March 2023 arXiv papers — page 103

Hun Jang

I introduce a way of constructing a fiber bundle whose fibers are given by hypercomplex algebras and woven by appropriate structure group, and present that a novel gauge theory can be built on the hypercomplex fiber bundle. In this work, I aim to answer a question about how nature selects one preferred vacuum among degenerate physical vacua, called {\it vacu

Sayantan Nag Chowdhury, Jeet Banerjee, Matjaž Perc, Dibakar Ghosh

Predator prey interactions are one of ecology's central research themes, but with many interdisciplinary implications across the social and natural sciences. Here we consider an often-overlooked species in these interactions, namely parasites. We first show that a simple predator prey parasite model, inspired by the classical Lotka Volterra equations, fails

Emmanouil Krasanakis, Symeon Papadopoulos

Graph filters that transform prior node values to posterior scores via edge propagation often support graph mining tasks affecting humans, such as recommendation and ranking. Thus, it is important to make them fair in terms of satisfying statistical parity constraints between groups of nodes (e.g., distribute score mass between genders proportionally to thei

Tingting Fang, Fei Zhu, Jie Chen

Unsupervised spectral unmixing consists of representing each observed pixel as a combination of several pure materials called endmembers with their corresponding abundance fractions. Beyond the linear assumption, various nonlinear unmixing models have been proposed, with the associated optimization problems solved either by traditional optimization algorithm

Brian M. Sutin

EMCCDs are efficient imaging devices for low surface brightness UV astronomy from space. The large amplification allows photon counting, the detection of events versus non-events. This paper provides the statistics of the observation process, the photon-counting process, the amplification, process, and the compression. The expression for the signal-to-noise

Shuo Liu, Shi-Xin Zhang, Shao-Kai Jian, Hong Yao

Variational quantum algorithms (VQAs) hold great potentials for near-term applications and are promising to achieve quantum advantage on practical tasks. However, VQAs suffer from severe barren plateau problem as well as have a large probability of being trapped in local minima. In this Letter, we propose a novel training algorithm with random quantum gate a

Charalampos Markakis, Sean Bray, Anıl Zenginoğlu

This work outlines a fast, high-precision time-domain solver for scalar, electromagnetic and gravitational perturbations on hyperboloidal foliations of Kerr space-times. Time-domain Teukolsky equation solvers have typically used explicit methods, which numerically violate Noether symmetries and are Courant-limited. These restrictions can limit the performanc

Yue Li, Martin Claassen

Dissipation is inevitable in realistic quantum circuits. We examine the effects of dissipation on a class of monitored random circuits that exhibit a measurement-induced entanglement phase transition. This transition has previously been understood as an order-to-disorder transition of an effective classical spin model. We extend this mapping to include on-si

Rachel A. Patton, Marc H. Pinsonneault, Lyra Cao, Mathieu Vrard

Rapidly rotating red giant stars are astrophysically interesting but rare. In this paper we present a catalog of 3217 active red giant candidates in the APOGEE DR16 survey. We use a control sample in the well-studied Kepler fields to demonstrate a strong relationship between rotation and anomalies in the spectroscopic solution relative to typical giants. Sta

Haowen Zhang, Peter Behroozi, Marta Volonteri, Joseph Silk

Using recent empirical constraints on the dark matter halo--galaxy--supermassive black hole (SMBH) connection from $z=0-7$, we infer how undermassive, typical, and overmassive SMBHs contribute to the quasar luminosity function (QLF) at $z=6$. We find that beyond $L_\mathrm{bol} = 5 \times 10^{46}$ erg/s, the $z=6$ QLF is dominated by SMBHs that are at least

Naren Manjunath, Abhinav Prem, Yuan-Ming Lu

Spatial symmetries can enrich the topological classification of interacting quantum matter and endow systems with non-trivial strong topological invariants (protected by internal symmetries) with additional "weak" topological indices. In this paper, we study the edge physics of systems with a non-trivial shift invariant, which is protected by either a contin

Nicholas Z. Rui, Jim Fuller

Strong magnetic fields in the cores of stars are expected to significantly modify the behavior of gravity waves: this is likely the origin of suppressed dipole modes observed in many red giants. However, a detailed understanding of how such fields alter the spectrum and spatial structure of magnetogravity waves has been elusive. For a dipole field, we analyt

Uri Keshet

A joint hadronic model is shown to quantitatively explain the observations of diffuse radio emission from galaxy clusters in the form of minihalos, giant halos, relics, and their hybrid, transitional stages. Cosmic-ray diffusion of order $D\sim 10^{31\text{--}32}\text{ cm}^2\text{ s}^{-1}$, inferred independently from relic energies, the spatial variability

