April 2023 arXiv papers — page 33

Gabriele Spada, Sebastiano Pilati, Stefano Giorgini

We study the thermodynamic behavior of attractive binary Bose mixtures using exact path-integral Monte-Carlo methods. Our focus is on the regime of interspecies interactions where the ground state is in a self-bound liquid phase, stabilized by beyond mean-field effects. We calculate the isothermal curves in the pressure vs density plane for different values

Muhammad A. Latif, Daniel J. Whalen, Mar Mezcua

Nearly 300 quasars have now been found at $z >$ 6, including nine at $z >$ 7. They are thought to form from the collapse of supermassive primordial stars to 10$^4$ - 10$^5$ M$_{\odot}$ black holes at $z \sim$ 20 - 25, which then rapidly grow in the low-shear environments of rare, massive halos fed by strong accretion flows. Sensitive new radio telescopes suc

Chonghyuk Song, Gengshan Yang, Kangle Deng, Jun-Yan Zhu

We explore the task of embodied view synthesis from monocular videos of deformable scenes. Given a minute-long RGBD video of people interacting with their pets, we render the scene from novel camera trajectories derived from the in-scene motion of actors: (1) egocentric cameras that simulate the point of view of a target actor and (2) 3rd-person cameras that

Noshad Khosravi Largani, Tobias Fischer, Niels Uwe F. Bastian

The occurrence of a first-order hadron-quark matter phase transition at high baryon densities is investigated in astrophysical simulations of core-collapse supernovae, to decipher yet incompletely understood properties of the dense matter equation of state (EOS) using neutrinos from such cosmic events. It is found that the emission of a nonstandard second ne

Lue Fan, Yuxue Yang, Yiming Mao, Feng Wang

This paper aims for high-performance offline LiDAR-based 3D object detection. We first observe that experienced human annotators annotate objects from a track-centric perspective. They first label the objects with clear shapes in a track, and then leverage the temporal coherence to infer the annotations of obscure objects. Drawing inspiration from this, we p

Kenneth Borup, Cheng Perng Phoo, Bharath Hariharan

We address the challenge of getting efficient yet accurate recognition systems with limited labels. While recognition models improve with model size and amount of data, many specialized applications of computer vision have severe resource constraints both during training and inference. Transfer learning is an effective solution for training with few labels,

Oliver Serang

The first worst-case linear-time algorithm for selection was discovered in 1973; however, linear-time binary heap construction was first published in 1964. Here we describe another worst-case linear selection algorithm,which is simply implemented and uses binary heap construction as its principal engine. The algorithm is implemented in place, and shown to pe

Abhijit Biswas, Rui Xu, Gustavo A. Alvarez, Jin Zhang

Understanding the emergent electronic structure in twisted atomically thin layers has led to the exciting field of twistronics. However, practical applications of such systems are challenging since the specific angular correlations between the layers must be precisely controlled and the layers have to be single crystalline with uniform atomic ordering. Here,

Pannagadatta Shivaswamy

In many recommender systems and search problems, presenting a well balanced set of results can be an important goal in addition to serving highly relevant content. For example, in a movie recommendation system, it may be helpful to achieve a certain balance of different genres, likewise, it may be important to balance between highly popular versus highly per

Johannes Schimunek, Philipp Seidl, Lukas Friedrich, Daniel Kuhn

A central task in computational drug discovery is to construct models from known active molecules to find further promising molecules for subsequent screening. However, typically only very few active molecules are known. Therefore, few-shot learning methods have the potential to improve the effectiveness of this critical phase of the drug discovery process.

Yingyan Li, Lue Fan, Yang Liu, Zehao Huang

Currently prevalent multimodal 3D detection methods are built upon LiDAR-based detectors that usually use dense Bird's-Eye-View (BEV) feature maps. However, the cost of such BEV feature maps is quadratic to the detection range, making it not suitable for long-range detection. Fully sparse architecture is gaining attention as they are highly efficient in long

Jiazhong Cen, Jiemin Fang, Zanwei Zhou, Chen Yang

The Segment Anything Model (SAM) emerges as a powerful vision foundation model to generate high-quality 2D segmentation results. This paper aims to generalize SAM to segment 3D objects. Rather than replicating the data acquisition and annotation procedure which is costly in 3D, we design an efficient solution, leveraging the radiance field as a cheap and off

