Irreversibility and time-translation symmetry are both fundamental in open quantum dynamics, and it is of great importance to study the interplay between them. In this paper, we study tabletop reversibility (TTR) for phase-covariant quantum operations and obtain sharply different conclusions for finite-dimensional and Gaussian systems. For finite-dimensional systems, we prove that any phase-covariant operation that admits a Petz recovery map can be implemented by a dilation which is both time-translational symmetric and tabletop time reversible. In contrast, for phase-covariant Gaussian operations we exhibit a concrete obstruction: any Gaussian dilation of a single-mode Gaussian amplification channel is not tabletop time reversible. As a byproduct, we find that almost every completely positive and trace preserving (CPTP) map admits a dilation that realizes TTR. These results clarify whether and how TTR can be realized under phase-covariant symmetry constraints and reveal a qualitative difference between finite-dimensional and Gaussian systems.

We investigate the charging dynamics and thermodynamic performance of a wireless quantum battery system mediated by a common structured bosonic environment. By employing a unified resource-theoretic analysis, we elucidate the distinct roles of non-Markovian memory effects and coupling symmetry in regulating energy transfer. In the Markovian weak-coupling regime, we identify a transformative mechanism where the dynamic reconstruction of $l_1$-norm coherence compensates for the monotonic decay of first-order coherence to sustain energy transport. Conversely, the non-Markovian strong-coupling regime facilitates a cooperative resonance, characterized by the synchronized oscillation of entanglement and stored energy induced by environmental backflow. Furthermore, we reveal that coupling symmetry acts as a critical control parameter: While asymmetric coupling favoring the battery optimizes energy gain in memoryless environments, symmetric coupling under strong interactions unlocks a dark-state protection mechanism, effectively trapping energy within a decoherence-free subspace. Finally, a thermodynamic analysis based on ergotropy demonstrates that first-order coherence establishes the activation threshold for incoherent work, whereas $l_1$-norm coherence serves as the explicit fuel for coherent work extraction. These findings provide a refined theoretical framework for engineering environment-assisted quantum energy-storage devices.

While there is strong evidence for advantages of quantum over classical computation, the repertoire of computational primitives with proven or conjectured quantum advantage remains limited. A big challenge of quantum algorithmic design is a still incomplete understanding of the sources of quantum computational power. Advancing toward systematic quantum advantage calls for a better understanding of the efficient use of nonclassical resources like nonstabilizer states. We present an approach to track nonclassical contributions in the form of nonstabilizerness across various algorithms by pairing resource theory of nonstabilizer entropies with the geometry of quantum state evolution, and introduce permutation agnostic distance measures that reveal and quantify nonstabilizer effects previously hidden by a subset of Clifford operations. We find different efficiency in the use of nonstabilizerness for structured and unstructured variational approaches and show that greater freedom for classical optimization in quantum-classical methods increases unnecessary nonstabilizer consumption. Our results open alternative means of analyzing the efficient utilization of quantum resources and contribute toward the targeted construction of algorithmic quantum advantage.

Constrained devices, such as smart sensors, wearable devices, and Internet of Things nodes, are increasingly prevalent in society and rely on secure communications to function properly. These devices often operate autonomously, exchanging sensitive data or commands over short distances, such as within a room, house, or warehouse. In this context, continuous-variable quantum key distribution (CV-QKD) offers the highest secure key rate and the greatest versatility for integration into existing infrastructure. A key challenge in this setting, where devices have limited storage and processing capacity, is obtaining a realistic and tight estimate of the CV-QKD secure key rate within a composable security framework, with error correction (EC) consuming most of the storage and computational power. To address this, we focus on low-density parity-check codes with nonbinary alphabets, which optimize mutual information and are particularly suited for short-distance communications. We develop a security framework to derive finite-size secret keys near the optimal EC leakage limit and model the related memory requirements for the encoding process in one-way error correction. This analysis facilitates the practical deployment of CV-QKD, particularly in constrained devices with limited storage and computational resources.

The electronic stopping power of protons in rare metal Gd is investigated by the ion-electron interaction simulations based on time-dependent density functional theory. We have analyzed the contribution of the inner-shell bound electronic excitation to the electronic stopping power of protons through Gd near the Bragg peak. The result shows that the inner $5p$-electron excitation plays a fundamental role in determining the curve trend of stopping vs velocity around and beyond the electronic stopping maximum. Under the condition of off-channeling, the incoming ion closely encounters the host atoms, and the electronic stopping power considering the participation of inner electrons is in good agreement with the experimental data. In addition, it is found that, as more electrons are involved, the peak position of the electronic stopping curve is gradually shifted towards the experimentally measured peak.

