Tootfinder

The magnon spectra of g-type altermagnet bulk CrSb
Murat Tas
https://arxiv.org/abs/2510.03759 https://arxiv.org/pdf/2510.03759

The magnon spectra of g-type altermagnet bulk CrSb
We present a calculation of the magnon spectra and chiral lifetimes of altermagnons in bulk CrSb using the many-body perturbation theory. The spin-split band structure is evident in the magnon spectra. Altermagnons attain an energy of 275 meV at the K point of the Brillouin zone. Due to large spin splitting at a specific ${\bf q}$ point along the A - M direction, lifetime differences of chiral altermagnons reach approximately 20 fs.

One of the things about long road trips is the need for housekeeping. Day six was spent in Ceduna, getting laundry done, restocking the pantry, sweeping out the van and filling gas bottles. Ceduna has a good bakery and a pub on the foreshore. #RoadTrip

Learning quadratic neural networks in high dimensions: SGD dynamics and scaling laws
G\'erard Ben Arous, Murat A. Erdogdu, N. Mert Vural, Denny Wu
https://arxiv.org/abs/2508.03688

Learning quadratic neural networks in high dimensions: SGD dynamics and scaling laws
We study the optimization and sample complexity of gradient-based training of a two-layer neural network with quadratic activation function in the high-dimensional regime, where the data is generated as $y \propto \sum_{j=1}^{r}λ_j σ\left(\langle \boldsymbol{θ_j}, \boldsymbol{x}\rangle\right), \boldsymbol{x} \sim N(0,\boldsymbol{I}_d)$, $σ$ is the 2nd Hermite polynomial, and $\lbrace\boldsymbolθ_j \rbrace_{j=1}^{r} \subset \mathbb{R}^d$ are orthonormal signal directions. We consider the ex…

AdS$_3$ black holes with primary Proca hair from regularized Gauss-Bonnet coupling
Gokhan Alkac, Murat Mesta, Gonul Unal
https://arxiv.org/abs/2508.03386 https://

AdS$_3$ black holes with primary Proca hair from regularized Gauss-Bonnet coupling
We construct a consistent three-dimensional Einstein-Gauss-Bonnet theory as a vector-tensor theory within the generalized Proca class by employing a regularization procedure based on the Weyl geometry, which was introduced recently in arXiv:2504.13084. We then obtain an asymptotically AdS$_3$, static, and circularly symmetric black hole solution with primary Proca hair. Afterwards, we investigate the effect of the scalar-tensor Gauss-Bonnet coupling constructed previously by different regulariz…

Preliminary Investigation into Uncertainty-Aware Attack Stage Classification
Alessandro Gaudenzi, Lorenzo Nodari, Lance Kaplan, Alessandra Russo, Murat Sensoy, Federico Cerutti
https://arxiv.org/abs/2508.00368

Preliminary Investigation into Uncertainty-Aware Attack Stage Classification
Advanced Persistent Threats (APTs) represent a significant challenge in cybersecurity due to their prolonged, multi-stage nature and the sophistication of their operators. Traditional detection systems typically focus on identifying malicious activity in binary terms (benign or malicious) without accounting for the progression of an attack. However, effective response strategies depend on accurate inference of the attack's current stage, as countermeasures must be tailored to whether an adversa…

C2AL: Cohort-Contrastive Auxiliary Learning for Large-scale Recommendation Systems
Mertcan Cokbas, Ziteng Liu, Zeyi Tao, Chengkai Zhang, Elder Veliz, Qin Huang, Ellie Wen, Huayu Li, Qiang Jin, Murat Duman, Benjamin Au, Guy Lebanon, Sagar Chordia
https://arxiv.org/abs/2510.02215

C2AL: Cohort-Contrastive Auxiliary Learning for Large-scale Recommendation Systems
Training large-scale recommendation models under a single global objective implicitly assumes homogeneity across user populations. However, real-world data are composites of heterogeneous cohorts with distinct conditional distributions. As models increase in scale and complexity and as more data is used for training, they become dominated by central distribution patterns, neglecting head and tail regions. This imbalance limits the model's learning ability and can result in inactive attention we…

