  We showcase a collection of practical strategies to deal with a problem
arising from an analysis of integral estimators derived via quasi-Monte Carlo
methods. The problem reduces to a triple binomial sum, thereby enabling us to
open up the holonomic toolkit, which contains tools such as creative
telescoping that can be used to deduce a recurrence satisfied by the sum. While
applying these techniques, a host of issues arose that partly needed to be
resolved by hand. In other words, no creative telescoping implementation
currently exists that can resolve all these issues automatically. Thus, we felt
the need to compile the different strategies we tried and the difficulties that
we encountered along the way. In particular, we highlight the necessity of the
certificate in these computations and how its complexity can greatly influence
the computation time.


  Recent XMM-Newton observations of clusters of galaxies have provided detailed
information on the distribution of heavy elements in the central regions of
clusters with cooling cores providing strong evidence that most of these metals
come from recent SN type Ia. In this paper we compile information on the
cumulative mass profiles of iron, the most important metallicity tracer. We
find that long enrichment times (larger than 5 Gyr) are necessary to produce
the central abundance peaks. Classical cooling flows, a strongly convective
intracluster medium, and a complete metal mixing by cluster mergers would
destroy the observed abundance peaks too rapidly. Thus the observations set
strong constraints on cluster evolution models requiring that the cooling cores
in clusters are preserved over very long times. We further conclude from the
observations that the innermost part of the intracluster medium is most
probably dominated by gas originating predominantly from stellar mass loss of
the cD galaxy.


  Thermal transport of nanocrystalline Si is of great importance for the
application of thermoelectrics. A better understanding of the modal thermal
conductivity of nanocrystalline Si will be expected to benefit the efficiency
of thermoelectrics. In this work, the variance reduced Monte Carlo simulation
with full band of phonon dispersion is applied to study the modal thermal
conductivity of nanocrystalline Si. Importantly, the phonon modal transmissions
across the grain boundaries which are modeled by the amorphous Si interface are
calculated by the mode-resolved atomistic Greens function method. The predicted
ratios of thermal conductivity of nanocrystalline Si to that of bulk Si agree
well with that of the experimental measurements in a wide range of grain size.
The thermal conductivity of nanocrystalline Si is decreased from 54 percent to
3 percent and the contribution of phonons with mean free path larger than the
grain size increases from 30 percent to 96 percnet as the grain size decreases
from 550 nm to 10 nm. This work demonstrates that the full band Monte Carlo
simulation using phonon modal transmission by the mode-resolved atomistic
Greens function method can capture the phonon transport picture in complex
nanostructures, and therefore can provide guidance for designing high
performance Si based thermoelectrics.


  In this paper we describe some of the constructions of FJRW theory. We also
briefly describe its relation to Saito-Givental theory via Landau-Ginzburg
mirror symmetry and its relation to Gromov-Witten theory via the
Landau-Ginzburg/Calabi-Yau correspondence. We conclude with a discussion of
some of the recent results in the field.


  Calcium batteries (CBs) are potential next-generation energy storage devices,
offering a promising alternative to lithium-ion batteries due to their
theoretically high energy density, better safety, and lower costs associated
with the natural abundance of calcium. However, the limited availability of
positive electrode (cathode) materials has constrained the development of CBs
so far. Given the similar ionic radii of Na$^+$ and Ca$^{2+}$, structures that
are effective at reversibly intercalating Na$^+$ may be able to reversibly
intercalate Ca$^{2+}$ as well. In this context, transition metal fluorides
(TMFs) exhibiting weberite and perovskite structures that are known for
intercalating Na$^+$ form an interesting set of possible CB cathode frameworks.
Thus, we use first principles calculations to explore weberite and perovskite
TMFs as CB cathodes, of compositions
Ca\textsubscript{x}M\textsubscript{2}F\textsubscript{7} and
Ca\textsubscrpt{x}MF\textsubscript{3}, respectively, where M = Ti, V, Cr, Mn,
Fe, Co, or Ni. We systematically evaluate key cathode properties, including
ground state structure, average Ca-intercalation voltage, thermodynamic
stability (at 0 K), theoretical capacity, and Ca$^{2+}$ migration barriers.
Importantly, we identify
Ca\textsubscript{x}Cr\textsubscript{2}F\textsubscript{7} and
Ca\textsubscript{x}Mn\textsubscript{2}F\textsubscript{7} weberite frameworks as
promising Ca-cathodes. Our study not only unveils potential CB cathodes but
also paves the way for further advancement in TMF-based intercalation cathodes,
diversifying the chemical space for next-generation energy storage systems.


  The existence of Davies-Unruh temperature in a uniformly accelerated frame
shows that quantum fluctuations of the inertial vacuum state appears as thermal
fluctuations in the accelerated frame. Hence thermodynamic experiments cannot
distinguish between phenomena occurring in a thermal bath of temperature T in
the inertial frame from those in a frame accelerating through inertial vacuum
with the acceleration $a=2\pi T$. We show that this indisguishability between
quantum fluctuations and thermal fluctuations goes far beyond the fluctuations
in the vacuum state. We show by an exact calculation, that the reduced density
matrix for a uniformly accelerated observer when the quantum field is in a
thermal state of temperature $T^\prime$ is symmetric between acceleration
temperature $T = a/(2\pi)$ and the thermal bath temperature $T^\prime$. Thus
thermal phenomena cannot distinguish whether (i) one is accelerating with $a =
2\pi T$ through a bath of temperature $T^\prime$ or (ii) accelerating with
$a=2\pi T^\prime$ through a bath of temperature T. This shows that thermal and
quantum fluctuations in an accelerated frame affect the observer in a symmetric
manner. The implications are discussed.


  We consider a generic model of quadratic gravity coupled to a single scalar
and investigate the effects of gravitational degrees of freedom on inflationary
parameters. We find that quantum corrections arising from the massive spin-2
ghost generate significant contributions to the effective inflationary
potential and allow for a realization of the spontaneous breakdown of global
scale invariance without the need for additional scalar fields. We compute
inflationary parameters, compare the resulting predictions to well-known
inflationary models, and find that they fit well within the Planck and
BICEP/Keck collaboration's constraints on inflation.


  We discuss the problem of classifying all local CR diffeomorphisms of a
strictly pseudoconvex surface. Our method exploits the Tanaka--Webster
pseudohermitian invariants, their transformation formulae, and the Chern--Moser
invariants. Our main application concerns a class of generalized ellipsoids
where we classify all local CR mappings.


  We present an alternative approach to decompose non-negative tensors, called
many-body approximation. Traditional decomposition methods assume low-rankness
in the representation, resulting in difficulties in global optimization and
target rank selection. We avoid these problems by energy-based modeling of
tensors, where a tensor and its mode correspond to a probability distribution
and a random variable, respectively. Our model can be globally optimized in
terms of the KL divergence minimization by taking the interaction between
variables (that is, modes), into account that can be tuned more intuitively
than ranks. Furthermore, we visualize interactions between modes as tensor
networks and reveal a nontrivial relationship between many-body approximation
and low-rank approximation. We demonstrate the effectiveness of our approach in
tensor completion and approximation.


  We study the supersymmetric version of the type-II seesaw mechanism assuming
minimal supergravity boundary conditions. We calculate branching ratios for
lepton flavour violating (LFV) scalar tau decays, potentially observable at the
LHC, as well as LFV decays at low energy, such as $l_i \to l_j + \gamma$ and
compare their sensitivity to the unknown seesaw parameters. In the minimal case
of only one triplet coupling to the standard model lepton doublets, ratios of
LFV branching ratios can be related unambigously to neutrino oscillation
parameters. We also discuss how measurements of soft SUSY breaking parameters
at the LHC can be used to indirectly extract information of the seesaw scale.


  The spectrum of $H$-monopoles of the heterotic string compactified on a six
torus and its relationship to the $S$-duality conjecture is briefly reviewed.
It is based on work done in collaboration with J. Harvey and is a contribution
to the proceedings of Strings '95, USC, March 1995.


  In underwater acoustic (UWA) random access communication networks with
multiple users and data packet transmissions, the packet collisions are the
main cause of the network performance degradation. The aim of this paper is to
investigate interference cancellation (IC) techniques capable of resolving such
collisions in a low-complexity modem with single-carrier modulation and single
transducer. More specifically, in this modem, the IC is used at multiple stages
of the receiver. Firstly, the IC is performed for cancelling the multipath
interference to improve the equalization performance in comparison with the
linear equalization and Rake combining. Secondly, the IC removes the
interference from collided data packets within extracted signal segments after
identifying the collisions. Finally, the IC is applied to the received baseband
signal to improve the data packet detection. The modem performance is
investigated in a lake experiment with intensive multipath channels. The
experimental results demonstrate high detection performance of the proposed
modem design and show that the proposed IC techniques can significantly improve
the throughput of random access UWA networks.


  Stochastic Variational Method (SVM) is the generalization of the variation
method to the case with stochastic variables. In the series of papers, we
investigate the applicability of SVM as an alternative field quantization
scheme. Here, we discuss the complex Klein-Gordon equation. In this scheme, the
Euler-Lagrangian equation for the stochastic fields leads to the functional
Schroedinger equation, which in turn can be interpreted as the ideal fluid
equation in the functional space. We show that the Fock state vector is given
by the stationary solution of these differential equations and various results
in the usual canonical quantization can be reproduced, including the effect of
anti-particles. The present formulation is a quantization scheme based on
commutable variables, so that there appears no ambiguity associated with the
ordering of operators, for example, in the definition of Noether charges.


  This is a survey on reverse Carleson measures for various Hilbert spaces of
analytic functions. These spaces include Hardy, Bergman, certain harmonically
weighted Dirichlet, Paley-Wiener, Fock, model, and de Branges-Rovnyak spaces.


  The thermodynamic uncertainty relation is a prominent result in stochastic
thermodynamics that provides a bound on the fluctuations of any thermodynamic
flux, also known as current, in terms of the average rate of entropy
production. Such fluctuations are quantified by the second moment of the
probability distribution of the current. The role of higher order standardized
moments such as skewness and kurtosis remains largely unexplored. We analyze
the skewness and kurtosis associated with the first passage time of
thermodynamic currents within the framework of stochastic thermodynamics. We
develop a method to evaluate higher order standardized moments associated with
the first passage time of any current. For systems with a unicyclic network of
states, we conjecture upper and lower bounds on skewness and kurtosis
associated with entropy production. These bounds depend on the number of states
and the thermodynamic force that drives the system out of equilibrium. We show
that these bounds for skewness and kurtosis do not hold for multicyclic
networks. We discuss the application of our results to infer an underlying
network of states.


