  Distribution matching can be used to learn invariant representations with
applications in fairness and robustness. Most prior works resort to adversarial
matching methods but the resulting minimax problems are unstable and
challenging to optimize. Non-adversarial likelihood-based approaches either
require model invertibility, impose constraints on the latent prior, or lack a
generic framework for distribution matching. To overcome these limitations, we
propose a non-adversarial VAE-based matching method that can be applied to any
model pipeline. We develop a set of alignment upper bounds for distribution
matching (including a noisy bound) that have VAE-like objectives but with a
different perspective. We carefully compare our method to prior VAE-based
matching approaches both theoretically and empirically. Finally, we demonstrate
that our novel matching losses can replace adversarial losses in standard
invariant representation learning pipelines without modifying the original
architectures -- thereby significantly broadening the applicability of
non-adversarial matching methods.


  Unlike Newtonian dynamics which is linear and obeys the strong equivalence
principle, in any nonlinear gravitation such as Milgromian dynamics (MOND), the
strong version of the equivalence principle is violated and the gravitational
dynamics of a system is influenced by the external gravitational field in which
it is embedded. This so called External Field Effect (EFE) is one of the
important implications of MOND and provides a special context to test
Milgromian dynamics. Here, we study the rotation curves (RCs) of 18 spiral
galaxies and find that their shapes constrain the EFE. We show that the EFE can
successfully remedy the overestimation of rotation velocities in 80\% of the
sample galaxies in Milgromian dynamics fits by decreasing the velocity in the
outer part of the RCs. We compare the implied external field with the
gravitational field for non-negligible nearby sources of each individual galaxy
and find that in many cases it is compatible with the EFE within the
uncertainties. We therefore argue that in the framework of Milgromian dynamics,
one can constrain the gravitational field induced from the environment of
galaxies using their RCs. We finally show that taking into account the EFE
yields more realistic values for the stellar mass-to-light ratio in terms of
stellar population synthesis than the ones implied without the EFE.


  We give a gauge-invariant treatment of the angular momentum sum-rule for the
proton in terms of matrix elements of three gauge-invariant, local composite
operators. These matrix elements are decomposed into three independent form
factors, one of which is the flavour singlet axial charge. The other two are
interpreted as total quark and gluon angular momentum. We further show that the
axial charge cancels out of the sum-rule. The general form of the
renormalisation mixing of the three operators is written down and also
determined to one loop from which the scale dependence and mixing of the form
factors is derived. We relate these results to a previous parton model
calculation by defining the parton model quantities in terms of the three form
factors. We also mention how the form factors can be measured in experiments.


  Using mean-field theory, we study the equilibrium properties of boson-fermion
mixtures confined in a harmonic pancake-shaped trap at zero temperature. When
the modulus of the s-wave scattering lengths are comparable to the mixture
thickness, two-dimensional scattering events introduce a logarithmic dependence
on density in the coupling constants, greatly modifying the density profiles
themselves. We show that for the case of a negative boson-fermion
three-dimensional s-wave scattering length, the dimensional crossover
stabilizes the mixture against collapse and drives it towards spatial demixing.


  We study quantum fields on an arbitrary, rigid background with boundary. We
derive the action for a scalar in the holographic basis that separates the
boundary and bulk degrees of freedom. A relation between Dirichlet and Neumann
propagators valid for any background is obtained from this holographic action.
As a simple application, we derive an exact formula for the flux of bulk modes
emitted from the boundary in a warped background. We also derive a formula for
the Casimir pressure on a $(d-1)$-brane depending only on the boundary-to-bulk
propagators, and apply it in AdS. Turning on couplings and using the
holographic basis, we evaluate the one-loop boundary effective action in AdS by
means of the heat kernel expansion. We extract anomalous dimensions of single
and double trace CFT operators generated by loops of heavy scalars and
nonabelian vectors, up to third order in the large squared mass expansion. From
the boundary heat kernel coefficients we identify CFT operator mixing and
corrections to OPE data, in addition to the radiative generation of local
operators. We integrate out nonabelian vector fluctuations in AdS$_{4,5,6}$ and
obtain the associated holographic Yang-Mills $\beta$ functions. Turning to the
expanding patch of dS, following recent proposals, we provide a boundary
effective action generating the perturbative cosmological correlators using
analytical continuation from dS to EAdS. We obtain the "cosmological" heat
kernel coefficients in the scalar case and work out the divergent part of the
dS$_4$ effective action which renormalizes the cosmological correlators. We
find that bulk masses and wavefunction can logarithmically run as a result of
the dS$_4$ curvature, and that operators on the late time boundary are
radiatively generated. More developments are needed to extract all one-loop
information from the cosmological effective action.


  Homogeneous melting of superheated crystals at constant energy is a dynamical
process, believed to be triggered by the accumulation of thermal vacancies and
their self-diffusion. From microcanonical simulations we know that if an ideal
crystal is prepared at a given kinetic energy, it takes a random time $t_w$
until the melting mechanism is actually triggered. In this work we have studied
in detail the statistics of $t_w$ for melting at different energies by
performing a large number of Z-method simulations and applying state-of-the-art
methods of Bayesian statistical inference. By focusing on the short-time tail
of the distribution function, we show that $t_w$ is actually gamma-distributed
rather than exponential (as asserted in previous work), with decreasing
probability near $t_w \sim 0$. We also explicitly incorporate in our model the
unavoidable truncation of the distribution function due to the limited total
time span of a Z method simulation. The probabilistic model presented in this
work can provide some insight into the dynamical nature of the homogeneous
melting process, as well as giving a well-defined practical procedure to
incorporate melting times from simulation into the Z-method in order to reduce
the uncertainty in the melting temperature.


  When measuring electromagnetic radiation of frequency $f$, the most sensitive
detector is the one that counts the single quanta of energy $h f$. Single
photon detectors (SPDs) were demonstrated from $\gamma$-rays to infrared
wavelengths, and extending this range down to the microwaves is the focus of
intense research. The energy of $10\,\mathrm{GHz}$ microwave photon, about
$40\,\mathrm{\mu eV}$ or $7\, \mathrm{yJ},$ is enough to force a
superconducting Josephson junction into its resistive state, making it suitable
to be used as a sensor. In this work, we use an underdamped Josephson junction
to detect single thermal photons stochastically emitted by a microwave copper
cavity at millikelvin temperatures. After characterizing the source and
detector, we vary the temperature of the resonant cavity and measure the
increased photon rate. The device shows an efficiency up to 40% and a dark
count rate of $0.1\,\mathrm{Hz}$ in a bandwidth of several gigahertz. To
confirm the thermal nature of the emitted photons we verify their
super-Poissonian statistics, which is also a signature of quantum chaos. We
discuss detector application in the scope of Dark Matter Axion searches, and
note its importance for quantum information, metrology and fundamental physics.


  A key open issue for galaxy evolution and formation models is the
understanding of the different mechanisms of galaxy assembly at various cosmic
epochs. The aim of this study is to derive the global and spatially-resolved
metal content in high-redshift galaxies. Using VLT/SINFONI IFU spectroscopy of
a first sample of 50 galaxies at z~1.2 in the MASSIV survey, we are able to
measure the Ha and [NII]6584 emission lines. Using the N2 ratio as a proxy for
oxygen abundance in the interstellar medium, we measure the metallicity of the
sample galaxies. We develop a tool to extract spectra in annular regions of
these galaxies, leading to a spatially-resolved estimate of the oxygen
abundance in each galaxy. We derive a metallicity gradient for 26 galaxies in
our sample and discover a significant fraction of galaxies with a "positive"
gradient. Using a simple chemical evolution model, we derive infall rates of
pristine gas onto the disks. Seven galaxies display a positive gradient at a
high confidence level. Four out of these are interacting and one is a chain
galaxy. We suggest that interactions might be responsible for shallowing and
even inverting the abundance gradient. We also identify two interesting
correlations in our sample: a) galaxies with higher gas velocity dispersion
have shallower/positive gradients; and b) metal-poor galaxies tend to show a
positive gradient whereas metal-rich ones tend to show a negative one. This
last observation can be explained by the infall of metal-poor gas into the
center of the disks. We address the question of the origin of this infall under
the influence of gas flows triggered by interactions and/or cold gas accretion.


  In this paper, we investigate fundamental performance limits of cumulative
distribution function (CDF)-based scheduling (CS) in downlink cellular
networks. CS is known as an efficient scheduling method that can assign
different time fractions for users or, equivalently, satisfy different channel
access ratio (CAR) requirements of users while exploiting multi-user diversity.
We first mathematically analyze the throughput characteristics of CS in
arbitrary fading statistics and data rate functions. It is shown that the
throughput gain of CS increases as the CAR of a user decreases or the number of
users in a cell increases. For Nakagami-m fading channels, we obtain the
average throughput in closed-form and investigate the effects of the average
signal-to-noise ratio, the shape parameter m, and the CAR on the throughput
performance. In addition, we propose a threshold-based opportunistic feedback
technique in order to reduce feedback overhead while satisfying the CAR
requirements of users. We prove that the average feedback overhead of the
proposed technique is upper bounded by -ln(p), where p is the probability that
no user satisfies the threshold condition in a cell. Finally, we adopt a novel
fairness criterion, called qualitative fairness, which considers not only the
quantity of the allocated resources to users but also the quality of the
resources. It is observed that CS provides a better qualitative fairness than
other scheduling algorithms designed for controlling CARs of users.


  Large language models have shown impressive capabilities across a variety of
NLP tasks, yet their generating text autoregressively is time-consuming. One
way to speed them up is speculative decoding, which generates candidate
segments (a sequence of tokens) from a fast draft model that is then verified
in parallel by the target model. However, the acceptance rate of candidate
tokens receives limitations from several factors, such as the model, the
dataset, and the decoding setup. This paper proposes sampling multiple
candidates from a draft model and then organising them in batches for
verification. We design algorithms for efficient multi-candidate verification
while maintaining the distribution of the target model. Our approach shows
significant improvements in acceptance rates on multiple datasets and models,
consistently outperforming standard speculative decoding.


