Tree tensor network approach to simulating Shor's algorithm

Simulating quantum systems constructively furthers our understanding of qualitative and quantitative features which may be analytically intractable. In this letter, we directly simulate and explore the entanglement structure present in a paradigmatic example of quantum information: Shor's wavefunction. The methodology employed is a dynamical tensor network which is initially constructed as a tree tensor network, inspired by the modular exponentiation quantum circuit, and later efficiently mapped to a matrix product state. Utilizing the Schmidt number as a local entanglement metric, our construction explicitly captures the wavefunction's non-local entanglement structure and an entanglement scaling relation is discovered. Specifically, we see that entanglement across a bipartition grows exponentially in the number of qubits before saturating at a critical scale which is proportional to the modular periodicity.

[1]  D. Aharonov,et al.  The quantum FFT can be classically simulated , 2006, quant-ph/0611156.

[2]  G. Vidal,et al.  Classical simulation of quantum many-body systems with a tree tensor network , 2005, quant-ph/0511070.

[3]  N. Yoran,et al.  Efficient classical simulation of the approximate quantum Fourier transform , 2006, quant-ph/0611241.

[4]  M. Hastings,et al.  An area law for one-dimensional quantum systems , 2007, 0705.2024.

[5]  J. Latorre,et al.  Universality of entanglement and quantum-computation complexity , 2003, quant-ph/0311017.

[6]  U. Schollwoeck The density-matrix renormalization group in the age of matrix product states , 2010, 1008.3477.

[7]  White,et al.  Density matrix formulation for quantum renormalization groups. , 1992, Physical review letters.

[8]  A. H. Werner,et al.  Positive Tensor Network Approach for Simulating Open Quantum Many-Body Systems. , 2014, Physical review letters.

[9]  T. H. Johnson,et al.  Solving search problems by strongly simulating quantum circuits , 2012, Scientific Reports.

[10]  R. V. Meter,et al.  Fast quantum modular exponentiation , 2004, quant-ph/0408006.

[11]  Igor L. Markov,et al.  Simulating Quantum Computation by Contracting Tensor Networks , 2008, SIAM J. Comput..

[12]  Alex W. Chin,et al.  Simulating open quantum dynamics with time-dependent variational matrix product states: Towards microscopic correlation of environment dynamics and reduced system evolution , 2015, 1507.02202.

[13]  F. Verstraete,et al.  Matrix product states for critical spin chains: Finite-size versus finite-entanglement scaling , 2012, Physical Review B.

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

[15]  Lloyd Christopher L. Hollenberg,et al.  Simulations of Shor’s algorithm using matrix product states , 2015, Quantum Inf. Process..

[16]  Dimitris Gizopoulos,et al.  Fast Quantum Modular Exponentiation Architecture for Shor's Factorization Algorithm , 2012, 1207.0511.

[17]  Roman Orus,et al.  A Practical Introduction to Tensor Networks: Matrix Product States and Projected Entangled Pair States , 2013, 1306.2164.