  We present near-infrared VLT ISAAC imaging and spectroscopy of the peculiar
Virgo galaxy NGC 4438, whose nucleus has been classified as a LINER. The data
are supplemented by mid-infrared imaging, and compared to previous WFPC2 HST
broadband images. Images and position-velocity maps of the [Fe II] and H2 line
emissions are presented and compared with the distribution of the optical
narrow-line region and radio features. Our results show that shocks (possibly
driven by a radio jet) contribute to an important fraction of the excitation of
[Fe II], while X-ray heating from a central AGN may be responsible for the H2
excitation. We address the question whether the outflow has an AGN or a
starburst origin by providing new estimates of the central star formation rate
and the kinetic energy associated with the gas. By fitting a Sersic bulge, an
exponential disc and a compact nuclear source to the light distribution, we
decomposed NGC 4438's light distribution and found an unresolved nuclear source
at 0.8 arcsec resolution with M_K = -18.7 and J-H = 0.69. Our measured bulge
velocity dispersion, 142 km/s, together with the standard M_bh-sigma relation,
suggests a central black hole mass of log(M_bh/Msun) ~ 7.0. The stellar
kinematics measured from the near-infrared CO lines shows a strong peak in the
velocity dispersion of 178 km/s in the central 0.5 arcsec, which is possible
kinematic evidence of a central black hole. We calculated a general expression
for the integrated Sersic profile flux density in elliptical geometry,
including the case of 'disky' isophotes.


  We study the low temperature transport characteristics of a disordered metal
in the presence of electron-electron interactions. We compare Hartree-Fock and
dynamical mean field theory (DMFT) calculations to investigate the scattering
processes of quasiparticles off the screened disorder potential and show that
both the local and non-local (coming from long-ranged Friedel oscillations)
contributions to the renormalized disorder potential are suppressed in strongly
renormalized Fermi liquids. Our results provide one more example of the power
of DMFT to include higher order terms left out by weak-coupling theories.


  Hadron production in lepton-nucleus deep inelastic scattering is studied in a
quark energy loss model. The leading-order computations for hadron multiplicity
ratios are presented and compared with the selected HERMES pions production
data with the quark hadronization occurring outside the nucleus by means of the
hadron formation time. It is found that the obtained energy loss per unit
length is $0.440 \pm 0.013$ GeV/fm for an outgoing quark by the global fit. It
is confirmed that the atomic mass number dependence of hadron attenuation is
theoretically and experimentally in good agreement with the $A^{2/3}$ power law
for quark hadronization occurring outside the nucleus.


  In this article we give a brief outline of the applications of the
generalized Heun equation (GHE) in the context of Quantum Field Theory in
curved space-times. In particular, we relate the separated radial part of a
massive Dirac equation in the Kerr-Newman metric and the static perturbations
for the non-extremal Reissner-Nordstr\"{o}m solution to a GHE.


  In this paper, we propose a generic technique to model temporal dependencies
and sequences using a combination of a recurrent neural network and a Deep
Belief Network. Our technique, RNN-DBN, is an amalgamation of the memory state
of the RNN that allows it to provide temporal information and a multi-layer DBN
that helps in high level representation of the data. This makes RNN-DBNs ideal
for sequence generation. Further, the use of a DBN in conjunction with the RNN
makes this model capable of significantly more complex data representation than
an RBM. We apply this technique to the task of polyphonic music generation.


  We improve the results by Siegelmann & Sontag (1995) by providing a novel and
parsimonious constructive mapping between Turing Machines and Recurrent
Artificial Neural Networks, based on recent developments of Nonlinear Dynamical
Automata. The architecture of the resulting R-ANNs is simple and elegant,
stemming from its transparent relation with the underlying NDAs. These
characteristics yield promise for developments in machine learning methods and
symbolic computation with continuous time dynamical systems. A framework is
provided to directly program the R-ANNs from Turing Machine descriptions, in
absence of network training. At the same time, the network can potentially be
trained to perform algorithmic tasks, with exciting possibilities in the
integration of approaches akin to Google DeepMind's Neural Turing Machines.


  The collapsibility number of simplicial complexes was introduced by Wegner in
order to understand the intersection patterns of convex sets. This number also
plays an important role in a variety of Helly type results. We show that the
non-cover complex of a hypergraph $\mathcal{H}$ is $|V(\mathcal{H)}|-
\gamma_i(\mathcal{H})-1$-collapsible, where $\gamma_i(\mathcal{H})$ is the
generalization of independence domination number of a graph to hypergraph. This
extends the result of Choi, Kim and Park from graphs to hypergraphs. Moreover,
the upper bound in terms of strong independence domination number given by Kim
and Kim for the Leray number of the non-cover complex of a hypergraph can be
obtained as a special case of our result.
  In general, there can be a large gap between the collapsibility number of a
complex and its well-known upper bounds.
  In this article, we construct a sequence of upper bounds $\mathcal{M}_k(X)$
for the collapsibility number of a simplicial complex $X$, which lie in this
gap. We also show that the bound given by $\mathcal{M}_k$ is tight if the
underlying complex is $k$-vertex decomposable.


  Deep learning models for semantic segmentation rely on expensive,
large-scale, manually annotated datasets. Labelling is a tedious process that
can take hours per image. Automatically annotating video sequences by
propagating sparsely labeled frames through time is a more scalable
alternative. In this work, we propose a novel label propagation method, termed
Warp-Refine Propagation, that combines semantic cues with geometric cues to
efficiently auto-label videos. Our method learns to refine geometrically-warped
labels and infuse them with learned semantic priors in a semi-supervised
setting by leveraging cycle consistency across time. We quantitatively show
that our method improves label-propagation by a noteworthy margin of 13.1 mIoU
on the ApolloScape dataset. Furthermore, by training with the auto-labelled
frames, we achieve competitive results on three semantic-segmentation
benchmarks, improving the state-of-the-art by a large margin of 1.8 and 3.61
mIoU on NYU-V2 and KITTI, while matching the current best results on
Cityscapes.


  The spread of an infectious disease can, in some cases, promote the
propagation of other pathogens favouring violent outbreaks, which cause a
discontinuous transition to an endemic state. The topology of the contact
network plays a crucial role in these cooperative dynamics. We consider a
susceptible--infected--removed (SIR) type model with two mutually cooperative
pathogens: an individual already infected with one disease has an increased
probability of getting infected by the other. We present an heterogeneous
mean-field theoretical approach to the co--infection dynamics on generic
uncorrelated power-law degree-distributed networks and validate its results by
means of numerical simulations. We show that, when the second moment of the
degree distribution is finite, the epidemic transition is continuous for low
cooperativity, while it is discontinuous when cooperativity is sufficiently
high. For scale-free networks, i.e. topologies with diverging second moment,
the transition is instead always continuous. In this way we clarify the effect
of heterogeneity and system size on the nature of the transition and we
validate the physical interpretation about the origin of the discontinuity.


  We present a new systematic method to evaluate one-loop tensor integrals in
conventional ultraviolet cutoff regularization. By deriving a new recursive
relation that describes the momentum translation variance of ultraviolet
integrals, we implement this relation in the Passarino-Veltman reduction
method. With this method, we recalculated the Higgs boson decay into two
photons process at one-loop level in the Standard Model. We reanalyze this
process carefully and clarify some issues arisen recently in cutoff
regularization.


  We develop a method for deriving approximate analytical formulae to integrate
photon geodesics in a Schwarzschild spacetime. Based on this, we derive the
approximate equations for light bending and propagation delay that have been
introduced empirically. We then derive for the first time an approximate
analytical equation for the solid angle. We discuss the accuracy and range of
applicability of the new equations and present a few simple applications of
them to known astrophysical problems.


  We report on the construction of four-dimensional string vacua by considering
general abelian and non-abelian bundles on an internal Calabi-Yau for both
heterotic theories. The structure of the resulting gauge sector is extremely
rich and gives rise to many new model building possibilities. We analyse the
chiral spectrum including the contribution from heterotic five-branes and
provide the general consistency conditions. The one-loop corrected
supersymmetry condition on the bundles is found to be that of pi-stability. As
an application we present a supersymmetric Standard-Model like example for the
SO(32) string with U(n) bundles on an elliptically fibered Calabi-Yau.


  Dual phase xenon time projection chambers (TPCs) detect both the
scintillation photons and ionization electrons created by energy depositions
within the liquid xenon (LXe) volume. The electrons are extracted from the
interaction site through a gas gap, where they meet a high electric field where
proportional scintillation occurs. This converts the electron signal into a
light signal, and yields a high electron detection efficiency with a gain of
tens of photoelectrons (PE) per electron. This technique of detecting both
scintillation and ionization gives dual phase xenon TPCs the capability to
distinguish between electronic and nuclear recoils, which is a key part of how
these detectors are able to reach world-leading limits on Weakly Interacting
Massive Particle (WIMP) dark matter. However, not all electrons can be
extracted through the liquid-gas interface, and a constant millimeter-scale gas
gap needs to be maintained, which may be a technological challenge if
dual-phase xenon TPCs are to be scaled up for future dark matter searches.
Furthermore, there is a background of single-electron peaks that follow a large
ionization signal (S2) of unclear origin which may be due in part to the
liquid-gas interface, and limits the sensitivity of these detectors towards low
mass dark matter. In this paper, we demonstrate that a purely single-phase
liquid xenon TPC which produces proportional scintillation directly in the
liquid is still capable of discriminating between electronic and nuclear
recoils, but that the background of single-electrons following an S2 is still
likely unrelated to the liquid-gas interface.


  We consider N single server infinite buffer queues with service rate beta.
Customers arrive at rate N times alpha,choose L queues uniformly, and join the
shortest one. The stability condition is alpha strictly less than beta. We
study in equilibrium the sequence of the fraction of queues of length at least
k, in the large N limit. We prove a functional central limit theorem on an
infinite-dimensional Hilbert space with its weak topology, with limit a
stationary Ornstein-Uhlenbeck process. We use ergodicity and justify the
inversion of limits of long times and large sizes N by a compactness-uniqueness
method. The main tool for proving tightness of the ill-known invariant laws and
ergodicity of the limit is a global exponential stability result for the
nonlinear dynamical system obtained in the functional law of large numbers
limit.


