title:
Physico-chemical properties extraction from the fluorescence spectrum
  with 1D-convolutional neural networks: application to olive oil

abstract:
  The olive oil sector produces a substantial impact in the Mediterranean's
economy and lifestyle. Many studies exist which try to optimize the different
steps in the olive oil's production process. One of the main challenges for
olive oil producers is the ability to asses and control the quality during the
production cycle. For this purpose, several parameters need to be determined,
such as the acidity, the UV absorption or the ethyl esters content. To achieve
this, samples must be sent to an approved laboratory for chemical analysis.
This approach is expensive and cannot be performed very frequently, making
quality control of olive oil a real challenge. This work explores a new
approach based on fluorescence spectroscopy and artificial intelligence
(namely, 1-D convolutional neural networks) to predict the five chemical
quality indicators of olive oil (acidity, peroxide value, UV spectroscopic
parameters $K_{270}$ and $K_{232}$, and ethyl esters) from simple fluorescence
spectra. Fluorescence spectroscopy is a very attractive optical technique since
it does not require sample preparation, is non destructive, and, as shown in
this work, can be easily implemented in small and cost-effective sensors. The
results indicate that the proposed approach gives exceptional results in the
quality determination and would make the continuous quality control of olive
oil during and after the production process a reality. Additionally, this novel
methodology presents potential applications as a support for quality
specifications of olive oil, as defined by the European regulation.


title: Laplacian Renormalization Group for heterogeneous networks

abstract:
  The renormalization group is the cornerstone of the modern theory of
universality and phase transitions, a powerful tool to scrutinize symmetries
and organizational scales in dynamical systems. However, its network
counterpart is particularly challenging due to correlations between intertwined
scales. To date, the explorations are based on hidden geometries hypotheses.
Here, we propose a Laplacian RG diffusion-based picture in complex networks,
defining both the Kadanoff supernodes' concept, the momentum space procedure,
\emph{\'a la Wilson}, and applying this RG scheme to real networks in a natural
and parsimonious way.

categories: cond-mat.stat-mech cond-mat.dis-nn nlin.AO physics.bio-ph


title: Coupled dynamical phase transitions in driven disk packings

abstract:
  Under the influence of oscillatory shear, a mono-layer of frictional granular
disks exhibits two dynamical phase transitions: a transition from an initially
disordered state to an ordered crystalline state, and a dynamic
active-absorbing phase transition. Although there is no reason, {\it a-priori},
for these to be at the same critical point, they are. The transitions may also
be characterized by the disk trajectories, which are non-trivial loops breaking
time-reversal invariance.


title:
The Dirichlet problem for Monge-Amp\`ere equation for $(n-1)$-PSH
  functions on Hermitian manifolds

abstract:
  We solve the Dirichlet problem for Monge-Amp\`ere equation for $(n-1)$-PSH
functions possibly with degenerate right-hand side, through deriving a
quantitative version of boundary estimate under the assumption of $(n-1)$-PSH
subsolutions. In addition, we confirm the subsolution assumption on a product
of a closed balanced manifold with a compact Riemann surface with boundary.


title:
Allocation of spinning reserves for autonomous grids subject to
  frequency stability constraints and short-term renewable power variations

abstract:
  Low-inertia, isolated power systems face the problem of resiliency to power
variations. The integration of renewable energy sources, such as wind and solar
photovoltaic, pushes the boundaries of this issue further. Higher shares of
renewables requires better evaluations of electrical system stability, to avoid
severe safety and economic consequences. Accounting for frequency stability
requirements and allocating proper spinning reserves, therefore becomes a topic
of pivotal importance in the long-term planning and operational management of
power systems. In this paper, dynamic frequency constraints are proposed to
ensure resiliency during short-term power variations due to, for example, wind
gusts or cloud passage. The use of the proposed constraints is exemplified in a
case study, the constraints being integrated into a mixed-integer linear
programming algorithm for sizing the optimal capacities of solar photovoltaic
and battery energy storage resources in an isolated industrial plant. Outcomes
of this case study show that reductions in the levelized cost of energy and
carbon emissions can be overestimated by 8.0% and 10.8% respectively, where
frequency constraints are neglected. The proposed optimal sizing is validated
using time-domain simulations of the case study. The results indicate that this
optimal system is frequency stable under the worst-case contingency.


title:
Modulating Retroreflector Based Free Space Optical Link for
  UAV-to-Ground Communications

abstract:
  Weight reduction and low power consumption are key requirements in the next
generation of unmanned aerial vehicle (UAV) networks. Employing modulating
retro-reflector (MRR)-based free space optical (FSO) technology is an
innovative technique for UAV-to-ground communication in order to reduce the
payload weight and power consumption of UAVs which leads to increased
maneuverability and flight time of UAV. In this paper, we consider an MRR-based
FSO system for UAV-to-ground communication. We will show that the performance
of the considered system is very sensitive to tracking errors. Therefore, to
assess the benefits of MRR-based UAV deployment for FSO communications, the
MRR-based UAV FSO channel is characterized by taking into account tracking
system errors along with UAV's orientation fluctuations, link length, UAV's
height, optical beam divergence angle, effective area of MRR, atmospheric
turbulence and optical channel loss in the double-pass channels. To enable
effective performance analysis, tractable and closed-form expressions are
derived for probability density function of end-to-end signal to noise ratio,
outage probability and bit error rate of the considered system under both
weak-to-moderate and moderate-to-strong atmospheric turbulence conditions. The
accuracy of the analytical expressions is verified by extensive simulations.
Analytical results are then used to study the relationship between the optimal
system design and tracking system errors.


title:
Dolbeault Harmonic $(1,1)$-forms on $4$-dimensional compact quotients of
  Lie Groups with a left invariant almost Hermitian structure

abstract:
  We study Dolbeault harmonic $(1,1)$-forms on compact quotients
$M=\Gamma\backslash G$ of $4$-dimensional Lie groups $G$ admitting a left
invariant almost Hermitian structure $(J,\omega)$. In this case, we prove that
the space of Dolbeault harmonic $(1,1)$-forms on $(M,J,\omega)$ has dimension
$b^-+1$ if and only if there exists a left invariant anti self dual
$(1,1)$-form $\gamma$ on $(G,J)$ satisfying $id^c\gamma=d\omega$. Otherwise,
its dimension is $b^-$. In this way, we answer to a question by Zhang.


title:
Electroweak renormalization based on gauge-invariant vacuum expectation
  values of non-linear Higgs representations: 1. Standard Model

abstract:
  The renormalization of vacuum expectation value parameters, such as $v$ in
the Standard Model (SM), is an important ingredient in electroweak
renormalization, where this issue is connected to the treatment of tadpoles.
Tadpole counterterms can be generated in two different ways in the Lagrangian:
in the course of parameter renormalization, or alternatively via Higgs field
redefinitions. The former typically leads to small corrections originating from
tadpoles, but in general suffers from gauge dependences if MSbar
renormalization conditions are used for mass parameters. The latter is free
from gauge dependences, but is prone to very large corrections in MSbar
schemes, jeopardizing perturbative stability in predictions. In this paper we
propose a new scheme for tadpole renormalization, dubbed Gauge-Invariant Vacuum
expectation value Scheme (GIVS), which is a hybrid scheme of the two mentioned
types, with the benefits of being gauge independent and perturbatively stable.
The GIVS is based on the gauge-invariance property of Higgs fields, and the
corresponding parameters like $v$, in non-linear representations of Higgs
multiplets. We demonstrate the perturbative stability of the GIVS in the SM by
discussing the conversion between on-shell and MSbar renormalized masses.


title: HEP computing collaborations for the challenges of the next decade

abstract:
  Large High Energy Physics (HEP) experiments adopted a distributed computing
model more than a decade ago. WLCG, the global computing infrastructure for
LHC, in partnership with the US Open Science Grid, has achieved data management
at the many-hundred-Petabyte scale, and provides access to the entire community
in a manner that is largely transparent to the end users. The main computing
challenge of the next decade for the LHC experiments is presented by the HL-LHC
program. Other large HEP experiments, such as DUNE and Belle II, have
large-scale computing needs and afford opportunities for collaboration on the
same timescale. Many of the computing facilities supporting HEP experiments are
shared and face common challenges, and the same is true for software libraries
and services. The LHC experiments and their WLCG- partners, DUNE and Belle II,
are now collaborating to evolve the computing infrastructure and services for
their future needs, facilitated by the WLCG organization, OSG, the HEP Software
Foundation and development projects such as HEP-CCE, IRIS-HEP and SWIFT-HEP. In
this paper we outline the strategy by which the international HEP computing
infrastructure, software and services should evolve through the collaboration
of large and smaller scale HEP experiments, while respecting the specific needs
of each community. We also highlight how the same infrastructure would be a
benefit for other sciences, sharing similar needs with HEP. This proposal is in
line with the OSG/WLCG strategy for addressing computing for HL-LHC and is
aligned with European and other international strategies in computing for large
scale science. The European Strategy for Particle Physics in 2020 agreed to the
principles laid out above, in its final report.


title: Multilayer crisscross error and erasure correction

abstract:
  In this work, multilayer crisscross error and erasures are considered, which
affect entire rows and columns in the matrices of a list of matrices. To
measure such errors and erasures, the multi-cover metric is introduced. Several
bounds are derived, including a Singleton bound, and maximum multi-cover
distance (MMCD) codes are defined as those attaining it. Duality, puncturing
and shortening of linear MMCD codes are studied. It is shown that the dual of a
linear MMCD code is not necessarily MMCD, and those satisfying this duality
condition are defined as dually MMCD codes. Finally, some constructions of
codes in the multi-cover metric are given, including dually MMCD codes,
together with efficient decoding algorithms for them.


title:
TransCAM: Transformer Attention-based CAM Refinement for Weakly
  Supervised Semantic Segmentation

abstract:
  Weakly supervised semantic segmentation (WSSS) with only image-level
supervision is a challenging task. Most existing methods exploit Class
Activation Maps (CAM) to generate pixel-level pseudo labels for supervised
training. However, due to the local receptive field of Convolution Neural
Networks (CNN), CAM applied to CNNs often suffers from partial activation --
highlighting the most discriminative part instead of the entire object area. In
order to capture both local features and global representations, the Conformer
has been proposed to combine a visual transformer branch with a CNN branch. In
this paper, we propose TransCAM, a Conformer-based solution to WSSS that
explicitly leverages the attention weights from the transformer branch of the
Conformer to refine the CAM generated from the CNN branch. TransCAM is
motivated by our observation that attention weights from shallow transformer
blocks are able to capture low-level spatial feature similarities while
attention weights from deep transformer blocks capture high-level semantic
context. Despite its simplicity, TransCAM achieves a new state-of-the-art
performance of 69.3% and 69.6% on the respective PASCAL VOC 2012 validation and
test sets, showing the effectiveness of transformer attention-based refinement
of CAM for WSSS.


