Tootfinder

Completions of Restricted Complexity I, Weak Arithmetical Theories
Ali Enayat, Mateusz {\L}e{\l}yk, Albert Visser
https://arxiv.org/abs/2508.14758 https://…

Completions of Restricted Complexity I, Weak Arithmetical Theories
Given a first-order theory $T$ formulated in the usual language of first-order arithmetic, we say that $T$ is of *restricted complexity* if there is some natural number $n$ and some set $\mathcal A$ of $Σ_n$-sentences such that $T$ can be axiomatized by $\mathcal A$. Motivated by the fact that no consistent arithmetical theory extending $\mathrm{I}Δ_{0}+\mathsf{Exp}$ has a consistent completion that is of restricted complexity, we construct models of arithmetic whose complete theories are of …

HERAKLES: Hierarchical Skill Compilation for Open-ended LLM Agents
Thomas Carta, Cl\'ement Romac, Loris Gaven, Pierre-Yves Oudeyer, Olivier Sigaud, Sylvain Lamprier
https://arxiv.org/abs/2508.14751

HERAKLES: Hierarchical Skill Compilation for Open-ended LLM Agents
Open-ended AI agents need to be able to learn efficiently goals of increasing complexity, abstraction and heterogeneity over their lifetime. Beyond sampling efficiently their own goals, autotelic agents specifically need to be able to keep the growing complexity of goals under control, limiting the associated growth in sample and computational complexity. To adress this challenge, recent approaches have leveraged hierarchical reinforcement learning (HRL) and language, capitalizing on its compos…

Effects of Cognitive Distraction and Driving Environment Complexity on Adaptive Cruise Control Use and Its Impact on Driving Performance: A Simulator Study
Ana\"is Halin, Marc Van Droogenbroeck, Christel Devue
https://arxiv.org/abs/2507.13886

Effects of Cognitive Distraction and Driving Environment Complexity on Adaptive Cruise Control Use and Its Impact on Driving Performance: A Simulator Study
In this simulator study, we adopt a human-centered approach to explore whether and how drivers' cognitive state and driving environment complexity influence reliance on driving automation features. Besides, we examine whether such reliance affects driving performance. Participants operated a vehicle equipped with adaptive cruise control (ACC) in a simulator across six predefined driving scenarios varying in traffic conditions while either performing a cognitively demanding task (i.e., respondin…

On subshifts with low maximal pattern complexity
Anh N. Le, Ronnie Pavlov, Casey Schlortt
https://arxiv.org/abs/2508.13420 https://arxiv.org/pdf/2508.13420…

On subshifts with low maximal pattern complexity
For a finite alphabet $\mathcal{A}$ and a sequence $x \in \mathcal{A}^{\mathbb{N}}$, Kamae and Zamboni defined the maximal pattern complexity function $p^*_x(n)$ as a natural generalization of usual word complexity. They defined a nonperiodic sequence $x$ to be pattern Sturmian if it achieves the minimal growth rate $p^*_x(n) = 2n$, and asked the question of whether one could classify recurrent pattern Sturmian sequences. We answer their question by characterizing recurrent pattern Sturmian s…

Loss-Complexity Landscape and Model Structure Functions
Alexander Kolpakov
https://arxiv.org/abs/2507.13543 https://arxiv.org/pdf/250…

Loss-Complexity Landscape and Model Structure Functions
We develop a framework for dualizing the Kolmogorov structure function $h_x(α)$, which then allows using computable complexity proxies. We establish a mathematical analogy between information-theoretic constructs and statistical mechanics, introducing a suitable partition function and free energy functional. We explicitly prove the Legendre-Fenchel duality between the structure function and free energy, showing detailed balance of the Metropolis kernel, and interpret acceptance probabilities a…

Krylov Complexity for Open Quantum System: Dissipation and Decoherence
Arpan Bhattacharyya, Sayed Gool, S. Shajidul Haque
https://arxiv.org/abs/2509.14810 https://

Krylov Complexity for Open Quantum System: Dissipation and Decoherence
We investigate Krylov complexity in open quantum systems using Lindblad master equations for bosonic bath models, with particular emphasis on the Caldeira--Leggett model. Krylov complexity is computed from the moments of the two-point function within the standard master equation framework. For the damped harmonic oscillator, the results reveal clear dissipative features in Krylov complexity. In the Caldeira--Leggett model, in the high-temperature limit, we find that Krylov complexity saturates …

Complexity of Abduction in \L{}ukasiewicz Logic
Katsumi Inoue, Daniil Kozhemiachenko
https://arxiv.org/abs/2507.13847 https://arxiv.o…

Complexity of Abduction in Łukasiewicz Logic
We explore the problem of explaining observations in contexts involving statements with truth degrees such as `the lift is loaded', `the symptoms are severe', etc. To formalise these contexts, we consider infinitely-valued Łukasiewicz fuzzy logic. We define and motivate the notions of abduction problems and explanations in the language of Łukasiewicz logic expanded with `interval literals' of the form $p\geq\mathbf{c}$, $p\leq\mathbf{c}$, and their negations that express the set of values a v…

Role of Non-conserved Gravity Theory and Electric Charge in Constructing Complexity-free Stellar Models: A Novel Approach under Non-minimal Coupling
Tayyab Naseer
https://arxiv.org/abs/2508.13903

Role of Non-conserved Gravity Theory and Electric Charge in Constructing Complexity-free Stellar Models: A Novel Approach under Non-minimal Coupling
This study explores the application of complexity factor within the context of Rastall gravity, exploring its implications on a static spacetime admitting spherical symmetry associated with anisotropic fluids under an electromagnetic field. The field equations are derived for a static charged sphere that provides a foundational framework for analyzing gravitational effects in this non-conserved theory. The mass function is formulated by incorporating both fluid and geometric parameters, offerin…

Guard [.] io says a new era of scam complexity is on the way because AI-powered browsers can interact with phishing pages and malicious prompts without human detection.
https://guard.io/labs/scamlexity-we-put-agentic-ai-browsers-to-t…

"Scamlexity": When Agentic AI Browsers Get Scammed
We Put Agentic AI Browsers to the Test - They Clicked, They Paid, They Failed

"When you work on anything, you want to find the range of impulses. which ones get portrayed is another question, but you want to have that complexity and that fullness, even if you’re playing a cartoon character."
—Willem Dafoe
#acting #coaching

Last-Iterate Complexity of SGD for Convex and Smooth Stochastic Problems
Guillaume Garrigos, Daniel Cortild, Lucas Ketels, Juan Peypouquet
https://arxiv.org/abs/2507.14122

Last-Iterate Complexity of SGD for Convex and Smooth Stochastic Problems
Most results on Stochastic Gradient Descent (SGD) in the convex and smooth setting are presented under the form of bounds on the ergodic function value gap. It is an open question whether bounds can be derived directly on the last iterate of SGD in this context. Recent advances suggest that it should be possible. For instance, it can be achieved by making the additional, yet unverifiable, assumption that the variance of the stochastic gradients is uniformly bounded. In this paper, we show that …

Crosslisted article(s) found for cs.CC. https://arxiv.org/list/cs.CC/new
[1/1]:
- Multi-Metric Algorithmic Complexity: Beyond Asymptotic Analysis
Sergii Kavun
htt…

Multi-Metric Algorithmic Complexity: Beyond Asymptotic Analysis
Sergii Kavun
https://arxiv.org/abs/2508.13249 https://arxiv.org/pdf/2508.13249

Multi-Metric Algorithmic Complexity: Beyond Asymptotic Analysis
Traditional algorithm analysis treats all basic operations as equally costly, which hides significant differences in time, energy consumption, and cost between different types of computations on modern processors. We propose a weighted-operation complexity model that assigns realistic cost values to different instruction types across multiple dimensions: computational effort, energy usage, carbon footprint, and monetary cost. The model computes overall efficiency scores based on user-defined pr…

On the Complexity of Decoded Quantum Interferometry
Kunal Marwaha, Bill Fefferman, Alexandru Gheorghiu, Vojtech Havlicek
https://arxiv.org/abs/2509.14443 https://

On the Complexity of Decoded Quantum Interferometry
We study the complexity of Decoded Quantum Interferometry (DQI), a recently proposed quantum algorithm for approximate optimization. We argue that DQI is hard to classically simulate, and that the hardness comes from locating an exponentially large hidden subset. This type of hardness is shared by Shor's algorithm, but the hidden subset here has no apparent group structure. We first prove that DQI can be simulated in a low level of the polynomial hierarchy, ruling out hardness arguments related…

Encoding Optimization for Low-Complexity Spiking Neural Network Equalizers in IM/DD Systems
Eike-Manuel Edelmann, Alexander von Bank, Laurent Schmalen
https://arxiv.org/abs/2508.13783

Encoding Optimization for Low-Complexity Spiking Neural Network Equalizers in IM/DD Systems
Neural encoding parameters for spiking neural networks (SNNs) are typically set heuristically. We propose a reinforcement learning-based algorithm to optimize them. Applied to an SNN-based equalizer and demapper in an IM/DD system, the method improves performance while reducing computational load and network size.