William M. Baker, Roberto Maiolino

The widely known relation between stellar mass and gas metallicity (mass-metallicity relation, MZR) in galaxies is often ascribed to the higher capability of more massive systems to retain metals against the action of galactic outflows. In this scenario the stellar mass would simply be an indirect proxy of the dynamical mass or of the gravitational potential

Martin Bies

The study of vector-like spectra in 4-dimensional F-theory compactifications involves root bundles, which are important for understanding the Quadrillion F-theory Standard Models (F-theory QSMs) and their potential implications in physics. Recent studies focused on a superset of physical root bundles whose cohomologies encode the vector-like spectra for cert

Kyle Devereaux, Wenqing Fan, Weiyao Ke, Kyle Lee

The future electron-ion collider (EIC) will produce the first-ever high energy collisions between electrons and a wide range of nuclei, opening a new era in the study of cold nuclear matter. Quarks and gluons produced in these collisions will propagate through the dense nuclear matter of nuclei, imprinting its structure into subtle correlations in the energy

Qidong Huang, Xiaoyi Dong, Dongdong Chen, Weiming Zhang

We present Diversity-Aware Meta Visual Prompting~(DAM-VP), an efficient and effective prompting method for transferring pre-trained models to downstream tasks with frozen backbone. A challenging issue in visual prompting is that image datasets sometimes have a large data diversity whereas a per-dataset generic prompt can hardly handle the complex distributio

Naoto Inoue, Kotaro Kikuchi, Edgar Simo-Serra, Mayu Otani

Controllable layout generation aims at synthesizing plausible arrangement of element bounding boxes with optional constraints, such as type or position of a specific element. In this work, we try to solve a broad range of layout generation tasks in a single model that is based on discrete state-space diffusion models. Our model, named LayoutDM, naturally han

Ryan Thorngren, Tibor Rakovszky, Ruben Verresen, Ashvin Vishwanath

Classifying Higgs phases within the landscape of gapped and symmetry preserving states of matter presents a conceptual challenge. We argue that $U(1)$ Higgs phases are symmetry-protected topological (SPT) phases and we derive their topological response theory and boundary anomaly -- applicable to superconductors treated with dynamical electromagnetic field.

Jianren Wang, Sudeep Dasari, Mohan Kumar Srirama, Shubham Tulsiani

The field of visual representation learning has seen explosive growth in the past years, but its benefits in robotics have been surprisingly limited so far. Prior work uses generic visual representations as a basis to learn (task-specific) robot action policies (e.g., via behavior cloning). While the visual representations do accelerate learning, they are pr

Renrui Zhang, Liuhui Wang, Ziyu Guo, Yali Wang

We present a Non-parametric Network for 3D point cloud analysis, Point-NN, which consists of purely non-learnable components: farthest point sampling (FPS), k-nearest neighbors (k-NN), and pooling operations, with trigonometric functions. Surprisingly, it performs well on various 3D tasks, requiring no parameters or training, and even surpasses existing full

Zhen Liu, Yao Feng, Michael J. Black, Derek Nowrouzezahrai

We consider the task of generating realistic 3D shapes, which is useful for a variety of applications such as automatic scene generation and physical simulation. Compared to other 3D representations like voxels and point clouds, meshes are more desirable in practice, because (1) they enable easy and arbitrary manipulation of shapes for relighting and simulat

Qihao Liu, Junfeng Wu, Yi Jiang, Xiang Bai

Despite significant efforts, cutting-edge video segmentation methods still remain sensitive to occlusion and rapid movement, due to their reliance on the appearance of objects in the form of object embeddings, which are vulnerable to these disturbances. A common solution is to use optical flow to provide motion information, but essentially it only considers

Hao Zhang, Feng Li, Xueyan Zou, Shilong Liu

We present OpenSeeD, a simple Open-vocabulary Segmentation and Detection framework that jointly learns from different segmentation and detection datasets. To bridge the gap of vocabulary and annotation granularity, we first introduce a pre-trained text encoder to encode all the visual concepts in two tasks and learn a common semantic space for them. This giv

B. T. Bolin, K. S. Noll, I. Caiazzo, C. Fremling

Recently, the inner main belt asteroid (152830) Dinkinesh was identified as an additional fly-by target for the Lucy mission. The heliocentric orbit and approximate absolute magnitude of Dinkinesh are known, but little additional information was available prior to its selection as a target. In particular, the lack of color spectrophotometry or spectra made i