title: NNLO+PS with MiNNLO$_{\rm PS}$: status and prospects

abstract:
  We summarize the current status and near future prospects for
next-to-next-to-leading order calculations matched to parton shower based on
the MiNNLO$_{\rm PS}$ method. We give a theoretical overview, illustrate
selected results for $ZZ\to 4\ell$ and top-pair production processes at the
LHC, and provide an outlook of the future challenges.


title:
Proceedings of the International Astronomical Union: Studying Magnetic
  Field Amplification in Interacting Galaxies Using Numerical Simulations

abstract:
  There are indications that the magnetic field evolution in galaxies might be
massively shaped by tidal interactions and mergers between galaxies. The
details of the connection between the evolution of magnetic fields and that of
their host galaxies is still a field of research. We use a combined approach of
magnetohydrodynamics for the baryons and an N-body scheme for the dark matter
to investigate magnetic field amplification and evolution in interacting
galaxies. We find that, for two colliding equal-mass galaxies and for varying
initial relative spatial orientations, magnetic fields are amplified during
interactions, yet cannot be sustained. Furthermore, we find clues for an active
mean-field dynamo.


title: Snowmass 2021 White Paper: The Windchime Project

abstract:
  The absence of clear signals from particle dark matter in direct detection
experiments motivates new approaches in disparate regions of viable parameter
space. In this Snowmass white paper, we outline the Windchime project, a
program to build a large array of quantum-enhanced mechanical sensors. The
ultimate aim is to build a detector capable of searching for Planck mass-scale
dark matter purely through its gravitational coupling to ordinary matter. In
the shorter term, we aim to search for a number of other physics targets,
especially some ultralight dark matter candidates. Here, we discuss the basic
design, open R&D challenges and opportunities, current experimental efforts,
and both short- and long-term physics targets of the Windchime project.


title:
Existence of the equivariant minimal model program for compact K\"ahler
  threefolds with the action of an abelian group of maximal rank

abstract:
  Let $X$ be a $\mathbb{Q}$-factorial compact K\"ahler klt threefold admitting
an action of a free abelian group $G$, which is of positive entropy and of
maximal rank. After running the $G$-equivariant log minimal model program, we
show that such $X$ is either rationally connected or bimeromorphic to a
$Q$-complex torus. In particular, we fix an issue in the proof of our previous
paper.


title: Two-Higgs-doublet models in light of current experiments: a brief review

abstract:
  We briefly survey several typical CP-conserving two-Higgs-doublet models
(2HDMs) in light of current experiments. First we derive the masses and
couplings of the mass eigenstates from the Lagrangians. Then we analyze the
constraints from theory and oblique electroweak parameters. Finally, we
delineate the status of 2HDM in light of the LHC searches, the dark matter
detections and the muon $g-2$ measurement.


title:
Real-time non-adiabatic dynamics in the one-dimensional Holstein model:
  trajectory-based versus exact methods

abstract:
  We benchmark a set of quantum-chemistry methods including the multitrajectory
Ehrenfest, the fewest-switches surface-hopping, and the multiconfigurational
Ehrenfest method against exact quantum-many-body techniques by studying
real-time dynamics in the Holstein model. This is a paradigmatic model in
condensed matter theory incorporating a local coupling of electrons to Einstein
phonons. For the two-site and three-site Holstein model, we discuss the exact
and quantum-chemistry methods in terms of the Born-Huang formalism, covering
different initial states, which either start on a single Born-Oppenheimer
surface, or with the electron localized to a single site. For extended systems
with up to 51 sites, we address both the physics of single Holstein polarons
and the dynamics of charge-density waves at finite electron densities. For
these extended systems, we compare the quantum-chemistry methods to exact
dynamics obtained from time-dependent density matrix renormalization group
calculations with local basis optimization (DMRG-LBO). We observe that the
multitrajectory Ehrenfest method in general only captures the ultra-short time
dynamics accurately. In contrast, the surface-hopping method with suitable
corrections provides a much better description of the long-time behavior, but
struggles with the short-time description of coherences between different
Born-Oppenheimer states. We show that the multiconfigurational Ehrenfest method
yields a significant improvement over the multitrajectory Ehrenfest method and
can be converged to the exact results in small systems with moderate
computational efforts. We further observe that for extended systems, this
convergence is slower with respect to the number of configurations. Our
benchmark study demonstrates that DMRG-LBO is a useful tool for assessing the
quality of the quantum-chemistry methods.


title:
Contribution to the 2022 Cosmology session of the 56th Rencontres de
  Moriond: Moment expansion of polarized dust SED: A new path towards capturing
  the CMB $B$-modes with LiteBIRD

abstract:
  Characterizing accurately the polarized dust emission from our Galaxy will be
decisive for the quest for the Cosmic Microwave Background (CMB) primordial
$B$-modes. The incomplete modeling of its potentially complex spectral
properties could lead to biases in the CMB polarization analyses and to a
spurious detection of the tensor-to-scalar ratio $r$. Variations of the dust
properties along and between lines of sight lead to unavoidable distortions of
the spectral energy distribution (SED) that can not be easily anticipated by
standard component separation methods. This issue can be tackled using a moment
expansion of the dust SED, an innovative parametrization method imposing
minimal assumptions on the sky complexity. In the recent work [Vacher \emph{et
al.} (2022)]\cite{Vacher_2022}, we apply this formalism to the $B$-mode
cross-angular power spectra computed from simulated \lb{} polarization data at
frequencies between 100 and 402\,GHz, containing CMB, dust and instrumental
noise. Thanks to the moment expansion, we can measure an unbiased value of the
tensor-to-scalar ratio with a dispersion compatible with the target values
aimed by the instrument.


title: Analytical Approach to Intensity Calculation in Scintillation Detectors

abstract:
  Scintillation detectors are widely used in modern physics, including various
medical tomographs. There are two types of position-sensitive scintillation
detectors: pixel arrays of "scintillator-photomultiplier" pairs and continuous
scintillator with multiple photomultipliers attached. For the last one, there
are two common ways to calculate the coordinates of the scintillation flash via
detector response in scintillation cameras: Anger's method and Monte-Carlo
simulation. In this article, we develop an analytical approach (so-called
"kaleidoscopic ray-tracing") to compute the energy outcome from several light
detectors in the scintillation camera with a continuous scintillator, which has
reflective and absorbing faces. We show that Anger's method is just an
approximation of the exact solution. Anger's method requires absorbing faces
only, so our approach covers a more general case. The derived method achieves
results, that are similar to the Monte-Carlo simulation, but it requires fewer
computations.


title:
Lann\'er diagrams and combinatorial properties of compact hyperbolic
  Coxeter polytopes

abstract:
  In this paper we study $\times_0$-products of Lann\'er diagrams. We prove
that every $\times_0$-product of at least four Lann\'er diagrams with at least
one diagram of order $\ge 3$ is superhyperbolic. This fact is used to classify
compact hyperbolic Coxeter polytopes that are combinatorially equivalent to
products of some number of simplices. Such polytopes were already classified in
different combinatorial cases: simplices [Lan50], cubes [Poi82, And70a, JT18],
simplicial prisms [Kap74], products of two simplices [Ess96], and products of
three simplices [Tum07]. As a corollary of our first result mentioned above, we
obtain that these classifications exhaust all compact hyperbolic Coxeter
polytopes that are combinatorially equivalent to products of simplices.
  We also consider compact hyperbolic Coxeter polytopes whose every Lann\'er
subdiagram has order 2. The second result of this paper slightly improves the
recent Burcroff upper bound on dimension for such polytopes to 12.


title:
The mean-field limit for particle systems with uniform full-rank
  constraints

abstract:
  We consider a particle system with uniform coupling between a macroscopic
component and individual particles. The constraint for each particle is of full
rank, which implies that each movement of the macroscopic component leads to a
movement of all particles and vice versa. Skeletal muscle tissues share a
similar property which motivates this work.
  We prove convergence of the mean-field limit, well-posedness and a stability
estimate for the mean-field PDE.


title:
Snowmass 2021: Quantum Sensors for HEP Science -- Interferometers,
  Mechanics, Traps, and Clocks

abstract:
  A wide range of quantum sensing technologies are rapidly being integrated
into the experimental portfolio of the high energy physics community. Here we
focus on sensing with atomic interferometers; mechanical devices read out with
optical or microwave fields; precision spectroscopic methods with atomic,
nuclear, and molecular systems; and trapped atoms and ions. We give a variety
of detection targets relevant to particle physics for which these systems are
uniquely poised to contribute. This includes experiments at the precision
frontier like measurements of the electron dipole moment and electromagnetic
fine structure constant and searches for fifth forces and modifications of
Newton's law of gravity at micron-to-millimeter scales. It also includes
experiments relevant to the cosmic frontier, especially searches for
gravitional waves and a wide variety of dark matter candidates spanning heavy,
WIMP-scale, light, and ultra-light mass ranges. We emphasize here the need for
more developments both in sensor technology and integration into the broader
particle physics community.

categories: quant-ph hep-ex hep-ph physics.atom-ph physics.ins-det


title: The early-time Lieb-Robinson correlation function for qubit arrays

abstract:
  The Lieb-Robinson correlation function captures propagation of quantum
correlations in a many-body system. We calculate the value of the leading order
of the correlation function, not its bound, for a system of interacting qubits
at early times. The general analytical result is compared to numerical
calculations and is applied to regular qubit lattices in one, two, and three
dimensions. The Lieb-Robinson velocity and the approximately exponential
leading edge of correlations emerge in the limit of large arrays.