On computing and the complexity of computing higher-order $U$-statistics, exactly
Xingyu Chen, Ruiqi Zhang, Lin Liu
https://arxiv.org/abs/2508.12627 https://

On computing and the complexity of computing higher-order $U$-statistics, exactly
Higher-order $U$-statistics abound in fields such as statistics, machine learning, and computer science, but are known to be highly time-consuming to compute in practice. Despite their widespread appearance, a comprehensive study of their computational complexity is surprisingly lacking. This paper aims to fill that gap by presenting several results related to the computational aspect of $U$-statistics. First, we derive a useful decomposition from an $m$-th order $U$-statistic to a linear combi…

A Multi-Agent Approach to Neurological Clinical Reasoning
Moran Sorka, Alon Gorenshtein, Dvir Aran, Shahar Shelly
https://arxiv.org/abs/2508.14063 https://…

A Multi-Agent Approach to Neurological Clinical Reasoning
Large language models (LLMs) have shown promise in medical domains, but their ability to handle specialized neurological reasoning requires systematic evaluation. We developed a comprehensive benchmark using 305 questions from Israeli Board Certification Exams in Neurology, classified along three complexity dimensions: factual knowledge depth, clinical concept integration, and reasoning complexity. We evaluated ten LLMs using base models, retrieval-augmented generation (RAG), and a novel multi-…

from my link log —
RE#: high performance derivative-based regex matching with intersection, complement, and lookarounds.
https://arxiv.org/abs/2407.20479
saved 2025-04-17

RE#: High Performance Derivative-Based Regex Matching with Intersection, Complement and Lookarounds
We present a tool and theory RE# for regular expression matching that is built on symbolic derivatives, does not use backtracking, and, in addition to the classical operators, also supports complement, intersection and lookarounds. We develop the theory formally and show that the main matching algorithm has input-linear complexity both in theory as well as experimentally. We apply thorough evaluation on popular benchmarks that show that RE# is over 71% faster than the next fastest regex engine …

New examples of words for which the binomial complexities and the subword complexity coincide
L\'eo Vivion
https://arxiv.org/abs/2509.11172 https://arx…

New examples of words for which the binomial complexities and the subword complexity coincide
The complexity of an infinite word can be measured in several ways, the two most common measures being the subword complexity and the abelian complexity. In 2015, Rigo and Salimov introduced a family of intermediate complexities indexed by $k\in\mathbb{N}_{>0}$: the $k$-binomial complexities. These complexities scale up from the abelian complexity, with which the $1$-binomial complexity coincides, to the subword complexity, to which they converge pointwise as $k$ tends to $\infty$. In this arti…

Round-Preserving Asymptotic Compression of Prior-Free Interactive Protocols
Gurleen Padda, Dave Touchette
https://arxiv.org/abs/2507.13464 https://

Round-Preserving Asymptotic Compression of Prior-Free Interactive Protocols
There is a close relationship between the communication complexity and information complexity of communication problems, as demonstrated by results such as Shannon's noiseless source coding theorem, and the Slepian-Wolf theorem. Here, we study this relationship in the prior-free and interactive setting, where we provide an alternate proof for the result of Braverman [SIAM Review, vol. 59, no. 4, 2017], that the amortized communication complexity of simulating a prior-free interactive communicat…

CrafterDojo: A Suite of Foundation Models for Building Open-Ended Embodied Agents in Crafter
Junyeong Park, Hyeonseo Cho, Sungjin Ahn
https://arxiv.org/abs/2508.13530 https://…

CrafterDojo: A Suite of Foundation Models for Building Open-Ended Embodied Agents in Crafter
Developing general-purpose embodied agents is a core challenge in AI. Minecraft provides rich complexity and internet-scale data, but its slow speed and engineering overhead make it unsuitable for rapid prototyping. Crafter offers a lightweight alternative that retains key challenges from Minecraft, yet its use has remained limited to narrow tasks due to the absence of foundation models that have driven progress in the Minecraft setting. In this paper, we present CrafterDojo, a suite of foundat…

Training-free Token Reduction for Vision Mamba
Qiankun Ma, Ziyao Zhang, Chi Su, Jie Chen, Zhen Song, Hairong Zheng, Wen Gao
https://arxiv.org/abs/2507.14042

Training-free Token Reduction for Vision Mamba
Vision Mamba has emerged as a strong competitor to Vision Transformers (ViTs) due to its ability to efficiently capture long-range dependencies with linear computational complexity. While token reduction, an effective compression technique in ViTs, has rarely been explored in Vision Mamba. Exploring Vision Mamba's efficiency is essential for enabling broader applications. However, we find that directly applying existing token reduction techniques for ViTs to Vision Mamba leads to significant pe…

InTraVisTo: Inside Transformer Visualisation Tool
Nicol\`o Brunello, Davide Rigamonti, Andrea Sassella, Vincenzo Scotti, Mark James Carman
https://arxiv.org/abs/2507.13858

InTraVisTo: Inside Transformer Visualisation Tool
The reasoning capabilities of Large Language Models (LLMs) have increased greatly over the last few years, as have their size and complexity. Nonetheless, the use of LLMs in production remains challenging due to their unpredictable nature and discrepancies that can exist between their desired behavior and their actual model output. In this paper, we introduce a new tool, InTraVisTo (Inside Transformer Visualisation Tool), designed to enable researchers to investigate and trace the computational…

Scaling Wideband Massive MIMO Radar via Beamspace Dimension Reduction
Oveys Delafrooz Noroozi, Jiyoon Han, Wei Tang, Zhengya Zhang, Upamanyu Madhow
https://arxiv.org/abs/2508.11790

Scaling Wideband Massive MIMO Radar via Beamspace Dimension Reduction
We present an architecture for scaling digital beamforming for wideband massive MIMO radar. Conventional spatial processing becomes computationally prohibitive as array size grows; for example, the computational complexity of MVDR beamforming scales as O(N^3) for an N-element array. In this paper, we show that energy concentration in beamspace provides the basis for drastic complexity reduction, with array scaling governed by the O(NlogN) complexity of the spatial FFT used for beamspace transfo…

Towards LLM-generated explanations for Component-based Knowledge Graph Question Answering Systems
Dennis Schiese, Aleksandr Perevalov, Andreas Both
https://arxiv.org/abs/2508.14553

Towards LLM-generated explanations for Component-based Knowledge Graph Question Answering Systems
Over time, software systems have reached a level of complexity that makes it difficult for their developers and users to explain particular decisions made by them. In this paper, we focus on the explainability of component-based systems for Question Answering (QA). These components often conduct processes driven by AI methods, in which behavior and decisions cannot be clearly explained or justified, s.t., even for QA experts interpreting the executed process and its results is hard. To address …

On local accumulation complexity of the set of log canonical volumes in dimension $\geq 2$
Weili Shao
https://arxiv.org/abs/2507.12710 https://

On local accumulation complexity of the set of log canonical volumes in dimension $\geq 2$
We prove that the local accumulation complexity of the set of log canonical volumes in dimension $\geq 2$ can be infinite.

