Abstract Entanglement of continuous-variable Gaussian states can be distilled by combination of de-Gaussifying operation such as single-photon subtraction and iterative heralded Gaussification. Here we present and analyze a simplified equivalent version of such entanglement distillation protocol, where the Gaussian measurements utilized in heralded Gaussification are eliminated and are absorbed into the preparation of suitable input Gaussian states of the simplified protocol. The simplified scheme contains less detectors and its overall success probability increases in comparison with the original scheme, while producing completely equivalent outputs. Our simplification of the entanglement distillation protocol closely parallels the recently proposed simplification of a scheme for breeding optical single-mode Gottesman–Kitaev–Preskill states (Aghaee Rad et al 2025 Nature 638 912 ). We investigate operation of the simplified entanglement distillation scheme for both pure and mixed input states and clarify how multicopy distillation of Gaussian entanglement emerges in a setup without any heralding Gaussian measurements.

Abstract Quantum communication enables secure information transmission and entanglement distribution, but these tasks are fundamentally limited by the capacities of quantum channels. While quantum repeaters can mitigate losses and noise, entanglement swapping via a central node is ineffective against the Pauli dephasing channel due to degradation from Bell-state measurements. This suggests that purifying distributed Bell states before entanglement swapping is necessary. Although one-way hashing codes are known to saturate the dephasing channel capacity, no explicit two-way purification protocol has previously been shown to achieve this bound. In this work, we present a two-way entanglement purification protocol with an explicit, scalable circuit that asymptotically achieves the dephasing channel capacity. With each iteration, the fidelity of Bell states increases. At the final round, the residual dephasing error is suppressed doubly-exponentially, scaling as Θ(p 2 n ), enabling near-perfect Bell pairs for any fixed number of purification rounds n. The explicit circuit we propose is versatile and applicable to any number of Bell pairs, offering a practical solution for mitigating decoherence in quantum networks and distributed quantum computing.

Abstract Quantum optimal control in color center physics plays a crucial role in advancing sensor
technology. This study focuses on optimizing microwave pulse shapes within a Ramsey
sequence for Nitrogen-Vacancy centers to enhance sensor sensitivity and signal detection
capabilities. We compare state-of-the-art optimization methods, including the dCRAB
Nelder-Mead algorithm and CMA-ES, and extend our search to machine learning
approaches, such as Gaussian processes and artificial neural networks. These machine
learning techniques are specifically designed to provide robust and global solutions that can
rapidly adapt to changing environmental conditions. Our results demonstrate more than a
sixfold increase in convergence speed compared to conventional methods and considerable
contrast improvements with a limited retraining set of 72 samples. Furthermore, we
demonstrate that the optimized Ramsey contrast translates into a significant enhancement
in the signal-to-noise ratio for detecting synthetic magnetic heart signals. This highlights
the potential of machine learning-driven quantum optimal control for developing more
flexible, adaptive, and efficient quantum sensing solutions in real-world scenarios.

Abstract Satellite quantum key distribution technology has developed rapidly using near-infrared wavelengths and is expected to enable global quantum communication. However, link availability is still hampered by detrimental effects in the free-space channel, such as background noise from solar radiation and attenuation from turbulence and weather such as haze and fog. One potential mitigation technique is to move to the mid-infrared atmospheric transmission window (3–5 µ ms) where background noise and turbulence effects are significantly reduced. While mid-infrared quantum technology is not as well developed, advancements in mid-infrared entangled photon pair generation and nonlinear upconversion single-photon detectors could be poised to enable daytime satellite downlinks with increased reliability. This review compares the state of the art for quantum transmitters and receivers in the mid-infrared to the more established near-infrared technology. The goal is to identify gaps in transmitter and/or receiver technology in the mid-infrared, and to determine if the mid-infrared can offer significant advantages over the near infrared for quantum communication.

Abstract We studied the dynamics of a pair of single-electron double quantum dots (DQD) under longitudinal and transverse static magnetic fields and time-dependent harmonic modulation of their interaction couplings. We propose to modulate the tunnel coupling between the QDs to produce one-qubit gates and the exchange coupling between DQDs to generate entangling gates, the set of operations required for quantum computing. We developed analytical approximations to set the conditions to control the qubits and applied them to numerical calculations to test the accuracy and robustness of the analytical model. The results shows that the unitary evolution of
the two-electron state performs the designed operations even under conditions shifted from the ideal ones.