title:
Snowmass2021: Vera C. Rubin Observatory as a Flagship Dark Matter
  Experiment

abstract:
  Establishing that Vera C. Rubin Observatory is a flagship dark matter
experiment is an essential pathway toward understanding the physical nature of
dark matter. In the past two decades, wide-field astronomical surveys and
terrestrial laboratories have jointly created a phase transition in the
ecosystem of dark matter models and probes. Going forward, any robust
understanding of dark matter requires astronomical observations, which still
provide the only empirical evidence for dark matter to date. We have a unique
opportunity right now to create a dark matter experiment with Rubin Observatory
Legacy Survey of Space and Time (LSST). This experiment will be a coordinated
effort to perform dark matter research, and provide a large collaborative team
of scientists with the necessary organizational and funding supports. This
approach leverages existing investments in Rubin. Studies of dark matter with
Rubin LSST will also guide the design of, and confirm the results from, other
dark matter experiments. Supporting a collaborative team to carry out a dark
matter experiment with Rubin LSST is the key to achieving the dark matter
science goals that have already been identified as high priority by the
high-energy physics and astronomy communities.


title:
Hamiltonians for polaron models with subcritical ultraviolet
  singularities

abstract:
  We treat the ultraviolet problem for polaron-type models in nonrelativistic
quantum field theory. Assuming that the dispersion relations of particles and
the field have the same growth at infinity, we cover all subcritical
(superrenormalisable) interactions. The Hamiltonian without cutoff is exhibited
as an explicit self-adjoint operator obtained by a finite iteration procedure.
The cutoff Hamiltonians converge to this operator in the strong resolvent sense
after subtraction of a perturbative approximation for the ground-state energy.


title: Refined Astrometry on Board a CubeSat

abstract:
  Optical navigation on a CubeSat must rely on the best extraction of the
directions of some beacons from on-board images. We present an experiment on
OPS-SAT, a CubeSat of the European Space Agency (ESA), that will characterize
an onboard algorithm to this aim, named Angle-based Correlation (AbC). OPS-SAT
is a 3-unit CubeSat with an Attitude Determination and Control System (ADCS)
and an imager that have proved their reliability with typical performance at
CubeSat scale. We selected a few star-fields that all present enough visible
stars within a 10 ? field of view. When our experiment is run, OPS-SAT is
pointed to the most convenient star-field at that time. There, the star-field
is imaged and subwindows are extracted from the image around the expected
location of each star, based on the attitude-quaternion reported by the ADCS.
The AbC reconstructs the absolute direction of the central body, in principle
unknown, which is the pointed known star in the experiment. The method
intensively uses the quaternion algebra. The beacon location is first
consolidated in the field of view with the AbC. Then, the field of view is
finely positioned against the sky, again with the AbC. A covariance is
associated with the found beacon direction. Our experiment with OPS-SAT manages
the pointing and the imager, and processes the taken images. Then, it downloads
the on-board computed absolute directions and their covariances, to be compared
with the actual directions. After a campaign of intensive use of the
experiment, the statistical performance of the algorithm will be established
and compared to the on-board computed covariances. As a bonus, an assessment of
OPS-SAT's inertial pointing stability will be available. The AbC can
theoretically get rid of the Attitude Control Error (ACE) of the platform and
of the Attitude Knowledge Error (AKE) estimated by the ADCS, and potentially
converge to (...)


title:
FisheyeHDK: Hyperbolic Deformable Kernel Learning for Ultra-Wide
  Field-of-View Image Recognition

abstract:
  Conventional convolution neural networks (CNNs) trained on narrow
Field-of-View (FoV) images are the state-of-the-art approaches for object
recognition tasks. Some methods proposed the adaptation of CNNs to ultra-wide
FoV images by learning deformable kernels. However, they are limited by the
Euclidean geometry and their accuracy degrades under strong distortions caused
by fisheye projections. In this work, we demonstrate that learning the shape of
convolution kernels in non-Euclidean spaces is better than existing deformable
kernel methods. In particular, we propose a new approach that learns deformable
kernel parameters (positions) in hyperbolic space. FisheyeHDK is a hybrid CNN
architecture combining hyperbolic and Euclidean convolution layers for
positions and features learning. First, we provide an intuition of hyperbolic
space for wide FoV images. Using synthetic distortion profiles, we demonstrate
the effectiveness of our approach. We select two datasets - Cityscapes and
BDD100K 2020 - of perspective images which we transform to fisheye equivalents
at different scaling factors (analog to focal lengths). Finally, we provide an
experiment on data collected by a real fisheye camera. Validations and
experiments show that our approach improves existing deformable kernel methods
for CNN adaptation on fisheye images.


title: Muon Collider Physics Summary

abstract:
  The perspective of designing muon colliders with high energy and luminosity,
which is being investigated by the International Muon Collider Collaboration,
has triggered a growing interest in their physics reach. We present a concise
summary of the muon colliders potential to explore new physics, leveraging on
the unique possibility of combining high available energy with very precise
measurements.


title: Optical manipulation of matter waves

abstract:
  Light is extensively used to steer the motion of atoms in free space,
enabling cooling and trapping of matter waves through ponderomotive forces and
Doppler-mediated photon scattering. Likewise, light interaction with free
electrons has recently emerged as a versatile approach to modulate the electron
wave function for applications in ultrafast electron microscopy. Here, we
combine these two worlds by theoretically demonstrating that matter waves can
be optically manipulated via inelastic interactions with optical fields,
allowing us to modulate the translational wave function and produce temporally
and spatially compressed atomic beam pulses. Specifically, we realize such
modulation through stimulated photon absorption and emission by atoms
traversing phase-matching evanescent optical fields generated upon light
scattering by a nanostructure, but also via stimulated Compton scattering in
free space without any assistance from material media. Our results support
optical manipulation of matter waves as a powerful tool for microscopy,
spectroscopy, and the exploration of novel fundamental phenomena associated
with light-atom interactions.


title:
Snowmass 2021 Cosmic Frontier White Paper: Cosmology with
  Millimeter-Wave Line Intensity Mapping

abstract:
  Next-generation tests of fundamental physics and cosmology using large scale
structure require measurements over large volumes of the Universe, including
high redshifts inaccessible to present-day surveys. Line intensity mapping, an
emerging technique that detects the integrated emission of atomic and molecular
lines without resolving sources, can efficiently map cosmic structure over a
wide range of redshifts. Observations at millimeter wavelengths detect far-IR
emission lines such as CO/[CII], and take advantage of observational and
analysis techniques developed by CMB experiments. These measurements can
provide constraints with unprecedented precision on the physics of inflation,
neutrino masses, light relativistic species, dark energy and modified gravity,
and dark matter, among many other science goals. In this white paper we
forecast the sensitivity requirements for future ground-based mm-wave intensity
mapping experiments to enable transformational cosmological constraints. We
outline a staged experimental program to steadily improve sensitivity, and
describe the necessary investments in developing detector technology and
analysis techniques.


title:
The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for
  Large Language Models

abstract:
  Pre-trained Transformer-based language models have become a key building
block for natural language processing (NLP) tasks. While these models are
extremely accurate, they can be too large and computationally intensive to run
on standard deployments. A variety of compression methods, including
distillation, quantization, structured and unstructured pruning are known to be
applicable to decrease model size and increase inference speed. In this
context, this paper's contributions are two-fold. We begin with an in-depth
study of the accuracy-compression trade-off for unstructured weight pruning in
the context of BERT models, and introduce Optimal BERT Surgeon (O-BERT-S), an
efficient and accurate weight pruning method based on approximate second-order
information, which we show to yield state-of-the-art results in terms of the
compression/accuracy trade-off. Specifically, Optimal BERT Surgeon extends
existing work on second-order pruning by allowing for pruning blocks of
weights, and by being applicable at BERT scale. Second, we investigate the
impact of this pruning method when compounding compression approaches for
Transformer-based models, which allows us to combine state-of-the-art
structured and unstructured pruning together with quantization, in order to
obtain highly compressed, but accurate models. The resulting compression
framework is powerful, yet general and efficient: we apply it to both the
fine-tuning and pre-training stages of language tasks, to obtain
state-of-the-art results on the accuracy-compression trade-off with relatively
simple compression recipes. For example, we obtain 10x model size compression
with < 1% relative drop in accuracy to the dense BERT-base, 10x end-to-end
CPU-inference speedup with < 2% relative drop in accuracy, and 29x inference
speedups with < 7.5% relative accuracy drop.


title:
Graph-Survival: A Survival Analysis Framework for Machine Learning on
  Temporal Networks

abstract:
  Continuous time temporal networks are attracting increasing attention due
their omnipresence in real-world datasets and they manifold applications. While
static network models have been successful in capturing static topological
regularities, they often fail to model effects coming from the causal nature
that explain the generation of networks. Exploiting the temporal aspect of
networks has thus been the focus of various studies in the last decades.
  We propose a framework for designing generative models for continuous time
temporal networks. Assuming a first order Markov assumption on the
edge-specific temporal point processes enables us to flexibly apply survival
analysis models directly on the waiting time between events, while using
time-varying history-based features as covariates for these predictions. This
approach links the well-documented field of temporal networks analysis through
multivariate point processes, with methodological tools adapted from survival
analysis. We propose a fitting method for models within this framework, and an
algorithm for simulating new temporal networks having desired properties. We
evaluate our method on a downstream future link prediction task, and provide a
qualitative assessment of the network simulations.


title: The physics case of a 3 TeV muon collider stage

abstract:
  In the path towards a muon collider with center of mass energy of 10 TeV or
more, a stage at 3 TeV emerges as an appealing option. Reviewing the physics
potential of such muon collider is the main purpose of this document. In order
to outline the progression of the physics performances across the stages, a few
sensitivity projections for higher energy are also presented. There are many
opportunities for probing new physics at a 3 TeV muon collider. Some of them
are in common with the extensively documented physics case of the CLIC 3 TeV
energy stage, and include measuring the Higgs trilinear coupling and testing
the possible composite nature of the Higgs boson and of the top quark at the 20
TeV scale. Other opportunities are unique of a 3 TeV muon collider, and stem
from the fact that muons are collided rather than electrons. This is
exemplified by studying the potential to explore the microscopic origin of the
current $g$-2 and $B$-physics anomalies, which are both related with muons.


title: Parametric invariance

abstract:
  We examine the development of the concept of parametric invariance in
classical mechanics, quantum mechanics, statistical mechanics, and
thermodynamics, and particularly its relation to entropy. The parametric
invariance was used by Ehrenfest as a principle related to the quantization
rules of the old quantum mechanics. It was also considered by Rayleigh in the
determination of pressure caused by vibration, and the general approach we
follow here is based on his. Specific calculation of invariants in classical
and quantum mechanics are determined. The Hertz invariant, which is a volume in
phase space, is extended to the case of a variable number of particles. We show
that the slow parametric change leads to the adiabatic process, allowing the
definition of entropy as a parametric invariance.