Domain Translation of a Soft Robotic Arm using Conditional Cycle Generative Adversarial Network
Nilay Kushawaha, Carlo Alessi, Lorenzo Fruzzetti, Egidio Falotico
https://arxiv.org/abs/2508.14100

Domain Translation of a Soft Robotic Arm using Conditional Cycle Generative Adversarial Network
Deep learning provides a powerful method for modeling the dynamics of soft robots, offering advantages over traditional analytical approaches that require precise knowledge of the robot's structure, material properties, and other physical characteristics. Given the inherent complexity and non-linearity of these systems, extracting such details can be challenging. The mappings learned in one domain cannot be directly transferred to another domain with different physical properties. This challeng…

On the Complexity of the Secret Protection Problem for Discrete-Event Systems
Tom\'a\v{s} Masopust, Jakub Ve\v{c}e\v{r}a
https://arxiv.org/abs/2509.14372 https://

On the Complexity of the Secret Protection Problem for Discrete-Event Systems
The secret protection problem (SPP) seeks to synthesize a minimum-cost policy ensuring that every execution from an initial state to a secret state includes a sufficient number of protected events. Previous work showed that the problem is solvable in polynomial time under the assumptions that transitions are uniquely labeled and that the clearance level for every event is uniformly set to one. When these assumptions are relaxed, the problem was shown to be weakly NP-hard, leaving the complexity…

Replaced article(s) found for cs.CC. https://arxiv.org/list/cs.CC/new
[1/1]:
- Certificate-Sensitive Subset Sum: Realizing Instance Complexity
Jesus Salas
https:/…

Dependency Pairs for Expected Innermost Runtime Complexity and Strong Almost-Sure Termination of Probabilistic Term Rewriting
Jan-Christoph Kassing, Leon Spitzer, J\"urgen Giesl
https://arxiv.org/abs/2507.12918

Dependency Pairs for Expected Innermost Runtime Complexity and Strong Almost-Sure Termination of Probabilistic Term Rewriting
The dependency pair (DP) framework is one of the most powerful techniques for automatic termination and complexity analysis of term rewrite systems. While DPs were extended to prove almost-sure termination of probabilistic term rewrite systems (PTRSs), automatic complexity analysis for PTRSs is largely unexplored. We introduce the first DP framework for analyzing expected complexity and for proving positive or strong almost-sure termination (SAST) of innermost rewriting with PTRSs, i.e., finite…

The AI-Fraud Diamond: A Novel Lens for Auditing Algorithmic Deception
Benjamin Zweers, Diptish Dey, Debarati Bhaumik
https://arxiv.org/abs/2508.13984 https://

The AI-Fraud Diamond: A Novel Lens for Auditing Algorithmic Deception
As artificial intelligence (AI) systems become increasingly integral to organizational processes, they introduce new forms of fraud that are often subtle, systemic, and concealed within technical complexity. This paper introduces the AI-Fraud Diamond, an extension of the traditional Fraud Triangle that adds technical opacity as a fourth condition alongside pressure, opportunity, and rationalization. Unlike traditional fraud, AI-enabled deception may not involve clear human intent but can arise …

DDoS Attacks in Cloud Computing: Detection and Prevention
Zain Ahmad, Musab Ahmad, Bilal Ahmad
https://arxiv.org/abs/2508.13522 https://arxiv.org/pdf/2508.…

DDoS Attacks in Cloud Computing: Detection and Prevention
DDoS attacks are one of the most prevalent and harmful cybersecurity threats faced by organizations and individuals today. In recent years, the complexity and frequency of DDoS attacks have increased significantly, making it challenging to detect and mitigate them effectively. The study analyzes various types of DDoS attacks, including volumetric, protocol, and application layer attacks, and discusses the characteristics, impact, and potential targets of each type. It also examines the existing…

On Modeling and Solving the Boltzmann Equation
Liliane Basso Barichello
https://arxiv.org/abs/2508.13232 https://arxiv.org/pdf/2508.13232

On Modeling and Solving the Boltzmann Equation
The Boltzmann equation has been a driving force behind significant mathematical research over the years. Its challenging theoretical complexity, combined with a wide variety of current scientific and technological problems that require numerical simulations based on this model, justifies such interest. This work provides a brief overview of studies and advances related to the solution of the linear Boltzmann equation in one- and two-dimensional spatial dimensions. In particular, relevant aspect…

The Space-Time Complexity of Sum-Product Queries
Kyle Deeds, Timo Camillo Merkl, Reinhard Pichler, Dan Suciu
https://arxiv.org/abs/2509.11920 https://arxiv…

The Space-Time Complexity of Sum-Product Queries
While extensive research on query evaluation has achieved consistent improvements in the time complexity of algorithms, the space complexity of query evaluation has been largely ignored. This is a particular challenge in settings with strict pre-defined space constraints. In this paper, we examine the combined space-time complexity of conjunctive queries (CQs) and, more generally, of sum-product queries (SPQs). We propose several classes of space-efficient algorithms for evaluating SPQs, and we…

Combinatorics of Palindromes
Michael Itzhaki
https://arxiv.org/abs/2507.13671 https://arxiv.org/pdf/2507.13671

Combinatorics of Palindromes
We investigate the structure and reconstruction complexity of Manacher arrays. First, we establish a combinatorial lower bound, proving that the number of rooted tandem repeat trees with $n+1$ genes exceeds the number of distinct Manacher arrays of length $n$. Second, we introduce a graph-theoretic framework that associates a graph to each Manacher array, where every proper vertex coloring yields a string consistent with the array. Finally, we analyze a reconstruction algorithm by I et al. (SPI…

Comparing Conditional Diffusion Models for Synthesizing Contrast-Enhanced Breast MRI from Pre-Contrast Images
Sebastian Ibarra, Javier del Riego, Alessandro Catanese, Julian Cuba, Julian Cardona, Nataly Leon, Jonathan Infante, Karim Lekadir, Oliver Diaz, Richard Osuala
https://arxiv.org/abs/2508.13776

Comparing Conditional Diffusion Models for Synthesizing Contrast-Enhanced Breast MRI from Pre-Contrast Images
Dynamic contrast-enhanced (DCE) MRI is essential for breast cancer diagnosis and treatment. However, its reliance on contrast agents introduces safety concerns, contraindications, increased cost, and workflow complexity. To this end, we present pre-contrast conditioned denoising diffusion probabilistic models to synthesize DCE-MRI, introducing, evaluating, and comparing a total of 22 generative model variants in both single-breast and full breast settings. Towards enhancing lesion fidelity, we …

MAHL: Multi-Agent LLM-Guided Hierarchical Chiplet Design with Adaptive Debugging
Jinwei Tang (Katie), Jiayin Qin (Katie), Nuo Xu (Katie), Pragnya Sudershan Nalla (Katie), Yu Cao (Katie), Yang (Katie), Zhao, Caiwen Ding
https://arxiv.org/abs/2508.14053

MAHL: Multi-Agent LLM-Guided Hierarchical Chiplet Design with Adaptive Debugging
As program workloads (e.g., AI) increase in size and algorithmic complexity, the primary challenge lies in their high dimensionality, encompassing computing cores, array sizes, and memory hierarchies. To overcome these obstacles, innovative approaches are required. Agile chip design has already benefited from machine learning integration at various stages, including logic synthesis, placement, and routing. With Large Language Models (LLMs) recently demonstrating impressive proficiency in Hardwa…

Small Scale Index Theory, Scalar Curvature, and Gromov's Simplicial Norms
Qiaochu Ma, Guoliang Yu
https://arxiv.org/abs/2508.14791 https://arxiv.org/pd…

Small Scale Index Theory, Scalar Curvature, and Gromov's Simplicial Norms
In this article, we study the topological complexity of manifolds with a lower scalar curvature bound. We introduce a small-scale index theorem to establish an upper bound on Gromov's simplicial norm of the Poincaré dual of the $\hat{A}$-class for Riemannian manifolds satisfying a scalar curvature lower bound. This result can be considered as a topological finiteness theorem for manifolds with a lower scalar curvature bound.

