May 2022 arXiv papers — page 140

Amishi Sanghi, Adrian E Fraser, Edward W Tian, Pascale Garaud

We study the properties of oscillatory double-diffusive convection (ODDC) in the presence of a uniform vertical background magnetic field. ODDC takes place in stellar regions that are unstable according to the Schwarzschild criterion and stable according to the Ledoux criterion (sometimes called semiconvective regions), which are often predicted to reside ju

Brian Campbell-Deem, Simon Knapen, Tongyan Lin, Ethan Villarama

In most direct detection experiments, the free nuclear recoil description of dark matter scattering breaks down for masses $\lesssim$ 100 MeV, or when the recoil energy is comparable to a few times the typical phonon energy. For dark matter lighter than 1 MeV, scattering via excitation of a single phonon dominates and has been computed previously, but for th

Ian Moult, Hua Xing Zhu, Yu Jiao Zhu

The rapidity anomalous dimension controls the scaling of transverse momentum dependent observables in the Sudakov region. In a conformal theory it is equivalent to the soft anomalous dimension, but in QCD this relation is broken by anomalous terms proportional to the $β$-function. In this paper we first give a simple proof of this relation using two differen

Baptiste Filoche, Rémy Larue, Jérémie Quevillon, Pham Ngoc Hoa Vuong

The path-integral measure of a gauge-invariant fermion theory is transformed under the chiral transformation and leads to an elegant derivation of the anomalous chiral Ward-Takahashi identities, as we know from the seminal work of Fujikawa. We present in this work an alternative and illuminating way to calculate the Jacobian in the path-integral measure from

Salvatore F. E. Oliviero, Lorenzo Leone, Alioscia Hamma

Ground states of quantum many-body systems are both entangled and possess a kind of quantum complexity as their preparation requires universal resources that go beyond the Clifford group and stabilizer states. These resources - sometimes described as magic - are also the crucial ingredient for quantum advantage. We study the behavior of the stabilizer Rényi

Moritz S. Fischer, Marcus Brüggen, Kai Schmidt-Hoberg, Klaus Dolag

Dark matter (DM) with self-interactions is a promising solution for the small-scale problems of the standard cosmological model. Here we perform the first cosmological simulation of frequent DM self-interactions, corresponding to small-angle DM scatterings. The focus of our analysis lies in finding and understanding differences to the traditionally assumed r

Claude Duhr, Bernhard Mistlberger, Gherardo Vita

We obtain the quark and gluon rapidity anomalous dimension to fourth order in QCD. We calculate the N$^3$LO rapidity anomalous dimensions to higher order in the dimensional regulator and make use of the soft/rapidity anomalous dimension correspondence in conjunction with the recent determination of the N$^4$LO threshold anomalous dimensions to achieve our re

Jessica Y. -C. Yeh, Aaron Smith, Rahul Kannan, Enrico Garaldi

A fundamental requirement for reionizing the Universe is that a sufficient fraction of the ionizing photons emitted by galaxies successfully escapes into the intergalactic medium. However, due to the scarcity of high-redshift observational data, the sources driving reionization remain uncertain. In this work we calculate the ionizing escape fractions ($f_{\r

Melissa van Beekveld, Silvia Ferrario Ravasio, Gavin P. Salam, Alba Soto-Ontoso

We formulate PanScales parton showers for hadron collisions so as to achieve next-to-leading logarithmic (NLL) accuracy across a broad set of observables. We do so specifically for colour singlet production. Relative to the existing PanScales final-state showers, the main new question is that of how to redistribute momentum imbalances from initial-state bran

Griffin Hosseinzadeh, David J. Sand, Peter Lundqvist, Jennifer E. Andrews

We present high-cadence optical and ultraviolet light curves of the normal Type Ia supernova (SN) 2021aefx, which shows an early bump during the first two days of observation. This bump may be a signature of interaction between the exploding white dwarf and a nondegenerate binary companion, or it may be intrinsic to the white dwarf explosion mechanism. In th

R. Andrew Gustafson, Ryan Plestid, Ian M. Shoemaker

We consider the upscattering of atmospheric neutrinos in the interior of the Earth producing heavy neutral leptons (HNLs) which subsequently decay inside large volume detectors (e.g. Super-Kamiokande or DUNE). We compute the flux of upscattered HNLs arriving at a detector, and the resultant event rate of visible decay products. Using Super-Kamiokande's atmos

Sergei Gukov, Vincent S. H. Lee, Kathryn M. Zurek

We study quantum fluctuations in the lightcone metric of the 4-d Einstein-Hilbert action via dimensional reduction to Jackiw-Teitelboim (JT) gravity. In particular, we show that, in Einstein gravity, the causal development of a region in flat Minkowski spacetime, near a horizon defined by light sheets, can be described by an effective two-dimensional dilaton

