March 2023 arXiv papers — page 9

Andrei Tokovinin

There should be about 10,000 stellar hierarchical systems within 100 pc with primary stars more massive than 0.5 Msun, and a similar amount of less massive hierarchies. A list of 8000 candidate multiples is derived from wide binaries found in the Gaia Catalog of Nearby Stars where one or both components have excessive astrometric noise or other indicators of

Federico Garcia-Gaitan, Branislav K. Nikolic

It is commonly assumed in spintronics and magnonics that localized spins within antiferromagnets are in the N\'{e}el ground state (GS), as well as that such state evolves, when pushed out of equilibrium by current or external fields, according to the Landau-Lifshitz-Gilbert (LLG) equation viewing localized spins as classical vectors of fixed length. On the o

Dongyoon Han, Junsuk Choe, Seonghyeok Chun, John Joon Young Chung

Supervised learning of image classifiers distills human knowledge into a parametric model through pairs of images and corresponding labels (X,Y). We argue that this simple and widely used representation of human knowledge neglects rich auxiliary information from the annotation procedure, such as the time-series of mouse traces and clicks left after image sel

Renhong Zhang, Tianheng Cheng, Shusheng Yang, Haoyi Jiang

Video instance segmentation on mobile devices is an important yet very challenging edge AI problem. It mainly suffers from (1) heavy computation and memory costs for frame-by-frame pixel-level instance perception and (2) complicated heuristics for tracking objects. To address those issues, we present MobileInst, a lightweight and mobile-friendly framework fo

Florin Condrea, Saikiran Rapaka, Lucian Itu, Puneet Sharma

Pulmonary Embolisms (PE) represent a leading cause of cardiovascular death. While medical imaging, through computed tomographic pulmonary angiography (CTPA), represents the gold standard for PE diagnosis, it is still susceptible to misdiagnosis or significant diagnosis delays, which may be fatal for critical cases. Despite the recently demonstrated power of

Sammy Christen, Wei Yang, Claudia Pérez-D'Arpino, Otmar Hilliges

We propose the first framework to learn control policies for vision-based human-to-robot handovers, a critical task for human-robot interaction. While research in Embodied AI has made significant progress in training robot agents in simulated environments, interacting with humans remains challenging due to the difficulties of simulating humans. Fortunately,

Eric Zhang, Kai Wang, Xingqian Xu, Zhangyang Wang

The unlearning problem of deep learning models, once primarily an academic concern, has become a prevalent issue in the industry. The significant advances in text-to-image generation techniques have prompted global discussions on privacy, copyright, and safety, as numerous unauthorized personal IDs, content, artistic creations, and potentially harmful materi

Paola Cascante-Bonilla, Khaled Shehada, James Seale Smith, Sivan Doveh

Large-scale pre-trained Vision & Language (VL) models have shown remarkable performance in many applications, enabling replacing a fixed set of supported classes with zero-shot open vocabulary reasoning over (almost arbitrary) natural language prompts. However, recent works have uncovered a fundamental weakness of these models. For example, their difficulty

Lisa Aoki Hillas, Rene Caldentey, Varun Gupta

This paper examines the performance of multi-class multi-server bipartite queueing systems under a FCFS-ALIS service discipline, where each arriving customer is only compatible with a subset of servers. We analyze the system under conventional heavy-traffic conditions, where the traffic intensity approaches one from below. Building upon the formulation and r

Xiangzhuo Xing, Chao Wang, Linchao Yu, Jie Xu

The recent report of near-ambient superconductivity in nitrogen doped lutetium hydride has triggered a worldwide fanaticism and raised major questions about the latest claims. An intriguing phenomenon of color changes in pressurized samples from blue to pink to red was observed and correlated with the claimed superconducting transition, but the origin and un

Aimo Hinkkanen, Ilgiz R. Kayumov, Diana M. Khammatova

We give an analytic proof of the dual Smale's mean value conjecture in the case $n=7$.

