title: What is the $i\varepsilon$ for the S-matrix?

abstract:
  Can the S-matrix be complexified in a way consistent with causality? Since
the 1960's, the affirmative answer to this question has been well-understood
for $2 \to 2$ scattering of the lightest particle in theories with a mass gap
at low momentum transfer, where the S-matrix is analytic everywhere except at
normal-threshold branch cuts. We ask whether an analogous picture extends to
realistic theories, such as the Standard Model, that include massless fields,
UV/IR divergences, and unstable particles. Especially in the presence of light
states running in the loops, the traditional $i\varepsilon$ prescription for
approaching physical regions might break down, because causality requirements
for the individual Feynman diagrams can be mutually incompatible. We
demonstrate that such analyticity problems are not in contradiction with
unitarity. Instead, they should be thought of as finite-width effects that
disappear in the idealized $2\to 2$ scattering amplitudes with no unstable
particles, but might persist at higher multiplicity. To fix these issues, we
propose an $i\varepsilon$-like prescription for deforming branch cuts in the
space of Mandelstam invariants without modifying the analytic properties. This
procedure results in a complex strip around the real part of the kinematic
space, where the S-matrix remains causal. In addition to giving a pedagogical
introduction to the analytic properties of the perturbative S-matrix from a
modern point of view, we illustrate all the points on explicit examples, both
symbolically and numerically. To help with the investigation of related
questions, we introduce a number of tools, including holomorphic cutting rules,
new approaches to dispersion relations, as well as formulae for local behavior
of Feynman integrals near branch points.


title: Birth of the Galactic Disk Revealed by the H3 Survey

abstract:
  We use chemistry ([alpha/Fe] and [Fe/H]), main sequence turnoff ages, and
kinematics determined from H3 Survey spectroscopy and Gaia astrometry to
identify the birth of the Galactic disk. We separate in-situ and accreted stars
on the basis of angular momenta and eccentricities. The sequence of high-alpha
in-situ stars persists down to at least [Fe/H]=-2.5 and shows unexpected
non-monotonic behavior: with increasing metallicity the population first
declines in [alpha/Fe], then increases over the range -1.3<[Fe/H]<-0.7, and
then declines again at higher metallicities. The number of stars in the in-situ
population rapidly increases above [Fe/H]=-1. The average kinematics of these
stars are hot and independent of metallicity at [Fe/H]<-1 and then become
increasingly cold and disk-like at higher metallicities. The ages of the
in-situ, high-alpha stars are uniformly very old (13 Gyr) at [Fe/H]<-1.3, and
span a wider range (8-12 Gyr) at higher metallicities. Interpreting the
chemistry with a simple chemical evolution model suggests that the
non-monotonic behavior is due to a significant increase in star formation
efficiency, which began 13 Gyr ago. These results support a picture in which
the first 1 Gyr of the Galaxy was characterized by a "simmering phase" in which
the star formation efficiency was low and the kinematics had substantial
disorder with some net rotation. The disk then underwent a dramatic
transformation to a "boiling phase", in which the star formation efficiency
increased substantially, the kinematics became disk-like, and the number of
stars formed increased tenfold. We interpret this transformation as the birth
of the Galactic disk at z~4. The physical origin of this transformation is
unclear and does not seem to be reproduced in current galaxy formation models.


title: M5-branes wrapped on four-dimensional orbifolds

abstract:
  We construct supersymmetric $AdS_3$ solutions of $D=11$ supergravity, dual to
$d=2$, $\mathcal{N}=(0,2)$ SCFTs, that are associated with M5-branes wrapping
two different four-dimensional orbifolds. In one case the orbifold is a spindle
fibred over another spindle, while in the other it is a spindle fibred over a
Riemann surface with genus $g>1$. We show that the central charges of the $d=2$
SCFTs calculated from the gravity solutions agree with field theory
computations using anomaly polynomials. The new $D=11$ solutions are obtained
after constructing a new consistent Kaluza-Klein truncation of maximal $D=7$
gauged supergravity reduced on a spindle down to $D=5$ minimal gauged
supergravity.


title:
Vertex Operator Algebras and Topologically Twisted Chern-Simons-Matter
  Theories

abstract:
  We consider several topologically twisted Chern-Simons-matter theories and
propose boundary VOAs whose module categories should model the category of line
operators of the 3d bulk. Our main examples come from the topological $A$ and
$B$ twists of the exotic $\mathcal{N}=4$ Chern-Simons-matter theories of
Gaiotto-Witten, but we show that there is a topological "$A$-twist" for a much
larger class of $\mathcal{N}\neq4$ theories. We illustrate a particular example
of this new class of theories that admits the $p=2$ singlet VOA
$\mathfrak{M}(2)$ on its boundary and comment on its relation to the $\psi \to
\infty$ limit of the Gaiotto-Rap{\v c}{\'a}k corner VOA $Y_{1,1,0}[\psi]$.


title: ABJM at finite $N$ via 4d supergravity

abstract:
  We apply the conjecture of arXiv:2111.06903 for higher derivative
gravitational blocks to the effective supergravity description of M-theory on
S$^7/\mathbb{Z}_k$. Utilizing known localization results for the
holographically dual ABJM theory, we are able to determine the complete
infinite derivative expression of the AdS$_4$ supergravity prepotential. This
uniquely fixes the gravitational block, leading to holographic predictions for
a number of exact ABJM observables, excluding only constant and
non-perturbative corrections in the gauge group rank $N$. The predicted S$^3$
partition function is an Airy function that reproduces previous results and
generalizes them to include arbitrary squashing and mass deformations/R-charge
assignments. The topologically twisted and superconformal indices are instead
products of two different Airy functions, in agreement with direct numeric
calculations in the unrefined limit of the former object. The general
fixed-point formula for an arbitrary supersymmetric background is similarly
given as a product of Airy functions.


title:
Long-distance distribution of qubit-qubit entanglement using
  Gaussian-correlated photonic beams

abstract:
  We investigate the deterministic generation and distribution of entanglement
in large quantum networks by driving distant qubits with the output fields of a
non-degenerate parametric amplifier. In this setting, the amplifier produces a
continuous Gaussian two-mode squeezed state, which acts as a quantum-correlated
reservoir for the qubits and relaxes them into a highly entangled steady state.
Here we are interested in the maximal amount of entanglement and the optimal
entanglement generation rates that can be achieved with this scheme under
realistic conditions taking, in particular, the finite amplifier bandwidth,
waveguide losses and propagation delays into account. By combining exact
numerical simulations of the full network with approximate analytic results, we
predict the optimal working point for the amplifier and the corresponding
qubit-qubit entanglement under various conditions. Our findings show that this
passive conversion of Gaussian- into discrete- variable entanglement offers a
robust and experimentally very attractive approach for operating large optical,
microwave or hybrid quantum networks, for which efficient parametric amplifiers
are currently developed.


title:
Superconductivity, charge density wave, and supersolidity in flat bands
  with tunable quantum metric

abstract:
  Predicting the fate of an interacting system in the limit where the
electronic bandwidth is quenched is often highly non-trivial. The complex
interplay between interactions and quantum fluctuations driven by the band
geometry can drive a competition between various ground states, such as charge
density wave order and superconductivity. In this work, we study an electronic
model of topologically-trivial flat bands with a continuously tunable
Fubini-Study metric in the presence of on-site attraction and nearest-neighbor
repulsion, using numerically exact quantum Monte Carlo simulations. By varying
the electron filling and the spatial extent of the localized flat-band Wannier
wavefunctions, we obtain a number of intertwined orders. These include a phase
with coexisting charge density wave order and superconductivity, i.e., a
supersolid. In spite of the non-perturbative nature of the problem, we identify
an analytically tractable limit associated with a `small' spatial extent of the
Wannier functions, and derive a low-energy effective Hamiltonian that can well
describe our numerical results.


title: Magic hinders quantum certification

abstract:
  We show how the resource theory of magic quantifies the hardness of quantum
certification protocols. In particular, the resources needed for a direct
fidelity estimation grow exponentially with the stabilizer R\'enyi entropy
[PRL, 128, 050402]: the more the magic, the harder the certification.
Remarkably, the verification turns out to be polynomially feasible only for
those states which are shown to be useless to attain any quantum advantage. We
then extend our results to quantum evolutions, showing that the resources
needed to certify the quality of the application of a given unitary $U$ are
governed by the magic in the Choi state associated with $U$, which is shown to
possess a profound connection with out-of-time order correlators.


title:
Enhanced Amplitude for Superconductivity due to Spectrum-wide Wave
  Function Criticality in Quasiperiodic and Power-law Random Hopping Models

abstract:
  We study the interplay of superconductivity and a wide spectrum of critical
(multifractal) wave functions ("spectrum-wide quantum criticality," SWQC) in
the one-dimensional Aubry-Andr\'e and power-law random-banded matrix models
with attractive interactions, using self-consistent BCS theory. We find that
SWQC survives the incorporation of attractive interactions at the Anderson
localization transition, while the pairing amplitude is maximized near this
transition in both models. Our results suggest that SWQC, recently discovered
in two-dimensional topological surface-state and nodal superconductor models,
can robustly enhance superconductivity.


title: Twisted Formalism for 3d $\mathcal{N}=4$ Theories

abstract:
  We describe the topological $A$ and $B$ twists of 3d $\mathcal{N}=4$ theories
of hypermultiplets gauged by $\mathcal{N}=4$ vector multiplets as certain
deformations of the holomorphic-topological ($HT$) twist of those theories,
utilizing the twisted superfields of Aganagic-Costello-Vafa-McNamara describing
$HT$-twisted 3d $\mathcal{N}=2$ theories. We rederive many known results from
this perspective, including state spaces on Riemann surfaces, deformations
induced by flavor symmetries, and the boundary VOAs of Costello-Gaiotto. Along
the way, we show how the secondary product of local operators in the
holomorphic-topological twist is related to the secondary product in the fully
topological twist.


