Variational quantum algorithms offer a promising route to combinatorial optimization, but their applicability is limited by the challenge of encoding large-scale problems within restricted qubit resources. In this work, we introduce a qubit-efficient variational framework based on Pauli correlation encoding (PCE) and apply it to electric power demand portfolio optimization. Binary variables are represented through expectation values of Pauli correlation operators, which encode multibody correlations of the quantum state and provide a continuous relaxation enabling compact representations with few qubits. We further propose a two-stage hybrid formulation, in which a time-averaged problem provides initialization for a time-resolved optimization. Numerical simulations demonstrate near-optimal performance across problem sizes ranging from $m=18$ to $\mathrm{10,296}$, with normalized cost gaps on the order of ${10}^{-4}$ relative to solutions with certified optimality. We show that the performance is governed by the interplay between continuous relaxation and discretization: the effective resolution of the correlator representation determines how reliably improvements in the continuous loss translate into better discrete solutions, with larger systems exhibiting more consistent behavior. Finally, we demonstrate robustness on a trapped-ion quantum processor, where high-quality solutions are obtained despite noise and finite sampling. These results establish PCE as a physically motivated and qubit-efficient framework for large-scale combinatorial optimization.

Time-continuous quantum error correction, necessary to protect quantum information under time-dependent Hamiltonians, relies on weak continuous syndrome measurements. Implementing these measurements requires a continuous coupling among at least two qubits and a meter, a demanding requirement. We show that, under continuous operation, common parity-measurement protocols in the circuit quantum electrodynamics platform corrupt the logical information. The failure arises from approximating the three-body interaction by a sum of two-body couplings to the meter, which prevents simultaneous suppression of measurement backaction on the logical and error subspaces. We argue that the same mechanism applies more generally beyond the circuit quantum electrodynamics setting. Taken together, our results impose a practical limitation on continuous stabilizer quantum error correction and point to the viable alternatives—architectures that realize native three-body interactions or erasure-based encodings in which the error subspace need not be protected.

We present a continuous-time, neural-network-based approach to optimal control in quantum systems, with a focus on pulse engineering for quantum gates. Leveraging the framework of neural ordinary differential equations (neural ODEs), we construct control fields as outputs of trainable neural networks, thereby eliminating the need for discrete parametrization or predefined bases. This allows for the generation of smooth, control-hardware-agnostic pulses that can be optimized directly using differentiable integrators. As a case study, we design and experimentally implement a short and detuning-robust $\pi /2$ pulse for photon number parity measurements in superconducting transmon circuits. This is achieved through simultaneous optimization for robustness and suppressing the leakage outside of the computational basis. These pulses have very high fidelity ($\approx 99.95\%$) and realize the parity measurement with an efficiency greater than 99.9% over a detuning range of $\approx \pm 20\mathrm{MHz}$, thereby outperforming traditional techniques while retaining comparable gate durations. This showcases the potential of neural ODEs for high-performance quantum control in experimentally relevant settings.

Quantum heuristics have shown promise in solving various optimization problems, including lattice protein folding. Equally relevant is the inverse problem, protein design, where one seeks sequences that fold to a given target structure. The latter problem is often split into two steps: (i) searching for sequences that minimize the energy in the target structure, and (ii) testing whether the generated sequences fold to the desired structure. Here, we investigate the utility of variational quantum algorithms for the first of these two steps on today’s noisy intermediate-scale quantum devices. We focus on the sequence optimization task, which is less resource-demanding than folding computations. We test the quantum approximate optimization algorithm and variants of it, with problem-informed quantum circuits, as well as the hardware-efficient ansatz, with problem-agnostic quantum circuits. While the former approach, with a careful choice of mixer, yields good results in noiseless simulations (success probability $\ge 0.95$ in all instances), its performance drops drastically under noise. With the problem-agnostic circuits, which are more compatible with hardware constraints, improved performance is observed in noisy simulations, compared to their problem-informed counterparts. When running the problem-agnostic circuits on a real quantum device, with parameters taken from simulations, we obtain a significant success probability ($\ge 0.2$) in most instances.

We have developed two modular dilution refrigerators with a cooling power on the order of 1 mW at 100 mK and $20\mathrm{\mu }\mathrm{W}$ at 20 mK, and further carried out joint operation by integrating the two modular units. In the integrated configuration, the base temperatures of the mixing chamber cold plates of both refrigerators remained below 10 mK and within the same temperature range; the combined cooling power essentially doubles that of a single module. In this way, a concurrent increase in both cooling power and available experimental space has been realized through the implementation of the modular integration, and the integrated prototype is already being used to conduct superconducting quantum computing experiments. We experimentally verified that, under integrated operation, the load condition of one module has only a negligible effect on the temperature and cooling power of the other refrigerator, demonstrating a certain degree of independence between the two modular units. Finally, we also point out the challenges that the proposed modular integration scheme may face in its further evolution and suggest possible improvement approaches. This study provides a reference for the future development and application of high-cooling power dilution refrigerators. The scalability demonstrated in cooling power and experimental space is expected to offer solutions for future large-scale quantum computing applications.

