  Electroencephalograph (EEG) emotion recognition is a significant task in the
brain-computer interface field. Although many deep learning methods are
proposed recently, it is still challenging to make full use of the information
contained in different domains of EEG signals. In this paper, we present a
novel method, called four-dimensional attention-based neural network (4D-aNN)
for EEG emotion recognition. First, raw EEG signals are transformed into 4D
spatial-spectral-temporal representations. Then, the proposed 4D-aNN adopts
spectral and spatial attention mechanisms to adaptively assign the weights of
different brain regions and frequency bands, and a convolutional neural network
(CNN) is utilized to deal with the spectral and spatial information of the 4D
representations. Moreover, a temporal attention mechanism is integrated into a
bidirectional Long Short-Term Memory (LSTM) to explore temporal dependencies of
the 4D representations. Our model achieves state-of-the-art performance on the
SEED dataset under intra-subject splitting. The experimental results have shown
the effectiveness of the attention mechanisms in different domains for EEG
emotion recognition.


  The IceCube Collaboration foresees to upgrade IceTop, the present surface
array, with scintillator detectors augmented by radio antennas. As one of
several goals the scintillator detectors will be used to measure and mitigate
the effects of snow accumulation on the IceTop tanks: the increasing energy
threshold and efficiency loss are nowadays the sources of the largest
systematic uncertainties in shower reconstruction and mass composition
analysis. In addition, the upgrade will provide useful experience for the
development of next generation neutrino detectors proposed for the South Pole.
In the Austral summer season, 2017-2018 two full "stations" were installed near
the center of the IceTop array. Each station features custom-designed
electronics and consists of seven detectors, each having an active area of
1.5m$^{2}$ plastic scintillator and wavelength shifting fibers read out by a
Silicon Photomultiplier. In this contribution we review the detector design and
performance, and show results from more than one year of operation of the
prototype stations. During that year several thousand air shower events have
been measured in coincidence with IceTop.


  We study the evolution of long-lived controversial debates as manifested on
Twitter from 2011 to 2016. Specifically, we explore how the structure of
interactions and content of discussion varies with the level of collective
attention, as evidenced by the number of users discussing a topic. Spikes in
the volume of users typically correspond to external events that increase the
public attention on the topic -- as, for instance, discussions about `gun
control' often erupt after a mass shooting.
  This work is the first to study the dynamic evolution of polarized online
debates at such scale. By employing a wide array of network and content
analysis measures, we find consistent evidence that increased collective
attention is associated with increased network polarization and network
concentration within each side of the debate; and overall more uniform lexicon
usage across all users.


  We review the observational evidence for extra mixing in stars on the red
giant branch (RGB) and discuss why thermohaline mixing is a strong candidate
mechanism. We recall the simple phenomenological description of thermohaline
mixing, and aspects of mixing in stars in general. We use observations of M3 to
constrain the form of the thermohaline diffusion coefficient and any associated
free parameters. This is done by matching [C/Fe] and [N/Fe] along the RGB of
M3. After taking into account a presumed initial primordial bimodality of
[C/Fe] in the CN-weak and CN-strong stars our thermohaline mixing models can
explain the full spread of [C/Fe]. Thermohaline mixing can produce a
significant change in [N/Fe] as a function of absolute magnitude on the RGB for
initially CN-weak stars, but not for initially CN-strong stars, which have so
much nitrogen to begin with that any extra mixing does not significantly affect
the surface nitrogen composition.


  A true Tree Calculus is being developed to make a joint study of the two
statistics "eoc" (end of minimal chain) and "pom" (parent of maximum leaf) on
the set of secant trees. Their joint distribution restricted to the set
{eoc-pom<= 1} is shown to satisfy two partial difference equation systems, to
be symmetric and to be expressed in the form of an explicit three-variable
generating function.


  Android is undergoing unprecedented malicious threats daily, but the existing
methods for malware detection often fail to cope with evolving camouflage in
malware. To address this issue, we present HAWK, a new malware detection
framework for evolutionary Android applications. We model Android entities and
behavioural relationships as a heterogeneous information network (HIN),
exploiting its rich semantic metastructures for specifying implicit
higher-order relationships. An incremental learning model is created to handle
the applications that manifest dynamically, without the need for
re-constructing the whole HIN and the subsequent embedding model. The model can
pinpoint rapidly the proximity between a new application and existing in-sample
applications and aggregate their numerical embeddings under various semantics.
Our experiments examine more than 80,860 malicious and 100,375 benign
applications developed over a period of seven years, showing that HAWK achieves
the highest detection accuracy against baselines and takes only 3.5ms on
average to detect an out-of-sample application, with the accelerated training
time of 50x faster than the existing approach.


  This paper investigates the achievable total degrees of freedom (DoF) of the
MIMO multi-way relay channel that consists of K users, where each user is
equipped with M antennas, and a decode-and-forward relay equipped with N
antennas. In this channel, each user wants to convey K-1 private messages to
the other users in addition to a common message to all of them. Due to the
absence of direct links between the users, communication occurs through the
relay in two phases; a multiple access channel phase (MAC) and a broadcast (BC)
phase. We drive cut-set bounds on the total DoF of the network, and show that
the network has DoF less than or equal to K min(N,M). Achievability of the
upper bound is shown by using signal space alignment for network coding in the
MAC phase, and zero-forcing precoding in the BC phase. We show that introducing
the common messages besides the private messages leads to achieving higher
total DoF than using the private messages only.


  The theta correspondence has been an important tool in studying cycles in
locally symmetric spaces of orthogonal type. In this paper, we establish for
O(p,2) an adjointness result between Borcherds' singular theta lift and the
Kudla-Millson theta lift. We extend this result to arbitrary signature by
introducing a new Borcherds lift for O(p,q). On the geometric side, this lift
can be interpreted as a differential character in the sense of Cheeger and
Simons.


  Films of all-important compound hafnia (HfO2) can be prepared in an
orthorhombic ferroelectric (FE) state that is ideal for applications, e.g. in
memories or negative-capacitance field-effect transistors. The origin of this
FE state remains a mystery, though, as none of the proposed mechanisms for its
stabilization -- from surface and size effects to formation kinetics -- is
fully convincing. Interestingly, it is known that doping HfO2 with various
cations favors the occurrence of the FE polymorph; however, existing
first-principles works suggest that doping by itself is not sufficient to
stabilize the polar phase over the usual non-polar monoclinic ground state.
Here we use first-principles methods to reexamine this question. We consider
two representative isovalent substitutional dopants, Si and Zr, and study their
preferred arrangement within the HfO2 lattice. Our results reveal that small
atoms like Si can adopt very stable configurations (forming layers within
specific crystallographic planes) in the FE orthorhombic phase of HfO2, but
comparatively less so in the non-polar monoclinic one. Further, we find that,
at low concentrations, such a dopant ordering yields a FE ground state, the
usual paraelectric phase becoming a higher-energy metastable polymorph. We
discuss the implications of our findings, which constitute a definite step
forward towards understanding ferroelectricity in HfO2.


  Chemically peculiar stars in eclipsing binary systems are rare objects that
allow the derivation of fundamental stellar parameters and important
information on the evolutionary status and the origin of the observed chemical
peculiarities. Here we present an investigation of the known eclipsing binary
system BD+09 1467 = V680 Mon. Using spectra from the Large Sky Area
Multi-Object Fiber Spectroscopic Telescope (LAMOST) and own observations, we
identify the primary component of the system as a mercury-manganese (HgMn/CP3)
star (spectral type kB9 hB8 HeB9 V HgMn). Furthermore, photometric time series
data from the Transiting Exoplanet Survey Satellite (TESS) indicate that the
system is a "heartbeat star", a rare class of eccentric binary stars with
short-period orbits that exhibit a characteristic signature near the time of
periastron in their light curves due to the tidal distortion of the components.
Using all available photometric observations, we present an updated ephemeris
and binary system parameters as derived from modelling of the system with the
ELISa code, which indicates that the secondary star has an effective
temperature of Teff = 8300+-200 K (spectral type of about A4). V680 Mon is only
the fifth known eclipsing CP3 star and the first one in a heartbeat binary.
Furthermore, our results indicate that the star is located on the zero-age main
sequence and a possible member of the open cluster NGC 2264. As such, it lends
itself perfectly for detailed studies and may turn out to be a keystone in the
understanding of the development of CP3 star peculiarities.


  Kernel methods play a critical role in many machine learning algorithms. They
are useful in manifold learning, classification, clustering and other data
analysis tasks. Setting the kernel's scale parameter, also referred to as the
kernel's bandwidth, highly affects the performance of the task in hand. We
propose to set a scale parameter that is tailored to one of two types of tasks:
classification and manifold learning. For manifold learning, we seek a scale
which is best at capturing the manifold's intrinsic dimension. For
classification, we propose three methods for estimating the scale, which
optimize the classification results in different senses. The proposed
frameworks are simulated on artificial and on real datasets. The results show a
high correlation between optimal classification rates and the estimated scales.
Finally, we demonstrate the approach on a seismic event classification task.


  We improve the estimation of the distribution of the nontrivial zeros of
Riemann zeta function $\zeta(\sigma+it)$ for sufficiently large $t$, which is
based on an exact calculation of some special logarithmic integrals of
nonvanishing $\zeta(\sigma+it)$ along well-chosen contours. A special and
single-valued coordinate transformation $s=\tau(z)$ is chosen as the inverse of
$z=\chi(s)$, and the functional equation $\zeta(s) = \chi(s)\zeta(1-s)$ is
simplified as $G(z) = z\, G_-(\frac{1}{z})$ in the $z$ coordinate, where
$G(z)=\zeta(s)=\zeta\circ\tau(z)$ and $G_-$ is the conjugated branch of $G$.
Two types of special and symmetric contours $\partial D_{\epsilon}^1$ and
$\partial D_{\epsilon}^2$ in the $s$ coordinate are specified, and improper
logarithmic integrals of nonvanishing $\zeta(s)$ along $\partial
D_{\epsilon}^1$ and $\partial D_{\epsilon}^2$ can be calculated as $2\pi i$ and
$0$ respectively, depending on the total increase in the argument of
$z=\chi(s)$. Any domains in the critical strip for sufficiently large $t$ can
be covered by the domains $D_{\epsilon}^1$ or $D_{\epsilon}^2$, and the
distribution of nontrivial zeros of $\zeta(s)$ is revealed in the end, which is
more subtle than Riemann's initial hypothesis and in rhythm with the argument
of $\chi(\frac{1}{2}+it)$.


