  We describe a major survey of the Milky Way halo designed to test for
kinematic substructure caused by destruction of accreted satellites. We use the
Washington photometric system to identify halo stars efficiently for
spectroscopic followup. Tracers include halo giants (detectable out to more
than 100 kpc), blue horizontal branch stars, halo stars near the main sequence
turnoff, and the ``blue metal-poor stars'' of Preston et al (1994). We
demonstrate the success of our survey by showing spectra of stars we have
identified in all these categories, including giants as distant as 75 kpc. We
discuss the problem of identifying the most distant halo giants. In particular,
extremely metal-poor halo K dwarfs are present in approximately equal numbers
to the distant giants for V fainter than 18, and we show that our method will
distinguish reliably between these two groups of metal-poor stars. We plan to
survey 100 square degrees at high galactic latitude, and expect to increase the
numbers of known halo giants, BHB stars and turnoff stars by more than an order
of magnitude. In addition to the strong test that this large sample will
provide for the question `was the Milky Way halo accreted from satellite
galaxies?', we will improve the accuracy of mass measurements of the Milky Way
beyond 50 kpc via the kinematics of the many distant giants and BHB stars we
will find. We show that one of our first datasets constrains the halo density
law over galactocentric radii of 5-20 kpc and z heights of 2-15 kpc. The data
support a flattened power-law halo with b/a of 0.6 and exponent -3.0. More
complex models with a varying axial ratio may be needed with a larger dataset.


  We study the brane world motion in non-static bulk by generalizing the second
Randall-Sundrum scenario Explicitly, we take the bulk to be a Vaidya-AdS
metric, which describes the gravitational collapse of a spherically symmetric
null dust fluid in Anti-de Sitter spacetime. We point out that during an
inflationary phase on the brane, black holes will tend to be thermally
nucleated in the bulk We analyze the thermodynamical properties of this
brane-world.We point out that during an inflationary phase on the brane, black
holes will tend to be thermally nucleated in the bulk. Thermal equilibrium of
the system is discussed. We calculate the late time behavior of this system,
including 1-loop effects. We argue that at late times a sufficiently large
black hole will relax to a point of thermal equilibrium with the brane-world
environment. This result has interesting implications for early-universe
cosmology.


  Motivated by the spin-triplet superconductor Sr2RuO4, the thermal Hall
conductivity is investigated for several pairing symmetries with broken
time-reversal symmetry. In the chiral p-wave phase with a fully opened
quasiparticle excitation gap, the temperature dependence of the thermal Hall
conductivity has a temperature linear term associated with the topological
property directly, and an exponential term, which shows a drastic change around
the Lifshitz transition. Examining f-wave states as alternative candidates with
$\bm d=\Delta_0\hat{z}(k_x^2-k_y^2)(k_x\pm ik_y)$ and $\bm
d=\Delta_0\hat{z}k_xk_y(k_x\pm ik_y)$ with gapless quasiparticle excitations,
we study the temperature dependence of the thermal Hall conductivity, where for
the former state the thermal Hall conductivity has a quadratic dependence on
temperature, originating from the linear dispersions, in addition to linear and
exponential behavior. The obtained result may enable us to distinguish between
the chiral p-wave and f-wave states in Sr2RuO4.


  First measurements of cross sections for isolated prompt photon production in
deep inelastic ep scattering have been made using the ZEUS detector at the HERA
electron-proton collider using an integrated luminosity of 121 pb^-1. A signal
for isolated photons in the transverse energy and rapidity ranges 5 < E_T^gamma
< 10 GeV and -0.7 < eta^gamma < 0.9 was observed for virtualities of the
exchanged photon of Q^2 > 35 GeV^2. Cross sections are presented for inclusive
prompt photons and for those accompanied by a single jet in the range E_T^jet
\geq 6 GeV and -1.5 \leq eta^jet < 1.8. Calculations at order alpha^3alpha_s
describe the data reasonably well.


  We use a large sample of galaxies at z~3 to establish a relationship between
reddening, neutral gas covering fraction (fcov(HI)), and the escape of ionizing
photons at high redshift. Our sample includes 933 galaxies at z~3, 121 of which
have very deep spectroscopic observations (>7 hrs) in the rest-UV
(lambda=850-1300 A) with Keck/LRIS. Based on the high covering fraction of
outflowing optically-thick HI indicated by the composite spectra of these
galaxies, we conclude that photoelectric absorption, rather than dust
attenuation, dominates the depletion of ionizing photons. By modeling the
composite spectra as the combination of an unattenuated stellar spectrum
including nebular continuum emission with one that is absorbed by HI and
reddened by a line-of-sight extinction, we derive an empirical relationship
between E(B-V) and fcov(HI). Galaxies with redder UV continua have larger
covering fractions of HI characterized by higher line-of-sight extinctions. Our
results are consistent with the escape of Lya through gas-free lines-of-sight.
Covering fractions based on low-ionization interstellar absorption lines
systematically underpredict those deduced from the HI lines, suggesting that
much of the outflowing gas may be metal-poor. We develop a model which connects
the ionizing escape fraction with E(B-V), and which may be used to estimate the
escape fraction for an ensemble of high-redshift galaxies. Alternatively,
direct measurements of the escape fraction for our data allow us to constrain
the intrinsic 900-to-1500 A flux density ratio to be >0.20, a value that favors
stellar population models that include weaker stellar winds, a flatter initial
mass function, and/or binary evolution. Lastly, we demonstrate how the
framework discussed here may be used to assess the pathways by which ionizing
radiation escapes from high-redshift galaxies. [Abridged]


  In a landmark 1981 paper, Valiant and Brebner gave birth to the study of
oblivious routing and, simultaneously, introduced its most powerful and
ubiquitous method: Valiant load balancing (VLB). By routing messages through a
randomly sampled intermediate node, VLB lengthens routing paths by a factor of
two but gains the crucial property of obliviousness. Forty years later, with
datacenters handling workloads whose communication pattern varies too rapidly
to allow centralized coordination, VLB continues to take center stage as a
widely used - and in some cases provably optimal - way to balance load in the
network obliviously to the traffic demands. However, the ability of the network
to rapidly reconfigure its interconnection topology gives rise to new
possibilities.
  In this work we revisit the question of whether VLB remains optimal in the
novel setting of reconfigurable networks. Prior work showed that VLB achieves
the optimal tradeoff between latency and guaranteed throughput. In this work we
show that a strictly superior latency-throughput tradeoff is achievable when
the throughput bound is relaxed to hold with high probability. The same
improved tradeoff is also achievable with guaranteed throughput under
time-stationary demands, provided the latency bound is relaxed to hold with
high probability and that the network is allowed to be semi-oblivious, using an
oblivious (randomized) connection schedule but demand-aware routing. We prove
that the latter result is not achievable by any fully-oblivious reconfigurable
network design, marking a rare case in which semi-oblivious routing has a
provable asymptotic advantage over oblivious routing. To analyze our routing
scheme we prove an exponential tail bound which may be of independent interest,
concerning the distribution of values of a bilinear form on an orbit of a
permutation group action.


  The elastic hadron-hadron scattering at high energies is one of the most
fundamental subjects of all particle physics problems and yet is least
understood in spite of many advances in quantum chromodynamics (QCD) at the
conceptual level. We review here the recent theoretical and experimental status
of the subject as well as the rigorous results of the high energy hadron-hadron
scattering. Surprisingly enough, the high-energy models for the elastic and
diffractive scattering abstracted from the Regge-Pomeron field theory is still
{\it phenomenologically} successful to explain the high-energy scattering data
though no rigorous derivation out of the QCD is yet available.


  We consider the entropy associated with the large-scale structure of the
Universe in the linear regime, where the Universe can be described by a
perturbed Friedmann-Lema\^itre spacetime. In particular, we compare two
different definitions proposed in the literature for the entropy using a
spatial averaging prescription. For one definition, the entropy of the
large-scale structure for a given comoving volume always grows with time, both
for a CDM and a $\Lambda$CDM model. In particular, while it diverges for a CDM
model, it saturates to a constant value in the presence of a cosmological
constant. The use of a light-cone averaging prescription in the context of the
evaluation of the entropy is also discussed.


  3D representation is essential to the significant advance of 3D generation
with 2D diffusion priors. As a flexible representation, NeRF has been first
adopted for 3D representation. With density-based volumetric rendering, it
however suffers both intensive computational overhead and inaccurate mesh
extraction. Using a signed distance field and Marching Tetrahedra, DMTet allows
for precise mesh extraction and real-time rendering but is limited in handling
large topological changes in meshes, leading to optimization challenges.
Alternatively, 3D Gaussian Splatting (3DGS) is favored in both training and
rendering efficiency while falling short in mesh extraction. In this work, we
introduce a novel 3D representation, Tetrahedron Splatting (TeT-Splatting),
that supports easy convergence during optimization, precise mesh extraction,
and real-time rendering simultaneously. This is achieved by integrating
surface-based volumetric rendering within a structured tetrahedral grid while
preserving the desired ability of precise mesh extraction, and a tile-based
differentiable tetrahedron rasterizer. Furthermore, we incorporate eikonal and
normal consistency regularization terms for the signed distance field to
improve generation quality and stability. Critically, our representation can be
trained without mesh extraction, making the optimization process easier to
converge. Our TeT-Splatting can be readily integrated in existing 3D generation
pipelines, along with polygonal mesh for texture optimization. Extensive
experiments show that our TeT-Splatting strikes a superior tradeoff among
convergence speed, render efficiency, and mesh quality as compared to previous
alternatives under varying 3D generation settings.


  We prove that if all roots of the discrete Wronskian with step 1 of a set of
quasi-exponentials with real bases are real, simple and differ by at least 1,
then the complex span of this set of quasi-exponentials has a basis consisting
of quasi-exponentials with real coefficients. This result generalizes the B.
and M.Shapiro conjecture about spaces of polynomials.
  The proof is based on the Bethe ansatz method for the XXX model.


