title:
GEANT4 simulation study of the response of a miniature radiation
  detector in Galactic Cosmic Rays and inside a spacecraft

abstract:
  The Miniaturized Detector for Application in Space (MIDAS) is a compact
device with dimensions 5 x 5 x 1 cm3 which combines position sensitive Si
detectors and a fast neutrons spectrometer. MIDAS is developed with purpose to
act as a linear energy transfer (LET) spectrometer for the charged particles
and measure dose and dose equivalent from both charged particles and neutrons.
It is based on fully depleted monolithic active Si pixel sensors for the
charged track and energy deposition measurements, while a plastic scintillator
read out by a silicon photomultiplier is used to determine energy depositions
from fast neutrons. A simulation study of the detector response in galactic
cosmic ray (GCR) radiation fields with the aid of GEANT4 has been performed.
Energy depositions and hit pixel addresses have been used to reconstruct tracks
and calculate LET spectra. A method to calculate $LET\infty$ in water from the
measured LET has been elaborated. Dose rate in water and dose equivalent rate
have been calculated. The energy and particle composition of the radiation
field produced by the interaction of GCR with the Al walls of a spacecraft
model has been determined and the response of MIDAS in this radiation field has
been investigated.


title: Simple Models and Biased Forecasts

abstract:
  This paper proposes a general framework in which agents are constrained to
use simple time-series models to forecast economic variables and characterizes
the resulting bias in the agents' forecasts. It considers agents who can only
entertain state-space models with no more than d states, where d measures the
agents' cognitive abilities. Agents' models are otherwise unrestricted a priori
and disciplined endogenously by maximizing the fit to the true process. When
the true process does not have a d-state representation, agents end up with
misspecified models and biased forecasts. If the true process satisfies an
ergodicity assumption, the bias manifests itself as persistence bias: a
tendency to attend to the most persistent observables at the expense of less
persistent ones. The bias causes agents' foreword-looking decisions to mimic
the dynamics of backward-looking, persistent variables in the economy. It also
dampens the response of agents' actions to shocks and leads to additional
co-movements between various choices. The paper then proceeds to study the
implications of the theory in the context of three calibrated workhorse macro
models: the new-Keynesian, real business cycle, and
Diamond--Mortensen--Pissarides models. In each case, constraining agents to use
simple models brings the model's predictions more in line with the data,
without adding any parameters other than the integer d.


title:
Convex Programs and Lyapunov Functions for Reinforcement Learning: A
  Unified Perspective on the Analysis of Value-Based Methods

abstract:
  Value-based methods play a fundamental role in Markov decision processes
(MDPs) and reinforcement learning (RL). In this paper, we present a unified
control-theoretic framework for analyzing valued-based methods such as value
computation (VC), value iteration (VI), and temporal difference (TD) learning
(with linear function approximation). Built upon an intrinsic connection
between value-based methods and dynamic systems, we can directly use existing
convex testing conditions in control theory to derive various convergence
results for the aforementioned value-based methods. These testing conditions
are convex programs in form of either linear programming (LP) or semidefinite
programming (SDP), and can be solved to construct Lyapunov functions in a
straightforward manner. Our analysis reveals some intriguing connections
between feedback control systems and RL algorithms. It is our hope that such
connections can inspire more work at the intersection of system/control theory
and RL.


title:
First evidence for off-shell production of the Higgs boson and
  measurement of its width

abstract:
  The first evidence for off-shell Higgs production is reported in the final
state with two Z bosons decaying into either four charged leptons (muons or
electrons), or two charged leptons and two neutrinos, and a measurement of the
Higgs boson width is performed. Results are based on data from the CMS
experiment at the LHC at a center-of-mass energy of 13 TeV, corresponding to an
integrated luminosity of up to 140 fb$^{-1}$. The total rate of off-shell Higgs
boson production beyond the Z boson pair production threshold, relative to its
standard model expectation, is constrained to the interval [0.0061, 2.0] at 95%
confidence level. The scenario with no off-shell production is excluded at
99.97% confidence level (3.6 standard deviations). The width of the Higgs boson
is extracted as $\Gamma_{\mathrm{H}}$ = 3.2$_{-1.7}^{+2.4}$ MeV, in agreement
with the standard model expectation of 4.1 MeV. The data are also used to set
new constraints on anomalous Higgs boson couplings to W and Z boson pairs.


title: Do Gradient Inversion Attacks Make Federated Learning Unsafe?

abstract:
  Federated learning (FL) allows the collaborative training of AI models
without needing to share raw data. This capability makes it especially
interesting for healthcare applications where patient and data privacy is of
utmost concern. However, recent works on the inversion of deep neural networks
from model gradients raised concerns about the security of FL in preventing the
leakage of training data. In this work, we show that these attacks presented in
the literature are impractical in real FL use-cases and provide a new baseline
attack that works for more realistic scenarios where the clients' training
involves updating the Batch Normalization (BN) statistics. Furthermore, we
present new ways to measure and visualize potential data leakage in FL. Our
work is a step towards establishing reproducible methods of measuring data
leakage in FL and could help determine the optimal tradeoffs between
privacy-preserving techniques, such as differential privacy, and model accuracy
based on quantifiable metrics.


title: Hedonic Games and Treewidth Revisited

abstract:
  We revisit the complexity of the well-studied notion of Additively Separable
Hedonic Games (ASHGs). Such games model a basic clustering or coalition
formation scenario in which selfish agents are represented by the vertices of
an edge-weighted digraph $G=(V,E)$, and the weight of an arc $uv$ denotes the
utility $u$ gains by being in the same coalition as $v$. We focus on (arguably)
the most basic stability question about such a game: given a graph, does a Nash
stable solution exist and can we find it efficiently?
  We study the (parameterized) complexity of ASHG stability when the underlying
graph has treewidth $t$ and maximum degree $\Delta$. The current best FPT
algorithm for this case was claimed by Peters [AAAI 2016], with time complexity
roughly $2^{O(\Delta^5t)}$. We present an algorithm with parameter dependence
$(\Delta t)^{O(\Delta t)}$, significantly improving upon the parameter
dependence on $\Delta$ given by Peters, albeit with a slightly worse dependence
on $t$. Our main result is that this slight performance deterioration with
respect to $t$ is actually completely justified: we observe that the previously
claimed algorithm is incorrect, and that in fact no algorithm can achieve
dependence $t^{o(t)}$ for bounded-degree graphs, unless the ETH fails. This,
together with corresponding bounds we provide on the dependence on $\Delta$ and
the joint parameter establishes that our algorithm is essentially optimal for
both parameters, under the ETH.
  We then revisit the parameterization by treewidth alone and resolve a
question also posed by Peters by showing that Nash Stability remains strongly
NP-hard on stars under additive preferences. Nevertheless, we also discover an
island of mild tractability: we show that Connected Nash Stability is solvable
in pseudo-polynomial time for constant $t$, though with an XP dependence on $t$
which, as we establish, cannot be avoided.


title:
Role of the companion lensing galaxy in the CLASS gravitational lens
  B1152+199

abstract:
  We reinvestigate the Cosmic Lens All-Sky Survey (CLASS) gravitational lens
B1152+199 using archived Hubble Space Telescope (HST) data and Very Long
Baseline Interferometry (VLBI) data. A consistent luminosity ratio within
effective radius between the host galaxy and the X-galaxy is measured from HST
tri-band images, which leads to a mass ratio between the two galaxies as
$r_b\sim 2$. To determine the role of the X-galaxy in the lens system, we
modelled the dual-lens system with constraints from the VLBI-resolved jet
components and the HST images. The 8.4-GHz global-VLBI data currently provide
the most stringent constraints to the mass model, especially to the radial
power-law slope. The optimized models for this two-image three-component radio
lens favour a steeper-than-isothermal inner slope. The jet bending in image B
was also investigated and it turned out to be rather a misalignment than a
curvature. The goodness of fit indicates that the role of the X-galaxy is
crucial in the lens system if three pairs of resolved jet components are to be
fitted. When we imported the optimal model from radio constraints to optical
modelling with the HST tri-band data, the optimization kept the consistency of
the optimal model and successfully reproduced the features observed in the HST
images. This implies that the diffuse emission discovered in the HST images is
actually a detection of the secondary lensing effects from the companion lens.


title:
Nonsymmorphic Symmetry-Protected Band Crossings in a Square-Net Metal
  PtPb$_4$

abstract:
  Topological semimetals with symmetry-protected band crossings have emerged as
a rich landscape to explore intriguing electronic phenomena. Nonsymmorphic
symmetries in particular have been shown to play an important role in
protecting the crossings along a line (rather than a point) in momentum space.
Here we report experimental and theoretical evidence for Dirac nodal line
crossings along the Brillouin zone boundaries in PtPb$_4$, arising from the
nonsymmorphic symmetry of its crystal structure. Interestingly, while the nodal
lines would remain gapless in the absence of spin-orbit coupling (SOC), the SOC
in this case plays a detrimental role to topology by lifting the band
degeneracy everywhere except at a set of isolated points. Nevertheless, the
nodal line is observed to have a bandwidth much smaller than that found in
density functional theory (DFT). Our findings reveal PtPb$_4$ to be a material
system with narrow crossings approximately protected by non-symmorhpic
crystalline symmetries.


title:
The X-ray spectral-timing contribution of the stellar wind in the hard
  state of Cyg X-1

abstract:
  The clumpy stellar wind from the companion star in high mass X-ray binaries
causes variable, partial absorption of the emission from the X-ray source. We
studied XMM-Newton observations from the 7.22 d-long "Cyg X-1 Hard state
Observations of a Complete Binary Orbit in X-rays" (CHOCBOX) monitoring
campaign, in order to constrain the effects of the stellar wind on the
short-timescale X-ray spectral-timing properties of the source. We find these
properties to change significantly in the presence of the wind. In particular,
the longest sampled timescales (corresponding to temporal frequencies of
$\nu\sim$ 0.1-1 Hz) reveal an enhancement of the fractional variability power,
while on the shortest sampled timescales ($\nu\sim$ 1-10 Hz) the variability is
suppressed. In addition, we observe a reduction (by up to a factor of $\sim$
1.8) of the otherwise high coherence between soft and hard band light curves,
as well as of the amplitude of the hard X-ray lags intrinsic to the X-ray
continuum. The observed increase of low frequency variability power can be
explained in terms of variations of the wind column density as a consequence of
motions of the intervening clumps. In this scenario (and assuming a terminal
velocity of $v_{\infty}=2400\ {\rm km\ s^{-1}}$), we obtain an estimate of $l
\sim$ 0.5-1.5 $\times 10^{-4} R_{\ast}$ for the average radial size of a clump.
On the other hand, we suggest the behaviour at high frequencies to be due to
scattering in an optically thicker medium, possibly formed by collision of the
stellar wind with the edge of the disc.


