Results 61 to 70 of about 386,203 (296)
When quantum state tomography benefits from willful ignorance
New Journal of Physics, 2021 We show that quantum state tomography with perfect knowledge of the measurement apparatus proves to be, in some instances, inferior to strategies discarding all information about the measurement at hand, as in the case of data pattern tomography.
Libor Motka +4 more
doaj +1 more source
Tomography of Quantum Operations [PDF]
, 2000 Quantum operations describe any state change allowed in quantum mechanics, including the evolution of an open system or the state change due to a measurement.
D.-G. Welsch +15 more
core +2 more sources
Verifying the quantumness of bipartite correlations [PDF]
, 2015 Entanglement is at the heart of most quantum information tasks, and therefore considerable effort has been made to find methods of deciding the entanglement content of a given bipartite quantum state.
Carmeli, Claudio +4 more
core +2 more sources
Shadow tomography of quantum states [PDF]
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018 29 pages, extended abstract appeared in Proceedings of STOC'2018, revised to give slightly better upper bound (1/eps^4 rather than 1/eps^5) and lower bounds with explicit dependence on the dimension ...
openaire +2 more sources
Optical neural network quantum state tomography
Advanced Photonics, 2022 . Quantum state tomography (QST) is a crucial ingredient for almost all aspects of experimental quantum information processing. As an analog of the “imaging” technique in quantum settings, QST is born to be a data science problem, where machine learning ...
Ying Zuo +5 more
semanticscholar +1 more source
Adaptive quantum state tomography with neural networks
npj Quantum Information, 2021 Current algorithms for quantum state tomography (QST) are costly both on the experimental front, requiring measurement of many copies of the state, and on the classical computational front, needing a long time to analyze the gathered data.
Yihui Quek, Stanislav Fort, Hui Khoon Ng
doaj +1 more source
Neural-network quantum state tomography in a two-qubit experiment [PDF]
Physical Review A, 2020 We study the performance of efficient quantum state tomography methods based on neural network quantum states using measured data from a two-photon experiment. Machine learning inspired variational methods provide a promising route towards scalable state
Marcel Neugebauer +6 more
semanticscholar +1 more source
NetKet: A machine learning toolkit for many-body quantum systems
SoftwareX, 2019 We introduce NetKet, a comprehensive open source framework for the study of many-body quantum systems using machine learning techniques. The framework is built around a general and flexible implementation of neural-network quantum states, which are used ...
Giuseppe Carleo +18 more
doaj +1 more source
Finite quantum tomography via semidefinite programming
, 2007 Using the the convex semidefinite programming method and superoperator formalism we obtain the finite quantum tomography of some mixed quantum states such as: qudit tomography, N-qubit tomography, phase tomography and coherent spin state tomography ...
A. C. Doherty +26 more
core +1 more source
Robust And Efficient High-Dimensional Quantum State Tomography [PDF]
2021 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC), 2020 Quantum tomography—characterising a quantum system by assigning it a quantum state—–is an essential building block for future technologies like quantum metrology or quantum computation.
M. Rambach +5 more
semanticscholar +1 more source