Shuliang Liu, Xuming Hu, Chenwei Zhang, Shu`ang Li

Unsupervised relation extraction aims to extract the relationship between entities from natural language sentences without prior information on relational scope or distribution. Existing works either utilize self-supervised schemes to refine relational feature signals by iteratively leveraging adaptive clustering and classification that provoke gradual drift

Maurizio Fagotti, Vanja Marić, Lenart Zadnik

We consider nonequilibrium time evolution in quantum spin chains after a global quench. Usually a nonequilibium quantum many-body system locally relaxes to a (generalised) Gibbs ensemble built from conserved operators with quasilocal densities. Here we exhibit explicit examples of local Hamiltonians that possess conservation laws with densities that are not

Simone Roncallo, Krzysztof Sacha, Lorenzo Maccone

We compare the proposals that have appeared in the literature to describe a measurement of the time of arrival of a quantum particle at a detector. We show that there are multiple regimes where different proposals give inequivalent, experimentally discriminable, predictions. This analysis paves the way for future experimental tests.

Ritu Dcruz, Anil Thapa

We present a singly charged scalar extension of the Scotogenic model, ScotoZee, which resolves the recently reported deviations in $W$ boson mass as well as lepton $g-2$. The model admits a scalar or a fermionic dark matter while realizing naturally small radiative neutrino masses. The mass splitting of $\sim 100$ GeV, required by the shift in $W$ boson mass

Yao-Chia Chan, Pouya Pezeshkpour, Chunhua Geng, Syed A. Jafar

Using ideas from Generalized Degrees of Freedom (GDoF) analyses and extremal network theory, this work studies the extremal gain of optimal power control over binary (on/off) power control, especially in large interference networks, in search of new theoretical insights. Whereas numerical studies have already established that in most practical settings binar

Davoud Ataee Tarzanagh, Mingchen Li, Christos Thrampoulidis, Samet Oymak

Standard federated optimization methods successfully apply to stochastic problems with single-level structure. However, many contemporary ML problems -- including adversarial robustness, hyperparameter tuning, and actor-critic -- fall under nested bilevel programming that subsumes minimax and compositional optimization. In this work, we propose \fedblo: A fe

Madhumita Saha, Bijay Kumar Agarwalla, Manas Kulkarni, Archak Purkayastha

We discover a deep connection between parity-time (PT) symmetric optical systems and quantum transport in one-dimensional fermionic chains in a two-terminal open system setting. The spectrum of one dimensional tight-binding chain with periodic on-site potential can be obtained by casting the problem in terms of $2 \times 2$ transfer matrices. We find that th

M. Bonavita, C. Fontanive, R. Gratton, K. Muzic

The last decade of direct imaging (DI) searches for sub-stellar companions has uncovered a widely diverse sample that challenges the current formation models, while highlighting the intrinsically low occurrence rate of wide companions, especially at the lower end of the mass distribution. These results clearly show how blind surveys, crucial to constrain the

Xin-Qiang Li, Ze-Jun Xie, Ya-Dong Yang, Xing-Bo Yuan

The recently updated measurement of the $W$-boson mass by the CDF collaboration exhibits a $7σ$ deviation from the SM expectation, which may imply a sign of new physics beyond the SM. The observed discrepancy could be explained by new fermions that carry the electroweak gauge charges and affect the vacuum polarization of gauge bosons. Notably, if the new fer

Eric De Giuli, Camille Scalliet

Both natural ecosystems and biochemical reaction networks involve populations of heterogeneous agents whose cooperative and competitive interactions lead to a rich dynamics of species' abundances, albeit at vastly different scales. The maintenance of diversity in large ecosystems is a longstanding puzzle, towards which recent progress has been made by th

Tim Kutta, Holger Dette

Statistical inference for large data panels is omnipresent in modern economic applications. An important benefit of panel analysis is the possibility to reduce noise and thus to guarantee stable inference by intersectional pooling. However, it is wellknown that pooling can lead to a biased analysis if individual heterogeneity is too strong. In classical line

Vítor H. Fernandes, Tânia Paulista

In this paper we consider the monoid $\DPC_n$ of all partial isometries of a $n$-cycle graph $C_n$. We show that $\DPC_n$ is the submonoid of the monoid of all oriented partial permutations on a $n$-chain whose elements are precisely all restrictions of the dihedral group of order $2n$. Our main aim is to exhibit a presentation of $\DPC_n$. We also describe

Armen Vagharshakyan

By correcting, simplifying and extending a result of Morimoto, we prove a Paley-Wiener type theorem for functions of exponential type in a sector. It serves as a sectorial analogue of Polya's theorem on the indicator of entire functions and improves a result of Dzhrbashyan and Avetisyan by finding the maximal convex set of analytic continuation inside a sect