title: Accelerating the Inference of the Exa.TrkX Pipeline

abstract:
  Recently, graph neural networks (GNNs) have been successfully used for a
variety of particle reconstruction problems in high energy physics, including
particle tracking. The Exa.TrkX pipeline based on GNNs demonstrated promising
performance in reconstructing particle tracks in dense environments. It
includes five discrete steps: data encoding, graph building, edge filtering,
GNN, and track labeling. All steps were written in Python and run on both GPUs
and CPUs. In this work, we accelerate the Python implementation of the pipeline
through customized and commercial GPU-enabled software libraries, and develop a
C++ implementation for inferencing the pipeline. The implementation features an
improved, CUDA-enabled fixed-radius nearest neighbor search for graph building
and a weakly connected component graph algorithm for track labeling. GNNs and
other trained deep learning models are converted to ONNX and inferenced via the
ONNX Runtime C++ API. The complete C++ implementation of the pipeline allows
integration with existing tracking software. We report the memory usage and
average event latency tracking performance of our implementation applied to the
TrackML benchmark dataset.


title: Tensor Moments of Gaussian Mixture Models: Theory and Applications

abstract:
  Gaussian mixture models (GMMs) are fundamental tools in statistical and data
sciences. We study the moments of multivariate Gaussians and GMMs. The $d$-th
moment of an $n$-dimensional random variable is a symmetric $d$-way tensor of
size $n^d$, so working with moments naively is assumed to be prohibitively
expensive for $d>2$ and larger values of $n$. In this work, we develop theory
and numerical methods for \emph{implicit computations} with moment tensors of
GMMs, reducing the computational and storage costs to $\mathcal{O}(n^2)$ and
$\mathcal{O}(n^3)$, respectively, for general covariance matrices, and to
$\mathcal{O}(n)$ and $\mathcal{O}(n)$, respectively, for diagonal ones. We
derive concise analytic expressions for the moments in terms of symmetrized
tensor products, relying on the correspondence between symmetric tensors and
homogeneous polynomials, and combinatorial identities involving Bell
polynomials. The primary application of this theory is to estimating GMM
parameters (means and covariances) from a set of observations, when formulated
as a moment-matching optimization problem. If there is a known and common
covariance matrix, we also show it is possible to debias the data observations,
in which case the problem of estimating the unknown means reduces to symmetric
CP tensor decomposition. Numerical results validate and illustrate the
numerical efficiency of our approaches. This work potentially opens the door to
the competitiveness of the method of moments as compared to expectation
maximization methods for parameter estimation of GMMs.


title:
Efficient quantitative assessment of robot swarms: coverage and
  targeting L\'{e}vy strategies

abstract:
  Biologically inspired strategies have long been adapted to swarm robotic
systems, including biased random walks, reaction to chemotactic cues and
long-range coordination. In this paper we apply analysis tools developed for
modeling biological systems, such as continuum descriptions, to the efficient
quantitative characterization of robot swarms. As an illustration, both
Brownian and L\'{e}vy strategies with a characteristic long-range movement are
discussed. As a result we obtain computationally fast methods for the
optimization of robot movement laws to achieve a prescribed collective
behavior. We show how to compute performance metrics like coverage and hitting
times, and illustrate the accuracy and efficiency of our approach for area
coverage and search problems. Comparisons between the continuum model and
robotic simulations confirm the quantitative agreement and speed up of our
approach. Results confirm and quantify the advantage of L\'{e}vy strategies
over Brownian motion for search and area coverage problems in swarm robotics.


title:
Strong spiral arms drive secular growth of pseudo bulges in disk
  galaxies

abstract:
  Spiral-driven instabilities may drive gas inflow to enhance central star
formation in disk galaxies. We investigate this hypothesis using the Sloan
Digital Sky Survey (SDSS) in a sample of 2779 nearby unbarred star-forming
main-sequence spiral galaxies. The strength of spiral arms is quantified by
their average Fourier amplitude relative to the axisymmetric disk. The star
formation properties in the central 1--3\,kpc region were derived from the SDSS
spectra. We show that galaxies with stronger spiral arms not only tend to have
more intense central specific star formation rate (sSFR), larger Balmer
absorption line index, and lower 4000-\AA\ break strength, but also have
enhanced central sSFR relative to sSFR measured for the whole galaxy. This link
is independent of redshift, stellar mass, surface density, and concentration.
There is a lack of evidence for strong spiral arms being associated with a
significant fraction of starburst or post-starburst galaxies, implying that the
spiral-induced central star formation is likely continuous rather than bursty.
We also show that stronger spiral arms tend to have an increasing fraction of
pseudo bulges, a relatively unchanged fraction of star-forming classical
bulges, and a decreasing fraction of quenched classical bulges. Moreover, the
concentration of galaxies hosting pseudo bulges mildly increases with stronger
spiral arms, implying that spirals help pseudo bulges grow. The connection
between spirals and the bulge type is partly attributed to the suppression of
spirals by classical bulges and partly to the enhanced central star formation
driven by spirals. We explain our results in a picture where spiral arms
transport cold gas inward to trigger continuous central star formation, which
facilitates the build-up of pseudo bulges. Spiral arms thus play a role in the
secular evolution of disk galaxies.


title:
Universal diamond edge Raman scale to 0.5 terapascal: The implication to
  metallization of hydrogen

abstract:
  The recent progress in generating static pressures up to terapascal values
opens opportunities for studying novel materials with unusual properties, such
as metallization of hydrogen and high-temperature superconductivity. However,
an evaluation of pressure above ~0.3 terapascal is a challenge. We report a
universal high-pressure scale up to ~0.5 terapascal, based on the shift of the
Raman edge of stressed diamond anvils correlated with the equation of state of
Au and does not require an additional pressure sensor. According to the new
scale, the pressure values are substantially lower by 20% at ~0.5 terapascal
compared to the extrapolation of the existing scales. We compared the available
data of H2 at the highest static pressures. We showed that the onset of the
proposed metallization of molecular hydrogen reported by different groups is
consistent when corrected with the new scale and can be compared with various
theoretical predictions.


title: Slicing Aided Hyper Inference and Fine-tuning for Small Object Detection

abstract:
  Detection of small objects and objects far away in the scene is a major
challenge in surveillance applications. Such objects are represented by small
number of pixels in the image and lack sufficient details, making them
difficult to detect using conventional detectors. In this work, an open-source
framework called Slicing Aided Hyper Inference (SAHI) is proposed that provides
a generic slicing aided inference and fine-tuning pipeline for small object
detection. The proposed technique is generic in the sense that it can be
applied on top of any available object detector without any fine-tuning.
Experimental evaluations, using object detection baselines on the Visdrone and
xView aerial object detection datasets show that the proposed inference method
can increase object detection AP by 6.8%, 5.1% and 5.3% for FCOS, VFNet and
TOOD detectors, respectively. Moreover, the detection accuracy can be further
increased with a slicing aided fine-tuning, resulting in a cumulative increase
of 12.7%, 13.4% and 14.5% AP in the same order. Proposed technique has been
integrated with Detectron2, MMDetection and YOLOv5 models and it is publicly
available at https://github.com/obss/sahi.git .


title:
Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation
  Practices for Generated Text

abstract:
  Evaluation practices in natural language generation (NLG) have many known
flaws, but improved evaluation approaches are rarely widely adopted. This issue
has become more urgent, since neural NLG models have improved to the point
where they can often no longer be distinguished based on the surface-level
features that older metrics rely on. This paper surveys the issues with human
and automatic model evaluations and with commonly used datasets in NLG that
have been pointed out over the past 20 years. We summarize, categorize, and
discuss how researchers have been addressing these issues and what their
findings mean for the current state of model evaluations. Building on those
insights, we lay out a long-term vision for NLG evaluation and propose concrete
steps for researchers to improve their evaluation processes. Finally, we
analyze 66 NLG papers from recent NLP conferences in how well they already
follow these suggestions and identify which areas require more drastic changes
to the status quo.


title: Minimum Action Method for Nonequilibrium Phase Transitions

abstract:
  First-order nonequilibrium phase transitions are challenging to analyze
because they occur via activated processes through transition states that are
not saddle points on a free energy landscape -- rather, no such landscape
exists when the system's dynamics is not in detailed-balance. In some
situations the path of these processes can be characterized as the minimizer of
an action, whose minimum value can be used in a nonequilibrium generalization
of the Arrhenius law. Here, a wide range of systems of this type is analyzed
and efficient numerical tools for the minimization of their action are
developed. These tools are general enough to be transportable to many
situations of interest. Their applicability is illustrated on the study of
first-order phase transitions in two spatially-extended nonequilibrium systems:
a modified Ginzburg-Landau equation with a chemical potential which is
non-gradient, and a reaction-diffusion network based on the Schl\"ogl model.
The phase diagrams of both systems are calculated as a function of their
control parameters, and the paths of the transition, including their critical
nuclei, are identified. These results clearly demonstrate the nonequilbrium
nature of the transitions, with differing forward and backward paths.


title:
Matrix quantum groups as matrix product operator representations of Lie
  groups

abstract:
  We demonstrate that the matrix quantum group $SL_q(2)$ gives rise to
nontrivial matrix product operator representations of the Lie group $SL(2)$,
providing an explicit characterization of the nontrivial global $SU(2)$
symmetry of the XXZ model with periodic boundary conditions. The matrix product
operators are non-injective and their set is closed under multiplication. This
allows to calculate the fusion tensors acting on the virtual or quantum degrees
of freedom and to obtain the recoupling coefficients, which satisfy a type of
pentagon relation. We argue that the combination of this data with the well
known $q$-deformed Clebsch-Gordan coefficients and 6j-symbols is consistent
with a description of this quantum group in terms of bimodule categories.

categories: cond-mat.stat-mech math-ph math.MP quant-ph


title: Equivariant Kazhdan-Lusztig theory of paving matroids

abstract:
  We study the way in which equivariant Kazhdan-Lusztig polynomials,
equivariant inverse Kazhdan-Lusztig polynomials, and equivariant Z-polynomials
of matroids change under the operation of relaxation of a collection of
stressed hyperplanes. This allows us to compute these polynomials for arbitrary
paving matroids, which we do in a number of examples, including various
matroids associated with Steiner systems that admit actions of Mathieu groups.


