February 2024 arXiv papers — page 36

Vicente Cortés, Alejandro Gil-García, Danu Thung

Q-map spaces form an important class of quaternionic K\"ahler manifolds of negative scalar curvature. Their one-loop deformations are always inhomogeneous and have been used to construct cohomogeneity one quaternionic K\"ahler manifolds as deformations of homogeneous spaces. Here we study the group of isometries in the deformed case. Our main result is the s

Kimya Fallah, Shahab Norouzian Alam, Bijan Ghafary Ghomi, Farzaneh Yekekar

We introduce a pioneering strategy to enhance the environmental stability of perovskite thin films, a critical step forward in advancing their application in optoelectronics. Through the innovative application of matrix encapsulation techniques, we focus on the stabilization of methylammonium lead iodide (MAPbI3) and methylammonium lead bromide (MAPbBr3) fil

Marek Lassak

For a hyperplane $H$ supporting a convex body $C$ in the hyperbolic space $\mathbb{H}^d$ we define the width of $C$ determined by $H$ as the distance between $H$ and a most distant ultraparallel hyperplane supporting $C$. The thickness (i.e., the minimum width) of $C$ is denoted by $\Delta(C)$. A convex body $R \subset \mathbb{H}^d$ is called reduced if for

O. A. Naranjo-Montoya, M. Bridger, R. Bhar, L. Kalkhoff

We present a table-top setup for femtosecond x-ray absorption spectroscopy based on high harmonic generation (HHG) in noble gases. Using sub-millijoule pump pulses at a central wavelength of 1550 nm broadband HHG in the range 70 to 350 eV was demonstrated. The HHG coherence lengths of several millimeters were achieved by reaching the nonadiabatic regime of h

Arnav Mishra, Aditi Shetkar, Ganesh M. Bapat, Rajdeep Ojha

Recent technological advancements in artificial intelligence and computer vision have enabled gait analysis on portable devices such as cell phones. However, most state-of-the-art vision-based systems still impose numerous constraints for capturing a patient's video, such as using a static camera and maintaining a specific distance from it. While these const

Xiao Chen, Quanyi Li, Tai Wang, Tianfan Xue

While recent advances in neural radiance field enable realistic digitization for large-scale scenes, the image-capturing process is still time-consuming and labor-intensive. Previous works attempt to automate this process using the Next-Best-View (NBV) policy for active 3D reconstruction. However, the existing NBV policies heavily rely on hand-crafted criter

Rajarshi Roy Chowdhury, Debashish Roy, Pg Emeroylariffion Abas

Internet of Things (IoT) is one of the technological advancements of the twenty-first century which can improve living standards. However, it also imposes new types of security challenges, including device authentication, traffic types classification, and malicious traffic identification, in the network domain. Traditionally, internet protocol (IP) and media

Tomer Hadad, Barak Kol, Michael Smolkin

We determine the gravito-magnetic Love numbers of non-rotating black holes in all spacetime dimensions through a novel and direct derivation. The Ishibashi- Kodama master field and its associated field equation are avoided. The matching to the EFT variables is simple. This method allows us to correct the values in the literature. Moreover, we highlight a par

José Espírito Santo, Gilda Ferreira

Since the observation in 2006 that it is possible to embed IPC into the atomic polymorphic lambda-calculus (a predicative fragment of system F with universal instantiations restricted to atomic formulas) different such embeddings appeared in the literature. All of them comprise the Russell-Prawitz translation of formulas, but have different strategies for th

Aleksandra Gorzkowska, Jakub Kwaśny

A distinguishing index of a (di)graph is the minimum number of colours in an edge (or arc) colouring such that the identity is the only automorphism that preserves that colouring. We investigate the minimum and maximum value of the distinguishing index over all orientations of a given graph $G$. We present sharp results for these parameters in terms of the d

Avik Pal, Madhura Pawar

Structural probes learn a linear transformation to find how dependency trees are embedded in the hidden states of language models. This simple design may not allow for full exploitation of the structure of the encoded information. Hence, to investigate the structure of the encoded information to its full extent, we incorporate non-linear structural probes. W

Manuel Krannich, Alexander Kupers

This note serves to record examples of diffeomorphisms of closed smooth $4$-manifolds $X$ that are homotopic but not pseudoisotopic to the identity, and to explain why there are no such examples when $X$ is orientable and its fundamental group is a free group.