Anthony Chen, Kevin Zhang, Renrui Zhang, Zihan Wang

Masked Autoencoders learn strong visual representations and achieve state-of-the-art results in several independent modalities, yet very few works have addressed their capabilities in multi-modality settings. In this work, we focus on point cloud and RGB image data, two modalities that are often presented together in the real world, and explore their meaning

Dídac Surís, Sachit Menon, Carl Vondrick

Answering visual queries is a complex task that requires both visual processing and reasoning. End-to-end models, the dominant approach for this task, do not explicitly differentiate between the two, limiting interpretability and generalization. Learning modular programs presents a promising alternative, but has proven challenging due to the difficulty of le

Jacob Sharf, Mustafa Omer Gul, Yoav Artzi

CB2 is a multi-agent platform to study collaborative natural language interaction in a grounded task-oriented scenario. It includes a 3D game environment, a backend server designed to serve trained models to human agents, and various tools and processes to enable scalable studies. We deploy CB2 at https://cb2.ai as a system demonstration with a learned instr

Sayantan Nag Chowdhury, Sarbendu Rakshit, Chittaranjan Hens, Dibakar Ghosh

With synchronization being one of nature's most ubiquitous collective behaviors, the field of network synchronization has experienced tremendous growth, leading to significant theoretical developments. However, most of these previous studies consider uniform connection weights and undirected networks with positive coupling. In the present article, we incorpo

Takahide Adachi, Mayu Tsukamoto

Extriangulated categories give a simultaneous generalization of triangulated categories and exact categories. In this paper, we study silting subcategories of an extriangulated category. First, we show that a silting subcategory induces a basis of the Grothendieck group of an extriangulated category. Secondly, we introduce the notion of silting mutation and

Alexis Derumigny, Johannes Schmidt-Hieber

We propose a new concept of codivergence, which quantifies the similarity between two probability measures $P_1, P_2$ relative to a reference probability measure $P_0$. In the neighborhood of the reference measure $P_0$, a codivergence behaves like an inner product between the measures $P_1 - P_0$ and $P_2 - P_0$. Codivergences of covariance-type and correla

Aleksandra Kusiak, Kristen M. Surrao, J. Colin Hill

Extracting the CMB blackbody temperature power spectrum -- which is dominated by the primary CMB signal and the kinematic Sunyaev-Zel'dovich (kSZ) effect -- from mm-wave sky maps requires cleaning other sky components. In this work, we develop new methods to use large-scale structure (LSS) tracers to remove cosmic infrared background (CIB) and thermal Sunyae

Chenyang Lei, Xuanchi Ren, Zhaoxiang Zhang, Qifeng Chen

Many videos contain flickering artifacts. Common causes of flicker include video processing algorithms, video generation algorithms, and capturing videos under specific situations. Prior work usually requires specific guidance such as the flickering frequency, manual annotations, or extra consistent videos to remove the flicker. In this work, we propose a ge

Jiuhai Chen, Lichang Chen, Chen Zhu, Tianyi Zhou

Large language models (LLMs) are capable to perform complex reasoning by in-context learning (ICL) when provided with a few input-output demonstrations (demos) and more powerful when intermediate reasoning steps ("chain of thoughts (CoT)") of the demos are given. Is it necessary to use multi-demo in ICL? In this paper, we study ICL using fewer demos for each

Leslie Ann Goldberg, Marc Roth, Tassilo Constantin Schwarz

The multi-type Moran process is an evolutionary process on a connected graph $G$ in which each vertex has one of $k$ types and, in each step, a vertex $v$ is chosen to reproduce its type to one of its neighbours. The probability of a vertex $v$ being chosen for reproduction is proportional to the fitness of the type of $v$. So far, the literature was almost

Haoyu Zhao, Abhishek Panigrahi, Rong Ge, Sanjeev Arora

Pre-trained language models have been shown to encode linguistic structures, e.g. dependency and constituency parse trees, in their embeddings while being trained on unsupervised loss functions like masked language modeling. Some doubts have been raised whether the models actually are doing parsing or only some computation weakly correlated with it. We study

Michael Milgram

By treating the multiple argument identity of the logarithm of the Gamma function as a functional equation, we obtain a curious infinite product representation of the $sinc$ function in terms of the cotangent function. This result is believed to be new. It is then shown how to convert the infinite product to a finite product, which turns out to be a simple t

Kelvin Guu, Albert Webson, Ellie Pavlick, Lucas Dixon

Training data attribution (TDA) methods offer to trace a model's prediction on any given example back to specific influential training examples. Existing approaches do so by assigning a scalar influence score to each training example, under a simplifying assumption that influence is additive. But in reality, we observe that training examples interact in high