Nikita Belokonev, Artem Melnikov, Maninadh Podapaka, Karan Pinto

Chemical component design is a computationally challenging procedure that often entails iterative numerical modeling and authentic experimental testing. We demonstrate a novel optimization method, Tensor train Optimization (TetraOpt), for the shape optimization of components focusing on a Y-shaped mixer of fluids. Due to its high parallelization and more ext

Jun Ma, Yuting He, Feifei Li, Lin Han

Medical image segmentation is a critical component in clinical practice, facilitating accurate diagnosis, treatment planning, and disease monitoring. However, existing methods, often tailored to specific modalities or disease types, lack generalizability across the diverse spectrum of medical image segmentation tasks. Here we present MedSAM, a foundation mod

Farhad MortezaPour Shiri, Thinagaran Perumal, Norwati Mustapha, Raihani Mohamed

Human activity recognition (HAR) is a rapidly growing field that utilizes smart devices, sensors, and algorithms to automatically classify and identify the actions of individuals within a given environment. These systems have a wide range of applications, including assisting with caring tasks, increasing security, and improving energy efficiency. However, th

Mason DiCicco, Henry Poskanzer, Daniel Reichman

We analyze a game-theoretic abstraction of epidemic containment played on an undirected graph $G$: each player is associated with a node in $G$ and can either acquire protection from a contagious process or risk infection. After decisions are made, an infection starts at a random node $v$ and propagates through all unprotected nodes reachable from $v$. It is

Ramkrishna Mishan, Matthew Egan, Mohammed Ben-Idris, Hanif Livani

Modern power grids combine conventional generators with distributed energy resource (DER) generators in response to concerns over climate change and long-term energy security. Due to the intermittent nature of DERs, different types of energy storage devices (ESDs) must be installed to minimize unit commitment problems and accommodate spinning reserve power.

Takehiko Ohkawa, Kun He, Fadime Sener, Tomas Hodan

We present AssemblyHands, a large-scale benchmark dataset with accurate 3D hand pose annotations, to facilitate the study of egocentric activities with challenging hand-object interactions. The dataset includes synchronized egocentric and exocentric images sampled from the recent Assembly101 dataset, in which participants assemble and disassemble take-apart

Chong Mou, Youmin Xu, Jiechong Song, Chen Zhao

Video steganography is the art of unobtrusively concealing secret data in a cover video and then recovering the secret data through a decoding protocol at the receiver end. Although several attempts have been made, most of them are limited to low-capacity and fixed steganography. To rectify these weaknesses, we propose a Large-capacity and Flexible Video Ste

Maximilian Andres

So far, the theory of equilibrium selection in the infinitely repeated prisoner's dilemma is insensitive to communication possibilities. To address this issue, we incorporate the assumption that communication reduces -- but does not entirely eliminate -- an agent's uncertainty that the other agent follows a cooperative strategy into the theory. Because of th

Eileen Otte, Alexander D. White, Nicholas A. Güsken, Jelena Vučković

Spatial modes of light have become highly attractive to increase the dimension and, thereby, security and information capacity in quantum key distribution (QKD). So far, only transverse electric field components have been considered, while longitudinal polarization components have remained neglected. Here, we present an approach to include all three spatial

Joseph Malbon

We prove that all smooth Fano threefolds with Picard rank 2 and degree 28 are K-polystable, except for some explicit cases which we describe. We also give a classification of the normal bundle of a rational normal quartic curve in a smooth quadric threefold.

Yuedong Chen, Haofei Xu, Qianyi Wu, Chuanxia Zheng

We present a new generalizable NeRF method that is able to directly generalize to new unseen scenarios and perform novel view synthesis with as few as two source views. The key to our approach lies in the explicitly modeled correspondence matching information, so as to provide the geometry prior to the prediction of NeRF color and density for volume renderin

Anitha G, P Vanchinathan

For a finite field of odd number of elements we construct families of permutation binomials and permutation trinomials with one fixed-point (namely zero) and remaining elements being permuted as disjoint cycles of same length. Binomials and trinomials providing permutations with cycles of many lengths with certain frequency are also constructed.