Image-Difficulty-Aware Evaluation of Super-Resolution Models
Atakan Topaloglu, Ahmet Bilican, Cansu Korkmaz, A. Murat Tekalp
https://arxiv.org/abs/2509.26398 https://

Image-Difficulty-Aware Evaluation of Super-Resolution Models
Image super-resolution models are commonly evaluated by average scores (over some benchmark test sets), which fail to reflect the performance of these models on images of varying difficulty and that some models generate artifacts on certain difficult images, which is not reflected by the average scores. We propose difficulty-aware performance evaluation procedures to better differentiate between SISR models that produce visually different results on some images but yield close average performan…

Joint UE positioning and distributed sensing in the upper mid-band exploiting virtual apertures
Soroush Mesforush, Murat Bayraktar, Nuria Gonz\'alez-Prelcic
https://arxiv.org/abs/2509.25557

Joint UE positioning and distributed sensing in the upper mid-band exploiting virtual apertures
Networks exploiting distributed integrated sensing and communication (DISAC) nodes can provide enhanced localization and sensing performance, further emphasized when operating with large arrays and bandwidths available in the upper mid-band (also known as FR3). In this paper, we consider a DISAC system operating at FR3 where a single base station (BS) acts as the transmitter and several vehicular user equipments (UEs) act as the receivers. We tackle the design of the signal processing chain at …

Set Invariance with Probability One for Controlled Diffusion: Score-based Approach
Wenqing Wang, Alexis M. H. Teter, Murat Arcak, Abhishek Halder
https://arxiv.org/abs/2507.22385

Set Invariance with Probability One for Controlled Diffusion: Score-based Approach
Given a controlled diffusion and a connected, bounded, Lipschitz set, when is it possible to guarantee controlled set invariance with probability one? In this work, we answer this question by deriving the necessary and sufficient conditions for the same in terms of gradients of certain log-likelihoods -- a.k.a. score vector fields -- for two cases: given finite time horizon and infinite time horizon. The deduced conditions comprise a score-based test that provably certifies or falsifies the exi…

From GPUs to RRAMs: Distributed In-Memory Primal-Dual Hybrid Gradient Method for Solving Large-Scale Linear Optimization Problem
Huynh Q. N. Vo, Md Tawsif Rahman Chowdhury, Paritosh Ramanan, Gozde Tutuncuoglu, Junchi Yang, Feng Qiu, Murat Yildirim
https://arxiv.org/abs/2509.21137

From GPUs to RRAMs: Distributed In-Memory Primal-Dual Hybrid Gradient Method for Solving Large-Scale Linear Optimization Problem
The exponential growth of computational workloads is surpassing the capabilities of conventional architectures, which are constrained by fundamental limits. In-memory computing (IMC) with RRAM provides a promising alternative by providing analog computations with significant gains in latency and energy use. However, existing algorithms developed for conventional architectures do not translate to IMC, particularly for constrained optimization problems where frequent matrix reprogramming remains …

Quantum teleportation of an elemental silicon nanophotonic CNOT gate
Kai-Chi Chang, Xiang Cheng, Felix Ribuot-Hirsch, Murat Can Sarihan, Yujie Chen, Jaime Gonzalo Flor Flores, Mingbin Yu, Patrick Guo-Qiang Lo, Dim-Lee Kwong, Chee Wei Wong
https://arxiv.org/abs/2507.16783

Quantum teleportation of an elemental silicon nanophotonic CNOT gate
Large-scale quantum computers possess the capacity to effectively tackle practical problems that can be insurmountable for classical computers. The main challenge in building these quantum computers is to realize scalable modules for remote qubits and entanglement. By assembling small, specialized parts into a larger architecture, the modular approach mitigates complexity and uncertainty. Such a distributed architecture requires non-local quantum gate operations between remote qubits. An essent…

Semantic Edge-Cloud Communication for Real-Time Urban Traffic Surveillance with ViT and LLMs over Mobile Networks
Murat Arda Onsu, Poonam Lohan, Burak Kantarci, Aisha Syed, Matthew Andrews, Sean Kennedy
https://arxiv.org/abs/2509.21259