  In inter-domain routing, a packet is not always forwarded along the
Autonomous System (AS) level path determined by the BGP routing protocol. This
is often called control-plane and data-plane (CD) mismatch, which allows for
flexible traffic control, but also leads to operation and security issues. We
systematically analyze this phenomenon with path pairs collected from 128 pairs
of vantage points over more than 5 years, and use multiple IP-to-AS mapping
methods to compare CD paths. What is interesting is that, working at such a
large scale in turn helps us design a novel method to fairly evaluate the
accuracy of various existing mapping methods, and further develop a new mapping
method, i.e., LearnToCorrect, that can correct more than 70\% mapping errors of
the state-of-the-art one. Then we devise to identify real mismatches with
LearnToCorrect, and estimate that the real-mismatch ratio in the wild is
typically less than 6\%. At last, we use our proposed methods to detect routing
security issues, which are previously difficult to accurately find out.


  We investigate the power spectra of outflow-driven turbulence through
high-resolution three-dimensional isothermal numerical simulations where the
turbulence is driven locally in real-space by a simple spherical outflow model.
The resulting turbulent flow saturates at an average Mach number of ~2.5 and is
analysed through density and velocity power spectra, including an investigation
of the evolution of the solenoidal and compressional components. We obtain a
shallow density power spectrum with a slope of ~-1.2 attributed to the presence
of a network of localised dense filamentary structures formed by strong shock
interactions. The total velocity power spectrum slope is found to be ~-2.0,
representative of Burgers shock dominated turbulence model. The density
weighted velocity power spectrum slope is measured as ~-1.6, slightly less than
the expected Kolmogorov scaling value (slope of -5/3) found in previous works.
The discrepancy may be caused by the nature of our real space driving model and
we suggest there is no universal scaling law for supersonic compressible
turbulence. We find that on average, solenoidal modes slightly dominate in our
turbulence model as the interaction between strong curved compressible shocks
generates solenoidal modes, and compressible modes decay faster.


  The high frequency component in blazars is thought to be due to inverse
Compton scattered radiation. Recent observations by Fermi-LAT are used to
evaluate the details of the scattering process. A comparison is made between
the usually assumed single scattering scenario and one in which multiple
scatterings are energetically important. In the latter case, most of the
radiation is emitted in the Klein-Nishina limit. It is argued that several of
the observed correlations defining the blazar sequence are most easily
understood in a multiple scattering scenario. Observations indicate also that,
in such a scenario, the blazar sequence is primarily governed by the energy
density of relativistic electrons rather than that of the seed photons. The
pronounced X-ray minimum in the spectral energy distribution often observed in
the most luminous blazars is discussed. It is shown how this feature can be
accounted for in a multiple scattering scenario by an extension of standard
one-zone models.


  In the single winner determination problem, we have n voters and m candidates
and each voter j incurs a cost c(i, j) if candidate i is chosen. Our objective
is to choose a candidate that minimizes the expected total cost incurred by the
voters; however as we only have access to the agents' preference rankings over
the outcomes, a loss of efficiency is inevitable. This loss of efficiency is
quantified by distortion. We give an instance of the metric single winner
determination problem for which any randomized social choice function has
distortion at least 2.063164. This disproves the long-standing conjecture that
there exists a randomized social choice function that has a worst-case
distortion of at most 2.


  We prove a `motivic' analogue of the Weyl character formula, computing the
Euler characteristic of a line bundle on a generalized flag manifold $G/B$
multiplied either by a motivic Chern class of a Schubert cell, or a Segre
analogue of it. The result, given in terms of Demazure-Lusztig (D-L) operators,
recovers formulas found by Brubaker, Bump and Licata for the Iwahori-Whittaker
functions of the principal series representation of a $p$-adic group. In
particular, we obtain a new proof of the classical Casselman-Shalika formula
for the spherical Whittaker function. The proofs are based on localization in
equivariant K theory, and require a geometric interpretation of how the Hecke
dual (or inverse) of a D-L operator acts on the class of a point. We prove that
the Hecke dual operators give Grothendieck-Serre dual classes of the motivic
classes, a result which might be of independent interest. In an Appendix joint
with Dave Anderson we show that if the line bundle is trivial, we recover a
generalization of a classical formula by Kostant, Macdonald, Shapiro and
Steinberg for the Poincar{\'e} polynomial of $G/B$; the generalization we
consider is due to Aky{\i}ld{\i}z and Carrell and replaces $G/B$ by any smooth
Schubert variety.


  Based on quintessence models with anticorrelation between the quintessence
fluctuations and adiabatic perturbations in the other matter components, we
show that if the quintessence potential is sufficiently steep in the initial
era, i.e., at the beginning of radiation dominated epoch, the quintessence
fluctuations can be large enough to sufficiently suppress the CMB power
spectrum at low multipoles without excess gravitational waves. The leaping
kinetic term quintessence and the crossover quintessence models, can realize
such steep potential at the initial stage, and therefore can give rise to a low
CMB quadrupole as required by observations.


  In this thesis, we study multiple tasks related to document layout analysis
such as the detection of text lines, the splitting into acts or the detection
of the writing support. Thus, we propose two deep neural models following two
different approaches. We aim at proposing a model for object detection that
considers the difficulties associated with document processing, including the
limited amount of training data available.
  In this respect, we propose a pixel-level detection model and a second
object-level detection model. We first propose a detection model with few
parameters, fast in prediction, and which can obtain accurate prediction masks
from a reduced number of training data. We implemented a strategy of collection
and uniformization of many datasets, which are used to train a single line
detection model that demonstrates high generalization capabilities to
out-of-sample documents.
  We also propose a Transformer-based detection model. The design of such a
model required redefining the task of object detection in document images and
to study different approaches. Following this study, we propose an object
detection strategy consisting in sequentially predicting the coordinates of the
objects enclosing rectangles through a pixel classification. This strategy
allows obtaining a fast model with only few parameters.
  Finally, in an industrial setting, new non-annotated data are often
available. Thus, in the case of a model adaptation to this new data, it is
expected to provide the system as few new annotated samples as possible. The
selection of relevant samples for manual annotation is therefore crucial to
enable successful adaptation. For this purpose, we propose confidence
estimators from different approaches for object detection. We show that these
estimators greatly reduce the amount of annotated data while optimizing the
performances.


  The code generation modules inside modern compilers such as GCC and LLVM,
which use a limited number of CPU registers to store a large number of program
variables, may introduce side-channel leaks even in software equipped with
state-of-the-art countermeasures. We propose a program analysis and
transformation based method to eliminate this side channel. Our method has a
type-based technique for detecting leaks, which leverages Datalog-based
declarative analysis and domain-specific optimizations to achieve high
efficiency and accuracy. It also has a mitigation technique for the compiler's
backend, more specifically the register allocation modules, to ensure that
potentially leaky intermediate computation results are always stored in
different CPU registers or spilled to memory with isolation. We have
implemented and evaluated our method in LLVM for the x86 instruction set
architecture. Our experiments on cryptographic software show that the method is
effective in removing the side channel while being efficient, i.e., our
mitigated code is more compact and runs faster than code mitigated using
state-of-the-art techniques.


  Let $G$ be a $d$-regular multigraph, and let $\lambda_2(G)$ be the second
largest eigenvalue of $G$. In this paper, we prove that if $\lambda_2(G) <
\frac{d-1+\sqrt{9d^2-10d+17}}4$, then $G$ is 2-edge-connected. Furthermore, for
$t\ge2$ we show that $G$ is $(t+1)$-edge-connected when $\lambda_2(G)<d-t$, and
in fact when $\lambda_2(G)<d-t+1$ if $t$ is odd.


  We prove Koll\'ar's effective base point free theorem for log canonical
pairs.


  Todays, researchers in the field of Pulmonary Embolism (PE) analysis need to
use a publicly available dataset to assess and compare their methods. Different
systems have been designed for the detection of pulmonary embolism (PE), but
none of them have used any public datasets. All papers have used their own
private dataset. In order to fill this gap, we have collected 5160 slices of
computed tomography angiography (CTA) images acquired from 20 patients, and
after labeling the image by experts in this field, we provided a reliable
dataset which is now publicly available. In some situation, PE detection can be
difficult, for example when it occurs in the peripheral branches or when
patients have pulmonary diseases (such as parenchymal disease). Therefore, the
efficiency of CAD systems highly depends on the dataset. In the given dataset,
66% of PE are located in peripheral branches, and different pulmonary diseases
are also included.


  We classify globally generated vector bundles on $\mathbf{P}^1 \times
\mathbf{P}^1 \times \mathbf{P}^1$ with small first Chern class, i.e. $c_1=
(a_1, a_2, a_3)$, $a_i \le 2$. Our main method is to investigate the associated
smooth curves to globally generated vector bundles via the Hartshorne-Serre
correspondence.


  We discover new hereditary classes of graphs that are minimal (with respect
to set inclusion) of unbounded clique-width. The new examples include split
permutation graphs and bichain graphs. Each of these classes is characterised
by a finite list of minimal forbidden induced subgraphs. These, therefore,
disprove a conjecture due to Daligault, Rao and Thomasse from 2010 claiming
that all such minimal classes must be defined by infinitely many forbidden
induced subgraphs.
  In the same paper, Daligault, Rao and Thomasse make another conjecture that
every hereditary class of unbounded clique-width must contain a labelled
infinite antichain. We show that the two example classes we consider here
satisfy this conjecture. Indeed, they each contain a canonical labelled
infinite antichain, which leads us to propose a stronger conjecture: that every
hereditary class of graphs that is minimal of unbounded clique-width contains a
canonical labelled infinite antichain.


  This letter proposes a new approach for online detection of low-quality
synchrophasor data under both normal and event conditions. The proposed
approach utilizes the features of synchrophasor data in time and frequency
domains to distinguish multiple regional PMU signals and detect low-quality
synchrophasor data. The proposed approach does not require any offline study
and it is more effective to detect low-quality data with apparently
indistinguishable profiles. Case studies from recorded synchrophasor
measurements verify the effectiveness of the proposed approach.


