Error Suppression Research Articles

Limitations to Dynamical Error Suppression and Gate-Error Virtualization from Temporally Correlated Nonclassical Noise

Realistic multiqubit noise processes often result in error mechanisms that are not captured by the probabilistic Markovian error models commonly employed in circuit-level analyses of quantum fault tolerance. By working within an open-quantum system Hamiltonian formulation, we revisit the validity of the notion of a constant gate error in the presence of noise that is both and , and the impact of which is mitigated through perfect instantaneous dynamical decoupling subject to finite timing constraints. We study a minimal exactly solvable single-qubit model under Gaussian quantum dephasing noise, showing that the fidelity of a dynamically protected idling gate can depend strongly on its location in the circuit and the history of applied control, even when the system-side error propagation is fully removed through perfect reset operations. For digital periodic control, we prove that, under mild conditions on the low-frequency behavior of the nonclassical noise spectrum, at a value that is strictly smaller than the one attainable in the absence of control history; the presence of high-frequency noise peaks is also found as especially harmful, due to the possible onset of . We explicitly relate these features to the evolution of the bath statistics during the computation, which has not been fully accounted for in existing treatments. We find that only if decoupling can keep the qubit highly pure over a time scale larger than the correlation time of the noise, the bath approximately converges to its original statistics and a stable-in-time control performance is recovered. Our work highlights the significance of the full bath evolution between circuit locations and suggests that additional trade-offs and design constraints may arise in layered quantum fault-tolerant architectures from the need to appropriately reequilibrate the quantum bath statistics, particularly when Markovian noise is present alongside temporally correlated noise. Published by the American Physical Society 2025

Research on NLOS error suppression in UWB based on RICT algorithm

Research on NLOS error suppression in UWB based on RICT algorithm

High-rate quantum LDPC codes for long-range-connected neutral atom registers

High-rate quantum error correcting (QEC) codes with moderate overheads in qubit number and control complexity are highly desirable for achieving fault-tolerant quantum computing. Recently, quantum error correction has experienced significant progress both in code development and experimental realizations, with neutral atom qubit architecture rapidly establishing itself as a leading platform in the field. Scalable quantum computing will require processing with QEC codes that have low qubit overhead and large error suppression, and while such codes do exist, they involve a degree of non-locality that has yet to be integrated into experimental platforms. In this work, we analyze a family of high-rate Low-Density Parity-Check (LDPC) codes with limited long-range interactions and outline a near-term implementation in neutral atom registers. By means of circuit-level simulations, we find that these codes outperform surface codes in all respects when the two-qubit nearest neighbour gate error probability is below ~ 0.1%. By using multiple laser colors, we show how these codes can be natively integrated in two-dimensional static neutral atom qubit architectures with open boundaries, where the desired long-range connectivity can be targeted via the Rydberg blockade interaction.

Relaxation Digital-to-Analog Converters Featuring Self-Calibration and Parasitics-Induced Error Suppression in 180-nm CMOS

Relaxation Digital-to-Analog Converters Featuring Self-Calibration and Parasitics-Induced Error Suppression in 180-nm CMOS

GALIC: hybrid multi-qubitwise pauli grouping for quantum computing measurement

Abstract Observable estimation is a core primitive in NISQ-era algorithms targeting quantum chemistry applications. To reduce the state preparation overhead required for accurate estimation, recent works have proposed various simultaneous measurement schemes to lower estimator variance. Two primary grouping schemes have been proposed: full commutativity (FC) and qubit-wise commutativity (QWC), with no compelling means of interpolation. In this work we propose a generalized framework for designing and analyzing context-aware hybrid FC/QWC commutativity relations. We use our framework to propose a noise-and-connectivity aware grouping strategy: Generalized backend-Aware pauLI Commutation (GALIC). We demonstrate how GALIC interpolates between FC and QWC, maintaining estimator accuracy in Hamiltonian estimation while lowering variance by an average of 20% compared to QWC. We also explore the design space of near-term quantum devices using the GALIC framework, specifically comparing device noise levels and connectivity. We find that error suppression has a more than 10 × larger impact on device-aware estimator variance than qubit connectivity with even larger correlation differences in estimator biases.

Enhanced Error Suppression for Accurate Detection of Low-Frequency Variants.

