely: i) class imbalance between foreground and background pixels and ii)
poor loss function convergence. To this end, we propose an adaptive logarithmic
loss function. We compare this loss function with the existing state-of-the-art
on the ISIC 2018 dataset, the nuclei segmentation dataset as well as the DRIVE
retinal vessel segmentation dataset. We measure the performance of our
methodology on benchmark metrics and demonstrate state-of-the-art performance.
More generally, we show that our system can be used as a framework for better
training of deep neural networks.


  Radio Resource Management (RRM) in 5G mobile communication is a challenging
problem for which Recurrent Neural Networks (RNN) have shown promising results.
Accelerating the compute-intensive RNN inference is therefore of utmost
importance. Programmable solutions are desirable for effective 5G-RRM top cope
with the rapidly evolving landscape of RNN variations. In this paper, we
investigate RNN inference acceleration by tuning both the instruction set and
micro-architecture of a micro-controller-class open-source RISC-V core. We
couple HW extensions with software optimizations to achieve an overall
improvement in throughput and energy efficiency of 15$\times$ and 10$\times$
w.r.t. the baseline core on a wide range of RNNs used in various RRM tasks.


  Diffusion-based generative models have recently emerged as powerful solutions
for high-quality synthesis in multiple domains. Leveraging the bidirectional
Markov chains, diffusion probabilistic models generate samples by inferring the
reversed Markov chain based on the learned distribution mapping at the forward
diffusion process. In this work, we propose Modiff, a conditional paradigm that
benefits from the denoising diffusion probabilistic model (DDPM) to tackle the
problem of realistic and diverse action-conditioned 3D skeleton-based motion
generation. We are a pioneering attempt that uses DDPM to synthesize a variable
number of motion sequences conditioned on a categorical action. We evaluate our
approach on the large-scale NTU RGB+D dataset and show improvements over
state-of-the-art motion generation methods.


  Recently Kahniashivili et al (2006) presented a unified treatment for
ultraviolet Lorentz violation (LV) testing through electromagnetic wave
propagation in magnetised plasmas, based on dispersion and rotation measured
data. Based on the fact discovered recently by Kostelecky et al (2008), that LV
may place constraints on spacetime torsion, in this paper it is shown that on
the limit of very low frequency torsion waves, it is possible to constraint
torsion from Faraday rotation and CMB on a similar fashion as Minkowski
spacetime plus torsion. Here the Maxwells modified equations are obtained by a
perturbative method introduced by de Sabbata and Gasperini (1981). Torsion is
constraint to $Q_{CMB}\approx{10^{-18}GeV}$ which is not so stringent as the
$10^{-31}GeV$ obtained by Kostelecky et al. However, Gamma Ray Bursts (GBRs)
may lead to the more string value obtined by Kostelecky et al. Another
interesting constraint on torsion is shown to be placed by galactic dynamo seed
magnetic fields. For torsion effects be compatible with the galactic dynamo
seeds one obtains a torsion constraint of $10^{-33}GeV$ which is two orders of
magnitude more stringent that the above Kostelecky et al limit.


  We discuss the physics of zero modes of ED3/M5 instantons at strong coupling
from three different viewpoints. Motivated by an anomaly inflow argument, we
give a prescription for describing neutral instanton modes in terms of string
junctions, unifying the language with that used for charged modes. We proceed
to discuss the physics of charged modes as we move between different points in
the moduli space of F-theory compactified on K3. In particular, we show how, in
going from the E6^3 point to the SO(8)^4 point, the structure of SO(8) zero
modes arises from a non-trivial mixing of massless 27's of E6 with massive
modes stretching between different E6 stacks. We observe a similar mixing in
going from SO(8)^4 to E6^3. Finally, we see how the zeroes of some exact
worldsheet instanton superpotentials in heterotic backgrounds preserving E6
symmetry admit a physical interpretation in terms of low energy physics. We
also discuss the behavior of the dual F-theory compactification as the
superpotential approaches a zero. An interesting observation is that in the
examples we study some of the zeroes of the superpotential correspond to points
of E8 enhancement in the worldvolume of the dual M5 instanton, and more
generally from enhancements of the singularity over the worldvolume of the
instanton.


  We study a two-dimensional Kolmogorov system when its two parameters vary in
a small neighbourhood of the value $0.$ The local behavior of the system is
described in terms of bifurcation diagrams.


  The exact range of the joined values of several R\'{e}nyi entropies is
determined. The method is based on topology with special emphasis on the
orientation of the objects studied. Like in the case when only two orders of
R\'{e}nyi entropies are studied one can parametrize upper and lower bounds but
an explicit formula for a tight upper or lower bound cannot be given.


  We rigorously prove a form of disorder-resistance for a class of
one-dimensional cellular automaton rules, including some that arise as boundary
dynamics of two-dimensional solidification rules. Specifically, when started
from a random initial seed on an interval of length $L$, with probability
tending to one as $L\to\infty$, the evolution is a replicator. That is, a
region of space-time of density one is filled with a spatially and temporally
periodic pattern, punctuated by a finite set of other finite patterns repeated
at a fractal set of locations. On the other hand, the same rules exhibit
provably more complex evolution from some seeds, while from other seeds their
behavior is apparently chaotic. A principal tool is a new variant of
percolation theory, in the context of additive cellular automata from random
initial states.