categories: cond-mat.stat-mech physics.class-ph physics.hist-ph quant-ph


title:
Logical shadow tomography: Efficient estimation of error-mitigated
  observables

abstract:
  We introduce a technique to estimate error-mitigated expectation values on
noisy quantum computers. Our technique performs shadow tomography on a logical
state to produce a memory-efficient classical reconstruction of the noisy
density matrix. Using efficient classical post-processing, one can mitigate
errors by projecting a general nonlinear function of the noisy density matrix
into the codespace. The subspace expansion and virtual distillation can be
viewed as special cases of the new framekwork. We show our method is favorable
in the quantum and classical resources overhead. Relative to subspace expansion
which requires $O\left(2^{N} \right)$ samples to estimate a logical Pauli
observable with $[[N, k]]$ error correction code, our technique requires only
$O\left(4^{k} \right)$ samples. Relative to virtual distillation, our technique
can compute powers of the density matrix without additional copies of quantum
states or quantum memory. We present numerical evidence using logical states
encoded with up to sixty physical qubits and show fast convergence to
error-free expectation values with only $10^5$ samples under 1% depolarizing
noise.


title:
Show Me More Details: Discovering Hierarchies of Procedures from
  Semi-structured Web Data

abstract:
  Procedures are inherently hierarchical. To "make videos", one may need to
"purchase a camera", which in turn may require one to "set a budget". While
such hierarchical knowledge is critical for reasoning about complex procedures,
most existing work has treated procedures as shallow structures without
modeling the parent-child relation. In this work, we attempt to construct an
open-domain hierarchical knowledge-base (KB) of procedures based on wikiHow, a
website containing more than 110k instructional articles, each documenting the
steps to carry out a complex procedure. To this end, we develop a simple and
efficient method that links steps (e.g., "purchase a camera") in an article to
other articles with similar goals (e.g., "how to choose a camera"), recursively
constructing the KB. Our method significantly outperforms several strong
baselines according to automatic evaluation, human judgment, and application to
downstream tasks such as instructional video retrieval.
  A demo with partial data can be found at https://wikihow-hierarchy.github.io.
The code and the data are at https://github.com/shuyanzhou/wikihow_hierarchy.


title: A simple determination of the halo size $L$ from $^{10}$Be/$^9$Be data

abstract:
  The AMS-02 and HELIX experiments should provide soon $^{10}$Be/$^9$Be
cosmic-ray data of unprecedented precision. We propose an analytical formula to
quickly and accurately determine $L$ from these data. Our formula is validated
against the full calculation performed with the propagation code USINE. We
compare the constraints on $L$ set by Be/B and $^{10}$Be/$^9$Be, relying on
updated sets of production cross sections. The best-fit $L$ from AMS-02 Be/B
data is shifted from 5 kpc to 3.8 kpc when using the updated cross sections. We
obtain consistent results from the Be/B analysis with USINE,
$L=3.8^{+2.8}_{-1.6}$ kpc (data and cross-section uncertainties), and from the
analysis of $^{10}$Be/$^9$Be data with the simplified formula, $L=4.7\pm0.6$
(data uncertainties) $\pm2$ (cross-section uncertainties) kpc. The analytical
formula indicates that improvements on $L$ brought by future data will be
limited by production cross-section uncertainties, unless either
$^{10}$Be/$^9$Be measurements are extended up to several tens of GeV/n or
nuclear data for the production of $^{10}$Be and $^{9}$Be are improved; new
data for the production cross section of $^{16}$O into Be isotopes above a few
GeV/n are especially desired.


title: On the commutativity of closed symmetric operators

abstract:
  In this article, we give conditions guaranteeing the commutativity of a
bounded self-adjoint operator with an unbounded closed symmetric operator.


title:
Development Frameworks for Microservice-based Applications: Evaluation
  and Comparison

abstract:
  The microservice architectural style has gained much attention from both
academia and industry recently as a novel way to design, develop, and deploy
cloud-native applications. This concept encourages the decomposition of a
monolith into multiple independently deployable units. A typical
microservices-based application is formed of two service types: functional
services, which provide the core business logic, and infrastructure services,
which provide essential functionalities for a microservices ecosystem. To
improve developers' productivity, many software frameworks have been developed
to provide those reusable infrastructure services, allowing programmers to
focus on implementing microservices in arbitrary ways. In this work, we made
use of four open source frameworks to develop a cloud-based application in
order to compare and evaluate their usability and practicability. While all
selected frameworks promote asynchronous microservice design in general, there
are differences in the ways each implements services. This leads to
interoperability issues, such as message topic naming convention. Additionally,
a key finding is the long startup times of JVM-based services that might reduce
application's resiliency and portability. Some other advantages come directly
from the programming language, such as the ability of Go to generate native
binary executables, which results in very small and compact Docker images (up
to 78\% smaller compared to other languages).


title: Heaps of modules and affine spaces

abstract:
  A notion of heaps of modules as an affine version of modules over a ring or,
more generally, over a truss, is introduced and studied. Basic properties of
heaps of modules are derived. Examples arising from geometry (connections,
affine spaces) and algebraic topology (chain contractions) are presented.
Relationships between heaps of modules and modules over a ring and affine
spaces are revealed and analysed.


title:
Constrained RIS Phase Profile Optimization and Time Sharing for
  Near-field Localization

abstract:
  The rising concept of reconfigurable intelligent surface (RIS) has promising
potential for Beyond 5G localization applications. We herein investigate
different phase profile designs at a reflective RIS, which enable
non-line-of-sight positioning in nearfield from downlink single antenna
transmissions. We first derive the closed-form expressions of the corresponding
Fisher information matrix (FIM) and position error bound (PEB). Accordingly, we
then propose a new localization-optimal phase profile design, assuming prior
knowledge of the user equipment location. Numerical simulations in a canonical
scenario show that our proposal outperforms conventional RIS random and
directional beam codebook designs in terms of PEB. We also illustrate the four
beams allocated at the RIS (i.e., one directional beam, along with its
derivatives with respect to space dimensions) and show how their relative
weights according to the optimal solution can be practically implemented
through time sharing (i.e., considering feasible beams sequentially).


title:
Phenomenological aspects of composite Higgs scenarios: exotic scalars
  and vector-like quarks

abstract:
  Composite Higgs models usually contain additional pseudo Nambu Goldstone
bosons and vector-like quarks. We discuss various aspects related to their LHC
phenomenology and provide summary plots of exclusion limits using currently
available information. We also describe a general parametrisation implemented
in a software for Monte Carlo simulations and study the SU(5)/SO(5) scenario as
a concrete example.


title:
Comment on the Evidence of isostructural phase transitions in elemental
  zirconium

abstract:
  It is argued that the article by O.Bannon et al. ; High pressure stability of
beta-Zr: no evidence for isostructural phase transitions, published recently
-July 2021 - in High Pressure Research has no experimental foundation and the
statement no evidence is absolutly misleading. Isostructural phase transition
has been reported only in Ce metal, thus, the Beta-Zr to beta prime -Zr
isostructural phase transitions has fundamental interest in condensed matter
physics.


title: Two-fermion final states at International Linear Collider

abstract:
  The pair productions of leptons and quarks at $e^+e^-$ Higgs factory are an
important probe for new physics via precise measurements. The discovery and
exclusion limits of $Z^\prime$ models at the International Linear Collider with
$\sqrt{s} = 250$, 500 and 1000 GeV are calculated with selection efficiencies
estimated in the existing full simulation studies. It shows a large potential
of BSM searches with precise measurements at future energy-frontier $e^+e^-$
colliders.


title:
An Observer-Based Composite Identifier for Online Estimation of the
  Thevenin Equivalent Parameters of a Power System

abstract:
  We consider a Th\'evenin equivalent circuit capturing the dynamics of a power
grid as seen from the point of common coupling with a power electronic
converter, and provide a solution to the problem of online identification of
the corresponding circuit parameters. For this purpose, we first derive a
linear regression model in the conventional abc coordinates and next design a
bounded observer-based composite identifier that requires local measurements
and knowledge of the grid frequency only. An extension that guarantees
exponential convergence of the estimates, under the additional assumption of
knowledge of the grid X/R ratio, is further provided. The performance of the
proposed identifier, which subsumes a conventional gradient descent algorithm,
is illustrated via detailed computer simulations.


title: Test samples and infrastructure for accelerator magnet developments

abstract:
  LHC still does not operate at full energy due to training features in
magnets. Higher field practical superconductors (Nb3Sn) show much worse
training behavior than NbTi. Most magnet performance issues relate to
quenching, and it is this phenomenon and its dependencies that need to be
understood for us to succeed addressing them in magnets. For pragmatic and
scientific reasons underlying mechanisms are hard to investigate in real
magnets. Available data suggest that emulating local conditions at quench
location may be enough to arrive at a good understanding of what drives
observed behavior. "Local" conditions imply emulation by small samples of
cables/"stacks" powered within a facility with controllable conditions,
including external magnetic and force fields. This paper argues about the
necessity of this approach, while reminding current understanding and
directions of quench studies, and pointing out inadequacy of available
techniques. Improved facilities and change of perspective are required for
consistent and affordable development.


title:
Reducing the cost of energy estimation in the variational quantum
  eigensolver algorithm with robust amplitude estimation

abstract:
  Quantum chemistry and materials is one of the most promising applications of
quantum computing. Yet much work is still to be done in matching
industry-relevant problems in these areas with quantum algorithms that can
solve them. Most previous efforts have carried out resource estimations for
quantum algorithms run on large-scale fault-tolerant architectures, which
include the quantum phase estimation algorithm. In contrast, few have assessed
the performance of near-term quantum algorithms, which include the variational
quantum eigensolver (VQE) algorithm. Recently, a large-scale benchmark study
[Gonthier et al. 2020] found evidence that the performance of the variational
quantum eigensolver for a set of industry-relevant molecules may be too
inefficient to be of practical use. This motivates the need for developing and
assessing methods that improve the efficiency of VQE. In this work, we predict
the runtime of the energy estimation subroutine of VQE when using robust
amplitude estimation (RAE) to estimate Pauli expectation values. Under
conservative assumptions, our resource estimation predicts that RAE can reduce
the runtime over the standard estimation method in VQE by one to two orders of
magnitude. Despite this improvement, we find that the runtimes are still too
large to be practical. These findings motivate two complementary efforts
towards quantum advantage: 1) the investigation of more efficient near-term
methods for ground state energy estimation and 2) the development of problem
instances that are of industrial value and classically challenging, but better
suited to quantum computation.