First Order Algorithm on an Optimization Problem with Improved Convergence when Problem is Convex
Chee-Khian Sim
https://arxiv.org/abs/2508.13302 https://a…

First Order Algorithm on an Optimization Problem with Improved Convergence when Problem is Convex
We propose a first order algorithm, a modified version of FISTA, to solve an optimization problem with an objective function that is a sum of a possibly nonconvex function, with Lipschitz continuous gradient, and a convex function which can be nonsmooth. The algorithm is shown to have an iteration complexity of $\mathcal{O}(ε^{-2})$ to find an $ε$-approximate solution to the problem, and this complexity improves to $\mathcal{O}(ε^{-2/3})$ when the objective function turns out to be convex. W…

Temporal Adaptation of Pre-trained Foundation Models for Music Structure Analysis
Yixiao Zhang, Haonan Chen, Ju-Chiang Wang, Jitong Chen
https://arxiv.org/abs/2507.13572

Temporal Adaptation of Pre-trained Foundation Models for Music Structure Analysis
Audio-based music structure analysis (MSA) is an essential task in Music Information Retrieval that remains challenging due to the complexity and variability of musical form. Recent advances highlight the potential of fine-tuning pre-trained music foundation models for MSA tasks. However, these models are typically trained with high temporal feature resolution and short audio windows, which limits their efficiency and introduces bias when applied to long-form audio. This paper presents a tempor…

Krylov complexity and Wightman power spectrum with positive chemical potentials in Schr\"odinger field theory
Peng-Zhang He, Lei-Hua Liu, Hai-Qing Zhang, Qing-Quan Jiang
https://arxiv.org/abs/2509.14742

Krylov complexity and Wightman power spectrum with positive chemical potentials in Schrödinger field theory
We systematically investigate the Krylov complexity of fermionic fields in Schrödinger field theory as the chemical potential is positive, validated by the engineered Wightman power spectra. For non-positive chemical potentials, the Lanczos coefficients exhibit linear behaviors with respect to $n$. However, as the chemical potential becomes positive, a dynamical transition occurs -- Lanczos coefficient $b_{n}$ develops a two-stage linear growth profile, transitioning from an initial slope of $…

ATRO: A Fast Solver-Free Algorithm for Topology and Routing Optimization of Reconfigurable Datacenter Networks
Yingming Mao, Qiaozhu Zhai, Zhen Yao, Xia Zhu, Ximeng Liu, Xinchi Han
https://arxiv.org/abs/2507.13717

ATRO: A Fast Solver-Free Algorithm for Topology and Routing Optimization of Reconfigurable Datacenter Networks
The growing scale and complexity of reconfigurable data center networks (DCNs) demand more scalable and efficient algorithms for computing logical topologies and routing. Reconfigurable DCNs typically operate in two modes: one-hop configurations that require frequent topology optimization (TO), and multi-hop scenarios that involve joint topology and routing optimization (TRO). In both cases, the combinatorial nature of topology decisions makes it difficult for existing methods to balance soluti…

Properties of Egalitarian Sequences of Committees: Theory and Experiments
Paula B\"ohm, Robert Bredereck, Till Fluschnik
https://arxiv.org/abs/2508.14439 https://

Properties of Egalitarian Sequences of Committees: Theory and Experiments
We study the task of electing egalitarian sequences of $τ$ committees given a set of agents with additive utilities for candidates available on each of $τ$ levels. We introduce several rules for electing an egalitarian committee sequence as well as properties for such rules. We settle the computational complexity of finding a winning sequence for our rules and classify them against our properties. Additionally, we transform sequential election data from existing election data from the literat…

Computational complexity of Berry phase estimation in topological phases of matter
Ryu Hayakawa, Kazuki Sakamoto, Chusei Kiumi
https://arxiv.org/abs/2509.13423 https://

Computational complexity of Berry phase estimation in topological phases of matter
The Berry phase is a fundamental quantity in the classification of topological phases of matter. In this paper, we present a new quantum algorithm and several complexity-theoretical results for the Berry phase estimation (BPE) problems. Our new quantum algorithm achieves BPE in a more general setting than previously known quantum algorithms, with a theoretical guarantee. For the complexity-theoretic results, we consider three cases. First, we prove $\mathsf{BQP}$-completeness when we are given …

AutoMPC: A Code Generator for MPC-based Automated Driving
Georg Schildbach, Jasper Pflughaupt
https://arxiv.org/abs/2508.13656 https://arxiv.org/pdf/2508.1…

AutoMPC: A Code Generator for MPC-based Automated Driving
Model Predictive Control (MPC) is a powerful technique to control nonlinear, multi-input multi-output systems subject to input and state constraints. It is now a standard tool for trajectory tracking control of automated vehicles. As such it has been used in many research and development projects. However, MPC faces several challenges to be integrated into industrial production vehicles. The most important ones are its high computational demands and the complexity of implementation. The softwar…

An Algorithm for Computing the Exact Convex Hull in High-Dimensional Spaces
Qianwei Zhuang
https://arxiv.org/abs/2508.14407 https://arxiv.org/pdf/2508.1440…

An Algorithm for Computing the Exact Convex Hull in High-Dimensional Spaces
This study introduces a novel algorithm for computing the convex hull of a point set in high-dimensional Euclidean space. The method iteratively solves a sequence of dynamically updated quadratic programming (QP) problems for each point and leverages the solutions to provide theoretical guarantees for exact convex hull identification. Given $n$ points in an $m$-dimensional space, the algorithm achieves a best-case time complexity of $O(nm^p)$, where $p$ depends on the specific QP solver employe…

A High Performance GPU CountSketch Implementation and Its Application to Multisketching and Least Squares Problems
Andrew J. Higgins, Erik G. Boman, Ichitaro Yamazaki
https://arxiv.org/abs/2508.14209

A High Performance GPU CountSketch Implementation and Its Application to Multisketching and Least Squares Problems
Random sketching is a dimensionality reduction technique that approximately preserves norms and singular values up to some $O(1)$ distortion factor with high probability. The most popular sketches in literature are the Gaussian sketch and the subsampled randomized Hadamard transform, while the CountSketch has lower complexity. Combining two sketches, known as multisketching, offers an inexpensive means of quickly reducing the dimension of a matrix by combining a CountSketch and Gaussian sketch.…

Leveraging the Spatial Hierarchy: Coarse-to-fine Trajectory Generation via Cascaded Hybrid Diffusion
Baoshen Guo, Zhiqing Hong, Junyi Li, Shenhao Wang, Jinhua Zhao
https://arxiv.org/abs/2507.13366

Leveraging the Spatial Hierarchy: Coarse-to-fine Trajectory Generation via Cascaded Hybrid Diffusion
Urban mobility data has significant connections with economic growth and plays an essential role in various smart-city applications. However, due to privacy concerns and substantial data collection costs, fine-grained human mobility trajectories are difficult to become publicly available on a large scale. A promising solution to address this issue is trajectory synthesizing. However, existing works often ignore the inherent structural complexity of trajectories, unable to handle complicated hig…

A High-Quality and Low-Complexity Streamable Neural Speech Codec with Knowledge Distillation
En-Wei Zhang, Hui-Peng Du, Xiao-Hang Jiang, Yang Ai, Zhen-Hua Ling
https://arxiv.org/abs/2509.13670

A High-Quality and Low-Complexity Streamable Neural Speech Codec with Knowledge Distillation
While many current neural speech codecs achieve impressive reconstructed speech quality, they often neglect latency and complexity considerations, limiting their practical deployment in downstream tasks such as real-time speech communication and efficient speech compression. In our previous work, we proposed StreamCodec, which enables streamable speech coding by leveraging model causalization and a scalar-vector-combined quantization strategy, but its reconstructed quality and complexity still …