  We explain a Macaulay2 implementation of a construction, which appeared in
[Holweck-Oeding arXiv:2206.13662], of a graded algebra structure on the direct
sum of a Lie algebra $\mathfrak{g}$ (typically $\mathfrak{sl}_n$) and a
$\mathfrak{g}$-module (typically a subspace of an exterior algebra
$\bigwedge^{\bullet}\mathbb{C}^n$). We implement brackets, a Killing form,
matrix representations of adjoint operators and ranks of blocks of their
powers.


  We develop a method for computing exact one-loop quantum corrections to the
energies of static classical backgrounds in renormalizable quantum field
theories. We use a continuum density of states formalism to construct a
regularized Casimir energy in terms of phase shifts and their Born
approximations. This method unambiguously incorporates definite counterterms
fixed in the standard way by physical renormalization conditions. The result is
a robust computation that can be efficiently implemented both numerically and
analytically. We carry out such calculations in models of bosons and fermions
in one and three dimensions.


  Mono-energetic $\gamma$-beams ($\Delata \approx$ 10 eV) based on thermal
neutron capture, in a nuclear reactor, using the Mn(n, $\gamma$) reaction were
utilized for generating a fast neutron source from Zinc, via the
${67}^Zn(\gamma, n)$ reaction. One of the incident $\gamma$-lines of the Mn
source at $E_\gamma$ = 7244 keV, photoexcites by chance a resonance level in
${67}^$Zn, with subsequent emission of neutrons at an energy of 191 keV. The
cross-section for this process was measured and found to be $\sigma(\gamma, n)$
= 252 $\pm$ 41 mb with an intensity of the order of 104 n/s. The angular
distribution of the 191 keV neutron group was also measured.


  In the current SPARQL specification the notion of correlation and
substitution are not well defined. This problem triggers several ambiguities in
the semantics. In fact, implementations as Fuseki and Virtuoso assume different
semantics.
  In this technical report, we provide a semantics of correlation and
substitution following the classic philosophy of substitution and correlation
in logic, programming languages and SQL. We think this proposal not only fix
the current ambiguities and problems, but helps to set a safe formal base to
further extensions of the language.
  This work is part of an ongoing work of Daniel Hernandez. These anomalies in
the W3C Specification of SPARQL 1.1 were detected early and reported no later
than 2014, when two erratas were registered (cf.
https://www.w3.org/2013/sparql-errata#errata-query-8 and
https://www.w3.org/2013/sparql-errata#errata-query-10).


  Stream processing addresses the needs of real-time applications. Transaction
processing addresses the coordination and safety of short atomic computations.
Heretofore, these two modes of operation existed in separate, stove-piped
systems. In this work, we attempt to fuse the two computational paradigms in a
single system called S-Store. In this way, S-Store can simultaneously
accommodate OLTP and streaming applications. We present a simple transaction
model for streams that integrates seamlessly with a traditional OLTP system. We
chose to build S-Store as an extension of H-Store, an open-source, in-memory,
distributed OLTP database system. By implementing S-Store in this way, we can
make use of the transaction processing facilities that H-Store already
supports, and we can concentrate on the additional implementation features that
are needed to support streaming. Similar implementations could be done using
other main-memory OLTP platforms. We show that we can actually achieve higher
throughput for streaming workloads in S-Store than an equivalent deployment in
H-Store alone. We also show how this can be achieved within H-Store with the
addition of a modest amount of new functionality. Furthermore, we compare
S-Store to two state-of-the-art streaming systems, Spark Streaming and Storm,
and show how S-Store matches and sometimes exceeds their performance while
providing stronger transactional guarantees.


  The wide success of Bitcoin has led to a huge surge of alternative
cryptocurrencies (altcoins). Most altcoins essentially fork Bitcoin's code with
minor modifications, such as the number of coins to be minted, the block size,
and the block generation time. As such, they are often deemed identical to
Bitcoin in terms of security, robustness, and maturity.
  In this paper, we show that this common conception is misleading. By mining
data retrieved from the GitHub repositories of various altcoin projects, we
estimate the time it took to propagate relevant patches from Bitcoin to the
altcoins. We find that, while the Bitcoin development community is quite active
in fixing security flaws of Bitcoin's code base, forked cryptocurrencies are
not as rigorous in patching the same vulnerabilities (inherited from Bitcoin).
In some cases, we observe that even critical vulnerabilities, discovered and
fixed within the Bitcoin community, have been addressed by the altcoins tens of
months after disclosure. Besides raising awareness of this problem, our work
aims to motivate the need for a proper responsible disclosure of
vulnerabilities to all forked chains prior to reporting them publicly.


  We present a description of the public code XIM, a virtual X-ray observatory.
XIM can be used to convert hydrodynamic simulations of astrophysical objects,
such as large scale structure, galaxy clusters, groups, galaxies, supernova
remnants, and similar extended objects, into virtual X-ray observations for
direct comparison with observations and for post-processing with standard X-ray
analysis tools. By default, XIM simulates Chandra and the International X-ray
Observatory (IXO), but can accommodate any user-specified telescope parameters
and instrument responses. Examples of XIM applications include virtual Chandra
imaging of simulated X-ray cavities from AGN feedback in galaxy clusters,
kinematic mapping of cluster velocity fields (e.g., due to mergers or AGN
feedback), as well as detailed spectral modeling of multi-phase,
multi-temperature spectra from space plasmas.