title:
FRL-FI: Transient Fault Analysis for Federated Reinforcement
  Learning-Based Navigation Systems

abstract:
  Swarm intelligence is being increasingly deployed in autonomous systems, such
as drones and unmanned vehicles. Federated reinforcement learning (FRL), a key
swarm intelligence paradigm where agents interact with their own environments
and cooperatively learn a consensus policy while preserving privacy, has
recently shown potential advantages and gained popularity. However, transient
faults are increasing in the hardware system with continuous technology node
scaling and can pose threats to FRL systems. Meanwhile, conventional
redundancy-based protection methods are challenging to deploy on
resource-constrained edge applications. In this paper, we experimentally
evaluate the fault tolerance of FRL navigation systems at various scales with
respect to fault models, fault locations, learning algorithms, layer types,
communication intervals, and data types at both training and inference stages.
We further propose two cost-effective fault detection and recovery techniques
that can achieve up to 3.3x improvement in resilience with <2.7% overhead in
FRL systems.


title:
A short note on the appearance of the simplest antilinear ODE in several
  physical contexts

abstract:
  In this short note, we review several one-dimensional problems such as those
involving linear Schroedinger equation, variable-coefficient Helmholtz
equation, Zakharov-Shabat system and Kubelka-Munk equations. We show that they
all can be reduced to solving one simple antilinear ordinary differential
equation $u^{\prime}\left(x\right)=f\left(x\right)\overline{u\left(x\right)}$
or its nonhomogeneous version
$u^{\prime}\left(x\right)=f\left(x\right)\overline{u\left(x\right)}+g\left(x\right)$,
$x\in\left(0,x_{0}\right)\subset\mathbb{R}$. We point out some of the
advantages of the proposed reformulation and call for further investigation of
the obtained ODE.


title:
Estimation of the trajectory and attitude of railway vehicles using
  inertial sensors with application to track geometry measurement

abstract:
  This paper describes a novel method for the estimation of the trajectory
curve and orientation of a rigid body moving along a railway track. Compared to
other recent developments in the literature, the presented approach has the
significant advantage of tracking the position and orientation of a railway
vehicle using inertial sensors only, excluding global position sensors (GNSS or
total station) and also excluding global orientation sensors (magnetometers or
inclinometers). The algorithm is based on a kinematic model of the relative
motion of the body with respect to the track. This kinematic model is used as
the system equations of a Kalman filter algorithm that includes in the state
vector the coordinates used to define the position and orientation of the body.
Two different Kalman filter approaches are described. In the first one, the
position and orientation are calculated independently. In the second one, both
position and orientation are calculated as a coupled problem. Crucial to the
success of the results of the Kalman filters is the use of the correct
covariance matrices associated with the system process and the measurements.
The calculated trajectory and orientation are applied in this research to the
problem of track geometry measurement. A scale track with known design geometry
and irregularities is used to conduct experiments for tuning and evaluating the
quality of the output of the algorithm. Results show that the developed
algorithm is accurate enough for this application. They also show that, using
either of the two proposed Kalman filtering approaches, the constrained maximum
likelihood method for the estimation of the covariance matrices performs
similarly to the known-output method. This is very convenient because it allows
a straightforward application of the observation model in different scenarios.


title:
Fairly Dividing Mixtures of Goods and Chores under Lexicographic
  Preferences

abstract:
  We study fair allocation of indivisible goods and chores among agents with
\emph{lexicographic} preferences -- a subclass of additive valuations. In sharp
contrast to the goods-only setting, we show that an allocation satisfying
\emph{envy-freeness up to any item} (EFX) could fail to exist for a mixture of
\emph{objective} goods and chores. To our knowledge, this negative result
provides the \emph{first} counterexample for EFX over (any subdomain of)
additive valuations. To complement this non-existence result, we identify a
class of instances with (possibly subjective) mixed items where an EFX and
Pareto optimal allocation always exists and can be efficiently computed. When
the fairness requirement is relaxed to \emph{maximin share} (MMS), we show
positive existence and computation for \emph{any} mixed instance. More broadly,
our work examines the existence and computation of fair and efficient
allocations both for mixed items as well as chores-only instances, and
highlights the additional difficulty of these problems vis-{\`a}-vis their
goods-only counterparts.


title:
On Cyclic Solutions to the Min-Max Latency Multi-Robot Patrolling
  Problem

abstract:
  We consider the following surveillance problem: Given a set $P$ of $n$ sites
in a metric space and a set of $k$ robots with the same maximum speed, compute
a patrol schedule of minimum latency for the robots. Here a patrol schedule
specifies for each robot an infinite sequence of sites to visit (in the given
order) and the latency $L$ of a schedule is the maximum latency of any site,
where the latency of a site $s$ is the supremum of the lengths of the time
intervals between consecutive visits to $s$. When $k=1$ the problem is
equivalent to the travelling salesman problem (TSP) and thus it is NP-hard. We
have two main results. We consider cyclic solutions in which the set of sites
must be partitioned into $\ell$ groups, for some~$\ell \leq k$, and each group
is assigned a subset of the robots that move along the travelling salesman tour
of the group at equal distance from each other. Our first main result is that
approximating the optimal latency of the class of cyclic solutions can be
reduced to approximating the optimal travelling salesman tour on some input,
with only a $1+\varepsilon$ factor loss in the approximation factor and an
$O\left(\left( k/\varepsilon \right)^k\right)$ factor loss in the runtime, for
any $\varepsilon >0$. Our second main result shows that an optimal cyclic
solution is a $2(1-1/k)$-approximation of the overall optimal solution. Note
that for $k=2$ this implies that an optimal cyclic solution is optimal overall.
The results have a number of consequences. For the Euclidean version of the
problem, for instance, combining our results with known results on Euclidean
TSP, yields a PTAS for approximating an optimal cyclic solution, and it yields
a $(2(1-1/k)+\varepsilon)$-approximation of the optimal unrestricted solution.
If the conjecture mentioned above is true, then our algorithm is actually a
PTAS for the general problem in the Euclidean setting.


title:
GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large
  Language Models

abstract:
  Providing natural language instructions in prompts is a useful new paradigm
for improving task performance of large language models in a zero-shot setting.
Recent work has aimed to improve such prompts via manual rewriting or
gradient-based tuning. However, manual rewriting is time-consuming and requires
subjective interpretation, while gradient-based tuning can be extremely
computationally demanding for large models and requires full access to model
weights, which may not be available for API-based models. In this work, we
introduce Gradient-free Instructional Prompt Search (GrIPS), a gradient-free,
edit-based search approach for improving task instructions for large language
models. GrIPS takes in instructions designed for humans and automatically
returns an improved, edited prompt, while allowing for API-based tuning. The
instructions in our search are iteratively edited using four operations
(delete, add, swap, paraphrase) on text at the phrase-level. With InstructGPT
models, GrIPS improves the average task performance by up to 4.30 percentage
points on eight classification tasks from the Natural-Instructions dataset. We
see improvements for both instruction-only prompts and for k-shot
example+instruction prompts. Notably, GrIPS outperforms manual rewriting
following the guidelines in Mishra et al. (2022) and also outperforms purely
example-based prompts while controlling for the available compute and data
budget. Lastly, we provide qualitative analysis of the edited instructions
across several scales of GPT models. Our code is available at:
https://github.com/archiki/GrIPS


title: Granular Linkages, Supplier Cost Shocks & Export Performance

abstract:
  This paper presents evidence on the granular nature of firms' network of
foreign suppliers and studies its implications for the impact of supplier
shocks on domestic firms' performance. To demonstrate this, I use customs level
information on transactions between Argentinean firms and foreign firms. I
highlight two novel stylized facts: (i) the distribution of domestic firms'
number of foreign suppliers is highly skewed with the median firm reporting
linkages with only two, (ii) firms focus imported value on one top-supplier,
even when controlling for firm size. Motivated by these facts I construct a
theoretical framework of heterogeneous firms subject to search frictions in the
market for foreign suppliers. Through a calibration exercise I study the
framework's predictions and test them in the data using a shift-share
identification strategy. Results present evidence of significant frictions in
the market for foreign suppliers and strong import-export complementarities.


title: A Logic for Hyperproperties in Multi-Agent Systems

abstract:
  Hyperproperties are commonly used in computer security to define
information-flow policies and other requirements that reason about the
relationship between multiple computations. In this paper, we study a novel
class of hyperproperties where the individual computation paths are chosen by
the strategic choices of a coalition of agents in a multi-agent system. We
introduce HyperATL*, an extension of computation tree logic with path variables
and strategy quantifiers. Our logic can express strategic hyperproperties, such
as that the scheduler in a concurrent system has a strategy to avoid
information leakage. HyperATL* is particularly useful to specify asynchronous
hyperproperties, i.e., hyperproperties where the speed of the execution on the
different computation paths depends on the choices of the scheduler. Unlike
other recent logics for the specification of asynchronous hyperproperties, our
logic is the first to admit decidable model checking for the full logic. We
present a model checking algorithm for HyperATL* based on alternating automata,
and show that our algorithm is asymptotically optimal by providing a matching
lower bound. We have implemented a prototype model checker for a fragment of
HyperATL*, able to check various security properties on small programs.


title:
Relational Diagrams: a pattern-preserving diagrammatic representation of
  non-disjunctive Relational Queries

abstract:
  Analyzing relational languages by their logical expressiveness is well
understood. Something not well understood or even formalized is the vague
concept of relational query patterns. What are query patterns? And how can we
reason about query patterns across different relational languages, irrespective
of their syntax and their procedural or declarative nature? In this paper, we
formalize the concept of query patterns with a variant of pattern-preserving
mappings between the relational atoms of queries. This formalism allows us to
analyze the relative pattern expressiveness of relational query languages and
to create a hierarchy of languages with equal logical expressiveness yet
different pattern expressiveness. In this analysis, relational calculus can
expressive more patterns than the basic operators of relational algebra. We
additionally contribute an intuitive, complete, and sound diagrammatic
representation of safe relational calculus that is not only relationally
complete, but can also express all logical patterns for the large and useful
fragment of non-disjunctive relational calculus. Among all diagrammatic
representations for relational queries that we are aware of, this is the only
one that is relationally complete and that can represent all logical patterns
in the non-disjunctive fragment.


