December 2023 arXiv papers — page 110

Swarna Kamal Paul

Sequential planning in large state space and action space quickly becomes intractable due to combinatorial explosion of the search space. Heuristic methods, like monte-carlo tree search, though effective for large state space, but struggle if action space is large. Pure reinforcement learning methods, relying only on reward signals, needs prohibitively large

Niklas Christoph Affolter

Miquel dynamics is a discrete time dynamics for circle patterns, which relies on Miquel's six circle theorem. Previous work shows that the evolution of the circle centers satisfy the dSKP equation on the octahedral lattice $A_3$. As a consequence, Miquel dynamics is a discrete integrable system. Moreover, Miquel dynamics give rise to a real-valued cluster st

Indranil Biswas, Manish Kumar, A. J. Parameswaran

We introduce three notion of tameness of the Nori fundamental group scheme for a normal quasiprojective variety $X$ over an algebraically closed field. It is proved that these three notions agree if $X$ admits a smooth completion with strict normal crossing divisor as the complement. We also prove a Lefschetz type restriction theorem for the tame Nori fundam

Sergey Barsuk, Oleg Bezshyyko, Ianina Boyarintseva, Andrey Boyarintsev

A novel type of calorimeter based on grains of inorganic scintillating crystal readout by wave length shifting fibers is proposed. The concept and main features as well as the prototype design are introduced and the first results obtained using cosmic rays are presented. The number of photo-electrons generated by cosmic rays muons in the prototype detector i

Qiwei Tian, Chenhao Lin, Zhengyu Zhao, Qian Li

Adversarial training has achieved substantial performance in defending image retrieval against adversarial examples. However, existing studies in deep metric learning (DML) still suffer from two major limitations: weak adversary and model collapse. In this paper, we address these two limitations by proposing Collapse-Aware TRIplet DEcoupling (CA-TRIDE). Spec

Alberto Abbondandolo, Gabriele Benedetti, Oliver Edtmair

We prove that all normalized symplectic capacities coincide on smooth domains in $\mathbb C^n$ which are $C^2$-close to the Euclidean ball, whereas this fails for some smooth domains which are just $C^1$-close to the ball. We also prove that all symplectic capacities whose value on ellipsoids agrees with that of the $n$-th Ekeland-Hofer capacity coincide in

Farhad Rezazadeh, Hatim Chergui, Shuaib Siddiqui, Josep Mangues

An adaptive standardized protocol is essential for addressing inter-slice resource contention and conflict in network slicing. Traditional protocol standardization is a cumbersome task that yields hardcoded predefined protocols, resulting in increased costs and delayed rollout. Going beyond these limitations, this paper proposes a novel multi-agent deep rein

Stephan Kigle, Tapio Schmidt-Achert, Miguel Ángel Martínez Pérez

Hydrogen is central to the global energy transition when produced at low emissions. This paper introduces a renewable hydrogen production system model (HPSM) that optimizes a hybrid hydrogen production system (HPS) on a worldwide 50x50 km grid, considering country-specific interest rates. Besides the renewable energy's impact on the HPS design, we analyze th

Johannes Schusterbauer, Ming Gui, Pingchuan Ma, Nick Stracke

Visual synthesis has recently seen significant leaps in performance, largely due to breakthroughs in generative models. Diffusion models have been a key enabler, as they excel in image diversity. However, this comes at the cost of slow training and synthesis, which is only partially alleviated by latent diffusion. To this end, flow matching is an appealing a

Leonardo Pedroso, Pedro Batista, Markos Papageorgiou

To cope with uncertain traffic patterns and traffic models, traffic-responsive signal control strategies in the literature are designed to be robust to these uncertainties. These robust strategies still require sensing infrastructure to implement traffic-responsiveness. In this paper, we take a novel perspective and show that it is possible to use the alread

Cyril Barrelet, Marc Chaumont, Gérard Subsol

In this paper we present a pipeline using stereo images in order to automatically identify, track in 3D fish, and measure fish population.