Benoît Vermersch, Aniket Rath, Bharathan Sundar, Cyril Branciard

We present a technique for enhancing the estimation of quantum state properties by incorporating approximate prior knowledge about the quantum state of interest. This method involves performing randomized measurements on a quantum processor and comparing the results with those obtained from a classical computer that stores an approximation of the quantum sta

B. Shukirgaliyev, P. Berczik, A. Otebay, M. Kalambay

Binary black holes (BHs) can be formed dynamically in the centers of star clusters. The high natal kicks for stellar-mass BHs used in previous works made it hard to retain BHs in star clusters. Recent studies of massive star evolution and supernovae (SN) propose kick velocities that are lower due to the fallback of the SN ejecta. We study the impact of these

Burak Çakmak, Eleni Gkiouzepi, Manfred Opper, Giuseppe Caire

We consider unsourced random access (uRA) in a cell-free (CF) user-centric wireless network, where a large number of potential users compete for a random access slot, while only a finite subset is active. The random access users transmit codewords of length $L$ symbols from a shared codebook, which are received by $B$ geographically distributed radio units (

Kuo-Hao Zeng, Luca Weihs, Roozbeh Mottaghi, Ali Farhadi

A common assumption when training embodied agents is that the impact of taking an action is stable; for instance, executing the "move ahead" action will always move the agent forward by a fixed distance, perhaps with some small amount of actuator-induced noise. This assumption is limiting; an agent may encounter settings that dramatically alter the impact of

Zhanibek Rysbek, Ki Hwan Oh, Afagh Mehri Shervedani, Timotej Klemencic

Physical Human-Human Interaction (pHHI) involves the use of multiple sensory modalities. Studies of communication through spoken utterances and gestures are well established, but communication through force signals is not well understood. In this paper, we focus on investigating the mechanisms employed by humans during the negotiation through force signals,

Adrianne Zhong, Benjamin Kuznets-Speck, Michael R. DeWeese

The free-energy difference $\Delta F$ between two high-dimensional systems is notoriously difficult to compute, but very important for many applications, such as drug discovery. We demonstrate that an unconventional definition of work introduced by Vaikuntanathan and Jarzynski (2008) satisfies a microscopic fluctuation theorem that relates path ensembles tha

Erroxe Etxabarri Alberdi

We complete the classification of local stability thresholds for smooth del Pezzo surfaces of degree~2. In particular, we show that this number is irrational if and only if a unique (-1)-curve passes through the point where we are computing the local invariant.

Prantar Ghosh, Manuel Stoeckl

For edge coloring, the online and the W-streaming models seem somewhat orthogonal: the former needs edges to be assigned colors immediately after insertion, typically without any space restrictions, while the latter limits memory to sublinear in the input size but allows an edge's color to be announced any time after its insertion. We aim for the best of bot

Bhavesh Neekhra, Kshitij Kapoor, Debayan Gupta

Population censuses are vital to public policy decision-making. They provide insight into human resources, demography, culture, and economic structure at local, regional, and national levels. However, such surveys are very expensive (especially for low and middle-income countries with high populations, such as India), time-consuming, and may also raise priva

Pavel Belov, Rostislav Arkhipov

The induced polarization oscillations in a one-dimensional rectangular quantum well are modeled by a numerical solution of the time-dependent Schroedinger equation. The finite-difference discretization over time is realized in the framework of the Crank-Nicolson algorithm, whereas over the spatial coordinate it is combined with the exterior complex-scaling t

Jingwen Chen

In this article, we generalize our previous results joint with Pedro Gaspar to higher dimensions, prove the existence of (infinitely many) eternal weak mean curvature flows in $S^{n+1}$ (for all $n \geq 2$) connecting a Clifford hypersurface $S^1(\sqrt{\frac{1}{n}}) \times S^{n-1} (\sqrt{\frac{n-1}{n}})$ to the equatorial spheres $S^n$.

Jia-Wei Liu, Yan-Pei Cao, Tianyuan Yang, Eric Zhongcong Xu

We introduce HOSNeRF, a novel 360{\deg} free-viewpoint rendering method that reconstructs neural radiance fields for dynamic human-object-scene from a single monocular in-the-wild video. Our method enables pausing the video at any frame and rendering all scene details (dynamic humans, objects, and backgrounds) from arbitrary viewpoints. The first challenge i

Ram Rachum, Yonatan Nakar, Reuth Mirsky

Recent research in multi-agent reinforcement learning (MARL) has shown success in learning social behavior and cooperation. Social dilemmas between agents in mixed-sum settings have been studied extensively, but there is little research into social dilemmas in fullycooperative settings, where agents have no prospect of gaining reward at another agent's expen

Veerpal, B. R. K. Nanda, Ajay

Here we present a theoretical analysis (applicable to all twist angles of TBG) of band dispersion and density of states in TBG relating evolution of flat band and Van-Hove singularities with evolution of interlayer coupling in TBG. A simple tight binding Hamiltonian with environment dependent interlayer hopping and incorporated with internal configuration of

