title:
Gravitational dynamics in Higgs inflation: Preinflation and preheating
  with an auxiliary field

abstract:
  The dynamics of both the preinflationary and the preheating epochs for a
model consisting of a Higgs inflaton plus an additional auxiliary field are
studied in full General Relativity. The minimally coupled auxiliary field
allows for parametric-type resonances that successfully transfer energy from
the inflaton condensate to particle excitations in both fields. Depending on
the interaction strengths of the fields, the broad resonance periods lead to
structure formation consisting of large under/over-densities, and possibly the
formation of compact objects. Moreover, when confronting the same model to
multi-field inhomogeneous preinflation, the onset of inflation is shown to be a
robust outcome. At relatively large Higgs values, the non-minimal coupling acts
as a stabilizer, protecting the dynamics of the inflaton, and significantly
reducing the impact of perturbations in other fields and matter sectors. These
investigations further confirm the robustness of Higgs inflation to multi-field
inhomogeneous initial conditions, while putting in evidence the formation of
complex structures during the reheating.


title:
UserBERT: Modeling Long- and Short-Term User Preferences via
  Self-Supervision

abstract:
  E-commerce platforms generate vast amounts of customer behavior data, such as
clicks and purchases, from millions of unique users every day. However,
effectively using this data for behavior understanding tasks is challenging
because there are usually not enough labels to learn from all users in a
supervised manner. This paper extends the BERT model to e-commerce user data
for pre-training representations in a self-supervised manner. By viewing user
actions in sequences as analogous to words in sentences, we extend the existing
BERT model to user behavior data. Further, our model adopts a unified structure
to simultaneously learn from long-term and short-term user behavior, as well as
user attributes. We propose methods for the tokenization of different types of
user behavior sequences, the generation of input representation vectors, and a
novel pretext task to enable the pre-trained model to learn from its own input,
eliminating the need for labeled training data. Extensive experiments
demonstrate that the learned representations result in significant improvements
when transferred to three different real-world tasks, particularly compared to
task-specific modeling and multi-task representation learning


title:
Improving Pedestrian Prediction Models with Self-Supervised Continual
  Learning

abstract:
  Autonomous mobile robots require accurate human motion predictions to safely
and efficiently navigate among pedestrians, whose behavior may adapt to
environmental changes. This paper introduces a self-supervised continual
learning framework to improve data-driven pedestrian prediction models online
across various scenarios continuously. In particular, we exploit online streams
of pedestrian data, commonly available from the robot's detection and tracking
pipeline, to refine the prediction model and its performance in unseen
scenarios. To avoid the forgetting of previously learned concepts, a problem
known as catastrophic forgetting, our framework includes a regularization loss
to penalize changes of model parameters that are important for previous
scenarios and retrains on a set of previous examples to retain past knowledge.
Experimental results on real and simulation data show that our approach can
improve prediction performance in unseen scenarios while retaining knowledge
from seen scenarios when compared to naively training the prediction model
online.


title: The Hybrid Bootstrap

abstract:
  Finding a method to combine the numerical bootstrap with the analytic
lightcone bootstrap is an important goal to advance the conformal bootstrap
program. We propose a hybrid bootstrap method to do just that. The numerical
and analytic bootstrap approaches are sensitive to different regions of the
spectrum and complement each other. When they are effectively combined, the
hybrid bootstrap enjoys the best of both worlds and the prediction for the
actual CFT can be significantly improved. In this work, we discuss the general
strategy to perform such a hybrid bootstrap, and we make a partial
implementation of the strategy for 3D Ising CFT $\{\sigma,\epsilon\}$ system.
Even at relatively low derivative order $\Lambda=19$, the hybrid bootstrap
predicts very precise values for the scaling dimension
$\Delta_\sigma,\Delta_\epsilon$ that are within the previous $\Lambda=43$
rigorous error bars.


title: Graphs of bounded twin-width are quasi-polynomially $\chi$-bounded

abstract:
  We prove that for every $t\in \mathbb{N}$ there is a constant $\gamma_t$ such
that every graph with twin-width at most $t$ and clique number $\omega$ has
chromatic number bounded by $2^{\gamma_t \log^{4t+3} \omega}$. In other words,
we prove that graph classes of bounded twin-width are quasi-polynomially
$\chi$-bounded. This provides a significant step towards resolving the question
of Bonnet et al. [ICALP 2021] about whether they are polynomially
$\chi$-bounded.


title: The Evolution of U.S. Retail Concentration

abstract:
  Increases in national concentration have been a salient feature of industry
dynamics in the U.S. and have contributed to concerns about increasing market
power. Yet, local trends may be more informative about market power,
particularly in the retail sector where consumers have traditionally shopped at
nearby stores. We find that local concentration has increased almost in
parallel with national concentration using novel Census data on product-level
revenue for all U.S. retail stores. The increases in concentration are broad
based, affecting most markets, products, and retail industries. We implement a
new decomposition of the national Herfindahl-Hirschman Index and show that
despite similar trends, national and local concentration reflect different
changes in the retail sector. The increase in national concentration comes from
consumers in different markets increasingly buying from the same firms and does
not reflect changes in local market power. We estimate a model of retail
competition which links local concentration to markups. The model implies that
the increase in local concentration explains one-third of the observed increase
in markups.


title:
Sensitivity to large losses and $\rho$-arbitrage for convex risk
  measures

abstract:
  This paper studies mean-risk portfolio selection in a one-period financial
market, where risk is quantified by a star-shaped risk measure $\rho$. We
introduce two new axioms: weak and strong sensitivity to large losses. We show
that the first axiom is key to ensure the existence of optimal portfolios and
the second one is key to ensure the absence of $\rho$-arbitrage.
  This leads to a new class of risk measures that are suitable for portfolio
selection. We show that $\rho$ belongs to this class if and only if $\rho$ is
real-valued and the smallest positively homogeneous risk measure dominating
$\rho$ is the worst-case risk measure.
  We then specialise to the case that $\rho$ is convex and admits a dual
representation. We derive necessary and sufficient dual characterisations of
(strong) $\rho$-arbitrage as well as the property that $\rho$ is suitable for
portfolio selection. Finally, we introduce the new risk measure of Loss
Sensitive Expected Shortfall, which is similar to and not more complicated to
compute than Expected Shortfall but suitable for portfolio selection -- which
Expected Shortfall is not.


title:
Quasilinear Schr\"odinger equations with Stein-Weiss type convolution
  and critical exponential nonlinearity in $\mathbb R^N$

abstract:
  In this article, we investigate the existence of the positive solutions to
the following class of quasilinear {Schr\"odinger} equations involving
Stein-Weiss type convolution
  \begin{align*}
  -\Delta_N u -\Delta_N (u^{2})u +V(x)|u|^{N-2}u=
  \left(\int_{\mathbb
R^N}\frac{F(y,u)}{|y|^\beta|x-y|^{\mu}}~dy\right)\frac{f(x,u)}{|x|^\beta} \;\;
\text{ in}\;
  \mathbb R^N,
  \end{align*} where $N\geq 2,\,$ $0<\mu<N,\, \beta\geq 0,$ and $2\beta+\mu\leq
N.$ The potential $V:\mathbb R^N\to \mathbb R$ is a continuous function
satisfying $0<V_0\leq V(x)$ for all $x\in \mathbb R^N$ and $\lim_{|x|\to
+\infty} V(x)=V_\infty$. The nonlinearity $f:\mathbb R^N\times \mathbb R\to
\mathbb R$ is a continuous function with critical exponential growth in the
sense of the Trudinger-Moser inequality and $F(x,s)=\int_{0}^s f(x,t)dt$ is the
primitive of $f$.


title:
CodeGen-Test: An Automatic Code Generation Model Integrating Program
  Test Information

abstract:
  Automatic code generation is to generate the program code according to the
given natural language description. The current mainstream approach uses neural
networks to encode natural language descriptions, and output abstract syntax
trees (AST) at the decoder, then convert the AST into program code. While the
generated code largely conforms to specific syntax rules, two problems are
still ignored. One is missing program testing, an essential step in the process
of complete code implementation; the other is only focusing on the syntax
compliance of the generated code, while ignoring the more important program
functional requirements. The paper proposes a CodeGen-Test model, which adds
program testing steps and incorporates program testing information to
iteratively generate code that meets the functional requirements of the
program, thereby improving the quality of code generation. At the same time,
the paper proposes a new evaluation metric, test accuracy (Test-Acc), which
represents the proportion of passing program test in generated code. Different
from the previous evaluation metric, which only evaluates the quality of code
generation from the perspective of character similarity, the Test-Acc can
evaluate the quality of code generation from the Program functions. Moreover,
the paper evaluates the CodeGen-test model on a python data set "hearthstone
legend". The experimental results show the proposed method can effectively
improve the quality of generated code. Compared with the existing optimal
model, CodeGen-Test model improves the Bleu value by 0.2%, Rouge-L value by
0.3% and Test-Acc by 6%.


title:
$q$-deformed rational numbers and the 2-Calabi--Yau category of type
  $A_2$

abstract:
  We describe a family of compactifications of the space of Bridgeland
stability conditions of any triangulated category following earlier work by
Bapat, Deopurkar, and Licata. We particularly consider the case of the
2-Calabi--Yau category of the $A_2$ quiver. The compactification is the closure
of an embedding (depending on $q$) of the stability space into an
infinite-dimensional projective space.
  In the $A_2$ case, the three-strand braid group $B_3$ acts on this closure.
We describe two distinguished braid group orbits in the boundary, points of
which can be identified with certain rational functions in $q$. Points in one
of the orbits are exactly the $q$-deformed rational numbers recently introduced
by Morier-Genoud and Ovsienko, while the other orbit gives a new
$q$-deformation of the rational numbers. Specialising $q$ to a positive real
number, we obtain a complete description of the boundary of the
compactification.


title:
Judging a socially assistive robot (SAR) by its cover; The effect of
  body structure, outline, and color on users' perception

abstract:
  Human-SAR (socially assistive robot) relationships vary by the context of use
and interaction level. We argue that context and interaction considerations
must be incorporated into the SAR's physical design requirements to align the
robotic visual qualities (VQs) with users' expectations. We propose to consider
situational-based and dynamics-based human-SAR relationship models in
constructing the requirements. Previous studies contributed to the
understanding of users` perceptions and preferences regarding existing
commercially available SARs. Yet, very few studies regarding SARs' appearance
used designated SAR designs, and even fewer evaluated isolated visual features.
In this work, we aim to systematically assess the effect of isolated VQs. To
achieve this, we first deconstruct the VQs attributed to SARs. Then, a
reconstruction of body structure, outline, and color scheme was done, resulting
in the creation of 30 new SAR models that differ in their VQs, allowing us to
isolate one character at a time. We used these new designs to evaluate users'
preferences and perceptions in two empirical studies. Our empirical findings
link visual qualities with perceptions of SAR characteristics. Together with
the relationship models, the outcomes are an exemplar of how to form guidelines
for the industrial design processes of new SARs to match user expectations.