Zhipeng Ma, Zheyan Tu, Xinhai Chen, Yan Zhang

Trajectory representation learning plays a pivotal role in supporting various downstream tasks. Traditional methods in order to filter the noise in GPS trajectories tend to focus on routing-based methods used to simplify the trajectories. However, this approach ignores the motion details contained in the GPS data, limiting the representation capability of tr

Hiroki Ishizaka

The purpose is to make an easy-to-understand note of "Special Topics in Finite Element Methods." There might be typos and mistakes. Therefore, I do not take any responsibility for unauthorised use.

Nguyen Thu Hang, Thanh Vu

We compute the projective dimension and regularity of $3$-path ideals of arbitrary graphs with at most one cycle.

Szilard Enyedi

Medical imaging is a very useful tool in healthcare, various technologies being employed to non-invasively peek inside the human body. Deep learning with neural networks in radiology was welcome - albeit cautiously - by the radiologist community. Most of the currently deployed or researched deep learning solutions are applied on already generated images of m

Chenying Liu, Conrad M Albrecht, Yi Wang, Xiao Xiang Zhu

Compared to supervised deep learning, self-supervision provides remote sensing a tool to reduce the amount of exact, human-crafted geospatial annotations. While image-level information for unsupervised pretraining efficiently works for various classification downstream tasks, the performance on pixel-level semantic segmentation lags behind in terms of model

Mario Novello, Júnior D. Toniato

In the general relativity theory the basic ingredient to describe gravity is the geometry, which interacts with all forms of matter and energy, and as such, the metric could be interpreted as a true physical quantity. However the metric is not matter nor energy, but instead it is a new dynamical variable that Einstein introduced to describe gravity. In order

Devansh Jalota, Matthew Tsao, Marco Pavone

Artificial currencies have grown in popularity in many real-world resource allocation settings, gaining traction in government benefits programs like food assistance and transit benefits programs. However, such programs are susceptible to misreporting fraud, wherein users can misreport their private attributes to gain access to more artificial currency (cred

Xirui Li, Ruochen Wang, Minhao Cheng, Tianyi Zhou

The safety alignment of Large Language Models (LLMs) is vulnerable to both manual and automated jailbreak attacks, which adversarially trigger LLMs to output harmful content. However, current methods for jailbreaking LLMs, which nest entire harmful prompts, are not effective at concealing malicious intent and can be easily identified and rejected by well-ali

Xinrui Zhu, Yaowen Hu, Shengyuan Lu, Hana K. Warner

The recent emergence of thin-film lithium niobate (TFLN) has extended the landscape of integrated photonics. This has been enabled by the commercialization of TFLN wafers and advanced nanofabrication of TFLN such as high-quality dry etching. However, fabrication imperfections still limit the propagation loss to a few dB/m, restricting the impact of this plat

Ghania Guettai, Diffalah Laissaoui, Mourad Rahmani

This paper sets out to introduce the generalized derangement polynomials of order $r $. It then proceeds to establish various identities associated with these polynomials, along with providing recurrence relations for derangement polynomials of order $ r$. Additionally, the paper offers a probabilistic approach for the generalized derangement polynomials of

Somnath Banerjee, Avik Dutta, Aaditya Agrawal, Rima Hazra

With the AI revolution in place, the trend for building automated systems to support professionals in different domains such as the open source software systems, healthcare systems, banking systems, transportation systems and many others have become increasingly prominent. A crucial requirement in the automation of support tools for such systems is the early

Shiyi Qi, Zenglin Xu, Yiduo Li, Liangjian Wen

Recent advancements in deep learning have led to the development of various models for long-term multivariate time-series forecasting (LMTF), many of which have shown promising results. Generally, the focus has been on historical-value-based models, which rely on past observations to predict future series. Notably, a new trend has emerged with time-index-bas

Qichuan Yin, Zexian Wang, Junzhou Huang, Huaxiu Yao

As federated learning gains increasing importance in real-world applications due to its capacity for decentralized data training, addressing fairness concerns across demographic groups becomes critically important. However, most existing machine learning algorithms for ensuring fairness are designed for centralized data environments and generally require lar

Horia Magureanu, Naïri Usher

The widespread adoption of large-scale machine learning models in recent years highlights the need for distributed computing for efficiency and scalability. This work introduces a novel distributed machine learning paradigm -- \emph{consensus learning} -- which combines classical ensemble methods with consensus protocols deployed in peer-to-peer systems. The

