activity
20172021
most citedNon-unitary operations for ground-state calculations in near term quantum computers

46 citations · 51 across the 3 of their papers we have counts for

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20 papers · 1 filter

quant-ph2021

Improving readout in quantum simulations with repetition codes

Jakob M. Günther, Francesco Tacchino, James R. Wootton +2

Near term quantum computers suffer from the presence of different noise sources. In order to mitigate for this effect and acquire results with significantly better accuracy, there…

quant-ph2021

Application of Quantum Machine Learning using the Quantum Kernel Algorithm on High Energy Physics Analysis at the LHC

Sau Lan Wu, Shaojun Sun, Wen Guan +20

Quantum machine learning could possibly become a valuable alternative to classical machine learning for applications in High Energy Physics by offering computational speed-ups. In…

quant-ph2021

Variational learning for quantum artificial neural networks

Francesco Tacchino, Stefano Mangini, Panagiotis Kl. Barkoutsos +4

In the last few years, quantum computing and machine learning fostered rapid developments in their respective areas of application, introducing new perspectives on how information…

quant-ph2021

Improved accuracy on noisy devices by non-unitary Variational Quantum Eigensolver for chemistry applications

Francesco Benfenati, Guglielmo Mazzola, Chiara Capecci +4

We propose a modification of the Variational Quantum Eigensolver algorithm for electronic structure optimization using quantum computers, named non-unitary Variational Quantum Eige…

quant-ph2020

Quantum HF/DFT-Embedding Algorithms for Electronic Structure Calculations: Scaling up to Complex Molecular Systems

Max Rossmannek, Panagiotis Kl. Barkoutsos, Pauline J. Ollitrault +1

In the near future, material and drug design may be aided by quantum computer assisted simulations. These have the potential to target chemical systems intractable by the most powe…

quant-ph2020

Microcanonical and finite temperature ab initio molecular dynamics simulations on quantum computers

Igor O. Sokolov, Panagiotis Kl. Barkoutsos, Lukas Moeller +3

Ab initio molecular dynamics (AIMD) is a powerful tool to predict properties of molecular and condensed matter systems. The quality of this procedure is based on accurate electroni…