title: PILED: An Identify-and-Localize Framework for Few-Shot Event Detection

abstract:
  Practical applications of event extraction systems have long been hindered by
their need for heavy human annotation. In order to scale up to new domains and
event types, models must learn to cope with limited supervision, as in few-shot
learning settings. To this end, the major challenge is to let the model master
the semantics of event types, without requiring abundant event mention
annotations. In our study, we employ cloze prompts to elicit event-related
knowledge from pretrained language models and further use event definitions and
keywords to pinpoint the trigger word. By formulating the event detection task
as an identify-then-localize procedure, we minimize the number of type-specific
parameters, enabling our model to quickly adapt to event detection tasks for
new types. Experiments on three event detection benchmark datasets (ACE,
FewEvent, MAVEN) show that our proposed method performs favorably under fully
supervised settings and surpasses existing few-shot methods by 21% F1 on the
FewEvent dataset and 20% on the MAVEN dataset when only 5 examples are provided
for each event type.


title: Winter (or delta-shell) Model at Small and Intermediate Volumes

abstract:
  We consider Winter (or delta-shell) model at finite volume, describing a
small resonating cavity weakly coupled to a large one, for small and
intermediate volumes (lengths). By defining N as the ratio of the length of the
large cavity over the small one, we study the symmetric case N=1, in which the
two cavities actually have the same length, as well as the cases N=2,3,4.
  By increasing N in the above range, the transition from a simple quantum
oscillating system to a system having a resonance spectrum is investigated. We
find that each resonant state is represented, at finite volume, by a cluster of
states, each one resonating in a specific coupling region, centered around a
state resonating at very small couplings.
  We derive high-energy expansions for the particle momenta in the above N
cases, which (approximately) resum their perturbative series to all orders in
the coupling among the cavities. These new expansions converge rather quickly
with the order, provide, surprisingly, a uniform approximation in the coupling
and also work, again surprisingly, at low energies.
  We construct a first resummation scheme having a clear physical picture,
which is based on a function-series expansion, as well as a second scheme based
on a recursion equation. The two schemes coincide at leading order, while they
differ from next-to-leading order on. In particular, the recursive scheme
realizes an approximate resummation of the function-series expansion generated
within the first scheme.


title: Sensitivity of a Chaotic Logic Gate

abstract:
  Chaotic logic gates or `chaogates' are a promising mixed-signal approach to
designing universal computers. However, chaotic systems are exponentially
sensitive to small perturbations, and the effects of noise can cause chaotic
computers to fail. Here, we examine the sensitivity of a simulated chaogate to
noise and other parameter variations (such as differences in supply voltage).
We find that the regions in parameter space corresponding to chaotic dynamics
coincide with the regions of maximum error in the computation. Further, this
error grows exponentially within 4-10 iterations of the chaotic map. As such,
we discuss the fundamental limitations of chaotic computing, and suggest
potential improvements. Our Python simulation methods are open-source and
available at https://github.com/Noeloikeau/chaogate.


title:
Semi-metallicity and electron-hole liquid in two-dimensional C and BN
  based compounds

abstract:
  Insulating-metallic transition mediated by substitutional atoms is predicted
in a series of two-dimensional carbon-based structures. Introducing Si atoms in
selected sites of tetrahexcarbon [Carbon 137 (2018) 266] according to rational
chemical rules, metallicity by trivial band inversion without band gap opening
is induced. Additional substitution of remaining C atoms by BN dimers
introduces no changes in the metallic properties. A series of isomorphous
two-dimensional materials with isoelectronic structures derived by exchanging
group IV elements exhibiting various band gaps is obtained. Dynamical stability
is verified with phonon analysis and beyond the harmonic approximation with
molecular dynamics up to room temperature. The semi-metallic compounds have
well-nested pockets of carriers and are good candidates for the formation of an
excitonic insulator.


title:
The Case of Itinerant Magnetism in CaMn$_{2}$Al$_{10}$: Self-Consistent
  Renormalisation (SCR) Theory Study

abstract:
  We have applied the powerful self-consistent renormalization theory of spin
fluctuations for the system CaMn$_{2}$Al$_{10}$ discovered in 2015 and was
conjectured to be an itinerant magnet. We have calculated the inverse static
(paramagnetic) susceptibility and have compared it with the experimental data
(Phys. Rev. B 92, 020413, 2015). The agreement is very good. We have calculated
spin fluctuations at various temperatures and have also estimated the strength
of the electronic correlation i.e., ($I=0.3136$ eV) in the Hubbard Hamiltonian.
Based on our quantitative explanation of the inverse static (paramagnetic)
susceptibility data within the framework of SCR theory, we can decisively
conclude CaMn$_{2}$Al$_{10}$ exhibits the phenomena of itinerant magnetism.
Further, our DFT and DFT+U calculations corroborate the strong Mn-Al
hybridization which is the key behind the itinerant magnetism in this system.
Our estimated correlations strength will provide a foundation for further
studies of itinerant magnetism in this system.


title:
Interplay of leakage radiation and protection in topological photonic
  crystal cavities

abstract:
  The introduction of topological concepts to the design of photonic crystal
cavities holds great promise for applications in integrated photonics due to
the prospect of topological protection. This study examines the signatures of
topological light confinement in the leakage radiation of two-dimensional
topological photonic crystal cavities. The cavities are implemented in an
all-dielectric platform that features the photonic quantum spin Hall effect at
telecom wavelengths and supports helical edge states that are weakly coupled to
the radiation continuum. The modes of resonators scaling down to single point
defects in the surrounding bulk lattice are characterized via spectral position
and multipolar nature of the eigenstates. The mode profiles in real and
momentum space are mapped using far field imaging and Fourier
spectropolarimetry, revealing how certain properties of the cavity modes
reflect on their origin in the topological bandstructure. This includes
band-inversion-induced confinement and inverted scaling of mode spectra for
trivial and topological defect cavities. Furthermore, hallmarks of topological
protection in the loss rates are demonstrated, which are largely unaffected by
cavity shape and size. The results constitute an important step toward the use
of radiative topological cavities for on-chip confinement of light, control of
emitted wave fronts, and enhancing light-matter interactions.


title: Second Best, Third Worst, Fourth in Line

abstract:
  We investigate decomposable combinatorial labeled structures more fully,
focusing on the exp-log class of type a=1 or 1/2. For instance, the modal
length of the second longest cycle in a random n-permutation is (0.2350...)n,
whereas the modal length of the second smallest component in a random n-mapping
is 2 (conjecturally, given n>=434). As in earlier work, our approach is to
establish how well existing theory matches experimental data and to raise open
questions.


title: Contact foliations and generalised Weinstein conjectures

abstract:
  We consider contact foliations: objects which generalise to higher dimensions
the flow of the Reeb vector field on contact manifolds. We list a number of
properties of such foliations, and propose two conjectures about the
topological types of their leaves, both of which coincide with the classical
Weinstein conjecture in the case of contact flows. We give positive partial
results for our conjectures in particular cases -- when the holonomy of the
contact foliation preserves a Riemannian metric, for instance -- extending
already established results from the field of Contact Dynamics.


title:
Defending against Reconstruction Attacks with R\'enyi Differential
  Privacy

abstract:
  Reconstruction attacks allow an adversary to regenerate data samples of the
training set using access to only a trained model. It has been recently shown
that simple heuristics can reconstruct data samples from language models,
making this threat scenario an important aspect of model release. Differential
privacy is a known solution to such attacks, but is often used with a
relatively large privacy budget (epsilon > 8) which does not translate to
meaningful guarantees. In this paper we show that, for a same mechanism, we can
derive privacy guarantees for reconstruction attacks that are better than the
traditional ones from the literature. In particular, we show that larger
privacy budgets do not protect against membership inference, but can still
protect extraction of rare secrets. We show experimentally that our guarantees
hold against various language models, including GPT-2 finetuned on
Wikitext-103.


title:
Design Principles and Physical Properties of Two-Dimensional
  Heterostructured Borides

abstract:
  Principles of design to create dynamically stable transition metal,
lanthanide, and actinide based low-dimensional borides are presented. A charge
transfer analysis of donor metal atoms to electron deficient honeycombed B
lattices allows to predict complex covalent heterostructures hosting Dirac
states. The applicable guidelines are supported with the analysis of phonon
spectra computed with first-principles calculations to demonstrate the physical
stability of nanometer-thick heterostructures. Similar or dissimilar layered
borides can be stacked on top of each other in a layer-by-layer fashion
creating an interface that can be fundamentally different from the individual
layers, opening a rich playground to explore novel physical properties and new
materials. Functionalities such as multiple Dirac states, highly dispersive
electronic bands, and decoupled acoustic-optical phonon are studied. The
combination of appealing electronic properties and physical realization make of
predicted layered borides promising materials to integrate a new generation of
two-dimensional materials.


title: Pulse-shape discrimination in water-based scintillators

abstract:
  This work describes a class of liquid scintillators that contain mostly water
(>50 wt. % of the entire composition) and can discriminate between interactions
induced by neutrons and gamma rays. By balancing the interface interactions
between the components of the formulation, these scintillators form emulsions
that can be thermodynamically stable. This approach, which considers a quantity
known as the hydrophilic-lipophilic difference, requires consideration of the
salinity and temperature as well as characterization of the surfactants and oil
phase. Emulsions comprised of water and various oils were characterized first.
Then, the effect of scintillating dyes in the oil phase was considered,
followed by the construction of partial phase diagrams of the emulsions. For
transparent oil-in-water emulsions with a single phase, the scintillation light
yield and properties of pulse-shape discrimination were measured. The best
performing scintillators contained 33 wt. % of a scintillating oil phase and
exhibited a light yield that was as high as 18% of the light yield of a
commercially available liquid scintillator that does not contain water
(EJ-309). These water-based liquid scintillators exhibited a figure of merit of
neutron/gamma ray discrimination as high as 1.79 at about 1500 keVee.


