  Large datasets in NLP suffer from noisy labels, due to erroneous automatic
and human annotation procedures. We study the problem of text classification
with label noise, and aim to capture this noise through an auxiliary noise
model over the classifier. We first assign a probability score to each training
sample of having a noisy label, through a beta mixture model fitted on the
losses at an early epoch of training. Then, we use this score to selectively
guide the learning of the noise model and classifier. Our empirical evaluation
on two text classification tasks shows that our approach can improve over the
baseline accuracy, and prevent over-fitting to the noise.


  While there have been numerous calls to increase the participation of people
with disabilities in STEM, many postsecondary institutions are not equipped to
support students with disabilities. We examined the digital accessibility of
139 webpages from 73 postsecondary institutions that contained information
about the undergraduate physics curriculum and graduate research programs. We
selected these webpages as they are common entry points for students interested
in pursuing a physics degree. We used Tenon and Mac OS X's Voiceover software
to assess the accessibility of these webpages as measured by alignment with the
Web Content Accessibility Guidelines (WCAG) 2.0. We found only one webpage was
accessible for students with disabilities. We present five common accessibility
errors we identified in the webpages in our sample, suggested solutions for
these errors, and implications for students with disabilities, instructors and
staff, institutional administration, and the broader physics community.


  Globular clusters (GC) are important objects for tracing the early evolution
of a galaxy. We study the relation between the properties of globular cluster
systems - as quantified by the GC specific frequency (SN) - and the properties
of their host galaxies. In order to understand the origin of the relation
between the GC specific frequency (SN) and galaxy mass, we devise a theoretical
model for the specific frequency (SN,th). GC erosion is considered to be an
important aspect for shaping this relation, since observations show that
galaxies with low densities have a higher SN, while high density galaxies have
a small SN. We construct a model based on the hypothesis that star-formation is
clustered and depends on the minimum embedded star cluster mass (Mecl,min), the
slope of the power-law embedded cluster mass function (beta) and the relation
between the star formation rate (SFR) and the maximum star cluster mass
(Mecl,max). We find an agreement between the primordial value of the specific
frequency (SNi) and our model for beta between 1.5 and 2.5 with Mecl,min <10^4
Msun.


  A first type of Multifractional Process with Random Exponent (MPRE) was
constructed several years ago in (Ayache, Taqqu, 2005) by replacing in a
wavelet series representation of Fractional Brownian Motion (FBM) the Hurst
parameter by a random variable depending on the time variable. In the present
article, we propose another approach for constructing another type of MPRE. It
consists in substituting to the Hurst parameter, in a stochastic integral
representation of the high-frequency part of FBM, a random variable depending
on the integration variable. The MPRE obtained in this way offers, among other
things, the advantages to have a representation through classical It\^o
integral and to be less difficult to simulate than the first type of MPRE,
previously introduced in (Ayache, Taqqu, 2005). Yet, the study of H\"older
regularity of this new MPRE is a significantly more challenging problem than in
the case of the previous one. Actually, it requires to develop a new
methodology relying on an extensive use of the Haar basis.


  In $D=2+1$ dimensions there are two dual descriptions of parity singlets of
helicity $\pm 1$, namely the self-dual model of first-order (in derivatives)
and the Maxwell-Chern-Simons theory of second-order. Correspondingly, for
helicity $\pm 2$ there are four models $S_{SD\pm}^{(r)}$ describing parity
singlets of helicities $\pm 2$. They are of first-, second-,third- and
fourth-order ($r=1,2,3,4$) respectively. Here we show that the generalized
soldering of the opposite helicity models $S_{SD+}^{(4)}$ and $S_{SD-}^{(4)}$
leads to the linearized form of the new massive gravity suggested by
Bergshoeff, Hohm and Townsend (BHT) similarly to the soldering of
$S_{SD+}^{(3)}$ and $S_{SD-}^{(3)}$. We argue why in both cases we have the
same result. We also find out a triple master action which interpolates between
the three dual models: linearized BHT theory, $S_{SD+}^{(3)} + S_{SD-}^{(3)}$
and $S_{SD+}^{(4)} + S_{SD-}^{(4)}$. By comparing gauge invariant correlation
functions we deduce dual maps between those models. In particular, we learn how
to decompose the field of the linearized BHT theory in helicity eigenstates of
the dual models up to gauge transformations.


  In this paper we will study Lorentz-invariant, infinite derivative quantum
field theories, where infinite derivatives give rise to non-local interactions
at the energy scale $M_s$, beyond the Standard Model. We will study a specific
class, where there are no it new dynamical degrees of freedom other than the
original ones of the corresponding local theory. We will show that the Green
functions are modified by a non-local extra term that is responsible for
acausal effects, which are confined in the region of non-locality, i.e.
$M_s^{-1}.$ The standard time-ordered structure of the causal Feynman
propagator is not preserved and the non-local analog of the retarded Green
function turns out to be non-vanishing for space-like separations. As a
consequence the local commutativity is violated. Formulating such theories in
the non-local region with Minkowski signature is not sensible, but they have
Euclidean interpretation. We will show how such non-local construction
ameliorates ultraviolet/short-distance singularities suffered typically in the
local quantum field theory. We will show that non-locality and acausality are
inherently off-shell in nature, and only quantum amplitudes are physically
meaningful, so that all the perturbative quantum corrections have to be
consistently taken into account.


  In approaches to quantum theory in which the quantum state is regarded as a
representation of knowledge, information, or belief, two agents can assign
different states to the same quantum system. This raises two questions: when
are such state assignments compatible? and how should the state assignments of
different agents be reconciled? In this paper, we address these questions from
the perspective of the recently developed conditional states formalism for
quantum theory [arXiv:1107.5849]. Specifically, we derive a compatibility
criterion proposed by Brun, Finkelstein and Mermin from the requirement that,
upon acquiring data, agents should update their states using a quantum
generalization of Bayesian conditioning. We provide two alternative arguments
for this criterion, based on the objective and subjective Bayesian
interpretations of probability theory. We then apply the same methodology to
the problem of quantum state improvement, i.e. how to update your state when
you learn someone else's state assignment, and to quantum state pooling, i.e.
how to combine the state assignments of several agents into a single assignment
that accurately represents the views of the group. In particular, we derive a
pooling rule previously proposed by Spekkens and Wiseman under much weaker
assumptions than those made in the original derivation. All of our results
apply to a much broader class of experimental scenarios than have been
considered previously in this context.


  In this paper we obtain a weighted average formula for special values of
$L$-functions attached to normalized elliptic modular forms of weight $k$ and
full level. These results are obtained by studying the pullback of a Siegel
Eisenstein series and working out an explicit spectral decomposition.


  It is well-known that the pointer basis of a quantum system satisfies the
condition to diagonalize the interaction Hamiltonian between the subsystems. We
show that this condition can be translated into the form $\delta\Lambda=0,$
where $\Lambda$, so-called the action, is the time integrated interaction
energy: it is found out naturally in the phase of state vectors due to diagonal
interaction. The careful treatment of a two states system demonstrates that the
states of the total system branch into the states with different values of the
action. Mathematically the pointer states are selected out by the saddle point
condition on the phase $\Lambda$. This study helps us to understand the precise
mechanism and the general dynamics of decoherence.


  The removal of noise typically correlated in time and wavelength is one of
the main challenges for using the radial velocity method to detect Earth
analogues. We analyze radial velocity data of tau Ceti and find robust evidence
for wavelength dependent noise. We find this noise can be modeled by a
combination of moving average models and "differential radial velocities". We
apply this noise model to various radial velocity data sets for tau Ceti, and
find four periodic signals at 20.0, 49.3, 160 and 642 d which we interpret as
planets. We identify two new signals with orbital periods of 20.0 and 49.3 d
while the other two previously suspected signals around 160 and 600 d are
quantified to a higher precision. The 20.0 d candidate is independently
detected in KECK data. All planets detected in this work have minimum masses
less than 4$M_\oplus$ with the two long period ones located around the inner
and outer edges of the habitable zone, respectively. We find that the
instrumental noise gives rise to a precision limit of the HARPS around 0.2 m/s.
We also find correlation between the HARPS data and the central moments of the
spectral line profile at around 0.5 m/s level, although these central moments
may contain both noise and signals. The signals detected in this work have
semi-amplitudes as low as 0.3 m/s, demonstrating the ability of the radial
velocity technique to detect relatively weak signals.


  Capacitated spatial clustering, a type of unsupervised machine learning
method, is often used to tackle problems in compressing, classifying, logistic
optimization and infrastructure optimization. Depending on the application at
hand, a wide set of extensions may be necessary in clustering.
  In this article we propose a number of novel extensions to PACK that is a
novel capacitated spatial clustering method. These extensions are relocation
and location preference of cluster centers, outliers, and non-spatial
attributes. The strength of PACK is that it can consider all of these
extensions jointly. We demonstrate the usefulness PACK with a real world
example in edge computing server placement for a city region with various
different set ups, where we take into consideration outliers, center placement,
and non-spatial attributes. Different setups are evaluated with summary
statistics on spatial proximity and attribute similarity. As a result, the
similarity of the clusters was improved at best by 53%, while simultaneously
the proximity degraded only 18%. In alternate scenarios, both proximity and
similarity were improved. The different extensions proved to provide a valuable
way to include non-spatial information into the cluster analysis, and attain
better overall proximity and similarity. Furthermore, we provide easy-to-use
software tools (rpack) for conducting clustering analyses.


  We show for the first time, to our knowledge, that it is possible to
reconcile in online learning in zero-sum games two seemingly contradictory
objectives: vanishing time-average regret and non-vanishing step sizes. This
phenomenon, that we coin ``fast and furious" learning in games, sets a new
benchmark about what is possible both in max-min optimization as well as in
multi-agent systems. Our analysis does not depend on introducing a carefully
tailored dynamic. Instead we focus on the most well studied online dynamic,
gradient descent. Similarly, we focus on the simplest textbook class of games,
two-agent two-strategy zero-sum games, such as Matching Pennies. Even for this
simplest of benchmarks the best known bound for total regret, prior to our
work, was the trivial one of $O(T)$, which is immediately applicable even to a
non-learning agent. Based on a tight understanding of the geometry of the
non-equilibrating trajectories in the dual space we prove a regret bound of
$\Theta(\sqrt{T})$ matching the well known optimal bound for adaptive step
sizes in the online setting. This guarantee holds for all fixed step-sizes
without having to know the time horizon in advance and adapt the fixed
step-size accordingly. As a corollary, we establish that even with fixed
learning rates the time-average of mixed strategies, utilities converge to
their exact Nash equilibrium values.