  In supervised deep learning, learning good representations for
remote--sensing images (RSI) relies on manual annotations. However, in the area
of remote sensing, it is hard to obtain huge amounts of labeled data. Recently,
self--supervised learning shows its outstanding capability to learn
representations of images, especially the methods of instance discrimination.
Comparing methods of instance discrimination, clustering--based methods not
only view the transformations of the same image as ``positive" samples but also
similar images. In this paper, we propose a new clustering-based method for
representation learning. We first introduce a quantity to measure
representations' discriminativeness and from which we show that even
distribution requires the most discriminative representations. This provides a
theoretical insight into why evenly distributing the images works well. We
notice that only the even distributions that preserve representations'
neighborhood relations are desirable. Therefore, we develop an algorithm that
translates the outputs of a neural network to achieve the goal of evenly
distributing the samples while preserving outputs' neighborhood relations.
Extensive experiments have demonstrated that our method can learn
representations that are as good as or better than the state of the art
approaches, and that our method performs computationally efficiently and
robustly on various RSI datasets.


  We study a class of representations of the Lie algebra of Laurent polynomials
with values in the nilpotent subalgebra of sl(3). We derive Weyl-type (bosonic)
character formulas for these representations. We establish a connection between
the bosonic formulas and the Whittaker vector in the Verma module for the
quantum group $U_v sl(3)$. We also obtain a fermionic formula for an
eigenfunction of the sl(3) quantum Toda Hamiltonian.


  While automatic dialogue tutors hold great potential in making education
personalized and more accessible, research on such systems has been hampered by
a lack of sufficiently large and high-quality datasets. Collecting such
datasets remains challenging, as recording tutoring sessions raises privacy
concerns and crowdsourcing leads to insufficient data quality. To address this,
we propose a framework to generate such dialogues by pairing human teachers
with a Large Language Model (LLM) prompted to represent common student errors.
We describe how we use this framework to collect MathDial, a dataset of 3k
one-to-one teacher-student tutoring dialogues grounded in multi-step math
reasoning problems. While models like GPT-3 are good problem solvers, they fail
at tutoring because they generate factually incorrect feedback or are prone to
revealing solutions to students too early. To overcome this, we let teachers
provide learning opportunities to students by guiding them using various
scaffolding questions according to a taxonomy of teacher moves. We demonstrate
MathDial and its extensive annotations can be used to finetune models to be
more effective tutors (and not just solvers). We confirm this by automatic and
human evaluation, notably in an interactive setting that measures the trade-off
between student solving success and telling solutions. The dataset is released
publicly.


  We establish dimension-free stability of Webb's sharp simplex slicing (1996).
Incidentally, we investigate Lipschitzness of volume of hyperplane central
sections of arbitrary convex bodies.


  Scalar-isoscalar states are analyzed within the large-Nc Regge approach. We
find that the lightest f0(600) scalar-isoscalar state fits very well into the
pattern of the radial Regge trajectory. We confirm the obtained mass values
from an analysis of the pion and nucleon spin-0 gravitational form factors,
recently measured on the lattice. We find that a simple two-state model
suggests a meson nature of f0(600), and a glueball nature of f0(980), which
naturally explains the ratios of various coupling constants. Finally, matching
to the OPE requires a fine-tuned mass condition of the vanishing dimension-2
condensate in the Regge approach with infinitely many scalar-isoscalar states.


  Present study provides a comprehensive theoretical analysis of the
superconducting phase in selected lithium-decorated bilayer graphene
nanostructures. The numerical calculations, conducted within the Eliashberg
formalism, give quantitative estimations of the most important thermodynamic
properties such as the critical temperature, specific heat, critical field and
others. It is shown that discussed lithium-graphene systems present enhancement
of their thermodynamic properties comparing to the monolayer case e.g. the
critical temperature can be raised to $\sim 15$ K. Furthermore, estimated
characteristic thermodynamic ratios exceed predictions of the
Bardeen-Cooper-Schrieffer theory suggesting that considered lithium-graphene
systems can be properly analyzed only within the strong-coupling regime.


  Using the high-quality observations of the Solar Dynamics Observatory, we
present the interaction of two filaments (F1 and F2) in a long filament channel
associated with twin coronal mass ejections (CMEs) on 2016 January 26. Before
the eruption, a sequence of rapid cancellation and emergence of the magnetic
flux has been observed, which likely triggered the ascending of the west
filament (F1). The east footpoints of rising F1 moved toward the east far end
of the filament channel, accompanying with post-eruption loops and flare
ribbons. It likely indicated a large-scale eruption involving the long filament
channel, resulted from the interaction between F1 and the east filament (F2).
Some bright plasma flew over F2, and F2 stayed at rest during the eruption,
likely due to the confinement of its overlying lower magnetic field.
Interestingly, the impulsive F1 pushed its overlying magnetic arcades to form
the first CME, and F1 finally evolved into the second CME after the collision
with the nearby coronal hole. We suggest that the interaction of F1 and the
overlying magnetic field of F2 led to the merging reconnection that form a
longer eruptive filament loop. Our results also provide a possible picture of
the origin of twin CMEs, and show the large-scale magnetic topology of the
coronal hole is important for the eventual propagation direction of CMEs.


  We present the theory of the k-core pruning process (progressive removal of
nodes with degree less than k) in uncorrelated random networks. We derive exact
equations describing this process and the evolution of the network structure,
and solve them numerically and, in the critical regime of the process,
analytically. We show that the pruning process exhibits three different
behaviors depending on whether the mean degree <q> of the initial network is
above, equal to, or below the threshold <q>_c corresponding to the emergence of
the giant k-core. We find that above the threshold the network relaxes
exponentially to the k-core. The system manifests the phenomenon known as
"critical slowing down", as the relaxation time diverges when <q> tends to
<q>_c. At the threshold, the dynamics become critical characterized by a
power-law relaxation (1/t^2). Below the threshold, a long-lasting transient
process (a "plateau" stage) occurs. This transient process ends with a collapse
in which the entire network disappears completely. The duration of the process
diverges when <q> tends to <q>_c. We show that the critical dynamics of the
pruning are determined by branching processes of spreading damage. Clusters of
nodes of degree exactly k are the evolving substrate for these branching
processes. Our theory completely describes this branching cascade of damage in
uncorrelated networks by providing the time dependent distribution function of
branching. These theoretical results are supported by our simulations of the
$k$-core pruning in Erdos-Renyi graphs.


  Liquid water at ambient temperature displays ultrafast molecular motions and
concomitant fluctuations of very strong electric fields originating from the
dipolar H2O molecules. We show that such random intermolecular fields induce
tunnel ionization of water molecules, which becomes irreversible if an external
terahertz (THz) pulse imposes an additional directed electric field on the
liquid. Time-resolved nonlinear THz spectroscopy maps charge separation,
transport and localization of the released electrons on a few-picosecond time
scale. The highly polarizable localized electrons modify the THz absorption
spectrum and refractive index of water, a manifestation of a highly nonlinear
response. Our results demonstrate how the interplay of local electric field
fluctuations and external electric fields allows for steering charge dynamics
and dielectric properties in aqueous systems.


  We present a new determination of the Cabibbo-Kobayashi-Maskawa matrix
element $|V_{\rm cb}|$ by using the three-loop perturbative QCD corrections for
the $B\to D^{\ast}$ semi-leptonic decay. The decay width of $B\to D^{\ast}$
semi-leptonic decay can be factorized as perturbatively calculable
short-distance part and the non-perturbative but universal long-distance part.
We adopt the principle of maximum conformality (PMC) single-scale setting
approach to deal with the perturbative series so as to achieve a precise
fixed-order prediction for the short-distance parameter $\eta_{A}$. By applying
the PMC, an overall effective $\alpha_s$ value is achieved by recursively using
the renormalization group equation, which inversely results in a precise
scale-invariant pQCD series. Such scale-invariant series also provides a
reliable basis for predicting the contributions from uncalculated perturbative
terms. We then obtain $\eta_{A}=0.9225^{+0.0117}_{-0.0168}$, where the error is
the squared average of those from $\Delta\alpha_{s}(M_Z)=\pm0.0010$ and the
uncertainties caused by the uncalculated higher-order perturbative terms. By
using the data of $B\to D^{\ast}\ell\bar{\nu}_{\ell}$, we finally obtain
$|V_{\rm cb}|_{\rm PMC} =(40.60^{+0.53}_{-0.57})\times10^{-3}$, which is
consistent with the PDG value within errors.


  The mass of a sphere of simmetry in the Lemaitre universe is discussed using
the Hawking-Hayward quasi-local energy and clarifying existing ambiguities. A
covariantly conserved current introduced by Cahill and McVittie is shown to be
a multiple of the Kodama energy current.


  Integrated fiducial cross sections for the production of four leptons via the
H to 4l decays (l = e, mu) are measured in pp collisions at sqrt(s) = 7 and 8
TeV. Measurements are performed with data corresponding to integrated
luminosities of 5.1 inverse femtobarns at 7 TeV, and 19.7 inverse femtobarns at
8 TeV, collected with the CMS experiment at the LHC. Differential cross
sections are measured using the 8 TeV data, and are determined as functions of
the transverse momentum and rapidity of the four-lepton system, accompanying
jet multiplicity, transverse momentum of the leading jet, and difference in
rapidity between the Higgs boson candidate and the leading jet. A measurement
of the Z to 4l cross section, and its ratio to the H to 4l cross section is
also performed. All cross sections are measured within a fiducial phase space
defined by the requirements on lepton kinematics and event topology. The
integrated H to 4l fiducial cross section is measured to be 0.56 +0.67-0.44
(stat) +0.21-0.06 (syst) fb at 7 TeV, and 1.11 +0.41-0.35 (stat) +0.14-0.10
(syst) fb at 8 TeV. The measurements are found to be compatible with
theoretical calculations based on the standard model.