  The safety of autonomous driving systems, particularly self-driving vehicles,
remains of paramount concern. These systems exhibit affine nonlinear dynamics
and face the challenge of executing predefined control tasks while adhering to
state and input constraints to mitigate risks. However, achieving safety
control within the framework of control input constraints, such as collision
avoidance and maintaining system states within secure boundaries, presents
challenges due to limited options. In this study, we introduce a novel approach
to address safety concerns by transforming safety conditions into control
constraints with a relative degree of 1. This transformation is facilitated
through the design of control barrier functions, enabling the creation of a
safety control system for affine nonlinear networks. Subsequently, we formulate
a robust control strategy that incorporates safety protocols and conduct a
comprehensive analysis of its stability and reliability. To illustrate the
effectiveness of our approach, we apply it to a specific problem involving
adaptive cruise control. Through simulations, we validate the efficiency of our
model in ensuring safety without compromising control performance. Our approach
signifies significant progress in the field, providing a practical solution to
enhance safety for autonomous driving systems operating within the context of
affine nonlinear dynamics.


  Let $G=GL(m|n)$ be a general linear supergroup and $G_{ev}$ be its even
subsupergroup isomorphic to $GL(m)\times GL(n)$. In this paper we use the
explicit description of $G_{ev}$-primitive vectors in the costandard
supermodule $\nabla(\lambda)$, the largest polynomial $G$-subsupermodule of the
induced supermodule $H^0_G(\lambda)$, for $(m|n)$-hook partition $\lambda$, and
a properties of certain morphisms $\psi_k$ to derive results related to the odd
linkage for $G$ over a field $F$ of characteristic different from $2$.


  We present a condition in which the dimer-monomer state is exactly the ground
state of an extended diamond chain with spin magnitude 1/2. The Hamiltonian of
the extended diamond chain includes next-nearest-neighbor exchange interactions
and distortions, where the spin magnitude of the spin pair on a singlet dimer
is not generally conserved. The method of deriving the condition is based on
representing the Hamiltonian in a complete square form. The dimer-monomer
ground state is found even if the Hamiltonian has no space-reflection
symmetries.


  The many $2^k$-pole boson states, $|N_kv_k\alpha_k I_kM_k>$ with $k=2,3$,
realize the irreducible representation (IR) for the group reduction chains
$SU(2k+1)\supset R_{2k+1}\supset R_3\supset R_2$. They have been analytically
studied and widely used for the description of nuclear systems. However, no
analytical expression for the degeneracy $d_v(I)$ of the $R_{2k+1}$'s IR,
determined by the reduction $R_{2k+1}\supset R_3$, is available. Thus, the
number of distinct values taken by $\alpha_k$ has been so far obtained by
solving some complex equations. Here we derive analytical expressions for the
degeneracy $d_v(I)$ characterizing the octupole and quadrupole boson states,
respectively. The merit of this work consists of the fact that it completes the
analytical expressions for the $2^k$-pole boson basis.


  Internal intervals spanned by finite ranges of a conformal coordinate $z$ and
terminating at a pair of singularities are a common feature of many string
compactifications with broken supersymmetry. The squared masses emerging in
lower-dimensional Minkowski spaces are then eigenvalues of Schr\"odinger-like
operators, whose potentials have double poles at the ends of the intervals. For
one-component systems, the possible self-adjoint extensions of Schr\"odinger
operators are described by points in $AdS_3 \times S^1$, and those
corresponding to independent boundary conditions at the ends of the intervals
by points on the boundary of $AdS_3$. The perturbative stability of
compactifications to Minkowski space time depends, in general, on these choices
of self-adjoint extensions. We apply this setup to the orientifold vacua driven
by the ``tadpole potential'' $V=T \ e^{\,\frac{3}{2}\,\phi}$ and find, in nine
dimensions, a massive scalar spectrum, a unique choice of boundary conditions
with stable tensor modes and a massless graviton, and a wide range of choices
leading to massless and/or massive vector modes.


  The effects of non-magnetic disorder on the critical temperature T_c of
organic weak-linked layered superconductors with singlet in-plane pairing are
considered. A randomness in the interlayer Josephson coupling is shown to
destroy phase coherence between the layers and T_c suppresses smoothly in a
large extent of the disorder strength. Nevertheless the disorder of arbitrarily
high strength can not destroy completely the superconducting phase. The
obtained quasi-linear decrease of the critical temperature with increasing
disorder strength is in good agreement with experimental measurements.


  Factors $\frac{X}{Y}$ in a free group $F$ with $Y$ normal in $X$ are
considered. Precise results on the free structure of ${Y}$ relative to the free
structure of ${X}$ when $\frac{X}{Y}$ is abelian are obtained. Some extensions
and applications are given, as for example to the construction of lower central
factors in general groups. A collecting process on free generators, which gives
basic commutator-type free generators for some subgroups, is also presented.
The notion of {\em relative basic commutators} is developed.


  We explore some novel connections between the main privacy models in use and
we recall a few known ones. We show these models to be more related than
commonly understood, around two main principles: deniability and permutation.
In particular, randomized response turns out to be very modern in spite of it
having been introduced over 50 years ago: it is a local anonymization method
and it allows understanding the protection offered by $\epsilon$-differential
privacy when $\epsilon$ is increased to improve utility. A similar
understanding on the effect of large $\epsilon$ in terms of deniability is
obtained from the connection between $\epsilon$-differential privacy and
t-closeness. Finally, the post-randomization method (PRAM) is shown to be
viewable as permutation and to be connected with randomized response and
differential privacy. Since the latter is also connected with t-closeness, it
follows that the permutation principle can explain the guarantees offered by
all those models. Thus, calibrating permutation is very relevant in
anonymization, and we conclude by sketching two ways of doing it.


  For an upstream supersonic flow past a straight-sided cone in $\R^3$ whose
vertex angle is less than the critical angle, a transonic (supersonic-subsonic)
shock-front attached to the cone vertex can be formed in the flow. In this
paper we analyze the stability of transonic shock-fronts in three-dimensional
steady potential flow past a perturbed cone. We establish that the self-similar
transonic shock-front solution is conditionally stable in structure with
respect to the conical perturbation of the cone boundary and the upstream flow
in appropriate function spaces. In particular, it is proved that the slope of
the shock-front tends asymptotically to the slope of the unperturbed
self-similar shock-front downstream at infinity.


  We study chiral symmetry breaking in $\rm QED_3$ with $N_f$ flavors of
four-component fermions. A closed system of Schwinger-Dyson equations for
fermion and photon propagators and the full fermion-photon vertex is proposed,
which is consistent with the Ward-Takahashi identity. A simplified version of
that set of equations is reduced (in nonlocal gauge) to the equation for a
dynamical fermion mass function, where the one-loop vacuum polarization with
dynamically massive fermions has been taken into account. The linearized
equation for the fermion mass function is analyzed in real space. The
analytical solution is compared with the results of numerical calculations of
the nonlinear integral equation in momentum space.


  We consider non-stationary oscillations of an infinite string with
time-varying tension. The string lies on the Winkler foundation with a point
inhomogeneity (a concentrated spring of negative stiffness). In such a system
with constant parameters (the string tension), under certain conditions a
trapped mode of oscillation exists and is unique. Therefore, applying a
non-stationary external excitation to this system can lead to the emergence of
the string oscillations localized near the inhomogeneity. We provide an
analytical description of non-stationary localized oscillations of the string
with slowly time-varying tension using the asymptotic procedure based on
successive application of two asymptotic methods, namely the method of
stationary phase and the method of multiple scales. The obtained analytical
results were verified by independent numerical calculations based on the finite
difference method. The applicability of the analytical formulas was
demonstrated for various types of external excitation and laws governing the
varying tension. In particular, we have shown that in the case when the trapped
mode frequency approaches zero, localized low-frequency oscillations with
increasing amplitude precede the localized string buckling. The dependence of
the amplitude of such oscillations on its frequency is more complicated in
comparison with the case of a one degree of freedom system with time-varying
stiffness.


  In order to fully exploit the physics potential of the Tevatron Run 2, the D0
detector has been upgraded. Having nearly completed the commissioning phase,
the D0 detector is starting to produce its first physics results. An overview
of the status of the main subdetectors involved in the upgrade is given,
followed by some examples of preliminary physics results already emerging.


  A typical process of learning to play a piece on a piano consists of a
progression through a series of practice units that focus on individual
dimensions of the skill, the so-called practice modes. Practice modes in
learning to play music comprise a particularly large set of possibilities, such
as hand coordination, posture, articulation, ability to read a music score,
correct timing or pitch, etc. Self-guided practice is known to be suboptimal,
and a model that schedules optimal practice to maximize a learner's progress
still does not exist. Because we each learn differently and there are many
choices for possible piano practice tasks and methods, the set of practice
modes should be dynamically adapted to the human learner, a process typically
guided by a teacher. However, having a human teacher guide individual practice
is not always feasible since it is time-consuming, expensive, and often
unavailable. In this work, we present a modeling framework to guide the human
learner through the learning process by choosing the practice modes generated
by a policy model. To this end, we present a computational architecture
building on a Gaussian process that incorporates 1) the learner state, 2) a
policy that selects a suitable practice mode, 3) performance evaluation, and 4)
expert knowledge. The proposed policy model is trained to approximate the
expert-learner interaction during a practice session. In our future work, we
will test different Bayesian optimization techniques, e.g., different
acquisition functions, and evaluate their effect on the learning progress.


  In this paper we develop an axiomatic approach to coarse homology theories.
We prove a uniqueness result concerning coarse homology theories on the
category of `coarse CW-complexes'. This uniqueness result is used to prove a
version of the coarse Baum-Connes conjecture for such spaces.


  Conformal Field Theories (CFTs) have been used extensively to understand the
physics of critical lattice models at equilibrium. However, the applicability
of CFT calculations to the behavior of the lattice systems in the
out-of-equilibrium setting is not entirely understood. In this work, we compare
the CFT results of the evolution of the entanglement spectrum after a quantum
quench with numerical calculations of the entanglement spectrum of the
three-state Potts model using matrix product state simulations. Our results
lead us to conjecture that CFT does not describe the entanglement spectrum of
the three-state Potts model at long times, contrary to what happens in the
Ising model. We thus numerically simulate the out-of-equilibrium behaviour of
the Potts model according to the CFT protocol - i.e. by taking a particular
product state and "cooling" it, then quenching to the critical point and find
that, in this case, the entanglement spectrum is indeed described by the CFT at
long times.