Abstract The erasure of information is fundamentally an irreversible logical operation, carrying profound consequences for the energetics of computation and information processing. We investigate the thermodynamic costs associated with erasing (and preparing) quantum processes. Specifically, we analyze an arbitrary bipartite unitary gate acting on logical and ancillary input-output systems, where the ancillary input is always initialized in the ground state. We focus on the adversarial erasure cost of the reduced dynamics—that is, the minimal thermodynamic work cost to erase the logical output of the gate for any logical input, assuming full access to the ancilla but no access to any purifying reference of the logical input state. We determine that this adversarial erasure cost is directly proportional to the negative min-entropy of the reduced dynamics, thereby giving the dynamical min-entropy a clear operational meaning. The dynamical min-entropy can take positive and negative values, depending on the underlying quantum dynamics. The negative value of the erasure cost implies that the extraction of thermodynamic work is possible instead of its consumption during the process. A key foundation of this result is the quantum process decoupling theorem, which quantitatively relates the decoupling ability of a process with its min-entropy. This insight bridges thermodynamics, information theory, and the fundamental limits of quantum computation.

Abstract Resource-efficient, low-depth implementations of quantum circuits remain a promising strategy for achieving reliable and scalable computation on quantum hardware, as they reduce gate resources and limit the accumulation of noisy operations. Here, we propose a low-depth implementation of a class of Hadamard test circuits, complemented by the development of a parameterized quantum ansatz specifically tailored for variational algorithms that exploit the underlying Hadamard test framework. Our findings demonstrate a significant reduction in single- and two-qubit gate counts, suggesting a reliable circuit architecture for noisy intermediate-scale quantum (NISQ) devices. Building on this foundation, we tested our low-depth scheme to investigate the expressive capacity of the proposed parameterized ansatz in simulating nonlinear Burgers' dynamics. The resulting variational quantum states faithfully capture the shockwave feature of the turbulent regime and maintain high overlaps with classical benchmarks, underscoring the practical effectiveness of our framework. Furthermore, we evaluate the effect of hardware noise by modeling the error properties of real quantum processors and by executing the variational algorithm on a trapped-ion-based IBEX Q1 device. The outcomes of our demonstrations highlight the resilience of our low-depth scheme in the turbulent regime, consistently preparing high-fidelity variational states that exhibit strong agreement with classical benchmarks. Our work contributes to the advancement of resource-efficient strategies for quantum computation, offering a robust framework for tackling a range of computationally intensive problems across numerous applications.

Abstract Compiling quantum circuits to account for hardware restrictions is an essential part of the quantum computing stack. Circuit compilation allows us to adapt algorithm descriptions into a sequence of operations supported by real quantum hardware, and has the potential to significantly improve their performance when optimization techniques are added to the process. One such optimization technique is reducing the number of quantum gates that are needed to execute a circuit. For instance, methods for reducing the number of non-Clifford gates or CNOT gates from a circuit is an extensive research area that has gathered significant interest over the years. For certain hardware platforms such as ion trap quantum computers, we can leverage some of their special properties to further reduce the cost of executing a quantum circuit in them. In this work we use global interactions, such as the Global M{\o}lmer-S{\o}rensen gate present in ion trap hardware, to optimize and synthesize quantum circuits. We design and implement an algorithm that is able to compile an arbitrary quantum circuit into another circuit that uses global gates as the entangling operation, while optimizing the number of global interactions needed. The algorithm is based on the ZX-calculus and uses an specialized circuit extraction routine that groups entangling gates into Global M{\o}lmer-S{\o}rensen gates. We benchmark the algorithm in a variety of circuits, and show how it improves their performance under state-of-the-art hardware considerations in comparison to a naive algorithm and the Qiskit optimizer.

Abstract This paper introduces a quantum-enhanced finite element method (FEM) designed for noisy intermediate-scale quantum (NISQ) devices, leveraging variational quantum algorithms (VQAs) to solve engineering partial differential equations (PDEs). We demonstrate the framework by solving the Euler-Bernoulli beam and the NAFEMS T4 heat transfer problems, which involve Dirichlet, Neumann, and Robin boundary conditions. A key innovation is a ``set-to-zero" strategy that incorporates boundary conditions through a correction matrix, $K_{bc}$, allowing for flexible imposition at any node without domain decomposition. The global stiffness matrix is decomposed into a constant number of Pauli terms, $O(1)$, using the method by Sato et al., while boundary terms are handled with a sublinearly scaling Partial Pauli Measurement (PPM) technique. The algorithm achieves logarithmic qubit scaling ($n = \lceil \log_2 N \rceil $ qubits for N degrees of freedom) and employs shallow, hardware-efficient circuits with empirically trainable depth for small-scale systems. Validation on the Qiskit statevector simulator shows high accuracy. For the Euler-Bernoulli beam problem with 4 to 64 degrees of freedom, the algorithm achieves relative errors of 0.5–1.5\% and fidelities of 0.998–0.999. For the NAFEMS T4 heat transfer benchmark, a 5.4\% relative error is observed. The VQA converges robustly within 77–350 iterations, though barren plateaus are a known challenge for scaling to larger systems. This work establishes a scalable framework for quantum FEM, offering a significant memory advantage over classical methods and advancing the potential for quantum-enhanced engineering simulations.