Tien Ngoc Ha, Daniel Romero, Roberto López-Valcarce

Next generation communication systems require accurate beam alignment to counteract the impairments that characterize propagation in high-frequency bands. The overhead of the pilot sequences required to select the best beam pair is prohibitive when codebooks contain a large number of beams, as is the case in practice. To remedy this issue, some schemes explo

Yanyong Hong, Chengming Bai, Li Guo

Generalizing S. Gelfand's classical construction of a Novikov algebra from a commutative differential algebra, a deformation family $(A,\circ_q)$, for scalars $q$, of Novikov algebras is constructed from what we call an admissible commutative differential algebra, by adding a second linear operator to the commutative differential algebra with certain admissi

Chaoyu Zhang, Shaoyu Li

This paper examines the evolving landscape of machine learning (ML) and its profound impact across various sectors, with a special focus on the emerging field of Privacy-preserving Machine Learning (PPML). As ML applications become increasingly integral to industries like telecommunications, financial technology, and surveillance, they raise significant priv

Yeping Wang, Carter Sifferman, Michael Gleicher

Many applications require a robot to accurately track reference end-effector trajectories. Certain trajectories may not be tracked as single, continuous paths due to the robot's kinematic constraints or obstacles elsewhere in the environment. In this situation, it becomes necessary to divide the trajectory into shorter segments. Each such division introduces

Narongkiat Rodphai, Zhimin Wang

The Jiangmen Underground Neutrino Observatory (JUNO) is a neutrino detection experiment characterized by an acrylic sphere, measuring 35.4 m in diameter, containing 20,000 tons of liquid scintillator. This sphere is encompassed by as many as 17,600 photomultiplier tubes (PMTs) with a 20-inch diameter, achieving an overall coverage of 77.9%. With these impres

Ruibin Yuan, Hanfeng Lin, Yi Wang, Zeyue Tian

While Large Language Models (LLMs) demonstrate impressive capabilities in text generation, we find that their ability has yet to be generalized to music, humanity's creative language. We introduce ChatMusician, an open-source LLM that integrates intrinsic musical abilities. It is based on continual pre-training and finetuning LLaMA2 on a text-compatible musi

Peter Adshead, John T. Giblin, Avery Tishue

We study gravitational wave production during kinetic preheating after inflation with a focus on scenarios that arise in $\alpha$-attractor models where a scalar dilaton-like inflaton is kinetically coupled to a second scalar field. We present high-resolution lattice simulations of three $\alpha$-attractor models for a range of parameters to probe regions wh

Masahito Uwamichi, He Li, Zihui Zhao, Yisong Yao

Cell alignment often forms nematic order, which can lead to anomalous collective cell flow due to the so-called active force. Although it is appreciated that cell migration is driven by traction force, a quantitative evaluation of the relationships between the traction force, the nematic patterning, and the cell flow velocity is still elusive. Here we have f

Lucas Bueri, Radu Iosif, Florian Zuleger

A class of graph languages is definable in Monadic Second-Order logic (MSO) if and only if it consists of sets of models of MSO formul{\ae}. If, moreover, there is a computable bound on the tree-widths of the graphs in each such set, the satisfiability and entailment problems are decidable, by Courcelle's Theorem. This motivates the comparison of other graph

Louise C. Head, Giuseppe Negro, Livio N. Carenza, Ryan R. Keogh

Quasiparticles are low-energy excitations with important roles in condensed matter physics. An intriguing example is provided by Majorana fermions, quasiparticles which are identical to their antiparticles. Despite being implicated in neutrino oscillations and topological superconductivity, their experimental realisations remain scarce. Here we propose a pur

Tomoki Yuji

In the present paper, we prove that a topological space admits a functorial Lindel\"ofification if and only if its realcompactification is Lindel\"of. To investigate the functorial Lindel\"ofifiability of a topological space, for each topological property $\mathsf{P}$, we introduce the notion of "functorial $\mathsf{P}$-ification" and give an explicit constr

Francesca De Falco, Andrea Ceschini, Alessandro Sebastianelli, Bertrand Le Saux

In this paper, we propose a new methodology to design quantum hybrid diffusion models, derived from classical U-Nets with ResNet and Attention layers. Specifically, we propose two possible different hybridization schemes combining quantum computing's superior generalization with classical networks' modularity. In the first one, we acted at the vertex: ResNet

Samia Bashir, Amjad Hussain

This paper showed that fractional p-adic Hardy operator norms in p-adic Herz-Morrey spaces with varying exponents are bounded. Corresponding commutator operators are also estimated for p-adic variable central bounded mean oscillations (CBMO).