Xuan-Lin Su, Alioscia Hamma, Antonino Marciano

The black hole information paradox remains a profound challenge in theoretical physics. Among the proposed resolutions, the soft-hair approach stands out for its independence from any specific quantum gravity model. In this paper, we investigate how the inclusion of soft degrees of freedom in the unitary evolution of quantum electrodynamics, within a spaceti

Xuan-Lin Su, Alioscia Hamma, Antonino Marciano

Observable scattering processes entail emission-absorption of soft photons. As these degrees of freedom go undetected, some information is lost. Whether some of this information can be recovered in the observation of the hard photons, depends of the actual pattern of the scrambling of information. We compute the information scrambling of photon scattering by

Ata Atay, Sylvain Funck, Ana Mauleon, Vincent Vannetelbosch

We adopt the notion of the farsighted stable set to determine which matchings are stable when agents are farsighted in matching markets with couples. We show that a singleton matching is a farsighted stable set if and only if the matching is stable. Thus, matchings that are stable with myopic agents remain stable when agents become farsighted. Examples of fa

Alix Deleporte, Gaultier Lambert

We consider the determinantal point processes associated with the spectral projectors of a Schr\"odinger operator on $\mathbb{R}$, with a smooth confining potential. In the semiclassical limit, where the number of particles tends to infinity, we obtain a Szeg\H{o}-type central limit theorem (CLT) for the fluctuations of smooth linear statistics. More precise

Vojtěch Patkóš, Vladimir A. Yerokhin, Krzysztof Pachucki

We present a calculation of the hyperfine splitting of the $2^3S$ state in the $^3$He atom with inclusion of all QED effects up to $\alpha^3E_F$, where $E_F$ is the Fermi splitting. Using the experimental value of the $1S$ hyperfine splitting in $^3$He$^+$, we obtain the theoretical prediction for $^3$He of $\nu_\mathrm{hfs}= -6\,739\,701\,181(41)$ Hz, which

Jianfeng Zhang

For time inconsistent optimal control problems, a quite popular approach is the equilibrium approach, taken by the sophisticated agents. In this short note we construct a deterministic continuous time example where the unique equilibrium is dominated by another control. Therefore, in this situation it may not be wise to take the equilibrium strategy.

Young-Suk Lee, Ramón Fernandez Astudillo, Radu Florian, Tahira Naseem

Instruction fine-tuned language models on a collection of instruction annotated datasets (FLAN) have shown highly effective to improve model performance and generalization to unseen tasks. However, a majority of standard parsing tasks including abstract meaning representation (AMR), universal dependency (UD), semantic role labeling (SRL) has been excluded fr

The NA62 Collaboration

A sample of $1.3 \times 10^5$ $K^+ \to \pi^0 e^+ \nu \gamma$ candidates with less than 1% background was collected by the NA62 experiment at the CERN SPS in 2017-2018. Branching fraction measurements are obtained at percent relative precision in three restricted kinematic regions, improving on existing results by a factor larger than two. An asymmetry, possi

Somnath Ghara, Maximilian Winkler, Korbinian Geirhos, Lilian Prodan

Electrical manipulation of antiferromagnetic states, a cornerstone of antiferromagnetic spintronics, is a great challenge, requiring novel material platforms. Here we report the full control over antiferromagnetic states by voltage pulses in the insulating Co$_3$O$_4$ spinel. We show that the strong linear magnetoelectric effect emerging in its antiferromagn

Tim van Dam, Maliheh Izadi, Arie van Deursen

Transformer-based pre-trained models have recently achieved great results in solving many software engineering tasks including automatic code completion which is a staple in a developer's toolkit. While many have striven to improve the code-understanding abilities of such models, the opposite -- making the code easier to understand -- has not been properly i

Francisco Lopez-Navarrete, Joaquin Sanchez-Soriano, Oscar M. Bonastre

The consumption of online videos on the Internet grows every year, making it a market that increasingly generates a greater volume of income. This paper deals with a problem of great interest in this context: the allocation of the generated revenues in a video website between the website and the video creators. For this, we consider a dynamic model of the re

Raf Cluckers, Mathias Stout

Since the work by Denef, $p$-adic cell decomposition provides a well-established method to study $p$-adic and motivic integrals. In this paper, we present a variant of this method that keeps track of existential quantifiers. This enables us to deduce descent properties for $p$-adic integrals. In particular, we show that integrability for `existential' functi