title:
Diversifying Content Generation for Commonsense Reasoning with Mixture
  of Knowledge Graph Experts

abstract:
  Generative commonsense reasoning (GCR) in natural language is to reason about
the commonsense while generating coherent text. Recent years have seen a surge
of interest in improving the generation quality of commonsense reasoning tasks.
Nevertheless, these approaches have seldom investigated diversity in the GCR
tasks, which aims to generate alternative explanations for a real-world
situation or predict all possible outcomes. Diversifying GCR is challenging as
it expects to generate multiple outputs that are not only semantically
different but also grounded in commonsense knowledge. In this paper, we propose
MoKGE, a novel method that diversifies the generative reasoning by a mixture of
expert (MoE) strategy on commonsense knowledge graphs (KG). A set of knowledge
experts seek diverse reasoning on KG to encourage various generation outputs.
Empirical experiments demonstrated that MoKGE can significantly improve the
diversity while achieving on par performance on accuracy on two GCR benchmarks,
based on both automatic and human evaluations.


title: Precision timing for collider-experiment-based calorimetry

abstract:
  In this White Paper for the 2021 Snowmass process, we discuss aspects of
precision timing within electromagnetic and hadronic calorimeter systems for
high-energy physics collider experiments. Areas of applications include
particle identification, event and object reconstruction, and pileup
mitigation. Two different system options are considered, namely cell-level
timing capabilities covering the full detector volume, and dedicated timing
layers integrated in calorimeter systems. A selection of technologies for the
different approaches is also discussed.


title: A TPC-based tracking system for a future Belle II upgrade

abstract:
  In the next decade, intensity frontier experiments will require tracking
systems that are robust against high event and background rates while
maintaining excellent tracking performance. We develop a first conceptual
design of a tracking system for a hypothetical future experiment--here imagined
as a successor to Belle II--built around a time projection chamber (TPC) with
high resolution readout. This choice necessitates a significant expansion of
the silicon vertex detector as well as a new fast timing layer. We simulate the
performance of such a system in the Belle II simulation framework, probe its
major technical challenges, and demonstrate that such a system is suitable for
projected luminosities at the next generation of intensity-frontier colliders.


title:
Local variations of the Stellar Velocity Ellipsoid-II: the effect of the
  bar in the inner regions of Auriga galaxies

abstract:
  Theoretical works have shown that off-plane motions of bars can heat stars in
the vertical direction during buckling but is not clear how do they affect the
rest of components of the Stellar Velocity Ellipsoid (SVE). We study the 2D
spatial distribution of the vertical, $\sigma_{z}$, azimuthal, $\sigma_{\phi}$
and radial, $\sigma_{r}$ velocity dispersions in the inner regions of Auriga
galaxies, a set of high-resolution magneto-hydrodynamical cosmological zoom-in
simulations, to unveil the influence of the bar on the stellar kinematics.
$\sigma_{z}$ and $\sigma_{\phi}$ maps exhibit non-axisymmetric features that
closely match the bar light distribution with low $\sigma$ regions along the
bar major axis and high values in the perpendicular direction. On the other
hand, $\sigma_{r}$ velocity dispersion maps present more axisymmetric
distributions. We show that isophotal profile differences best capture the
impact of the bar on the three SVE components providing strong correlations
with bar morphology proxies although there is no relation with individual
$\sigma$. Time evolution analysis shows that these differences are a
consequence of the bar formation and that they tightly coevolve with the
strength of the bar. We discuss the presence of different behaviours of
$\sigma_{z}$ and its connection with observations. This work helps us
understand the intrinsic $\sigma$ distribution and motivates the use of
isophotal profiles as a mean to quantify the effect of bars.


title:
A Phase-field model for simulating hydrogen-induced pitting corrosion
  with solid-solid phase transformation in the metal

abstract:
  Hydrogen-induced pitting corrosion of metallic is a common phenomenon that
damages the integrity and durability of the materials. Its numerical simulation
is still a challenge due to many complex mechanisms, especially solid-solid
phase transformation and mechanical interaction, leading to the anisotropic
growth of hydride and inducing some bulges on the metal surface. In our work,
we propose a phase-field model and numerical technique for simulation of
hydrogen-induced pitting corrosion, and apply it to the system of
$\alpha$-Uranium. In our model, the elastic strain energy is introduced to
approximate the anisotropic pit morphology induced by the mechanical
interaction between metal and hydride. For the numerical technique, the free
boundary condition based on the finite element method is adopted to introduce
the bulges of the metal surface. By the application of our model and numerical
technique, the anisotropic pit morphology with a bulge on the metal surface in
agreement with experiments of $\alpha$-Uranium is obtained. Moreover, the
compression of $\alpha$-Uranium and the dilation of its hydride are discovered,
which develops the deep understanding of hydrogen-induced pitting corrosion.
This model is expected to be applied to the health detection of
hydrogen-induced pitting corrosion of metal in the industry.


title: GradTac: Spatio-Temporal Gradient Based Tactile Sensing

abstract:
  Tactile sensing for robotics is achieved through a variety of mechanisms,
including magnetic, optical-tactile, and conductive fluid. Currently, the
fluid-based sensors have struck the right balance of anthropomorphic sizes and
shapes and accuracy of tactile response measurement. However, this design is
plagued by a low Signal to Noise Ratio (SNR) due to the fluid based sensing
mechanism "damping" the measurement values that are hard to model. To this end,
we present a spatio-temporal gradient representation on the data obtained from
fluid-based tactile sensors, which is inspired from neuromorphic principles of
event based sensing. We present a novel algorithm (GradTac) that converts
discrete data points from spatial tactile sensors into spatio-temporal surfaces
and tracks tactile contours across these surfaces. Processing the tactile data
using the proposed spatio-temporal domain is robust, makes it less susceptible
to the inherent noise from the fluid based sensors, and allows accurate
tracking of regions of touch as compared to using the raw data. We successfully
evaluate and demonstrate the efficacy of GradTac on many real-world experiments
performed using the Shadow Dexterous Hand, equipped with the BioTac SP sensors.
Specifically, we use it for tracking tactile input across the sensor's surface,
measuring relative forces, detecting linear and rotational slip, and for edge
tracking. We also release an accompanying task-agnostic dataset for the BioTac
SP, which we hope will provide a resource to compare and quantify various novel
approaches, and motivate further research.


title:
Snowmass2021 Cosmic Frontier White Paper: High Density Galaxy Clustering
  in the Regime of Cosmic Acceleration

abstract:
  Joint studies of imaging and spectroscopic samples, informed by theory and
simulations, offer the potential for comprehensive tests of the cosmological
model over redshifts z<1.5. Spectroscopic galaxy samples at these redshifts can
be increased beyond the planned Dark Energy Spectroscopic Instrument (DESI)
program by at least an order of magnitude, thus offering significantly more
constraining power for these joint studies. Spectroscopic observations of these
galaxies in the latter half of the 2020's and beyond would leverage the theory
and simulation effort in this regime. In turn, these high density observations
will allow enhanced tests of dark energy, physics beyond the standard model,
and neutrino masses that will greatly exceed what is currently possible. Here,
we present a coordinated program of simulations, theoretical modeling, and
future spectroscopy that would enable precise cosmological studies in the
accelerating epoch where the effects of dark energy are most apparent.


title: Hyperbolic topological band insulators

abstract:
  The Bloch band theory describes energy levels of crystalline media by a
collection of bands in momentum space. These bands can be characterized by
non-trivial topological invariants, which via bulk-boundary correspondence
imply protected boundary states inside the bulk energy gap. Recently,
hyperbolic lattices that tile the negatively curved hyperbolic plane emerged as
a new paradigm of synthetic matter, and their energy levels were characterized
by a band structure in a four- (or higher-)dimensional momentum space. To
explore the uncharted topological aspects arising in hyperbolic band theory, we
here introduce elementary models of hyperbolic topological band insulators: the
hyperbolic Haldane model and the hyperbolic Kane-Mele model; both obtained by
replacing the hexagonal cells of their Euclidean counterparts by octagons.
Their non-trivial topology is revealed by computing topological invariants in
both position and momentum space. The bulk-boundary correspondence is evidenced
by comparing bulk and boundary density of states, by modelling propagation of
edge excitations, and by their robustness against disorder.


title: InsetGAN for Full-Body Image Generation

abstract:
  While GANs can produce photo-realistic images in ideal conditions for certain
domains, the generation of full-body human images remains difficult due to the
diversity of identities, hairstyles, clothing, and the variance in pose.
Instead of modeling this complex domain with a single GAN, we propose a novel
method to combine multiple pretrained GANs, where one GAN generates a global
canvas (e.g., human body) and a set of specialized GANs, or insets, focus on
different parts (e.g., faces, shoes) that can be seamlessly inserted onto the
global canvas. We model the problem as jointly exploring the respective latent
spaces such that the generated images can be combined, by inserting the parts
from the specialized generators onto the global canvas, without introducing
seams. We demonstrate the setup by combining a full body GAN with a dedicated
high-quality face GAN to produce plausible-looking humans. We evaluate our
results with quantitative metrics and user studies.


title:
The ESO-VLT MIKiS survey reloaded: velocity dispersion profile and
  rotation curve of NGC 1904

abstract:
  We present an investigation of the internal kinematic properties of M79 (NGC
1904). Our study is based on radial velocity measurements obtained from the
ESO-VLT Multi-Instrument Kinematic Survey (MIKiS) of Galactic globular clusters
for more than 1700 individual stars distributed between $\sim
0.3^{\prime\prime}$ and $770^{\prime\prime}$ ($\sim14$ three-dimensional
half-mass radii), from the center. Our analysis reveals the presence of ordered
line-of-sight rotation with a rotation axis almost aligned along the East-West
direction and a velocity peak of $1.5$ km s$^{-1}$ at $\sim 70^{\prime\prime}$
from the rotation axis. The velocity dispersion profile is well described by
the same King model that best fits the projected density distribution, with a
constant central plateau at $\sigma_0\sim 6$ km s$^{-1}$. To investigate the
cluster rotation in the plane of the sky, we have analyzed the proper motions
provided by the Gaia EDR3, finding a signature of rotation with a maximum
amplitude of $\sim 2.0$ km s$^{-1}$ at $\sim 80^{\prime\prime}$ from the
cluster center. Analyzing the three-dimensional velocity distribution, for a
sub-sample of 130 stars, we confirm the presence of systemic rotation and find
a rotation axis inclination angle of $37${\deg} with respect to the
line-of-sight. As a final result, the comparison of the observed rotation
curves with the results of a representative N-body simulation of a rotating
star cluster shows that the present-day kinematic properties of NGC 1904 are
consistent with those of a dynamically old system that has lost a significant
fraction of its initial angular momentum.


