Constraint satisfaction problems are a central pillar of modern computational complexity theory. This survey provides an introduction to the rapidly growing field of Quantum Hamiltonian Complexity, which includes the study of quantum constraint satisfaction problems. Over the past decade and a half, this field has witnessed fundamental breakthroughs, ranging from the establishment of a “Quantum Cook-Levin Theorem” to deep insights into the structure of 1D low-temperature quantum systems via so-called area laws. Our aim here is to provide a computer science-oriented introduction to the subject in order to help bridge the language barrier between computer scientists and physicists in the field. As such, we include the following in this survey: (1) The motivations and history of the field, (2) a glossary of condensed matter physics terms explained in computer-science friendly language, (3) overviews of central ideas from condensed matter physics, such as indistinguishable particles, mean field theory, tensor networks, and area laws, and (4) brief expositions of selected computer science-based results in the area. For example, as part of the latter, we provide a novel information theoretic presentation of Bravyi’s polynomial time algorithm for Quantum 2-SAT.
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13 October 2015
Research Article|
October 13 2015
Quantum Hamiltonian Complexity
Sevag Gharibian;
Sevag Gharibian
Simons Institute for the Theory of Computing,
University of California
, Berkeley
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Yichen Huang;
Yichen Huang
University of California
, Berkeley
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Zeph Landau;
Zeph Landau
Simons Institute for the Theory of Computing, University of California
, Berkeley
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Seung Woo Shin
Seung Woo Shin
University of California
, Berkeley
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Online ISSN: 1551-3068
Print ISSN: 1551-305X
© 2015 S. Gharibian, Y. Huang, Z. Landau and S. W. Shin
2015
S. Gharibian, Y. Huang, Z. Landau and S. W. Shin
Licensed re-use rights only
Foundations and Trends in Theoretical Computer Science (2015) 10 (3): 159–282.
Citation
Gharibian S, Huang Y, Landau Z, Shin SW (2015), "Quantum Hamiltonian Complexity". Foundations and Trends in Theoretical Computer Science, Vol. 10 No. 3 pp. 159–282, doi: https://doi.org/10.1561/0400000066
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