title:
High-contrast, high-angular resolution view of the GJ 367 exoplanet
  system

abstract:
  We search for additional companions in the GJ 367 exoplanet system, and aim
at better constraining its age and evolutionary status. We analyse high
contrast direct imaging observations obtained with HST/NICMOS, VLT/NACO, and
VLT/SPHERE. We investigate and critically discuss conflicting age indicators
based on theoretical isochrones and models for Galactic dynamics. A comparison
of GAIA EDR3 parallax and photometric measurements with theoretical isochrones
suggest a young age $\le$60 Myr for GJ 367. The star's Galactic kinematics
exclude membership to any nearby young moving group or stellar stream. Its
highly eccentric Galactic orbit, however, is atypical for a young star. Age
estimates considering Galactic dynamical evolution are most consistent with an
age of 1 to 8 Gyr. We find no evidence for a significant mid-infrared excess in
the WISE bands, suggesting the absence of warm dust in the GJ 367 system. The
direct imaging data provide significantly improved detection limits compared to
previous studies. At 530 mas (5 au) separation, the SPHERE data achieve a 5
sigma contrast of $2.6 \times 10^{-6}$. The data exclude the presence of a
stellar companion at projected separations $\ge$0.4 au. At projected
separations $\ge$5 au we can exclude substellar companions with a mass $\ge$
1.5 M$_{\rm Jup}$ for an age of 50 Myr, and $\ge$ 20 M$_{\rm Jup}$ for an age
of 5 Gyr. By applying the stellar parameters corresponding to the 50 Myr
isochrone, we derive a bulk density of $\rho_{\rm planet} = 6.2$ g/cm$^3$ for
GJ 367b, which is 25% smaller than a previous estimate.


title:
Quantum fluctuations in the chiral order parameter of quantum skyrmion
  crystals

abstract:
  Traditionally, skyrmions are treated as continuum magnetic textures of
classical spins with a well-defined topological skyrmion number. Owing to their
topological protection, skyrmions have attracted great interest as building
blocks in future memory technology. Smaller skyrmions offer greater memory
density, however, quantum effects are not negligible for skyrmions with sizes
of just a few lattice constants. In this paper we study quantum fluctuations
around dense skyrmion crystal ground states, and focus on the utility of a
discretized, chiral order parameter for quantum skyrmions. The order parameter
is found to be a useful indicator of the existence of quantum skyrmions, and
captures the quantum phase transition between two distinct skyrmion ground
states.


title:
Implementation of an atomtronic SQUID in a strongly confined toroidal
  condensate

abstract:
  We investigate the dynamics of an atomtronic SQUID created by two mobile
barriers, moving at two different, constant velocities in a quasi-1D toroidal
condensate. We implement a multi-band truncated Wigner approximation
numerically, to demonstrate the functionality of a SQUID reflected in the
oscillatory voltage-flux dependence. The relative velocity of the two barriers
results in a chemical potential imbalance analogous to a voltage in an
electronic system. The average velocity of the two barriers corresponds to a
rotation of the condensate, analogous to a magnetic flux. We demonstrate that
the voltage equivalent shows characteristic flux-dependent oscillations. We
point out the parameter regime of barrier heights and relaxation times for the
phase slip dynamics, resulting in a realistic protocol for atomtronic SQUID
operation.


title:
Grand unification and the Planck scale: An $\mathit{SO}(10)$ example of
  radiative symmetry breaking

abstract:
  Grand unification of gauge couplings and fermionic representations remains an
appealing proposal to explain the seemingly coincidental structure of the
Standard Model. However, to realise the Standard Model at low energies, the
unified symmetry group has to be partially broken by a suitable scalar
potential in just the right way. The scalar potential contains several
couplings, whose values dictate the residual symmetry at a global minimum. Some
(and possibly many) of the corresponding symmetry-breaking patterns are
incompatible with the Standard Model and therefore non-admissible. Here, we
initiate a systematic study of radiative symmetry breaking to thereby constrain
viable initial conditions for the scalar couplings, for instance, at the Planck
scale. We combine these new constraints on an admissible scalar potential with
well-known constraints in the gauge-Yukawa sector into a general blueprint that
carves out the viable effective-field-theory parameter space of any underlying
theory of quantum gravity. We exemplify the constraining power of our blueprint
within a non-supersymmetric $\mathit{SO}(10)$ GUT containing a $\mathbf{16}_H$-
and a $\mathbf{45}_H$-dimensional scalar representation. We explicitly
demonstrate that the requirement of successful radiative symmetry breaking to
the correct subgroups significantly constraints the underlying microscopic
dynamics. The presence of non-admissible radiative minima can even entirely
exclude specific breaking chains: In the $\mathit{SO}(10)$ example, Pati-Salam
breaking chains cannot be realised since the respective minima are never the
deepest ones.


title:
Non-Gaussianity in the Squeezed Three-Point Correlation from the
  Relativistic Effects

abstract:
  Assuming a LCDM universe in a single-field inflationary scenario, we compute
the three-point correlation function of the observed matter density fluctuation
in the squeezed triangular configuration, accounting for all the relativistic
effects at the second order in perturbations. This squeezed three-point
correlation function characterizes the local-type primordial non-Gaussianity,
and it has been extensively debated in literature whether there exists a
prominent feature in galaxy clustering on large scales in a single-field
inflationary scenario either from the primordial origin or the intrinsic
nonlinearity in general relativity. First, we show that theoretical
descriptions of galaxy bias are incomplete in general relativity due to
ambiguities in spatial gauge choice, while those of cosmological observables
are independent of spatial gauge choice. Hence a proper relativistic
description of galaxy bias is needed to reach a definitive conclusion in galaxy
clustering. Second, we demonstrate that the gauge-invariant calculations of the
cosmological observables remain unaffected by extra coordinate transformations
like CFC or large diffeomorphism like dilatation. Finally, we show that the
relativistic effects associated with light propagation in observations cancel
each other, and hence there exists NO non-Gaussian contribution from the
so-called projection effects.


title: Coupling Metric-Affine Gravity to a Higgs-Like Scalar Field

abstract:
  General Relativity (GR) exists in different formulations. They are equivalent
in pure gravity but generically lead to distinct predictions once matter is
included. After a brief overview of various versions of GR, we focus on
metric-affine gravity, which avoids any assumption about the vanishing of
curvature, torsion or non-metricity. We use it to construct an action of a
scalar field coupled non-minimally to gravity. It encompasses as special cases
numerous previously studied models. Eliminating non-propagating degrees of
freedom, we derive an equivalent theory in the metric formulation of GR.
Finally, we give a brief outlook to implications for Higgs inflation.


title:
Probing magnetic anisotropy and spin-reorientation transition in 3D
  antiferromagnet, Ho$_{0.5}$Dy$_{0.5}$FeO$_{3}\vert$Pt using spin Hall
  magnetoresistance

abstract:
  Orthoferrites ($RE$FeO$_{3}$) containing rare-earth ($RE$) elements are 3D
antiferromagnets (AFM) that exhibit characteristic weak ferromagnetism
originating due to slight canting of the spin moments and display a rich
variety of spin reorientation transitions in the magnetic field
($H$)-temperature ($T$) parameter space. We present spin Hall magnetoresistance
(SMR) studies on a $b$-plate ($ac$-plane) of crystalline
Ho$_{0.5}$Dy$_{0.5}$FeO$_{3}|$Pt (HDFO$|$Pt) hybrid at various $T$ in the
range, 11 to 300 K. In the room temperature $\Gamma_4(G_x, A_y, F_z)$ phase,
the switching between two degenerate domains, $\Gamma_4(+G_x, +F_z)$ and
$\Gamma_4(-G_x, -F_z)$ occurs at fields above a critical value, $H_{\text{c}}
\approx 713$ Oe. Under $H > H_{\text{c}}$, the angular dependence of SMR
($\alpha$-scan) in the $\Gamma_4(G_x, A_y, F_z)$ phase yielded a highly skewed
curve with a sharp change (sign-reversal) along with a rotational hysteresis
around $a$-axis. This hysteresis decreases with an increase in $H$. Notably, at
$H < H_{\text{c}} $, the $\alpha$-scan measurements on the single domain,
$\Gamma_4(\pm G_x, \pm F_z)$ exhibited an anomalous sinusoidal signal of
periodicity 360 deg. Low-$T$ SMR curves ($H$ = 2.4 kOe), showed a systematic
narrowing of the hysteresis (down to 150 K) and a gradual reduction in the
skewness (150 to 52 K), suggesting weakening of the anisotropy possibly due to
the $T$-evolution of Fe-$RE$ exchange coupling. Below 25 K, the SMR modulation
showed an abrupt change around the $c$-axis, marking the presence of
$\Gamma_2(F_x,C_y,G_z)$ phase. We have employed a simple Hamiltonian and
computed SMR to examine the observed skewed SMR modulation. In summary, SMR is
found to be an effective tool to probe magnetic anisotropy as well as a spin
reorientation in HDFO. Our spin-transport study highlights the potential of
HDFO for future AFM spintronic devices.


title:
Long-term 3D-MHD Simulations of Black Hole Accretion Disks formed in
  Neutron Star Mergers

abstract:
  We examine the long-term evolution of accretion tori around black hole (BH)
remnants of compact object mergers involving at least one neutron star, to
better understand their contribution to kilonovae and the synthesis of
r-process elements. To this end, we modify the unsplit magnetohydrodynamic
(MHD) solver in FLASH4.5 to work in non-uniform three-dimensional spherical
coordinates, enabling more efficient coverage of a large dynamic range in
length scales while exploiting symmetries in the system. This modified code is
used to perform BH accretion disk simulations that vary the initial magnetic
field geometry and disk compactness, utilizing a physical equation of state, a
neutrino leakage scheme for emission and absorption, and modeling the BH's
gravity with a pseudo-Newtonian potential. Simulations run for long enough to
achieve a radiatively-inefficient state in the disk. We find robust mass
ejection with both poloidal and toroidal initial field geometries, and
suppressed outflow at high disk compactness. With the included physics, we
obtain bimodal velocity distributions that trace back to mass ejection by
magnetic stresses at early times, and to thermal processes in the
radiatively-inefficient state at late times. The electron fraction distribution
of the disk outflow is broad in all models, and the ejecta geometry follows a
characteristic hourglass shape. We test the effect of removing neutrino
absorption or nuclear recombination with axisymmetric models, finding $\sim
50\%$ less mass ejection and more neutron-rich composition without neutrino
absorption, and a subdominant contribution from nuclear recombination. Tests of
the MHD and neutrino leakage implementations are included.


title: Gravitational time dilation as a resource in quantum sensing

abstract:
  Atomic clock interferometers are a valuable tool to test the interface
between quantum theory and gravity, in particular via the measurement of
gravitational time dilation in the quantum regime. Here, we investigate whether
gravitational time dilation may be also used as a resource in quantum
information theory. In particular, we show that for a freely falling
interferometer and for a Mach-Zehnder interferometer, the gravitational time
dilation may enhance the precision in estimating the gravitational acceleration
for long interferometric times. To this aim, the interferometric measurements
should be performed on both the path and the clock degrees of freedom.