  Two-ribbon brightenings are one of the most remarkable characteristics of an
eruptive solar flare and are often used for predicting the occurrence of
coronal mass ejections (CMEs). Nevertheless, it was called in question recently
whether all two-ribbon flares are eruptive. In this paper, we investigate a two
ribbon-like white-light (WL) flare that is associated with a failed magnetic
flux rope (MFR) eruption on 2015 January 13, which has no accompanying CME in
the WL coronagraph. Observations by \textit{Optical and Near-infrared Solar
Eruption Tracer} and \textit{Solar Dynamics Observatory} reveal that, with the
increase of the flare emission and the acceleration of the unsuccessfully
erupting MFR, two isolated kernels appear at the WL 3600 {\AA} passband and
quickly develop into two elongated ribbon-like structures. The evolution of the
WL continuum enhancement is completely coincident in time with the variation of
\textit{Fermi} hard X-ray 26--50 keV flux. Increase of continuum emission is
also clearly visible at the whole FUV and NUV passbands observed by
\textit{Interface Region Imaging Spectrograph}. Moreover, in one WL kernel, the
\ion{Si}{4}, \ion{C}{2}, and \ion{Mg}{2} h/k lines display significant
enhancement and non-thermal broadening. However, their Doppler velocity pattern
is location-dependent. At the strongly bright pixels, these lines exhibit a
blueshift; while at moderately bright ones, the lines are generally redshifted.
These results show that the failed MFR eruption is also able to produce a
two-ribbon flare and high-energy electrons that heat the lower atmosphere,
causing the enhancement of the WL and FUV/NUV continuum emissions and
chromospheric evaporation.


  Black box models of technical systems are purely descriptive. They do not
explain why a system works the way it does. Thus, black box models are
insufficient for some problems. But there are numerous applications, for
example, in control engineering, for which a black box model is absolutely
sufficient. In this article, we describe a general stochastic framework with
which such models can be built easily and fully automated by observation.
Furthermore, we give a practical example and show how this framework can be
used to model and control a motorcar powertrain.


  The study of the critical dynamics in complex systems is always interesting
yet challenging. Here, we choose financial market as an example of a complex
system, and do a comparative analyses of two stock markets - the S&P 500 (USA)
and Nikkei 225 (JPN). Our analyses are based on the evolution of
crosscorrelation structure patterns of short time-epochs for a 32-year period
(1985-2016). We identify "market states" as clusters of similar correlation
structures, which occur more frequently than by pure chance (randomness). The
dynamical transitions between the correlation structures reflect the evolution
of the market states. Power mapping method from the random matrix theory is
used to suppress the noise on correlation patterns, and an adaptation of the
intra-cluster distance method is used to obtain the "optimum" number of market
states. We find that the USA is characterized by four market states and JPN by
five. We further analyze the co-occurrence of paired market states; the
probability of remaining in the same state is much higher than the transition
to a different state. The transitions to other states mainly occur among the
immediately adjacent states, with a few rare intermittent transitions to the
remote states. The state adjacent to the critical state (market crash) may
serve as an indicator or a "precursor" for the critical state and this novel
method of identifying the long-term precursors may be very helpful for
constructing the early warning system in financial markets, as well as in other
complex systems.


  A search is performed for a long-lived particle decaying into a final state
that includes a pair of muons of opposite-sign electric charge, using
proton-proton collision data collected at $\sqrt{s}=$ 13 TeV by the ATLAS
detector at the Large Hadron Collider corresponding to an integrated luminosity
of 32.9 fb$^{-1}$. No significant excess over the Standard Model expectation is
observed. Limits at 95% confidence level on the lifetime of the long-lived
particle are presented in models of new phenomena including gauge-mediated
supersymmetry or decay of the Higgs boson, $H$, to a pair of dark photons,
$Z_D$. Lifetimes in the range c$\tau$ = 1-2400 cm are excluded, depending on
the parameters of the model. In the supersymmetric model, the lightest
neutralino is the next-to-lightest supersymmetric particle, with a relatively
long lifetime due to its weak coupling to the gravitino, the lightest
supersymmetric particle. The lifetime limits are determined for very light
gravitino mass and various assumptions for the neutralino mass in the range 300
GeV to 1000 GeV. In the dark photon model, the lifetime limits are interpreted
as exclusion contours in the plane of the coupling between the $Z_D$ and the
Standard Model $Z$ boson versus the $Z_D$ mass (in the range 20-60 GeV), for
various assumptions for the $H\rightarrow Z_D Z_D$ branching fraction.


  With the rapid growth of software, using third-party libraries (TPLs) has
become increasingly popular. The prosperity of the library usage has provided
the software engineers with handful of methods to facilitate and boost the
program development. Unfortunately, it also poses great challenges as it
becomes much more difficult to manage the large volume of libraries. Researches
and studies have been proposed to detect and understand the TPLs in the
software. However, most existing approaches rely on syntactic features, which
are not robust when these features are changed or deliberately hidden by the
adversarial parties. Moreover, these approaches typically model each of the
imported libraries as a whole, therefore, cannot be applied to scenarios where
the host software only partially uses the library code segments.
  To detect both fully and partially imported TPLs at the semantic level, we
propose ModX, a framework that leverages novel program modularization
techniques to decompose the program into finegrained functionality-based
modules. By extracting both syntactic and semantic features, it measures the
distance between modules to detect similar library module reuse in the program.
Experimental results show that ModX outperforms other modularization tools by
distinguishing more coherent program modules with 353% higher module quality
scores and beats other TPL detection tools with on average 17% better in
precision and 8% better in recall.


  We show that the class of Krasner hyperfields is not elementary. To show
this, we determine the rational rank of quotients of multiplicative groups in
field extensions. Our argument uses Chebotarev's density theorem. We also
discuss some related questions.


  Segment Routing is a form of loose source routing. It provides the ability to
include a list of instructions (called segments), in the packet headers. The
Segment Routing architecture has been first implemented with the MPLS dataplane
and then, quite recently, with the IPv6 dataplane (SRv6). IPv6 Segment Routing
(SRv6) is a promising solution to support advanced services such as Traffic
Engineering, Service Function Chaining, Virtual Private Networks, and Load
Balancing. The SRv6 data-plane is supported in many different software
forwarding engines including the Linux kernel and VPP software router, as well
as in hardware devices. In this paper, we present SRPerf, a performance
evaluation framework for software and hardware implementations of SRv6. SRPerf
is able to perform different benchmarking tests such as throughput and latency.
For throughput tests, we use the Partial Drop Rate (PDR) to characterize a
system under test. The architecture of SRPerf can be easily extended to support
new benchmarking methodologies as well as different SRv6 implementations. We
have used SRPerf to evaluate the performance of the SRv6 implementation in the
Linux kernel and in VPP. SRPerf is a valuable tool in the context of software
forwarding engines where new features can be added at fast pace, as it helps
experimenters to validate their work. In particular, we describe how we have
leveraged SRPerf to validate the implementation of some SRv6 behaviors that
were missing or wrongly implemented in the Linux kernel mainline.


  We propose that the contrasting low-temperature behaviors observed
experimentally among isostructural and isoelectronic materials, like
non-superconducting and nonmagnetic MgFeGe, magnetically ordered NaFeAs, and
superconducting LiFeAs, can be well understood from itinerant weak coupling
limit. We find that stronger $(\pi,\pi)$ instability appearing in the
d$_{x^2-y^2}$ orbital of NaFeAs is responsible for the occurrence of weak
magnetism while weaker but still prominent $(\pi,\pi)$ instability in LiFeAs
leads to a superconducting state. In contrast, multiple competing instabilities
coexisting in orbital-resolved momentum-dependent susceptibilities, serving as
magnetic frustrations from itinerant electrons, may account for the nonmagnetic
state in MgFeGe, while poorer Fermi surface nesting leads to a
non-superconducting state. Based on above findings, we predict a possible way
to make MgFeGe a new Fe-based superconductor.


  In the Localization game played on graphs, a set of cops uses distance probes
to identify the location of an invisible robber. We present an extension of the
game and its main parameter, the localization number, to directed graphs. We
present several bounds on the localization number of a directed graphs,
including a tight bound via strong components, a bound using a linear
programming problem on hypergraphs, and bounds in terms of pathwidth and
DAG-width. A family of digraphs of order $n$ is given with localization number
$(1-o(1))n/2$. We investigate the localization number of random and
quasi-random tournaments, and apply our results to doubly regular tournaments,
which include Paley tournaments.


  Network pruning is an effective method to reduce the computational expense of
over-parameterized neural networks for deployment on low-resource systems.
Recent state-of-the-art techniques for retraining pruned networks such as
weight rewinding and learning rate rewinding have been shown to outperform the
traditional fine-tuning technique in recovering the lost accuracy (Renda et
al., 2020), but so far it is unclear what accounts for such performance. In
this work, we conduct extensive experiments to verify and analyze the uncanny
effectiveness of learning rate rewinding. We find that the reason behind the
success of learning rate rewinding is the usage of a large learning rate.
Similar phenomenon can be observed in other learning rate schedules that
involve large learning rates, e.g., the 1-cycle learning rate schedule (Smith
et al., 2019). By leveraging the right learning rate schedule in retraining, we
demonstrate a counter-intuitive phenomenon in that randomly pruned networks
could even achieve better performance than methodically pruned networks
(fine-tuned with the conventional approach). Our results emphasize the
cruciality of the learning rate schedule in pruned network retraining - a
detail often overlooked by practitioners during the implementation of network
pruning. One-sentence Summary: We study the effective of different retraining
mechanisms while doing pruning


  In this paper we prove the equivalence of definitions for metric trees and
for \delta-hyperbolic spaces. We point out how these equivalences can be used
to understand the geometric and metric properties of \delta-hyperbolic spaces
and its relation to CAT(\kappa) spaces.


  A survey of young bipolar outflows in regions of low-to-intermediate-mass
star formation has been carried out in two class I methanol maser transitions:
7_0-6_1A+ at 44 GHz and 4_{-1}-3_0E at 36 GHz. We detected narrow features
towards NGC 1333I2A, NGC 1333I4A, HH25MMS, and L1157 at 44 GHz, and towards NGC
2023 at 36 GHz. Flux densities of the lines detected at 44 GHz are no higher
than 11 Jy and the relevant source luminosities are about 10^{22} erg s{-1},
which is much lower than those of strong masers in high-mass star formation
regions. No emission was found towards 39 outflows. All masers detected at 44
GHz are located in clouds with methanol column densities of the order of or
larger than a few x 10^{14} cm$^{-2}. The upper limits for the non-detections
are typically of the order of 3--5 Jy. Observations in 2004, 2006, and 2008 did
not reveal any significant variability of the 44 GHz masers in NGC 1333I4A,
HH25MMS, and L1157.


