July 2023 arXiv papers — page 159

Carlos Rodriguez-Pardo, Konstantinos Kazatzis, Jorge Lopez-Moreno, Elena Garces

Neural material representations are becoming a popular way to represent materials for rendering. They are more expressive than analytic models and occupy less memory than tabulated BTFs. However, existing neural materials are immutable, meaning that their output for a certain query of UVs, camera, and light vector is fixed once they are trained. While this i

Lorenz Richter, Julius Berner

Recently, a series of papers proposed deep learning-based approaches to sample from target distributions using controlled diffusion processes, being trained only on the unnormalized target densities without access to samples. Building on previous work, we identify these approaches as special cases of a generalized Schr\"odinger bridge problem, seeking a stoc

Frano Rajič, Lei Ke, Yu-Wing Tai, Chi-Keung Tang

The Segment Anything Model (SAM) has established itself as a powerful zero-shot image segmentation model, enabled by efficient point-centric annotation and prompt-based models. While click and brush interactions are both well explored in interactive image segmentation, the existing methods on videos focus on mask annotation and propagation. This paper presen

Mousumi Mandal, Shruti Priya

Let $(R,\mathfrak m)$ be a Cohen-Macaulay local ring of dimension $d\geq 2$ and $I$ an $\mathfrak m$-primary ideal. Let rd$(I)$ be the reduction number of $I$ and n$(I)$ the postulation number. We prove that for $d=2,$ if n$(I)=\rho(I)-1,$ then rd$(I) \leq$n$(I)+2$ and if n$(I)\neq \rho(I)-1,$ then rd$(I)\geq$n$(I)+2.$ For $d \geq 3$, if $I$ is integrally cl

Xuce Niu, Moinul Hossain Rahat

Several pulsar timing arrays including NANOGrav, EPTA, PPTA, and CPTA have recently reported the observation of a stochastic background of gravitational wave spectrum in the nano-Hz frequencies. An inflationary interpretation of this observation is challenging from various aspects. We report that such a signal can arise from the Chern-Simons coupling in axio

Arunima Bhattacharya, Anna Skorobogatova

We develop regularity theory for critical points of variational integrals defined on Hessian spaces of functions on open, bounded subdomains of $\mathbb{R}^n$, under compactly supported variations. The critical point solves a fourth order nonlinear equation in double divergence form. We show that for smooth convex functionals, a $W^{2,\infty}$ critical point

Igor Krasnov

Heavy Neutral Leptons are popular hypothetical particles, first introduced as a way to explain neutrino oscillations, and since then extensively studied in relation to many other aspects of physics beyond the Standard Model. They also serve as viable targets for direct experimental searches, being effectively described only by HNL mass and mixing with each n

Abhishek Panigrahi, Sadhika Malladi, Mengzhou Xia, Sanjeev Arora

Recent works attribute the capability of in-context learning (ICL) in large pre-trained language models to implicitly simulating and fine-tuning an internal model (e.g., linear or 2-layer MLP) during inference. However, such constructions require large memory overhead, which makes simulation of more sophisticated internal models intractable. In this work, we

Debika Chowdhury, Gianmassimo Tasinato, Ivonne Zavala

Several pulsar timing array (PTA) collaborations recently announced the first detection of a stochastic gravitational wave (GW) background, leaving open the question of its source. We explore the possibility that it originates from cosmic inflation, a guaranteed source of primordial GW. The inflationary GW background amplitude is enhanced at PTA scales by a

Haixing Dai, Chong Ma, Zhiling Yan, Zhengliang Liu

This paper introduces SAMAug, a novel visual point augmentation method for the Segment Anything Model (SAM) that enhances interactive image segmentation performance. SAMAug generates augmented point prompts to provide more information about the user's intention to SAM. Starting with an initial point prompt, SAM produces an initial mask, which is then fed int

Andrei S. Rapinchuk, Igor A. Rapinchuk

Let $K$ be a field and $V$ be a set of rank one valuations of $K$. The corresponding Tate-Shafarevich group of a $K$-torus $T$ is $Sha(T , V) = \ker\left(H^1(K , T) \to \prod_{v \in V} H^1(K_v , T)\right)$. We prove that if $K = k(X)$ is the function field of a smooth geometrically integral quasi-projective variety over a field $k$ of characteristic 0 and $V

Kevin Hendrey, Sergey Norin, Raphael Steiner, Jérémie Turcotte

Motivated by Hadwiger's conjecture, we study the problem of finding the densest possible $t$-vertex minor in graphs of average degree at least $t-1$. We show that if $G$ has average degree at least $t-1$, it contains a minor on $t$ vertices with at least $(\sqrt{2}-1-o(1))\binom{t}{2}$ edges. We show that this cannot be improved beyond $\left(\frac{3}{4}+o(1