title: The Prospects for Hurricane-like Vortices in Protoplanetary Disks

abstract:
  When ice on the surface of dust grains in protoplanetary disk sublimates, it
adds its latent heat of water sublimation to the surrounding flow. Drawing on
the analogy provided by tropical cyclones on Earth, we investigate if this
energy source is sufficient to sustain or magnify anticyclonic disk vortices
that would otherwise fall victim to viscous dissipation. An analytical
treatment, supported by exploratory two-dimensional simulations, suggests that
even modestly under-saturated flows can extend the lifetime of vortices,
potentially to a degree sufficient to aid particle trapping and planetesimal
formation. We expect the best conditions for this mechanism to occur will be
found near the disk's water ice line if turbulent motions displace gas parcels
out of thermodynamic equilibrium with the dust mid-plane.


title:
First Census of Gas-phase Metallicity Gradients of Star-forming Galaxies
  in Overdense Environments at Cosmic Noon

abstract:
  We report the first spatially resolved measurements of gas-phase metallicity
radial gradients in star-forming galaxies in overdense environments at
$z\gtrsim2$. The spectroscopic data are acquired by the \mg\ survey, a Hubble
Space Telescope (HST) cycle-28 medium program. This program is obtaining 45
orbits of WFC3/IR grism spectroscopy in the density peak regions of three
massive galaxy protoclusters (BOSS 1244, BOSS 1542 and BOSS 1441) at $z=2-3$.
Our sample in the BOSS 1244 field consists of 20 galaxies with stellar-mass
ranging from $10^{9.0}$ to $10^{10.3}$ \Msun\ , star formation rate (SFR) from
10 to 240 \Msun\,yr$^{-1}$, and global gas-phase metallicity (\oh) from 8.2 to
8.6. At $1\sigma$ confidence level, 2/20 galaxies in our sample show positive
(inverted) gradients -- the relative abundance of oxygen increasing with
galactocentric radius, opposite the usual trend. Furthermore, 1/20 shows
negative gradients and 17/20 are consistent with flat gradients. This high
fraction of flat/inverted gradients is uncommon in simulations and previous
observations conducted in blank fields at similar redshifts. To understand
this, we investigate the correlations among various observed properties of our
sample galaxies. We find an anticorrelation between metallicity gradient and
global metallicity of our galaxies residing in extreme overdensities, and a
marked deficiency of metallicity in our massive galaxies as compared to their
coeval field counterparts. We conclude that the cold-mode gas accretion plays
an active role in shaping the chemical evolution of galaxies in the
protocluster environments, diluting their central chemical abundance, and
flattening/inverting their metallicity gradients.


title: Melting of magnetic order in ${\mathrm{NaOsO}}_{3}$ by fs laser pulses

abstract:
  NaOsO$_3$ has recently attracted significant attention for the strong
coupling between its electronic band structure and magnetic ordering. Here, we
used time-resolved magnetic X-ray diffraction to determine the timescale of the
photoinduced \afm dynamics in NaOsO$_3$. Our measurements are consistent with a
sub-100~fs melting of the \afm long-range order, that occurs significantly
faster than the lattice dynamics as monitored by the transient change in
intensity of selected Bragg structural reflections, which instead show a
decrease of intensity on a timescale of several ps.


title: Poset Ramsey number $R(P,Q_n)$. I. Complete multipartite posets

abstract:
  A poset $(P',\le_{P'})$ contains a copy of some other poset $(P,\le_P)$ if
there is an injection $f\colon P'\to P$ where for every $X,Y\in P$, $X\le_P Y$
if and only if $f(X)\le_{P'} f(Y)$. For any posets $P$ and $Q$, the poset
Ramsey number $R(P,Q)$ is the smallest integer $N$ such that any blue/red
coloring of a Boolean lattice of dimension $N$ contains either a copy of $P$
with all elements blue or a copy of $Q$ with all elements red. We denote by
$K_{t_1,\dots,t_\ell}$ a complete $\ell$-partite poset, i.e.\ a poset
consisting of $\ell$ pairwise disjoint sets $A^i$ of size $t_i$, $1\le i\le
\ell$, such that for any $i,j\in\{1,\dots,\ell\}$ and any two $X\in A^{i}$ and
$Y\in A^{j}$, $X<Y$ if and only if $i<j$. In this paper we show that
$R(K_{t_1,\dots,t_\ell},Q_n)\le n+\frac{(2+o_n(1))\ell n}{\log n}$.


title: Constraining New Physics with Borexino Phase-II spectral data

abstract:
  We present a detailed analysis of the spectral data of Borexino Phase II,
with the aim of exploiting its full potential to constrain scenarios beyond the
Standard Model. In particular, we quantify the constraints imposed on neutrino
magnetic moments, neutrino non-standard interactions, and several simplified
models with light scalar, pseudoscalar or vector mediators. Our analysis shows
perfect agreement with those performed by the collaboration on neutrino
magnetic moments and neutrino non-standard interactions in the same restricted
cases and expands beyond those, stressing the interplay between flavour
oscillations and and flavour non-diagonal interaction effects for the correct
evaluation of the event rates. For simplified models with light mediators we
show the power of the spectral data to obtain robust limits beyond those
previously estimated in the literature.


title: Classical dissipative cost of quantum control

abstract:
  Protocols for non-adiabatic quantum control often require the use of
classical time varying fields. Assessing the thermodynamic cost of such
protocols, however, is far from trivial. In this letter we study the
irreversible entropy produced by the classical apparatus generating the control
fields, thus providing a direct link between the cost of a control protocol and
dissipation. We focus, in particular, on the case of time-dependent magnetic
fields and shortcuts to adiabaticity. Our results are showcased with two
experimentally realisable case studies: the Landau-Zener model of a spin-1/2
particle in a magnetic field and an ion confined in a Penning trap.


title: Adiabatic quantum algorithm for artificial graphene

abstract:
  We devise a quantum-circuit algorithm to solve the ground state and ground
energy of artificial graphene. The algorithm implements a Trotterized adiabatic
evolution from a purely tight-binding Hamiltonian to one including kinetic,
spin-orbit and Coulomb terms. The initial state is obtained efficiently using
Gaussian-state preparation, while the readout of the ground energy is organized
into seventeen sets of measurements, irrespective of the size of the problem.
The total depth of the corresponding quantum circuit scales polynomially with
the size of the system. A full simulation of the algorithm is performed and
ground energies are obtained for lattices with up to four hexagons. Our results
are benchmarked with exact diagonalization for systems with one and two
hexagons. For larger systems we use the exact statevector and approximate
matrix product state simulation techniques. The latter allows to systematically
trade off precision with memory and therefore to tackle larger systems. We
analyze adiabatic and Trotterization errors, providing estimates for optimal
periods and time discretizations given a finite accuracy. In the case of large
systems we also study approximation errors.


title:
EfficientCellSeg: Efficient Volumetric Cell Segmentation Using Context
  Aware Pseudocoloring

abstract:
  Volumetric cell segmentation in fluorescence microscopy images is important
to study a wide variety of cellular processes. Applications range from the
analysis of cancer cells to behavioral studies of cells in the embryonic stage.
Like in other computer vision fields, most recent methods use either large
convolutional neural networks (CNNs) or vision transformer models (ViTs). Since
the number of available 3D microscopy images is typically limited in
applications, we take a different approach and introduce a small CNN for
volumetric cell segmentation. Compared to previous CNN models for cell
segmentation, our model is efficient and has an asymmetric encoder-decoder
structure with very few parameters in the decoder. Training efficiency is
further improved via transfer learning. In addition, we introduce Context Aware
Pseudocoloring to exploit spatial context in z-direction of 3D images while
performing volumetric cell segmentation slice-wise. We evaluated our method
using different 3D datasets from the Cell Segmentation Benchmark of the Cell
Tracking Challenge. Our segmentation method achieves top-ranking results, while
our CNN model has an up to 25x lower number of parameters than other
top-ranking methods. Code and pretrained models are available at:
https://github.com/roydenwa/efficient-cell-seg


title:
Sweeping process approach to stress analysis in elastoplastic Lattice
  Springs Models with applications to Hyperuniform Network Materials

abstract:
  Disordered network materials abound in both nature and synthetic situations
while rigorous analysis of their nonlinear mechanical behaviors still is very
challenging. The purpose of this paper is to connect the mathematical framework
of sweeping process originally proposed by Moreau to a generic class of Lattice
Spring Models with plasticity phenomenon. We explicitly construct a sweeping
process and provide numerical schemes to find the evolution of stresses in a
Lattice Spring Model with infinitesimal strains and perfect plasticity. In
particular, we develop a highly efficient "leapfrog" computational framework
that allow ones to rigorously track the progression of plastic events in the
system based on the sweeping process theory. The utility of our framework is
demonstrated by analyzing the elastoplastic stresses in a novel class of
disordered network materials exhibiting the property of hyperuniformity, in
which the infinite wave-length density fluctuations associated with the
distribution of network nodes are completely suppressed. We find enhanced
mechanical properties such as increasing stiffness, yield strength and tensile
strength as the degree of hyperuniformity of the material system increases. Our
results have implications for optimal network material design and our
event-based framework can be readily generalized for nonlinear stress analysis
of other heterogeneous material systems. We also include some insights to the
model from the viewpoint of the rigidity theory.


title:
Bridging the gap between classical and quantum many-body information
  dynamics

abstract:
  The fundamental question of how information spreads in closed quantum
many-body systems is often addressed through the lens of the bipartite
entanglement entropy, a quantity that describes correlations in a comprehensive
(nonlocal) way. Among the most striking features of the entanglement entropy
are its unbounded linear growth in the thermodynamic limit, its asymptotic
extensivity in finite-size systems, and the possibility of measurement-induced
phase transitions, all of which have no obvious classical counterpart. Here, we
show how these key qualitative features emerge naturally also in classical
information spreading, as long as one treats the classical many-body problem on
par with the quantum one, that is, by explicitly accounting for the
exponentially large classical probability distribution. Our analysis is
supported by extensive numerics on prototypical cellular automata and
Hamiltonian systems, for which we focus on the classical mutual information and
also introduce a `classical entanglement entropy'. Our study sheds light on the
nature of information spreading in classical and quantum systems, and opens new
avenues for quantum-inspired classical approaches across physics, information
theory, and statistics.