  This is the fourth in a series of papers on the growth of regular partitions
in $3$-uniform hypergraphs. In this paper, we consider a form of regularity for
$3$-uniform hypergraphs which was developed by Frankl, Gowers, Kohayakawa,
Nagle, R\"{o}dl, Skokan, and Schacht. Regular decompositions of this type
involve two components, a partition on the vertex set and a partition on the
pairs of vertices. To each hereditary property $\mathcal{H}$ of $3$-uniform
hypergraphs, we associate two corresponding growth functions: $T_{\mathcal{H}}$
for the size of the vertex component, and $L_{\mathcal{H}}$ for the size of the
pairs component. In this paper we consider the behavior of the function
$L_{\mathcal{H}}$. We show any such function is either constant, bounded above
and below by a polynomial, or bounded below by an exponential.


  Specific heat ($C_V$) measurements in the spin-1/2
Cu$_2$(C$_2$H$_{12}$N$_2$)$_2$Cl$_4$ system under a magnetic field up to
$H=8.25 T$ are reported and compared to the results of numerical calculations
based on the 2-leg antiferromagnetic Heisenberg ladder. While the temperature
dependences of both the susceptibility and the low field specific heat are
accurately reproduced by this model, deviations are observed below the critical
field $H_{C1}$ at which the spin gap closes. In this Quantum High Field phase,
the contribution of the low-energy quantum fluctuations are stronger than in
the Heisenberg ladder model. We argue that this enhancement can be attributed
to dynamical lattice fluctuations. Finally, we show that such a Heisenberg
ladder, for $H>H_{C1}$, is unstable, when coupled to the 3D lattice, against a
lattice distortion. These results provide an alternative explanation for the
observed low temperature ($T_C\sim 0.5K$ -- $0.8K$) phase (previously
interpreted as a 3D magnetic ordering) as a new type of incommensurate gapped
state.


  In principle, the angular anisotropy in the extragalactic gamma-ray
background (EGRB) places severe constraints upon putative populations of
unresolved gamma-ray point sources. Existing estimates of the EGRB anisotropy
have been constructed by excising known point sources, e.g., taken from the
First or 2 Year Fermi-LAT Source Catalog (1FGL or 2FGL, respectively) and
statistically analyzing the residual gamma-ray sky maps. We perform an
independent check of the EGRB anisotropy limits by comparing the values
obtained from the 1FGL-masked sky maps to the signal implied by sources that
lie below the 1FGL detection threshold in the more sensitive 2FGL and 1FHL
(First Fermi-LAT catalog of >10 GeV sources). As such, our analysis provides an
internal consistency check of implications for source counts and spectral index
distributions of gamma-ray bright active galactic nuclei obtained from
Fermi-LAT data. Based on this, we find evidence for substantially larger
anisotropies than those previously reported at energies above 5 GeV, where BL
Lac objects are likely to provide the bulk of their contribution to the EGRB.
This uncertainty in the EGRB anisotropy cautions against using it as an
independent constraint for the high-redshift gamma-ray universe. Moreover, this
would suggest that contrary to previous claims, smooth extensions of the
resolved point-source population may be able to simultaneously explain both the
isotropic and anisotropic components of the EGRB.


  In this paper, we establish a $p$-adic Simpson correspondence on the arena of
Liu-Zhu for rigid analytic varieties $X$ over $\Cp$ with a liftable good
reduction by constructing a new period sheaf on $X_{\proet}$. To do so, we use
the theory of cotangent complex after Beilinson and Bhatt. Then we give an
integral decompletion theorem and complete the proof by local calculations. Our
construction is compatible with the previous works of Faltings and Liu-Zhu.


  Phase transitions and collective dynamics of active colloidal suspensions are
fascinating topics in soft matter physics, particularly for out-of-equilibrium
systems, which can lead to rich rheological behaviours in the presence of
steady shear flow. In this article, the role of self-propulsion in the
rheological response of a dense colloidal suspension is investigated by using
particle-resolved simulations. First, the interplay between activity and shear
in the solid to the liquid transition of the suspension is analysed. While both
self-propulsion and shear destroy order and melt the system by themselves above
their critical values, self-propulsion lowers the stress barrier that needs to
be overcome during the transition. Once the suspension reaches a
non-equilibrium steady state the rheological response is analysed. While
passive suspensions show a solid-like behaviour, turning on particle motility
fluidises the system and, at low self-propulsion, the suspension behaves as a
shear-thinning fluid. Increasing the self-propulsion of the colloids induces a
transition from a shear-thinning to a shear-thickening behaviour, which we
attribute to clustering in the suspensions induced by motility. This
interesting phenomenon of motility-induced shear thickening (MIST) can be used
to tailor the rheological response of colloidal suspensions.


  The correlation between galaxies' integrated stellar masses and star
formation rates (the `star formation main sequence'; SFMS) is a
well-established scaling relation. Recently, surveys have found a relationship
between the star formation rate and stellar mass surface densities on kpc and
sub-kpc scales (the `resolved SFMS'; rSFMS). In this work, we demonstrate that
the rSFMS emerges naturally in FIRE-2 zoom-in simulations of Milky Way-mass
galaxies. We make SFR and stellar mass maps of the simulated galaxies at a
variety of spatial resolutions and star formation averaging time-scales and fit
the rSFMS using multiple methods from the literature. While the absolute value
of the SFMS slope depends on the fitting method, the slope is steeper for
longer star formation time-scales and lower spatial resolutions regardless of
the fitting method employed. We present a toy model that quantitatively
captures the dependence of the simulated galaxies' rSFMS slope on spatial
resolution and use it to illustrate how this dependence can be used to
constrain the characteristic mass of star-forming clumps.


  By finding rare (but not exponentially rare) large-angle deflections of
partons within a jet produced in a heavy ion collision, or of such a jet
itself, experimentalists can find the weakly coupled short-distance quark and
gluon particles (scatterers) within the strongly coupled liquid quark-gluon
plasma (QGP) produced in heavy ion collisions. This is the closest one can come
to probing QGP via a scattering experiment and ultimately learning how a
strongly coupled liquid emerges from an asymptotically free gauge theory. The
short-distance, particulate, structure of liquid QGP can be revealed in events
in which a jet parton resolves, and scatters off, a parton from the droplet of
QGP. The probability for picking up significant transverse momentum via a
single scattering was calculated previously, but only in the limit of infinite
parton energy which means zero angle scattering. Here, we provide a leading
order perturbative QCD calculation of the Moli\`ere scattering probability for
incident partons with finite energy, scattering at a large angle. We set up a
thought experiment in which an incident parton with a finite energy scatters
off a parton constituent within a "brick" of QGP, which we treat as if it were
weakly coupled, as appropriate for scattering with large momentum transfer, and
compute the probability for a parton to show up at a nonzero angle with some
energy. We include all relevant channels, including those in which the parton
that shows up at a large angle was kicked out of the medium as well as the
Rutherford-like channel in which what is seen is the scattered incident parton.
The results that we obtain will serve as inputs to future jet Monte Carlo
calculations and can provide qualitative guidance for how to use future
precise, high statistics, suitably differential measurements of jet
modification in heavy ion collisions to find the scatterers within the QGP
liquid.


  The hamiltonian BRST-anti-BRST theory is developed in the general case of
arbitrary reducible first class systems. This is done by extending the methods
of homological perturbation theory, originally based on the use of a single
resolution, to the case of a biresolution. The BRST and the anti-BRST
generators are shown to exist. The respective links with the ordinary BRST
formulation and with the $ sp(2) $-covariant formalism are also established.


  We use Brown-Peterson cohomology to obtain lower bounds for the higher
topological complexity, TC_k(RP^n), of real projective spaces, which are often
much stronger than those implied by ordinary mod-2 cohomology.


  Restoring and inpainting the visual memories that are present, but often
impaired, in old photos remains an intriguing but unsolved research topic.
Decades-old photos often suffer from severe and commingled degradation such as
cracks, defocus, and color-fading, which are difficult to treat individually
and harder to repair when they interact. Deep learning presents a plausible
avenue, but the lack of large-scale datasets of old photos makes addressing
this restoration task very challenging. Here we present a novel reference-based
end-to-end learning framework that is able to both repair and colorize old,
degraded pictures. Our proposed framework consists of three modules: a
restoration sub-network that conducts restoration from degradations, a
similarity network that performs color histogram matching and color transfer,
and a colorization subnet that learns to predict the chroma elements of images
conditioned on chromatic reference signals. The overall system makes uses of
color histogram priors from reference images, which greatly reduces the need
for large-scale training data. We have also created a first-of-a-kind public
dataset of real old photos that are paired with ground truth ''pristine''
photos that have been manually restored by PhotoShop experts. We conducted
extensive experiments on this dataset and synthetic datasets, and found that
our method significantly outperforms previous state-of-the-art models using
both qualitative comparisons and quantitative measurements. The code is
available at https://github.com/DerrickXuNu/Pik-Fix.


  We perform a detailed and systematic investigation of the possible impacts of
dark stars upon the reionization history of the Universe, and its signatures in
the cosmic microwave background (CMB). We compute hydrogen reionization
histories, CMB optical depths and anisotropy power spectra for a range of
stellar populations including dark stars. If dark stars capture large amounts
of dark matter via nuclear scattering, reionization can be substantially
delayed, leading to decreases in the integrated optical depth to last
scattering and large-scale power in the EE polarization power spectrum. Using
the integrated optical depth observed by WMAP7, in our canonical reionization
model we rule out the section of parameter space where dark stars with high
scattering-induced capture rates tie up more than ~90% of all the first
star-forming baryons, and live for over ~250 Myr. When nuclear scattering
delivers only moderate amounts of dark matter, reionization can instead be sped
up slightly, modestly increasing the CMB optical depth. If dark stars do not
obtain any dark matter via nuclear scattering, effects upon reionization and
the CMB are negligible. The effects of dark stars upon reionization and its CMB
markers can be largely mimicked or compensated for by changes in the existing
parameters of reionization models, making dark stars difficult to disentangle
from astrophysical uncertainties, but also widening the range of standard
parameters in reionization models that can be made consistent with
observations.


