Improved Digital Quantum Simulation by Non-Unitary Channels

Simulating quantum systems is one of the most promising avenues to harness the computational power of quantum computers. However, hardware errors in noisy near-term devices remain a major obstacle for applications. Ideas based on the randomization of Suzuki-Trotter product formulas have been shown to be a powerful approach to reducing the errors of quantum simulation and lowering the gate count. In this paper, we study the performance of non-unitary simulation channels and consider the error structure of channels constructed from a weighted average of unitary circuits. We show that averaging over just a few simulation circuits can significantly reduce the Trotterization error for both single-step short-time and multi-step long-time simulations. We focus our analysis on two approaches for constructing circuit ensembles for averaging: (i) permuting the order of the terms in the Hamiltonian and (ii) applying a set of global symmetry transformations. We compare our analytical error bounds to empirical performance and show that empirical error reduction surpasses our analytical estimates in most cases. Finally, we test our method on an IonQ trapped-ion quantum computer accessed via the Amazon Braket cloud platform, and benchmark the performance of the averaging approach.

[1]  S. Bravyi,et al.  Trotter error bounds and dynamic multi-product formulas for Hamiltonian simulation , 2023, ArXiv.

[2]  Ewout van den Berg,et al.  Evidence for the utility of quantum computing before fault tolerance , 2023, Nature.

[3]  A. Aspuru‐Guzik,et al.  qSWIFT: High-order randomized compiler for Hamiltonian simulation , 2023, 2302.14811.

[4]  Minh C. Tran,et al.  On the complexity of implementing Trotter steps , 2022, PRX Quantum.

[5]  D. Berry,et al.  Doubling the order of approximation via the randomized product formula , 2022, 2210.11281.

[6]  D. Deng,et al.  Digital quantum simulation of Floquet symmetry-protected topological phases , 2022, Nature.

[7]  A. Pal,et al.  Quantum scars and bulk coherence in a symmetry-protected topological phase , 2021, Physical Review B.

[8]  Minh C. Tran,et al.  Theory of Trotter Error with Commutator Scaling , 2021 .

[9]  Paul K. Faehrmann,et al.  Randomizing multi-product formulas for Hamiltonian simulation , 2021, Quantum.

[10]  Joel A. Tropp,et al.  Concentration for Random Product Formulas , 2020, PRX Quantum.

[11]  Minh C. Tran,et al.  Faster Digital Quantum Simulation by Symmetry Protection , 2020, PRX Quantum.

[12]  R. Somma,et al.  Hamiltonian simulation in the low-energy subspace , 2020, 2006.02660.

[13]  Tobias J. Osborne,et al.  No Free Lunch for Quantum Machine Learning , 2020, 2003.14103.

[14]  C. Monroe,et al.  Programmable quantum simulations of spin systems with trapped ions , 2019, Reviews of Modern Physics.

[15]  E. Campbell,et al.  Compilation by stochastic Hamiltonian sparsification , 2019, Quantum.

[16]  Nathan Wiebe,et al.  Well-conditioned multiproduct Hamiltonian simulation , 2019, 1907.11679.

[17]  Morten Kjaergaard,et al.  Superconducting Qubits: Current State of Play , 2019, Annual Review of Condensed Matter Physics.

[18]  J. D. Wong-Campos,et al.  Benchmarking an 11-qubit quantum computer , 2019, Nature Communications.

[19]  Yuan Su,et al.  Nearly optimal lattice simulation by product formulas , 2019, Physical review letters.

[20]  E. Campbell Random Compiler for Fast Hamiltonian Simulation. , 2018, Physical review letters.

[21]  Yuan Su,et al.  Faster quantum simulation by randomization , 2018, Quantum.

[22]  Dmitri Maslov,et al.  Toward the first quantum simulation with quantum speedup , 2017, Proceedings of the National Academy of Sciences.

[23]  Matthew B. Hastings,et al.  Turning gate synthesis errors into incoherent errors , 2016, Quantum Inf. Comput..