Carsten Lutz, Leif Sabellek, Lukas Schulze

We study the evaluation of ontology-mediated queries (OMQs) on databases of bounded cliquewidth from the viewpoint of parameterized complexity theory. As the ontology language, we consider the description logics $\mathcal{ALC}$ and $\mathcal{ALCI}$ as well as the guarded two-variable fragment GF$_2$ of first-order logic. Queries are atomic queries (AQs), con

Yichul Choi, Kantaro Ohmori

When a quantum field theory is trivially gapped, its infrared fixed point is an invertible field theory. The partition function of the invertible field theory records the response to various background fields in the long-distance limit. The set of background fields can include spacetime-dependent coupling constants, in which case we call the corresponding in

Lauren Conger, Jing Shuang Li, Eric Mazumdar, Steven L. Brunton

This work introduces a controller synthesis method via system level synthesis for nonlinear systems characterized by polynomial dynamics. The resulting framework yields finite impulse response, time-invariant, closed-loop transfer functions with guaranteed disturbance cancellation. Our method generalizes feedback linearization to enable partial feedback line

Shuo Xiao, Yan-Qiu Zhang, Zi-Pei Zhu, Shao-Lin Xiong

The milestone discovery of GW 170817-GRB 170817A-AT 2017gfo has shown that gravitational wave (GW) could be produced during the merger of neutron star-neutron star/black hole and that in electromagnetic (EM) wave a gamma-ray burst (GRB) and a kilonova (KN) are generated in sequence after the merger. Observationally, however, EM property before the merger pha

Shane Storks, Keunwoo Peter Yu, Joyce Chai

As NLP research attracts public attention and excitement, it becomes increasingly important for it to be accessible to a broad audience. As the research community works to democratize NLP, it remains unclear whether beginners to the field can easily apply the latest developments. To understand their needs, we conducted a study with 93 students in an introduc

Sebastian Müller, Andreas Penzkofer, Nikita Polyanskii, Jonas Theis

We introduce the theoretical foundations of the Tangle 2.0, a probabilistic leaderless consensus protocol based on a directed acyclic graph (DAG) called the Tangle. The Tangle naturally succeeds the blockchain as its next evolutionary step as it offers features suited to establish more efficient and scalable distributed ledger solutions. Consensus is no long

Alexander Kalinin, Thilo Meyer-Brandis, Frank Proske

We deduce stability and pathwise uniqueness for a McKean-Vlasov equation with random coefficients and a multidimensional Brownian motion as driver. Our analysis focuses on a non-Lipschitz drift coefficient and includes moment estimates for random It\^o processes that are of independent interest. For deterministic coefficients we provide unique strong solutio

Arthur Bražinskas, Ramesh Nallapati, Mohit Bansal, Markus Dreyer

Abstractive summarization models are typically pre-trained on large amounts of generic texts, then fine-tuned on tens or hundreds of thousands of annotated samples. However, in opinion summarization, large annotated datasets of reviews paired with reference summaries are not available and would be expensive to create. This calls for fine-tuning methods robus

Kairi Furui, Masahito Ohue

Learning-to-rank, a machine learning technique widely used in information retrieval, has recently been applied to the problem of ligand-based virtual screening, to accelerate the early stages of new drug development. Ranking prediction models learn based on ordinal relationships, making them suitable for integrating assay data from various environments. Exis

Mika Göös, Alexandros Hollender, Siddhartha Jain, Gilbert Maystre

It is well-known that Resolution proofs can be efficiently simulated by Sherali-Adams (SA) proofs. We show, however, that any such simulation needs to exploit huge coefficients: Resolution cannot be efficiently simulated by SA when the coefficients are written in unary. We also show that Reversible Resolution (a variant of MaxSAT Resolution) cannot be effici

César A. Hidalgo

In recent years economic complexity has grown into an active field of fundamental and applied research. Yet, despite important advances, the policy implications of economic complexity remain unclear or misunderstood. Here I organize the policy implications of economic complexity in a framework grounded on 4 Ws: what approaches, focused on identifying target

Zhen Dong, Kaicheng Zhou, Guohao Li, Qiang Zhou

Neural architecture search (NAS) has shown great success in the automatic design of deep neural networks (DNNs). However, the best way to use data to search network architectures is still unclear and under exploration. Previous work has analyzed the necessity of having ground-truth labels in NAS and inspired broad interest. In this work, we take a further st