  For simple Lie algebras of types B, C, and D, we provide new explicit
formulas for the generators of the Feigin-Frenkel centre. These formulas make
use of the symmetrisation map as well as some well-chosen symmetric invariants
of $\mathfrak g$. There are some general results on the role of the
symmetrisation map in the explicit description of the FF-centre. The advantage
of our method is that it reduces questions about elements of the FF-centre to
questions on the structure of the symmetric invariants in a type-free way. As
an illustration, we deal with type G$_2$ by hand.


  We introduce web supercategories of type Q. We describe the structure of
these categories and show they have a symmetric braiding. The main result of
the paper shows these diagrammatically defined monoidal supercategories provide
combinatorial models for the monoidal supercategories generated by the
supersymmetric tensor powers of the natural supermodule for the Lie
superalgebra of type Q.


  We investigate how the marginal deformations of N=4 supersymmetric Yang-Mills
theory (analysed in particular by Leigh and Strassler) arise within B-model
topological string theory on supertwistor space CP(3|4). This is achieved by
turning on a certain closed string background in the fermionic directions.
Through a specific open/closed correlation function, this mode induces a
correction to holomorphic Chern-Simons theory, corresponding to the self-dual
part of the chiral operator added on the gauge theory side. The effect of the
deformation is interpreted as non-anticommutativity between some of the odd
coordinates of CP(3|4). Motivated by this, we extend the twistor formalism for
calculating MHV amplitudes in N=4 SYM to these N=1 theories by introducing a
suitable star product between the wavefunctions. We check that our prescription
yields the expected results to linear order in the deformation parameter.


  Large networks of sparsely coupled, excitatory and inhibitory cells occur
throughout the brain. A striking feature of these networks is that they are
chaotic. How does this chaos manifest in the neural code? Specifically, how
variable are the spike patterns that such a network produces in response to an
input signal? To answer this, we derive a bound for the entropy of multi-cell
spike pattern distributions in large recurrent networks of spiking neurons
responding to fluctuating inputs. The analysis is based on results from random
dynamical systems theory and is complimented by detailed numerical simulations.
We find that the spike pattern entropy is an order of magnitude lower than what
would be extrapolated from single cells. This holds despite the fact that
network coupling becomes vanishingly sparse as network size grows -- a
phenomenon that depends on ``extensive chaos," as previously discovered for
balanced networks without stimulus drive. Moreover, we show how spike pattern
entropy is controlled by temporal features of the inputs. Our findings provide
insight into how neural networks may encode stimuli in the presence of
inherently chaotic dynamics.


  Agent-based models (ABMs) are ubiquitous in research and industry. Currently,
simulating ABMs involves at least some imperative (step-by-step) computer
instructions. An alternative approach is declarative programming, in which a
set of requirements is described at a high level of abstraction. Here we
describe a fully declarative approach to the automated construction of
simulations for ABMs. In this framework, logic for ABM simulations is
encapsulated into predefined components. The user specifies a set of
requirements describing the desired functionality. Additionally, each component
has a set of consistency requirements. The framework iteratively seeks a
simulation design that satisfies both user and system requirements. This
approach allows the user to omit most details from the simulation
specification, simplifying simulation design.


  To control and utilize quantum features in small scale for practical
applications such as quantum transport, it is crucial to gain deep
understanding of quantum characteristics of states such as coherence. Here by
introducing a technique that simplifies solving the dynamical equation, we
study the dynamics of coherence in a system of qubits interacting with each
other through a common bath at non zero temperature. Our results demonstrate
that depending on initial state, environment temperature affect coherence and
excitation transfer in different ways. We show that when initial state is
incoherent, as time goes on, coherence and probability of excitation transfer
increase. But for coherent initial state, we find a critical value of
temperature, below which system loses its coherence in time which diminishes
the probability of excitation transfer. Hence in order to achieve higher value
of coherence and also higher probability of excitation transfer, temperature of
the bath should go beyond that critical value. Stationary coherence and
probability of finding excited qubits in steady state, are discussed. We also
elaborate on dependence of critical value of bath temperature on system size.


  The exploding rate of multimedia publishing in our networked society has
magnified the risk of sensitive information leakage and misuse, pushing the
need to secure data against possible exposure. Data sanitization -- the process
of obfuscating or removing sensitive content related to the data -- helps to
mitigate the severe impact of potential security and privacy risks. This paper
presents a review of the mechanisms designed for protecting digital visual
contents (i.e., images and videos), the attacks against the cited mechanisms,
and possible countermeasures. The provided thorough systematization, alongside
the discussed challenges and research directions, can pave the way to new
research.


  We present and analyze new exact gyraton solutions of algebraic type II on
generalized Melvin universe of type D which admit non-vanishing cosmological
constant $\Lambda$. We show that it generalizes both, gyraton solutions on
Melvin and on direct product spacetimes. When we set $\Lambda = 0$ we get
solutions on Melvin spacetime and for $\Sigma = 1$ we obtain solutions on
direct product spacetimes. We demonstrate that the solutions are member of the
Kundt family of spacetimes as its subcases. We show that the Einstein equations
reduce to a set of equations on the transverse 2-space. We also discuss the
polynomial scalar invariants which are non-constant in general but constant for
sub-solutions on direct product spacetimes.


  This article consists of two papers: $\textit{Typical dynamics of Newton's
method}$ by Steele and $\textit{Erratum to "Typical dynamics of Newton's
method"}$ by Dud\'ak and Steele.
  Let $C^1(M)$ be the space of continuously differentiable real-valued
functions defined on $[-M,M]$. We show that for the typical element $f$ in
$C^1(M)$, there exists a set $S \subseteq [-M,M]$, both residual and of full
measure in $[-M,M]$, such that for any $x \in S$, the trajectory generated by
Newton's method using $f$ and $x$ either diverges, converges to a root of $f$,
or generates a Cantor set as its attractor. Whenever the Cantor set is the
attractor, the dynamics on the attractor are described by a single type of
adding machine, so that the dynamics on all of these attracting Cantor sets are
topologically equivalent.


  Voice Type Discrimination (VTD) refers to discrimination between regions in a
recording where speech was produced by speakers that are physically within
proximity of the recording device ("Live Speech") from speech and other types
of audio that were played back such as traffic noise and television broadcasts
("Distractor Audio"). In this work, we propose a deep-learning-based VTD system
that features an initial layer of learnable spectro-temporal receptive fields
(STRFs). Our approach is also shown to provide very strong performance on a
similar spoofing detection task in the ASVspoof 2019 challenge. We evaluate our
approach on a new standardized VTD database that was collected to support
research in this area. In particular, we study the effect of using learnable
STRFs compared to static STRFs or unconstrained kernels. We also show that our
system consistently improves a competitive baseline system across a wide range
of signal-to-noise ratios on spoofing detection in the presence of VTD
distractor noise.


  The design and operation of systems are conventionally viewed as a sequential
decision-making process that is informed by data from physical experiments and
simulations. However, the integration of these high-dimensional and
heterogeneous data sources requires the consideration of the impact of a
decision on a system's remaining life cycle. Consequently, this introduces a
degree of complexity that in most cases can only be solved through an
integrated decision-making approach. In this perspective paper, we use the
digital twin concept to formulate an integrated perspective for the design of
systems. Specifically, we show how the digital twin concept enables the
integration of system design decisions and operational decisions during each
stage of a system's life cycle. This perspective has two advantages: (i)
improved system performance as more effective decisions can be made, and (ii)
improved data efficiency as it provides a framework to utilize data from
multiple sources and design instances. From the formal definition, we identify
a set of eight capabilities that are vital constructs to bring about the
potential, as defined in this paper, that the digital twin concept holds for
the design of systems. Subsequently, by comparing these capabilities with the
available literature on digital twins, we identify a set of research questions
and forecast what their broader impact might be. By conceptualizing the
potential that the digital twin concept holds for the design of systems, we
hope to contribute to the convergence of definitions, problem formulations,
research gaps, and value propositions in this burgeoning field. Addressing the
research questions, associated with the digital twin-inspired formulation for
the design of systems, will bring about more advanced systems that can meet
some of the societies' grand challenges.


  Nanophotonic platforms in theory uniquely enable < femtomoles of chiral
biological and pharmaceutical molecules to be detected, through the highly
localised changes in the chiral asymmetries of the near-fields that they
induce. However, current chiral nanophotonic based strategies are intrinsically
limited because they rely on far-field optical measurements that are sensitive
to a much larger near-field volume, than that influenced by the chiral
molecules. Consequently, they depend on detecting small changes in far-field
optical response restricting detection sensitivities. Here we exploit an
intriguing phenomenon, plasmonic circularly polarised luminescence (PCPL),
which is an incisive local probe of near-field chirality. This allows chiral
detection of monolayer quantities of a de novo designed peptide, which is not
achieved with a far-field response. Our work demonstrates that by leveraging
the capabilities of nanophotonic platforms with the near-field sensitivity of
PCPL, optimal biomolecular detection performance can be achieved, opening new
avenues for nanometrology.


  Low-cost message passing (MP) algorithm has been recognized as a promising
technique for sparse vector recovery. However, the existing MP algorithms
either focus on mean square error (MSE) of the value recovery while ignoring
the sparsity requirement, or support error rate (SER) of the sparse support
(non-zero position) recovery while ignoring its value. A novel low-complexity
Bernoulli-Gaussian MP (BGMP) is proposed to perform the value recovery as well
as the support recovery. Particularly, in the proposed BGMP, support-related
Bernoulli messages and value-related Gaussian messages are jointly processed
and assist each other. In addition, a strict lower bound is developed for the
MSE of BGMP via the genie-aided minimum mean-square-error (GA-MMSE) method. The
GA-MMSE lower bound is shown to be tight in high signal-to-noise ratio.
Numerical results are provided to verify the advantage of BGMP in terms of
final MSE, SER and convergence speed.