[24]  I. Chuang,et al.  Hamiltonian Simulation by Qubitization , 2016, Quantum.

[25]  I. Chuang,et al.  Optimal Hamiltonian Simulation by Quantum Signal Processing. , 2016, Physical review letters.

[26]  S. Wüster,et al.  Quantum simulation of energy transport with embedded Rydberg aggregates. , 2015, Physical review letters.

[27]  E. Bogomolny,et al.  Quantum Ising model in transverse and longitudinal fields: chaotic wave functions , 2015, 1503.04508.

[28]  Joel A. Tropp,et al.  An Introduction to Matrix Concentration Inequalities , 2015, Found. Trends Mach. Learn..

[29]  Andrew M. Childs,et al.  Simulating Hamiltonian dynamics with a truncated Taylor series. , 2014, Physical review letters.

[30]  Lin Zhang,et al.  Matrix integrals over unitary groups: An application of Schur-Weyl duality , 2014, 1408.3782.

[31]  Yasaman Bahri,et al.  Localization and topology protected quantum coherence at the edge of hot matter , 2013, Nature Communications.

[32]  J. Dalibard,et al.  Quantum simulations with ultracold quantum gases , 2012, Nature Physics.

[33]  I. Lesanovsky Liquid ground state, gap, and excited states of a strongly correlated spin chain. , 2011, Physical review letters.

[34]  R. Blatt,et al.  Quantum simulations with trapped ions , 2011, Nature Physics.

[35]  Hans Peter Büchler,et al.  Digital quantum simulation with Rydberg atoms , 2011, Quantum Inf. Process..

[36]  J. Tropp FREEDMAN'S INEQUALITY FOR MATRIX MARTINGALES , 2011, 1101.3039.

[37]  R. Oliveira Concentration of the adjacency matrix and of the Laplacian in random graphs with independent edges , 2009, 0911.0600.

[38]  David Gross,et al.  Recovering Low-Rank Matrices From Few Coefficients in Any Basis , 2009, IEEE Transactions on Information Theory.

[39]  P. Zoller,et al.  A Rydberg quantum simulator , 2009, 0907.1657.

[40]  G. Vidal,et al.  Infinite time-evolving block decimation algorithm beyond unitary evolution , 2008 .

[41]  F. Verstraete,et al.  Classical simulation of infinite-size quantum lattice systems in two spatial dimensions. , 2007, Physical review letters.

[42]  Frank Verstraete,et al.  Matrix product state representations , 2006, Quantum Inf. Comput..

[43]  G. Vidal Classical simulation of infinite-size quantum lattice systems in one spatial dimension. , 2006, Physical review letters.

[44]  R. Cleve,et al.  Efficient Quantum Algorithms for Simulating Sparse Hamiltonians , 2005, quant-ph/0508139.

[45]  M. Nielsen A simple formula for the average gate fidelity of a quantum dynamical operation [rapid communication] , 2002, quant-ph/0205035.

[46]  I. Pinelis OPTIMUM BOUNDS FOR THE DISTRIBUTIONS OF MARTINGALES IN BANACH SPACES , 1994, 1208.2200.

[47]  M. Suzuki,et al.  General theory of fractal path integrals with applications to many‐body theories and statistical physics , 1991 .

[48]  de Hans Raedt,et al.  PRODUCT FORMULA METHODS FOR TIME-DEPENDENT SCHRODINGER PROBLEMS , 1990 .

[49]  M. Suzuki,et al.  Fractal decomposition of exponential operators with applications to many-body theories and Monte Carlo simulations , 1990 .

[50]  M. Suzuki,et al.  Decomposition formulas of exponential operators and Lie exponentials with some applications to quantum mechanics and statistical physics , 1985 .

[51]  Chi-Fang Chen,et al.  Concentration for Trotter error , 2021 .

[52]  Andrew M. Childs,et al.  Quantum information processing in continuous time , 2004 .