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Given a function<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mi>f<\/mml:mi><mml:mo>:<\/mml:mo><mml:msup><mml:mrow class=\"MJX-TeXAtom-ORD\"><mml:mi mathvariant=\"double-struck\">R<\/mml:mi><\/mml:mrow><mml:mrow class=\"MJX-TeXAtom-ORD\"><mml:mi>n<\/mml:mi><\/mml:mrow><\/mml:msup><mml:mo stretchy=\"false\">\u2192<\/mml:mo><mml:mrow class=\"MJX-TeXAtom-ORD\"><mml:mi mathvariant=\"double-struck\">R<\/mml:mi><\/mml:mrow><\/mml:math>, our quantum algorithm outputs an<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mi>\u03f5<\/mml:mi><\/mml:math>-approximate second-order stationary point using<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mrow class=\"MJX-TeXAtom-ORD\"><mml:mover><mml:mi>O<\/mml:mi><mml:mo stretchy=\"false\">~<\/mml:mo><\/mml:mover><\/mml:mrow><mml:mo stretchy=\"false\">(<\/mml:mo><mml:msup><mml:mi>log<\/mml:mi><mml:mrow class=\"MJX-TeXAtom-ORD\"><mml:mn>2<\/mml:mn><\/mml:mrow><\/mml:msup><mml:mo>\u2061<\/mml:mo><mml:mo stretchy=\"false\">(<\/mml:mo><mml:mi>n<\/mml:mi><mml:mo stretchy=\"false\">)<\/mml:mo><mml:mrow class=\"MJX-TeXAtom-ORD\"><mml:mo>\/<\/mml:mo><\/mml:mrow><mml:msup><mml:mi>\u03f5<\/mml:mi><mml:mrow class=\"MJX-TeXAtom-ORD\"><mml:mn>1.75<\/mml:mn><\/mml:mrow><\/mml:msup><mml:mo stretchy=\"false\">)<\/mml:mo><\/mml:math>queries to the quantum evaluation oracle (i.e., the zeroth-order oracle). Compared to the classical state-of-the-art algorithm by Jin et al. with<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mrow class=\"MJX-TeXAtom-ORD\"><mml:mover><mml:mi>O<\/mml:mi><mml:mo stretchy=\"false\">~<\/mml:mo><\/mml:mover><\/mml:mrow><mml:mo stretchy=\"false\">(<\/mml:mo><mml:msup><mml:mi>log<\/mml:mi><mml:mrow class=\"MJX-TeXAtom-ORD\"><mml:mn>6<\/mml:mn><\/mml:mrow><\/mml:msup><mml:mo>\u2061<\/mml:mo><mml:mo stretchy=\"false\">(<\/mml:mo><mml:mi>n<\/mml:mi><mml:mo stretchy=\"false\">)<\/mml:mo><mml:mrow class=\"MJX-TeXAtom-ORD\"><mml:mo>\/<\/mml:mo><\/mml:mrow><mml:msup><mml:mi>\u03f5<\/mml:mi><mml:mrow class=\"MJX-TeXAtom-ORD\"><mml:mn>1.75<\/mml:mn><\/mml:mrow><\/mml:msup><mml:mo stretchy=\"false\">)<\/mml:mo><\/mml:math>queries to the gradient oracle (i.e., the first-order oracle), our quantum algorithm is polynomially better in terms of<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mi>log<\/mml:mi><mml:mo>\u2061<\/mml:mo><mml:mi>n<\/mml:mi><\/mml:math>and matches its complexity in terms of<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mn>1<\/mml:mn><mml:mrow class=\"MJX-TeXAtom-ORD\"><mml:mo>\/<\/mml:mo><\/mml:mrow><mml:mi>\u03f5<\/mml:mi><\/mml:math>. Technically, our main contribution is the idea of replacing the classical perturbations in gradient descent methods by simulating quantum wave equations, which constitutes the improvement in the quantum query complexity with<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mi>log<\/mml:mi><mml:mo>\u2061<\/mml:mo><mml:mi>n<\/mml:mi><\/mml:math>factors for escaping from saddle points. We also show how to use a quantum gradient computation algorithm due to Jordan to replace the classical gradient queries by quantum evaluation queries with the same complexity. Finally, we also perform numerical experiments that support our theoretical findings.