title:
A simple proof that the $hp$-FEM does not suffer from the pollution
  effect for the constant-coefficient full-space Helmholtz equation

abstract:
  In $d$ dimensions, approximating an arbitrary function oscillating with
frequency $\lesssim k$ requires $\sim k^d$ degrees of freedom. A numerical
method for solving the Helmholtz equation (with wavenumber $k$) suffers from
the pollution effect if, as $k\to \infty$, the total number of degrees of
freedom needed to maintain accuracy grows faster than this natural threshold.
  While the $h$-version of the finite element method (FEM) (where accuracy is
increased by decreasing the meshwidth $h$ and keeping the polynomial degree $p$
fixed) suffers from the pollution effect, the celebrated papers [Melenk, Sauter
2010], [Melenk, Sauter 2011], [Esterhazy, Melenk 2012], and [Melenk, Parsania,
Sauter 2013] showed that the $hp$-FEM (where accuracy is increased by
decreasing the meshwidth $h$ and increasing the polynomial degree $p$) applied
to a variety of constant-coefficient Helmholtz problems does not suffer from
the pollution effect.
  The heart of the proofs of these results is a PDE result splitting the
solution of the Helmholtz equation into "high" and "low" frequency components.
In this expository paper we prove this splitting for the constant-coefficient
Helmholtz equation in full space (i.e., in $\mathbb{R}^d$) using only
integration by parts and elementary properties of the Fourier transform; this
is in contrast to the proof for this set-up in [Melenk, Sauter 2010] which uses
somewhat-involved bounds on Bessel and Hankel functions. The proof in this
paper is motivated by the recent proof in [Lafontaine, Spence, Wunsch 2020] of
this splitting for the variable-coefficient Helmholtz equation in full space;
indeed, the proof in [Lafontaine, Spence, Wunsch 2020] uses more-sophisticated
tools that reduce to the elementary ones above for constant coefficients.


title:
Long-lived fermionic Feshbach molecules with tunable $p$-wave
  interactions

abstract:
  Ultracold fermionic Feshbach molecules are promising candidates for exploring
quantum matter with strong $p$-wave interactions, however, their lifetimes were
measured to be short. Here, we characterize the $p$-wave collisions of
ultracold fermionic $^{23}\mathrm{Na}^{40}\mathrm{K}$ Feshbach molecules for
different scattering lengths and temperatures. By increasing the binding energy
of the molecules, the two-body loss coefficient reduces by three orders of
magnitude leading to a second-long lifetime, 20 times longer than that of
ground-state molecules. We exploit the scaling of elastic and inelastic
collisions with the scattering length and temperature to identify a regime
where the elastic collisions dominate over the inelastic ones allowing the
molecular sample to thermalize. Our work provides a benchmark for four-body
calculations of molecular collisions and is essential for producing a
degenerate Fermi gas of Feshbach molecules.


title: Semi-Equivariant GNN Architectures for Jet Tagging

abstract:
  Composing Graph Neural Networks (GNNs) of operations that respect physical
symmetries has been suggested to give better model performance with a smaller
number of learnable parameters. However, real-world applications, such as in
high energy physics have not born this out. We present the novel architecture
VecNet that combines both symmetry-respecting and unconstrained operations to
study and tune the degree of physics-informed GNNs. We introduce a novel
metric, the \textit{ant factor}, to quantify the resource-efficiency of each
configuration in the search-space. We find that a generalized architecture such
as ours can deliver optimal performance in resource-constrained applications.


title:
Symbiotic joint operation of quantum and classical coherent
  communications

abstract:
  We report successful joint operation of quantum and classical communications
with shared hardware. Leveraging information learned from the classical DSP,
low-noise quantum communications (0.009 SNU at 15 km) compatible with 15 Mbit/s
QKD is demonstrated.


title: Triangular-Grid Billiards and Plabic Graphs

abstract:
  Given a polygon $P$ in the triangular grid, we obtain a permutation $\pi_P$
via a natural billiards system in which beams of light bounce around inside of
$P$. The different cycles in $\pi_P$ correspond to the different trajectories
of light beams. We prove that \[\text{area}(P)\geq
6\text{cyc}(P)-6\quad\text{and}\quad\text{perim}(P)\geq\frac{7}{2}\text{cyc}(P)-\frac{3}{2},\]
where $\text{area}(P)$ and $\text{perim}(P)$ are the (appropriately normalized)
area and perimeter of $P$, respectively, and $\text{cyc}(P)$ is the number of
cycles in $\pi_P$. The inequality concerning $\text{area}(P)$ is tight, and we
characterize the polygons $P$ satisfying $\text{area}(P)=6\text{cyc}(P)-6$.
These results can be reformulated in the language of Postnikov's plabic graphs
as follows. Let $G$ be a connected reduced plabic graph with essential
dimension $2$. Suppose $G$ has $n$ marked boundary points and $v$ (internal)
vertices, and let $c$ be the number of cycles in the trip permutation of $G$.
Then we have \[v\geq 6c-6\quad\text{and}\quad n\geq\frac{7}{2}c-\frac{3}{2}.\]


title: Stochastic models of Jaya and semi-steady-state Jaya algorithms

abstract:
  We build stochastic models for analyzing Jaya and semi-steady-state Jaya
algorithms. The analysis shows that for semi-steady-state Jaya (a) the maximum
expected value of the number of worst-index updates per generation is a paltry
1.7 regardless of the population size; (b) regardless of the population size,
the expectation of the number of best-index updates per generation decreases
monotonically with generations; (c) exact upper bounds as well as asymptotics
of the expected best-update counts can be obtained for specific distributions;
the upper bound is 0.5 for normal and logistic distributions, $\ln 2$ for the
uniform distribution, and $e^{-\gamma} \ln 2$ for the exponential distribution,
where $\gamma$ is the Euler-Mascheroni constant; the asymptotic is $e^{-\gamma}
\ln 2$ for logistic and exponential distributions and $\ln 2$ for the uniform
distribution (the asymptotic cannot be obtained analytically for the normal
distribution). The models lead to the derivation of computational complexities
of Jaya and semi-steady-state Jaya. The theoretical analysis is supported with
empirical results on a benchmark suite. The insights provided by our stochastic
models should help design new, improved population-based search/optimization
heuristics.


title: Alignment Performance of FSOC in Stratosphere and to the Ground Station

abstract:
  Airborne platforms, such as drones, balloons, and aerostats, have recently
gained considerable interest in the communication sector. Free-space optical
communication (FSOC) systems can deliver information wirelessly at high data
rates (above 1 Gbps) using compact and lightweight optical terminals. Thus,
airborne FSOC systems have been a recent subject of interest and activity,
including emerging projects such as Google Loon and Facebook Aquila. One of
major technical challenges of FSOC system is the stringent requirement of
pointing, acquisition, and tracking (PAT) capability to ensure the reliable
transmission between the transmitter and receiver, due to narrow beam width and
movement of airborne platforms. By identifying and validating improvement
techniques dealing with this issue, we developed simple models of propeller and
wind induced vibrations and investigated the effect of those vibrations on the
performance of FSOC systems operating in the stratosphere.


title: Prototyping a Virtual Agent for Pre-school English Teaching

abstract:
  This paper describes a case study and the insights gained from prototyping an
Intelligent Virtual Agent (IVA) for English vocabulary building for
Spanish-speaking preschool children. After an initial exploration to evaluate
the feasibility of developing an IVA, we followed a Human-Centered Design (HCD)
approach to create a prototype. We report on the multidisciplinary process used
that incorporated two well-known educative concepts: gamification and
story-telling as the main components for engagement. Our results suggest that a
multidisciplinary approach to developing an educational IVA is effective. We
report on the relevant aspects of the ideation and design processes that
informed the vision and mission of the project.


title:
Theoretical Investigation of Structural, Electronic Properties and
  Half-Metallic Ferromagnetism in Ti doped CaS

abstract:
  In this research paper, we investigated the structural, electronic, and
magnetic features of titanium atom substituting calciumatom in rock salt
structure of CaS to explore the new dilute magnetic semiconductor compounds.
The calculations are carried out using the full potential linearized augmented
plane wave (FP-LAPW) method based on spin-polarized density functional theory,
implemented in WIEN2k code. The generalized gradient approximation and
Tran-Balaha modified Becke-Johnson exchange potential. The stability of Ti
doped CaS in ferromagnetic state is provided by the total energy released from
the optimized structures and defect formation energies. The classical model of
Heisenberg is employed to estimate Curie temperature of these compounds. It is
found that the room temperature ferromagnetism is achieved at low
concentrations. The studied materials exhibit half metallic ferromagnetic
demeanor. The half metallic gaps (GHM) are the extremely significant factors to
consider for spintronic applications. The insertion of impurity significantly
decreased the value of GHM due the broadening of 3d Ti states in the gap of the
minority spin. Furthermore, to evaluate the effects of the exchange splitting
process, the pd exchange splitting and the exchange constants are predicted.


title:
Towards Best Practice of Interpreting Deep Learning Models for EEG-based
  Brain Computer Interfaces

abstract:
  Understanding deep learning models is important for EEG-based brain-computer
interface (BCI), since it not only can boost trust of end users but also
potentially shed light on reasons that cause a model to fail. However, deep
learning interpretability has not yet raised wide attention in this field. It
remains unknown how reliably existing interpretation techniques can be used and
to which extent they can reflect the model decisions. In order to fill this
research gap, we conduct the first quantitative evaluation and explore the best
practice of interpreting deep learning models designed for EEG-based BCI. We
design metrics and test seven well-known interpretation techniques on benchmark
deep learning models. Results show that methods of GradientInput, DeepLIFT,
integrated gradient, and layer-wise relevance propagation (LRP) have similar
and better performance than saliency map, deconvolution and guided
backpropagation methods for interpreting the model decisions. In addition, we
propose a set of processing steps that allow the interpretation results to be
visualized in an understandable and trusted way. Finally, we illustrate with
samples on how deep learning interpretability can benefit the domain of
EEG-based BCI. Our work presents a promising direction of introducing deep
learning interpretability to EEG-based BCI.


