Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Johnnie Gray"'
Autor:
Seunghoon Lee, Joonho Lee, Huanchen Zhai, Yu Tong, Alexander M. Dalzell, Ashutosh Kumar, Phillip Helms, Johnnie Gray, Zhi-Hao Cui, Wenyuan Liu, Michael Kastoryano, Ryan Babbush, John Preskill, David R. Reichman, Earl T. Campbell, Edward F. Valeev, Lin Lin, Garnet Kin-Lic Chan
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-7 (2023)
The extent of problems in quantum chemistry for which quantum algorithms could provide a speedup is still unclear, as well as the kind of speedup one should expect. Here, the authors look at the problem of ground state energy estimation, and gather t
Externí odkaz:
https://doaj.org/article/bf9e0274d52c4891bee800a0d650eeba
Autor:
Johnnie Gray, Garnet Kin-Lic Chan
Publikováno v:
Physical Review X, Vol 14, Iss 1, p 011009 (2024)
Tensor network contraction is central to problems ranging from many-body physics to computer science. We describe how to approximate tensor network contraction through bond compression on arbitrary graphs. In particular, we introduce a hyperoptimizat
Externí odkaz:
https://doaj.org/article/68d645ff95a4490983952339ce8e83c5
Publikováno v:
Physical Review Research, Vol 5, Iss 1, p 013156 (2023)
Many computational problems can be formulated in terms of high-dimensional functions. Simple representations of such functions and resulting computations with them typically suffer from the “curse of dimensionality,” an exponential cost dependenc
Externí odkaz:
https://doaj.org/article/d3b373b5f5744ac6996db4ae90ead703
Publikováno v:
Physical Review X, Vol 12, Iss 1, p 011047 (2022)
We characterize the variational power of quantum circuit tensor networks in the representation of physical many-body ground states. Such tensor networks are formed by replacing the dense block unitaries and isometries in standard tensor networks by l
Externí odkaz:
https://doaj.org/article/ff169f6034904c0986df55907ba4b7f2
Publikováno v:
PRX Quantum, Vol 2, Iss 2, p 020348 (2021)
We use a metalearning neural-network approach to analyze data from a measured quantum state. Once our neural network has been trained, it can be used to efficiently sample measurements of the state in measurement bases not contained in the training d
Externí odkaz:
https://doaj.org/article/dfdc11bb39144e44bba90a050516e4f5
Autor:
Johnnie Gray, Stefanos Kourtis
Publikováno v:
Quantum, Vol 5, p 410 (2021)
Tensor networks represent the state-of-the-art in computational methods across many disciplines, including the classical simulation of quantum many-body systems and quantum circuits. Several applications of current interest give rise to tensor networ
Externí odkaz:
https://doaj.org/article/e34116e28a084e43ba047d30dde71d26
Autor:
Dian-Teng Chen, Phillip Helms, Ashlyn R. Hale, Minseong Lee, Chenghan Li, Johnnie Gray, George Christou, Vivien S. Zapf, Garnet Kin-Lic Chan, Hai-Ping Cheng
Publikováno v:
The Journal of Physical Chemistry Letters. 13:2365-2370
Publikováno v:
240406 – 6
240406 – 1
240406 – 1
Classical mechanics obeys the intuitive logic that a physical event happens at a definite spatial point. Entanglement however, breaks this logic by enabling interactions without a specific location. In this work we study these delocalised-interaction
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::02ff1154a29a5c6b2676e058227b6654
http://hdl.handle.net/10044/1/85160
http://hdl.handle.net/10044/1/85160
Autor:
Johnnie Gray, Stefanos Kourtis
Publikováno v:
Quantum, Vol 5, p 410 (2021)
Tensor networks represent the state-of-the-art in computational methods across many disciplines, including the classical simulation of quantum many-body systems and quantum circuits. Several applications of current interest give rise to tensor networ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b50989a6ef297a005877e92fdc91ff3
Publikováno v:
Physical Review B. 97
Many-body localization has become an important phenomenon for illuminating a potential rift between non-equilibrium quantum systems and statistical mechanics. However, the nature of the transition between ergodic and localized phases in models displa