Tootfinder

How Complex is a Complex Network? Insights from Linear Systems Theory
Giacomo Baggio, Marco Fabris
https://arxiv.org/abs/2507.06389 https://

How Complex is a Complex Network? Insights from Linear Systems Theory
This paper leverages linear systems theory to propose a principled measure of complexity for network systems. We focus on a network of first-order scalar linear systems interconnected through a directed graph. By locally filtering out the effect of nodal dynamics in the interconnected system, we propose a new quantitative index of network complexity rooted in the notion of McMillan degree of a linear system. First, we show that network systems with the same interconnection structure share the s…

Inward and Outward Spillover Effects of One Unit's Treatment on Network Neighbors under Partial Interference
Fei Fang, Edoardo M Airoldi, Laura Forastiere
https://arxiv.org/abs/2506.06615

Inward and Outward Spillover Effects of One Unit's Treatment on Network Neighbors under Partial Interference
In settings where interference is present, direct effects are commonly defined as the average effect of a unit's treatment on their own outcome while fixing the treatment status or probability among interfering units, and spillover effects measure the average effect of a change in the latter while the individual's treatment status is kept fixed. Here, we define the average causal effect of a unit's treatment status on the outcome of their network neighbors, while fixing the treatment probabilit…

On the Effect of Ruleset Tuning and Data Imbalance on Explainable Network Security Alert Classifications: a Case-Study on DeepCASE
Koen T. W. Teuwen, Sam Baggen, Emmanuele Zambon, Luca Allodi
https://arxiv.org/abs/2507.01571

On the Effect of Ruleset Tuning and Data Imbalance on Explainable Network Security Alert Classifications: a Case-Study on DeepCASE
Automation in Security Operations Centers (SOCs) plays a prominent role in alert classification and incident escalation. However, automated methods must be robust in the presence of imbalanced input data, which can negatively affect performance. Additionally, automated methods should make explainable decisions. In this work, we evaluate the effect of label imbalance on the classification of network intrusion alerts. As our use-case we employ DeepCASE, the state-of-the-art method for automated a…

The "Gollum effect" - wow didn't know this name, but yes, this is exactly what makes certain fields so terrible (like network science). It's just about old men behaving like Gorillas 🤮 https://www.nature.com/articles/d41586-025-01588-w
It's so n…

Science’s ‘Gollum effect’: PhDs bear brunt of territorial behaviour
Survey respondents at all career stages report colleagues engaging in territorial and possessive behaviours — but early-career researchers are most often affected.

Temporal passing network in basketball: the effect of time pressure on the dynamics of team organization at micro and meso levels
Quentin Bourgeais (CETAPS, LITIS), Rodolphe Charrier (LITIS), Eric Sanlaville (LITIS), Ludovic Seifert (CETAPS, IUF)
https://arxiv.org/abs/2506.04808

Temporal passing network in basketball: the effect of time pressure on the dynamics of team organization at micro and meso levels
In this study, basketball teams are conceptualized as complex adaptive systems to examine their (re)organizational processes in response the time remaining to shoot. Using temporal passing networks to model team behavior, the focus is on the dynamics of the temporal patterns of interaction between players. Several metrics grounded in social network analysis are calculated at different level to assess the dynamics of the patterns used by teams and of the individual roles within those patterns. T…

A Tree-guided CNN for image super-resolution
Chunwei Tian, Mingjian Song, Xiaopeng Fan, Xiangtao Zheng, Bob Zhang, David Zhang
https://arxiv.org/abs/2506.02585

A Tree-guided CNN for image super-resolution
Deep convolutional neural networks can extract more accurate structural information via deep architectures to obtain good performance in image super-resolution. However, it is not easy to find effect of important layers in a single network architecture to decrease performance of super-resolution. In this paper, we design a tree-guided CNN for image super-resolution (TSRNet). It uses a tree architecture to guide a deep network to enhance effect of key nodes to amplify the relation of hierarchica…