title:
Learning from Untrimmed Videos: Self-Supervised Video Representation
  Learning with Hierarchical Consistency

abstract:
  Natural videos provide rich visual contents for self-supervised learning. Yet
most existing approaches for learning spatio-temporal representations rely on
manually trimmed videos, leading to limited diversity in visual patterns and
limited performance gain. In this work, we aim to learn representations by
leveraging more abundant information in untrimmed videos. To this end, we
propose to learn a hierarchy of consistencies in videos, i.e., visual
consistency and topical consistency, corresponding respectively to clip pairs
that tend to be visually similar when separated by a short time span and share
similar topics when separated by a long time span. Specifically, a hierarchical
consistency learning framework HiCo is presented, where the visually consistent
pairs are encouraged to have the same representation through contrastive
learning, while the topically consistent pairs are coupled through a topical
classifier that distinguishes whether they are topic related. Further, we
impose a gradual sampling algorithm for proposed hierarchical consistency
learning, and demonstrate its theoretical superiority. Empirically, we show
that not only HiCo can generate stronger representations on untrimmed videos,
it also improves the representation quality when applied to trimmed videos.
This is in contrast to standard contrastive learning that fails to learn
appropriate representations from untrimmed videos.


title:
From a microscopic inertial active matter model to the Schr\"odinger
  equation

abstract:
  Field theories for the one-body density of an active fluid, such as the
paradigmatic active model B+, are simple yet very powerful tools for describing
phenomena such as motility-induced phase separation. No comparable theory has
been derived yet for the underdamped case. In this work, we introduce active
model I+, an extension of active model B+ to particles with inertia. The
governing equations of active model I+ are systematically derived from the
microscopic Langevin equations. We show that, for underdamped active particles,
thermodynamic and mechanical definitions of the velocity field no longer
coincide and that the density-dependent swimming speed plays the role of an
effective viscosity. Moreover, active model I+ contains the Schr\"odinger
equation in Madelung form as a limiting case, allowing to find analoga of the
quantum-mechanical tunnel effect and of fuzzy dark matter in the active fluid.
We investigate the active tunnel effect analytically and via numerical
continuation.

categories: cond-mat.soft cond-mat.stat-mech physics.flu-dyn quant-ph


title: Descent cohomology and factorizations of groups

abstract:
  The aim of the paper is to give a full classification of factorizations of
groups in terms of descent cohomology (pointed) sets introduced in [5]. We show
that descent cohomology includes Serre's non-abelian group cohomology as a
special case. This enables us to generalize Serre's theory further to include
monoids.


title: Double Source Lensing Probing High Redshift Cosmology

abstract:
  Double source lensing, with two sources lensed by the same foreground galaxy,
involves the distance between each source and the lens and hence is a probe of
the universe away from the observer. The double source distance ratio also
reduces sensitivity to the lens model and has good complementarity with
standard distance probes. We show that using this technique at high redshifts
$z>1$, to be enabled by data from the Euclid satellite and other surveys, can
give insights on dark energy, both in terms of $w_0$-$w_a$ and redshift binned
density. We find a dark energy figure of merit of 245 from combination of 256
double source systems with moderate quality cosmic microwave background and
supernova data. Using instead five redshift bins between $z=1.1$-5, we could
detect the dark energy density out to $z\approx5$, or make measurements ranging
between 31$\sigma$ and 2.5$\sigma$ of its values in the bins.


title: The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systems

abstract:
  Conversational agents have come increasingly closer to human competence in
open-domain dialogue settings; however, such models can reflect insensitive,
hurtful, or entirely incoherent viewpoints that erode a user's trust in the
moral integrity of the system. Moral deviations are difficult to mitigate
because moral judgments are not universal, and there may be multiple competing
judgments that apply to a situation simultaneously. In this work, we introduce
a new resource, not to authoritatively resolve moral ambiguities, but instead
to facilitate systematic understanding of the intuitions, values and moral
judgments reflected in the utterances of dialogue systems. The Moral Integrity
Corpus, MIC, is such a resource, which captures the moral assumptions of 38k
prompt-reply pairs, using 99k distinct Rules of Thumb (RoTs). Each RoT reflects
a particular moral conviction that can explain why a chatbot's reply may appear
acceptable or problematic. We further organize RoTs with a set of 9 moral and
social attributes and benchmark performance for attribute classification. Most
importantly, we show that current neural language models can automatically
generate new RoTs that reasonably describe previously unseen interactions, but
they still struggle with certain scenarios. Our findings suggest that MIC will
be a useful resource for understanding and language models' implicit moral
assumptions and flexibly benchmarking the integrity of conversational agents.
To download the data, see https://github.com/GT-SALT/mic


title:
Composing (with) automorphisms in the colored Cube Dance: an interactive
  tool for musical chord transformation

abstract:
  The `colored Cube Dance' is an extension of Douthett's and Steinbach's Cube
Dance graph, related to a monoid of binary relations defined on the set of
major, minor, and augmented triads. This contribution explores the automorphism
group of this monoid action, as a way to transform chord progressions. We show
that this automorphism group is of order 7776 and is isomorphic to
$({\mathbb{Z}_3}^4 \rtimes D_8) \rtimes (D_6 \times \mathbb{Z}_2)$. The size
and complexity of this group makes it unwieldy: we therefore provide an
interactive tool via a web interface based on common HTML/Javascript frameworks
for students, musicians, and composers to explore these automorphisms, showing
the potential of these technologies for math/music outreach activities.


title:
Investigation of hydrogen incorporations in bulk infinite-layer
  nickelates

abstract:
  Infinite-layer (IL) nickelates are an emerging class of superconductors,
where the Ni$^{1+}$ valence state in a square planar NiO$_2$ coordination can
only be reached via topotactic reduction of the perovskite phase. However, this
topotactic soft chemistry with hydrogenous reagents is still at a stage of
rapid development, and there is a number of open issues, especially considering
the possibility of hydrogen incorporation. Here we study the time dependence of
the topotactic transformation of LaNiO$_3$ to LaNiO$_2$ for powder samples with
x-ray diffraction and gas extraction techniques. While the hydrogen content of
the powder increases with time, neutron diffraction shows no negative
scattering of hydrogen in the LaNiO$_2$ crystal lattice. The extra hydrogen
appears to be confined to grain boundaries or secondary-phase precipitates. The
average crystal structure, and possibly also the physical properties, of the
primary LaNiO$_2$ phase are therefore not noticeably affected by hydrogen
residues created by the topotactic transformation.


title: Solvable time-like cosets and holography beyond $AdS$

abstract:
  We build a novel time-like coset sigma-model describing type-II superstring
theory in a charged rotating black-brane background that interpolates between a
locally $AdS_3$ in the IR and a linear-dilaton geometry in the UV. This allows
one to perform a systematic study of holography in non-AdS backgrounds which
are smoothly connected to $AdS_3$. We construct massless closed string states
vertex operators in the NS-NS sector, calculate the corresponding two-point
correlation functions, and discuss holographic interpretation of our results
from 4+1 dimensional boundary field theory point of view. Compactifying the
theory on $\mathbb{T}^4$, we show that the spectrum of a single long string
with unit winding agrees with the spectrum of a CFT$_2$ deformed by $T\bar{T}$.
We also calculate correlation functions of operators of the dual 1+1
dimensional non-conformal boundary field theory using world-sheet techniques.


title:
Using Interactive Feedback to Improve the Accuracy and Explainability of
  Question Answering Systems Post-Deployment

abstract:
  Most research on question answering focuses on the pre-deployment stage;
i.e., building an accurate model for deployment. In this paper, we ask the
question: Can we improve QA systems further \emph{post-}deployment based on
user interactions? We focus on two kinds of improvements: 1) improving the QA
system's performance itself, and 2) providing the model with the ability to
explain the correctness or incorrectness of an answer. We collect a
retrieval-based QA dataset, FeedbackQA, which contains interactive feedback
from users. We collect this dataset by deploying a base QA system to
crowdworkers who then engage with the system and provide feedback on the
quality of its answers. The feedback contains both structured ratings and
unstructured natural language explanations. We train a neural model with this
feedback data that can generate explanations and re-score answer candidates. We
show that feedback data not only improves the accuracy of the deployed QA
system but also other stronger non-deployed systems. The generated explanations
also help users make informed decisions about the correctness of answers.
Project page: https://mcgill-nlp.github.io/feedbackqa/


title:
Single Inclusive Jet Production in $pA$ Collisions at NLO in the
  small-$x$ regime

abstract:
  We present the first complete NLO prediction with full jet algorithm
implementation for the single inclusive jet production in $pA$ collisions
within the CGC effective theory. Our prediction is fully differential over the
final state physical kinematics, which allows the implementation of any IR safe
observable including the jet clustering procedure. The NLO calculation is
organized with the aid of the power counting proposed in [1] which gives rise
to the novel soft contributions in the CGC factorization. We achieve the
fully-differential calculation by constructing suitable subtraction terms to
handle the singularities in the real corrections. The subtraction contributions
can be exactly integrated analytically. We present the NLO cross section with
the jets constructed using the anti-$k_T$ algorithm. The NLO calculation
demonstrates explicitly the validity of the CGC factorization in jet
production. Furthermore, as a byproduct of the subtraction method, we also
derive the fully analytic cross section for the forward jet production in the
small-$R$ limit. We show that in the small-$R$ approximation, the forward jet
cross section can be factorized into a semi-hard cross section that produces a
parton and the semi-inclusive jet functions. We argue that this feature holds
for generic jet production and jet substructure observables in the CGC
framework. Last, we show numerical analyses of the derived formula to validate
our calculations. We justify when the small-$R$ approximation is appropriate.
Like forward hadron production, the obtained NLO result also exhibits the
negativity of the cross section in the large jet transverse regime, which
signals the need for the threshold resummation. A sketch of the threshold
resummation in the CGC framework is presented based on the multiple emission
picture.


title:
Federated Learning for Distributed Spectrum Sensing in NextG
  Communication Networks

abstract:
  NextG networks are intended to provide the flexibility of sharing the
spectrum with incumbent users and support various spectrum monitoring tasks
such as anomaly detection, fault diagnostics, user equipment identification,
and authentication. A network of wireless sensors is needed to monitor the
spectrum for signal transmissions of interest over a large deployment area.
Each sensor receives signals under a specific channel condition depending on
its location and trains an individual model of a deep neural network (DNN)
accordingly to classify signals. To improve the accuracy, individual sensors
may exchange sensing data or sensor results with each other or with a fusion
center (such as in cooperative spectrum sensing). In this paper, distributed
federated learning over a multi-hop wireless network is considered to
collectively train a DNN for signal identification. In distributed federated
learning, each sensor broadcasts its trained model to its neighbors, collects
the DNN models from its neighbors, and aggregates them to initialize its own
model for the next round of training. Without exchanging any spectrum data,
this process is repeated over time such that a common DNN is built across the
network while preserving the privacy associated with signals collected at
different locations. Signal classification accuracy and convergence time are
evaluated for different network topologies (including line, star, ring, grid,
and random networks) and packet loss events. Then, the reduction of
communication overhead and energy consumption is considered with random
participation of sensors in model updates. The results show the feasibility of
extending cooperative spectrum sensing over a general multi-hop wireless
network through federated learning and indicate its robustness to wireless
network effects, thereby sustaining high accuracy with low communication
overhead and energy consumption.


