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arXiv:2407.04770 · Communications Physics

Dynamic thermalization on noisy quantum hardware

Hugo Perrin, Thibault Scoquart, Andrei I. Pavlov, N. V. Gnezdilov

Published Mar 7, 2025• 1 citation
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Abstract

Abstract Emulating thermal observables on a digital quantum computer is essential for quantum simulation of many-body physics. However, thermalization typically requires a large system size due to incorporating a thermal bath, whilst limited resources of near-term digital quantum processors allow for simulating relatively small systems. We show that thermal observables and fluctuations may be obtained for a small closed system without a thermal bath. Thermal observables occur upon classically averaging quantum mechanical observables over randomized variants of their time evolution that run independently on a digital quantum processor. Using an IBM quantum computer, we experimentally find thermal occupation probabilities with finite positive and negative temperatures defined by the initial state’s energy. Averaging over random evolutions facilitates error mitigation, with the noise contributing to the temperature in the simulated observables. This result fosters probing the dynamical emergence of equilibrium properties of matter at finite temperatures on noisy intermediate-scale quantum hardware.

DOI
10.1038/s42005-025-02011-6

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Abstract Emulating thermal observables on a digital quantum computer is essential for quantum simulation of many-body physics. However, thermalization typically requires a large system size due to incorporating a thermal bath, whilst limited resources of near-term digital quantum processors allow for simulating relatively small systems. We show that thermal observables and fluctuations may be obtained for a small closed system without a thermal bath. Thermal observables occur upon classically averaging quantum mechanical observables over randomized variants of their time evolution that run independently on a digital quantum processor. Using an IBM quantum computer, we experimentally find thermal occupation probabilities with finite positive and negative temperatures defined by the initial state’s energy. Averaging over random evolutions facilitates error mitigation, with the noise contributing to the temperature in the simulated observables. This result fosters probing the dynamical emergence of equilibrium properties of matter at finite temperatures on noisy intermediate-scale quantum hardware.
Quantum simulation is one of the most promising scientific applications of quantum computers.Due to decoherence and noise in current devices, it is however challenging to perform digital quantum simulation in a regime that is intractable with classical computers.In this work, we propose an experimental protocol for probing dynamics and equilibrium properties on near-term digital quantum computers.As a key ingredient of our work, we show that it is possible to study thermalization even with a relatively coarse Trotter decomposition of the Hamiltonian evolution of interest.Even though the step size is too large to permit a rigorous bound on the Trotter error, we observe that the system prethermalizes in accordance with previous results for Floquet systems.The dynamics closely resemble the thermalization of the model underlying the Trotterization up to long times.We make our approach resilient to noise by developing an error mitigation scheme based on measurement and rescaling of survival probabilities, which is applicable to time-evolution problems in general.We demonstrate the effectiveness of the entire protocol by applying it to the two-dimensional XY model and we numerically verify its performance with realistic noise parameters for superconducting quantum devices.Our proposal thus provides a route to achieving quantum advantage for relevant problems in condensed-matter physics.
Nature is governed by precise physical laws, which can inspire the discovery of new computer-run simulation algorithms. Thermal states are the most ubiquitous for they are the equilibrium states of matter. Simulating thermal states of quantum matter has applications ranging from quantum machine learning to better understanding of high-temperature superconductivity and quantum chemistry. The computational complexity of this task is hopelessly hard for classical computers. The existing quantum algorithms come with caveats: most either require quantum phase estimation rendering them impractical for current noisy hardware, or are variational which face obstacles such as initialization, barren plateaus, and a general lack of provable guarantee. We provide two quantum algorithms with provable guarantees to prepare thermal states on (near-term) quantum computers that avoid these drawbacks. The first algorithm is inspired by the natural thermalization process where the ancilla qubits act as the infinite thermal bath. This algorithm can potentially run in polynomial time to sample thermal distributions of ergodic systems -- the vast class of physical systems that equilibrate in isolation with respect to local observables. The second algorithm works for any system and in general runs in exponential time. However, it requires significantly smaller quantum resources than previous such algorithms. In addition, we provide an error mitigation technique for both algorithms to fight back decoherence, which enables us to run our algorithms on the near-term quantum devices. To illustration, we simulate the thermal state of the hardcore Bose-Hubbard model on the latest generation of available quantum computers.