Salim Cerci, Zuhal Seyma Demiroglu, Abhay Deshpande, Paul R. Newman

Sensitivity to the strong coupling $\alpha_S(M^2_Z)$ is investigated using existing Deep Inelastic Scattering data from HERA in combination with projected future measurements from the Electron Ion Collider (EIC) in a next-to-next-to-leading order QCD analysis. A potentially world-leading level of precision is achievable when combining simulated inclusive neu

Afonso S. Bandeira, Antoine Maillard, Shahar Mendelson, Elliot Paquette

We consider the problem $(\mathrm{P})$ of fitting $n$ standard Gaussian random vectors in $\mathbb{R}^d$ to the boundary of a centered ellipsoid, as $n, d \to \infty$. This problem is conjectured to have a sharp feasibility transition: for any $\varepsilon > 0$, if $n \leq (1 - \varepsilon) d^2 / 4$ then $(\mathrm{P})$ has a solution with high probability, w

Radoslav Dimitrov, Zeyang Zhao, Ralph Abboud, İsmail İlkan Ceylan

Graph neural networks are prominent models for representation learning over graphs, where the idea is to iteratively compute representations of nodes of an input graph through a series of transformations in such a way that the learned graph function is isomorphism invariant on graphs, which makes the learned representations graph invariants. On the other han

Sayan Das, Yuchen Liao, Matteo Mucciconi

In this paper, we study large time large deviations for the height function $\mathfrak{h}(x,t)$ of the $q$-deformed polynuclear growth introduced in ABW22 [arXiv:2108.06018]. We show that the upper-tail deviations have speed $t$ and derive an explicit formula for the rate function $\Phi_+(\mu)$. On the other hand, we show that the lower-tail deviations have

Milan Krstajić, Péter Juhász, Jiří Kučera, Lucas R. Hofer

Ultracold gases of highly magnetic lanthanide atoms have enabled the realisation of dipolar quantum droplets and supersolids. However, future studies could be limited by the achievable atom numbers and hindered by high three-body loss rates. Here we study density-dependent atom loss in an ultracold gas of ${}^{166}$Er for magnetic fields below 4 G, identifyi

Zhengdao Chen

To characterize the function space explored by neural networks (NNs) is an important aspect of learning theory. In this work, noticing that a multi-layer NN generates implicitly a hierarchy of reproducing kernel Hilbert spaces (RKHSs) - named a neural Hilbert ladder (NHL) - we define the function space as an infinite union of RKHSs, which generalizes the exi

Mariana Haragus, Mathew A. Johnson, Wesley R. Perkins, Björn de Rijk

We study the nonlinear dynamics of perturbed, spectrally stable $T$-periodic stationary solutions of the Lugiato-Lefever equation (LLE), a damped nonlinear Schr\"odinger equation with forcing that arises in nonlinear optics. It is known that for each $N\in\mathbb{N}$, such a $T$-periodic wave train is (orbitally) asymptotically stable against $NT$-periodic,

Markus Utke, Ulrike Schmidt-Kraepelin

Liquid democracy with ranked delegations is a novel voting scheme that unites the practicability of representative democracy with the idealistic appeal of direct democracy: Every voter decides between casting their vote on a question at hand or delegating their voting weight to some other, trusted agent. Delegations are transitive, and since voters may end u

Emiel Lorist, Zoe Nieraeth

In this survey, we discuss the definition of a (quasi-)Banach function space. We advertise the original definition by Zaanen and Luxemburg, which does not have various issues introduced by other, subsequent definitions. Moreover, we prove versions of well-known basic properties of Banach function spaces in the setting of quasi-Banach function spaces.

Amir Eskandari-asl, Adolfo Avella

In this manuscript, after discussing in detail the internals of our recently developed method, the dynamical projective operatorial approach (DPOA), we provide the framework to apply this method to pumped semiconductor lattice systems and, in particular, to study and analyze their electronic excitations and TR-ARPES signal. The expressions for relevant out-o

Ziv Goldfeld, Dhrumil Patel, Sreejith Sreekumar, Mark M. Wilde

Entropy measures quantify the amount of information and correlation present in a quantum system. In practice, when the quantum state is unknown and only copies thereof are available, one must resort to the estimation of such entropy measures. Here we propose a variational quantum algorithm for estimating the von Neumann and R\'enyi entropies, as well as the

