Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Zichang He"'
Publikováno v:
IEEE Transactions on Quantum Engineering, Vol 5, Pp 1-12 (2024)
Given their potential to demonstrate near-term quantum advantage, variational quantum algorithms (VQAs) have been extensively studied. Although numerous techniques have been developed for VQA parameter optimization, it remains a significant challenge
Externí odkaz:
https://doaj.org/article/1f70c6c338424805ae31b652f8ace178
Autor:
Zichang He, Ruslan Shaydulin, Shouvanik Chakrabarti, Dylan Herman, Changhao Li, Yue Sun, Marco Pistoia
Publikováno v:
npj Quantum Information, Vol 9, Iss 1, Pp 1-11 (2023)
Abstract Quantum alternating operator ansatz (QAOA) has a strong connection to the adiabatic algorithm, which it can approximate with sufficient depth. However, it is unclear to what extent the lessons from the adiabatic regime apply to QAOA as execu
Externí odkaz:
https://doaj.org/article/0b5b1bec92c048c48bc618d261714eb2
Publikováno v:
International Journal of Distributed Sensor Networks, Vol 13 (2017)
In real applications, sensors may work in complicated environments; thus, how to measure the uncertain degree of sensor reports before applying sensor data fusion is a big challenge. To address this issue, an improved belief entropy–based uncertain
Externí odkaz:
https://doaj.org/article/f8377c7d49944be980bb0f09765ecc62
Publikováno v:
Sensors, Vol 17, Iss 9, p 1972 (2017)
Specific emitter identification plays an important role in contemporary military affairs. However, most of the existing specific emitter identification methods haven’t taken into account the processing of uncertain information. Therefore, this pape
Externí odkaz:
https://doaj.org/article/d9e4e132326641e18476100bdd915882
QuYBE is an open-source algebraic compiler for the compression of quantum circuits. It has been applied for the efficient simulation of the Heisenberg Hamiltonian on quantum computers. Currently, it can simulate the time dynamics of one-dimensional c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::24e1fc0467ac00b4cc9a73ea7d99a84d
http://arxiv.org/abs/2212.06948
http://arxiv.org/abs/2212.06948
Publikováno v:
2022 IEEE High Performance Extreme Computing Conference (HPEC).
One of the key problems in tensor network based quantum circuit simulation is the construction of a contraction tree which minimizes the cost of the simulation, where the cost can be expressed in the number of operations as a proxy for the simulation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::04968e82a9f074e067e0816bfcdd7831
https://doi.org/10.1109/hpec55821.2022.9926353
https://doi.org/10.1109/hpec55821.2022.9926353
Publikováno v:
Annu Int Conf IEEE Eng Med Biol Soc
Magnetic resonance imaging (MRI) is a powerful imaging modality that revolutionizes medicine and biology. The imaging speed of high-dimensional MRI is often limited, which constrains its practical utility. Recently, low-rank tensor models have been e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::721df035167e94b309eb85b522be719c
https://doi.org/10.1109/embc48229.2022.9871360
https://doi.org/10.1109/embc48229.2022.9871360
Autor:
Zichang He, Zheng Zhang
Fabrication process variations can significantly influence the performance and yield of nano-scale electronic and photonic circuits. Stochastic spectral methods have achieved great success in quantifying the impact of process variations, but they suf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::977564b214a434765059e29f9128a69d
Autor:
Zichang He, Zheng Zhang
Conventional yield optimization algorithms try to maximize the success rate of a circuit under process variations. These methods often obtain a high yield but reach a design performance that is far from the optimal value. This paper investigates an a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c59887e255c86b681d0c27db104ed56
Autor:
Zheng Zhang, Zichang He
Uncertainty quantification based on stochastic spectral methods suffers from the curse of dimensionality. This issue was mitigated recently by low-rank tensor methods. However, there exist two fundamental challenges in low-rank tensor-based uncertain
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d99756194838b02e63bd463b060713af