  We propose a fine analysis of second order optimality conditions for the
optimal control of semi-linear parabolic equations with respect to the initial
condition. More precisely, we investigate the following problem: maximise with
respect to $y\in L^\infty({(0;T)\times \Omega})$ the cost functional
$J(y)=\iint_{(0;T)\times \Omega}j_1(t,x,u)+\int_\Omega j_2(x,u(T,\cdot))$ where
$\partial_t u-\Delta u=f(t,x,u)+y\,, u(0,\cdot)=u_0$ with some classical
boundary conditions, under constraints of the form $-\kappa_0\leq y\leq
\kappa_1\text{ a.e.}\,, \int_\Omega y(t,\cdot)=V_0$. This class of problems
arises in several application fields. A challenging feature of these problems
is the study of the so-called abnormal set $ \{-\kappa_0<y^*<\kappa_1\}$ where
$y^*$ is an optimiser. This set is in general non-empty and it is important
(for instance for numerical applications) to understand the behaviour of $y^*$
in this set: which values can $ y^*$ take? In this paper, we introduce a
Laplace-type method to provide some answers to this question. This Laplace type
method is of independent interest.


  We introduce a class of inequalities based on low order correlations of
operators to detect entanglement in bipartite systems. The operators may either
be Hermitian or non-Hermitian and are applicable to any physical system or
class of states. Testing the criteria on example systems reveals that they
outperform other common correlation based criteria, such as those by
Duan-Giedke-Cirac-Zoller and Hillery-Zubairy. One unusual feature of the
criteria is that it includes a term involving the average of the density matrix
squared, related to the purity of the system. We discuss how such a term could
be measured in relation to the criteria.


  A novel concept of a high luminosity hadron collider is proposed. This would
be a typical application of an induction synchrotron being newly developed.
Extremely long bunches, referred to as superbunches, are generated by a multi-
bunch stacking method employing barrier buckets at the injection into the
collider, and are accelerated to the collider energy with an step-voltage
induced in the induction gaps. Superbunches intersect with each other, yielding
a luminosity of more than $10^{35} /cm^2/sec$. A combination of vertical
crossing and horizontal crossing can be used in order to avoid any significant
beam-beam tune shift.


  We present a novel realisation of the $\mathbb{Z}_2\times\mathbb{Z}_2$-graded
Lie superalgebra $\mathfrak{gl}(m_1,m_2|n_1,n_2)$ inside an algebraic extension
of the enveloping algebra of the $\mathbb{Z}_2$-graded Lie superalgebra
$\mathfrak{gl}(m|n)$, with $m=m_1+m_2$ and $n=n_1+n_2$. A consequence of this
realisation is that the representations of $\mathfrak{gl}(m|n)$ "lift up" to
representations of $\mathfrak{gl}(m_1,m_2|n_1,n_2)$, with matrix elements
differing only by a sign, which we are able to characterise concisely.


  We analyze the dependence of the QCD transition temperature on the quark (or
pion) mass. We find that a linear sigma model, which links the transition to
chiral symmetry restoration, predicts a much stronger dependence of T_c on m_pi
than seen in present lattice data for m_pi >~ 0.4 GeV. On the other hand,
working down from m_pi=infinity, an effective Lagrangian for the Polyakov loop
requires only small explicit symmetry breaking, b_1 ~ exp(-m_pi), to describe
T_c(m_pi) in the above mass range. Physically, this is a consequence of the
flat potential (large correlation length) for the Polyakov loop in the
three-color pure gauge theory at T_c. We quantitatively estimate the end point
of the line of first order deconfining phase transitions: m_pi = 1.8 GeV and Tc
= 240 MeV for three flavors and three colors.


  Post-editing has proven effective in improving the quality of text generated
by large language models (LLMs) such as GPT-3.5 or GPT-4, particularly when
direct updating of their parameters to enhance text quality is infeasible or
expensive. However, relying solely on smaller language models for post-editing
can limit the LLMs' ability to generalize across domains. Moreover, the editing
strategies in these methods are not optimally designed for text-generation
tasks. To address these limitations, we propose a neural programmer-interpreter
approach that preserves the domain generalization ability of LLMs when editing
their output. The editing actions in this framework are specifically devised
for text generation. Extensive experiments demonstrate that the
programmer-interpreter significantly enhances GPT-3.5's performance in logical
form-to-text conversion and low-resource machine translation, surpassing other
state-of-the-art (SOTA) LLM post-editing methods in cross-domain settings.


  Super-Resolution (SR) has gained increasing research attention over the past
few years. With the development of Deep Neural Networks (DNNs), many
super-resolution methods based on DNNs have been proposed. Although most of
these methods are aimed at ordinary frames, there are few works on
super-resolution of omnidirectional frames. In these works, omnidirectional
frames are projected from the 3D sphere to a 2D plane by Equi-Rectangular
Projection (ERP). Although ERP has been widely used for projection, it has
severe projection distortion near poles. Current DNN-based SR methods use 2D
convolution modules, which is more suitable for the regular grid. In this
paper, we find that different projection methods have great impact on the
performance of DNNs. To study this problem, a comprehensive comparison of
projections in omnidirectional super-resolution is conducted. We compare the SR
results of different projection methods. Experimental results show that
Equi-Angular cube map projection (EAC), which has minimal distortion, achieves
the best result in terms of WS-PSNR compared with other projections. Code and
data will be released.


  An electron-multiplying charge-coupled device (EMCCD) is often used for
taking images with space telescopes and other devices. Photons hit the pixels
and photo-electrons are created, and these are multiplied via impact ionization
as they travel through the gain register from one gain stage to the next. A
high gain means a high multiplication factor, and this is achieved through a
high voltage difference across a gain stage. If the gain is high enough, the
chance of clock-induced charge production in the gain register increases. The
probability distribution function governing the gain process in the literature
only accounts for charge multiplication if one or more electrons enters the
gain register. I derive from first principles the modified probability
distribution that accounts for clock-induced charge production in the gain
register. I also examine some EMCCD data and show through maximum likelihood
estimation that the data conform better to the modified distribution versus the
usual one in the literature. The use of the modified distribution would in
principle improve the accuracy of signal extraction from a frame.


  We briefly review the electromagnetic model of Gamma Ray Bursts and then
discuss how various models account for high prompt polarization. We argue that
if polarization is confirmed at a level $\Pi \geq 10%$ the internal shock model
is excluded.


  The real unit interval is the fundamental building block for many branches of
mathematics like probability theory, measure theory, convex sets and homotopy
theory. However, a priori the unit interval could be considered an arbitrary
choice and one can wonder if there is some more canonical way in which the unit
interval can be constructed. In this paper we find such a construction by using
the theory of effect algebras. We show that the real unit interval is the
unique non-initial, non-final irreducible algebra of a particular monad on the
category of bounded posets. The algebras of this monad carry an order,
multiplication, addition and complement, and as such model much of the
operations we need to do on probabilities. On a technical level, we show that
both the categories of omega-complete effect algebras as well as that of
omega-complete effect monoids are monadic over the category of bounded posets
using Beck's monadicity theorem. The characterisation of the real unit interval
then follows easily using a recent representation theorem for omega-complete
effect monoids.


  We study the 1:4 resonance for the conservative cubic H\'enon maps
$\mathbf{C}_\pm$ with positive and negative cubic term. These maps show up
different bifurcation structures both for fixed points with eigenvalues $\pm i$
and for 4-periodic orbits. While for $\mathbf{C}_-$ the 1:4 resonance unfolding
has the so-called Arnold degeneracy (the first Birkhoff twist coefficient
equals (in absolute value) to the first resonant term coefficient), the map
$\mathbf{C}_+$ has a different type of degeneracy because the resonant term can
vanish. In the last case, non-symmetric points are created and destroyed at
pitchfork bifurcations and, as a result of global bifurcations, the 1:4
resonant chain of islands rotates by $\pi/4$. For both maps several
bifurcations are detected and illustrated.


  Let Gamma be a discrete group satisfying the rapid decay property with
respect to a length function which is conditionally negative. Then the reduced
C*-algebra of Gamma has the metric approximation property.
  The central point of our proof is an observation that the proof of the same
property for free groups due to Haagerup transfers directly to this more
general situation. Examples of groups satisfying the hypotheses include free
groups, surface groups, finitely generated Coxeter groups, right angled Artin
groups and many small cancellation groups.


  Solutions are obtained for the dual form of the Schr\"odinger equation got
from the transformation of Poisson equation for the vector and the scalar
potential, in dielectric and magnetic materials, having into account
homogeneous isotropic linear mechanisms. We study and apply these dual equation
solutions in some specific potentials.


  We report on a new experiment that tests for a violation of Lorentz
invariance (LI), by searching for a dependence of atomic transition frequencies
on the orientation of the spin of the involved states (Hughes-Drever type
experiment). The atomic frequencies are measured using a laser cooled
$^{133}$Cs atomic fountain clock, operating on a particular combination of
Zeeman substates. We analyze the results within the framework of the Lorentz
violating standard model extension (SME), where our experiment is sensitive to
a largely unexplored region of the SME parameter space, corresponding to first
measurements of four proton parameters and improvements by 11 and 13 orders of
magnitude on the determination of four others. In spite of the attained
uncertainties, and of having extended the search into a new region of the SME,
we still find no indication of LI violation.


  Using the Geant4 code, we have performed a full-scale simulation of the LSD
response to the neutrino burst from SN1987A. The neutrino flux parameters were
chosen according to one of the models: the standard collapse model or the
rotational supernova explosion model. We showed that, depending on the chosen
parameters, one can either obtain the required number of pulses in the detector
or reproduce their energy spectrum, but not both together. The interaction of
neutrino radiation both with LSD itself and with the material of the
surrounding soil was taken into account in our simulation. We also explored the
hypothesis that the entire unique LSD signal at 2:52 UT was produced by neutron
fluxes from the surrounding granite. However, this hypothesis was not confirmed
by our simulation. The results obtained provide a rich material for possible
interpretations.


  We present our novel deep multi-task learning method for medical image
segmentation. Existing multi-task methods demand ground truth annotations for
both the primary and auxiliary tasks. Contrary to it, we propose to generate
the pseudo-labels of an auxiliary task in an unsupervised manner. To generate
the pseudo-labels, we leverage Histogram of Oriented Gradients (HOGs), one of
the most widely used and powerful hand-crafted features for detection. Together
with the ground truth semantic segmentation masks for the primary task and
pseudo-labels for the auxiliary task, we learn the parameters of the deep
network to minimise the loss of both the primary task and the auxiliary task
jointly. We employed our method on two powerful and widely used semantic
segmentation networks: UNet and U2Net to train in a multi-task setup. To
validate our hypothesis, we performed experiments on two different medical
image segmentation data sets. From the extensive quantitative and qualitative
results, we observe that our method consistently improves the performance
compared to the counter-part method. Moreover, our method is the winner of
FetReg Endovis Sub-challenge on Semantic Segmentation organised in conjunction
with MICCAI 2021.


