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Quantum Analogues of Markov Chains

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Years and Authors of Summarized Original Work

  • 2004; Szegedy

Problem Definition

Spatial Search and Walk Processes

Spatial search by quantum walk is database search with the additional constraint that one is required to move through the search space that obeys some locality structure. For example, the data items may be stored at the vertices of a two-dimensional grid. The requirement of moves along the edges of the grid captures the cost of accessing different items starting from some fixed position in the database.

One of possible ways of carrying out spatial search is by performing a random walk on the search space or its quantum analog, a quantum walk. The complexity of spatial search by quantum walk is strongly tied to the quantum hitting time [19] of the walk.

Let S, with | S | = n, be a finite set of states. Assume that a subset \(M \subseteq S\) of states are marked. We are given a procedure \(\mathcal{C}\) that, on input xS and an associated data structure d(x), checks...

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Recommended Reading

  1. Aaronson S, Shi Y (2004) Quantum lower bounds for the collision and the element distinctness problems. J ACM 51(4):595–605

    Article  MathSciNet  MATH  Google Scholar 

  2. Aharonov D, Ambainis A, Kempe J, Vazirani U (2001) Quantum walks on graphs. In: Proceedings of the thirty-third annual ACM Symposium on Theory of Computing, STOC ’01, New York. ACM, pp 50–59

    Chapter  Google Scholar 

  3. Ambainis A (2007) Quantum walk algorithm for Element Distinctness. SIAM J Comput 37(1):210–239

    Article  MathSciNet  MATH  Google Scholar 

  4. Ambainis A, Bach E, Nayak A, Vishwanath A, Watrous J (2001) One-dimensional quantum walks. In: Proceedings of the thirty-third annual ACM Symposium on Theory of Computing, STOC ’01, New York. ACM, pp 37–49

    Chapter  Google Scholar 

  5. Ambainis A, Kempe J, Rivosh A (2005) Coins make quantum walks faster. In: Proceedings of the sixteenth annual ACM-SIAM Symposium on Discrete Algorithms, SODA ’05, Philadelphia. Society for Industrial and Applied Mathematics, pp 1099–1108

    Google Scholar 

  6. Belovs A (2012) Learning-graph-based quantum algorithm for k-Distinctness. In: Proceedings of the 53rd annual IEEE Symposium on Foundations of Computer Science. IEEE Computer Society, Los Alamitos, pp 207–216

    Google Scholar 

  7. Belovs A (2012) Span programs for functions with constant-sized 1-certificates: extended abstract. In: Proceedings of the forty-fourth annual ACM Symposium on Theory of Computing, STOC ’12, New York. ACM, pp 77–84

    Google Scholar 

  8. Belovs A, Childs AM, Jeffery S, Kothari R, Magniez F (2013) Time-efficient quantum walks for 3-Distinctness. In: Fomin FV, Freivalds R, Kwiatkowska M, Peleg D (eds) Automata, Languages, and Programming. Volume 7965 of Lecture Notes in Computer Science. Springer, Berlin/Heidelberg, pp 105–122

    Google Scholar 

  9. Brassard G, Høyer P, Mosca M, Tapp A (2002) Quantum amplitude amplification and estimation. In: Quantum Computation and Information (Washington, DC, 2000). Volume 305 of Contemporary Mathematics. American Mathematical Society, Providence, pp 53–74

    Google Scholar 

  10. Buhrman H, Špalek R (2006) Quantum verification of matrix products. In: Proceedings of the seventeenth annual ACM-SIAM Symposium on Discrete Algorithms, SODA ’06, Philadelphia. Society for Industrial and Applied Mathematics, pp 880–889

    Chapter  Google Scholar 

  11. Childs A, Goldstone J (2004) Spatial search by quantum walk. Phys Rev A 70:022314

    Article  MathSciNet  Google Scholar 

  12. Childs AM, Kothari R (2012) Quantum query complexity of minor-closed graph properties. SIAM J Comput 41(6):1426–1450

    Article  MathSciNet  MATH  Google Scholar 

  13. Childs AM, Cleve R, Deotto E, Farhi E, Gutmann S, Spielman DA (2003) Exponential algorithmic speedup by a quantum walk. In: Proceedings of the thirty-fifth annual ACM Symposium on Theory of Computing, STOC ’03, New York. ACM, pp 59–68

    Chapter  Google Scholar 

  14. Cleve R, Ekert A, Macchiavello C, Mosca M (1998) Quantum algorithms revisited. Proc R Soc A Math Phys Eng Sci 454(1969):339–354

    Article  MathSciNet  MATH  Google Scholar 

  15. Farhi E, Gutmann S (1998) Quantum computation and decision trees. Phys Rev A 58:915–928

    Article  MathSciNet  Google Scholar 

  16. Jeffery S, Kothari R, Magniez F (2012) Improving quantum query complexity of Boolean Matrix Multiplication using Graph Collision. In: Czumaj A, Mehlhorn K, Pitts A, Wattenhofer R (eds) Automata, Languages, and Programming. Volume 7391 of Lecture Notes in Computer Science. Springer, Berlin/Heidelberg, pp 522–532