Semantic Edge-Cloud Communication for Real-Time Urban Traffic Surveillance with ViT and LLMs over Mobile Networks
Real-time urban traffic surveillance is vital for Intelligent Transportation Systems (ITS) to ensure road safety, optimize traffic flow, track vehicle trajectories, and prevent collisions in smart cities. Deploying edge cameras across urban environments is a standard practice for monitoring road conditions. However, integrating these with intelligent models requires a robust understanding of dynamic traffic scenarios and a responsive interface for user interaction. Although multimodal Large Lan…

On the consistency of non-commutative geometry inspired Reissner-Nordstr\"{o}m black hole solution
Gokhan Alkac, Murat Mesta, Gonul Unal
https://arxiv.org/abs/2507.16780

On the consistency of non-commutative geometry inspired Reissner-Nordström black hole solution
We revisit the non-commutative geometry inspired Reissner-Nordström black hole solution obtained by smearing the point sources with a Gaussian distribution. We show that while the form of the metric function and the physical properties derived from that remain valid, not all the components of Einstein equations are satisfied. We construct an improved energy-momentum tensor that consistently satisfies Einstein equations and show that it leads to a different prediction for the region where the s…

TRUST 2025: SCRITA and RTSS @ RO-MAN 2025
Alessandra Rossi, Patrick Holthaus, Gabriella Lakatos, S\'ilvia Moros, Ali Fallahi, Murat Kirtay, Marie Postma, Erhan Oztop
https://arxiv.org/abs/2509.11402

TRUST 2025: SCRITA and RTSS @ RO-MAN 2025
The TRUST workshop is the result of a collaboration between two established workshops in the field of Human-Robot Interaction: SCRITA (Trust, Acceptance and Social Cues in Human-Robot Interaction) and RTSS (Robot Trust for Symbiotic Societies). This joint initiative brings together the complementary goals of these workshops to advance research on trust from both the human and robot perspectives. Website: https://scrita.herts.ac.uk/2025/

Hijacking Living Cells with Surface Engineering for the Internet of Bio-Nano Things
Ekin Ince, Murat Kuscu
https://arxiv.org/abs/2509.17227 https://arxiv.o…

Hijacking Living Cells with Surface Engineering for the Internet of Bio-Nano Things
The Internet of Bio-Nano Things (IoBNT) promises to revolutionize healthcare by interfacing the cyber domain with the living systems at unprecedented resolution. Realizing this vision hinges on the development of Bio-Nano Things (BNTs), i.e., functional nodes capable of sensing, actuation, and communications within biological environments. Existing BNT architectures, e.g., nanomaterial-based, biosynthetic, and passive molecular agents, face significant limitations, including toxicity, lack of a…

A Framework for Energy Management Modelling in Hubs for Circularity
Tobias L{\o}vebakke Nielsen, Daniela Guericke, Alessio Trivella, Devrim Murat Yazan
https://arxiv.org/abs/2508.19765

A Framework for Energy Management Modelling in Hubs for Circularity
The concept Hubs for Circularity (H4C) represents integrated systems that combine efficient use of clean energy and circular economy to enhance resource efficiency within a region. H4C benefit from the geographical proximity of different industries within industrial zones and the surrounding urban and rural areas, allowing them to share resources, technology, and infrastructure. They reduce the use of virgin resources through Industrial Symbiosis (IS), where one company uses waste of another co…

Replaced article(s) found for hep-ph. https://arxiv.org/list/hep-ph/new
[1/2]:
- Dirac Neutrinos and Dark Matter within a Minimal Discrete Symmetry Model
Yakefu Reyimuaji, Murat Abdughani

Crosslisted article(s) found for cs.IR. https://arxiv.org/list/cs.IR/new
[1/1]:
- Identifying Information Technology Research Trends through Text Mining of NSF Awards
Said Varlioglu, Hazem Said, Murat Ozer, Nelly Elsayed