  We study the effects of grain surface reactions on the chemistry of
protoplanetary disks where gas, ice surface layers and icy mantles of dust
grains are considered as three distinct phases. Gas phase and grain surface
chemistry is found to be mainly driven by photo-reactions and dust temperature
gradients. The icy disk interior has three distinct chemical regions: (i) the
inner midplane with low FUV fluxes and warm dust ($\gtrsim 15$K) that lead to
the formation of complex organic molecules, (ii) the outer midplane with higher
FUV from the ISM and cold dust where hydrogenation reactions dominate and,
(iii) a molecular layer above the midplane but below the water condensation
front where photodissociation of ices affects gas phase compositions. Some
common radicals, e.g., CN and C$_2$H, exhibit a two-layered vertical structure
and are abundant near the CO photodissociation front and near the water
condensation front. The 3-phase approximation in general leads to lower
vertical column densities than 2-phase models for many gas-phase molecules due
to reduced desorption, e.g., H$_2$O, CO$_2$, HCN and HCOOH decrease by $\sim$
two orders of magnitude. Finally, we find that many observed gas phase species
originate near the water condensation front; photo-processes determine their
column densities which do not vary significantly with key disk properties such
as mass and dust/gas ratio.


  We investigate modifications of hadron masses at finite quark chemical
potential in two-flavor and two-color QCD, of which the data are available from
lattice simulations, within a linear sigma model based on approximate
Pauli-Gursey $SU(4)$ symmetry. The model describes not only ground-state scalar
diquarks and pseudo-scalar mesons but also the excited pseudo-scalar diquarks
and scalar mesons; each ground-state diquark (meson) has the corresponding
excited diquark (hadron) with opposite parity as a chiral partner. Effects of
chiral symmetry breaking and diquark condensates are incorporated by a
mean-field treatment. We show that various mixings among the hadrons, which are
triggered by the breakdown of baryon number conservation in the superfluid
phase, lead to a rich hadron mass spectrum. We discuss the influence of
$U(1)_A$ anomaly on the density dependence of the mass spectrum and also
manifestations of the chiral partner structures as density increases in the
superfluid phase. The predicted hadron masses are expected to provide future
lattice simulations with useful information on such symmetry properties in
dense two-color QCD.


  We introduce the task of changing the narrative point of view, where
characters are assigned a narrative perspective that is different from the one
originally used by the writer. The resulting shift in the narrative point of
view alters the reading experience and can be used as a tool in fiction writing
or to generate types of text ranging from educational to self-help and
self-diagnosis. We introduce a benchmark dataset containing a wide range of
types of narratives annotated with changes in point of view from deictic (first
or second person) to anaphoric (third person) and describe a pipeline for
processing raw text that relies on a neural architecture for mention selection.
Evaluations on the new benchmark dataset show that the proposed architecture
substantially outperforms the baselines by generating mentions that are less
ambiguous and more natural.


  The constant increase in parallelism available on large-scale distributed
computers poses major scalability challenges to many scientific applications. A
common strategy to improve scalability is to express the algorithm in terms of
independent tasks that can be executed concurrently on a runtime system. In
this manuscript, we consider a generalization of this approach where task-level
speculation is allowed. In this context, a probability is attached to each task
which corresponds to the likelihood that the product of the task will be
consumed as part of the calculation. We consider the problem of optimal
resource allocation to each of the possible tasks so as too maximize the
expected overall computational throughput. The power of this approach is
demonstrated by analyzing its application to Parallel Trajectory Splicing, a
massively-parallel long-time-dynamics method for atomistic simulations.


  We prove that the the kernel of the reciprocity map for a product of curves
over a $p$-adic field with split semi-stable reduction is divisible. We also
consider the $K_1$ of a product of curves over a number field.


  The unified $ (p,q; \alpha,\gamma, l)$-deformation of a number of well-known
deformed oscillator algebras is introduced.The deformation is constructed by
imputing new free parameters into the structure functions and by generalizing
the defining relations of these algebras. The generalized Jordan-Schwinger and
Holstein-Primakoff realizations of the $U_{pq}^{\alpha \gamma l}(su(2))$
algebra by the generalized $ (p,q; \alpha,\gamma, l)$-deformed operators are
found.
  The generalized $ (p,q; \alpha,\gamma, l)$-deformation of the two-dimensional
conformal field theory is established. By introducing the $ (p,q;
\alpha,\gamma, l)$-operator product expansion (OPE) between the energy momentum
tensor and primary fields, we obtain the $ (p,q; \alpha,\gamma, l)$-deformed
centerless Virasoro algebra. The two-point correlation function of the primary
generalized $ (p,q; \alpha,\gamma, l)$-deformed fields is calculated.


  Extant chemical evolution models underestimate the Galactic production of Sr,
Y and Zr as well as the Solar System abundances of s-only isotopes with
90<A<130. To solve this problem, an additional (unknown) process has been
invoked, the so-called LEPP (Light Element Primary Process). In this paper we
investigate possible alternative solutions. Basing on Full Network Stellar
evolutionary calculations, we investigate the effects on the Solar System
s-only distribution induced by the inclusion of some commonly ignored physical
processes (e.g. rotation) or by the variation of the treatment of convective
overshoot, mass-loss and the efficiency of nuclear processes. Our main findings
are: 1) at the epoch of the formation of the Solar System, our reference model
produces super-solar abundances for the whole s-only distribution, even in the
range 90<A<130; 2) within errors, the s-only distribution relative to 150Sm is
flat; 3) the s-process contribution of the less massive AGB stars (M<1.5 M_SUN)
as well as of the more massive ones (M>4.0 M_SUN) are negligible; 4) the
inclusion of rotation implies a downward shift of the whole distribution with
an higher efficiency for the heavy s-only isotopes, leading to a flatter s-only
distribution; 5) different prescriptions on convection or mass-loss produce
nearly rigid shifts of the whole distribution. In summary, a variation of the
standard paradigm of AGB nucleosynthesis would allow to reconcile models
predictions with Solar System s-only abundances. Nonetheless, the LEPP cannot
be definitely ruled out, because of the uncertainties still affecting stellar
and Galactic chemical evolution models.


  We determine the minimum Wehrl entropy among the quantum states with a given
von Neumann entropy, and prove that it is achieved by thermal Gaussian states.
This result determines the relation between the von Neumann and the Wehrl
entropies. The key idea is proving that the quantum-classical channel that
associates to a quantum state its Husimi Q representation is asymptotically
equivalent to the Gaussian quantum-limited amplifier with infinite
amplification parameter. This equivalence also permits to determine the p->q
norms of the aforementioned quantum-classical channel in the two particular
cases of one mode and p=q, and prove that they are achieved by thermal Gaussian
states. The same equivalence permits to prove that the Husimi Q representation
of a one-mode passive state (i.e. a state diagonal in the Fock basis with
eigenvalues decreasing as the energy increases) majorizes the Husimi Q
representation of any other one-mode state with the same spectrum, i.e. it
maximizes any convex functional.


  In this letter, we analyze the achievable rate of ultra-reliable low-latency
communications (URLLC) in a randomly modeled wireless network. We use two
mathematical tools to properly characterize the considered system: i)
stochastic geometry to model spatial locations of the transmitters in a
network, and ii) finite block-length analysis to reflect the features of the
short-packets. Exploiting these tools, we derive an integral-form expression of
the decoding error probability as a function of the target rate, the path-loss
exponent, the communication range, the density, and the channel coding length.
We also obtain a tight approximation as a closed-form. The main finding from
the analytical results is that, in URLLC, increasing the signal-to-interference
ratio (SIR) brings significant improvement of the rate performance compared to
increasing the channel coding length. Via simulations, we show that fractional
frequency reuse improves the area spectral efficiency by reducing the amount of
mutual interference.


  In this paper we investigate the asymptotic behavior of the Riesz $s$-energy
of the first $N$ points of a greedy $s$-energy sequence on the unit circle, for
all values of $s$ in the range $0\leq s<\infty$ (identifying as usual the case
$s=0$ with the logarithmic energy). In the context of the unit circle, greedy
$s$-energy sequences coincide with the classical Leja sequences constructed
using the logarithmic potential. We obtain first-order and second-order
asymptotic results. The key idea is to express the Riesz $s$-energy of the
first $N$ points of a greedy $s$-energy sequence in terms of the binary
representation of $N$. Motivated by our results, we pose some conjectures for
general sequences on the unit circle.


  Two near-threshold peaking structures with spin-parities $J^{\mathrm{PC}
}=0^{++}$ were recently discovered by the LHCb Collaboration in the $
D_{s}^{+}D_{s}^{-}$ invariant mass distribution of the decay $ B^{+}\rightarrow
D_{s}^{+}D_{s}^{-}K^{+}$. The first of them is the resonance $X(3960)$, whereas
the second one, $X_0(4140)$, is a structure with the mass around
$4140~\mathrm{MeV}$. To explore their natures and model them, we study the
hadronic molecule $\mathcal{M}=D_s^{+}D_s^{-}$ and calculate its mass, current
coupling, and width. The mass and current coupling of the molecule are
extracted from the QCD two-point sum rule analyses by taking into account
vacuum condensates up to dimension $10$. To evaluate its full width, we
consider the processes $\mathcal{M} \to D_{s}^{+}D_{s}^{-}$, $\mathcal{M}
\to\eta_{c}\eta^{(\prime)}$, and $\mathcal{ M} \to J/\psi\phi$. Partial widths
of these decays are determined by the strong couplings $g_i, \ i=1,2,3,4 $ at
vertices $\mathcal{M} D_{s}^{+}D_{s}^{-}$, $\mathcal{M}\eta_{c}
\eta^{(\prime)}$, and $\mathcal{M} J/\psi\phi$. They are computed by means of
the three-point sum rule method. Predictions for the mass $m=(4117 \pm
85)~\mathrm{MeV}$ and width $\Gamma_{ \mathcal{M}}=(62 \pm 12)~\mathrm{MeV}$ of
the molecule $\mathcal{M}$ are compared with the corresponding LHCb data, and
also with our results for the diquark-antidiquark state
$X=[cs][\overline{c}\overline{s}]$. We argue that the structure $X_0(4140)$ may
be interpreted as the hadronic molecule $ D_s^{+}D_s^{-}$, whereas the
resonance $X(3960)$ can be identified with the tetraquark $X$.


  The goal of this article is to present interactive didactic software for
analog to digital conversion using PCM method. After a short introduction
regarding vocal signal processing we present some method for analog to digital
conversion. The didactic software is an applet that can be direct accessed by
any interested person.