Andres Vicente Arevalo, Jiri Stepan, Tanausu del Pino Aleman, Maria Jesus Martinez Gonzalez

We study the formation of the Stokes profiles of the He I multiplet at 10830 A when relaxing two of the approximations that are often considered in the modeling of this multiplet, namely the lack of self-consistent radiation transfer and the assumption of equal illumination of the individual multiplet components. This He I multiplet is among the most importa

Kaicheng Niu, Chaouki Abdallah, Mohammad Hayajneh

This paper proposes a consensus controller for multi-agent systems that can guarantee the agents' safety. The controller, built with the idea of output prediction and the Newton-Raphson method, achieves consensus for a class of heterogeneous nonlinear systems. The Integral Control Barrier Function is applied in conjunction with the controller, such that the

Alexander M. Tanaka, Avishai Gilkis, Robert G. Izzard, Christopher A. Tout

We use the rapid binary stellar evolution code BINARY_C to estimate the rate of merging neutron stars with numerous combinations of envelope ejection efficiency and natal kick dispersion. We find a peak in the local rate of merging neutron stars around $\alpha \approx 0.3$$-$$0.4$, depending on the metallicity, where $\alpha$ is the efficiency of utilising o

Sachin Shah, Sakshum Kulshrestha, Christopher A. Metzler

Point-spread-function (PSF) engineering is a powerful computational imaging techniques wherein a custom phase mask is integrated into an optical system to encode additional information into captured images. Used in combination with deep learning, such systems now offer state-of-the-art performance at monocular depth estimation, extended depth-of-field imagin

Ahmad Amine, Mostafa Aldilati, Hadi Hasan, Noel Maalouf

Robots have become ubiquitous tools in various industries and households, highlighting the importance of human-robot interaction (HRI). This has increased the need for easy and accessible communication between humans and robots. Recent research has focused on the intersection of virtual assistant technology, such as Amazon's Alexa, with robots and its effect

Neïl Zaïm, Antonin Sainte-Marie, Luca Fedeli, Pierre Bartoli

The Schwinger limit could be approached by focusing to its diffraction limit the light reflected by a plasma mirror irradiated by a multi-petawatt laser. We explore numerically the interaction between such intense light and matter. We find that the interaction with a relativistic counterpropagative electron beam would enable the exploration of the fully nonp

Yongliang Shen, Kaitao Song, Xu Tan, Dongsheng Li

Solving complicated AI tasks with different domains and modalities is a key step toward artificial general intelligence. While there are numerous AI models available for various domains and modalities, they cannot handle complicated AI tasks autonomously. Considering large language models (LLMs) have exhibited exceptional abilities in language understanding,

Tsun-Ming Cheung, Hamed Hatami, Pooya Hatami, Kaave Hosseini

In a recent article, Alon, Hanneke, Holzman, and Moran (FOCS '21) introduced a unifying framework to study the learnability of classes of partial concepts. One of the central questions studied in their work is whether the learnability of a partial concept class is always inherited from the learnability of some ``extension'' of it to a total concept class. Th

Alio Issoufou Arzika, Andrea Solfanelli, Harald Schmid, Stefano Ruffo

We study the transition from integrability to chaos for the three-particle Fermi-Pasta-Ulam- Tsingou (FPUT) model. We can show that both the quartic b-FPUT model ($\alpha$ = 0) and the cubic one ($\beta$ = 0) are integrable by introducing an appropriate Fourier representation to express the nonlinear terms of the Hamiltonian. For generic values of $\alpha$ a

William Salkeld

A Bialgebra is a module over a ring that is both an associative algebra and a co-associative coalgebra with the product and coproduct additionally satisfying an appropriate commutative relationship. One application of Bialgebras is in the study of Taylor expansions where the product describes how for any increment, two terms of the Taylor expansion can be co

Misha Gavrilovich

A definable type of a first-order theory is the same as a section (retraction) of the simplicial path space (decalage) of its space of types viewed as a simplicial topological space; as is well-known, in the category of simplicial sets such sections correspond to homotopies contracting each connected component. Without the simplicial language this is stated

Nico Daheim, Nouha Dziri, Mrinmaya Sachan, Iryna Gurevych

Ideally, dialogue systems should generate responses that are faithful to the knowledge contained in relevant documents. However, many models generate hallucinated responses instead that contradict it or contain unverifiable information. To mitigate such undesirable behaviour, it has been proposed to fine-tune a `negative expert' on negative examples and subt

Md Saiful Islam, Wasifur Rahman, Abdelrahman Abdelkader, Phillip T. Yang

We present an artificial intelligence system to remotely assess the motor performance of individuals with Parkinson's disease (PD). Participants performed a motor task (i.e., tapping fingers) in front of a webcam, and data from 250 global participants were rated by three expert neurologists following the Movement Disorder Society Unified Parkinson's Disease

Amine Asselah, Bruno Schapira, Perla Sousi

We consider branching random walks on the Euclidean lattice in dimensions five and higher. In this non-Markovian setting, we first obtain a relationship between the equilibrium measure and Green's function, in the form of an approximate last passage decomposition. Secondly, we obtain exponential moment bounds for functionals of the branching random walk, und

William Salkeld

In this paper, we provide some of the necessary mathematics to describe higher order Lions-Taylor expansions. The Lions derivative of a functional on the Wasserstein space of measures quantifies infinitesimal perturbations on measures in terms of infinite variation on a linear space of random variables.