title: Open-Air Microwave Entanglement Distribution for Quantum Teleportation

abstract:
  Microwave technology plays a central role in current wireless communications,
standing among them mobile communication and local area networks (LANs). The
microwave range shows relevant advantages with respect to other frequencies in
open-air transmission, such as low absorption losses and low energy
consumption, and it is additionally the natural working frequency in
superconducting quantum technologies. Entanglement distribution between
separate parties is at the core of secure quantum communications. Therefore,
understanding its limitations in realistic open-air settings, specially in the
rather unexplored microwave regime, is crucial for transforming microwave
quantum communications into a mainstream technology. Here, we investigate the
feasibility of an open-air entanglement distribution scheme with microwave
two-mode squeezed states. First, we study the reach of direct entanglement
transmission in open-air, obtaining a maximum distance of approximately 500
meters in a realistic setting with state-of-the-art experimental parameters.
Afterwards, we adapt entanglement distillation and entanglement swapping
protocols to microwave technology in order to reduce environmental entanglement
degradation. While entanglement distillation helps to increase quantum
correlations in the short-distance low-squeezing regime by up to $46\%$,
entanglement swapping increases the reach by $14\%$. Then, we compute the
fidelity of a continuous-variable quantum teleportation protocol using
open-air-distributed entanglement as a resource. Finally, we adapt the
machinery to explore the limitations of quantum communication between
satellites, where the thermal noise impact is substantially reduced and
diffraction losses are dominant.


title: Non self-adjoint perturbations of the Heisenberg sublaplacian

abstract:
  We prove uniform resolvent estimates in weighted $L^2$-spaces for the
sublaplacian $\mathcal{L}$ on the Heisenberg group $\mathbb{H}^d$. The proof
are based on multiplier methods, and strongly rely on the use of horizontal
multipliers and the associated Hardy inequalities. The constants of our
inequalities are explicit and depend only on the dimension $d$. As applications
of this method, we obtain some suitable smallness and repulsivity conditions on
a complex potential $V$ on $\mathbb{H}^d$ such that the spectrum of
$\mathcal{L}+V$ does not contain eigenvalues.


title: First-passage percolation on random simple triangulations

abstract:
  We study first-passage percolation on random simple triangulations and their
dual maps with independent identically distributed link weights. Our main
result shows that the first-passage percolation distance concentrates in an
$o_p(n^{1/4})$ window around a constant multiple of the graph distance.


title:
Violation of bound on chaos for charged probe in Kerr-Newman-AdS black
  hole

abstract:
  We investigate the conjectured bound on the Lyapunov exponent for a charged
particle with angular motion in the Kerr-Newman-AdS black hole. The Lyapunov
exponent is calculated based on the effective Lagrangian. We show that the
negative cosmological constant reduces the chaotic behavior of the particle,
namely, it decreases the Lyapunov exponent. Hence, the bound is more effective
in the AdS spacetime than in the flat spacetime. Nevertheless, we find that the
bound can be violated when the angular momenta of the black hole are turned on.
Moreover, we show that in an extremal black hole, the bound is more easily
violated compared to the nonextremal black hole.


title:
Embedding between Lebesgue and weak Lebesgue sequence spaces is strictly
  singular

abstract:
  Given $1< p < q < \infty$ it is well know that the natural embedding of
Lebesgue sequence spaces $\ell_p \hookrightarrow \ell_q$ is strictly singular.
In this paper we extend this classical results and show that even the natural
non-compact embedding between Lebesgue and weak Lebesgue sequence spaces
$\ell_{p}\hookrightarrow \ell_{p,\infty}$ is strictly singular.


title: Mobile Behavioral Biometrics for Passive Authentication

abstract:
  Current mobile user authentication systems based on PIN codes, fingerprint,
and face recognition have several shortcomings. Such limitations have been
addressed in the literature by exploring the feasibility of passive
authentication on mobile devices through behavioral biometrics. In this line of
research, this work carries out a comparative analysis of unimodal and
multimodal behavioral biometric traits acquired while the subjects perform
different activities on the phone such as typing, scrolling, drawing a number,
and tapping on the screen, considering the touchscreen and the simultaneous
background sensor data (accelerometer, gravity sensor, gyroscope, linear
accelerometer, and magnetometer). Our experiments are performed over HuMIdb,
one of the largest and most comprehensive freely available mobile user
interaction databases to date. A separate Recurrent Neural Network (RNN) with
triplet loss is implemented for each single modality. Then, the weighted fusion
of the different modalities is carried out at score level. In our experiments,
the most discriminative background sensor is the magnetometer, whereas among
touch tasks the best results are achieved with keystroke in a fixed-text
scenario. In all cases, the fusion of modalities is very beneficial, leading to
Equal Error Rates (EER) ranging from 4% to 9% depending on the modality
combination in a 3-second interval.


title: Psitrum: An Open Source Simulator for Universal Quantum Computers

abstract:
  Quantum computing is a radical new paradigm for a technology that is capable
to revolutionize information processing. Simulators of universal quantum
computer are important for understanding the basic principles and operations of
the current noisy intermediate-scale quantum (NISQ) processors, and for
building in future fault-tolerant quantum computers. In this work, we present
simulation of universal quantum computers by introducing Psitrum -- a universal
gate-model quantum computer simulator implemented on classical hardware. The
simulator allows to emulate and debug quantum algorithms in form of quantum
circuits for many applications with the choice of adding variety of noise
modules to simulate decoherence in quantum circuits. Psitrum allows to simulate
all basic quantum operations and provides variety of visualization tools. The
simulator allows to trace out all possible quantum states at each stage M of an
N-qubit implemented quantum circuit. Psitrum software and source codes are
freely available at:
\href{https://github.com/MoGhadeer/Psitrum}{https://github.com/MoGhadeer/Psitrum} .


title:
Do DNNs trained on Natural Images organize visual features into
  Gestalts?

abstract:
  Gestalt psychologists have identified a range of conditions in which humans
organize elements of a scene into a group or whole, and these perceptual
grouping principles play an important role in scene perception and object
identification. More recently, Deep Neural Networks (DNNs) trained on natural
images have been proposed as compelling models of human vision based on reports
that they perform well on various brain and behavioral benchmarks. Here we
compared human and DNNs responses in discrimination judgments that assess a
range of Gestalt organization principles. We found that most networks exhibited
a moderate degree of Gestalt grouping for some complex stimuli at the last
fully connected layer. However, in contrast with human neural data, this
sensitivity vanishes at earlier visual processing layers. In a second
experiment, by using simple dots configuration patterns, we found that all
networks were only weakly sensitive to the grouping properties of proximity,
and completely insensitive to orientation and linearity, three principles that
have been shown to have a strong and robust effect on humans. Even
top-performing models on the behavioral and brain benchmark Brain-Score miss
these fundamental properties of human vision. Our overall conclusion is that,
even when exhibiting Gestalt grouping, networks trained on 2D images use
perceptual principles fundamentally different than humans.


title: All in One: Exploring Unified Video-Language Pre-training

abstract:
  Mainstream Video-Language Pre-training models \cite{actbert,clipbert,violet}
consist of three parts, a video encoder, a text encoder, and a video-text
fusion Transformer. They pursue better performance via utilizing heavier
unimodal encoders or multimodal fusion Transformers, resulting in increased
parameters with lower efficiency in downstream tasks. In this work, we for the
first time introduce an end-to-end video-language model, namely
\textit{all-in-one Transformer}, that embeds raw video and textual signals into
joint representations using a unified backbone architecture. We argue that the
unique temporal information of video data turns out to be a key barrier
hindering the design of a modality-agnostic Transformer. To overcome the
challenge, we introduce a novel and effective token rolling operation to encode
temporal representations from video clips in a non-parametric manner. The
careful design enables the representation learning of both video-text
multimodal inputs and unimodal inputs using a unified backbone model. Our
pre-trained all-in-one Transformer is transferred to various downstream
video-text tasks after fine-tuning, including text-video retrieval,
video-question answering, multiple choice and visual commonsense reasoning.
State-of-the-art performances with the minimal model FLOPs on nine datasets
demonstrate the superiority of our method compared to the competitive
counterparts. The code and pretrained model have been released in
https://github.com/showlab/all-in-one.


title: $L^2$-Gradient Flows of Spectral Functionals

abstract:
  We study the $L^2$-gradient flow of functionals $\mathcal F$ depending on the
eigenvalues of Schr\"odinger potentials $V$ for a wide class of differential
operators associated to closed, symmetric, and coercive bilinear forms,
including the case of all the Dirichlet forms (as for second order elliptic
operators in Euclidean domains or Riemannian manifolds).
  We suppose that $\mathcal F$ arises as the sum of a $-\theta$-convex
functional $\mathcal K$ with proper domain $\mathbb{K}\subset L^2$ forcing the
admissible potentials to stay above a constant $V_{\rm min}$ and a term
$\mathcal H(V)=\varphi(\lambda_1(V),\cdots,\lambda_J(V))$ which depends on the
first $J$ eigenvalues associated to $V$ through a $C^1$ function $\varphi$.
  Even if $\mathcal H$ is not a smooth perturbation of a convex functional (and
it is in fact concave in simple important cases as the sum of the first $J$
eigenvalues) and we do not assume any compactness of the sublevels of $\mathcal
K$, we prove the convergence of the Minimizing Movement method to a solution
$V\in H^1(0,T;L^2)$ of the differential inclusion $V'(t)\in
-\partial_L^-\mathcal F(V(t))$, which under suitable compatibility conditions
on $\varphi$ can be written as \[
V'(t)+\sum_{i=1}^J\partial_i\varphi(\lambda_1(V(t)),\dots,
\lambda_J(V(t)))u_i^2(t)\in -\partial_F^-\mathcal K(V(t)) \] where
$(u_1(t),\dots, u_J(t))$ is an orthonormal system of eigenfunctions associated
to the eigenvalues $(\lambda_1(V(t)), ,\dots,\lambda_J(V(t)))$.