Karen Frilya Celine, Muhammad Ayaz Dzulfikar, Ivan Adrian Koswara

In the context of fair division, the concept of price of fairness has been introduced to quantify the loss of welfare when we have to satisfy some fairness condition. In other words, it is the price we have to pay to guarantee fairness. Various settings of fair division have been considered previously; we extend to the setting of indivisible goods by using e

Cheng Cheng, Sovan Das, Stefan Videv, Adrian Spark

In this paper, we demonstrate the communication capabilities of light-fidelity (LiFi) systems based on highbrightness and high-bandwidth integrated laser-based sources in a surface mount device (SMD) packaging platform. The laserbased source is able to deliver 450 lumens of white light illumination and the resultant light brightness is over 1000 cd mm2. It i

Hongda Jiang, Xi Wang, Marc Christie, Libin Liu

Designing effective camera trajectories in virtual 3D environments is a challenging task even for experienced animators. Despite an elaborate film grammar, forged through years of experience, that enables the specification of camera motions through cinematographic properties (framing, shots sizes, angles, motions), there are endless possibilities in deciding

Pravneet Kaur, Gautam Siddharth Kashyap, Ankit Kumar, Md Tabrez Nafis

This groundbreaking study explores the expanse of Large Language Models (LLMs), such as Generative Pre-Trained Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT) across varied domains ranging from technology, finance, healthcare to education. Despite their established prowess in Natural Language Processing (NLP), these LLMs

Vedant Tapiavala, Joshua Piesner, Sourjyamoy Barman, Feng Fu

Live performances of music are always charming, with the unpredictability of improvisation due to the dynamic between musicians and interactions with the audience. Jazz improvisation is a particularly noteworthy example for further investigation from a theoretical perspective. Here, we introduce a novel mathematical game theory model for jazz improvisation,

João Vitorino, Miguel Silva, Eva Maia, Isabel Praça

As cyber-attacks become more sophisticated, improving the robustness of Machine Learning (ML) models must be a priority for enterprises of all sizes. To reliably compare the robustness of different ML models for cyber-attack detection in enterprise computer networks, they must be evaluated in standardized conditions. This work presents a methodical adversari

Xiangdi Meng, Damai Dai, Weiyao Luo, Zhe Yang

Supervised fine-tuning is the most common method to adapt large language models (LLMs) to downstream tasks, but full fine-tuning LLMs requires massive computational resources. Recently, parameter-efficient fine-tuning (PEFT) methods have been widely studied due to its cost-effectiveness. LoRA is one of the most widely used methods, which assumes that the opt

Shanuja Sasi, Onur Günlü, B. Sundar Rajan

A novel distributed computing model called "Multi-access Distributed Computing (MADC)" was recently introduced in http://www.arXiv:2206.12851. In this paper, we represent MADC models via 2-layered bipartite graphs called Map-Reduce Graphs (MRGs) and a set of arrays called Map-Reduce Arrays (MRAs) inspired from the Placement Delivery Arrays (PDAs) used in the

Antonio San Martín

This paper examines the impact of Generative Artificial Intelligence (GenAI) tools like ChatGPT on the creation and consumption of terminological definitions. From the terminologist's point of view, the strategic use of GenAI tools can streamline the process of crafting definitions, reducing both time and effort, while potentially enhancing quality. GenAI to

Zhipeng Huang, Tobias Roos, Yujin Tong, R. Kramer Campen

Experimental insight into the elementary processes underlying charge transfer across interfaces has blossomed with the wide-spread availability of ultra-high vacuum set-ups that allow the preparation and characterization of solid surfaces with well-defined molecular adsorbates over a wide ranges of temperatures. Thick layers of molecular adsorbates or hetero

Kuan-Nan Lin, Evgenii Ievlev, Michael R. R. Good, Pisin Chen

We investigate the radiation from accelerating electrons with asymptotic constant velocity and their analog signatures as evaporating black holes with left-over remnants. We find high-speed electrons, while having a high temperature, correspond to low-temperature analog remnants.