  The experimental realization of many-body entangled states is one of the main
goals of quantum technology as these states are a key resource for quantum
computation and quantum sensing. However, increasing the number of photons in
an entangled state has been proved to be a painstakingly hard task. This is a
result of the non-deterministic emission of current photon sources and the
distinguishability between photons from different sources. Moreover, the
generation rate and the complexity of the optical setups hinder scalability.
Here we present a new scheme that is compact, requires a very modest amount of
components, and avoids the distinguishability issues by using only one
single-photon source. States of any number of photons are generated with the
same configuration, with no need for increasing the optical setup. The basic
operation of this scheme is experimentally demonstrated and its sensitivity to
imperfections is considered.


  Information about the last stages of a binary neutron star inspiral and the
final merger can be extracted from quasi-equilibrium configurations and
dynamical evolutions. In this article, we construct quasi-equilibrium
configurations for different spins, eccentricities, mass ratios, compactnesses,
and equations of state. For this purpose we employ the SGRID code, which allows
us to construct such data in previously inaccessible regions of the parameter
space. In particular, we consider spinning neutron stars in isolation and in
binary systems; we incorporate new methods to produce highly eccentric and
eccentricity reduced data; we present the possibility of computing data for
significantly unequal-mass binaries; and we create equal-mass binaries with
individual compactness up to 0.23. As a proof of principle, we explore the
dynamical evolution of three new configurations. First, we simulate a $q=2.06$
mass ratio which is the highest mass ratio for a binary neutron star evolved in
numerical relativity to date. We find that mass transfer from the companion
star sets in a few revolutions before merger and a rest mass of
$\sim10^{-2}M_\odot$ is transferred between the two stars. This configuration
also ejects a large amount of material during merger, imparting a substantial
kick to the remnant. Second, we simulate the first merger of a precessing
binary neutron star. We present the dominant modes of the gravitational waves
for the precessing simulation, where a clear imprint of the precession is
visible in the (2,1) mode. Finally, we quantify the effect of an eccentricity
reduction procedure on the gravitational waveform. The procedure improves the
waveform quality and should be employed in future precision studies, but also
other errors, notably truncation errors, need to be reduced in order for the
improvement due to eccentricity reduction to be effective. [abridged]


  We adapt in the present note the perturbation method introduced in [3] to get
a Gaussian lower bound for the Neumann heat kernel of the Laplace-Beltrami
operator on an open subset of a compact Riemannian manifold.


  We give a simple proof of Tian's theorem that the Kodaira embeddings
associated to a positive line bundle over a compact complex manifold are
asymptotically isometric. The proof is based on the diagonal asymptotics of the
Szego kernel (i.e. the orthogonal projection onto holomorphic sections). In
deriving these asymptotics we use the Boutet de Monvel-Sjostrand parametrix for
the Szego kernel.


  First we recall homology groups of prer Lie superalgebras. Then introducing
double weighted chain spaces, we deal with pre Lie superalgebra of multi-vector
fields with polynomial coefficients on n-dimensional number space. The bracket
is Schouten bracket. We have several results about Euler number and Betti
numbers of those homology groups of special pre Lie superalgebra.


  We present an algorithm that computes the Hasse-Witt matrix of given
hyperelliptic curve over Q at all primes of good reduction up to a given bound
N. It is simpler and faster than the previous algorithm developed by the
authors.


  We introduce SpreadsheetBench, a challenging spreadsheet manipulation
benchmark exclusively derived from real-world scenarios, designed to immerse
current large language models (LLMs) in the actual workflow of spreadsheet
users. Unlike existing benchmarks that rely on synthesized queries and
simplified spreadsheet files, SpreadsheetBench is built from 912 real questions
gathered from online Excel forums, which reflect the intricate needs of users.
The associated spreadsheets from the forums contain a variety of tabular data
such as multiple tables, non-standard relational tables, and abundant
non-textual elements. Furthermore, we propose a more reliable evaluation metric
akin to online judge platforms, where multiple spreadsheet files are created as
test cases for each instruction, ensuring the evaluation of robust solutions
capable of handling spreadsheets with varying values. Our comprehensive
evaluation of various LLMs under both single-round and multi-round inference
settings reveals a substantial gap between the state-of-the-art (SOTA) models
and human performance, highlighting the benchmark's difficulty.


  We give an explicit definition of decentralization and show you that
decentralization is almost impossible for the current stage and Bitcoin is the
first truly noncentralized currency in the currency history. We propose a new
framework of noncentralized cryptocurrency system with an assumption of the
existence of a weak adversary for a bank alliance. It abandons the mining
process and blockchain, and removes history transactions from data
synchronization. We propose a consensus algorithm named Converged Consensus for
a noncentralized cryptocurrency system.


  A quantum particle propagates subdiffusively on a strongly disordered chain
when it is coupled to itinerant hard-core bosons. We establish a generalized
Einstein relation (GER) that relates such subdiffusive spread to an unusual
time-dependent drift velocity, which appears as a consequence of a constant
electric field. We show that GER remains valid much beyond the regime of the
linear response. Qualitatively, it holds true up to strongest drivings when the
nonlinear field-effects lead to the Stark-like localization. Numerical
calculations based on full quantum evolution are substantiated by much simpler
rate equations for the boson-assisted transitions between localized Anderson
states.


  The Transiting Exoplanet Survey Satellite (TESS) will be conducting a nearly
all-sky photometric survey over two years, with a core mission goal to discover
small transiting exoplanets orbiting nearby bright stars. It will obtain
30-minute cadence observations of all objects in the TESS fields of view, along
with 2-minute cadence observations of 200,000 to 400,000 selected stars. The
choice of which stars to observe at the 2-min cadence is driven by the need to
detect small transiting planets, which leads to the selection of primarily
bright, cool dwarfs. We describe the catalogs assembled and the algorithms used
to populate the TESS Input Catalog (TIC). We also describe a ranking system for
prioritizing stars according to the smallest transiting planet detectable, and
assemble a Candidate Target List (CTL) using that ranking. We discuss
additional factors that affect the ability to photometrically detect and
dynamically confirm small planets, and we note additional stellar populations
of interest that may be added to the final target list. The TIC is available on
the STScI MAST server, and an enhanced CTL is available through the Filtergraph
data visualization portal system at the URL
https://filtergraph.vanderbilt.edu/tess_ctl .


  We examine the ultrafast optical response of the crystalline and amorphous
phases of the phase change material Ge$_2$Sb$_2$Te$_5$ below the phase
transformation threshold. Simultaneous measurement of the transmissivity and
reflectivity of thin film samples yields the time-dependent evolution of the
dielectric function for both phases. We then identify how lattice motion and
electronic excitation manifest in the dielectric response. The dielectric
response of both phases is large but markedly different. At 800 nm, the changes
in amorphous GST are well described by the Drude response of the generated
photo-carriers, whereas the crystalline phase is better described by the
depopulation of resonant bonds. We find that the generated coherent phonons
have a greater influence in the amorphous phase than the crystalline phase.
Furthermore, coherent phonons do not influence resonant bonding. For fluences
up to 50% of the transformation threshold, the structure does not exhibit bond
softening in either phase, enabling large changes of the optical properties
without structural modification.


  This paper describes a multi-functional deep in-memory processor for
inference applications. Deep in-memory processing is achieved by embedding
pitch-matched low-SNR analog processing into a standard 6T 16KB SRAM array in
65 nm CMOS. Four applications are demonstrated. The prototype achieves up to
5.6X (9.7X estimated for multi-bank scenario) energy savings with negligible
(<1%) accuracy degradation in all four applications as compared to the
conventional architecture.


  We investigate the holographic fermions over a gravitational lattice
background with a rather low temperature. Since the rotation symmetry is broken
on the plane, the lattice effects change the shape of the Fermi surface within
the first Brillouin zone from a circle to an ellipse. When the Fermi surface
intersects with the Brillouin zone boundary, the band structure with a band gap
is observed through a numerical analysis. We construct a lattice model sourced
by a scalar field as well as an ionic lattice model without the scalar field.
In both cases we find the similar physical results.


  It is well-known that a charged particle moving with constant velocity in
vacuum does not radiate. In a medium the situation can be different. If the so
called Cherenkov condition is satisfied, i.e. the particle velocity exceeds the
phase speed in the medium, the particle will radiate. We show that a charge
moving with a constant velocity in a gas of photons emits Cherenkov radiation,
even in the gamma-ray regime, due to nonlinear quantum electrodynamic effects.
Our result is evaluated with respect to the radiation background in the early
universe, and it is argued that the effect can be significant.


  We study the quantum groups appearing via models $C(G)\subset M_K(C(X))$
which are "stationary", in the sense that the Haar integration over $G$ is the
functional $tr\otimes\int_X$. Our results include a number of generalities,
notably with a substantial list of examples, and a detailed discussion in the
quantum permutation group case.


  As a prominent member of the next generation multiple access (NGMA) family,
non-orthogonal multiple access (NOMA) has been recognized as a promising
multiple access candidate for the sixth-generation (6G) networks. This article
focuses on applying NOMA in 6G networks, with an emphasis on proposing the
so-called "One Basic Principle plus Four New" concept. Starting with the basic
NOMA principle, the importance of successive interference cancellation (SIC)
becomes evident. In particular, the advantages and drawbacks of both the
channel state information based SIC and quality-of-service based SIC are
discussed. Then, the application of NOMA to meet the new 6G performance
requirements, especially for massive connectivity, is explored. Furthermore,
the integration of NOMA with new physical layer techniques is considered,
followed by introducing new application scenarios for NOMA towards 6G. Finally,
the application of machine learning in NOMA networks is investigated, ushering
in the machine learning empowered NGMA era.


  We have simulated four-dimensional interacting self-avoiding trails (ISAT) on
the hyper-cubic lattice with standard interactions at a wide range of
temperatures up to length 4096 and at some temperatures up to length 16384. The
results confirm the earlier prediction (using data from a non-standard model at
a single temperature) of a collapse phase transition occurring at finite
temperature. Moreover they are in accord with the phenomenological theory
originally proposed by Lifshitz, Grosberg and Khokhlov in three dimensions and
recently given new impetus by its use in the description of simulational
results for four-dimensional interacting self-avoiding walks (ISAW). In fact,
we argue that the available data is consistent with the conclusion that the
collapse transitions of ISAT and ISAW lie in the same universality class, in
contradiction with long-standing predictions. We deduce that there exists a
pseudo-first order transition for ISAT in four dimensions at finite lengths
while the thermodynamic limit is described by the standard polymer mean-field
theory (giving a second-order transition), in contradiction to the prediction
that the upper critical dimension for ISAT is $d_u=4$.


