Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Panagiotis Kl. Barkoutsos"'
Autor:
Tanvi P. Gujarati, Mario Motta, Triet Nguyen Friedhoff, Julia E. Rice, Nam Nguyen, Panagiotis Kl. Barkoutsos, Richard J. Thompson, Tyler Smith, Marna Kagele, Mark Brei, Barbara A. Jones, Kristen Williams
Publikováno v:
npj Quantum Information, Vol 9, Iss 1, Pp 1-10 (2023)
Abstract Modeling electronic systems is an important application for quantum computers. In the context of materials science, an important open problem is the computational description of chemical reactions on surfaces. In this work, we outline a work
Externí odkaz:
https://doaj.org/article/8ae13659cb894a4bb5db66cdcf86023a
Autor:
Daniel J. Egger, Chiara Capecci, Bibek Pokharel, Panagiotis Kl. Barkoutsos, Laurin E. Fischer, Leonardo Guidoni, Ivano Tavernelli
Publikováno v:
Physical Review Research, Vol 5, Iss 3, p 033159 (2023)
State-of-the-art noisy digital quantum computers can only execute short-depth quantum circuits. Variational algorithms are a promising route to unlock the potential of noisy quantum computers since the depth of the corresponding circuits can be kept
Externí odkaz:
https://doaj.org/article/241f05b4c2a9458993ba32d6177e373f
Publikováno v:
npj Quantum Information, Vol 7, Iss 1, Pp 1-5 (2021)
Abstract Predicting the three-dimensional structure of a protein from its primary sequence of amino acids is known as the protein folding problem. Due to the central role of proteins’ structures in chemistry, biology and medicine applications, this
Externí odkaz:
https://doaj.org/article/10c48308b29c41958c920067b06a39e8
Autor:
Francesco Tacchino, Stefano Mangini, Panagiotis Kl. Barkoutsos, Chiara Macchiavello, Dario Gerace, Ivano Tavernelli, Daniele Bajoni
Publikováno v:
IEEE Transactions on Quantum Engineering, Vol 2, Pp 1-10 (2021)
In the past few years, quantum computing and machine learning fostered rapid developments in their respective areas of application, introducing new perspectives on how information processing systems can be realized and programmed. The rapidly growing
Externí odkaz:
https://doaj.org/article/d036c83a2bb74f6fbe75519aed09938f
Autor:
Laurin E. Fischer, Daniel Miller, Francesco Tacchino, Panagiotis Kl. Barkoutsos, Daniel J. Egger, Ivano Tavernelli
Publikováno v:
Physical Review Research, Vol 4, Iss 3, p 033027 (2022)
Informationally complete (IC) positive operator-valued measures (POVMs) are generalized quantum measurements that offer advantages over the standard computational basis readout of qubits. For instance, IC-POVMs enable efficient extraction of operator
Externí odkaz:
https://doaj.org/article/03f9abcb60c84e9a8372808fdfa4de1b
Autor:
Philippe Suchsland, Panagiotis Kl. Barkoutsos, Ivano Tavernelli, Mark H. Fischer, Titus Neupert
Publikováno v:
Physical Review Research, Vol 4, Iss 1, p 013165 (2022)
We develop a workflow to use current quantum computing hardware for solving quantum many-body problems, using the example of the fermionic Hubbard model. Concretely, we study a four-site Hubbard ring that exhibits a transition from a product state to
Externí odkaz:
https://doaj.org/article/38d14e74b64448c4ba8db89c32d791e6
Autor:
Guillermo García-Pérez, Matteo A.C. Rossi, Boris Sokolov, Francesco Tacchino, Panagiotis Kl. Barkoutsos, Guglielmo Mazzola, Ivano Tavernelli, Sabrina Maniscalco
Publikováno v:
PRX Quantum, Vol 2, Iss 4, p 040342 (2021)
Many prominent quantum computing algorithms with applications in fields such as chemistry and materials science require a large number of measurements, which represents an important roadblock for future real-world use cases. We introduce a novel appr
Externí odkaz:
https://doaj.org/article/5da1496b21fb49308f6dfc6cbb4cd089
Autor:
Sau Lan Wu, Shaojun Sun, Wen Guan, Chen Zhou, Jay Chan, Chi Lung Cheng, Tuan Pham, Yan Qian, Alex Zeng Wang, Rui Zhang, Miron Livny, Jennifer Glick, Panagiotis Kl. Barkoutsos, Stefan Woerner, Ivano Tavernelli, Federico Carminati, Alberto Di Meglio, Andy C. Y. Li, Joseph Lykken, Panagiotis Spentzouris, Samuel Yen-Chi Chen, Shinjae Yoo, Tzu-Chieh Wei
Publikováno v:
Physical Review Research, Vol 3, Iss 3, p 033221 (2021)
Quantum machine learning could possibly become a valuable alternative to classical machine learning for applications in high energy physics by offering computational speedups. In this study, we employ a support vector machine with a quantum kernel es
Externí odkaz:
https://doaj.org/article/47e6843f125a47ed8b9a8f9972bb4712
Autor:
Philippe Suchsland, Francesco Tacchino, Mark H. Fischer, Titus Neupert, Panagiotis Kl. Barkoutsos, Ivano Tavernelli
Publikováno v:
Quantum, Vol 5, p 492 (2021)
We present a hardware agnostic error mitigation algorithm for near term quantum processors inspired by the classical Lanczos method. This technique can reduce the impact of different sources of noise at the sole cost of an increase in the number of m
Externí odkaz:
https://doaj.org/article/9e269a88c6774412a1cbf7b07b017f87
Autor:
Alexandre Choquette, Agustin Di Paolo, Panagiotis Kl. Barkoutsos, David Sénéchal, Ivano Tavernelli, Alexandre Blais
Publikováno v:
Physical Review Research, Vol 3, Iss 2, p 023092 (2021)
A central component of variational quantum algorithms (VQAs) is the state-preparation circuit, also known as ansatz or variational form. This circuit is most commonly designed such as to exploit symmetries of the problem Hamiltonian and, in this way,
Externí odkaz:
https://doaj.org/article/3ed201530e3d444d84ea0c668b955eae