title:
Random Feature Amplification: Feature Learning and Generalization in
  Neural Networks

abstract:
  In this work, we provide a characterization of the feature-learning process
in two-layer ReLU networks trained by gradient descent on the logistic loss
following random initialization. We consider data with binary labels that are
generated by an XOR-like function of the input features. We permit a constant
fraction of the training labels to be corrupted by an adversary. We show that,
although linear classifiers are no better than random guessing for the
distribution we consider, two-layer ReLU networks trained by gradient descent
achieve generalization error close to the label noise rate, refuting the
conjecture of Malach and Shalev-Shwartz that 'deeper is better only when
shallow is good'. We develop a novel proof technique that shows that at
initialization, the vast majority of neurons function as random features that
are only weakly correlated with useful features, and the gradient descent
dynamics 'amplify' these weak, random features to strong, useful features.


title:
Large Charges on the Wilson Loop in $\mathcal{N}=4$ SYM: II. Quantum
  Fluctuations, OPE, and Spectral Curve

abstract:
  We continue our study of large charge limits of the defect CFT defined by the
half-BPS Wilson loop in planar $\mathcal{N}=4$ supersymmetric Yang-Mills
theory. In this paper, we compute $1/J$ corrections to the correlation function
of two heavy insertions of charge $J$ and two light insertions, in the double
scaling limit where the charge $J$ and the 't Hooft coupling $\lambda$ are sent
to infinity with the ratio $J/\sqrt{\lambda}$ fixed. Holographically, they
correspond to quantum fluctuations around a classical string solution with
large angular momentum, and can be computed by evaluating Green's functions on
the worldsheet. We derive a representation of the Green's functions in terms of
a sum over residues in the complexified Fourier space, and show that it gives
rise to the conformal block expansion in the heavy-light channel. This allows
us to extract the scaling dimensions and structure constants for an infinite
tower of non-protected dCFT operators. We also find a close connection between
our results and the semi-classical integrability of the string sigma model. The
series of poles of the Green's functions in Fourier space corresponds to points
on the spectral curve where the so-called quasi-momentum satisfies a
quantization condition, and both the scaling dimensions and the structure
constants in the heavy-light channel take simple forms when written in terms of
the spectral curve. These observations suggest extensions of the results by
Gromov, Schafer-Nameki and Vieira on the semiclassical energy of closed
strings, and in particular hint at the possibility of determining the structure
constants directly from the spectral curve.


title:
Suppressing ZZ Crosstalk of Quantum Computers through Pulse and
  Scheduling Co-Optimization

abstract:
  Noise is a significant obstacle to quantum computing, and $ZZ$ crosstalk is
one of the most destructive types of noise affecting superconducting qubits.
Previous approaches to suppressing $ZZ$ crosstalk have mainly relied on
specific chip design that can complicate chip fabrication and aggravate
decoherence. To some extent, special chip design can be avoided by relying on
pulse optimization to suppress $ZZ$ crosstalk. However, existing approaches are
non-scalable, as their required time and memory grow exponentially with the
number of qubits involved. To address the above problems, we propose a scalable
approach by co-optimizing pulses and scheduling. We optimize pulses to offer an
ability to suppress $ZZ$ crosstalk surrounding a gate, and then design
scheduling strategies to exploit this ability and achieve suppression across
the whole circuit. A main advantage of such co-optimization is that it does not
require special hardware support. Besides, we implement our approach as a
general framework that is compatible with different pulse optimization methods.
We have conducted extensive evaluations by simulation and on a real quantum
computer. Simulation results show that our proposal can improve the fidelity of
quantum computing on $4{\sim}12$ qubits by up to $81\times$ ($11\times$ on
average). Ramsey experiments on a real quantum computer also demonstrate that
our method can eliminate the effect of $ZZ$ crosstalk to a great extent.


title: Deciding What is Good-for-MDPs

abstract:
  Nondeterministic Good-for-MDP (GFM) automata are for MDP model checking and
reinforcement learning what good-for-games automata are for synthesis: a more
compact alternative to deterministic automata that displays nondeterminism, but
only so much that it can be resolved locally, such that a syntactic product can
be analysed. GFM has recently been introduced as a property for reinforcement
learning, where the simpler B\"uchi acceptance conditions it allows to use is
key. However, while there are classic and novel techniques to obtain automata
that are GFM, there has not been a decision procedure for checking whether or
not an automaton is GFM. We show that GFM-ness is decidable and provide an
EXPTIME decision procedure as well as a PSPACE-hardness proof.


title: Delving Deeper into Cross-lingual Visual Question Answering

abstract:
  Visual question answering (VQA) is one of the crucial vision-and-language
tasks. Yet, the bulk of research until recently has focused only on the English
language due to the lack of appropriate evaluation resources. Previous work on
cross-lingual VQA has reported poor zero-shot transfer performance of current
multilingual multimodal Transformers and large gaps to monolingual performance,
attributed mostly to misalignment of text embeddings between the source and
target languages, without providing any additional deeper analyses. In this
work, we delve deeper and address different aspects of cross-lingual VQA
holistically, aiming to understand the impact of input data, fine-tuning and
evaluation regimes, and interactions between the two modalities in
cross-lingual setups. 1) We tackle low transfer performance via novel methods
that substantially reduce the gap to monolingual English performance, yielding
+10 accuracy points over existing transfer methods. 2) We study and dissect
cross-lingual VQA across different question types of varying complexity, across
different multilingual multi-modal Transformers, and in zero-shot and few-shot
scenarios. 3) We further conduct extensive analyses on modality biases in
training data and models, aimed to further understand why zero-shot performance
gaps remain for some question types and languages. We hope that the novel
methods and detailed analyses will guide further progress in multilingual VQA.


title:
One Configuration to Rule Them All? Towards Hyperparameter Transfer in
  Topic Models using Multi-Objective Bayesian Optimization

abstract:
  Topic models are statistical methods that extract underlying topics from
document collections. When performing topic modeling, a user usually desires
topics that are coherent, diverse between each other, and that constitute good
document representations for downstream tasks (e.g. document classification).
In this paper, we conduct a multi-objective hyperparameter optimization of
three well-known topic models. The obtained results reveal the conflicting
nature of different objectives and that the training corpus characteristics are
crucial for the hyperparameter selection, suggesting that it is possible to
transfer the optimal hyperparameter configurations between datasets.


title:
Wireless Resource Management in Intelligent Semantic Communication
  Networks

abstract:
  The prosperity of artificial intelligence (AI) has laid a promising paradigm
of communication system, i.e., intelligent semantic communication (ISC), where
semantic contents, instead of traditional bit sequences, are coded by AI models
for efficient communication. Due to the unique demand of background knowledge
for semantic recovery, wireless resource management faces new challenges in
ISC. In this paper, we address the user association (UA) and bandwidth
allocation (BA) problems in an ISC-enabled heterogeneous network (ISC-HetNet).
We first introduce the auxiliary knowledge base (KB) into the system model, and
develop a new performance metric for the ISC-HetNet, named system throughput in
message (STM). Joint optimization of UA and BA is then formulated with the aim
of STM maximization subject to KB matching and wireless bandwidth constraints.
To this end, we propose a two-stage solution, including a stochastic
programming method in the first stage to obtain a deterministic objective with
semantic confidence, and a heuristic algorithm in the second stage to reach the
optimality of UA and BA. Numerical results show great superiority and
reliability of our proposed solution on the STM performance when compared with
two baseline algorithms.


title: Hydrodynamical Evolution of Black-Hole Binaries Embedded in AGN Discs

abstract:
  Stellar-mass binary black holes (BBHs) embedded in active galactic nucleus
(AGN) discs are possible progenitors of black-hole mergers detected in
gravitational waves by LIGO/VIRGO. To better understand the hydrodynamical
evolution of BBHs interacting with the disc gas, we perform a suite of
high-resolution 2D simulations of binaries in local disc (shearing-box) models,
considering various binary mass ratios, eccentricities and background disc
properties. We use the $\gamma$-law equation of state and adopt a robust
post-processing treatment to evaluate the mass accretion rate, torque and
energy transfer rate on the binary to determine its long-term orbital
evolution. We find that circular comparable-mass binaries contract, with an
orbital decay rate of a few times the mass doubling rate. Eccentric binaries
always experience eccentricity damping. Prograde binaries with higher
eccentricities or smaller mass ratios generally have slower orbital decay
rates, with some extreme cases exhibiting orbital expansion. The averaged
binary mass accretion rate depends on the physical size of the accretor. The
accretion flows are highly variable, and the dominant variability frequency is
the apparent binary orbital frequency (in the rotating frame around the central
massive BH) for circular binaries but gradually shifts to the radial epicyclic
frequency as the binary eccentricity increases. Our findings demonstrate that
the dynamics of BBHs embedded in AGN discs is quite different from that of
isolated binaries in their own circumbinary discs. Furthermore, our results
suggest that the hardening timescales of the binaries are much shorter than
their migration timescales in the disc, for all reasonable binary and disc
parameters.


title:
Sharp hierarchical upper bounds on the critical two-point function for
  long-range percolation on $\mathbb{Z}^d$

abstract:
  Consider long-range Bernoulli percolation on $\mathbb{Z}^d$ in which we
connect each pair of distinct points $x$ and $y$ by an edge with probability
$1-\exp(-\beta\|x-y\|^{-d-\alpha})$, where $\alpha>0$ is fixed and $\beta\geq
0$ is a parameter. We prove that if $0<\alpha<d$ then the critical two-point
function satisfies \[ \frac{1}{|\Lambda_r|}\sum_{x\in \Lambda_r}
\mathbf{P}_{\beta_c}(0\leftrightarrow x) \preceq r^{-d+\alpha} \] for every
$r\geq 1$, where $\Lambda_r=[-r,r]^d \cap \mathbb{Z}^d$. In other words, the
critical two-point function on $\mathbb{Z}^d$ is always bounded above on
average by the critical two-point function on the hierarchical lattice. This
upper bound is believed to be sharp for values of $\alpha$ strictly below the
crossover value $\alpha_c(d)$, where the values of several critical exponents
for long-range percolation on $\mathbb{Z}^d$ and the hierarchical lattice are
believed to be equal.


title:
Evolution of density fluctuations in the Lema\^itre--Tolman--Bondi
  metric containing coupled dark energy

abstract:
  We consider inhomogeneous spherically symmetric models based on the
Lema\^{i}tre-Tolman-Bondi (LTB) metric, assuming as its source an interactive
mixture of ordinary baryonic matter, cold dark matter and dark energy with a
coupling term proportional to the addition of energy densities of both dark
fluids. We reduce Einstein's field equations to a first order 7-dimensional
autonomous dynamical system of evolution equations and algebraic constraints.
We study in detail the evolution of the energy density and spatial curvature
profiles along the phase space by means of two subspace projections: a
three-dimensional projection associated with the solutions of the
Friedman-Lema\^\i tre-Robertson-Walker metric (invariant subspace) and a
four-dimensional projection describing the evolution of the inhomogeneous
fluctuations. We also classify and study the critical points of the system in
comparison with previous work on similar sources, as well as solving
numerically the equations for initial energy density and curvature profiles
that lead to a spherical bounce whose collapsing time we estimate
appropriately.