Chemical Enrichment of Isolated Relic Galaxy Mrk1216
M. K{\i}yami Erdim, Emine G\"ulmez, Murat H\"udaverdi
https://arxiv.org/abs/2509.14613 https://

Chemical Enrichment of Isolated Relic Galaxy Mrk1216
In this study, we investigate the chemical enrichment and structural evolution of the isolated elliptical relic galaxy Mrk1216 through X-ray observations. As a red-nugget relic, Mrk1216 provides a rare window into the early Universe, owing to its minimal interaction with the surrounding environment. Using data from the XMM-Newton telescope, we model the X-ray emission of its interstellar medium to derive radial temperature and abundance profiles. We find that the central region exhibits an elev…

Identifying Information Technology Research Trends through Text Mining of NSF Awards
Said Varlioglu, Hazem Said, Murat Ozer, Nelly Elsayed
https://arxiv.org/abs/2509.12245 https…

Identifying Information Technology Research Trends through Text Mining of NSF Awards
Information Technology (IT) is recognized as an independent and unique research field. However, there has been ambiguity and difficulty in identifying and differentiating IT research from other close variations. Given this context, this paper aimed to explore the roots of the Information Technology (IT) research domain by conducting a large-scale text mining analysis of 50,780 abstracts from awarded NSF CISE grants from 1985 to 2024. We categorized the awards based on their program content, lab…

Multimodal Quantum Vision Transformer for Enzyme Commission Classification from Biochemical Representations
Murat Isik, Mandeep Kaur Saggi, Humaira Gowher, Sabre Kais
https://arxiv.org/abs/2508.14844

Multimodal Quantum Vision Transformer for Enzyme Commission Classification from Biochemical Representations
Accurately predicting enzyme functionality remains one of the major challenges in computational biology, particularly for enzymes with limited structural annotations or sequence homology. We present a novel multimodal Quantum Machine Learning (QML) framework that enhances Enzyme Commission (EC) classification by integrating four complementary biochemical modalities: protein sequence embeddings, quantum-derived electronic descriptors, molecular graph structures, and 2D molecular image representa…

Exceptionality, Supersymmetry and Non-associativity in Physics
Murat Gunaydin
https://arxiv.org/abs/2507.17938 https://arxiv.org/pdf/2507.17938

Exceptionality, Supersymmetry and Non-associativity in Physics
This is an expanded and updated version of the talk I gave at the meeting organized at CERN on April 27-28, 2015 dedicated to honoring the memory of Bruno Zumino and his legacy. In this talk I review the emergence of exceptional structures and non-associative algebras in quantum mechanics, supergravity and M/superstring theories.

A Fuzzy Supervisor Agent Design for Clinical Reasoning Assistance in a Multi-Agent Educational Clinical Scenario Simulation
Weibing Zheng, Laurah Turner, Jess Kropczynski, Murat Ozer, Seth Overla, Shane Halse
https://arxiv.org/abs/2507.05275

A Fuzzy Supervisor Agent Design for Clinical Reasoning Assistance in a Multi-Agent Educational Clinical Scenario Simulation
Assisting medical students with clinical reasoning (CR) during clinical scenario training remains a persistent challenge in medical education. This paper presents the design and architecture of the Fuzzy Supervisor Agent (FSA), a novel component for the Multi-Agent Educational Clinical Scenario Simulation (MAECSS) platform. The FSA leverages a Fuzzy Inference System (FIS) to continuously interpret student interactions with specialized clinical agents (e.g., patient, physical exam, diagnostic, i…

Spatial Encoding of Flow Spaces for Intelligent SDN Applications
Abdur Rouf, Murat Yuksel
https://arxiv.org/abs/2509.16485 https://arxiv.org/pdf/2509.16485…

Spatial Encoding of Flow Spaces for Intelligent SDN Applications
Efficient encoding of network flow spaces while preserving spatial locality is essential for intelligent Software-Defined Networking (SDN) applications, particularly those employing reinforcement learning (RL) methods in a reactive manner. In this work, we introduce a spatially aware Bloom Filter-based approach to encode IP flow pairs, leveraging their inherent geographical locality. Through controlled experiments using IoT traffic data, we demonstrate that Bloom Filters effectively preserve sp…