Systematic Rabi-amplitude and detuning errors remain important sources of infidelity in high-fidelity quantum gates. We develop a robust pulse-engineering scheme for nonadiabatic holonomic quantum computing in a three-level $\mathrm{\Lambda }$-type qutrit, combining inverse engineering with time-dependent perturbative analysis. Pulse shaping eliminates the leading second-order Rabi-amplitude contribution, while static detuning introduces a distinct population-mediated channel that cannot be removed within a single control loop. We therefore introduce a compensation loop that exactly cancels the dominant second-order $O_{13}^{\delta }$ contribution, with the residual $O_{12}^{\delta }$ channel further suppressed by pulse shaping. Using the logical average gate fidelity over the complete computational subspace, the optimized composite sequence reaches closed-system fidelities of 99.88%–99.99% for four representative single-qubit gates at $ϵ=0.2$ and $\delta /2\pi =2\mathrm{MHz}$. With phenomenological decoherence at $T_1=T_2=30\mathrm{\mu }\mathrm{s}$, the NOT and S gates retain fidelities of 99.72% and 99.79%, respectively, with a coherence-time crossover near $0.58\mathrm{\mu }\mathrm{s}$. These results identify the regime in which systematic-error suppression outweighs the decoherence cost of the additional control loop.

Random pulse sequences are a powerful method for qubit noise spectroscopy, enabling efficient reconstruction of sparse noise spectra. Here, we advance this method in two complementary directions. First, we extend the method using a regularizer based on the total generalized variation norm in order to reconstruct a larger class of noise spectra, namely, piecewise-linear noise spectra, which more realistically model many physical systems. We show through numerical simulations that the new method resolves finer spectral features, while maintaining an order-of-magnitude speedup over conventional approaches to noise spectroscopy. Second, we simplify the experimental implementation of the method by introducing Rademacher measurements for reconstructing sparse noise spectra. These measurements use pseudorandom pulse sequences that can be generated in real time from a short random seed, reducing experimental complexity without compromising reconstruction accuracy. Together, these developments broaden the reach of random pulse sequences for accurate and efficient noise characterization in realistic quantum systems.

In the transmitter of a quantum key distribution (QKD) system, a wavelength-division multiplexer (WDM) is typically used to combine quantum and synchronization signals and is directly connected to the quantum channel. As a result, it becomes the first optical component exposed to laser-injection attacks. Therefore, understanding the behavior of WDMs under such attacks is essential for assessing the practical security of QKD systems. In this work, we systematically investigate the characteristics of WDMs under high-power laser illumination. Our experimental results show that certain WDM samples exhibit pronounced changes in their spectral features once the injected laser power surpasses a specific threshold. Taking the Trojan-horse attack as an illustrative example, we further perform a theoretical analysis of the resulting spectral side channel and show that it can reduce the maximum secure transmission distance to below 66.9% of its original value. By combining experimental observations with theoretical modeling, this study advances the understanding of the influence of WDMs on the practical security of QKD systems.

Noisy intermediate-scale quantum (NISQ) devices impose dual challenges on quantum circuit execution: limited qubit connectivity requires extensive SWAP-gate routing, while time-dependent decoherence progressively degrades quantum information. Existing qubit-mapping algorithms optimize for hardware topology and static calibration metrics but systematically neglect transverse relaxation dynamics ($T_2$), creating a fundamental gap between compiler decisions and evolving noise characteristics. We present transverse relaxation time–aware qubit-mapping (TRAM), a coherence-guided compilation framework that elevates decoherence mitigation to a primary optimization objective. TRAM integrates calibration-informed community detection to construct noise-resilient qubit partitions, generates time-weighted initial mappings that anticipate coherence decay, and dynamically schedules SWAP operations to minimize cumulative error accumulation. Evaluated on Qiskit-based simulators with realistic noise models, TRAM outperforms SABRE by 3.29% in fidelity, reduces gate count by 11.47%, and shortens circuit depth by 12.29%, establishing coherence-aware optimization as essential for practical quantum compilation in the NISQ era.

Phonon modes within pristine crystalline resonators now routinely reach the quantum ground state. Such systems are attractive for quantum information science applications, as advanced fabrication and processing can enable relatively long quantum coherence times, and precision control can be realized through optical, electrical, or qubit coupling. In many state-of-the-art systems, the phonon lifetime is limited by disorder. In particular, native oxides or damaged “dead layers” at surfaces can host two-level tunneling states (TLS) that lead to a particularly problematic form of dissipation that increases at lower temperatures. As mechanical losses are driven down in systems such as microfabricated bulk acoustic wave resonators, tunneling states are expected to emerge as the dominant mechanism for phonon decoherence. A quantitative description of these mesoscopic systems therefore requires a framework that captures interactions between a selected phonon mode and a large ensemble of TLS. Here, we derive a quantum master equation for this coupled system, permitting the phonon decoherence produced by two-level tunneling states to be calculated. As an example, we estimate the lifetime of several quantum states within quartz microresonators hosting a thin surface layer of tunneling states. We find that the phonon coherence time is maximized at low temperatures, in spite of increased mechanical dissipation, and that phonon-TLS coupling can be reduced for modes with strain nodes at the surfaces.