  Photoproduction of $\pi^0\pi^{\pm}$-pairs from quasifree nucleons bound in
the deuteron has been investigated to study the helicity dependence of this
reaction. Measurements with a liquid deuterium target were used to extract the
unpolarized cross sections for reactions on protons and neutrons. A deuterated,
longitudinally polarized solid-butanol target, together with a circularly
polarized photon beam, determined the double polarization observable $E$. From
these results the spin-dependent cross sections $\sigma_{1/2}$ and
$\sigma_{3/2}$, corresponding to the anti-parallel and parallel spin
configurations of the beam photon and target nucleon, have been derived. The
measurements were performed at the Mainz MAMI accelerator with tagged,
circularly-polarized photon beams produced via bremsstrahlung from
longitudinally polarized electron beams. The reaction products were detected
with an almost $4\pi$ solid-angle covering calorimeter composed of the Crystal
Ball and TAPS detectors, supplemented by plastic scintillation detectors for
charged particle identification. The results are sensitive to sequential decays
of nucleon resonances via intermediate states and also to the decay of nucleon
resonances by emission of charged $\rho$ mesons, and are compared to recent
model results.


  Using the sunflower method, we show that if $\theta \in (0,1) \cap
\mathbb{Q}$ and $\mathcal{F}$ is a $O(n^{1/3})$-bounded $\theta$-intersecting
family over $[n]$, then $\lvert \mathcal{F} \rvert = O(n)$, and that if
$\mathcal{F}$ is $o(n^{1/3})$-bounded, then $\lvert \mathcal{F} \rvert \leq
(\frac{3}{2} + o(1))n$. This partially solves a conjecture raised in
(Balachandran et al., Electron J. Combin. 26 (2019), #P2.40) that any
$\theta$-intersecting family over $[n]$ has size at most linear in $n$, in the
regime where we have no very large sets.


  The "polyhedral product functor" produces a space from a simplicial complex L
and a collection of pairs of spaces, {(A(i),B(i))}, where i ranges over the
vertex set of L. We give necessary and sufficient conditions for the resulting
space to be aspherical. There are two similar constructions, each of which
starts with a space X and a collection of subspaces, {X_i} and then produces a
new space. We give conditions for the results of these constructions to be
aspherical. All three techniques can be used to produce examples of closed
aspherical manifolds.
  Abstract for Corrigenda: This note concerns two refinements to the earlier
work by the first author. First, when L is infinite, the definition of
polyhedral product needs clarification. Second, the earlier paper omitted some
subtle parts of the necessary and sufficient conditions for polyhedral products
to be aspherical. Correct versions of these necessary and sufficient conditions
are given in the present paper.


  This book consists of material originally appearing in the Problem Section of
the journal Topology Proceedings since 1976 as well as some other well-known
problem lists in general topology from the 1970's that have some connection to
the journal. The problems have been updated with current information on
solutions with bibliographic references. In particular, the book features these
collections: All contributed problems to the Problem Section, classified by
subject; Eight Classic Problems by Peter J. Nyikos, including information from
the two recent articles Twenty-five years later; New Classic Problems from
1990; Problems from Mary Ellen Rudin's Lecture notes in set-theoretic topology
(1975/7); Problems from A.V. Arhangelskii's Structure and classification of
topological spaces and cardinal invariants (1978); Continuum theory problems by
Wayne Lewis (1983); Problems in continuum theory by Janusz R. Prajs, including
essays by Charles L. Hagopian and Janusz J. Charatonik; Classification of
homogeneous continua by James T. Rogers, Jr., including material from survey
articles of 1983 and 1989.


  Pyramid schemes are investment scams in which top-level participants in a
hierarchical network recruit and profit from an expanding base of defrauded
newer participants. Pyramid schemes have existed for over a century, but there
have been no in-depth studies of their dynamics and communities because of the
opacity of participants' transactions.
  In this paper, we present an empirical study of Forsage, a pyramid scheme
implemented as a smart contract and at its peak one of the largest consumers of
resources in Ethereum. As a smart contract, Forsage makes its (byte)code and
all of its transactions visible on the blockchain. We take advantage of this
unprecedented transparency to gain insight into the mechanics, impact on
participants, and evolution of Forsage.
  We quantify the (multi-million-dollar) gains of top-level participants as
well as the losses of the vast majority (around 88%) of users. We analyze
Forsage code both manually and using a purpose-built transaction simulator to
uncover the complex mechanics of the scheme. Through complementary study of
promotional videos and social media, we show how Forsage promoters have
leveraged the unique features of smart contracts to lure users with false
claims of trustworthiness and profitability, and how Forsage activity is
concentrated within a small number of national communities.


  It is shown that the influence of the undulator field on the motion of a
relativistic electron leads to a significant increase of the bremsstrahlung
cross section on an atom near the end of the spectrum of undulator radiation.
Observation of this effect is quite a realistic task.


  A stellar system is dynamically hot when its kinetic energy is dominated by
random motion represented by the velocity dispersion $\sigma_{\rm hot} (M_*)$.
We use MaNGA data to obtain inner and outer dispersion of a galaxy,
$\sigma_{\rm in}$ and $\sigma_{\rm out}$, to characterize its dynamical status
and study its connection with star formation quenching and the growth of
supermassive black hole (SMBH). We divide galaxies into fully quenched (FQGs),
partially quenched (PQGs) and fully star-forming (FSGs) populations, and
identify quenched central cores (QCCs) in PQGs. The galaxy distribution in
$\sigma_{\rm in}/\sigma_{\rm hot}$-$\sigma_{\rm out}/\sigma_{\rm hot}$ diagram
is L-shaped, consisting of a horizontal sequence ($\sigma_{\rm out}/\sigma_{\rm
hot}\sim0$) and a vertical sequence ($\sigma_{\rm in}/\sigma_{\rm hot}\sim1$).
FQGs and QCCs are located at the top of vertical sequence, $\sigma_{\rm
out}/\sigma_{\rm hot}\sim1$, therefore they are dynamically hot over their
entire bodies. PQGs reside along vertical sequence, so they have hot center but
cold outskirt. FSGs are diverse and can be found in both sequences. Galaxy
structural properties, star formation and AGN activities make a transition
along horizontal sequence at $\log(\sigma_{\rm in}/\sigma_{\rm hot})\sim-0.3$,
and along vertical sequence at $\log(\sigma_{\rm out}/\sigma_{\rm
hot})\sim-0.3$. The fractions of optical AGNs and barred galaxies increase
rapidly in the first transition and decline rapidly in the second; radio
galaxies are located at the top of vertical sequence. Our results demonstrate
that star formation quenching and SMBH growth are effective only in dynamically
hot systems. A simple model along this line can reproduce the observed SMBH
scaling relations. We discuss how secular processes and strong interactions can
make a system dynamically hot, and lead to the SMBH growth and star formation
quenching.


  We have studied the magnetism of the Pr3+ ions in PrFeAsO_1-xF_x (x = 0;
0.15) and its interaction with the Fe magnetic order (for x = 0). Specific heat
data confirm the presence of a first excited crystal electric field (CEF) level
around 3.5 meV in the undoped compound PrFeAsO. This finding is in agreement
with recent neutron scattering experiments. The doped compound is found to have
a much lower first CEF splitting of about 2.0 meV. The Pr ordering in PrFeAsO
gives rise to large anomalies in the specific heat and the thermal expansion
coefficient. In addition, a field-induced transition is found at low
temperatures that is most pronounced for the magnetostriction coefficient. This
transition, which is absent in the doped compound, is attributed to a reversal
of the Fe spin canting as the antiferromagnetic Pr order is destroyed by the
external magnetic field.


  We develop a universal framework which allows quickly solve a wide class of
problems for longitudinal space charge effects in beams and plasmas in
cylindrical geometry. We introduce the longitudinal dielectric permittivity for
the beam of charged particles, which describes its collective space charge
response. The analyis yields an effective plasma frequency, which depends on
the transverse geometry of the system. This dielectric permittivity mirrors the
dielectric permittivity of plasma and matches the one dimensional (1D)
expression once the transverse size of the beam is large. Several particle
species can be included as additive terms describing susceptibility of each
specie. The developed approach allows to study stability criteria for
collective beam-beam and beam-plasma instabilities for arbitrary transverse
distributions in particle densities.


  In recent years, understanding the implicit regularization of neural networks
(NNs) has become a central task in deep learning theory. However, implicit
regularization is itself not completely defined and well understood. In this
work, we attempt to mathematically define and study implicit regularization.
Importantly, we explore the limitations of a common approach to characterizing
implicit regularization using data-independent functions. We propose two
dynamical mechanisms, i.e., Two-point and One-point Overlapping mechanisms,
based on which we provide two recipes for producing classes of
one-hidden-neuron NNs that provably cannot be fully characterized by a type of
or all data-independent functions. Following the previous works, our results
further emphasize the profound data dependency of implicit regularization in
general, inspiring us to study in detail the data dependency of NN implicit
regularization in the future.


  Traditional methods for solvability region analysis can only have inner
approximations with inconclusive conservatism. Machine learning methods have
been proposed to approach the real region. In this letter, we propose a deep
active learning framework for power system solvability prediction. Compared
with the passive learning methods where the training is performed after all
instances are labeled, the active learning selects most informative instances
to be label and therefore significantly reduce the size of labeled dataset for
training. In the active learning framework, the acquisition functions, which
correspond to different sampling strategies, are defined in terms of the
on-the-fly posterior probability from the classifier. The IEEE 39-bus system is
employed to validate the proposed framework, where a two-dimensional case is
illustrated to visualize the effectiveness of the sampling method followed by
the full-dimensional numerical experiments.


  We present a complete calculation of the electroweak one-loop corrections to
the relic density within the MSSM framework. In the context of the neutralino
as dark matter candidate, we review different scenarios of annihilation and
coannihilation with a chargino. In particular we investigate predictions for
the annihilation into gauge boson pairs for different kinds of neutralino:
bino-, wino- and higgsino-like. We present some interesting effects which are
not present at tree-level and show up at one-loop. To deal with the large
number of diagrams occuring in the calculations, we have developed an automatic
tool for the computation at one-loop of any process in the MSSM. We have
implemented a complete on-shell gauge invariant renormalization scheme, with
the possibility of switching to other schemes. We emphasize the variations due
to the choice of the renormalization scheme, in particular the one-loop
definition of the parameter tan(beta).


