Efficient adiabatic preparation of tensor network states
نویسندگان
چکیده
The Affleck-Kennedy-Lieb-Tasaki (AKLT) states have significant applications in condensed matter physics and quantum computation. An adiabatic path that enables the deterministic preparation of a broad range many-body states, including AKLT on arbitrary lattice geometries, is proposed. numerical results 1D 2D demonstrate high efficiency this approach.
منابع مشابه
Categorical Tensor Network States
Jacob D. Biamonte, Stephen R. Clark and Dieter Jaksch Oxford University Computing Laboratory, Parks Road Oxford, OX1 3QD, United Kingdom Centre for Quantum Technologies, National University of Singapore, 3 Science Drive 2, Singapore 117543, Singapore Keble College, Parks Road, University of Oxford, Oxford OX1 3PG, United Kingdom Clarendon Laboratory, Department of Physics, University of Oxford,...
متن کاملAdiabatic preparation of many-body states in optical lattices
Anders S. Sørensen,1 Ehud Altman,2 Michael Gullans,3 J. V. Porto,4 Mikhail D. Lukin,3 and Eugene Demler3 1QUANTOP, The Niels Bohr Institute, University of Copenhagen, DK-2100 Copenhagen Ø, Denmark 2Department of Condensed Matter Physics, Weizmann Institute of Science, Rehovot, IL-76100, Israel 3Department of Physics, Harvard University, Cambridge, Massachusetts 02138, USA 4Joint Quantum Institu...
متن کاملLectures on Tensor Network States
1 1) The most updated version of these notes will be kept on the webpage listed above. Feedback welcome. Other University webpages storing a copy of these notes will not be updated.
متن کاملSecond renormalization of tensor-network states.
We propose a second renormalization group method to handle the tensor-network states or models. This method dramatically reduces the truncation error of the tensor renormalization group. It allows physical quantities of classical tensor-network models or tensor-network ground states of quantum systems to be accurately and efficiently determined.
متن کاملNeural network representation of tensor network and chiral states
We study the representational power of a Boltzmann machine (a type of neural network) in quantum many-body systems. We prove that any (local) tensor network state has a (local) neural network representation. The construction is almost optimal in the sense that the number of parameters in the neural network representation is almost linear in the number of nonzero parameters in the tensor network...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Physical review research
سال: 2023
ISSN: ['2643-1564']
DOI: https://doi.org/10.1103/physrevresearch.5.l022037