  Astrophysical black holes are ideal laboratories for testing Einstein's
theory of general relativity in the strong field regime. In this manuscript, we
present an analysis of Suzaku and NuSTAR spectra of the black hole binary
Cygnus X-1 using RELXILL_NK. Unlike our previous study on Cygnus X-1 with
NuSTAR data, here we are able to constrain the Johannsen deformation parameter
$\alpha_{13}$. However, despite the high energy resolution near the iron line
provided by Suzaku, our constraints on the Kerr metric from Cygnus X-1 are not
very stringent in comparison with those that have been obtained from other
sources, confirming that Cygnus X-1 is quite a complicated source.


  Let $s_0,s_1,\dots,s_{m-1}$ be complex numbers and $r_0,\dots,r_{m-1}$
rational integers in the range $0\le r_j\le m-1$. Our first goal is to prove
that if an entire function $f$ of sufficiently small exponential type satisfies
$f^{(mn+r_j)}(s_j)\in{\mathbb Z}$ for $0\le j\le m-1$ and all sufficiently
large $n$, then $f$ is a polynomial. Under suitable assumptions on
$s_0,s_1,\dots,s_{m-1}$ and $r_0,\dots,r_{m-1}$, we introduce interpolation
polynomials $\Lambda_{nj}$, ($n\ge 0$, $0\le j\le m-1$) satisfying $$
\Lambda_{nj}^{(mk+r_\ell)}(s_\ell)=\delta_{j\ell}\delta_{nk},
\quad\hbox{for}\quad n, k\ge 0 \quad\hbox{and}\quad 0\le j, \ell\le m-1 $$ and
we show that any entire function $f$ of sufficiently small exponential type has
a convergent expansion $$ f(z)=\sum_{n\ge 0}
\sum_{j=0}^{m-1}f^{(mn+r_j)}(s_j)\Lambda_{nj}(z). $$ The case $r_j=j$ for $0\le
j\le m-1$ involves successive derivatives $f^{(n)}(w_n)$ of $f$ evaluated at
points of a periodic sequence ${\mathbf{w}}=(w_n)_{n\ge 0}$ of complex numbers,
where $w_{mh+j}=s_j$ ($h\ge 0$, $0\le j\le m$). More generally, given a bounded
(not necessarily periodic) sequence ${\mathbf{w}}=(w_n)_{n\ge 0}$ of complex
numbers, we consider similar interpolation formulae $$ f(z)=\sum_{n\ge
0}f^{(n)}(w_n)\Omega_{{\mathbf{w}},n}(z) $$ involving polynomials
$\Omega_{{\mathbf{w}},n}(z)$ which were introduced by W.~Gontcharoff in 1930.
Under suitable assumptions, we show that the hypothesis
$f^{(n)}(w_n)\in{\mathbb Z}$ for all sufficiently large $n$ implies that $f$ is
a polynomial.


  Cosmology requires at least half of the baryons in the Universe to be in the
intergalactic medium, much of which is believed to form hot coronae around
galaxies. Star-forming galaxies must be accreting from their coronae. HI
observations of external galaxies show that they have HI halos associated with
star formation. These halos are naturally modelled as ensembles of clouds
driven up by supernova bubbles. These models can fit the data successfully only
if clouds exchange mass and momentum with the corona. As a cloud orbits, it is
ablated and forms a turbulent wake where cold high-metallicity gas mixes with
hot coronal gas causing the prompt cooling of the latter. As a consequence the
total mass of HI increases. This model has recently been used to model the
Leiden-Argentina-Bonn survey of Galactic HI. The values of the model's
parameters that are required to model NGC 891, NGC 2403 and our Galaxy show a
remarkable degree of consistency, despite the very different natures of the two
external galaxies and the dramatic difference in the nature of the data for our
Galaxy and the external galaxies. The parameter values are also consistent with
hydrodynamical simulations of the ablation of individual clouds. The model
predicts that a galaxy that loses its cool-gas disc for instance through a
major merger cannot reform it from its corona; it can return to steady star
formation only if it can capture a large body of cool gas, for example by
accreting a gas-rich dwarf. Thus the model explains how major mergers can make
galaxies "red and dead."


  Coherent electron cooling is an ultra-high-bandwidth form of stochastic
cooling which utilizes the charge perturbation from Debye screening as a seed
for a free-electron laser. The amplified and frequency-modulated signal that
results from the free-electron laser process is then used to give an
energy-dependent kick on the hadrons in a bunch. In this paper, we present a
theoretical description of a high-gain free-electron laser with applications to
a complete theoretical description of coherent electron cooling.


  A variety of quantum gravity models (including spin foams) can be described
using a path integral formulation. A path integral has a well-known statistical
mechanical interpretation in connection with a canonical ensemble. In this
sense, a path integral describes the thermodynamic equilibrium of a local
system in a thermal bath. This interpretation is in contrast to solutions of
Einstein's Equations which depart from local thermodynamical equilibrium (one
example is shown explicitly). For this reason, we examine an extension of the
path integral model to a (locally) non-equilibrium description. As a
non-equilibrium description, we propose to use a global microcanonical ensemble
with constraints. The constraints reduce the set of admissible microscopic
states to be consistent with the macroscopic geometry. We also analyse the
relation between the microcanonical description and a statistical approach not
based on dynamical assumptions which has been proposed recently. This analysis
is of interest for the test of consistency of the non-equilibrium description
with general relativity and quantum field theory.


  In the field of algebraic systems biology, the number of minimal polynomial
models constructed using discretized data from an underlying system is related
to the number of distinct reduced Gr\"obner bases for the ideal of the data
points. While the theory of Gr\"obner bases is extensive, what is missing is a
closed form for their number for a given ideal. This work contributes
connections between the geometry of data points and the number of Gr\"obner
bases associated to small data sets. Furthermore we improve an existing upper
bound for the number of Gr\"obner bases specialized for data over a finite
field.


  Electrons, when scattered by static random disorder, form standing waves that
can be imaged using scanning tunneling microscopy. Such interference patterns,
observable by the recently developed technique of Fourier transform scanning
tunneling spectroscopy (FT-STS), are shown to carry unique fingerprints
characteristic of the electronic order present in a material. We exploit this
feature of the FT-STS technique to propose a test for the nature of the
enigmatic pseudogap phase in the high-$T_c$ cuprate superconductors. Through
their sensitivity to the quasiparticle spectra and coherence factors, the
FT-STS patterns in principle carry enough information to unambiguously
determine the nature of the condensate responsible for the pseudogap
phenomenon. We argue that the next generation of FT-STS experiments, currently
underway, should be able to distinguish between the pseudogap dominated by the
remnants of superconducting order from the pseudogap dominated by some
competing order in the particle-hole channel. Using general arguments and
detailed numerical calculations, we point to certain fundamental differences
between the two scenarios and discuss the prospects for future experiments.


  Methods utilizing instrumental variables have been a fundamental statistical
approach to estimation in the presence of unmeasured confounding, usually
occurring in non-randomized observational data common to fields such as
economics and public health. However, such methods usually make constricting
linearity and additivity assumptions that are inapplicable to the complex
modeling challenges of today. The growing body of observational data being
collected will necessitate flexible regression modeling while also being able
to control for confounding using instrumental variables. Therefore, this
article presents a nonlinear instrumental variable regression model based on
Bayesian regression tree ensembles to estimate such relationships, including
interactions, in the presence of confounding. One exciting application of this
method is to use genetic variants as instruments, known as Mendelian
randomization. Body mass index is one factor that is hypothesized to have a
nonlinear relationship with cardiovascular risk factors such as blood pressure
while interacting with age. Heterogeneity in patient characteristics such as
age could be clinically interesting from a precision medicine perspective where
individualized treatment is emphasized. We present our flexible Bayesian
instrumental variable regression tree method with an example from the UK
Biobank where body mass index is related to blood pressure using genetic
variants as the instruments.


  In this paper, inspired by the Costello's seminal work, we present a general
formulation of exact renormalization group (RG) within the Batalin-Vilkovisky
(BV) quantization scheme. In the spirit of effective field theory, the BV
bracket and Laplacian structure as well as the BV effective action (EA) depend
on an effective energy scale. The BV EA at a certain scale satisfies the BV
quantum master equation at that scale. The RG flow of the EA is implemented by
BV canonical maps intertwining the BV structures at different scales.
Infinitesimally, this generates the BV exact renormalization group equation
(RGE). We show that BV RG theory can be extended by augmenting the scale
parameter space R to its shifted tangent bundle T[1]R. The extra odd direction
in scale space allows for a BV RG supersymmetry that constrains the structure
of the BV RGE bringing it to Polchinski's form. We investigate the implications
of BV RG supersymmetry in perturbation theory. Finally, we illustrate our
findings by constructing free models of BV RG flow and EA exhibiting RG
supersymmetry in the degree -1 symplectic framework and studying the
perturbation theory thereof. We find in particular that the odd partner of
effective action describes perturbatively the deviation of the interacting RG
flow from its free counterpart.


  We present a detailed study of a new mathematical object in
$\mathrm{E}_{6(6)}\times \mathbb{R}^{+}$ generalised geometry called an
`exceptional complex structure' (ECS). It is the extension of a conventional
complex structure to one that includes all the degrees of freedom of M-theory
or type IIB supergravity in six or five dimensions, and as such characterises,
in part, the geometry of generic supersymmetric compactifications to
five-dimensional Minkowkski space. We define an ECS as an integrable
$\mathrm{U}^{*}(6)\times \mathbb{R}^{+}$ structure and show it is equivalent to
a particular form of involutive subbundle of the complexified generalised
tangent bundle $L_{1} \subset E_{\mathbb{C}}$. We also define a refinement, an
$\mathrm{SU}^{*}(6)$ structure, and show that its integrability requires in
addition a vanishing moment map on the space of structures. We are able to
classify all possible ECSs, showing that they are characterised by two numbers
denoted `type' and `class'. We then use the deformation theory of ECS to find
the moduli of any $\mathrm{SU}^{*}(6)$ structure. We relate these structures to
the geometry of generic minimally supersymmetric flux backgrounds of M-theory
of the form $\mathbb{R}^{4,1}\times M$, where the $\mathrm{SU}^{*}(6)$ moduli
correspond to the hypermultiplet moduli in the lower-dimensional theory. Such
geometries are of class zero or one. The former are equivalent to a choice of
(non-metric-compatible) conventional $\mathrm{SL}(3,\mathbb{C})$ structure and
strikingly have the same space of hypermultiplet moduli as the fluxless
Calabi--Yau case.