Alexander Marinšek, Xuesong Cai, Lieven De Strycker, Fredrik Tufvesson

Immersing a user in life-like extended reality (XR) scenery using a head-mounted display (HMD) with a constrained form factor and hardware complexity requires remote rendering on a nearby edge server or computer. Millimeter-wave (mmWave) communication technology can provide sufficient data rate for wireless XR content transmission. However, mmWave channels e

Amit Kumar Kabat, Shubhang Pandey, TG Venkatesh

In Near Memory Processing (NMP), processing elements(PEs) are placed near the 3D memory, reducing unnecessary data transfers between the CPU and the memory. However, as the CPUs and the PEs of the NMP use a shared memory space, maintaining coherency between them is a challenge. Most current literature relies on maintaining coherence for fine-grained or coars

Ziqiao Wang, Yi Liu, Chengcheng Ji, Jian Wang

Superconductor-insulator/metal transition (SIT/SMT) as a paradigm of quantum phase transition has been a research highlight over the last three decades. Benefit from recent developments in the fabrication and measurements of 2D superconducting films and nanodevices, unprecedented quantum phenomena have been revealed in the quantum phase transitions of 2D sup

Zihao Zhao, Yuxiao Liu, Han Wu, Mei Wang

Contrastive Language-Image Pre-training (CLIP), a simple yet effective pre-training paradigm, successfully introduces text supervision to vision models. It has shown promising results across various tasks due to its generalizability and interpretability. The use of CLIP has recently gained increasing interest in the medical imaging domain, serving as a pre-t

Chinedu Innocent Nwoye, Kareem Elgohary, Anvita Srinivas, Fauzan Zaid

Tool tracking in surgical videos is essential for advancing computer-assisted interventions, such as skill assessment, safety zone estimation, and human-machine collaboration. However, the lack of context-rich datasets limits AI applications in this field. Existing datasets rely on overly generic tracking formalizations that fail to capture surgical-specific

Yen-Jen Cheng, Sen-Peng Eu, Tung-Shan Fu, Jyun-Cheng Yao

For a finite Coxeter group $W$, Josuat-Verg\`es derived a $q$-polynomial counting the maximal chains in the lattice of noncrossing partitions of $W$ by weighting some of the covering relations, which we call bad edges, in these chains with a parameter $q$. We study the connection of these weighted chains with parking functions of type $A$ ($B$, respectively)

Sylwester Piątek

Inequality (concentration) curves such as Lorenz, Bonferroni, Zenga curves, as well as a new inequality curve -- the $D$ curve, are broadly used to analyse inequalities in wealth and income distribution in certain populations. Quantile versions of these inequality curves are more robust to outliers. We discuss several parametric estimators of quantile versio

Maksym Luz, Mikhail Moklyachuk

We propose solution of the problem of the mean square optimal estimation of linear functionals which depend on the unobserved values of a continuous time stochastic process with periodically correlated increments based on observations of this process with periodically stationary noise. To solve the problem, we transform the processes to the sequences of stoc

Sai Kubair Kota, Siddhant Kumar, Bianca Giovanardi

Slender beams are often employed as constituents in engineering materials and structures. Prior experiments on lattices of slender beams have highlighted their complex failure response, where the interplay between buckling and fracture plays a critical role. In this paper, we introduce a novel computational approach for modeling fracture in slender beams sub

Lin Kyi, Abraham Mhaidli, Cristiana Santos, Franziska Roesner

Data collection purposes and their descriptions are presented on almost all privacy notices under the GDPR, yet there is a lack of research focusing on how effective they are at informing users about data practices. We fill this gap by investigating users' perceptions of data collection purposes and their descriptions, a crucial aspect of informed consent. W

Cheng Li, Gudrid Moortgat-Pick

We study possible CP-violation effects of the Higgs to $Z$-boson coupling at a future $e^+ e^-$ collider, e.g. the International Linear Collider (ILC). We find that the azimuthal angular distribution of the muon pair, produced by $e^+ e^- \rightarrow H Z \rightarrow H \mu^+ \mu^-$, can be sensitive to such a CP-violation effect when we apply initial transver

Chun-Zheng Wang

The interplay between the chiral anomaly and the strong magnetic or vortical fields created in noncentral heavy-ion collisions can lead to various anomalous chiral effects in the quark--gluon plasma, including the chiral magnetic effect (CME), the chiral magnetic wave (CMW), and the chiral vortical effect (CVE). In this proceeding, recent ALICE measurements

Vrushabh Zinage, Rohan Chandra, Efstathios Bakolas

In this paper, we propose a deep learning based control synthesis framework for fast and online computation of controllers that guarantees the safety of general nonlinear control systems with unknown dynamics in the presence of input constraints. Towards this goal, we propose a framework for simultaneously learning the unknown system dynamics, which can chan

Guillaume Baverez, Baojun Wu

This paper studies the analytic continuation of Liouville eigenstates and shows that they assemble into irreducible highest-weight representations of the Virasoro algebra, for all values of the conformal weights. This builds on previous results from the first author and Guillarmou, Kupiainen, Rhodes & Vargas, where such representations were constructed excep