The identification of low-frequency variants remains challenging due to the inevitable high error rates of next-generation sequencing (NGS). Numerous promising strategies employ unique molecular identifiers (UMIs) for error suppression. However, their efficiency depends highly on redundant sequencing and quality control, leading to tremendous read waste and cost inefficiency. Here, we describe a novel approach, enhanced error suppression strategy (EES), that addresses these challenges by (1) optimizing data utilization and reducing read waste by utilizing single-read correction that reserves abundant single reads that complement other single reads or single-strand consensus sequences (SSCSs), and (2) effectively enhancing the accuracy of NGS by employing Bayes' theorem. EES significantly improves variant detection accuracy, achieving a background error rate of less than 4.4×10-5 per base pair. Additionally, the data utilization rate is dramatically increased, with a 22.9-fold enhancement in duplex consensus sequence (DCS) recovery compared to traditional methodologies. Furthermore, EES demonstrates superior error suppression performance across various base substitutions. In conclusion, EES represents a significant advancement in detecting low-frequency variants by improving data utilization and reducing sequencing errors. It potentially enhances the sensitivity and accuracy of NGS applications, proving highly valuable in clinical and research contexts where precise variant detection is critical.

Accuracy-Monitoring Path Optimization With Error Suppression in Laser Triangulation On-Machine Measurement

Accuracy-Monitoring Path Optimization With Error Suppression in Laser Triangulation On-Machine Measurement

The autonomous error suppression method based on phase delay modulation for the SINS

The autonomous error suppression method based on phase delay modulation for the SINS

Study of magnetic field error suppression methods based on atomic parameters of cell in atomic co-magnetometer rotation measurement

Abstract We propose a new model for magnetic field errors based on the rotation measurement of the K-Rb- 21 Ne co-magnetometer, considering the density ratio and spin collisions. The spin polarization characteristics of different alkali metal density ratios were analyzed by creating five cells with different density ratios, and the correctness of the magnetic field error model was verified experimentally. Moreover, the effects of five different alkali metal density ratios of cells on the sensitivity, long-term stability and magnetic field error suppression of the K-Rb- 21 Ne co-magnetometer were investigated experimentally. When the density ratio is 1:107, there can be the optimal magnetic field error suppression effect, sensitivity and long-term stability. According to the derived magnetic field error equation, the magnetic noise error of the K-Rb- 21 Ne co-magnetometer with an optimized density ratio is reduced by nearly 5 times from 260°/h/nT to 56.5°/h/nT, the sensitivity is improved from 2.9×10−5 °/s/Hz 1 / 2 to 7.0×10−6 °/s/Hz 1 / 2 at 1 Hz, and the long-term stability Allan variance over two hours is improved from 1.9×10−2 °/h to 8.9×10−3 °/h. This result provides a theoretical basis for designing the parameters of the K-Rb- 21 Ne co-magnetometer cell.

Abstract B009: Individualized-tumor-informed panel approach enables ultra-sensitive ctDNA-based minimal residue disease monitoring for high-risk pediatric cancers

Abstract While the use of ctDNA-based minimal residual disease (MRD) monitoring is gaining popularity in adult cancers, this approach is not yet widely adopted in pediatric cancers (PCs). We developed a robust and sensitive assay to monitor ctDNA in PCs, which overcomes PC-specific challenges including low tumor mutational burden, paucity of hotspot mutations and low blood volume. To address these challenges, our innovations include personalized panel design that targets primary tumor mutations from each patient, a fixed panel targeting hotspot mutations, error suppression from duplex deep sequencing and customized pipeline for tumor burden estimation. We retrospectively analyzed 661 blood or cerebrospinal fluid (CSF) samples from 168 patients. We achieved an average detection limit of 0.005% ctDNA purity leading to MRD detected ranging from 0.001% to 100% with brain tumor consistently showing a low MRD. At disease diagnosis, progression and relapse, our assay identified ctDNA in over 93% of extra- cranial solid tumors, 90% of leukemia, 89% of sarcoma, and 90% of neuroblastoma. For brain tumors, we detected MRD in ∼90% of CSF samples, and in ∼60% of blood samples, a major advance over previous approaches. Importantly, we detected MRD in ∼ 20% of cases with a clinically complete response, predicting relapse up to 6 months before clinical confirmation. Overall, these results demonstrate that our monitoring assay for PCs is an important addition to standard of care for precision-guided treatment. Citation Format: Rob Salomon, Wenhan Chen, Charles Shale, Mojgan Toumari, Aileen Lowe, Wenyan Li, Jingwei Chen, Sajad Razavi-Bazaz, Paulette Barahona, Louise Cui, Chelsea Mayoh, Sam El-Kamand, Vanessa Tyrrell, Marie Wong-Erasmus, Loretta MS Lau, Noemi Fuentes-Bolanos, Edwin Cuppen, Dong-Anh Khoung-Quang, Jordan Staunton, Marion K Mateos, Toby Trahair, Michelle Haber, David S Ziegler, Paul Ekert, Peter Priestley, Mark Cowley. Individualized-tumor-informed panel approach enables ultra-sensitive ctDNA-based minimal residue disease monitoring for high-risk pediatric cancers [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B009.