  Conventional absolute camera pose via a Perspective-n-Point (PnP) solver
often assumes that the correspondences between 2D image pixels and 3D points
are given. When the correspondences between 2D and 3D points are not known a
priori, the task becomes the much more challenging blind PnP problem. This
paper proposes a deep CNN model which simultaneously solves for both the 6-DoF
absolute camera pose and 2D--3D correspondences. Our model comprises three
neural modules connected in sequence. First, a two-stream PointNet-inspired
network is applied directly to both the 2D image keypoints and the 3D scene
points in order to extract discriminative point-wise features harnessing both
local and contextual information. Second, a global feature matching module is
employed to estimate a matchability matrix among all 2D--3D pairs. Third, the
obtained matchability matrix is fed into a classification module to
disambiguate inlier matches. The entire network is trained end-to-end, followed
by a robust model fitting (P3P-RANSAC) at test time only to recover the 6-DoF
camera pose. Extensive tests on both real and simulated data have shown that
our method substantially outperforms existing approaches, and is capable of
processing thousands of points a second with the state-of-the-art accuracy.


  Multilingual representations embed words from many languages into a single
semantic space such that words with similar meanings are close to each other
regardless of the language. These embeddings have been widely used in various
settings, such as cross-lingual transfer, where a natural language processing
(NLP) model trained on one language is deployed to another language. While the
cross-lingual transfer techniques are powerful, they carry gender bias from the
source to target languages. In this paper, we study gender bias in multilingual
embeddings and how it affects transfer learning for NLP applications. We create
a multilingual dataset for bias analysis and propose several ways for
quantifying bias in multilingual representations from both the intrinsic and
extrinsic perspectives. Experimental results show that the magnitude of bias in
the multilingual representations changes differently when we align the
embeddings to different target spaces and that the alignment direction can also
have an influence on the bias in transfer learning. We further provide
recommendations for using the multilingual word representations for downstream
tasks.


  In this paper, we discuss the tunneling of scalar particles near the event
horizon of stationary and nonstationary Kerr-de Sitter black hole using Lorentz
violation theory in curved space time. The modified form of Hamilton-Jacobi
equation is derived from the Klein-Gordon equation by applying Lorentz
violation theory. The Hawking temperatures derived from stationary and
nonstationary Kerr-de Sitter black holes are modified due to Lorentz violation
theory. It is noted that the change in Bekenstein-Hawking entropy and modified
Hawking temperatures of stationary and nonstationary Kerr-de Sitter black hole
not only depend on the black hole parameters but also on ether like vectors
${\rm u^\alpha}$.


  We prove central and local limit theorems for random walks on the
Poincar{\'e} hyperbolic space of dimension n {\v e} 2. To this end we use the
ball model and describe the walk therein through the M{\"o}bius addition and
multiplication. This also allows to derive a corresponding law of large
numbers.


  The 1-in-3 and Not-All-Equal satisfiability problems for Boolean CNF formulas
are two well-known NP-hard problems. In contrast, the promise 1-in-3 vs.
Not-All-Equal problem can be solved in polynomial time. In the present work, we
investigate this constraint satisfaction problem in a regime where the promise
is weakened from either side by a rainbow-free structure, and establish a
complexity dichotomy for the resulting class of computational problems.


  We investigate the origin of the most iron-poor stars including SMSS
J031300.36-670839.3 with [Fe/H] < -7.52. We compute the change of surface
metallicity of stars with the accretion of interstellar matter (ISM) after
their birth using the chemical evolution model within the framework of the
hierarchical galaxy formation. The predicted metallicity distribution function
agrees very well with that observed from extremely metal-poor stars. In
particular, the lowest metallicity tail is well reproduced by the Population
III stars whose surfaces are polluted with metals through ISM accretion. This
suggests that the origin of iron group elements is explained by ISM accretion
for the stars with [Fe/H]$\lesssim -5$. The present results give new insights
into the nature of the most metal-poor stars and the search for Population III
stars with pristine abundances.


  The critical height of a rational function (with algebraic coefficients) is a
natural measure of dynamical complexity, essentially an adelic analogue of the
Lyapunov exponent. Coordinate-free, it is well-defined on moduli space, but
bears no obvious relation to the arithmetic geometry of that space as a
variety. At a conference in 2010, Silverman conjectured that this disconnect is
superficial, and that in fact the critical height should be at least
commensurate to any ample Weil height on the moduli space, except on the Lattes
locus (where that has no hope of being true). Here, we prove that conjecture.


  Reported here are transverse single-spin asymmetries ($A_{N}$) in the
production of charged hadrons as a function of transverse momentum ($p_T$) and
Feynman-$x$ ($x_F$) in polarized $p^{\uparrow}$+$p$, $p^{\uparrow}$+Al, and
$p^{\uparrow}$+Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV. The measurements
have been performed at forward and backward rapidity ($1.4<|\eta|<2.4$) over
the range of $1.5<p_{T}<7.0~{\rm GeV}/c$ and $0.04<|x_{F}|<0.2$. A nonzero
asymmetry is observed for positively charged hadrons at forward rapidity
($x_F>0$) in $p^{\uparrow}$+$p$ collisions, whereas the $p^{\uparrow}$+Al and
$p^{\uparrow}$+Au results show smaller asymmetries. This finding provides new
opportunities to investigate the origin of transverse single-spin asymmetries
and a tool to study nuclear effects in $p$+$A$ collisions.


  We prove a non-generosity theorem for proper cosets in groups of finite
Morley rank and elaborate on the theory of Weyl groups in this context.


  In our recent work [Phys. Rev. Lett. 102, 230502 (2009)] we showed that the
partition function of all classical spin models, including all discrete
standard statistical models and all Abelian discrete lattice gauge theories
(LGTs), can be expressed as a special instance of the partition function of a
4-dimensional pure LGT with gauge group Z_2 (4D Z_2 LGT). This provides a
unification of models with apparently very different features into a single
complete model. The result uses an equality between the Hamilton function of
any classical spin model and the Hamilton function of a model with all possible
k-body Ising-type interactions, for all k, which we also prove. Here, we
elaborate on the proof of the result, and we illustrate it by computing
quantities of a specific model as a function of the partition function of the
4D Z_2 LGT. The result also allows one to establish a new method to compute the
mean-field theory of Z_2 LGTs with d > 3, and to show that computing the
partition function of the 4D Z_2 LGT is computationally hard (#P hard). The
proof uses techniques from quantum information.


  Neutral atom arrays have recently emerged as a promising platform for quantum
information processing. One important remaining roadblock for the large-scale
application of these systems is the ability to perform error-corrected quantum
operations. To entangle the qubits in these systems, atoms are typically
excited to Rydberg states, which could decay or give rise to various correlated
errors that cannot be addressed directly through traditional methods of
fault-tolerant quantum computation. In this work, we provide the first complete
characterization of these sources of error in a neutral-atom quantum computer
and propose hardware-efficient, fault-tolerant quantum computation schemes that
mitigate them. Notably, we develop a novel and distinctly efficient method to
address the most important errors associated with the decay of atomic qubits to
states outside of the computational subspace. These advances allow us to
significantly reduce the resource cost for fault-tolerant quantum computation
compared to existing, general-purpose schemes. Our protocols can be implemented
in the near-term using state-of-the-art neutral atom platforms with qubits
encoded in both alkali and alkaline-earth atoms.


  Motion style transfer is a significant research direction in multimedia
applications. It enables the rapid switching of different styles of the same
motion for virtual digital humans, thus vastly increasing the diversity and
realism of movements. It is widely applied in multimedia scenarios such as
movies, games, and the Metaverse. However, most of the current work in this
field adopts the GAN, which may lead to instability and convergence issues,
making the final generated motion sequence somewhat chaotic and unable to
reflect a highly realistic and natural style. To address these problems, we
consider style motion as a condition and propose the Style Motion Conditioned
Diffusion (SMCD) framework for the first time, which can more comprehensively
learn the style features of motion. Moreover, we apply Mamba model for the
first time in the motion style transfer field, introducing the Motion Style
Mamba (MSM) module to handle longer motion sequences. Thirdly, aiming at the
SMCD framework, we propose Diffusion-based Content Consistency Loss and Content
Consistency Loss to assist the overall framework's training. Finally, we
conduct extensive experiments. The results reveal that our method surpasses
state-of-the-art methods in both qualitative and quantitative comparisons,
capable of generating more realistic motion sequences.


  We study the asymptotic behaviour of a family of dynamic models of crawling
locomotion, with the aim of characterizing a gait as a limit property. The
locomotors, which might have a discrete or continuous body, move on a line with
a periodic prescribed shape change, and might possibly be subject to external
forcing (e.g., crawling on a slope). We discuss how their behaviour is affected
by different types of friction forces, including also set-valued ones such as
dry friction. We show that, under mild natural assumptions, the dynamics always
converge to a relative periodic solution. The asymptotic average velocity of
the crawler yet might still depend on its initial state, so we provide
additional assumption for its uniqueness. In particular, we show that the
asymptotic average velocity is unique both for strictly monotone friction
forces, and also for dry friction, provided in the latter case that the
actuation is sufficiently smooth (for discrete models) or that the friction
coefficients are always nonzero (for continuous models). We present several
examples and counterexamples illustrating the necessity of our assumptions.


  Neural networks (NNs) are growing in importance and complexity. A neural
network's performance (and energy efficiency) can be bound either by
computation or memory resources. The processing-in-memory (PIM) paradigm, where
computation is placed near or within memory arrays, is a viable solution to
accelerate memory-bound NNs. However, PIM architectures vary in form, where
different PIM approaches lead to different trade-offs. Our goal is to analyze,
discuss, and contrast DRAM-based PIM architectures for NN performance and
energy efficiency. To do so, we analyze three state-of-the-art PIM
architectures: (1) UPMEM, which integrates processors and DRAM arrays into a
single 2D chip; (2) Mensa, a 3D-stack-based PIM architecture tailored for edge
devices; and (3) SIMDRAM, which uses the analog principles of DRAM to execute
bit-serial operations. Our analysis reveals that PIM greatly benefits
memory-bound NNs: (1) UPMEM provides 23x the performance of a high-end GPU when
the GPU requires memory oversubscription for a general matrix-vector
multiplication kernel; (2) Mensa improves energy efficiency and throughput by
3.0x and 3.1x over the Google Edge TPU for 24 Google edge NN models; and (3)
SIMDRAM outperforms a CPU/GPU by 16.7x/1.4x for three binary NNs. We conclude
that the ideal PIM architecture for NN models depends on a model's distinct
attributes, due to the inherent architectural design choices.