Anishka, Atharva Mehta, Nipun Gupta, Aarav Balachandran

The emergence of Large language models (LLMs) is expected to have a major impact on education. This paper explores the potential of using ChatGPT, an LLM, as a virtual Teaching Assistant (TA) in an Introductory Programming Course. We evaluate ChatGPT's capabilities by comparing its performance with that of human TAs in some of the important TA functions. The

Jiyoung Kim, Kyuhong Shim, Insu Lee, Byonghyo Shim

Unsupervised semantic segmentation (USS) aims to discover and recognize meaningful categories without any labels. For a successful USS, two key abilities are required: 1) information compression and 2) clustering capability. Previous methods have relied on feature dimension reduction for information compression, however, this approach may hinder the process

Pascal Puphal, Pascal Reiss, Niklas Enderlein, Yu-Mi Wu

The discovery of high-temperature superconductivity in La$_3$Ni$_2$O$_7$ at pressures above 14 GPa has spurred extensive research efforts. Yet, fundamental aspects of the superconducting phase, including the possibility of a filamentary character, are currently subjects of controversial debates. Conversely, a crystal structure with NiO$_6$ octahedral bilayer

Yusen Feng, Xiyan Xu, Libin Liu

In this paper, we present a simulation and control framework for generating biomechanically plausible motion for muscle-actuated characters. We incorporate a fatigue dynamics model, the 3CC-r model, into the widely-adopted Hill-type muscle model to simulate the development and recovery of fatigue in muscles, which creates a natural evolution of motion style

Marc Kegel, Lukas Lewark, Naageswaran Manikandan, Filip Misev

The unknotting number $u$ and the genus $g$ of braid positive knots are equal, as shown by Rudolph. We prove the stronger statement that any positive braid diagram of a genus $g$ knot contains $g$ crossings, such that changing them produces a diagram of the trivial knot. Then, we turn to unknotting the more general class of fibered positive knots, for which

Mohammed Maqsood Shaik, Dietrich Klakow, Badr M. Abdullah

Pre-trained Transformer-based speech models have shown striking performance when fine-tuned on various downstream tasks such as automatic speech recognition and spoken language identification (SLID). However, the problem of domain mismatch remains a challenge in this area, where the domain of the pre-training data might differ from that of the downstream lab

Pavel Petracek, Kostas Alexis, Martin Saska

The typical point cloud sampling methods used in state estimation for mobile robots preserve a high level of point redundancy. This redundancy unnecessarily slows down the estimation pipeline and may cause drift under real-time constraints. Such undue latency becomes a bottleneck for resource-constrained robots (especially UAVs), requiring minimal delay for

Wei Xia, Bo Bai, Xuejiao Chen, Yichen Yang

Generally, the dissipationless Hall effect in solids requires time-reversal symmetry breaking (TRSB), where TRSB induced by external magnetic field results in ordinary Hall effect, while TRSB caused by spontaneous magnetization gives rise to anomalous Hall effect (AHE) which scales with the net magnetization. The AHE is therefore not expected in antiferromag

Jen Ning Lim, Juan Kuntz, Samuel Power, Adam M. Johansen

Maximum likelihood estimation (MLE) of latent variable models is often recast as the minimization of a free energy functional over an extended space of parameters and probability distributions. This perspective was recently combined with insights from optimal transport to obtain novel particle-based algorithms for fitting latent variable models to data. Draw

Elia Cenci, Robert Feldmann, Jindra Gensior, James S. Bullock

A kinematic misalignment of the stellar and gas components is a phenomenon observed in a significant fraction of galaxies. However, the underlying physical mechanisms are not well understood. A commonly proposed scenario for the formation of a misaligned component requires any pre-existing gas disc to be removed, via fly-bys or ejective feedback from an acti

Anton T. Jaelani, Anupreeta More, Kenneth C. Wong, Kaiki T. Inoue

We apply a novel model based on convolutional neural networks (CNNs) to identify gravitationally-lensed galaxies in multi-band imaging of the Hyper Suprime Cam Subaru Strategic Program (HSC-SSP) Survey. The trained model is applied to a parent sample of 2 350 061 galaxies selected from the $\sim$ 800 deg$^2$ Wide area of the HSC-SSP Public Data Release 2. Th

Abhijeet Kumar, Denis Yagodkin, Roberto Rosati, Douglas J Bock

Momentum-indirect excitons composed of electrons and holes in different valleys define optoelectronic properties of many semiconductors, but are challenging to detect due to their weak coupling to light. The identification of an excitons' valley character is further limited by complexities associated with momentum-selective probes. Here, we study the photolu