abstract:
  In this paper we presented the Software Testing, AI and Robotics (STAIR)
Learning Lab. STAIR is an initiative started at the University of Innsbruck to
bring robotics, Artificial Intelligence (AI) and software testing into schools.
In the lab physical and virtual learning units are developed in parallel and in
sync with each other. Its core learning approach is based the develop of both a
physical and simulated robotics environment. In both environments AI scenarios
(like traffic sign recognition) are deployed and tested. We present and focus
on our newly designed MiniBot that are both built on hardware which was
designed for educational and research purposes as well as the simulation
environment. Additionally, we describe first learning design concepts and a
showcase scenario (i.e., AI-based traffic sign recognition) with different
exercises which can easily be extended.


title: Fidelity bounds for storage and retrieval of von Neumann measurements

abstract:
  This work examines the problem of learning an unknown single-qubit von
Neumann measurements from a finite number of copies. To obtain a faithful
approximation of the given measurement we are allowed to use it $N$ times. Our
main goal is to estimate an asymptotic behavior of the maximum value of the
average fidelity function $F$ for a general $N \rightarrow 1$ learning scheme.
We obtained results showing that $1 - \frac1N \le F \le 1 -
\Theta\left(\frac{1}{N^2}\right)$. In addition to that, we discovered a
particular class of learning schemes, which we call the pretty good learning
scheme. This scheme, despite its lack of optimality, provides a relatively high
value for $F$, asymptotically behaving as $1 - \frac1N$. Additionally, it
employs a simple storage strategy, which uses only two-qubit entangled memory
states and the learning process is done in parallel. Finally, the fidelity
function calculated for the pretty good learning scheme is uniform over all
single-qubit von Neumann measurements.


title: Statistical Model Criticism of Variational Auto-Encoders

abstract:
  We propose a framework for the statistical evaluation of variational
auto-encoders (VAEs) and test two instances of this framework in the context of
modelling images of handwritten digits and a corpus of English text. Our take
on evaluation is based on the idea of statistical model criticism, popular in
Bayesian data analysis, whereby a statistical model is evaluated in terms of
its ability to reproduce statistics of an unknown data generating process from
which we can obtain samples. A VAE learns not one, but two joint distributions
over a shared sample space, each exploiting a choice of factorisation that
makes sampling tractable in one of two directions (latent-to-data,
data-to-latent). We evaluate samples from these distributions, assessing their
(marginal) fit to the observed data and our choice of prior, and we also
evaluate samples through a pipeline that connects the two distributions
starting from a data sample, assessing whether together they exploit and reveal
latent factors of variation that are useful to a practitioner. We show that
this methodology offers possibilities for model selection qualitatively beyond
intrinsic evaluation metrics and at a finer granularity than commonly used
statistics can offer.


title: VALUE: Understanding Dialect Disparity in NLU

abstract:
  English Natural Language Understanding (NLU) systems have achieved great
performances and even outperformed humans on benchmarks like GLUE and
SuperGLUE. However, these benchmarks contain only textbook Standard American
English (SAE). Other dialects have been largely overlooked in the NLP
community. This leads to biased and inequitable NLU systems that serve only a
sub-population of speakers. To understand disparities in current models and to
facilitate more dialect-competent NLU systems, we introduce the VernAcular
Language Understanding Evaluation (VALUE) benchmark, a challenging variant of
GLUE that we created with a set of lexical and morphosyntactic transformation
rules. In this initial release (V.1), we construct rules for 11 features of
African American Vernacular English (AAVE), and we recruit fluent AAVE speakers
to validate each feature transformation via linguistic acceptability judgments
in a participatory design manner. Experiments show that these new dialectal
features can lead to a drop in model performance.


title:
Benchmarking Apache Arrow Flight -- A wire-speed protocol for data
  transfer, querying and microservices

abstract:
  Moving structured data between different big data frameworks and/or data
warehouses/storage systems often cause significant overhead. Most of the time
more than 80\% of the total time spent in accessing data is elapsed in
serialization/de-serialization step. Columnar data formats are gaining
popularity in both analytics and transactional databases. Apache Arrow, a
unified columnar in-memory data format promises to provide efficient data
storage, access, manipulation and transport. In addition, with the introduction
of the Arrow Flight communication capabilities, which is built on top of gRPC,
Arrow enables high performance data transfer over TCP networks. Arrow Flight
allows parallel Arrow RecordBatch transfer over networks in a platform and
language-independent way, and offers high performance, parallelism and security
based on open-source standards.
  In this paper, we bring together some recently implemented use cases of Arrow
Flight with their benchmarking results. These use cases include bulk Arrow data
transfer, querying subsystems and Flight as a microservice integration into
different frameworks to show the throughput and scalability results of this
protocol. We show that Flight is able to achieve up to 6000 MB/s and 4800 MB/s
throughput for DoGet() and DoPut() operations respectively. On Mellanox
ConnectX-3 or Connect-IB interconnect nodes Flight can utilize upto 95\% of the
total available bandwidth. Flight is scalable and can use upto half of the
available system cores efficiently for a bidirectional communication. For query
systems like Dremio, Flight is order of magnitude faster than ODBC and turbodbc
protocols. Arrow Flight based implementation on Dremio performs 20x and 30x
better as compared to turbodbc and ODBC connections respectively.


title:
Repeatable patterns and the maximum multiplicity of a generator in a
  reduced word

abstract:
  We study the maximum multiplicity $\mathcal{M}(k,n)$ of a simple
transposition $s_k=(k \: k+1)$ in a reduced word for the longest permutation
$w_0=n \: n-1 \: \cdots \: 2 \: 1$, a problem closely related to much previous
work on sorting networks and on the "$k$-sets" problem. After reinterpreting
the problem in terms of monotone weakly separated paths, we show that, for
fixed $k$ and growing $n$, the optimal paths are periodic in a precise sense,
so that \[ \mathcal{M}(k,n)=c_k n + p_k(n) \] for a periodic function $p_k$ and
constant $c_k$. In fact we show that $c_k$ is always rational, and compute
several bounds and exact values for this quantity using "repeatable patterns",
which we introduce.


title:
The impact of the uncertainties in the 12C({\alpha},{\gamma})16O
  reaction rate on the evolution of low- to intermediate-mass stars

abstract:
  One of the largest uncertainties in stellar evolutionary computations is the
accuracy of the considered reaction rates. The 12C(alpha,gamma)16O reaction is
particularly important for the study of low- and intermediate-mass stars as it
determines the final C/O ratio in the core which influences the white dwarf
cooling evolution. Thus, there is a need for a study of how the computations of
white dwarfs and their progenitors that are made to date may be affected by the
uncertainties of the 12C(alpha,gamma)16O reaction rates. In this work we
compute fully evolutionary sequences using the MESA code with initial masses in
the range of 0.90 <= Mi/Msun <= 3.05. We consider different adopted reaction
rates, obtained from the literature, as well as the extreme limits within their
uncertainties. As expected, we find that previous to the core helium burning
stage there are no changes to the evolution of the stars. However, the
subsequent stages are all affected by the uncertainties of the considered
reaction rate. In particular, we find differences to the convective core mass
during the core helium burning stage which may affect pulsation properties of
subdwarfs, the number of thermal pulses during the asymptotic giant branch and
trends between final oxygen abundance in the core and the progenitor masses of
the remnant white dwarfs.


title:
Hierarchical Annotation for Building A Suite of Clinical Natural
  Language Processing Tasks: Progress Note Understanding

abstract:
  Applying methods in natural language processing on electronic health records
(EHR) data is a growing field. Existing corpus and annotation focus on modeling
textual features and relation prediction. However, there is a paucity of
annotated corpus built to model clinical diagnostic thinking, a process
involving text understanding, domain knowledge abstraction and reasoning. This
work introduces a hierarchical annotation schema with three stages to address
clinical text understanding, clinical reasoning, and summarization. We created
an annotated corpus based on an extensive collection of publicly available
daily progress notes, a type of EHR documentation that is collected in time
series in a problem-oriented format. The conventional format for a progress
note follows a Subjective, Objective, Assessment and Plan heading (SOAP). We
also define a new suite of tasks, Progress Note Understanding, with three tasks
utilizing the three annotation stages. The novel suite of tasks was designed to
train and evaluate future NLP models for clinical text understanding, clinical
knowledge representation, inference, and summarization.


title:
First-Order Pontryagin Maximum Principle for Risk-Averse Stochastic
  Optimal Control Problems

abstract:
  In this paper, we derive a set of first-order Pontryagin optimality
conditions for a risk-averse stochastic optimal control problem subject to
final time inequality constraints, and whose cost is a general finite coherent
risk measure. Unlike previous contributions in the literature, our analysis
holds for classical stochastic differential equations driven by standard
Brownian motions. Moreover, it presents the advantages of neither involving
second-order adjoint equations, nor leading to the so-called weak version of
the PMP, in which the maximization condition with respect to the control
variable is replaced by the stationarity of the Hamiltonian.


title: Universal Relations for Neutron Star F-Mode and G-Mode Oscillations

abstract:
  Among the various oscillation modes of neutron stars, f- and g- modes are the
most likely to be ultimately observed in binary neutron star mergers. The
f-mode is known to correlate in normal neutron stars with their tidal
deformability, moment of inertia and quadrupole moment. Using a piecewise
polytropic parameterization scheme to model the uncertain hadronic high-density
EOS and a constant sound-speed scheme to model pure quark matter, we refine
this correlation and show that these universal relations also apply to both
self-bound stars and hybrid stars containing phase transitions. We identify a
novel 1-node branch of the f-mode that occurs in low-mass hybrid stars in a
narrow mass range just beyond the critical mass necessary for a phase
transition to appear. This 1-node branch shows the largest, but still small,
deviations from the universal correlation we have found. The g-mode frequency
only exists in matter with a non-barotropic equation of state involving
temperature, chemical potential or composition, or a phase transition in
barotropic matter. The g-mode therefore could serve as a probe for studying
phase transitions in hybrid stars. In contrast with the f-mode, discontinuity
g-mode frequencies depend strongly on properties of the transition (the density
and the magnitude of the discontinuity) at the transition. Imposing causality
and maximum mass constraints, the g-mode frequency in hybrid stars is found to
have an upper bound of about 1.25 kHz. However, if the sound speed c_s in the
inner core at densities above the phase transition density is restricted to
c_s^2 < c^2/3, the g-mode frequencies can only reach about 0.8 kHz, which are
significantly lower than f-mode frequencies, 1.3-2.8 kHz. Also, g-mode
gravitational wave damping times are extremely long, >10^4 s (10^2 s) in the
inner core with c_s^2< c^{2/3} (c^2), in comparison with the f-mode damping
time, 0.1-1 s.