    Google Scholar 

  17. Jeffery S, Kothari R, Magniez F (2013) Nested quantum walks with quantum data structures. In: Proceedings of the twenty-fourth annual ACM-SIAM Symposium on Discrete Algorithms, SODA ’13. SIAM, Philadelphia, pp 1474–1485

    Chapter  Google Scholar 

  18. Jerrum M, Sinclair A (1997) The Markov Chain Monte Carlo method: an approach to approximate counting and integration. In: Hochbaum DS (ed) Approximation algorithms for NP-hard problems. PWS Publishing Co., Boston, pp 482–520

    Google Scholar 

  19. Kempe J (2005) Discrete quantum walks hit exponentially faster. Probab Theory Relat Fields 133(2):215–235

    Article  MathSciNet  MATH  Google Scholar 

  20. Kendon V, Tregenna B (2003) Decoherence can be useful in quantum walks. Phys Rev A 67:042315

    Article  Google Scholar 

  21. Kitaev A (1995) Quantum measurements and the Abelian stabilizer problem. Technical report. quant-ph/9511026, arXiv.org

    Google Scholar 

  22. Kothari R (2014) Efficient algorithms in quantum query complexity. PhD thesis, University of Waterloo, Waterloo

    Google Scholar 

  23. Krovi H, Magniez F, Ozols M, Roland J (2014) Quantum walks can find a marked element on any graph. Technical report. arXiv:1002.2419v2, arXiv.org

    Google Scholar 

  24. Le Gall F (2012) Improved output-sensitive quantum algorithms for boolean matrix multiplication. In: Proceedings of the twenty-third annual ACM-SIAM Symposium on Discrete Algorithms, SODA ’12. SIAM, Philadelphia, pp 1464–1476

    Chapter  Google Scholar 

  25. Le Gall F (2014) Improved quantum algorithm for triangle finding via combinatorial arguments. In: Proceedings of the 55th annual IEEE Symposium on Foundations of Computer Science, Los Alamitos, 18–21 Oct 2014. IEEE Computer Society Press, pp 216–225

    Google Scholar 

  26. Lee T, Magniez F, Santha M (2013) Improved quantum query algorithms for triangle finding and associativity testing. In: Proceedings of the twenty-fourth annual ACM-SIAM Symposium on Discrete Algorithms, SODA ’13. SIAM, Philadelphia, pp 1486–1502

    Chapter  Google Scholar 

  27. Magniez F, Nayak A (2007) Quantum complexity of testing group commutativity. Algorithmica 48(3):221–232

    Article  MathSciNet  MATH  Google Scholar 

  28. Magniez F, Santha M, Szegedy M (2007) Quantum algorithms for the triangle problem. SIAM J Comput 37(2):413–424

    Article  MathSciNet  MATH  Google Scholar 

  29. Magniez F, Nayak A, Roland J, Santha M (2011) Search via quantum walk. SIAM J Comput 40:142–164

    Article  MathSciNet  MATH  Google Scholar 

  30. Magniez F, Nayak A, Richter PC, Santha M (2012) On the hitting times of quantum versus random walks. Algorithmica 63(1):91–116

    Article  MathSciNet  MATH  Google Scholar 

  31. Moore C, Russell A (2002) Quantum walks on the hypercube. In: Rolim JDP, Vadhan S (eds) Randomization and Approximation Techniques in Computer Science. Volume 2483 of Lecture Notes in Computer Science. Springer, Berlin/Heidelberg, pp 164–178

    Google Scholar 

  32. Nayak A, Vishwanath A (2000) Quantum walk on the line. Technical report. quant-ph/0010117, arXiv.org.

    Google Scholar 

  33. Richter P (2007) Quantum speedup of classical mixing processes. Phys Rev A 76:042306

    Article  Google Scholar 

  34. Shenvi N, Kempe J, Birgitta Whaley K (2003) Quantum random-walk search algorithm. Phys Rev A 67:052307

    Article  Google Scholar 

  35. Szegedy M (2004) Quantum speed-up of markov chain based algorithms. In: Proceedings of the 45th annual IEEE Symposium on Foundations of Computer Science. IEEE Computer Society, Los Alamitos, pp 32–41

    Chapter  Google Scholar 

  36. Tulsi A (2008) Faster quantum walk algorithm for the two dimensional spatial search. Phys Rev A 78:012310

    Article  MATH  Google Scholar 

  37. Williams VV, Williams R (2010) Subcubic equivalences between path, matrix and triangle problems. In: Proceedings of the 51st annual IEEE Symposium on Foundations of Computer Science, FOCS ’10, Washington. IEEE Computer Society, pp 645–654

    Chapter  Google Scholar 

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Correspondence to Ashwin Nayak .

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Nayak, A., Richter, P.C., Szegedy, M. (2016). Quantum Analogues of Markov Chains. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2864-4_302

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