Samuel L. Braunstein, Mir Faizal, Lawrence M. Krauss, Francesco Marino

The recent technological advances in controlling and manipulating fluids have enabled the experimental realization of acoustic analogues of gravitational black holes. A flowing fluid provides an effective curved spacetime on which sound waves can propagate, allowing the simulation of gravitational geometries and related phenomena. The last decade has witness

A. Zec, S. Premathilake, J. C. Cornejo, M. M. Dalton

We report a high precision measurement of electron beam polarization using Compton polarimetry. The measurement was made in experimental Hall A at Jefferson Lab during the CREX experiment in 2020. A total uncertainty of dP/P=0.36% was achieved detecting the back-scattered photons from the Compton scattering process. This is the highest accuracy in a measurem

A. A. Fedotov, P. V. Khrapov, A. E. Dengovskaya

An initial-boundary value problem for an unsteady two-dimensional heat conduction equation in a bounded domain modeling the unsteady temperature distribution of permafrost soil in the vicinity of a main gas pipeline, taking into account climate warming, is investigated. The parameters of the mathematical model are selected in accordance with experimental dat

Zhiwei Hao, Xinru Ding, Libo Li, Ferenc Weisz

In this paper, we introduce a new class of function spaces, which unify and generalize Lorentz-Karamata spaces, variable Lorentz spaces and other several classical function spaces. Based on the new spaces, we develop the theory of variable martingale Hardy-Lorentz-Karamata spaces and apply it to Fourier Analysis. To be precise, we discuss the basic propertie

Haoxin Liu, Zhiyuan Zhao, Jindong Wang, Harshavardhan Kamarthi

Time-series forecasting (TSF) finds broad applications in real-world scenarios. Prompting off-the-shelf Large Language Models (LLMs) demonstrates strong zero-shot TSF capabilities while preserving computational efficiency. However, existing prompting methods oversimplify TSF as language next-token predictions, overlooking its dynamic nature and lack of integ

Jiahe Lin, Huitian Lei, George Michailidis

Granger causality has been widely used in various application domains to capture lead-lag relationships amongst the components of complex dynamical systems, and the focus in extant literature has been on a single dynamical system. In certain applications in macroeconomics and neuroscience, one has access to data from a collection of related such systems, whe

Stephanie Egler, Elisabeth M. Werner

We introduce extremal affine surface areas in a functional setting. We show their main properties. Among them are linear invariance, isoperimetric inequalities and monotonicity properties. We establish a new duality formula, which shows that the maximal (resp. minimal) inner affine surface area of an $s$-concave function on $\mathbb{R}^n$ equals the maximal

Kunlun Li, Jiguang He, Mohammed El-Hajjar, Lie-Liang Yang

The sparsity of millimeter wave (mmWave) channels in the angular and temporal domains is beneficial to channel estimation, while the associated channel parameters can be utilized for localization. However, line-of-sight (LoS) blockage poses a significant challenge on the localization in mmWave systems, potentially leading to substantial positioning errors. A

Sandeep Singh, Ramandeep Kaur

For integers $m$ and $n$, the Baumslag-Solitar groups, denoted as $BS(m,n)$, are groups generated by two elements with a single defining relation: $BS(m,n) = \langle a, b | a^mb=ba^n\rangle$. The sum of dilates, denoted as $r \cdot A + s \cdot B$ for integers $r$ and $s$, is defined as $\{ra + sb; a\in A, b\in B\}$. In 2014, Freiman et al. \cite{freiman} der

M. G. Huber, I. Taminiau, D. G. Cory, B. Heacock

Perfect-crystal neutron interferometry which is analogous to Mach-Zehnder interferometry, uses Bragg diffraction to form interfering neutron paths. The measured phase shifts can be used to probe many types of interactions whether it be nuclear, electromagnetic, gravitational, or topological in nature. For a perfect-crystal interferometer to preserve coherenc

Vitalii Makogin, Duc Nguyen, Evgeny Spodarev

In practical applications, effectively segmenting cracks in large-scale computed tomography (CT) images holds significant importance for understanding the structural integrity of materials. Classical image-processing techniques and modern deep-learning models both face substantial computational challenges when applied directly to high resolution big data vol

Saverio Moroni, Fabio Cinti, Massimo Boninsegni, Giuseppe Pellicane

Discovering novel emergent behavior in quantum many-body systems is a main objective of contemporary research. In this paper, we explore the effects on phases and phase transitions of the proximity to a Ruelle-Fisher instability, marking the transition to a collapsed state. To accomplish this, we study by quantum Monte Carlo simulations a two-dimensional sys