title:
On Dynamic Lifting and Effect Typing in Circuit Description Languages
  (Extended Version)

abstract:
  In the realm of quantum computing, circuit description languages represent a
valid alternative to traditional QRAM-style languages. They indeed allow for
finer control over the output circuit, without sacrificing flexibility nor
modularity. We introduce a generalization of the paradigmatic lambda-calculus
Proto-Quipper-M, itself modeling the core features of the quantum circuit
description language Quipper. The extension, called Proto-Quipper-K, is meant
to capture a very general form of dynamic lifting. This is made possible by the
introduction of a rich type and effect system in which not only computations,
but also the very types are effectful. The main results we give for the
introduced language are the classic type soundness results, namely subject
reduction and progress.


title: Review of a Simplified Approach to study the Bose gas at all densities

abstract:
  In this paper, we will review the results obtained thus far by Eric A.
Carlen, Elliott H. Lieb and me on a Simplified Approach to the Bose gas. The
Simplified Approach yields a family of effective one-particle equations, which
capture some non-trivial physical properties of the Bose gas at both low and
high densities, and even some of the behavior at intermediate densities. In
particular, the Simplified Approach reproduces Bogolyubov's estimates for the
ground state energy and condensate fraction at low density, as well as the
mean-field estimate for the energy at high densities. We will also discuss a
phase that appears at intermediate densities with liquid-like properties. The
simplest of the effective equations in the Simplified Approach can be studied
analytically, and we will review several results about it; the others are so
far only amenable to numerical analysis, and we will discuss several numerical
results. We will start by reviewing some results and conjectures on the Bose
gas, and then introduce the Simplified Approach and its derivation from the
Bose gas. We will then discuss the predictions of the Simplified Approach and
compare these to results and conjectures about the Bose gas. Finally, we will
discuss a few open problems about the Simplified Approach.

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


title: On the design of scalable networks to reject polynomial disturbances

abstract:
  This paper is concerned with the problem of designing distributed control
protocols for network systems affected by delays and disturbances consisting of
a polynomial component and a residual signal. We propose the use of a multiplex
architecture to design distributed control protocols to reject polynomial
disturbances up to ramps and guarantee a scalability property that prohibits
the amplification of residual disturbances. For this architecture, we give a
delay-independent sufficient condition on the control protocols to guarantee
scalability and ramps rejection. The effectiveness of the result, which can be
used to study networks of nonlinearly coupled nonlinear agents, is illustrated
via a robot formation control problem.


title: Unconventional pairing in few-fermion systems at finite temperature

abstract:
  Attractively interacting two-component mixtures of fermionic particles
confined in a one-dimensional harmonic trap are investigated. Properties of
balanced and imbalanced systems are systematically explored with the exact
diagonalization approach, focusing on the finite-temperature effects. Using
single- and two-particle density distributions, specific non-classical pairing
correlations are analyzed in terms of the noise correlations -- quantity
directly accessible in state-of-the-art experiments with ultra-cold atoms. It
is shown that along with increasing temperature, any imbalanced system hosting
Fulde-Ferrel-Larkin-Ovchinnikov pairs crossovers to a standard
Bardeen-Cooper-Schrieffer one characterized by zero net momentum of resulting
pairs. By performing calculations for systems with different imbalances, the
approximate boundary between the two phases on a phase diagram is determined.


title:
Suppression of fluctuations in a two-band superconductor with a quasi-1D
  band

abstract:
  Chain-like structured superconductive materials exhibit the multiband
structure of single-particle states, where coexisting quasi-one-dimensional
(Q1D) and conventional higher-dimensional bands take part in the creation of
the aggregate superconducting condensate. When the chemical potential
approaches the edge of a Q1D band in a single-band superconductor, the
corresponding mean-field critical temperature increases significantly but the
superconductivity is quenched by fluctuations. However, recent investigation
has revealed that when a Q1D band is coupled to a higher dimensional one by the
interband Cooper-pair transfer, the thermal superconductive fluctuations can be
suppressed so that the resulting critical temperature can be close to its
mean-field value. In the present work, we calculate the mean-field T_c0 and
fluctuation-shifted T_c critical temperatures for a two-band superconductor
where a Q1D band coexists with a higher-dimensional band, and investigate how
the thermal fluctuations are sensitive to the system parameters. We find that
T_c is close to T_c0 in a wide range of microscopic parameters, and even the
dimensionality of the higher-dimensional band does not play an essential role.
Thus, the mechanism for suppressing fluctuations via the pair-exchange coupling
between the bands is indeed relevant for a large class of Q1D multiband
superconducting materials, encouraging further experiments aimed at reaching
larger critical temperatures in such multiband superconductors.


title: The $L^p$ convergence of Fourier series on triangular domains

abstract:
  We prove $L^p$ norm convergence for (appropriate truncations of) the Fourier
series arising from the Dirichlet Laplacian eigenfunctions on three types of
triangular domains in $\mathbb{R}^2$: (i) the 45-90-45 triangle, (ii) the
equilateral triangle and (iii) the hemiequilateral triangle (i.e. half an
equilateral triangle cut along its height). The limitations of our argument to
these three types are discussed in light of Lam\'e's Theorem.


title: Aut\`omats de Stallings, un cam\'i d'anada i tornada

abstract:
  In this paper we review some of the fundamental properties of the free group
and give a detailed account of Stallings's theory of automata, a geometric
interpretation of its subgroups that has been (and still is) immensely
fruitful, both as a means of understanding classical results, as as a source of
new results. We review some of the most important ones.
  --
  En aquest article revisem algunes de les propietats fonamentals del group
lliure i fem una exposici\'o detallada de la teoria dels aut\`omats de
Stallings, una interpretaci\'o geom\`etrica dels seus subgrups que ha estat (i
segueix essent) immensament fruct\'ifera, tant com a mitj\`a per entendre
resultats cl\`assics, com com a font de nous resultats. N'expliquem alguns dels
m\'es rellevants.


title: Lie Point Symmetry Data Augmentation for Neural PDE Solvers

abstract:
  Neural networks are increasingly being used to solve partial differential
equations (PDEs), replacing slower numerical solvers. However, a critical issue
is that neural PDE solvers require high-quality ground truth data, which
usually must come from the very solvers they are designed to replace. Thus, we
are presented with a proverbial chicken-and-egg problem. In this paper, we
present a method, which can partially alleviate this problem, by improving
neural PDE solver sample complexity -- Lie point symmetry data augmentation
(LPSDA). In the context of PDEs, it turns out that we are able to
quantitatively derive an exhaustive list of data transformations, based on the
Lie point symmetry group of the PDEs in question, something not possible in
other application areas. We present this framework and demonstrate how it can
easily be deployed to improve neural PDE solver sample complexity by an order
of magnitude.


title: Identifying subdominant collective effects in a large motorway network

abstract:
  In a motorway network, correlations between parts or, more precisely, between
the sections of (different) motorways, are of considerable interest. Knowledge
of flows and velocities on individual motorways is not sufficient, rather,
their correlations determine or reflect, respectively, the functionality of and
the dynamics on the network. These correlations are time-dependent as the
dynamics on the network is highly non-stationary. Apart from the conceptual
importance, correlations are also indispensable to detect risks of failure in a
traffic network. Here, we proceed with revealing a certain hierarchy of
correlations in traffic networks that is due to the presence and to the extent
of collectivity. In a previous study, we focused on the collectivity motion
present in the entire traffic network, i.e. the collectivity of the system as a
whole. Here, we manage to subtract this dominant effect from the data and
identify the subdominant collectivities which affect different, large parts of
the traffic network. To this end, we employ a spectral analysis of the
correlation matrix for the whole system. We thereby extract information from
the virtual network induced by the correlations and map it on the true
topology, i.e. on the real motorway network. The uncovered subdominant
collectivities provide a new characterization of the traffic network. We carry
out our study for the large motorway network of North Rhine-Westphalia (NRW),
Germany.


title: Towards a maturity model for crypto-agility assessment

abstract:
  This work proposes the Crypto-Agility Maturity Model (CAMM for short), a
maturity model for determining the state of crypto-agility of a given software
or IT landscape. CAMM consists of five levels, for each level a set of
requirements have been formulated based on literature review. Initial feedback
from field experts confirms that CAMM has a well-designed structure and is easy
to comprehend. Based on our model, the crytographic agility of an IT landscape
can be systematically measured and improved step by step. We expect that this
will enable companies and to respond better and faster to threats resulting
from broken cryptographic schemes. This work serves to promote CAMM and
encourage others to apply it in practice and develop it jointly.


title: Quantifying Memorization Across Neural Language Models

abstract:
  Large language models (LMs) have been shown to memorize parts of their
training data, and when prompted appropriately, they will emit the memorized
training data verbatim. This is undesirable because memorization violates
privacy (exposing user data), degrades utility (repeated easy-to-memorize text
is often low quality), and hurts fairness (some texts are memorized over
others).
  We describe three log-linear relationships that quantify the degree to which
LMs emit memorized training data. Memorization significantly grows as we
increase (1) the capacity of a model, (2) the number of times an example has
been duplicated, and (3) the number of tokens of context used to prompt the
model. Surprisingly, we find the situation becomes complicated when
generalizing these results across model families. On the whole, we find that
memorization in LMs is more prevalent than previously believed and will likely
get worse as models continues to scale, at least without active mitigations.


title: Can a spin chain relate combinatorics to number theory?

abstract:
  The Motzkin spin chain is a spin-$1$ frustration-free model introduced by
Shor & Movassagh. The ground state is constructed by mapping of random walks on
upper half of the square lattice to spin configurations. It has unusually large
entanglement entropy [quantum fluctuations]. We simplify the model by removing
one of the local equivalence moves of the Motzkin paths. The system becomes
integrable [similar to the XXX spin chain]. We call it free Motzkin chain. From
the point of view of quantum integrability, the model is special since its
$R$-matrix does not have crossing-unitarity. We solve the periodic free Motzkin
chain by generalized functional Bethe Ansatz method. We construct a $T-Q$
relation with an additional parameter to formulate the energy spectrum. This
new parameter is related to the roots of unity and can be described by the
M\"obius function of the number theory. We observe further patterns of the
number theory.