title: Consensus Division in an Arbitrary Ratio

abstract:
  We consider the problem of partitioning a line segment into two subsets, so
that $n$ finite measures all has the same ratio of values for the subsets.
Letting $\alpha\in[0,1]$ denote the desired ratio, this generalises the
PPA-complete consensus-halving problem, in which $\alpha=\frac{1}{2}$. It is
known that for any $\alpha$, there exists a solution using $2n$ cuts of the
segment. Here we show that if $\alpha$ is irrational, that upper bound is
almost optimal. We also obtain bounds that are nearly exact for a large subset
of rational values $\alpha$. On the computational side, we explore its
dependence on the number of cuts available. More specifically,
  1. when using the minimal number of cuts for each instance is required, the
problem is NP-hard for any $\alpha$;
  2. for a large subset of rational $\alpha = \frac{\ell}{k}$, when
$\frac{k-1}{k} \cdot 2n$ cuts are available, the problem is in the Turing
closure of PPA-$k$;
  3. when $2n$ cuts are allowed, the problem belongs to PPA for any $\alpha$;
furthermore, the problem belong to PPA-$p$ for any prime $p$ if $2(p-1)\cdot
\frac{\lceil p/2 \rceil}{\lfloor p/2 \rfloor} \cdot n$ cuts are available.


title: Minimax in Geodesic Metric Spaces: Sion's Theorem and Algorithms

abstract:
  Determining whether saddle points exist or are approximable for
nonconvex-nonconcave problems is usually intractable. We take a step towards
understanding certain nonconvex-nonconcave minimax problems that do remain
tractable. Specifically, we study minimax problems cast in geodesic metric
spaces, which provide a vast generalization of the usual convex-concave saddle
point problems. The first main result of the paper is a geodesic metric space
version of Sion's minimax theorem; we believe our proof is novel and
transparent, as it relies on Helly's theorem only. In our second main result,
we specialize to geodesically complete Riemannian manifolds: we devise and
analyze the complexity of first-order methods for smooth minimax problems.


title: Implications of a holographic density of states on inflation

abstract:
  There is theoretical evidence that the number of degrees of freedom in
quantum fields decreases as one studies them at extremely short distances. This
emerges from the study of entropy of black holes, as well as from holographic
theories in AdS geometries. Presumably a theory of quantum gravity will provide
an explicit description of how the number of degrees of freedom thin out as one
studies high energy scales.
  We do not have a comprehensive theory of how such a thinning of degrees of
freedom would occur. It is likely that there might be residual (and measurable)
effects at larger length scales, though this might be significant only near the
Planck scale. There are very few instances in Nature where one might be able to
see effects of this thinning. One promising venue is in the phenomenon of
inflation, produced in the simplest models through a scalar inflaton field in a
potential with a flat ("slow-roll") part as well as a potential well. We
compute the effect of such a thinning of degrees of freedom upon the running of
the spectral index of quantum fluctuations of the inflaton and deduce that this
will lead to a positive power of wave-vector (opposite to the usual $\sim
-\epsilon$, i.e., negative power correction). Some comments are then made about
the impact on observations (or non-observations) of such fluctuations
\cite{Martin}.


title: Remark on Laquer's theorem for circulant determinants

abstract:
  Olga Taussky-Todd suggested the problem of determining the possible values of
integer circulant determinants. To solve a special case of the problem, Laquer
gave a factorization of circulant determinants. In this paper, we give a modest
generalization of Laquer's theorem.


title: Purity correction for cumulants of hyperon number distribution

abstract:
  We propose a purity correction to subtract effects of combinatorial
backgrounds from cumulants of hyperon number distributions. We argue that
cumulants and mix-cumulants of sidebands, whose yield is comparable with that
of background particles in the signal region, can be used for the correction.
The method is demonstrated in a simple toy model by introducing effects of
reconstruction efficiencies and backgrounds. We show that topological cut
parameters for hyperon reconstructions can be optimized to achieve the best
statistical significance after purity and efficiency corrections. The method
will enable us to measure cumulants of net-baryon, net-strangenss, and their
correlations with better figure of merit than the conventional approach.


title: LiDiTE: a Full-Fledged and Featherweight Digital Twin Framework

abstract:
  The rising of the Cyber-Physical System (CPS) and the Industry 4.0 paradigms
demands the design and the implementation of Digital Twin Frameworks (DTFs)
that may support the quick build of reliable Digital Twins (DTs) for
experimental and testing purposes. Most of the current DTF proposals allow
generating DTs at a good pace but affect generality, scalability, portability,
and completeness. As a consequence, current DTF are mostly domain-specific and
hardly span several application domains (e.g., from simple IoT deployments to
the modeling of complex critical infrastructures). Furthermore, the generated
DTs often requires a high amount of computational resource to run. In this
paper, we present LiDiTE, a novel DTF that overcomes the previous limitations
by, on the one hand, supporting the building of general-purpose DTs at a
fine-grained level, but, on the other hand, with a reduced resource footprint
w.r.t. the current state of the art. We show the characteristics of the LiDiTE
by building the DT of a complex and real critical infrastructure (i.e., the
Smart Poligeneration Microgrid of the Savona Campus) and evaluating its
resource consumption. The source code of LiDiTE, as well as the experimental
dataset, is publicly available.


title: Integrability in the dynamics of axially symmetric membranes

abstract:
  B\"acklund-type transformations in four-dimensional space-time and an
intriguing reduced zero-curvature formulation for axially symmetric membranes,
with diffeomorphism-, resp. Lorentz-, symmetries reappearing after orthonormal
gauge-fixing, are found.


title:
DermX: an end-to-end framework for explainable automated dermatological
  diagnosis

abstract:
  Dermatological diagnosis automation is essential in addressing the high
prevalence of skin diseases and critical shortage of dermatologists. Despite
approaching expert-level diagnosis performance, convolutional neural network
(ConvNet) adoption in clinical practice is impeded by their limited
explainability, and by subjective, expensive explainability validations. We
introduce DermX and DermX+, an end-to-end framework for explainable automated
dermatological diagnosis. DermX is a clinically-inspired explainable
dermatological diagnosis ConvNet, trained using DermXDB, a 554 images dataset
annotated by eight dermatologists with diagnoses and supporting explanations.
DermX+ extends DermX with guided attention training for explanation attention
maps. Both methods achieve near-expert diagnosis performance, with DermX,
DermX+, and dermatologist F1 scores of 0.79, 0.79, and 0.87, respectively. We
assess the explanation plausibility in terms of identification and
localization, by comparing model-selected with dermatologist-selected
explanations, and gradient-weighted class-activation maps with dermatologist
explanation maps. Both DermX and DermX+ obtain an identification F1 score of
0.78. The localization F1 score is 0.39 for DermX and 0.35 for DermX+.
Explanation faithfulness is assessed through contrasting samples, DermX
obtaining 0.53 faithfulness and DermX+ 0.25. These results show that
explainability does not necessarily come at the expense of predictive power, as
our high-performance models provide both plausible and faithful explanations
for their diagnoses.


title: Quantum chaos and the complexity of spread of states

abstract:
  We propose a measure of quantum state complexity defined by minimizing the
spread of the wave-function over all choices of basis. Our measure is
controlled by the "survival amplitude" for a state to remain unchanged, and can
be efficiently computed in theories with discrete spectra. For continuous
Hamiltonian evolution, it generalizes Krylov operator complexity to quantum
states. We apply our methods to the harmonic and inverted oscillators,
particles on group manifolds, the Schwarzian theory, the SYK model, and random
matrix models. For time-evolved thermofield double states in chaotic systems
our measure shows four regimes: a linear "ramp" up to a "peak" that is
exponential in the entropy, followed by a "slope" down to a "plateau". These
regimes arise in the same physics producing the slope-dip-ramp-plateau
structure of the Spectral Form Factor. Specifically, the complexity slope
arises from spectral rigidity, distinguishing different random matrix
ensembles.


title:
Acceleration and cooling of the corona during X-ray flares from the
  Seyfert galaxy I Zw 1

abstract:
  We report on X-ray flares that were observed from the active galactic nucleus
I Zwicky 1 (I Zw 1) in 2020 January by the NuSTAR and XMM-Newton observatories.
The X-ray spectrum is well-described by a model comprised of the continuum
emission from the corona and its reflection from the accretion disc around a
rapidly spinning (a > 0.94) black hole. In order to model the broadband
spectrum, it is necessary to account for the variation in ionisation across the
disc. Analysis of the X-ray spectrum in time periods before, during and after
the flares reveal the underlying changes to the corona associated with the
flaring. During the flares, the reflection fraction drops significantly,
consistent with the acceleration of the corona away from the accretion disc. We
find the first evidence that during the X-ray flares, the temperature drops
from 140(-20,+100)keV before to 45(-9,+40)keV during the flares. The profile of
the iron K line reveals the emissivity profile of the accretion disc, showing
it to be illuminated by a compact corona extending no more than 7(-2,+4)rg over
the disc before the flares, but with tentative evidence that the corona expands
as it is accelerated during the flares. Once the flares subsided, the corona
had collapsed to a radius of 6(-2,+2)rg. The rapid timescale of the flares
suggests that they arise within the black-hole magnetosphere rather than in the
accretion disc, and the variation of the corona is consistent with the
continuum arising from the Comptonisation of seed photons from the disc.


title:
Needles in a haystack: An algorithmic approach to the classification of
  4d $\mathcal{N}=2$ SCFTs

abstract:
  There is a well-known map from 4d $\mathcal{N}=2$ superconformal field
theories (SCFTs) to 2d vertex operator algebras (VOAs). The 4d Schur index
corresponds to the VOA vacuum character, and must be a solution with integral
coefficients of a modular differential equation. This suggests a classification
program for 4d $\mathcal{N}=2$ SCFTs that starts with modular differential
equations and proceeds by imposing all known constraints that follow from the
4d $\to$ 2d map. This program becomes fully algorithmic once one specifies the
$\mathrm{\textit{order}}$ of the modular differential equation and the
$\mathrm{\textit{rank}}$ (complex dimension of the Coulomb branch) of the
$\mathcal{N}=2$ theory. As a proof of concept, we apply the algorithm to the
study of rank-two $\mathcal{N}=2$ SCFTs whose Schur indices satisfy a
fourth-order untwisted modular differential equation. Scanning over a large
number of putative cases, only 15 satisfy all of the constraints imposed by our
algorithm, six of which correspond to known 4d SCFTs. More sophisticated
constraints can be used to argue against the existence of the remaining nine
cases. Altogether, this indicates that our knowledge of such rank-two SCFTs is
surprisingly complete.