Non-invasive Reversible Software-based Configuration of a Clinically Used Linear Accelerator for Preclinical Electron FLASH Radiobiology
Stavros Melemenidis, Dixin Chen, Cody Jensen, Joseph B. Schulz, Murat Surucu, Amy S. Yu, Edward E. Graves, Mengying Shi, Michael Reilly, Peter G. Maxim, Andrew Currell, Billy W. Loo Jr, Lawrie Skinner, M. Ramish Ashraf
https:/…

Non-invasive Reversible Software-based Configuration of a Clinically Used Linear Accelerator for Preclinical Electron FLASH Radiobiology
Configuring clinical linear accelerators (linacs) for ultra-high dose rate (UHDR) electron experiments typically requires invasive hardware manipulation and/or irreversible manufacturer modifications, limiting broader implementation. We present an independently developed UHDR electron configuration of a clinical TrueBeam linac that allows reversible switching between preclinical UHDR and conventional (CONV) modes using only non-invasive software settings. UHDR mode was achieved via service mode…

A Refined Alternating Optimization for Sum Rate Maximization in SIM-Aided Multiuser MISO Systems
Eduard E. Bahingayi, Shuying Lin, Murat Uysal, Marco Di Renzo, Le-Nam Tran
https://arxiv.org/abs/2508.15257

A Refined Alternating Optimization for Sum Rate Maximization in SIM-Aided Multiuser MISO Systems
Stacked intelligent metasurfaces (SIMs) have emerged as a disruptive technology for future wireless networks. To investigate their capabilities, we study the sum rate maximization problem in an SIM-based multiuser (MU) multiple-input single-output (MISO) downlink system. A vast majority of pioneer studies, if not all, address this fundamental problem using the prevailing alternating optimization (AO) framework, where the digital beamforming (DB) and SIM phase shifts are optimized alternately. H…

Harnessing the Full Potential of RRAMs through Scalable and Distributed In-Memory Computing with Integrated Error Correction
Huynh Q. N. Vo, Md Tawsif Rahman Chowdhury, Paritosh Ramanan, Murat Yildirim, Gozde Tutuncuoglu
https://arxiv.org/abs/2508.13298

Harnessing the Full Potential of RRAMs through Scalable and Distributed In-Memory Computing with Integrated Error Correction
Exponential growth in global computing demand is exacerbated due to the higher-energy requirements of conventional architectures, primarily due to energy-intensive data movement. In-memory computing with Resistive Random Access Memory (RRAM) addresses this by co-integrating memory and processing, but faces significant hurdles related to device-level non-idealities and poor scalability for large computing tasks. Here, we introduce \textbf{MELISO+} (In-\textbf{Me}mory \textbf{Li}near \textbf{So}l…

Crosslisted article(s) found for q-bio.QM. https://arxiv.org/list/q-bio.QM/new
[1/1]:
- STL-based Optimization of Biomolecular Neural Networks for Regression and Control
Eric Palanques-Tost, Hanna Krasowski, Murat Arcak, Ron Weiss, Calin Belta

Replaced article(s) found for cs.ET. https://arxiv.org/list/cs.ET/new
[1/1]:
- Molecular Communication Channel as a Physical Reservoir Computer
Mustafa Uzun, Kaan Burak Ikiz, Murat Kuscu

Electromagnetic Simulations of Antennas on GPUs for Machine Learning Applications
Murat Temiz, Vemund Bakken
https://arxiv.org/abs/2508.10713 https://arxiv…

Electromagnetic Simulations of Antennas on GPUs for Machine Learning Applications
This study proposes an antenna simulation framework powered by graphics processing units (GPUs) based on an open-source electromagnetic (EM) simulation software (gprMax) for machine learning applications of antenna design and optimization. Furthermore, it compares the simulation results with those obtained through commercial EM software. The proposed software framework for machine learning and surrogate model applications will produce antenna data sets consisting of a large number of antenna si…