Exploiting scattering-based point spread functions for snapshot 5D and modality-switchable lensless imaging
Ze Zheng, Baolei Liu, Jiaqi Song, Muchen Zhu, Yao Wang, Menghan Tian, Ying Xiong, Zhaohua Yang, Xiaolan Zhong, David McGloin, Fan Wang
https://arxiv.org/abs/2507.13813

Exploiting scattering-based point spread functions for snapshot 5D and modality-switchable lensless imaging
Snapshot multi-dimensional imaging offers a promising alternative to traditional low-dimensional imaging techniques by enabling the simultaneous capture of spatial, spectral, polarization, and other information in a single shot for improved imaging speed and acquisition efficiency. However, existing snapshot multi-dimensional imaging systems are often hindered by their large size, complexity, and high cost, which constrain their practical applicability. In this work, we propose a compact lensle…

Beyond Simple Edits: Composed Video Retrieval with Dense Modifications
Omkar Thawakar, Dmitry Demidov, Ritesh Thawkar, Rao Muhammad Anwer, Mubarak Shah, Fahad Shahbaz Khan, Salman Khan
https://arxiv.org/abs/2508.14039

Beyond Simple Edits: Composed Video Retrieval with Dense Modifications
Composed video retrieval is a challenging task that strives to retrieve a target video based on a query video and a textual description detailing specific modifications. Standard retrieval frameworks typically struggle to handle the complexity of fine-grained compositional queries and variations in temporal understanding limiting their retrieval ability in the fine-grained setting. To address this issue, we introduce a novel dataset that captures both fine-grained and composed actions across di…

Open Automatic Speech Recognition Models for Classical and Modern Standard Arabic
Lilit Grigoryan, Nikolay Karpov, Enas Albasiri, Vitaly Lavrukhin, Boris Ginsburg
https://arxiv.org/abs/2507.13977

Open Automatic Speech Recognition Models for Classical and Modern Standard Arabic
Despite Arabic being one of the most widely spoken languages, the development of Arabic Automatic Speech Recognition (ASR) systems faces significant challenges due to the language's complexity, and only a limited number of public Arabic ASR models exist. While much of the focus has been on Modern Standard Arabic (MSA), there is considerably less attention given to the variations within the language. This paper introduces a universal methodology for Arabic speech and text processing designed to …

MHSNet:An MoE-based Hierarchical Semantic Representation Network for Accurate Duplicate Resume Detection with Large Language Model
Yu Li, Zulong Chen, Wenjian Xu, Hong Wen, Yipeng Yu, Man Lung Yiu, Yuyu Yin
https://arxiv.org/abs/2508.13676

MHSNet:An MoE-based Hierarchical Semantic Representation Network for Accurate Duplicate Resume Detection with Large Language Model
To maintain the company's talent pool, recruiters need to continuously search for resumes from third-party websites (e.g., LinkedIn, Indeed). However, fetched resumes are often incomplete and inaccurate. To improve the quality of third-party resumes and enrich the company's talent pool, it is essential to conduct duplication detection between the fetched resumes and those already in the company's talent pool. Such duplication detection is challenging due to the semantic complexity, structural h…

Large Language Models as Visualization Agents for Immersive Binary Reverse Engineering
Dennis Brown, Samuel Mulder
https://arxiv.org/abs/2508.13413 https://

Large Language Models as Visualization Agents for Immersive Binary Reverse Engineering
Immersive virtual reality (VR) offers affordances that may reduce cognitive complexity in binary reverse engineering (RE), enabling embodied and external cognition to augment the RE process through enhancing memory, hypothesis testing, and visual organization. In prior work, we applied a cognitive systems engineering approach to identify an initial set of affordances and implemented a VR environment to support RE through spatial persistence and interactivity. In this work, we extend that platfo…

A Survey of Dimension Estimation Methods
James A. D. Binnie, Pawe{\l} D{\l}otko, John Harvey, Jakub Malinowski, Ka Man Yim
https://arxiv.org/abs/2507.13887

A Survey of Dimension Estimation Methods
It is a standard assumption that datasets in high dimension have an internal structure which means that they in fact lie on, or near, subsets of a lower dimension. In many instances it is important to understand the real dimension of the data, hence the complexity of the dataset at hand. A great variety of dimension estimators have been developed to find the intrinsic dimension of the data but there is little guidance on how to reliably use these estimators. This survey reviews a wide range o…

Logics with the axiom of convergence: complexity with a small number of variables in the language (extended version)
M. Rybakov, M. Shcherbakov
https://arxiv.org/abs/2507.12343 …

Logics with the axiom of convergence: complexity with a small number of variables in the language (extended version)
It is known that many modal and superintuitionistic logics are PSPACE-hard in languages with a small number of variables; however, questions about the complexity of similar fragments of many logics obtained by adding various axioms to "standard" ones remain unexplored. We investigate the complexity of fragments of modal logics obtained by adding an axiom requiring the convergence of the accessibility relation in Kripke frames: S4.2, K4.2, Grz.2, and GL.2. The main result is that S4.2 and Grz.2 …

The Complexity of Finding and Counting Subtournaments
Simon D\"oring, Sarah Houdaigoui, Lucas Picasarri-Arrieta, Philip Wellnitz
https://arxiv.org/abs/2509.14807 https://…

The Complexity of Finding and Counting Subtournaments
We study the complexity of counting and finding small tournament patterns inside large tournaments. Given a fixed tournament $T$ of order $k$, we write ${\#}\text{IndSub}_{\text{To}}(\{T\})$ for the problem whose input is a tournament $G$ and the task is to compute the number of subtournaments of $G$ that are isomorphic to $T$. Previously, Yuster [Yus25] obtained that ${\#}\text{IndSub}_{\text{To}}(\{T\})$ is hard to compute for random tournaments $T$. We consider a new approach that uses linea…

Accelerating Signal-Temporal-Logic-Based Task and Motion Planning of Bipedal Navigation using Benders Decomposition
Jiming Ren, Xuan Lin, Roman Mineyev, Karen M. Feigh, Samuel Coogan, Ye Zhao
https://arxiv.org/abs/2508.13407

Accelerating Signal-Temporal-Logic-Based Task and Motion Planning of Bipedal Navigation using Benders Decomposition
Task and motion planning under Signal Temporal Logic constraints is known to be NP-hard. A common class of approaches formulates these hybrid problems, which involve discrete task scheduling and continuous motion planning, as mixed-integer programs (MIP). However, in applications for bipedal locomotion, introduction of non-convex constraints such as kinematic reachability and footstep rotation exacerbates the computational complexity of MIPs. In this work, we present a method based on Benders D…

Symmetry-Resolved Spread Complexity
Pawel Caputa, Giuseppe Di Giulio, Tran Quang Loc
https://arxiv.org/abs/2509.12992 https://arxiv.org/pdf/2509.12992

Symmetry-Resolved Spread Complexity
In this work, we investigate the impact of conserved charges on the dynamics of spread complexity of quantum states. Building on the notion of symmetry-resolved Krylov complexity [1], we extend the framework to general quantum states and analyze the relation between the total spread complexity and its decomposition into fixed-charge sectors. After exploring a range of analytical examples and using orthogonal polynomial approach, we identify conditions under which spread complexity exhibits equi…

The Complexity of Generalized HyperLTL with Stuttering and Contexts
Ga\"etan Regaud (ENS Rennes), Martin Zimmermann (Aalborg University)
https://arxiv.org/abs/2509.14095 ht…

The Complexity of Generalized HyperLTL with Stuttering and Contexts
We settle the complexity of satisfiability and model-checking for generalized HyperLTL with stuttering and contexts, an expressive logic for the specification of asynchronous hyperproperties. Such properties cannot be specified in HyperLTL, as it is restricted to synchronous hyperproperties. Nevertheless, we prove that satisfiability is $Σ_1^1$-complete and thus not harder than for HyperLTL. On the other hand, we prove that model-checking is equivalent to truth in second-order arithmetic, and …