title: Generalized Matching Condition for Unity Efficiency Quantum Transduction

abstract:
  Coherently converting quantum states between distinct elements via quantum
transducers remains a crucial yet challenging task in quantum science.
Especially in demand is quantum transduction between optical frequencies, which
are ideal for low-loss transmission across long distances, and microwave
frequencies, which admit high-fidelity quantum operations. We present a generic
formalism for $N$-stage quantum transduction that covers various leading
microwave-to-optical, microwave-to-microwave, and optical-to-optical linear
conversion approaches. We then identify effective circuit models and the
resulting generalized matching conditions for achieving maximum conversion
efficiency. The generalized matching condition requires resistance matching as
well as frequency matching beyond the usual resonant assumption, with simple
impedance-matched transmission interpretation. Our formalism provides a generic
toolbox for determining experimental parameters to realize efficient quantum
transduction, and suggests new regimes of non-resonant conversions that might
outperform all-resonant ones.


title:
Introducing EMP-Pathfinder: modelling the simultaneous formation and
  evolution of stellar clusters in their host galaxies

abstract:
  The formation and evolution of stellar clusters is intimately linked to that
of their host galaxies. To study this connection, we present the EMP-Pathfinder
suite of cosmological zoom-in Milky Way-mass simulations. These simulations
contain a sub-grid description for stellar cluster formation and evolution,
allowing us to study the simultaneous formation and evolution of stellar
clusters alongside their host galaxies across cosmic time. As a key ingredient
in these simulations, we include the physics of the multi-phase nature of the
interstellar medium (ISM), which enables studies of how the presence of a cold,
dense ISM affects cluster formation and evolution. We consider two different
star formation prescriptions: a constant star formation efficiency per
free-fall time, as well as an environmentally-dependent, turbulence-based
prescription. We identify two key results drawn from these simulations.
Firstly, we find that tidal shock-driven disruption caused by the graininess of
the cold ISM produces old ($\tau>10~$Gyr) stellar cluster populations with
properties that are in excellent agreement with the observed populations in the
Milky Way and M31. Importantly, the addition of the cold ISM addresses the
areas of disagreement found in previous simulations that lacked the cold gas
phase. Secondly, the formation of stellar clusters is extremely sensitive to
the baryonic physics that govern the properties of the cold, dense gas
reservoir in the galaxy. This implies that the demographics of stellar cluster
populations represent an important diagnostic tool for constraining baryonic
physics models in upcoming galaxy formation simulations that also include a
description of the cold ISM.


title:
Classification of X-ray Flare Driven Chemical Variability in
  Protoplanetary Disks

abstract:
  Young stars are highly variable in the X-ray regime. In particular, bright
X-ray flares can substantially enhance ionization in the surrounding
protoplanetary disk. Since disk chemical evolution is impacted by ionization,
X-ray flares have the potential to fundamentally alter the chemistry of planet
forming regions. We present 2D disk chemical models that incorporate a
stochastic X-ray flaring module, named \xgen, and examine the flares' overall
chemical impact compared to models that assume a constant X-ray flux. We
examine the impact of 500 years of flaring events and find global chemical
changes on both short time scales (days) in response to discrete flaring events
and long time-scales (centuries) in response to the cumulative impact of many
flares. Individual X-ray flares most strongly affect small gas-phase cations,
where a single flare can temporarily enhance the abundance of species such as
H$_3^+$, HCO$^+$, CH$_3^+$, and C$^+$. We find that flares can also drive
chemistry out of "steady state" over longer time periods, where the
disk-integrated abundance of some species, such as O and O$_2$, changes by a
few percent over the 500 year model. We also explore whether the specific
history of X-ray flaring events (randomly drawn but from the same energy
distribution) impacts the chemical evolution and find that it does not.
Finally, we examine the impact of X-ray flares on the electron fraction. While
most molecules modeled are not highly sensitive to flares, certain species,
including observable molecules, are very reactive to the dynamic environment of
a young star.


title:
Astrometric identification of nearby binary stars II: Astrometric
  binaries in the Gaia Catalogue of Nearby Stars

abstract:
  We examine the capacity to identify binary systems from astrometric
deviations alone. We apply our analysis to the Gaia eDR3 and DR2 data,
specifically the Gaia Catalogue of Nearby Stars. We show we must renormalize
(R)UWE over the local volume to avoid biasing local observations, giving a
Local Unit Weight Error (LUWE). We use the simple criterion of LUWE>2, along
with a handful of quality cuts to remove likely contaminants, to identify
unresolved binary candidates. We identify 22,699 binary candidates within 100
pc of the Sun (just under 10% of sources in this volume). We find an
astrometric binary candidate fraction of around 20% for giant stars, 10% on the
Main Sequence and lower than 1% for White Dwarfs. We also look for Variability
Induced Movers, by computing the correlation between photometric variability
and astrometric noise -- and show that VIMs may dominate the binary population
of sub-Solar mass MS stars. We discuss the possibility and limitations of
identifying non-luminous massive companions from astrometry alone, but find
that our method is insensitive to these. Finally, we compare the astrometric
deviations of MS binaries to the simulated sample from paper I, which show
excellent agreement, and compute the astrometric candidate binary fraction as a
function of absolute magnitude.


title:
Planet Hunters TESS IV: A massive, compact hierarchical triple star
  system TIC 470710327

abstract:
  We report the discovery and analysis of a massive, compact, hierarchical
triple system (TIC 470710327) initially identified by citizen scientists in
data obtained by NASA's Transiting Exoplanet Survey Satellite (TESS).
Spectroscopic follow-up observations obtained with the HERMES spectrograph,
combined with eclipse timing variations (ETVs), confirm that the system is
comprised of three OB stars, with a compact 1.10 d eclipsing binary and a
non-eclipsing tertiary on a 52.04 d orbit. Dynamical modelling of the system
(from radial velocity and ETVs) reveal a rare configuration wherein the
tertiary star (O9.5-B0.5V; 14-17 M$_{\odot}$) is more massive than the combined
mass of the inner binary (10.9-13.2 M$_{\odot}$). Given the high mass of the
tertiary, we predict that this system will undergo multiple phases of mass
transfer in the future, and likely end up as a double neutron star
gravitational wave progenitor or an exotic Thorne-Zytkow object. Further
observational characterisation of this system promises constraints on both
formation scenarios of massive stars as well as their exotic evolutionary
end-products.


title: On-Shell Covariance of Quantum Field Theory Amplitudes

abstract:
  Scattering amplitudes in quantum field theory are independent of the field
parameterization, which has a natural geometric interpretation as a form of
`coordinate invariance.' Amplitudes can be expressed in terms of Riemannian
curvature tensors, which makes the covariance of amplitudes under
non-derivative field redefinitions manifest. We present a generalized geometric
framework that extends this manifest covariance to $all$ allowed field
redefinitions. Amplitudes satisfy a recursion relation that closely resembles
the application of covariant derivatives to increase the rank of a tensor. This
allows us to argue that (tree-level) amplitudes possess a notion of `on-shell
covariance,' in that they transform as a tensor under any allowed field
redefinition up to a set of terms that vanish when the equations of motion and
on-shell momentum constraints are imposed. We highlight a variety of immediate
applications to effective field theories.


title: String Stars in Anti de Sitter Space

abstract:
  We study the `string star' saddle, also known as the Horowitz-Polchinski
solution, in the middle of d+1 dimensional thermal AdS space. We show that
there's a regime of temperatures in which the saddle is very similar to the
flat space solution found by Horowitz and Polchinski. This saddle is
hypothetically connected at lower temperatures to the small AdS black hole
saddle. We also study, numerically and analytically, how the solutions are
changed due to the AdS geometry for higher temperatures. Specifically, we
describe how the solution joins with the thermal gas phase, and find the
leading correction to the Hagedorn temperature due to the AdS curvature.
Finally, we study the thermodynamic instabilities of the solution and argue for
a Gregory-Laflamme-like instability whenever extra dimensions are present at
the AdS curvature scale.


title:
ERGO-ML I: Inferring the assembly histories of IllustrisTNG galaxies
  from integral observable properties via invertible neural networks

abstract:
  A fundamental prediction of the LambdaCDM cosmology is the hierarchical
build-up of structure and therefore the successive merging of galaxies into
more massive ones. As one can only observe galaxies at one specific time in
cosmic history, this merger history remains in principle unobservable. By using
the TNG100 simulation of the IllustrisTNG project, we show that it is possible
to infer the unobservable stellar assembly and merger history of central
galaxies from their observable properties by using machine learning techniques.
In particular, in this first paper of ERGO-ML (Extracting Reality from Galaxy
Observables with Machine Learning), we choose a set of 7 observable integral
properties of galaxies (i.e. total stellar mass, redshift, color, stellar size,
morphology, metallicity, and age) to infer, from those, the stellar ex-situ
fraction, the average merger lookback times and mass ratios, and the lookback
time and stellar mass of the last major merger. To do so, we use and compare a
Multilayer Perceptron Neural Network and a conditional Invertible Neural
Network (cINN): thanks to the latter we are also able to infer the posterior
distribution for these parameters and hence estimate the uncertainties in the
predictions. We find that the stellar ex-situ fraction and the time of the last
major merger are well determined by the selected set of observables, that the
mass-weighted merger mass ratio is unconstrained, and that, beyond stellar
mass, stellar morphology and stellar age are the most informative properties.
Finally, we show that the cINN recovers the remaining unexplained scatter and
secondary cross-correlations. Our tools can be applied to large galaxy surveys
in order to infer unobservable properties of galaxies' past, enabling empirical
studies of galaxy evolution enriched by cosmological simulations.


title:
Dark Matter Effective Field Theory and an Application to Vector Dark
  Matter

abstract:
  The Standard Model Effective Field Theory (SMEFT) and the Low Energy
Effective Field Theory (LEFT) can be extended by adding additional spin 0, 1/2
and 1 dark matter particles which are singlets under the Standard Model (SM)
gauge group. We classify all gauge invariant interactions in the Lagrangian up
to terms of dimension six, and present the tree-level matching conditions
between the two theories at the electroweak scale. The most widely studied dark
matter models, such as those based on the Higgs portal or on kinetic mixing
between the photon and a dark photon, are based on dimension-four interactions
with the SM sector. We consider a model with dark vector particles with a
$\mathbb{Z}_2$ symmetry, so that the lightest dark matter particle is stable.
The leading interaction with the SM is through dimension-six operators
involving two dark vector field-strength tensors and the electromagnetic
field-strength tensor. This model is a viable dark matter model in the
freeze-in scenario for a wide range of parameters.