  In this article, we have explored the very important quantity of lepton pair
production from a hot and dense QCD medium in presence of an arbitrary external
magnetic field for simultaneous nonzero values of both the parallel (along the
direction of the external field) and perpendicular (lying on the transverse
plane to the external field) components of the dilepton momentum. As opposed to
the zero magnetic field case (the so-called Born rate) or the lowest Landau
level approximated rate, where only the annihilation process contributes, here
we observe contributions also arising out of the quark and antiquark decay
processes. We found the encouraging result of considerable enhancement of
lepton pair production in presence of an arbitrary magnetic field. We decompose
the total rate into different physical processes and discuss their behaviors
for both zero and nonzero baryon density. The whole analysis is then subjected
to an effective model treatment, where we have incorporated the magnetic field
induced novel effects of magnetic catalysis (MC) and inverse MC (IMC) through a
medium dependent scalar coupling, which leads to some further interesting
observations.


  We show that the relatively large best fit value of $\sin^2 2 \theta_{13} =
0.14 \, (0.17)$ measured in the T2K experiment for fixed values of i) the Dirac
CP violation phase $\delta = 0$, and ii) the atmospheric neutrino mixing
parameters $\theta_{23} = \pi/4$, $|\Delta m^2_{32}| = 2.4 \times 10^{-3} \;
{\rm eV}^2$, can be reconciled with the Daya Bay result $\sin^2 2 \theta_{13} =
0.090 \pm 0.009$ if the effects of non-standard neutrino interactions (NSI) in
the relevant $\bar \nu_e \to \bar \nu_e$ and $\nu_\mu \to \nu_e$ oscillation
probabilities are taken into account.


  We theoretically study the spin fluctuation and superconductivity in La1111
and Sm1111 iron-based superconductors for a wide range of electron doping. When
we take into account the band structure variation by electron doping, the hole
Fermi surface originating from the $d_{X^2-Y^2}$ orbital turns out to be robust
against electron doping, and this gives rise to large spin fluctuations and
consequently $s\pm$ pairing even in the heavily doped regime. The stable hole
Fermi surface is larger for Sm1111 than for La1111, which can be considered as
the origin of the apparent difference in the phase diagram.


  Canis Major OB1 (CMa OB1) is a Galactic stellar association with a very
intriguing star-formation scenario. There are more than two dozen known star
clusters in its line of sight, but it is not clear which ones are physically
associated with CMa OB1. We use a clustering code that employs 5-dimensional
data from the Gaia DR2 catalogue to identify physical groups and obtain their
astrometric parameters and, in addition, we use two different isochrone-fitting
methods to estimate the ages of these groups. We find 15 stellar groups with
distances between 570 pc and 1650 pc, including 10 previously known and 5 new
open cluster candidates. Four groups, precisely the youngest ones ($<$ 20 Myr),
CMa05, CMa06, CMa07 and CMa08, are confirmed to be part of CMa OB1. We find
that CMa08, a new cluster candidate, may be the progenitor cluster of runaway
stars. CMa06 coincides with the well-studied CMa R1 star-forming region. While
CMa06 is still forming stars, due to the remaining material of the molecular
cloud associated with the Sh 2-262 nebula, CMa05, CMa07 and CMa08 seem to be in
more evolved stages of evolution, with no recent star-forming activity. The
properties of these CMa OB1 physical groups fit well in a monolithic scenario
of star formation, with a common formation mechanism, and having suffered
multiple episodes of star formation. This suggests that the hierarchical model
alone, which explains the populations of other parts of the same association,
is not sufficient to explain its whole formation history.


  We introduce the notion of strongly independent matrices and show the
existence of strongly independent matrices in $GL(n,\mathbb{Z})$ over
$\mathbb{Z}^n\setminus\{0\}$ when $2n+1$ is a prime number. As an application
of strong independence, we give a measure rigidity result for endomorphisms on
$n$-torus $\mathbb{T}^n$.


  This work describes an outlier detection procedure (named "OutlierTree")
loosely based on the GritBot software developed by RuleQuest research, which
works by evaluating and following supervised decision tree splits on variables,
in whose branches 1-d confidence intervals are constructed for the target
variable and potential outliers flagged according to these confidence
intervals. Under this logic, it's possible to produce human-readable
explanations for why a given value of a variable in an observation can be
considered as outlier, by considering the decision tree branch conditions along
with general distribution statistics among the non-outlier observations that
fell into the same branch, which can then be contrasted against the value which
lies outside the CI. The supervised splits help to ensure that the generated
conditions are not spurious, but rather related to the target variable and
having logical breakpoints.


  Automatically generating stories is a challenging problem that requires
producing causally related and logical sequences of events about a topic.
Previous approaches in this domain have focused largely on one-shot generation,
where a language model outputs a complete story based on limited initial input
from a user. Here, we instead focus on the task of interactive story
generation, where the user provides the model mid-level sentence abstractions
in the form of cue phrases during the generation process. This provides an
interface for human users to guide the story generation. We present two
content-inducing approaches to effectively incorporate this additional
information. Experimental results from both automatic and human evaluations
show that these methods produce more topically coherent and personalized
stories compared to baseline methods.


  Super star clusters --- extremely massive clusters found predominately in
starburst environments --- are essential building blocks in the formation of
galaxies and thought to dominate star formation in the high-redshift universe.
However, the transformation from molecular gas into these ultra-compact star
clusters is not well understood. To study this process, we used the
Submillimeter Array and the Plateau de Bure Interferometer to obtain high
angular resolution (~1.5" or 160 pc) images of the Antennae overlap region in
CO(2--1) to search for the molecular progenitors of the super star clusters. We
resolve the molecular gas distribution into a large number of clouds, extending
the differential cloud mass function down to a 5\sigma completeness limit of
3.8x10^5 M_sun. We identify a distinct break in the mass function around log
M_mol/M_sun ~ 6.5, which separates the molecular clouds into two distinct
populations. The smaller, less massive clouds reside in more quiescent areas in
the region, while the larger, more massive clouds cluster around regions of
intense star formation. A broken power-law fit to the mass function yields
slopes of \alpha = -1.39+/-0.10 and \alpha = -1.44+/-0.14 for the low- and
high-mass cloud population, well-matched to the mass function found for super
star clusters in the Antennae galaxies. We find large velocity gradients and
velocity dispersions at the locations of intense star formation, suggestive of
compressive shocks. It is likely that these environmental factors contribute to
the formation of the observed massive molecular clouds and super star clusters
in the Antennae galaxies.


  Novel bis(biphenyl)-capped polyynes have been synthesized to investigate the
modulation of the electronic and optical properties of sp-hybridized
carbon-atom wires (CAWs) capped with {\pi}-conjugated $sp^{2}$ endgroups. Raman
and Surface Enhanced Raman spectroscopy (SERS) investigation of these systems
and Density Functional Theory (DFT) calculations reveal structural changes from
polyyne-like with alternating single-triple bonds towards cumulene-like with
more equalized bonds as a consequence of the charge transfer occurring when
wires interact with metallic nanoparticles. While polyynes have semiconducting
electronic properties, a more equalized system tends to a cumulene-like
structure characterized by a nearly metallic behavior. The possibility to drive
a semiconductor-to-metal transition has been investigated by systematic DFT
calculations on a series of CAWs capped with different conjugated endgroups
revealing that the modulation of the structural, electronic and vibrational
properties of the sp-carbon chain towards the metallic wire cannot be simply
obtained by using extended {\pi}-conjugated $sp^{2}$ carbon endgroups, but
require a suitable chemical design of the endgroup and control of charge
transfer. These results provide useful guidelines for the design of novel
$sp-sp^2$ hybrid carbon nanosystems with tunable properties, where
graphene-like and polyyne-like domains are closely interconnected. The
capability to tune the final electronic or optical response of the material
makes these hybrid $sp-sp^2$ systems appealing for a future all-carbon-based
science and technology.


  A novel machine learning optimization process coined Restrictive Federated
Model Selection (RFMS) is proposed under the scenario, for example, when data
from healthcare units can not leave the site it is situated on and it is
forbidden to carry out training algorithms on remote data sites due to either
technical or privacy and trust concerns. To carry out a clinical research under
this scenario, an analyst could train a machine learning model only on local
data site, but it is still possible to execute a statistical query at a certain
cost in the form of sending a machine learning model to some of the remote data
sites and get the performance measures as feedback, maybe due to prediction
being usually much cheaper. Compared to federated learning, which is optimizing
the model parameters directly by carrying out training across all data sites,
RFMS trains model parameters only on one local data site but optimizes
hyper-parameters across other data sites jointly since hyper-parameters play an
important role in machine learning performance. The aim is to get a Pareto
optimal model with respective to both local and remote unseen prediction
losses, which could generalize well across data sites. In this work, we
specifically consider high dimensional data with shifted distributions over
data sites. As an initial investigation, Bayesian Optimization especially
multi-objective Bayesian Optimization is used to guide an adaptive
hyper-parameter optimization process to select models under the RFMS scenario.
Empirical results show that solely using the local data site to tune
hyper-parameters generalizes poorly across data sites, compared to methods that
utilize the local and remote performances. Furthermore, in terms of dominated
hypervolumes, multi-objective Bayesian Optimization algorithms show increased
performance across multiple data sites among other candidates.


  Recent generalizations of the Camassa-Holm equation are studied from the
point of view of existence of global solutions, criteria for wave breaking
phenomena and integrability. We provide conditions, based on lower bounds for
the first spatial derivative of local solutions, for global well-posedness for
the family under consideration in Sobolev spaces. Moreover, we prove that wave
breaking phenomena occurs under certain mild hypothesis. Regarding
integrability, we apply the machinery developed by Dubrovin [Commun. Math.
Phys. 267, 117--139 (2006)] to prove that there exists a unique bi-hamiltonian
structure for the equation only when it is reduced to the Dullin-Gotwald-Holm
equation. Our results suggest that a recent shallow water model incorporating
Coriollis efects is integrable only in specific situations. Finally, to finish
the scheme of geometric integrability of the family of equations initiated in a
previous work, we prove that the Dullin-Gotwald-Holm equation describes
pseudo-spherical surfaces.


