QOC — Closed-loop & in-situ optimization

Distinguishing Coherent Crosstalk from Calibration Drift via Pauli-Transfer Signatures and Quantum Edge Detection

2026-09-30T00:00:00Z

Multi-tenant quantum processors expose a pulse-level attack surface in which coherent crosstalk can mimic benign calibration drift at matched average gate infidelity. We present a structural verification and detection framework based on the residual Pauli transfer matrix (PTM). We prove that products of local unital, trace-preserving channels cannot mix weight-1 and weight-2 Pauli operators, even under coherent drift of arbitrary strength or axis. Building on established PTM-to-Hamiltonian relations, we prove that, for any specified qubit pair in an arbitrarily large system, the first-order map from its nine interaction coefficients to the antisymmetric cross-weight feature is an isometry up to scale. Thus, every interaction direction is locally observable near the identity. We also exhibit cancellation of this feature under large local rotations and prove that the full cross-weight norm is invariant under local unitary composition, providing a structural countermeasure. For calibrated small local rotations, shared randomized-Pauli measurements support periodic verification using the evaluated antisymmetric detector. In simulation, $16{,}384$ randomized settings yield a detection threshold of $λ_{\min}\approx0.13$ at a $5\%$ calibrated false-positive target, with approximately $M^{-1/2}$ scaling in the number of settings $M$. Further experiments characterize detection under relaxation, depolarization, native ZZ fluctuations, and time-dependent pulse dynamics. Finally, an FRQI encoding with Pauli-graph quantum Hadamard edge detection reproduces the classical structural edge score to numerical precision.

Preparation Changes the Cost of Calibration for Quantum Control

2026-09-25T00:00:00Z

Error-correction records can reveal noise yet supply the information needed for control too slowly. In a surface code under Gaussian dephasing, encoded calibration learns a correlation that reverses the preferred control mainly through rare events. A product probe exposes it more often through the same checks, reducing ideal-record sample complexity from inverse-square to inverse-linear in phase variance. Counting both calibration and execution costs, we show that this gain can repay probe overhead and enable protected tasks within budgets that exclude encoded calibration.

Room-temperature quantum-sensing molecular crystals grown in minutes

2026-09-25T00:00:00Z

Quantum sensing increasingly demands materials combining room-temperature optical spin addressability and coherent control with rapid, accessible fabrication. Yet semiconductor platforms require costly materials and specialized processing, while molecular systems often depend on bespoke synthesis or involved crystal growth. Here we apply microspacing in-air sublimation (MAS) to rapidly fabricate quantum-sensing materials within minutes. Microgram quantities of commercially available precursors crystallize on glass, in air and without vacuum or inert-gas handling. Monitored in situ, growth yields optically clear, stoichiometric single crystals of excellent quality, including plates and needles with intrinsic optical waveguiding. Donor-acceptor charge-transfer co-crystals pairing anthracene or biphenyl with tetracyanobenzene, together with localized-exciton pentacene:pentacenequinone (P:PQ), exhibit room-temperature optically detected magnetic resonance (ODMR). Charge-transfer ODMR resonances reach linewidths below $4\mathrm{MHz}$, consistent with motional narrowing of mobile triplet excitons, while P:PQ supports coherent ensemble spin control with $T_2=0.56μ\mathrm{s}$. Functionality across chemically and electronically distinct pairs establishes MAS as an accessible screen for molecular quantum-sensing materials, connecting molecular crystal engineering with low-cost, chemically tunable thin triplet-spin layers and waveguiding sensor geometries for quantum sensing and microscopy.

Parametric two-qubit gates via Landau-Zener interference

2026-09-14T00:00:00Z

We propose and demonstrate gates between two superconducting qubits based on quantum interference of consecutive Landau-Zener (LZ) transitions. This gate mechanism bridges between baseband and parametric two-qubit control, enabling in situ tuning of the control frequency across a continuous interval up to hundreds of MHz. Another advantage compared to dispersive couplers is that the speed of the LZ gate is on the order of the full coupling strength. We experimentally demonstrate the gate on two platforms, a modular chiplet architecture of coupled generalized flux qubits, and on a monolithic transmon architecture. The combination of tunability and gate speed establishes the LZ gate as a unique tool for multiplexing control pulses and interconnecting superconducting chiplet architectures.