Tathagata Ghosh, Anish Ghoshal, Huai-Ke Guo, Fazlollah Hajkarim

In this paper, we analyse sound waves arising from a cosmic phase transition where the full velocity profile is taken into account as an explanation for the gravitational wave spectrum observed by multiple pulsar timing array groups. Unlike the broken power law used in the literature, in this scenario the power law after the peak depends on the macroscopic p

Moritz Lange, Pontus Havström, Basudha Srivastava, Isak Bengtsson

To leverage the full potential of quantum error-correcting stabilizer codes it is crucial to have an efficient and accurate decoder. Accurate, maximum likelihood, decoders are computationally very expensive whereas decoders based on more efficient algorithms give sub-optimal performance. In addition, the accuracy will depend on the quality of models and esti

Jože M. Rožanec, Elias Montini, Vincenzo Cutrona, Dimitrios Papamartzivanos

Industrial revolutions have historically disrupted manufacturing by introducing automation into production. Increasing automation reshapes the role of the human worker. Advances in robotics and artificial intelligence open new frontiers of human-machine collaboration. Such collaboration can be realized considering two sub-fields of artificial intelligence: a

Lauren Conger, Franca Hoffmann, Eric Mazumdar, Lillian Ratliff

We propose a novel framework for analyzing the dynamics of distribution shift in real-world systems that captures the feedback loop between learning algorithms and the distributions on which they are deployed. Prior work largely models feedback-induced distribution shift as adversarial or via an overly simplistic distribution-shift structure. In contrast, we

Joshin John Bejoy, Jayesh Dave, G. Ambika

We present a study on the spatio-temporal pattern underlying the climate dynamics in various locations spread over India, including the Himalayan region, coastal region, central and northeastern parts of India. We try to capture the variations in the complexity of their dynamics derived from temperature and relative humidity data and classify them based on t

Yihong Chen, Kelly Marchisio, Roberta Raileanu, David Ifeoluwa Adelani

Pretrained language models (PLMs) are today the primary model for natural language processing. Despite their impressive downstream performance, it can be difficult to apply PLMs to new languages, a barrier to making their capabilities universally accessible. While prior work has shown it possible to address this issue by learning a new embedding layer for th

Barbara Dembin, Dor Elboim, Ron Peled

We study first-passage percolation on $\mathbb Z^d$, $d\ge 2$, with independent weights whose common distribution is compactly supported in $(0,\infty)$ with a uniformly-positive density. Given $\epsilon>0$ and $v\in\mathbb Z^d$, which edges have probability at least $\epsilon$ to lie on the geodesic between the origin and $v$? It is expected that all such e

Dimitra-Dionysia Stergiopoulou

We give characterizations of Gorenstein projective, Gorenstein flat and Gorenstein injective modules over the group algebra for large families of infinite groups and show that every weak Gorenstein projective, weak Gorenstein flat and weak Gorenstein injective module is Gorenstein projective, Gorenstein flat and Gorenstein injective, respectively. These char

Marek Kopciuch, Magdalena Smolis, Adam Miranowicz, Szymon Pustelny

We demonstrate a novel experimental technique for quantum-state tomography of the collective density matrix. It is based on measurements of the polarization of light, traversing the atomic vapor. To assess the technique's robustness against errors, experimental investigations are supported with numerical simulations. This not only allows to determine the fid

Dhaminda B. Abeywickrama, Nguyen Hao Le, Greg Chance, Peter D. Winter

Soft robotics is an emerging technology in which engineers create flexible devices for use in a variety of applications. In order to advance the wide adoption of soft robots, ensuring their trustworthiness is essential; if soft robots are not trusted, they will not be used to their full potential. In order to demonstrate trustworthiness, a specification need

Ini Oguntola, Joseph Campbell, Simon Stepputtis, Katia Sycara

The ability to model the mental states of others is crucial to human social intelligence, and can offer similar benefits to artificial agents with respect to the social dynamics induced in multi-agent settings. We present a method of grounding semantically meaningful, human-interpretable beliefs within policies modeled by deep networks. We then consider the

Nasser Golestani, Maryam Hosseini, Hamed Yahya Oghli

We show that every topological factoring between two zero dimensional dynamical systems can be represented by a sequence of morphisms between the levels of the associated ordered Bratteli diagrams. Conversely, we will prove that given an ordered Bratteli diagram $B$ with a continuous Vershik map on it, every sequence of morphisms between levels of $B$ and $C

John Ryan Westernacher-Schneider, Jonathan Zrake, Andrew MacFadyen, Zoltán Haiman

We show that gas disks around the components of an orbiting binary system (so-called minidisks) may be susceptible to a resonant instability which causes the minidisks to become significantly eccentric. Eccentricity is injected by, and also induces, regular impacts between the minidisks at roughly the orbital period of the binary. Such eccentric minidisks ar