Most studies of quantum batteries have been restricted to conventional atoms whose size is much smaller than the electromagnetic modes. Here we propose a scheme for a quantum battery based on giant atoms in a coupled-resonator waveguide. Specifically, both the charger and the battery are giant atoms coupled to the waveguide in a braided configuration at multiple spatially separated points, enabling nonlocal and non-Markovian interactions mediated by propagating photons. We show that the charging process is governed by the formation of bound states in the continuum, which arise from constructive interference between spatially separated coupling channels. The stored energy exhibits long-lived Rabi oscillations associated with the suppression of decay into the waveguide continuum. The ergotropy and energy extraction efficiency can be significantly enhanced by tuning the atom-field interaction and the distance between the coupling points. Our work highlights the potential of giant atoms for high-performance quantum batteries, revealing that the spatially distributed coupling provides a promising route toward enhancing both charging efficiency and energy storage stability.

Magic state distillation (MSD) is a cornerstone of fault-tolerant quantum computing, enabling non-Clifford gates via state injection into stabilizer circuits. However, the substantial overhead of current MSD protocols remains a major obstacle to scalable implementations. We propose a general framework for pre-distillation based on composite pulse sequences that suppress systematic errors in the generation of magic states. While most composite designs target simple gates such as $X, Z$, or Hadamard, our schemes directly implement the non-Clifford $\mathcal{T}$ gate with enhanced robustness to the targeted systematic errors. We develop composite sequences tailored to the dominant control imperfections in superconducting, trapped-ion, neutral-atom, and integrated photonic platforms. To quantify improvement in the implementation, we introduce an operationally motivated fidelity measure specifically tailored to the $\mathcal{T}$ gate, which captures the gate's effectiveness in preparing high-fidelity magic states. We further show that the error in the channel arising from the injection of faulty magic states scales linearly with the leading-order error of the states. Within the systematic-error-dominated regimes considered, this approach lowers the number of required distillation levels by up to three across the platforms we study, translating to substantial qubit-overhead savings and offering a practical route toward more resource-efficient universal quantum computation.

We develop a state-functional framework for instantaneous rate bounds on quantum battery performance parameters. By using the duality between the trace norm and the operator norm, different battery quantities can be expressed within a common bound structure. Energetic, extractable work, and information-theoretic quantities are treated as functionals of the reduced battery state. For each functional, a sensitivity operator separates the bound into a universal trace-norm speed and a parameter-dependent spectral sensitivity factor, and also determines the equality condition. We apply the framework to the charging power, the ergotropy rate, and the change rate of purity in Jaynes-Cummings, anisotropic Rabi, central-spin, and $\mathit{XY}$ spin-chain batteries. The results show that these rates share the same state space speed, while their approach to equality depends on the corresponding sensitivity operator and on the reduced-state dynamics. Counter-rotating wave terms and many-body couplings do not invalidate the bounds, but modify their saturation behavior. Overall, the framework is model independent and provides general limits for battery performance parameters.

We show that a parametrized quantum neural network can be used to build a nonparametric quantum kernel for machine learning that inherits the concentration properties of the neural network cost function. This construction establishes a rigorous connection between barren plateaus (BPs) in variational quantum algorithms and exponential concentration of quantum kernels for machine learning. Our results imply that recently proposed algorithms for building BP-free quantum circuits can be utilized to construct useful quantum kernels for machine learning with unknown inductive bias. This is illustrated by a numerical example employing a provably BP-free quantum neural network to construct kernel matrices for multiple classification datasets of increasing dimensionality.

Quantum generative models exploit quantum superposition and entanglement to enhance learning efficiency for both classical and quantum data. Recently, inspired by classical diffusion frameworks, the quantum denoising diffusion probabilistic model has emerged as a powerful tool for learning correlated noise models, many-body phases, and topological data structures. However, we demonstrate that this framework is currently restricted to small-scale systems. As the system size increases, a severe barren plateau problem emerges, fundamentally limiting the model's scalability. We provide rigorous theoretical proofs and experimental validation to identify the origin of this barren plateau, distinct from previously known causes. To restore trainability, we introduce an enhanced architecture that effectively mitigates the barren plateau phenomenon and guarantees the model's trainability in the tested settings. Building on this architecture, we further propose a conditional quantum denoising diffusion probabilistic model, capable of generating ground states based on Hamiltonian parameters, expanding the utility of quantum generative models for complex quantum state preparation to a certain extent. Our approach not only holds the potential to address the scalability and trainability bottlenecks of quantum diffusion models, but also provides a robust tool for exploring complex quantum matter and state preparation in the noisy intermediate-scale quantum era.