Shuzhou Yang, Chong Mou, Jiwen Yu, Yuhan Wang

Diffusion models have revolutionized text-driven video editing. However, applying these methods to real-world editing encounters two significant challenges: (1) the rapid increase in GPU memory demand as the number of frames grows, and (2) the inter-frame inconsistency in edited videos. To this end, we propose NVEdit, a novel text-driven video editing framew

Hansong Zhang, Shikun Li, Dan Zeng, Chenggang Yan

As the size of the datasets getting larger, accurately annotating such datasets is becoming more impractical due to the expensiveness on both time and economy. Therefore, crowd-sourcing has been widely adopted to alleviate the cost of collecting labels, which also inevitably introduces label noise and eventually degrades the performance of the model. To lear

Alexandros Graikos, Srikar Yellapragada, Minh-Quan Le, Saarthak Kapse

To synthesize high-fidelity samples, diffusion models typically require auxiliary data to guide the generation process. However, it is impractical to procure the painstaking patch-level annotation effort required in specialized domains like histopathology and satellite imagery; it is often performed by domain experts and involves hundreds of millions of patc

Yasuaki Gyoda, Shuhei Maruyama

In this paper, we study positive integer solutions to a generalized form of the Markov equation, given as $x^2 + y^2 + z^2 + k(yz + zx + xy) = (3 + 3k)xyz$. This equation extends the classical Markov equation $x^2 + y^2 + z^2 = 3xyz$. We generalize the concept of Cohn triples for the classical Markov equation to the generalized Markov equations. Using this,

Maria Shishanina, Anatoly Sidorov

The article discusses the basic concepts of strategic planning in the Russian Federation, highlights the legal, financial and resource features that act as restrictions in decision making in the field of socio-economic development of municipalities. The analysis concluded that to design an adequate model of socio-economic development of municipalities is a v

Vadim Kotov, Mantej Rajpal

Crypto-Ransomware has been increasing in sophistication since it first appeared in September 2013, leveraging new attack vectors, incorporating advanced encryption algorithms, and expanding the number of file types it targets. In this report, we dissect nearly 30 samples of ransomware variants that have been encountered since September 2013, revealing a tren

Jian Zhu, Yu Cui, Zhangmin Huang, Xingyu Li

The multi-view hash method converts heterogeneous data from multiple views into binary hash codes, which is one of the critical technologies in multimedia retrieval. However, the current methods mainly explore the complementarity among multiple views while lacking confidence learning and fusion. Moreover, in practical application scenarios, the single-view d

Fateme Mahdikhany, Sean Driskill, Jeremy G. Philbrick, Davoud Adinehloo

One-dimensional (1D) van der Waals materials have emerged as an intriguing playground to explore novel electronic and optical effects. We report on inorganic one-dimensional SbPS4 nanotubes bundles obtained via mechanical exfoliation from bulk crystals. The ability to mechanically exfoliate SbPS4 nanobundles offers the possibility of applying modern 2D mater

Kevin Janßen, Philipp Rüßmann, Sergej Liberda, Michael Schleenvoigt

With increasing attention in Majorana physics for possible quantum bit applications, a large interest has been developed to understand the properties of the interface between a $s$-type superconductor and a topological insulator. Up to this point the interface analysis was mainly focused on in situ prepared Josephson junctions, which consist of two coupled s

Jean-Sébastien Brouillon, Andrea Martin, John Lygeros, Florian Dörfler

We study control of constrained linear systems with only partial statistical information about the uncertainty affecting the system dynamics and the sensor measurements. Specifically, given a finite collection of disturbance realizations drawn from a generic distribution, we consider the problem of designing a stabilizing control policy with provable safety

David Nkansah

We construct Nakayama functors on proper abelian subcategories of triangulated categories with a Serre functor using approximation theory. This, in turn, allows for the construction of Auslander-Reiten translates. As a result, we prove that suitable proper abelian subcategories are dualising $k$-varieties and have enough projectives if and only if they have

Tomáš Souček, Dima Damen, Michael Wray, Ivan Laptev

We address the task of generating temporally consistent and physically plausible images of actions and object state transformations. Given an input image and a text prompt describing the targeted transformation, our generated images preserve the environment and transform objects in the initial image. Our contributions are threefold. First, we leverage a larg

Ai Guan, Fernando Muro

We prove that the (homotopy) hypercommutative algebra structure on the de Rham cohomology of a Poisson or Jacobi manifold defined by several authors is (homotopically) trivial, i.e. it reduces to the underlying (homotopy) commutative algebra structure. We do so by showing that the DG operads which codify the algebraic structure on the de Rham complex of Pois

Conor Osborne, Aretha L. Teckentrup

The focus of this work is the convergence of non-stationary and deep Gaussian process regression. More precisely, we follow a Bayesian approach to regression or interpolation, where the prior placed on the unknown function $f$ is a non-stationary or deep Gaussian process, and we derive convergence rates of the posterior mean to the true function $f$ in terms