Koushik Brahma

In this paper, we introduce `Pl\"{u}cker weight vector' and establish the definition of a weighted Grassmann orbifold ${\rm Gr}_{\bf b}(k,n)$, corresponding to a Pl\"{u}cker weight vector `${\bf b}$'. We achieve an explicit classification of weighted Grassmann orbifolds up to certain homeomorphism in terms of the Pl\"{u}cker weight vectors. We study the inte

Beatrice Franzolini, Maria De Iorio, Johan Eriksson

Standard clustering techniques assume a common configuration for all features in a dataset. However, when dealing with multi-view or longitudinal data, the clusters' number, frequencies, and shapes may need to vary across features to accurately capture dependence structures and heterogeneity. In this setting, classical model-based clustering fails to account

Chengde Qian, Guanghui Wang, Changliang Zou

Changepoint detection typically relies on a grid-search strategy for optimal data segmentation. When model fitting itself is expensive, repeatedly fitting a model on every candidate segment dominates the computation. Existing approaches mitigate this by pruning the grid, thus reducing the number of segments (and model fits). We propose Reliever, which instea

Sasank Budaraju, Yasir Iqbal, Federico Becca, Didier Poilblanc

The parton approach for quantum spin liquids gives a transparent description of low-energy elementary excitations, e.g., spinons and emergent gauge-field fluctuations. The latter ones are directly coupled to the hopping/pairing of spinons. By using the fermionic representation of the $U(1)$ Dirac state on the kagome lattice and variational Monte Carlo techni

Salman Ul Hassan Dar, Arman Ghanaat, Jannik Kahmann, Isabelle Ayx

Generative latent diffusion models have been established as state-of-the-art in data generation. One promising application is generation of realistic synthetic medical imaging data for open data sharing without compromising patient privacy. Despite the promise, the capacity of such models to memorize sensitive patient training data and synthesize samples sho

Syeda Lammim Ahad, Adam Muzzin, Yannick M. Bahé, Henk Hoekstra

Many $z=1.5$ galaxies with a stellar mass ($M_{\star}$) $\geq 10^{10}\,\mathrm{M}_\odot$ are already quenched in both galaxy clusters ($>50$ per cent) and the field ($>20$ per cent), with clusters having a higher quenched fraction at all stellar masses compared to the field. A puzzling issue is that these massive quenched galaxies have stellar populations of

Shengyi Gao, Zhe Chen, Guo Chen, Wenhai Wang

The combination of audio and vision has long been a topic of interest in the multi-modal community. Recently, a new audio-visual segmentation (AVS) task has been introduced, aiming to locate and segment the sounding objects in a given video. This task demands audio-driven pixel-level scene understanding for the first time, posing significant challenges. In t

Mikhail Gorchtein, Chien-Yeah Seng

We review the status of the Standard Model theory of neutron beta decay. Particular emphasis is put on the recent developments in the electroweak radiative corrections. Given that some existing approaches give slightly different results, we thoroughly review the origin of discrepancies, and provide our recommended value for the radiative correction to the ne

Fernando Lorén, Cyriaque Genet, Luis Martín-Moreno

We present a scattering formalism to analyze the spin-momentum locking in structured holey plasmonic metasurfaces. It is valid for any unit cell for arbitrary position and orientation of the holes. The spin-momentum locking emergence is found to originate from the unit cell configuration. Additionally, we find that there are several breakdown terms spoiling

Adam Bartoš, Tristan Bice, Alessandro Vignati

We develop a simple method of constructing topological spaces from countable posets with finite levels, one which applies to all second countable T_1 compacta. This results in a duality amenable to building such spaces from finite building blocks, essentially an abstract analog of classical constructions defining compacta from progressively finer open covers

Michał Lipka, Michał Parniak

The Fractional Fourier Transform (FRT) corresponds to an arbitrary-angle rotation in the phase space, e.g. the time-frequency (TF) space, and generalizes the fundamentally important Fourier Transform. FRT applications range from classical signal processing (e.g. time-correlated noise optimal filtering) to emerging quantum technologies (e.g. super-resolution

Sylvio R. Bistafa

The major hindrance in the study of earlier scientific literature is the availability of Latin translations into modern languages. This is particular true for the works of Euler who authored about 850 manuscripts and wrote a thousand letters and received back almost two thousand more. The translation of many of these manuscripts, books and letters have been

Dan Cristofaro-Gardiner, Richard Hind

A finite volume symplectic manifold is said to have "packing stability" if the only obstruction to symplectically embedding sufficiently small balls is the volume obstruction. Packing stability has been shown in a variety of cases and it has been conjectured that it always holds. We give counterexamples to this conjecture; in fact, we give examples that cann