The Effect of Network Topology on the Equilibria of Influence-Opinion Games
Yigit Ege Bayiz, Arash Amini, Radu Marculescu, Ufuk Topcu
https://arxiv.org/abs/2506.22293

The Effect of Network Topology on the Equilibria of Influence-Opinion Games
Online social networks exert a powerful influence on public opinion. Adversaries weaponize these networks to manipulate discourse, underscoring the need for more resilient social networks. To this end, we investigate the impact of network connectivity on Stackelberg equilibria in a two-player game to shape public opinion. We model opinion evolution as a repeated competitive influence-propagation process. Players iteratively inject \textit{messages} that diffuse until reaching a steady state, mo…

Energy Efficiency Analysis of Active RIS-enhanced Wireless Network under Power-Sum Constraint
Jingdie Xin, Yan Wang, Feng Shu, Feng Zhao, Yifan Zhao, Hao Jiang
https://arxiv.org/abs/2506.02823

Energy Efficiency Analysis of Active RIS-enhanced Wireless Network under Power-Sum Constraint
Recently, as a green wireless technology, active reconfigurable intelligent surface (RIS) attracts numerous research activities due to its amplifying ability to combat the double-fading effect compared to passive one. How about its energy efficiency (EE) over passive one? Below, the EE of active RIS-aided wireless network in Rayleigh fading channels is analyzed. Using the law of large numbers, EE is derived as a function of five factors: power allocation factor, the number (N) of RIS elements, …

Decoding Cellular Temperature via Neural Network-Aided Fluorescent Thermometry
Tong Zhang, Tian-Tian Li, Jing-Ru Wang, Yu-Wen Zhang, Chao Sun, Zheng Huang, Jing-Juan Xu, Bin Kang
https://arxiv.org/abs/2506.00389

Decoding Cellular Temperature via Neural Network-Aided Fluorescent Thermometry
The temperature distribution within cells, especially the debates on mitochondrial temperature, has recently attracted widespread attention. Some studies have claimed that the temperature of mitochondria can reach up to 50-53 degrees Celsius. Yet others have questioned that this is due to measurement errors from fluorescent thermometry caused by other factors, like cell viscosity. Here we present a neural network-aided fluorescent thermometry and decouple the effect of cellular viscosity on tem…

This https://arxiv.org/abs/2412.17779 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Ergodic Network Stochastic Differential Equations
We propose a novel framework for Network Stochastic Differential Equations (N-SDE), where each node in a network is governed by an SDE influenced by interactions with its neighbors. The evolution of each node is driven by the interplay of three key components: the node's intrinsic dynamics (\emph{momentum effect}), feedback from neighboring nodes (\emph{network effect}), and a \emph{stochastic volatility} term modeled by Brownian motion. Our primary objective is to estimate the parameters of th…

Orthogonality-Constrained Deep Instrumental Variable Model for Causal Effect Estimation
Shunxin Yao
https://arxiv.org/abs/2506.02790 https://

Orthogonality-Constrained Deep Instrumental Variable Model for Causal Effect Estimation
OC-DeepIV is a neural network model designed for estimating causal effects. It characterizes heterogeneity by adding interaction features and reduces redundancy through orthogonal constraints. The model includes two feature extractors, one for the instrumental variable Z and the other for the covariate X*. The training process is divided into two stages: the first stage uses the mean squared error (MSE) loss function, and the second stage incorporates orthogonal regularization. Experimental res…

Practical insights on the effect of different encodings, ans\"atze and measurements in quantum and hybrid convolutional neural networks
Jes\'us Lozano-Cruz, Albert Nieto-Morales, Oriol Ball\'o-Gimbernat, Adan Garriga, Ant\'on Rodr\'iguez-Otero, Alejandro Borrallo-Rentero
https://arxiv.org/abs/2506.20355