Maximilian Kasperowski, Reinhard von Hanxleden

Bottom-up layout algorithms for compound graphs are suitable for presenting the microscale view of models and are often used in model-driven engineering. However, they have difficulties at the macroscale where maintaining the overview of large models becomes challenging. We propose top-down layout, which utilizes scale to hide low-level details at high zoom

Orlando Luongo, Francesco Pace, Sebastiano Tomasi

We analyze time-dependent dark energy equations of state through linear and nonlinear structure formation and their quintessence potentials, characterized by fast, recent transitions, inspired by parameter space studies of selected classes of the more general Horndeski models. The influence of dark energy on structures comes from modifications to the backgro

Markus Wolff

We consider null mean curvature flow along the standard lightcone in the de Sitter spacetime. This flow was first studied by Roesch--Scheuer along null hypersurfaces for the detection of MOTS, and independently by the author in the specific case of the standard Minkowski lightcone. Similar to the Minkowski case, null mean curvature flow along the de Sitter l

Lukas Fisch, Michael O. Heming, Andreas Schulte-Mecklenbeck, Catharina C. Gross

Flow cytometry is widely used to identify cell populations in patient-derived fluids such as peripheral blood (PB) or cerebrospinal fluid (CSF). While ubiquitous in research and clinical practice, flow cytometry requires gating, i.e. cell type identification which requires labor-intensive and error-prone manual adjustments. To facilitate this process, we des

Yoonwoo Jeong, Jinwoo Lee, Chiheon Kim, Minsu Cho

Transfer learning of large-scale Text-to-Image (T2I) models has recently shown impressive potential for Novel View Synthesis (NVS) of diverse objects from a single image. While previous methods typically train large models on multi-view datasets for NVS, fine-tuning the whole parameters of T2I models not only demands a high cost but also reduces the generali

Rui Jin, Yachun Li, Liang Zhao

Due to extreme difficulties in numerical simulations of Euler-Maxwell equations, which are caused by the highly complicated structures of the equations, this paper concerns the simplification of Euler-Maxwell system through the zero-relaxation limit towards the drift-diffusion equations with non-constant doping functions. We carry out the global-in-time conv

Van Hao Can, Adrian Röllin

Consider the mean-field spin models where the Gibbs measure of each configuration depends only on its magnetization. Based on the Stein and Laplace methods, we give a new and short proof for the scaling limit theorems with convergence rate for the magnetization in a perturbed model. As an application, we derive the scaling limit theorems for the maximum like

Oscar Castillo-Felisola, Bastian Grez, Jose Perdiguero, Aureliano Skirzewski

In this paper we inquire inflationary scenarios built on a simplified version of the polynomial affine model of gravity. Given the absence of a metric tensor in the formulation of the model, we build a \emph{kinetic term} contracting the derivatives of scalar field with the most general $(2,0)$-tensor density build using the affine connection, and introduce

Wenjie Yin, Yi Yu, Hang Yin, Danica Kragic

Current training of motion style transfer systems relies on consistency losses across style domains to preserve contents, hindering its scalable application to a large number of domains and private data. Recent image transfer works show the potential of independent training on each domain by leveraging implicit bridging between diffusion models, with the con

Božidar N. Šoškić, Jonas Bekaert, Cem Sevik, Željko Šljivančanin

We explore the emergence of phonon-mediated superconductivity in bilayer borophenes by controlled intercalation with elements from the groups of alkali, alkaline-earth, and transition metals, using systematic first-principles and Eliashberg calculations. We show that the superconducting properties are primarily governed by the interplay between the out-of-pl

Hang Guo, Tao Dai, Yuanchao Bai, Bin Chen

Designing single-task image restoration models for specific degradation has seen great success in recent years. To achieve generalized image restoration, all-in-one methods have recently been proposed and shown potential for multiple restoration tasks using one single model. Despite the promising results, the existing all-in-one paradigm still suffers from h

Valentina Ciccone, Mateus Sousa

In this note, we study maximizers for Fourier extension inequalities on the sphere. We prove that constant functions are local maximizers for the $L^p(\mathbb{S}^{d-1})$ to $L^p(\mathbb{R}^d)$ Fourier extension estimates in the same range of exponents $p$ for which they are global maximizers for the $L^2(\mathbb{S}^{d-1})$ to $L^p_{rad}L^2_{ang}(\mathbb{R}^d

Luigi Alfonsi

This survey article is an invited contribution to the Encyclopedia of Mathematical Physics, 2nd edition. We provide an accessible overview on relevant applications of higher and derived geometry to theoretical physics, including higher gauge theory, higher geometric quantization and Batalin-Vilkovisky formalism.