Noise-aware derivative feedback of a harmonic oscillator under quantum-limited position measurement

2026-09-12T00:00:00Z

We study measurement-based feedback control of a damped harmonic oscillator, motivated by optomechanical and interferometric position measurements, in which feedback is synthesized from a displacement measurement. For a band-limited derivative controller, the loop shapes the mechanical susceptibility and reinjects measurement noise, creating a tradeoff between stabilization and noise amplification. We present a compact classical formulation that isolates this tradeoff in the closed-loop displacement spectrum and identifies the parameters governing resonance suppression versus noise-driven actuation. We then extend the same topology to a quantum-limited position detector, enforcing the imprecision-backaction constraint and introducing finite measurement bandwidth that regularizes high-frequency noise reinjection and adds phase lag in the feedback path. In the high-$Q$ regime we obtain an analytic design rule for the optimal feedback gain at fixed controller and measurement bandwidths and compare it with full-spectrum calculations. The comparison shows that a high mechanical quality factor alone does not guarantee quantitative agreement: the accuracy of the near-resonant approximation depends strongly on the controller and measurement bandwidths. Because finite measurement bandwidth changes both the magnitude and phase of the feedback loop, the analysis separates the near-resonant damping contribution from imprecision-noise reinjection and shows that positive near-resonant feedback damping requires the product of the controller cutoff and measurement bandwidth to exceed the square of the mechanical resonance frequency. Finally, we present a dimensionless map of the gain-optimized high-$Q$ occupation and compare its predictions with full-spectrum optimization. All analytical gains evaluated in this map satisfy the full closed-loop stability criterion for these parameters.

Exponential speedup of polarization stabilization for long distance DWDM quantum networks

2026-09-02T00:00:00Z

Fibre-based quantum networks distributing polarization entanglement require a stable and uninterrupted transmission basis for reliable operation. Bright classical reference light enables rapid polarization feedback but can introduce noise into quantum channels. Entangled-photon-based feedback avoids this noise, but typically interrupts the target entanglement channel during calibration and becomes prohibitively slow over long distances due to the product loss of fibre links. Here, we overcome both limitations by combining wavelength-bracketed probing with switch-enabled path decomposition. Spectrally adjacent entangled-photon sidebands track the polarization response of the central distribution channel without interrupting its transmission, while optical switches and local reference fibres independently determine the signal and idler network transformations. Transferring the resulting compensation settings to the central channel eliminates calibration-induced downtime and changes the acquisition-time scaling from the product of the link losses to the sum of losses. We demonstrate the method on a 133 km fibre testbed and achieve continuous closed-loop stabilization for more than 24 hours without classical reference light. The decomposition of multi-link quantum feedback into single-link measurements provides a scalable stabilization strategy for wavelength-multiplexed quantum networks.

Verification Meets Calibration: Bounds and Secret-Independent State Preparation with an NV-Center as a Case Study

2026-08-19T00:00:00Z

Verification protocols provide cryptographic guarantees that the outcome of a delegated quantum computation is correct, a key requirement for scalable and trustworthy quantum computing. A central assumption underlying these protocols is secret independence: the noise affecting state preparation must not depend on the classical secrets that specify the prepared states. In earlier protocols this assumption was enforced by the physical separation of client and server; in the recent on-chip setting it becomes a property of the hardware itself, and one that high-fidelity devices do not automatically satisfy. We first make the requirement quantitative, deriving a bound that shows how residual secret dependence limits the size of any verifiable computation within this framework. Motivated by this, we introduce a calibration framework that enforces secret independence through pulse-level quantum control, producing state preparations that are simultaneously high-fidelity and secret-independent. We assess its performance on a nitrogen-vacancy centre system via emulation, showing that it reduces the secret dependence of the preparations by more than an order of magnitude compared to standard optimal control, and that it is robust against detuning and drive-amplitude errors commonly encountered in experiment. The framework operates entirely at the calibration stage and is platform-agnostic, offering a practical pathway towards verifiable quantum computing at scale.

QCORE: A Quantum-Control-Oriented Real-Time Execution Architecture with Extensible Closed-Loop Services and Shared AI Acceleration

2026-08-07T00:00:00Z

Scalable quantum processors require control, readout, feedback, calibration, and error correction to coexist under bounded latency and shared-resource constraints, whereas existing platforms typically optimize only a subset of these capabilities. This article presents QCORE (Quantum-Control-Oriented Real-Time Execution), a QPU-side digital control reference architecture positioned between the Host and a platform-specific analog/mixed-signal front end. QCORE separates task management, shared resources, hard-real-time execution, and long-timescale services into four hardware partitions. A fast-result sideband closes same-round feedback, a Measurement Packet provides a traceable measurement and service interface, and a common service-control skeleton, Tile-local QEC, and versioned safe-point commit organize calibration, error correction, and long-term state updates. Transaction-level, event-driven, and quantum-behavioral models are used for evaluation. At a background load of 0.8, the $P_{99}$ latency of the shared Measurement Packet/Event feedback path is $(1.984\pm0.004)L_{\max}$. Closed-loop operation reduces the mean frequency error by $83.2\%\pm0.8\%$ and lowers the state-assignment error at maximum readout drift from $10.39\%\pm0.54\%$ to $5.37\%\pm0.29\%$. No unsafe acceptance or mixed-version observation is observed in 100,000 configuration transactions, and Tile-local QEC reduces modeled global-boundary demand and yields a $2.08\times$ capacity-normalized scaling estimate.