Jing Zou, Noémie Debroux, Lihao Liu, Jing Qin

Deformable image registration is a fundamental task in medical image analysis and plays a crucial role in a wide range of clinical applications. Recently, deep learning-based approaches have been widely studied for deformable medical image registration and achieved promising results. However, existing deep learning image registration techniques do not theore

Nora Belrose, Igor Ostrovsky, Lev McKinney, Zach Furman

We analyze transformers from the perspective of iterative inference, seeking to understand how model predictions are refined layer by layer. To do so, we train an affine probe for each block in a frozen pretrained model, making it possible to decode every hidden state into a distribution over the vocabulary. Our method, the tuned lens, is a refinement of the

Syunji Moriya

We compute some differentials of Sinha's spectral sequence for cohomology of the space of long knots modulo immersions in codimension one, mainly over a field of characteristic $2$ or $3$. This spectral sequence is closely related to Vassiliev's spectral sequence for the space of long knots in codimension $\geq 2$. We prove that the $d_2$-differential of an

Martin Bies, Lars Kastner

We report on the computer implementation for toric geometry in the computer algebra system $\texttt{OSCAR}$. The main architectural feature of $\texttt{OSCAR}$ is that its four fundamental tools $\texttt{Antic}$ (Hecke, Nemo), $\texttt{GAP}$, $\texttt{Polymake}$ and $\texttt{Singular}$ are $\mathit{integral~components}$, rather than external software. Toric

Lu Yihe, Rana Alkhoury Maroun, Barbara Webb

We compared the efficiency of the FlyHash model, an insect-inspired sparse neural network (Dasgupta et al., 2017), to similar but non-sparse models in an embodied navigation task. This requires a model to control steering by comparing current visual inputs to memories stored along a training route. We concluded the FlyHash model is more efficient than others

Josefine Bohr Brask, Andreas Koher, Darren P. Croft, Sune Lehmann

Social network structures play an important role in the lives of animals by affecting individual fitness and the spread of disease and information. Nevertheless, we still lack a good understanding of how these structures emerge from the behavior of individuals. Generative network models provide a powerful approach that can help close this gap. Empirical rese

Kaspars Dadzis

A new setup for Czochralski growth of model materials in air atmosphere has been developed. It includes various in-situ measurements to access the basic physical phenomena on a macroscopic level: heat transfer, electromagnetism, melt and gas flows, crystal stresses. A reference experiment with tin is performed and analyzed using simple analytical estimates a

Joshua Isaacson, Stefan Höche, Frank Siegert, Sherry Wang

We present the first fully differential predictions for tau neutrino scattering in the energy region relevant to the DUNE experiment, including all spin correlations and all tau lepton decay channels. The calculation is performed using a generic interface between the neutrino event generator Achilles and the publicly available, general-purpose collider event

Khaled Eldowa, Nicolò Cesa-Bianchi, Alberto Maria Metelli, Marcello Restelli

We investigate the problem of bandits with expert advice when the experts are fixed and known distributions over the actions. Improving on previous analyses, we show that the regret in this setting is controlled by information-theoretic quantities that measure the similarity between experts. In some natural special cases, this allows us to obtain the first r

Haoya Li, Hongkang Ni, Lexing Ying

This paper is an algorithmic study of quantum phase estimation with multiple eigenvalues. We present robust multiple-phase estimation (RMPE) algorithms with Heisenberg-limited scaling. The proposed algorithms improve significantly from the idea of single-phase estimation methods by combining carefully designed signal processing routines and an adaptive deter

Jaewook Joo

We are keenly interested in finding the limiting behaviors of total tumor size when tumor cells are subject to the periodic repetition of therapy and rest periods, called intermittent cyclic therapy. We hypothesize that each tumor cell can take either therapy-sensitive or therapy-tolerant phenotype, its phenotype transition is mainly driven by the presence o

Axel Levy, Mark Matthews, Matan Sela, Gordon Wetzstein

Neural radiance fields enable novel-view synthesis and scene reconstruction with photorealistic quality from a few images, but require known and accurate camera poses. Conventional pose estimation algorithms fail on smooth or self-similar scenes, while methods performing inverse rendering from unposed views require a rough initialization of the camera orient