Ben Jourdan, Peter Macgregor, He Sun

We study the following $\mathsf{KS}_2(c)$ problem: let $c \in\mathbb{R}^+$ be some constant, and $v_1,\ldots, v_m\in\mathbb{R}^d$ be vectors such that $\|v_i\|^2\leq α$ for any $i\in[m]$ and $\sum_{i=1}^m \langle v_i, x\rangle^2 =1$ for any $x\in\mathbb{R}^d$ with $\|x\|=1$. The $\mathsf{KS}_2(c)$ problem asks to find some $S\subset [m]$, such that it holds

Yair Carmon, Oliver Hinder

We develop an algorithm for parameter-free stochastic convex optimization (SCO) whose rate of convergence is only a double-logarithmic factor larger than the optimal rate for the corresponding known-parameter setting. In contrast, the best previously known rates for parameter-free SCO are based on online parameter-free regret bounds, which contain unavoidabl

Ziming Shi, Ruixiang Zhang

Let $f$ be the germ of a real analytic function at the origin in $\mathbb{R}^n $ for $n \geq 2$, and suppose the codimension of the zero set of $f$ at $\mathbf{0}$ is at least $2$. We show that $\log |f|$ is $W^{1,1}_{\operatorname{loc}}$ near $\mathbf{0}$. In particular, this implies the differential inequality $|\nabla f |\leq V |f|$ holds with $V \in L^1_

Vladimir Rovenski

An $f$-structure, introduced by K. Yano in 1963 and subsequently studied by a number of geometers, is a higher dimensional analog of almost complex and almost contact structures, defined by a (1,1)-tensor field $f$ on a $(2n+p)$-dimensional manifold, which satisfies $f^3 + f = 0$ and has constant rank $2n$. We recently introduced the weakened (globally frame

Ting-yan Li, Ya-rong Wang, Cheng-qun Pang

Two observed structures with $M=1868 \pm 8^{+ 40}_{- 57}$ MeV and $M=2073 \pm 94^{+ 245}_{- 240}$ MeV are the same states ($K_2^*(1980)$) in PDG.The analysis of the mass spectrum and the calculation of the strong decay of $K_2^*$ mesons support the low mass state of $K_2^*(1980)$ as $2^3P_2$ and the high mass state of $K_2^*(1980)$ as $1^3F_2$ in this letter

Yvonne Alama Bronsard, Yvain Bruned, Katharina Schratz

We introduce a new class of numerical schemes which allow for low regularity approximations to the expectation $ \mathbb{E}(|u_{k}(\tau, v^{\eta})|^2)$, where $u_k$ denotes the $k$-th Fourier coefficient of the solution $u$ of the dispersive equation and $ v^{\eta}(x) $ the associated random initial data. This quantity plays an important role in physics, in

Igor Filikhin, Abdennaceur Karoui, Branislav Vlahovic

Based on the effective-mass concept, we perform the Faddeev calculations for a low-lying spectrum of 3$α$ states in $^{12}$C nucleus. A three-body potential is used to describe the known breaking of the 3$α$-cluster structure in the nucleus. We show that the contribution of the three-body potential to the Hamiltonian can be compensated by increasing/decreasi

Gabriele Franciolini, Anshuman Maharana, Francesco Muia

Light primordial black holes may comprise a dominant fraction of the dark matter in our Universe. This paper critically assesses whether planned and future gravitational wave detectors in the ultra-high-frequency band could constrain the fraction of dark matter composed of sub-solar primordial black holes. Adopting the state-of-the-art description of primord

Constantine Maganaris, Eftychios Protopapadakis, Nikolaos Bakalos, Nikolaos Doulamis

Recent studies indicate that detecting radiographic patterns on CT scans can yield high sensitivity and specificity for Covid-19 localization. In this paper, we investigate the appropriateness of deep learning models transferability, for semantic segmentation of pneumonia-infected areas in CT images. Transfer learning allows for the fast initialization/reuti

Supin P Surendran, Aiswarya A, Rinsy Thomas, Minu Joy

A novel evolutionary method is introduced that can be used for constraining the parameters and theoretical models of Cosmology. The newly proposed algorithm, which is inherently parallel by design, is able to obtain the full potential of multi-core machines. With this algorithm, we could obtain the best-fit parameters of the $\Lambda CDM$ cosmological model

Fulvio Gesmundo, Purnata Ghosal, Christian Ikenmeyer, Vladimir Lysikov

We analyze Kumar's recent quadratic algebraic branching program size lower bound proof method (CCC 2017) for the power sum polynomial. We present a refinement of this method that gives better bounds in some cases. The lower bound relies on Noether-Lefschetz type conditions on the hypersurface defined by the homogeneous polynomial. In the explicit example