  The definition of plasmon at the microscopic scale is far from being
understood. Yet, it is very important to recognize plasmonic features in
optical excitations, as they can inspire new applications and trigger new
discoveries by analogy with the rich phenomenology of metal nanoparticle
plasmons. Recently, the concepts of plasmonicity index and the generalized
plasmonicity index (GPI) have been devised as computational tools to quantify
the plasmonic nature of optical excitations. The question may arise whether any
strong absorption band, possibly with some sort of collective character in its
microscopic origin, shares the status of plasmon. Here we demonstrate that this
is not always the case, by considering a well-known class of systems
represented by J-aggregates molecular crystals, characterized by the intense J
band of absorption. By means of first-principles simulations, based on a
many-body perturbation theory formalism, we investigate the optical properties
of a J-aggregate made of push-pull organic dyes. We show that the effect of
aggregation is to lower the GPI associated with the J-band with respect to the
isolated dye one, which corresponds to a nonplasmonic character of the
electronic excitations. In order to rationalize our finding, we then propose a
simplified one-dimensional theoretical model of the J-aggregate. A useful
microscopic picture of what discriminates a collective molecular crystal
excitation from a plasmon is eventually obtained.


  The problem of the strong momentum dependence of the $\rho\pi\pi$-vertex in
the extended Nambu -- Jona-Lasinio model is solved by an appropriate choice of
fields for spin-1 particles. A corresponding phenomenological Lagrangian is
derived. As straightforward applications, the decay widths of $\rho\to\pi\pi$,
and $a_1\to\rho\pi$ transitions are calculated and compared with known
empirical data and previous theoretical estimates.


  The uniaxial structure of Si and Ge (001) facets leads to nontrivial
topological properties of steps and hence to interesting equilibrium phase
transitions. The disordered flat phase and the preroughening transition can be
stabilized without the need for step-step interactions. A model describing this
is studied numerically by transfer matrix type finite-size-scaling of interface
free energies. Its phase diagram contains a flat, rough, and disordered flat
phase, separated by roughening and preroughening transition lines. Our estimate
for the location of the multicritical point where the preroughening line merges
with the roughening line, predicts that Si and Ge (001) undergo preroughening
induced simultaneous deconstruction transitions.


  We design polynomial size, constant depth (namely, $\mathsf{AC}^0$)
arithmetic formulae for the greatest common divisor (GCD) of two polynomials,
as well as the related problems of the discriminant, resultant, B\'ezout
coefficients, squarefree decomposition, and the inversion of structured
matrices like Sylvester and B\'ezout matrices. Our GCD algorithm extends to any
number of polynomials. Previously, the best known arithmetic formulae for these
problems required super-polynomial size, regardless of depth.
  These results are based on new algorithmic techniques to compute various
symmetric functions in the roots of polynomials, as well as manipulate the
multiplicities of these roots, without having access to them. These techniques
allow $\mathsf{AC}^0$ computation of a large class of linear and polynomial
algebra problems, which include the above as special cases.
  We extend these techniques to problems whose inputs are multivariate
polynomials, which are represented by $\mathsf{AC}^0$ arithmetic circuits. Here
too we solve problems such as computing the GCD and squarefree decomposition in
$\mathsf{AC}^0$.


  We study varieties of certain ordered $\Sigma$-algebras with restricted
completeness and continuity properties. We give a general characterization of
their free algebras in terms of submonads of the monad of $\Sigma$-coterms.
Varieties of this form are called \emph{quasi-regular}. For example, we show
that if $E$ is a set of inequalities between finite $\Sigma$-terms, and if
$\mathcal{V}_\omega$ and $\mathcal{V}_\mathrm{reg}$ denote the varieties of all
$\omega$-continuous ordered $\Sigma$-algebras and regular ordered
$\Sigma$-algebras satisfying $E$, respectively, then the free
$\mathcal{V}_\mathrm{reg}$-algebra $F_\mathrm{reg}(X)$ on generators $X$ is the
subalgebra of the corresponding free $\mathcal{V}_\omega$-algebra $F_\omega(X)$
determined by those elements of $F_\omega(X)$ denoted by the regular
$\Sigma$-coterms. This is a special case of a more general construction that
applies to any quasi-regular family. Examples include the *-continuous Kleene
algebras, context-free languages, $\omega$-continuous semirings and
$\omega$-continuous idempotent semirings, OI-macro languages, and iteration
theories.


  In finitely cocomplete homological categories, co-smash products give rise to
(possibly higher-order) commutators of subobjects. We use binary and ternary
co-smash products and the associated commutators to give characterisations of
internal crossed modules and internal categories, respectively. The ternary
terms are redundant if the category has the Smith is Huq property, which means
that two equivalence relations on a given object commute precisely when their
normalisations do. In fact, we show that the difference between the Smith
commutator of such relations and the Huq commutator of their normalisations is
measured by a ternary commutator, so that the Smith is Huq property itself can
be characterised by the relation between the latter two commutators. This
allows to show that the category of loops does not have the Smith is Huq
property, which also implies that ternary commutators are generally not
decomposable into nested binary ones.
  Thus, in contexts where Smith is Huq need not hold, we obtain a new
description of internal categories, Beck modules and double central extensions,
as well as a decomposition formula for the Smith commutator. The ternary
commutator now also appears in the Hopf formula for the third homology with
coefficients in the abelianisation functor.


  We investigate the quantum theory of a vortex line in a stack of
weakly-coupled two-dimensional Bose-Einstein condensates, that is created by a
one-dimensional optical lattice. We derive the dispersion relation of the
Kelvin modes of the vortex line and also study the coupling between the Kelvin
modes and the quadrupole modes. We solve the coupled dynamics of the vortex
line and the quadrupole modes, both classically as well as quantum
mechanically. The quantum mechanical solution reveals the possibility of
generating nonequilibrium squeezed vortex states by strongly driving the
quadrupole modes.


  We establish a correspondence between orbifold and singular elliptic genera
of a global quotient. While the former is defined in terms of the fixed point
set of the action, the latter is defined in terms of the resolution of
singularities. As a byproduct, the second quantization formula of Dijkgraaf,
Moore, Verlinde and Verlinde is extended to arbitrary Kawamata log-terminal
pairs.


  We deploy BT node (sensor) that offers passive and active sensing capability
to save energy. BT node works in passive mode for outdoor communication and
active for indoor communication. The BT node is supported with novel automatic
energy saving (AES) mathematical model to decide either modes. It provides
robust and faster communication with less energy consumption. To validate this
approach, network simulator-2 (ns2) simulation is used to simulate the behavior
of network with the supporting mathematical model. The main objective of this
research is to remotely access different types of servers, laptops, desktops
and other static and moving objects. This prototype is initially deployed to
control MSCS [13] & [14] from remote place through mobile devices. The
prototype can further be enhanced to handle several objects simultaneously
consuming less energy and resources.


  Great advances in precision quantum measurement have been achieved with
trapped ions and atomic gases at the lowest possible temperatures. These
successes have inspired ideas to merge the two systems. In this way one can
study the unique properties of ionic impurities inside a quantum fluid or
explore buffer gas cooling of the trapped ion quantum computer. Remarkably, in
spite of its importance, experiments with atom-ion mixtures remained firmly
confined to the classical collision regime. We report a collision energy of
1.15(0.23) times the $s$-wave energy (or 9.9(2.0)~$\mu$K) for a trapped
ytterbium ion in an ultracold lithium gas. We observed a deviation from
classical Langevin theory by studying the spin-exchange dynamics, indicating
quantum behavior in the atom-ion collisions. Our results open up numerous
opportunities, such as the exploration of atom-ion Feshbach resonances, in
analogy to neutral systems.


  It has long been known that null unstable geodesics are related to the
characteristic modes of black holes-- the so called quasinormal resonances. The
basic idea is to interpret the free oscillations of a black hole in the eikonal
limit in terms of null particles trapped at the unstable circular orbit and
slowly leaking out. The real part of the complex quasinormal resonances is
related to the angular velocity at the unstable null geodesic. The imaginary
part of the resonances is related to the instability timescale (or the inverse
Lyapunov exponent) of the orbit. While this geometric-optics description of the
black-hole quasinormal resonances in terms of perturbed null {\it rays} is very
appealing and intuitive, it is still highly important to verify the validity of
this approach by directly analyzing the Teukolsky wave equation which governs
the dynamics of perturbation {\it waves} in the black-hole spacetime. This is
the main goal of the present paper. We first use the geometric-optics technique
of perturbing a bundle of unstable null rays to calculate the resonances of
near-extremal Kerr black holes in the eikonal approximation. We then directly
solve the Teukolsky wave equation (supplemented by the appropriate physical
boundary conditions) and show that the resultant quasinormal spectrum obtained
directly from the wave analysis is in accord with the spectrum obtained from
the geometric-optics approximation of perturbed null rays.


  We consider the spike mass density profile in a dark halo by
self-consistently solving the relativistic Bondi accretion of dark matter onto
a non-spining black hole of mass $M$. We assume that the dominant component of
the dark matter in the halo is a Standard model gauge-singlet scalar. Its mass
$m\simeq 10^{-5}{\rm eV}$ and quartic self-coupling $\lambda\lesssim10^{-19}$
are constrained to be compatible with the properties of galactic dark halos. In
the hydrodynamic limit, we find that the accretion rate is bounded from below,
$\dot{M}_{\rm min}=96\pi G^2M^2 m^4/\lambda\hbar^3$. Therefore, for
$M=10^6~{\rm M}_\odot$ we have $\dot{M}_{\rm min}\simeq1.41\times 10^{-9}~{\rm
M}_\odot~{\rm yr}^{-1}$, which is subdominant compared to the Eddington
accretion of baryons. The spike density profile $\rho_0(r)$ within the
self-gravitating regime cannot be fitted well by a single-power law but a
double-power one. Despite that, we can fit $\rho_0(r)$ piecewise and find that
$\rho_0(r) \propto r^{-1.20}$ near the sound horizon, $\rho_0(r) \propto
r^{-1.00}$ towards the Bondi radius and $\rho_0(r) \propto r^{-1.08}$ for the
region in between. This contrasts with more cuspy $\rho_0(r) \propto r^{-1.75}$
for dark matter with Coulomb-like self-interaction.


