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Efficient Quantum Algorithms for Simulating Sparse Hamiltonians

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Abstract

We present an efficient quantum algorithm for simulating the evolution of a quantum state for a sparse Hamiltonian H over a given time t in terms of a procedure for computing the matrix entries of H. In particular, when H acts on n qubits, has at most a constant number of nonzero entries in each row/column, and ||H|| is bounded by a constant, we may select any positive integer k such that the simulation requires O((log* n)t 1+1/2k) accesses to matrix entries of H. We also show that the temporal scaling cannot be significantly improved beyond this, because sublinear time scaling is not possible.

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References

  1. Shor, P. W.: Algorithms for quantum computation: Discrete logarithms and factoring. In: Proc. 35th Symp. on Foundations of Computer Science, Los Alamitos, CA:IEEE, 1994, pp. 124–134

  2. Grover L. (1997) Quantum mechanics helps in searching for a needle in a haystack. Phys. Rev. Lett. 79, 325–328

    Article  ADS  Google Scholar 

  3. Kempe J., Kitaev A., Regev O. (2006) The complexity of the local Hamiltonian problem. SIAM J. Computing 35: 1070–1097

    Article  MathSciNet  Google Scholar 

  4. Feynman R.P. (1982) Simulating physics with computers. Int. J. Theoret. Phys. 21, 467–488

    MathSciNet  Google Scholar 

  5. Lloyd S. (1996) Universal quantum simulators. Science 273: 1073–1078

    Article  MathSciNet  ADS  Google Scholar 

  6. Aharonov, D., Ta-Shma, A.: Adiabatic quantum state generation and statistical zero knowledge. In: Proc. 35th Annual ACM Symp. on Theory of Computing, New York:ACM, 2003, pp. 20–29

  7. Childs A., Farhi E., Gutmann S. (2002) An example of the difference between quantum and classical random walks. J. Quant. Inf. Proc. 1, 35–43

    Article  MathSciNet  Google Scholar 

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

    Article  ADS  Google Scholar 

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

    Article  MathSciNet  ADS  Google Scholar 

  10. Ambainis, A.: Quantum walk algorithm for element distinctness. In: Proc. 45th Symp. on Foundations of Computer Science, Los Alamitos, CA: IEEE, 2004, pp. 22–31

  11. Ambainis, A., Kempe, J., Rivosh, A.: Coins make quantum walks faster. In: Proc. 16th ACM-SIAM SODA, Philadelphia, PA:SIAM, 2005, pp. 1099–1108

  12. Suzuki M. (1990) Fractal decomposition of exponential operators with applications to many-body theories and Monte Carlo simulations. Phys. Lett. A 146, 319–323

    Article  MathSciNet  ADS  Google Scholar 

  13. Suzuki M. (1991) General theory of fractal path integrals with applications to many-body theories and statistical physics. J. Math. Phys. 32, 400–407

    Article  MathSciNet  ADS  Google Scholar 

  14. Childs A.M. Quantum information processing in continuous time. Ph.D. Thesis, Massachusetts Institute of Technology, 2004

  15. Cole R., Vishkin U. (1986) Deterministic coin tossing with applications to optimal parallel list ranking. Inform. and Control 70, 32–53

    Article  MathSciNet  Google Scholar 

  16. Linial N. (1992) Locality in distributed graph algorithms. SIAM J. Comput. 21, 193–201

    Article  MathSciNet  Google Scholar 

  17. Childs, A.M., Cleve, R., Deotto, E., Farhi, E., Guttman, S., Spielman, D.A.: Exponential algorithmic speedup by quantum walk. In: Proc. 35th Annual ACM Symp. on Theory of Computing, New York: ACM, 2003, pp. 59–68

  18. Ahokas, G.: Improved algorithms for approximate quantum Fourier transforms and sparse Hamiltonian simulations. M.Sc. Thesis, University of Calgary, 2004

  19. Beals R., Buhrman H., Cleve R., Mosca M., de Wolf R. (2001) Quantum lower bounds by polynomials. J. ACM 48, 778–797

    Article  MathSciNet  Google Scholar 

  20. Farhi E., Goldstone J., Gutmann S., Sipser M. (1998) Limit on the speed of quantum computation in determining parity. Phys. Rev. Lett. 81: 5442–5444

    Article  ADS  Google Scholar 

  21. Nielsen M.A., Chuang I.L., (2000) Quantum Computation and Quantum Information. Cambridge, Cambridge University Press

    MATH  Google Scholar 

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Communicated by M.B. Ruskai

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Berry, D.W., Ahokas, G., Cleve, R. et al. Efficient Quantum Algorithms for Simulating Sparse Hamiltonians. Commun. Math. Phys. 270, 359–371 (2007). https://doi.org/10.1007/s00220-006-0150-x

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  • DOI: https://doi.org/10.1007/s00220-006-0150-x

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