  The linear complexity and k-error linear complexity of a sequence have been
used as important measures of keystream strength, hence designing a sequence
with high linear complexity and $k$-error linear complexity is a popular
research topic in cryptography. In this paper, the concept of stable $k$-error
linear complexity is proposed to study sequences with stable and large
$k$-error linear complexity. In order to study k-error linear complexity of
binary sequences with period $2^n$, a new tool called cube theory is developed.
By using the cube theory, one can easily construct sequences with the maximum
stable $k$-error linear complexity. For such purpose, we first prove that a
binary sequence with period $2^n$ can be decomposed into some disjoint cubes
and further give a general decomposition approach. Second, it is proved that
the maximum $k$-error linear complexity is $2^n-(2^l-1)$ over all
$2^n$-periodic binary sequences, where $2^{l-1}\le k<2^{l}$. Thirdly, a
characterization is presented about the $t$th ($t>1$) decrease in the $k$-error
linear complexity for a $2^n$-periodic binary sequence $s$ and this is a
continuation of Kurosawa et al. recent work for the first decrease of k-error
linear complexity. Finally, A counting formula for $m$-cubes with the same
linear complexity is derived, which is equivalent to the counting formula for
$k$-error vectors. The counting formula of $2^n$-periodic binary sequences
which can be decomposed into more than one cube is also investigated, which
extends an important result by Etzion et al..


  We present an investigation of different thin-film evaporated ferromagnetic
materials for their suitability as electrodes in individual single-wall and
multi-wall carbon nanotube-based spin devices. Various electrode shapes made
from permalloy (Ni_{81}Fe_{19}), the diluted ferromagnet PdFe, and PdFe/Fe
bilayers are studied for both their micromagnetic properties and their contact
formation to carbon nanotubes. Suitable devices are tested in low-temperature
electron transport measurements, displaying the typical tunneling
magnetoresistance of carbon nanotube pseudo spin valves.


  We present an effective harmonic density interpolation method for the
numerical evaluation of singular and nearly singular Laplace boundary integral
operators and layer potentials in two and three spatial dimensions. The method
relies on the use of Green's third identity and local Taylor-like
interpolations of density functions in terms of harmonic polynomials. The
proposed technique effectively regularizes the singularities present in
boundary integral operators and layer potentials, and recasts the latter in
terms of integrands that are bounded or even more regular, depending on the
order of the density interpolation. The resulting boundary integrals can then
be easily, accurately, and inexpensively evaluated by means of standard
quadrature rules. A variety of numerical examples demonstrate the effectiveness
of the technique when used in conjunction with the classical trapezoidal rule
(to integrate over smooth curves) in two-dimensions, and with a Chebyshev-type
quadrature rule (to integrate over surfaces given as unions of non-overlapping
quadrilateral patches) in three-dimensions.


  The space $\widehat{\ell }_k$ of absolutely almost convergent series was
introduced and studied by Das et al [4]; which plays an important role in
summability theory, approximation theory, Fourier analysis, etc. In the present
paper we generalize the space making use of some factors and weighted mean
transformations, investigate its topological structures and relations between
classical sequence spaces. Also we characterize certain matrix operators on it.


  The probability density is a fundamental quantity for characterizing
diffusion processes. However, it is seldom known except in a few renowned
cases, including Brownian motion and the Ornstein-Uhlenbeck process and their
bridges, geometric Brownian motion, Brownian excursion, or Bessel processes. In
this paper, we utilize Girsanov's theorem, along with a variation of the method
of images, to derive the exact expression of the probability density for
diffusions that have one entrance boundary. Our analysis encompasses numerous
families of conditioned diffusions, including the Taboo process and Brownian
motion conditioned on its growth behavior, as well as the drifted Brownian
meander and generalized Brownian excursion.


  We propose a new discretization method for PDEs on moving domains in the
setting of unfitted finite element methods, which is provably higher-order
accurate in space and time. In the considered setting, the physical domain that
evolves essentially arbitrarily through a time-independent computational
background domain, is represented by a level set function. For the time
discretization, the application of standard time stepping schemes that are
based on finite difference approximations of the time derivative is not
directly possible, as the degrees of freedom may get active or inactive across
such a finite difference stencil in time. In [Lehrenfeld, Olshanskii. An
Eulerian finite element method for PDEs in time-dependent domains. ESAIM: M2AN,
53:585--614, 2019] this problem is overcome by extending the discrete solution
at every timestep to a sufficiently large neighborhood so that all the degrees
of freedom that are relevant at the next time step stay active. But that paper
focuses on low-order methods. We advance these results with introducing and
analyzing realizable techniques for the extension to higher order. To obtain
higher-order convergence in space and time, we combine the BDF time stepping
with the isoparametric unfitted FEM. The latter has been used and analyzed for
several stationary problems before. However, for moving domains the key
ingredient in the method, the transformation of the underlying mesh, becomes
time-dependent which gives rise to some technical issues. We treat these with
special care, carry out an a priori error analysis and two numerical
experiments.


  We explore use of the harmonic Einstein equations to numerically find
stationary black holes where the problem is posed on an ingoing slice that
extends into the interior of the black hole. Requiring no boundary conditions
at the horizon beyond smoothness of the metric, this method may be applied for
horizons that are not Killing. As a non-trivial illustration we find black
holes which, via AdS-CFT, describe a time-independent CFT plasma flowing
through a static spacetime which asymptotes to Minkowski in the flow's past and
future, with a varying spatial geometry in-between. These are the first
explicit examples of stationary black holes which do not have Killing horizons.
When the CFT spacetime slowly varies, the CFT stress tensor derived from
gravity is well described by viscous hydrodynamics. For fast variation it is
not, and the solutions are stationary analogs of dynamical quenches, with the
plasma being suddenly driven out of equilibrium. We find evidence these flows
become unstable for sufficiently strong quenches, and speculate the instability
may be turbulent.


  This paper studies the statistical nature of TV channels streaming variable
bit rate distribution and allocation. The goal of the paper is to derive the
best-fit rate distribution to describe TV streaming bandwidth allocation, which
can reveal traffic demands of users. Our analysis uses multiplexers channel
bandwidth allocation (PID) data of 13 TV live channels. We apply 17 continuous
and 3 discrete distributions to determine the best-fit distribution function
for each individual channel and for the whole set of channels. We found that
the generalized extreme distribution fitting most of our channels most
precisely according to the Bayesian information criterion. By the same
criterion tlocationscale distribution matches best for the whole system. We use
these results to propose parameters for streaming server queuing model. Results
are useful for streaming servers scheduling policy design process targeting to
improve limited infrastructural resources, traffic engineering through dynamic
routing at CDN, SDN.


  When two different parties use the same learning rule on their own data, how
can we test whether the distributions of the two outcomes are similar? In this
paper, we study the similarity of outcomes of learning rules through the lens
of the Total Variation (TV) distance of distributions. We say that a learning
rule is TV indistinguishable if the expected TV distance between the posterior
distributions of its outputs, executed on two training data sets drawn
independently from the same distribution, is small. We first investigate the
learnability of hypothesis classes using TV indistinguishable learners. Our
main results are information-theoretic equivalences between TV
indistinguishability and existing algorithmic stability notions such as
replicability and approximate differential privacy. Then, we provide
statistical amplification and boosting algorithms for TV indistinguishable
learners.


  The Kronecker polynomial $K(z)$ is a finite product of cyclotomic polynomials
$C_j(z)$. Any Kronecker polynomial $K(z)$ of degree $N+1$ with simple roots on
the unit circle generates a finite set $\Phi_0=1, \Phi_1(z), \dots, \Phi_N(z) $
of polynomials (para) orthogonal on the unit circle (POPUC). This set is
determined uniquely by the condition $\Phi_N(z) = (N+1)^{-1} K'(z)$. Such set
can be called the set of Sturmian Kronecker POPUC. We present several new
explicit examples of such POPUC. In particular, we define and analyze
properties of the Sturmian cyclotomic POPUC generated by the cyclotomic
polynomials $C_M(z)$. Expressions of these polynomials strongly depend on the
decomposition of $M$ into prime factors.


  We study world-volume effective theories of five-branes in type II string
theories. We determine the bosonic zero-modes of the NS5-brane, the
Kaluza-Klein monopole, the exotic Q5-, R5-branes and a space-filling brane, by
direct calculations within the formalism of double field theory (DFT). We show
that these zero-modes are Nambu-Goldstone modes associated with the
spontaneously broken gauge symmetries in DFT. They are organized into the
bosonic part of the six-dimensional $\mathcal{N} = (1,1)$ vector and the
$\mathcal{N} = (2,0)$ tensor multiplets. Among other things, we examine the
locally non-geometric R5-branes and space-filling branes that are characterized
by the winding space. We also study effective theories of five-branes with
string worldsheet instanton corrections.


  Much recent work in physics education research has focused on ontological
metaphors for energy, particularly the substance ontology and its pedagogical
affordances. The concept of negative energy problematizes the substance
ontology for energy, but in many instructional settings, the specific
difficulties around negative energy are outweighed by the general advantages of
the substance ontology. However, we claim that our interdisciplinary setting (a
physics class that builds deep connections to biology and chemistry) leads to a
different set of considerations and conclusions. In a course designed to draw
interdisciplinary connections, the centrality of chemical bond energy in
biology necessitates foregrounding negative energy from the beginning. We argue
that the emphasis on negative energy requires a combination of substance and
location ontologies. The location ontology enables energies both "above" and
"below" zero. We present preliminary student data that illustrate difficulties
in reasoning about negative energy, and the affordances of the location
metaphor.


  We use Multi Unit Spectroscopic Explorer (MUSE) observations of the galaxy
cluster MACS J1149.5+2223 to explore the kinematics of the grand-design spiral
galaxy Sp1149 hosting the SN Refsdal. Sp1149 lies at $z\simeq1.49$, has a
stellar mass $M_*\simeq5\times10^9 \, \mathrm{M_\odot}$, a star-formation rate
$\mathrm{SFR} \simeq1-6 \, \mathrm{M_\odot/yr}$ and represents a likely
progenitor of a Milky-Way-like galaxy. All the four multiple images of Sp1149
in our data show strong OII-line emissions pointing to a clear rotation
pattern. We take advantage of the gravitational lensing magnification effect
($\simeq 4 \times$) on the OII emission of the least distorted image to fit 3D
kinematic models to the MUSE data-cube and derive the rotation curve and the
velocity dispersion profile of Sp1149. We find that the rotation curve steeply
rises, peaks at $R\simeq1$ kpc and then (initially) declines and flattens to an
average $V_\mathrm{flat} = 128^{+29}_{-19}$ km/s. The shape of the rotation
curve is well determined but the actual value of $V_\mathrm{flat}$ is quite
uncertain because of the nearly face-on configuration of the galaxy. The
intrinsic velocity dispersion due to gas turbulence is almost constant across
the entire disc with an average of $27\pm5$ km/s. This value is consistent with
$z=0$ measurements in the ionized gas component and a factor 2-4 lower than
other estimates in different galaxies at similar redshifts. The average
stellar-to-total mass fraction is of the order of one fifth. Our kinematic
analysis returns the picture of a regular star-forming, mildly turbulent,
rotation-dominated ($V / \sigma\simeq5$) spiral galaxy in a 4 Gyr old Universe.