title: Safe Interactive Industrial Robots using Jerk-based Safe Set Algorithm

abstract:
  The need to increase the flexibility of production lines is calling for
robots to collaborate with human workers. However, existing interactive
industrial robots only guarantee intrinsic safety (reduce collision impact),
but not interactive safety (collision avoidance), which greatly limited their
flexibility. The issue arises from two limitations in existing control software
for industrial robots: 1) lack of support for real-time trajectory
modification; 2) lack of intelligent safe control algorithms with guaranteed
collision avoidance under robot dynamics constraints. To address the first
issue, a jerk-bounded position controller (JPC) was developed previously. This
paper addresses the second limitation, on top of the JPC. Specifically, we
introduce a jerk-based safe set algorithm (JSSA) to ensure collision avoidance
while considering the robot dynamics constraints. The JSSA greatly extends the
scope of the original safe set algorithm, which has only been applied for
second-order systems with unbounded accelerations. The JSSA is implemented on
the FANUC LR Mate 200id/7L robot and validated with HRI tasks. Experiments show
that the JSSA can consistently keep the robot at a safe distance from the human
while executing the designated task.


title: DSGN++: Exploiting Visual-Spatial Relation for Stereo-based 3D Detectors

abstract:
  Camera-based 3D object detectors are welcome due to their wider deployment
and lower price than LiDAR sensors. We revisit the prior stereo modeling DSGN
about the stereo volume constructions for representing both 3D geometry and
semantics. We polish the stereo modeling and propose our approach, DSGN++,
aiming for improving information flow throughout the 2D-to-3D pipeline in the
following three main aspects. First, to effectively lift the 2D information to
stereo volume, we propose depth-wise plane sweeping (DPS) that allows denser
connections and extracts depth-guided features. Second, for better grasping
differently spaced features, we present a novel stereo volume -- Dual-view
Stereo Volume (DSV) that integrates front-view and top-view features and
reconstructs sub-voxel depth in the camera frustum. Third, as the foreground
region becomes less dominant in 3D space, we firstly propose a multi-modal data
editing strategy -- Stereo-LiDAR Copy-Paste, which ensures cross-modal
alignment and improves data efficiency. Without bells and whistles, extensive
experiments in various modality setups on the popular KITTI benchmark show that
our method consistently outperforms other camera-based 3D detectors for all
categories. Code will be released at https://github.com/chenyilun95/DSGN2.


title:
SOMOS: The Samsung Open MOS Dataset for the Evaluation of Neural
  Text-to-Speech Synthesis

abstract:
  In this work, we present the SOMOS dataset, the first large-scale mean
opinion scores (MOS) dataset consisting of solely neural text-to-speech (TTS)
samples. It can be employed to train automatic MOS prediction systems focused
on the assessment of modern synthesizers, and can stimulate advancements in
acoustic model evaluation. It consists of 20K synthetic utterances of the LJ
Speech voice, a public domain speech dataset which is a common benchmark for
building neural acoustic models and vocoders. Utterances are generated from 200
TTS systems including vanilla neural acoustic models as well as models which
allow prosodic variations. An LPCNet vocoder is used for all systems, so that
the samples' variation depends only on the acoustic models. The synthesized
utterances provide balanced and adequate domain and length coverage. We collect
MOS naturalness evaluations on 3 English Amazon Mechanical Turk locales and
share practices leading to reliable crowdsourced annotations for this task.
Baseline results of state-of-the-art MOS prediction models on the SOMOS dataset
are presented, while we show the challenges that such models face when assigned
to evaluate synthetic utterances.


title:
MIGHTEE-HI: The relation between the HI gas in galaxies and the cosmic
  web

abstract:
  We study the 3D axis of rotation (3D spin) of 77 HI galaxies from the
MIGHTEE-HI Early Science observations, and its relation to the filaments of the
cosmic web. For this HI-selected sample, the alignment between the spin axis
and the closest filament ($\lvert \cos \psi \rvert$) is higher for galaxies
closer to the filaments, with $\langle\lvert \cos \psi \rvert\rangle= 0.66 \pm
0.04$ for galaxies $<5$ Mpc from their closest filament compared to
$\langle\lvert \cos \psi \rvert\rangle= 0.37 \pm 0.08$ for galaxies at $5 < d
<10$ Mpc. We find that galaxies with a low HI-to-stellar mass ratio
($\log_{10}(M_{\rm HI}/M_{\star}) < 0.11$) are more aligned with their closest
filaments, with $\langle\lvert \cos \psi \rvert\rangle= 0.58 \pm 0.04$; whilst
galaxies with ($\log_{10}(M_{\rm HI}/M_{\star}) > 0.11$) tend to be
mis-aligned, with $\langle\lvert \cos \psi \rvert\rangle= 0.44 \pm 0.04$. We
find tentative evidence that the spin axis of HI-selected galaxies tend to be
aligned with associated filaments ($d<10$ Mpc), but this depends on the gas
fractions. Galaxies that have accumulated more stellar mass compared to their
gas mass tend towards stronger alignment. Our results suggest that those
galaxies that have accrued high gas fraction with respect to their stellar mass
may have had their spin axis alignment with the filament disrupted by a recent
gas-rich merger, whereas the spin vector for those galaxies in which the
neutral gas has not been strongly replenished through a recent merger tend to
orientate towards alignment with the filament. We also investigate the spin
transition between galaxies with a high HI content and a low HI content at a
threshold of $M_{\mathrm{HI}}\approx 10^{9.5} M_{\odot}$ found in simulations,
however we find no evidence for such a transition with the current data.


title: FFC-SE: Fast Fourier Convolution for Speech Enhancement

abstract:
  Fast Fourier convolution (FFC) is the recently proposed neural operator
showing promising performance in several computer vision problems. The FFC
operator allows employing large receptive field operations within early layers
of the neural network. It was shown to be especially helpful for inpainting of
periodic structures which are common in audio processing. In this work, we
design neural network architectures which adapt FFC for speech enhancement. We
hypothesize that a large receptive field allows these networks to produce more
coherent phases than vanilla convolutional models, and validate this hypothesis
experimentally. We found that neural networks based on Fast Fourier convolution
outperform analogous convolutional models and show better or comparable results
with other speech enhancement baselines.


title: Time Evolution in Quantum Cosmology

abstract:
  The quantum description of time evolution in non-linear gravitational systems
such as cosmological space-times is not well understood. We show, in the
simplified setting of mini-superspace, that time evolution of this system can
be obtained using a gauge fixed path integral, as long as one does not
integrate over proper time. Using this gauge fixed action we can construct a
Hamiltonian in the coherent - or classical - state basis. We show that by
construction the coherent states satisfy the classical dynamical equations of
General Relativity. They do not satisfy the Hamiltonian constraint. A
consequence of this is that the Wheeler-DeWitt equation should not be satisfied
in quantum gravity. Classical states have a natural non-trivial time evolution
since they are not eigenstates of the Hamiltonian. A general feature of the
unconstrained quantum theory of gravity is the prediction of a pressureless
dark matter component of either sign energy density in the classical universe
which may lead to novel phenomenology.


title: Fusing finetuned models for better pretraining

abstract:
  Pretrained models are the standard starting point for training. This approach
consistently outperforms the use of a random initialization. However,
pretraining is a costly endeavour that few can undertake.
  In this paper, we create better base models at hardly any cost, by fusing
multiple existing fine tuned models into one. Specifically, we fuse by
averaging the weights of these models. We show that the fused model results
surpass the pretrained model ones. We also show that fusing is often better
than intertraining.
  We find that fusing is less dependent on the target task. Furthermore, weight
decay nullifies intertraining effects but not those of fusing.


title: Generalized Symmetries in Condensed Matter

abstract:
  Recent advances in our understanding of symmetry in quantum many-body systems
offer the possibility of a generalized Landau paradigm that encompasses all
equilibrium phases of matter. This is a brief and elementary review of some of
these developments.


title: Effective Exposure Amortizing for Fair Top-k Recommendation

abstract:
  Result ranking often affects customer satisfaction as well as the amount of
exposure each product receives in recommendation systems (RecSys). Myopically
maximizing customer satisfaction by ranking products only according to
relevance will lead to unfair distribution of exposure for products, followed
by unfair opportunities and economic gains for product producers. This
unfairness will force producers to leave the system, and discourage new
producers from coming in. Eventually, fewer purchase options would be left for
customers and the overall transaction rates on e-commerce platforms would
decrease. Thus, how to maintain a balance between ranking relevance and
fairness is important to both producers and customers. In this paper, we focus
on the task of exposure fairness in offline recommendation settings. We
demonstrate that existing methods for amortized fairness optimization are
suboptimal for offline recommendation because they fail to utilize the prior
knowledge of customers. We further propose a novel fair recommendation
algorithm to reach a better balance between exposure fairness and
recommendation performance. Extensive experiments on three real-world datasets
demonstrate that our method significantly outperforms the state-of-the-art fair
ranking algorithm in terms of fairness-performance trade off from both
individual level and group level.


title: Analytic Spread and Associated primes of divisorial filtrations

abstract:
  We prove that a classical theorem of McAdam about the analytic spread of an
ideal in a Noetherian local ring is true for divisorial filtrations on a normal
excellent local ring $R$ which is either of equicharacteristic zero or of
dimension $\le 3$. In fact, the proof is valid whenever resolution of
singularities holds.


