Blog
Magnetic-field oscillations of the critical temperature in ultraclean, two-dimensional Type-I superconductor
We investigate the influence of Landau Levels (LLs) and Zeeman energy, induced by an applied magnetic field ${\bf B}$, on the critical temperature $T_c$ for two-dimensional (2D) ultraclean metals using a fully quantum mechanical approach within the Bardeen-Cooper-Schrieffer (BCS) teoria. In contrast...
Perturbed Gradient Descent via Convex Quadratic Approximation for Nonconvex Bilevel Optimization
Bilevel optimization is a fundamental tool in hierarchical decision-making and has been widely applied to machine learning tasks such as hyperparameter tuning, meta-learning, and continual learning. While significant progress has been made in bilevel optimization, existing methods predominantly focus on the {nonconvex-strongly...
Robotic Grinding Skills Learning Based on Geodesic Length Dynamic Motion Primitives
Learning grinding skills from human craftsmen via imitation learning has become a key research topic in robotic machining. Due to their strong generalization and robustness to external disturbances, Dynamical Movement Primitives (DMPs) offer a promising approach for robotic grinding skill learning. Tuttavia,...
FLAG: Formal and LLM-assisted SVA Generation for Formal Specifications of On-Chip Communication Protocols
Formal specifications of on-chip communication protocols are crucial for system-on-chip (SoC) design and verification. Tuttavia, manually constructing these formal specifications from informal documents remains a tedious and error-prone task. Although recent efforts have used Large Language Models (LLM) to generate SystemVerilog Assertion...
Synchronized in-gap edge states and robust copropagation in topological insulators without magnetic flux
Copropagation of antichiral edge states in the metallic phase requires the bulk states as counterpropagating modes. Without the band gap protection, the copropagation along the boundaries is easily scattered into the bulk and the counterpropagation in the bulk is not robust against...
Multi-Modal Traffic Analysis: Integrating Time-Series Forecasting, Accident Prediction, and Image Classification
This study proposes an integrated machine learning framework for advanced traffic analysis, combining time-series forecasting, classificazione, and computer vision techniques. The system utilizes an ARIMA(2,0,1) model for traffic prediction (MAE: 2.1), an XGBoost classifier for accident severity classification (100% accuracy on balanced...
An Adaptive Finite Element DtN Method for the Acoustic-Elastic Interaction Problem in Periodic Structures
Consider a time-harmonic acoustic plane wave incident onto an elastic body with an unbounded periodic surface. The medium above the surface is supposed to be filled with a homogeneous compressible inviscid air/fluid of constant mass density, while the elastic body is assumed...
Quantum stream cipher and Quantum block cipher -The Era of 100 Gbit/sec real-time encryption-
This paper is the part-II of the previous paper and introduces the world of Yuen’s concept. In the theory of cryptology, the Shannon impossibility theorem states that the upper bound of the security of a plaintext against a ciphertext-only attack is the...
Targeted AMP generation through controlled diffusion with efficient embeddings
Deep learning-based antimicrobial peptide (AMP) discovery faces critical challenges such as low experimental hit rates as well as the need for nuanced controllability and efficient modeling of peptide properties. Per affrontare queste sfide, we introduce OmegAMP, a framework that leverages a diffusion-based...
Efficient simulation of discrete galaxy populations and associated radiation fields during the first billion years
Understanding the epochs of cosmic dawn and reionisation requires us to leverage multi-wavelength and multi-tracer observations, with each dataset providing a complimentary piece of the puzzle. To interpret such data, we update the public simulation code, 21cmFASTv4, to include a discrete source...