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 classical computers. In this paper we demonstrate that the simulation of limits can be a potent diagnostic tool for the resilience of quantum information hardware against chaotic instabilities 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 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 433-qubit processor of the Osprey generation, as well as devices with 1 121 qubits (Condor generation). For realistic system parameters, we find a systematic increase of Lyapunov exponents with system size, suggesting that larger layouts require added efforts in information protection. Published by the American Physical Society 2024
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 classical computers. In this paper we demonstrate that the simulation of limits can be a potent diagnostic tool for the resilience of quantum information hardware against chaotic instabilities 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 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 433-qubit processor of the Osprey generation, as well as devices with 1 121 qubits (Condor generation). For realistic system parameters, we find a systematic increase of Lyapunov exponents with system size, suggesting that larger layouts require added efforts in information protection. Published by the American Physical Society 2024
In the effort to develop useful quantum computers, simulating quantum machines with conventional classical computing resources is a key capability. Such simulations will always face limits, preventing the emulation of quantum computers at substantial scale; however, by pushing the envelope through optimal choices of algorithms and hardware, the value of simulator tools can be maximized. This work reviews state-of-the-art numerical simulation methods, i.e., classical algorithms that emulate quantum computer evolution under specific operations. We focus on the mainstream state-vector and tensor-network paradigms, while briefly mentioning alternative methods. Moreover, we review the diverse applications of simulation across different facets of quantum computer development, including understanding the fundamental differences between quantum and classical computations, exploring algorithmic design for quantum advantage, predicting quantum processor performance at the design stage, and efficiently characterizing fabricated devices for rapid iterations. This review complements recent surveys of current tools and implementations; here, we aim to provide readers with an essential understanding of the theoretical basis of classical simulation methods, a detailed discussion of their advantages and limitations, and an overview of the demands and challenges arising from practical use cases.
In certain regimes, the fidelity of quantum states will decay at a rate set by the classical Lyapunov exponent. This serves both as one of the most important examples of the quantum-classical correspondence principle and as an accurate test for the presence of chaos. While detecting this phenomenon is one of the first useful calculations that noisy quantum computers without error correction can perform [G. Benenti et al., Phys. Rev. E 65, 066205 (2001)], a thorough study of the quantum sawtooth map reveals that observing the Lyapunov regime is just beyond the reach of present-day devices. We prove that there are three bounds on the ability of any device to observe the Lyapunov regime and give the first quantitatively accurate description of these bounds: (1) the Fermi golden rule decay rate must be larger than the Lyapunov rate, (2) the quantum dynamics must be diffusive rather than localized, and (3) the initial decay rate must be slow enough for Lyapunov decay to be observable. This last bound, which has not been recognized previously, places a limit on the maximum amount of noise that can be tolerated. The theory implies that an absolute minimum of 6 qubits is required. Recent experiments on IBM-Q and IonQ imply that some combination of a noise reduction by up to 100 × per gate and large increases in connectivity and gate parallelization are also necessary. Finally, scaling arguments are given that quantify the ability of future devices to observe the Lyapunov regime based on trade-offs between hardware architecture and performance.
From the perspective of many-body physics, the transmon qubit architectures currently developed for quantum computing are systems of coupled nonlinear quantum resonators. A certain amount of intentional frequency detuning ('disorder') is crucially required to protect individual qubit states against the destabilizing effects of nonlinear resonator coupling. Here we investigate the stability of this variant of a many-body localized phase for system parameters relevant to current quantum processors developed by the IBM, Delft, and Google consortia, considering the cases of natural or engineered disorder. Applying three independent diagnostics of localization theory - a Kullback-Leibler analysis of spectral statistics, statistics of many-body wave functions (inverse participation ratios), and a Walsh transform of the many-body spectrum - we find that some of these computing platforms are dangerously close to a phase of uncontrollable chaotic fluctuations.
This paper investigates the intersection of quantum chaos and quantum computing control. It explores the potential influence of chaotic behavior within quantum systems on computational processes and proposes control strategies to mitigate these effects. The core argument centers on the recognition of quantum chaos as a crucial, yet often overlooked, element in the precise control required for reliable quantum computation. Through the application of chaos theory, this work analyzes the manifestation of chaotic dynamics in quantum systems, detailing the implications for qubit stability and gate fidelity. Specific control techniques, including feedback mechanisms and tailored Hamiltonian designs, are examined and discussed, ultimately aiming to harness, rather than suppress, chaotic behavior to potentially enhance certain quantum algorithms. The research contributes to a deeper understanding of the complex relationship between quantum systems and chaos, providing a foundation for the development of more robust and adaptable quantum control protocols. The study utilizes mathematical formalism to rigorously define and analyze the concepts explored, focusing on key equations governing quantum dynamics and chaotic systems.
Although the emergence of a fully-functional quantum computer may still be far away from today, in the near future, it is possible to have medium-size, special-purpose, quantum devices that can perform computational tasks not efficiently simulable with any classical computer. This status is known as quantum supremacy (or quantum advantage), where one of the promising approaches is through the sampling of chaotic quantum circuits. Sampling of ideal chaotic quantum circuits has been argued to require an exponential time for classical devices. A major question is whether quantum supremacy can be maintained under noise without error correction, as the implementation of fault-tolerance would cost lots of extra qubits and quantum gates. Here we show that, for a family of chaotic quantum circuits subject to Pauli errors, there exists an non-exponential classical algorithm capable of simulating the noisy chaotic quantum circuits with bounded errors. This result represents a serious challenge to a previous result in the literature suggesting the failure of classical devices in simulating noisy chaotic circuits with about 48 qubits and depth 25. Moreover, even though our model does not cover all types of experimental errors, from a practical point view, our result describes a well-defined setting where quantum supremacy can be tested against the challenges of classical rivals, in the context of chaotic quantum circuits.
The increasingly complex quantum electronic circuits with a number of coupled quantum degrees of freedom will become intractable to be simulated on classical computers, and requires quantum computers for an efficient simulation. In turn, it will be a central concept in quantum-aided design for next-generation quantum processors. Here, we demonstrate variational quantum eigensolvers to simulate superconducting quantum circuits with varying parameters covering a plasmon-transition regime, which reveals an advanced post-transmon qubit, "plasmonium". We fabricate this new qubit and demonstrate that it exhibits not only high single- and two-qubit gate fidelities (99.85(1)% and 99.58(3)%, respectively), but also a shrinking (by 60%) physical size and larger (by 50%) anharmonicity than the transmon, which can bring a number of advantages for scaling up multi-qubit devices. Our work opens the way to designing advanced quantum processors using existing quantum computing resources.