Telecomunicaciones, información y comunicación

Stochastic modeling of Fourier modes in two-dimensional turbulence via filtered white noise

- Modeling turbulent flows by a random Fourier decomposition is a classical procedure in order to use simplified models of turbulence in heat transport and other applications. We carefully investigate...

Backdoor Threats in Variational Quantum Circuits: Taxonomy, Attacks, and Defenses

- Variational quantum algorithms (VQAs) are a central paradigm for noisy intermediate-scale (NISQ) quantum computing, yet their reliance on predesigned and pretrained variational quantum circuits...

Parallel Scan Recurrent Neural Quantum States for Scalable Variational Monte Carlo

- Neural-network quantum states have emerged as a powerful variational framework for quantum many-body systems, with recent progress often driven by massively parallel architectures such as...

What is Learnable in Valiant's Theory of the Learnable?

- Valiant's 1984 paper is widely credited with introducing the PAC learning model, but it, in fact, introduced a different model: unlike PAC learning, the learner receives only positives, may issue...

Beyond Explained Variance: A Cautionary Tale of PCA

- We address shortcomings of principal component analysis (PCA) for visualizing high-dimensional data lying on a nonlinear low-dimensional manifold via two-dimensional scatterplots, focusing on a...

Generating synthetic computed tomography for radiotherapy: SynthRAD2025 challenge report

- Radiation therapy (RT) requires precise dose delivery over multiple fractions, with CT fundamental for treatment planning due to its electron density information. Repeated CT acquisitions impose...

Ergodicity Library: A Python Toolkit for Stochastic-Process Simulation, Time-Average Diagnostics, and Agent-Based Experiments

- ergodicity is an open-source Python library for computational work on stochastic dynamics, with particular emphasis on non-ergodicity, time-average behavior, heavy-tailed processes, and decision...

OpenAaaS: An Open Agent-as-a-Service Framework for Distributed Materials-Informatics Research

- The Materials Genome Initiative catalyzed the proliferation of centralized platforms--SaaS, PaaS, and IaaS--that aggregate computational and experimental resources for accelerated materials...

DeepFilters: Scattering-Aware Pupil Engineering with Learned Digital Filter Reconstruction for Extended Depth of Field Microscopy

- Extended depth of field microscopy encodes axial information into a single acquisition through engineered point spread functions, but conventional and deep optics approaches are subject to...

CO-MAP: A Reinforcement Learning Approach to the Qubit Allocation Problem

- A quantum compiler is a critical piece in the quantum computing pipeline since it allows an abstract quantum circuit to be run on a physical quantum computer. One extremely important subproblem in...

Sticky CIR process with potential: invariant measure and exact sampling

- We study the sticky Cox-Ingersoll-Ross (CIR) process in one dimension, a diffusion on $[0,\infty)$ with a sticky boundary condition at the origin, arising as the marginal process in a sparse Bayesian...

Proximal-Based Generative Modeling for Bayesian Inverse Problems

- Score-based diffusion models demonstrate superior performance in generative tasks but encounter fundamental bottlenecks in inverse problems due to the analytical intractability of the time-dependent...

Learning Perturbations to Extrapolate Your LLM

- Recent advancements in large language models demonstrate that injecting perturbations can substantially enhance extrapolation performance. However, current approaches often rely on discrete...

TRUST-TAEA: A trustworthiness-guided two-archive evolutionary algorithm with variable-grouping sparse search for large-scale multi-objective optimization

- Large-scale multi-objective optimization remains challenging because high-dimensional decision spaces, complex variable interactions, and limited function evaluation budgets make it difficult to...

Universal Design and Physical Applications of Non-Uniform Cellular Automata on Translationally Invariant Lattices

- Lattice geometry profoundly shapes physical phenomena such as subsystem symmetry and directed percolation (DP). Among various lattice geometries, hyperbolic lattices are characterized by constant...

Neural QAOA$^{2}$: Differentiable Joint Graph Partitioning and Parameter Initialization for Quantum Combinatorial Optimization

- The quantum approximate optimization algorithm (QAOA) holds promise for combinatorial optimization but is constrained by limited qubits. While divide-and-conquer frameworks like QAOA$^{2}$ address...

Adaptive Kernel Density Estimation with Pre-training

- Density estimation in high-dimensional settings is an important and challenging statistical this http URL methods based on kernel smoothing...

QCIVET: A Quantum--Classical Pipeline Integrity Framework with Contract-Based Subtype Verification and Hash-Chained Audit Traces

- Hybrid quantum--classical pipelines increasingly support applications such as drug discovery, fraud detection, and cloud quantum processing unit (QPU) auditing, yet existing integrity-verification...

State-of-art minibatches via novel DPP kernels: discretization, wavelets, and rough objectives

- Determinantal point processes (DPPs) have emerged as a kernelized alternative to vanilla independent sampling for generating efficient minibatches, coresets and other parsimonious representations of...

Amortized Neural Clustering of Time Series based on Statistical Features

- This paper introduces an algorithm-agnostic approach to feature-based time series clustering via amortized neural inference. By training neural networks to approximate the optimal partitioning rule...

On Hallucinations in Inverse Problems: Fundamental Limits and Provable Assessment Methods

- Artificial intelligence (AI) has transformed imaging inverse problems, from medical diagnostics to Earth observation. Yet deep neural networks can produce hallucinations, realistic-looking but...