  Current models that explain giant (type II) X-ray outbursts in Be/X-ray
binaries (BeXB), are based on the idea of highly distorted disks. They are
believed to occur when a misaligned and warped disk becomes eccentric, allowing
the neutron star to capture a large amount of material. The BeXB 4U 0115+63
underwent two major outbursts in 2015 and 2017. Our aim is to investigate
whether the structural changes in the disk expected during type II outbursts
can be detected through optical polarimetry. We present the first optical
polarimetric observations and new optical spectra of the BeXB 4U 0115+63
covering the period 2013-2017. We study in detail the shape of the H$\alpha$
line profile and the polarization parameters before, during, and after the
occurrence of a type II X-ray outburst. We find significant changes in
polarization degree and polarization angle and highly distorted line profiles
during the 2017 X-ray outburst. The degree of polarization decreased by $\sim$
1%, while the polarization angle, which is supposed to be related with the disk
orientation, first increased by $\sim 10^{\circ}$ in about two months and then
decreased by a similar amount and on a similar timescale once the X-ray
activity ceased.We interpret the polarimetric and spectroscopic variability as
evidence for the presence of a warped disk.


  Let F be a nonarchimedean local field, let D be a division algebra over F,
let GL(n) = GL(n,F). Let \nu denote Plancherel measure for GL(n). Each
component \Omega in the Bernstein variety \Omega(GL(n)) has several numerical
invariants attached to it. We provide explicit formulas for the Bernstein
component \nu_{\Omega} of Plancherel measure in terms of these invariants. We
also prove some new formal degree formulas, a transfer-of-measure formula for
GL(n), and a transfer-of-measure formula from GL(n,F) to GL(m,D).


  The capacity to confine light into a small region of space is of paramount
importance in many areas of modern science. Here, we suggest a mechanism to
store a quantized "bit" of light - with a very precise amount of energy - in an
open core-shell plasmonic structure ("meta-atom") with a nonlinear optical
response. Notwithstanding the trapped light state is embedded in the radiation
continuum, its lifetime is not limited by the radiation loss. Interestingly, it
is shown that the interplay between the nonlinear response and volume plasmons
enables breaking fundamental reciprocity restrictions, and coupling very
efficiently an external light source to the meta-atom. The collision of an
incident optical pulse with the meta-atom may be used to release the trapped
radiation "bit".


  We propose an algorithm inspired by optical coherent Ising machines to solve
the problem of polynomial unconstrained binary optimization (PUBO). We
benchmark the proposed algorithm against existing PUBO algorithms on the
extended Sherrington-Kirkpatrick model and random third-degree polynomial
pseudo-Boolean functions, and observe its superior performance. We also address
instances of practically relevant computational problems such as protein
folding and electronic structure calculations with problem sizes not accessible
to existing quantum annealing devices. The application of our algorithm to
protein folding and quantum chemistry problems sheds light on the shortcomings
of approximating the electronic structure problem by a PUBO problem, which, in
turn, puts into question the applicability of the unconstrained binary
optimization formulation, such as that of quantum annealers and coherent Ising
machines, in this context.


  The famous Perona-Malik (P-M) equation which was at first introduced for
image restoration has been solved via various numerical methods. In this paper
we will solve it for the first time via applying a new numerical method called
Homotopy Perturbation Method (HMP) and the correspondent approximated solutions
will be obtained for the P-M equation with regards to relevant error analysis.
Through implementation of our algorithm we will access some effective results
which are deserved to be considered as worthy as the other solutions issued by
the other methods.


  We study the interaction of an electron/hole with inhomogeneous magnetic
field in the presence of a screw dislocation. We consider the internal
structure of the defect, i.e., we consider the core that gives rise to a finite
size to the defect. In addition, we assume that this core determines a
forbidden region for the electron/hole. Then, we solve the Schr\"odinger
equation and show that an Aharonov-Bohm-type effect arises from the influence
of the topological defect and the missing magnetic flux on the eigenvalues of
energy.


  The $H_0$ tension and the accompanying $r_d$ tension are a hot topic in
current cosmology. In order to remove the degeneracy between the Hubble
parameter $H_0$ and the sound horizon scale $r_d$ from the Baryon Acoustic
Oscillations (BAO) datasets, we redefine the likelihood by marginalizing over
the $H_0 \cdot r_d$ parameter and then we perform full Bayesian analysis for
different models of dark energy (DE). We find that our uncalibrated by early or
late physics {datasets cannot} constrain the DE models properly without further
assumptions. By adding the type IA supernova dataset, the models are
constrained better with smaller errors on the DE parameters. The two BAO
datasets we use -- one with angular measurements and one with angular and
radial ones with their covariances, show statistical preferences for different
models, with $\Lambda$CDM being the best model for one of them. Adding the
Pantheon SnIA dataset with its covariance matrix boosts the statistical
preference for $\Lambda$CDM.


  We present a first-principles investigation of the electronic and optical
properties of hybrid organic-inorganic interfaces consisting of MoS$_2$
monolayer and the $\pi$-conjugate molecules pyrene and pyridine. For both
hybrid systems, the quasi-particle band structure obtained from the $G_0W_0$
approximation shows -- in contrast to density-functional theory -- level
alignment of type II, owing to the mutual dynamical screening of the interface
constituents. $\textit{Ab initio}$ calculations of the absorption spectrum
based on the Bethe-Salpeter equation reveal besides intra-layer excitons on the
MoS$_2$ side, hybrid as well as charge-transfer excitons at the interface.
These findings indicate that hybrid systems consisting of semiconducting
transition-metal dichalcogenides and organic $\pi$-conjugate molecules can host
a rich variety of optical excitations and thus provide a promising venue to
explore many-body interactions and exciton physics in low dimensionality.


  This report presents an approach to the exact solutions of the time-dependent
Jaynes-Cummings (J-C) model without the rotating wave approximation (RWA). It
is shown that there is a squeezing-operator unitary transformation for relating
the J-C model without RWA and the one with RWA. Thus by using an appropriate
squeezing unitary transformation, the time-dependent J-C model without RWA can
be transformed into the one with RWA that has been exactly solved previously,
and based on this one can readily obtain the exact solutions of the
time-dependent Jaynes-Cummings (J-C) model without RWA. The approach presented
here also shows that we can treat these two kinds of time-dependent J-C models
(both with and without RWA) in a unified way.


  The symmetric $\lambda \mu$-calculus is the $\lambda \mu$-calculus introduced
by Parigot in which the reduction rule $\m'$, which is the symmetric of $\mu$,
is added. We give arithmetical proofs of some strong normalization results for
this calculus. We show (this is a new result) that the $\mu\mu'$-reduction is
strongly normalizing for the un-typed calculus. We also show the strong
normalization of the $\beta\mu\mu'$-reduction for the typed calculus: this was
already known but the previous proofs use candidates of reducibility where the
interpretation of a type was defined as the fix point of some increasing
operator and thus, were highly non arithmetical.


  Vaccine adverse events have been presumed to be a relatively objective
measure that is immune to political polarization. The real-world data, however,
shows the correlation between presidential disapproval ratings and the
subjective severity of adverse events. This paper investigates the partisan
bias in COVID vaccine adverse events coverage with language models that can
classify the topic of vaccine-related articles and the political disposition of
news comments. Based on 90K news articles from 52 major newspaper companies, we
found that conservative media are inclined to report adverse events more
frequently than their liberal counterparts, while the coverage itself was
statistically uncorrelated with the severity of real-world adverse events. The
users who support the conservative opposing party were more likely to write the
popular comments from 2.3K random sampled articles on news platforms. This
research implies that bipartisanship can still play a significant role in
forming public opinion on the COVID vaccine even after the majority of the
population's vaccination


  We study an extension of the minimal gauged $L_{\mu}-L_{\tau}$ model in order
to explain the anomalous magnetic moments of muon and electron simultaneously.
Presence of an additional scalar doublet $\eta$ and an in-built $Z_2$ symmetry
under which the right handed singlet fermions and $\eta$ are odd, leads to
light neutrino mass in scotogenic fashion along with a stable dark matter
candidate. In spite of the possibility of having positive and negative
contributions to $(g-2)$ from vector boson and charged scalar loops
respectively, the minimal scotogenic $L_{\mu}-L_{\tau}$ model can not explain
muon and electron $(g-2)$ simultaneously while being consistent with other
experimental bounds. We then extend the model with a vector like lepton doublet
which not only leads to a chirally enhanced negative contribution to electron
$(g-2)$ but also leads to the popular singlet-doublet fermion dark matter
scenario. With this extension, the model can explain both electron and muon
$(g-2)$ while being consistent with neutrino mass, dark matter and other direct
search bounds. The model remains predictive at high energy experiments like
collider as well as low energy experiments looking for charged lepton flavour
violation, dark photon searches, in addition to future $(g-2)$ measurements.


  Electron microscopy (EM) enables the reconstruction of neural circuits at the
level of individual synapses, which has been transformative for scientific
discoveries. However, due to the complex morphology, an accurate reconstruction
of cortical axons has become a major challenge. Worse still, there is no
publicly available large-scale EM dataset from the cortex that provides dense
ground truth segmentation for axons, making it difficult to develop and
evaluate large-scale axon reconstruction methods. To address this, we introduce
the AxonEM dataset, which consists of two 30x30x30 um^3 EM image volumes from
the human and mouse cortex, respectively. We thoroughly proofread over 18,000
axon instances to provide dense 3D axon instance segmentation, enabling
large-scale evaluation of axon reconstruction methods. In addition, we densely
annotate nine ground truth subvolumes for training, per each data volume. With
this, we reproduce two published state-of-the-art methods and provide their
evaluation results as a baseline. We publicly release our code and data at
https://connectomics-bazaar.github.io/proj/AxonEM/index.html to foster the
development of advanced methods.


  In this paper, we consider multi-objective reinforcement learning, which
arises in many real-world problems with multiple optimization goals. We
approach the problem with a max-min framework focusing on fairness among the
multiple goals and develop a relevant theory and a practical model-free
algorithm under the max-min framework. The developed theory provides a
theoretical advance in multi-objective reinforcement learning, and the proposed
algorithm demonstrates a notable performance improvement over existing baseline
methods.