Superconducting circuits are a leading platform for scalable quantum computing, where parametric modulation is a widely used technique for implementing high-fidelity multiqubit operations. A critical challenge, however, is that this modulation can induce a dense landscape of parasitic couplings, leading to detrimental frequency collisions that constrain processor performance. In this work, we develop a comprehensive numerical framework, grounded in Floquet theory, to systematically analyze and mitigate these collisions. Our approach integrates this numerical analysis with newly derived analytical models for both qubit-modulated and coupler-modulated schemes, allowing us to characterize the major parasitic sideband interactions captured by the model and their distinct error budgets. This analysis forms the basis of a constraint-based optimization methodology designed to identify parameter configurations that satisfy the derived physical constraints, thereby avoiding detrimental parasitic interactions. We illustrate the utility of this framework with applications to analog quantum simulation and gate design. Our work provides a predictive tool for co-engineering device parameters and control protocols, enabling the systematic suppression of crosstalk and paving the way for large-scale, high-performance quantum processors.

Fusion measurements are a key primitive for linear-optical quantum computing and quantum networks. Type-I and type-II fusion gates are widely used to combine small entangled resource states into larger photonic states, but without ancillary resources their success probability is limited to $1/2$. Existing $3/4$-efficient type-I schemes rely on entangled Bell-pair ancillary states, whose preparation is itself probabilistic and resource-intensive. Here, we propose a boosted type-I fusion gate using only four ancillary single photons and standard linear-optical primitives. For multiqubit GHZ and graph states, the gate succeeds directly with probability $5/8$, while a distillation protocol converts partially entangled outcomes into additional successful events, raising the total success probability to $11/16$ after one stage and asymptotically to $3/4$. We quantify the practical advantage of this scheme by estimating the photonic resources required for generating representative large entangled photonic states and show that the proposed gate significantly reduces the required overhead compared with existing schemes. These results expand the set of resource-efficient linear-optical primitives and enable a substantial reduction in the resource requirements for scalable photonic quantum computing and quantum communication.

Color-center spins in 4H-SiC offer a rare combination of wafer-scale materials maturity with long spin coherence and chip-level photonics, making them promising building blocks for scalable quantum technologies. In particular, the silicon vacancy hosts an $\mathrm{S}=3/2$ ground state, a native qudit that enables compact encodings and subspace-selective control but also introduces spectator transitions: short, detuned pulses can coherently drive nonaddressed level pairs and create crosstalk. Here we use broadband Ramsey interferometry to reveal and quantify such spectator-transition crosstalk. Experimentally, the Ramsey Fourier spectra display multiple lines beyond the addressed single-quantum transition. Analytically, we map each line to a pairwise energy difference between qudit levels of the rotating-frame Hamiltonian and assign its weight via compact amplitudes set by the prepared state and the microwave pulse parameters, predicting a deterministic six-branch structure. Numerical time-domain propagation with the experimental sampling reproduces the detuning map, and the measured peak positions coincide with the analytic branch lines without frequency fitting. Together these results provide a practical, spectator-aware framework for multilevel control in the silicon-vacancy qudit. The approach offers clear guidance to suppress crosstalk or, conversely, to exploit spectator lines, e.g., as additional constraints for in situ pulse calibration and for phase-sensitive quantum state and process estimation.

We propose a broadband Purcell-protection scheme based on a single shared filter integrated directly into the feedline, enabling simultaneous protection of multiple qubits in a compact architecture with minimal hardware overhead. The filter consists of two open-ended stubs connected by an in-line transmission line, forming a $\mathrm{\Pi }$ geometry, and operates via engineered passive microwave interference that suppresses the real part of the environmental admittance over a wide frequency window. Circuit simulations and finite-element modeling show that transmission is suppressed by several orders of magnitude within the target band (the qubits’ frequencies) while preserving the readout mode of the multiplexed architecture. For realistic device parameters, the proposed design yields Purcell-limited relaxation times exceeding 1 ms over a frequency span of approximately 1.5 GHz. Our results establish the $\mathrm{\Pi }$ filter as a compact and scalable solution for broadband impedance engineering in superconducting quantum circuits, compatible with standard dispersive readout protocols.

We propose a time- and wavelength-multiplexed remote atom-atom entanglement generation protocol based on cavity-assisted photon scattering (CAPS). This is designed to achieve a high rate and high fidelity with robustness to operational imperfections, parameter fluctuations, and auxiliary time costs, such as percent-level photon impurity, timing and cavity parameter jitter, and atom shuttling time costs. We benchmark this protocol using comprehensive analytical and numerical modeling of the atom-cavity dynamics, including state-dependent pulse-delay effects, photon temporal impurity, atom-cavity system parameter fluctuations, and crosstalk among atoms through a shared cavity mode. With realistic atom-cavity system performance, we predict $2\times {10}^5{\mathrm{s}}^{-1}$ successful atom-atom Bell pair generation even without in-cavity qubit reset, substantially enhanced from two-photon-interference-based protocols, at a predicted heralded fidelity of 0.999. We further show that the predicted rate scales further by the use of wavelength multiplexing while maintaining the fidelity.