A Short Path Quantum Algorithm for Exact Optimization
We give a quantum algorithm to exactly solve certain problems in combinatorial optimization, including weighted MAX-2-SAT as well as problems where the objective function is a weighted sum of products of Ising variables, all terms of the same degree D ; this problem is called weighted MAX-E D -LIN2....
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| Published in | Quantum (Vienna, Austria) Vol. 2; p. 78 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften
26.07.2018
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| Online Access | Get full text |
| ISSN | 2521-327X 2521-327X |
| DOI | 10.22331/q-2018-07-26-78 |
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| Abstract | We give a quantum algorithm to exactly solve certain problems in combinatorial optimization, including weighted MAX-2-SAT as well as problems where the objective function is a weighted sum of products of Ising variables, all terms of the same degree
D
; this problem is called weighted MAX-E
D
-LIN2. We require that the optimal solution be unique for odd
D
and doubly degenerate for even
D
; however, we expect that the algorithm still works without this condition and we show how to reduce to the case without this assumption at the cost of an additional overhead. While the time required is still exponential, the algorithm provably outperforms Grover's algorithm assuming a mild condition on the number of low energy states of the target Hamiltonian. The detailed analysis of the runtime dependence on a tradeoff between the number of such states and algorithm speed: fewer such states allows a greater speedup. This leads to a natural hybrid algorithm that finds either an exact or approximate solution. |
|---|---|
| AbstractList | We give a quantum algorithm to exactly solve certain problems in combinatorial optimization, including weighted MAX-2-SAT as well as problems where the objective function is a weighted sum of products of Ising variables, all terms of the same degree
D
; this problem is called weighted MAX-E
D
-LIN2. We require that the optimal solution be unique for odd
D
and doubly degenerate for even
D
; however, we expect that the algorithm still works without this condition and we show how to reduce to the case without this assumption at the cost of an additional overhead. While the time required is still exponential, the algorithm provably outperforms Grover's algorithm assuming a mild condition on the number of low energy states of the target Hamiltonian. The detailed analysis of the runtime dependence on a tradeoff between the number of such states and algorithm speed: fewer such states allows a greater speedup. This leads to a natural hybrid algorithm that finds either an exact or approximate solution. We give a quantum algorithm to exactly solve certain problems in combinatorial optimization, including weighted MAX-2-SAT as well as problems where the objective function is a weighted sum of products of Ising variables, all terms of the same degree $D$; this problem is called weighted MAX-E$D$-LIN2. We require that the optimal solution be unique for odd $D$ and doubly degenerate for even $D$; however, we expect that the algorithm still works without this condition and we show how to reduce to the case without this assumption at the cost of an additional overhead. While the time required is still exponential, the algorithm provably outperforms Grover's algorithm assuming a mild condition on the number of low energy states of the target Hamiltonian. The detailed analysis of the runtime dependence on a tradeoff between the number of such states and algorithm speed: fewer such states allows a greater speedup. This leads to a natural hybrid algorithm that finds either an exact or approximate solution. |
| ArticleNumber | 78 |
| Author | Hastings, M. B. |
| Author_xml | – sequence: 1 givenname: M. B. surname: Hastings fullname: Hastings, M. B. organization: Station Q, Microsoft Research, Santa Barbara, CA 93106-6105, USA, Quantum Architectures and Computation Group, Microsoft Research, Redmond, WA 98052, USA |
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| CitedBy_id | crossref_primary_10_1103_PhysRevA_110_032434 crossref_primary_10_1038_s42254_023_00603_1 crossref_primary_10_2151_sola_2025_006 crossref_primary_10_1126_sciadv_adm6761 crossref_primary_10_1016_j_biosystems_2023_105037 crossref_primary_10_1103_PRXQuantum_1_020312 crossref_primary_10_22331_q_2021_12_06_597 crossref_primary_10_22331_q_2019_11_11_201 crossref_primary_10_22331_q_2019_05_20_145 crossref_primary_10_22331_q_2023_09_14_1111 |
| Cites_doi | 10.1103/physrevlett.35.1792 10.1103/physrevlett.43.1754 10.1103/physrevlett.101.130504 10.4086/cjtcs.2018.002 10.1103/PhysRevLett.114.090502 10.1137/s0097539796300933 10.1016/j.disopt.2007.08.001 10.1126/science.1057726 10.1090/conm/305 10.1090/gsm/047 10.1103/physrevlett.50.1946 10.2307/2373688 10.1103/PhysRevLett.118.010501 10.1016/j.tcs.2014.01.010 10.1103/physreva.94.022309 10.1103/physrevlett.103.150502 10.1145/2591796.2591854 10.1103/physrevlett.96.197204 10.1073/pnas.1002116107 10.1016/j.tcs.2005.09.023 10.1137/15m1050902 10.1145/1007352.1007428 10.1109/FOCS.2015.54 10.1007/978-3-540-69507-3_22 10.1017/cbo9781139814782.002 10.1145/237814.237866 10.1103/physreve.65.046137 10.1016/0003-4916(78)90222-1 |
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| Title | A Short Path Quantum Algorithm for Exact Optimization |
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