Timo Keller, Michael Stoll

We develop the theory and algorithms necessary to be able to verify the strong Birch--Swinnerton-Dyer Conjecture for absolutely simple modular abelian varieties over $\mathbf{Q}$. We apply our methods to all 28 Atkin--Lehner quotients of $X_0(N)$ of genus $2$, all 97 genus $2$ curves from the LMFDB whose Jacobian is of this type and six further curves origin

Shubham Krishna, Carsten Lemmen, Serra Örey, Jennifer Rehren

Coastal ecosystems are increasingly experiencing anthropogenic pressures such as climate heating, CO2 increase, metal and organic pollution, overfishing and resource extraction. Some resulting stressors are more direct like fisheries, others more indirect like ocean acidification, yet they jointly affect marine biota, communities and entire ecosystems. While

Yuxiang Guo

Sparse attention as a efficient method can significantly decrease the computation cost, but current sparse attention tend to rely on window self attention which block the global information flow. For this problem, we present Shifted Cross Chunk Attention (SCCA), using different KV shifting strategy to extend respective field in each attention layer. Except,

Tatjana Škrbić, Achille Giacometti, Trinh X. Hoang, Amos Maritan

We present a geometrical analysis of the protrusion statistics of side chains in more than 4,000 high-resolution protein structures. We employ a coarse-grained representation of the protein backbone viewed as a linear chain of C{\alpha} atoms and consider just the heavy atoms of the side chains. We study the large variety of behaviors of the amino acids base

Shahriar Esmaeili, Navid Rajil, Ayla Hazrathosseini, Benjamin W. Neuman

The development and application of upconversion nanoparticles (UCNPs) have garnered significant attention due to their unique optical properties and potential uses in bioimaging, drug delivery, and solar cells. However, the hydrophobic nature of UCNPs presents challenges in their synthesis and application, particularly in aqueous environments. We provide an

Fausto Giunchiglia, Mayukh Bagchi

Knowledge Representation (KR) and facet-analytical Knowledge Organization (KO) have been the two most prominent methodologies of data and knowledge modelling in the Artificial Intelligence community and the Information Science community, respectively. KR boasts of a robust and scalable ecosystem of technologies to support knowledge modelling while, often, un

Ahmed Salem, Andrew Paverd, Boris Köpf

Prompt injection has emerged as a serious security threat to large language models (LLMs). At present, the current best-practice for defending against newly-discovered prompt injection techniques is to add additional guardrails to the system (e.g., by updating the system prompt or using classifiers on the input and/or output of the model.) However, in the sa

Diana Cholakova, Martin Pantov, Slavka Tcholakova, Nikolai Denkov

Crystallization of alkane mixtures has been studied extensively for decades. However, majority of the available data consider the behaviour of alkanes with chain length of 21 C-atoms or more. Furthermore, important information about the changes of the unit cell structure with temperature is practically absent. In this work, the phase behavior of several pure

Marlon Placke, Jan Schlegel, Felix Mann, Pietro Della Casa

Widespread commercial adoption of telecom-band quantum-key-distribution (QKD) will require fully integrated, room-temperature transmitters. Implementing highly efficient spontaneous parametric down-conversion (SPDC) on a platform that offers co-integration of the pump laser has been an outstanding challenge. Here, using such a platform based on AlGaAs-on-ins

Yuta Kozakai, Arashi Sakai

Let $G$ be a finite group, $N$ a normal subgroup of $G$, and $k$ a field of characteristic $p>0$. In this paper, we formulate the brick version of Clifford's theorem under suitable assumptions and prove it by using the theory of wide subcategories. As an application of our theorem, we consider the restrictions of semibricks and two-term simple-minded collect

Jingze You, Chao Huang, Hao Zhang

Recently, a novel system identification method based on invariant subspace theory is introduced, aiming to address the identification problem of continuous-time (CT) linear time-invariant (LTI) systems by combining time-domain and frequency-domain methods. Subsequently, the combined Invariant-Subspace and Subspace Identification Method (cISSIM) is introduced

Bertrand Stone, Fan Yang, Jun Yin

Consider $D$ random systems that are modeled by independent $N\times N$ complex Hermitian Wigner matrices. Suppose they are lying on a circle and the neighboring systems interact with each other through a deterministic matrix $A$. We prove that in the asymptotic limit $N\to \infty$, the whole system exhibits a quantum chaos transition when the interaction st

