Tootfinder

The near infrared airglow continuum conundrum. Constraints for ground-based faint object spectroscopy
J. K. M. Viuho (Cosmic Dawn Center, Niels Bohr Institute, University of Copenhagen, Jagtvej 155A, DK-2200, Copenhagen N, Denmark, Nordic Optical Telescope, Rambla Jose Ana Fernandez Perez 7, ES-38711 Brena Baja, Spain, Department of Physics and Astronomy, Aarhus University, Munkegade 120, DK-8000 Aarhus C, Denmark), J. P. U. Fynbo (Cosmic Dawn Center, Niels Bohr Institute, University of Copenhagen, Jagtvej 155A, DK-2200, Copenhagen N, Denmark), M. I. Andersen (Cosmic Dawn Center, Niels Bohr Institute, University of Copenhagen, Jagtvej 155A, DK-2200, Copenhagen N, Denmark)
#toXiv_bot_toot

Mitigating Data Poisoning Attacks to Local Differential Privacy
Xiaolin Li, Ninghui Li, Boyang Wang, Wenhai Sun
https://arxiv.org/abs/2506.02156 https://…

Mitigating Data Poisoning Attacks to Local Differential Privacy
The distributed nature of local differential privacy (LDP) invites data poisoning attacks and poses unforeseen threats to the underlying LDP-supported applications. In this paper, we propose a comprehensive mitigation framework for popular frequency estimation, which contains a suite of novel defenses, including malicious user detection, attack pattern recognition, and damaged utility recovery. In addition to existing attacks, we explore new adaptive adversarial activities for our mitigation de…

Adaptive Exploration in Lenia with Intrinsic Multi-Objective Ranking
Niko Lorantos, Lee Spector
https://arxiv.org/abs/2506.02990 https://

Adaptive Exploration in Lenia with Intrinsic Multi-Objective Ranking
Artificial life aims to understand the fundamental principles of biological life by creating computational models that exhibit life-like properties. Although artificial life systems show promise for simulating biological evolution, achieving open-endedness remains a central challenge. This work investigates mechanisms to promote exploration and unbounded innovation within evolving populations of Lenia continuous cellular automata by evaluating individuals against each other with respect to dist…

First-Principles and Machine Learning Investigation of the Structural and Optoelectronic Properties of Dodecaphenylyne: A Novel Carbon Allotrope
Kleuton A. L. Lima, Jose A. S. Laranjeira, Nicolas F. Martins, Julio R. Sambrano, Alexandre C. Dias, Luiz A. Ribeiro Junior, Douglas S. Galvao
https://arxiv.org/abs/2506.02218

First-Principles and Machine Learning Investigation of the Structural and Optoelectronic Properties of Dodecaphenylyne: A Novel Carbon Allotrope
We report the computational discovery and characterization of Dodecaphenylyne (DP), a novel carbon allotrope with a distinctive geometric arrangement. DP structural, thermodynamic, mechanical, electronic, and optical properties were evaluated using density functional theory and a machine learning interatomic potential trained explicitly for this material. The formation energy of -7.98 eV/atom indicates high thermodynamic stability, further supported by the absence of imaginary phonon modes and …

Characterizing circle graphs with binomial partial Petrial polynomials
Ruiqing Feng, Qi Yan, Xuan Zheng
https://arxiv.org/abs/2507.02421 https://

Characterizing circle graphs with binomial partial Petrial polynomials
The partial Petrial polynomial was first introduced by Gross, Mansour, and Tucker as a generating function that enumerates the Euler genera of all possible partial Petrials on a ribbon graph. Yan and Li later extended this polynomial invariant to circle graphs by utilizing the correspondence between circle graphs and bouquets. Their explicit computation demonstrated that paths produce binomial polynomials, specifically those containing exactly two non-zero terms. This discovery led them to pose…

StarVC: A Unified Auto-Regressive Framework for Joint Text and Speech Generation in Voice Conversion
Fengjin Li, Jie Wang, Yadong Niu, Yongqing Wang, Meng Meng, Jian Luan, Zhiyong Wu
https://arxiv.org/abs/2506.02414

StarVC: A Unified Auto-Regressive Framework for Joint Text and Speech Generation in Voice Conversion
Voice Conversion (VC) modifies speech to match a target speaker while preserving linguistic content. Traditional methods usually extract speaker information directly from speech while neglecting the explicit utilization of linguistic content. Since VC fundamentally involves disentangling speaker identity from linguistic content, leveraging structured semantic features could enhance conversion performance. However, previous attempts to incorporate semantic features into VC have shown limited eff…

This https://arxiv.org/abs/2103.02626 has been replaced.
link: https://scholar.google.com/scholar?q=a

Coherent and dissipative dynamics at quantum phase transitions
The many-body physics at quantum phase transitions shows a subtle interplay between quantum and thermal fluctuations, emerging in the low-temperature limit. In this review, we first give a pedagogical introduction to the equilibrium behavior of systems in that context, whose scaling framework is essentially developed by exploiting the quantum-to-classical mapping and the renormalization-group theory of critical phenomena at continuous phase transitions. Then we specialize to protocols entailing…

This https://arxiv.org/abs/2502.07955 has been replaced.
initial toot: https://mastoxiv.page/@a…

Revealing isotropic abundant low-energy excitations in UTe$_2$ through complex microwave surface impedance
The complex surface impedance is a well-established tool to study the super- and normal-fluid responses of superconductors. Fundamental properties of the superconductor, such as the pairing mechanism, Fermi surface, and topological properties, also influence the surface impedance. We explore the microwave surface impedance of spin-triplet UTe$_2$ single crystals as a function of temperature using resonant cavity perturbation measurements employing a novel multi-modal analysis to gain insight in…

Equivalence of Left- and Right-Invariant Extended Kalman Filters on Matrix Lie Groups
Finn G. Maurer, Erlend A. Basso, Henrik M. Schmidt-Didlaukies, Torleiv H. Bryne
https://arxiv.org/abs/2506.01514

Equivalence of Left- and Right-Invariant Extended Kalman Filters on Matrix Lie Groups
This paper derives the extended Kalman filter (EKF) for continuous-time systems on matrix Lie groups observed through discrete-time measurements. By modeling the system noise on the Lie algebra and adopting a Stratonovich interpretation for the stochastic differential equation (SDE), we ensure that solutions remain on the manifold. The derivation of the filter follows classical EKF principles, naturally integrating a necessary full-order covariance reset post-measurement update. A key contribut…

High-Throughput NEB for Li-Ion Conductor Discovery via Fine-Tuned CHGNet Potential
Jingchen Lian, Xiao Fu, Xuhe Gong, Ruijuan Xiao, Hong Li
https://arxiv.org/abs/2507.02334

High-Throughput NEB for Li-Ion Conductor Discovery via Fine-Tuned CHGNet Potential
Solid-state electrolytes are essential in the development of all-solid-state batteries. While density functional theory (DFT)-based nudged elastic band (NEB) and ab initio molecular dynamics (AIMD) methods provide fundamental insights on lithium-ion migration barriers and ionic conductivity, their computational costs make large-scale materials exploration challenging. In this study, we developed a high-throughput NEB computational framework integrated with the fine-tuned universal machine learn…