  When the Lake Louise Winter Institute started twenty-five years ago, many
properties of quantum chromodynamics (QCD) were believed to be true, but had
not been demonstrated to be true. This talk surveys a variety of results that
have been established with lattice gauge theory, directly from the QCD
Lagrangian, shedding light on the origin of (your) mass and its interplay with
dynamical symmetry breaking, as well as some further intriguing features of the
natural world.


  Immersive displays such as VR headsets, AR glasses, Multiview displays, Free
point televisions have emerged as a new class of display technologies in recent
years, offering a better visual experience and viewer engagement as compared to
conventional displays. With the evolution of 3D video and display technologies,
the consumer market for High Dynamic Range (HDR) cameras and displays is
quickly growing. The lack of appropriate experimental data is a critical
hindrance for the development of primary research efforts in the field of 3D
HDR video technology. Also, the unavailability of sufficient real world
multi-exposure experimental dataset is a major bottleneck for HDR imaging
research, thereby limiting the quality of experience (QoE) for the viewers. In
this paper, we introduce a diversified stereoscopic multi-exposure dataset
captured within the campus of Indian Institute of Technology Madras, which is
home to a diverse flora and fauna. The dataset is captured using ZED
stereoscopic camera and provides intricate scenes of outdoor locations such as
gardens, roadside views, festival venues, buildings and indoor locations such
as academic and residential areas. The proposed dataset accommodates wide depth
range, complex depth structure, complicate object movement, illumination
variations, rich color dynamics, texture discrepancy in addition to significant
randomness introduced by moving camera and background motion. The proposed
dataset is made publicly available to the research community. Furthermore, the
procedure for capturing, aligning and calibrating multi-exposure stereo videos
and images is described in detail. Finally, we have discussed the progress,
challenges, potential use cases and future research opportunities with respect
to HDR imaging, depth estimation, consistent tone mapping and 3D HDR coding.


  We study some problems inherent with certain forms of functional depth, in
particular, zero depth and lack of consistency.


  The detection of early signs of volcanic unrest preceding an eruption, in the
form of ground deformation in Interferometric Synthetic Aperture Radar (InSAR)
data is critical for assessing volcanic hazard. In this work we treat this as a
binary classification problem of InSAR images, and propose a novel deep
learning methodology that exploits a rich source of synthetically generated
interferograms to train quality classifiers that perform equally well in real
interferograms. The imbalanced nature of the problem, with orders of magnitude
fewer positive samples, coupled with the lack of a curated database with
labeled InSAR data, sets a challenging task for conventional deep learning
architectures. We propose a new framework for domain adaptation, in which we
learn class prototypes from synthetic data with vision transformers. We report
detection accuracy that amounts to the highest reported accuracy on a large
test set for volcanic unrest detection. Moreover, we built upon this knowledge
by learning a new, non-linear, projection between the learnt representations
and prototype space, using pseudo labels produced by our model from an
unlabeled real InSAR dataset. This leads to the new state of the art with 97.1%
accuracy on our test set. We demonstrate the robustness of our approach by
training a simple ResNet-18 Convolutional Neural Network on the unlabeled real
InSAR dataset with pseudo-labels generated from our top transformer-prototype
model. Our methodology provides a significant improvement in performance
without the need of manually labeling any sample, opening the road for further
exploitation of synthetic InSAR data in various remote sensing applications.


  We investigate Dirac mass matrices derived in the gauge field theory of a
horizontal symmetry generated by a central extension of the Pauli algebra.
Through numerical analyses of the observed data of the charged fermion masses
and the flavor mixing matrix of quarks, values of free parameters in the mass
matrices are determined and several empirical relations are found among the
Yukawa coupling constants. As one specific feature of the theory, we find
different orderings in squared mass eigenvalues for the up and down quark
sectors.


  Neural networks for structured data like graphs have been studied extensively
in recent years. To date, the bulk of research activity has focused mainly on
static graphs. However, most real-world networks are dynamic since their
topology tends to change over time. Predicting the evolution of dynamic graphs
is a task of high significance in the area of graph mining. Despite its
practical importance, the task has not been explored in depth so far, mainly
due to its challenging nature. In this paper, we propose a model that predicts
the evolution of dynamic graphs. Specifically, we use a graph neural network
along with a recurrent architecture to capture the temporal evolution patterns
of dynamic graphs. Then, we employ a generative model which predicts the
topology of the graph at the next time step and constructs a graph instance
that corresponds to that topology. We evaluate the proposed model on several
artificial datasets following common network evolving dynamics, as well as on
real-world datasets. Results demonstrate the effectiveness of the proposed
model.