Augustus Brown, Congkao Wen, Haitian Xie

We recently proved that, when integrating out spacetime dependence with a certain measure, four-point correlators $\langle \mathcal{O}_2\mathcal{O}_2\mathcal{O}^{(i)}_p \mathcal{O}^{(j)}_p \rangle$ in $SU(N)$ $\mathcal{N}=4$ super Yang-Mills are governed by a universal Laplace-difference equation. Here $\mathcal{O}^{(i)}_p$ is a superconformal primary with c

Zhexin Liang, Chongyi Li, Shangchen Zhou, Ruicheng Feng

We propose a novel unsupervised backlit image enhancement method, abbreviated as CLIP-LIT, by exploring the potential of Contrastive Language-Image Pre-Training (CLIP) for pixel-level image enhancement. We show that the open-world CLIP prior not only aids in distinguishing between backlit and well-lit images, but also in perceiving heterogeneous regions with

Qinkai Zheng, Xiao Xia, Xu Zou, Yuxiao Dong

Large pre-trained code generation models, such as OpenAI Codex, can generate syntax- and function-correct code, making the coding of programmers more productive and our pursuit of artificial general intelligence closer. In this paper, we introduce CodeGeeX, a multilingual model with 13 billion parameters for code generation. CodeGeeX is pre-trained on 850 bi

Iryna Raievska, Maryna Raievska

We consider groups of the nilpotency class $2$ of order $p^4$ which are the additive groups of local nearrings. It was shown that, for odd p, out of 6 of such groups 4 of them are the additive groups of local nearrings. Some examples of such nearrings are explicitly constructed.

Ke Yang, Alexandra Meliou

Machine Learning (ML) models are widely employed to drive many modern data systems. While they are undeniably powerful tools, ML models often demonstrate imbalanced performance and unfair behaviors. The root of this problem often lies in the fact that different subpopulations commonly display divergent trends: as a learning algorithm tries to identify trends

Dripto M. Debroy, Elie Genois, Jonathan A. Gross, Wojciech Mruczkiewicz

We present Context Aware Fidelity Estimation (CAFE), a framework for benchmarking quantum operations that offers several practical advantages over existing methods such as Randomized Benchmarking (RB) and Cross-Entropy Benchmarking (XEB). In CAFE, a gate or a subcircuit from some target experiment is repeated n times before being measured. By using a subcirc

Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski

The use of NLP in the realm of financial technology is broad and complex, with applications ranging from sentiment analysis and named entity recognition to question answering. Large Language Models (LLMs) have been shown to be effective on a variety of tasks; however, no LLM specialized for the financial domain has been reported in literature. In this work,

Sangita Dey, B. V. Rathish Kumar

A theoretical and computational finite element study of modified Navier-Stokes Equations coupled with energy conservation governing the flow and heat transfer in complex domains with hybrid nanofluid$(HNF)$ is carried out. The apriori error estimates providing the convergence analysis for the finite element scheme is derived in the $H^1$ norm. A detailed par

Panagiotis Mougkogiannis, Andrew Adamatzky

Proteinoids, or thermal proteins, are produced by heating amino acids to their melting point and initiation of polymerisation to produce polymeric chains. In aqueous solutions proteinoids swell into hollow microspheres. These microspheres produce endogenous burst of electrical potential spikes and change patterns of their electrical activity in response to i

Raghav Singhal, Sailen Dutta, Jiten C. Kalita

In this paper we carry out a numerical investigation of forced convection heat transfer from a heated elliptical cylinder in a uniform free stream with angle of inclination $\theta^{\circ}$. Numerical simulations were carried out for $10 \leq Re \leq 120$, $0^{\circ} \leq \theta \leq 180^{\circ}$, and $Pr = 0.71$. Results are reported for both steady and uns

Yuting Gao, Jinfeng Liu, Zihan Xu, Tong Wu Enwei Zhang

During the preceding biennium, vision-language pre-training has achieved noteworthy success on several downstream tasks. Nevertheless, acquiring high-quality image-text pairs, where the pairs are entirely exclusive of each other, remains a challenging task, and noise exists in the commonly used datasets. To address this issue, we propose SoftCLIP, a novel ap