  Instrumenting the LHC to measure the outgoing protons in the process pp ->
p+X+p opens up new possibilities for physics studies in the Standard Model and
beyond. In this talk I first present an overview of the underlying QCD
calculation and its uncertainties. I then move on to present a variety of new
physics scenarios which one would want to explore via this unique channel.
There is a short discussion of the recent CDF data which may provide evidence
for the existence of central exclusive jet production at the Tevatron.


  Chimera state is defined as a mixed type of collective state in which
synchronized and desynchronized subpopulations of a network of coupled
oscillators coexist and the appearance of such anomalous behavior has strong
connection to diverse neuronal developments. Most of the previous studies on
chimera states are not extensively done in two-dimensional ensembles of coupled
oscillators by taking neuronal systems with nonlinear coupling function into
account while such ensembles of oscillators are more realistic from a
neurobiological point of view. In this paper, we report the emergence and
existence of chimera states by considering locally coupled two-dimensional
networks of identical oscillators where each node is interacting through
nonlinear coupling function. This is in contrast with the existence of chimera
states in two-dimensional nonlocally coupled oscillators with rectangular
kernel in the coupling function. We find that the presence of nonlinearity in
the coupling function plays a key role to produce chimera states in
two-dimensional locally coupled oscillators. We analytically verify explicitly
in the case of a network of coupled Stuart - Landau oscillators in two
dimensions that the obtained results using Ott-Antonsen approach and our
analytical finding very well matches with the numerical results. Next, we
consider another type of important nonlinear coupling function which exists in
neuronal systems, namely chemical synaptic function, through which the
nearest-neighbor (locally coupled) neurons interact with each other. In
numerical simulations, we consider two paradigmatic neuronal oscillators,
namely Hindmarsh-Rose neuron model and Rulkov map for each node which exhibit
bursting dynamics. The existence of chimera states is confirmed by
instantaneous angular frequency, order parameter and strength of incoherence.


  Neural networks do not generalize well to unseen data with domain shifts -- a
longstanding problem in machine learning and AI. To overcome the problem, we
propose MixStyle, a simple plug-and-play, parameter-free module that can
improve domain generalization performance without the need to collect more data
or increase model capacity. The design of MixStyle is simple: it mixes the
feature statistics of two random instances in a single forward pass during
training. The idea is grounded by the finding from recent style transfer
research that feature statistics capture image style information, which
essentially defines visual domains. Therefore, mixing feature statistics can be
seen as an efficient way to synthesize new domains in the feature space, thus
achieving data augmentation. MixStyle is easy to implement with a few lines of
code, does not require modification to training objectives, and can fit a
variety of learning paradigms including supervised domain generalization,
semi-supervised domain generalization, and unsupervised domain adaptation. Our
experiments show that MixStyle can significantly boost out-of-distribution
generalization performance across a wide range of tasks including image
recognition, instance retrieval and reinforcement learning.


  We formulate a version of Hopkins' chromatic splitting conjecture for an
arbitrary structured ring spectrum $R$, and prove it whenever $\pi_*R$ is
Noetherian. As an application, these results provide a new local-to-global
principle in the modular representation theory of finite groups.


  With the aid of the quasiclassical Eilenberger formalism we develop a theory
of non-local electron transport across three-terminal ballistic
normal-superconducting-normal (NSN) devices with spin-active NS interfaces. The
phenomenon of crossed Andreev reflection (CAR) is known to play the key role in
such transport. We demonstrate that CAR is highly sensitive to electron spins
and yields a rich variety of properties of non-local conductance which we
describe non-perturbatively at arbitrary voltages, temperature, spin-dependent
interface transmissions and their polarizations. Our results can be applied to
multi-terminal hybrid structures with normal, ferromagnetic and half-metallic
electrodes and can be directly tested in future experiments.


  Calibrated data for 143 flat-spectrum extragalactic radio sources are
presented at a wavelength of 850 microns covering a five-year period from April
2000. The data, obtained at the James Clerk Maxwell Telescope using the SCUBA
camera in pointing mode, were analysed using an automated pipeline process
based on the Observatory Reduction and Acquisition Control - Data Reduction
(ORAC-DR) system. This paper describes the techniques used to analyse and
calibrate the data, and presents the database of results along with a
representative sample of the better-sampled lightcurves. A re-analysis of
previously published data from 1997 to 2000 is also presented. The combined
catalogue, comprising 10493 flux density measurements, provides a unique and
valuable resource for studies of extragalactic radio sources.


  We present mean angular diameters for two cepheid variables, alpha Ursae
Minoris and zeta Geminorum, determined with the Navy Prototype Optical
Interferometer (NPOI). We present linear radii for these cepheids and two
additional cepheids, delta Cephei and eta Aquilae, previously observed at the
NPOI. We find the limb-darkened angular diameter of alpha Ursae Minoris and of
zeta Geminorum to be 3.28 +/- 0.02 and 1.55 +/- 0.09 milliarcseconds
respectively. Using trigonometric parallaxes, we find the linear radii of alpha
Ursae Minoris, zeta Geminorum, delta Cephei and eta Aquilae to be 46 (+/- 3),
60 (+25, -14), 45 (+8, -6), and 69 (+28, -15) Solar radii respectively. We
compare the pulsation periods and linear radii of this sample of cepheids,
which range in period from three to 11 days, to theoretical and empirical
period-radius and period-radius-mass relations found in the literature. We find
that the observed diameter of alpha Ursae Minoris is in excellent agreement
with the predicted diameter as determined from both surface brightness
techniques and theory only if alpha Ursae Minoris is a first overtone pulsator.


  We address the problem of predicting the occurrence of infrequent adverse
events in the context of predictive maintenance. We cast the corresponding
machine learning task as an imbalanced classification problem and propose a
framework for solving it that is capable of leveraging different classifiers in
order to predict the occurrence of an adverse event before it takes place. In
particular, we focus on two applications arising in low-carbon energy
production: foam formation in anaerobic digestion and condenser tube leakage in
the steam turbines of a nuclear power station. The results of an extensive set
of omputational experiments show the effectiveness of the techniques that we
propose.


  Diffusive transport is among the most common phenomena in nature [1].
However, as predicted by Anderson [2], diffusion may break down due to
interference. This transition from diffusive transport to localization of waves
should occur for any type of classical or quantum wave in any media as long as
the wavelength becomes comparable to the transport mean free path $\ell^*$ [3].
The signatures of localization and those of absorption, or bound states, can
however be similar, such that an unequivocal proof of the existence of wave
localization in disordered bulk materials is still lacking. Here we present
measurements of time resolved non-classical diffusion of visible light in
strongly scattering samples, which cannot be explained by absorption, sample
geometry or reduction in transport velocity. Deviations from classical
diffusion increase strongly with decreasing $\ell^*$ as expected for a phase
transition. This constitutes an experimental realization of the critical regime
in the approach to Anderson localization.


  Zero-sum stochastic games have found important applications in a variety of
fields, from machine learning to economics. Work on this model has primarily
focused on the computation of Nash equilibrium due to its effectiveness in
solving adversarial board and video games. Unfortunately, a Nash equilibrium is
not guaranteed to exist in zero-sum stochastic games when the payoffs at each
state are not convex-concave in the players' actions. A Stackelberg
equilibrium, however, is guaranteed to exist. Consequently, in this paper, we
study zero-sum stochastic Stackelberg games. Going beyond known existence
results for (non-stationary) Stackelberg equilibria, we prove the existence of
recursive (i.e., Markov perfect) Stackelberg equilibria (recSE) in these games,
provide necessary and sufficient conditions for a policy profile to be a recSE,
and show that recSE can be computed in (weakly) polynomial time via value
iteration. Finally, we show that zero-sum stochastic Stackelberg games can
model the problem of pricing and allocating goods across agents and time. More
specifically, we propose a zero-sum stochastic Stackelberg game whose recSE
correspond to the recursive competitive equilibria of a large class of
stochastic Fisher markets. We close with a series of experiments that showcase
how our methodology can be used to solve the consumption-savings problem in
stochastic Fisher markets.


  Recently, the Degrees-of-Freedom (DoF) region of multiple-input-single-output
(MISO) networks with imperfect channel state information at the transmitter
(CSIT) has attracted significant attentions. An achievable scheme is known as
rate-splitting (RS) that integrates common-message-multicasting and
private-message-unicasting. In this paper, focusing on the general $K$-cell
MISO IC where the CSIT of each interference link has an arbitrary quality of
imperfectness, we firstly identify the DoF region achieved by RS. Secondly, we
introduce a novel scheme, so called Topological RS (TRS), whose novelties
compared to RS lie in a multi-layer structure and transmitting multiple common
messages to be decoded by groups of users rather than all users. The design of
TRS is motivated by a novel interpretation of the $K$-cell IC with imperfect
CSIT as a weighted-sum of a series of partially connected networks. We show
that the DoF region achieved by TRS covers that achieved by RS. Also, we find
the maximal sum DoF achieved by TRS via hypergraph fractional packing, which
yields the best sum DoF so far. Lastly, for a realistic scenario where each
user is connected to three dominant transmitters, we identify the sufficient
condition where TRS strictly outperforms conventional schemes.


  Advances in generative models have made it possible for AI-generated text,
code, and images to mirror human-generated content in many applications.
Watermarking, a technique that aims to embed information in the output of a
model to verify its source, is useful for mitigating the misuse of such
AI-generated content. However, we show that common design choices in LLM
watermarking schemes make the resulting systems surprisingly susceptible to
attack -- leading to fundamental trade-offs in robustness, utility, and
usability. To navigate these trade-offs, we rigorously study a set of simple
yet effective attacks on common watermarking systems, and propose guidelines
and defenses for LLM watermarking in practice.


  Based on Gaia Early Data Release 3 (EDR3), we estimate the proper motions for
46 dwarf spheroidal galaxies (dSphs) of the Milky Way. The uncertainties in
proper motions, determined by combining both statistical and systematic errors,
are smaller by a factor 2.5, when compared with Gaia Data Release 2. We have
derived orbits in four Milky Way potential models that are consistent with the
MW rotation curve, with total mass ranging from $2.8\times10^{11}$ $M_{\odot}$
to $15\times10^{11}$ $M_{\odot}$. Although the type of orbit (ellipse or
hyperbola) are very dependent on the potential model, the pericenter values are
firmly determined, largely independent of the adopted MW mass model. By
analyzing the orbital phases, we found that the dSphs are highly concentrated
close to their pericenter, rather than to their apocenter as expected from
Kepler's law. This may challenge the fact that most dSphs are Milky Way
satellites, or alternatively indicates an unexpected large number of
undiscovered dSphs lying very close to their apocenters. Between half and two
thirds of the satellites have orbital poles that indicate them to orbit along
the Vast Polar Structure (VPOS), with the vast majority of these co-orbiting in
a common direction also shared by the Magellanic Clouds, which is indicative of
a real structure of dSphs.