  Novikov's conjecture on the Riemann-Schottky problem: {\it the Jacobians of
smooth algebraic curves are precisely those indecomposable principally
polarized abelian varieties (ppavs) whose theta-functions provide solutions to
the Kadomtsev-Petviashvili (KP) equation}, was the first evidence of nowadays
well-established fact: connections between the algebraic geometry and the
modern theory of integrable systems is beneficial for both sides.
  The purpose of this paper is twofold. Our first goal is to present a proof of
the strongest known characterization of a Jacobian variety in this direction:
{\it an indecomposable ppav $X$ is the Jacobian of a curve if and only if its
Kummer variety $K(X)$ has a trisecant line} and the solution of the
characterization problem of principally polarized Prym varieties. The latter
problem is almost as old and famous as the Riemann-Schottky problem but is much
harder. In some sense the Prym varieties may be geometrically the
easiest-to-understand ppavs beyond Jacobians, and studying them may be a first
step towards understanding the geometry of more general abelian varieties as
well.
  Our second and primary objective is to take this opportunity to elaborate on
motivations underlining the proposed solution of the Riemann-Schottky problem,
to introduce a certain circle of ideas and methods, developed in the theory of
soliton equations, and to convince the reader that they are algebro-geometric
in nature, simple and universal enough to be included in the Handbook of
moduli.


  Transfer learning (TL) approaches have shown promising results when handling
tasks with limited training data. However, considerable memory and
computational resources are often required for fine-tuning pre-trained neural
networks with target domain data. In this work, we introduce a novel method for
leveraging pre-trained models for low-resource (music) classification based on
the concept of Neural Model Reprogramming (NMR). NMR aims at re-purposing a
pre-trained model from a source domain to a target domain by modifying the
input of a frozen pre-trained model. In addition to the known,
input-independent, reprogramming method, we propose an advanced reprogramming
paradigm: Input-dependent NMR, to increase adaptability to complex input data
such as musical audio. Experimental results suggest that a neural model
pre-trained on large-scale datasets can successfully perform music genre
classification by using this reprogramming method. The two proposed
Input-dependent NMR TL methods outperform fine-tuning-based TL methods on a
small genre classification dataset.


  Compact binaries inspiralling along eccentric orbits are plausible
gravitational wave (GW) sources for the ground-based laser interferometers. We
explore the losses in the event rates incurred when searching for GWs from
compact binaries inspiralling along post-Newtonian accurate eccentric orbits
with certain obvious non-optimal search templates. For the present analysis, GW
signals having 2.5 post-Newtonian accurate orbital evolution are modeled
following the phasing formalism, presented in [T. Damour, A. Gopakumar, and B.
R. Iyer, Phys. Rev. D \textbf{70}, 064028 (2004)]. We demonstrate that the
search templates that model in a gauge-invariant manner GWs from compact
binaries inspiralling under qudrupolar radiation reaction along 2PN accurate
circular orbits are very efficient in capturing our somewhat realistic GW
signals. However, three types of search templates based on the adiabatic,
complete adiabatic and gauge-dependent complete non-adiabatic approximants,
detailed in [P. Ajith, B. R. Iyer, C. A. K. Robinson and B. S. Sathyaprakash,
%``A new class of post-Newtonian approximants to the dynamics of inspiralling
%compact binaries: Test-mass in the Schwarzschild spacetime,'' Phys. Rev. D
{\bf 71}, 044029 (2005)], relevant for the circular inspiral under the
qudrupolar radiation reaction were found to be inefficient in capturing the
above mentioned eccentric signal. We conclude that further investigations will
be required to probe the ability of various types of PN accurate circular
templates, employed to analyze the LIGO/VIRGO data, to capture GWs from compact
binaries having tiny orbital eccentricities.


  The lack of open-source tools for hyperspectral data visualization and
analysiscreates a demand for new tools. In this paper we present the new
PlanetServer,a set of tools comprising a web Geographic Information System
(GIS) and arecently developed Python Application Programming Interface (API)
capableof visualizing and analyzing a wide variety of hyperspectral data from
differentplanetary bodies. Current WebGIS open-source tools are evaluated in
orderto give an overview and contextualize how PlanetServer can help in this
mat-ters. The web client is thoroughly described as well as the datasets
availablein PlanetServer. Also, the Python API is described and exposed the
reason ofits development. Two different examples of mineral characterization of
differenthydrosilicates such as chlorites, prehnites and kaolinites in the Nili
Fossae areaon Mars are presented. As the obtained results show positive outcome
in hyper-spectral analysis and visualization compared to previous literature,
we suggestusing the PlanetServer approach for such investigations.


  Transfer learning with pre-training on large-scale datasets has played an
increasingly significant role in computer vision and natural language
processing recently. However, as there exist numerous application scenarios
that have distinctive demands such as certain latency constraints and
specialized data distributions, it is prohibitively expensive to take advantage
of large-scale pre-training for per-task requirements. In this paper, we focus
on the area of object detection and present a transfer learning system named
GAIA, which could automatically and efficiently give birth to customized
solutions according to heterogeneous downstream needs. GAIA is capable of
providing powerful pre-trained weights, selecting models that conform to
downstream demands such as latency constraints and specified data domains, and
collecting relevant data for practitioners who have very few datapoints for
their tasks. With GAIA, we achieve promising results on COCO, Objects365, Open
Images, Caltech, CityPersons, and UODB which is a collection of datasets
including KITTI, VOC, WiderFace, DOTA, Clipart, Comic, and more. Taking COCO as
an example, GAIA is able to efficiently produce models covering a wide range of
latency from 16ms to 53ms, and yields AP from 38.2 to 46.5 without whistles and
bells. To benefit every practitioner in the community of object detection, GAIA
is released at https://github.com/GAIA-vision.


  In this paper we define an addition operation on the class of quasi-concave
functions. While the new operation is similar to the well-known
sup-convolution, it has the property that it polarizes the Lebesgue integral.
This allows us to define mixed integrals, which are the functional analogs of
the classic mixed volumes.
  We extend various classic inequalities, such as the Brunn-Minkowski and the
Alexandrov-Fenchel inequality, to the functional setting. For general
quasi-concave functions, this is done by restating those results in the
language of rearrangement inequalities. Restricting ourselves to log-concave
functions, we prove generalizations of the Alexandrov inequalities in a more
familiar form.


  We consider the Schr\"odinger operator on $[0,1]$ with potential in $L^1$. We
prove that two potentials already known on $[a,1]$ ($a\in(0,{1/2}]$) and having
their difference in $L^p$ are equal if the number of their common eigenvalues
is sufficiently large. The result here is to write down explicitly this number
in terms of $p$ (and $a$) showing the role of $p$.


  We study, by means of the density-matrix renormalization group (DMRG)
technique, the evolution of the ground state in a one-dimensional topological
insulator, from the non-interacting to the strongly-interacting limit, where
the system can be mapped onto a topological Kondo-insulator model. We focus on
a toy model Hamiltonian (i.e., the interacting "$sp$-ladder" model), which
could be experimentally realized in optical lattices with higher orbitals
loaded with ultra-cold fermionic atoms. Our goal is to shed light on the
emergence of the strongly-interacting ground state and its topological
classification as the Hubbard-$U$ interaction parameter of the model is
increased. Our numerical results show that the ground state can be generically
classified as a symmetry-protected topological phase of the Haldane-type, even
in the non-interacting case $U=0$ where the system can be additionally
classified as a time-reversal $\mathbb{Z}_{2}$-topological insulator, and
evolves adiabatically between the non-interacting and strongly interacting
limits.


  An overview about C*-algebra bundles with a Z-grading is presented, with
particular emphasis on classification questions. In particular, we discuss the
role of the representable KK(X ; -, -)-bifunctor introduced by Kasparov. As an
application, we consider Cuntz-Pimsner algebras associated with vector bundles,
and give a classification in terms of K-theoretical invariants in the case in
which the base space is an n-sphere.


  Let $S$ be a closed Riemann surface of genus $p>1$ with one point removed. In
this paper, we identify those point-pushing pseudo-Anosov maps on $S$ that
preserve at least one bi-infinite geodesic in the curve complex.


  Self-assignment, where software developers choose their own tasks, is a
common practice in agile teams. However, it is not known why developers select
certain tasks. It is important for managers to be aware of these reasons to
ensure sustainable self-assignment practices. We investigated developers'
preferences while they are choosing tasks for themselves. We collected data
from 42 participants working in 25 different software companies. We applied
Grounded Theory procedures to study and analyse factors for self-assigning
tasks, which we grouped into three categories: task-based, developer-based, and
opinion-based. We found that developers have individual preferences and not all
factors are important to every developer. Managers share some common and
varying perspectives around the identified factors. Most managers want
developers to give higher priority to certain factors. Developers often need to
balance between task priority and their own individual preferences, and
managers facilitate this through a variety of strategies. More risk-averse
managers encourage expertise-based self-assignment to ensure tasks are
completed quickly. Managers who are risk-balancing encourage developers to
choose tasks that provide learning opportunities only when there is little risk
of delays or reduced quality. Finally, growth-seeking managers regularly
encourage team members to pick tasks outside their comfort zone to encourage
growth opportunities. Our findings will help managers to understand what
developers consider when self-assigning tasks and help them empower their teams
to practice self-assignment in a sustainable manner.


  We propose a methodology to explore and measure the pairwise correlations
that exist between variables in a dataset. The methodology leverages copulas
for encoding dependence between two variables, state-of-the-art optimal
transport for providing a relevant geometry to the copulas, and clustering for
summarizing the main dependence patterns found between the variables. Some of
the clusters centers can be used to parameterize a novel dependence coefficient
which can target or forget specific dependence patterns. Finally, we illustrate
and benchmark the methodology on several datasets. Code and numerical
experiments are available online for reproducible research.