  We investigate the capacity of a multiple access channel with cooperating
encoders where partial state information is known to each encoder and full
state information is known to the decoder. The cooperation between the encoders
has a two-fold purpose: to generate empirical state coordination between the
encoders, and to share information about the private messages that each encoder
has. For two-way cooperation, this two-fold purpose is achieved by
double-binning, where the first layer of binning is used to generate the state
coordination similarly to the two-way source coding, and the second layer of
binning is used to transmit information about the private messages. The
complete result provides the framework and perspective for addressing a complex
level of cooperation that mixes states and messages in an optimal way.


  The SU(1,1) coherent states for a relativistic model of the linear singular
oscillator are considered. The corresponding partition function is evaluated.
The path integral for the transition amplitude between SU(1,1) coherent states
is given. Classical equations of the motion in the generalized curved phase
space are obtained. It is shown that the use of quasiclassical Bohr-Sommerfeld
quantization rule yields the exact expression for the energy spectrum.


  Context: Understanding how protostars accrete their mass is a central
question of star formation. One aspect of this is trying to understand whether
the time evolution of accretion rates in deeply embedded objects is best
characterised by a smooth decline from early to late stages or by intermittent
bursts of high accretion.
  Aims: We create synthetic observations of deeply embedded protostars in a
large numerical simulation of a molecular cloud, which are compared directly to
real observations. The goal is to compare episodic accretion events in the
simulation to observations and to test the methodology used for analysing the
observations.
  Methods: Simple freeze-out and sublimation chemistry is added to the
simulation, and synthetic C$^{18}$O line cubes are created for a large number
of simulated protostars. The spatial extent of C$^{18}$O is measured for the
simulated protostars and compared directly to a sample of 16 deeply embedded
protostars observed with the Submillimeter Array. If CO is distributed over a
larger area than predicted based on the protostellar luminosity, it may
indicate that the luminosity has been higher in the past and that CO is still
in the process of refreezing.
  Results: Approximately 1% of the protostars in the simulation show extended
C$^{18}$O emission, as opposed to approximately 50% in the observations,
indicating that the magnitude and frequency of episodic accretion events in the
simulation is too low relative to observations. The protostellar accretion
rates in the simulation are primarily modulated by infall from the larger
scales of the molecular cloud, and do not include any disk physics. The
discrepancy between simulation and observations is taken as support for the
necessity of disks, even in deeply embedded objects, to produce episodic
accretion events of sufficient frequency and amplitude.


  This paper has been withdrawn by the author. The statement of the Main
Theorem but is wrong in general, there have been provided counterexamples. The
main theorem only holds conditionally, under the finiteness statement of
theorem 2.8.


  We present a new version of our code for modeling the atmospheric circulation
on gaseous exoplanets, now employing a "double-gray" radiative transfer scheme,
which self-consistently solves for fluxes and heating throughout the
atmosphere, including the emerging (observable) infrared flux. We separate the
radiation into infrared and optical components, each with its own absorption
coefficient, and solve standard two-stream radiative transfer equations. We use
a constant optical absorption coefficient, while the infrared coefficient can
scale as a powerlaw with pressure. Here we describe our new code in detail and
demonstrate its utility by presenting a generic hot Jupiter model. We discuss
issues related to modeling the deepest pressures of the atmosphere and describe
our use of the diffusion approximation for radiative fluxes at high optical
depths. In addition, we present new models using a simple form for magnetic
drag on the atmosphere. We calculate emitted thermal phase curves and find that
our drag-free model has the brightest region of the atmosphere offset by ~12
degrees from the substellar point and a minimum flux that is 17% of the
maximum, while the model with the strongest magnetic drag has an offset of only
~2 degrees and a ratio of 13%. Finally, we calculate rates of numerical loss of
kinetic energy at ~15% for every model except for our strong-drag model, where
there is no measurable loss; we speculate that this is due to the much
decreased wind speeds in that model.


  The recently developed self-consistent vertex corrected GW method is used to
calculate the 5f electronic structure in delocalized $\alpha$-U and localized
$\delta$-Pu, each of which is confirmed by the historical experimental
approaches of direct and inverse photoemission. Tender X-Ray Emission
Spectroscopy (XES), in a novel application to 5f electronic structure, is used
to experimentally prove the existence of 5f delocalization in $\alpha$-U.


  We Use the method of linearly independent polynomials to derive an upper
bound for the cardinality of a spherical s-distance set F where the sum of
distinct inner products of any two elements from F is zero. Our result
generalizes the well-known Gerzon's bound for the cardinality of an equiangular
spherical set to a significantly broader class of spherical s-distance sets.


  We provide a systematic classification of multiparticle entanglement in terms
of equivalence classes of states under stochastic local operations and
classical communication (SLOCC). We show that such an SLOCC equivalency class
of states is characterized by ratios of homogenous polynomials that are
invariant under local action of the special linear group. We then construct the
complete set of all such SL-invariant polynomials (SLIPs). Our construction is
based on Schur-Weyl duality and applies to any number of qudits in all (finite)
dimensions. In addition, we provide an elegant formula for the dimension of the
homogenous SLIPs space of a fixed degree as a function of the number of qudits.
The expressions for the SLIPs involve in general many terms, but for the case
of qubits we also provide much simpler expressions.


  By means of two dimensional, general-relativistic, magneto-hydrodynamical
simulations we investigate the oscillations of magnetized neutron star models
(magnetars) including the description of an extended solid crust. The aim of
this study is to understand the origin of the QPOs observed in the giant flares
of SGRs. We confirm the existence of three different regimes: (a) a weak
magnetic field regime B<5 x 10^13 G, where crustal shear modes dominate the
evolution; (b) a regime of intermediate magnetic fields 5 x 10^13 G<B< 10^15 G,
where Alfv\'en QPOs are mainly confined to the core of the neutron star and the
crustal shear modes are damped very efficiently; and (c) a strong field regime
B>10^15 G, where magneto-elastic oscillations reach the surface and approach
the behavior of purely Alfv\'en QPOs. When the Alfv\'en QPOs are confined to
the core of the neutron star, we find qualitatively similar QPOs as in the
absence of a crust. The lower QPOs associated with the closed field lines of
the dipolar magnetic field configuration are reproduced as in our previous
simulations without crust, while the upper QPOs connected to the open field
lines are displaced from the polar axis. Additionally, we observe a family of
edge QPOs. Our results do not leave much room for a crustal-mode interpretation
of observed QPOs in SGR giant flares, but can accommodate an interpretation of
these observations as originating from Alfv\'en-like, global, turning-point
QPOs in models with dipolar magnetic field strengths in the narrow range of 5 x
10^15 G < B < 1.4 x 10^16 G. This range is somewhat larger than estimates for
magnetic field strengths in known magnetars. The discrepancy may be resolved in
models including a more complicated magnetic field structure or with models
taking superfluidity of the neutrons and superconductivity of the protons in
the core into account.


  Improving earlier work of Balasubramanian, Conrey and Heath-Brown, we obtain
an asymptotic formula for the mean-square of the Riemann zeta-function times an
arbitrary Dirichlet polynomial of length $T^{1/2 + \delta}$, with $\delta =
0.01515....$ As an application we obtain an upper bound of the correct order of
magnitude for the third moment of the Riemann zeta-function. We also refine
previous work of Deshouillers and Iwaniec, obtaining asymptotic estimates in
place of bounds. Using the work of Watt, we compute the mean-square of the
Riemann zeta-function times a Dirichlet polynomial of length going up to
$T^{3/4}$ provided that the Dirichlet polynomial assumes a special shape.
Finally, we exhibit a conjectural estimate for trilinear sums of Kloosterman
fractions which implies the Lindelof Hypothesis.


  The unknotting number is the classical invariant of a knot. However, its
determination is difficult in general. To obtain the unknotting number from
definition one has to investigate all possible diagrams of the knot. We tried
to show the unknotting number can be obtained from any one diagram of the knot.
To do this we tried to prove the unknotting number is not changed under
Riedemiester moves, but such a proposition is not correct. Reidemeister II move
can change unknotting number. See Nakanishi-Bleiler example. So this article is
withdrawn.


  Many applications of reinforcement learning can be formalized as
goal-conditioned environments, where, in each episode, there is a "goal" that
affects the rewards obtained during that episode but does not affect the
dynamics. Various techniques have been proposed to improve performance in
goal-conditioned environments, such as automatic curriculum generation and goal
relabeling. In this work, we explore a connection between off-policy
reinforcement learning in goal-conditioned settings and knowledge distillation.
In particular: the current Q-value function and the target Q-value estimate are
both functions of the goal, and we would like to train the Q-value function to
match its target for all goals. We therefore apply Gradient-Based Attention
Transfer (Zagoruyko and Komodakis 2017), a knowledge distillation technique, to
the Q-function update. We empirically show that this can improve the
performance of goal-conditioned off-policy reinforcement learning when the
space of goals is high-dimensional. We also show that this technique can be
adapted to allow for efficient learning in the case of multiple simultaneous
sparse goals, where the agent can attain a reward by achieving any one of a
large set of objectives, all specified at test time. Finally, to provide
theoretical support, we give examples of classes of environments where (under
some assumptions) standard off-policy algorithms such as DDPG require at least
O(d^2) replay buffer transitions to learn an optimal policy, while our proposed
technique requires only O(d) transitions, where d is the dimensionality of the
goal and state space. Code is available at
https://github.com/alevine0/ReenGAGE.


  Nanocrystalline bulk materials are desirable for many applications as they
combine mechanical strength and specific electronic transport properties. Our
bottom up approach starts with tailored nanoparticles. Compaction and thermal
treatment are crucial, but usually the final stage sintering is accompanied by
rapid grain growth which spoils nanocristallinity. For electrically conducting
nanoparticles, field activated sintering techniques overcome this problem.
Small grain sizes have been maintained in spite of consolidation. Nevertheless,
the underlying principles, which are of high practical impact, have not been
fully elucidated yet. In this combined experimental and theoretical work we
show, how the developing microstructure during sintering correlates to the
percolation paths of the current through the powder using highly doped silicon
nanoparticles as a model system. It is possible to achieve a nanocrystalline
bulk material and a homogeneous microstructure. For this, not only the
generation of current paths due compaction, but also the disintegration due to
joule heating is required. The observed density fluctuations on the micrometer
scale are attributed to the specific heat profile of the simulated powder
networks.