  The emerging technology of Vehicle-to-Vehicle (V2V) communication over
vehicular ad hoc networks promises to improve road safety by allowing vehicles
to autonomously warn each other of road hazards. However, research on other
transportation information systems has shown that informing only a subset of
drivers of road conditions may have a perverse effect of increasing congestion.
In the context of a simple (yet novel) model of V2V hazard information sharing,
we ask whether partial adoption of this technology can similarly lead to
undesirable outcomes. In our model, drivers individually choose how recklessly
to behave as a function of information received from other V2V-enabled cars,
and the resulting aggregate behavior influences the likelihood of accidents
(and thus the information propagated by the vehicular network). We fully
characterize the game-theoretic equilibria of this model. Our model indicates
that for a wide range of our parameter space, V2V information sharing
surprisingly increases the equilibrium frequency of accidents relative to no
V2V information sharing, and that it may increase equilibrium social cost as
well.


  Multi-principle element alloys have enormous potential, but their exploration
suffers from the tremendously large range of configurations. In the last decade
such alloys have been designed with a focus on random solid solutions. Here we
apply an experimentally verified, combined thermodynamic and first-principles
design strategy to reverse the traditional approach and to generate a new type
of hcp Al-Hf-Sc-Ti-Zr high entropy alloy with a hitherto unique structure. A
phase diagram analysis narrows down the large compositional space to a
well-defined set of candidates. First-principles calculations demonstrate the
energetic preference of an ordered superstructure over the competing disordered
solid solutions. The chief ingredient is the Al concentration, which can be
tuned to achieve a D019 ordering of the hexagonal lattice. The computationally
designed D019 superstructure is experimentally confirmed by transmission
electron microscopy and X-ray studies. Our scheme enables the exploration of a
new class of high entropy alloys.


  It has long been speculated that electronic flat band systems can be a
fertile ground for hosting novel emergent phenomena including unconventional
magnetism and superconductivity. Although flat bands are known to exist in a
few systems such as heavy fermion materials and twisted bilayer graphene, their
microscopic roles and underlying mechanisms in generating emergent behavior
remain elusive. Here we use scanning tunneling microscopy to elucidate the
atomically resolved electronic states and their magnetic response in the kagome
magnet Co3Sn2S2. We observe a pronounced peak at the Fermi level, which is
identified to arise from the kinetically frustrated kagome flat band.
Increasing magnetic field up to +-8T, this state exhibits an anomalous
magnetization-polarized Zeeman shift, dominated by an orbital moment in
opposite to the field direction. Such negative magnetism can be understood as
spin-orbit coupling induced quantum phase effects tied to non-trivial flat band
systems. We image the flat band peak, resolve the associated negative
magnetism, and provide its connection to the Berry curvature field, showing
that Co3Sn2S2 is a rare example of kagome magnet where the low energy physics
can be dominated by the spin-orbit coupled flat band. Our methodology of
probing band-resolved ordering phenomena such as spin-orbit magnetism can also
be applied in future experiments to elucidate other exotic phenomena including
flat band superconductivity and anomalous quantum transport.


  Numerous studies have shown that wind turbine wakes within a large wind farm
bring about changes to both the dynamics and thermodynamics of the atmospheric
boundary layers (ABL). Previously, we investigated the relative humidity budget
within a wind farm via field measurements in the near-wake region and large
eddy simulations (LES). The effect of the compounding wakes within a large wind
farm on the relative humidity was also investigated by LES. In this study, we
investigate how the areas of relative humidity variation, that was observed in
the near-wake, develop downstream in the shadow region of a large wind farm. To
this end, LES of a wind farm consisting of 8x6 wind turbines with periodic
boundary condition in the lateral direction (inferring an infinitely wide farm)
interacting with a stable ABL is carried out. Two wind farm layouts, aligned
and staggered, are considered in the analysis and the results from both
configurations are compared to each other. It is observed that a decrease of
relative humidity underneath the hub height and an increase above the hub
height build up within the wind farm, and are maintained in the downstream of
the farm for long distances. The staggered farm layout is more effective in
keeping a more elongated region of low relative humidity underneath the hub,
when compared to the aligned layout.


  In applications of dynamical systems, situations can arise where it is
desired to predict the onset of synchronization as it can lead to
characteristic and significant changes in the system performance and behaviors,
for better or worse. In experimental and real settings, the system equations
are often unknown, raising the need to develop a prediction framework that is
model free and fully data driven. We contemplate that this challenging problem
can be addressed with machine learning. In particular, exploiting reservoir
computing or echo state networks, we devise a "parameter-aware" scheme to train
the neural machine using asynchronous time series, i.e., in the parameter
regime prior to the onset of synchronization. A properly trained machine will
possess the power to predict the synchronization transition in that, with a
given amount of parameter drift, whether the system would remain asynchronous
or exhibit synchronous dynamics can be accurately anticipated. We demonstrate
the machine-learning based framework using representative chaotic models and
small network systems that exhibit continuous (second-order) or abrupt
(first-order) transitions. A remarkable feature is that, for a network system
exhibiting an explosive (first-order) transition and a hysteresis loop in
synchronization, the machine learning scheme is capable of accurately
predicting these features, including the precise locations of the transition
points associated with the forward and backward transition paths.


  We adapt the notion of processes to introduce an abstract framework for
dynamics in finite time, i.e.\ on compact time sets. For linear finite-time
processes a notion of hyperbolicity namely exponential monotonicity dichotomy
(EMD) is introduced, thereby generalizing and unifying several existing
approaches. We present a spectral theory for linear processes in a coherent
way, based only on a logarithmic difference quotient, prove robustness of EMD
with respect to a suitable (semi-)metric and provide exact perturbation bounds.
Furthermore, we give a complete description of the local geometry around
hyperbolic trajectories, including a direct and intrinsic proof of finite-time
analogues of the local (un)stable manifold theorem and theorem of linearized
asymptotic stability. As an application, we discuss our results for ordinary
differential equations on a compact time-interval.


  Regularization plays a pivotal role in ill-posed machine learning and inverse
problems. However, the fundamental comparative analysis of various
regularization norms remains open. We establish a small noise analysis
framework to assess the effects of norms in Tikhonov and RKHS regularizations,
in the context of ill-posed linear inverse problems with Gaussian noise. This
framework studies the convergence rates of regularized estimators in the small
noise limit and reveals the potential instability of the conventional
L2-regularizer. We solve such instability by proposing an innovative class of
adaptive fractional RKHS regularizers, which covers the L2 Tikhonov and RKHS
regularizations by adjusting the fractional smoothness parameter. A surprising
insight is that over-smoothing via these fractional RKHSs consistently yields
optimal convergence rates, but the optimal hyper-parameter may decay too fast
to be selected in practice.


  Quantum mechanical search induces polynomial speed up in an unsorted database
search process. In case of classical linear search the computational time
increases with the dimensionality of the query. However, quantum parallelism,
inherent to quantum systems, does not let multi-dimensional query processing
affect the computational time of the quantum search algorithm. In this letter,
a two-dimensional search process has been proposed. It has been shown that a
two-dimensional search process can be accomplished without increasing the
computational time due to implicit quantum parallelism


  Investigating microstructure of suspensions with particles having anisotropic
shape that share complex interactions is a challenging task leading to
competing claims. This work investigates phase behavior of one such system:
aqueous Laponite suspension, which is highly contested in the literature, using
rheological and microscopic tools. Remarkably, we observe that over a broad
range of Laponite (1.4 to 4 weight %) and salt concentrations (0 to 7 mM), the
system overwhelmingly demonstrates all the rheological characteristics of the
sol-gel transition leading to a percolated network. Analysis of the rheological
response leads to fractal dimension that primarily depends on the Laponite
concentration. We also obtain the activation energy for gelation, which is
observed to decrease with increase in Laponite as well as salt concentration.
Significantly, the cryo-TEM images of the post-gel state clearly show presence
of a percolated network formed by inter-particle bonds. The present work
therefore conclusively establishes the system to be in an attractive gel state
resolving a long-standing debate in the literature.


  News in social media such as Twitter has been generated in high volume and
speed. However, very few of them can be labeled (as fake or true news) in a
short time. In order to achieve timely detection of fake news in social media,
a novel deep two-path semi-supervised learning model is proposed, where one
path is for supervised learning and the other is for unsupervised learning.
These two paths implemented with convolutional neural networks are jointly
optimized to enhance detection performance. In addition, we build a shared
convolutional neural networks between these two paths to share the low level
features. Experimental results using Twitter datasets show that the proposed
model can recognize fake news effectively with very few labeled data.


  An autonomous system is constructed by a manufacturer, operates in a society
subject to norms and laws, and interacts with end users. All of these actors
are stakeholders affected by the behavior of the autonomous system. We address
the challenge of how the ethical views of such stakeholders can be integrated
in the behavior of an autonomous system. We propose an ethical recommendation
component called Jiminy which uses techniques from normative systems and formal
argumentation to reach moral agreements among stakeholders. A Jiminy represents
the ethical views of each stakeholder by using normative systems, and has three
ways of resolving moral dilemmas that involve the opinions of the stakeholders.
First, the Jiminy considers how the arguments of the stakeholders relate to one
another, which may already resolve the dilemma. Secondly, the Jiminy combines
the normative systems of the stakeholders such that the combined expertise of
the stakeholders may resolve the dilemma. Thirdly, and only if these two other
methods have failed, the Jiminy uses context-sensitive rules to decide which of
the stakeholders take preference over the others. At the abstract level, these
three methods are characterized by adding arguments, adding attacks between
arguments, and revising attacks between arguments. We show how a Jiminy can be
used not only for ethical reasoning and collaborative decision-making, but also
to provide explanations about ethical behavior.


  For Bezier curves, subdivision algorithms create control polygons as
piecewise linear (PL) approximations that converge in terms of Hausdorff
distance. We prove that the exterior angles of control polygons under
subdivision converge to 0 at the rate of $O(\sqrt{\frac{1}{2^i}})$, where $i$
is the number of subdivisions. This angular convergence is useful for
determining topological features. We use it to show homeomorphism between a
Bezier curve and its control polygon under subdivision. The constructive
geometric proofs yield closed-form formulas to compute sufficient numbers of
subdivision iterations to obtain small exterior angles and achieve
homeomorphism.