title:
Public data release of the FIRE-2 cosmological zoom-in simulations of
  galaxy formation

abstract:
  We describe a public data release of the FIRE-2 cosmological zoom-in
simulations of galaxy formation, available at
http://flathub.flatironinstitute.org/fire, from the Feedback In Realistic
Environments (FIRE) project. The FIRE-2 simulations achieve parsec-scale
resolution to explicitly model the multi-phase interstellar medium while
implementing direct models for stellar evolution and feedback, including
stellar winds, core-collapse and Ia supernovae, radiation pressure,
photoionization, and photoelectric heating. We release complete snapshots from
3 suites of simulations. The first comprises 20 simulations that zoom in on 14
Milky Way-mass galaxies, 5 SMC/LMC-mass galaxies, and 4 lower-mass galaxies
including 1 ultra-faint; we release snapshots at z = 0, 1, 2, 3, 4. The second
comprises 4 more massive galaxies simulated to z = 1, with snapshots at z = 1,
2, 3, 4, 5, 6. Finally, a high-redshift suite comprises 22 simulations at z = 5
and 6. Each simulation also includes dozens of resolved lower-mass (satellite)
galaxies in its zoom-in region. Snapshots include all stored properties for all
dark matter, gas, and star particles, including 11 elemental abundances for
stars and gas, and formation times (ages) of star particles. We also release
accompanying (sub)halo catalogs, which include galaxy properties and member
star particles. For the simulations to z = 0, including all Milky Way-mass
galaxies, we release an "ex-situ" flag for star particles, pointers to track
particles across snapshots, catalogs of stellar streams, and multipole basis
expansions for the halo mass distributions. We describe several publicly
available python packages for reading and analyzing these simulations.


title: Semiclassics of three-dimensional SCFTs from holography

abstract:
  We use holography to compute the large-$N$ effective field theory along the
moduli space of vacua of an infinite class of three-dimensional $\mathcal{N}=2$
SCFTs admitting a dual M-theory description. We focus in particular on toric
models and show how the spectrum of large $R$-charge SCFT chiral scalar
operators corresponds to a set of explicit semiclassical solutions of our
effective field theory, which describe bound states of backreacting giant
gravitons and baryonic-like M5-branes. Our semiclassical description allows for
a direct computation of the scaling dimensions of these operators and provides
a starting point for a semiclassical investigation of the SCFT data in the
large $R$-charge sector. We consider the models corresponding to the
$Y^{12}(\mathbb{P}^2)$ and $Q^{111}$ Sasaki-Einstein spaces as explicit
examples.


title: Lithospheric Structure of Venusian Crustal Plateaus

abstract:
  Crustal plateaus are Venusian highlands characterized by tectonized terrains.
It is commonly interpreted that their topography is isostatically supported and
that they represent fossils of an extinct tectonic regime. Using gravity and
topography we perform a comprehensive investigation of the lithospheric
structure of six crustal plateaus. We computed the admittance (gravity to
topography wavelength-dependent ratio) for each region and compared them to
modeled admittances. Three compensation scenarios were tested: Airy isostasy, a
surface-loading flexural model, and a flexural model with surface and
subsurface loads. Our results show that the topography of most plateaus is
supported by crustal thickening and that the addition of a mantle support
component is not necessary at the investigated wavelengths. The elastic
thickness was constrained to be less than 35 km with a best-fitting average of
15 km, confirming that these regions are consistent with an isostatic regime.
The average crustal thickness of the plateaus ranges from 15 to 34 km, and if
they are in Airy isostasy, this implies that the global average crustal
thickness of Venus is about 20 km. Phoebe Regio is the sole exception of our
analysis in that crustal thicknesses that are compatible with the other
plateaus are obtained only when a buoyant layer is included. Heat flow
estimations computed from the elastic thickness indicate that the plateaus
formed under higher heat flow conditions compared to the current global average
and could have caused localized melting. Present-day heat flow predictions
suggest that eclogitization could occur where the crust is thickest.


title: Geometry-Kinematics Duality

abstract:
  We propose a mapping between geometry and kinematics that implies the
classical equivalence of any theory of massless bosons -- including spin and
exhibiting arbitrary derivative or potential interactions -- to a nonlinear
sigma model (NLSM) with a momentum-dependent metric in field space. From this
kinematic metric we construct a corresponding kinematic connection, covariant
derivative, and curvature, all of which transform appropriately under general
field redefinitions, even including derivatives. We show explicitly how all
tree-level on-shell scattering amplitudes of massless bosons are equal to those
of the NLSM via the replacement of geometry with kinematics. Lastly, we
describe how the recently introduced geometric soft theorem of the NLSM, which
universally encodes all leading and subleading soft scalar theorems, also
captures the soft photon theorems.


title: Mass Segregation in the Hyades Cluster

abstract:
  Using the Gaia colour-magnitude diagram, we assign masses to a catalogue of
979 confirmed members of the Hyades cluster and tails. By fitting the
cumulative mass profile, stars within the tidal radius have a Plummer-like
profile with half-mass radius $r_{\rm h}$ of 5.75 pc. The tails are extended
with $r_{\rm h} = 69.35$ pc and fall off more slowly than Plummer with density
proportional to distance$^{-1.36}$. The cluster stars are separated into two
groups at BP-RP $=2$ or $0.56 M_\odot$ to give a high mass (${\bar M} = 0.95
M_\odot$) and a low mass (${\bar M} = 0.32 M_\odot$) population. We show that:
(i) the high mass population has a half-mass radius $r_{\rm h}$ of 4.88 pc,
whilst the low mass population has $r_{\rm h} = 8.10$ pc; (ii) despite the
differences in spatial extent, the kinematics and binarity properties of the
high and low mass populations are similar. They have isotropic velocity
ellipsoids with mean 1d velocity dispersions $\sigma$ of 0.427 and 0.415 km
s$^{-1}$ respectively. The dynamical state of the Hyades is far from energy
equipartition ($\sigma \propto {\bar M}^{-1/2}$). We identify a new mass
segregation instability for clusters with escape speed $V$. Populations with
$V/\sigma \lesssim 2\sqrt{2}$ can never attain thermal equilibrium and
equipartition. This regime encompasses many Galactic open and globular
clusters. For the Hyades, there must be an outward energy flux of at least $9.5
\times 10^{-4} M_\odot\,{\rm km^2\, s^{-2} Myr^{-1}}$ to maintain its current
configuration. The present mass loss of $0.26 M_\odot {\rm Myr}^{-1}$ due to
tidal stripping by itself implies a substantial energy flow beyond the required
magnitude.


title:
Using Multiple Emission Line Ratios to Constrain the Slope of the Dust
  Attenuation Law

abstract:
  We explore the possibility and practical limitations of using a three-line
approach to measure both the slope and normalization of the dust attenuation
law in individual galaxies. To do this, we focus on a sample of eleven galaxies
with existing ground-based Balmer H$\alpha$ and H$\beta$ measurements from slit
spectra, plus space-based grism constraints on Paschen-$\beta$. When accounting
for observational uncertainties, we show that one galaxy has a well-constrained
dust law slope and normalization in the range expected from theoretical
arguments; this galaxy therefore provides an example of what may be possible in
the future. However, most of the galaxies are best-fit by unusually steep or
shallow slopes. We then explore whether additional astrophysical effects or
observational biases could explain the elevated Paschen-$\beta$/H$\alpha$
ratios driving these results. We find that galaxies with high
Paschen-$\beta$/H$\alpha$ ratios may be explained by slightly sub-unity
covering fractions ($>$97%). Alternatively, differing slit losses for different
lines can have a large impact on the results, emphasizing the importance of
measuring all three lines with a consistent spectroscopic aperture. We conclude
that while the three-line approach to constraining the shape of the dust
attenuation law in individual galaxies is promising, deep observations and a
consistent observational strategy will be required to minimize observational
biases and to disentangle the astrophysically interesting effect of differing
covering fractions. The James Webb Space Telescope will provide more sensitive
measurements of Balmer and Paschen lines for galaxies at $z\approx0.3-2$,
enabling uniform constraints on the optical-infrared dust attenuation law and
its intrinsic variation.


title: Probing Neutrino Mass Models through Resonances at Neutrino Telescopes

abstract:
  We study the detection prospects of relatively light charged scalars in
radiative Majorana neutrino mass models, such as the Zee model and its variants
using scalar leptoquarks, at current and future neutrino telescopes. In
particular, we show that these scalar mediators can give rise to Glashow-like
resonance features in the ultra-high energy neutrino (UHE) event spectrum at
the IceCube neutrino observatory and its high-energy upgrade IceCube-Gen2. The
same scalars can also give rise to observable non-standard neutrino
interactions (NSI), and we show that the UHE neutrinos provide a complementary
probe of NSI. We also discuss an interesting possibility of producing such
resonances by incoming sterile neutrino components in the case where neutrinos
are pseudo-Dirac particles.


title: Optimizing quantum circuits with Riemannian gradient-flow

abstract:
  Variational quantum algorithms are a promising class of algorithms that can
be performed on currently available quantum computers. In most settings, the
free parameters of a variational circuit are optimized using a classical
optimizer that updates parameters in Euclidean geometry. Since quantum circuits
are elements of the special unitary group, we can consider an alternative
optimization perspective that depends on the structure of this group. In this
work, we investigate a Riemannian optimization scheme over the special unitary
group and we discuss its implementation on a quantum computer. We illustrate
that the resulting Riemannian gradient-flow algorithm has favorable
optimization properties for deep circuits and that an approximate version of
this algorithm can be performed on near-term hardware.


title:
Hidden Variables of Gravity and Geometry and the Cosmological Constant
  Problem

abstract:
  We extend General Relativity by adding $4$-form field strengths to the
gravitational sector of the theory. This promotes Planck scale and the
cosmological constant into integration constants of these $4$-forms. When we
include the charges of the $4$-forms, these `constants' can jump discretely
from region to region. We explain how the cosmological constant problem can be
solved in this framework. When the cosmological constant picks up contributions
from two different $4$-forms, with an irrational ratio of charges, the spectrum
of its values is a very fine discretuum. If the membrane charges satisfy
$\frac{2\kappa_{\tt eff}^2 \kappa^2 |{\cal Q}_i|}{3{\cal T}^2_i} < 1$, the
discharge processes populating this discretuum dynamically relax $\Lambda$,
ceasing as $\Lambda$ approaches zero. Thus the theory exponentially favors a
huge hierarchy $\Lambda/\mpl^4 \ll 1$ instead of $\Lambda/\mpl^4 \simeq 1$.