  We explicitly construct a class of holographic quantum error correction codes
with non-trivial centers in the code subalgebra. Specifically, we use the
Bacon-Shor codes and perfect tensors to construct a gauge code (or a stabilizer
code with gauge-fixing), which we call the holographic hybrid code. This code
admits a local log-depth encoding/decoding circuit, and can be represented as a
holographic tensor network which satisfies an analog of the Ryu-Takayanagi
formula and reproduces features of the sub-region duality. We then construct
approximate versions of the holographic hybrid codes by "skewing" the code
subspace, where the size of skewing is analogous to the size of the
gravitational constant in holography. These approximate hybrid codes are not
necessarily stabilizer codes, but they can be expressed as the superposition of
holographic tensor networks that are stabilizer codes. For such constructions,
different logical states, representing different bulk matter content, can
"back-react" on the emergent geometry, resembling a key feature of gravity. The
locality of the bulk degrees of freedom becomes subspace-dependent and
approximate. Such subspace-dependence is manifest from the point of view of the
"entanglement wedge" and bulk operator reconstruction from the boundary. Exact
complementary error correction breaks down for certain bipartition of the
boundary degrees of freedom; however, a limited, state-dependent form is
preserved for particular subspaces. We also construct an example where the
connected two-point correlation functions can have a power-law decay. Coupled
with known constraints from holography, a weakly back-reacting bulk also forces
these skewed tensor network models to the "large $N$ limit" where they are
built by concatenating a large $N$ number of copies.


  We introduce a noncommutative binary operation on matroids, called free
product. We show that this operation respects matroid duality, and has the
property that, given only the cardinalities, an ordered pair of matroids may be
recovered, up to isomorphism, from its free product. We use these results to
give a short proof of Welsh's 1969 conjecture, which provides a progressive
lower bound for the number of isomorphism classes of matroids on an n-element
set.


  When first deploying an anomaly detection system, e.g., to detect
out-of-scope queries in chatbots, there are no observed data, making
data-driven approaches ineffective. Zero-shot anomaly detection methods offer a
solution to such "cold-start" cases, but unfortunately they are often not
accurate enough. This paper studies the realistic but underexplored cold-start
setting where an anomaly detection model is initialized using zero-shot
guidance, but subsequently receives a small number of contaminated observations
(namely, that may include anomalies). The goal is to make efficient use of both
the zero-shot guidance and the observations. We propose ColdFusion, a method
that effectively adapts the zero-shot anomaly detector to contaminated
observations. To support future development of this new setting, we propose an
evaluation suite consisting of evaluation protocols and metrics.


  The shortest bibranching problem is a common generalization of the
minimum-weight edge cover problem in bipartite graphs and the minimum-weight
arborescence problem in directed graphs. For the shortest bibranching problem,
an efficient primal-dual algorithm is given by Keijsper and Pendavingh (1998),
and the tractability of the problem is ascribed to total dual integrality in a
linear programming formulation by Schrijver (1982). Another view on the
tractability of this problem is afforded by a valuated matroid intersection
formulation by Takazawa (2012). In the present paper, we discuss the
relationship between these two formulations for the shortest bibranching
problem. We first demonstrate that the valuated matroid intersection
formulation can be derived from the linear programming formulation through the
Benders decomposition, where integrality is preserved in the decomposition
process and the resulting convex programming is endowed with discrete
convexity. We then show how a pair of primal and dual optimal solutions of one
formulation is constructed from that of the other formulation, thereby
providing a connection between polyhedral combinatorics and discrete convex
analysis.


  The quantum triangular XXZ model has recently enjoyed a wealth of new
theoretical results, especially in relation to the modeling of the
Ba$_3$CoSb$_2$O$_9$ compound. In particular, it has been understood that in a
longitudinal magnetic field the umbrella (cone) phase, classically stable in
all the easy-plane region of the ground-state phase diagram, is considerably
reduced by the effect of quantum fluctuations. We provide more quantitative
information for this phenomenon at arbitrary value of the site spin $S$, by
employing the dilute Bose gas expansion, valid in the high-field regime; our
results improve the available estimates of the $1/S$ expansion. We quantify the
extent to which a higher spin suppresses the effect of quantum fluctuations.
Besides, we show how in three-dimensional layered systems a relatively small
antiferromagnetic interlayer coupling has a similar consequence of bringing
back the umbrella phase in some part of the phase diagram.


  Error mitigation is likely to be key in obtaining near term quantum
advantage. In this work we present one of the first implementations of several
Clifford data regression based methods which are used to mitigate the effect of
noise in real quantum data. We explore the dynamics of the 1-D Ising model with
transverse and longitudinal magnetic fields, highlighting signatures of
confinement. We find in general Clifford data regression based techniques are
advantageous in comparison with zero-noise extrapolation and obtain
quantitative agreement with exact results for systems of 9 qubits with circuit
depths of up to 176, involving hundreds of CNOT gates. This is the largest
systems investigated so far in a study of this type. We also investigate the
two-point correlation function and find the effect of noise on this more
complicated observable can be mitigated using Clifford quantum circuit data
highlighting the utility of these methods.


  The application of Stochastic Differential Equations (SDEs) to the analysis
of temporal data has attracted increasing attention, due to their ability to
describe complex dynamics with physically interpretable equations. In this
paper, we introduce a non-parametric method for estimating the drift and
diffusion terms of SDEs from a densely observed discrete time series. The use
of Gaussian processes as priors permits working directly in a function-space
view and thus the inference takes place directly in this space. To cope with
the computational complexity that requires the use of Gaussian processes, a
sparse Gaussian process approximation is provided. This approximation permits
the efficient computation of predictions for the drift and diffusion terms by
using a distribution over a small subset of pseudo-samples. The proposed method
has been validated using both simulated data and real data from economy and
paleoclimatology. The application of the method to real data demonstrates its
ability to capture the behaviour of complex systems.


  Dark matter or violations of the Einstein equivalence principle influence the
motion of atoms, their internal states as well as electromagnetic fields, thus
causing a signature in the signal of atomic detectors. To model such new
physics, we introduce dilaton fields and study the modified propagation of
light used to manipulate atoms in light-pulse atom interferometers. Their
interference signal is dominated by the matter's coupling to gravity and the
dilaton. Even though the electromagnetic field contributes to the phase, no
additional dilaton-dependent effect can be observed. However, the light's
propagation in gravity enters via a modified momentum transfer and its finite
speed. For illustration, we discuss effects from light propagation and the
dilaton on different atom-interferometric setups, including gradiometers,
equivalence principle tests, and dark matter detection.


  Analytical approximations for ${< \phi^2 >}$ and ${< T^{\mu}_{\nu} >}$ of a
quantized scalar field in static spherically symmetric spacetimes are obtained.
The field is assumed to be both massive and massless, with an arbitrary
coupling $\xi$ to the scalar curvature, and in a zero temperature vacuum state.
The expressions for ${< \phi^2 >}$ and ${< T^{\mu}_{\nu} >}$ are divided into
low- and high-frequency parts. The contributions of the high-frequency modes to
these quantities are calculated for an arbitrary quantum state. As an example,
the low-frequency contributions to ${< \phi^2 >}$ and ${< T^{\mu}_{\nu} >}$ are
calculated in asymptotically flat spacetimes in a quantum state corresponding
to the Minkowski vacuum (Boulware quantum state). The limits of the
applicability of these approximations are discussed.


  As revealed recently by the modeling of the multi-wavelength data of the
emission following GW170817/GRB 170817A, there was an off-axis energetic
relativistic outflow component launched by this historic double neutron star
merger event. In this work we use the results of these modeling to examine the
energy extraction process of the central engine. We show that the magnetic
process (i.e., the Blandford-Znajek mechanism) is favored, while the neutrino
process usually requires a too massive accretion disk if the duration of the
central engine activity is comparable to the observed $T_{90}$ of GRB 170817A,
unless the timescale of the central engine activity is less than $\sim$ 0.2s.
We propose that the GRB observations are helpful to constrain the combined
tidal parameter $\tilde{\Lambda}$, and by adopting the accretion disk mass
distribution estimated in BZ mechanism, the $90\%$ credible interval of
$\tilde{\Lambda}$ for the progenitor of GW170817 is inferred as $309-954$.


  By defining multiplicities for zeros of polynomials over hyperfields, Baker
and Lorscheid were able to provide a unifying perspective on Descartes's rule
and the Newton polygon rule for polynomials over a formally-real and valued
field respectively. In this paper, we apply their multiplicity formula to the
hyperfield associated with formally-real, valued fields to prove a Newton
polygon rule which combines Descartes's rule of signs with the classical Newton
polygon rule.


  Deep Learning models have shown remarkable performance in a broad range of
vision tasks. However, they are often vulnerable against domain shifts at
test-time. Test-time training (TTT) methods have been developed in an attempt
to mitigate these vulnerabilities, where a secondary task is solved at training
time simultaneously with the main task, to be later used as an self-supervised
proxy task at test-time. In this work, we propose a novel unsupervised TTT
technique based on the maximization of Mutual Information between multi-scale
feature maps and a discrete latent representation, which can be integrated to
the standard training as an auxiliary clustering task. Experimental results
demonstrate competitive classification performance on different popular
test-time adaptation benchmarks.


