Papers
Research papers from arXiv and related sources
High-Fidelity Digital Twin Dataset Generation for Inverter-Based Microgrids Under Multi-Scenario Disturbances
Public power-system datasets often lack electromagnetic transient (EMT) waveforms, inverter control dynamics, and diverse disturbance coverage, which limits their usefulness for training surrogate ...
Osasumwen Cedric Ogiesoba-Eguakun, Kaveh Ashenayi, Suman Rath
Degeneracy-Resilient Teach and Repeat for Geometrically Challenging Environments Using FMCW Lidar
Teach and Repeat (T&R) topometric navigation enables robots to autonomously repeat previously traversed paths without relying on GPS, making it well suited for operations in GPS-denied environments...
Katya M. Papais, Wenda Zhao, Timothy D. Barfoot
At the stellar noise frontier: a transit survey of 121 TESS M3--M6 dwarfs
M-dwarf stars are the most favorable hosts for detecting small transiting planets, yet mid-to-late M-dwarfs that acquired sufficient TESS multi-sector coverage only through recent Cycle 6+ observat...
Yohann Tschudi
ACE Runtime - A ZKP-Native Blockchain Runtime with Sub-Second Cryptographic Finality
Existing high performance blockchains verify one signature per transaction on the critical path, which creates O(N) verification cost, high hardware pressure, and difficult post quantum migration. ...
Jian Sheng Wang
A Trust-Region Interior-Point Stochastic Sequential Quadratic Programming Method
In this paper, we propose a trust-region interior-point stochastic sequential quadratic programming (TR-IP-SSQP) method for solving optimization problems with a stochastic objective and determinist...
Yuchen Fang, Jihun Kim, Sen Na, James Demmel, Javad Lavaei
Rethinking the Harmonic Loss via Non-Euclidean Distance Layers
Cross-entropy loss has long been the standard choice for training deep neural networks, yet it suffers from interpretability limitations, unbounded weight growth, and inefficiencies that can contri...
Maxwell Miller-Golub, Kamil Faber, Marcin Pietron, Panpan Zheng, Pasquale Minervini, Roberto Corizzo
Hybrid Hidden Markov Model for Modeling Equity Excess Growth Rate Dynamics: A Discrete-State Approach with Jump-Diffusion
Generating synthetic financial time series that preserve statistical properties of real market data is essential for stress testing, risk model validation, and scenario design. Existing approaches,...
Abdulrahman Alswaidan, Jeffrey D. Varner
Octopus-inspired Distributed Control for Soft Robotic Arms: A Graph Neural Network-Based Attention Policy with Environmental Interaction
This paper proposes SoftGM, an octopus-inspired distributed control architecture for segmented soft robotic arms that learn to reach targets in contact-rich environments using online obstacle disco...
Linxin Hou, Qirui Wu, Zhihang Qin, Yongxin Guo, Cecilia Laschi
Fully Symbolic Analysis of Loop Locality: Using Imaginary Reuse to Infer Real Performance
This paper presents a new theory of locality and its compiler support. The theory is fully symbolic and derives locality as polynomials, and the compiler analysis supports affine loop nests. They d...
Yifan Zhu, Yekai Pan, Chen Ding, Yanghui Wu
Cosmological simulation of radio synchrotron bridge between pre-merging galaxy clusters
Radio bridges are diffuse synchrotron emission observed between merging galaxy clusters. Recent radio observations have reported both detections and non-detections of radio bridges between clusters...
Kosuke Nishiwaki, Gianfranco Brunetti, Franco Vazza, Claudio Gheller
A modern halo streaming model for redshift space distortions
Accurate modelling of redshift-space distortions (RSD) in galaxy clustering is essential for extracting cosmological information from current and forthcoming large-scale structure surveys. While pe...
Cheng-Zong Ruan, Baojiu Li, Carlton M. Baugh, Sownak Bose, Alexander Eggemeier, David F. Mota
Radio selection of heavily obscured AGN in the J1030 field: unraveling a missing Compton-thick population
We tested the effectiveness of radio selection to discover heavily obscured AGNs, particularly at high-z, and we measured their abundance for the first time from a radio perspective. We consider th...
Giovanni Mazzolari, Roberto Gilli, Marco Mignoli, Marcella Brusa, Isabella Prandoni, Fabio Vito, ...
Bias in Universal Machine-Learned Interatomic Potentials and its Effects on Fine-Tuning
Universal machine learned interatomic potentials (uMLIPs) embody a growing area of interest due to their transferability across the periodic table, displaying an error of about 0.6 kcal/mol against...
Nicolas Wong, Julia H. Yang
Towards macroeconomic analysis without microfoundations: measuring the entropy of simulated exchange economies
The theory of thermal macroeconomics (TM) analyses economic phenomena within the mathematical framework of classical thermodynamics, using a set of axioms that apply to the purely macroscopic aspec...
Yihang Luo, Robert S. MacKay, Nick Chater
Shrinkage Regularization for (Non)Linear Serial Dependence Test
This paper introduces a regularized test of the null hypothesis of the absence of linear and nonlinear serial dependence for high-dimensional non-Gaussian time series. Our approach extends the port...
Francesco Giancaterini, Alain Hecq, Joann Jasiak, Aryan Manafi Neyazi
A neural operator for predicting vibration frequency response curves from limited data
In the design of engineered components, rigorous vibration testing is essential for performance validation and identification of resonant frequencies and amplitudes encountered during operation. Pe...
D. Bluedorn, A. Badawy, B. E. Saunders, D. Roettgen, A. Abdelkefi
Reason and Verify: A Framework for Faithful Retrieval-Augmented Generation
Retrieval-Augmented Generation (RAG) significantly improves the factuality of Large Language Models (LLMs), yet standard pipelines often lack mechanisms to verify inter- mediate reasoning, leaving ...
Eeham Khan, Luis Rodriguez, Marc Queudot
Uncertainty-Aware Deep Hedging
Deep hedging trains neural networks to manage derivative risk under market frictions, but produces hedge ratios with no measure of model confidence -- a significant barrier to deployment. We introd...
Manan Poddar
Adiabatic evolution of asymmetric binaries on generic orbits with new fundamental fields I: characterization of gravitational wave fluxes
We investigate the dynamics of asymmetric binaries in extensions of General Relativity featuring a massless scalar field non-minimally coupled to gravity, focusing on the interplay between eccentri...
Sara Gliorio, Matteo Della Rocca, Susanna Barsanti, Leonardo Gualtieri, Andrea Maselli, Thomas P....
The Cosmological Simulation Code OpenGadget3 -- Implementation of Self-Interacting Dark Matter
Dark matter (DM) could be subject to non-gravitational self-interactions which is relevant to resolve potential problems of cold DM on small scales. Their impact on astrophysical objects such as ga...
Moritz S. Fischer, Marc Wiertel, Cenanda Arido, Yashraj Patil, Antonio Ragagnin, Klaus Dolag, Mar...