Jason P. Bell, Khoa D. Nguyen, Umberto Zannier

We consider D-finite power series $f(z)=\sum a_n z^n$ with coefficients in a number field $K$. We show that there is a dichotomy governing the behaviour of $h(a_n)$ as a function of $n$, where $h$ is the absolute logarithmic Weil height. As an immediate consequence of our results, we have that either $f(z)$ is rational or $h(a_n)>[K:\mathbb{Q}]^{-1}\cdot \lo

Peter Z. Schochet

RCTs sometimes test interventions that aim to improve existing services targeted to a subset of individuals identified after randomization. Accordingly, the treatment could affect the composition of service recipients and the offered services. With such bias, intention-to-treat estimates using data on service recipients and nonrecipients may be difficult to

Alejandro Díaz-Caro, Octavio Malherbe

We explore a proof language for intuitionistic multiplicative additive linear logic, incorporating the sup connective that introduces additive pairs with a probabilistic elimination, and sum and scalar products within the proof-terms. We provide an abstract characterisation of the language, revealing that any symmetric monoidal closed category with biproduct

Vincenzo Alba, Federico Carollo

We derive the quasiparticle picture for the fermionic logarithmic negativity in a tight-binding chain subject to gain and loss dissipation. We focus on the dynamics after the quantum quench from the fermionic N\'eel state. We consider the negativity between both adjacent and disjoint intervals embedded in an infinite chain. Our result holds in the standard h

Joonas Malmi, Matteo A. C. Rossi, Guillermo García-Pérez, Sabrina Maniscalco

We study spatial search with continuous-time quantum walks on real-world complex networks. We use smaller replicas of the Internet network obtained with a recent geometric renormalization method introduced by García-Pérez et al., Nat. Phys. 14, 583 (2018). This allows us to infer for the first time the behavior of a quantum spatial search algorithm on a real

Yinan Bao, Qianwen Ma, Lingwei Wei, Wei Zhou

The Emotion-Cause Pair Extraction (ECPE) task aims to extract emotions and causes as pairs from documents. We observe that the relative distance distribution of emotions and causes is extremely imbalanced in the typical ECPE dataset. Existing methods have set a fixed size window to capture relations between neighboring clauses. However, they neglect the effe

Kaveena Persand, Andrew Anderson, David Gregg

Channel pruning is used to reduce the number of weights in a Convolutional Neural Network (CNN). Channel pruning removes slices of the weight tensor so that the convolution layer remains dense. The removal of these weight slices from a single layer causes mismatching number of feature maps between layers of the network. A simple solution is to force the numb

Adam Block, Zeyu Jia, Yury Polyanskiy, Alexander Rakhlin

Consider an empirical measure $\mathbb{P}_n$ induced by $n$ iid samples from a $d$-dimensional $K$-subgaussian distribution $\mathbb{P}$ and let $\gamma = N(0,\sigma^2 I_d)$ be the isotropic Gaussian measure. We study the speed of convergence of the smoothed Wasserstein distance $W_2(\mathbb{P}_n * \gamma, \mathbb{P}*\gamma) = n^{-\alpha + o(1)}$ with $*$ be

Oliver Russell, Wei Sun

The long-standing Gaussian product inequality (GPI) conjecture states that $E [\prod_{j=1}^{n}X_j^{2m_j}]\geq\prod_{j=1}^{n}E[X_j^{2m_j}]$ for any centered Gaussian random vector $(X_1,\dots,X_n)$ and $m_1,\dots,m_n\in\mathbb{N}$. In this paper, we describe a computational algorithm involving sums-of-squares representations of multivariate polynomials that c

Moumanti Podder, Dhruv Bhasin

We study the $k$-jump normal and $k$-jump mis\`{e}re games on rooted Galton-Watson trees, expressing the probabilities of various outcomes of these games as specific fixed points of certain functions that depend on $k$ and the offspring distribution. We discuss results on phase transitions pertaining to draw probabilities when the offspring distribution is P

Xiaobo Guo, Yuhang Lu, Benrong Mu, Peng Wang

We conjecture that there exists a relationship between Lyapunov exponents and black hole phase transitions. To support our conjecture, Lyapunov exponents of the motion of particles and ring strings are calculated for Reissner-Nordström-AdS black holes. When a phase transition occurs, the Lyapunov exponents become multivalued, and branches of the Lyapunov exp

Vladimir Slesar, Gabriel-Eduard Vîlcu

We use the transverse Kähler-Ricci flow on the canonical foliation of a closed Vaisman manifold to deform the Vaisman metric into another Vaisman metric with a transverse Kähler-Einstein structure. We also study the main features of such a manifold. Among other results, using techniques from the theory of parabolic equations, we obtain a direct proof for the