  Kerr optical frequency combs generated in a coherently driven Kerr nonlinear
resonator has the potential for a wide range of applications. However, in a
single cavity which is a widely adopted configuration for Kerr optical
frequency combs generation, modulation instability is suppressed in normal
dispersion regime and the pump-to-comb conversion efficiency is extremely low
for a single dissipative Kerr soliton in anomalous dispersion regime.
Dual-coupled cavities have been proposed to generate Kerr optical frequency
combs in normal dispersion regime, and have potential to remarkably increase
conversion efficiency for Kerr optical frequency combs. Here, we investigate
modulation instability and Kerr optical frequency-comb formation in
dual-coupled cavities. Based on solutions of the continuous-wave steady state,
we obtain a quadric algebraic equation describing the modulation instability
gain, and we find that it is intensely influenced by the group velocity
mismatch between the two cavities. Our numerical simulations demonstrate that
platicons can be generated via pump scanning scheme for the case that both the
two cavities possess normal dispersion, and a single dissipative Kerr soliton
can be generated in the cavity with anomalous dispersion while the dispersion
of the other cavity is normal. Our analysis of modulation instability provides
a powerful tool for Kerr optical frequency-comb generation via pump modulation
and cavity detuning tuning scheme in dual-coupled cavities.


  Surface reconstruction from raw point clouds has been studied for decades in
the computer graphics community, which is highly demanded by modeling and
rendering applications nowadays. Classic solutions, such as Poisson surface
reconstruction, require point normals as extra input to perform reasonable
results. Modern transformer-based methods can work without normals, while the
results are less fine-grained due to limited encoding performance in local
fusion from discrete points. We introduce a novel normalized matrix attention
transformer (Tensorformer) to perform high-quality reconstruction. The proposed
matrix attention allows for simultaneous point-wise and channel-wise message
passing, while the previous vector attention loses neighbor point information
across different channels. It brings more degree of freedom in feature learning
and thus facilitates better modeling of local geometries. Our method achieves
state-of-the-art on two commonly used datasets, ShapeNetCore and ABC, and
attains 4% improvements on IOU on ShapeNet. Code can be accessed
https://github.com/THHHomas/Tensorformer6.


  Data outsourcing is a growing business model offering services to individuals
and enterprises for processing and storing a huge amount of data. It is not
only economical but also promises higher availability, scalability, and more
effective quality of service than in-house solutions. Despite all its benefits,
data outsourcing raises serious security concerns for preserving data
confidentiality. There are solutions for preserving confidentiality of data
while supporting search on the data stored in outsourced environments. However,
such solutions do not support access policies to regulate access to a
particular subset of the stored data.
  For complex user management, large enterprises employ Role-Based Access
Controls (RBAC) models for making access decisions based on the role in which a
user is active in. However, RBAC models cannot be deployed in outsourced
environments as they rely on trusted infrastructure in order to regulate access
to the data. The deployment of RBAC models may reveal private information about
sensitive data they aim to protect. In this paper, we aim at filling this gap
by proposing \textbf{$\mathit{ESPOON_{ERBAC}}$} for enforcing RBAC policies in
outsourced environments. $\mathit{ESPOON_{ERBAC}}$ enforces RBAC policies in an
encrypted manner where a curious service provider may learn a very limited
information about RBAC policies. We have implemented $\mathit{ESPOON_{ERBAC}}$
and provided its performance evaluation showing a limited overhead, thus
confirming viability of our approach.


  Generative adversarial networks (GANs) have shown potential in learning
emotional attributes and generating new data samples. However, their
performance is usually hindered by the unavailability of larger speech emotion
recognition (SER) data. In this work, we propose a framework that utilises the
mixup data augmentation scheme to augment the GAN in feature learning and
generation. To show the effectiveness of the proposed framework, we present
results for SER on (i) synthetic feature vectors, (ii) augmentation of the
training data with synthetic features, (iii) encoded features in compressed
representation. Our results show that the proposed framework can effectively
learn compressed emotional representations as well as it can generate synthetic
samples that help improve performance in within-corpus and cross-corpus
evaluation.


  To investigate ferromagnetic semiconductors and insulators, such as the
famous EuO, EuS, or CrBr$_3$, we propose a hybridized Kondo-lattice model,
where, in addition to the conduction electrons, localized moments (e.g., the
$4f$-electrons) are modeled as a strongly correlated band system. The
quasi-empty conduction band is weakly filled due to the hybridization term.
This activates the intraatomic exchange coupling between conduction and
localized electrons. Temperature-dependent phase diagrams and quasiparticle
densities of states are presented for various coupling and hybridization
strengths. Moreover, the influence of the one-particle energy of the localized
electrons $E_f$ is discussed. A comparison with mean field calculations is
given at the end of this work.


  The effective theory of isoscalar dark matter-nucleon interactions mediated
by heavy spin-one or spin-zero particles depends on 10 coupling constants
besides the dark matter particle mass. Here we compare this 11-dimensional
effective theory to current observations in a comprehensive statistical
analysis of several direct detection experiments, including the recent LUX,
SuperCDMS and CDMSlite results. From a multidimensional scan with about 3
million likelihood evaluations, we extract the marginalized posterior
probability density functions (a Bayesian approach) and the profile likelihoods
(a frequentist approach), as well as the associated credible regions and
confidence levels, for each coupling constant vs dark matter mass and for each
pair of coupling constants. We compare the Bayesian and frequentist approach in
the light of the currently limited amount of data. We find that current direct
detection data contain sufficient information to simultaneously constrain not
only the familiar spin-independent and spin-dependent interactions, but also
the remaining velocity and momentum dependent couplings predicted by the dark
matter-nucleon effective theory. For current experiments associated with a null
result, we find strong correlations between some pairs of coupling constants.
For experiments that claim a signal (i.e., CoGeNT and DAMA), we find that pairs
of coupling constants produce degenerate results.


