Generalized Deutsch-Jozsa problem and the optimal quantum algorithm

The Deutsch-Jozsa algorithm is one of the first examples of a quantum algorithm that is exponentially faster than any possible deterministic classical algorithm. It was proposed by Deutsch and Jozsa in 1992 with improvements by Cleve, Ekert, Macchiavello, and Mosca in 1998. The Deutsch-Jozsa problem is a promise problem and we can equivalently describe it as a partial function ${\text{DJ}}_{n}^{0}:{{0,1}}^{n}\ensuremath{\rightarrow}{0,1}$ defined as ${\text{DJ}}_{n}^{0}(x)=1$ for $|x|=n/2, {\text{DJ}}_{n}^{0}(x)=0$ for $|x|=0,n$, and it is undefined for the rest of the cases, where $n$ is even, and $|x|$ is the Hamming weight of $x$. The optimal quantum algorithm needs only one query to compute ${\text{DJ}}_{n}^{0}$ but the classical deterministic algorithm requires ${2}^{n\ensuremath{-}1}+1$ queries to compute it in the worse case. In this article, we generalize the Deutsch-Jozsa problem as ${\text{DJ}}_{n}^{k}(x)=1$ for $|x|=n/2, {\text{DJ}}_{n}^{k}(x)=0$ for $|x|$ in the set ${0,1,...,k,n\ensuremath{-}k,n\ensuremath{-}k+1,...,n}$, and it is undefined for the rest of the cases, where $0\ensuremath{\le}kln/2$. In particular, we give and prove an optimal exact quantum query algorithm with complexity $k+1$ for computing the generalized Deutsch-Jozsa problem ${\text{DJ}}_{n}^{k}$. It is clear that the case of $k=0$ is in accordance with the Deutsch-Jozsa problem. Also, we give a method for finding the approximate and exact degrees of symmetric partial Boolean functions.

[1]  R. Cleve,et al.  Quantum algorithms revisited , 1997, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[2]  Debajyoti Bera A different Deutsch–Jozsa , 2015, Quantum Inf. Process..

[3]  Andrew Forbes,et al.  Quantum computation with classical light: Implementation of the Deutsch–Jozsa algorithm , 2016 .

[4]  K. Kim,et al.  Deutsch-Jozsa algorithm as a test of quantum computation , 1998, quant-ph/9807012.

[5]  M. Sipser,et al.  Limit on the Speed of Quantum Computation in Determining Parity , 1998, quant-ph/9802045.

[6]  D. Deutsch,et al.  Rapid solution of problems by quantum computation , 1992, Proceedings of the Royal Society of London. Series A: Mathematical and Physical Sciences.

[7]  Yacov Yacobi,et al.  The Complexity of Promise Problems with Applications to Public-Key Cryptography , 1984, Inf. Control..

[8]  Andris Ambainis Superlinear Advantage for Exact Quantum Algorithms , 2016, SIAM J. Comput..

[9]  Ronald de Wolf,et al.  Quantum lower bounds by polynomials , 2001, JACM.

[10]  Yuichi Yoshida,et al.  Partially Symmetric Functions Are Efficiently Isomorphism Testable , 2015, SIAM J. Comput..

[11]  Andrew M. Childs,et al.  Quantum algorithms for algebraic problems , 2008, 0812.0380.

[12]  Thomas P. Hayes,et al.  The Quantum Black-Box Complexity of Majority , 2002, Algorithmica.

[13]  Shenggen Zheng,et al.  Potential of Quantum Finite Automata with Exact Acceptance , 2014, Int. J. Found. Comput. Sci..

[14]  H. Buhrman,et al.  Complexity measures and decision tree complexity: a survey , 2002, Theor. Comput. Sci..

[15]  Andris Ambainis,et al.  Superiority of exact quantum automata for promise problems , 2011, Inf. Process. Lett..

[16]  Ashley Montanaro,et al.  On Exact Quantum Query Complexity , 2011, Algorithmica.

[17]  Andris Ambainis,et al.  A Note on Quantum Black-Box Complexity of Almost all Boolean Functions , 1998, Inf. Process. Lett..

[18]  Shenggen Zheng,et al.  Generalizations of the distributed Deutsch–Jozsa promise problem , 2014, Mathematical Structures in Computer Science.

[19]  Narendra Karmarkar,et al.  A new polynomial-time algorithm for linear programming , 1984, Comb..

[20]  Anne Canteaut,et al.  Symmetric Boolean functions , 2005, IEEE Transactions on Information Theory.