categories: quant-ph cond-mat.str-el math-ph math.MP


title:
EvoKG: Jointly Modeling Event Time and Network Structure for Reasoning
  over Temporal Knowledge Graphs

abstract:
  How can we perform knowledge reasoning over temporal knowledge graphs (TKGs)?
TKGs represent facts about entities and their relations, where each fact is
associated with a timestamp. Reasoning over TKGs, i.e., inferring new facts
from time-evolving KGs, is crucial for many applications to provide intelligent
services. However, despite the prevalence of real-world data that can be
represented as TKGs, most methods focus on reasoning over static knowledge
graphs, or cannot predict future events. In this paper, we present a problem
formulation that unifies the two major problems that need to be addressed for
an effective reasoning over TKGs, namely, modeling the event time and the
evolving network structure. Our proposed method EvoKG jointly models both tasks
in an effective framework, which captures the ever-changing structural and
temporal dynamics in TKGs via recurrent event modeling, and models the
interactions between entities based on the temporal neighborhood aggregation
framework. Further, EvoKG achieves an accurate modeling of event time, using
flexible and efficient mechanisms based on neural density estimation.
Experiments show that EvoKG outperforms existing methods in terms of
effectiveness (up to 77% and 116% more accurate time and link prediction) and
efficiency.


title: Mapping class group representations derived from stated skein algebras

abstract:
  We construct finite dimensional projective representations of the mapping
class groups of compact connected oriented surfaces having one boundary
component using stated skein algebras.


title: Conformal Prediction Sets with Limited False Positives

abstract:
  We develop a new approach to multi-label conformal prediction in which we aim
to output a precise set of promising prediction candidates with a bounded
number of incorrect answers. Standard conformal prediction provides the ability
to adapt to model uncertainty by constructing a calibrated candidate set in
place of a single prediction, with guarantees that the set contains the correct
answer with high probability. In order to obey this coverage property, however,
conformal sets can become inundated with noisy candidates -- which can render
them unhelpful in practice. This is particularly relevant to practical
applications where there is a limited budget, and the cost (monetary or
otherwise) associated with false positives is non-negligible. We propose to
trade coverage for a notion of precision by enforcing that the presence of
incorrect candidates in the predicted conformal sets (i.e., the total number of
false positives) is bounded according to a user-specified tolerance. Subject to
this constraint, our algorithm then optimizes for a generalized notion of set
coverage (i.e., the true positive rate) that allows for any number of true
answers for a given query (including zero). We demonstrate the effectiveness of
this approach across a number of classification tasks in natural language
processing, computer vision, and computational chemistry.


title: Anti-persistent random walks in time-delayed systems

abstract:
  We show that the occurrence of chaotic diffusion in a typical class of
time-delayed systems with linear instantaneous and nonlinear delayed term can
be well described by an anti-persistent random walk. We numerically investigate
the dependence of all relevant quantities characterizing the random walk on the
strength of the nonlinearity and on the delay. With the help of analytical
considerations, we show that for a decreasing nonlinearity parameter the
resulting dependence of the diffusion coefficient is well described by Markov
processes of increasing order.


title: Predicting on the Edge: Identifying Where a Larger Model Does Better

abstract:
  Much effort has been devoted to making large and more accurate models, but
relatively little has been put into understanding which examples are benefiting
from the added complexity. In this paper, we demonstrate and analyze the
surprisingly tight link between a model's predictive uncertainty on individual
examples and the likelihood that larger models will improve prediction on them.
Through extensive numerical studies on the T5 encoder-decoder architecture, we
show that large models have the largest improvement on examples where the small
model is most uncertain. On more certain examples, even those where the small
model is not particularly accurate, large models are often unable to improve at
all, and can even perform worse than the smaller model. Based on these
findings, we show that a switcher model which defers examples to a larger model
when a small model is uncertain can achieve striking improvements in
performance and resource usage. We also explore committee-based uncertainty
metrics that can be more effective but less practical.


title: The thermodynamic efficiency of the Lorenz system

abstract:
  We study the thermodynamic efficiency of the Malkus-Lorenz waterwheel. For
this purpose, we derive an exact analytical formula that describes the
efficiency of this dissipative structure as a function of the phase space
variables and the constant parameters of the dynamical system. We show that,
generally, as the machine is progressively driven far from thermodynamic
equilibrium by increasing its uptake of matter from the environment, it also
tends to increase its efficiency. However, sudden drops in the efficiency are
found at critical bifurcation points leading to chaotic dynamics. We relate
these discontinuous crises in the efficiency to a reduction of the attractor's
average value projected along the phase space dimensions that contribute to the
rate of entropy generation in the system. In this manner, we provide a
thermodynamic criterion that, presumably, governs the evolution of
far-from-equilibrium dissipative systems towards their self-assembly and
synchronization into increasingly complex networks and structures.


title:
Tomayto, Tomahto. Beyond Token-level Answer Equivalence for Question
  Answering Evaluation

abstract:
  The predictions of question answering (QA) systems are typically evaluated
against manually annotated finite sets of one or more answers. This leads to a
coverage limitation that results in underestimating the true performance of
systems, and is typically addressed by extending over exact match (EM) with
predefined rules or with the token-level F1 measure. In this paper, we present
the first systematic conceptual and data-driven analysis to examine the
shortcomings of token-level equivalence measures.
  To this end, we define the asymmetric notion of answer equivalence (AE),
accepting answers that are equivalent to or improve over the reference, and
collect over 26K human judgements for candidates produced by multiple QA
systems on SQuAD. Through a careful analysis of this data, we reveal and
quantify several concrete limitations of the F1 measure, such as false
impression of graduality, missing dependence on question, and more.
  Since collecting AE annotations for each evaluated model is expensive, we
learn a BERT matching BEM measure to approximate this task. Being a simpler
task than QA, we find BEM to provide significantly better AE approximations
than F1, and more accurately reflect the performance of systems.
  Finally, we also demonstrate the practical utility of AE and BEM on the
concrete application of minimal accurate prediction sets, reducing the number
of required answers by up to 2.6 times.


title: Topology of multiple cross-linked Su-Schrieffer-Heeger chains

abstract:
  In polymer science, cross-linking of polymer chains yields a substantially
modified system compared to the one-dimensional constituent chains, due to the
increase of dimensionality and effective seeding by defects (cross-linking
sites). Inspired by this concept, we analyze topological features of a unit
cell of a generalized topological mesh comprised of several one-dimensional
Su-Schrieffer-Heeger (SSH) lattices cross-linked via a single site. The
coupling site functions as a defect with protected states in the trivial regime
and also induces edges inside the bulk with protected localized states centered
around it in the topological regime. When more than two lattices are coupled by
the defect, namely, a dimensionality larger than one, the crossed chains
support two types of localized eigenstates around the defect. One type is
highly controllable by modifying the cross-linking strength, enabling broad
tuning of eigenenergies from being submerged in the bulk band to becoming
highly isolated and protected. We show that these unique features can be
explained by an equivalence of the aforementioned system to an SSH chain
coupled nonreciprocally to an external reservoir, yielding a unique
pseudospectrum for both the bulk and localized states, with spatially symmetric
eigenstates. Applying non-Hermiticity by adding gain and loss to alternating
sites, relevant for example to a possible realization of topological
coupled-laser fabric, we observe an abrupt transition of the topologically
protected mid-gap state from anti-localized to localized near the defect. By
changing the gain/loss parameters, we observe a cascaded spatial symmetry
breaking of the supported states at exceptional points where parity-time
symmetry is broken, for both the localized and the bulk states. The combination
of the non-Hermiticity and higher-dimensionality yields various novel phases.


title:
Direct determination of the atomic mass difference of the pairs
  $^{76}$As-$^{76}$Se and $^{155}$Tb-$^{155}$Gd rules out $^{76}$As and
  $^{155}$Tb as possible candidates for electron (anti)neutrino mass
  measurements

abstract:
  The first direct determination of the ground-state-to-ground-state $Q$ values
of the $\beta^-$ decay $^{76}$As $\rightarrow$ $^{76}$Se and the
electron-capture decay $^{155}$Tb $\rightarrow$ $^{155}$Gd was performed
utilizing the double Penning trap mass spectrometer JYFLTRAP. By measuring the
atomic mass difference of the decay pairs via the phase-imaging
ion-cyclotron-resonance (PI-ICR) technique, the $Q$ values of $^{76}$As
$\rightarrow$ $^{76}$Se and $^{155}$Tb $\rightarrow$ $^{155}$Gd were determined
to be 2959.265(74) keV and 814.94(18) keV, respectively. The precision was
increased relative to earlier measurements by factors of 12 and 57,
respectively. The new $Q$ values are 1.33 keV and 5 keV lower compared to the
values adopted in the most recent Atomic Mass Evaluation 2020. With the newly
determined ground-state-to-ground-state $Q$ values combined with the excitation
energy from $\gamma$-ray spectroscopy, the $Q$ values for
ground-state-to-excited-state transitions $^{76}$As (ground state)
$\rightarrow$ $^{76}$Se$^*$ (2968.4(7) keV) and $^{155}$Tb (ground state)
$\rightarrow$ $^{155}$Gd$^*$ (815.731(3) keV) were derived to be -9.13(70) keV
and -0.79(18) keV. Thus we have confirmed that both of the $\beta^{-}$-decay
and EC-decay candidate transitions are energetically forbidden at a level of at
least 4$\sigma$, thus definitely excluding these two cases from the list of
potential candidates for the search of low-$Q$-value $\beta^-$ or EC decays to
determine the electron-(anti)neutrino mass.


title: Mobile impurity in a one-dimensional gas at finite temperatures

abstract:
  We consider the McGuire model of a one-dimensional gas of free fermions
interacting with a single impurity. We compute the static one-body function and
momentum distribution of the impurity at finite temperatures. The results
involve averages over Fredholm determinants that we further analyse using the
effective form factors approach. With this approach, we derive the
large-distance behaviour of the one-body function, which takes the form of an
averaged exponential decay. This method allows us to study an experimentally
important regime of small momenta of the impurity's momentum distribution. We
also consider the one-body function at short distances and compute finite
temperature Tan's contact.