We present a unified scheme for generating high-fidelity entangling gates in superconducting platforms by continuous dynamical decoupling (CDD) combined with variational minimal-energy optimal control. During the CDD stage, we suppress residual couplings, calibration drifting, and quasistatic noise, resulting in a stable effective Hamiltonian that preserves an interaction proportional to ZZ and YY coupling terms, necessary for generating entanglement. In this stable $\mathrm{SU}\left(4\right)$ manifold, we calculate smooth low-energy single-quibt control functions using a variational geodesic optimization process that directly minimizes gate infidelity. We illustrate the methodology by applying it to CZ, CX, and a two-qubit gate constructed as a CX followed by random single-qubit rotations, achieving virtually unit fidelity and robustness under restricted single-qubit action, with experimentally realistic control fields. These results establish CDD-enhanced variational geometric optimal control as a practical and noise-resilient scheme for designing superconducting entangling gates.

Quantum generative models constitute an important class of quantum machine learning approaches for preparing complex quantum states and probability distributions, and most existing studies rely on variational quantum circuits with universal logic gates. However, in discrete-variable linear-optical quantum systems, the implementation of universal logic gates typically requires measurement-induced nonlinearities, which are accompanied by substantial ancillary-photon overheads and rapidly decreasing postselection success probabilities. These constraints severely limit the scalability of gate-based generative models on linear-optical platforms. In this work, we develop an interferometer-based quantum optical generative model framework together with a dedicated training methodology for discrete-variable linear-optical systems under postselection constraints. The framework directly optimizes the interferometer matrix while balancing generation fidelity and postselection success probability, enabling the generation of target quantum states and probability distributions with significantly higher success probabilities than gate-based schemes. Furthermore, we introduce an adaptive optimization strategy and a sampling-based training scheme, showing that the proposed framework exhibits good convergence behavior and broad applicability under limited sampling resources. Thus, our work provides a physically feasible pathway toward scalable quantum generative models and in situ training on linear-optical platforms.

We develop a measurement-based protocol for purifying logical states of a quantum system, including quantum error correcting codes, in arbitrary thermal states with unit fidelity and finite probability, using a single auxiliary qubit. The protocol entails a time evolution caused by an engineered Hamiltonian realizable using current technology, which results in transitions between the logical and error subspaces of the system mediated by the auxiliary qubit, followed by a projective measurement in an optimum basis on the auxiliary qubit and an appropriate postselection of the measurement outcomes. We show that the protocol is flexible in using suboptimal measurements to achieve a fidelity as high as $90\%$ via multiple iterations of the purifying procedure, thereby highlighting its robustness against variations in the measurement basis. We demonstrate the applicability of the developed protocol in quantum error correcting codes as well as in paradigmatic quantum spin models. We observe that the performance of the protocol is robust even when the thermal noise persists during the purification process, and discuss a number of possible generalizations of the prescription.

We evaluate the feasibility of remote high-temperature thermometry based on the blackbody-radiation-induced AC Stark shift of Rydberg electromagnetically induced transparency (EIT) resonances in ${}^{87}\mathrm{Rb}$ vapor. Extending the Farley-Wing formalism to the 1000–4000 K range, we show that the BBR shift of Rydberg states converges to the state-independent ${\mathrm{T}}^2$ asymptotic for principal quantum numbers $\mathrm{n}>20$, with convergence accelerating at elevated temperatures. A geometric dilution model accounts for the finite solid angle subtended by a remote blackbody source, and a shutter-based differential protocol removes the ambient BBR baseline. For a reference geometry with a 5 cm aperture at 3 cm standoff (path-averaged dilution factor ${\eta }^0=0.24$), the measurable signal reaches 25 kHz at 2000 K and exceeds 100 kHz at 4000 K. Absolute-mode EIT spectroscopy yields a thermometric sensitivity of 26 Hz/K at 2000 K in an ideal transparent cell, while differential Rydberg-Rydberg measurements are 2 orders of magnitude less sensitive due to the universality of the asymptotic shift. The $5{\mathrm{S}}_{1/2}$ ground-state BBR correction to the two-photon signal, evaluated dynamically using relativistic all-order matrix elements, is negligible at room temperature but reaches 6.7% at 2000 K and 18.6% at 4000 K, exhibiting nonmonotonic behavior driven by the interplay of the thermal spectrum with the $5\mathrm{S}\to 5\mathrm{P}$ resonance. With comb-referenced spectroscopy, subkelvin temperature uncertainty is achievable at 2000 K within $\sim {10}^2$ s of averaging, paving a path toward SI-traceable remote high-temperature thermometry linked directly to the definition of the second.