We investigate how to simulate a quantum many body system using near term device known as noisy intermediate scale quantum (NISQ) hardware. We explore the two different types of hardware, analog and digital device, and discuss their potential for quantum many body simulation. For instance, one of the applications is to use the analog device to simulate the slow dynamics under a strong staggered field. However, noise is a major challenge for quantum hardware. Hence, we discuss the quantum error mitigation methods which are suitable for NISQ hardware. We apply the most commonly-used quantum error mitigation techniques to our many body simulation. We simulate quantum body scar dynamics using zero noise extrapolation techniques, Pauli twirling, and dynamical decoupling. We also calculate the corresponding correlation function using direct measurement without resorting to ancilla qubits. Furthermore, we use the same error mitigation techniques to explore dynamics of energy correlators. As additional error mitigation technique, we divide the noisy correlation results by their sum, which is ideally constant due to energy conservation. By doing so, we significantly improve our result. Finally, we consider another NISQ friendly quantum algorithm for imaginary time evolution. With enough samples from minimally entangled typical thermal state algorithms, we can obtain the thermal expectation value of observable and explore their thermodynamics. In chapter 2, we provide the background knowledge for the following 4 chapters. We introduce the rydberg atom system as the analog system and their special parameter regime for interesting physics. Moreover, we introduce the digital quantum hardware and trotterization that enable one to simulate many body dynamics on the quantum hardware. We also introduce the quantum error mitigation techniques to reduce the the impact of noise from the results. Finally, we introduce the variation quantum dynamics method for the dynamics simulation. In chapter 3, we explore the Rydberg blockade regime with a strong staggered field. With the strong staggered field, any computational basis states are thermalized. Here, we investigate the slow dynamics using a Schrieffer-Wolff (SW) transformation, which is similar to perturbation theory in calculating the different-order effective Hamiltonian in terms of energy scale. As numerical result shown, the naive Schrieffer-Wolff transformation is not enough to explain the some dynamics' relaxation time. Hence, here, we also consider another conservative quantity to perform the SW transformation. The corresponding analytical result agrees with the numerical result. In chapter 4, we simulate quantum many body scarred dynamics in IBM quantum superconducting hardware. We also use custom pulse gates, quantum error mitigation techniques, and quantum error suppression methods to help us handle the noise. The error mitigated result outperforms the raw result. With the all techniques, we also explore non-trivial correlation function which also manifest the long lived oscillation in the rydberg blockade regime. In chapter 5, we use the same quantum error mitigation techniques, which we used in ch. 5, to study the energy transport properties of the mixed Ising model at infinite temperature. Here, instead of using some random state to evaluate the necessary two point energy density correlations, we use Y basis product state sampling to evaluate them. Surprisingly, few samples are enough to estimate the correlation. In addition to the quantum error mitigation techniques, we also use the fact that sum of all correlation functions is constant to renormalize the noisy results. With this trick, we are able to extract an effective dynamical exponent, which enables us to classify the transport properties. In chapter 6, we combine a variational quantum algorithm and the minimally entangled typical thermal states approach to investigate the thermodynamics of 1+1-dimensional Z2 lattice gauge theory. In particular, with a confining field, the 1+1-dimensional Z2 lattice gauge theory cannot be solved exactly. We estimate the corresponding thermal particle number density and energy density to distinguish the confined and deconfined regime. Chapter 7 provides a short review of the main results described in the thesis and a discussion of future research directions that they motivate. We mainly give insight into the recent experimental breakthrough in quantum error correction. We also clarify that quantum error mitigation methods do not become totally useless when a fault-tolerant quantum computer is realized. Finally, we also comment on variational quantum algorithms and their potential applications.
Understanding how isolated quantum many-body systems thermalize remains a central question in modern physics. We study the onset of ergodicity in a two-dimensional disordered Heisenberg Floquet model using digital quantum simulation on IBM's Nighthawk superconducting processor, reaching system sizes of up to 10×1010\times1010×10 qubits. We probe ergodicity across different length scales by coarse-graining the system into spatial patches of varying sizes and introducing a measure based on the collision entropy of each patch, enabling a detailed study of when ergodic behavior emerges across scales. The high sampling rate of superconducting quantum processing units, together with an optimal sample estimator, allow us to access patches of sizes up to 3×33\times33×3. We observe that as the Heisenberg coupling JJJ increases, the noiseless system undergoes a smooth crossover from subergodic to ergodic behavior, with smaller patches approaching their random-matrix-theory values first, thereby revealing a hierarchy across scales. In the region of parameter space where classical tensor-network simulations are reliable, small patches or small values of JJJ, we find excellent agreement with the error-mitigated quantum simulation. Beyond this regime, volume-law entanglement and contraction complexity growth causes the cost of classical methods to rise sharply. Our results open new directions for the use of quantum computers in the study of quantum thermalization.