title:
Branch-and-Bound Performance Estimation Programming: A Unified
  Methodology for Constructing Optimal Optimization Methods

abstract:
  We present the Branch-and-Bound Performance Estimation Programming (BnB-PEP),
a unified methodology for constructing optimal first-order methods for convex
and nonconvex optimization. BnB-PEP poses the problem of finding the optimal
optimization method as a nonconvex but practically tractable quadratically
constrained quadratic optimization problem and solves it to certifiable global
optimality using a customized branch-and-bound algorithm. By directly
confronting the nonconvexity, BnB-PEP offers significantly more flexibility and
removes the many limitations of the prior methodologies. Our customized
branch-and-bound algorithm, through exploiting specific problem structures,
outperforms the latest off-the-shelf implementations by orders of magnitude,
accelerating the solution time from hours to seconds and weeks to minutes. We
apply BnB-PEP to several setups for which the prior methodologies do not apply
and obtain methods with bounds that improve upon prior state-of-the-art
results. Finally, we use the BnB-PEP methodology to find proofs with potential
function structures, thereby systematically generating analytical convergence
proofs.


title: The scaling limit of random cubic planar graphs

abstract:
  We study the random simple connected cubic planar graph $\mathsf{C}_n$ with
an even number $n$ of vertices. We show that the Brownian map arises as
Gromov--Hausdorff--Prokhorov scaling limit of $\mathsf{C}_n$ as $n \in 2 \ndN$
tends to infinity, after rescaling distances by $\gamma n^{-1/4} $ for a
specific constant $\gamma>0$.


title:
S5CL: Unifying Fully-Supervised, Self-Supervised, and Semi-Supervised
  Learning Through Hierarchical Contrastive Learning

abstract:
  In computational pathology, we often face a scarcity of annotations and a
large amount of unlabeled data. One method for dealing with this is
semi-supervised learning which is commonly split into a self-supervised pretext
task and a subsequent model fine-tuning. Here, we compress this two-stage
training into one by introducing S5CL, a unified framework for
fully-supervised, self-supervised, and semi-supervised learning. With three
contrastive losses defined for labeled, unlabeled, and pseudo-labeled images,
S5CL can learn feature representations that reflect the hierarchy of distance
relationships: similar images and augmentations are embedded the closest,
followed by different looking images of the same class, while images from
separate classes have the largest distance. Moreover, S5CL allows us to
flexibly combine these losses to adapt to different scenarios. Evaluations of
our framework on two public histopathological datasets show strong improvements
in the case of sparse labels: for a H&E-stained colorectal cancer dataset, the
accuracy increases by up to 9% compared to supervised cross-entropy loss; for a
highly imbalanced dataset of single white blood cells from leukemia patient
blood smears, the F1-score increases by up to 6%.


title:
Accelerating Plug-and-Play Image Reconstruction via Multi-Stage Sketched
  Gradients

abstract:
  In this work we propose a new paradigm for designing fast plug-and-play (PnP)
algorithms using dimensionality reduction techniques. Unlike existing
approaches which utilize stochastic gradient iterations for acceleration, we
propose novel multi-stage sketched gradient iterations which first perform
downsampling dimensionality reduction in the image space, and then efficiently
approximate the true gradient using the sketched gradient in the
low-dimensional space. This sketched gradient scheme can also be naturally
combined with PnP-SGD methods for further improvement on computational
complexity. As a generic acceleration scheme, it can be applied to accelerate
any existing PnP/RED algorithm. Our numerical experiments on X-ray fan-beam CT
demonstrate the remarkable effectiveness of our scheme, that a computational
free-lunch can be obtained using this dimensionality reduction in the image
space.


title:
Shadow Distillation: Quantum Error Mitigation with Classical Shadows for
  Near-Term Quantum Processors

abstract:
  Mitigating errors in quantum information processing devices is especially
important in the absence of fault tolerance. An effective method in suppressing
state-preparation errors is using multiple copies to distill the ideal
component from a noisy quantum state. Here, we use classical shadows and
randomized measurements to circumvent the need for coherent access to multiple
copies at an exponential cost. We study the scaling of resources using
numerical simulations and find that the overhead is still favorable compared to
full state tomography. We optimize measurement resources under realistic
experimental constraints and apply our method to an experiment preparing
Greenberger-Horne-Zeilinger (GHZ) state with trapped ions. In addition to
improving stabilizer measurements, the analysis of the improved results reveals
the nature of errors affecting the experiment. Hence, our results provide a
directly applicable method for mitigating errors in near-term quantum
computers.


title:
Noncollinear antiferromagnetic textures driven high harmonic generation
  from magnetic dynamics in the absence of spin-orbit coupling

abstract:
  We demonstrate the generation of high order harmonics in carrier pumping from
precessing ferromagnetic or antiferromagnetic orders, excited via magnetic
resonance, in the presence of topological antiferromagnetic textures. This
results in an enhancement of the carrier dynamics by orders of magnitude.
Interestingly, the generation process occurs in an intrinsic manner, and is
solely governed by the interplay between the s-d exchange coupling underlying
the noncollinear antiferromagnetic order and the dynamical s-d exchange
parameter of the magnetic drive. Therefore, the relativistic spin-orbit
interaction is not required for the emergence of high harmonics in the pumped
currents. Accordingly, the noncollinear topological antiferromagnetic order is
presented as an alternative to spin-orbit interaction for the purpose of
harnessing high harmonic emission in carrier pumping. Our proposal initiates a
tantalizing perspective for the exploitation of topological magnetic textures
in the context of the highly active domain of ultrafast spintronics.


title:
Entanglements and Whitehead Products: Generalizing Kleman's Construction
  to Higher-Dimensional Defects

abstract:
  We review the interpretation of Whitehead products in homotopy theory as an
entanglement of topological defects in ordered media.


title:
Revisiting Kepler Transiting Systems: Unvetting Planets and Constraining
  Relationships among Harmonics in Phase Curves

abstract:
  Space-based photometric missions widely use statistical validation tools for
vetting transiting planetary candidates, particularly when other traditional
methods of planet confirmation are unviable. In this paper, we refute the
planetary nature of three previously validated planets -- Kepler-854~b,
Kepler-840~b, and Kepler-699~b -- and possibly a fourth, Kepler-747~b, using
updated stellar parameters from Gaia and phase-curve analysis. In all four
cases, the inferred physical radii rule out their planetary nature given the
stellar radiation the companions receive. For Kepler-854~b, the mass derived
from the host star's ellipsoidal variation, which had not been part of the
original vetting procedure, similarly points to a non-planetary value. To
contextualize our understanding of the phase curve for stellar mass companions
in particular and extend our understanding of high-order harmonics, we examine
Kepler eclipsing binaries with periods between 1.5 and 10 days. Using a sample
of 20 systems, we report a strong power-law relation between the second cosine
harmonic of the phase-curve signal and the higher cosine harmonics, which
supports the hypothesis that those signals arise from the tidal interaction
between the binary components. We find that the ratio between the second and
third-harmonic amplitudes is $2.24 \pm 0.48$, in good agreement with the
expected value of 2.4 from the classical formalism for the ellipsoidal
distortion.


title:
Loewner evolution driven by complex Brownian motion (with simulations by
  Minjae Park)

abstract:
  We study the Loewner evolution whose driving function is $W_t = B_t^1 + i
B_t^2$, where $(B^1,B^2)$ is a pair of Brownian motions with a given covariance
matrix. This model can be thought of as a generalization of Schramm-Loewner
evolution (SLE) with complex parameter values. We show that our Loewner
evolutions behave very differently from ordinary SLE. For example, if neither
$B^1$ nor $B^2$ is identically equal to zero, then the set of points
disconnected from $\infty$ by the Loewner hull has non-empty interior at each
time. We also show that our model exhibits three phases analogous to the phases
of SLE: a phase where the hulls have zero Lebesgue measure, a phase where
points are swallowed but not hit by the hulls, and a phase where the hulls are
space-filling. The phase boundaries are expressed in terms of the signs of
explicit integrals. These boundaries have a simple closed form when the
correlation of the two Brownian motions is zero.


title: Track-Based Triggers for Exotic Signatures

abstract:
  Standard triggers at the Large Hadron Collider are designed to select events
with high momentum Standard Model particles which originate from the
proton-proton collision of interest. However, several Beyond the Standard Model
scenarios predict signatures with displaced or extremely low momentum charged
particles, and pose significant challenges for LHC triggers. This article
presents a study of track-based triggers for long-lived particles and other
unconventional exotic signatures at the upcoming High Luminosity LHC.
Representative scenarios studied include soft-unclustered-energy-patterns
resulting in large multiplicities of low momentum tracks, a GMSB Supersymmetry
scenario with long-lived staus resulting in displaced leptons or anomalous
prompt tracks, and a higgs portal scenario with long-lived scalars resulting in
displaced hadronic tracks. Trigger efficiency is measured as a function of the
baseline parameters of a track trigger, including transverse momentum and
impact parameters. Recommendations for future hardware-based track triggers are
presented.


title: Producing "new" semi-orthogonal decompositions in arithmetic geometry

abstract:
  This paper is dedicated to constructing "new" admissible subcategories and
semi-orthogonal decompositions of triangulated categories out of "old" ones.
For two triangulated subcategories $T$ and $T'$ of a certain $D$ and a
decomposition $(L,R)$ of $T$ we look either for a decomposition $(L',R')$ of
$T'$ such that there are no non-zero $D$-morphisms from $L$ into $L'$ and from
$R$ into $R'$, or for a decomposition $(L_D,R_D)$ of $D$ such that $L_D\cap
T=L$ and $R_D\cap T=R$. We prove some general existence statements (that also
extend to semi-orthogonal decompositions with any number of components) and
apply them to various derived categories of coherent sheaves over a scheme $X$
that is proper over a noetherian ring $R$. This gives a one-to-one
correspondence between semi-orthogonal decompositions of $D_{perf}(X)$ and
$D^b_{coh}(X)$; the latter extend to $D^-_{coh}(X)$, $D^+_{coh}(X)$,
$D_{coh}(X)$ and $D_{qcoh}(X)$ under very mild conditions. In particular, we
obtain a vast generalization of a theorem of J. Karmazyn, A. Kuznetsov, and E.
Shinder.
  These applications rely on recent results of Neeman that express
$D^b_{coh}(X)$ and $D^-_{coh}(X)$ in terms of $D_{perf}(X)$ along with a
(rather similar) new theorem relating $D^+_{coh}(X)$ and $D_{coh}(X)$ to
homological functors $D_{perf}(X)^{op}\to R-mod$ as well. We also discuss an
application of this theorem to the construction of certain adjoint functors.