Sk Saniur Rahaman, Manoranjan Kumar, Shaon Sahoo

We study a frustrated two-leg spin-1/2 ladder with alternate Ising and isotropic Heisenberg rung exchange interactions, whereas, interactions along legs and diagonals are Ising type. The ground-state (GS) of this model has four exotic phases: (i) the stripe rung ferromagnet (SRFM), (ii) the anisotropic anti-ferromagnet (AAFM), (iii) the Dimer, and (iv) the s

Gabriel Nicolosi, Christopher Griffin

The Bass diffusion equation is a well-known and established modeling approach for describing new product adoption in a competitive market. This model also describes diffusion phenomena in various contexts: infectious disease spread modeling and estimation, rumor spread on social networks, prediction of renewable energy technology markets, among others. Most

Farzad Pourkamali, Nicolas Macris

We propose a rectangular rotational invariant estimator to recover a real matrix from noisy matrix observations coming from an arbitrary additive rotational invariant perturbation, in the large dimension limit. Using the Bayes-optimality of this estimator, we derive the asymptotic minimum mean squared error (MMSE). For the particular case of Gaussian noise,

James Dallas, Michael Thompson, Jonathan Y. M. Goh, Avinash Balachandran

The ability to reliably maximize tire force usage would improve the safety of autonomous vehicles, especially in challenging edge cases. However, vehicle control near the limits of handling has many challenges, including robustly contending with tire force saturation, balancing model fidelity and computational efficiency, and coordinating inputs with the low

Alex Weygandt

This work concerns a generalization of property (RD) from discrete groups to twisted \'etale groupoids equipped with a length function. We show that, under the assumption that the \'etale groupoid is principal, twisted property (RD) is equivalent to polynomial growth. This generalizes a result of Chen and Wei concerning rapid decay for metric spaces with bou

Aidan P. Reddy, Faisal F. Alsallom, Yang Zhang, Trithep Devakul

We demonstrate via exact diagonalization that AA-stacked TMD homobilayers host fractional quantum anomalous Hall (FQAH) states with fractionally quantized Hall conductance at fractional fillings $n=\frac{1}{3},\, \frac{2}{3}$ and zero magnetic field. While both states are most robust at angles near $\theta\approx 2^{\circ}$, the $n=\frac{1}{3}$ state gives w

Barnabás Janzer, Oliver Janzer

Given a graph $H$, let $g(n,H)$ denote the smallest $k$ for which the following holds. We can assign a $k$-colouring $f_v$ of the edge set of $K_n$ to each vertex $v$ in $K_n$ with the property that for any copy $T$ of $H$ in $K_n$, there is some $u\in V(T)$ such that every edge in $T$ has a different colour in $f_u$. The study of this function was initiated

Jonathan Schwartz, Zichao Wendy Di, Yi Jiang, Jason Manassa

Measuring the three-dimensional (3D) distribution of chemistry in nanoscale matter is a longstanding challenge for metrological science. The inelastic scattering events required for 3D chemical imaging are too rare, requiring high beam exposure that destroys the specimen before an experiment completes. Even larger doses are required to achieve high resolutio

Pablo Alonso-Jiménez, Xavier Favory, Hadrien Foroughmand, Grigoris Bourdalas

In this work, we investigate an approach that relies on contrastive learning and music metadata as a weak source of supervision to train music representation models. Recent studies show that contrastive learning can be used with editorial metadata (e.g., artist or album name) to learn audio representations that are useful for different classification tasks.

Peng Zou, Ali Maatouk, Jin Zhang, Suresh Subramaniam

In this paper, we introduce a new metric, named Penalty upon Decision (PuD), for measuring the impact of communication delays and state changes at the source on a remote decision maker. Specifically, the metric quantifies the performance degradation at the decision maker's side due to delayed, erroneous, and (possibly) missed decisions. We clarify the ration

Connor Kapahi, Andrew E. Silva, David G. Cory, Mukhit Kulmaganbetov

The ability to perceive polarization-related entoptic phenomena arises from the dichroism of macular pigments held in Henle's fiber layer of the retina and can be inhibited by retinal diseases such as age-related macular degeneration, which alter the structure of the macula. Structured light tools enable the direct probing of macular pigment density through

Renan B. Magalhães, Luiz C. S. Leite, Luís C. B. Crispino

We study the scattering of light-like geodesics and massless scalar waves by a static Konoplya-Zhidenko black hole, considering the case that the parametrized black hole solution contains a single deformation parameter. By performing a geodesic analysis, we compute the classical differential scattering cross section and probe the influence of the deformation