Md Manirul Islam, Md. Sadad Mahamud, Umme Salsabil, A. A. M. Mazharul Amin

With a large number of populations, many problems are rising rapidly in Dhaka, the capital city of Bangladesh. Water-logging is one of the major issues among them. Heavy rainfall, lack of awareness and poor maintenance causes bad sewerage system in the city. As a result, water is overflowed on the roads and sometimes it gets mixed with the drinking water. To

Yasheng Sun, Wenqing Chu, Hang Zhou, Kaisiyuan Wang

While considerable progress has been made in achieving accurate lip synchronization for 3D speech-driven talking face generation, the task of incorporating expressive facial detail synthesis aligned with the speaker's speaking status remains challenging. Our goal is to directly leverage the inherent style information conveyed by human speech for generating a

Ningyu Zhang, Bozhong Tian, Siyuan Cheng, Xiaozhuan Liang

Knowledge editing for large language models can offer an efficient solution to alter a model's behavior without negatively impacting the overall performance. However, the current approaches encounter issues with limited generalizability across tasks, necessitating one distinct editor for each task, significantly hindering the broader applications. To address

Rostislav Arkhipov

Rapidly changing the refractive index of a medium in space and time (space-time photonic crystal, STPC) has been a challenging task. Such a rapid change can be achieved by carrier-wave Rabi flopping. We show that it can be realized when a train of half-cycle light pulses collide in a simple three-level atomic medium. We found the formation of Bragg microcavi

Luoming Zhang, Yefei He, Wen Fei, Zhenyu Lou

Model reparameterization is a widely accepted technique for improving inference speed without compromising performance. However, current Post-training Quantization (PTQ) methods often lead to significant accuracy degradation when applied to reparameterized models. This is primarily caused by channel-specific and sample-specific outliers, which appear only at

Artur Galiullin, Sergey Khoroshkin, Maxim Lyachko

Using Zhelobenko-Stern formulas for the action of the generators of orthogonal Lie algebra in corresponding Gelfand-Tsetlin basis, we derive Mellin-Barnes presentations for the wave functions of $B_n$ Toda lattice. They are in accordance with Iorgov-Shadura formulas.

Jan Petrik, Markus Bambach

This study presents a novel method for microstructure control in closed die hot forging that combines Model Predictive Control (MPC) with a developed machine learning model called DeepForge. DeepForge uses an architecture that combines 1D convolutional neural networks and gated recurrent units. It uses surface temperature measurements of a workpiece as input

Bruno Gašperov, Marko Đurasević, Domagoj Jakobovic

The majority of standard approaches to financial portfolio optimization (PO) are based on the mean-variance (MV) framework. Given a risk aversion coefficient, the MV procedure yields a single portfolio that represents the optimal trade-off between risk and return. However, the resulting optimal portfolio is known to be highly sensitive to the input parameter

Yao Mu, Junting Chen, Qinglong Zhang, Shoufa Chen

Robotic behavior synthesis, the problem of understanding multimodal inputs and generating precise physical control for robots, is an important part of Embodied AI. Despite successes in applying multimodal large language models for high-level understanding, it remains challenging to translate these conceptual understandings into detailed robotic actions while

Farshad Rostami Ghadi, Kai-Kit Wong, Wee Kiat New, Hao Xu

This letter studies the performance of reconfigurable intelligent surface (RIS)-aided communications for a fluid antenna system (FAS) enabled receiver. Specifically, a fixed singleantenna base station (BS) transmits information through a RIS to a mobile user (MU) which is equipped with a planar fluid antenna in the absence of a direct link.We first analyze t

Herbert Eßl, Matthias Reitner, Giorgio Sangiovanni, Alessandro Toschi

By applying the Shiba mapping on the two particle level, we derive the relation between the local four-point correlation functions of bipartite lattice models with on-site electronic repulsion and those of the corresponding models with attractive interaction in the most general setting. In particular, we extend the results of [Phys. Rev. B, 101, 155148 (2020

Sebastien Tiburzio, Tomás Coleman, Daniel Feliu-Talegon, Cosimo Della Santina

Model-based manipulation of deformable objects has traditionally dealt with objects while neglecting their dynamics, thus mostly focusing on very lightweight objects at steady state. At the same time, soft robotic research has made considerable strides toward general modeling and control, despite soft robots and deformable objects being very similar from a m