Sameera Horawalavithana, Sai Munikoti, Ian Stewart, Henry Kvinge

Instruction finetuning is a popular paradigm to align large language models (LLM) with human intent. Despite its popularity, this idea is less explored in improving LLMs to align existing foundation models with scientific disciplines, concepts and goals. In this work, we present \textit{SciTune} as a tuning framework to improve the ability of LLMs to follow

Sven Günther

Bayesian parameter inference is one of the key elements for model selection in cosmological research. However, the available inference tools require a large number of calls to simulation codes which can lead to high and sometimes even infeasible computational costs. In this work we propose a new way of emulating simulation codes for Bayesian parameter infere

Scott G. Engle, Edward F. Guinan

Age is a fundamental stellar property, yet for many stars it is difficult to reliably determine. For M dwarfs it has been notoriously so. Due to their lower masses, core hydrogen fusion proceeds at a much slower rate in M dwarfs than it does in more massive stars like the Sun. As a consequence, more customary age determination methods (e.g. isochrones and as

Djidenou Montcho, Daiane Zuanetti, Thierry Chekouo, Luis Milan

From a practical perspective, proposals are one of the main bottleneck for any Markov Chain Monte Carlo (MCMC) algorithm. This paper suggests a novel data driven or informed proposal for reversible jump MCMC for Bayesian variable selection in the context of predictive risk assessment for schizophrenia based on imaging genetic data. Given functional Magnetic

Paula Mellado

In the Van der Waal material $\rm NiPS_3$, Ni atoms have spin S=1 and realize a honeycomb lattice. Six sulfur atoms surround each Ni and split their d manifold into three filled and two unfilled bands. Aimed to determine the spin Hamiltonian of $\rm NiPS_3$, we study its exchange mechanisms using a two-band half-filled Hubbard model. Hopping between d orbita

Won-Kwang Park

It has been demonstrated that the MUltiple SIgnal Classification (MUSIC) algorithm is fast, stable, and effective for localizing small anomalies in microwave imaging. For the successful application of MUSIC, exact values of permittivity, conductivity, and permeability of the background must be known. If one of these values is unknown, it will fail to identif

Young-Hoon Kiem, Donggun Lee

Recently, Masuda-Sato and Precup-Sommers independently proved an LLT version of the Shareshian-Wachs conjecture which says that the Frobenius characteristics of the cohomology of the twin manifolds of regular semisimple Hessenberg varieties are unicellular LLT polynomials. The purpose of this paper is to study the geometry of twin manifolds and we prove that

Viola Gattus, Apostolos Pilaftsis

We formulate minimal SuperGeometric Quantum Field Theories (SG-QFTs) that allow for scalar-fermion field transformations in a manifestly reparameterisation covariant manner. First, we discuss the issue of uniqueness in defining the field-space supermetric of the underlying supermanifold, and clarify the fact that different supermetric definitions can lead to

Kirill Cherednichenko, Alexander Kiselev, Igor Velčić, Josip Žubrinić

We construct an order-sharp theory for a double-porosity model in the full linear elasticity setup. Crucially, we uncover time and frequency dispersive properties of highly oscillatory elastic composites.

Xiaoyu Shi, Shurong Chai, Yinhao Li, Jingliang Cheng

According to the 2021 World Health Organization (WHO) Classification scheme for gliomas, glioma segmentation is a very important basis for diagnosis and genotype prediction. In general, 3D multimodal brain MRI is an effective diagnostic tool. In the past decade, there has been an increase in the use of machine learning, particularly deep learning, for medica

Hao Guo, Chen Shen, Shuyue Hu, Junliang Xing

Cooperation is a vital social behavior that plays a crucial role in human prosperity, enabling conflict resolution and averting disastrous outcomes. With the increasing presence of autonomous agents (AAs), human-agent interaction becomes more frequent in modern society. We investigate the impact of cooperative and defective AAs on human cooperation within th

Federico Rollo, Gennaro Raiola, Andrea Zunino, Nikolaos Tsagarakis

Geometric navigation is nowadays a well-established field of robotics and the research focus is shifting towards higher-level scene understanding, such as Semantic Mapping. When a robot needs to interact with its environment, it must be able to comprehend the contextual information of its surroundings. This work focuses on classifying and localising objects

Ana Llorens, Federico Simonetta, Martín Serrano, Álvaro Torrente

In this work, we introduce musif, a Python package that facilitates the automatic extraction of features from symbolic music scores. The package includes the implementation of a large number of features, which have been developed by a team of experts in musicology, music theory, statistics, and computer science. Additionally, the package allows for the easy