Romain Demur, Luc Leviandier, Elsa Turpin, Jerome Bourderionnet

Coherent beam combination is one promising way to overcome the power limit of one single laser. In this paper, we use a Multi-Plane Light Converter to combine 12 fibers at 1.03 micron with a phase locking setup. The overall loss measurement gives a combination efficiency in the fundamental Hermite-Gaussian mode as high as 70%. This setup can generate the fun

Nguyen N. Hung, Alexander Moretó, Lucia Morotti

We study the zero-sharing behavior among irreducible characters of a finite group. For symmetric groups $S_n$, it is proved that, with one exception, any two irreducible characters have at least one common zero. To further explore this phenomenon, we introduce the common-zero graph of a finite group $G$, with non-linear irreducible characters of $G$ as verti

A. Parra-Rodriguez, I. L. Egusquiza

In lumped-element electrical circuit theory, the problem of solving Maxwell's equations in the presence of media is reduced to two sets of equations, the constitutive equations encapsulating local geometry and dynamics of a confined energy density, and the Kirchhoff equations enforcing conservation of charge and energy in a larger, topological, scale. We dev

Ángel López Oriona, José Antonio Vilar Fernández

The 21st century has witnessed a growing interest in the analysis of time series data. Whereas most of the literature on the topic deals with real-valued time series, ordinal time series have typically received much less attention. However, the development of specific analytical tools for the latter objects has substantially increased in recent years. The R

R. J. Bueno Rogerio, R. T. Cavalcanti, J. M. Hoff da Silva, C. H. Coronado Villalobos

The so-called Takahashi's \emph{Inversion Theorem}, the reconstruction of a given spinor based on its bilinear covariants, are re-examined, considering alternative dual structures. In contrast to the classical results, where the Dirac dual structure plays the central role, new duals are built using the discrete symmetries $\mathcal{C}, \mathcal{P}, \mathcal{

Marc Kegel, Felix Schmäschke

We describe an algorithm that takes as input an open book decomposition of a closed oriented 4-manifold and outputs an explicit trisection diagram of that 4-manifold. Moreover, a slight variation of this algorithm also works for open books on manifolds with non-empty boundary and for 3-manifold bundles over the circle. We apply this algorithm to several simp

Ángel López Oriona, Christian Weiss, José Antonio Vilar

Time series clustering is a central machine learning task with applications in many fields. While the majority of the methods focus on real-valued time series, very few works consider series with discrete response. In this paper, the problem of clustering ordinal time series is addressed. To this aim, two novel distances between ordinal time series are intro

Ke Sun, Chao Fang, Mingyu Kang, Zhendian Zhang

Electron transfer within and between molecules is crucial in chemistry, biochemistry, and energy science. This study describes a quantum simulation method that explores the influence of light polarization on the electron transfer between two molecules. By implementing precise and coherent control among the quantum states of trapped atomic ions, we can induce

I. A. Ivanov-Pogodaev

The paper is devoted to the study of combinatorial determinacy properties of a family of substitution complexes consisting of quadrilaterals glued side-to-side with each other. These properties are useful in constructing algebraic structures with a finite number of defining relations. In particular, this method was used when constructing a finitely presented

Matteo Bruno, Dario Mazzilli, Aurelio Patelli, Tiziano Squartini

We revise the procedure proposed by Balassa to infer comparative advantage, which is a standard tool, in Economics, to analyze specialization (of countries, regions, etc.). Balassa's approach compares the export of a product for each country with what would be expected from a benchmark based on the total volumes of countries and products flows. Based on resu

Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng

Training large language models (LLMs) with open-domain instruction following data brings colossal success. However, manually creating such instruction data is very time-consuming and labor-intensive. Moreover, humans may struggle to produce high-complexity instructions. In this paper, we show an avenue for creating large amounts of instruction data with vary

Soham Chakraborty

We provide a complete classification for regular subalgebras $B \subset M$ of injective factors satisfying a natural relative commutant condition. We show that such subalgebras are classified by their associated amenable discrete measured groupoid $\mathcal{G}= \mathcal{G}_{B \subset M}$ and the action $\text{mod}(\alpha)$ of $\mathcal{G}$ on the flow of wei

Yu-Hao Deng, Yi-Chao Gu, Hua-Liang Liu, Si-Qiu Gong

We report new Gaussian boson sampling experiments with pseudo-photon-number-resolving detection, which register up to 255 photon-click events. We consider partial photon distinguishability and develop a more complete model for the characterization of the noisy Gaussian boson sampling. In the quantum computational advantage regime, we use Bayesian tests and c

Zhifeng Gao, Xiaohong Ji, Guojiang Zhao, Hongshuai Wang

Recently deep learning based quantitative structure-activity relationship (QSAR) models has shown surpassing performance than traditional methods for property prediction tasks in drug discovery. However, most DL based QSAR models are restricted to limited labeled data to achieve better performance, and also are sensitive to model scale and hyper-parameters.