D. J. Watts, A. Basyrov, J. R. Eskilt, M. Galloway

We present Cosmoglobe Data Release 1, which implements the first joint analysis of WMAP and Planck LFI time-ordered data, processed within a single Bayesian end-to-end framework. This framework builds directly on a similar analysis of the LFI measurements by the BeyondPlanck collaboration, and approaches the CMB analysis challenge through Gibbs sampling of a

Asma Hassannezhad, David Sher

We prove an improved Pleijel nodal domain theorem for the Robin eigenvalue problem. In particular we remove the restriction, imposed in previous work, that the Robin parameter be non-negative. We also improve the upper bound in the statement of the Pleijel theorem. In the particular example of a Euclidean ball, we calculate the explicit value of the Pleijel

David Nguyen

It is a classic result of Selberg in the 1950's that $\theta_2 = 2/3$, where $\theta_2$ is the level of distribution of the divisor function in arithmetic progressions (defined more precisely below). Selberg applies this estimate, together with his $\Lambda^2$ sieve, to prove weak forms of the binary Goldbach and twin prime conjectures. In this note, we give

Patrick M. O'Keefe, Viacheslav Sadykov, Alexander Kosovichev, Irina N. Kitiashvili

The application of machine learning and deep learning, including the wide use of non-ensemble, conventional neural networks (CoNN), for predicting various phenomena has become very popular in recent years thanks to the efficiencies and the abilities of these techniques to find relationships in data without human intervention. However, certain CoNN setups may

T. Luo, F. A. Hahl, J. Langer, V. Cimalla

The use of diamond color centers such as the nitrogen-vacancy (NV) center is increasingly enabling quantum sensing and computing applications. Novel concepts like cavity coupling and readout, laser threshold magnetometry and multi-pass geometries allow significantly improved sensitivity and performance via increased signals and strong light fields. Enabling

Alberto Baccini, Eugenio Petrovich

Self-citations are a key topic in evaluative bibliometrics because they can artificially inflate citation-related performance indicators. Recently, self-citations defined at the largest scale, i.e., country self-citations, have started to attract the attention of researchers and policymakers. According to a recent research, in fact, the anomalous trends in t

Duy-Nhat Ly, Dai-Nam Le, Duy-Anh P. Nguyen, Ngoc-Tram D. Hoang

Reduced exciton mass, polarizability, and dielectric constant of the surrounding medium are essential properties for semiconducting materials, and they have been extracted recently from the magnetoexciton energies. However, the acceptable accuracy of the suggested method requires very high magnetic intensity. Therefore, in the present paper, we propose an al

Uluk Rasulov, Anupama Acharya, Marina Carravetta, Guinevere Mathies

Response functions of resonant circuits create ringing artefacts if their input changes rapidly. When physical limits of electromagnetic spectroscopies are explored, this creates two types of problems. Firstly, simulation: the system must be propagated accurately through every response transient, this may be computationally expensive. Secondly, optimal contr

Cheng-Hao Tu, Hong-You Chen, David Carlyn, Wei-Lun Chao

Fractals are geometric shapes that can display complex and self-similar patterns found in nature (e.g., clouds and plants). Recent works in visual recognition have leveraged this property to create random fractal images for model pre-training. In this paper, we study the inverse problem -- given a target image (not necessarily a fractal), we aim to generate

Farhanul Hasan, Joseph N. Burchett, Alyssa Abeyta, Douglas Hellinger

We investigate how cosmic web structures affect galaxy quenching in the IllustrisTNG (TNG100) cosmological simulations by reconstructing the cosmic web within each snapshot using the DisPerSE framework. We measure the comoving distance from each galaxy with stellar mass $\log(M_{\ast}/\mathrm{M}_{\odot}) \geq 8$ to the nearest node ($d_{\mathrm{node}}$) and

A. Kuruvanthodi, D. Schaerer, M. Messa, A. Adamo

Supermassive stars (SMS) with masses $M \gtrsim 10^3-10^4 M_{\odot}$, formed by runaway collisions in young, massive, and dense star clusters have been invoked as a possible solution to the puzzles raised by the presence of multiple stellar populations and peculiar abundance patterns observed in globular clusters. However, such objects have not been observed

Mobasshir Mahbub, Raed M. Shubair

The work analyzed the positioning of IRS over the coverage region of micro cell to derive optimal placement location to support cell-edge Internet of Things (IoT) devices with a favorable signal-to-interference plus noise ratio (SINR). Moreover, the work derived that the implementation of IRS significantly enhances energy efficiency notably reducing the tran

Hagay Michaeli, Tomer Michaeli, Daniel Soudry

Although CNNs are believed to be invariant to translations, recent works have shown this is not the case, due to aliasing effects that stem from downsampling layers. The existing architectural solutions to prevent aliasing are partial since they do not solve these effects, that originate in non-linearities. We propose an extended anti-aliasing method that ta