  Penalized regression methods, most notably the lasso, are a popular approach
to analyzing high-dimensional data. An attractive property of the lasso is that
it naturally performs variable selection. An important area of concern,
however, is the reliability of these variable selections. Motivated by local
false discovery rate methodology from the large-scale hypothesis testing
literature, we propose a method for calculating a local false discovery rate
for each variable under consideration by the lasso model. These rates can be
used to assess the reliability of an individual feature, or to estimate the
model's overall false discovery rate. The method can be used for all values of
$\lambda$. This is particularly useful for models with a few highly significant
features but a high overall Fdr, which are a relatively common occurrence when
using cross validation to select $\lambda$. It is also flexible enough to be
applied to many varieties of penalized likelihoods including GLM and Cox
models, and a variety of penalties, including MCP and SCAD. We demonstrate the
validity of this approach and contrast it with other inferential methods for
penalized regression as well as with local false discovery rates for univariate
hypothesis tests. Finally, we show the practical utility of our method by
applying it to two case studies involving high dimensional genetic data.


  The system of cavity polaritons driven by a plane electromagnetic wave is
found to undergo the spontaneous breaking of spatial symmetry, which results in
a lifted phase locking with respect to the driving field and, consequently, in
the possibility of internal ordering. In particular, periodic spin and
intensity patterns arise in polariton wires; they exhibit strong long-range
order and can serve as media for signal transmission. Such patterns have the
properties of dynamical chimeras: they are formed spontaneously in perfectly
homogeneous media and can be partially chaotic. The reported new mechanism of
chimera formation requires neither time-delayed feedback loops nor non-local
interactions.


  We optimize the area and latency of Shor's factoring while simultaneously
improving fault tolerance through: (1) balancing the use of ancilla generators,
(2) aggressive optimization of error correction, and (3) tuning the core adder
circuits. Our custom CAD flow produces detailed layouts of the physical
components and utilizes simulation to analyze circuits in terms of area,
latency, and success probability. We introduce a metric, called ADCR, which is
the probabilistic equivalent of the classic Area-Delay product. Our error
correction optimization can reduce ADCR by an order of magnitude or more.
Contrary to conventional wisdom, we show that the area of an optimized quantum
circuit is not dominated exclusively by error correction. Further, our adder
evaluation shows that quantum carry-lookahead adders (QCLA) beat ripple-carry
adders in ADCR, despite being larger and more complex. We conclude with what we
believe is one of most accurate estimates of the area and latency required for
1024-bit Shor's factorization: 7659 mm$^{2}$ for the smallest circuit and $6 *
10^8$ seconds for the fastest circuit.


  The research explores the utilization of a deep learning model employing an
attention mechanism in medical text mining. It targets the challenge of
analyzing unstructured text information within medical data. This research
seeks to enhance the model's capability to identify essential medical
information by incorporating deep learning and attention mechanisms. This paper
reviews the basic principles and typical model architecture of attention
mechanisms and shows the effectiveness of their application in the tasks of
disease prediction, drug side effect monitoring, and entity relationship
extraction. Aiming at the particularity of medical texts, an adaptive attention
model integrating domain knowledge is proposed, and its ability to understand
medical terms and process complex contexts is optimized. The experiment
verifies the model's effectiveness in improving task accuracy and robustness,
especially when dealing with long text. The future research path of enhancing
model interpretation, realizing cross-domain knowledge transfer, and adapting
to low-resource scenarios is discussed in the research outlook, which provides
a new perspective and method support for intelligent medical information
processing and clinical decision assistance. Finally, cross-domain knowledge
transfer and adaptation strategies for low-resource scenarios, providing
theoretical basis and technical reference for promoting the development of
intelligent medical information processing and clinical decision support
systems.


  Metamaterials are engineered materials composed of small electrical circuits
producing novel interactions with electromagnetic waves. Recently, a new class
of metamaterials has been created to mimic the behavior of media displaying
electromagnetically induced transparency (EIT). Here we introduce a planar EIT
metamaterial that creates a very large loss contrast between the dark and
radiative resonators by employing a superconducting Nb film in the dark element
and a normal-metal Au film in the radiative element. Below the critical
temperature of Nb, the resistance contrast opens up a transparency window along
with a large enhancement in group delay, enabling a significant slowdown of
waves. We further demonstrate precise control of the EIT response through
changes in the superfluid density. Such tunable metamaterials may be useful for
telecommunication because of their large delay-bandwidth products.


  The Dirac eigenvalues form a subset of observables of the Euclidean gravity.
The symplectic two-form in the covariant phase space could be expressed, in
principle, in terms of the Dirac eigenvalues. We discuss the existence of the
formal solution of the equations defining the components of the symplectic form
in this framework.


  Contemporary field-programmable gate arrays (FPGAs) are predestined for the
application of finite impulse response (FIR) filters. Their embedded digital
signal processing (DSP) blocks for multiply-accumulate operations enable
efficient fixed-point computations, in cases where the filter structure is
accurately mapped to the dedicated hardware architecture. This brief presents a
generic systolic structure for high-order FIR filters, efficiently exploiting
the hardware resources of an FPGA in terms of routability and timing. Although
this seems to be an easily implementable task, the synthesizing tools require
an adaptation of the straightforward digital filter implementation for an
optimal mapping. Using the example of a symmetric FIR filter with 90 taps, we
demonstrate the performance of the proposed structure with FPGAs from Xilinx
and Altera. The implementation utilizes less than 1% of slice logic and runs at
clock frequencies up to 526 MHz. Moreover, an enhancement of the structure
ultimately provides an extended dynamic range for the quantized coefficients
without the costs of additional slice logic.


  We investigate the polycyclic aromatic hydrocarbon features in the young
Galactic planetary nebula PN G095.2+00.7 based on mid-infrared observations.
The near- to mid-infrared spectra obtained with the AKARI/IRC and the
Spitzer/IRS show the PAH features as well as the broad emission feature at 12
{\mu}m usually seen in proto-planetary nebulae (pPNe). The spatially resolved
spectra obtained with Subaru/COMICS suggest that the broad emission around 12
{\mu}m is distributed in a shell-like structure, but the unidentified infrared
band at 11.3 {\mu}m is selectively enhanced at the southern part of the nebula.
The variation can be explained by a difference in the amount of the UV
radiation to excite PAHs, and does not necessarily require the chemical
processing of dust grains and PAHs. It suggests that the UV self-extinction is
important to understand the mid-infrared spectral features. We propose a
mechanism which accounts for the evolutionary sequence of the mid-infrared dust
features seen in a transition from pPNe to PNe.


  Although it has been known for some time that quantum mechanics can be
formulated in a way that treats prediction and retrodiction on an equal
footing, most attention in engineering quantum states has been devoted to
predictive states, that is, states associated with the a preparation event.
Retrodictive states, which are associated with a measurement event and
propagate backwards in time, are also useful, however. In this paper we show
how any retrodictive state of light that can be written to a good approximation
as a finite superposition of photon number states can be generated by an
optical multiport device. The composition of the state is adjusted by
controlling predictive coherent input states. We show how the probability of
successful state generation can be optimised by adjusting the multiport device
and also examine a versatile configuration that is useful for generating a
range of states.


  Neutron star merger remnants are unique sites for exploring neutrino flavor
conversion in dense media. Because of the natural excess of $\bar{\nu}_e$ over
$\nu_e$, the neutrino-neutrino potential can cancel the matter potential,
giving rise to matter-neutrino resonant flavor conversion. Under the assumption
of two (anti)neutrino flavors and spatial homogeneity, we solve the neutrino
quantum kinetic equations to investigate the occurrence of the matter-neutrino
resonance within a multi-angle framework. We find that isotropy is broken
spontaneously, regardless of the mass ordering. Relying on a hydrodynamical
simulation of a binary neutron star merger remnant with a black hole of $3\
M_\odot$ and an accretion torus of $0.3\ M_\odot$, we find that complete flavor
conversion caused by the matter-neutrino resonance is unlikely, although the
matter and neutrino potentials cancel at various locations above the disk.
Importantly, the matter-neutrino resonant flavor conversion crucially depends
on the shape of the neutrino angular distributions. Our findings suggest that
an accurate modeling of the neutrino angular distributions is necessary to
understand flavor conversion physics in merger remnants, its implications on
the disk physics and synthesis of the elements heavier than iron.


  In this paper we consider the most general least-order derivative theory of
gravity in which not only curvature but also torsion is explicitly present in
the Lagrangian, and where all independent fields have their own coupling
constant: we will apply this theory to the case of ELKO fields, which is the
acronym of the German \textit{Eigenspinoren des LadungsKonjugationsOperators}
designating eigenspinors of the charge conjugation operator, and thus they are
a Majorana-like special type of spinors; and to the Dirac fields, the most
general type of spinors. We shall see that because torsion has a coupling
constant that is still undetermined, the ELKO and Dirac field equations are
endowed with self-interactions whose coupling constant is undetermined: we
discuss different applications according to the value of the coupling constants
and the different properties that consequently follow. We highlight that in
this approach, the ELKO and Dirac field's self-interactions depend on the
coupling constant as a parameter that may even make these non-linearities
manifest at subatomic scales.


  We present here the results of a detailed study of the X-ray properties of
the cluster of galaxies Abell 3128 (z=0.06), based on the analysis of deep (100
ks) XMM-Newton data. The most obvious feature of the X-ray morphology of A3128
is the presence of two X-ray peaks separated by ~12'. By detecting the
redshifted Fe K line, we find that the Northeast (NE) X-ray peak observed
toward A3128 is a distant luminous cluster of galaxies at redshift z=0.44. Our
subsequent optical spectroscopic observation of a distant radio bright galaxy
in the centre of the NE X-ray peak with the Magellan telescope also revealed a
redshift of z=0.44, confirming the association of the galaxy with the cluster
seen in X-rays. We detect a gravitational arc around the galaxy. The properties
of this galaxy indicate that it is the cD galaxy of the cluster in the
background. The properties of the Southwest X-ray peak suggest that it is the
core of a group merging with A3128 along our line of sight. Based on 2D maps of
thermodynamic properties of the intra-cluster medium determined after
subtracting a model for the background cluster, we conclude that an enhanced
surface brightness region at a distance of ~2.8' from the centre of the galaxy
distribution is the centre of the gravitational potential of the cluster A3128.
The unrelaxed nature of A3128 can be attributed to its location in the high
density environment of the Horologium-Reticulum supercluster.