Baptiste Debecker, John Martin, François Damanet

Controlling phase transitions in quantum systems via coupling to reservoirs has been mostly studied for idealized memory-less environments under the so-called Markov approximation. Yet, most quantum materials and experiments in the solid state, atomic, molecular and optical physics are coupled to reservoirs with finite memory times. Here, using the spectral

Tanumoy Mandal, Aniket Masaye, Subhadip Mitra, Cyrin Neeraj

A leptophobic $Z^\prime$ that does not couple with the Standard Model leptons can evade the stringent bounds from the dilepton-resonance searches. In our earlier paper [T. Arun et al., Search for the $Z'$ boson decaying to a right-handed neutrino pair in leptophobic $U(1)$ models, Phys. Rev. D, 106 (2022) 095035; arXiv:2204.02949], we presented two gauge ano

Ehsan Azmoodeh, Ozan Hür

Introduced by M\"uller et al. in their seminal paper \cite{muller}, fractional stochastic dominance (SD) offers a nuanced approach to ordering distributions. In this paper, we propose a fundamentally new framework by replacing the fixed parameter $\gamma \in [0,1]$ in fractional SD with a function $\boldsymbol{\gamma}: \mathbb{R} \to [0,1]$. This yields two

Asbjørn Bækgaard Lauritsen, Robert Seiringer

We consider a dilute spin-polarized Fermi gas at positive temperature in dimensions $d\in\{1,2,3\}$. We show that the pressure of the interacting gas is bounded from below by that of the free gas plus, to leading order, an explicit term of order $a^d\rho^{2+2/d}$, where $a$ is the $p$-wave scattering length of the repulsive interaction and $\rho$ is the part

Arkady Kitover, Mehmet Orhon

We obtain some results about the spectrum and the upper semi-Fredholm spectrum of weighted composition operators on uniform algebras, assuming that the corresponding map maps the Shilov boundary onto itself. In particular, it follows from our results that in the case of analytic uniform algebras the spectrum is a connected rotation invariant subset of the co

Oumar Baldé, Guillaume Damblin, Amandine Marrel, Antoine Bouloré

Computer models are widely used in science and engineering to simulate complex systems. However, these models are affected by several sources of uncertainty, which may limit their use for decision making in risk management. We present a Bayesian approach for quantifying parameter uncertainty in a chain of two computer models motivated by multiphysics simulat

R. A. Konoplya, A. Zhidenko

We demonstrate that the late time oscillatory tails of massive gravitons, present in both massive theories of gravity and effectively in extra-dimensional scenarios, could potentially contribute to gravitational waves with very long wavelengths. However, their impact on recent pulsar timing array observations might be relatively small, predominantly consisti

Anton Güthge

We show an equivalence between the two categories in the title, thus establishing a link between Frobenius-linear objects of formal (schematic) and analytic (adic) nature. We will do this for arbitrary p-complete rings, arbitrary affine-flat group schemes and without making use of the Frobenius structure. As a possible application, we take a look at prismati

Michele Caselle, Elia Cellini, Alessandro Nada

Effective String Theory (EST) represents a powerful non-perturbative approach to describe confinement in Yang-Mills theory that models the confining flux tube as a thin vibrating string. EST calculations are usually performed using the zeta-function regularization: however there are situations (for instance the study of the shape of the flux tube or of the h

Cristina Martinez-Lombilla, Raul Infante-Sainz, Felipe Jimenez-Ibarra, Johan H. Knapen

Context: The hierarchical model of galaxy formation suggests that galaxies are continuously growing. However, our position inside the Milky Way prevents us from studying the disk edge. Truncations are low surface brightness features located in the disk outskirts of external galaxies. They indicate where the disk brightness abruptly drops and their location i

Mehboob Rashid, Muzaffar Qadir Lone, Prince A Ganai

Quantum information protocols are often designed in the ideal situation with no decoherence. However, in real setup, these protocols are subject to the decoherence and thus reducing fidelity of the measurement outcome. In this work, we analyze the effect of state dependent bath on the quantum correlations and the fidelity of a single qubit teleportation. We

Lang Liu, Zu-Cheng Chen, Qing-Guo Huang

The recently released data by pulsar timing array (PTA) collaborations present strong evidence for a stochastic signal consistent with a gravitational-wave background. Assuming this signal originates from scalar-induced gravitational waves, we jointly use the PTA data from the NANOGrav 15-yr data set, PPTA DR3, and EPTA DR2 to probe the small-scale non-Gauss

Brian Parkinson, Ádám Wolf, Péter Galambos, Károly Széll

Drug development is becoming more and more complex and resource-intensive. To reduce the costs and the time-to-market, the pharmaceutical industry employs cutting-edge automation solutions. Supportive robotics technologies, such as stationary and mobile manipulators, exist in various laboratory settings. However, they still lack the mobility and dexterity to