  This study focuses on the Cauchy problem associated with the two-component
peakon system featuring a cubic nonlinearity, constrained to the class
$(m,n)\in C^{k}(\mathbb{R}) \cap W^{k,1}(\mathbb{R})$ with
$k\in\mathbb{N}\cup\{0\}$.This system extends the celebrated
Fokas-Olver-Rosenau-Qiao equation, and the following nonlocal (two-place)
counterpart proposed by Lou and Qiao: $$ \partial_t m(t,x)=
\partial_x[m(t,x)(u(t,x)-\partial_xu(t,x)) (u(-t,-x)+\partial_x(u(-t,-x)))], $$
where $m(t,x)=\left(1-\partial_{x}^2\right)u(t,x)$. Employing an approach based
on Lagrangian coordinates, we establish the local existence, uniqueness, and
Lipschitz continuity of the data-to-solution map in the class $C^k\cap
W^{k,1}$. Moreover, we derive criteria for blow-up of the local solution in
this class.


  We introduce the notion of isoclinism among crossed modules of Lie algebras,
which will be called "Lie crossed modules" hereafter, and investigate some
basic properties. Additionally, we introduce the notion of class preserving
actor of a Lie crossed module and the relation with isoclinism.


  The rapid emergence and the disastrous impact of the severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-2) pandemic on public health, societies, and
economies around the world has created an urgent need for understanding the
pathways critical for virus transmission. Airborne virus transmission by
asymptomatic SARS-CoV-2-infected individuals is considered to be a major
contributor to the spread of SARS-CoV-2 and social distancing and wearing of
face masks in public have been implemented as countermeasures in many
countries. However, a comprehensive risk assessment framework for the airborne
transmission of SARS-CoV-2 incorporating realistic assumptions on the
filtration of infectious aerosols (IAs) by face masks is not available yet. In
particular, in most end-to-end models for airborne virus transmission, it is
neglected that the stochastic spread of IAs through imperfectly fitted face
masks depends on the dynamics of the breathing of the wearer. In this paper, we
consider airborne virus transmission from an infected but asymptomatic person
to a healthy person, both wearing imperfectly fitted face masks, in an indoor
environment. By framing the end-to-end virus transmission as a Molecular
Communications (MC) system, we obtain a statistical description of the number
of IAs inhaled by the healthy person subject to the respective configurations
of the face masks of both persons. We demonstrate that the exhalation and
inhalation air flow dynamics have a significant impact on the stochastic
filtering of IAs by the face masks. Furthermore, we show that the fit of the
face mask of the infected person can highly impact the infection probability.
We conclude that the proposed MC model may contribute a valuable assessment
tool to fight the spread of SARS-CoV-2 as it encompasses the randomness of the
transmission process and enables comprehensive risk analysis beyond statistical
averages.


  In this work pair productions of charged and doubly charged scalars in the
framework of littlest Higgs model at $e^+e^-$ colliders are studied. In the
allowed parameter space of the littlest Higgs model, the production rates of
the scalar pairs are calculated. It is obtained that pair productions of
charged and doubly charged scalars are reachable at $e^+ e^-$ colliders with
energy $\sqrt{S}\geq 1.7TeV$. Using the lepton flavor violating decays of
charged scalars calculated in literature, final state analysis is done for pair
production processes. This analysis show that depending on the model
parameters, lepton number and lepton flavor violations can be observed free
from any backgrounds.


  A number of top-spin observables are computed within the Standard Model (SM),
at next-to-leading order in the strong and weak gauge couplings for hadronic
top-quark anti-quark (ttbar) production and decay at the LHC for center-of-mass
energies 7 and 8 TeV. For dileptonic final states we consider the azimuthal
angle correlation, the helicity correlation, and the opening angle
distribution; for lepton plus jets final states we determine distributions and
asymmetries that trace a longitudinal and transverse polarization,
respectively, of the t and t-bar samples. In addition, we investigate the
effects of a non-zero chromo-magnetic and chromo-electric dipole moment of the
top quark on these and other top-spin observables and associated asymmetries.
These observables allow to disentangle the contributions from the real and
imaginary parts of these moments.


  Light-induced chemical processes are ubiquitous in nature and have widespread
technological applications. For example, photoisomerization can allow a drug
with a photo-switchable scaffold such as azobenzene to be activated with light.
In principle, photoswitches with desired photophysical properties like high
isomerization quantum yields can be identified through virtual screening with
reactive simulations. In practice, these simulations are rarely used for
screening, since they require hundreds of trajectories and expensive quantum
chemical methods to account for non-adiabatic excited state effects. Here we
introduce a diabatic artificial neural network (DANN) based on diabatic states
to accelerate such simulations for azobenzene derivatives. The network is six
orders of magnitude faster than the quantum chemistry method used for training.
DANN is transferable to azobenzene molecules outside the training set,
predicting quantum yields for unseen species that are correlated with
experiment. We use the model to virtually screen 3,100 hypothetical molecules,
and identify novel species with extremely high predicted quantum yields. The
model predictions are confirmed using high accuracy non-adiabatic dynamics. Our
results pave the way for fast and accurate virtual screening of photoactive
compounds.


