Scalable coherent control hardware for quantum information platforms is rapidly growing in priority as their number of available qubits continues to increase. As these systems scale, more calibration steps are needed, leading to challenges with system instability as calibrated parameters drift. Moreover, the sheer amount of data required to run circuits with large depth tends to balloon, especially when implementing state-of-the-art dynamical-decoupling gates which require advanced modulation techniques. We present a control system that addresses these challenges for trapped-ion systems, through a combination of novel features that eliminate the need for manual bookkeeping, reduction in data transfer bandwidth requirements via gate compression schemes, and other automated error handling techniques. Moreover, we describe an embedded pulse compiler that applies staged optimization, including compressed intermediate representations of parsed output products, performs in-situ mutation of compressed gate data to support high-level algorithmic feedback to account for drift, and can be run entirely on chip.
Scalable coherent control hardware for quantum information platforms is rapidly growing in priority as their number of available qubits continues to increase. As these systems scale, more calibration steps are needed, leading to challenges with system instability as calibrated parameters drift. Moreover, the sheer amount of data required to run circuits with large depth tends to balloon, especially when implementing state-of-the-art dynamical-decoupling gates which require advanced modulation techniques. We present a control system that addresses these challenges for trapped-ion systems, through a combination of novel features that eliminate the need for manual bookkeeping, reduction in data transfer bandwidth requirements via gate compression schemes, and other automated error handling techniques. Moreover, we describe an embedded pulse compiler that applies staged optimization, including compressed intermediate representations of parsed output products, performs in-situ mutation of compressed gate data to support high-level algorithmic feedback to account for drift, and can be run entirely on chip.
Scalable coherent control hardware for quantum information platforms is rapidly growing in priority as their number of available qubits continues to increase. As these systems scale, more calibration steps are needed, leading to challenges with system instability as calibrated parameters drift. Moreover, the sheer amount of data required to run circuits with large depth tends to balloon, especially when implementing state-of-the-art dynamical-decoupling gates which require advanced modulation techniques. We present a control system that addresses these challenges for trapped-ion systems, through a combination of novel features that eliminate the need for manual bookkeeping, reduction in data transfer bandwidth requirements via gate compression schemes, and other automated error handling techniques. Moreover, we describe an embedded pulse compiler that applies staged optimization, including compressed intermediate representations of parsed output products, performs in-situ mutation of compressed gate data to support high-level algorithmic feedback to account for drift, and can be run entirely on chip.
We present hereby a high-level hardware-agnostic framework for a resonant-control-based approach to stabilizing quantum processors. The method improves coherence and logical error performance by aligning control operations with intrinsic system response features through generalized resonance and quasi-aperiodic timing. This paper intentionally omits implementation details, proprietary algorithms, and confidential calibration methods to avoid prejudicing ongoing patent proceedings. Instead, we focus on conceptual formalism, theoretical motivation, and simulated indicators of performance improvement. Detailed implementation remains confidential pending patent issuance and licensing discussions. Patent pending (U.S. Provisional Application filed November 2025). All specific resonant carrier frequencies, base timing periods, numerical ratio scaling constants, envelope-shaping functions, and adaptive feedback algorithms are trade secrets of Dubito Inc. and are not disclosed in this work The resonant-control architecture (RCA) introduced in this work suggests a conceptual shift in how quantum decoherence and control noise are addressed at scale. Rather than treating decoherence purely as a consequence of microscopic material limitations or stochastic fluctuations, RCA frames the problem in terms of macroscopic dynamical structure, namely, the presence of device-specific resonance features and stability basins embedded within the quantum system’s effective response landscape. By aligning control pulses with these structural features, one can reduce sensitivity to low-frequency drift and non-Markovian disturbances without requiring explicit modeling of their origins. From a theoretical standpoint, RCA generalizes the idea behind dynamical-decoupling