Quantum Charging Advantage in Superconducting Solid-State Batteries

TL;DR

This work experimentally demonstrates scalable quantum charging advantage (QCA) in a solid-state superconducting battery by implementing a nearest-neighbor double-excitation Hamiltonian to charge 2–12 cells and compare against a classical charging protocol under energetically fair conditions. The authors quantify QCA using the average power scaling $\bar{\mathcal{P}}^{\mathrm{opt}}$, the adiabatic advantage $\Gamma_{\mathrm{ad}}$, and the driving-potential ratio $\eta$, revealing substantial quantum enhancement without requiring long-range interactions. They identify an anti-blockade-like mechanism via two-photon transitions and corroborate the quantum nature of charging by analyzing coherent versus incoherent ergotropy and measuring entanglement through the second-order Rényi entropy, showing entanglement growth during charging absent in classical cases. The results establish that short-range, pairwise interactions can realize scalable QCA, with implications for practical quantum energy storage technologies and onboard quantum resources such as coherence and entanglement.

Abstract

Quantum battery, as a novel energy storage device, offers the potential for unprecedented efficiency and performance beyond the capabilities of classical systems, with broad implications for future quantum technologies. Here, we experimentally \RefC{demonstrate quantum charging advantage (QCA)} in a scalable solid-state quantum battery. More specifically, we show how double-excitation Hamiltonians for two-level systems promote scalable QCA \RefB{with standard methods.} We effectively implement the collective evolution of quantum systems with 2 up to 12 battery cells in a superconducting quantum processor, and study the performance of quantum charging compared to its uncorrelated classical counterpart. The model considered is a linear chain of superconducting transmon qubits with only \textit{nearest-neighbor} and \textit{pairwise} interactions, which constitute the simplest model of a multi-cell quantum battery. Our results empirically realize substantial QCA without the necessity of adopting long-range and many-body interactions \RefB{ and showcase the quantum features of the QB charging processes with measurements of non-zero coherent ergotropy, incoherent ergotropy and entanglement,} revealing a promising prospect for further developments of efficient and experimentally feasible protocols for QCA.

Figures (15)

• Figure 1: (a) Pictorial representation of our QB encoded in a 16-qubit lattice, with 12 cells activated in the system. The tunable qubit-qubit interactions control the number of cells during the quantum charging (green cells), while the rest of the system is not charged (red cells). (b) and (c) show the local drives used for classical and quantum charging processes, respectively. (d) Frequency profile for two neighboring qubits, and their corresponding coupler, to implement a two-photon transition by blocking transitions to single-excitation subspace, as depicted in Fig. (e). (f) Population dynamics for a two-cell QB showing low population in the single excitation subspace, $P_\mathrm{se} = P_\mathrm{\ket{\uparrow\downarrow}} + P_\mathrm{\ket{\downarrow\uparrow}}\ll 1$, while transitions $\ket{\downarrow\downarrow}\rightleftarrows\ket{\uparrow\uparrow}$ dominate the evolution, a clear witness of the anti-blockade-like mechanism through two-photon transition.
• Figure 2: (a) Advantage parameters for a $5$-cell QB as a function of the ratio $\alpha = \Omega/g$, showing the transition from artificial energy powered to QCA (around $\alpha = 0.56$). (b) For the cases highlighted in (a), we show the classical average power over time, as a function of $\Delta t$, with the quantum charging power as reference. The experimentally measured coupling of the quantum charging is $g\approx 1.04 \times 2\pi$ MHz. Except for the parameter $\eta (\alpha)$, all other datasets are based on experimental data. Error bars indicate the statistical uncertainty, which is too small to display.
• Figure 3: (a) Time-average quantum charging power for different values of $N$. (b) The scaling of the maximum power for the quantum and classical protocols as a function the $N$. (c) Shows the behavior of the advantage parameters, used to characterize QCA. (d) Correlation function $g^{(2)}$ as a function of the charging time interval $\Delta t$ for different values of $N$, showing the giant-bunching in the optimal charging interval $\Delta t\leq 0.2~\mu$s. See SM for further details about the behavior of the parameters $\alpha$, $v_{\mathrm{qu}}$ and $v_{\mathrm{cl}}$ as function of $N$. Error bars indicate the statistical uncertainty as shown in the shaded regions.
• Figure 4: (a) Schematic representation of density matrix coherences and populations, and their connection to coherent and incoherent components of the total ergotropy. (b-c) Behavior of optimal coherent (b) and incoherent (c) ergotropy power as a function of the number of cells $N$, for classical and quantum charging. (d) Coherent and incoherent power advantage parameter as a function of $N$. All datasets are based on experimental data, with their error bars shown as shaded regions.
• Figure 5: Experimental data for instantaneous power as a function of time for different values of $N$, for (a) quantum and (b) classical charging. Quantum charging bound for (c) quantum and (d) classical charging as defined from Eq. \ref{['Eq:Bounds']}. Experimental parameters are similar to Fig. \ref{['Fig:QCA_scaling']}. Error bars indicating the statistical uncertainty are shown as shaded regions.