Virtual Multiplex Staining for Histological Images using a Marker-wise Conditioned Diffusion Model
Hyun-Jic Oh, Junsik Kim, Zhiyi Shi, Yichen Wu, Yu-An Chen, Peter K. Sorger, Hanspeter Pfister, Won-Ki Jeong
https://arxiv.org/abs/2508.14681

Virtual Multiplex Staining for Histological Images using a Marker-wise Conditioned Diffusion Model
Multiplex imaging is revolutionizing pathology by enabling the simultaneous visualization of multiple biomarkers within tissue samples, providing molecular-level insights that traditional hematoxylin and eosin (H&E) staining cannot provide. However, the complexity and cost of multiplex data acquisition have hindered its widespread adoption. Additionally, most existing large repositories of H&E images lack corresponding multiplex images, limiting opportunities for multimodal analysis. To address…

GPT-2 as a Compression Preprocessor: Improving Gzip for Structured Text Domains
Anurag Kumar Ojha
https://arxiv.org/abs/2508.14061 https://arxiv.org/pdf/25…

GPT-2 as a Compression Preprocessor: Improving Gzip for Structured Text Domains
In the modern era, large volumes of data are being produced continuously, especially in domain-specific fields such as medical records and clinical files, defence logs and HTML-based web traffic. Data with such volume and complexity needs to be compressed before storing and transmitting efficiently. Data compression has gained significant attention from modern researchers, resulting in the development of fast and efficient compression algorithms such as Gzip. However, since gzip works on the pr…

Learning Internal Biological Neuron Parameters and Complexity-Based Encoding for Improved Spiking Neural Networks Performance
Zofia Rudnicka, Janusz Szczepanski, Agnieszka Pregowska
https://arxiv.org/abs/2508.11674

Learning Internal Biological Neuron Parameters and Complexity-Based Encoding for Improved Spiking Neural Networks Performance
This study introduces a novel approach by replacing the traditional perceptron neuron model with a biologically inspired probabilistic meta neuron, where the internal neuron parameters are jointly learned, leading to improved classification accuracy of spiking neural networks (SNNs). To validate this innovation, we implement and compare two SNN architectures: one based on standard leaky integrate-and-fire (LIF) neurons and another utilizing the proposed probabilistic meta neuron model. As a sec…

Crosslisted article(s) found for cs.AR. https://arxiv.org/list/cs.AR/new
[1/1]:
- Multi-Metric Algorithmic Complexity: Beyond Asymptotic Analysis
Sergii Kavun
htt…

BioSonix: Can Physics-Based Sonification Perceptualize Tissue Deformations From Tool Interactions?
Veronica Ruozzi, Sasan Matinfar, Laura Sch\"utz, Benedikt Wiestler, Alberto Redaelli, Emiliano Votta, Nassir Navab
https://arxiv.org/abs/2508.14688

BioSonix: Can Physics-Based Sonification Perceptualize Tissue Deformations From Tool Interactions?
Perceptualizing tool interactions with deformable structures in surgical procedures remains challenging, as unimodal visualization techniques often fail to capture the complexity of these interactions due to constraints such as occlusion and limited depth perception. This paper presents a novel approach to augment tool navigation in mixed reality environments by providing auditory representations of tool-tissue dynamics, particularly for interactions with soft tissue. BioSonix, a physics-inform…

Project-connex Decompositions and Tractability of Aggregate Group-by Conjunctive Queries
Diego Figueira, Cibele Freire
https://arxiv.org/abs/2507.14101 htt…

Project-connex Decompositions and Tractability of Aggregate Group-by Conjunctive Queries
We introduce 'project-connex' tree-width as a measure of tractability for counting and aggregate conjunctive queries over semirings with 'group-by' projection (also known as 'AJAR' or 'FAQ' queries). This elementary measure allows to obtain comparable complexity bounds to the ones obtained by previous structural conditions tailored for efficient evaluation of semiring aggregate queries, enumeration algorithms of conjunctive queries, and tractability of counting answers to conjunctive queries. …

Crosslisted article(s) found for cs.DS. https://arxiv.org/list/cs.DS/new
[1/1]:
- Multi-Metric Algorithmic Complexity: Beyond Asymptotic Analysis
Sergii Kavun
htt…

UST-SSM: Unified Spatio-Temporal State Space Models for Point Cloud Video Modeling
Peiming Li, Ziyi Wang, Yulin Yuan, Hong Liu, Xiangming Meng, Junsong Yuan, Mengyuan Liu
https://arxiv.org/abs/2508.14604

UST-SSM: Unified Spatio-Temporal State Space Models for Point Cloud Video Modeling
Point cloud videos capture dynamic 3D motion while reducing the effects of lighting and viewpoint variations, making them highly effective for recognizing subtle and continuous human actions. Although Selective State Space Models (SSMs) have shown good performance in sequence modeling with linear complexity, the spatio-temporal disorder of point cloud videos hinders their unidirectional modeling when directly unfolding the point cloud video into a 1D sequence through temporally sequential scann…

End-to-End Complexity Analysis for Quantum Simulation of the Extended Jaynes-Cummings Models
Nam Nguyen, Michael Yu, Alan Robertson, Hiromichi Nishimura, Samuel J. Elman, Benjamin Koltenbah
https://arxiv.org/abs/2509.13546

End-to-End Complexity Analysis for Quantum Simulation of the Extended Jaynes-Cummings Models
The extended Jaynes-Cummings model (eJCM) is a foundational framework for describing multi-mode light-matter interactions, with direct applications in quantum technologies such as photon addition and quasi-noiseless amplification. However, the model's complexity makes classical simulation intractable for large systems that could be of practical interest. In this work, we present a comprehensive, end-to-end framework for the quantum simulation of the eJCM. We develop explicit quantum algorithms …

Transient Stability Analysis for Grid Following Converters in Low-Inertia Power Systems by Direct Method
Fangyuan Sun, Ruisheng Diao, Ruiyuan Zeng, Zhanning Liu, Baorong Zhou, Junjie Li, Wangqianyun Tang
https://arxiv.org/abs/2508.13641

Transient Stability Analysis for Grid Following Converters in Low-Inertia Power Systems by Direct Method
With the increased penetration of renewable energy and reduced proportion of synchronous generators, the low-inertia characteristics of todays power system become prominent, and the transient stability issue of grid following converter (GFLC) under low inertia system (LIS) condition becomes critical. There are two prominent problems in the transient stability analysis of GFLC-LIS. The angular dynamic of LIS increases the complexity of transient stability analysis, and the nonlinear, possibly ne…

Democratizing Game Modding with GenAI: A Case Study of StarCharM, a Stardew Valley Character Maker
Hamid Zand Miralvand, Mohammad Ronagh Nikghalb, Mohammad Darandeh, Abidullah Khan, Ian Arawjo, Jinghui Cheng
https://arxiv.org/abs/2507.13951

Democratizing Game Modding with GenAI: A Case Study of StarCharM, a Stardew Valley Character Maker
Game modding offers unique and personalized gaming experiences, but the technical complexity of creating mods often limits participation to skilled users. We envision a future where every player can create personalized mods for their games. To explore this space, we designed StarCharM, a GenAI-based non-player character (NPC) creator for Stardew Valley. Our tool enables players to iteratively create new NPC mods, requiring minimal user input while allowing for fine-grained adjustments through u…

Complexity Bounds for Smooth Convex Multiobjective Optimization
Phillipe R. Sampaio
https://arxiv.org/abs/2509.13550 https://arxiv.org/pdf/2509.13550

Complexity Bounds for Smooth Convex Multiobjective Optimization
We study the oracle complexity of finding $\varepsilon$-Pareto stationary points in smooth multiobjective optimization with $m$ objectives. The progress metric is the Pareto stationarity gap $\mathcal{G}(x)$ (the norm of an optimal convex combination of gradients). Our contributions are fourfold. (i) For strongly convex objectives, any span first-order method (iterates lie in the span of past gradients) exhibits linear convergence no faster than $\exp(-Θ(T/\sqrtκ))$ after $T$ oracle calls, wh…