Yuanfeng Ji, Zhe Chen, Enze Xie, Lanqing Hong

We propose a simple, efficient, yet powerful framework for dense visual predictions based on the conditional diffusion pipeline. Our approach follows a "noise-to-map" generative paradigm for prediction by progressively removing noise from a random Gaussian distribution, guided by the image. The method, called DDP, efficiently extends the denoising diffusion

A. Emin Orhan

The training of modern large language models (LLMs) takes place in a regime where most training examples are seen only a few times by the model during the course of training. What does a model remember about such examples seen only a few times during training and how long does that memory persist in the face of continuous training with new examples? Here, we

Aaron L Putterman, Edward Pyne

We introduce a novel family of expander-based error correcting codes. These codes can be sampled with randomness linear in the block-length, and achieve list-decoding capacity (among other local properties). Our expander-based codes can be made starting from any family of sufficiently low-bias codes, and as a consequence, we give the first construction of a

Junyeong Ahn, Barun Ghosh

Uncovering the physical contents of the nontrivial topology of quantum states is a critical problem in condensed matter physics. Here, we study the topological circular dichroism in chiral semimetals using linear response theory and first-principles calculations. We show that, when the low-energy spectrum respects emergent SO(3) rotational symmetry, topologi

D. Jackson, R. Bufalo

In this study, we investigate the growth of structures within the Deser-Woodard nonlocal theory and extend it to various bouncing cosmology scenarios. Our findings show that the observable structure growth rate, $f\sigma_8$, in a vacuum-dominated universe is finite within the redshift range of $0<z<2$, contrary to previous literature. Although $f\sigma_8$ ex

Adam Lechowicz, Nicolas Christianson, Jinhang Zuo, Noman Bashir

We introduce and study the online pause and resume problem. In this problem, a player attempts to find the $k$ lowest (alternatively, highest) prices in a sequence of fixed length $T$, which is revealed sequentially. At each time step, the player is presented with a price and decides whether to accept or reject it. The player incurs a switching cost whenever

Chenpeng Du, Qi Chen, Tianyu He, Xu Tan

While recent research has made significant progress in speech-driven talking face generation, the quality of the generated video still lags behind that of real recordings. One reason for this is the use of handcrafted intermediate representations like facial landmarks and 3DMM coefficients, which are designed based on human knowledge and are insufficient to

Vahid Jannessary, Fatemeh Rezazadeh, Sadegh Raeisi, Vahid Karimipour

Having common reference frames or aligned coordinate systems, is one of the presumptions in witnessing entanglement in a two-party state possessed by two remote parties. This assumption may fail for many reasons. With an unlimited supply of singlet states, the two parties can first align their coordinate systems and then measure any entanglement witness. In

Shibani Santurkar, Esin Durmus, Faisal Ladhak, Cinoo Lee

Language models (LMs) are increasingly being used in open-ended contexts, where the opinions reflected by LMs in response to subjective queries can have a profound impact, both on user satisfaction, as well as shaping the views of society at large. In this work, we put forth a quantitative framework to investigate the opinions reflected by LMs -- by leveragi

C. A. Büsser

In recent years, silicene, germanene, and stanene have received considerable attention due to their possibilities to show a spin Hall effect. Nanoribbons made of these materials are expected to have topologically protected states. In this work, we study the electronic properties of nanotubes made of Si, Ge, Sn, and functionalized Sn. The main difference betw

Vidit Goel, Elia Peruzzo, Yifan Jiang, Dejia Xu

Generative image editing has recently witnessed extremely fast-paced growth. Some works use high-level conditioning such as text, while others use low-level conditioning. Nevertheless, most of them lack fine-grained control over the properties of the different objects present in the image, i.e. object-level image editing. In this work, we tackle the task by

Zi-Qing Xia, Tian-Peng Tang, Xiaoyuan Huang, Qiang Yuan

Ultralight dark matter (ULDM) is proposed as a theoretical candidate of dark matter particles with masses of approximately $10^{-22}$ eV. The interactions between ULDM particles and standard model particles would cause variations in pulse arrival times of millisecond pulsars, which means that the pulsar timing array (PTA) can be used to indirectly detect ULD