Luis A. Anchordoqui, Ignatios Antoniadis, Dieter Lust

We propose a new dark matter contender within the context of the so-called ``dark dimension'', an innovative 5-dimensional construct that has a compact space with characteristic length-scale in the micron range. The new dark matter candidate is the radion, a bulk scalar field whose quintessence-like potential drives an inflationary phase described by a 5-dim

Jeff Murugan, Ruach Pillay Slayen, Hendrik J. R. Van Zyl

We study a version of the 2-body Sachdev-Ye-Kitaev (SYK$_{2}$) model whose complex fermions exhibit twisted boundary conditions on the thermal circle. As we show, this is physically equivalent to coupling the fermions to a 1-dimensional external gauge field $A(t)$. In the latter formulation, the gauge field itself can be thought of as arising from a radial s

Yanyun Liu, Xiumeng Hua, Shouping Zhu, Congrui Wang

This study aims to develop a new computational pathology approach that automates the identification and quantification of myocardial inflammatory infiltration in digital HE-stained images to provide a quantitative histological diagnosis of myocarditis.898 HE-stained whole slide images (WSIs) of myocardium from 154 heart transplant patients diagnosed with myo

Shitao Tang, Fuyang Zhang, Jiacheng Chen, Peng Wang

This paper introduces MVDiffusion, a simple yet effective method for generating consistent multi-view images from text prompts given pixel-to-pixel correspondences (e.g., perspective crops from a panorama or multi-view images given depth maps and poses). Unlike prior methods that rely on iterative image warping and inpainting, MVDiffusion simultaneously gene

Arpita Ghosh, Neil Hindman

There are several notions of size for semigroups that have natural analogues for partial semigroups. Among these are thick, syndetic, central, piecewise syndetic, IP, J, and the more recently introduced notion of combinatorially rich, abbreviated CR. We investigate the notion of CR set for adequate partial semigroups, its relation to other notions, especiall

ATLAS Collaboration

A search for pair production of squarks or gluinos decaying via sleptons or weak bosons is reported. The search targets a final state with exactly two leptons with same-sign electric charge or at least three leptons without any charge requirement. The analysed data set corresponds to an integrated luminosity of 139 fb$^{-1}$ of proton$-$proton collisions col

Rita Pucci, Niki Martinel

Underwater images are fundamental for studying and understanding the status of marine life. We focus on reducing the memory space required for image storage while the memory space consumption in the collecting phase limits the time lasting of this phase leading to the need for more image collection campaigns. We present a novel machine-learning model that re

Irham Taufik Andika, Sherry H. Suyu, Raoul Cañameras, Alejandra Melo

Quasars experiencing strong lensing offer unique viewpoints on subjects related to the cosmic expansion rate, the dark matter profile within the foreground deflectors, and the quasar host galaxies. Unfortunately, identifying them in astronomical images is challenging since they are overwhelmed by the abundance of non-lenses. To address this, we have develope

Jason J. Bramburger, Steven Dahdah, James Richard Forbes

The control Lyapunov function (CLF) approach to nonlinear control design is well established. Moreover, when the plant is control affine and polynomial, sum-of-squares (SOS) optimization can be used to find a polynomial controller as a solution to a semidefinite program. This letter considers the use of data-driven methods to design a polynomial controller b

Shao-Ping Li, Ke-Pan Xie

A cosmic first-order phase transition (FOPT) occurring at MeV-scale provides an attractive explanation for the nano-Hertz gravitational wave (GW) background indicated by the recent pulsar timing array data from the NANOGrav, CPTA, EPTA and PPTA collaborations. We propose this explanation can be further tested at the colliders if the hidden sector couples to

Hao Wu, Xiequan Fan, Zhiqiang Gao, Yinna Ye

Let $ (Z_{n})_{n\geq 0} $ be a supercritical branching process in an independent and identically distributed random environment. We establish an optimal convergence rate in the Wasserstein-$1$ distance for the process $ (Z_{n})_{n\geq 0} $, which completes a result of Grama et al. [Stochastic Process. Appl., 127(4), 1255-1281, 2017]. Moreover, an exponential

R. Laker, T. S. Horbury, H. O'Brien, E. J. Fauchon-Jones

Coronal mass ejections (CMEs) can create significant disruption to human activities and systems on Earth, much of which can be mitigated with prior warning of the upstream solar wind conditions. However, it is currently extremely challenging to accurately predict the arrival time and internal structure of a CME from coronagraph images alone. In this study, w