  We set up a left ring of fractions over a certain ring of boundary problems
for linear ordinary differential equations. The fraction ring acts naturally on
a new module of generalized functions. The latter includes an isomorphic copy
of the differential algebra underlying the given ring of boundary problems. Our
methodology employs noncommutative localization in the theory of
integro-differential algebras and operators. The resulting structure allows to
build a symbolic calculus in the style of Heaviside and Mikusinski, but with
the added benefit of incorporating boundary conditions where the traditional
calculi allow only initial conditions.


  We have found the possible region of parameters of the minimal supersymmetric
standard model (MSSM) within the bounds from the experimental results of the
Higgs mass, the rare decay mode of $b$-quark, the muon $g-2$, the dark matter
abundance, and the direct searches for the lighter stop (i.e., one of the
supersymmetric partners of top quark) at the LHC. We present numerical results
of calculations for the one loop effects of supersymmetric particles in the
processes of $\tau^+ \tau^-$, $b \overline{b}$, $t \overline{t}$, and $Z h$
production at the ILC by using benchmark points within the possible region of
the MSSM parameters.


  We report the first results of a program to measure accurate stellar velocity
dispersions in the bulges of the host galaxies of active galactic nuclei (AGNs)
for which accurate black hole (BH) masses have been determined via
reverberation mapping. We find good agreement between BH masses obtained from
reverberation mapping, and from the M(BH) - sigma relation as defined by
quiescent galaxies, indicating a common relationship between active and
quiescent black holes and their large-scale environments.


  We propose a class of variational wave functions, namely the correlated
valence bond states, for the frustrated Hamiltonian in the paramagnetic phase.
This class of wave functions admits negative amplitude and the same sub-lattice
pairing when a bipartite lattice is considered, thus suffers from the negative
sign problem. However if applied to small systems, the sign problem is
manageable using the standard variational Monte Carlo method. We optimize the
wave functions for the J1-J2 Anti ferromagnetic Heisenberg model on a square
lattice in the coupling region J2/J1 \in [0.45 : 0.56] for system sizes L = 4,
6, 8. To calculate the correlation functions and the order parameters for
larger systems, we make the extensive Monte Carlo samplings using the
variational parameters optimized at system size L = 8. We find that the
paramagnetic phase is a gap-less spin liquid in the entire range of J2/J1 \in
[0.45 : 0.56] with a gap-less singlet excitation and a gaped triplet
excitation.


  Swirling flows in conical pipe can be found in a number of industrial
processes, such as hydrocylone, separator and rotating machinery. It has been
found that wall oscillations can reduce the drag in water channel and pipe
flows, but there is no study of a swirling flow combined with a vibrating wall
in conical pipes, though there are many applications of such combination in
engineering processes. A two-dimensional particle image velocimetry (PIV) is
used to measure the swirling flow field in a water conical pipe subjected to a
periodic vibrating wall for a Reynolds number 3800. The flow velocity
statistics are studied under different vibration frequencies corresponding to
Strouhal numbers from 60 to 242. The instantaneous axial and vertical velocity
in one vibrating period, the mean velocities, and Reynolds stresses were
obtained. The results show the existence of an intermediary recirculation cell
in the middle of the pipe. They also show that the vibration improves the
symmetry for the swirling flow while decreasing dramatically the velocity
fluctuation.


  The compact configuration of Phase II of the Murchison Widefield Array (MWA)
consists of both a redundant subarray and pseudo-random baselines, offering
unique opportunities to perform sky-model and redundant interferometric
calibration. The highly redundant hexagonal cores give improved power spectrum
sensitivity. In this paper, we present the analysis of nearly 40 hours of data
targeting one of the MWA's EoR fields observed in 2016. We use both improved
analysis techniques presented in Barry et al. (2019) as well as several
additional techniques developed for this work, including data quality control
methods and interferometric calibration approaches. We show the EoR power
spectrum limits at redshift 6.5, 6.8 and 7.1 based on our deep analysis on this
40-hour data set. These limits span a range in $k$ space of $0.18$ $h$
$\mathrm{Mpc^{-1}}$ $<k<1.6$ $h$ $\mathrm{Mpc^{-1}}$, with a lowest measurement
of $\Delta^2\leqslant2.39\times 10^3$ $\mathrm{mK}^2$ at $k=0.59$ $h$
$\mathrm{Mpc^{-1}}$ and $z=6.5$.


  There are anthropic reasons to suspect that life in more than three spatial
dimensions is not possible, and if the same could be said of fewer than three,
then one would have an anthropic argument for why we experience precisely three
large spatial dimensions. There are two main arguments levelled against the
possibility of life in 2 + 1 dimensions: the lack of a local gravitational
force and Newtonian limit in 3D general relativity, and the claim that the
restriction to a planar topology means that the possibilities are 'too simple'
for life to exist. I will examine these arguments and show how a purely scalar
theory of gravity may evade the first one, before considering certain families
of planar graphs which share properties which are observed in real-life
biological neural networks and are argued to be important for their
functioning.


  We report the results of x-ray scattering studies of AlN on c-plane sapphire
during reactive radiofrequency magnetron sputtering. The sensitivity of in situ
x-ray measurements allowed us to follow the structural evolution of strain and
roughness from initial nucleation layers to fullyrelaxed AlN films. A growth
rate transient was observed, consistent with the initial formation of
non-coalesced islands with significant oxygen incorporation from the substrate.
Following island coalescence, a steady state growth rate was seen with a
continuous shift of the c and a lattice parameters towards the relaxed bulk
values as growth progressed, with films reaching a fully relaxed state at
thicknesses of about 30 nm.


  We give a direct proof of (a slight generalization of) the recent result of
A. Premet related to generalized Gelfand-Graev representations and of an
equivalence due to Skryabin.


  Measurements that occur within the internal layers of a quantum circuit --
mid-circuit measurements -- are an important quantum computing primitive, most
notably for quantum error correction. Mid-circuit measurements have both
classical and quantum outputs, so they can be subject to error modes that do
not exist for measurements that terminate quantum circuits. Here we show how to
characterize mid-circuit measurements, modelled by quantum instruments, using a
technique that we call quantum instrument linear gate set tomography (QILGST).
We then apply this technique to characterize a dispersive measurement on a
superconducting transmon qubit within a multiqubit system. By varying the delay
time between the measurement pulse and subsequent gates, we explore the impact
of residual cavity photon population on measurement error. QILGST can resolve
different error modes and quantify the total error from a measurement; in our
experiment, for delay times above 1000 ns we measured a total error rate (i.e.,
half diamond distance) of $\epsilon_{\diamond} = 8.1 \pm 1.4 \%$, a readout
fidelity of $97.0 \pm 0.3\%$, and output quantum state fidelities of $96.7 \pm
0.6\%$ and $93.7 \pm 0.7\%$ when measuring $0$ and $1$, respectively.


  The theory of pseudo-differential operators is a powerful tool to deal with
differential equations involving differential operators under the square root
sign. These type of equations are pivotal elements to treat problems in
anomalous diffusion and in relativistic quantum mechanics. In this paper we
report on new and unsuspected links between fractional diffusion, quantum
relativistic equations and particular families of polynomials, linked to the
Carlitz family, and playing the role of relativistic heat polynomials. We
introduce generalizations of these polynomial families and point out their
specific use for the solutions of problems of practical importance.


  We find the noise sensitivities (i.e., the quadratic terms of the energy with
respect to the perturbation of the noise) of a particle shuttled by an optical
lattice that moves according to a shortcut-to-adiabaticity transport protocol.
Noises affecting different optical lattice parameters, trap depth, position,
and lattice periodicity, are considered. We find generic expressions of the
sensitivities for arbitrary noise spectra but focus on the white-noise limit as
a basic reference, and on Ornstein-Uhlenbeck noise to account for the effect of
non-zero correlation times.


  The amount and size of spatiotemporal data sets from different domains have
been rapidly increasing in the last years, which demands the development of
robust and fast methods to analyze and extract information from them. In this
paper, we propose a network-based model for spatiotemporal data analysis called
chronnet. It consists of dividing a geometrical space into grid cells
represented by nodes connected chronologically. The main goal of this model is
to represent consecutive recurrent events between cells with strong links in
the network. This representation permits the use of network science and
graphing mining tools to extract information from spatiotemporal data. The
chronnet construction process is fast, which makes it suitable for large data
sets. In this paper, we describe how to use our model considering artificial
and real data. For this purpose, we propose an artificial spatiotemporal data
set generator to show how chronnets capture not just simple statistics, but
also frequent patterns, spatial changes, outliers, and spatiotemporal clusters.
Additionally, we analyze a real-world data set composed of global fire
detections, in which we describe the frequency of fire events, outlier fire
detections, and the seasonal activity, using a single chronnet.


  New COVID-19 epidemic strains like Delta and Omicron with increased
transmissibility and pathogenicity emerge and spread across the whole world
rapidly while causing high mortality during the pandemic period. Early
prediction of possible variants (especially spike protein) of COVID-19 epidemic
strains based on available mutated SARS-CoV-2 RNA sequences may lead to early
prevention and treatment. Here, combining the advantage of quantum and
quantum-inspired algorithms with the wide application of deep learning, we
propose a development tool named DeepQuantum, and use this software to realize
the goal of predicting spike protein variation structure of COVID-19 epidemic
strains. In addition, this hybrid quantum-classical model for the first time
achieves quantum-inspired blur convolution similar to classical depthwise
convolution and also successfully applies quantum progressive training with
quantum circuits, both of which guarantee that our model is the quantum
counterpart of the famous style-based GAN. The results state that the
fidelities of random generating spike protein variation structure are always
beyond 96% for Delta, 94% for Omicron. The training loss curve is more stable
and converges better with multiple loss functions compared with the
corresponding classical algorithm. At last, evidences that quantum-inspired
algorithms promote the classical deep learning and hybrid models effectively
predict the mutant strains are strong.


  In a pure C*-algebra (i.e., one having suitable regularity properties in its
Cuntz semigroup), any element on which all bounded traces vanish is a sum of 7
commutators.