  We study transport properties and the charge quantization phenomenon in a
small metallic island connected to the leads through two quantum point contacts
(QPCs). The linear conductance is calculated perturbatively with respect to
weak tunneling and weak backscattering at QPCs as a function of the temperature
$T$ and gate voltage. The conductance shows Coulomb blockade (CB) oscillations
as a function of the gate voltage that decay with the temperature as a result
of thermally activated fluctuations of the charge in the island. The regimes of
quantum, $T \ll E_C$, and thermal, $T \gg E_C$, fluctuations are considered,
where $E_C$ is the charging energy of an isolated island. Our predictions for
CB oscillations in the quantum regime coincide with previous findings in [A.
Furusaki and K. A. Matveev, Phys. Rev. B {\bf 52}, 16676 (1995)]. In the
thermal regime the visibility of Coulomb blockade oscillations decays with the
temperature as $\sqrt{T/E_C}\exp(-\pi^2T/E_C)$, where the exponential
dependence originates from the thermal averaging over the instant charge
fluctuations, while the prefactor has a quantum origin. This dependence does
not depend on the strength of couplings to the leads. The differential
capacitance, calculated in the case of a single tunnel junction, shows the same
exponential decay, however the prefactor is linear in the temperature. This
difference can be attributed to the non-locality of the quantum effects. Our
results agree with the recent experiment [S. Jezouin {\em et al}., Nature {\bf
536}, 58 (2016)] in the whole range of the parameter $T/E_C$.


  Image fusion typically employs non-invertible neural networks to merge
multiple source images into a single fused image. However, for clinical
experts, solely relying on fused images may be insufficient for making
diagnostic decisions, as the fusion mechanism blends features from source
images, thereby making it difficult to interpret the underlying tumor
pathology. We introduce FusionINN, a novel decomposable image fusion framework,
capable of efficiently generating fused images and also decomposing them back
to the source images. FusionINN is designed to be bijective by including a
latent image alongside the fused image, while ensuring minimal transfer of
information from the source images to the latent representation. To the best of
our knowledge, we are the first to investigate the decomposability of fused
images, which is particularly crucial for life-sensitive applications such as
medical image fusion compared to other tasks like multi-focus or multi-exposure
image fusion. Our extensive experimentation validates FusionINN over existing
discriminative and generative fusion methods, both subjectively and
objectively. Moreover, compared to a recent denoising diffusion-based fusion
model, our approach offers faster and qualitatively better fusion results.


  We characterise the kinematic image of the constraint variety of a 2R dyad as
a regular ruled quadric in a 3-space that contains a "null quadrilateral".
Three prescribed poses determine, in general, two such quadrics. This allows us
to modify a recent algorithm for the synthesis of 6R linkages in such a way
that two consecutive revolute axes coincide, thus producing a 5R linkage. Using
the classical geometry of twisted cubics on a quadric, we explain some of the
peculiar properties of the the resulting synthesis procedure for 5R linkages.


  I discuss the use of cross correlations between galaxies with distance
information and projected weak lensing dark matter maps to obtain a fully three
dimensional dark matter map and power spectrum. On large scales l<100 one
expects the galaxies to be biased, but not stochastic. I show that this allows
a simultaneous solution of the full 3-D evolving galaxy bias and the dark
matter power spectrum simultaneously. Within the photo-z information of the CFH
lensing legacy survey, this allows a threefold reduction of statistical error,
while a cross correlation with CLAR or other deep spectroscopic surveys allows
a tenfold improvement in dark matter power accuracy on linear scales. This
makes lensing surveys more sensitive to the cosmic equation of state and the
neutrino masses.


  A low-emittance, high-intensity atomic beam of muonium ($\mathrm{M}=\mu^+ +
\mathrm{e}^-$) using superfluid helium as muon-to-muonium converter is being
developed at the Paul Scherrer Institute (PSI). This beam could advance laser
spectroscopy of muonium and allow the first atomic interferometry experiments
for the direct observation of the M gravitational interaction. In this paper,
we describe the development of compact detection schemes which resulted in the
background-suppressed observation of atomic muonium in vacuum, and can be
adapted for cryogenic measurements. Using these setups, we compared the
emission characteristics of various muonium production targets using low
momentum ($p_{\mu} = 11$-$13~$MeV/c) muons, and observed muonium emission from
zeolite targets into vacuum for the first time. For a specific laser-ablated
aerogel target, we determined a muon-to-vacuum-muonium conversion efficiency of
$7.23 \pm 0.05 \text{(stat)} ^{+1.06}_{-0.76}\text{(sys)}\,\text{%}$, assuming
thermal emission of muonium. Moreover, we investigated muonium-helium
collisions and from it we determined an upper temperature limit of 0.3 K for
the superfluid helium converter.


  Ray optics has proven to be an effcient and versatile tool to describe
dielectric optical microcavities and their far-field emission based on the
principle of ray-wave correspondence. Whereas often the well-known ray-optics
at planar interfaces yields reasonable results, semiclassically and
boundary-curvature induced corrections will become more important as the cavity
size is further reduced. In this paper we summarize the various ray optics
descriptions of optical microresonators, paying in addition special attention
to the differences that arise between chaotic vs. non-chaotic (integrable or
nearly integrable) resonator geometries, respectively. Whereas the far-field
pattern in the chaotic case is known to be determined by the overlap of the
unstable manifold with the leaky region, it results from the emission of
trajectories with the smallest nonzero decay rates in the non-chaotic
situation. We present an enhanced ray optical description, extended by
wave-inspired (semiclassical) corrections, and discuss their consequences for
the ray dynamics. In particular we find clear indications for the presence of
attractors resulting from the non-Hamiltonian character of the extended ray
dynamics in phase space. We illustrate their impact on the far-field emission
and show that it can considerably differ from the conventional ray description
result.


  We show that one of exact solutions of the second-order Dirac-Coulomb
equation were pseudo. In the corresponding original literature, it was
considered that the mass of the electron with a Coulomb potential was
position-dependent, but the obtained eigenvalues set was not the inevitable
mathematical deduction of the given second-order Dirac equation, and the
second-order Dirac equations were not the inevitable mathematical deduction of
the given couplet first-order Dirac equation with the position-dependent mass
of the electron. In the present paper, we obtain the correct solution of the
introduced first-order differential equations. This new solution would be
tenable only when the wave equation is correct, but there is not any experiment
date to validate the so-called position-dependent of the electron in the
Coulomb field.


  This report presents a robust composite resonator known as the high overtone
bulk acoustic wave resonator (HBAR) for demonstrating experimentally the
ability of the resonator to tune the envelope of the spectrum by applying dc
bias. The reported HBAR exhibits exceptionally high-quality factor in the
frequency range of 700 MHz to 3 GHz and high effective coupling coefficient
over the broad range of microwave frequencies. The HBAR is based on thin
Ba0.5Sr0.5TiO3 film sandwiched between two electrodes forming a transducer,
supported by a thick sapphire substrate which is a low acoustic loss material.
The resonator works on the principle of induced piezoelectricity due to the
applied dc bias. The minima of the envelope changes from 1.16 GHz with S11 of
-3.51 dB at 100 kV/cm bias to 1.90 GHz with S11 of -42.23 dB at 700 kV/cm bias,
giving a relative tunability of the envelope to be around 64%. The spacing of
the parallel resonance frequency (SPRF) for different bias voltages are also
presented in this report. The quality factor of the resonator is over 22,000 at
around 2GHz.


  The ROC curve is the major tool for assessing not only the performance but
also the fairness properties of a similarity scoring function. In order to draw
reliable conclusions based on empirical ROC analysis, accurately evaluating the
uncertainty level related to statistical versions of the ROC curves of interest
is absolutely necessary, especially for applications with considerable societal
impact such as Face Recognition. In this article, we prove asymptotic
guarantees for empirical ROC curves of similarity functions as well as for
by-product metrics useful to assess fairness. We also explain that, because the
false acceptance/rejection rates are of the form of U-statistics in the case of
similarity scoring, the naive bootstrap approach may jeopardize the assessment
procedure. A dedicated recentering technique must be used instead. Beyond the
theoretical analysis carried out, various experiments using real face image
datasets provide strong empirical evidence of the practical relevance of the
methods promoted here, when applied to several ROC-based measures such as
popular fairness metrics.


  The effect due to the inter-subsystem coupling on the off-diagonal geometric
phase in a composite system is investigated. We analyze the case where the
system undergo an adiabatic evolution. Two coupled qubits driven by
time-dependent external magnetic fields are presented as an example, the
off-diagonal geometric phase as well as the adiabatic condition are examined
and discussed.


  We compute the tachyon potential to level 4 in NS superstring field theory.
We obtain 89% of the conjectured vacuum energy.


  In optimization the duality gap between the primal and the dual problems is a
measure of the suboptimality of any primal-dual point. In classical mechanics
the equations of motion of a system can be derived from the Hamiltonian
function, which is a quantity that describes the total energy of the system. In
this paper we consider a convex optimization problem consisting of the sum of
two convex functions, sometimes referred to as a composite objective, and we
identify the duality gap to be the 'energy' of the system. In the Hamiltonian
formalism the energy is conserved, so we add a contractive term to the standard
equations of motion so that this energy decreases linearly (i.e.,
geometrically) with time. This yields a continuous-time ordinary differential
equation (ODE) in the primal and dual variables which converges to zero duality
gap, i.e., optimality. This ODE has several useful properties: it induces a
natural operator splitting; at convergence it yields both the primal and dual
solutions; and it is invariant to affine transformation despite only using
first order information. We provide several discretizations of this ODE, some
of which are new algorithms and others correspond to known techniques, such as
the alternating direction method of multipliers (ADMM). We conclude with some
numerical examples that show the promise of our approach. We give an example
where our technique can solve a convex quadratic minimization problem orders of
magnitude faster than several commonly-used gradient methods, including
conjugate gradient, when the conditioning of the problem is poor. Our framework
provides new insights into previously known algorithms in the literature as
well as providing a technique to generate new primal-dual algorithms.