Ema Becirovic, Emil Björnson, Erik G. Larsson

Reciprocity-based time-division duplex (TDD) Massive MIMO (multiple-input multiple-output) systems utilize channel estimates obtained in the uplink to perform precoding in the downlink. However, this method has been criticized of breaking down, in the sense that the channel estimates are not good enough to spatially separate multiple user terminals, at low u

Joshua Lackman

We generalize the van Est map and isomorphism theorem in three ways, and we discuss conjectured connections with homotopy theory, including a proposal of a category which unifies differentiable stacks, Lie algebroids and homotopy theory. In Part 2 of this thesis we generalize the van Est map from a comparison map between Lie groupoid cohomology and Lie algeb

Fergal Stapleton, Edgar Galván, Ganesh Sistu, Senthil Yogamani

The incentive for using Evolutionary Algorithms (EAs) for the automated optimization and training of deep neural networks (DNNs), a process referred to as neuroevolution, has gained momentum in recent years. The configuration and training of these networks can be posed as optimization problems. Indeed, most of the recent works on neuroevolution have focused

Yacheng Kang, Chang Liu, Lijing Shao

We investigate the prospects of electromagnetic follow-up observations for binary neutron star (BNS) mergers, with the help of early warnings from decihertz gravitational-wave (GW) observatories, B-DECIGO and DO-Optimal. Extending the previous work, we not only give quick assessments of joint short $γ$-ray burst (sGRB) detection rates for different $γ$-ray s

Asier Alonso-Bardaji, David Brizuela, Raül Vera

We present a covariant model of a spherically symmetric black hole with corrections motivated by loop quantum gravity. The effective modifications, parametrized by a positive constant $λ$, are implemented through a canonical transformation and a linear combination of the constraints of general relativity, in such a way that the theory remains free of anomali

Utkarsh Azad, Animesh Sinha

We present qLEET, an open-source Python package for studying parameterized quantum circuits (PQCs), which are widely used in various variational quantum algorithms (VQAs) and quantum machine learning (QML) algorithms. qLEET enables the computation of properties such as expressibility and entangling power of a PQC by studying its entanglement spectrum and the

Lucy Knight, Alexander Stasinski

For a principal ideal domain $A$, the Latimer--MacDuffee correspondence sets up a bijection between the similarity classes of matrices in $\operatorname{M}_{n}(A)$ with irreducible characteristic polynomial $f(x)$ and the ideal classes of the order $A[x]/(f(x))$. We prove that when $A[x]/(f(x))$ is maximal (i.e., integrally closed, i.e., a Dedekind domain),

Isaac Torres, Felipe de Melo Santos

The so-called Nonminimal Derivative Coupling (NDC) is an alternative to General Relativity, which produces an asymptotic inflationary mechanism when applied to cosmology. The detection of gravitational waves in the last decade has imposed very stringent constraints over gravitational theories, which gave rise to a massive revision of those theories, in order

Shi-Ping He

The CDF collaboration recently announced a new measurement result of the $W$ boson mass, and it is in tension with the standard model (SM) prediction. In this paper, we explain this anomaly in the vector-like quark (VLQ) $(X,T,B)_{L,R}$ and leptoquark (LQ) $S_3$ extended model. In this model, both the VLQ and LQ have positive corrections to the $W$ boson mas

Daniela Di Donato, Enrico Le Donne

We introduce a notion of intrinsically Lipschitz graphs in the context of metric spaces. This is a broad generalization of what in Carnot groups has been considered by Franchi, Serapioni, and Serra Cassano, and later by many others. We proceed by focusing our attention on the graphs as subsets of a metric space given by the image of a section of a quotient m

Ziyi Xu, Maximilian Strake, Tim Fingscheidt

Perceptual evaluation of speech quality (PESQ) requires a clean speech reference as input, but predicts the results from (reference-free) absolute category rating (ACR) tests. In this work, we train a fully convolutional recurrent neural network (FCRN) as deep noise suppression (DNS) model, with either a non-intrusive or an intrusive PESQNet, where only the

Yunzhi Zhang, Jiajun Wu

Novel view synthesis (NVS) and video prediction (VP) are typically considered disjoint tasks in computer vision. However, they can both be seen as ways to observe the spatial-temporal world: NVS aims to synthesize a scene from a new point of view, while VP aims to see a scene from a new point of time. These two tasks provide complementary signals to obtain a

Athul Kunjipurayil, Tianqi Zhao, Bharat Kumar, Bijay K. Agrawal

We investigate the impact of the neutron-star matter equation of state on the $f$- and $p_1$-mode oscillations of neutron stars obtained within the Cowling approximation and linearized general relativity. The $f$- and $p_1$-mode oscillation frequencies, and their damping times are calculated using representative sets of Skyrme Hartree-Fock and relativistic m

David Benson, John Greenlees

Let $G$ be a compact Lie group with maximal torus $T$. If $|N_G(T)/T|$ is invertible in the field $k$ then the algebra of cochains $C^*(BG;k)$ is formal as an $A_\infty$ algebra, or equivalently as a DG algebra.