Practical insights on the effect of different encodings, ansätze and measurements in quantum and hybrid convolutional neural networks
This study investigates the design choices of parameterized quantum circuits (PQCs) within quantum and hybrid convolutional neural network (HQNN and QCNN) architectures, applied to the task of satellite image classification using the EuroSAT dataset. We systematically evaluate the performance implications of data encoding techniques, variational ansätze, and measurement in approx. 500 distinct model configurations. Our analysis reveals a clear hierarchy of influence on model performance. For h…

This https://arxiv.org/abs/2404.02497 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Balancing Efficiency and Equity in Classroom Assignment under Endogenous Peer Effects
This paper presents a three-step empirical framework for optimizing classroom assignments under endogenous peer effects, using data from the China Education Panel Survey (CEPS). We design \textit{PeerNN}, a neural network that mimics endogenous network formation as a discrete choice model, generating a friendship-intensity matrix ($Ω$) that captures student popularity. \textbf{Step 2: Estimating Peer Effects.} We measure the peer effect friends' average 6th-grade class rank weighted by $Ω…

Spin Seebeck Effect of Triangular-lattice Spin Supersolid
Yuan Gao, Yixuan Huang, Sadamichi Maekawa, Wei Li
https://arxiv.org/abs/2506.22414 https://

Spin Seebeck Effect of Triangular-lattice Spin Supersolid
Using our developed thermal tensor-network approach, we investigate the spin Seebeck effect (SSE) of the triangular-lattice quantum antiferromagnet hosting spin supersolid phase. We focus on the low-temperature scaling of normalized spin current $\tilde{I}_S$ through the interface, and benchmark our approach on 1D Heisenberg chain, with the negative spinon spin current reproduced. In addition, we find an algebraic scaling $\tilde{I}_S \sim T^α$ with varying exponent $α$ in the Tomonaga-Luttin…

This https://arxiv.org/abs/2410.00075 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSI_…

Optimizing Treatment Allocation in the Presence of Interference
In Influence Maximization (IM), the objective is to -- given a budget -- select the optimal set of entities in a network to target with a treatment so as to maximize the total effect. For instance, in marketing, the objective is to target the set of customers that maximizes the total response rate, resulting from both direct treatment effects on targeted customers and indirect, spillover, effects that follow from targeting these customers. Recently, new methods to estimate treatment effects in …

A Novel Thermal Network Model and Electro-Thermal Coupling Study for NSFETs and CFETs Considering Thermal Crosstalk
Tianci Miao, Qihang Zheng, Yangyang Hu, Xiaoyu Cheng, Jie Liang, Liang Chen, Aiying Guo, Jingjing Liu, Kailin Ren, Jianhua Zhang
https://arxiv.org/abs/2506.12264

A Novel Thermal Network Model and Electro-Thermal Coupling Study for NSFETs and CFETs Considering Thermal Crosstalk
As the technology node continues to shrink, nanosheet field effect transistors (NSFETs) and complementary FETs (CFETs) become valid candidates for the 3nm and sub-nanometre nodes. However, due to the shrinking device size, self-heating and inter-device thermal crosstalk of NSFETs and CFETs become more severe. It is important to accurately calculate the self-heating and thermal crosstalk of devices and to study the electrical and thermal characteristics of logic gates, etc. In this work, a therm…

Role of bubble positioning in force induced melting of DNA
Bidisha Mukherjee, Amit Raj Singh, Garima Mishra
https://arxiv.org/abs/2506.18821 https://

Role of bubble positioning in force induced melting of DNA
We investigate the role of bubble positioning in the force-induced melting of double-stranded DNA using two distinct approaches: Brownian Dynamics simulations and the Gaussian Network Model. We isolate the effect of bubble positioning by using DNA molecules with 50% AT - 50% GC base-pair composition which ensures constant enthalpy. Our results reveal that it is not just the sequence itself, but its specific arrangement that influences DNA stability. We examine two types of DNA sequences contain…