Krylov complexity, path integrals, and instantons
Cameron Beetar, Eric L Graef, Jeff Murugan, Horatiu Nastase, Hendrik J R Van Zyl
https://arxiv.org/abs/2507.13226

Krylov complexity, path integrals, and instantons
Krylov complexity has emerged as an important tool in the description of quantum information and, in particular, quantum chaos. Here we formulate Krylov complexity $K(t)$ for quantum mechanical systems as a path integral, and argue that at large times, for classical chaotic systems with at least two minima of the potential, that have a plateau for $K(t)$, the value of the plateau is described by quantum mechanical instantons, as is the case for standard transition amplitudes. We explain and tes…

Cylindrical RIS-Assisted Low-Complexity Transmission with Differentiated Visible Regions Exploiting Statistical CSI
Wenjun Teng, Weicong Chen, Yiping Zuo, Wankai Tang, Shi Jin
https://arxiv.org/abs/2508.12229

Cylindrical RIS-Assisted Low-Complexity Transmission with Differentiated Visible Regions Exploiting Statistical CSI
Reconfigurable intelligent surfaces (RIS), recognized as a critical enabler for 6G networks, exhibit unprecedented capabilities in electromagnetic wave manipulation and wireless channel reconfiguration. By leveraging existing network infrastructure, RIS can cost-effectively create signal hotspots in low-altitude environments, ensuring robust connectivity to support the sustainable development of the low-altitude economy. However, achieving optimal phase shift design in multi-user scenarios face…

The Complexity of Deciding Characteristic Formulae Modulo Nested Simulation (extended abstract)
Luca Aceto, Antonis Achilleos, Aggeliki Chalki, Anna Ing\'olfsd\'ottir
https://arxiv.org/abs/2509.14089

The Complexity of Deciding Characteristic Formulae Modulo Nested Simulation (extended abstract)
This paper studies the complexity of determining whether a formula in the modal logics characterizing the nested-simulation semantics is characteristic for some process, which is equivalent to determining whether the formula is satisfiable and prime. The main results are that the problem of determining whether a formula is prime in the modal logic characterizing the 2-nested-simulation preorder is coNP-complete and is PSPACE-complete in the case of the n-nested-simulation preorder, when n>=3. T…

Linear Complexity $\mathcal{H}^2$ Direct Solver for Fine-Grained Parallel Architectures
Wajih Boukaram, David Keyes, Sherry Li, Yang Liu, George Turkiyyah
https://arxiv.org/abs/2509.11152

Linear Complexity $\mathcal{H}^2$ Direct Solver for Fine-Grained Parallel Architectures
We present factorization and solution phases for a new linear complexity direct solver designed for concurrent batch operations on fine-grained parallel architectures, for matrices amenable to hierarchical representation. We focus on the strong-admissibility-based $\mathcal{H}^2$ format, where strong recursive skeletonization factorization compresses remote interactions. We build upon previous implementations of $\mathcal{H}^2$ matrix construction for efficient factorization and solution algori…

Replaced article(s) found for cs.CC. https://arxiv.org/list/cs.CC/new
[1/1]:
- Computable one-way functions on the reals
George Barmpalias, Xiaoyan Zhang

Reliable Smoke Detection via Optical Flow-Guided Feature Fusion and Transformer-Based Uncertainty Modeling
Nitish Kumar Mahala, Muzammil Khan, Pushpendra Kumar
https://arxiv.org/abs/2508.14597

Reliable Smoke Detection via Optical Flow-Guided Feature Fusion and Transformer-Based Uncertainty Modeling
Fire outbreaks pose critical threats to human life and infrastructure, necessitating high-fidelity early-warning systems that detect combustion precursors such as smoke. However, smoke plumes exhibit complex spatiotemporal dynamics influenced by illumination variability, flow kinematics, and environmental noise, undermining the reliability of traditional detectors. To address these challenges without the logistical complexity of multi-sensor arrays, we propose an information-fusion framework by…

Sustainable AI Training via Hardware-Software Co-Design on NVIDIA, AMD, and Emerging GPU Architectures
Yashasvi Makin, Rahul Maliakkal
https://arxiv.org/abs/2508.13163 https://

Sustainable AI Training via Hardware-Software Co-Design on NVIDIA, AMD, and Emerging GPU Architectures
In particular, large-scale deep learning and artificial intelligence model training uses a lot of computational power and energy, so it poses serious sustainability issues. The fast rise in model complexity has resulted in exponential increases in energy consumption, increasing the demand for techniques maximizing computational efficiency and lowering environmental impact. This work explores environmentally driven performance optimization methods especially intended for advanced GPU architectur…

Qudit-based scalable quantum algorithm for solving the integer programming problem
Kapil Goswami, Peter Schmelcher, Rick Mukherjee
https://arxiv.org/abs/2508.13906 https://

Qudit-based scalable quantum algorithm for solving the integer programming problem
Integer programming (IP) is an NP-hard combinatorial optimization problem that is widely used to represent a diverse set of real-world problems spanning multiple fields, such as finance, engineering, logistics, and operations research. It is a hard problem to solve using classical algorithms, as its complexity increases exponentially with problem size. Most quantum algorithms for solving IP are highly resource inefficient because they encode integers into qubits. In [1], the issue of resource i…

Fast and Compact Sketch-Based Dynamic Connectivity
Quinten De Man, Qamber Jafri, Daniel Delayo, Evan T. West, Michael A. Bender, David Tench
https://arxiv.org/abs/2509.14433 htt…

Fast and Compact Sketch-Based Dynamic Connectivity
We study the dynamic connectivity problem for massive, dense graphs. Our goal is to build a system for dense graphs that simultaneously answers connectivity queries quickly, maintains a fast update throughput, and a uses a small amount of memory. Existing systems at best achieve two of these three performance goals at once. We present a parallel dynamic connectivity algorithm using graph sketching techniques that has space complexity $O(V \log^3 V)$ and query complexity $O(\log V/\log\log V)$…

Replaced article(s) found for cs.CC. https://arxiv.org/list/cs.CC/new
[1/1]:
- Minimum Stable Cut and Treewidth
Michael Lampis
https://arxiv…

Correct Black-Box Monitors for Distributed Deadlock Detection: Formalisation and Implementation (Technical Report)
Rados{\l}aw Jan Rowicki, Adrian Francalanza, Alceste Scalas
https://arxiv.org/abs/2508.14851

Correct Black-Box Monitors for Distributed Deadlock Detection: Formalisation and Implementation (Technical Report)
Many software applications rely on concurrent and distributed (micro)services that interact via message-passing and various forms of remote procedure calls (RPC). As these systems organically evolve and grow in scale and complexity, the risk of introducing deadlocks increases and their impact may worsen: even if only a few services deadlock, many other services may block while awaiting responses from the deadlocked ones. As a result, the "core" of the deadlock can be obfuscated by its consequen…

Online Stochastic Packing with General Correlations
Sabri Cetin, Yilun Chen, David A. Goldberg
https://arxiv.org/abs/2508.13458 https://arxiv.org/pdf/2508.…

Online Stochastic Packing with General Correlations
There has been a growing interest in studying online stochastic packing under more general correlation structures, motivated by the complex data sets and models driving modern applications. Several past works either assume correlations are weak or have a particular structure, have a complexity scaling with the number of Markovian "states of the world" (which may be exponentially large e.g. in the case of full history dependence), scale poorly with the horizon $T$, or make additional continuity …

Stoquasticity is not enough: towards a sharper diagnostic for Quantum Monte Carlo simulability
Arman Babakhani, Armen Karakashian
https://arxiv.org/abs/2508.14382 https://