Provably Efficient Self-Calibrating Quantum Fault Tolerance

2026-08-06T00:00:00Z

Quantum error correction protects logical information only when every physical operation remains below the fault-tolerance threshold, a condition that must be maintained continuously rather than only at the initial calibration. In practice, however, analog control parameters inevitably drift because of environmental fluctuations. As future fault-tolerant quantum computations are expected to run for days or even months, interrupting computation for repeated recalibration becomes fundamentally impractical. A promising alternative is to integrate calibration directly into computation by repurposing syndrome measurements as a calibration signal (Sivak et al, Nature 2026), but whether such self-calibration can be achieved with provable efficiency remains an open question. Here we establish a theoretical framework for such self-calibrating quantum fault tolerance. We prove that, for a broad class of control-induced errors, the detection rate defines a locally strongly convex surrogate objective for analog calibration with high probability. This geometric property enables a simple and efficient online optimization algorithm using only syndrome measurements collected during normal error correction. We prove convergence to an $\varepsilon$ detection rate within $O(1/\varepsilon^2)$ epochs for time-independent drifts and also establish guarantees for time-dependent drifts. We further show that the convergence rate is independent of the code distance for quantum low-density parity-check (LDPC) codes. Pulse-level simulations of neutral-atom arrays and large-scale circuit-level Clifford simulations confirm these theoretical predictions. Our results establish self-calibrating fault tolerance as a provably efficient paradigm in which the same syndrome measurements simultaneously protect logical information and stabilize the underlying hardware.

Exceptional-point braiding with native controls

2026-07-27T00:00:00Z

Exceptional points define branch-exchange state transfers through holomorphic continuation of non-Hermitian eigenmodes, but realizing these transfers dynamically remains difficult. Slow encircling does not generally transport the full set of instantaneous eigenstates, while shortcuts to adiabaticity can require controls outside the native experimental manifold. Here, we introduce a constrained shortcut-to-adiabaticity principle for exceptional-point braiding using native controls. In a dressed instantaneous-eigenstate frame, the available controls cancel the accessible transition channels locally, while the residual channels remain active during the evolution but are constrained to have no net accumulated effect over the closed loop. The protocol therefore targets the endpoint state transfer selected by ideal adiabatic branch exchange, rather than enforcing complete local cancellation or adiabatic following throughout the trajectory. We demonstrate the construction in a minimal two-mode non-Hermitian model equivalent, up to a trace shift and a basis convention, to the effective Hamiltonian used in dissipative-transmon exceptional-point experiments, where detuning and drive amplitude provide real controls and the relative loss imbalance fixes the non-Hermitian scale. Smooth real waveforms reshape only these controls, reproduce the branch-exchange transfer, and remain accurate under calibration errors, exceptional-point uncertainty and finite-bandwidth filtering with modest overhead.

Simultaneous calibration of rotation and phase errors in a single experiment

2026-07-21T00:00:00Z

In weakly anharmonic qubits, coherent control errors take two generic forms -- over/under-rotation and phase errors -- whose suppression normally requires iterated experiments. We show that, for any symmetric $π/2$ pulse in the weak-driving regime, both follow from a single parametrization, $\mathcal{X}(π/2)=Z(δ)X(π/2+ε)Z(δ)$, that ties the rotation error $ε$ and the phase error $δ$ directly to the system parameters. The parametrization enables DRAPE, a Ramsey-type protocol in which sweeping the phase-error correction reveals a crossing point that fixes both corrections at once. The phase correction is estimated with Heisenberg scaling while the rotation error saturates the standard quantum limit. We experimentally demonstrate DRAPE by calibrating a $π/2$ gate on the $|1\rangle\leftrightarrow |2\rangle$ transition of an IBM transmon, reducing the over-rotation from $0.997^\circ$ to $-0.007^\circ$ and the phase error from $2.52^\circ$ to $0.0052^\circ$ per gate, validated independently by phase- and rotation-error amplification protocols.