and filter-function approaches, but differs critically in its departure from strict periodicity or analytically prescribed timing sequences. Whereas classical decoupling protocols rely on precise, regular intervals with well-defined spectral notches, our resonant alignment leverages quasi-aperiodic intervals to avoid aliasing while maintaining coherence with intrinsic dynamical modes. This opens a pathway to more stable long-time behavior, especially under significant drift or structured noise. Another key implication concerns scalability. Fault-tolerant quantum computing requires the ability to sustain high-rate syndrome extraction and realtime feedback, not only sufficiently low physical error rates. A reduction in effective sensitivity to slow drifts or burst-like errors directly impacts the stability of logical operations, potentially easing the overhead associated with syndrome cycles and decoder latency. Though we intentionally avoid specifying exact performance metrics, simulation trends indicate that RCA can modify the effective scaling constants governing logical error suppression, providing a complementary layer to code-level corrections. Because RCA is hardware-agnostic, its implications extend across modalities, including superconducting qubits, bosonic encodings, trapped ions, and photonic platforms. Each modality has distinct noise profiles, yet all exhibit some form of internal dynamical structure that can be harnessed for resonant alignment. This offers a unifying perspective that could aid in cross-platform benchmarking and co-design strategies between hardware and control layers. Finally, RCA opens conceptual avenues for understanding the interplay between classical control and quantum dynamics. By abstracting away implementation details while emphasizing structural alignment, it establishes a theoretical foundation for future studies on stability basins, quasi-periodic scheduling, and adaptive resonance identification in noisy quantum systems. The RCA framework generalizes known dynamical-decoupling and frequency-modulated approaches while remaining distinct in its treatment of internal resonance and adaptive quasi-aperiodicity. Because implementation-specific algorithms are withheld, the paper serves as a conceptual introduction rather than a disclosure of patent-sensitive information. We have outlined a resonant-control framework that enhances quantum coherence and suppresses logical error accumulation by exploiting intrinsic dynamical structure within quantum hardware. The approach is fundamentally architecture-neutral and can be integrated into existing control stacks without requiring modifications to qubit design or measurement infrastructure. While the specific algorithms and calibration methods are withheld to preserve ongoing patent protections, the conceptual and theoretical basis presented here provides a foundation for future analyses and controlled experimental evaluations. This work suggests that progress toward scalable quantum computation may depend as much on control-level innovation as on hardware improvements. Resonant alignment and quasi-aperiodic timing sequences offer a pathway for mitigating drift sensitivity and noise coupling, potentially reducing the resource overhead associated with quantum error correction. Future research will focus on detailed modeling, cross-platform validation, and integration with advanced decoding and feedback systems. In summary, the resonant-control architecture represents a promising direction for improving quantum system stability and should be considered an essential component of next-generation quantum control and fault tolerance. We present a trade-secret-safe exposition of a resonant-control approach to improving quantum coherence and logical error performance. Detailed mechanisms remain proprietary pending patent review. Nov. 25, 2025, Daniel Solis Dubito Inc. www.dubito-ergo.com
The central challenge of quantum computing is implementing high-fidelity quantum gates at scale. However, many existing approaches to qubit control suffer from a scale-performance trade-off, impeding progress towards the creation of useful devices. Here, we present a vision for an electronically controlled trapped-ion quantum computer that alleviates this bottleneck. Our architecture utilizes shared current-carrying traces and local tuning electrodes in a microfabricated chip to perform quantum gates with low noise and crosstalk regardless of device size. To verify our approach, we experimentally demonstrate low-noise site-selective single- and two-qubit gates in a seven-zone ion trap. We implement electronic single-qubit gates with fidelities ≥ 99.99912 ( 8 ) % and demonstrate consistent performance with low crosstalk across the device. We also electronically generate two-qubit maximally entangled states with 99.97 ( 1 ) % fidelity and long-term stable performance over continuous system operation. These state-of-the-art results highlight the potential of our all-electronic approach for coherent control of trapped-ion qubits in large-scale quantum computers.