  Together with one of its variants, the recently proposed phase-merging
enhanced harmonic generation (PEHG) free-electron lasers (FELs) have been
systematically studied in this paper. Different form the standard-HGHG, a
transverse gradient undulator is employed for introducing a phase-merging
effect into the transversely dispersed electron beam in PEHG. The analytical
theory of the phase-merging effect and the physical mechanism behind the
phenomenon were presented. Using a representative and realistic set of beam
parameters, intensive start-to-end simulations for soft x-ray FEL generation
were given to illustrate the performance of PEHG. Moreover, some practical
issues that may affect the performance of PEHG were also discussed.


  We analyze several recently detected gamma-ray bursts (GRBs) with late X-ray
flares in the context of late internal shock and late external shock models. We
find that the X-ray flares in GRB 050421 and GRB 050502B originate from late
internal shocks, while the main X-ray flares in GRB 050406 and GRB 050607 may
arise from late external shocks. Under the assumption that the central engine
has two periods of activities, we get four basic types of X-ray light curves.
The classification of these types depends on which period of activities
produces the prompt gamma-ray emission (Type 1 and Type 2: the earlier period;
Type 3 and Type 4: the late period), and on whether the late ejecta catching up
with the early ejecta happens earlier than the deceleration of the early ejecta
(Type 1 and Type 3) or not (Type 2 and Type 4). We find that the X-ray flare
caused by a late external shock is a special case of Type 1. Our analysis
reveals that the X-ray light curves of GRBs 050406, 050421, and 050607 can be
classified as Type 1, while the X-ray light curve of GRB 050502B is classified
as Type 2. However, the X-ray light curve of GRB 050406 is also likely to be
Type 2. We also predict a long-lag short-lived X-ray flare caused by the inner
external shock, which forms when a low baryon-loading long-lag late ejecta
decelerates in the non-relativistic tail of an outer external shock driven by
an early ejecta.


  Chest X-Ray imaging is one of the most common radiological tools for
detection of various pathologies related to the chest area and lung function.
In a clinical setting, automated assessment of chest radiographs has the
potential of assisting physicians in their decision making process and optimize
clinical workflows, for example by prioritizing emergency patients.
  Most work analyzing the potential of machine learning models to classify
chest X-ray images focuses on vision methods processing and predicting
pathologies for one image at a time. However, many patients undergo such a
procedure multiple times during course of a treatment or during a single
hospital stay. The patient history, that is previous images and especially the
corresponding diagnosis contain useful information that can aid a
classification system in its prediction.
  In this study, we analyze how information about diagnosis can improve
CNN-based image classification models by constructing a novel dataset from the
well studied CheXpert dataset of chest X-rays. We show that a model trained on
additional patient history information outperforms a model trained without the
information by a significant margin.
  We provide code to replicate the dataset creation and model training.


  We developed a calorimeter with a vacuum container made of superconducting
niobium (Nb) to study monolayers of helium adsorbed on graphite which are
prototypical two-dimensional quantum matters below 1 K. Nb was chosen because
of its small specific heat in the superconducting state. It is crucially
important to reduce the addendum heat capacity ($C_{\rm{ad}}$) when the
specific surface area of substrate is small. Here we show details of design,
construction and results of $C_{\rm{ad}}$ measurements of the Nb calorimeter
down to 40 mK. The measured $C_{\rm{ad}}$ was sufficiently small so that we can
use it for heat capacity measurements on helium monolayers in a wide
temperature range below 1 K. We found a relatively large excess heat capacity
in $C_{\rm{ad}}$, which was successfully attributed to atomic tunneling of
hydrogen (H) and deuterium (D) between trap centers near oxygen or nitrogen
impurities in Nb. The tunnel frequencies of H and D deduced by fitting the data
to the tunneling model are consistent with the previous experiments on Nb doped
with H or D.


  We suggest a scalar singlet extension of the standard model, in which the
multiple-point principle (MPP) condition of a vanishing Higgs potential at the
Planck scale is realized. Although there have been lots of attempts to realize
the MPP at the Planck scale, the realization with keeping naturalness is quite
difficult. Our model can easily achieve the MPP at the Planck scale without
large Higgs mass corrections. It is worth noting that the electroweak symmetry
can be radiatively broken in our model. In the naturalness point of view, the
singlet scalar mass should be of ${\cal O}(1)\,{\rm TeV}$ or less. We also
consider right-handed neutrino extension of the model for neutrino mass
generation. The model does not affect the MPP scenario, and might keep the
naturalness with the new particle mass scale beyond TeV, thanks to accidental
cancellation of Higgs mass corrections.


  Depth completion, which aims to generate high-quality dense depth maps from
sparse depth maps, has attracted increasing attention in recent years. Previous
work usually employs RGB images as guidance, and introduces iterative spatial
propagation to refine estimated coarse depth maps. However, most of the
propagation refinement methods require several iterations and suffer from a
fixed receptive field, which may contain irrelevant and useless information
with very sparse input. In this paper, we address these two challenges
simultaneously by revisiting the idea of deformable convolution. We propose an
effective architecture that leverages deformable kernel convolution as a
single-pass refinement module, and empirically demonstrate its superiority. To
better understand the function of deformable convolution and exploit it for
depth completion, we further systematically investigate a variety of
representative strategies. Our study reveals that, different from prior work,
deformable convolution needs to be applied on an estimated depth map with a
relatively high density for better performance. We evaluate our model on the
large-scale KITTI dataset and achieve state-of-the-art level performance in
both accuracy and inference speed. Our code is available at
https://github.com/AlexSunNik/ReDC.


  Predicting the future trajectory of agents from visual observations is an
important problem for realization of safe and effective navigation of
autonomous systems in dynamic environments. This paper focuses on two important
aspects of future trajectory forecast which are particularly relevant for
mobile platforms: 1) modeling uncertainty of the predictions, particularly from
egocentric views, where uncertainty in the interactive reactions and behaviors
of other agents must consider the uncertainty in the ego-motion, and 2)
modeling multi-modality nature of the problem, which are particularly prevalent
at junctions in urban traffic scenes. To address these problems in a unified
approach, we propose NEMO (Noisy Ego MOtion priors for future object
localization) for future forecast of agents in the egocentric view. In the
proposed approach, a predictive distribution of future forecast is jointly
modeled with the uncertainty of predictions. For this, we divide the problem
into two tasks: future ego-motion prediction and future object localization. We
first model the multi-modal distribution of future ego-motion with uncertainty
estimates. The resulting distribution of ego-behavior is used to sample
multiple modes of future ego-motion. Then, each modality is used as a prior to
understand the interactions between the ego-vehicle and target agent. We
predict the multi-modal future locations of the target from individual modes of
the ego-vehicle while modeling the uncertainty of the target's behavior. To
this end, we extensively evaluate the proposed framework using the publicly
available benchmark dataset (HEV-I) supplemented with odometry data from an
Inertial Measurement Unit (IMU).


  An observation of the gravitationally lensed system 2016+112 with the Chandra
X-ray Observatory has resolved a mystery regarding the proposed presence of a
dark matter object in the lens plane of this system. The Chandra ACIS
observation has clearly detected the lensed images of 2016+112 with positions
in good agreement with those reported in the optical and also detects 13
additional X-ray sources within a radius of 3.5 arcmin. Previous X-ray
observations in the direction of 2016+112 with the ROSAT HRI and ASCA SIS have
interpreted the X-ray data as arising from extended emission from a dark
cluster. However, the present Chandra observation can account for all the X-ray
emission as originating from the lensed images and additional point X-ray
sources in the field. Thus cluster parameters based on previous X-ray
observations are unreliable. We estimate an upper limit on the mass-to-light
ratio within a radius of 800 h_(50)^(-1) kpc of M/L_(V) < 190 h_(50)
(M/L_(V))_Sun. The lensed object is quite unusual, with reported narrow
emission lines in the optical that suggest it may be a type-2 quasar (Yamada
et. al. 1999). Our modeling of the X-ray spectrum of the lensed object implies
that the column density of an intrinsic absorber must lie between 3 and 85 x
10^22 cm^-2 (3 sigma confidence level). The 2-10 keV luminosity of the lensed
object, corrected for the lens magnification effect and using the above range
of intrinsic absorption, is 3 x 10^43 - 1.4 x 10^44 erg/s.


  Allostery is a form of protein regulation, where ligands that bind sites
located apart from the active site can modify the activity of the protein. The
molecular mechanisms of allostery have been extensively studied, because
allosteric sites are less conserved than active sites, and drugs targeting them
are more specific than drugs binding the active sites. Here we quantify the
importance of allostery in genetic disease. We show that 1) known allosteric
proteins are central in disease networks, and contribute to genetic disease and
comorbidities much more than non-allosteric proteins, in many major disease
types like hematopoietic diseases, cardiovascular diseases, cancers, diabetes,
or diseases of the central nervous system. 2) variants from cancer genome-wide
association studies are enriched near allosteric proteins, indicating their
importance to polygenic traits; and 3) the importance of allosteric proteins in
disease is due, at least partly, to their central positions in protein-protein
interaction networks, and probably not due to their dynamical properties.


  In this paper, we examine both stability and sustainability of a
network-based model of natural resource consumption. Stability is studied from
a dynamical systems perspective, though we argue that sustainability is a
fundamentally different notion from stability in social-ecological systems.
Accordingly, we also present a criterion for sustainability that is guided by
the existing literature on sustainable development. Assuming a generic social
network of consuming agents' interactions, we derive sufficient conditions for
both the stability and sustainability of the model as constraints on the
network structure itself. We complement these analytical results with numerical
simulations and discuss the implications of our findings for policy-making for
sustainable resource governance.


  China adjusted the zero-COVID strategy in late 2022, triggering an
unprecedented Omicron wave. We estimated the time-varying reproduction numbers
of 32 provincial-level administrative divisions from December 2022 to January
2023. We found that the pooled estimate of initial reproduction numbers is 4.74
(95% CI: 4.41, 5.07).