Hadas Orgad, Bahjat Kawar, Yonatan Belinkov

Text-to-image diffusion models often make implicit assumptions about the world when generating images. While some assumptions are useful (e.g., the sky is blue), they can also be outdated, incorrect, or reflective of social biases present in the training data. Thus, there is a need to control these assumptions without requiring explicit user input or costly

Maiara F. Bollauf, Hsuan-Yin Lin, Øyvind Ytrehus

Recently, a design criterion depending on a lattice's volume and theta series, called the secrecy gain, was proposed to quantify the secrecy-goodness of the applied lattice code for the Gaussian wiretap channel. To address the secrecy gain of Construction $\text{A}_4$ lattices from formally self-dual $\mathbb{Z}_4$-linear codes, i.e., codes for which the sym

Thang T. Q. Lê, Tao Yu

We establish the existence of several quantum trace maps. The simplest one is an algebra map between two quantizations of the algebra of regular functions on the $SL_n$-character variety of a surface $\mathfrak{S}$ equipped with an ideal triangulation $\lambda$. The first is the (stated) $SL_n$-skein algebra $\mathscr{S}(\mathfrak{S})$. The second $\overline

Carlos Mougan, Klaus Broelemann, David Masip, Gjergji Kasneci

As input data distributions evolve, the predictive performance of machine learning models tends to deteriorate. In practice, new input data tend to come without target labels. Then, state-of-the-art techniques model input data distributions or model prediction distributions and try to understand issues regarding the interactions between learned models and sh

Grant Kopitzke

The Gini index is a function that attempts to measure the amount of inequality in the distribution of a finite resource throughout a population. It is commonly used in economics as a measure of inequality of income or wealth. We define a discrete Gini index on the set of integer partitions with at most $n$ parts and show how this function emerges in the repr

William J. Eckner, Nelson Darkwah Oppong, Alec Cao, Aaron W. Young

Neutral-atom arrays trapped in optical potentials are a powerful platform for studying quantum physics, combining precise single-particle control and detection with a range of tunable entangling interactions. For example, these capabilities have been leveraged for state-of-the-art frequency metrology as well as microscopic studies of entangled many-particle

Pierre S. Houdayer, Daniel R. Reese

We present RUBIS (Rotation code Using Barotropy conservation over Isopotential Surfaces), a fully Python-based centrifugal deformation program available at \url{https://github.com/pierrehoudayer/RUBIS}. The code has been designed to calculate the centrifugal deformation of stars and planets resulting from a given cylindrical rotation profile, starting from a

Mahdi Razzaghpour, Shahriar Shahram, Rodolfo Valiente, Mahdi Zaman

In this study, we explore an innovative approach to enhance cooperative driving in vehicle platooning systems through the use of vehicle-to-everything (V2X) communication technologies. As Connected and Autonomous Vehicles (CAVs) integrate into increasingly dense traffic networks, the challenge of efficiently managing communication resources becomes crucial.

Yunbo Zhang, Alexander Clegg, Sehoon Ha, Greg Turk

In-hand object manipulation is challenging to simulate due to complex contact dynamics, non-repetitive finger gaits, and the need to indirectly control unactuated objects. Further adapting a successful manipulation skill to new objects with different shapes and physical properties is a similarly challenging problem. In this work, we show that natural and rob

T. Pauletti, M. Garcia, G. A. Canella, V. V. França

Entanglement is considered a fundamental ingredient for quantum technologies and condensed matter systems are among the good candidates for quantum devices. For bipartite pure states the von Neumann entropy is a proper measure of entanglement, while the linear entropy, associated to the mixedness of the reduced density matrices, is a simpler quantity to be o

Marie-Françoise Bidaut-Véron, Laurent Véron

We study the local properties of positive solutions of the equation $-\Delta u=u^p-m|\nabla u|^q$ in a punctured domain $\Omega\setminus\{0\}$ of $\mathbb{R}^N$ or in a exterior domain $\mathbb{R}^N\setminus B_{r_0}$ in the range $\min\{p,q\}>1$ and $m>0$. We prove a series of a priori estimates depending $p$ and $q$, and of the sign of $q-\frac {2p}{p+1}$ a

Eric Braaten, Li-Ping He, Kevin Ingles, Jun Jiang

The thermal corrections to the propagator of a loosely bound charm-meson molecule in a pion gas are calculated to next-to-leading order in the heavy-meson expansion using a zero-range effective field theory. Ultraviolet divergences in the charm-meson-pair self energy are canceled by corrections to the charm-meson-pair contact vertex. Terms that are singular