  The maximum size of an $r$-uniform hypergraph without a Berge cycle of length
at least $k$ has been determined for all $k \ge r+3$ by F\"uredi, Kostochka and
Luo and for $k<r$ (and $k=r$, asymptotically) by Kostochka and Luo. In this
paper, we settle the remaining cases: $k=r+1$ and $k=r+2$, proving a conjecture
of F\"uredi, Kostochka and Luo.


  The exclusive charge exchange reaction pD->n(pp) at intermediate and high
energies is studied within the Bethe-Salpeter formalism. The final state
interaction in the detected at zero-near excitation energy pp-pair is described
by the 1S0 component of the Bethe-Salpeter amplitude. Results of numerical
calculations of polarization observables and differential cross-section
persuade that, as in the non relativistic case, this reaction can be utilized
for a relativistic deuteron tensor polarimeter and as a source of information
about the elementary nucleon-nucleon charge exchange amplitude.


  Greenhouse gas emissions have dramatically risen since the early 1900s with
U.S. transportation generating 28% of U.S. emissions. As such, there is
interest in reducing transportation-related emissions. Specifically,
sustainability research has sprouted around signalized intersections as
intersections allow different streams of traffic to cross and change
directions. Recent research has developed mixed traffic control eco-driving
strategies at signalized intersections to decrease emissions. However, the
inherent structure of a signalized intersection generates increased emissions
by creating frequent acceleration/deceleration events, excessive idling from
traffic congestion, and stop-and-go waves. Thus, we believe unsignalized
intersections hold potential for further sustainability improvements. In this
work, we provide an emissions analysis on unsignalized intersections with
complex, real-world topologies and traffic demands where mixed traffic control
strategies are employed by robot vehicles (RVs) to reduce wait times and
congestion. We find with at least 10% RV penetration rate, RVs generate less
fuel consumption, CO2 emissions, and NOx emissions than signalized
intersections by up to 27%, 27% and 28%, respectively. With at least 30% RVs,
CO and HC emissions are reduced by up to 42% and 43%, respectively.
Additionally, RVs can reduce network-wide emissions despite only employing
their strategies at intersections.


  We introduce an $A_\infty$-algebra structure on the Hochschild cohomology of
the endomorphism bimodule of a finite-dimensional representation of an
associative algebra. We prove that this structure determines a presentation for
non-commutative deformations of the representation. From this, we deduce
presentations of universal deformation rings of Galois representations. In
turn, we apply these presentations in order to deduce universal deformation
rings of Galois pseudorepresentations, supplying a a tangent and obstruction
theory for pseudorepresentations. This generalizes the broadly used tangent and
obstruction theory for Galois representations. We also give applications,
calculating the ranks of certain Hecke algebras.


  We establish new interaction estimates for a system introduced by Baiti and
Jenssen. These estimates are pivotal to the analysis of the wave front-tracking
approximation. In a companion paper we use them to construct a counter-example
which shows that Schaeffer's Regularity Theorem for scalar conservation laws
does not extend to systems. The counter-example we construct shows,
furthermore, that a wave-pattern containing infinitely many shocks can be
robust with respect to perturbations of the initial data. The proof of the
interaction estimates is based on the explicit computation of the wave fan
curves and on a perturbation argument.


  We present high time-resolution optical photometry of the eclipsing binary UZ
For using a superconducting tunnel junction (STJ) device, a photon-counting
array detector with intrinsic energy resolution. Three eclipses of the $\sim$18
mag 126.5 min orbital binary were observed using a $6\times6$ array of Tantalum
STJs at the 4.2-m William Herschel Telescope on La Palma. The detector
presently provides individual photon arrival time accuracy to about 5 $\mu$s,
and a wavelength resolution of about 60 nm at 500 nm, with each array element
capable of counting up to $\sim$5000 photons s$^{-1}$. The data allow us to
place accurate constraints on the accretion geometry from our time- and
spectrally-resolved monitoring, especially of the eclipse ingress and egress.
We find that there are two small accretion regions, located close to the poles
of the white dwarf. The positions of these are accurately constrained, and show
little movement from eclipse to eclipse, even over a number of years. The
colour of the emission from the two regions appears similar, although their
X-ray properties are known to be significantly different: we argue that the
usual accretion shock may be absent at the non-X-ray emitting region, and
instead the flow here interacts directly with the white dwarf surface;
alternatively, a special grazing occultation of this region is required. There
is no evidence for any quasi-periodic oscillations on time-scales of the order
of seconds, consistent with relatively stable cyclotron cooling in each
accretion region.


  We consider a dynamically decoupled network of agents each with a local
output-feedback controller. We assume each agent is a node in a directed
acyclic graph and the controllers share information along the edges in order to
cooperatively optimize a global objective. We develop explicit state-space
formulations for the jointly optimal networked controllers that highlight the
role of the graph structure. Specifically, we provide generically minimal
agent-level implementations of the local controllers along with intuitive
interpretations of their states and the information that should be transmitted
between controllers.