The simulation of non-equilibrium quantum many-body systems on noisy intermediate-scale quantum (NISQ) processors represents a central challenge and opportunity in modern condensed matter physics. Periodically driven (Floquet) systems can host exotic phases of matter with no equilibrium counterpart, most notably discrete time crystals (DTCs) characterized by spontaneous breaking of discrete time-translation symmetry and robust subharmonic responses. However, the realization of DTCs faces fundamental obstacles: driven many-body systems generically absorb energy and thermalize to an infinite-temperature state, destroying time-crystalline order. Two primary mechanisms have been identified to stabilize DTCs—many-body localization (MBL) through strong disorder, and Floquet prethermalization wherein high-frequency driving suppresses heating over exponentially long timescales. This work investigates the digital quantum simulation of prethermal DTCs on current superconducting quantum processors, with a focus on understanding and mitigating the impact of hardware noise. Recent experiments on 133-qubit heavy-hexagonal devices have demonstrated the realization of clean two-dimensional DTCs and incommensurately modulated DTCs (IM-DTCs) using kicked Ising models, observing period-doubling oscillations persisting for up to 100 Floquet cycles . Crucially, these simulations reveal that quantum noise, often perceived as detrimental, can in certain regimes stabilize novel prethermal DTC phases—a phenomenon identified as noise-induced DTCs supported by symmetry charge pumping or random gate fluctuations . The heavy-hexagonal lattice geometry, compared to square lattices, exhibits significantly slower quantum scrambling, thereby extending the prethermal plateau and enhancing DTC stability. We address two key challenges limiting the scalability of DTC simulations: limited qubit connectivity and environmental noise. By leveraging the universality of native gate sets, we demonstrate how to implement effective couplings among physically disconnected qubits at the cost of increased circuit depth, enabling the study of interaction-range effects on DTC stabilization—a phenomenon previously unobserved experimentally . Furthermore, we benchmark the performance of error mitigation protocols based on depolarising noise models, achieving excellent agreement between error-mitigated hardware data and tensor-network simulations in regimes where classical computations remain tractable . Our results highlight the complementary roles of quantum hardware and classical simulation: quantum processors provide access to regimes where entanglement growth outpaces tensor-network methods, while careful validation against classical benchmarks ensures the reliability of quantum outcomes. This study establishes a concrete pathway for using NISQ devices as experimental platforms for synthesizing and probing novel non-equilibrium quantum phases, advancing both our fundamental understanding of Floquet many-body dynamics and the practical capabilities of quantum simulation. The identification of noise as an active ingredient in phase stabilization suggests new directions for quantum engineering of spatiotemporal orders on near-term hardware.
Chaotic quantum many-body dynamics typically lead to relaxation of local observables. In this process, known as quantum thermalization, a subregion reaches a thermal state due to quantum correlations with the remainder of the system, which acts as an intrinsic bath. While the bath is generally assumed to be unobserved, modern quantum science experiments have the ability to track both subsystem and bath at a microscopic level. Here, by utilizing this ability, we discover that measurement results associated with small subsystems exhibit universal random statistics following chaotic quantum many-body dynamics, a phenomenon beyond the standard paradigm of quantum thermalization. We explain these observations with an ensemble of pure states, defined via correlations with the bath, that dynamically acquires a close to random distribution. Such random ensembles play an important role in quantum information science, associated with quantum supremacy tests and device verification, but typically require highly-engineered, time-dependent control for their preparation. In contrast, our approach uncovers random ensembles naturally emerging from evolution with a time-independent Hamiltonian. As an application of this emergent randomness, we develop a benchmarking protocol which estimates the many-body fidelity during generic chaotic evolution and demonstrate it using our Rydberg quantum simulator. Our work has wide ranging implications for the understanding of quantum many-body chaos and thermalization in terms of emergent randomness and at the same time paves the way for applications of this concept in a much wider context.