Afonso Vilalonga, João S. Resende, Henrique Domingos

Anonymity networks like Tor significantly enhance online privacy but are vulnerable to correlation attacks by state-level adversaries. While covert channels encapsulated in media protocols, particularly WebRTC-based encapsulation, have demonstrated effectiveness against passive traffic correlation attacks, their resilience against active correlation attacks

Jyotish Robin, Elza Erkip

Reliable and prompt identification of active users is critical for enabling random access in massive machine-to-machine type networks which typically operate within stringent access delay and energy constraints. In this paper, an energy efficient active user identification protocol is envisioned in which the active users simultaneously transmit On-Off Keying

C. A. Büsser

We investigate the entanglement between the spins of two quantum dots that are not connected at once to the same system. Quantum entanglement between localized spins is an essential property for the development of quantum computing and quantum information. It is for this reason that generating and controlling an entangled state between quantum dots received

Felix Bartel, Fabian Taubert

In this paper we approximate high-dimensional functions $f\colon\mathbb T^d\to\mathbb C$ by sparse trigonometric polynomials based on function evaluations. Recently it was shown that a dimension-incremental sparse Fourier transform (SFT) approach does not require the signal to be exactly sparse and is applicable in this setting. We combine this approach with

Huayue Gu, Ruozhou Yu, Zhouyu Li, Xiaojian Wang

Quantum entanglement distribution between remote nodes is key to many promising quantum applications. Existing mechanisms have mainly focused on improving throughput and fidelity via entanglement routing or single-node scheduling. This paper considers entanglement scheduling and distribution among many source-destination pairs with different requests over an

A. P. Majtey, A. Valdés-Hernández, E. Cuestas

The study of entanglement in systems composed of identical particles raises interesting challenges with far-reaching implications in both, our fundamental understanding of the physics of composite quantum systems, and our capability of exploiting quantum indistinguishability as a resource in quantum information theory. Impressive theoretical and experimental

Marcin Kotowski, Michał Oszmaniec, Michał Horodecki

We investigate circuit complexity of unitaries generated by time evolution of randomly chosen strongly interacting Hamiltonians in finite dimensional Hilbert spaces. Specifically, we focus on two ensembles of random generators -- the so called Gaussian Unitary Ensemble (GUE) and the ensemble of diagonal Gaussian matrices conjugated by Haar random unitary tra

Julia Lindberg, Pierpaola Santarsiero

Inspired by recent work of Kopparty-Moshkovitz-Zuiddam and motivated by problems in combinatorics and hypergraphs, we introduce the notion of the symmetric geometric rank of a symmetric tensor. This quantity is equal to the codimension of the singular locus of the hypersurface associated to the tensor. We first derive fundamental properties of the symmetric

Quentin Henry, François Larrouturou, Christophe Le Poncin-Lafitte

Galactic binaries, and notably double white dwarfs systems, will be a prominent source for the future LISA and Einstein Telescope detectors. Contrarily to the black holes observed by the current LIGO-Virgo-KAGRA network, such objects bear intense magnetic fields, that are naturally expected to leave some imprints on the gravitational wave emission. The purpo

Agniva Roy, D Yogeshwaran

We consider the random clique complex process - the process of clique complexes induced by the complete graph with i.i.d. Uniform edge weights. We investigate the evolution of the Betti numbers of the clique complex process in the critical window and in particular, show a process-level convergence of the Betti numbers to a Poisson process. Our proof techniqu

Matija Tapušković

In the first part of this paper we study the coaction dual to the action of the cosmic Galois group on the motivic lift of the sunrise Feynman integral with generic masses and momenta, and we express its conjugates in terms of motivic lifts of Feynman integrals associated to related Feynman graphs. Only one of the conjugates of the motivic lift of the sunris

R. Bruschini

Heavy-quark spin symmetry is explicitly broken by the mass splitting between a heavy-light pseudoscalar meson and its vector partner. This fact plays a pivotal role in the physics of states whose mass lies close to the threshold of an open-flavor meson pair, like $X(3872)$. We show that this source of heavy-quark spin symmetry breaking can be systematically

Yossathorn Tawabutr

A small-$x$ helicity evolution has been derived in 2016-18 and received an important modification in 2022. This article discusses its general framework and summarizes the recent theoretical developments, including the asymptotic behaviors of helicity PDFs and $g_1$ structure function at small $x$. The latest fits to various polarized scattering data are also

Ori Linial, Alon Shoshan, Nadav Bhonker, Elad Hirsch

The asymmetrical retrieval setting is a well suited solution for resource constrained applications such as face recognition and image retrieval. In this setting, a large model is used for indexing the gallery while a lightweight model is used for querying. The key principle in such systems is ensuring that both models share the same embedding space. Most met