  Principal component analysis (PCA) is an indispensable tool in many learning
tasks that finds the best linear representation for data. Classically,
principal components of a dataset are interpreted as the directions that
preserve most of its "energy", an interpretation that is theoretically
underpinned by the celebrated Eckart-Young-Mirsky Theorem. There are yet other
ways of interpreting PCA that are rarely exploited in practice, largely because
it is not known how to reliably solve the corresponding non-convex optimisation
programs. In this paper, we consider one such interpretation of principal
components as the directions that preserve most of the "volume" of the dataset.
Our main contribution is a theorem that shows that the corresponding non-convex
program has no spurious local optima. We apply a number of solvers for
empirical confirmation.


  In geostatistics, traditional spatial models often rely on the Gaussian
Process (GP) to fit stationary covariances to data. It is well known that this
approach becomes computationally infeasible when dealing with large data
volumes, necessitating the use of approximate methods. A powerful class of
methods approximate the GP as a sum of basis functions with random
coefficients. Although this technique offers computational efficiency, it does
not inherently guarantee a stationary covariance. To mitigate this issue, the
basis functions can be "normalized" to maintain a constant marginal variance,
avoiding unwanted artifacts and edge effects. This allows for the fitting of
nearly stationary models to large, potentially non-stationary datasets,
providing a rigorous base to extend to more complex problems. Unfortunately,
the process of normalizing these basis functions is computationally demanding.
To address this, we introduce two fast and accurate algorithms to the
normalization step, allowing for efficient prediction on fine grids. The
practical value of these algorithms is showcased in the context of a spatial
analysis on a large dataset, where significant computational speedups are
achieved. While implementation and testing are done specifically within the
LatticeKrig framework, these algorithms can be adapted to other basis function
methods operating on regular grids.


  We contemplate this article to help the teachers of programming in his
aspiration for giving some appropriate and interesting examples. The work will
be especially useful for students-future programmers, and for their lecturers.
Some of the strong sides of these programming languages C/C++ and Java are the
possibilities of low-level programming. Some of the means for this possibility
are the introduced standard bitwise operations, with the help of which, it is
possible to directly operate with every bit of an arbitrary variable situated
in the computers memory. In the current study, we are going to describe some
methodical aspects for work with the bitwise operations and we will discuss the
benefit of using bitwise operations in programming. The article shows some
advantages of using bitwise operations, realizing various operations with sets.


  We estimate the main systematic effects relevant in a mission to test and
characterize the Pioneer anomaly through the flight formation concept, by
launching probing spheres from a mother spacecraft and tracking their motion
via laser ranging.


  We prove mixing convergence of the least squares estimator of autoregressive
parameters for supercritical autoregressive processes of order 2 with Gaussian
innovations having real characteristic roots with different absolute values. We
use an appropriate random scaling such that the limit distribution is a
two-dimensional normal distribution concentrated on a one-dimensional ray
determined by the characteristic root having the larger absolute value.


  In the context of core-collapse supernova explosions (CCSNe), the interaction
of standing accretion shocks with upstream vorticity perturbations is
investigated by linear theory analysis. The endothermic effect associated to
the nuclear dissociation, which takes place right behind the shock wave,
affects the amplitude of the perturbations amplified/generated across the
front. For upstream disturbances whose characteristic size is much larger than
the post-shock dissociation-layer thickness, the effect of nuclear dissociation
can be reduced to that of considering the global endothermic effect that scales
with the inflow energy flux. The present study focuses on perturbation fields
that are not isotropic, which mimic the perturbations in collapsing convective
shells of massive stars. The linear interaction of the shock with bidimensional
mono-frequency vorticity perturbations is theoretically addressed, with the
limit of highly-stretched vortices being analyzed in detail. The exact spatial
distribution of the rotational and acoustic perturbations generated in the
post-shock flow are provided along with the transient evolution of the shock
front. It is found that nuclear dissociation contributes to stabilize the shock
oscillations, but increases the amplitude of the density perturbations
downstream. An extension of this work that addresses the interaction with
tridimensional isotropic turbulent flows can be found in reference Huete, C.,
et al. 2018, MNRAS, 475, 3305-3323, which analyzes the effect of the post-shock
flow on the critical conditions that ultimately trigger explosion.


  In a digital communication system, information is sent from one place to
another over a noisy communication channel using binary symbols (bits).
Original information is encoded by adding redundant bits, which are then used
by low--density parity--check (LDPC) codes to detect and correct errors that
may have been introduced during transmission. Error correction capability of an
LDPC code is severely degraded due to harmful structures such as small cycles
in its bipartite graph representation known as Tanner graph (TG). We introduce
an integer programming formulation to generate a TG for a given smallest cycle
length. We propose a branch-and-cut algorithm for its solution and investigate
structural properties of the problem to derive valid inequalities and variable
fixing rules. We introduce a heuristic to obtain feasible solutions of the
problem. Our computational experiments show that our algorithm can generate
LDPC codes without small cycles in acceptable amount of time for practically
relevant code lengths.


  Convolutional Neural Networks (CNNs) have gained a remarkable success on many
image classification tasks in recent years. However, the performance of CNNs
highly relies upon their architectures. For most state-of-the-art CNNs, their
architectures are often manually-designed with expertise in both CNNs and the
investigated problems. Therefore, it is difficult for users, who have no
extended expertise in CNNs, to design optimal CNN architectures for their own
image classification problems of interest. In this paper, we propose an
automatic CNN architecture design method by using genetic algorithms, to
effectively address the image classification tasks. The most merit of the
proposed algorithm remains in its "automatic" characteristic that users do not
need domain knowledge of CNNs when using the proposed algorithm, while they can
still obtain a promising CNN architecture for the given images. The proposed
algorithm is validated on widely used benchmark image classification datasets,
by comparing to the state-of-the-art peer competitors covering eight
manually-designed CNNs, seven automatic+manually tuning and five automatic CNN
architecture design algorithms. The experimental results indicate the proposed
algorithm outperforms the existing automatic CNN architecture design algorithms
in terms of classification accuracy, parameter numbers and consumed
computational resources. The proposed algorithm also shows the very comparable
classification accuracy to the best one from manually-designed and
automatic+manually tuning CNNs, while consumes much less of computational
resource.


  The equilibrium value of an observable defines a manifold in the phase space
of an ergodic and equipartitioned many-body system. A typical trajectory
pierces that manifold infinitely often as time goes to infinity. We use these
piercings to measure both the relaxation time of the lowest frequency eigenmode
of the Fermi-Pasta-Ulam chain (FPU), as well as the fluctuations of the
subsequent dynamics in equilibrium. The dynamics in equilibrium is
characterized by a power-law distribution of excursion times far off
equilibrium, with diverging variance. Long excursions arise from sticky
dynamics close to q-breathers localized in normal mode space. Measuring the
exponent allows to predict the transition into nonergodic dynamics. We
generalize our method to Klein-Gordon lattices (KG) where the sticky dynamics
is due to discrete breathers localized in real space.


  Organic-inorganic lead halide perovskites containing a mixture of iodide and
bromide anions consistently perform better in donor-acceptor heterojunction
solar cells than the standard methylammonium lead triiodide material. This
observation is counterintuitive, as it is generally expected for photovoltaic
materials that heterogeneities and compositional disorder cause reduced carrier
diffusion length and conversion efficiency. Here, we combine ultrafast
photoinduced electroabsorption and broadband fluorescence up-conversion
spectroscopy measurements to scrutinize the carrier dynamics in mixed-cations,
mixed-halide lead perovskite thin films. Our results evidence the formation of
charge transfer excitons (CTE) across the boundaries of domains of various
halide compositions. A global analysis of photoinduced transient Stark signals
shows that CTE evolve gradually from Br-rich to I-rich domains over tens to
hundreds of picoseconds. Rather than constituting recombination centres,
boundaries between domains of various halide compositions appear then to favour
charge carrier separation by driving photogenerated holes along channels of
decreasing bromide content.


  We study the light quark effect on the Higgs boson production in association
with a jet at the LHC in the intermediate transverse momentum region between
the quark and the Higgs boson mass scales. Though the effect is suppressed by
the small Yukawa coupling, it is enhanced by large logarithms of the quark mass
ratio to the Higgs boson mass or transverse momentum. Following a remarkable
success of the logarithmic expansion [39] for the prediction of the
next-to-next-to-leading bottom quark contribution to the total cross section of
the Higgs boson production we extend the analysis to its kinematical
distributions. A new factorization formula is derived for the light quark
mediated $gg\to Hg$ amplitudes and the differential cross section of the
process is computed in the logarithmic approximation, which is used for an
estimate of the bottom quark effect at the next-to-next-to-leading order.


  Whenever a distinct state is immersed in a sea of complicated and dense
states, the strength of the distinct state, which we refer to as a doorway, is
distributed in their neighboring states. We analyze this mechanism for 2-D
billiards with different geometries. One of them is symmetric and integrable,
another is symmetric but chaotic, and the third has a capricious form. The fact
that the doorway-state mechanism is valid for such highly diverse cases, proves
that it is robust.


  An unresolved issue concerning cuprate superconductors is whether the
distribution of carriers in the CuO(2) plane is uniform or inhomogeneous.
Because the carriers comprise a small fraction of the total charge density and
may be rapidly fluctuating, modulations are difficult to detect directly. Here
we demonstrate that in anomalous x-ray scattering at the oxygen K edge of the
cuprates, the contribution of carriers to the scattering amplitude is
selectively magnified 82 times. This enhances diffraction from the doped holes
by more than 10^3, permitting direct structural analysis of the superconducting
ground state. Scattering from thin films of La(2)CuO(4+x) (Tc = 39 K) at T=(50
+/- 5) K on the reciprocal space intervals (0,0,0.21) -> (0,0,1.21) and
(0,0,0.6) -> (0.3,0,0.6) show a rounding of the carrier density near the
substrate suggestive of a depletion zone or similar effect. The structure
factor for off-specular scattering was less than 3x10-7 e, suggesting an
absence of in-plane hole ordering in this material.