  The equation of motion method (EOM) is one of the approximations to calculate
transport coefficients of interacting electron systems. The method is known to
be useful to examine high-temperature properties. However, sometimes a naive
application of the EOM fails to capture an important physics at low-energy
scale, and it happens in recent preprints cond-mat/0309458 and cond-mat/0308413
which study a series of quantum dots. These preprints concluded that a
unitarity-limit transport due to the Kondo resonance, which has been deduced
from a Fermi-liquid behavior of the self-energy at T=0, $\omega=0$ [A.O., PRB
{\bf 63}, 115305 (2001)], does not occur. We show that the EOM self-energy
obtained with a finite cluster has accidentally a singular $1/\omega$
dependence around the Fermi energy, and it misleads one to the result
incompatible with a Fermi-liquid ground state.


  [Abridged] We study the thermal and kinetic Sunyaev-Zel'dovich (SZ) effect
associated with superclusters of galaxies using the MareNostrum Universe SPH
simulation. We consider superclusters similar to the Corona Borealis
Supercluster (CrB-SC). This paper is motivated by the detection at 33GHz of a
strong temperature decrement in the CMB towards the core of this supercluster.
Multifrequency observations with VSA and MITO suggest the existence of a
thermal SZ effect component in the spectrum of this cold spot, which would
account for roughly 25% of the total observed decrement. We identify nine
regions containing superclusters similar to CrB-SC, obtain the associated SZ
maps and calculate the probability of finding such SZ signals arising from hot
gas within the supercluster. Our results show that WHIM produces a thermal SZ
effect much smaller than the observed value. Neither can summing the
contribution of small clusters and galaxy groups in the region explain the
amplitude of the SZ signal. When we take into account the actual posterior
distribution from the observations, the probability that WHIM can cause a
thermal SZ signal like the one observed is <1%, rising up to a 3.2% when the
contribution of small clusters and galaxy groups is included. If the
simulations provide a suitable description of the gas physics, then we conclude
that the thermal SZ component of the CrB spot most probably arises from an
unknown galaxy cluster along the line of sight. The simulations also show that
the kinetic SZ signal associated with the supercluster cannot provide an
explanation for the remaining 75% of the observed cold spot in CrB.


  Plane-wave representations are used to formulate the exact solutions to
frequency-domain and time-domain sources illuminating a magnetodielectric slab
with complex permittivity and permeability. In the special case of a line
source at z=0 a distance d<L in front of an L wide lossless double negative
(DNG) slab with permittivity and permeability equal to -1, the single-frequency
solution exhibits not only "perfectly focused" fields for z>2L but also
divergent infinite fields in the region 2d<z<2L. In contrast, the solution to
the same lossless -1 DNG slab illuminated by a sinusoidal wave that begins at
some initial time t =0 (and thus has a nonzero bandwidth, unlike the
single-frequency excitation that begins at t=-infinity) is proven to have
imperfectly focused fields and convergent finite fields everywhere for all
finite time t. The proof hinges on the variation of permittivity and
permeability having a lower bound imposed by causality and energy conservation.
The minimum time found to produce a given resolution is proportional to the
estimate obtained by [Gomez-Santos, Phys. Rev. Lett., 90, 077401 (2003)]. Only
as t approaches infinity do the fields become perfectly focused in the region
z>2L and divergent in the region 2d<z<2L. These theoretical results, which are
confirmed by numerical examples, imply that divergent fields of the
single-frequency solution are not caused by an inherent inconsistency in
assuming an ideal lossless -1 DNG material, but are the result of the
continuous single-frequency wave (which contains infinite energy) building up
infinite reactive fields during the infinite duration of time from t=-infinity
to the present time t that the single-frequency excitation has been applied.


  There are several notions of convergence for sequences of bounded degree
graphs. One such notion is left convergence, which is based on counting
neighborhood distributions. Another notion is right convergence, based on
counting homomorphisms to a target (weighted) graph. Borgs, Chayes, Kahn and
Lov\'asz showed that a sequence of bounded degree graphs is left convergent if
and only if it is right convergent for certain target graphs $H$ with all
weights (including loops) close to $1$. We give a short alternative proof of
this statement. In particular, for each bounded degree graph $G$ we associate
functions $f_{G,k}$ for every positive integer $k$, and we show that left
convergence of a sequence of graphs is equivalent to the convergence of the
partial derivatives of each of these functions at the origin, while right
convergence is equivalent to pointwise convergence. Using the bound on the
maximum degree of the graphs, we can uniformly bound the partial derivatives at
the origin, and show that the Taylor series converges uniformly on a domain
independent of the graph, which implies the equivalence.


  The ad hoc coordination problem is to design an autonomous agent which is
able to achieve optimal flexibility and efficiency in a multiagent system with
no mechanisms for prior coordination. We conceptualise this problem formally
using a game-theoretic model, called the stochastic Bayesian game, in which the
behaviour of a player is determined by its private information, or type. Based
on this model, we derive a solution, called Harsanyi-Bellman Ad Hoc
Coordination (HBA), which utilises the concept of Bayesian Nash equilibrium in
a planning procedure to find optimal actions in the sense of Bellman optimal
control. We evaluate HBA in a multiagent logistics domain called level-based
foraging, showing that it achieves higher flexibility and efficiency than
several alternative algorithms. We also report on a human-machine experiment at
a public science exhibition in which the human participants played repeated
Prisoner's Dilemma and Rock-Paper-Scissors against HBA and alternative
algorithms, showing that HBA achieves equal efficiency and a significantly
higher welfare and winning rate.


  We introduce a discriminative multimodal descriptor based on a pair of sensor
readings: a point cloud from a LiDAR and an image from an RGB camera. Our
descriptor, named MinkLoc++, can be used for place recognition, re-localization
and loop closure purposes in robotics or autonomous vehicles applications. We
use late fusion approach, where each modality is processed separately and fused
in the final part of the processing pipeline. The proposed method achieves
state-of-the-art performance on standard place recognition benchmarks. We also
identify dominating modality problem when training a multimodal descriptor. The
problem manifests itself when the network focuses on a modality with a larger
overfit to the training data. This drives the loss down during the training but
leads to suboptimal performance on the evaluation set. In this work we describe
how to detect and mitigate such risk when using a deep metric learning approach
to train a multimodal neural network. Our code is publicly available on the
project website: https://github.com/jac99/MinkLocMultimodal.


  Non-local self similarity (NSS) is a powerful prior of natural images for
image denoising. Most of existing denoising methods employ similar patches,
which is a patch-level NSS prior. In this paper, we take one step forward by
introducing a pixel-level NSS prior, i.e., searching similar pixels across a
non-local region. This is motivated by the fact that finding closely similar
pixels is more feasible than similar patches in natural images, which can be
used to enhance image denoising performance. With the introduced pixel-level
NSS prior, we propose an accurate noise level estimation method, and then
develop a blind image denoising method based on the lifting Haar transform and
Wiener filtering techniques. Experiments on benchmark datasets demonstrate
that, the proposed method achieves much better performance than previous
non-deep methods, and is still competitive with existing state-of-the-art deep
learning based methods on real-world image denoising. The code is publicly
available at https://github.com/njusthyk1972/NLH.


  Examples of almost-positively and quasi-positively curved spaces of the form
M=H((G,h)xF) were discovered recently. Here, h is a left-invariant metric on a
compact Lie group G, F is a compact Riemannian manifold on which the subgroup H
of G acts isometrically on the left, and M is the orbit space of the diagonal
left action of H on (G,h)xF with the induced Riemannian submersion metric. We
prove that no new examples of strictly positive sectional curvature exist in
this class of metrics. This result generalizes the case F={point} proven by
Geroch.


  As WiFi grows ever more popular, airtime contention becomes an increasing
problem. One way to alleviate this is through network policy enforcement.
Unfortunately, WiFi lacks protocol support for configuring policies for its
usage, and since network-wide coordination cannot generally be ensured,
enforcing policy is challenging. However, as we have shown in previous work, an
access point can influence the behaviour of connected devices by changing its
scheduling of transmission opportunities, which can be used to achieve airtime
fairness. In this work, we show that this mechanism can be extended to
successfully enforce airtime usage policies in WiFi networks. We implement this
as an extension our previous airtime fairness work, and present PoliFi, the
resulting policy enforcement system. Our evaluation shows that PoliFi makes it
possible to express a range of useful policies. These include prioritisation of
specific devices; balancing groups of devices for sharing between different
logical networks or network slices; and limiting groups of devices to implement
guest networks or other low-priority services. We also show how these can be
used to improve the performance of a real-world DASH video streaming
application.


  This report is a combined version of two talks presented by the authors at
the Edinburgh $b$-physics Workshop, December 1991. It presents the ideas of
heavy quark symmetry and gives an introduction to some applications. The
references indicate where to go for more information: they are not intended to
be complete, nor do they necessarily refer to the original work on any
particular subject.


  Image captioning is a challenging task involving generating a textual
description for an image using computer vision and natural language processing
techniques. This paper proposes a deep neural framework for image caption
generation using a GRU-based attention mechanism. Our approach employs multiple
pre-trained convolutional neural networks as the encoder to extract features
from the image and a GRU-based language model as the decoder to generate
descriptive sentences. To improve performance, we integrate the Bahdanau
attention model with the GRU decoder to enable learning to focus on specific
image parts. We evaluate our approach using the MSCOCO and Flickr30k datasets
and show that it achieves competitive scores compared to state-of-the-art
methods. Our proposed framework can bridge the gap between computer vision and
natural language and can be extended to specific domains.


  We study the one-loop radiative corrections to the SU(2) breaking mass
splittings between sfermions in SU(2) doublets in the Minimal Supersymmetric
Standard Model. At tree-level, the differences of mass squared
$m_{\tilde{f}_{1L}}^2-m_{\tilde{f}_{2L}}^2$ of SU(2) doublet sfermions
$(\tilde{f}_1, \tilde{f}_2)_L$ in the first two generations are determined by
$\tan\beta$, and are universal to sleptons and squarks. The radiative
correction, however, breaks this relation. The typical deviation from the
universality between sleptons and squarks is within $\pm0.05$ in terms of the
``effective $\cos2\beta$''. We also study the SUSY parameter dependence of the
deviation. For very heavy sfermions, the relative corrections become large.