Branch-resolved Pauli-block spectroscopy of residual conditional phase in two-qubit gates

2026-07-11T00:00:00Z

Recent progress in quantum physics and quantum technologies is driving quantum computing from the noisy intermediate-scale (NISQ) era toward fault-tolerant operation. High-precision control of two-qubit gates is among the most critical requirements in this transition and hinges on accurate two-qubit calibration. For controlled-phase and CZ-style operations, the residual conditional phase (the nonlocal ZZ-type deviation after local compensation) is weakly resolved at leading order in average infidelity and randomized benchmarking, and repeated Ramsey amplification does not reliably isolate it from ordinary target detuning, SPAM errors, and contrast loss in long sequences. We introduce branch-resolved Pauli-block spectroscopy to estimate the per-cycle residual ZZ-rotation angle theta_c with its sign, from which the controlled-phase residual follows by a fixed convention. The protocol repeats a fixed probe for N cycles, measures the closed Pauli block IX, IY, ZX, and ZY, and forms branch coherences C+ and C- conditioned on the control qubit; theta_c splits the two branch phase slopes in opposite directions, while local target phase beta_c shifts them together. An echoed-cycle variant suppresses removable local terms while preserving the nonlocal contribution. Numerical simulations with injected theta_c, detuning, damping, and SPAM confirm unbiased signed readout where scalar-sector alternatives fail and distinguish opposite-sign errors at equal infidelity. On one superconducting cloud qubit-coupler pair, a pulse-level calibration closed loop shows near-linear injection, preserved branch contrast, and tracking of the native residual conditional phase through one iteration. The approach yields a low-overhead, signed per-cycle estimate of residual conditional phase that standard fidelity benchmarks underresolve at leading order.

QuBE/Qubex: an integrated hardware-software system for superconducting qubit experiments with broadband control

2026-06-11T00:00:00Z

Achieving high-fidelity operation in large-scale superconducting qubit systems requires not only control hardware with broad frequency coverage, low crosstalk, and tight synchronization but also software that coordinates system configuration, experiment execution, and data analysis. Here we present an integrated qubit-control system that combines broadband microwave hardware with a pulse-level software stack for scalable superconducting qubit experiments. The hardware provides broadband microwave coverage, including an instantaneous span of up to 1.6 GHz from a control output, while the software reduces setup and calibration overhead through automated configuration and built-in experiment workflows. We validate the system on a 64-qubit fixed-frequency transmon chip through full-chip frequency identification and representative demonstrations, including multi-unit far-detuned cross-resonance calibration and benchmarking that yields a measured two-qubit gate fidelity of 98.34%, and multilevel readout beyond the computational subspace. By disclosing the hardware architecture and releasing the software stack as open source, this work provides an inspectable hardware-software foundation for scalable superconducting qubit control experiments.

Driving Exchange Interaction in Spin Qubits with Quasi-Zero Pulses

2026-06-05T00:00:00Z

The implementation of high-fidelity quantum gates for spin qubits requires accurate control of exchange interactions between electrons confined in quantum dots, but pulse distortions can limit this control accuracy. Although linear-dynamical distortions can be compensated for by appropriately convolving the control signal, determining the necessary convolution requires detailed knowledge of the distortion's transfer function, and therefore the calibration of numerous parameters. Alternatively, control pulses can be designed to have a net-zero time integral canceling out linear-dynamical pulse distortions. We generalize net-zero pulse designs to quasi-zero pulses allowing net-positive but reduced time integrals. Using these pulse designs, we systematically develop complete gate sets for exchange-only qubits, and study the resulting tradeoffs between pulse duration, fidelity, and the required number of tunable parameters, both in simulation and experiment. We benchmark the optimized gate pulses on Intel's Tunnel Falls six-dot device and show they achieve fidelities similar to those obtained with a full filtering approach, with identical pulse durations and fewer tuning parameters. This reduction in complexity opens the door to fast and easily automated calibration schemes compatible with large-scale commercial quantum devices.

High-fidelity neutral atom gates leveraging low-rank Hessian optimization

2026-06-03T00:00:00Z

Quantum optimal control can produce fast and robust multi-qubit gates, but experimentally calibrating the resulting high-dimensional waveforms remains challenging because direct searches over large parameter spaces converge slowly. Building on the low-rank structure of quantum-control landscapes, we develop and benchmark a Hessian-based calibration method for optimal-control gates. The method identifies the few waveform directions that affect fidelity to leading order, with the number of directions set by the accessible leakage and coherent error channels, and optimizes only within this principal space using closed-loop experimental feedback. We apply this approach to an amplitude-robust controlled-Z gate on metastable-state 171Yb nuclear-spin qubits. Experimentally, we verify the predicted Hessian-sensitive directions and demonstrate rapid convergence of the optimization protocol. The optimized gate reaches a raw fidelity of 0.9959(2), increasing to 0.99902(7) after postselection on no detected loss, and the performance is essentially unchanged under laser-power variations of up to 20%. We further show that the same fidelity Hessian directions can correct certain Hamiltonian parameter errors. These results establish low-rank Hessian optimization as an efficient and physically motivated calibration strategy for high-dimensional optimal-control gates, which is broadly applicable to many qubit types.