Mercè Claverol, Andrea de las Heras-Parrilla, David Flores-Peñaloza, Clemens Huemer

Three polynomials are defined for given sets $S$ of $n$ points in general position in the plane: The Voronoi polynomial with coefficients the numbers of vertices of the order-$k$ Voronoi diagrams of $S$, the circle polynomial with coefficients the numbers of circles through three points of $S$ enclosing $k$ points of $S$, and the $E_{\leq k}$ polynomial with

Robert B. Olsen, Maria L. Vasquez-Rossi

Sampling methods such as Stratified Random Sampling can be used to select representative samples of schools for randomized controlled trials of educational interventions. However, these methods may still yield external validity bias when participation by schools is voluntary and participation decisions are associated with unobserved variables. This paper off

IceCube Collaboration, R. Abbasi, M. Ackermann, J. Adams

We describe a new data sample of IceCube DeepCore and report on the latest measurement of atmospheric neutrino oscillations obtained with data recorded between 2011-2019. The sample includes significant improvements in data calibration, detector simulation, and data processing, and the analysis benefits from a detailed treatment of systematic uncertainties,

Chen Zhao, Wei-Ling Cai, Zheng Yuan, Cheng-Wei Hu

Recently, unsupervised image-to-image translation methods based on contrastive learning have achieved state-of-the-art results in many tasks. However, in the previous works, the negatives are sampled from the input image itself, which inspires us to design a data augmentation method to improve the quality of the selected negatives. Moreover, the previous met

Anastasis Kratsios, Chong Liu, Matti Lassas, Maarten V. de Hoop

Motivated by the developing mathematics of deep learning, we build universal functions approximators of continuous maps between arbitrary Polish metric spaces $\mathcal{X}$ and $\mathcal{Y}$ using elementary functions between Euclidean spaces as building blocks. Earlier results assume that the target space $\mathcal{Y}$ is a topological vector space. We over

Haoyuan Zhong, Hongyun Zhang, Haoxiong Zhang, Ting Bao

Van der Waals superlattices are important for tailoring the electronic structures and properties of layered materials. Here we report the superconducting properties and electronic structure of a natural van der Waals superlattice (PbSe)$_{1.14}$NbSe$_2$. Anisotropic superconductivity with a transition temperature $T_c$ = 5.6 $\pm$ 0.1 K, which is higher than

Nian Liu, Xiao Wang, Hui Han, Chuan Shi

Heterogeneous graph neural networks (HGNNs) as an emerging technique have shown superior capacity of dealing with heterogeneous information network (HIN). However, most HGNNs follow a semi-supervised learning manner, which notably limits their wide use in reality since labels are usually scarce in real applications. Recently, contrastive learning, a self-sup

Ángel López Oriona, José Antonio Vilar Fernández

Time series data are ubiquitous nowadays. Whereas most of the literature on the topic deals with real-valued time series, categorical time series have received much less attention. However, the development of data mining techniques for this kind of data has substantially increased in recent years. The R package ctsfeatures offers users a set of useful tools

Pavamana K J, Chandramani Singh

We study content caching in a wireless network in which the users are connected through a base station that is equipped with a finite-capacity cache. We assume a fixed set of contents whose popularity varies with time. Users' requests for the content depend on their instantaneous popularity levels. Proactively caching contents at the base station incurs a co

Yi C. Huang

We simplify the proof of a Gaussian correlation inequality for plurisubharmonic functions found by Barthe and Cordero-Erausquin. The new observation is a second-order integration-by-parts formula in the complex Gaussian setting.