  The compound Ce3Co4Sn13 is an extremely heavy cubic heavy fermion system with
a low temperature electronic specific heat of order ~4 J/mol-K2. If the
compound is nonmagnetic, it would be one of the heaviest nonmagnetic Ce-based
heavy fermions reported to date and therefore would be expected to lie
extremely close to a quantum critical point. However, a broad peak of unknown
origin is observed at 0.8 K in the specific heat and magnetic susceptibility,
suggesting the possibility of antiferromagnetic order. We present neutron
diffraction data from polycrystalline samples which do not show any sign of
magnetic scattering below 0.8 K. In addition, we present inelastic neutron
scattering data from a single crystal sample which is consistent with the 1.2 K
energy scale for Kondo spin fluctuations determined from specific heat
measurements.


  Akin's notion of good measure, introduced to classify measures on Cantor sets
has been translated to dimension groups and corresponding traces by Bezuglyi
and the author, but emphasizing the simple (minimal dynamical system) case.
Here we deal with non-simple (non-minimal) dimension groups. In particular,
goodness of tensor products of large classes of non-good traces (measures) is
established. We also determine the pure faithful traces on the dimension groups
associated to xerox type actions on AF C*-algebras; the criteria turn out to
involve algebraic geometry and number theory. We also deal with a coproduct of
dimension groups, wherein, despite expectations, goodness of direct sums is
nontrivial. In addition, we verify a conjecture of [BeH] concerning good
subsets of Choquet simplices, in the finite-dimensional case.


  To investigate the physics of mass accretion onto weakly-magnetized neutron
stars, 95 archival RXTE datasets of an atoll source 4U 1608-522, acquired over
1996-2004 in so-called upper-banana state, were analyzed. The object meantime
exhibited 3-30 keV luminosity in the range of <~ 10^35 - 4 x 10^37 erg s^-1,
assuming a distance of 3.6 kpc. The 3-30 keV PCA spectra, produced one from
each dataset, were represented successfully with a combination of a soft and a
hard component, of which the presence was revealed in a model-independent
manner by studying spectral variations among the observations. The soft
component is expressed by so-called multi-color disk model with a temperature
of ~1.8 keV, and is attributed to the emission from an optically-thick standard
accretion disk. The hard component is a blackbody emission with a temperature
of ~2.7 keV, thought to be emitted from the neutron-star surface. As the total
luminosity increases, a continuous decrease was observed in the ratio of the
blackbody luminosity to that of the disk component. This property suggests that
the matter flowing through the accretion disk gradually becomes difficult to
reach the neutron-star surface, presumably forming outflows driven by the
increased radiation pressure. On time scales of hours to days, the overall
source variability was found to be controlled by two independent variables; the
mass accretion rate, and the innermost disk radius which changes both
physically and artificially.


  The isovector partners of the X(3872), recently found at BES III, Belle and
CLEO-c were predicted in a simple model based on the chromomagnetic interaction
among quarks (H. Hogaasen, J-M. Richard and P. Sorba, Phys. Rev. D73, 054013,
2006). The extension to the hidden-beauty sector is discussed.


  As manifested in the similarity relation of diffuse light transport, it is
difficult to assess single scattering characteristics from multiply scattered
light. We take advantage of the limited validity of the diffusion approximation
of light transport and demonstrate, experimentally and numerically, that even
deep into the multiple scattering regime, time-resolved detection of
transmitted light allows simultaneous assessment of both single scattering
anisotropy and scattering mean free path, and therefore also macroscopic
parameters like the diffusion constant and the transport mean free path. This
is achieved via careful assessment of early light and matching against Monte
Carlo simulations of radiative transfer.


  Advances in material processing such as silicon micromachining are opening
the way to vacuum microelectronics. Two-dimensional vacuum components can be
fabricated using the microsystems processes. We developed such devices using a
single metal layer and silicon micromachining by DRIE. The latter technological
step has significant impact on the characteristics of the vacuum components.
This paper presents a brief summary of electron emission possibilities and the
design leading to the fabrication of a lateral field emission diode. First
measurement results and the aging of the devices are also discussed.


  We introduce colored Jones polynomials of nanowords and their
categorification. We also prove the existence of a Khovanov-type bicomplex
which has three grades.


  Random testing approaches work by generating inputs at random, or by
selecting inputs randomly from some pre-defined operational profile. One
long-standing question that arises in this and other testing contexts is as
follows: When can we stop testing? At what point can we be certain that
executing further tests in this manner will not explore previously untested
(and potentially buggy) software behaviors? This is analogous to the question
in Machine Learning, of how many training examples are required in order to
infer an accurate model. In this paper we show how probabilistic approaches to
answer this question in Machine Learning (arising from Computational Learning
Theory) can be applied in our testing context. This enables us to produce an
upper bound on the number of tests that are required to achieve a given level
of adequacy. We are the first to enable this from only knowing the number of
coverage targets (e.g. lines of code) in the source code, without needing to
observe a sample test executions. We validate this bound on a large set of Java
units, and an autonomous driving system.


  This paper provides a quantitative method for estimating the risk associated
with candidate transportation technology, before it is developed and deployed.
The proposed solution extends previous methods that rely exclusively on
low-fidelity human-in-the-loop experimental data, or high-fidelity traffic
data, by adopting a multifidelity approach that leverages data from both low-
and high-fidelity sources. The multifidelity method overcomes limitations
inherent to existing approaches by allowing a model to be trained
inexpensively, while still assuring that its predictions generalize to the
real-world. This allows for candidate technologies to be evaluated at the stage
of conception, and enables a mechanism for only the safest and most effective
technology to be developed and released.


  We are interested in the structure of the crystal graph of level $l$ Fock
spaces representations of $\mathcal{U}_q (\widehat{\mathfrak{sl}_e})$. Since
the work of Shan [26], we know that this graph encodes the modular branching
rule for a corresponding cyclotomic rational Cherednik algebra. Besides, it
appears to be closely related to the Harish-Chandra branching graph for the
appropriate finite unitary group, according to [8]. In this paper, we make
explicit a particular isomorphism between connected components of the crystal
graphs of Fock spaces. This so-called "canonical" crystal isomorphism turns out
to be expressible only in terms of: - Schensted's classic bumping procedure, -
the cyclage isomorphism defined in [13], - a new crystal isomorphism, easy to
describe, acting on cylindric multipartitions. We explain how this can be seen
as an analogue of the bumping algorithm for affine type $A$. Moreover, it
yields a combinatorial characterisation of the vertices of any connected
component of the crystal of the Fock space.


  This study employs an improved volume of fluid method and adaptive mesh
refinement algorithm to numerically investigate the internal jet-like mixing
upon the coalescence of two initially stationary droplets of unequal sizes. The
emergence of the internal jet is attributed to the formation of a main vortex
ring, as the jet-like structure shows a strong correlation with the main vortex
ring inside the merged droplet. By tracking the evolution of the main vortex
ring together with its circulation, we identified two mechanisms that are
essential to the internal-jet formation: the vortex-ring growth and the
vortex-ring detachment. Recognizing that the manifestation of the
vortex-ring-induced jet physically relies on the competition between the
convection and viscous dissipation of the vortex ring, we further developed and
substantiated a vortex-ring-based Reynolds number criterion to interpret the
occurrence of the internal jet at various Ohnesorge numbers and size ratios.
For the merged droplet with apparent jet formation, the average mixing rate
after jet formation increases monotonically with the vortex-ring Reynolds
number, which therefore serves as an approximate measure of the jet strength.
In this respect, stronger internal jet is responsible for enhanced mixing of
the merged droplet.


  We report a joint simulation and theoretical study of the liquid-vapor phase
behaviour of a fluid in which polydispersity in the particle size couples to
the strength of the interparticle interactions. Attention is focussed on the
case in which the particles diameters are distributed according to a fixed
Schulz form with degree of polydispersity $\delta=14%$. The coexistence
properties of this model are studied using grand canonical ensemble Monte Carlo
simulations and moment free energy calculations. We obtain the cloud and shadow
curves as well as the daughter phase density distributions and fractional
volumes along selected isothermal dilution lines. In contrast to the case of
size-{\em independent} interaction strengths (N.B. Wilding, M. Fasolo and P.
Sollich, J. Chem. Phys. {\bf 121}, 6887 (2004)), the cloud and shadow curves
are found to be well separated, with the critical point lying significantly
below the cloud curve maximum. For densities below the critical value, we
observe that the phase behaviour is highly sensitive to the choice of upper
cutoff on the particle size distribution. We elucidate the origins of this
effect in terms of extremely pronounced fractionation effects and discuss the
likely appearance of new phases in the limit of very large values of the
cutoff.


  The main result of this paper is that in order to prove the local
uniformization theorem for local rings it is enough to prove it for rank one
valuations. Our proof does not depend on the nature of the class of local rings
for which we want to prove local uniformization. We prove also the reductions
for different versions of the local uniformization theorem.


  We propose the design of a Resonance SPin-echo spECtrometer for exTreme
studies, RESPECT, that is ideally suited for the exploration of non-dispersive
processes such as diffusion, crystallization, slow dynamics, tunneling
processes, crystal electric field excitations, and spin fluctuations. It is a
variant of the conventional neutron spin-echo technique (NSE) by i) replacing
the long precession coils by pairs of longitudinal neutron spin-echo coils
combined with RF-spin flippers and ii) by stabilizing the neutron polarization
with small longitudinal guide fields that can in addition be used as field
subtraction coils thus allowing to adjust the field integrals over a range of 8
orders of magnitude. Therefore, the dynamic range of RESPECT can in principle
be varied over 8 orders of magnitude in time, if neutrons with the required
energy are made available. Similarly as for existing NSE-spectrometers, spin
echo times of up to approximately 1 microsecond can be reached if the
divergence and the correction elements are properly adjusted. Thanks to the
optional use of neutron guides and the fact that the currents for the
correction coils are much smaller than in standard NSE, intensity gains of at
least one order of magnitude are expected , making the concept of RESPECT also
competitive for operation at medium flux neutron sources. RESPECT can also be
operated in a MIEZE configuration allowing the investigation of relaxation
processes in depolarizing environments as they occur when magnetic fields are
applied at the sample position, i.e. for the investigation of the dynamics of
flux lines in superconductors, magnetic fluctuations in ferromagnetic
materials, and samples containing hydrogen.