  The inductive matrix completion (IMC) problem is to recover a low rank matrix
from few observed entries while incorporating prior knowledge about its row and
column subspaces. In this work, we make three contributions to the IMC problem:
(i) we prove that under suitable conditions, the IMC optimization landscape has
no bad local minima; (ii) we derive a simple scheme with theoretical guarantees
to estimate the rank of the unknown matrix; and (iii) we propose GNIMC, a
simple Gauss-Newton based method to solve the IMC problem, analyze its runtime
and derive recovery guarantees for it. The guarantees for GNIMC are sharper in
several aspects than those available for other methods, including a quadratic
convergence rate, fewer required observed entries and stability to errors or
deviations from low-rank. Empirically, given entries observed uniformly at
random, GNIMC recovers the underlying matrix substantially faster than several
competing methods.


  Semantic Overlap Summarization (SOS) is a constrained multi-document
summarization task, where the constraint is to capture the common/overlapping
information between two alternative narratives. While recent advancements in
Large Language Models (LLMs) have achieved superior performance in numerous
summarization tasks, a benchmarking study of the SOS task using LLMs is yet to
be performed. As LLMs' responses are sensitive to slight variations in prompt
design, a major challenge in conducting such a benchmarking study is to
systematically explore a variety of prompts before drawing a reliable
conclusion. Fortunately, very recently, the TELeR taxonomy has been proposed
which can be used to design and explore various prompts for LLMs. Using this
TELeR taxonomy and 15 popular LLMs, this paper comprehensively evaluates LLMs
on the SOS Task, assessing their ability to summarize overlapping information
from multiple alternative narratives. For evaluation, we report
well-established metrics like ROUGE, BERTscore, and SEM-F1$ on two different
datasets of alternative narratives. We conclude the paper by analyzing the
strengths and limitations of various LLMs in terms of their capabilities in
capturing overlapping information The code and datasets used to conduct this
study are available at https://anonymous.4open.science/r/llm_eval-E16D.


  In performative prediction, the deployment of a predictive model triggers a
shift in the data distribution. As these shifts are typically unknown ahead of
time, the learner needs to deploy a model to get feedback about the
distribution it induces. We study the problem of finding near-optimal models
under performativity while maintaining low regret. On the surface, this problem
might seem equivalent to a bandit problem. However, it exhibits a fundamentally
richer feedback structure that we refer to as performative feedback: after
every deployment, the learner receives samples from the shifted distribution
rather than only bandit feedback about the reward. Our main contribution is an
algorithm that achieves regret bounds scaling only with the complexity of the
distribution shifts and not that of the reward function. The algorithm only
relies on smoothness of the shifts and does not assume convexity. Moreover, its
final iterate is guaranteed to be near-optimal. The key algorithmic idea is
careful exploration of the distribution shifts that informs a novel
construction of confidence bounds on the risk of unexplored models. More
broadly, our work establishes a conceptual approach for leveraging tools from
the bandits literature for the purpose of regret minimization with performative
feedback.


  We propose a new Conditional BEKK matrix-F (CBF) model for the time-varying
realized covariance (RCOV) matrices. This CBF model is capable of capturing
heavy-tailed RCOV, which is an important stylized fact but could not be handled
adequately by the Wishart-based models. To further mimic the long memory
feature of the RCOV, a special CBF model with the conditional heterogeneous
autoregressive (HAR) structure is introduced. Moreover, we give a systematical
study on the probabilistic properties and statistical inferences of the CBF
model, including exploring its stationarity, establishing the asymptotics of
its maximum likelihood estimator, and giving some new inner-product-based tests
for its model checking. In order to handle a large dimensional RCOV matrix, we
construct two reduced CBF models -- the variance-target CBF model (for moderate
but fixed dimensional RCOV matrix) and the factor CBF model (for high
dimensional RCOV matrix). For both reduced models, the asymptotic theory of the
estimated parameters is derived. The importance of our entire methodology is
illustrated by simulation results and two real examples.


  In this paper, we study eigenvalues of the closed eigenvalue problem of the
differential operator $ L$, which is introduced by Colding and Minicozzi in
[4], on an $n$-dimensional compact self-shrinker in ${R}^{n+p}$. Estimates for
eigenvalues of the differential operator $ L$ are obtained. Our estimates for
eigenvalues of the differential operator $ L$ are sharp. Furthermore, we also
study the Dirichlet eigenvalue problem of the differential operator $ L$ on a
bounded domain with a piecewise smooth boundary in an $n$-dimensional complete
self-shrinker in $ {R}^{n+p}$. For Euclidean space $ {R}^{n}$, the differential
operator $ L$ becomes the Ornstein-Uhlenbeck operator in stochastic analysis.
Hence, we also give estimates for eigenvalues of the Ornstein-Uhlenbeck
operator.


  The scattering amplitude of D Pi at the energy of the B mass can be
calculated using Regge theory. Recent papers have used this to calculate the
final state strong phases in the decays B to D Pi. It is argued that while the
Regge amplitude can yield an absorption correction to the decay rate, it is not
useful for determining the strong phase.


  The objective of this work is to provide high-resolution rain rate maps at
short lead-time forecasts (nowcasts) necessary to anticipate flooding and
properly manage sewage systems in urban areas by combining radars, rain gauges,
and operational microwave links, and taking into account their respective
uncertainties. A variational approach (3D-Var) is used to find the best
estimate for the rain rate, and its error covariance, from the different rain
sensors. Short-term rain rate forecasts are then produced by assuming
Lagrangian persistence. A velocity field is obtained from the operational
radar-derived rain fields, and the rain rate field is advected using the Total
Variance Diminishing (TVD) scheme. The error covariance associated to the
estimated rain rate is also propagated, and we use these two in the 3D-Var at
the next observation time step. This approach can be seen as a Variational
Kalman Filter (VKF), in which the covariance of the prior is not constant but
dependent on time. The proposed approach has been tested using data from 14
rain gauges, 14 microwave links and the operational radar rain product from
MeteoSwiss in the area of Zurich (Switzerland). During the applications the
assumption of the Lagrangian persistence appears to be valid up to 20 min (a
bit longer for stratiform events). During convective events, the algorithm is
less powerful and shorter lead times should be considered (i.e., 15 min).
Although such lead times are short, they are still useful to various
hydrological and outdoor applications.


  Temperature dependent single-crystal x-ray diffraction (XRD) in transmission
mode probing the bulk of the newly discovered K0.8Fe1.6Se2 superconductor (Tc =
31.8 K) using synchrotron radiation is reported. A clear evidence of intrinsic
phase separation at 520 K between two competing phases, (i) a first majority
magnetic phase with a ThCr2Si2-type tetragonal lattice modulated by the iron
vacancy ordering and (ii) a minority non-magnetic phase having an in-plane
compressed lattice volume and a weak superstructure, is reported. The XRD peaks
due to the Fe vacancy ordering in the majority phase disappear by increasing
the temperature at 580 K, well above phase separation temperature confirming
the order-disorder phase transition. The intrinsic phase separation at 520K
between a competing first magnetic phase and a second non-magnetic phase in the
normal phase both having lattice superstructures (that imply different Fermi
surface topology reconstruction and charge density) is assigned to a
lattice-electronic instability of the K0.8Fe1.6Se2 system typical of a system
tuned at a Lifshitz critical point of an electronic topological transition that
gives a multi-gaps superconductor tuned a shape resonance.


  Let $F$ be a non-Archimedean locally compact field of residual characteristic
$p$ with $p\neq 2$. Let $n$ be a power of $p$ and let $G$ be an inner form of
the general linear group $\text{\rm GL}_n(F)$. We give a transparent
parametrization of the irreducible, totally ramified, cuspidal representations
of $G$ of parametric degree $n$. We show that the parametrization is respected
by the Jacquet-Langlands correspondence, relative to any other inner form. This
expresses the Jacquet-Langlands correspondence for such representations within
a single, compact formula.


  Disentangled visual representations have largely been studied with generative
models such as Variational AutoEncoders (VAEs). While prior work has focused on
generative methods for disentangled representation learning, these approaches
do not scale to large datasets due to current limitations of generative models.
Instead, we explore regularization methods with contrastive learning, which
could result in disentangled representations that are powerful enough for large
scale datasets and downstream applications. However, we find that unsupervised
disentanglement is difficult to achieve due to optimization and initialization
sensitivity, with trade-offs in task performance. We evaluate disentanglement
with downstream tasks, analyze the benefits and disadvantages of each
regularization used, and discuss future directions.


  We show that double Lie algebroids, together with a chosen linear splitting,
are equivalent to pairs of 2-term representations up to homotopy satisfying
compatibility conditions which extend the notion of matched pair of Lie
algebroids. We discuss in detail the tangent of a Lie algebroid.


  We point out that the polarization state of radiation from a photonic crystal
slab is strongly constrained by the direct non-resonant scattering process. The
phase difference between the two linearly-polarized components in the far field
can be predicted analytically and is largely independent of the periodic
pattern. We verify the prediction with full-field electromagnetic simulations.


  The recently developed Wigner functional theory is used to formulate an
evolution equation for arbitrary multi-photon states, propagating through a
turbulent atmosphere under arbitrary conditions. The resulting evolution
equation, which is obtained from an infinitesimal propagation approach, is in
the form of a Fokker-Planck equation for the Wigner functional of the state and
therefore incorporates functional derivatives. We show consistency with
previously obtained solutions from different approaches and consider possible
ways to find additional solutions for this equation.


  We investigate whether the baryon asymmetry of the universe is explained in
the framework of the supersymmetric extension of the Standard Model with
R-parity violating interactions. It is shown that the Affleck-Dine mechanism
naturally works via a trilinear interaction $LLE^c$, $LQD^c$, or $U^cD^cD^c$,
if the magnitude of the coupling corresponding to the operator $\lambda$,
$\lambda'$, or $\lambda''$ is sufficiently small. The formation of Q-balls and
their subsequent evolution are also discussed. The present baryon asymmetry can
be explained in the parameter region where R-parity is mildly violated
$10^{-9}\lesssim\lambda,\lambda',\lambda''\lesssim 10^{-6}$ and the mass of the
gravitino is relatively heavy $m_{3/2}\gtrsim 10^4\mathrm{GeV}$. On the other
hand, it is difficult to explain the present baryon asymmetry for larger values
of R-parity violating couplings $\lambda,\lambda',\lambda''\gtrsim 10^{-5}$,
since Q-balls are likely to be destructed in the thermal environment and the
primordial baryon number is washed away.