Novak Boškov, Ari Trachtenberg, David Starobinski

The problem of data synchronization arises in networked applications that require some measure of consistency. Indeed data synchronization approaches have demonstrated a significant potential for improving performance in various applications ranging from distributed ledgers to fog-enabled storage offloading for IoT. Although several protocols for data sets s

Maine Christos, Subir Sachdev, Mathias S. Scheurer

The superconducting state and mechanism are among the least understood phenomena in twisted graphene systems. For instance, recent tunneling experiments indicate a transition between nodal and gapped pairing with electron filling, which is not naturally understood within current theory. We demonstrate that the coexistence of superconductivity and flavor pola

Hela Ladjimi, Michał Tomza

We study the energetics of chemical reactions between ultracold ground-state alkaline-earth-metal diatomic molecules. We show that the atom-exchange reactions forming homonuclear dimers are energetically allowed for all heteronuclear alkaline-earth-metal combinations. We perform high-level electronic structure calculations on the potential energy surfaces of

Hela Ladjimi, Michał Tomza

Ultracold diatomic molecules find application in quantum studies ranging from controlled chemistry and precision measurement physics to quantum many-body simulation and potentially quantum computing. Accurate knowledge of molecular properties is required to guide and explain ongoing experiments. Here, in an extensive and comparative study, we theoretically i

Wenqiao Zhang, Changshuo Liu, Can Cui, Beng Chin Ooi

Semi-supervised domain adaptation (SSDA) adapts a learner to a new domain by effectively utilizing source domain data and a few labeled target samples. It is a practical yet under-investigated research topic. In this paper, we analyze the SSDA problem from two perspectives that have previously been overlooked, and correspondingly decompose it into two \emph{

Zekai Chen, Min Sha, Chen Wei

In this paper, as an analogue of the integer case, we study detailedly the period and the rank of the generalized Fibonacci sequence of polynomials over a finite field modulo an arbitrary polynomial. We establish some formulas to compute them, and we also obtain some properties about the quotient of the period and the rank. We find that the polynomial case i

Ruizhong Wei

Cover-free families were considered from different subjects by numerous researchers. Recently, cover-free families are also found useful in cryptography. In this paper, we use an uniform method to survey known results of cover-free families. Many old results are updated or generalized. Some new results are also given.

Yikai Mao, Shaswot Shresthamali, Masaaki Kondo

The fidelity of quantum circuits (QC) is influenced by several factors, including hardware characteristics, calibration status, and the transpilation process, all of which impact their susceptibility to noise. However, existing methods struggle to estimate and compare the noise performance of different circuit layouts due to fluctuating error rates and the a

Melody Merle, Leah Friedman, Corinne Chureau, Armin Shoushtarizadeh

Gene expression is inherently noisy, posing a challenge to understanding how precise and reproducible patterns of gene expression emerge in mammals. We investigate this phenomenon using gastruloids, an in vitro model for early mammalian development. Our study reveals intrinsic reproducibility in the self-organization of gastruloids, encompassing growth dynam

Shintaro Suzuki

We consider an independent and identically distributed (i.i.d.) random dynamical system of simple linear transformations on the unit interval $T_{\beta}(x)=\beta x$ (mod $1$), $x\in[0,1]$, $\beta>0$, which are the so-called beta-transformations. For such a random dynamical system, including the case that it is generated by uncountably many maps, we give an e

Mahak Bhatia, Aled Williams

With increases in population, there is a noticeable change across the world in pollution levels. Recently there has been growing demand for renewable energy operated devices boomed. Numerous reasons have led to such growth including lower operating costs and reduced greenhouse gas emissions. In order to obtain the optimised output, it is required to consider

Haleh Hayati, Nathan van de Wouw, Carlos Murguia

We address the problem of synthesizing distorting mechanisms that maximize infinite horizon privacy for Networked Control Systems (NCSs). We consider stochastic LTI systems where information about the system state is obtained through noisy sensor measurements and transmitted to a (possibly adversarial) remote station via unsecured/public communication networ

Chun Huang, Geert Raaijmakers, Anna L. Watts, Laura Tolos

Measurements of neutron star mass and radius or tidal deformability deliver unique insight into the equation of state (EOS) of cold dense matter. EOS inference is very often done using generalized parametric or non-parametric models which deliver no information on composition. In this paper we consider a microscopic nuclear EOS model based on a field theoret