Shoichiro Miyashita

At first glance, thermodynamic properties of gravity with asymptotically AdS conditions and those with box boundary conditions, where the spatial section of the boundary is a sphere of finite radius, appear similar. Both exhibit a similar phase structure and Hawking-Page phase transition. However, when we introduce a U(1) gauge field to the system, discrepan

Omri Y. Cohen, Yael Klein, Eran Sharon

The locomotion of flexible membrane-like organisms on top of curved surfaces appears in different contexts and scales. Still, such dynamics have not yet been quantitatively modeled and no realization of such motion in manmade systems has been achieved. We present an experimental and theoretical study of active gel ribbons surfing on a curved fluid-fluid inte

Ricardo Gómez Aíza

We present families of combinatorial classes described as trees with nodes that can carry one of two types of "flowers": integer partitions or integer compositions. Two parameters on the flowers of trees will be considered: the number of "petals" in all the flowers (petals' weight) and the number of edges in the petals of all the flowers (flowers' weight). W

Xin Zhou, Chunyan Miao

Multimodal recommender systems amalgamate multimodal information (e.g., textual descriptions, images) into a collaborative filtering framework to provide more accurate recommendations. While the incorporation of multimodal information could enhance the interpretability of these systems, current multimodal models represent users and items utilizing entangled

Alex Buchel

We extend the computational framework of \cite{Buchel:2023fst} to analysis of shear and bulk viscosities in generic strongly coupled holographic Gauss-Bonnet gauge theories. The finite Gauss-Bonnet coupling constant encodes holographic plasma with non-equal central charges $c\ne a$ at the ultraviolet fixed point. In a simple model we discuss transport coeffi

David Criens

Continuous time financial market models are often motivated as scaling limits of discrete time models. The objective of this paper is to establish such a connection for a robust framework. More specifically, we consider discrete time models that are parameterized by Markovian transition kernels, and a continuous time framework with drift and volatility uncer

Fanqi Wan, Ziyi Yang, Longguang Zhong, Xiaojun Quan

Recently, FuseLLM introduced the concept of knowledge fusion to transfer the collective knowledge of multiple structurally varied LLMs into a target LLM through lightweight continual training. In this report, we extend the scalability and flexibility of the FuseLLM framework to realize the fusion of chat LLMs, resulting in FusionChat. FusionChat comprises tw

H. A. Verrill

We describe an algorithm to find an L-system for the boundary of space-filling square grid based folding curves, such as the fractal dragon curves. This complements work of Dekking, Arndt, Handl, on space filling curves.

Katarzyna Kobalczyk, Mihaela van der Schaar

A significant challenge in machine learning, particularly in noisy and low-data environments, lies in effectively incorporating inductive biases to enhance data efficiency and robustness. Despite the success of informed machine learning methods, designing algorithms with explicit inductive biases remains largely a manual process. In this work, we explore how

J. Krsnik, O. Simard, P. Werner, A. Kauch

Correlated electron systems often show strong bosonic fluctuations, e.g., of antiferromagnetic nature, around a large wave vector such as $\mathbf{q}=(\pi,\pi\ldots)$. These fluctuations can give rise to vertex corrections to the optical conductivity through the (transversal) particle-hole channel, coined $\pi$-ton contributions. Previous numerical results d

Joris Baan, Raquel Fernández, Barbara Plank, Wilker Aziz

With the rise of increasingly powerful and user-facing NLP systems, there is growing interest in assessing whether they have a good representation of uncertainty by evaluating the quality of their predictive distribution over outcomes. We identify two main perspectives that drive starkly different evaluation protocols. The first treats predictive probability

Jeonghyeon Yoon, Junhyun Park, Hyojae Park, Hakyoon Lee

In robot-assisted minimally invasive surgery (RAMIS), optimal placement of the surgical robot base is crucial for successful surgery. Improper placement can hinder performance because of manipulator limitations and inaccessible workspaces. Conventional base placement relies on the experience of trained medical staff. This study proposes a novel method for de

Hideto Kamei

In this note, in the context of the AdS/CFT correspondence, the holographic derivation of the Wilsonian effective action is proposed. Then, the exact RG equation in the boundary theory is derived from the Wheeler-DeWitt equation of the bulk, following the suggestion of arXiv:hep-th/9912012,arXiv:hep-th/9912018, and arXiv:1010.1264. The relationship between t

Jiong Mei, Kun Jiang, Shengshan Qin, Jiangping Hu

Intrinsic Rashba spin-orbital coupling (SOC) can exist in centrosymmetric materials with local inversion symmetry breaking. Here we show that such a SOC can induce topological superconductivity together with an in-plane Zeeman field in planar Josephson junctions formed by the centrosymmetric materials. A single Majorana mode can be created at each end of the

Dessislava H. Kochloukova, Victor Petrogradsky

We prove that the Fibonacci Lie algebra and the related just infinite self-similar Lie algebra are not finitely presented.