title: State Preparation Boosters for Early Fault-Tolerant Quantum Computation

abstract:
  Quantum computing is believed to be particularly useful for the simulation of
chemistry and materials, among the various applications. In recent years, there
have been significant advancements in the development of near-term quantum
algorithms for quantum simulation, including VQE and many of its variants.
However, for such algorithms to be useful, they need to overcome several
critical barriers including the inability to prepare high-quality
approximations of the ground state. Current challenges to state preparation,
including barren plateaus and the high-dimensionality of the optimization
landscape, make state preparation through ansatz optimization unreliable. In
this work, we introduce the method of ground state boosting, which uses a
limited-depth quantum circuit to reliably increase the overlap with the ground
state. This circuit, which we call a booster, can be used to augment an ansatz
from VQE or be used as a stand-alone state preparation method. The booster
converts circuit depth into ground state overlap in a controllable manner. We
numerically demonstrate the capabilities of boosters by simulating the
performance of a particular type of booster, namely the Gaussian booster, for
preparing the ground state of $N_2$ molecular system. Beyond ground state
preparation as a direct objective, many quantum algorithms, such as quantum
phase estimation, rely on high-quality state preparation as a subroutine.
Therefore, we foresee ground state boosting and similar methods as becoming
essential algorithmic components as the field transitions into using early
fault-tolerant quantum computers.


title:
Hardware-efficient entangled measurements for variational quantum
  algorithms

abstract:
  Variational algorithms have received significant attention in recent years
due to their potential to solve practical problems in noisy intermediate-scale
quantum (NISQ) devices. A fundamental step of these algorithms is the
evaluation of the expected value of Hamiltonians, and hence, efficient schemes
to perform this task are required. The standard approach employs local
measurements of Pauli operators and requires a large number of circuits. An
alternative is to make use of entangled measurements, which significantly
reduces the number of circuits but involves entangling gates between
non-physically connected qubits, introducing intermediate entangling operations
that increase the depth of the circuits. As a solution to this problem we
propose hardware-efficient entangled measurements (HEEM), that is, measurements
that only permit entanglement between physically connected qubits. We show that
this strategy enhances the evaluation of molecular Hamiltonians in NISQ
devices, reducing the number of circuits required without increasing their
depth. We provide quantitative metrics of how this approach offers better
results than only local measurements and arbitrarily entangled ones. We
estimate with classical simulators and quantum hardware the ground state energy
of the H$_2$O molecule by the variational quantum eigensolver using HEEM.


title: Observation of a continuous time crystal

abstract:
  Time crystals are classified as discrete or continuous depending on whether
they spontaneously break discrete or continuous time translation symmetry.
While discrete time crystals have been extensively studied in periodically
driven systems since their recent discovery, the experimental realization of a
continuous time crystal is still pending. Here, we report the observation of a
limit cycle phase in a continuously pumped dissipative atom-cavity system,
which is characterized by emergent oscillations in the intracavity photon
number. We observe that the phase of this oscillation is random for different
realizations, and hence this dynamical many-body state breaks continuous time
translation symmetry spontaneously. The observed robustness of the limit cycles
against temporal perturbations confirms the realization of a continuous time
crystal.


title:
Minimum quantum run-time characterization and calibration via restless
  measurements with dynamic repetition rates

abstract:
  The performance of a quantum processor depends on the characteristics of the
device and the quality of the control pulses. Characterizing cloud-based
quantum computers and calibrating the pulses that control them is necessary for
high-fidelity operations. However, this time intensive task eats into the
availability of the device. Here, we show restless measurements with a dynamic
repetition rate that speed-up calibration and characterization tasks.
Randomized benchmarking is performed 5.3 times faster on the quantum device
than when an active reset is used and without discarding any data. In addition,
we calibrate a qubit with parameter scans and error-amplifying gate sequences
and show speed-ups of up to a factor of forty on the quantum device over active
reset. Finally, we present a methodology to perform restless quantum process
tomography that mitigates restless state preparation errors. These results
reduce the footprint of characterization and calibration tasks. Quantum
computers can thus either spend more time running applications or run
calibrations more often to maintain gate fidelity.


title:
RR Lyrae and Type II Cepheid Variables in Globular Clusters: Optical and
  Infrared Properties

abstract:
  Globular clusters are both primary fossils of galactic evolution and
formation and are ideal laboratories for constraining the evolution of low-mass
and metal-poor stars. RR Lyrae and type II Cepheid variables are low-mass,
radially pulsating stars that trace old-age stellar populations. These stellar
standard candles in globular clusters are crucial for measuring their precise
distances and, in turn, absolute ages, and for the calibration of the
extragalactic distance scale. Herein, the evolutionary stages of RR Lyrae and
type II Cepheids are discussed, and their pulsation properties, including the
light curves, color-magnitude and period-amplitude diagrams, and
period-luminosity relations in globular clusters at optical and infrared
wavelengths are presented. The RR Lyrae visual magnitude-metallicity relation
and the multiband period-luminosity-metallicity relations in globular clusters
covering a wide metallicity range are also discussed in detail for their
application to the RR Lyrae-based distance~scale.


title:
Evolvability Degeneration in Multi-Objective Genetic Programming for
  Symbolic Regression

abstract:
  Genetic programming (GP) is one of the best approaches today to discover
symbolic regression models. To find models that trade off accuracy and
complexity, the non-dominated sorting genetic algorithm II (NSGA-II) is widely
used. Unfortunately, it has been shown that NSGA-II can be inefficient: in
early generations, low-complexity models over-replicate and take over most of
the population. Consequently, studies have proposed different approaches to
promote diversity. Here, we study the root of this problem, in order to design
a superior approach. We find that the over-replication of low complexity-models
is due to a lack of evolvability, i.e., the inability to produce offspring with
improved accuracy. We therefore extend NSGA-II to track, over time, the
evolvability of models of different levels of complexity. With this
information, we limit how many models of each complexity level are allowed to
survive the generation. We compare this new version of NSGA-II, evoNSGA-II,
with the use of seven existing multi-objective GP approaches on ten widely-used
data sets, and find that evoNSGA-II is equal or superior to using these
approaches in almost all comparisons. Furthermore, our results confirm that
evoNSGA-II behaves as intended: models that are more evolvable form the
majority of the population.


title:
A quantum computation capability verification protocol for NISQ devices
  with dihedral coset problem

abstract:
  In this article, we propose an interactive protocol for one party (the
verifier) holding a quantum computer to verify the quantum computation power of
another party's (the prover) device via a one-way quantum channel. This
protocol is referred to as the dihedral coset problem (DCP) challenge. The
verifier needs to prepare quantum states encoding secrets (DCP samples) and
send them to the prover. The prover is then tasked with recovering those
secrets with a certain accuracy. Numerical simulation demonstrates that this
accuracy is sensitive to errors in quantum hardware. Additionally, the DCP
challenge serves as benchmarking protocol for locally fully connected (LFC)
quantum architecture and aims to be performed on current and near-future
quantum resources. We conduct a 4-qubit experiment on one of IBM Q devices.


title: Deep Ensembles Work, But Are They Necessary?

abstract:
  Ensembling neural networks is an effective way to increase accuracy, and can
often match the performance of larger models. This observation poses a natural
question: given the choice between a deep ensemble and a single neural network
with similar accuracy, is one preferable over the other? Recent work suggests
that deep ensembles may offer benefits beyond predictive power: namely,
uncertainty quantification and robustness to dataset shift. In this work, we
demonstrate limitations to these purported benefits, and show that a single
(but larger) neural network can replicate these qualities. First, we show that
ensemble diversity, by any metric, does not meaningfully contribute to an
ensemble's ability to detect out-of-distribution (OOD) data, and that one can
estimate ensemble diversity by measuring the relative improvement of a single
larger model. Second, we show that the OOD performance afforded by ensembles is
strongly determined by their in-distribution (InD) performance, and -- in this
sense -- is not indicative of any "effective robustness". While deep ensembles
are a practical way to achieve performance improvement (in agreement with prior
work), our results show that they may be a tool of convenience rather than a
fundamentally better model class.


title:
A multi-wavelength view of distinct accretion regimes in the pulsating
  ultraluminous X-ray source NGC 1313 X-2

abstract:
  NGC 1313 X-2 is one of the few known pulsating ultraluminous X-ray sources
(PULXs), and so is thought to contain a neutron star that accretes at highly
super-Eddington rates. However, the physics of this accretion remains to be
determined. Here we report the results of two simultaneous XMM-Newton and HST
observations of this PULX taken to observe two distinct X-ray behaviours as
defined from its Swift light curve. We find that the X-ray spectrum of the PULX
is best described by the hard ultraluminous (HUL) regime during the observation
taken in the lower flux, lower variability amplitude behaviour; its spectrum
changes to a broadened disc during the higher flux, higher variability
amplitude epoch. However, we see no accompanying changes in the optical/UV
fluxes, with the only difference being a reduction in flux in the near-IR as
the X-ray flux increased. We attempt to fit irradiation models to explain the
UV/optical/IR fluxes but they fail to provide meaningful constraints. Instead,
a physical model for the system leads us to conclude that the optical light is
dominated by a companion O/B star, albeit with an IR excess that may be
indicative of a jet. We discuss how these results may be consistent with the
precession of the inner regions of the accretion disc leading to changes in the
observed X-ray properties, but not the optical, and whether we should expect to
observe reprocessed emission from ULXs.


title: ASC me to Do Anything: Multi-task Training for Embodied AI

abstract:
  Embodied AI has seen steady progress across a diverse set of independent
tasks. While these varied tasks have different end goals, the basic skills
required to complete them successfully overlap significantly. In this paper,
our goal is to leverage these shared skills to learn to perform multiple tasks
jointly. We propose Atomic Skill Completion (ASC), an approach for multi-task
training for Embodied AI, where a set of atomic skills shared across multiple
tasks are composed together to perform the tasks. The key to the success of
this approach is a pre-training scheme that decouples learning of the skills
from the high-level tasks making joint training effective. We use ASC to train
agents within the AI2-THOR environment to perform four interactive tasks
jointly and find it to be remarkably effective. In a multi-task setting, ASC
improves success rates by a factor of 2x on Seen scenes and 4x on Unseen scenes
compared to no pre-training. Importantly, ASC enables us to train a multi-task
agent that has a 52% higher Success Rate than training 4 independent single
task agents. Finally, our hierarchical agents are more interpretable than
traditional black-box architectures.