  An epidemiological compartmental model was used to simulate social distancing
strategies to contain the COVID-19 pandemic and prevent a second wave in Sao
Paulo, Brazil. Optimization using genetic algorithm was used to determine the
optimal solutions. Our results suggest the best-case strategy for Sao Paulo is
to maintain or increase the current magnitude of social distancing for at least
60 more days and increase the current levels of personal protection behaviors
by a minimum of 10% (e.g., wearing facemasks, proper hand hygiene and avoid
agglomeration). Followed by a long-term oscillatory level of social distancing
with a stepping-down approach every 80 days over a period of two years with
continued protective behavior.


  Enabling full robotic workloads with diverse behaviors on mobile systems with
stringent resource and energy constraints remains a challenge. In recent years,
attempts have been made to deploy single-accelerator-based computing platforms
(such as GPU, DSP, or FPGA) to address this challenge, but with little success.
The core problem is two-fold: firstly, different robotic tasks require
different accelerators, and secondly, managing multiple accelerators
simultaneously is overwhelming for developers. In this paper, we propose PIRT,
the first robotic runtime framework to efficiently manage dynamic task
executions on mobile systems with multiple accelerators as well as on the cloud
to achieve better performance and energy savings. With PIRT, we enable a robot
to simultaneously perform autonomous navigation with 25 FPS of localization,
obstacle detection with 3 FPS, route planning, large map generation, and scene
understanding, traveling at a max speed of 5 miles per hour, all within an 11W
computing power envelope.


  Let $\phi$ be a positive unital normal map of a von Neumann algebra $M$ into
itself, and assume there is a family of normal $\phi$-invariant states which is
faithful on the von Neumann algebra generated by the image of $\phi$. It is
shown that there exists a largest Jordan subalgebra $C_\phi$ of $M$ such that
the restriction of $\phi$ to $C_\phi$ is a Jordan automorphhism, and each weak
limit point of $(\phi^n (a))$ for $a\in M$ belongs to $C_\phi$.


  In his PhD thesis, Abrams proved that, for a natural number n and a graph G
with at least n vertices, the n-strand configuration space of G deformation
retracts to a compact subspace, the discretized n-strand configuration space,
provided G satisfies two conditions: each path between distinct essential
vertices (vertices of degree not equal to 2) is of length at least n+1 edges,
and each path from a vertex to itself which is not nullhomotopic is of length
at least n+1 edges. Using Forman's discrete Morse theory for CW-complexes, we
show the first condition can be relaxed to require only that each path between
distinct essential vertices is of length at least n-1.


  Datacenter networks commonly facilitate the transmission of data in
distributed computing frameworks through coflows, which are collections of
parallel flows associated with a common task. Most of the existing research has
concentrated on scheduling coflows to minimize the time required for their
completion, i.e., to optimize the average dispatch rate of coflows in the
network fabric. Nevertheless, modern applications often produce coflows that
are specifically intended for online services and mission-crucial computational
tasks, necessitating adherence to specific deadlines for their completion. In
this paper, we introduce \wdcoflow,~ a new algorithm to maximize the weighted
number of coflows that complete before their deadline. By combining a dynamic
programming algorithm along with parallel inequalities, our heuristic solution
performs at once coflow admission control and coflow prioritization, imposing a
$\sigma$-order on the set of coflows. With extensive simulation, we demonstrate
the effectiveness of our algorithm in improving up to $3\times$ more coflows
that meet their deadline in comparison the best SoA solution, namely
$\mathtt{CS\text{-}MHA}$. Furthermore, when weights are used to differentiate
coflow classes, \wdcoflow~ is able to improve the admission per class up to
$4\times$, while increasing the average weighted coflow admission rate.


  Used in the paper is an overcomplete piecewise-polynomial image model
incorporating sparsity. The paper shows that using such a model, the edges in
the image can be resolved robustly with respect to noise. Two variants of the
proposed approach are both shown to be superior to the use of the classic edge
detecting kernels. The proposed method is in turn also suitable for image
segmentation.


  In this paper, we consider the problem of testing the mean vector in the high
dimensional settings. We proposed a new robust scalar transform invariant test
based on spatial sign. The proposed test statistic is asymptotically normal
under elliptical distributions. Simulation studies show that our test is very
robust and efficient in a wide range of distributions.


  The paper studies the supersingular locus of the characteristic p moduli
space of principally polarized abelian 8-folds that are equipped with an action
of a maximal order in a quaternion algebra, that is non-split at the infinite
place, but split at p. The main result is that its irreducible components are
Fermat surfaces of degree p+1.


  The purpose of this article is to give a complete study of the weak solutions
of the fractional elliptic equation \begin{equation}\label{00}
  \arraycolsep=1pt \begin{array}{lll}
  (-\Delta)^{\alpha} u+u^p=0\ \ \ \ &\ {\rm in}\ \
B_1(e_N),\\[2mm]\phantom{(-\Delta)^{\alpha} +u^p}
  u=\delta_{0}& \ {\rm in}\ \ \mathbb{R}^N\setminus B_1(e_N), \end{array}
\end{equation} where $p>0$, $ (-\Delta)^{\alpha}$ with $\alpha\in(0,1)$ denotes
the fractional Laplacian operator in the principle value sense, $B_1(e_N)$ is
the unit ball
  centered at $e_N=(0,\cdots,0,1)$ in $\mathbb{R}^N$ with $N\ge 2$ and
$\delta_0$ is the Dirac mass concentrated at the origin. We prove that problem
(\ref{00}) admits a unique weak solution when
  $p> 1+\frac{2\alpha}{N}$. Moreover, if in addition $p\ge \frac{N+2}{N-2}$,
the weak solution vanishes as $\alpha\to 1^-$. We also show that problem
(\ref{00}) doesn't have any weak solution when $p\in[0, 1+\frac{2\alpha}{N}]$.
These results are very surprising since there are in total contradiction with
the classical setting, i.e.
  $$ \arraycolsep=1pt \begin{array}{lll}
  -\Delta u+ u^p=0\ \ \ \ &\ {\rm in}\ \B_1(e_N),\\[2mm]
  \phantom{-\Delta +u^{p} } u=\delta_{0}& \ {\rm in}\ \ \R^N\setminus B_1(e_N),
\end{array} $$
  for which it has been proved that there are no solutions for $p\ge
\frac{N+1}{N-1}$.


  We study thermodynamics of an ideal gas in Doubly Special Relativity. New
type of special functions (which we call Incomplete Modified Bessel functions)
emerge. We obtain a series solution for the partition function and derive
thermodynamic quantities. We observe that DSR thermodynamics is
non-perturbative in the SR and massless limits. A stiffer equation of state is
found.


  In this work it is pointed out that some physical theories, even being
themselves falsifiable, predict the existence of regions of spacetime which are
not falsifiable with relation to each other due to their impossibility of
mutually exchanging information as, for instance, before and after the event
horizon of black holes. If we require scientific theories to be falsifiable, an
isolated region should be discarded from scientific models developed by
observers in other regions. Here it is proposed that their existence can
satisfy a weaker falsifiability condition, here called conditional asymptotic
provability, which extend scientific reasoning through Bayesian inference.
Limitations and some epistemic consequences of this proposal are discussed.


  There exists a multiplicative homomorphism from the braid group B to the
Temperley-Lieb algebra TL. Moreover, the homomorphic images in TL of the simple
elements form a basis for the vector space underlying TL. In analogy with the
case of B, there exists a multiplicative homomorphism from the structure group
G of a non-degenerate, involutive set-theoretic solution to an algebra, which
extends to a homomorphism of algebras. We construct a finite basis of the
underlying vector space of the image of G using the Garsideness properties of
the solution.


  We discuss the non-equilibrium fluctuation problem, which corresponds to the
hydrodynamic limit established in \cite{FS}, for the dynamics of
two-dimensional Young diagrams associated with the uniform and restricted
uniform statistics, and derive linear stochastic partial differential equations
in the limit. We show that their invariant measures are identical to the
Gaussian measures which appear in the fluctuation limits in the static
situations.


  Primary ferroicities like ferroelectricity and ferromagnetism are essential
physical properties of matter. Multiferroics, with coexisting multiple ferroic
orders in a single phase, provide a convenient route to magnetoelectricity.
Even so, the general trade-off between magnetism and polarity remains
inevitable, which prevents practicable magnetoelectric cross control in the
multiferroic framework. Here an alternative strategy, i.e. the so-called
alterferroicity, is proposed to circumvent the magnetoelectric exclusiveness,
which exhibits multiple but non-coexisting ferroic orders. The natural
exclusion between magnetism and polarity, as an insurmountable weakness of
multiferroicity, becomes a distinct advantage in alterferroicity, making it an
inborn rich ore for intrinsic strong magnetoelectricity. The general design
rules for alterferroic materials rely on the competition between the
instabilities of phononic and electronic structures in covalent systems. Based
on primary density functional theory calculations, Ti-based trichalcogenides
are predicted to be alterferroic candidates, which exhibit unique seesaw type
magnetoelectricity. This alterferroicity, as an emerging branch of ferroic
family, re-shapes the framework of magnetoelectricity, going beyond the
established scenario based on multiferroicity.


  The two dimensional conducting interfaces in SrTiO$_3$-based systems are
known to show a variety of coexisting and competing phenomena in a complex
phase space. Magnetoresistance measurements, which are typically used to
extract information about the various interactions in these systems, must be
interpreted with care, since multiple interactions can contribute to the
resistivity in a given range of magnetic field and temperature. Here we review
all the phenomena that can contribute to transport in SrTiO$_3$-based
conducting interfaces at low temperatures, and discuss possible ways to
distinguish between various phenomena. We apply this analysis to the
magnetoresistance data of (111) oriented
(La$_{0.3}$Sr$_{0.7}$)(Al$_{0.65}$Ta$_{0.35}$)/STO (LSAT/STO) heterostructures
in perpendicular field, and find an excess negative magnetoresistance
contribution which cannot be explained by weak localization alone. We argue
that contributions from magnetic scattering as well as electron-electron
interactions can provide a possible explanation for the observed
magnetoresistance.