Quantum Speed Limit under Calibration Uncertainty

2026-05-19T00:00:00Z

Standard quantum speed limits presuppose exactly known parameters, overestimating operational speed under calibration uncertainty. We introduce a projected speed limit based on the quantum Fisher information that profiles out these nuisance parameters on a quotient manifold. We derive constructive bounds for general Markovian evolution using sensitivity equations. Applying this to Jaynes--Cummings sensors, we obtain explicit detuning tolerances and quantify speed limits arising from field-dependent Purcell loss. This framework turns geometric bounds into concrete design rules for calibration and interrogation time.

Runtime Calibration as State-Trajectory Feedback Control in Quantum-Classical Workflows

2026-05-12T00:00:00Z

In superconducting devices running variational workloads, gate and readout fidelities drift on hour timescales, while existing runtime schedulers treat backend quality as static. The temporal dimension of calibration remains unresolved. We formulate runtime calibration as a state-trajectory feedback-control problem under a fixed wall-clock budget, and investigate whether spending time on calibration now can improve the future optimization trajectory. Calibration quality proxy is represented as a drifting equivalent-age state, recovery action is modeled as costly state reset, and policies are evaluated by time-integrated optimization gap over the full execution window. Using a finite-horizon rollout controller, we compare feedback calibration against a strengthened family of open-loop baselines across three latency regimes: cloud-like (25 ms), local-millisecond (1 ms), and tight-loop (4 $\mathrmμ$s). The results show a clear ordering: cloud-like feedback is generally uncompetitive, while local-ms and tight-loop regimes open a positive-gain region that grows with workload quality-sensitivity and initial calibration age. Crucially, the gap between local-ms and tight-loop control is modest for single-target recovery. The advantage of tight-loop integration emerges under capacity pressure, when many calibration targets must be processed within the same control window.

Multi-Qubit Stabilizer Readout on a Dual-Species Rydberg Array

2026-05-11T00:00:00Z

The ability to locally control and measure subsets of ancilla qubits in an efficient and crosstalk-free manner is a key ingredient in quantum error correction (QEC). Dual-species neutral atom arrays offer an ideal implementation of these capabilities, enabling independent state preparation, manipulation, and detection on each species. In this work, we realize such a dual-species Rydberg array of Na and Cs atoms trapped in co-localized 2D optical tweezer arrays, using Na as an ancilla to measure stabilizers of surrounding Cs data qubits. We identify the finite interspecies Rydberg-Rydberg interaction strength as a practical obstacle to high-fidelity multi-body entanglement and show that, by tuning the Rabi frequency and the detuning of the Rydberg driving field, the resulting geometric phase error can be compensated. This yields a protocol for simultaneous, non-destructive, in situ stabilizer readout of multiple data qubits via global pulses alone. Using this protocol, we demonstrate non-destructive measurement of Pauli-Z stabilizers on four-qubit Cs plaquettes via a single global Rydberg pulse sequence. Our results demonstrate dual-species tweezer arrays as a promising route towards scalable QEC and open the door to new quantum control protocols leveraging both interspecies and intraspecies interactions.

From Characterization To Construction: Generative Quantum Circuit Synthesis from Gate Set Tomography Data

2026-05-02T00:00:00Z

High-fidelity circuit execution on noisy intermediate-scale quantum devices is bottlenecked by compilation pipelines that disregard complex, correlated noise. To address this, this methodology article proposes a quantum machine learning control (QMLC) framework for generative quantum circuit synthesis from gate-set tomography (GST) data that bypasses the traditional two-step pipeline of characterizing native quantum gates via GST followed by unitary decomposition algorithms. Instead, a generative concept space is directly learnt from GST data, enabling conditional synthesis of quantum circuits on a desired output distribution. Our approach tokenizes GST germ circuits and embeds them into a structured latent space using a curriculum-learning-motivated strategy, starting with short circuits and progressively incorporating longer ones with diverse output statistics. The embedded sequences are processed by a set-vision transformer with permutation-invariant pooling, producing k-seed vectors that represent the learned concept space of the quantum device. Aggregating data across multiple circuits makes this latent representation inherently context-aware, capturing the shared physical noise environment (e.g., crosstalk, drift) that isolated gate metrics miss. We propose an unconditional diffusion model to sample from the concept space. During inference, a user provides a target measurement distribution, and the model generates a corresponding circuit. To ensure fidelity and robustness, the output is denoised using a diffusion model that operates on the target conditional covariance matrix. This end-to-end framework is a step towards context-aware, hardware-native circuit synthesis directly from raw GST data, which offers a new paradigm for integrating quantum control and compilation. The QMLC framework is particularly suited for near-term quantum devices with complex calibration procedures.