Thermal Conductivity Limits of MoS$_2$ and MoSe$_2$: Revisiting High-Order Anharmonic Lattice Dynamics with Machine Learning Potentials
Tugbey Kocabas, Murat Keceli, Tanju Gurel, Milorad Milosevic, Cem Sevik
https://arxiv.org/abs/2509.13798

Thermal Conductivity Limits of MoS$_2$ and MoSe$_2$: Revisiting High-Order Anharmonic Lattice Dynamics with Machine Learning Potentials
Group-VI transition metal dichalcogenides (TMDs), MoS$_2$ and MoSe$_2$, have emerged as prototypical low-dimensional systems with distinctive phononic and electronic properties, making them attractive for applications in nanoelectronics, optoelectronics, and thermoelectrics. Yet, their reported lattice thermal conductivities ($κ$) remain highly inconsistent, with experimental values and theoretical predictions differing by more than an order of magnitude. These discrepancies stem from uncertai…

Regular AdS$_3$ black holes from regularized Gauss-Bonnet coupling
Gokhan Alkac, Murat Mesta, Gonul Unal
https://arxiv.org/abs/2508.14010 https://arxiv.org…

Regular AdS$_3$ black holes from regularized Gauss-Bonnet coupling
We obtain a three-dimensional bi-vector-tensor theory of the generalized Proca class by regularizing the Gauss-Bonnet invariant within the Weyl geometry. We show that the theory admits a regular AdS$_3$ black hole solution with primary hairs. Introducing a deformation in the theory, a different regular AdS$_3$ black hole solution is obtained. Charged generalizations of these solutions are given by coupling to Born-Infeld electrodynamics.

Crosslisted article(s) found for q-bio.MN. https://arxiv.org/list/q-bio.MN/new
[1/1]:
- STL-based Optimization of Biomolecular Neural Networks for Regression and Control
Eric Palanques-Tost, Hanna Krasowski, Murat Arcak, Ron Weiss, Calin Belta

Affine Frequency Division Multiplexing with Subcarrier Power-Level Index Modulation for Integrated Sensing and Communications
Murat Temiz, Christos Masouros
https://arxiv.org/abs/2508.10783

Affine Frequency Division Multiplexing with Subcarrier Power-Level Index Modulation for Integrated Sensing and Communications
This study proposes an index modulation (IM) technique for affine frequency division multiplexing (AFDM) signals and examines its communication and sensing performance toward integrated sensing and communication (ISAC) systems. The power levels of subcarriers are utilized as modulation indices while also transmitting data symbols within each subcarrier. Thus, the proposed AFDM with subcarrier power-level index modulation (AFDM-PLIM) maintains all subcarriers active at all times to achieve a hig…

A Stochastic Programming Approach to the Railcar Maintenance Problem with Service Level and Track Capacity Considerations
Murat Elh\"useyni, Burak Kocuk
https://arxiv.org/abs/2509.08427

A Stochastic Programming Approach to the Railcar Maintenance Problem with Service Level and Track Capacity Considerations
Railcars, as part of the rolling stock, perform regular transportation tasks with respect to a service level agreement (SLA) and undergo preventive maintenance at regular intervals based on the recommendations of train manufacturers. When unexpected failures occur, they need to enter corrective maintenance immediately. However, this reactive approach may result in large SLA violations and an excessive number of corrective maintenance actions. In this study, we utilize a predictive maintenance a…

Laser-Induced Topological Toggle Switching at Room Temperature in the van der Waals Ferromagnet \ce{Fe3GaTe2}
Charlie W. F. Freeman, Woohyun Cho, Paul S. Keatley, PeiYu Cai, Elton J. G. Santos, Robert J. Hicken, H. Yang, Hidekazu Kurebayashi, Murat Cubukcu, Maciej Dabrowski
https://arxiv.org/abs/2507.12959

Laser-Induced Topological Toggle Switching at Room Temperature in the van der Waals Ferromagnet \ce{Fe3GaTe2}
We demonstrate room-temperature nucleation and manipulation of topological spin textures in the van der Waals (vdW) ferromagnet, Fe3GaTe2, through laser pulse excitation. By leveraging laser-induced heating and subsequent cooling, we access the skyrmion/bubble state at low fields and achieve toggle switching between two topological spin textures - skyrmion/bubble and labyrinth. Micromagnetic simulations reveal that this switching behaviour arises from laser-induced heating and cooling. Our find…