  The non-dispersive fundamental shear horizontal (SH0) wave in plate-like
structures is of practical importance in non-destructive testing (NDT) and
structural health monitoring (SHM). Theoretically, an omnidirectional SH0
transducer phased array system can be used to inspect defects in a large plate
in the similar manner to the phased array transducers used in medical B-scan
ultrasonics. However, very few omnidirectional SH transducers have been
proposed so far. In this work, an omnidirectional SH wave piezoelectric
transducer (OSH-PT) was proposed which consists of a ring array of twelve
face-shear (d24) trapezoidal PZT elements. Each PZT element can produce
face-shear deformation under applied voltage, resulting in circumferential
shear deformation in the OSH-PT and omnidirectional SH waves in the hosting
plate. Both finite element simulations and experiments were conducted to
examine the performance of the proposed OSH-PT. Experimental testing shows that
the OSH-PT exhibits good omnidirectional properties, on matter it is used as a
SH wave transmitter or a SH wave receiver. This work may greatly promote the
applications of SH waves in NDT and SHM.


  This paper is concerned with the study of the criticality of families of
planar centers. More precisely, we study sufficient conditions to bound the
number of critical periodic orbits that bifurcate from the outer boundary of
the period annulus of potential centers. In the recent years, the new approach
of embedding the derivative of the period function into a collection of
functions that form a Chebyshev system near the outer boundary has shown to be
fruitful in this issue. In this work, we tackle with a remaining case that was
not taken into account in the previous studies in which the Roussarie-Ecalle
compensator plays an essential role. The theoretical results we develop are
applied to study the bifurcation diagram of the period function of two
different families of centers: the power-like family $\ddot x=x^p-x^q$,
$p,q\in\mathbb{R}$ with $p>q$; and the family of dehomogenized Loud's centers.


  Local(multiplicative) effective potential energy theories of electronic
structure comprise the transformation of the Schr{\"o}dinger equation for
interacting fermi systems to model noninteracting fermi or bose systems whereby
the equivalent density and energy are obtained. By employing the integrated
form of the Kato electron-nucleus cusp condition, we prove that the effective
electron -interaction potential energy of these model fermions or bosons is
finite at a nucleus. The proof is general and valid for arbitrary system
whether it be atomic, molecular, or solid state, and for arbitrary state and
symmetry. This then provides justification for all prior work in the literature
based on the assumption of finiteness of this potential energy at a nucleus. We
further demonstrate the criticality of the electron-nucleus cusp condition to
such theories by example of the Hydrogen molecule. We show thereby that both
model system effective electron-interaction potential energies, as determined
from densities derived from accurate wave functions, will be singular at the
nucleus unless the wave function satisfies the electron-nucleus cusp condition.


  In this paper we present a multilayer particle deposition model on a random
tree. We derive the time dependent densities of the first and second layer
analytically and show that in all trees the limiting density of the first layer
exceeds the density in the second layer. We also provide a procedure to
calculate higher layer densities and prove that random trees have a higher
limiting density in the first layer than regular trees. Finally, we compare
densities between the first and second layer and between regular and random
trees.


  The core of an ideal is the intersection of all its reductions. We describe
the core of a zero-dimensional monomial ideal I as the largest monomial ideal
contained in a general reduction of I. This provides a new interpretation of
the core in the monomial case as well as an efficient algorithm for computing
it. We relate the core to adjoints and first coefficient ideals, and in
dimension two and three we give explicit formulas.


  We consider a qubit that is driven along its logical $z$ axis, with noise
along the $z$ axis in the driving field $\Omega$ proportional to some function
$f(\Omega)$, as well as noise along the logical $x$ axis. We establish that
whether or not errors due to both types of noise can be canceled out, even
approximately, depends on the explicit functional form of $f(\Omega)$ by
considering a power-law form, $f(\Omega)\propto\Omega^k$. In particular, we
show that such cancellation is impossible for $k=0$, $1$, or any even integer.
However, any other odd integer value of $k$ besides $1$ does permit
cancellation; in fact, we show that both types of errors can be corrected with
a sequence of four square pulses of equal duration. We provide sets of
parameters that correct for errors for various rotations and evaluate the
error, measured by the infidelity, for the corrected rotations versus the
na\"ive rotations, i.e., the operations that, in the complete absence of noise,
would produce the desired rotations (in this case a single pulse of appropriate
duration and magnitude). We also consider a train of four trapezoidal pulses,
which take into account the fact that there will be, in real experimental
systems, a finite rise time, again providing parameters for error-corrected
rotations that employ such pulse sequences. Our dynamical decoupling error
correction scheme works for any qubit platform as long as the errors are
quasistatic.


  Brownian motions on star graphs in the sense of It\^o-McKean, that is, Walsh
processes admitting a generalized boundary behavior including stickiness and
jumps and having an angular distribution with finite support, are examined.
Their generators are identified as Laplace operators on the graph subject to
non-local Feller-Wentzell boundary conditions. A pathwise description is
achieved for every admissible boundary condition: For finite jump measures, a
construction of Kostrykin, Potthoff and Schrader in the continuous setting is
expanded via a technique of successive killings and revivals; for infinite jump
measures, the pathwise solution of It\^o-McKean for the half line is analyzed
and extended to the star graph. These processes can then be used as main
building blocks for Brownian motions on general metric graphs with non-local
boundary conditions.