Yoshiaki Sofue

We report the discovery of an expanding cylinder of HI gas of radius 1 kpc and vertical extent 800 pc by analyzing the 21-cm line survey data from the literature. The cylinder is expanding at 150 km s$^{-1}$ and rotating at 100 km s$^{-1}$, and is interpreted as due to a high-velocity conical wind at $\sim 180$ km s$^{-1}$ from the Galactic Center. The total

I. Brevik, A. V. Timoshkin

We investigate the accelerated expansion of the late-time universe in the Friedmann-Robertson-Walker metric with nonzero curvature, applying a holographic principle based on a generalized holographic dark energy model introduced by Nojiri and Odintsov (2005,2006). We describe the evolution of the universe using a generalized equation of state in the presence

Souhardya Sen, Shubham Kumar, Athul Kunjipurayi, Pinku Routaray

We study radial oscillations in non-rotating neutron stars by considering the unified equation of states (EoSs), which support the 2 M$_\odot$ star criterion. We solve the Sturm-Liouville problem to compute 20 lowest radial oscillation modes and their eigenfunctions for neutron star modelled with eight selected unified EoSs from distinct Skyrme-Hartree Fock,

Muneya Matsui

We show the equivalence of three properties for an infinitely divisible distribution: the subexponentiality of the density, the subexponentiality of the density of its Lévy measure and the tail equivalence between the density and its Lévy measure density, under monotonic-type assumptions on the Lévy measure density. The key assumption is that tail of the Lév

Zh. Sagidullayeva, K. Yesmakhanova, R. Myrzakulov, Zh. Myrzakulova

The present work addresses the study and characterization of the integrability of some generalized spin systems (ISS) in 1+1 dimensions. Lax representations for these ISS are successfully obtained. The gauge equivalent counterparts of these integrable ISS are presented. Finally, we consider Zhanbota transcendents and some integrable Zhanbota equations. In pa

Xian Wu, Chen Wang, Hongbo Fu, Ariel Shamir

Researchers have explored various ways to generate realistic images from freehand sketches, e.g., for objects and human faces. However, how to generate realistic human body images from sketches is still a challenging problem. It is, first because of the sensitivity to human shapes, second because of the complexity of human images caused by body shape and pos

Simone Costa

Archdeacon, in his seminal paper $[1]$, defined the concept of Heffter array in order to provide explicit constructions of $\mathbb{Z}_{v}$-regular biembeddings of complete graphs $K_v$ into orientable surfaces. In this paper, we first introduce the quasi-Heffter arrays as a generalization of the concept of Heffer array and we show that, in this context, we

Prakash Thakolkaran, Akshay Joshi, Yiwen Zheng, Moritz Flaschel

We propose a new approach for unsupervised learning of hyperelastic constitutive laws with physics-consistent deep neural networks. In contrast to supervised learning, which assumes the availability of stress-strain pairs, the approach only uses realistically measurable full-field displacement and global reaction force data, thus it lies within the scope of

Julien Posso, Guy Bois, Yvon Savaria

Spacecraft pose estimation is an essential computer vision application that can improve the autonomy of in-orbit operations. An ESA/Stanford competition brought out solutions that seem hardly compatible with the constraints imposed on spacecraft onboard computers. URSONet is among the best in the competition for its generalization capabilities but at the cos

Ross G. Pinsky

For $d\ge1$ and $r>0$, let $X^{(d;r)}(\cdot)$ be a $d$-dimensional Brownian motion with diffusion coefficient $D$, equipped with an exponential clock with rate $r$. When the clock rings, the process jumps to the origin and begins anew. For a parameter $T>0$, let $X^{\text{bb},d;T}(\cdot)$ be the process that performs a $d$-dimensional Brownian bridge with di

Vedansh Arya, Dharmendra Kumar

In this note, we establish a new Carleman estimate with singular weights for the sub-Laplacian on a Carnot group $\mathbb G$ for functions satisfying the discrepancy assumption in (2.16) below. We use such an estimate to derive a sharp vanishing order estimate for solutions to stationary Schrödinger equations.