Stoquasticity is not enough: towards a sharper diagnostic for Quantum Monte Carlo simulability
Quantum Monte Carlo (QMC) methods are powerful tools for simulating quantum many-body systems, yet their applicability is limited by the infamous sign problem. We approach this challenge through the lens of Vanishing Geometric Phases (VGP) \cite{Hen_2021}, introducing it as a `geometric' criterion for diagnosing QMC simulability. We characterize the class of VGP Hamiltonians, and analyze the complexity of recognizing this class, identifying both hard and efficiently identifiable cases. We furth…

Crosslisted article(s) found for cs.CC. https://arxiv.org/list/cs.CC/new
[1/1]:
- Sublinear-Time Approximation for Graph Frequency Vectors in Hyperfinite Graphs
Gregory Moroie

Quantum Chaos Diagnostics for Open Quantum Systems from Bi-Lanczos Krylov Dynamics
Matteo Baggioli, Kyoung-Bum Huh, Hyun-Sik Jeong, Xuhao Jiang, Keun-Young Kim, Juan F. Pedraza
https://arxiv.org/abs/2508.13956

Quantum Chaos Diagnostics for Open Quantum Systems from Bi-Lanczos Krylov Dynamics
In Hermitian systems, Krylov complexity has emerged as a powerful diagnostic of quantum dynamics, capable of distinguishing chaotic from integrable phases, in agreement with established probes such as spectral statistics and out-of-time-order correlators. By contrast, its role in non-Hermitian settings, relevant for modeling open quantum systems, remains less understood due to the challenges posed by complex eigenvalues and the limitations of standard approaches such as singular value decomposi…

GAP-LA: GPU-Accelerated Performance-Driven Layer Assignment
Chunyuan Zhao, Zizheng Guo, Zuodong Zhang, Yibo Lin
https://arxiv.org/abs/2507.13375 https://…

GAP-LA: GPU-Accelerated Performance-Driven Layer Assignment
Layer assignment is critical for global routing of VLSI circuits. It converts 2D routing paths into 3D routing solutions by determining the proper metal layer for each routing segments to minimize congestion and via count. As different layers have different unit resistance and capacitance, layer assignment also has significant impacts to timing and power. With growing design complexity, it becomes increasingly challenging to simultaneously optimize timing, power, and congestion efficiently. Exi…

Linear Complexity Computation of Code Distance and Minimum Size of Trapping Sets for LDPC Codes with Bounded Treewidth
Qingqing Peng, Ke Liu, Guiying Yan, Guanghui Wang
https://arxiv.org/abs/2509.13040

Linear Complexity Computation of Code Distance and Minimum Size of Trapping Sets for LDPC Codes with Bounded Treewidth
It is well known that, given \(b\ge 0\), finding an $(a,b)$-trapping set with the minimum \(a\) in a binary linear code is NP-hard. In this paper, we demonstrate that this problem can be solved with linear complexity with respect to the code length for codes with bounded treewidth. Furthermore, suppose a tree decomposition corresponding to the treewidth of the binary linear code is known. In that case, we also provide a specific algorithm to compute the minimum \(a\) and the number of the corre…

New complexity bounds for primal--dual interior-point algorithms in conic optimization
Joachim Dahl, Levent Tun\c{c}el, Lieven Vandenberghe
https://arxiv.org/abs/2509.10263 http…

New complexity bounds for primal--dual interior-point algorithms in conic optimization
We provide improved complexity results for symmetric primal--dual interior-point algorithms in conic optimization. The results follow from new uniform bounds on a key complexity measure for primal--dual metrics at pairs of primal and dual points. The complexity measure is defined as the largest eigenvalue of the product of the Hessians of the primal and dual barrier functions, normalized by the proximity of the points to the central path. For algorithms based on self-scaled barriers for symmetr…

Replaced article(s) found for cs.CC. https://arxiv.org/list/cs.CC/new
[1/1]:
- On the complexity of unique quantum witnesses and quantum approximate counting
Anurag Anshu, Jonas Haferkamp, Yeongwoo Hwang, Quynh T. Nguyen

On the complexity of constrained reconfiguration and motion planning
Nicolas Bousquet, Remy El Sabeh, Amer E. Mouawad, Naomi Nishimura
https://arxiv.org/abs/2508.13032 https://

On the complexity of constrained reconfiguration and motion planning
Coordinating the motion of multiple agents in constrained environments is a fundamental challenge in robotics, motion planning, and scheduling. A motivating example involves $n$ robotic arms, each represented as a line segment. The objective is to rotate each arm to its vertical orientation, one at a time (clockwise or counterclockwise), without collisions nor rotating any arm more than once. This scenario is an example of the more general $k$-Compatible Ordering problem, where $n$ agents, each…

Spectral Small-Incremental-Entangling: Breaking Quasi-Polynomial Complexity Barriers in Long-Range Interacting Systems
Donghoon Kim, Yusuke Kimura, Hugo Mackay, Yosuke Mitsuhashi, Hideaki Nishikawa, Carla Rubiliani, Cheng Shang, Ayumi Ukai, Tomotaka Kuwahara
https://arxiv.org/abs/2509.12014

Spectral Small-Incremental-Entangling: Breaking Quasi-Polynomial Complexity Barriers in Long-Range Interacting Systems
A key challenge in quantum complexity is how entanglement structure emerges from dynamics, highlighted by advances in simulators and information processing. The Lieb--Robinson bound sets a locality-based speed limit on information propagation, while the Small-Incremental-Entangling (SIE) theorem gives a universal constraint on entanglement growth. Yet, SIE bounds only total entanglement, leaving open the fine entanglement structure. In this work, we introduce Spectral-Entangling Strength, measu…

De Sitter Complexity Grows Linearly in the Static Patch
Vyshnav Mohan, Watse Sybesma
https://arxiv.org/abs/2508.10093 https://arxiv.org/pdf/2508.10093

De Sitter Complexity Grows Linearly in the Static Patch
The observable universe has undergone periods of expansion that are well approximated by de Sitter (dS) space. Still lacking is a quantum mechanical description of dS, both globally and when restricted to the static patch. We develop a novel prescription for computing holographic complexity in the dS static patch to determine its microscopic features. Specifically, we propose that the natural candidate for dS complexity is the volume of extremal timelike surfaces restricted to the static patch,…

[2025-07-21 Mon (UTC), 3 new articles found for cs.CC Computational Complexity]
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[2025-08-21 Thu (UTC), 2 new articles found for cs.CC Computational Complexity]
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Low-complexity CV-QKD system with optical pilot-tone local oscillator synchronization
Samael Sarmiento, Jeison Tabares, Sebastian Etcheverry
https://arxiv.org/abs/2509.12735 htt…

Low-complexity CV-QKD system with optical pilot-tone local oscillator synchronization
This study presents a comprehensive simulation-based analysis of optical pilot tone generation for local oscillator synchronization in continuous-variable quantum key distribution (CV-QKD) systems using Gaussian-modulated (GM) coherent states. We compare system performance when the pilot tone is generated either electrically or optically, examining the effects of key parameters such as pilot tone power, laser linewidth, digital-to-analog converter resolution, and link distance. The results prov…

[2025-08-20 Wed (UTC), 3 new articles found for cs.CC Computational Complexity]
toXiv_bot_toot

Exact versus Approximate Representations of Boolean Functions in the De Morgan Basis
Arkadev Chattopadhyay, Yogesh Dahiya, Shachar Lovett
https://arxiv.org/abs/2507.13963

Exact versus Approximate Representations of Boolean Functions in the De Morgan Basis
A seminal result of Nisan and Szegedy (STOC, 1992) shows that for any total Boolean function, the degree of the real polynomial that computes the function, and the minimal degree of a real polynomial that point-wise approximates the function, are at most polynomially separated. Extending this result from degree to other complexity measures like sparsity of the polynomial representation, or total weight of the coefficients, remains poorly understood. In this work, we consider this problem in t…

Crosslisted article(s) found for cs.CC. https://arxiv.org/list/cs.CC/new
[1/1]:
- Computational complexity of Berry phase estimation in topological phases of matter
Ryu Hayakawa, Kazuki Sakamoto, Chusei Kiumi