Amirhossein Azarbahram, Onel L. A. Lopez, Richard D. Souza, Rui Zhang

Radio frequency (RF) wireless power transfer (WPT) is a promising technology for charging the Internet of Things. Practical RF-WPT systems usually require energy beamforming (EB), which can compensate for the severe propagation loss by directing beams toward the devices. The EB flexibility depends on the transmitter architecture, existing a trade-off between

Amirhossein Azarbahram, Onel L. A. López, Matti Latva-Aho

Radio frequency (RF) wireless power transfer (WPT) is a promising technology for future wireless systems. However, the low power transfer efficiency (PTE) is a critical challenge for practical implementations. One of the main inefficiency sources is the power consumption and loss introduced by key components such as high-power amplifier (HPA) and rectenna, t

Sara Ayhan

In this paper I will develop a lambda-term calculus, lambda-2Int, for a bi-intuitionistic logic and discuss its implications for the notions of sense and denotation of derivations in a bilateralist setting. Thus, I will use the Curry-Howard correspondence, which has been well-established between the simply typed lambda-calculus and natural deduction systems

Gajendra Babu, Hemant K. Mishra

Williamson's theorem states that for any $2n \times 2n$ real positive definite matrix $A$, there exists a $2n \times 2n$ real symplectic matrix $S$ such that $S^TAS=D \oplus D$, where $D$ is an $n\times n$ diagonal matrix with positive diagonal entries which are known as the symplectic eigenvalues of $A$. Let $H$ be any $2n \times 2n$ real symmetric matrix s

Soumyaditya Das, Soumyajyoti Biswas, Anirban Chakraborti, Bikas K. Chakrabarti

The order parameter for a continuous transition shows diverging fluctuation near the critical point. Here we show, through numerical simulations and scaling arguments, that the inequality (or variability) between the values of an order parameter, measured near a critical point, is independent of the system size. Quantification of such variability through Gin

Laura Monk, Rares Stan

In this article, we study the Dirac spectrum of typical hyperbolic surfaces of finite area, equipped with a nontrivial spin structure (so that the Dirac spectrum is discrete). For random Weil-Petersson surfaces of large genus $g$ with $o(\sqrt{g})$ cusps, we prove convergence of the spectral density to the spectral density of the hyperbolic plane, with quant

Fnu Suya, Xiao Zhang, Yuan Tian, David Evans

We study indiscriminate poisoning for linear learners where an adversary injects a few crafted examples into the training data with the goal of forcing the induced model to incur higher test error. Inspired by the observation that linear learners on some datasets are able to resist the best known attacks even without any defenses, we further investigate whet

Yang Xiao, Jin Min Yang, Yang Zhang

Inspired by the recent evidences of nano-Hertz stochastic gravitational waves observed by the pulsar timing array collaborations, we explore their implied supercooled electroweak phase transition in the singlet extension of the Standard Model. Our findings reveal that by adjusting the model parameter at per milli level, the corresponding percolation temperat

Konstantin Pakulev, Alexander Vakhitov, Gonzalo Ferrer

Learning a feature point detector presents a challenge both due to the ambiguity of the definition of a keypoint and, correspondingly, the need for specially prepared ground truth labels for such points. In our work, we address both of these issues by utilizing a combination of a hand-crafted Shi-Tomasi detector, a specially designed metric that assesses the

Wen-Bin Liu, Jiang Long

We reduce the gravitational theory in an asymptotically flat spacetime to future null infinity. We compute the Poincar\'e flux operators at future null infinity and construct the supertranslation and superrotation generators. The generators are shown to form a closed symmetry algebra by including a generalized gravitational duality operator. We could regard

Seokhyun Moon, Sang-Yeon Hwang, Jaechang Lim, Woo Youn Kim

Prediction of protein-ligand interactions (PLI) plays a crucial role in drug discovery as it guides the identification and optimization of molecules that effectively bind to target proteins. Despite remarkable advances in deep learning-based PLI prediction, the development of a versatile model capable of accurately scoring binding affinity and conducting eff

Dietmar Berwanger, Laurent Doyen, Thomas Soullard

We lay out a model of games with imperfect information that features explicit communication actions, by which the entire observation history of a player is revealed to another player. Such full-information protocols are common in asynchronous distributed systems; here, we consider a synchronous setting with a single active player who may communicate with mul

Siming Deng, Junning Liu, Bibekananda Datta, Aishwarya Pantula

It is challenging to perform system identification on soft robots due to their underactuated, high-dimensional dynamics. In this work, we present a data-driven modeling framework, based on geometric mechanics (also known as gauge theory) that can be applied to systems with low-bandwidth control of the system's internal configuration. This method constructs a