  Parametric empirical Bayes (EB) estimators have been widely used in variety
of fields including small area estimation, disease mapping. Since EB estimator
is constructed by plugging in the estimator of parameters in prior
distributions, it might perform poorly if the estimator of parameters is
unstable. This can happen when the number of samples are small or moderate.
This paper suggests bootstrapping averaging approach, known as "bagging" in
machine learning literatures, to improve the performances of EB estimators. We
consider two typical hierarchical models, two-stage normal hierarchical model
and Poisson-gamma model, and compare the proposed method with the classical
parametric EB method through simulation and empirical studies.


  We propose diatomic molecules built from gold and carbon-group atoms as
promising candidates for optical cycling and precision measurements. We show
that this class of molecules (AuX, X = C, Si, Ge, Sn, Pb) features
laser-accessible electronic transitions with nearly diagonal Franck-Condon
factors. The $^2\Pi_{1/2}$ ground states can be easily polarized in the
laboratory frame and have near-zero magnetic moments, valuable features for
quantum science and precision measurement applications. The sensitivities of
AuX molecules to the electron electric dipole moment (EDM) are found to be
favorable, with effective electric fields of 10-30 GV/cm. Together, these
features imply that AuX molecules may enable significantly improved searches
for time-reversal symmetry violation.


  We investigate whether inflation in the early universe can be induced by an
extra component of a five-dimensional ${\rm U(1)}$ gauge field in the
Randall-Sundrum warped spacetime or not. We show that an effective potential
obtained by quantum corrections can act as an inflaton potential by finding
parameter regions consistent with Planck 2018 results. In our model, fields
involved in inflation obey a different type of boundary condition from that of
the visible particles, and a surviving Wilson line phase can play a specific
role for physics beyond the standard model.


  This paper is the first thorough investigation into the coarsest notion of
bisimilarity for the applied pi-calculus that is a congruence relation: open
barbed bisimilarity. An open variant of labelled bisimilarity (quasi-open
bisimilarity), better suited to constructing bisimulations, is proven to
coincide with open barbed bisimilarity. These bisimilary congruences are shown
to be characterised by an intuitionistic modal logic that can be used, for
example, to describe an attack on privacy whenever a privacy property is
violated. Open barbed bisimilarity provides a compositional approach to
verifying cryptographic protocols, since properties proven can be reused in any
context, including under input prefix. Furthermore, open barbed bisimilarity is
sufficiently coarse for reasoning about security and privacy properties of
cryptographic protocols; in constrast to the finer bisimilarity congruence,
open bisimilarity, which cannot verify certain privacy properties.


  We introduce a Quantum Monte Carlo (QMC) method which efficiently simulates
in a sign-problem-free way a broad class of frustrated $S=1/2$ models with
competing antiferromagnetic interactions. Our scheme uses the basis of total
spin eigenstates of clusters of spins to avoid the severe sign problem faced by
other QMC methods. We also flag important limitations of the new method, and
comment on possibilities for further progress.


  We explore the self-regulation of star formation using a large suite of high
resolution hydrodynamic simulations, focusing on molecule-dominated regions
(galactic centers and [U]LIRGS) where feedback from star formation drives
highly supersonic turbulence. In equilibrium the total midplane pressure,
dominated by turbulence, must balance the vertical weight of the ISM. Under
self-regulation, the momentum flux injected by feedback evolves until it
matches the vertical weight. We test this flux balance in simulations spanning
a range of parameters, including surface density $\Sigma$, momentum injected
per stellar mass formed ($p_*/m_*$), and angular velocity. The simulations are
2D radial-vertical slices, including both self-gravity and an external
potential that confines gas to the disk midplane. After the simulations reach a
steady state in all relevant quantities, including the star formation rate
$\Sigma_{SFR}$, there is remarkably good agreement between the vertical weight,
the turbulent pressure, and the momentum injection rate from supernovae. Gas
velocity dispersions and disk thicknesses increase with $p_*/m_*$. The
efficiency of star formation per free-fall time at the mid-plane density is
insensitive to the local conditions and to the star formation prescription in
very dense gas. We measure efficiencies $\sim$0.004-0.01, consistent with low
and approximately constant efficiencies inferred from observations. For
$\Sigma\in$(100--1000) \msunpc, we find $\Sigma_{SFR}\in$(0.1--4) \sfrunits,
generally following a $\Sigma_{SFR}\propto \Sigma^2$ relationship. The measured
relationships agree very well with vertical equilibrium and with turbulent
energy replenishment by feedback within a vertical crossing time. These
results, along with the observed $\Sigma_{SFR}-\Sigma$ relation in high density
environments, provide strong evidence for the self-regulation of star
formation.


  Some features of neutron emission from dense plasma focus suggest that the
participating deuterons have energy in the range of 105 eV and have a
directionality of toroidal motion. Theoretical models of these devices assume
that the plasma evolves through a purely irrotational flow and thus fail to
predict such solenoidal flow on the scale of the plasma dimensions. Predictions
of a relaxation theory are consistent with experimental data [S K H Auluck,
Physics of Plasmas,18, 032508 (2011)], but the assumptions upon which it is
based are not compatible with known features of these devices. There is thus no
satisfactory theoretical construct which provides the necessity for solenoidal
flow in these devices. This paper proposes such theoretical construct, namely,
the principle of constrained dynamics, and describes an experiment which
provides support for this idea. The experiment consisted of low inductance,
self-breaking spark discharge in helium at a pressure ~100 hPa between two
pointed electrodes separated by 30-50 mm distance kept inside a vacuum chamber
mounted on a low inductance high voltage capacitor. The current derivative
signal showed reproducible sharp dips at all the extrema of the damped
sinusoidal discharge. A planar diamagnetic loop centered with and perpendicular
to the discharge axis consistently showed a signal representing rate of change
of axial magnetic flux. A qualitative explanation of observed phenomena is
obtained using a simple model using the proposed principle.


  We show that any minimal Cayley graph of a (finitely generated) generalized
dihedral or nilpotent group has chromatic number at most 3, while 4 colors are
sometimes necessary for soluble groups. On the other hand we construct graphs
of unbounded chromatic number that admit a proper edge coloring such that each
cycle has some color at least twice. The latter disproves a conjecture of
Babai'78 that would have implied that all minimal Cayley graphs have bounded
chromatic number -- a problem that remains open.


  A cosmic ray detection system, consisting of standardized detector stations
connected through the Internet, is described. The system can be used for
detecting air showers that arrive over a wide area with correlated time. The
data at each site are exchanged in (quasi) real time, which makes the system
suitable for displaying cosmic ray arrivals at museumns and schools.


  General bounds are presented for the diameters of orbital graphs of finite
affine primitive permutation groups. For example, it is proved that the orbital
diameter of a finite affine primitive permutation group with a nontrivial point
stabilizer $ H \leq \mathrm{GL}(V) $, where the vector space $ V $ has
dimension $ d $ over the prime field, can be bounded in terms of $ d $ and $
\log |V| / \log |H| $ only. Several infinite families of affine primitive
permutation groups with large orbital diameter are constructed. The results are
independent from the classification of finite simple groups.


  We study the real-time dynamics of string breaking in quantum electrodynamics
in one spatial dimension. A two-stage process with a clear separation of time
and energy scales for the fermion--antifermion pair creation and subsequent
charge separation leading to the screening of external charges is found. Going
away from the traditional setup of external static charges, we establish the
phenomenon of multiple string breaking by considering dynamical charges flying
apart.


  We present soft (0.5-2 keV) X-ray luminosity functions (XLFs) in the Great
Observatories Origins Deep Survey (GOODS) fields, derived for galaxies at
z~0.25 and 0.75. SED fitting was used to estimate photometric redshifts and
separate galaxy types, resulting in a sample of 40 early-type galaxies and 46
late-type galaxies. We estimate k-corrections for both the X-ray/optical and
X-ray/NIR flux ratios, which facilitates the separation of AGN from the
normal/starburst galaxies. We fit the XLFs with a power-law model using both
traditional and Markov-Chain Monte Carlo (MCMC) procedures. The XLFs differ
between z<0.5 and z>0.5, at >99% significance levels for early-type, late-type
and all (early and late-type) galaxies.We also fit Schechter and log-normal
models to the XLFs, fitting the low and high redshift XLFs for a given sample
simultaneously assuming only pure luminosity evolution. In the case of
log-normal fits, the results of MCMC fitting of the local FIR luminosity
function were used as priors for the faint and bright-end slopes (similar to
``fixing'' these parameters at the FIR values except here the FIR uncertainty
is included). The best-fit values of the change in log L* with redshift were
dlogL* = 0.23 +/- 0.16 dex (for early-type galaxies) and 0.34 +/- 0.12 dex (for
late-type galaxies), corresponding to (1+z)^1.6 and (1+z)^2.3. These results
were insensitive to whether the Schechter or log-normal function was adopted.


  The leading color-singlet contribution to the fragmentation function for a
gluon to split into spin-triplet S-wave quarkonium is presented. In the case of
charmonium, we find that this color-singlet term is always negligible compared
to the leading color-octet contribution.


  We aim at reproducing the chemical evolution of the bulge of M31 by means of
a detailed chemical evolution model, including radial gas flows coming from the
disk. We study the impact of the initial mass function, the star formation rate
and the time scale for bulge formation on the metallicity distribution function
of stars. We compute several models of chemical evolution using the metallicity
distribution of dwarf stars as an observational constraint for the bulge of
M31. Then, by means of the model which best reproduces the metallicity
distribution function, we predict the [X/Fe] vs. [Fe/H] relations for several
chemical elements (O, Mg, Si, Ca, C, N). Our best model for the bulge of M31 is
obtained by means of a robust statistical method and assumes a Salpeter initial
mass function, a Schmidt-Kennicutt law for star formation with an exponent
k=1.5, an efficiency of star formation of $\sim 15\pm 0.27\, Gyr^{-1}$, and an
infall timescale of $\sim 0.10\pm 0.03$Gyr. Our results suggest that the bulge
of M31 formed very quickly by means of an intense star formation rate and an
initial mass function flatter than in the solar vicinity but similar to that
inferred for the Milky Way bulge. The [$\alpha$/Fe] ratios in the stars of the
bulge of M31 should be high for most of the [Fe/H] range, as is observed in the
Milky Way bulge. These predictions await future data to be proven.