  In this paper, the parametrization of the nuclear structure function which is
directly constrained by the dynamics of QCD in its high-energy limit is
considered. This simple parameterization of the nuclear structure function is
obtained from the proton experimental data by relying on a Froissart-bounded
parametrization of the proton structure function. This phenomenological model
describes high-energy QCD in the presence of saturation effects. Numerical
calculations and comparison with available data from NMC, EMC and E665
Collaborations demonstrate that the suggested method by N.Armesto, C.A.Salgado
and U.A. Wiedemann (ASW model) provides reliable ratio of nuclear structure
functions $F_{2}^{A}/AF^{p}_{2}$ at low $x$ for light and heavy nuclei. The
magnitude of nuclear shadowing is predicted for various kinematic regions and
can be applied as well in analysis of ultra-high energy processes by future
experiments at electron-ion colliders.


  We investigate some aspects of the c=-2 logarithmic conformal field theory.
These include the various representations related to this theory, the
structures which come out of the Zhu algebra and the W algebra related to this
theory. We try to find the fermionic representations of all of the fields in
the extended Kac table especially for the untwisted sector case. In addition,
we calculate the various OPEs of the fields, especially the energy-momentum
tensor. Moreover, we investigate the important role of the zero modes in this
model. We close the paper by considering the perturbations of this theory and
their relationship to integrable models and generalization of Zamolodchikov's
$c-$theorem.


  We develop the general theory of spinning particles with electric and
magnetic dipole moments moving in arbitrary electromagnetic, inertial and
gravitational fields. Both the quantum-mechanical and classical dynamics is
investigated. We start from the covariant Dirac equation extended to a
spin-${\frac 12}$ fermion with anomalous magnetic and electric dipole moments
and then perform the relativistic Foldy-Wouthuysen transformation. This
transformation allows us to obtain the quantum-mechanical equations of motion
for the physical operators in the Schr\"odinger form and to establish the
classical limit of relativistic quantum mechanics. The results obtained are
then compared to the general classical description of the spinning particle
interacting with electromagnetic, inertial and gravitational fields. The
complete agreement between the quantum mechanics and the classical theory is
proven in the general case. As an application of the results obtained, we
consider the dynamics of a spinning particle in a gravitational wave and
analyze the prospects of using the magnetic resonance setup to find possible
manifestations of the gravitational wave on spin.


  This paper elucidates a model for acoustic single and multi-tone
classification in resource constrained edge devices. The proposed model is of
State-of-the-art Fast Accurate Stable Tiny Gated Recurrent Neural Network. This
model has resulted in improved performance metrics and lower size compared to
previous hypothesized methods by using lesser parameters with higher efficiency
and employment of a noise reduction algorithm. The model is implemented as an
acoustic AI module, focused for the application of sound identification,
localization, and deployment on AI systems like that of an autonomous car.
Further, the inclusion of localization techniques carries the potential of
adding a new dimension to the multi-tone classifiers present in autonomous
vehicles, as its demand increases in urban cities and developing countries in
the future.


  Mott transition has been realized in atomically thin monolayer (ML) of two
dimensional semiconductors (WS$_2$) via optically excited carriers above a
critical carrier density through many body interactions. The above nonlinear
optical transition occurs when excited electron hole pairs in ML WS2 continuum
heavily interact with each other followed by transformation into a collective
electron hole plasma phase (EHP), by losing their identity as individual
quasiparticles. This is manifested by the alluring red-shift-blue-shift
crossover (RBC) phenomena of the excitonic peaks in the emission spectra,
resulting from the synergistic attraction-repulsion processes at the
Mott-transition point. A systematic investigation of many-body effects is
reported on ML WS$_2$, while considering the modulated dielectric screening of
three different substrates, viz., silicon dioxide, sapphire, and gold.
Substrate doping effects on ML WS$_2$ are discussed using the Raman
fingerprints and PL spectral weight, which are further corroborated using
theoretical DFT calculations. Further the substrate dependent excitonic Bohr
radius of ML WS$_2$ is extracted via modelling the emission energy shift with
Lennard-Jones potential. The variation of Mott point as well as excitonic Bohr
radius is explained via substrate induced dielectric screening effect for both
the dielectric substrates, which is however absent in ML WS$_2$ on Au. Our
study therefore reveals diverse many-body ramifications in 2D semiconductors
and offers decisive outlooks on selecting the impeccable substrate materials
for innovative device engineering.


  In this paper, the classical Schr\"odinger equation, which allows the study
of classical dynamics in terms of wave functions, is analyzed theoretically and
numerically. First, departing from classical (Newtonian) mechanics, and
assuming an additional single-valued condition for the Hamilton's principal
function, the classical Schr\"odinger equation is obtained. This additional
assumption implies inherent non-classical features on the description of the
dynamics obtained from the classical Schr\"odinger equation: the trajectories
do not cross in the configuration space. Second, departing from Bohmian
mechanics and invoking the quantum-to-classical transition, the classical
Schr\"odinger equation is obtained in a natural way for the center of mass of a
quantum system with a large number of identical particles. This quantum
development imposes the condition of dealing with a narrow wave packet, which
implicitly avoids the non-classical features mentioned above. We illustrate all
the above points with numerical simulations of the classical and quantum
Schr\"odinger equations for different systems.


  Recent years have witnessed the availability of richer and richer datasets in
a variety of domains, where signals often have a multi-modal nature, blending
temporal, relational and semantic information. Within this context, several
works have shown that standard network models are sometimes not sufficient to
properly capture the complexity of real-world interacting systems. For this
reason, different attempts have been made to enrich the network language,
leading to the emerging field of higher-order networks. In this work, we
investigate the possibility of applying methods from higher-order networks to
extract information from the online trade of Non-fungible tokens (NFTs),
leveraging on their intrinsic temporal and non-Markovian nature. While NFTs as
a technology open up the realms for many exciting applications, its future is
marred by challenges of proof of ownership, scams, wash trading and possible
money laundering. We demonstrate that by investigating time-respecting
non-Markovian paths exhibited by NFT trades, we provide a practical path-based
approach to fraud detection.


  In this short note we consider the finite-dimensional distributions of sets
of states generated by dispersing billiards with a random initial condition. We
establish a functional correlation bound on the distance between the
finite-dimensional distributions and corresponding product distributions. We
demonstrate the usefulness of the bound by showing that it implies several
limit theorems. The purpose of this note is to provide a tool facilitating the
study of more general functionals of the billiard process.


  Prediction in quantum cosmology requires a specification of the universe's
quantum dynamics and its quantum state. We expect only a few general features
of the universe to be predicted with probabilities near unity conditioned on
the dynamics and quantum state alone. Most useful predictions are of
conditional probabilities that assume additional information beyond the
dynamics and quantum state. Anthropic reasoning utilizes probabilities
conditioned on `us'. This paper discusses the utility, limitations, and
theoretical uncertainty involved in using such probabilities. The predictions
resulting from various levels of ignorance of the quantum state are discussed
including those related to uncertainty in the vacuum of string theory. Some
obstacles to using anthropic reasoning to determine this vacuum are described.


  Nucleation at large metastability is still largely an unsolved problem,
although is a problem of tremendous current interest, with wide practical
value. It is well-accepted that the classical nucleation theory (CNT) fails to
provide a qualitative picture and gives incorrect quantitative values for such
quantities as activation free energy barrier and supersaturation dependence of
nucleation rate, especially at large metastability. In this article, we present
a powerful alternative formalism to treat nucleation at large supersaturation.
This formalism goes over to the classical picture at small supersaturation
where CNT is expected to be valid. The new theory is based on an extended set
of order parameters in terms of k-th largest liquid-like clusters where k=1 is
the largest cluster in the system, k=2 is the second largest cluster and so on.
We derive an analytic expression for the free energy of formation of the k-th
largest cluster which shows that at large metastability the barrier of growth
for the few largest liquid-like clusters disappear, the nucleation becomes
collective and the approach to the critical size occurs by barrierless
diffusion in the cluster size space. The expression for the rate of barrier
crossing predicts a weaker supersaturation dependence than that of CNT at large
metastability. Such a cross-over behavior has indeed been observed in recent
experiments but eluded an explanation till now. In order to understand the
large numerical difference between simulation predictions and experimental
results, we carried out a study of the dependence on the range of
intermolecular interaction of both the surface tension of an equilibrium planar
gas-liquid interface and the free energy barrier of nucleation. Both are found
to depend significantly on the range of interaction for a Lennard-Jones
potential, both in two and three dimensions.


  $\mathcal{I}$-non-degenerate spaces are spacetimes that can be characterized
uniquely by their scalar curvature invariants. The ultimate goal of the current
work is to construct a basis for the scalar polynomial curvature invariants in
three dimensional Lorentzian spacetimes. In particular, we seek a minimal set
of algebraically independent scalar curvature invariants formed by the
contraction of the Riemann tensor and its covariant derivatives up to fifth
order of differentiation. We use the computer software \emph{Invar} to
calculate an overdetermined basis of scalar curvature invariants in three
dimensions. We also discuss the equivalence method and the Karlhede algorithm
for computing Cartan invariants in three dimensions.


  We consider the question of which virtual knots have finite fundamental
medial bikei. We describe and implement an algorithm for completing a
presentation matrix of a medial bikei to an operation table, determining both
the cardinality and isomorphism class of the fundamental medial bikei, each of
which are link invariants. As an example, we compute the fundamental medial
bikei for all of the prime virtual knots with up to four classical crossings as
listed in the knot atlas.


  Herein, we report a improved method for the physical grafting of
1-nitropyrene (Pyr-NO2) onto highly graphitized carbon onion. This is achieved
through a lowering of the onset potential of the pyrene polymerization via in
situ reduction of the NO2 group. The additional redox activity pertaining to
the reduced NO2 enables exceeding the faradaic capacity which is associated
with the p-doping of the grafted pyrene backbone, as observed for pyrene,
1-aminopyrene, and unreduced Pyr- NO2. Theoretical calculations demonstrate the
charge transfer and binding enthalpy capabilities of Pyr-NO2, which are
significantly higher than those of the other two species, and which allow for
improved p-stacking on the carbon surface. Upon 20 wt % grafting of Pyr-NO2,
the capacity of the electrode jumps from 20 mAh g-1 electrode to 38 mAh g-
electrode, which corresponds to 110 mAh g-1 per mass of Pyr-NO2 and the average
potential is increased by 200 mV. Very interestingly, this high performance is
also coupled with outstanding retention with respect to both the initial
capacity for more than 4000 cycles, as well as the power characteristics,
demonstrating the considerable advantages of employing the present in situ
grafting technique.