categories: cond-mat.quant-gas math-ph math.MP nlin.SI


title: Inner Skin Effects on Non-Hermitian Topological Fractals

abstract:
  Non-Hermitian (NH) crystals, quasicrystals and amorphous network with only
open boundary condition feature skin effect, displaying accumulation of a
macroscopic number of states near one of its specific interfaces (edge,
surface, hinge or corner, for example) with vacuum. In this regard fractals, by
virtue of manifesting self-similarity, resulting in inner boundaries in the
interior of the system harbor a novel phenomenon, the \emph{inner skin effect}
(ISE), in which the skin effect appears at inner boundaries of the fractal
lattice with periodic boundary condition. We showcase this observation by
implementing paradigmatic models for NH insulators and superconductors on
representative planar Sierpinski carpet fractals, accommodating both first- and
second-order ISEs at inner edges and corners, respectively, for charged and
neutral Majorana fermions. Furthermore, over extended parameter regimes ISEs
are tied with nontrivial bulk topological invariants, thereby yielding
intrinsic ISEs. With the recent success in engineering NH topological phases on
highly tunable metamaterial platforms, such as photonic and phononic lattices,
as well as topolectric circuits, the proposed ISEs can be observed
experimentally at least on periodic fractal metamaterials.


title: Survey of Big Data sizes in 2021

abstract:
  The modern increase in data production is driven by multiple factors, and
several stakeholders from various sectors contribute to it. Although drawing a
comparison of the sizes at stake for different big data players is hard due to
the lack of official data, this report tries to reconstruct the yearly orders
of magnitude generated by some of the most important organizations by mining
several online sources. The estimation is based on retrieving meaningful
unitary data production measures for each of the big data sources considered,
and the yearly amounts are then obtained by conjecturing reasonable per-unit
sizes. The final result is summarized in the form of a bubble plot.


title:
The Global Dynamical Atlas of the Milky Way mergers: Constraints from
  Gaia EDR3 based orbits of globular clusters, stellar streams and satellite
  galaxies

abstract:
  The Milky Way halo was predominantly formed by the merging of numerous
progenitor galaxies. However, our knowledge of this process is still
incomplete, especially in regard to the total number of mergers, their global
dynamical properties and their contribution to the stellar population of the
Galactic halo. Here, we uncover the Milky Way mergers by detecting groupings of
globular clusters, stellar streams and satellite galaxies in action
($\mathbf{J}$) space. While actions fully characterize the orbits, we
additionally use the redundant information on their energy ($\textit{E}$) to
enhance the contrast between groupings. For this endeavour, we use
$\textit{Gaia}$ EDR3 based measurements of $170$ globular clusters, $41$
streams and $46$ satellites to derive their $\mathbf{J}$ and $\textit{E}$. To
detect groups, we use the $\texttt{ENLINK}$ software, coupled with a
statistical procedure that accounts for the observed phase-space uncertainties
of these objects. We detect a total of $N=6$ groups, including the previously
known mergers $\textit{Sagittarius}$, $\textit{Cetus}$,
$\textit{Gaia-Sausage/Enceladus}$, $\textit{LMS-1/Wukong}$,
$\textit{Arjuna/Sequoia/I'itoi}$ and one new merger that we call
$\textit{Pontus}$. All of these mergers, together, comprise $62$ objects
($\approx 25\%$ of our sample). We discuss their members, orbital properties
and metallicity distributions. We find that the three most metal-poor streams
of our Galaxy -- "C-19" ([Fe/H]$=-3.4$ dex), "Sylgr" ([Fe/H]$=-2.9$ dex) and
"Phoenix" ([Fe/H]$=-2.7$ dex) -- are associated with $\textit{LMS-1/Wukong}$;
showing it to be the most metal-poor merger. The global dynamical atlas of
Milky Way mergers that we present here provides a present-day reference for
galaxy formation models.


title:
An Eddington ratio-driven origin for the ${\rm L}_{\rm X}-{\rm M}_{*}$
  relation in quiescent and star forming active galaxies

abstract:
  A mild correlation exists in active galaxies between the mean black hole
accretion, as traced by the mean X-ray luminosity $\left<{\rm L}_{\rm
X}\right>$, and the host galaxy stellar mass M$_*$, characterised by a
normalisation steadily decreasing with cosmic time and lower in more quiescent
galaxies. We create comprehensive semi-empirical mock catalogues of active
black holes to pin down which parameters control the shape and evolution of the
$\left<{\rm L}_{\rm X}\right>-{\rm M}_*$ relation of X-ray detected active
galaxies. We find that the normalisation of the $\left<{\rm L}_{\rm
X}\right>-{\rm M}_*$ relation is largely independent of the fraction of active
galaxies (the duty cycle), but strongly dependent on the mean Eddington ratio,
when adopting a constant underlying M$_{\rm BH}-{\rm M}_*$ relation as
suggested by observational studies. The data point to a decreasing mean
Eddington ratio with cosmic time and with galaxy stellar mass at fixed
redshift. Our data can be reproduced by black holes and galaxies evolving on
similar M$_{\rm BH}-{\rm M}_*$ relations but progressively decreasing their
average Eddington ratios, mean X-ray luminosities, and specific star formation
rates, when moving from the starburst to the quiescent phase. Models consistent
with the observed $\left<{\rm L}_{\rm X}\right>-{\rm M}_*$ relation and
independent measurements of the mean Eddington ratios, are characterised by
M$_{\rm BH}-{\rm M}_*$ relations lower than those derived from dynamically
measured local black holes. Our results point to the $\left<{\rm L}_{\rm
X}\right>-{\rm M}_*$ relation as a powerful diagnostic to: 1) probe black
hole-galaxy scaling relations and the level of accretion onto black holes; 2)
efficiently break the degeneracies between duty cycles and accretion rates in
cosmological models of black holes.


title: A Tilt in the Dark Matter Halo of the Galaxy

abstract:
  Recent observations of the stellar halo have uncovered the debris of an
ancient merger, Gaia-Sausage-Enceladus, estimated to have occurred ~8 Gyr ago.
Follow-up studies have associated GSE with a large-scale tilt in the stellar
halo that links two well-known stellar over-densities in diagonally opposing
octants of the Galaxy (the Hercules-Aquila Cloud and Virgo Overdensity; HAC and
VOD). In this paper, we study the plausibility of such unmixed merger debris
persisting over several Gyr in the Galactic halo. We employ the simulated
stellar halo from Naidu et al. (2021), which reproduces several key properties
of the merger remnant, including the large-scale tilt. By integrating the
orbits of these simulated stellar halo particles, we show that adoption of a
spherical halo potential results in rapid phase mixing of the asymmetry.
However, adopting a tilted halo potential preserves the initial asymmetry in
the stellar halo for many Gyr. The asymmetry is preserved even when a realistic
growing disk is added to the potential. These results suggest that HAC and VOD
are long-lived structures that are associated with GSE and that the dark matter
halo of the Galaxy is tilted with respect to the disk and aligned in the
direction of HAC-VOD. Such halo-disk misalignment is common in modern
cosmological simulations. Lastly, we study the relationship between the local
and global stellar halo in light of a tilted global halo comprised of highly
radial orbits. We find that the local halo offers a dynamically biased view of
the global halo due to its displacement from the Galactic Center.


title:
GIGA-Lens: Fast Bayesian Inference for Strong Gravitational Lens
  Modeling

abstract:
  We present GIGA-Lens: a gradient-informed, GPU-accelerated Bayesian framework
for modeling strong gravitational lensing systems, implemented in TensorFlow
and JAX. The three components, optimization using multi-start gradient descent,
posterior covariance estimation with variational inference, and sampling via
Hamiltonian Monte Carlo, all take advantage of gradient information through
automatic differentiation and massive parallelization on graphics processing
units (GPUs). We test our pipeline on a large set of simulated systems and
demonstrate in detail its high level of performance. The average time to model
a single system on four Nvidia A100 GPUs is 105 seconds. The robustness, speed,
and scalability offered by this framework make it possible to model the large
number of strong lenses found in current surveys and present a very promising
prospect for the modeling of $\mathcal{O}(10^5)$ lensing systems expected to be
discovered in the era of the Vera C. Rubin Observatory, Euclid, and the Nancy
Grace Roman Space Telescope.


title: Chiral Symmetry Breaking and Quark Bilinear Condensate in Large N QCD

abstract:
  We discuss spontaneous chiral symmetry breaking and quark bilinear condensate
in large $N_c$ QCD. It has been known that the existence of $\eta'$ meson is
implied in large $N_c$ QCD as pointed out by Witten and Veneziano. First, we
show that the existence of $\eta'$ and Ward-Takahashi identities imply the
existence of the Nambu-Goldstone bosons from chiral symmetry breaking
$SU(N_f)_L \times SU(N_f)_R \to SU(N_f)_V$. Second, we show that a QCD
inequality implies a nonzero lower bound on the quark bilinear condensate.


title:
Black Hole Discs and Spheres in Galactic Nuclei -- Exploring the
  Landscape of Vector Resonant Relaxation Equilibria

abstract:
  Vector resonant relaxation (VRR) is known to be the fastest gravitational
process that shapes the geometry of stellar orbits in nuclear star clusters.
This leads to the realignment of the orbital planes on the corresponding VRR
time scale $t_{\rm VRR}$ of a few million years, while the eccentricity $e$ and
semimajor axis $a$ of the individual orbits are approximately conserved. The
distribution of orbital inclinations reaches an internal equilibrium
characterised by two conserved quantities, the total potential energy among
stellar orbits, $E_{\rm tot}$, and the total angular momentum, $L_{\rm tot}$.
On timescales longer than $t_\mathrm{VRR}$, the eccentricities and semimajor
axes change slowly and the distribution of orbital inclinations are expected to
evolve through a series of VRR equilibria. Using a Monte Carlo Markov Chain
method, we determine the equilibrium distribution of orbital inclinations in
the microcanonical ensemble with fixed $E_{\rm tot}$ and $L_{\rm tot}$ for
isolated nuclear star clusters with a power-law distribution of $a$, $e$, and
$m$, where $m$ is the stellar mass. We explore the possible equilibria for $9$
representative $E_{\rm tot}$--$L_{\rm tot}$ pairs that cover the possible
parameter space. For all cases, the equilibria show anisotropic mass
segregation where the distribution of more massive objects is more flattened
than that for lighter objects. Given that stellar black holes are more massive
than the average main sequence stars, these findings suggest that black holes
reside in disc-like structures within nuclear star clusters for a wide range of
initial conditions.