title:
Non-commutativity and non-inertial effects on a scalar field in a cosmic
  string space-time. Part 1: Klein-Gordon oscillator

abstract:
  We analyse the Klein-Gordon oscillator in a cosmic string space-time and
study the effects stemming from the rotating frame and non-commutativity in
momentum space. We show that the latter mimics a constant magnetic field,
imparting physical interpretation to the setup. The field equation for the
scalar field is solved via separations of variables, and we obtain quantization
of energy and angular momentum. The space-time metric is non-degenerate as long
as the particle is confined within a hard-wall, whose position depends on the
rotation frame velocity and the string mass parameter. We investigate the
energy quantization both for a finite hard-wall (numerical evaluation) and in
the limit of an infinite hard-wall (analytical treatment). We stress the effect
of non-commutativity upon the energy quantization in each case.


title:
Non-commutativity and non-inertial effects on a scalar field in a cosmic
  string space-time. Part 2: Spin-zero Duffin-Kemmer-Petiau-like oscillator

abstract:
  We study the non-inertial effects of a rotating frame on a spin-zero,
Duffin-Kemmer-Petiau (DKP)-like oscillator in a cosmic string space-time with
non-commutative geometry in the momentum space. The spin-zero DKP-like
oscillator is obtained from the Klein-Gordon Lagrangian with a non-standard
prescription for the oscillator coupling. We find that the solutions of the
time-independent radial equation with the non-zero non-commutativity parameter
parallel to the string are related to the confluent hypergeometric function. We
find the quantized energy eigenvalues of the non-commutative oscillator.


title: Investigation of $\Delta^0\Delta^0$ Dibaryon in QCD

abstract:
  We study a hypothetical $\Delta^0\Delta^0$ dibaryon state by means of QCD sum
rule method. We construct a scalar interpolating current to extract the mass
and decay constant of this state taking into account contributions of various
quark, gluon and mixed vacuum condensates. The predictions for the mass and
decay constants are $m_D=2326^{+114}_{-126} ~\mathrm{MeV}$ and
$f_D=2.94^{+0.30}_{-0.34}\times 10^{-4} ~\mathrm{GeV}^7$, respectively. We also
made an estimation about binding energy and size of the $\Delta^0\Delta^0$
dibaryon. The obtained mass value is below the $\Delta^0\Delta^0$ threshold and
may be a good dibaryon candidate for being observed experimentally.


title:
Perceive, Represent, Generate: Translating Multimodal Information to
  Robotic Motion Trajectories

abstract:
  We present Perceive-Represent-Generate (PRG), a novel three-stage framework
that maps perceptual information of different modalities (e.g., visual or
sound), corresponding to a sequence of instructions, to an adequate sequence of
movements to be executed by a robot. In the first stage, we perceive and
pre-process the given inputs, isolating individual commands from the complete
instruction provided by a human user. In the second stage we encode the
individual commands into a multimodal latent space, employing a deep generative
model. Finally, in the third stage we convert the multimodal latent values into
individual trajectories and combine them into a single dynamic movement
primitive, allowing its execution in a robotic platform. We evaluate our
pipeline in the context of a novel robotic handwriting task, where the robot
receives as input a word through different perceptual modalities (e.g., image,
sound), and generates the corresponding motion trajectory to write it, creating
coherent and readable handwritten words.


title: Three isometrically equivalent models of the Finsler-Poincar\'e disk

abstract:
  We present the isometry between the 2-dimensional Funk model and the
Finsler-Poincar\'e disk. Then, we introduce the Finslerian Poincar\'e upper
half plane model, which turns out to be also isometrically equivalent to the
previous models. As application, we state the gapless character of the first
eigenvalue for the aforementioned three spaces.


title: Highlights on Supersymmetry and Exotic Searches at the LHC

abstract:
  The Run 2 data taking period of the Large Hadron Collider (LHC) at CERN in
years 2015-2018 has presented a great opportunity to search for physics beyond
the standard model (BSM). It will be followed by the Run 3 period starting in
2022, and by the High-Luminosity LHC (HL-LHC) era starting in late 2020s, where
the latter promises an unprecedented wealth of physics prospects due to very
high expected integrated luminosity and improved detector features. The ATLAS,
CMS and LHCb experiments pursued a rich physics program in Run 2, and are
already assessing the physics expectations at the HL-LHC era. This report
presents highlights from recent search results and HL-LHC studies on BSM
physics by the ATLAS, CMS and LHCb experiments. Examples will be shown from
model-independent generic searches, searches for supersymmetry, extended Higgs
sectors, and new exotic fermions and bosons.


title:
Interferon-induced transmembrane protein 3 (IFITM3) and its antiviral
  activity

abstract:
  Enveloped viral infections require fusion with cellular membranes for viral
genome entry, occurring only following interaction of viral and cellular
membranes allowing fusion pore formation, by which the virus accesses the
cytoplasm. Here, we focus on interferon-induced transmembrane protein 3
(IFITM3) and its antiviral activity. IFITM3 is predicted to block or stall
viral fusion at an intermediate state, causing viral propagation to fail. After
introducing IFITM3, we describe the generalized lipid membrane fusion pathway
and how it can be stalled, particularly with respect to IFITM3, and current
questions regarding IFITM3's topology. Specific emphasis is placed on IFITM3's
amphipathic a-helix (AAH) 59V-68M, necessary for antiviral activity.
Calculations are reported of hydrophobicity and hydrophobic moment of this
peptide and active site peptides from other membrane-remodeling proteins.
Finally, we discuss the effects of post-translational modifications and
localization, how IFITM3's AAH may block viral fusion, and possible
ramifications of membrane composition.


title:
To Participate Or Not To Participate: An Investigation Of Strategic
  Participation In Standards

abstract:
  Essential functionality in the ICT (Information and Communication Technology)
space draws from standards such as HTTP (IETF RFC 2616, Bluetooth (IEEE 802.15)
and various telecommunication standards (4G, 5G). They have fuelled rapid
growth of ICT sector in the last decades by ensuring interoperability and
consistency in computing environment. Research shows that firms that backed ICT
standards and participated in standards development, have emerged as industry
innovators. Standards development thus clearly has benefits for participating
companies as well as technology development and innovation in general. However,
significant costs are also associated with development of standards and need to
be better understood to support investment in standardization necessary for
todays ICT environment. We present a conceptual model that considers the
potential for market innovation across a standards lifecycle and efficiency
from standardization work, to build a forward-looking decision model that can
guide an organizations standards development activities. We investigate and
formalize motivations that drive firms to participate in standardization,
specifically, changes in market innovation. Our model can serve as a strategic
decision framework to drive assessments of a firms participation in standards
development. We test our model with a use case on an established access control
approach that was standardized more than two decades ago, Role Based Access
Control (RBAC) using historical data. The investigation of the case study shows
that change in market innovation is a significant indicator of success in
standards development and are viable criteria to model a firms decision to
participate (or not to participate) in a specific area of standardization.


title:
Twisted geometry coherent states in all dimensional loop quantum
  gravity: II. Ehrenfest Property

abstract:
  In the preceding paper of this series of articles we constructed the twisted
geometry coherent states in all dimensional loop quantum gravity and
established their peakedness properties. In this paper we establish the
"Ehrenfest property" of these coherent states which are labelled by the twisted
geometry parameters. By this we mean that the expectation values of the
polynomials of the elementary operators as well as the operators which are not
polynomial functions of the elementary operators, reproduce, to zeroth order in
$\hbar$, the values of the corresponding classical functions at the twisted
geometry space point where the coherent state is peaked.


title: Thermal to Visible Image Synthesis under Atmospheric Turbulence

abstract:
  In many practical applications of long-range imaging such as biometrics and
surveillance, thermal imagining modalities are often used to capture images in
low-light and nighttime conditions. However, such imaging systems often suffer
from atmospheric turbulence, which introduces severe blur and deformation
artifacts to the captured images. Such an issue is unavoidable in long-range
imaging and significantly decreases the face verification accuracy. In this
paper, we first investigate the problem with a turbulence simulation method on
real-world thermal images. An end-to-end reconstruction method is then proposed
which can directly transform thermal images into visible-spectrum images by
utilizing natural image priors based on a pre-trained StyleGAN2 network.
Compared with the existing two-steps methods of consecutive turbulence
mitigation and thermal to visible image translation, our method is demonstrated
to be effective in terms of both the visual quality of the reconstructed
results and face verification accuracy. Moreover, to the best of our knowledge,
this is the first work that studies the problem of thermal to visible image
translation under atmospheric turbulence.


title:
On the action of the (2,3,7)-homology sphere group on its space of
  left-orders

abstract:
  We show that the action of the group $\Sigma=\langle a,b,c\mid
a^2=b^3=c^7=abc\rangle$ on its space of left-orders has exactly two minimal
components.


title:
Semantic Sensor Network Ontology based Decision Support System for
  Forest Fire Management

abstract:
  The forests are significant assets for every country. When it gets destroyed,
it may negatively impact the environment, and forest fire is one of the primary
causes. Fire weather indices are widely used to measure fire danger and are
used to issue bushfire warnings. It can also be used to predict the demand for
emergency management resources. Sensor networks have grown in popularity in
data collection and processing capabilities for a variety of applications in
industries such as medical, environmental monitoring, home automation etc.
Semantic sensor networks can collect various climatic circumstances like wind
speed, temperature, and relative humidity. However, estimating fire weather
indices is challenging due to the various issues involved in processing the
data streams generated by the sensors. Hence, the importance of forest fire
detection has increased day by day. The underlying Semantic Sensor Network
(SSN) ontologies are built to allow developers to create rules for calculating
fire weather indices and also the convert dataset into Resource Description
Framework (RDF). This research describes the various steps involved in
developing rules for calculating fire weather indices. Besides, this work
presents a Web-based mapping interface to help users visualize the changes in
fire weather indices over time. With the help of the inference rule, it
designed a decision support system using the SSN ontology and query on it
through SPARQL. The proposed fire management system acts according to the
situation, supports reasoning and the general semantics of the open-world
followed by all the ontologies


title: Multiparticle Collision Dynamics for Ferrofluids

abstract:
  Detailed studies of the intriguing field-dependent dynamics and transport
properties of confined flowing ferrofluids require efficient mesoscopic
simulation methods that account for fluctuating ferrohydrodynamics. Here, we
propose such a new mesoscopic model for the dynamics and flow of ferrofluids,
where we couple the multi-particle collision dynamics method as a solver for
the fluctuating hydrodynamics equations to the stochastic magnetization
dynamics of suspended magnetic nanoparticles. This hybrid model is validated by
reproducing the magnetoviscous effect in Poiseuille flow, obtaining the
rotational viscosity in quantitative agreement with theoretical predictions. We
also illustrate the new method for the benchmark problem of flow around a
square cylinder. Interestingly, we observe that the length of the recirculation
region is increased whereas the drag coefficient is decreased in ferrofluids
when an external magnetic field is applied, compared with the field-free case
at the same effective Reynolds number. The presence of thermal fluctuations and
the flexibility of this particle-based mesoscopic method provides a promising
tool to investigate a broad range of flow phenomena of magnetic fluids and
could also serve as an efficient way to simulate solvent effects when colloidal
particles are immersed in ferrofluids.


