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of 46
pro vyhledávání: '"García, Roy"'
Quantum computers promise to solve computational problems significantly faster than classical computers. These 'speed-ups' are achieved by utilizing a resource known as magic. Measuring the amount of magic used by a device allows us to quantify its p
Externí odkaz:
http://arxiv.org/abs/2408.01663
Publikováno v:
Phys. Rev. B 109, 174207 (2024)
Magic, or nonstabilizerness, characterizes how far away a state is from the stabilizer states, making it an important resource in quantum computing, under the formalism of the Gotteman-Knill theorem. In this paper, we study the magic of the $1$-dimen
Externí odkaz:
http://arxiv.org/abs/2211.10350
Quantum scrambling refers to the spread of local quantum information into the many degrees of freedom of a quantum system. In this work, we introduce a resource theory of scrambling which incorporates two mechanisms, "entanglement scrambling" and "ma
Externí odkaz:
http://arxiv.org/abs/2208.10477
The existence of barren plateaus has recently revealed new training challenges in quantum machine learning (QML). Uncovering the mechanisms behind barren plateaus is essential in understanding the scope of problems that QML can efficiently tackle. Ba
Externí odkaz:
http://arxiv.org/abs/2205.06679
Publikováno v:
Commun. Math. Phys. 405,161 (2024)
Quantum circuit complexity-a measure of the minimum number of gates needed to implement a given unitary transformation-is a fundamental concept in quantum computation, with widespread applications ranging from determining the running time of quantum
Externí odkaz:
http://arxiv.org/abs/2204.12051
Publikováno v:
npj Quantum Inf 10, 6 (2024)
The classical shadow estimation protocol is a noise-resilient and sample-efficient quantum algorithm for learning the properties of quantum systems. Its performance depends on the choice of a unitary ensemble, which must be chosen by a user in advanc
Externí odkaz:
http://arxiv.org/abs/2202.03272
We characterize a quantum neural network's error in terms of the network's scrambling properties via the out-of-time-ordered correlator. A network can be trained by optimizing either a loss function or a cost function. We show that, with some probabi
Externí odkaz:
http://arxiv.org/abs/2112.01440
Publikováno v:
Phys. Rev. Research 3, 033155 (2021)
Quantum dynamics is of fundamental interest and has implications in quantum information processing. The four-point out-of-time-ordered correlator (OTOC) is traditionally used to quantify quantum information scrambling under many-body dynamics. Due to
Externí odkaz:
http://arxiv.org/abs/2102.01008
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