title:
The ALMA REBELS Survey. Epoch of Reionization giants: properties of
  dusty galaxies at $z \approx 7$

abstract:
  We analyse FIR dust continuum measurements for 14 galaxies ($z\approx 7$) in
the ALMA REBELS LP to derive their physical properties. Our model uses three
input data: (a) the UV spectral slope, $\beta$, (b) the observed UV continuum
flux at $1500$A, $F_{\rm UV}$, (c) the observed continuum flux at $\approx
158\mu$m, $F_{158}$, and considers Milky Way (MW) and SMC extinction curves,
along with different dust geometries. We find that REBELS galaxies have
(28-90.5)% of their star formation obscured; the total (UV+IR) star formation
rates are in the range $31.5 < {\rm SFR}/ (M_\odot {\rm yr}^{-1}) < 129.5$. The
sample-averaged dust mass and temperature are $(1.3\pm 1.1)\times 10^7 M_\odot$
and $52 \pm 11$ K, respectively. In some galaxies dust is abundant (REBELS-14,
$M'_d \approx 3.4 \times 10^7 M_\odot$), or hot (REBELS-18, $T'_d \approx 67$
K). The dust distribution is compact ($<0.3$ kpc for 70% of the galaxies). The
dust yield per supernova is $0.1 \le y_d/M_\odot \le 3.3$, with 70% of the
galaxies requiring $y_d < 0.25 M_\odot$. Three galaxies (REBELS-12, 14, 39)
require $y_d > 1 M_\odot$. With the SFR predicted by the model and a MW
extinction curve, REBELS galaxies detected in [CII] nicely follow the local
$L_{\rm CII}-$SFR relation, and are approximately located on the
Kennicutt-Schmidt relation. The sample-averaged gas depletion time is of
$0.11\, y_P^{-2}$ Gyr, where $y_P$ is the ratio of the gas-to-stellar
distribution radius. For some systems a solution simultaneously matching the
observed ($\beta, F_{\rm UV}, F_{158}$) values cannot be found. This occurs
when the index $I_m = (F_{158}/F_{\rm UV})/(\beta-\beta_{\rm int})$, where
$\beta_{\rm int}$ is the intrinsic UV slope, exceeds $I_m^*\approx 1120$ for a
MW curve. For these objects we argue that the FIR and UV emitting regions are
not co-spatial, questioning the use of the IRX-$\beta$ relation.


title: A 16 au Binary in the Class 0 Protostar L1157 MMS

abstract:
  We present VLA observations toward the Class 0 protostar L1157 MMS at 6.8 mm
and 9 mm with a resolution of ~0.04" (14 au). We detect two sources within
L1157 MMS and interpret these sources as a binary protostar with a separation
of ~16 au. The material directly surrounding the binary system within the inner
50 au radius of the system has an estimated mass of 0.11 M_sun, calculated from
the observed dust emission. We interpret the observed binary system in the
context of previous observations of its flattened envelope structure, low rates
of envelope rotation from 5000 to 200 au scales, and an ordered, poloidal
magnetic field aligned with the outflow. Thus, L1157 MMS is a prototype system
for magnetically-regulated collapse and the presence of a compact binary within
L1157 MMS demonstrates that multiple star formation can still occur within
envelopes that likely have dynamically important magnetic fields.


title:
Tidal Disruption Events by Relatively Compact Supermassive Black Hole
  Binaries

abstract:
  Stars can be tidally destroyed or swallowed by supermassive black hole
binaries. Using a large number of accurate few-body simulations, we investigate
the enhancement and suppression of full and partial disruption and direct
capture events by hard supermassive black hole binaries with a wide ranges of
key parameters, i.e., the primary black hole mass ($10^{5}-10^{8}M_{\odot}$),
the binary mass ratio ($10^{-3}-1$), the ratio of the binary semimajor axis to
the hardening radius ($10^{-4}-1$), the binary eccentricity ($0.0-0.9$) and the
stellar mass ($0.3-3M_{\odot}$). This is a significant extension of the
parameter space compared to previous work. We show that the encounter
probabilities of all three events are well-described by the encounter cross
section, which is proportional to the pericenter distance. The probability of
full disruptions by supermassive black hole binaries can be enhanced by up to a
factor of $40-50$ or suppressed by up to a factor of $10$, relative to that by
single black holes, depending on the binary parameters. The Post-Newtonian
effects are not important for the primary black hole mass $\leq
10^{7}M_{\odot}$, but can provide an additional enhancement of the full
disruption probability by less than a factor of $2-3$ for higher primary black
hole masses. We provide a fitting formula for the full disruption probability
by the hard supermassive black hole binaries that works for a wide range of
parameters. We also find that partial disruption events can occur multiple
times before full disruptions or direct captures, and their probabilities can
be greater than that of full disruption events by a factor of three. Because
partial disruption events can induce stellar spins and mass loss and change the
orbits, it can significantly affect the overall full disruption event rate and
the shape of the light curves.


title: RG-Inspired Neural Networks for Computing Topological Invariants

abstract:
  We show that artificial neural networks (ANNs) can, to high accuracy,
determine the topological invariant of a disordered system given its
two-dimensional real-space Hamiltonian. Furthermore, we describe a
"renormalization-group" (RG) network, an ANN which converts a Hamiltonian on a
large lattice to another on a small lattice while preserving the invariant. By
iteratively applying the RG network to a "base" network that computes the Chern
number of a small lattice of set size, we are able to process larger lattices
without re-training the system. We therefore show that it is possible to
compute real-space topological invariants for systems larger than those on
which the network was trained. This opens the door for computation times
significantly faster and more scalable than previous methods.


title: Ultrasound detection of emergent photons in generic quantum spin ice

abstract:
  Experimental identification of quantum spin ice (QSI), a U(1) quantum spin
liquid on the pyrochlore lattice hosting emergent photons, is a major challenge
in frustrated magnets. In this work, we propose ultrasound measurements as a
novel tool for probing the emergent photons of various QSI phases. Our analysis
includes QSI phases in non-Kramers doublet compounds such as $\rm{Pr}_2
\rm{Zr}_2 \rm{O}_7$ as well as dipolar-octupolar Kramers doublet compounds such
as $\rm{Ce}_2 \rm{Zr}_2 \rm{O}_7$. The latter may host emergent photons
associated with an octupolar component which renders them difficult to detect
with inelastic neutron scattering. We demonstrate theoretically how the speed
of the emergent photons can be obtained from the renormalization of the phonon
spectrum and show that ultrasound measurements provide a means of
distinguishing the dipolar from the octupolar QSI phase in dipolar-octupolar
materials.


title: Corner mode dynamics of periodically driven higher-order Weyl semimetals

abstract:
  We study the stroboscopic dynamics of corner modes of a second-order
topological material modeled by a tight-binding free fermion Hamiltonian on a
cubic lattice in the intermediate drive frequency regime for both discrete
(square pulse) and continuous (cosine) periodic drive protocols. We analyze the
Floquet phases of this system and show that its quasienergy spectrum becomes
almost gapless in the large drive amplitude regime at special drive
frequencies. Away from these frequencies, the gapped quasienergy spectrum
supports weakly dispersing Floquet corner modes. Near them, these corner modes
penetrate into the bulk and eventually become indistinguishable from the bulk
modes. We provide an analytic, albeit perturbative, expression for the Floquet
Hamiltonian using Floquet perturbation theory (FPT) which explains this
phenomenon and leads to analytic expressions of these special frequencies. We
also show that in the large drive amplitude regime, the zero energy corner
modes corresponding to the static tight binding Hamiltonian display
qualitatively different dynamics at these special frequencies. We discuss
possible local density of state measurement using a scanning tunneling
microscope which can test our theory.


title: The velocity distribution of white dwarfs in Gaia EDR3

abstract:
  Using a penalised maximum likelihood we estimate, for the first time, the
velocity distribution of white dwarfs in the Solar neighbourhood. Our sample
consists of 129 675 white dwarfs within 500 pc in Gaia Early Data Release 3 The
white dwarf velocity distributions reveal a similar structure to the rest of
the Solar neighbourhood stars, reflecting that white dwarfs are subjected to
the same dynamical processes. In the velocity distribution for three
magnitude-binned subsamples we however find a novel structure at $(U, V) = (7,
-19)$ km s$^{-1}$ in fainter samples, potentially related to the Coma Berenices
stream. We also see a double-peaked feature in $U$-$W$ at $U \approx -30$ km
s$^{-1}$ and in $V$-$W$ at $V \approx -20$ km s$^{-1}$ for fainter samples. We
determine the velocity distribution and velocity moments as a function of
absolute magnitude for two samples based on the bifurcation identified in Gaia
Data Release 2 in the colour-magnitude diagram. The brighter, redder sequence
has a larger velocity dispersion than the fainter, bluer sequence across all
magnitudes. It is hard to reconcile this kinematic difference with a
bifurcation caused purely by atmospheric composition, while it fits neatly with
a significant age difference between the two sequences. Our results provide
novel insights into the kinematic properties of white dwarfs and demonstrate
the power of analytical techniques that work for the large fraction of stars
that do not have measured radial velocities in the current era of large-scale
astrometric surveys.


title: Scaling relations of clusters and groups, and their evolution

abstract:
  X-ray observations of the hot intra-cluster medium (ICM) in galaxy groups and
clusters provide quantities such as their gas mass, X-ray luminosity, and
temperature. The analysis of the scaling relations between these observable
properties gives considerable insight into the physical processes taking place
in the ICM. Furthermore, an understanding of the scaling relations between ICM
properties and the total cluster mass is essential for cosmological studies
with clusters. For these reasons, the X-ray scaling relations of groups and
clusters have been a major focus of research over the past several decades. In
this Chapter, after presenting the expectations from the self-similar model,
based on the assumption that only gravity drives the evolution of the ICM, we
discuss how the processes of gas cooling and non-gravitational heating are
believed to be responsible for the observed deviations from the self-similar
scenario. We also describe important complications that must be considered when
measuring and interpreting the scaling relations.


title:
Decimation technique for open quantum systems: a case study with
  driven-dissipative bosonic chains

abstract:
  The unavoidable coupling of quantum systems to external degrees of freedom
leads to dissipative (non-unitary) dynamics, which can be radically different
from closed-system scenarios. Such open quantum system dynamics is generally
described by Lindblad master equations, whose dynamical and steady-state
properties are challenging to obtain, especially in the many-particle regime.
Here, we introduce a method to deal with these systems based on the calculation
of (dissipative) lattice Green's function with a real-space decimation
technique. Compared to other methods, such technique enables obtaining compact
analytical expressions for the dynamics and steady-state properties, such as
asymptotic decays or correlation lengths. We illustrate the power of this
method with several examples of driven-dissipative bosonic chains of increasing
complexity, including the Hatano-Nelson model. The latter is especially
illustrative because its surface and bulk dissipative behavior are linked due
to its non-trivial topology, which manifests in directional amplification.