Hyeonggon Ryu, Arda Senocak, In So Kweon, Joon Son Chung

The objective of this work is to explore the learning of visually grounded speech models (VGS) from multilingual perspective. Bilingual VGS models are generally trained with an equal number of spoken captions from both languages. However, in reality, there can be an imbalance among the languages for the available spoken captions. Our key contribution in this

L. Filipe O. Costa, José Natário, F. Frutos-Alfaro, Michael Soffel

The physical interpretation of the exact solutions of the Einstein field equations is, in general, a challenging task, part of the difficulties lying in the significance of the coordinate system. We discuss the extension of the International Astronomical Union (IAU) reference system to the exact theory. It is seen that such an extension, retaining some of it

Ming Zhang, Jie Jiang

Setting the cosmological constant to be dynamical, we study the bulk and boundary thermodynamics of charged Anti-de Sitter black holes. We develop mass/energy formulas in terms of thermodynamic state functions for the extended thermodynamics, mixed thermodynamics, and boundary conformal field theory thermodynamics. We employ the residue method to study the t

Zishuo Li, Anh Tung Nguyen, André Teixeira, Yilin Mo

This paper proposes a secure state estimation scheme with non-periodic asynchronous measurements for linear continuous-time systems under false data attacks on the measurement transmit channel. After sampling the output of the system, a sensor transmits the measurement information in a triple composed of sensor index, time-stamp, and measurement value to the

Georgios D. Chondrogiannis, Nikos A. Mitsiou, Nestor D. Chatzidiamantis, Alexandros-Apostolos A. Boulogeorgos

This paper investigates the usage of hybrid automatic repeat request (HARQ) protocols for power-efficient and reliable communications over free space optical (FSO) links. By exploiting the large coherence time of the FSO channel, the proposed transmission schemes combat turbulence-induced fading by retransmitting the failed packets in the same coherence inte

Noel Murasko, John C. Bowman

Efficient algorithms for computing linear convolutions based on the fast Fourier transform are developed. A hybrid approach is described that combines the conventional practice of explicit dealiasing (explicitly padding the input data with zeros) and implicit dealiasing (mathematically accounting for these zero values). The new approach generalizes implicit

Tailia Malloy, Miao Liu, Matthew D. Riemer, Tim Klinger

Humans learn quickly even in tasks that contain complex visual information. This is due in part to the efficient formation of compressed representations of visual information, allowing for better generalization and robustness. However, compressed representations alone are insufficient for explaining the high speed of human learning. Reinforcement learning (R

Saronath Halder, Alexander Streltsov

In this work, we explore the notions unextendible product basis and uncompletability for operators which remain positive under partial transpose. Then, we analyze their connections to the ensembles which are many-copy indistinguishable under local operations and classical communication (LOCC). We show that the orthogonal complement of any bipartite pure enta

Chris Jones, Aaron Potechin, Goutham Rajendran, Jeff Xu

Given a graph and an integer $k$, Densest $k$-Subgraph is the algorithmic task of finding the subgraph on $k$ vertices with the maximum number of edges. This is a fundamental problem that has been subject to intense study for decades, with applications spanning a wide variety of fields. The state-of-the-art algorithm is an $O(n^{1/4 + \epsilon})$-factor appr

Shaohui Liu, Yifan Yu, Rémi Pautrat, Marc Pollefeys

In contrast to sparse keypoints, a handful of line segments can concisely encode the high-level scene layout, as they often delineate the main structural elements. In addition to offering strong geometric cues, they are also omnipresent in urban landscapes and indoor scenes. Despite their apparent advantages, current line-based reconstruction methods are far

Louisa Smieska, Mary Lou Guerinot, Karin Olson Hoal, Matthew Reid

The movement of metals through the environment links together a wide range of scientific fields: from earth sciences and geology as weathering releases minerals; to environmental sciences as metals are mobilized and transformed, cycling through soil and water; to biology as living things take up metals from their surroundings. Studies of these fundamental pr

J. Vallejo Bustamante, R. Ribeiro-Palau, C. Fermon, M. Pannetier-Lecoeur K. Watanabe

The recent detection of the singular diamagnetism of Dirac electrons in a single graphene layer paved a new way of probing 2D quantum materials through the measurement of equilibrium orbital currents which cannot be accessed in usual transport experiments. Among the theoretical predictions is an intriguing orbital paramagnetism at saddle points of the disper