Lorenzo Chicchi, Lorenzo Giambagli, Lorenzo Buffoni, Raffaele Marino

This paper presents a novel approach to advancing artificial intelligence (AI) through the development of the Complex Recurrent Spectral Network ($\mathbb{C}$-RSN), an innovative variant of the Recurrent Spectral Network (RSN) model. The $\mathbb{C}$-RSN is designed to address a critical limitation in existing neural network models: their inability to emulat

Sunil Singh Bohra, Subhodeep Sarkar, Anjan Ananda Sen

In the Randall-Sundrum (RS) II braneworld scenario, general relativity (GR) is modified by adding an extra dimension such that it is indistinguishable from GR in the weak gravity limit. However, such modifications may leave a mark in the strong field regime. We therefore analyze massive scalar perturbations around rotating black holes in the RS II model. Unl

Mianzhi Pan, Jianfei Li, Mingyue Yu, Zheng Ma

Commonsense reasoning, the ability to make logical assumptions about daily scenes, is one core intelligence of human beings. In this work, we present a novel task and dataset for evaluating the ability of text-to-image generative models to conduct commonsense reasoning, which we call PAINTaboo. Given a description with few visual clues of one object, the goa

Ferheen Ayaz, Maziar Nekovee

The increasing number of Electric Vehicles (EVs) have led to rising energy demands which aggregates the burden on grid supply. A few solutions have been proposed to reduce grid load, for example, using storage systems for storing surplus energy from EVs or time-scheduling supply. These solutions are costly and limited to specific regions and times. This pape

Tatjana Škrbić, Achille Giacometti, Trinh X. Hoang, Amos Maritan

We have shown recently that the notion of poking pairwise interactions along a chain provides a unifying framework for understanding the formation of both secondary and the tertiary protein structure based on symmetry and geometry. $\alpha$-helices and $\beta$-sheets are found to be special geometries that have systematic poking contacts in a repetitive mann

Nils Wilde, Javier Alonso-Mora

We study the problem of finding statistically distinct plans for stochastic planning and task assignment problems such as online multi-robot pickup and delivery (MRPD) when facing multiple competing objectives. In many real-world settings robot fleets do not only need to fulfil delivery requests, but also have to consider auxiliary objectives such as energy

Shubhang Pandey, T G Venkatesh

Recent advances in 3D fabrication have allowed handling the memory bottlenecks for modern data-intensive applications by bringing the computation closer to the memory, enabling Near Memory Processing (NMP). Memory Centric Networks (MCN) are advanced memory architectures that use NMP architectures, where multiple stacks of the 3D memory units are equipped wit

E. D. Khoroshikh, V. G. Kurbatov

The Laguerre functions $l_{n,\tau}^\alpha$, $n=0,1,\dots$, are constructed from generalized Laguerre polynomials. The functions $l_{n,\tau}^\alpha$ depend on two parameters: scale $\tau>0$ and order of generalization $\alpha>-1$, and form an orthogonal basis in $L_2[0,\infty)$. Let the spectrum of a square matrix $A$ lie in the open left half-plane. Then the

Dongyue Huang, Minghao Dou, Xuchen Liu, Tao Sun

Coupling-Tiltable Unmanned Aerial-Aquatic Vehicles (UAAVs) have gained increasing importance, yet lack comprehensive analysis and suitable controllers. This paper analyzes the underwater motion characteristics of a self-designed UAAV, Mirs-Alioth, and designs a controller for it. The effectiveness of the controller is validated through experiments. The singu

Steven Cunnington, Laura Wolz

Estimators for $n$-point clustering statistics in Fourier-space demand that modern surveys of large-scale structure be transformed to Cartesian coordinates to perform Fast Fourier Transforms (FFTs). In this work, we explore this transformation in the context of pixelised line intensity maps (LIM), highlighting potential biasing effects on power spectrum meas

Anum Umer, Ivo Müürsepp, Muhammad Mahtab Alam, Henk Wymeersch

In this survey paper, we present an extensive review of the use of RIS in 6G radio localization, highlighting their pivotal role as a low-cost, energy-efficient technology that reshapes wireless communication and localization landscapes. Investigating the versatile capabilities of RIS, we explore their dynamic control over electromagnetic wave manipulation,

Sergio Chion, Marcos Dajczer

This paper is about non-holomorphic isometric immersions of Kaehler manifolds into Euclidean space $f\colon M^{2n}\to\R^{2n+p}$, $p\leq n-1$, with low codimension $p\leq 11$. In particular, it addresses a conjecture proposed by J. Yan and F. Zheng. The claim that if the index of complex relative nullity of the submanifold satisfies $\nu_f^c<2n-2p$ at any poi