title:
Topological defects in a double-mirror quadrupole insulator displace
  diverging charge

abstract:
  We show that topological defects in quadrupole insulators do not host
quantized fractional charges, contrary to what their Wannier representation
indicates. In particular, we test the charge quantization hypothesis based on
the Wannier representation of a parametric defect and a disclination. Against
the expectations, we find that the local charge density decays as $\sim 1/r^2$
with distance, leading to a diverging defect charge. We identify sublattice
symmetry and not higher order topology as the origin of the previously reported
charge quantization.


title:
Signatures of a surviving helium-star companion in Type Ia supernovae
  and constraints on the progenitor companion of SN 2011fe

abstract:
  Single-degenerate (SD) binary systems composed of a white dwarf and a
non-degenerate helium (He)-star companion have been proposed as the potential
progenitors of Type Ia supernovae (SNe Ia). The He-star companions are expected
to survive the SN Ia explosion in this SD progenitor model. In the present
work, we map the surviving He-star companion models computed from our previous
three-dimensional hydrodynamical simulations of ejecta-companion interaction
into the one-dimensional stellar evolution code MESA to follow their long-term
evolution to make predictions on their post-impact observational properties,
which can be helpful for searches of such surviving He-star companions in
future observations. By comparing with the very late-epoch light curve of the
best observed SN Ia, SN 2011fe, we find that our surviving He-star companions
become significantly more luminous than SN 2011fe about 1000d after the maximum
light. This suggests that a He star is very unlikely to be a companion to the
progenitor of SN 2011fe.


title:
Blue Stragglers as tracers of the dynamical state of two clusters in the
  Small Magellanic Cloud: NGC 339 and NGC 419

abstract:
  The level of central segregation of Blue Straggler stars proved to be an
excellent tracer of the dynamical evolution of old star clusters (the so-called
"dynamical clock"), both in the Milky Way and in the Large Magellanic Cloud.
The $A^{+}$ parameter, used to measure the Blue Stragglers degree of
segregation, has in fact been found to strongly correlate with the parent
cluster central relaxation time. Here we studied the Blue-Straggler population
of two young stellar systems in the Small Magellanic Cloud, namely NGC 339
(which is 6 Gyr old) and NGC 419 (with an age of only 1.5 Gyr), in order to
study their dynamical state. Thanks to multi-epoch, high angular resolution
Hubble Space Telescope observations available for both clusters, we took
advantage of the stellar proper motions measured in the regions of the two
systems and we selected a population of likely cluster members, removing the
strong contamination from Small Magellanic Cloud stars. This enabled us to
study, with unprecedented accuracy, the radial distribution of Blue Stragglers
in these two extragalactic clusters and to measure their dynamical age. As
expected for such young clusters, we found that both systems are poorly evolved
from the dynamical point of view, also fully confirming that the $A^{+}$
parameter is a sensitive "clock hand" even in the dynamically-young regime.


title:
Coronal Mass Ejection Image Edge Detection In Heliospheric Imager STEREO
  SECCHI Data

abstract:
  We present an algorithm to detect the outer edges of Coronal Mass Ejection
(CME) events as seen in differences of Heliospheric Imager STEREO SECCHI HI-1
images from either A or B spacecraft, as well as its implementation in Python.


title:
Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for
  Deep Neural Networks

abstract:
  Deep neural network (DNN) classifiers are often overconfident, producing
miscalibrated class probabilities. Most existing calibration methods either
lack theoretical guarantees for producing calibrated outputs or reduce the
classification accuracy in the process. This paper proposes a new Kernel-based
calibration method called KCal. Unlike other calibration procedures, KCal does
not operate directly on the logits or softmax outputs of the DNN. Instead, it
uses the penultimate-layer latent embedding to train a metric space in a
supervised manner. In effect, KCal amounts to a supervised dimensionality
reduction of the neural network embedding, and generates a prediction using
kernel density estimation on a holdout calibration set. We first analyze KCal
theoretically, showing that it enjoys a provable asymptotic calibration
guarantee. Then, through extensive experiments, we confirm that KCal
consistently outperforms existing calibration methods in terms of both the
classification accuracy and the (confidence and class-wise) calibration error.


title:
The halo bispectrum as a sensitive probe of massive neutrinos and baryon
  physics

abstract:
  The power spectrum has been a workhorse for cosmological studies of
large-scale structure. However, the present-day matter distribution is highly
non-Gaussian and significant cosmological information is also contained in
higher-order correlation functions. Meanwhile, baryon physics (particularly AGN
feedback) has previously been shown to strongly affect the two-point statistics
but there has been limited exploration of its effects on higher-order functions
to date. Here we use the BAHAMAS suite of cosmological hydrodynamical
simulations to explore the effects of baryon physics and massive neutrinos on
the halo bispectrum. In contrast to matter clustering which is suppressed by
baryon physics, we find that the halo clustering is typically enhanced. The
strength of the effect and the scale over which it extends depends on how
haloes are selected. On small scales (k > 1 $h$ Mpc$^{-1}$, dominated by
satellites of groups/clusters), we find that the bispectrum is highly sensitive
to the efficiency of star formation and feedback, making it an excellent
testing ground for galaxy formation models. We show that the effects of
feedback and the effects of massive neutrinos are largely separable
(independent of each other) and that massive neutrinos strongly suppress the
halo bispectrum on virtually all scales up to the free-streaming length (apart
from the smallest scales, where baryon physics dominates). The strong
sensitivity of the bispectrum to neutrinos on the largest scales and galaxy
formation physics on the smallest scales bodes well for upcoming precision
measurements from the next generation of wide-field surveys.


title: Gamma rays reveal proton acceleration in thermonuclear novae explosions

abstract:
  Classical novae are cataclysmic binary star systems in which the matter of a
companion star is accreted on a white dwarf (WD). Accumulation of the matter in
a layer eventually causes a thermonuclear explosion on the surface of the WD,
brightening the WD to ~ 10 5 solar luminosities and triggering ejection of the
accumulated matter. They provide extreme conditions required to accelerate
particles, electrons or protons, to high energies. Here we present the
detection of gamma rays by the MAGIC telescopes from the 2021 outburst of RS
Ophiuchi (RS Oph), a recurrent symbiotic nova, that allowed us, for the first
time, to accurately characterize the emission from a nova in the 60 GeV to 250
GeV energy range. The theoretical interpretation of the combined Fermi -LAT and
MAGIC data suggests that protons are accelerated to hundreds of GeV in the nova
shock. Such protons should create bubbles of enhanced Cosmic Ray density up to
about 13 pc from the recurrent novae.


title: Better Together? An Evaluation of AI-Supported Code Translation

abstract:
  Generative machine learning models have recently been applied to source code,
for use cases including translating code between programming languages,
creating documentation from code, and auto-completing methods. Yet,
state-of-the-art models often produce code that is erroneous or incomplete. In
a controlled study with 32 software engineers, we examined whether such
imperfect outputs are helpful in the context of Java-to-Python code
translation. When aided by the outputs of a code translation model,
participants produced code with fewer errors than when working alone. We also
examined how the quality and quantity of AI translations affected the work
process and quality of outcomes, and observed that providing multiple
translations had a larger impact on the translation process than varying the
quality of provided translations. Our results tell a complex, nuanced story
about the benefits of generative code models and the challenges software
engineers face when working with their outputs. Our work motivates the need for
intelligent user interfaces that help software engineers effectively work with
generative code models in order to understand and evaluate their outputs and
achieve superior outcomes to working alone.


title: Snowmass White Paper on SCFTs

abstract:
  Superconformal field theories (SCFTs) occupy a central role in the study of
many aspects of quantum field theory. In this white paper for the Snowmass
process we give a brief overview of aspects of SCFTs in $3\leq D \leq 6$
space-time dimensions, including classification efforts and some of the vast
current research trends on the physical and mathematical structures generated
by this rich class of physical theories.


title:
Boundary-dependent dynamical instability of bosonic Green's function:
  Dissipative Bogoliubov-de Gennes Hamiltonian and its application to
  non-Hermitian skin effect

abstract:
  The energy spectrum of bosonic excitations from a condensate is given by the
spectrum of a non-Hermitian Hamiltonian constructed from a bosonic
Bogoliubov-de Gennes (BdG) Hamiltonian in general even though the system is
essentially Hermitian. In other words, two types of non-Hermiticity can
coexist: one from the bosonic BdG nature and the other from the open quantum
nature. In this paper, we propose boundary-dependent dynamical instability. We
first define the bosonic dissipative BdG Hamiltonian in terms of Green's
function in Nambu space and discuss the correct particle-hole symmetry of the
corresponding non-Hermitian Hamiltonian. We then construct a model of the
boundary-dependent dynamical instability so that it satisfies the correct
particle-hole symmetry. In this model, an anomalous term that breaks the
particle number conservation represents the non-Hermiticity of the BdG nature,
while a normal term is given by a dissipative Hatano-Nelson model. Thanks to
the competition between the two types of non-Hermiticity, the imaginary part of
the spectrum can be positive without the help of the amplification of the
normal part and the particle-hole band touching that causes the Landau
instability. This leads to the boundary-dependent dynamical instability under
the non-Hermitian skin effect, -strong dependence of spectra on boundary
conditions for non-Hermitian Hamiltonians-, of the Bogoliubov spectrum.

categories: cond-mat.mes-hall cond-mat.mtrl-sci cond-mat.quant-gas cond-mat.str-el quant-ph


title:
Post-explosion positive jet-feedback activity in inner ejecta of core
  collapse supernovae

abstract:
  We conduct three-dimensional hydrodynamical simulations of weak jets that we
launch into a core collapse supernovae (CCSNe) ejecta half an hour after the
explosion and find that the interaction of the fast jets with the CCSN ejecta
creates high pressure zones that induce a backflow that results in mass
accretion onto the newly born neutron star. In cases of weak jets, a total
power of 10^45-10^46 erg, the backflow mass accretion might power up to an
order of magnitude more energetic jets. In total, the jets of the two
post-explosion jet-launching episodes have enough energy to influence the
morphology of the very inner ejecta, a mass of 0.1 M_O. Our results imply that
in some, probably a minority of, CCSN remnants the very inner regions might
display a bipolar structure that results from post-explosion weak jets. The
regions outside this part might display the morphology of jittering jets.


title: On finite groups with certain complemented $p$-subgroups

abstract:
  Given a prime power $p^d$ with $p$ a prime and $d$ a positive integer, we
classify the finite groups $G$ with $p^{2d}$ dividing $|G|$ in which all
subgroups of order $p^d$ are complemented and the finite groups $G$ having a
normal elementary abelian Sylow $p$-subgroup $P$ such that $p^d<|P|$ in which
all subgroups of order $p^d$ are complemented.