In this paper, we provide a system level perspective on the design of control electronics for large scale quantum systems. Quantum computing systems with high-fidelity control and readout, coherent coupling, calibrated gates, and reconfigurable circuits with low error rates are expected to have superior quantum volumes. Cryogenic CMOS plays a crucial role in the realization of scalable quantum computers, by minimizing the feature size, lowering the cost, power consumption, and implementing low latency error correction. Our approach toward achieving scalable feed-back based control systems includes the design of memory based arbitrary waveform generators (AWG’s), wide band radio frequency analog to digital converters, integrated amplifier chain, and state discriminators that can be synchronized with gate sequences. Digitally assisted designs, when implemented in an advanced CMOS node such as 7 nm can reap the benefits of low power due to scaling. A qubit readout chain demands several amplification stages before the digitizer. We propose the co-integration of our in-house developed InP HEMT LNAs with CMOS LNA stages to achieve the required gain at the digitizer input with minimal area. Our approach using high impedance matching between the HEMT LNA and the cryogenic CMOS receiver can relax the design constraints of an inverter-based CMOS LNA, paving the way toward a fully integrated qubit readout chain. The qubit state discriminator consists of a digital signal processor that computes the qubit state from the digitizer output and a pre-determined threshold. The proposed system realizes feedback-based optimal control for error mitigation and reduction of the required data rate through the serial interface to room temperature electronics.
Quantum mechanics allows for the processing of information in entirely new ways, surpassing the computational limits set by classical physics. Termed `quantum information processing', scaling this scheme relies on simultaneously increasing the number of qubits -- the fundamental unit of quantum computation -- whilst reducing their error rates. With this comes a variety of challenges, including the ability to readout the quantum state of large numbers of qubits, as well as to control their evolution in order to mitigate errors. This thesis aims to address these challenges by developing techniques for the readout and control of quantum systems. The first series of experiments focuses on the readout of GaAs/AlGaAs semiconductor quantum systems, primarily relating to the technique of dispersive gate sensing (DGS). DGS is used to probe electron transmission in an open system, a quantum point contact, demonstrating an ability to resolve characteristic features of a one-dimensional ballistic channel in the limit where transport is not possible. DGS is also used to observe anomalous signals in the potential landscape of quantum-dot defining gate electrodes. A technique for time domain multiplexing is also presented, which allows for readout resources, in the form of microwave components, to be shared between multiple qubits, increasing the capacity of a single readout line. The second series of experiments validates control techniques using trapped 171Yb+ ions. Classical error models are engineered using high-bandwidth IQ modulation of the microwave source used to drive qubit rotations. Reductions in the coherent lifetime of the quantum system are shown to match well with quantitative models. This segues in to developing techniques to understand and suppress noise in the system. This is achieved using the filter-transfer function approach, which casts arbitrary quantum control operations on qubits as noise spectral filters.
As superconducting quantum processors scale toward hundreds of qubits, manual calibration becomes increasingly costly and difficult to sustain. Here we address two system-level factors governing automated calibration, namely, crosstalk induced by parallel operations and temporal drift of control parameters. On a 66-qubit superconducting processor, cross-entropy benchmarking shows that single-qubit calibration tolerates full-chip concurrency with minimal fidelity loss, whereas CZ calibration requires a minimum coupler-graph distance of four to avoid elevated control errors. Continuous monitoring of representative qubit and coupler parameters further yields quantitative refresh rules that assign refresh priority by error-budget consumption. These results turn two conventionally heuristic choices, the concurrency density of calibration tasks and the refresh priority of each control parameter, into measurable operating rules. Implemented within an automated calibration framework, the rules support a six-qubit Greenberger-Horne-Zeilinger state with a zero-noise-extrapolated fidelity of 89.64%, distance-dependent logical-error suppression in a single-cycle repetition-code benchmark, and a reduction of the mean single-qubit error from 0.023 to 0.011 on a 337-qubit processor, providing an experimentally grounded reference for the automated calibration and maintenance of current and future large-scale superconducting quantum systems.