<\/jats:p>","DOI":"10.22331\/q-2021-08-20-529","type":"journal-article","created":{"date-parts":[[2021,8,20]],"date-time":"2021-08-20T11:48:15Z","timestamp":1629460095000},"page":"529","update-policy":"https:\/\/doi.org\/10.22331\/q-crossmark-policy-page","source":"Crossref","is-referenced-by-count":13,"title":["Quantum algorithms for escaping from saddle points"],"prefix":"10.22331","volume":"5","author":[{"given":"Chenyi","family":"Zhang","sequence":"first","affiliation":[{"name":"Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaqi","family":"Leng","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Joint Center for Quantum Information and Computer Science, University of Maryland, College Park, MD, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tongyang","family":"Li","sequence":"additional","affiliation":[{"name":"Center on Frontiers of Computing Studies, Peking University, Beijing, China"},{"name":"Center for Theoretical Physics, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"name":"Department of Computer Science and Joint Center for Quantum Information and Computer Science, University of Maryland, College Park, MD, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"9598","published-online":{"date-parts":[[2021,8,20]]},"reference":[{"key":"0","doi-asserted-by":"publisher","unstructured":"Naman Agarwal, Zeyuan Allen-Zhu, Brian Bullins, Elad Hazan, and Tengyu Ma, Finding approximate local minima faster than gradient descent, Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, pp. 1195\u20131199, 2017, arXiv:1611.01146. https:\/\/doi.org\/10.1145\/3055399.3055464.","DOI":"10.1145\/3055399.3055464"},{"key":"1","unstructured":"Zeyuan Allen-Zhu, Natasha 2: Faster non-convex optimization than SGD, Advances in Neural Information Processing Systems, pp. 2675\u20132686, 2018, arXiv:1708.08694."},{"key":"2","unstructured":"Zeyuan Allen-Zhu and Yuanzhi Li, Neon2: Finding local minima via first-order oracles, Advances in Neural Information Processing Systems, pp. 3716\u20133726, 2018, arXiv:1711.06673."},{"key":"3","doi-asserted-by":"publisher","unstructured":"Joran van Apeldoorn and Andr\u00e1s Gily\u00e9n, Improvements in quantum SDP-solving with applications, Proceedings of the 46th International Colloquium on Automata, Languages, and Programming, Leibniz International Proceedings in Informatics (LIPIcs), vol. 132, pp. 99:1\u201399:15, Schloss Dagstuhl\u2013Leibniz-Zentrum fuer Informatik, 2019, arXiv:1804.05058. https:\/\/doi.org\/10.4230\/LIPIcs.ICALP.2019.99.","DOI":"10.4230\/LIPIcs.ICALP.2019.99"},{"key":"4","doi-asserted-by":"publisher","unstructured":"Joran van Apeldoorn, Andr\u00e1s Gily\u00e9n, Sander Gribling, and Ronald de Wolf, Quantum SDP-solvers: Better upper and lower bounds, 58th Annual Symposium on Foundations of Computer Science, IEEE, 2017, arXiv:1705.01843. https:\/\/doi.org\/10.22331\/q-2020-02-14-230.","DOI":"10.22331\/q-2020-02-14-230"},{"key":"5","doi-asserted-by":"publisher","unstructured":"Joran van Apeldoorn, Andr\u00e1s Gily\u00e9n, Sander Gribling, and Ronald de Wolf, Convex optimization using quantum oracles, Quantum 4 (2020), 220, arXiv:1809.00643. https:\/\/doi.org\/10.22331\/q-2020-01-13-220.","DOI":"10.22331\/q-2020-01-13-220"},{"key":"6","doi-asserted-by":"publisher","unstructured":"Frank Arute et al., Quantum supremacy using a programmable superconducting processor, Nature 574 (2019), no. 7779, 505\u2013510, arXiv:1910.11333. https:\/\/doi.org\/10.1038\/s41586-019-1666-5.","DOI":"10.1038\/s41586-019-1666-5"},{"key":"7","doi-asserted-by":"crossref","unstructured":"Ivo Babu\u0161ka and Manil Suri, The $h$-$p$ version of the finite element method with quasiuniform meshes, ESAIM: Mathematical Modelling and Numerical Analysis-Mod\u00e9lisation Math\u00e9matique et Analyse Num\u00e9rique 21 (1987), no. 2, 199\u2013238.","DOI":"10.1051\/m2an\/1987210201991"},{"key":"8","doi-asserted-by":"publisher","unstructured":"Dominic W. 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