HEOM-in-Calibration-Loop: Exposing Non-Markovian Bath Signatures That Markovian Calibration Elides in Superconducting-Qubit Tune-Up

2026-04-23T00:00:00Z

Closed-loop superconducting-qubit calibration has matured into DAG-orchestrated protocol chains, yet published frameworks treat the bath via a Markovian master equation or a phenomenological likelihood, absorbing bath structure into fit residuals instead of reporting it as a diagnostic. We integrate a QuTiP 5.x hierarchical-equations-of-motion (HEOM) solver driven by a Tier-1 1/f Burkard bath into a multi-protocol calibration DAG (Rabi -> {Ramsey || T1}) and benchmark it against sesolve and mesolve on a frozen platform in a pulse-level simulator (no hardware validation). The Ramsey channel carries the headline: the Markovian fit is censored by its exponential-family numerical ceiling, while HEOM recovers a physical revival envelope whose primary T2* separates from the Markovian reference by at least 13x at 95% independent-bootstrap confidence within the HEOM-feasible budget; the point-estimate ratio reaches >=28x on the 50-point primary-t1 grid and ~72x on the 30-point biexp-family tau_aw pivot at L=5. Rabi contrast falls 2.17% below mesolve on a noise-limited 30-point grid; the paired-bootstrap CI crosses zero, so this channel corroborates rather than independently establishes the non-Markovian signature. T1 decay shape matches across backends (beta=1.000), yet HEOM's initial occupation drops from 1.000 to 0.879 -- a bath-dressed contamination stable under a 16-point densification. The DAG adds 9.62 us average per-protocol scheduling overhead, no meaningful latency penalty at protocol granularity. HEOM-in-loop thereby changes what calibration reports: bath structure appears as a quantifiable residual rather than a hidden confound.

Reinforcement Learning for Robust Calibration of Multi-Qudit Quantum Gates

2026-04-21T00:00:00Z

Higher-dimensional quantum systems, such as qudits, offer architectural and algorithmic advantages over qubits, but their increased spectral crowding and limited controllability render high-fidelity quantum gates particularly challenging. We propose a hybrid optimization framework that integrates optimal control theory methods with contextual deep reinforcement learning to achieve robust controlled-phase gates on two qutrits. Optimal control is first used to design high-fidelity control pulses for a nominal system model. Reinforcement learning is then employed as a calibration stage that learns small residual corrections to these pulses in the presence of static model mismatch, thereby preserving good gate performance under realistic parameter uncertainties. By learning structured, low-dimensional residual corrections conditioned on device-specific parameter variations, reinforcement learning enhances the transfer robustness of nominally optimal but parameter-sensitive control solutions across ensembles of devices. Crucially, the reinforcement learning step in our framework does not compete with the optimal control step but provides the adaptability required for realistic hardware, systematically reducing the sensitivity to parameter fluctuations. Our results establish reinforcement learning as a practical and scalable ingredient for robust calibration of quantum gates in high-dimensional systems.

Model-Free Quantum Stabilization via Finite-Difference Lyapunov Control

2026-04-11T00:00:00Z

We develop a model-free framework for stabilizing quantum states using only empirical finite-difference evaluations of a measurement-derived Lyapunov observable. The controller requires no knowledge of the Hamiltonian, dissipative structure, or generator of the dynamics, and relies solely on discrete measurement data. The approach combines three key elements: sign-based Lyapunov descent, adaptive gain amplification, and a finite-difference analogue of LaSalle's invariance principle. We provide rigorous conditions under which these mechanisms guarantee asymptotic stabilization along the sampling instants in the drift-free case and practical input-to-state stability (ISS) in the presence of unknown drift and noise. The resulting feedback law is simple, derivative-free, and experimentally feasible. A qubit example illustrates the complete closed-loop scheme and the predicted ISS-type behavior. Although demonstrated on a single qubit, the theory applies to arbitrary finite-dimensional quantum systems and offers a foundation for further developments in stochastic, subspace, and multi-qudit model-free quantum control.

Laser-induced creation of coherent V2 centers in bulk-grown silicon carbide

2026-03-24T00:00:00Z

Solid-state spin defects are promising qubits for quantum network nodes. A key challenge towards larger networks is creating defects with high yield into nanophotonic devices, while maintaining good optical and spin properties. Here, we demonstrate the creation of V2 centers in nanopillars fabricated from commercial bulk-grown 4H-silicon carbide using a pulsed above-bandgap (UV) laser. We observe an eleven-fold increase in the V2 center occurrence after UV laser illumination. These laser-induced V2 centers exhibit narrow optical linewidths and spectral diffusion rates comparable to naturally occurring V2 centers in nanopillars of the same material. Furthermore, we measure a spin coherence time of $T_{2}^{\mathrm{DD}} = 3.6 \pm 0.3~\text{ms}$ under dynamical decoupling, consistent with dephasing by the nuclear-spin bath. This demonstration of the in-situ, post-fabrication generation of coherent V2 centers in nanostructures in widely available bulk-grown 4H-SiC, shows the potential for above-bandgap laser illumination for scalable defect creation in integrated photonic devices.