title: Learned Turbulence Modelling with Differentiable Fluid Solvers

abstract:
  In this paper, we train turbulence models based on convolutional neural
networks. These learned turbulence models improve under-resolved low resolution
solutions to the incompressible Navier-Stokes equations at simulation time. Our
method involves the development of a differentiable numerical solver that
supports the propagation of optimisation gradients through multiple solver
steps. We showcase the significance of this property by demonstrating the
superior stability and accuracy of those models that featured a higher number
of unrolled steps during training. This approach is applied to three
two-dimensional turbulence flow scenarios, a homogeneous decaying turbulence
case, a temporally evolving mixing layer and a spatially evolving mixing layer.
Our method achieves significant improvements of long-term \textit{a-posteriori}
statistics when compared to no-model simulations, without requiring these
statistics to be directly included in the learning targets. At inference time,
our proposed method also gains substantial performance improvements over
similarly accurate, purely numerical methods.


title:
Slow dynamics and large deviations in classical stochastic Fredkin
  chains

abstract:
  The Fredkin spin chain serves as an interesting theoretical example of a
quantum Hamiltonian whose ground state exhibits a phase transition between
three distinct phases, one of which violates the area law. Here we consider a
classical stochastic version of the Fredkin model, which can be thought of as a
simple exclusion process subject to additional kinetic constraints, and study
its classical stochastic dynamics. The ground state phase transition of the
quantum chain implies an equilibrium phase transition in the stochastic
problem, whose properties we quantify in terms of numerical matrix product
states (MPS). The stochastic model displays slow dynamics, including power law
decaying autocorrelation functions and hierarchical relaxation processes due to
exponential localization. Like in other kinetically constrained models, the
Fredkin chain has a rich structure in its dynamical large deviations - which we
compute accurately via numerical MPS - including an active-inactive phase
transition, and a hierarchy of trajectory phases connected to particular
equilibrium states of the model. We also propose, via its height field
representation, a generalization of the Fredkin model to two dimensions in
terms of constrained dimer coverings of the honeycomb lattice.


title:
Three-point functions in a $\mathcal{N}=2$ superconformal gauge theory
  and their strong-coupling limit

abstract:
  We study the 3-point functions of single-trace scalar operators in a
four-dimensional $\mathcal{N}=2$ SYM theory with gauge group $\mathrm{SU}(N)$
and matter in the symmetric plus anti-symmetric representation, which has a
vanishing $\beta$-function. By mapping this computation to the matrix model
arising from localization on a 4-sphere we are able to resum the perturbative
expansion in the large-$N$ 't Hooft limit and derive the behavior of the
correlators at strong coupling. Finally, by combining our results on the
3-point functions with those on the 2-point functions that have been recently
found, we obtain the normalized 3-point coefficients of this conformal field
theory at strong coupling and find that they depend in a simple way on the
conformal dimensions of the single-trace operators.


title: Transformer Memory as a Differentiable Search Index

abstract:
  In this paper, we demonstrate that information retrieval can be accomplished
with a single Transformer, in which all information about the corpus is encoded
in the parameters of the model. To this end, we introduce the Differentiable
Search Index (DSI), a new paradigm that learns a text-to-text model that maps
string queries directly to relevant docids; in other words, a DSI model answers
queries directly using only its parameters, dramatically simplifying the whole
retrieval process. We study variations in how documents and their identifiers
are represented, variations in training procedures, and the interplay between
models and corpus sizes. Experiments demonstrate that given appropriate design
choices, DSI significantly outperforms strong baselines such as dual encoder
models. Moreover, DSI demonstrates strong generalization capabilities,
outperforming a BM25 baseline in a zero-shot setup.


title: Deterministic Photon Sorting in Waveguide QED Systems

abstract:
  Sorting quantum fields into different modes according to their Fock-space
quantum numbers is a highly desirable quantum operation. In this Letter, we
show that a pair of two-level emitters, chirally coupled to a waveguide, may
scatter single- and two-photon components of an input pulse into orthogonal
temporal modes with a fidelity $\gtrsim 0.9997$. We develop a general theory to
characterize and optimize this process and observe an interesting dynamics in
the two-photon scattering regime: while the first emitter gives rise to a
complex multimode field, the second emitter recombines the field amplitudes and
the net two-photon scattering induces a self-time reversal of the pulse mode.
The presented scheme can be employed to construct logic elements for
propagating photons, such as a deterministic nonlinear-sign gate with a
fidelity $\gtrsim 0.9995$


title:
A skyrmion fluid and bimeron glass emerging from competition with a
  chiral spin liquid

abstract:
  Skyrmions are of interest both from a fundamental and technological point of
view, due to their potential to act as information carriers. One great
challenge concerns their manipulation and control, especially at higher
temperatures. Here we combine skyrmion physics with another aspects of modern
condensed matter: spin liquids. Using the high entropy and broken symmetry of a
chiral spin liquid, we design a theoretical model to control the density of
well defined skyrmions with temperature, all the way from a diluted gas to a
dense liquid and a crystallised solid. At high field, the skyrmion fluid forms
an original bimeron glass with high degeneracy and out-of-equilibrium dynamics,
reminiscent of co-polymer physics and chain models in statistical mechanics.
Our approach illustrates how spin-liquid properties can be used for the design
of tailored models, and further connects skyrmions to phenomena beyond
condensed matter.


title: Looking out for a sustainable space

abstract:
  October 1957, and the successful launch of Sputnik 1 into Earth orbit, marked
the dawn of the Space Age. The first of the 'fellow travellers' - humanity's
first artificial satellite - orbited for a mere three months before re-entering
the Earth's atmosphere, though its mission paved the way for an era of
exploration that has endured to the present day. For many, a world without
satellites would be a difficult one to imagine. As a society, we have become
reliant on them for a vast array of services and applications. With a divine
view of large swathes of the Earth's surface, and the ability to relay signals
around its curvature, satellites have enabled the fast transfer of data on a
global scale, bypassing the challenges associated with ground-based
broadcasting, long-distance wiring, and so on. Positioning, Navigation and
Timing (PNT) satellites have revolutionised transportation by land, air, and
sea, while weather satellites enable scientists to monitor and warn of
large-scale phenomena as they develop in near real-time. Satellites have
extended the frontiers of observation: looking outwards, astronomers are able
to circumvent the Earth's atmosphere to look deeper into the cosmos than ever
before; looking inwards, patterns and processes that feed into general
circulation models can be monitored on a range of timescales, improving our
understanding of climate change. Satellites, and the services they provide, are
not going to disappear any time soon. That said, threats to satellite safety do
exist, and it is important that they be addressed as soon as possible to avoid
long-lasting damage to operations in the space domain. Nearly sixty-five years
on from the advent of human activity in space, I chart the evolution of the
orbital debris environment and review latest efforts to make space operations
more sustainable.


title:
Intent-Aware Permission Architecture: A Model for Rethinking Informed
  Consent for Android Apps

abstract:
  As data privacy continues to be a crucial human-right concern as recognized
by the UN, regulatory agencies have demanded developers obtain user permission
before accessing user-sensitive data. Mainly through the use of privacy
policies statements, developers fulfill their legal requirements to keep users
abreast of the requests for their data. In addition, platforms such as Android
enforces explicit permission request using the permission model. Nonetheless,
recent research has shown that service providers hardly make full disclosure
when requesting data in these statements. Neither is the current permission
model designed to provide adequate informed consent. Often users have no clear
understanding of the reason and scope of usage of the data request. This paper
proposes an unambiguous, informed consent process that provides developers with
a standardized method for declaring Intent. Our proposed Intent-aware
permission architecture extends the current Android permission model with a
precise mechanism for full disclosure of purpose and scope limitation. The
design of which is based on an ontology study of data requests purposes. The
overarching objective of this model is to ensure end-users are adequately
informed before making decisions on their data. Additionally, this model has
the potential to improve trust between end-users and developers.


title: Unlabeled Data Help: Minimax Analysis and Adversarial Robustness

abstract:
  The recent proposed self-supervised learning (SSL) approaches successfully
demonstrate the great potential of supplementing learning algorithms with
additional unlabeled data. However, it is still unclear whether the existing
SSL algorithms can fully utilize the information of both labelled and unlabeled
data. This paper gives an affirmative answer for the reconstruction-based SSL
algorithm \citep{lee2020predicting} under several statistical models. While
existing literature only focuses on establishing the upper bound of the
convergence rate, we provide a rigorous minimax analysis, and successfully
justify the rate-optimality of the reconstruction-based SSL algorithm under
different data generation models. Furthermore, we incorporate the
reconstruction-based SSL into the existing adversarial training algorithms and
show that learning from unlabeled data helps improve the robustness.


title: A Survey of Cross-Modality Brain Image Synthesis

abstract:
  The existence of completely aligned and paired multi-modal neuroimaging data
has proved its effectiveness in diagnosis of brain diseases. However,
collecting the full set of well-aligned and paired data is impractical or even
luxurious, since the practical difficulties may include high cost, long time
acquisition, image corruption, and privacy issues. A realistic solution is to
explore either an unsupervised learning or a semi-supervised learning to
synthesize the absent neuroimaging data. In this paper, we tend to approach
multi-modality brain image synthesis task from different perspectives, which
include the level of supervision, the range of modality synthesis, and the
synthesis-based downstream tasks. Particularly, we provide in-depth analysis on
how cross-modality brain image synthesis can improve the performance of
different downstream tasks. Finally, we evaluate the challenges and provide
several open directions for this community. All resources are available at
https://github.com/M-3LAB/awesome-multimodal-brain-image-systhesis


title:
Influence of Lithium Interstitial Doping on the Optoelectronic
  Properties of NiO and WO$_3$

abstract:
  First principles calculations through density functional theory (DFT)+$U$
method were performed to assess the effect of Li interstitial doping on the
optoelectronic properties of NiO and of cubic, hexagonal, and monoclinic
WO$_3$. The implications on the structural and electronic properties and their
relationship with the optical properties, such as dielectric response and
absorption coefficient in the context of electrochromism, are discussed. Li
interstitial doping (i.e., electron doping) turns these materials metallic-like
even for low Li concentration ($x<0.083$). In metallic-like materials, optical
properties are largely influenced by intraband transitions. Compared to NiO,
Li-doped NiO shows larger absorption in the visible region while, with respect
to WO$_3$, Li-doped WO$_3$ exhibits an increment in absorption in the whole
spectrum, particularly, in the infrared region. These results help to
understand the changes in optical properties observed in electrochromic devices
based on these materials.