Rodrigo Mira, Alexandros Haliassos, Stavros Petridis, Björn W. Schuller

Video-to-speech synthesis (also known as lip-to-speech) refers to the translation of silent lip movements into the corresponding audio. This task has received an increasing amount of attention due to its self-supervised nature (i.e., can be trained without manual labelling) combined with the ever-growing collection of audio-visual data available online. Desp

Sina Akbari, Jalal Etesami, Negar Kiyavash

Pearl's do calculus is a complete axiomatic approach to learn the identifiable causal effects from observational data. When such an effect is not identifiable, it is necessary to perform a collection of often costly interventions in the system to learn the causal effect. In this work, we consider the problem of designing the collection of interventions with

Guoliang Qiu, Yanheng Wang, Chihao Zhang

The problem of uniformly sampling hypergraph independent sets is revisited. We design an efficient perfect sampler for the problem under a condition similar to that of the asymmetric Lovász Local Lemma. When applied to $d$-regular $k$-uniform hypergraphs on $n$ vertices, our sampler terminates in expected $O(n\log n)$ time provided $d\le c\cdot 2^{k/2}/k$ fo

Pallavi Jain, Bianca Schoen-Phelan, Robert Ross

Self-Supervised learning (SSL) has become the new state-of-art in several domain classification and segmentation tasks. Of these, one popular category in SSL is distillation networks such as BYOL. This work proposes RSDnet, which applies the distillation network (BYOL) in the remote sensing (RS) domain where data is non-trivially different from natural RGB i

Nicholas Popovic, Michael Färber

We present FREDo, a few-shot document-level relation extraction (FSDLRE) benchmark. As opposed to existing benchmarks which are built on sentence-level relation extraction corpora, we argue that document-level corpora provide more realism, particularly regarding none-of-the-above (NOTA) distributions. Therefore, we propose a set of FSDLRE tasks and construct

Mingyang Song, Yi Feng, Liping Jing

Keyphrase extraction is a fundamental task in natural language processing and information retrieval that aims to extract a set of phrases with important information from a source document. Identifying important keyphrase is the central component of the keyphrase extraction task, and its main challenge is how to represent information comprehensively and discr

André H. Gomes

Generalized uncertainty principles (GUP) and, independently, Lorentz symmetry violations are two common features in many candidate theories of quantum gravity. Despite that, the overlap between both has received limited attention so far. In this brief paper, we carry out further investigations on this topic. At the nonrelativistic level and in the realm of c

Jie Wang, Minshuo Chen, Tuo Zhao, Wenjing Liao

Two-sample tests are important areas aiming to determine whether two collections of observations follow the same distribution or not. We propose two-sample tests based on integral probability metric (IPM) for high-dimensional samples supported on a low-dimensional manifold. We characterize the properties of proposed tests with respect to the number of sample

Songheng Zhang, Yong Wang, Haotian Li, Wanyu Zhang

Crowdfunding provides project founders with a convenient way to reach online investors. However, it is challenging for founders to find the most potential investors and successfully raise money for their projects on crowdfunding platforms. A few machine learning based methods have been proposed to recommend investors' interest in a specific crowdfunding

Fujun Hou

I present an example in which the individuals' preferences are strict orderings, and under the majority rule, a transitive social ordering can be obtained and thus a non-empty choice set can also be obtained. However, the individuals' preferences in that example do not satisfy any conditions (restrictions) of which at least one is required by Inada (

Felix Schremmer

We describe the generic $σ$-conjugacy classes associated with the Iwahori-Bruhat decomposition of a reductive group. As an application, we classify cordial elements as introduced by Milićević-Viehmann.

Tamás Gombor, Balázs Pozsgay

Superintegrable models are very special dynamical systems: they possess more conservation laws than what is necessary for complete integrability. This severely constrains their dynamical processes, and it often leads to their exact solvability, even in non-equilibrium situations. In this paper we consider special Hamiltonian deformations of superintegrable q

Akansha Sanwal, Robert Schippa

We prove new well-posedness results for dispersion-generalized Kadomtsev--Petviashvili I equations in $\mathbb{R}^2$, which family links the classical KP-I equation with the fifth order KP-I equation. For strong enough dispersion, we show global well-posedness in $L^2(\mathbb{R}^2)$. To this end, we combine resonance and transversality considerations with St

Hongyu Li, Yijie Mao, Onur Dizdar, Bruno Clerckx

This letter is the third part of a three-part tutorial that focuses on rate-splitting multiple access (RSMA) for 6G. As Part III of the tutorial, this letter provides an overview of integrating RSMA and reconfigurable intelligent surface (RIS). We first introduce two potential PHY layer techniques, namely, RSMA and RIS, including the need for integrating RSM

Nikolin Hima, Davide Bigoni, Francesco Dal Corso

A structural element is designed and investigated, forming the basis for the development of an elastic multistable metamaterial. The leitmotif of the structural design is the implementation of a strut characterized by a bifurcation occurring at either vanishing tensile or compressive load. It is shown that buckling at null load leads to a mechanical equivale