  We apply previous results on the O(N) Bethe Ansatz [1 to 3] to construct a
general form factor formula for the O(N) Gross-Neveu model. We examine this
formula for several operators, such as the energy momentum, the spin-field and
the current. We also compare these results with the 1/N expansion of this model
and obtain full agreement. We discuss bound state form factors, in particular
for the three particle form factor of the field. In addition for the two
particle case we prove a recursion relation for the K-functions of the higher
level Bethe Ansatz.


  We state an open problem in the theory of diversities: what is the worst case
minimal distortion embedding of a diversity on $n$ points in $\ell_1$. This
problem is the diversity analogue of a famous problem in metric geometry: what
is the worst case minimal distortion embedding of an $n$-point metric space in
$\ell_1$. We explain the problem, state some special classes of diversities for
which the answer is known, and show why the standard techniques from the metric
space case do not work. We then outline some possible lines of attack for the
problem that are not yet fully explored.


  We present the catalogue of the REFLEX Cluster Survey providing information
on the X-ray properties, redshifts, and some identification details of the
clusters in the REFLEX sample. The catalogue describes a statistically complete
X-ray flux-limited sample of 447 galaxy clusters above an X-ray flux of 3
10(-12) erg /s/cm**2 (0.1 to 2.4 keV) in an area of 4.24 ster in the southern
sky. The cluster candidates were first selected by their X-ray emission in the
ROSAT-All Sky Survey and subsequently spectroscopically identified in the frame
of an ESO key programme. In addition to the cluster catalogue we also describe
the complete selection criteria as a function of the sky position and the
conversion functions used to analyse the X-ray data. These are essential for
the precise statistical analysis of the large-scale cluster distribution. This
data set is at present the largest, statistically complete X-ray galaxy cluster
sample. Together with these data set we also provide for the first time the
full three-dimensional selection function. The sample forms the basis of
several cosmological studies, one of the most important applications being the
assessment of the statistics of the large-scale structure of the universe and
the test of cosmological models.


  If we approximate light quarks as massless and apply the Schwinger
confinement mechanism to light quarks, we will reach the conclusion that a
light quark $q$ and its antiquark $\bar q$ will be confined as a $q\bar q$
boson in the Abelian U(1) QED gauge interaction in (1+1)D, as in an open
string. From the work of Coleman, Jackiw, and Susskind, we can infer further
that the Schwinger confinement mechanism persists even for massive quarks in
(1+1)D. Could such a QED-confined $q\bar q$ one-dimensional open string in
(1+1)D be the idealization of a flux tube in the physical world in (3+1)D,
similar to the case of QCD-confined $q\bar q$ open string? If so, the
QED-confined $q\bar q$ bosons may show up as neutral QED mesons in the mass
region of many tens of MeV (PRC81(2010)064903 & JHEP2020(8)165). Is it ever
possible that a quark and an antiquark be produced and interact in QED alone to
form a confined QED meson? Is there any experimental evidence for the existence
of a QED meson (or QED mesons)? The observations of the anomalous soft photons,
the X17 particle, and the E38 particle suggest that they may bear the
experimental evidence for the existence of such QED mesons. Further
confirmation and investigations on the X17 and E38 particles will shed
definitive light on the question of quark confinement in QED in (3+1)D.
Implications of quark confinement in the QED interaction are discussed.


  Using minimal hypersurfaces, we obtain topological obstructions to admitting
complete metrics with positive scalar curvature on a given class of non-compact
n-manifolds with n less than 8. We show that the Liouville theorem for a
locally conformally flat n-manifold of non-negative scalar curvature follows
from the impossibility of there being a positive scalar curvature metric on its
connect sum with the n-torus. With the recent work of Chodosh-Li, the Liouville
theorem is now proved in all remaining cases. Finally, using MOTS instead of
minimal hypersurfaces, we show an Initial Data Set version of these results
with the Dominant Energy Scalar appearing instead of positive scalar curvature.


  We present a conjecture on the exact location of the multicritical point in
the phase diagram of spin glass models in finite dimensions. By generalizing
our previous work, we combine duality and gauge symmetry for replicated random
systems to derive formulas which make it possible to understand all the
relevant available numerical results in a unified way. The method applies to
non-self-dual lattices as well as to self dual cases, in the former case of
which we derive a relation for a pair of values of multicritical points for
mutually dual lattices. The examples include the +-J and Gaussian Ising spin
glasses on the square, hexagonal and triangular lattices, the Potts and Z_q
models with chiral randomness on these lattices, and the three-dimensional +-J
Ising spin glass and the random plaquette gauge model.


  We propose a class of weighted $L_2$-type tests of fit to the Gamma
distribution. Our novel procedure is based on a fixed point property of a new
transformation connected to a Steinian characterization of the family of Gamma
distributions. We derive the weak limits of the statistic under the null
hypothesis and under contiguous alternatives. Further, we establish the global
consistency of the tests and apply a parametric bootstrap technique in a Monte
Carlo simulation study to show the competitiveness to existing procedures.


  We present an electrostatically defined few-electron double quantum dot (QD)
realized in a molecular beam epitaxy grown Si/SiGe heterostructure. Transport
and charge spectroscopy with an additional QD as well as pulsed-gate
measurements are demonstrated. We discuss technological challenges specific for
silicon-based heterostructures and the effect of a comparably large effective
electron mass on transport properties and tunability of the double QD. Charge
noise, which might be intrinsically induced due to strain-engineering is proven
not to affect the stable operation of our device as a spin qubit. Our results
promise the suitability of electrostatically defined QDs in Si/SiGe
heterostructures for quantum information processing.


  In this paper, we present a method for identifying discourse marker usage in
spontaneous speech based on machine learning. Discourse markers are denoted by
special POS tags, and thus the process of POS tagging can be used to identify
discourse markers. By incorporating POS tagging into language modeling,
discourse markers can be identified during speech recognition, in which the
timeliness of the information can be used to help predict the following words.
We contrast this approach with an alternative machine learning approach
proposed by Litman (1996). This paper also argues that discourse markers can be
used to help the hearer predict the role that the upcoming utterance plays in
the dialog. Thus discourse markers should provide valuable evidence for
automatic dialog act prediction.


  I review the theoretical expectactions for the top-quark mass in a variety of
models: the Standard Model, unified models (GUTs), low-energy supersymmetric
models (SUSY), unified supersymmetric models (SUSY GUTs), supergravity models,
and superstring models. In all instances I consider the constraints on the
top-quark mass which arise by demanding that these theories be weakly
interacting. This assumption is quantified by the use of partial-wave unitarity
or triviality. The resulting upper bounds on the top-quark mass are most
stringent in SUSY GUTs models ($m^{\rm pole}_t\lsim200\sin\beta\GeV$). I also
discuss a class of $SU(5)\times U(1)$ superstring models where $m^{\rm
pole}_t\sim(170-195)\GeV$ is predicted. I conclude that experimental
determinations of the top-quark mass can be {\em naturally} understood in SUSY
GUTs and superstring models. (Lecture presented at the International School of
Subnuclear Physics, 32nd Course: From Superstring to Present-Day Physics,
Erice--Sicily: July 3--11, 1994.)


  We have determined extinction corrections for a sample of 441 late-type stars
in the inner Galaxy, which we previously searched for SiO maser emission, using
the 2MASS near-infrared photometry of the surrounding stars. From this, the
near-infrared extinction law is found to be approximated by a power law
A$_\lambda \propto \lambda^{-1.9\pm0.1}$. Near- and mid-infrared colour-colour
properties of known Mira stars are reviewed. From the distribution of the
dereddened infrared colours of the SiO target stars we infer mass-loss rates
between $10^{-7}$ and $10^{-5}$ M$_\odot$ yr$^{-1}$.


  The observed rotation curves of dark matter-dominated dwarf galaxies indicate
low density cores, contrary to the predictions of CDM models. A possible
solution of this problem involves stellar feedback. A strong baryonic wind
driven by vigorous star formation can remove a large fraction of the gas,
causing the dark matter to expand. We explore the maximum effect of the
feedback with an instantaneous removal of the gaseous disk. The energy input
depends on the compactness of the disk, hence the specific angular momentum of
the disk. For the plausible cosmological parameters and a large range of the
disk angular momentum, the feedback is insufficient to destroy the central halo
cusp, while the inner density is lowered only by a modest factor of 2 to 6. Any
realistic modeling of the feedback would have even lesser impact on dark
matter. We find that no star formation effect can resolve the problems of CDM
cusps.


  Different GPU applications exhibit varying scalability patterns with
network-on-chip (NoC), coalescing, memory and control divergence, and L1 cache
behavior. A GPU consists of several StreamingMulti-processors (SMs) that
collectively determine how shared resources are partitioned and accessed.
Recent years have seen divergent paths in SM scaling towards scale-up (fewer,
larger SMs) vs. scale-out (more, smaller SMs). However, neither scaling up nor
scaling out can meet the scalability requirement of all applications running on
a given GPU system, which inevitably results in performance degradation and
resource under-utilization for some applications. In this work, we investigate
major design parameters that influence GPU scaling. We then propose AMOEBA, a
solution to GPU scaling through reconfigurable SM cores. AMOEBA monitors and
predicts application scalability at run-time and adjusts the SM configuration
to meet program requirements. AMOEBA also enables dynamic creation of
heterogeneous SMs through independent fusing or splitting. AMOEBA is a
microarchitecture-based solution and requires no additional programming effort
or custom compiler support. Our experimental evaluations with application
programs from various benchmark suites indicate that AMOEBA is able to achieve
a maximum performance gain of 4.3x, and generates an average performance
improvement of 47% when considering all benchmarks tested.


  The unconditionally squeezing of the collective spin of an atomic ensemble in
a laser driven optical cavity (I. D. Leroux, M. H. Schleier-Smith, and V.
Vuletic, Phys. Rev. Lett 104, 073602 (2010)) is studied and analyzed
theoretically. Surprisingly, we find that the largely detuned driving laser can
improve the scaling of cavity squeezing from $S^{-2/5}$ to $S^{-2/3}$, where S
is the total atomic spin. Moreover, we also demonstrate that the experimental
imperfection of photon scattering into free space can be efficiently suppressed
by detuning.