Md Jamil Hossain, Prashik Gaikwad, Yun Kyung Shin, Jessica Schulze

Electrocatalysis is a catalytic process where the rate of an electrochemical reaction occurring at the electrode-electrolyte interface can be controlled by varying the electrical potential. Electrocatalysis can be applied to generate hydrogen which can be stored for future use in fuel cells for clean electricity. The use of solid oxide in electrocatalysis sp

A. Della Vedova, M. Spreafico

Let $G$ be a (non compact) connected simply connected locally compact second countable Lie group, either abelian or unimodular of type I, and $\rho$ an irreducible unitary representation of $G$. Then, we define the analytic torsion of $G$ localised at the representation $\rho$. Next, let $\Gamma$ a discrete cocompact subgroup of $G$. We use the localised ana

R. Altmann, M. Deiml

Within this paper, we introduce and analyze a novel time stepping scheme for linear poroelasticity. In each time frame, we iteratively solve the flow and mechanics equations with an additional damping step for the pressure variable. Depending on the coupling strength of the two equations, we explicitly quantify the needed number of inner iteration steps to g

Andac Demir, Elie Massaad, Bulent Kiziltan

The efficacy of segmentation algorithms is frequently compromised by topological errors like overlapping regions, disrupted connections, and voids. To tackle this problem, we introduce a novel loss function, namely Topology-Aware Focal Loss (TAFL), that incorporates the conventional Focal Loss with a topological constraint term based on the Wasserstein dista

Tae-Hun Lee, Jarosław K. Korbicz

We address the problem of fundamental limitations of information extraction from the environment in open quantum systems. We derive a model-independent, hybrid quantum-classical solution of open dynamics in the recoil-less limit, which includes environmental degrees of freedom. Specifying to the celebrated Caldeira-Leggett model of hot thermal environments,

A. L. Chudnovskiy, Alex Levchenko, Alex Kamenev

We address Coulomb drag and near-field heat transfer in a double-layer system of incoherent metals. Each layer is modeled by an array of tunnel-coupled SYK dots with random inter-layer interactions. Depending on the strength of intra-dot interactions and inter-dot tunneling, this model captures the crossover from the Fermi liquid to a strange metal phase. Th

Maksym Luz, Mikhail Moklyachuk

We deal with the problem of optimal estimation of the linear functionals constructed from unobserved values of a continuous time stochastic process with periodically correlated increments based on past observations of this process. To solve the problem, we construct a corresponding to the process sequence of stochastic functions which forms an infinite dimen

Thomas Michalke, Yassin Kaddar, Thomas Nürnberg, Linh Kästner

The detection of previously unseen, unexpected obstacles on the road is a major challenge for automated driving systems. Different from the detection of ordinary objects with pre-definable classes, detecting unexpected obstacles on the road cannot be resolved by upscaling the sensor technology alone (e.g., high resolution video imagers / radar antennas, dens

Bertrand Clarke, Yuling Yao

This paper reviews the growing field of Bayesian prediction. Bayes point and interval prediction are defined and exemplified and situated in statistical prediction more generally. Then, four general approaches to Bayes prediction are defined and we turn to predictor selection. This can be done predictively or non-predictively and predictors can be based on s

Yuankai Luo, Lei Shi, Mufan Xu, Yuwen Ji

Quantitatively profiling a scholar's scientific impact is important to modern research society. Current practices with bibliometric indicators (e.g., h-index), lists, and networks perform well at scholar ranking, but do not provide structured context for scholar-centric, analytical tasks such as profile reasoning and understanding. This work presents Genetic

Romain Chor, Milad Sefidgaran, Abdellatif Zaidi

We study the generalization error of statistical learning models in a Federated Learning (FL) setting. Specifically, there are $K$ devices or clients, each holding an independent own dataset of size $n$. Individual models, learned locally via Stochastic Gradient Descent, are aggregated (averaged) by a central server into a global model and then sent back to

R. Merlin

The concept of Wannier-Stark ladders, describing the equally spaced spectrum of a tightly-bound particle in a constant electric field, is generalized to account for arbitrary slowly-varying potentials. It is shown that an abrupt transition exists that separates Wannier-Stark-like from effective-mass-like behavior when the depth of the perturbation becomes eq

Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei

Biologically inspired Spiking Neural Networks (SNNs) have attracted significant attention for their ability to provide extremely energy-efficient machine intelligence through event-driven operation and sparse activities. As artificial intelligence (AI) becomes ever more democratized, there is an increasing need to execute SNN models on edge devices. Existing

F. Giannazzo, S. E. Panasci, E. Schilirò, G. Greco

The integration of two-dimensional $MoS_{2}$ with $GaN$ recently attracted significant interest for future electronic/optoelectronic applications. However, the reported studies have been mainly carried out using heteroepitaxial $GaN$ templates on sapphire substrates, whereas the growth of $MoS_{2}$ on low-dislocation-density bulk GaN can be strategic for the