  We prove sharp $L^p$ estimates for a singular transport equation by building
what we call a \emph{cascading solution}; the equation studies the combined
effect of multiplying by a bounded function and application of the Hilbert
transform. Along the way we prove an invariance result for the Hilbert
transform which could be of independent interest. Finally, we give an example
of a bounded and \emph{incompressible} velocity field for which the equation:
  $$\partial_t f +u\cdot\nabla f= H(f)$$ develops sharp $L^p$ growth. The
equations we study are relevant, as models, in the study of fluid equations as
well as in general relativity.


  During the past few decades, abundant evidence for physics beyond the two
standard models of particle physics and cosmology was found. Yet, we are
tapping into the dark regarding our understanding of the dark sector. For more
than a century, open problems related to the nature of the vacuum remain
unresolved. Besides the traditional high-energy frontier and cosmology,
technological advancement provides complementary access to new physics via
high-precision experiments. Among the latter, the Casimir And Non-Newtonian
force EXperiment (\cannex{}) has successfully completed its proof-of-principle
phase and will soon commence operation. Benefiting from its plane parallel
plate geometry, both interfacial and gravity-like forces are maximized, leading
to increased sensitivity. A wide range of dark sector forces, Casimir forces in
and out of thermal equilibrium, and gravity will be tested. This article
describes the final experimental design, its sensitivity, and expected results.


  [abridged] Quasars (QSOs) at the highest known redshift (z~6) are unique
probes of the early growth of supermassive black holes (BHs). Until now, only
the most luminous QSOs have been studied, often one object at a time. Here we
present the most extensive consistent analysis to date of z>4 QSOs with
observed NIR spectra, combining three new z~6 objects from our ongoing
VLT-ISAAC program with nineteen 4<z<6.5 sources from the literature. The new
sources extend the existing SDSS sample towards the faint end of the QSO
luminosity function. Using a maximum likelihood fitting routine optimized for
our spectral decomposition, we estimate the black hole mass (MBH), the
Eddington ratio (defined as Lbol/LEdd) and the FeII/MgII line ratio, a proxy
for the chemical abundance, to characterize both the central object and the
broad line region gas. The QSOs in our sample host BHs with masses of ~10^9
M\odot that are accreting close to the Eddington luminosity, consistent with
earlier results. We find that the distribution of observed Eddington ratios is
significantly different than that of a luminosity-matched comparison sample of
SDSS QSOs at lower redshift (0.35<z<2.25): the average <log(Lbol/LEdd)>=-0.37
(Lbol/LEdd~0.43) with a scatter of 0.20 dex for the z>4 sample and the
<log(Lbol/LEdd)>=-0.80 (Lbol/LEdd~0.16) with a scatter of 0.24 dex for the
0.35<z<2.25 sample. This implies that, at a given luminosity, the MBH at high-z
is typically lower than the average MBH of the lower-redshift population, i.e.
the z>4 sources are accreting significantly faster than the lower-redshift
ones. We show that the derived FeII/MgII ratios depend sensitively on the
performed analysis: our self-consistent, homogeneous analysis significantly
reduces the FeII/MgII scatter found in previous studies. The measured FeII/MgII
line ratios show no sign of evolution with cosmic time in the redshift range
4<z<6.5 [...]


  First-order algorithms have been popular for solving convex and non-convex
optimization problems. A key assumption for the majority of these algorithms is
that the gradient of the objective function is globally Lipschitz continuous,
but many contemporary problems such as tensor decomposition fail to satisfy
such an assumption. This paper develops a sequential local optimization (SLO)
framework of first-order algorithms that can effectively optimize problems
without Lipschitz gradient. Operating on the assumption that the gradients are
{\it locally} Lipschitz continuous over any compact set, the proposed framework
carefully restricts the distance between two successive iterates. We show that
the proposed framework can easily adapt to existing first-order methods such as
gradient descent (GD), normalized gradient descent (NGD), accelerated gradient
descent (AGD), as well as GD with Armijo line search. Remarkably, the latter
algorithm is totally parameter-free and do not even require the knowledge of
local Lipschitz constants.
  We show that for the proposed algorithms to achieve gradient error bound of
$\|\nabla f(x)\|^2\le \epsilon$, it requires at most
$\mathcal{O}(\frac{1}{\epsilon}\times \mathcal{L}(Y))$ total access to the
gradient oracle, where $\mathcal{L}(Y)$ characterizes how the local Lipschitz
constants grow with the size of a given set $Y$. Moreover, we show that the
variant of AGD improves the dependency on both $\epsilon$ and the growth
function $\mathcal{L}(Y)$. The proposed algorithms complement the existing
Bregman Proximal Gradient (BPG) algorithm, because they do not require the
global information about problem structure to construct and solve Bregman
proximal mappings.


  We prove that every MAD family can be destroyed by a proper forcing that
preserves $P$-points. With this result, we prove that it is consistent that
$\omega_{1}=\mathfrak{u}<\mathfrak{a,}$ solving a nearly 20 year old problem of
Shelah and a problem of Brendle. We will also present a simple proof of a
result of Blass and Shelah that the inequality $\mathfrak{u<s}$ is consistent.