Andreas Zinonos, Alexandros Haliassos, Pingchuan Ma, Stavros Petridis

Cross-lingual self-supervised learning has been a growing research topic in the last few years. However, current works only explored the use of audio signals to create representations. In this work, we study cross-lingual self-supervised visual representation learning. We use the recently-proposed Raw Audio-Visual Speech Encoders (RAVEn) framework to pre-tra

Peter A. Monkewitz, Hassan M. Nagib

The logarithmic law of the wall, joining the inner, near-wall mean velocity profile (abbreviated MVP) in wall-bounded turbulent flows to the outer region, has been a permanent fixture of turbulence research for over hundred years, but there is still no general agreement on the value of the pre-factor, the inverse of the K\'arm\'an ``constant'' $\kappa$, or o

David Kalaj, João P. G. Ramos

Assume that $\Delta_h$ is the hyperbolic Laplacian in the unit ball $\mathbb{B}$ and assume that $\Phi_n$ is the unique radial solution of Poisson equation $\Delta_h \log \Phi_n =-4 (n-1)^2$ satisfying the condition $\Phi_n(0)=1$ and $\Phi_n(\zeta)=0$ for $\zeta\in \partial\mathbb{B}$. We explicitly solve the question of maximizing $$ R_n(f,\Omega)= \frac{\i

Mengjia Yu, Sheng Zhong, Yunzhao Xing, Li Wang

Given progressive developments and demands on clinical trials, accurate enrollment timeline forecasting is increasingly crucial for both strategic decision-making and trial execution excellence. Naive approach assumes flat rates on enrollment using average of historical data, while traditional statistical approach applies simple Poisson-Gamma model using tim

Weiyang Jin, Yongpei Zhu, Yuxi Peng

For a considerable time, researchers have focused on developing a method that establishes a deep connection between the generative diffusion model and mathematical physics. Despite previous efforts, progress has been limited to the pursuit of a single specialized method. In order to advance the interpretability of diffusion models and explore new research di

Elias R. Most, Eliot Quataert

Using numerical relativity simulations with a subgrid dynamo prescription to generate strong initial magnetic fields, we investigate the possibility of launching a jet-like outflow from the hypermassive neutron star (HMNS) during the early stages of the merger, prior to the remnants collapse to a black hole. We demonstrate that buoyant instabilities in the s

Paul Friedrich, Julia Wolleb, Florentin Bieder, Florian M. Thieringer

Advances in 3D printing of biocompatible materials make patient-specific implants increasingly popular. The design of these implants is, however, still a tedious and largely manual process. Existing approaches to automate implant generation are mainly based on 3D U-Net architectures on downsampled or patch-wise data, which can result in a loss of detail or c

Marco Kemmerling, Daniel Lütticke, Robert H. Schmitt

The advent of AlphaGo and its successors marked the beginning of a new paradigm in playing games using artificial intelligence. This was achieved by combining Monte Carlo tree search, a planning procedure, and deep learning. While the impact on the domain of games has been undeniable, it is less clear how useful similar approaches are in applications beyond

Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines

We address the challenge of exploration in reinforcement learning (RL) when the agent operates in an unknown environment with sparse or no rewards. In this work, we study the maximum entropy exploration problem of two different types. The first type is visitation entropy maximization previously considered by Hazan et al.(2019) in the discounted setting. For

Mario Stipčević

Randomness is a crucial resource for a broad range of important applications, such as Monte Carlo simulation and computation, generative artificial intelligence and cryptography. But what is randomness? A widely accepted definition has eluded researchers thus far, yet without one any work that relies on notion of randomness lacks scientific rigor and its res

Anastasiia Plotnikova, Giovanni Carraro, Sandro Villanova, Sergio Ortolani

Very metal-poor stars contain crucial information on the Milky Way's infancy. In our previous study \citep{Plotnikova_2022} we derived a mean age of $\sim$ 13.7 Gyr for a sample of these stars in the Sun's vicinity. In this work, we investigate the chemical and kinematics properties of these stars with the goal of obtaining some insights on their origin and

Renjie Luo, Tanner J. Legvold, Liyang Chen, Douglas Natelson

As spin caloritronic measurements become increasingly common techniques for characterizing material properties, it is important to quantify potentially confounding effects. We report measurements of the Nernst-Ettingshausen response from room temperature to 5 K in thin film wires of Pt and W, metals commonly used as inverse spin Hall detectors in spin Seebec