Certified Quantum Schrödinger Control via Hierarchical Tucker Models

2026-03-20T00:00:00Z

High-dimensional Schrödinger systems arising from tensor-product discretizations suffer from exponential state growth, making direct controller synthesis and real-time closed-loop simulation computationally challenging. Hierarchical Tucker (HT) tensor representations offer scalable low-rank surrogates, but the impact of fixed-rank truncation on closed-loop stability is not well understood. This paper develops a local robustness framework for sampled-data feedback control implemented with fixed-rank HT projections. By viewing each truncation as a bounded, rank-dependent perturbation of the nominal closed loop, and assuming a local phase-invariant contraction certificate together with trajectory-level hierarchical spectral decay, we show that the HT-projected dynamics are practically exponentially stable: trajectories converge to a dimension-independent tube whose radius decreases with the prescribed rank. We further obtain an explicit logarithmic rank-accuracy relation and establish conditions under which controllers designed on the HT-truncated surrogate model retain practical exponential tracking guarantees when deployed on the full system, together with an explicit bound quantifying the resulting surrogate-to-plant mismatch. A compact lattice example demonstrates the applicability of the framework.

Closed-loop dual-channel atomic beam interferometry beyond the half-fringe limit

2026-03-16T00:00:00Z

Atom interferometric inertial sensors offer exceptional sensitivity but are fundamentally constrained by the periodic phase response of matter-wave interference, which imposes an intrinsic half-fringe dynamic-range limit and prevents continuous inertial tracking. In multi-axis configurations, additional cross coupling between acceleration and rotation further complicates closed-loop operation. Here we demonstrate the first dual-channel closed-loop operation of an atomic beam interferometer, realizing decoupled feedback control of acceleration- and rotation-induced phases and overcoming the half-fringe limitation. Using continuous, transversely cooled $^{87}$Rb atomic beams, the interferometric phases associated with rotation and acceleration are independently extracted, tracked across multiple fringes, and actively compensated through Raman frequency modulation. This closed-loop scheme enables unambiguous measurements up to $\pm1\,\mathrm{^{\circ}/s}$ in rotation and $\pm0.17\,\mathrm{g}$ in acceleration while maintaining high fringe contrast, corresponding to nearly two orders-of-magnitude extension beyond the conventional half-fringe limit. The sensor achieves a long-term stability of $4\times10^{-4}\,\mathrm{^{\circ}/h}$ for rotation and $4\,\mathrm{μg}$ for acceleration at an averaging time of $1000\,\mathrm{s}$. By converting the intrinsically periodic interferometric response into stabilized phase-encoded inertial channels, this work establishes a new operating regime for atomic beam interferometry and advances matter-wave sensors toward practical quantum inertial navigation under dynamic conditions.

Gate Optimization via Efficient Two-Qubit Benchmarking for NV Centers in Diamond

2026-03-09T00:00:00Z

High-fidelity gate implementation requires sophisticated control pulses that steer the quantum system to undergo the desired transformation. Quantum Optimal Control allows to derive these control pulses in an open-loop fashion based on numerical simulations. However, their precision can be limited by incomplete knowledge of the system. Closed-loop optimization overcomes this limitation by incorporating feedback from measurements, provided a suitable and efficient measure of the gate performance can be defined. In this article, we present an efficient method to evaluate the performance of a two-qubit gate by preparation and measurement of only two quantum states, enabling experimental closed-loop optimization with a metric previously believed to be limited to open-loop control. We tailor the approach to nitrogen-vacancy centers in diamond and, through numerical simulations, demonstrate how the method can optimize a two-qubit gate while reducing the number of required measurements by two orders of magnitude compared to standard process tomography under realistic experimental settings.

QASMTrans: An End-to-End QASM Compilation Framework with Pulse Generation for Near-Term Quantum Devices