Comparative Analysis of Attention Mechanisms for Automatic Modulation Classification in Radio Frequency Signals
Ferhat Ozgur Catak, Murat Kuzlu, Umit Cali
https://arxiv.org/abs/2508.09996

Comparative Analysis of Attention Mechanisms for Automatic Modulation Classification in Radio Frequency Signals
Automatic Modulation Classification (AMC) is a critical component in cognitive radio systems and spectrum management applications. This study presents a comprehensive comparative analysis of three attention mechanisms (i.e., baseline multi-head attention, causal attention, and sparse attention) integrated with Convolutional Neural Networks (CNNs) for radio frequency (RF) signal classification. It proposes a novel CNN-Transformer hybrid architecture that leverages different attention patterns to…

On-Dyn-CDA: A Real-Time Cost-Driven Task Offloading Algorithm for Vehicular Networks with Reduced Latency and Task Loss
Mahsa Paknejad, Parisa Fard Moshiri, Murat Simsek, Burak Kantarci, Hussein T. Mouftah
https://arxiv.org/abs/2509.05889

On-Dyn-CDA: A Real-Time Cost-Driven Task Offloading Algorithm for Vehicular Networks with Reduced Latency and Task Loss
Real-time task processing is a critical challenge in vehicular networks, where achieving low latency and minimizing dropped task ratio depend on efficient task execution. Our primary objective is to maximize the number of completed tasks while minimizing overall latency, with a particular focus on reducing number of dropped tasks. To this end, we investigate both static and dynamic versions of an optimization algorithm. The static version assumes full task availability, while the dynamic versio…

Scalable Production of Photochromic Yttrium Oxyhydride Powder via Ball Milling
Elbruz Murat Baba, Stefano Deledda, Smagul Karazhanov
https://arxiv.org/abs/2508.06200 https://

Scalable Production of Photochromic Yttrium Oxyhydride Powder via Ball Milling
Yttrium oxyhydride (YHO) represents one of the most promising photochromic materials discovered in recent years, yet its practical deployment has been severely constrained by the limitations of thin film deposition methods. Here we demonstrate the first successful synthesis of photochromic YHO powders through reactive ball milling under hydrogen atmosphere followed by controlled oxidation a fundamentally scalable approach that overcomes the production barriers facing this technology. High-energ…

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities
Murat Temiz, Yongwei Zhang, Yanwei Fu, Chi Zhang, Chenfeng Meng, Orhan Kaplan, Christos Masouros
https://arxiv.org/abs/2509.06968

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities
This article comprehensively reviews recent developments and research on deep learning-based (DL-based) techniques for integrated sensing and communication (ISAC) systems. ISAC, which combines sensing and communication functionalities, is regarded as a key enabler for 6G and beyond networks, as many emerging applications, such as vehicular networks and industrial robotics, necessitate both sensing and communication capabilities for effective operation. A unified platform that provides both func…

Multi-Functional Chirp Signalling for Next-Generation Multi-Carrier Wireless Networks: Communications, Sensing and ISAC Perspectives
Zeping Sui, Qu Luo, Zilong Liu, Murat Temiz, Leila Musavian, Christos Masouros, Yong Liang Guan, Pei Xiao, Lajos Hanzo
https://arxiv.org/abs/2508.06022

Multi-Functional Chirp Signalling for Next-Generation Multi-Carrier Wireless Networks: Communications, Sensing and ISAC Perspectives
To meet the increasingly demanding quality-of-service requirements of the next-generation multi-carrier mobile networks, it is essential to design multi-functional signalling schemes facilitating efficient, flexible, and reliable communication and sensing in complex wireless environments. As a compelling candidate, we advocate chirp signalling, beneficially amalgamating sequences (e.g., Zadoff-Chu sequences) with waveforms (e.g., chirp spread spectrum and frequency-modulated continuous wave (FM…