  Diffusion models have emerged as preeminent contenders in the realm of
generative models. Distinguished by their distinctive sequential generative
processes, characterized by hundreds or even thousands of timesteps, diffusion
models progressively reconstruct images from pure Gaussian noise, with each
timestep necessitating full inference of the entire model. However, the
substantial computational demands inherent to these models present challenges
for deployment, quantization is thus widely used to lower the bit-width for
reducing the storage and computing overheads. Current quantization
methodologies primarily focus on model-side optimization, disregarding the
temporal dimension, such as the length of the timestep sequence, thereby
allowing redundant timesteps to continue consuming computational resources,
leaving substantial scope for accelerating the generative process. In this
paper, we introduce TMPQ-DM, which jointly optimizes timestep reduction and
quantization to achieve a superior performance-efficiency trade-off, addressing
both temporal and model optimization aspects. For timestep reduction, we devise
a non-uniform grouping scheme tailored to the non-uniform nature of the
denoising process, thereby mitigating the explosive combinations of timesteps.
In terms of quantization, we adopt a fine-grained layer-wise approach to
allocate varying bit-widths to different layers based on their respective
contributions to the final generative performance, thus rectifying performance
degradation observed in prior studies. To expedite the evaluation of
fine-grained quantization, we further devise a super-network to serve as a
precision solver by leveraging shared quantization results. These two design
components are seamlessly integrated within our framework, enabling rapid joint
exploration of the exponentially large decision space via a gradient-free
evolutionary search algorithm.


  The design of the nanostructures that are used in the field of nano-photonics
has remained complex, very often relying on the intuition and expertise of the
designer, ultimately limiting the reach and penetration of this groundbreaking
approach. Recently, there has been an increasing number of studies suggesting
to apply Machine Learning techniques for the design of nanostructures. Most of
these studies engage Deep Learning techniques, which entails training a Deep
Neural Network (DNN) to approximate the highly non-linear function of the
underlying physical process between spectra and nanostructures. At the end of
the training, the DNN allows an on-demand design of nanostructures, i.e. the
model can infer nanostructure geometries for desired spectra. In this work, we
introduce spectra2pix, which is a model DNN trained to generate 2D images of
the designed nanostructures. Our model architecture is not limited to a closed
set of nanostructure shapes, and can be trained for the design of any geometry.
We show, for the first time, a successful generalization ability by designing a
completely unseen sub-family of geometries. This generalization capability
highlights the importance of our model architecture, and allows higher
applicability for real-world design problems.


  Given any finite simplicial complex \Delta, we show how to construct a new
simplicial complex \Delta_{\chi} that is balanced and vertex decomposable.
Moreover, we show that the h-vector of the simplicial complex \Delta_{\chi} is
precisely the f-vector, denoted f(\Delta), of the original complex \Delta. We
deduce this result by relating f(\Delta) with the graded Betti numbers of the
Alexander dual of \Delta_{\chi}. Our construction generalizes the "whiskering"
construction of Villarreal, and Cook and Nagel. As a corollary of our work, we
add a new equivalent statement to a theorem of Bj\"orner, Frankl, and Stanley
that classifies the f-vectors of simplicial complexes. We also prove a special
case of a conjecture of Cook and Nagel, and Constantinescu and Varbaro on the
h-vectors of flag complexes.


  The gravitational wave observations of colliding black holes have opened a
new window into the unexplored extreme gravity sector of physics, where the
gravitational fields are immensely strong, non-linear, and dynamical. 10 binary
black hole merger events observed so far can be used to test Einstein's theory
of general relativity, which has otherwise been proven to agree with
observations from several sources in the weak- or static-field regimes. One
interesting future possibility is to detect gravitational waves from
GW150914-like stellar-mass black hole binaries with both ground-based and
space-based detectors. We here demonstrate the power of testing extreme gravity
with such multi-band gravitational-wave observations. In particular, we
consider two theory-agnostic methods to test gravity using gravitational waves.
The first test is the parameterized test where we introduce generic
non-Einsteinian corrections to the waveform, which can easily be mapped to
parameters in known example theories beyond general relativity. The second test
is the inspiral-merger-ringdown consistency test where one derives the mass and
spin of a merger remnant from the inspiral and merger-ringdown independently
assuming general relativity is correct, and then check their consistency. In
both cases, we use Fisher analyses and compare the results with Bayesian ones
wherever possible. Regarding the first test, we find that multi-band
observations can be crucial in probing certain modified theories of gravity,
including those with gravitational parity violation. Regarding the second test,
we show that future single-band detections can improve upon the current tests
by roughly three orders of magnitude, and further 7-10 times improvement may be
realized with multi-band observations.


  Hot subdwarfs (sdO/B) are the stripped helium cores of red giants formed by
binary interactions. Close hot subdwarf binaries with massive white dwarf
companions have been proposed as possible progenitors of thermonuclear
supernovae type Ia (SN Ia). If the supernova is triggered by stable mass
transfer from the helium star, the companion should survive the explosion and
should be accelerated to high velocities. The hypervelocity star US 708 is
regarded as the prototype for such an ejected companion. To find more of those
objects we conducted an extensive spectroscopic survey. Candidates for such
fast stars have been selected from the spectroscopic database of the Sloan
Digital Sky Survey (SDSS) and several ground-based proper motion surveys.
Follow-up spectroscopy has been obtained with several 4m- to 10m-class
telescopes. Combining the results from quantitative spectroscopic analyses with
space-based astrometry from \textit{Gaia} Early Data Release 3 (EDR3) we
determined the atmospheric and kinematic parameters of 53 fast hot subdwarf
stars. None of these stars is unbound to the Galaxy, although some have
Galactic restframe velocities close to the Galactic escape velocity. 21 stars
are apparently single objects, which crossed the Galactic disc within their
lifetimes in the sdO/B stage and could be regarded as potential candidates for
the SN Ia ejection scenario. However, the properties of the full sample are
more consistent with a pure old Galactic halo population. We therefore conclude
that the fast sdO/B stars we found are likely to be extreme halo stars.


  The statistics of primordial curvature fluctuations are our window into the
period of inflation, where these fluctuations were generated. To date, the
cosmic microwave background has been the dominant source of information about
these perturbations. Large scale structure is however from where drastic
improvements should originate. In this paper, we explain the theoretical
motivations for pursuing such measurements and the challenges that lie ahead.
In particular, we discuss and identify theoretical targets regarding the
measurement of primordial non-Gaussianity. We argue that when quantified in
terms of the local (equilateral) template amplitude $f_{\rm NL}^{\rm loc}$
($f_{\rm NL}^{\rm eq}$), natural target levels of sensitivity are $\Delta
f_{\rm NL}^{\rm loc, eq.} \simeq 1$. We highlight that such levels are within
reach of future surveys by measuring 2-, 3- and 4-point statistics of the
galaxy spatial distribution. This paper summarizes a workshop held at CITA
(University of Toronto) on October 23-24, 2014.


  We study the quench dynamics of an Anderson impurity model using the
configuration interaction (CI) method. In particular, we focus on the
relaxation behavior of the impurity occupation. The system is found to behave
very differently in the weak-coupling and strong-coupling regimes. In the
weak-coupling regime, the impurity occupation relaxes to a time-independent
constant quickly after only a few oscillations. In the strong-coupling regime,
the impurity occupation develops a fast oscillation, with a much slower
relaxation. We show that it is the multi-peak structure in the many-body energy
spectrum that separates these two regimes. The characteristic behavior,
including the power-law decay and the period of oscillation, can also be
related to certain features in the many-body energy spectrum. The respective
advantages of several impurity solvers are discussed, and the convergence of
different CI truncation schemes is provided.


  The random variable $1+z_1+z_1z_2+\dots$ appears in many contexts and was
shown by Kesten to exhibit a heavy tail distribution. We consider natural
extensions of this variable and its associated recursion to $N \times N$
matrices either real symmetric $\beta=1$ or complex Hermitian $\beta=2$. In the
continuum limit of this recursion, we show that the matrix distribution
converges to the inverse-Wishart ensemble of random matrices. The full dynamics
is solved using a mapping to $N$ fermions in a Morse potential, which are
non-interacting for $\beta=2$. At finite $N$ the distribution of eigenvalues
exhibits heavy tails, generalizing Kesten's results in the scalar case. The
density of fermions in this potential is studied for large $N$, and the
power-law tail of the eigenvalue distribution is related to the properties of
the so-called determinantal Bessel process which describes the hard edge
universality of random matrices. For the discrete matrix recursion, using free
probability in the large $N$ limit, we obtain a self-consistent equation for
the stationary distribution. The relation of our results to recent works of
Rider and Valk\'o, Grabsch and Texier, as well as Ossipov, is discussed.


  Billions of USD are invested in new artists and songs by the music industry
every year. This research provides a new strategy for assessing the hit
potential of songs, which can help record companies support their investment
decisions. A number of models were developed that use both audio data, and a
novel feature based on social media listening behaviour. The results show that
models based on early adopter behaviour perform well when predicting top 20
dance hits.


  It has been argued that requiring low electroweak fine-tuning (EWFT) along
with a (partial) decoupling solution to the SUSY flavor and CP problems leads
to a sparticle mass spectra characterized by light Higgsinos at 100-300 GeV,
sub-TeV third generation scalars, gluinos at a few TeV and multi-TeV
first/second generation scalars (natural SUSY). We show that by starting with
multi-TeV first/second and third generation scalars and trilinear soft breaking
terms, the natural SUSY spectrum can be generated radiatively via
renormalization group running effects. Using the complete 1-loop effective
potential to calculate EWFT, significantly heavier third generation squarks can
be allowed even with low EWFT. The large negative trilinear term and heavier
top squarks allow for a light Higgs scalar in the ~125 GeV regime.


  We consider the Cauchy problem for an equation of Korteweg-de Vries-Kawahara
type with initial data in the analytic Gevrey spaces. By using linear, bilinear
and trilinear estimates in analytic Bourgain spaces, we establish the local
well-posedness for this problem. By using an approximate conservation law, we
extend this to a global result in such a way that the radius of analyticity of
solutions is uniformly bounded below by a fixed positive number for all time.


  After a summary of Bohr's views and their relation to Kant's theory of
science, two fruitless lines of attack on the measurement problem are
discussed: the way of the psi-ontologist and the way of the QBist. In the
remainder of the paper the following results are obtained. (i) Because the
testable correlations between outcomes of measurements of macroscopic positions
are consistent with both the classical and the quantum laws, there is no
conflict between the superposition principle and the existence of measurement
outcomes. (ii) Intrinsically, each fundamental particle is numerically
identical with every other fundamental particle. What presents itself here and
now with these properties and what presents itself there and then with those
properties is one and the same entity, herein called "Being." (iii) The
distinction between a classical domain and a quantum domain is essentially a
distinction between the manifested world and its manifestation. By entering
into reflexive spatial relations, Being gives rise to (a) what looks like a
multiplicity of relata if the reflexive quality of the relations is ignored,
and (b) what looks like a substantial expanse if the spatial quality of the
relations is reified. (iv) The reason why quantum mechanics is a calculus of
correlations between measurement outcomes is that it concerns the progressive
realization of distinguishable objects and distinguishable regions of space.
(v) The key to the relation between quantum mechanics and experience is that
Being does not simply manifest the world, Being manifests the world to itself.
It is at once the single substance by which the world exists and the ultimate
self or subject for which it exists. The question how we are related to this
ultimate self or subject is discussed.