Shashank Tripathi, Volker Skwarek

With the rising numbers for IoT objects, it is becoming easier to penetrate counterfeit objects into the mainstream market by adversaries. Such infiltration of bogus products can be addressed with third-party-verifiable identification. Generally, state-of-the-art identification schemes do not guarantee that an identifier e.g. barcodes or RFID itself cannot b

Joseph R. L. Cousins, Akhshay S. Bhadwal, Lindsey T. Corson, Brian R. Duffy

A theoretical investigation of weak-anchoring effects in a thin two-dimensional pinned static ridge of nematic liquid crystal resting on a flat solid substrate in an atmosphere of passive gas is performed. Specifically, we solve a reduced version of the general system of governing equations recently derived by Cousins et al. [Proc. Roy. Soc. A}, 478(2259):20

Laurent Freidel, Jerzy Kowalski-Glikman, Robert G. Leigh, Djordje Minic

In this essay, we present a new understanding of the cosmological constant problem, built upon the realization that the vacuum energy density can be expressed in terms of a phase space volume. We introduce a UV-IR regularization which implies a relationship between the vacuum energy and entropy. Combining this insight with the holographic bound on entropy th

Etienne Granet

We consider the 1D Tonks-Girardeau gas with a space-dependent potential out of equilibrium. We derive the exact dynamics of the system when divided into $n$ boxes and decomposed into energy eigenstates within each box. It is a representation of the wave function that is mixed between real space and momentum space, whose basis elements are plane waves localiz

Davide Stirpe, Juuso Manninen, Francesco Massel

We study here the semiclassical dynamics of a superconducting circuit constituted by two Josephson junctions in series, in the presence of a voltage bias. We derive the equations of motion for the circuit through a Hamiltonian description of the problem, considering the voltage sources as semi-holonomic constraints. We find that the dynamics of the system co

Geunwoo Kim, Pierre Baldi, Stephen McAleer

Agents capable of carrying out general tasks on a computer can improve efficiency and productivity by automating repetitive tasks and assisting in complex problem-solving. Ideally, such agents should be able to solve new computer tasks presented to them through natural language commands. However, previous approaches to this problem require large amounts of e

Kim Sung-Bin, Arda Senocak, Hyunwoo Ha, Andrew Owens

How does audio describe the world around us? In this paper, we propose a method for generating an image of a scene from sound. Our method addresses the challenges of dealing with the large gaps that often exist between sight and sound. We design a model that works by scheduling the learning procedure of each model component to associate audio-visual modaliti

Minkyu Kim, Kim Sung-Bin, Tae-Hyun Oh

Audio captioning aims to generate text descriptions from environmental sounds. One challenge of audio captioning is the difficulty of the generalization due to the lack of audio-text paired training data. In this work, we propose a simple yet effective method of dealing with small-scaled datasets by leveraging a pre-trained language model. We keep the langua

G. C. Jones, R. Maiolino, S. Carniani, C. Circosta

While observations of molecular gas at cosmic noon and beyond have focused on the gas within galaxies (i.e., the interstellar medium; ISM), it is also crucial to study the molecular gas reservoirs surrounding each galaxy (i.e., in the circumgalactic medium; CGM). Recent observations of galaxies and quasars hosts at high redshift (z>2) have revealed evidence

Ping Sun, Ze-Chun Hu, Wei Sun

Motivated by Chv\'{a}tal's conjecture and Tomaszewaki's conjecture, we investigate the extreme value problem of two probability functions for the Gamma distribution. Let $\alpha,\beta$ be arbitrary positive real numbers and $X_{\alpha,\beta}$ be a Gamma random variable with shape parameter $\alpha$ and scale parameter $\beta$. We study the extreme values of

Bjorn H. C. Emonts, Matthew D. Lehnert, Ilsang Yoon, Nir Mandelker

The growth of galaxies in the early Universe is driven by accretion of circum- and inter-galactic gas. Simulations predict that steady streams of cold gas penetrate the dark matter halos of galaxies, providing the raw material necessary to sustain star formation. We report a filamentary stream of gas that extends for 100 kiloparsecs and connects to the massi

Christian Hegeler, Filippo Rozzi, Loris Roveda, Kevin Haninger

Contact-rich manipulation involves kinematic constraints on the task motion, typically with discrete transitions between these constraints during the task. Allowing the robot to detect and reason about these contact constraints can support robust and dynamic manipulation, but how can these contact models be efficiently learned? Purely visual observations are