  In this survey article, we describe recent work that connects three separate
objects of interest: totally nonnegative matrices; quantum matrices; and matrix
Poisson varieties.


  We demonstrate a method for using arrays of point sources that emulate --
when measured from a standoff of at least several meters -- distributed
gamma-ray sources, and present results using this method from outdoor aerial
measurements of several planar arrays each comprising up to $100$ ${\sim}7$ mCi
Cu-64 sealed sources. The method relies on the Poisson deviance to
statistically test whether the array source ''looks like'' its continuous
analogue to a particular gamma-ray detector given the counts recorded as the
detector moves about 3D space. We use this deviance metric to design eight
different mock distributed sources, ranging in complexity from a $36\times36$ m
uniform square grid of sources to a configuration where regions of higher and
zero activity are superimposed on a uniform baseline. We then detail the
design, manufacture, and testing of the ${\sim} 7$ mCi Cu-64 sealed sources at
the Washington State University research reactor, and their deployment during
the aerial measurement campaign. We show the results of two such measurements,
in which approximate source shapes and qualitative source intensities can be
seen. Operationally, we find that the point-source array technique provides
high source placement accuracy and ease of quantifying the true source
configuration, scalability to source dimensions of ${\lesssim}100$ m, ease of
reconfiguration and removal, and relatively low dose to personnel. Finally, we
consider potential improvements and generalizations of the point-source array
technique for future measurement campaigns.


  We use Type Ia supernovae studied by the High-Z Supernova Search Team to
constrain the properties of an energy component which may have contributed to
accelerating the cosmic expansion. We find that for a flat geometry the
equation of state parameter for the unknown component, alpha_x=P_x/rho_x, must
be less than -0.55 (95% confidence) for any value of Omega_m and is further
limited to alpha_x<-0.60 (95%) if Omega_m is assumed to be greater than 0.1 .
These values are inconsistent with the unknown component being topological
defects such as domain walls, strings, or textures. The supernova data are
consistent with a cosmological constant (alpha_x=-1) or a scalar field which
has had, on average, an equation of state parameter similar to the cosmological
constant value of -1 over the redshift range of z=1 to the present. Supernova
and cosmic microwave background observations give complementary constraints on
the densities of matter and the unknown component. If only matter and vacuum
energy are considered, then the current combined data sets provide direct
evidence for a spatially flat Universe with Omega_tot=Omega_m+Omega_Lambda =
0.94 +/- 0.26 (1-sigma).


  Network data has emerged as an active research area in statistics. Much of
the focus of ongoing research has been on static networks that represent a
single snapshot or aggregated historical data unchanging over time. However,
most networks result from temporally-evolving systems that exhibit intrinsic
dynamic behavior. Monitoring such temporally-varying networks to detect
anomalous changes has applications in both social and physical sciences. In
this work, we perform an evaluation study of summary statistics for anomaly
detection in temporally-evolving networks by incorporating principles from
statistical process monitoring. In contrast to previous studies, we
deliberately incorporate temporal auto-correlation in our study. Other
considerations in our comprehensive assessment include types and duration of
anomaly, model type, and sparsity in temporally-evolving networks. We conclude
that summary statistics can be valuable tools for network monitoring and often
perform better than more complicated statistics.


  We consider the problem of computing the k-means centers for a large
high-dimensional dataset in the context of edge-based machine learning, where
data sources offload machine learning computation to nearby edge servers.
k-Means computation is fundamental to many data analytics, and the capability
of computing provably accurate k-means centers by leveraging the computation
power of the edge servers, at a low communication and computation cost to the
data sources, will greatly improve the performance of these analytics. We
propose to let the data sources send small summaries, generated by joint
dimensionality reduction (DR), cardinality reduction (CR), and quantization
(QT), to support approximate k-means computation at reduced complexity and
communication cost. By analyzing the complexity, the communication cost, and
the approximation error of k-means algorithms based on carefully designed
composition of DR/CR/QT methods, we show that: (i) it is possible to compute
near-optimal k-means centers at a near-linear complexity and a constant or
logarithmic communication cost, (ii) the order of applying DR and CR
significantly affects the complexity and the communication cost, and (iii)
combining DR/CR methods with a properly configured quantizer can further reduce
the communication cost without compromising the other performance metrics. Our
theoretical analysis has been validated through experiments based on real
datasets.


  We analyze reheating scenarios where a hidden sector is populated during
reheating along with the sector containing the Standard Model. We numerically
solve the Boltzmann equations describing perturbative reheating of the two
sectors, including the full dependence on quantum statistics, and study how
quantum statistical effects during reheating as well as the non-equilibrium
inflaton-mediated energy transfer between the two sectors affects the
temperature evolution of the two radiation baths. We obtain new power laws
describing the temperature evolution of fermions and bosons when quantum
statistics are important during reheating. We show that inflaton-mediated
scattering is generically most important at radiation temperatures $T\sim
M_\phi/4$, and build on this observation to obtain analytic estimates for the
temperature asymmetry produced by asymmetric reheating. We find that for
reheating temperatures $T_{\textrm{rh}} \ll M_{\phi}/4$, classical perturbative
reheating provides an excellent approximation to the final temperature
asymmetry, while for $T_{\textrm{rh}}\gg M_{\phi}/4$, inflaton-mediated
scattering dominates the population of the colder sector and thus the final
temperature asymmetry. We additionally present new techniques to calculate
energy transfer rates between two relativistic species at different
temperatures.


  Hypersonic phononic bandgap structures confine acoustic vibrations whose
wavelength is commensurate with that of light, and have been studied using
either time- or frequency-domain optical spectroscopy. Pulsed pump-probe lasers
are the preferred instruments for characterizing periodic multilayer stacks
from common vacuum deposition techniques, but the detection mechanism requires
the injected sound wave to maintain coherence during propagation. Beyond
acoustic Bragg mirrors, frequency-domain studies using a tandem Fabry-Perot
interferometer (TFPI) find dispersions of two- and three-dimensional phononic
crystals (PnCs) even for highly disordered samples, but with the caveat that
PnCs must be transparent. Here, we demonstrate a hybrid technique for
overcoming the limitations that time- and frequency-domain approaches exhibit
separately: We inject coherent phonons into a non-transparent PnC using a
pulsed laser and acquire the acoustic transmission spectrum on a TFPI, where
pumped appear alongside spontaneously excited (i.e. incoherent) phonons.
Choosing a metallic Bragg mirror for illustration, we determine the bandgap and
compare with conventional time-domain spectroscopy, finding resolution of the
hybrid approach to match that of a state-of-the-art asynchronous optical
sampling setup. Thus, the hybrid pump-probe technique retains key performance
features of the established one and going forward will likely be preferred for
disordered samples.


  We study the numerical effects of several renormalization schemes of the
Cabibbo-Kobayashi-Maskawa (CKM) quark mixing matrix on the top-quark decay
widths. We then employ these results to infer the relative shifts in the CKM
parameters |V_{tq}|^2 due to the quark mixing renormalization corrections,
assuming that they are determined directly from the top-quark partial decay
widths, without imposing unitarity constraints. We also discuss the
implications of these effects on the ratio R = Gamma(t -> Wb) / Gamma_t and the
determination of |V_{tb}|^2.


  We introduce the novel concept of integral Read-Bajraktarevi\'c (iRB)
operator and discuss some of its properties. We show that this iRB operator
generalizes the known Read-Bajraktarevi\'c (RB) operator and we derive
conditions for the fixed point of the iRB operator to belong to certain
function spaces.


  We present new CO ($J=5-4$ and $7-6$) and [CI] ($^3P_2\,-\, ^3P_1$ and
$^3P_1\,-\, ^3P_0$) emission line observations of the star-forming galaxy D49
at the massive end of the Main Sequence at $z=3$. We incorporate previous CO
($J=3-2$) and optical-to-millimetre continuum observations to fit its spectral
energy distribution (SED). Our results hint at high-$J$ CO luminosities
exceeding the expected location on the empirical correlations with the infrared
luminosity. [CI] emission fully consistent with the literature trends is found.
We do not retrieve any signatures of a bright active galactic nucleus that
could boost the $J=5-4,\,7-6$ lines in either the infrared or X-ray bands, but
warm photon-dominated regions, shocks or turbulence could in principle do so.
We suggest that mechanical heating could be a favourable mechanism able to
enhance the gas emission at fixed infrared luminosity in D49 and other
main-sequence star-forming galaxies at high redshift, but further investigation
is necessary to confirm this explanation. We derive molecular gas masses from
dust, CO, and [CI] that all agree within the uncertainties. Given its large
star formation rate (SFR) $\sim 500~M_\odot~{\rm yr}^{-1}$ and stellar mass
$>10^{11.5}~M_\odot$, the short depletion time scale of $<0.3$ Gyr might
indicate that D49 is experiencing its last growth spurt and will soon transit
to quiescence.


  Collective motion in nonequilibrium steady state suspensions of
self-propelled Janus motors driven by chemical reactions can arise due to
interactions coming from direct intermolecular forces, hydrodynamic flow
effects, or chemotactic effects mediated by chemical gradients. The relative
importance of these interactions depends on the reactive characteristics of the
motors, the way in which the system is maintained in a steady state, and
properties of the suspension, such as the volume fraction. From simulations of
a microscopic hard collision model for the interaction of fluid particles with
the Janus motor we show that dynamic cluster states exist and determine the
interaction mechanisms that are responsible for their formation. The relative
importance of chemotactic and hydrodynamic effects is identified by considering
a microscopic model in which chemotactic effects are turned off while the full
hydrodynamic interactions are retained. The system is maintained in a steady
state by means of a bulk reaction in which product particles are reconverted
into fuel particles. The influence of the bulk reaction rate on the collective
dynamics is also studied.


  The task of programming a quantum computer is just as strange as quantum
mechanics itself. But it now looks like a simple 3D puzzle may be the future
tool of quantum software engineers.


  The ab initio $GW$ method is considered as the most accurate approach for
calculating the band gaps of semiconductors and insulators. Yet its application
to transition metal oxides (TMOs) has been hindered by the failure of
traditional approximations developed for conventional semiconductors. In this
work, we examine the effects of these approximations on the values of band gaps
for ZnO, Cu$_2$O, and TiO$_2$. In particular, we explore the origin of the
differences between the two widely used plasmon-pole models. Based on the
comparison of our results with the experimental data and previously published
calculations, we discuss which approximations are suitable for TMOs and why.