collaborators

7 papers

quant-ph2026

Emission and Absorption of Microwave Photons in Orthogonal Temporal Modes across a 30-Meter Two-Node Network

Alonso Hernández-Antón, Josua D. Schär, Aleksandr Grigorev +6

The tunable interaction between stationary quantum bits and propagating modes of light allows for the encoding of quantum information in the state of itinerant photons. This abilit…

quant-ph2026

Decoherence-Free Qubit and Chiral Emission from a Giant Molecule in Waveguide QED

Yang Wang, Juan José García-Ripoll, Alan C. Santos

Combining decoherence protection with directional photon emission in a single waveguide quantum electrodynamics (QED) device remains an open challenge. Here we show that an artific…

stat.ML2026

High-Resolution Tensor-Network Fourier Methods for Exponentially Compressed Non-Gaussian Aggregate Distributions

Juan José Rodríguez-Aldavero, Juan José García-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

Photon-echo synchronization and quantum state transfer in short quantum links

Hong Jiang, Carlos Barahona-Pascual, Juan José García-Ripoll

The short quantum link regime, where the photon travel time is comparable to the emitter lifetime , is experimentally relevant but theoretically underexplored: existing fe…

quant-ph2026

Resource-Efficient Digitized Adiabatic Quantum Factorization

Felip Pellicer, Juan José García-Ripoll, Alan C. Santos

Digitized adiabatic quantum factorization is a hybrid algorithm that exploits the advantage of digitized quantum computers to implement efficient adiabatic algorithms for factoriza…

quant-ph2026

SeeMPS: A Python-based Matrix Product State and Tensor Train Library

Paula García-Molina, Juan José Rodríguez-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…