  We review recent results by the author, in collaboration with Erwann Delay,
Olivier Lengard, and Rafe Mazzeo, on existence and properties of space-times
with controlled asymptotic behavior at null infinity.


  The fringe pattern that allows geometrical and orbital structure information
to be extracted from LIED spectra of symmetric molecules is shown to reflect a
symmetry conservation principle. We show that under a field polarization which
preserves certain symmetry elements of the molecule, the symmetry character of
the initial wave function is conserved during its time-evolution. We present a
symmetry analysis of a deviation from a perfect alignment by decomposing the
field into a major, symmetry-determining part, and a minor, symmetry breaking,
part. This decomposition leads to a corresponding factorization of the
time-evolution operator. The formalism is applied to the analysis of the
robustness of LIED readings and inversions with respect to deviations from a
perfect perpendicular and parallel alignment of a symmetric ABA triatomic
molecule. The results indicate a particularly strong stability of the type of
LIED spectra associated with the perpendicular alignment situation.


  Commercial graphics processors (GPUs) have high compute capacity at very low
cost, which makes them attractive for general purpose scientific computing. In
this paper we show how graphics processors can be used for N-body simulations
to obtain improvements in performance over current generation CPUs. We have
developed a highly optimized algorithm for performing the O(N^2) force
calculations that constitute the major part of stellar and molecular dynamics
simulations. In some of the calculations, we achieve sustained performance of
nearly 100 GFlops on an ATI X1900XTX. The performance on GPUs is comparable to
specialized processors such as GRAPE-6A and MDGRAPE-3, but at a fraction of the
cost. Furthermore, the wide availability of GPUs has significant implications
for cluster computing and distributed computing efforts like Folding@Home.


  Based on a thermodynamic approach, we have calculated the resistivity of a 2D
electron gas, assumed $dissipationless$ in a strong quantum limit. Standard
measurements, with extra current leads, define the resistivity caused by a
combination of Peltier and Seebeck effects. The current causes heating(cooling)
at the first(second) sample contacts, due to the Peltier effect. The contact
temperatures are different. The measured voltage is equal to the Peltier
effect-induced thermoemf which is linear in current. As a result, the
resistivity is non-zero as $I\to 0$. The resistivity is a universal function of
magnetic field and temperature, expressed in fundamental units $h/e^{2}$. The
universal features of magnetotransport data observed in experiment confirm our
predictions.


  Protoplanetary disk mass is a key parameter controlling the process of
planetary system formation. CO molecular emission is often used as a tracer of
gas mass in the disk. In this study we consider the ability of CO to trace the
gas mass over a wide range of disk structural parameters and search for
chemical species that could possibly be used as alternative mass tracers to CO.
Specifically, we apply detailed astrochemical modeling to a large set of models
of protoplanetary disks around low-mass stars, to select molecules with
abundances correlated with the disk mass and being relatively insensitive to
other disk properties. We do not consider sophisticated dust evolution models,
restricting ourselves with the standard astrochemical assumption of $0.1~\mu $m
dust. We find that CO is indeed the best molecular tracer for total gas mass,
despite the fact that it is not the main carbon carrier, provided reasonable
assumptions about CO abundance in the disk are used. Typically, chemical
reprocessing lowers the abundance of CO by a factor of 3, compared to the case
of photo-dissociation and freeze-out as the only ways of CO depletion. On
average only 13% C-atoms reside in gas-phase CO, albeit with variations from 2
to 30%. CO$_2$, H$_2$O and H$_2$CO can potentially serve as alternative mass
tracers, the latter two being only applicable if disk structural parameters are
known.


  It is proved that the additive group of every semidistributive nearring $R$
with an identity is abelian and if R has no elements of order $2$, then the
nearring $R$ actually is an associative ring.


  A restricted Boltzmann machine (RBM) learns a probability distribution over
its input samples and has numerous uses like dimensionality reduction,
classification and generative modeling. Conventional RBMs accept vectorized
data that dismisses potentially important structural information in the
original tensor (multi-way) input. Matrix-variate and tensor-variate RBMs,
named MvRBM and TvRBM, have been proposed but are all restrictive by model
construction, which leads to a weak model expression power. This work presents
the matrix product operator RBM (MPORBM) that utilizes a tensor network
generalization of Mv/TvRBM, preserves input formats in both the visible and
hidden layers, and results in higher expressive power. A novel training
algorithm integrating contrastive divergence and an alternating optimization
procedure is also developed. Numerical experiments compare the MPORBM with the
traditional RBM and MvRBM for data classification and image completion and
denoising tasks. The expressive power of the MPORBM as a function of the
MPO-rank is also investigated.


  We derive exact operator average expressions for the first two spectral
moments of nonequilibrium Green's functions for the Falicov-Kimball model and
the Hubbard model in the presence of a spatially uniform, time-dependent
electric field. The moments are similar to the well-known moments in
equilibrium, but we extend those results to systems in arbitrary time-dependent
electric fields. Moment sum rules can be employed to estimate the accuracy of
numerical calculations; we compare our theoretical results to numerical
calculations for the nonequilibrium dynamical mean-field theory solution of the
Falicov-Kimball model at half-filling.


  Image captioning is shown to be able to achieve a better performance by using
scene graphs to represent the relations of objects in the image. The current
captioning encoders generally use a Graph Convolutional Net (GCN) to represent
the relation information and merge it with the object region features via
concatenation or convolution to get the final input for sentence decoding.
However, the GCN-based encoders in the existing methods are less effective for
captioning due to two reasons. First, using the image captioning as the
objective (i.e., Maximum Likelihood Estimation) rather than a relation-centric
loss cannot fully explore the potential of the encoder. Second, using a
pre-trained model instead of the encoder itself to extract the relationships is
not flexible and cannot contribute to the explainability of the model. To
improve the quality of image captioning, we propose a novel architecture
ReFormer -- a RElational transFORMER to generate features with relation
information embedded and to explicitly express the pair-wise relationships
between objects in the image. ReFormer incorporates the objective of scene
graph generation with that of image captioning using one modified Transformer
model. This design allows ReFormer to generate not only better image captions
with the bene-fit of extracting strong relational image features, but also
scene graphs to explicitly describe the pair-wise relation-ships. Experiments
on publicly available datasets show that our model significantly outperforms
state-of-the-art methods on image captioning and scene graph generation


  3D visual perception tasks based on multi-camera images are essential for
autonomous driving systems. Latest work in this field performs 3D object
detection by leveraging multi-view images as an input and iteratively enhancing
object queries (object proposals) by cross-attending multi-view features.
However, individual backbone features are not updated with multi-view features
and it stays as a mere collection of the output of the single-image backbone
network. Therefore we propose 3M3D: A Multi-view, Multi-path,
Multi-representation for 3D Object Detection where we update both multi-view
features and query features to enhance the representation of the scene in both
fine panoramic view and coarse global view. Firstly, we update multi-view
features by multi-view axis self-attention. It will incorporate panoramic
information in the multi-view features and enhance understanding of the global
scene. Secondly, we update multi-view features by self-attention of the ROI
(Region of Interest) windows which encodes local finer details in the features.
It will help exchange the information not only along the multi-view axis but
also along the other spatial dimension. Lastly, we leverage the fact of
multi-representation of queries in different domains to further boost the
performance. Here we use sparse floating queries along with dense BEV (Bird's
Eye View) queries, which are later post-processed to filter duplicate
detections. Moreover, we show performance improvements on nuScenes benchmark
dataset on top of our baselines.


  We consider different methods to probe chameleons with slow neutrons.
Chameleon modify the potential of bouncing neutrons over a flat mirror in the
terrestrial gravitational field. This induces a shift in the energy levels of
the neutrons which could be detected in current experiments like GRANIT.
Chameleons between parallel plates have a field profile which is bubble-like
and which would modify the phase of neutrons in interferometric experiments. We
show that this new method of detection is competitive with the bouncing neutron
one, hopefully providing an efficient probe of chameleons when strongly coupled
to matter.


  The main idea of this challenging research is to revisit the solar-centric
dynamics of Earth around the Sun in analysis of its position on 13 April 2029
close to asteroid Apophis which is supposed to be moving in fly-by near the
Earth on its orbit. As of now, we can be sure that trajectory of Apophis is
well-known with respect to the center of Sun. Also, NASA experts calculated
that relative distance between center of Earth and Apophis should be less than
38 thousands of kilometers during closest Apophis approach to the Earth. But
the reasonable question is: will the center of Earth be at the predicted
position at the beginning of April 2029? The matter is that NASA solving
procedure disregards influence of Milankovich cycles to the orbit of Earth but
alternative concept suggests another solution (with additional quasi-periodic
deviation from their solution, proportional to square of eccentricity of Earth
orbit around the Sun equals to ~ 0.017). So, possible perturbation of Earth
orbit is likely to be proportional to (0.017)$^2$ ~ 0.03% from 1 a.e. or ~ 43
200 km which could be compared with gap between Earth and Apophis during
closest Apophis approach to Earth in April 2029.


  Abridged. Are all filaments bundles of fibers? To address this question, we
have investigated the gas organization within the paradigmatic Integral Shape
Filament (ISF). We combined two new ALMA Cycle 3 mosaics with previous IRAM 30m
observations to produce a high-dynamic range N$_2$H$^+$(1-0) emission map of
the ISF tracing its high-density material and velocity structure down to scales
of 0.009 pc. From the analysis of the gas kinematics, we identify a total of 55
dense fibers in the central region of the ISF. Independently of their location,
these fibers are characterized by transonic internal motions, lengths of ~0.15
pc, and masses per-unit-length close to those expected in hydrostatic
equilibrium. The ISF fibers are spatially organized forming a dense bundle with
multiple hub-like associations likely shaped by the local gravitational
potential. Within this complex network, the ISF fibers show a compact radial
emission profile with a median FWHM of 0.035 pc systematically narrower than
the previously proposed universal 0.1 pc filament width. Our ALMA observations
reveal complex bundles of fibers in the ISF, suggesting strong similarities
between the internal substructure of this massive filament and previously
studied lower-mass objects. The fibers show identical dynamic properties in
both low- and high-mass regions, and their widespread detection suggests a
preferred organizational mechanism of gas in which the physical fiber
dimensions (width and length) are self-regulated depending on their intrinsic
gas density. Combined with previous works, we identify a systematic increase of
the surface density of fibers as a function of the total mass per-unit-length
in filamentary clouds. Based on this empirical correlation, we propose a
unified star-formation scenario where the observed differences between low- and
high-mass clouds emerge naturally from the initial concentration of fibers.