Ashkan Shekaari, Mahmoud Jafari

Motivated by some recent works showing the ability of semiconducting monolayers to disintegrate the structures of biological fibrils, we have applied molecular dynamics (MD) simulations in both classical and quantum regimes to investigate whether semiconducting Si$_3$N$_4$ monolayer has the same ability on interaction with U-shaped amyloid beta (A$\beta$) fi

Weidong Gao, Lu Shi, Lie-Liang Yang

To accomplish relatively complex tasks, in Internet of Bio-Nano Things (IoBNT), information collected by different nano-machines (NMs) is usually sent via multiple-access channels to fusion centers (FCs) for further processing. Relying on two types of molecules, in this paper, a molecular code-division multiple-access (MoCDMA) scheme is designed for multiple

Anael Ben-Asher, Antonio I. Fernández-Domínguez, Johannes Feist

Memoryless (Markovian) system-bath interactions are of fundamental interest in physics. While typically, the absence of memory originates from the characteristics of the bath, here we demonstrate that it can result from the system becoming lossy due to the Markovian interaction with a second bath. This uncovers an interesting interplay between independent ba

Zahra Motaqy, Mohamed E. Najd, Ghada Almashaqbeh

Cryptocurrencies and blockchain technology provide an innovative model for reshaping digital services. Driven by the movement toward Web 3.0, recent systems started to provide distributed services, such as computation outsourcing or file storage, on top of the currency exchange medium. By allowing anyone to join and collect payments for serving others, these

Nicolas Ruiz

Although the bulk of the research in privacy and statistical disclosure control is designed for static data, more and more data are often collected as continuous streams, and extensions of popular privacy tools and models have been proposed for this scenario. However, most of these proposals require buffers, where incoming individuals are momentarily stored,

Manujith K. Michel, Varadharaj R. Srinivasan

Let $F$ be a $\delta-$field (differential field) of characteristic zero with an algebraically closed field of constants $F^\delta$, $A$ be a $\delta-F-$central simple algebra, $K$ be a Picard-Vessiot extension for the $\delta-F-$module $A$ and $\mathscr G(K|F)$ be the $\delta-$Galois group of $K$ over $F.$ We prove that a $\delta-$field extension $L$ of $F,$

Zhenxing Dong, Jidong Jia, Yan Li, Yuye Ling

Recently, deep learning-based computer-generated holography (CGH) has demonstrated tremendous potential in three-dimensional (3D) displays and yielded impressive display quality. However, most existing deep learning-based CGH techniques can only generate holograms of 1080p resolution, which is far from the ultra-high resolution (16K+) required for practical

Seungwon Seo, Suho Lee, Sangheum Hwang

Utilizing large-scale pretrained models is a well-known strategy to enhance performance on various target tasks. It is typically achieved through fine-tuning pretrained models on target tasks. However, na\"{\i}ve fine-tuning may not fully leverage knowledge embedded in pretrained models. In this study, we introduce a novel fine-tuning method, called stochast

Mengen Luo, Ercan Engin Kuruoglu

Federated learning's poor performance in the presence of heterogeneous data remains one of the most pressing issues in the field. Personalized federated learning departs from the conventional paradigm in which all clients employ the same model, instead striving to discover an individualized model for each client to address the heterogeneity in the data. One

Andrea Maracani, Raffaello Camoriano, Elisa Maiettini, Davide Talon

This study provides a comprehensive benchmark framework for Source-Free Unsupervised Domain Adaptation (SF-UDA) in image classification, aiming to achieve a rigorous empirical understanding of the complex relationships between multiple key design factors in SF-UDA methods. The study empirically examines a diverse set of SF-UDA techniques, assessing their con

Chun Lin, Armando Consiglio, Ola Kenji Forslund, Julia Kuspert

Tunable quantum materials hold great potential for applications. Of special interest are materials in which small lattice strain induces giant electronic responses. The kagome compounds AV3Sb5 (A = K, Rb, Cs) provide a testbed for such singular electronic states. In this study, through angle-resolved photoemission spectroscopy, we provide comprehensive spect