  After release from the trap the momentum distribution of an impenetrable gas
asymptotically approaches that of a spinless noninteracting Fermi gas in the
initial trap. This phenomenon is called dynamical fermionization and, very
recently, has been experimentally confirmed in the case of the Lieb-Liniger
model in the Tonks-Girardeau regime. We prove analytically and confirm
numerically that following the removal of axial confinement the strongly
interacting Bose-Fermi mixture exhibits dynamical fermionization and the
asymptotical momentum distribution of each component has the same shape as its
density profile at $t=0$. Under a sudden change of the trap frequency to a new
non-zero value the dynamics of both fermionic and bosonic momentum
distributions presents characteristics which are similar to the case of single
component bosons experiencing a similar quench. Our results are derived using a
product representation for the correlation functions which, in addition to
analytical considerations, can be implemented numerically very easily with
complexity which scales polynomially in the number of particles.


  In this paper, we focus on the Audio-Visual Question Answering (AVQA) task,
which aims to answer questions regarding different visual objects, sounds, and
their associations in videos. The problem requires comprehensive multimodal
understanding and spatio-temporal reasoning over audio-visual scenes. To
benchmark this task and facilitate our study, we introduce a large-scale
MUSIC-AVQA dataset, which contains more than 45K question-answer pairs covering
33 different question templates spanning over different modalities and question
types. We develop several baselines and introduce a spatio-temporal grounded
audio-visual network for the AVQA problem. Our results demonstrate that AVQA
benefits from multisensory perception and our model outperforms recent A-, V-,
and AVQA approaches. We believe that our built dataset has the potential to
serve as testbed for evaluating and promoting progress in audio-visual scene
understanding and spatio-temporal reasoning. Code and dataset:
http://gewu-lab.github.io/MUSIC-AVQA/


  This paper reviews some recent progress on QCD functional integrals at
nonzero chemical potentials. One issue discussed is the use of QCD inequalities
for this regime. In particular, the positivity of the integrand of particular
Euclidean space functional integrals for two-flavor QCD with degenerate quark
masses is used to demonstrate that the free energy per unit volume for QCD with
a baryon chemical potential $\mu_B$ (and zero isospin chemical potential) is
necessarily greater than the free energy with isospin chemical potential $\mu_I
= \frac{2 \mu_B}{N_c} $ (and zero baryon chemical potential). This result may
be of use in model finite density systems. A corollary to this result is a
rigorous {\it ab initio} bound on the nucleon mass. The second major issue
addressed is the so-called ``Silver Blaze'' problem: the fact that at zero
temperature and chemical potentials less than some critical value the free
energy remains as that of the vacuum. This is puzzling in the context of a
functional integral since a chemical potential affects the functional
determinant of the Dirac operator and any nonzero $\mu$ changes every
eigenvalue of the Dirac operator compared to the $\mu=0$ value. The isospin
Silver Blaze problem is solved through the study of the spectrum of the
operator $\gamma_0 (\dslash + m)$. The status of the baryon Silver Blaze
problem is briefly discussed.


  The outflows from neutrino-cooled black-hole (BH) accretion disks formed in
neutron-star mergers or cores of collapsing stars are expected to be
neutron-rich enough to explain a large fraction of elements created by the
rapid neutron-capture (r-) process, but their precise chemical composition
remains elusive. Here, we investigate the role of fast neutrino flavor
conversion, motivated by the findings of our post-processing analysis that
shows evidence of electron-neutrino lepton-number (ELN) crossings deep inside
the disk, hence suggesting possibly non-trivial effects due to neutrino flavor
mixing. We implement a parametric, dynamically self-consistent treatment of
fast conversion in time-dependent simulations and examine the impact on the
disk and its outflows. By activating the, otherwise inefficient, emission of
heavy-lepton neutrinos, fast conversions enhance the disk cooling rates and
reduce the absorption rates of electron-type neutrinos, causing a reduction of
the electron fraction in the disk by 0.03-0.06 and in the ejected material by
0.01-0.03. The r-process yields are enhanced by typically no more than a factor
of two, rendering the overall impact of fast conversions modest. The kilonova
is prolonged as a net result of increased lanthanide opacities and enhanced
radioactive heating rates. We observe only mild sensitivity to the disk mass,
the condition for the onset of flavor conversion, and to the considered cases
of flavor mixing. Remarkably, parametric models of flavor mixing that conserve
the lepton numbers per family result in an overall smaller impact than models
invoking three-flavor equipartition, often assumed in previous works.


  We perform the projector quantum Monte Carlo (QMC) simulation to study the
trion formation and quantum phase transition in the half-filled attractive
SU(3) Hubbard model on a honeycomb lattice. With increasing attractive Hubbard
interaction, our simulations demonstrate a continuous quantum phase transition
from the semimetal to charge density wave (CDW) at the critical coupling
$U_c/t=-1.52(2)$. The critical exponents $\nu=0.82(3)$ and $\eta=0.58(4)$
determined by the QMC simulation remarkably disagree with those of the $N=3$
chiral Ising universality class suggested by the effective Gross-Neveu-Yukawa
(GNY) theory, but coincide with the $N=1$ chiral Ising universality class. In
the CDW phase, we show that on-site and off-site trions coexist and the
off-site trion forms a local bond state. Our work not only illustrates the
formation of off-site trions in two-dimensional Hubbard model, but also raises
doubts about the extent of applicability of GNY model on the attractive SU(3)
Dirac fermions.


  The generalization of Kasteleyn and Fortuin clusters formalism is introduced
in XY (or more generally O(n)) models. Clusters geometrical structure may be
linked to spin physical properties as correlation functions. To investigate
percolative characteristics, the new cluster definition is analytically
explored in one dimension and with Monte Carlo simulations in 2D and 3D
frustrated and unfrustrated n-clock models. In these models (also in
unfrustrated cases for large n) the percolative transition temperature is
higher than the usual thermodynamical critical one.


  Intervening metal absorption lines in the spectra of z > 6 quasars are
fundamental probes of the ionization state and chemical composition of
circumgalactic and intergalactic gas near the end of the reionization epoch.
Large absorber samples are required to robustly measure typical absorber
properties and to refine models of the synthesis, transport, and ionization of
metals in the early Universe. The "Ultimate XSHOOTER legacy survey of quasars
at z~5.8-6.6" (XQR-30) has obtained high signal-to-noise spectra of 30 luminous
quasars, nearly quadrupling the existing sample of 12 high quality z~6 quasar
spectra. We use this unprecedented sample to construct a catalog of 778 systems
showing absorption in one or more of MgII (360 systems), FeII (184), CII (46),
CIV (479), SiIV (127), and NV (13) which span 2 < z < 6.5. This catalog
significantly expands on existing samples of z > 5 absorbers, especially for
CIV and SiIV which are important probes of the ionizing photon background at
high redshift. The sample is 50% (90%) complete for rest-frame equivalent
widths W > 0.03AA (0.09AA). We publicly release the absorber catalog along with
completeness statistics and a Python script to compute the absorption search
path for different ions and redshift ranges. This dataset is a key legacy
resource for studies of enriched gas from the era of galaxy assembly to cosmic
noon, and paves the way for even higher redshift studies with the James Webb
Space Telescope and 30m-class telescopes.


  Existing instance segmentation techniques are primarily tailored for
high-visibility inputs, but their performance significantly deteriorates in
extremely low-light environments. In this work, we take a deep look at instance
segmentation in the dark and introduce several techniques that substantially
boost the low-light inference accuracy. The proposed method is motivated by the
observation that noise in low-light images introduces high-frequency
disturbances to the feature maps of neural networks, thereby significantly
degrading performance. To suppress this ``feature noise", we propose a novel
learning method that relies on an adaptive weighted downsampling layer, a
smooth-oriented convolutional block, and disturbance suppression learning.
These components effectively reduce feature noise during downsampling and
convolution operations, enabling the model to learn disturbance-invariant
features. Furthermore, we discover that high-bit-depth RAW images can better
preserve richer scene information in low-light conditions compared to typical
camera sRGB outputs, thus supporting the use of RAW-input algorithms. Our
analysis indicates that high bit-depth can be critical for low-light instance
segmentation. To mitigate the scarcity of annotated RAW datasets, we leverage a
low-light RAW synthetic pipeline to generate realistic low-light data. In
addition, to facilitate further research in this direction, we capture a
real-world low-light instance segmentation dataset comprising over two thousand
paired low/normal-light images with instance-level pixel-wise annotations.
Remarkably, without any image preprocessing, we achieve satisfactory
performance on instance segmentation in very low light (4~\% AP higher than
state-of-the-art competitors), meanwhile opening new opportunities for future
research.


  We study the definability of convex valuations on ordered fields, with a
particular focus on the distinguished subclass of henselian valuations. In the
setting of ordered fields, one can consider definability both in the language
of rings $\mathcal{L}_{\mathrm{r}}$ and in the richer language of ordered rings
$\mathcal{L}_{\mathrm{or}}$. We analyse and compare definability in both
languages and show the following contrary results: while there are convex
valuations that are definable in the language $\mathcal{L}_{\mathrm{or}}$ but
not in the language $\mathcal{L}_{\mathrm{r}}$, any
$\mathcal{L}_{\mathrm{or}}$-definable henselian valuation is already
$\mathcal{L}_{\mathrm{r}}$-definable. To prove the latter, we show that the
value group and the ordered residue field of an ordered henselian valued field
are stably embedded (as an ordered abelian group, respectively as an ordered
field). Moreover, we show that in almost real closed fields any
$\mathcal{L}_{\mathrm{or}}$-definable valuation is henselian.


  This chapter presents SMuGA, an integration of symbiogenesis with the
Multiset Genetic Algorithm (MuGA). The symbiogenetic approach used here is
based on the host-parasite model with the novelty of varying the length of
parasites along the evolutionary process. Additionally, it models
collaborations between multiple parasites and a single host. To improve
efficiency, we introduced proxy evaluation of parasites, which saves fitness
function calls and exponentially reduces the symbiotic collaborations produced.
Another novel feature consists of breaking the evolutionary cycle into two
phases: a symbiotic phase and a phase of independent evolution of both hosts
and parasites. SMuGA was tested in optimization of a variety of deceptive
functions, with results one order of magnitude better than state of the art
symbiotic algorithms. This allowed to optimize deceptive problems with large
sizes, and showed a linear scaling in the number of iterations to attain the
optimum.