  This paper presents millimeter-wave propagation measurements for urban
micro-cellular and indoor office scenarios at 28 GHz and 73 GHz, and
investigates the corresponding path loss using five types of path loss models,
the singlefrequency floating-intercept (FI) model, single-frequency closein
(CI) free space reference distance model, multi-frequency alpha-beta-gamma
(ABG) model, multi-frequency CI model, and multi-frequency CI model with a
frequency-weighted path loss exponent (CIF), in both line-of-sight and
non-line-of-sight environments. Results show that the CI and CIF models provide
good estimation and exhibit stable behavior over frequencies and distances,
with a solid physical basis and less computational complexity when compared
with the FI and ABG models. Furthermore, path loss in outdoor scenarios shows
little dependence on frequency beyond the first meter of free space
propagation, whereas path loss tends to increase with frequency in addition to
the increased free space path loss in indoor environments. Therefore, the CI
model is suitable for outdoor environments over multiple frequencies, while the
CIF model is more appropriate for indoor modeling. This work shows that both
the CI and CIF models use fewer parameters and offer more convenient closedform
expressions suitable for analysis, without compromising model accuracy when
compared to current 3GPP and WINNER path loss models.


  In order to investigate star formation (SF) processes in extreme
environments, we have carried out a multi-wavelength analysis of the
mid-infrared bubble N46, which hosts a WN7 Wolf-Rayet (W-R) star. We have used
13CO line data to trace an expanding shell surrounding the W-R star containing
about five condensations within the molecular cloud associated with the bubble.
The W-R star is associated with a powerful stellar wind having a mechanical
luminosity of ~4 x 10^37 ergs/s. A deviation of the H-band starlight mean
polarization angles around the bubble has also been traced, indicating the
impact of stellar wind on the surroundings. The Herschel temperature map shows
a temperature range of ~18 - 24 K toward the five molecular condensations. The
photometric analysis reveals that these condensations are associated with the
identified clusters of young stellar objects, revealing ongoing SF process. The
densest among these five condensations (peak N(H_2) ~9.2 x 10^22 cm^-2 and A_V
~ 98 mag) is associated with a 6.7 GHz methanol maser, an infrared dark cloud,
and the CO outflow, tracing active massive SF within it. At least five compact
radio sources (crss) are physically linked with the edges of the bubble and
each of them is consistent with the radio spectral class of a B0V - B0.5V type
star. The ages of the individual infrared counterparts of three crss (~1 - 2
Myr) and a typical age of WN7 W-R star (~4 Myr) indicate that the SF activities
around the bubble are influenced by the feedback of the W-R star.


  In this work, we present the results of two-dimensional
radiation-hydrodynamics simulations of a hohlraum target whose outgoing
radiation is used to produce a homogeneously ionized carbon plasma for ion-beam
stopping measurements. The cylindrical hohlraum with gold walls is heated by a
frequency-doubled ($\lambda_l = 526.5$ $\mu m$) $1.4$ $ns$ long laser pulse
with the total energy of $E_l = 180$ $J$. At the laser spot, the peak matter
and radiation temperatures of, respectively, $T \approx 380$ $eV$ and $T_r
\approx 120$ $eV$ are observed. X-rays from the hohlraum heat the attached
carbon foam with a mean density of $\rho_C = 2$ $mg/cm^3$ to a temperature of
$T \approx 25$ $eV$. The simulation shows that the carbon ionization degree ($Z
\approx 3.75$) and its column density stay relatively stable (within variations
of about $\pm7\%$) long enough to conduct the ion-stopping measurements. Also,
it is found that a special attention should be paid to the shock wave, emerging
from the X-ray heated copper support plate, which at later times may
significantly distort the carbon column density traversed by the fast ions.


  We introduce a distributed algorithm, termed noise-robust distributed maximum
consensus (RD-MC), for estimating the maximum value within a multi-agent
network in the presence of noisy communication links. Our approach entails
redefining the maximum consensus problem as a distributed optimization problem,
allowing a solution using the alternating direction method of multipliers.
Unlike existing algorithms that rely on multiple sets of noise-corrupted
estimates, RD-MC employs a single set, enhancing both robustness and
efficiency. To further mitigate the effects of link noise and improve
robustness, we apply moving averaging to the local estimates. Through extensive
simulations, we demonstrate that RD-MC is significantly more robust to
communication link noise compared to existing maximum-consensus algorithms.


  Several aspects of the laws of first hitting times of points are investigated
for one-dimensional symmetric stable L\'evy processes. It\^o's excursion theory
plays a key role in this study.


  Computations in the calculable small coupling regime of string theories and
the general consensus that no new physics has to be invoked in continuing to
the large coupling (black hole) regime, suggest the following picture. Quantum
states are not black holes even if energy distributions would suggest so. Black
holes appear as macrostates, i.e. with the same procedure that blures the
quantum coherence of microstates. It is also discussed how a spacetime
description - and thus geometry, causal properties and event horizons - may
stem from decoherence in the pregeometric approach represented by string
theories.


  The development of novel platforms and techniques for emerging "Big Data"
applications requires the availability of real-life datasets for data-driven
experiments, which are however out of reach for academic research in most cases
as they are typically proprietary. A possible solution is to use synthesized
datasets that reflect patterns of real ones in order to ensure high quality
experimental findings. A first step in this direction is to use inverse mining
techniques such as inverse frequent itemset mining (IFM) that consists of
generating a transactional database satisfying given support constraints on the
itemsets in an input set, that are typically the frequent ones. This paper
introduces an extension of IFM, called many-sorted IFM, where the schemes for
the datasets to be generated are those typical of Big Tables as required in
emerging big data applications, e.g., social network analytics.


  Four dimensional $\mathcal{N}=2$ Argyres-Douglas theories have been recently
conjectured to be described by $\mathcal{N}=1$ Lagrangian theories. Such
models, once reduced to 3d, should be mirror dual to Lagrangian $\mathcal{N}=4$
theories. This has been numerically checked through the matching of the
partition functions on the three sphere. In this article, we provide an
analytic derivation for this result in the $A_n$ case via hyperbolic
hypergeometric integrals. We study the $D_4$ case as well, commenting on some
open questions and possible resolutions. In the second part of the paper we
discuss other integral identities leading to the matching of the partition
functions in 3d dual pairs involving higher monopole superpotentials.


  Skepticism about the assumption of no unmeasured confounding, also known as
exchangeability, is often warranted in making causal inferences from
observational data; because exchangeability hinges on an investigator's ability
to accurately measure covariates that capture all potential sources of
confounding. In practice, the most one can hope for is that covariate
measurements are at best proxies of the true underlying confounding mechanism
operating in a given observational study. In this paper, we consider the
framework of proximal causal inference introduced by Miao et al. (2018);
Tchetgen Tchetgen et al. (2020), which while explicitly acknowledging covariate
measurements as imperfect proxies of confounding mechanisms, offers an
opportunity to learn about causal effects in settings where exchangeability on
the basis of measured covariates fails. We make a number of contributions to
proximal inference including (i) an alternative set of conditions for
nonparametric proximal identification of the average treatment effect; (ii)
general semiparametric theory for proximal estimation of the average treatment
effect including efficiency bounds for key semiparametric models of interest;
(iii) a characterization of proximal doubly robust and locally efficient
estimators of the average treatment effect. Moreover, we provide analogous
identification and efficiency results for the average treatment effect on the
treated. Our approach is illustrated via simulation studies and a data
application on evaluating the effectiveness of right heart catheterization in
the intensive care unit of critically ill patients.


  We continue the program of constructing (pre)modular tensor categories from
3-manifolds first initiated by Cho-Gang-Kim using $M$ theory in physics and
then mathematically studied by Cui-Qiu-Wang. An important structure involved is
a collection of certain $\text{SL}(2, \mathbb{C})$ characters on a given
manifold which serve as the simple object types in the corresponding category.
Chern-Simons invariants and adjoint Reidemeister torsions play a key role in
the construction, and they are related to topological twists and quantum
dimensions, respectively, of simple objects. The modular $S$-matrix is computed
from local operators and follows a trial-and-error procedure. It is currently
unknown how to produce data beyond the modular $S$- and $T$-matrices. There are
also a number of subtleties in the construction which remain to be solved. In
this paper, we consider an infinite family of 3-manifolds, that is, torus
bundles over the circle. We show that the modular data produced by such
manifolds are realized by the $\mathbb{Z}_2$-equivariantization of certain
pointed premodular categories. Here the equivariantization is performed for the
$\mathbb{Z}_2$-action sending a simple (invertible) object to its inverse, also
called the particle-hole symmetry. It is our hope that this extensive class of
examples will shed light on how to improve the program to recover the full data
of a premodular category.


  We show that the emergence of the axial anomaly is a universal phenomenon for
a generic three dimensional metal in the presence of parallel electric ($E$)
and magnetic ($B$) fields. In contrast to the expectations of the classical
theory of magnetotransport, this intrinsically quantum mechanical phenomenon
gives rise to the longitudinal magnetoresistance for any three dimensional
metal. However, the emergence of the axial anomaly does not guarantee the
existence of negative longitudinal magnetoresistance. We show this through an
explicit calculation of the longitudinal magnetoconductivity in the quantum
limit using the Boltzmann equation, for both short-range neutral and long-range
ionic impurity scattering processes. We demonstrate that the ionic scattering
contributes a large positive magnetoconductivity $\propto B^2$ in the quantum
limit, which can cause a strong negative magnetoresistance for any three
dimensional or quasi-two dimensional metal. In contrast, the finite range
neutral impurities and zero range point impurities can lead to both positive
and negative longitudinal magnetoresistance depending on the underlying band
structure. In the presence of both neutral and ionic impurities, the
longitudinal magnetoresistance of a generic metal in the quantum limit
initially becomes negative, and ultimately becomes positive after passing
through a minimum. We discuss in detail the qualitative agreement between our
theory and recent observations of negative longitudinal magnetoresistance in
Weyl semimetals TaAs and TaP, Dirac semimetals Na$_3$Bi, Bi$_{1-x}$Sb$_x$, and
ZrTe$_5$, and quasi-two dimensional metals PdCoO$_2$,
$\alpha$-(BEDT-TTF)$_2$I$_3$ which do not possess any bulk three dimensional
Dirac or Weyl quasiparticles.