Rafael M. Jungmann, Thaís Feliciano, Leandro A. A. Aguiar, Carina Soares-Cunha

The local field potential (LFP) is as a measure of the combined activity of neurons within a region of brain tissue. While biophysical modeling schemes for LFP in cortical circuits are well established, there is a paramount lack of understanding regarding the LFP properties along the states assumed in cortical circuits over long periods. Here we use a symbol

Han Qi, Fei Guo, Li Zhu

The multi-armed bandit(MAB) is a classical sequential decision problem. Most work requires assumptions about the reward distribution (e.g., bounded), while practitioners may have difficulty obtaining information about these distributions to design models for their problems, especially in non-stationary MAB problems. This paper aims to design a multi-armed ba

Koen van Hove, Jeroen van der Ham-de Vos, Roland van Rijswijk-Deij

It is a public secret that doing email securely is fraught with challenges. We found a vulnerability present at many email providers, allowing us to spoof email on behalf of many organisations. As email vulnerabilities are ten a penny, instead of focusing on yet another email vulnerability we ask a different question: how do organisations react to the disclo

Nathan O. Silvano, Daniel G. Barci

We investigate a two-dimensional system of interacting Active Brownian Particles. Using the Martin-Siggia-Rose-Janssen-de Dominicis formalism, we built up the generating functional for correlation functions. We study in detail the hydrodynamic regime with a constant density stationary state. Our findings reveal that, within a small density fluctuations regim

Hongwei Wen, Annika Betken, Hanyuan Hang

In domain adaptation, covariate shift and label shift problems are two distinct and complementary tasks. In covariate shift adaptation where the differences in data distribution arise from variations in feature probabilities, existing approaches naturally address this problem based on \textit{feature probability matching} (\textit{FPM}). However, for label s

Jannis O. Lübsen, Christian Hespe, Annika Eichler

Bayesian optimization has emerged as a highly effective tool for the safe online optimization of systems, due to its high sample efficiency and noise robustness. To further enhance its efficiency, reduced physical models of the system can be incorporated into the optimization process, accelerating it. These models are able to offer an approximation of the ac

Chen Huang, Peixin Qin, Wenqiang Lei, Jiancheng Lv

One of the key factors in language productivity and human cognition is the ability of systematic compositionality, which refers to understanding composed unseen examples of seen primitives. However, recent evidence reveals that the Transformers have difficulty generalizing the composed context based on the seen primitives. To this end, we take the first step

Elisa A. Tau, A. Katherina Vivas, Clara E. Martínez-Vázquez

The possible existence of stellar halos in low-mass galaxies is being intensely discussed nowadays after some recent discoveries of stars located in the outskirts of dwarf galaxies of the Local Group. RR Lyrae stars can be used to identify the extent of these structures, taking advantage of the minimization of foreground contamination they provide. In this w

Kathleen Mandt, Adrienn Luspay-Kuti, Olivier Mousis, Sarah E. Anderson

Ocean worlds, or icy bodies in the outer solar system that have or once had subsurface liquid water oceans, are among the most compelling topics of astrobiology. Typically, confirming the existence of a subsurface ocean requires close spacecraft observations. However, combining our understanding of the chemistry that takes place in a subsurface ocean with ou

Xueqin Peng, Matteo Rizzi

In this paper we prove the existence of normalized solutions $(\lambda,u)\subset (0,\infty)\times H^1(\mathbb{R}^3)$ to the following Schr\"{o}dinger-Poisson equation $$ \begin{cases} -\Delta u+V(x)u+\lambda u+(|x|^{-1}\ast u^2)u=|u|^{p-2}u&\text{in}\,\mathbb{R}^{3},\\ u>0,\quad \int_{\mathbb{R}^{3}}u^2dx=a^2, \end{cases} $$ where $a>0$ is fixed, $p\in(\frac

Shourya Bose, Kejun Chen, Yu Zhang

Convex relaxations and approximations of the optimal power flow (OPF) problem have gained significant research and industrial interest for planning and operations in electric power networks. One approach for reducing their solve times is presolving which eliminates constraints from the problem definition, thereby reducing the burden of the underlying optimiz

S. Goedhart, W. D. Cotton, F. Camilo, M. A. Thompson

We present the SARAO MeerKAT Galactic Plane Survey (SMGPS), a 1.3 GHz continuum survey of almost half of the Galactic Plane (251\deg $\le l \le$ 358\deg and 2\deg $\le l \le$ 61\deg at $|b| \le 1.5\deg $). SMGPS is the largest, most sensitive and highest angular resolution 1 GHz survey of the Plane yet carried out, with an angular resolution of 8" and a broa