title:
Standardized feature extraction from pairwise conflicts applied to the
  train rescheduling problem

abstract:
  We propose a train rescheduling algorithm which applies a standardized
feature selection based on pairwise conflicts in order to serve as input for
the reinforcement learning framework. We implement an analytical method which
identifies and optimally solves every conflict arising between two trains, then
we design a corresponding observation space which features the most relevant
information considering these conflicts. The data obtained this way then
translates to actions in the context of the reinforcement learning framework.
We test our preliminary model using the evaluation metrics of the Flatland
Challenge. The empirical results indicate that the suggested feature space
provides meaningful observations, from which a sensible scheduling policy can
be learned.


title:
Abusive and Threatening Language Detection in Urdu using Supervised
  Machine Learning and Feature Combinations

abstract:
  This paper presents the system descriptions submitted at the FIRE Shared Task
2021 on Urdu's Abusive and Threatening Language Detection Task. This challenge
aims at automatically identifying abusive and threatening tweets written in
Urdu. Our submitted results were selected for the third recognition at the
competition. This paper reports a non-exhaustive list of experiments that
allowed us to reach the submitted results. Moreover, after the result
declaration of the competition, we managed to attain even better results than
the submitted results. Our models achieved 0.8318 F1 score on Task A (Abusive
Language Detection for Urdu Tweets) and 0.4931 F1 score on Task B (Threatening
Language Detection for Urdu Tweets). Results show that Support Vector Machines
with stopwords removed, lemmatization applied, and features vector created by
the combinations of word n-grams for n=1,2,3 produced the best results for Task
A. For Task B, Support Vector Machines with stopwords removed, lemmatization
not applied, feature vector created from a pre-trained Urdu Word2Vec (on word
unigrams and bigrams), and making the dataset balanced using oversampling
technique produced the best results. The code is made available for
reproducibility.


title: Late multimodal fusion for image and audio music transcription

abstract:
  Music transcription, which deals with the conversion of music sources into a
structured digital format, is a key problem for Music Information Retrieval
(MIR). When addressing this challenge in computational terms, the MIR community
follows two lines of research: music documents, which is the case of Optical
Music Recognition (OMR), or audio recordings, which is the case of Automatic
Music Transcription (AMT). The different nature of the aforementioned input
data has conditioned these fields to develop modality-specific frameworks.
However, their recent definition in terms of sequence labeling tasks leads to a
common output representation, which enables research on a combined paradigm. In
this respect, multimodal image and audio music transcription comprises the
challenge of effectively combining the information conveyed by image and audio
modalities. In this work, we explore this question at a late-fusion level: we
study four combination approaches in order to merge, for the first time, the
hypotheses regarding end-to-end OMR and AMT systems in a lattice-based search
space. The results obtained for a series of performance scenarios -- in which
the corresponding single-modality models yield different error rates -- showed
interesting benefits of these approaches. In addition, two of the four
strategies considered significantly improve the corresponding unimodal standard
recognition frameworks.


title:
The 2021 Urdu Fake News Detection Task using Supervised Machine Learning
  and Feature Combinations

abstract:
  This paper presents the system description submitted at the FIRE Shared Task:
"The 2021 Fake News Detection in the Urdu Language". This challenge aims at
automatically identifying Fake news written in Urdu. Our submitted results
ranked fifth in the competition. However, after the result declaration of the
competition, we managed to attain even better results than the submitted
results. The best F1 Macro score achieved by one of our models is 0.6674,
higher than the second-best score in the competition. The result is achieved on
Support Vector Machines (polynomial kernel degree 1) with stopwords removed,
lemmatization applied, and selecting the 20K best features out of 1.557 million
features in total (which were produced by Word n-grams n=1,2,3,4 and Char
n-grams n=2,3,4,5,6). The code is made available for reproducibility.


title: The Self-Optimal-Transport Feature Transform

abstract:
  The Self-Optimal-Transport (SOT) feature transform is designed to upgrade the
set of features of a data instance to facilitate downstream matching or
grouping related tasks. The transformed set encodes a rich representation of
high order relations between the instance features. Distances between
transformed features capture their direct original similarity and their third
party agreement regarding similarity to other features in the set. A particular
min-cost-max-flow fractional matching problem, whose entropy regularized
version can be approximated by an optimal transport (OT) optimization, results
in our transductive transform which is efficient, differentiable, equivariant,
parameterless and probabilistically interpretable. Empirically, the transform
is highly effective and flexible in its use, consistently improving networks it
is inserted into, in a variety of tasks and training schemes. We demonstrate
its merits through the problem of unsupervised clustering and its efficiency
and wide applicability for few-shot-classification, with state-of-the-art
results, and large-scale person re-identification.


title: The Impact of Remote Pair Programming in an Upper-Level CS Course

abstract:
  Pair programming has been highlighted as an active learning technique with
several benefits to students, including increasing participation and improving
outcomes, particularly for female computer science students. However, most of
the literature highlights the effects of pair programming in introductory
courses, where students have varied levels of prior programming experience and
thus may experience related group issues. This work analyzes the effect of pair
programming in an upper-level computer science course, where students have a
more consistent background education, particularly in languages learned and
best practices in coding. Secondly, the effect of remote pair programming on
student outcomes is still an open question and one of increasing importance
with the advent of Covid-19. This work utilized split sections with a control
and treatment group in a large, public university. In addition to comparing
pair programming to individual programming, results were analyzed by modality
(remote vs. in person) and by gender, focusing on how pair programming benefits
female computer science students in confidence, persistence in the major, and
outcomes. We found that pair programming groups scored higher on assignments
and exams, that remote pair programming groups performed as well as in person
groups, and that female students increased their confidence in asking questions
in class and scored 12\% higher in the course when utilizing pair programming.


title: ByT5 model for massively multilingual grapheme-to-phoneme conversion

abstract:
  In this study, we tackle massively multilingual grapheme-to-phoneme
conversion through implementing G2P models based on ByT5. We have curated a G2P
dataset from various sources that covers around 100 languages and trained
large-scale multilingual G2P models based on ByT5. We found that ByT5 operating
on byte-level inputs significantly outperformed the token-based mT5 model in
terms of multilingual G2P. Pairwise comparison with monolingual models in these
languages suggests that multilingual ByT5 models generally lower the phone
error rate by jointly learning from a variety of languages. The pretrained
model can further benefit low resource G2P through zero-shot prediction on
unseen languages or provides pretrained weights for finetuning, which helps the
model converge to a lower phone error rate than randomly initialized weights.
To facilitate future research on multilingual G2P, we make available our code
and pretrained multilingual G2P models at:
https://github.com/lingjzhu/CharsiuG2P.


title:
A Fractal Uncertainty Principle for the Short-Time Fourier Transform and
  Gabor multipliers

abstract:
  We study the fractal uncertainty principle in the joint time-frequency
representation, and we prove a version for the Short-Time Fourier transform
with Gaussian window on the modulation spaces. This can equivalently be
formulated in terms of projection operators on the Bargmann-Fock spaces of
entire functions. Specifically for signals in $L^2(\mathbb{R}^d)$, we obtain
norm estimates of Daubechies' time-frequency localization operator localizing
on porous sets. The proof is based on the maximal Nyquist density of such sets,
and for multidimensional Cantor iterates we derive explicit upper bound
asymptotes. Finally, we translate the fractal uncertainty principle to discrete
Gaussian Gabor multipliers.


title:
Generalized level measure based on a family of conditional aggregation
  operators

abstract:
  Extending the concept of level measure $\mu(\{f\ge a\})$ we introduce a
generalized level measure based on a~family of conditional aggregations
operators. We investigate in detail several basic properties, including
connections with the family of level measures, the generalized survival
function and the transformation of monotone measures to hyperset. Applications
in scientometrics and information science are described.


title:
Bayesian Control Variates for optimal covariance estimation with pairs
  of simulations and surrogates

abstract:
  Predictions of the mean and covariance matrix of summary statistics are
critical for confronting cosmological theories with observations, not least for
likelihood approximations and parameter inference. The price to pay for
accurate estimates is the extreme cost of running $N$-body and hydrodynamics
simulations. Approximate solvers, or surrogates, greatly reduce the
computational cost but can introduce significant biases, for example in the
non-linear regime of cosmic structure growth. We propose "CARPool Bayes", an
approach to solve the inference problem for both the means and covariances
using a combination of simulations and surrogates. Our framework allows
incorporating prior information for the mean and covariance. We derive
closed-form solutions for Maximum A Posteriori covariance estimates that are
efficient Bayesian shrinkage estimators, guarantee positive semi-definiteness,
and can optionally leverage analytical covariance approximations. We discuss
choices of the prior and propose a simple procedure for obtaining optimal prior
hyperparameter values with a small set of test simulations. We test our method
by estimating the covariances of clustering statistics of GADGET-III $N$-body
simulations at redshift $z=0.5$ using surrogates from a 100-1000$\times$ faster
particle-mesh code. Taking the sample covariance from 15,000 simulations as the
truth, and using an empirical Bayes prior with diagonal blocks, our estimator
produces nearly identical Fisher matrix contours for $\Lambda$CDM parameters
using only $15$ simulations of the non-linear dark matter power spectrum. In
this case the number of simulations is so small that the sample covariance
would be degenerate. We show cases where even with a na\"ive prior our method
still improves the estimate. Our framework is applicable to a wide range of
cosmological and astrophysical problems where fast surrogates are available.


title: Urdu Morphology, Orthography and Lexicon Extraction

abstract:
  Urdu is a challenging language because of, first, its Perso-Arabic script and
second, its morphological system having inherent grammatical forms and
vocabulary of Arabic, Persian and the native languages of South Asia. This
paper describes an implementation of the Urdu language as a software API, and
we deal with orthography, morphology and the extraction of the lexicon. The
morphology is implemented in a toolkit called Functional Morphology (Forsberg &
Ranta, 2004), which is based on the idea of dealing grammars as software
libraries. Therefore this implementation could be reused in applications such
as intelligent search of keywords, language training and infrastructure for
syntax. We also present an implementation of a small part of Urdu syntax to
demonstrate this reusability.