2026-02-05T00:00:00Z

QASMTrans is a lightweight, high-performance, C++-based quantum compiler that bridges abstract quantum algorithms to device-level control and is designed for just-in-time (JIT) deployment on QPU testbeds with tightly integrated FPGAs or CPUs. We focus on achieving fast transpilation times on circuits of interest, we find more than 100x faster compilation than Qiskit in some circuits with similar circuit quality, enabling transpilation of large, high-depth circuits in seconds. Unlike existing tools, QASMTrans offers end-to-end device-pulse compilation and direct quantum control integration with QICK, closing the gap between logical circuits and hardware control enabling closed-loop optimization. QASMTrans supports latency-aware Application-tailored Gate Sets (AGS) at the pulse level, identifying high-impact gate sequences on the circuit critical path and synthesizing optimized pulse schedules using pre-defined robust circuit ansatz. Validated through integrated QuTiP pulse-level simulation, this is found to significantly reduce execution latency and can improve final-state fidelity by up to 12% in some tested circuits. QASMTrans further implements device-aware, noise-adaptive transpilation that uses device calibration data for circuit placement on high-quality qubits and can focus on the circuit critical path to reduce transpilation-pass time while maintaining comparable fidelity. Additionally, it introduces circuit space sharing via calibration-aware device partitioning, enabling concurrent execution of multiple circuits or shots on a single QPU. Moreover, QASMTrans is entirely self-contained and has no external library dependencies, making it easy for practical deployment. By combining fast compilation, pulse-level control, and noise-aware optimization, QASMTrans enables real-time adaptive algorithms such as ADAPT-VQE and ADAPT-QAOA.

When Does Adaptation Win? Scaling Laws for Meta-Learning in Quantum Control

2026-01-26T00:00:00Z

Quantum hardware suffers from intrinsic device heterogeneity and environmental drift, forcing practitioners to choose between suboptimal non-adaptive controllers or costly per-device recalibration. We derive a scaling law lower bound for meta-learning showing that the adaptation gain (expected fidelity improvement from task-specific gradient steps) saturates exponentially with gradient steps and scales linearly with task variance, providing a quantitative criterion for when adaptation justifies its overhead. Validation on quantum gate calibration shows negligible benefits for low-variance tasks but >40% fidelity gains on two-qubit gates under extreme out-of-distribution conditions (10$\times$ the training noise), with implications for reducing per-device calibration time on cloud quantum processors. Further validation on classical linear-quadratic control confirms these laws emerge from general optimization geometry rather than quantum-specific physics. We further introduce a few-shot pre-adaptation protocol that estimates the optimal adaptation budget from $N{=}3$-5 probe steps within 3-19% relative error across out-of-distribution regimes.

Closed-Loop Phase-Coherence Compensation for Superconducting Qubits Integrated Computational and Hardware Validation of the Aurora Method

2025-11-25T00:00:00Z

We present an emulator-based and hardware feasibility study of Aurora-DD, a phase-coherence compensation method that integrates a sign-based feedback update of a global phase offset (Delta phi) with a fixed-depth XY8 dynamical decoupling (DD) scaffold. The feedback optimization is performed offline on a calibrated emulator and the resulting Delta phi* is deployed as pre-calibrated phase compensation on hardware. This represents an "offline closed-loop, online open-loop" feasibility demonstration. Using an Aer-based emulator calibrated with ibm_fez device parameters, Aurora-DD achieves substantial reductions in mean-squared error of the measured expectation value , yielding 68-97% improvement across phase settings phi = 0.05, 0.10, 0.15, 0.20 over n=30 randomized trials. These large-n emulator results provide statistically stable evidence that the combined effect of XY8 and Delta phi* suppresses both dephasing and systematic phase bias. On real superconducting hardware (ibm_fez), we perform a small-sample (n=3) multi-phase validation campaign. Aurora-DD yields point estimates corresponding to approximately 99.2-99.6% reduction in absolute error relative to a no-DD baseline across all tested phase points. These hardware numbers are reported transparently as feasibility evidence under tight queue and credit constraints. In contrast, the auxiliary Aurora+ZNE branch exhibits instability: shallow two-point ZNE occasionally amplifies calibration inconsistencies and produces large error outliers. We therefore relegate ZNE analysis to the Appendix and position Aurora-DD (without ZNE) as the primary contribution. Overall, the combined results support pre-calibrated Aurora-DD as a practical, stable, and hardware-compatible phase-coherence compensator for NISQ devices in single-qubit settings.

Benchmarking Optimization Algorithms for Automated Calibration of Quantum Devices

2025-09-10T00:00:00Z

We present the results of a comprehensive study of optimization algorithms for the calibration of quantum devices. As part of our ongoing efforts to automate bring-up, tune-up, and system identification procedures, we investigate a broad range of optimizers within a simulated environment designed to closely mimic the challenges of real-world experimental conditions. Our benchmark includes widely used algorithms such as Nelder-Mead and the state-of-the-art Covariance Matrix Adaptation Evolution Strategy (CMA-ES). We evaluate performance in both low-dimensional settings, representing simple pulse shapes used in current optimal control protocols with a limited number of parameters, and high-dimensional regimes, which reflect the demands of complex control pulses with many parameters. Based on our findings, we recommend the CMA-ES algorithm and provide empirical evidence for its superior performance across all tested scenarios.