  In this paper, we propose a model-driven channel estimation method utilizing
a convolutional neural network (CNN) derived from image super-resolution (SR).
Instead of completely abandoning traditional communication modules as
data-driven approaches always do, we first obtain rough channel matrix by the
simplest least square (LS) channel estimation, and then use a CNN-based SR
network to learn the subtle connections within channel matrix for accuracy
improvement. The results show that our proposed method significantly
outperforms the linear minimum mean squared error (LMMSE) estimation and has
potential in spectrum saving. The impacts of network structure and SNR mismatch
problem are also investigated in this paper.


  We present an R-band and J-band photometry of an optical transient which is
likely to be associated with the gamma-ray burst event GRB 971214. Our first
measurement took place 13 hours after the gamma-ray event. The brightness
decayed with a power-law exponent alpha = -1.20 +- 0.02, which is similar to
those of GRB 970228 and GRB 970508 which had exponents of alpha = -1.10 +- 0.04
and alpha = -1.141 +- 0.014 respectively. The transient decayed monotonically
during the first four days following the gamma-ray event in contrast with the
optical transient associated with GRB 970508 which increased in brightness,
peaking two days after the burst, before settling to a power-law decay.


  We define Gromov-Witten classes and invariants of smooth projective schemes
of finite presentation over a Dedekind domain. We prove that they are
deformation invariants and verify the fundamental axioms. For a smooth
projective scheme over a Dedekind domain, we prove that the invariants of
fibers in different characteristics are the same. We show that genus zero
Gromov-Witten invariants define a potential which satisfies the WDVV equation
and we deduce from this a reconstruction theorem for genus zero Gromov-Witten
invariants in arbitrary characteristic.


  An electric inductor-capacitor (ELC) resonator provides a series of
electrical resonances and a pair of ELC resonators leads to the split of each
resonance into two modes, i.e., magnetic and electric modes, corresponding to
antisymmetric and symmetric current distributions. With the meticulous design
of the ELC resonator, we can achieve a negative index metamaterial through mode
hybridization by overlapping the first electric resonance mode and the second
magnetic resonance mode. Such non-connected designs may offer opportunities to
achieve three-dimensional negative index metamaterials.


  Accurate and controllable image editing is a challenging task that has
attracted significant attention recently. Notably, DragGAN is an interactive
point-based image editing framework that achieves impressive editing results
with pixel-level precision. However, due to its reliance on generative
adversarial networks (GANs), its generality is limited by the capacity of
pretrained GAN models. In this work, we extend this editing framework to
diffusion models and propose a novel approach DragDiffusion. By harnessing
large-scale pretrained diffusion models, we greatly enhance the applicability
of interactive point-based editing on both real and diffusion-generated images.
Our approach involves optimizing the diffusion latents to achieve precise
spatial control. The supervision signal of this optimization process is from
the diffusion model's UNet features, which are known to contain rich semantic
and geometric information. Moreover, we introduce two additional techniques,
namely LoRA fine-tuning and latent-MasaCtrl, to further preserve the identity
of the original image. Lastly, we present a challenging benchmark dataset
called DragBench -- the first benchmark to evaluate the performance of
interactive point-based image editing methods. Experiments across a wide range
of challenging cases (e.g., images with multiple objects, diverse object
categories, various styles, etc.) demonstrate the versatility and generality of
DragDiffusion. Code: https://github.com/Yujun-Shi/DragDiffusion.


  The concept of a noncommutative field is formulated based on the interplay
between twisted Poincar\'e symmetry and residual symmetry of the Lorentz group.
Various general dynamical results supporting this construction, such as the
light-wedge causality condition and the integrability condition for
Tomonaga-Schwinger equation, are presented. Based on this analysis, the claim
of the identity between commutative QFT and noncommutative QFT with twisted
Poincar\'e symmetry is refuted.


  Collisions between cosmic bubbles of different vacua are a generic feature of
false vacuum eternal inflation scenarios. While previous studies have focused
on the consequences of a single collision event in an observer's past, we begin
here an investigation of the more general scenario allowing for many "mild"
collisions intersecting our past light cone (and one another). We discuss the
general features of multiple collision scenarios and consider their impact on
the cosmic microwave background (CMB) temperature power spectrum, treating the
collisions perturbatively. In a large class of models, one can approximate a
multiple collision scenario as a superposition of individual collision events
governed by nearly isotropic and scale-invariant distributions, most appearing
to take up less than half of the sky. In this case, the shape of the expected
CMB temperature spectrum maintains statistical isotropy and typically features
a dramatic increase in power in the low multipoles relative to that of the
best-fit $\Lambda$CDM model, which is in tension particularly with the observed
quadrupole. We argue that this predicted spectrum is largely model-independent
and can be used to outline features of the underlying statistical distributions
of colliding bubbles consistent with CMB temperature measurements.


  Effectively and efficiently adapting a pre-trained language model (PLM) for
human-centered text understanding (HCTU) is challenging since user tokens are
million-level in most personalized applications and do not have concrete
explicit semantics. A standard and parameter-efficient approach (e.g., LoRA)
necessitates memorizing numerous suits of adapters for each user. In this work,
we introduce a personalized LoRA (PLoRA) with a plug-and-play (PnP) framework
for the HCTU task. PLoRA is effective, parameter-efficient, and dynamically
deploying in PLMs. Moreover, a personalized dropout and a mutual information
maximizing strategies are adopted and hence the proposed PLoRA can be well
adapted to few/zero-shot learning scenarios for the cold-start issue.
Experiments conducted on four benchmark datasets show that the proposed method
outperforms existing methods in full/few/zero-shot learning scenarios for the
HCTU task, even though it has fewer trainable parameters. For reproducibility,
the code for this paper is available at: https://github.com/yoyo-yun/PLoRA.


  A three-member platoon of Ahmed bodies was studied to investigate the effects
of drag variation when the middle member goes out of synchronization and starts
to oscillate longitudinally. Oscillations were carried out at two different
reduced frequencies corresponding to two different drafting scenarios in
NASCAR. Computational Fluid Dynamics simulations were performed to calculate
the transient drag force, which was compared with the steady averaged drag
results obtained with the middle member in different locations with respect to
the lead and trailing bodies. Oscillations create dynamic forces in a platoon,
such as suction and compression, which are taken into account by transient
analysis. Since the steady cases failed to reproduce these forces on the
oscillating vehicle, steady and transient drag comparison for the middle
vehicle showed about 75\% difference at normalized time of 1.5 for reduced
frequency of 0.4. Drag oscillates for every platoon member and remains
cyclically repeatable after the first cycle. Higher reduced frequency increases
the drag amplitude for the oscillating member. For the rest of the platoon,
changing frequencies does not show significant effects. At very small
separation gaps, pressure loss occurs resulting in sudden change in the drag.
Drag peaks are mostly governed by the dynamic forces, therefore transient
methods should be used for studying the oscillating effects in a platoon.


  Bayesian network models are finding success in characterizing
enzyme-catalyzed reactions, slow conformational changes, predicting enzyme
inhibition, and genomics. In this work, we apply them to statistical modeling
of peptides by simultaneously identifying amino acid sequence motifs and using
a motif-based model to clarify the role motifs may play in antimicrobial
activity. We construct models of increasing sophistication, demonstrating how
chemical knowledge of a peptide system may be embedded without requiring new
derivation of model fitting equations after changing model structure. These
models are used to construct classifiers with good performance (94% accuracy,
Matthews correlation coefficient of 0.87) at predicting antimicrobial activity
in peptides, while at the same time being built of interpretable parameters. We
demonstrate use of these models to identify peptides that are potentially both
antimicrobial and antifouling, and show that the background distribution of
amino acids could play a greater role in activity than sequence motifs do. This
provides an advancement in the type of peptide activity modeling that can be
done and the ease in which models can be constructed.


  Low-energy medium-luminosity Muon Collider (MC) is being studied as a
possible Higgs Factory (HF). Electrons from muon decays will deposit more than
300 kW in superconducting magnets of the HF collider ring. This imposes
significant challenges to superconducting (SC) magnets used in the MC storage
ring (SR) and interaction regions (IR). The magnet designs are proposed which
provide high operating gradient and magnetic field in a large aperture to
accommodate the large size of muon beams due to low \b{eta}* as well as the
cooling system to intercept the large heat deposition from the showers induced
by decay electrons. Specific distribution of heat deposition in the lattice
elements MC SR requires large aperture magnets to accommodate thick high-Z
absorbers to protect the SC coils. Based on the developed MARS15 model and
intense simulations, a sophisticated radiation protection system was designed
for the collider SR and IR to bring the peak power density in the
superconducting coils below the quench limit and reduce the dynamic heat
deposition in the cold mass by a factor of 100. The system consists of tight
tungsten masks in the magnet interconnect regions and elliptical tungsten
liners in magnet aperture optimized for each magnet. It also reduces the
background particle fluxes in the collider detector.


  We prove approach to thermal equilibrium for the fully Hamiltonian dynamics
of a dynamical Lorentz gas, by which we mean an ensemble of particles moving
through a $d$-dimensional array of fixed soft scatterers that each possess an
internal harmonic or anharmonic degree of freedom to which moving particles
locally couple. We establish that the momentum distribution of the moving
particles approaches a Maxwell-Boltzmann distribution at a certain temperature
$T$, provided that they are initially fast and the scatterers are in a
sufficiently energetic but otherwise arbitrary stationary state of their free
dynamics--they need not be in a state of thermal equilibrium. The temperature
$T$ to which the particles equilibrate obeys a generalized equipartition
relation, in which the associated thermal energy $k_{\mathrm B}T$ is equal to
an appropriately defined average of the scatterers' kinetic energy. In the
equilibrated state, particle motion is diffusive.


  The self-consistent theory of Anderson localization of quantum particles or
classical waves in disordered media is reviewed. After presenting the basic
concepts of the theory of Anderson localization in the case of electrons in
disordered solids, the regimes of weak and strong localization are discussed.
Then the scaling theory of the Anderson localization transition is reviewed.
The renormalization group theory is introduced and results and consequences are
presented. It is shown how scale-dependent terms in the renormalized
perturbation theory of the inverse diffusion coefficient lead in a natural way
to a self-consistent equation for the diffusion coefficient. The latter
accounts quantitatively for the static and dynamic transport properties except
for a region near the critical point. Several recent applications and
extensions of the self-consistent theory, in particular for classical waves,
are discussed.