Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Gordon, Max Hunter"'
Autor:
Melanson, Denis, Khater, Mohammad Abu, Aifer, Maxwell, Donatella, Kaelan, Gordon, Max Hunter, Ahle, Thomas, Crooks, Gavin, Martinez, Antonio J., Sbahi, Faris, Coles, Patrick J.
Recent breakthroughs in artificial intelligence (AI) algorithms have highlighted the need for novel computing hardware in order to truly unlock the potential for AI. Physics-based hardware, such as thermodynamic computing, has the potential to provid
Externí odkaz:
http://arxiv.org/abs/2312.04836
Publikováno v:
Quantum 8, 1356 (2024)
The Bethe ansatz represents an analytical method enabling the exact solution of numerous models in condensed matter physics and statistical mechanics. When a global symmetry is present, the trial wavefunctions of the Bethe ansatz consist of plane wav
Externí odkaz:
http://arxiv.org/abs/2309.14430
Autor:
Aifer, Maxwell, Donatella, Kaelan, Gordon, Max Hunter, Duffield, Samuel, Ahle, Thomas, Simpson, Daniel, Crooks, Gavin E., Coles, Patrick J.
Linear algebraic primitives are at the core of many modern algorithms in engineering, science, and machine learning. Hence, accelerating these primitives with novel computing hardware would have tremendous economic impact. Quantum computing has been
Externí odkaz:
http://arxiv.org/abs/2308.05660
Autor:
Moussa, Charles, Gordon, Max Hunter, Baczyk, Michal, Cerezo, M., Cincio, Lukasz, Coles, Patrick J.
Publikováno v:
Quantum Sci. Technol. 8 045019 (2023)
Quantum-enhanced data science, also known as quantum machine learning (QML), is of growing interest as an application of near-term quantum computers. Variational QML algorithms have the potential to solve practical problems on real hardware, particul
Externí odkaz:
http://arxiv.org/abs/2211.04965
Autor:
Alderete, C. Huerta, Gordon, Max Hunter, Sauvage, Frederic, Sone, Akira, Sornborger, Andrew T., Coles, Patrick J., Cerezo, M.
Publikováno v:
Phys. Rev. Lett. 129, 190501 (2022)
In a standard Quantum Sensing (QS) task one aims at estimating an unknown parameter $\theta$, encoded into an $n$-qubit probe state, via measurements of the system. The success of this task hinges on the ability to correlate changes in the parameter
Externí odkaz:
http://arxiv.org/abs/2206.09919
Autor:
Bultrini, Daniel, Wang, Samson, Czarnik, Piotr, Gordon, Max Hunter, Cerezo, M., Coles, Patrick J., Cincio, Lukasz
Publikováno v:
Quantum 7, 1060 (2023)
When error correction becomes possible it will be necessary to dedicate a large number of physical qubits to each logical qubit. Error correction allows for deeper circuits to be run, but each additional physical qubit can potentially contribute an e
Externí odkaz:
http://arxiv.org/abs/2205.13454
Publikováno v:
PRX Quantum 3, 030334 (2022)
Principal component analysis (PCA) is a dimensionality reduction method in data analysis that involves diagonalizing the covariance matrix of the dataset. Recently, quantum algorithms have been formulated for PCA based on diagonalizing a density matr
Externí odkaz:
http://arxiv.org/abs/2204.03495
Autor:
Sopena, Alejandro, Gordon, Max Hunter, García-Martín, Diego, Sierra, Germán, López, Esperanza
Publikováno v:
Quantum 6, 796 (2022)
The Algebraic Bethe Ansatz (ABA) is a highly successful analytical method used to exactly solve several physical models in both statistical mechanics and condensed-matter physics. Here we bring the ABA into unitary form, for its direct implementation
Externí odkaz:
http://arxiv.org/abs/2202.04673
Autor:
Bultrini, Daniel, Gordon, Max Hunter, Czarnik, Piotr, Arrasmith, Andrew, Cerezo, M., Coles, Patrick J., Cincio, Lukasz
Publikováno v:
Quantum 7, 1034 (2023)
Error mitigation is an essential component of achieving a practical quantum advantage in the near term, and a number of different approaches have been proposed. In this work, we recognize that many state-of-the-art error mitigation methods share a co
Externí odkaz:
http://arxiv.org/abs/2107.13470
Error mitigation is likely to be key in obtaining near term quantum advantage. In this work we present one of the first implementations of several Clifford data regression based methods which are used to mitigate the effect of noise in real quantum d
Externí odkaz:
http://arxiv.org/abs/2103.12680