Chiara Gallese

The debate about the concept of the so called right to explanation in AI is the subject of a wealth of literature. It has focused, in the legal scholarship, on art. 22 GDPR and, in the technical scholarship, on techniques that help explain the output of a certain model (XAI). The purpose of this work is to investigate if the new provisions introduced by the

Alireza Ghaffari, Masoud Asgharian, Yvon Savaria

With the rising complexity of numerous novel applications that serve our modern society comes the strong need to design efficient computing platforms. Designing efficient hardware is, however, a complex multi-objective problem that deals with multiple parameters and their interactions. Given that there are a large number of parameters and objectives involved

Guillaume Bornet, Gabriel Emperauger, Cheng Chen, Bingtian Ye

The standard quantum limit bounds the precision of measurements that can be achieved by ensembles of uncorrelated particles. Fundamentally, this limit arises from the non-commuting nature of quantum mechanics, leading to the presence of fluctuations often referred to as quantum projection noise. Quantum metrology relies on the use of non-classical states of

Annika Briegleb, Thomas Haubner, Vasileios Belagiannis, Walter Kellermann

Beamforming for multichannel speech enhancement relies on the estimation of spatial characteristics of the acoustic scene. In its simplest form, the delay-and-sum beamformer (DSB) introduces a time delay to all channels to align the desired signal components for constructive superposition. Recent investigations of neural spatiospectral filtering revealed tha

Zicheng Zhang, Wei Sun, Yingjie Zhou, Jun Jia

Computer graphics images (CGIs) are artificially generated by means of computer programs and are widely perceived under various scenarios, such as games, streaming media, etc. In practice, the quality of CGIs consistently suffers from poor rendering during production, inevitable compression artifacts during the transmission of multimedia applications, and lo

Dipankar Roy, David A. Huse, Manas Kulkarni

The out-of-time-ordered correlator (OTOC) has emerged as an interesting object in both classical and quantum systems for probing the spatial spread and temporal growth of initially local perturbations in spatially extended chaotic systems. Here, we study the (classical) OTOC and its ``light-cone'' in the nonlinear Kuramoto-Sivashinsky (KS) equation, using ex

Savelii Chezhegov, Alexander Rogozin, Alexander Gasnikov

In decentralized optimization, several nodes connected by a network collaboratively minimize some objective function. For minimization of Lipschitz functions lower bounds are known along with optimal algorithms. We study a specific class of problems: linear models with nonsmooth loss functions. Our algorithm combines regularization and dual reformulation to

L. Thomas van Binsbergen, Damian Frolich

Parser generators and parser combinator libraries are the most popular tools for producing parsers. Parser combinators use the host language to provide reusable components in the form of higher-order functions with parsers as parameters. Very few parser generators support this kind of reuse through abstraction and even fewer generate parsers that are as modu

Spencer Hobson-Gutierrez, Edo Kussell

We analyze the advantage of cell size control strategies in growing populations under mortality constraints. We demonstrate a general advantage of the adder control strategy in the presence of growth-dependent mortality, and for different size-dependent mortality landscapes. Its advantage stems from epigenetic heritability of cell size, which enables selecti

Anton Tselishchev

In this paper we study the following problem: for a given bounded positive function $f$ on a filtered probability space can we find another function (a multiplier) $m$, $0\le m\le 1$, such that the function $mf$ is not ``too small'' but its square function is bounded? We explicitly show how to construct such multipliers for the usual martingale square functi

Carlos Mougan, Laura State, Antonio Ferrara, Salvatore Ruggieri

Liberalism-oriented political philosophy reasons that all individuals should be treated equally independently of their protected characteristics. Related work in machine learning has translated the concept of \emph{equal treatment} into terms of \emph{equal outcome} and measured it as \emph{demographic parity} (also called \emph{statistical parity}). Our ana

Yanjun Gao, Dmitriy Dligach, Timothy Miller, Matthew M Churpek

Daily progress notes are common types in the electronic health record (EHR) where healthcare providers document the patient's daily progress and treatment plans. The EHR is designed to document all the care provided to patients, but it also enables note bloat with extraneous information that distracts from the diagnoses and treatment plans. Applications of n

Omkar H. Ramachandran, Leo C. Kempel, John Luginsland, B. Shanker

The state of art of charge-conserving electromagnetic finite element particle-in-cell has grown by leaps and bounds in the past few years. These advances have primarily been achieved for leap-frog time stepping schemes for Maxwell solvers, in large part, due to the method strictly following the proper space for representing fields, charges, and measuring cur