  A unique constraint is defined within the framework of scalar-tensor
theories, whereby the conformal factor is fixed to the fluctuation associated
to the effective mass of the Hamilton-Jacobi equation for a Klein-Gordon field.
The effective mass is extended to its exponential form to remove any ghost
(energy) states. The constraint's Lagrange multiplier $\lambda$, referred to as
the mediating field, is shown to act as a mediator between the scalar and
tensor degrees of freedom. In its linear form, Heisenberg's uncertainty
principle appears as a natural artifact of the mediating field. In its
exponential form, the mediating field is shown to be bound, nonsingular, and of
increasing significance for smaller masses. Furthermore, in acquiring the
stress-energy tensors, the cosmological constant $\Lambda$ is formulated for a
stationary solution of the particle density and mediating field. As a result,
the mysterious variation in $\Lambda$ is properly evaluated from its
cosmological value to that of an electron, from which a 77 order difference is
obtained. In our final remarks, the mediating field $\lambda$ is suggested to
be characteristic of the vacuum's energy density.


  Deep Neural Networks (DNNs) are rapidly being applied to safety-critical
domains such as drone and airplane control, motivating techniques for verifying
the safety of their behavior. Unfortunately, DNN verification is NP-hard, with
current algorithms slowing exponentially with the number of nodes in the DNN.
This paper introduces the notion of Abstract Neural Networks (ANNs), which can
be used to soundly overapproximate DNNs while using fewer nodes. An ANN is like
a DNN except weight matrices are replaced by values in a given abstract domain.
We present a framework parameterized by the abstract domain and activation
functions used in the DNN that can be used to construct a corresponding ANN. We
present necessary and sufficient conditions on the DNN activation functions for
the constructed ANN to soundly over-approximate the given DNN. Prior work on
DNN abstraction was restricted to the interval domain and ReLU activation
function. Our framework can be instantiated with other abstract domains such as
octagons and polyhedra, as well as other activation functions such as Leaky
ReLU, Sigmoid, and Hyperbolic Tangent.


  We present a detailed analysis of a highly ionized, multiphased and
collimated outflowing gas detected through O V, O VI, Ne VIII and Mg X
absorption associated with the QSO HE 0238 - 1904 (z_em ~ 0.629). Based on the
similarities in the absorption line profiles and estimated covering fractions,
we find that the O VI and Ne VIII absorption trace the same phase of the
absorbing gas. Simple photoionization models can reproduce the observed N(Ne
VIII), N(O VI) and N(Mg X) from a single phase whereas the low ionization
species (e.g. N III, N IV, O IV) originate from a different phase. The measured
N(Ne VIII)/N(O VI) ratio is found to be remarkably similar (within a factor of
~ 2) in several individual absorption components kinematically spread over ~
1800 km/s. Under photoionization this requires a fine tuning between hydrogen
density (nH) and the distance of the absorbing gas from the QSO. Alternatively
this can also be explained by collisional ionization in hot gas with T >
10^{5.7} K. Long-term stability favors the absorbing gas being located outside
the broad line region (BLR). We speculate that the collimated flow of such a
hot gas could possibly be triggered by the radio jet interaction.


  We determine the finite-volume corrections to the spectrum and matrix
elements of two-hadron states in a moving frame, i.e. one in which the total
momentum of the two-hadrons is non-zero. The analysis is performed entirely
within field theory and the results are accurate up to exponential corrections
in the volume. Our results for the spectrum are equivalent to those of
Rummukainen and Gottlieb which had been obtained using a relativistic quantum
mechanical approach. A technical step in our analysis is a simple derivation of
the summation formulae relating the loop summations over the momenta of the two
hadrons in finite volume to the corresponding integrals in infinite volume.


  We demonstrate that single-photon as well as biphoton revivals are possible
in a new class of dynamic optical systems-the so-called Glauber-Fock oscillator
lattices. In these arrays, both Bloch-like oscillations and dynamic
delocalization can occur which can be described in closed form. The bunching
and anti-bunching response of path-entangled photons can be pre-engineered in
such coupled optical arrangements and the possibility of emulating Fermionic
behavior in this family of lattices is also considered. We elucidate these
effects via pertinent examples and we discuss the prospect of experimentally
observing these quantum interactions.


  The antiferromagnetic quantum Ising chain has a quantum critical point which
belongs to the universality class of the transverse Ising model (TIM). When a
longitudinal field ($h$) is switched on, the phase transition is preserved,
which turns to first-order for $h/\Gamma \to \infty$, $\Gamma$ being the
strength of the transverse field. Here we will re-examine the critical
properties along the phase transition line. During a quantum block
renormalization group calculation, the TIM fixed point for $h/\Gamma>0$ is
found to be unstable. Using DMRG techniques, we calculated the entanglement
entropy and the spin-spin correlation function, both of which signaled a
divergent correlation length at the transition point with the TIM exponents. At
the same time, the bulk correlation function has a jump and the end-to-end
correlation function has a discontinuous derivative at the transition point.
Consequently for finite $h/\Gamma$ the transition is of mixed-order.


  Point cloud completion has become increasingly popular among generation tasks
of 3D point clouds, as it is a challenging yet indispensable problem to recover
the complete shape of a 3D object from its partial observation. In this paper,
we propose a novel SeedFormer to improve the ability of detail preservation and
recovery in point cloud completion. Unlike previous methods based on a global
feature vector, we introduce a new shape representation, namely Patch Seeds,
which not only captures general structures from partial inputs but also
preserves regional information of local patterns. Then, by integrating seed
features into the generation process, we can recover faithful details for
complete point clouds in a coarse-to-fine manner. Moreover, we devise an
Upsample Transformer by extending the transformer structure into basic
operations of point generators, which effectively incorporates spatial and
semantic relationships between neighboring points. Qualitative and quantitative
evaluations demonstrate that our method outperforms state-of-the-art completion
networks on several benchmark datasets. Our code is available at
https://github.com/hrzhou2/seedformer.


  We describe a composite Higgs scenario in which a cosmological relaxation
mechanism naturally gives rise to a hierarchy between the weak scale and the
scale of spontaneous global symmetry breaking. This is achieved through the
scanning of sources of explicit global symmetry breaking by a relaxion field
during an exponentially long period of inflation in the early universe. We
explore this mechanism in detail in a specific composite Higgs scenario with
QCD-like dynamics, based on an ultraviolet $SU(N)_{\textrm{TC}}$ 'technicolor'
confining gauge theory with three Dirac technifermion flavors. We find that we
can successfully generate a hierarchy of scales $\xi \equiv \langle h \rangle^2
/ F_\pi^2 \gtrsim 1.2 \times 10^{-4}$ (i.e., compositeness scales $F_\pi \sim
20$ TeV) without tuning. This evades all current electroweak precision bounds
on our (custodial violating) model. While directly observing the heavy
composite states in this model will be challenging, a future electroweak
precision measurement program can probe most of the natural parameter space for
the model. We also highlight signatures of more general composite Higgs models
in the cosmological relaxation framework, including some implications for
flavor and dark matter.


  The thermodynamic properties of strong short-range attractive Yukawa fluids,
k=10, 9, 8, and 7, are determined by combining the slab technique with the
standard and the replica exchange Monte Carlo (REMC) methods. A good agreement
was found among the coexistence curves of these systems calculated by REMC and
those previously reported in the literature. However, REMC allows exploring the
coexistence at lower temperatures, where dynamics turns glassy. To obtain the
surface tension we employed, for both methods, a procedure that yields the
pressure tensor components for discontinuous potentials. The surface tension
results obtained by the standard MC and REMC techniques are in good agreement.


  This work presents an interpretation of high precision jet data from the
ATLAS experiment in terms of exclusion limits for new coloured matter. To this
end, the effect of a new coloured fermion with a mass $m_X$ on the solution of
the renormalization group equation QCD is studied. Theoretical predictions for
the transverse energy-energy correlation function and its asymmetry are
obtained with such a modified solution and, from the comparison to data, 95\%
CL exclusion limits are set on such models.


  Higher harmonics in current phase relations of Josephson Junctions (JJs) are
predicted to be observed when the first harmonic is suppressed. Conventional
theoretical models predict higher harmonics to be extremely sensitive to
changes in barrier thickness, temperature, etc. In contrast, experiments with
JJs incorporating a spin dependent tunnelling barrier reported here reveal a
current phase relation for highly spin polarized barriers which is purely 2nd
harmonic in nature, and this is insensitive to changes in barrier thickness.
This observation is consistent with recent theoretical predictions of a robust
2nd harmonic current phase relation for certain JJs with ferromagnetic barriers
and implies that the standard theory of Cooper pair transport through
tunnelling barriers is not applicable for spin dependent tunnelling barriers.


  Major complications arise from the recent increase in the amount of
high-dimensional data, including high computational costs and memory
requirements. Feature selection, which identifies the most relevant and
informative attributes of a dataset, has been introduced as a solution to this
problem. Most of the existing feature selection methods are computationally
inefficient; inefficient algorithms lead to high energy consumption, which is
not desirable for devices with limited computational and energy resources. In
this paper, a novel and flexible method for unsupervised feature selection is
proposed. This method, named QuickSelection, introduces the strength of the
neuron in sparse neural networks as a criterion to measure the feature
importance. This criterion, blended with sparsely connected denoising
autoencoders trained with the sparse evolutionary training procedure, derives
the importance of all input features simultaneously. We implement
QuickSelection in a purely sparse manner as opposed to the typical approach of
using a binary mask over connections to simulate sparsity. It results in a
considerable speed increase and memory reduction. When tested on several
benchmark datasets, including five low-dimensional and three high-dimensional
datasets, the proposed method is able to achieve the best trade-off of
classification and clustering accuracy, running time, and maximum memory usage,
among widely used approaches for feature selection. Besides, our proposed
method requires the least amount of energy among the state-of-the-art
autoencoder-based feature selection methods.


