QUANTUM KOLMOGOROV COMPLEXITY AND ITS APPLICATIONS

Kolmogorov complexity is a measure of the information contained in a binary string. We investigate here the notion of quantum Kolmogorov complexity, a measure of the information required to describe a quantum state. We show that for any definition of quantum Kolmogorov complexity measuring the number of classical bits required to describe a pure quantum state, there exists a pure n-qubit state which requires exponentially many bits of description. This is shown by relating the classical communication complexity to the quantum Kolmogorov complexity. Furthermore, we give some examples of how quantum Kolmogorov complexity can be applied to prove results in different fields, such as quantum computation and thermodynamics, and we generalize it to the case of mixed quantum states.

[1]  Andris Ambainis,et al.  Communication complexity in a 3-computer model , 1996, Algorithmica.

[2]  Paul M. B. Vitányi,et al.  Three approaches to the quantitative definition of information in an individual pure quantum state , 1999, Proceedings 15th Annual IEEE Conference on Computational Complexity.

[3]  Zurek,et al.  Algorithmic randomness and physical entropy. , 1989, Physical review. A, General physics.

[4]  R. Jozsa,et al.  On the role of entanglement in quantum-computational speed-up , 2002, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[5]  Caves Information and entropy. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[6]  Péter Gács,et al.  Quantum algorithmic entropy , 2000, Proceedings 16th Annual IEEE Conference on Computational Complexity.

[7]  Ming Li,et al.  An Introduction to Kolmogorov Complexity and Its Applications , 1997, Texts in Computer Science.

[8]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[9]  Jørn Justesen,et al.  Class of constructive asymptotically good algebraic codes , 1972, IEEE Trans. Inf. Theory.

[10]  H. Briegel,et al.  Algorithmic complexity and entanglement of quantum states. , 2005, Physical review letters.

[11]  Gregory J. Chaitin,et al.  On the Length of Programs for Computing Finite Binary Sequences , 1966, JACM.

[12]  A. Kolmogorov Three approaches to the quantitative definition of information , 1968 .

[13]  K. Gödel Über formal unentscheidbare Sätze der Principia Mathematica und verwandter Systeme I , 1931 .

[14]  R. Landauer,et al.  Irreversibility and heat generation in the computing process , 1961, IBM J. Res. Dev..

[15]  V. Akila,et al.  Information , 2001, The Lancet.

[16]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[17]  Carlton M. Caves,et al.  Unpredictability, information, and chaos , 1997 .

[18]  R. Cleve,et al.  Quantum fingerprinting. , 2001, Physical review letters.

[19]  J. Eisert,et al.  Schmidt measure as a tool for quantifying multiparticle entanglement , 2000, quant-ph/0007081.

[20]  de Ronald Wolf,et al.  Quantum Computing and Communication Complexity , 2001 .

[21]  C. Caves Information, entropy, and chaos. , 1994 .

[22]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[23]  Thierry Paul,et al.  Quantum computation and quantum information , 2007, Mathematical Structures in Computer Science.

[24]  W. H. Zurek,et al.  Thermodynamic cost of computation, algorithmic complexity and the information metric , 1989, Nature.

[25]  Charles H. Bennett,et al.  The thermodynamics of computation—a review , 1982 .