  We present a harmonic model for the data analysis of an all-sky cosmic
microwave background survey, such as Planck, where the survey is obtained
through ring-scans of the sky. In this model, resampling and pixelisation of
the data are avoided. The spherical transforms of the sky at each frequency, in
total intensity and polarization, as well as the bright-point-source catalogue,
are derived directly from the data reduced onto the rings. Formal errors and
the most significant correlation coefficients for the spherical transforms of
the frequency maps are preserved. A clean and transparent path from the
original samplings in the time domain to the final scientific products is thus
obtained. The data analysis is largely based on Fourier analysis of rings; the
positional stability of the instrument's spin axis during these scans is a
requirement for the data model and is investigated here for the Planck
satellite. Brighter point sources are recognised and extracted as part of the
ring reductions and, on the basis of accumulated data, used to build a
catalogue. The analysis of the rings is performed iteratively, involving a
range of geometric and detector response calibrations. The reconstructed
spherical transforms of the sky form the input to the subsequent analysis
stages. Although the methods in this paper were developed with the data
processing for Planck in mind, many aspects should have wider application, such
as in the construction of real-space pixelised maps. (Abridged)


  Recently proposed de Sitter Swampland conjectures imply non-trivial
constraints on a scalar field potential in any effective field theory that
admits a quantum gravity completion. The original conjecture apparently
excludes many phenomenologically motivated scalar potentials with de Sitter
extrema, such as the perturbative Standard Model Higgs potential and the QCD
axion potential, as the viable low-energy theories. Subsequently, the refined,
weaker conjecture was proposed. However, the full effective potential, having
been defined as a Legendre transform, is necessarily convex. This ensures that
the original Swampland conjecture can actually be satisfied in
phenomenologically relevant models, providing no de Sitter vacua exist.


  The main aim of this paper is to provide a unified approach to deriving
identities for the Bernstein polynomials using a novel generating function. We
derive various functional equations and differential equations using this
generating function. Using these equations, we give new proofs both for a
recursive definition of the Bernstein basis functions and for derivatives of
the nth degree Bernstein polynomials. We also find some new identities and
properties for the Bernstein basis functions. Furthermore, we discuss analytic
representations for the generalized Bernstein polynomials through the binomial
or Newton distribution and Poisson distribution with mean and variance. Using
this novel generating function, we also derive an identity which represents a
pointwise orthogonality relation for the Bernstein basis functions. Finally, by
using the mean and the variance, we generalize Szasz-Mirakjan type basis
functions.


  This article reviews lattice QCD results for the light hadron spectrum. We
give an overview of different formulations of lattice QCD, with discussions on
the fermion doubling problem and improvement programs. We summarize recent
developments in algorithms and analysis techniques, that render calculations
with light, dynamical quarks feasible on present day computer resources.
Finally, we summarize spectrum results for ground state hadrons and resonances
using various actions.


  We give the first examples of (non-amenable group) amenable actions on stably
finite simple C*-algebras. More precisely, we give such actions for any
countable group in an explicit way. The main ingredients of our construction
are the full Fock space of the regular representation and a trace-scaling
automorphism.


  In this work we have done phenomenology based model calculations for some of
the thermodynamic and electrodynamic properties of the strongly correlated
superconductors of Cuprate type. The method involves the application of the
theoretical result for electronic specific heat in the normal phase from
Marginal Fermi Liquid theory to the Gorter-Casimir two fluid model to derive
the temperature dependence of the critical magnetic field corresponding to a
type-I system, using the standard variational technique. We also applied this
modified two fluid scheme to the London theory and obtained an expression for
the temperature dependence of the magnetic field penetration depth in the
superconducting phase. Our results are in fairly good agreement with other
theoretical results based on different approaches, as well as with the
experimental results.


  In networks of coupled oscillators, it is of interest to understand how
interaction topology affects synchronization. Many studies have gained key
insights into this question by studying the classic Kuramoto oscillator model
on static networks. However, new questions arise when network structure is
time-varying or when the oscillator system is multistable, the latter of which
can occur when an inertial term is added to the Kuramoto model. While the
consequences of evolving topology and multistability on collective behavior
have been examined separately, real-world systems such as gene regulatory
networks and the brain can exhibit these properties simultaneously. How does
the rewiring of network connectivity affect synchronization in systems with
multistability, where different paths of network evolution may differentially
impact system dynamics? To address this question, we study the effects of
time-evolving network topology on coupled Kuramoto oscillators with inertia. We
show that hysteretic synchronization behavior occurs when the network density
of coupled inertial oscillators is slowly varied as the dynamics evolve.
Moreover, we find that certain fixed-density rewiring schemes induce
significant changes to the level of global synchrony, and that these changes
remain after the network returns to its initial configuration and are robust to
a wide range of network perturbations. Our findings suggest that the specific
progression of network topology, in addition to its initial or final static
structure, can play a considerable role in modulating the collective behavior
of systems evolving on complex networks.


  A new fanning topology is proposed to precisely fan out fast control signals
in the Beijing Spectrometer (BES III) end-cap time-of-flight (ETOF)
electronics. However, uncertainty in transfer latency is introduced by the new
fanning channel, which will degrade the precision of fast control. In this
paper, latency uncertainty elimination for the BESIII ETOF upgrade is
introduced. The latency uncertainty is determined by a Time-Digital-Converter
(TDC) embedded in a Field-Programmable Gate Array (FPGA) and is eliminated by
re-capturing at synchronous and determinate time. Compared with the existing
method of Barrel-cap TOF (BTOF), it has advantages of flexible structure, easy
calibration and good adaptability. Field tests on the BES III ETOF system show
that this method effectively eliminates transfer latency uncertainty.


  Many algorithms have been developed to solve the inverse problem of coded
aperture snapshot spectral imaging (CASSI), i.e., recovering the 3D
hyperspectral images (HSIs) from a 2D compressive measurement. In recent years,
learning-based methods have demonstrated promising performance and dominated
the mainstream research direction. However, existing CNN-based methods show
limitations in capturing long-range dependencies and non-local self-similarity.
Previous Transformer-based methods densely sample tokens, some of which are
uninformative, and calculate the multi-head self-attention (MSA) between some
tokens that are unrelated in content. This does not fit the spatially sparse
nature of HSI signals and limits the model scalability. In this paper, we
propose a novel Transformer-based method, coarse-to-fine sparse Transformer
(CST), firstly embedding HSI sparsity into deep learning for HSI
reconstruction. In particular, CST uses our proposed spectra-aware screening
mechanism (SASM) for coarse patch selecting. Then the selected patches are fed
into our customized spectra-aggregation hashing multi-head self-attention
(SAH-MSA) for fine pixel clustering and self-similarity capturing.
Comprehensive experiments show that our CST significantly outperforms
state-of-the-art methods while requiring cheaper computational costs. The code
and models will be released at https://github.com/caiyuanhao1998/MST


  General non-commutative supersymmetric quantum mechanics models in two and
three dimensions are constructed and some two and three dimensional examples
are explicitly studied. The structure of the theory studied suggest other
possible applications in physical systems with potentials involving spin and
non-local interactions.


  In the field of computational pathology, the use of decision support systems
powered by state-of-the-art deep learning solutions has been hampered by the
lack of large labeled datasets. Until recently, studies relied on datasets in
the order of few hundreds of slides which are not enough to train a model that
can work at scale in the clinic. Here, we have gathered a dataset consisting of
12,160 slides, two orders of magnitude larger than previous datasets in
pathology and equivalent to 25 times the pixel count of the entire ImageNet
dataset. Given the size of our dataset it is possible for us to train a deep
learning model under the Multiple Instance Learning (MIL) assumption where only
the overall slide diagnosis is necessary for training, avoiding all the
expensive pixel-wise annotations that are usually part of supervised learning
approaches. We test our framework on a complex task, that of prostate cancer
diagnosis on needle biopsies. We performed a thorough evaluation of the
performance of our MIL pipeline under several conditions achieving an AUC of
0.98 on a held-out test set of 1,824 slides. These results open the way for
training accurate diagnosis prediction models at scale, laying the foundation
for decision support system deployment in the clinic.


  Let $\phi: M\to M$ be a diffeomorphism of a $C^\infty$ compact connected
manifold, and $X$ its mapping torus. There is a natural fibration $p:X\to S^1$,
denote by $\xi\in H^1(X, \mathbb{Z})$ the corresponding cohomology class. Let
$\lambda\in \mathbb{Z}^*$. Consider the endomorphism $\phi_k^*$ induced by
$\phi$ in the cohomology of $M$ of degree $k$, and denote by $J_k(\lambda)$ the
maximal size of its Jordan block of eigenvalue $\lambda$. Define a
representation $\rho_\lambda : \pi_1(X)\to\mathbb{C}^*$ by $\rho_\lambda (g) =
\lambda^{p_*(g)}.$ Let $H^*(X,\rho_\lambda)$ be the corresponding twisted
cohomology of $X$. We prove that $J_k(\lambda)$ is equal to the maximal length
of a non-zero Massey product of the form $\langle \xi, \ldots , \xi, a\rangle$
where $a\in H^k(X,\rho_\lambda)$ (here the length means the number of entries
of $\xi$). In particular, if $X$ is a strongly formal space (e.g. a K\"ahler
manifold) then all the Jordan blocks of $\phi_k^*$ are of size 1. If $X$ is a
formal space, then all the Jordan blocks of eigenvalue 1 are of size 1. This
leads to a simple construction of formal but not strongly formal mapping tori.
The proof of the main theorem is based on the fact that the Massey products of
the above form can be identified with differentials in a Massey spectral
sequence, which in turn can be explicitly computed in terms of the Jordan
normal form of $\phi^*$.


  We present an algorithm that identifies the reasoning patterns of agents in a
game, by iteratively examining the graph structure of its Multi-Agent Influence
Diagram (MAID) representation. If the decision of an agent participates in no
reasoning patterns, then we can effectively ignore that decision for the
purpose of calculating a Nash equilibrium for the game. In some cases, this can
lead to exponential time savings in the process of equilibrium calculation.
Moreover, our algorithm can be used to enumerate the reasoning patterns in a
game, which can be useful for constructing more effective computerized agents
interacting with humans.