37 citations · 46 across the 8 of their papers we have counts for
9 papers
Factorized approximate inverse preconditioners in the tensor train format
Pau Torrente Badia, Daniel Pérez García, Artur Garcia-Saez +1
We present a preconditioning pipeline that accelerates Tensor Train (TT) linear solvers for symmetric positive-definite problems. Extending the Factorized Sparse Approximate Invers…
Quantum Metropolis-Hastings via Penalised Qubitized Walks: Spectral Filtering and Circuit Implementation
Miguel Carrasco-Arango, Rosa M. Badia, Artur Garcia-Saez
The Metropolis-Hastings algorithm is a cornerstone of Markov Chain Monte Carlo methods, underpinning a wide range of applications in computational physics, Bayesian inference, and…
Limits of Clifford Disentangling in Tensor Network States
Sergi Masot-Llima, Piotr Sierant, Paolo Stornati +1
Tensor network methods leverage the limited entanglement of quantum states to efficiently simulate many-body systems. Alternatively, Clifford circuits provide a framework for handl…
Computing quantum magic of state vectors
Piotr Sierant, Jofre Vallès-Muns, Artur Garcia-Saez
Non-stabilizerness, also known as ``magic,'' quantifies how far a quantum state departs from the stabilizer set. It is a central resource behind quantum advantage and a useful prob…
Tensor Network for Anomaly Detection in the Latent Space of Proton Collision Events at the LHC
Ema Puljak, Maurizio Pierini, Artur Garcia-Saez
The pursuit of discovering new phenomena at the Large Hadron Collider (LHC) demands constant innovation in algorithms and technologies. Tensor networks are mathematical models on t…
tn4ml: Tensor Network Training and Customization for Machine Learning
Ema Puljak, Sergio Sanchez-Ramirez, Sergi Masot-Llima +3
Tensor Networks have emerged as a prominent alternative to neural networks for addressing Machine Learning challenges in foundational sciences, paving the way for their application…
Advantages of density in tensor network geometries for gradient based training
Sergi Masot-Llima, Artur Garcia-Saez
Tensor networks are a very powerful data structure tool originating from quantum system simulations. In recent years, they have seen increased use in machine learning, mostly in tr…
Stabilizer Tensor Networks: universal quantum simulator on a basis of stabilizer states
Sergi Masot-Llima, Artur Garcia-Saez
Efficient simulation of quantum computers relies on understanding and exploiting the properties of quantum states. This is the case for methods such as tensor networks, based on en…
EinExprs: Contraction Paths of Tensor Networks as Symbolic Expressions
Sergio Sanchez-Ramirez, Jofre Vallès-Muns, Artur Garcia-Saez
Tensor Networks are graph representations of summation expressions in which vertices represent tensors and edges represent tensor indices or vector spaces. In this work, we present…