Exceptional points (EPs) in non-Hermitian (NH) systems give rise to enhanced sensitivity and chiral state transfer, which are important for quantum technologies. Although parameter trajectories encircling EPs can control symmetric and chiral state transfer, their robustness against practical perturbations and their role in quantum sensing remain largely unexplored. Here, we study three time-modulated parameter loops in an NH two-level system to show how trajectory design governs state-transfer symmetry, robustness, and sensing performance. Trajectories avoiding the exceptional point (EP) support robust symmetric transfer, while those encircling the EP yield chiral transfer governed by the topological winding number $\nu =\pm 1/2$, whose robustness depends on the distance to the EP and the encircling direction. For quantum sensing, trajectory engineering enables tuning of sensitivity amplitude, time window, and parameter selectivity in both eigenvalue-based and eigenstate-based sensors. Notably, eigenstate-based sensing achieves full parameter selectivity that is unattainable with eigenvalue-based methods. Our results establish a quantitative connection between trajectory topology and system dynamics, providing a unified framework for robust state-transfer protocols and high-performance quantum sensors.

We report laser-induced-fluorescence spectroscopy of the ${}^{1}S_0\to {}^{3}P_1$ intercombination transition in neutral zinc at $307.6\mathrm{nm}$. Isotope shifts are measured for all stable isotopes with kHz-level precision, improving previous data by about two orders of magnitude. For ${}^{67}\mathrm{Zn}$, we resolve the excited-state hyperfine structure and determine $\delta {\nu }_{\mathrm{COG}}^{67,64}=1085.933\left(7\right)\mathrm{MHz}, A=608.922\left(3\right)\mathrm{MHz}$, and $B=-18.995\left(10\right)\mathrm{MHz}$. A King plot comparison with the ${}^{1}S_0\to {}^{1}P_1$ 214-nm transition results in field- and mass-shift parameters of $F_{307.6,214}=1.17\left(5\right)$ and $K_{307.6,214}=-153\left(60\right)\mathrm{GHz}\mathrm{u}$. These results provide the spectroscopic basis for narrow-line cooling and precision measurements based on zinc, including the development of an optical clock.

The single- and double-electron capture processes in ${\mathrm{Ne}}^{8+}+\mathrm{He}$ collisions are investigated using a two-active-electron semiclassical atomic-orbital close-coupling method in the energy range from 0.2 to 100 keV/u. A sufficiently large basis set with 98 and 19 Gaussian-type orbitals in ${\mathrm{Ne}}^{8+}$ and He, respectively, is employed to include electron-electron correlation and the coupling of numerous autoionizing channels. Total and $nl$ state-selective single-electron-capture cross sections show excellent agreement with available experimental data. The double-electron-capture cross sections for the $3ln{l}^{\prime }(n=3-5)$ channels, which contribute 30%–40% to the total single-electron-capture cross sections through postcollision autoionization, are reported. Further analysis reveals that electron correlation and the coupling between single- and double-capture channels significantly affect the cross sections by a factor of 2–3 for subdominant single-capture channels and double-capture autoionization states. The x-ray spectra and the Auger-electron spectra from double capture to autoionizing states are simulated and successfully reproduce the fundamental features of the experimental data, which indicates that at a collision energy of 20 keV/u, previous single-active-electron theoretical calculations significantly underestimated the cross sections for weak double-electron capture channels, including the $3s3d{}^{1}D^e, 3s3p{}^{1}P^o, 3p3d{}^{1}D^o$, and $3p^2{}^{1}D^e$ states.

The photoionization (PI) spectrum of the ${\mathrm{N}}_2$ molecule is modeled using a first-principles approach combining the multichannel quantum defect theory and electron scattering calculations performed using the uk r-matrix codes. The PI spectra were determined starting from the ground and several excited vibrational levels of ${\mathrm{N}}_2$ in the ground electronic state $X^1{\mathrm{\Sigma }}_g^{+}$. Excited electronic states and vibrational motion of the $\mathrm{N}{{}^{+}}_2$ ion are accounted for. The spectrum obtained for the lowest vibrational level of ${\mathrm{N}}_2$ was compared to the available experimental data. Major resonances in the obtained spectrum were characterized using the quantum defect technique.