Classical Chaos in Quantum Computers

The development of quantum computing hardware is facing the challenge that current-day quantum processors, comprising 50-100 qubits, already operate outside the range of quantum simulation on silicon computers. In this paper we demonstrate that the simulation of \textit{classical} limits can be a potent diagnostic tool potentially mitigating this problem. As a testbed for our approach we consider the transmon qubit processor, a computing platform in which the coupling of large numbers of nonlinear quantum oscillators may trigger destabilizing chaotic resonances. We find that classical and quantum simulations lead to similar stability metrics (classical Lyapunov exponents vs. quantum wave function participation ratios) in systems with $\mathcal{O}(10)$ transmons. However, the big advantage of classical simulation is that it can be pushed to large systems comprising up to thousands of qubits. We exhibit the utility of this classical toolbox by simulating all current IBM transmon chips, including the recently announced 433-qubit processor of the Osprey generation, as well as future devices with 1,121 qubits (Condor generation). For realistic system parameters, we find a systematic increase of Lyapunov exponents in system size, suggesting that larger layouts require added efforts in information protection.

[1]  A. Blais,et al.  Reminiscence of Classical Chaos in Driven Transmons , 2022, PRX Quantum.

[2]  Michael J. Hoffmann,et al.  Suppressing quantum errors by scaling a surface code logical qubit , 2022, Nature.

[3]  C. K. Andersen,et al.  Realizing repeated quantum error correction in a distance-three surface code , 2021, Nature.

[4]  C. Deng,et al.  Fluxonium: An Alternative Qubit Platform for High-Fidelity Operations. , 2021, Physical review letters.

[5]  H. Neven,et al.  Realizing topologically ordered states on a quantum processor , 2021, Science.

[6]  D. DiVincenzo,et al.  Transmon platform for quantum computing challenged by chaotic fluctuations , 2020, Nature Communications.

[7]  A. Polkovnikov,et al.  Dynamical obstruction to localization in a disordered spin chain , 2020, Physical Review E.

[8]  Markus Brink,et al.  Laser-annealing Josephson junctions for yielding scaled-up superconducting quantum processors , 2020, npj Quantum Information.

[9]  Fei Yan,et al.  High-Fidelity, High-Scalability Two-Qubit Gate Scheme for Superconducting Qubits. , 2020, Physical review letters.

[10]  John C. Platt,et al.  Quantum supremacy using a programmable superconducting processor , 2019, Nature.

[11]  Andrew W. Cross,et al.  Topological and Subsystem Codes on Low-Degree Graphs with Flag Qubits , 2019, Physical Review X.

[12]  A. Michailidis,et al.  Probing the many-body localization phase transition with superconducting circuits , 2019, Physical Review B.

[13]  J. Healey The Preparation: , 2019, Walter Baade.

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

[15]  Fei Yan,et al.  A quantum engineer's guide to superconducting qubits , 2019, Applied Physics Reviews.

[16]  Alexander N. Korotkov,et al.  Operation and intrinsic error budget of a two-qubit cross-resonance gate , 2019, Physical Review A.

[17]  Immanuel Bloch,et al.  Colloquium : Many-body localization, thermalization, and entanglement , 2018, Reviews of Modern Physics.

[18]  Jay M. Gambetta,et al.  Effective Hamiltonian models of the cross-resonance gate , 2018, Physical Review A.

[19]  Fei Yan,et al.  Tunable Coupling Scheme for Implementing High-Fidelity Two-Qubit Gates , 2018, Physical Review Applied.

[20]  George Datseris,et al.  DynamicalSystems.jl: A Julia software library for chaos and nonlinear dynamics , 2018, J. Open Source Softw..

[21]  F. Alet,et al.  Shift-invert diagonalization of large many-body localizing spin chains , 2018, SciPost Physics.

[22]  Herbert S. Parmet,et al.  With High Fidelity , 2018 .

[23]  John Preskill,et al.  Quantum Computing in the NISQ era and beyond , 2018, Quantum.

[24]  Qing Nie,et al.  DifferentialEquations.jl – A Performant and Feature-Rich Ecosystem for Solving Differential Equations in Julia , 2017, Journal of Open Research Software.

[25]  J. Gambetta,et al.  Variability metrics in Josephson Junction fabrication for Quantum Computing circuits , 2017 .

[26]  L. DiCarlo,et al.  Scalable Quantum Circuit and Control for a Superconducting Surface Code , 2016, 1612.08208.

[27]  J. Gambetta,et al.  Procedure for systematically tuning up cross-talk in the cross-resonance gate , 2016, 1603.04821.

[28]  Jay M. Gambetta,et al.  Building logical qubits in a superconducting quantum computing system , 2015, 1510.04375.

[29]  J. Clarke,et al.  The flux qubit revisited to enhance coherence and reproducibility , 2015, Nature Communications.

[30]  R. Barends,et al.  Superconducting quantum circuits at the surface code threshold for fault tolerance , 2014, Nature.

[31]  A N Cleland,et al.  Qubit Architecture with High Coherence and Fast Tunable Coupling. , 2014, Physical review letters.

[32]  F. Alet,et al.  Universal behavior beyond multifractality in quantum many-body systems. , 2013, Physical review letters.

[33]  D. Huse,et al.  Phenomenology of fully many-body-localized systems , 2013, 1408.4297.

[34]  Charalampos Tsitouras,et al.  Runge-Kutta pairs of order 5(4) satisfying only the first column simplifying assumption , 2011, Comput. Math. Appl..

[35]  L. Bishop Circuit quantum electrodynamics , 2010, 1007.3520.

[36]  Chad Rigetti,et al.  Fully microwave-tunable universal gates in superconducting qubits with linear couplings and fixed transition frequencies , 2010 .

[37]  J. Pöschel,et al.  A lecture on the classical KAM theorem , 2009, 0908.2234.

[38]  Jens Koch,et al.  Fluxonium: Single Cooper-Pair Circuit Free of Charge Offsets , 2009, Science.

[39]  A. Mirlin,et al.  Anderson Transitions , 2007, 0707.4378.

[40]  S. Girvin,et al.  Charge-insensitive qubit design derived from the Cooper pair box , 2007, cond-mat/0703002.

[41]  G. S. Paraoanu,et al.  Microwave-induced coupling of superconducting qubits , 2006, 0801.4541.

[42]  M. Tabor Chaos and Integrability in Nonlinear Dynamics: An Introduction , 1989 .

[43]  G. Benettin,et al.  Lyapunov Characteristic Exponents for smooth dynamical systems and for hamiltonian systems; a method for computing all of them. Part 1: Theory , 1980 .

[44]  J. Verner Explicit Runge–Kutta Methods with Estimates of the Local Truncation Error , 1978 .

[45]  G. Benettin,et al.  Kolmogorov Entropy and Numerical Experiments , 1976 .