3 papers
stat.ML2026
High-Resolution Tensor-Network Fourier Methods for Exponentially Compressed Non-Gaussian Aggregate Distributions
Juan José RodrÃguez-Aldavero, Juan José GarcÃa-Ripoll
Characteristic functions of weighted sums of independent random variables exhibit low-rank structure in the quantized tensor train (QTT) representation, also known as matrix produc…
quant-ph2026
SeeMPS: A Python-based Matrix Product State and Tensor Train Library
Paula GarcÃa-Molina, Juan José RodrÃguez-Aldavero, Jorge Gidi +1
We introduce SeeMPS, a Python library dedicated to implementing tensor network algorithms based on the well-known Matrix Product States (MPS) and Quantized Tensor Train (QTT) forma…
quant-ph2025
Chebyshev approximation and composition of functions in matrix product states for quantum-inspired numerical analysis
Juan José RodrÃguez-Aldavero, Paula GarcÃa-Molina, Luca Tagliacozzo +1
This work explores the representation of univariate and multivariate functions as matrix product states (MPS), also known as quantized tensor-trains (QTT). It proposes an algorithm…