  This paper investigates the decay properties of solutions to the massive
linear wave equation $\Box_g \psi + \frac{{\alpha}}{l^2} \psi =0$ for $g$ the
metric of a Kerr-AdS spacetime satisfying $|a|l<r_+^2$ and $\alpha<9/4$
satisfying the Breitenlohner Freedman bound. We prove that the non-degenerate
energy of $\psi$ with respect to an appropriate foliation of spacelike slices
decays like $(\log t^\star)^{-2}$. Our estimates are expected to be sharp from
heuristic and numerical arguments in the physics literature suggesting that
general solutions will only decay logarithmically. The underlying reason for
the slow decay rate can be traced back to a stable trapping phenomenon for
asymptotically anti de Sitter black holes which is in turn a consequence of the
reflecting boundary conditions for $\psi$ at null-infinity.


  Deep neural networks are known to be susceptible to adversarial perturbations
-- small perturbations that alter the output of the network and exist under
strict norm limitations. While such perturbations are usually discussed as
tailored to a specific input, a universal perturbation can be constructed to
alter the model's output on a set of inputs. Universal perturbations present a
more realistic case of adversarial attacks, as awareness of the model's exact
input is not required. In addition, the universal attack setting raises the
subject of generalization to unseen data, where given a set of inputs, the
universal perturbations aim to alter the model's output on out-of-sample data.
In this work, we study physical passive patch adversarial attacks on visual
odometry-based autonomous navigation systems. A visual odometry system aims to
infer the relative camera motion between two corresponding viewpoints, and is
frequently used by vision-based autonomous navigation systems to estimate their
state. For such navigation systems, a patch adversarial perturbation poses a
severe security issue, as it can be used to mislead a system onto some
collision course. To the best of our knowledge, we show for the first time that
the error margin of a visual odometry model can be significantly increased by
deploying patch adversarial attacks in the scene. We provide evaluation on
synthetic closed-loop drone navigation data and demonstrate that a comparable
vulnerability exists in real data. A reference implementation of the proposed
method and the reported experiments is provided at
https://github.com/patchadversarialattacks/patchadversarialattacks.


  In this study, we numerically investigate the internal structure of localized
quantum turbulence in superfluid $^4$He at zero temperature with the
expectation of self-similarity in the real space. In our previous study, we
collected the statistics of vortex rings emitted from a localized vortex
tangle. As a result, the power law between the minimum size of detectable
vortex rings and the emission frequency is obtained, which suggests that the
vortex tangle has self-similarity in the real space [Nakagawa $et$ $al.$, Phys.
Rev. B $\boldsymbol{101}$, 184515 (2020)]. In this work, we study the fractal
dimension and vortex length distribution of localized vortex tangles, which can
show their self-similar structure. We generate statistically steady and
localized vortex tangles by injecting vortex rings with a fixed size. We used
two types of injection methods that produce anisotropic or isotropic tangles.
The injected vortex rings develop into a localized vortex tangle consisting of
vortex rings of various sizes through reconnections (fusions and splitting of
vortices). The fractal dimension is an increasing function of the vortex line
density and becomes saturated to a value of approximately 1.8, as the density
increases sufficiently. The behavior of the fractal dimension was independent
of the anisotropy of the vortex tangles. The vortex length distribution
indicates the number of vortex rings of each size that are distributed in a
tangle. The distribution of the anisotropic vortex tangle shows the power law
in the range above the injected vortex size, although the distribution of the
isotropic vortex does not.


  The efficiency of business processes relies on business key performance
indicators (Biz-KPIs), that can be negatively impacted by IT failures. Business
and IT Observability (BizITObs) data fuses both Biz-KPIs and IT event channels
together as multivariate time series data. Forecasting Biz-KPIs in advance can
enhance efficiency and revenue through proactive corrective measures. However,
BizITObs data generally exhibit both useful and noisy inter-channel
interactions between Biz-KPIs and IT events that need to be effectively
decoupled. This leads to suboptimal forecasting performance when existing
multivariate forecasting models are employed. To address this, we introduce
AutoMixer, a time-series Foundation Model (FM) approach, grounded on the novel
technique of channel-compressed pretrain and finetune workflows. AutoMixer
leverages an AutoEncoder for channel-compressed pretraining and integrates it
with the advanced TSMixer model for multivariate time series forecasting. This
fusion greatly enhances the potency of TSMixer for accurate forecasts and also
generalizes well across several downstream tasks. Through detailed experiments
and dashboard analytics, we show AutoMixer's capability to consistently improve
the Biz-KPI's forecasting accuracy (by 11-15\%) which directly translates to
actionable business insights.


  Consequences of a strong version of the AdS/CFT correspondence for extremely
stringy physics are examined. In particular, properties of N = 4 supersymmetric
Yang-Mills theory are used to extract results about interacting tensionless
strings and massless higher spin fields in an AdS_5 x S^5 background.
Furthermore, the thermodynamics of this model signals the presence of a
Hawking-Page phase transition between AdS_5 space and a "black hole"-like high
temperature configuration even in the extreme string limit.


  We develop approximation methods in the hybrid quantization of the Gowdy
model with linear polarization and a massless scalar field, for the case of
three-torus spatial topology. The loop quantization of the homogeneous
gravitational sector of the Gowdy model (according to the improved dynamics
prescription) and the presence of inhomogeneities lead to a very complicated
Hamiltonian constraint. Therefore, the extraction of physical results calls for
the introduction of well justified approximations. We first show how to
approximate the homogeneous part of the Hamiltonian constraint, corresponding
to Bianchi I geometries, as if it described a Friedmann-Robertson-Walker (FRW)
model corrected with anisotropies. This approximation is valid in the
high-energy sector of the FRW geometry (concerning its contribution to the
constraint) and for anisotropy profiles that are sufficiently smooth. In
addition, for certain families of states associated to regimes of physical
interest, with negligible effects of the anisotropies and small
inhomogeneities, one can approximate the Hamiltonian constraint of the
inhomogeneous system by that of an FRW geometry with a relatively simple matter
content, and then obtain its solutions.


  We have determined the proper motion (PM) of the Large Magellanic Cloud (LMC)
relative to four background quasi-stellar objects, combining data from two
previous studies made by our group, and new observations carried out in four
epochs not included the original investigations. The new observations provided
a significant increase in the time base and in the number of frames, relative
to what was available in our previous studies. We have derived a total LMC PM
of $\mu$ = ($+2.0\pm$0.1) mas yr$^{-1}$, with a position angle of $\theta$ =
(62.4$\pm$3.1)$^\circ$. Our new values agree well with most results obtained by
other authors, and we believe we have clarified the large discrepancy between
previous results from our group. Using published values of the radial velocity
for the center of the LMC, in combination with the transverse velocity vector
derived from our measured PM, we have calculated the absolute space velocity of
the LMC. This value, along with some assumptions regarding the mass
distribution of the Galaxy, has in turn been used to calculate the mass of the
Milky Way. Our measured PM also indicates that the LMC is not a member of a
proposed stream of galaxies with similar orbits around our galaxy.


  Invariant representation learning (IRL) encourages the prediction from
invariant causal features to labels de-confounded from the environments,
advancing the technical roadmap of out-of-distribution (OOD) generalization.
Despite spotlights around, recent theoretical results verified that some causal
features recovered by IRLs merely pretend domain-invariantly in the training
environments but fail in unseen domains. The \emph{fake invariance} severely
endangers OOD generalization since the trustful objective can not be diagnosed
and existing causal surgeries are invalid to rectify. In this paper, we review
a IRL family (InvRat) under the Partially and Fully Informative Invariant
Feature Structural Causal Models (PIIF SCM /FIIF SCM) respectively, to certify
their weaknesses in representing fake invariant features, then, unify their
causal diagrams to propose ReStructured SCM (RS-SCM). RS-SCM can ideally
rebuild the spurious and the fake invariant features simultaneously. Given
this, we further develop an approach based on conditional mutual information
with respect to RS-SCM, then rigorously rectify the spurious and fake invariant
effects. It can be easily implemented by a small feature selection subnet
introduced in the IRL family, which is alternatively optimized to achieve our
goal. Experiments verified the superiority of our approach to fight against the
fake invariant issue across a variety of OOD generalization benchmarks.


  A method employing Bayesian statistics is used to incorporate recent
experimental results on BdBdbar and BsBsbar mixing into a measurement of the
Cabibbo-Kobayashi-Maskawa matrix elements. The neutral B meson mixing results
yield a slight improvement in the estimation of Vtd.


  We prove that a Dirichlet series with a functional equation and Euler product
of a particular form can only arise from a holomorphic cusp form on the Hecke
congruence group $\Gamma_0(13)$. The proof does not assume a functional
equation for the twists of the Dirichlet series. The main new ingredient is a
generalization of the familiar Weil's lemma that played a prominent role in
previous converse theorems.


  A monolayer of CrI3 has an amazing ferromagnetic ground-state. In this work,
we calculate band structures and magnetic moments of tensile-strained and bent
zigzag CrI3 nanoribbons with density functional theory. The edge iodine atoms
form flat low-lying conduction bands and couple with chromium atoms
ferromagnetically, while the non-edge iodine atoms weakly couple
antiferromagnetically. CrI3 nanoribbons have a nearly equal preference for the
out-of-plane and in-plane magnetic moment configurations, slightly favoring the
in-plane one. We also calculate optical absorption with many-body perturbation
GW-BSE (Bethe-Salpeter equation) and investigate magneto-optical properties,
including magnetic dichroism, Faraday and magneto-optical Kerr effects. The
low-energy dark excitons are mainly from transitions between electrons and
holes with unlike spins and are non-Frenkel-like, while the bright excitons
have mixed spin configurations. Tensile strains and bending manifestly modulate
the absorption spectra and magneto-optical properties of CrI3 nanoribbons
within a technologically important photon energy-range of ~1.0-2.0 eV,
suggesting a potential application in tunable magnetic optoelectronics.


  Let $k$ be a field, with absolute Galois group $\Gamma$. Let $A/k$ be a
finite \'etale group scheme of multiplicative type, i.e. a discrete
$\Gamma$-module. Let $n \geq 2$ be an integer, and let $x \in H^n(k,A)$ be a
cohomology class. We show that there exists a countable set $I$, and a familiy
$(X_i)_{i \in I}$ of (smooth, geometrically integral) $k$-varieties, such that
the following holds. For any field extension $l/k$, the restriction of $x$
vanishes in $H^n(l,A)$ if and only if (at least) one of the $X_i$'s has an
$l$-point. We moreover show that the $X_i$'s can be made into an ind-variety.
In the case $n=2$, we note that one variety is enough.