Benchmarking Digital Quantum Simulations Above Hundreds of Qubits Using Quantum Critical Dynamics

The real-time simulation of large many-body quantum systems is a formidable task, that may only be achievable with a genuine quantum computational platform. Currently, quantum hardware with a number of qubits sufficient to make classical emulation challenging is available. This condition is necessary for the pursuit of a so-called quantum advantage, but it also makes verifying the results very difficult. In this paper, we flip the perspective and utilize known theoretical results about many-body quantum critical dynamics to qualitatively benchmark digital quantum hardware and various error mitigation techniques. In particular, we benchmark against known universal scaling laws in the Hamiltonian simulation of a time-dependent transverse-field Ising Hamiltonian of up to 133 qubits. Incorporating only basic error mitigation and suppression methods, our study shows reliable control up to a two-qubit gate depth of 28, featuring a maximum of 1396 two-qubit gates, before noise becomes prevalent. These results are transferable to applications such as Hamiltonian simulation, variational algorithms, optimization, or quantum machine learning. We demonstrate this on the example of digitized quantum annealing for optimization and identify an optimal working point in terms of both circuit depth and time step on a 133-site optimization problem. Published by the American Physical Society 2024

Optimal quantum controls robust against detuning error

Abstract Precise control of quantum systems is one of the most important milestones for achieving practical quantum technologies, such as computation, sensing, and communication. Several factors deteriorate the control precision and thus their suppression is strongly demanded. One of the dominant factors is systematic errors, which are caused by discord between an expected parameter in control and its actual value. Error-robust control sequences, known as composite pulses, have been invented in the field of nuclear magnetic resonance (NMR). These sequences mainly focus on the suppression of errors in one-qubit control. The one-qubit control, which is the most fundamental in a wide range of quantum technologies, often suffers from detuning error. As there are many possible control sequences robust against the detuning error, it will practically be important to find ‘optimal’ robust controls with respect to several cost functions such as time required for operation, and pulse-area during the operation, which corresponds to the energy necessary for control. In this paper, we utilize the Pontryagin’s maximum principle (PMP), a tool for solving optimization problems under inequality constraints, to solve the time and pulse-area optimization problems. We analytically obtain pulse-area optimal controls robust against the detuning error. Moreover, we found that short-CORPSE, which is the shortest known composite pulse so far, is a probable candidate of the time optimal solution according to the PMP. We evaluate the performance of the pulse-area optimal robust control and the short-CORPSE, comparing with that of the direct operation.

Coupler-Assisted Leakage Reduction for Scalable Quantum Error Correction with Superconducting Qubits.

Superconducting qubits are a promising platform for building fault-tolerant quantum computers, with recent achievement showing the suppression of logical error with increasing code size. However, leakage into noncomputational states, a common issue in practical quantum systems including superconducting circuits, introduces correlated errors that undermine quantum error correction (QEC) scalability. Here, we propose and demonstrate a leakage reduction scheme utilizing tunable couplers, a widely adopted ingredient in large-scale superconducting quantum processors. Leveraging the strong frequency tunability of the couplers and stray interaction between the couplers and readout resonators, we eliminate state leakage on the couplers, thus suppressing space-correlated errors caused by population propagation among the couplers. Assisted by the couplers, we further reduce leakage to higher qubit levels with high efficiency (98.1%) and low error rate on the computational subspace (0.58%), suppressing time-correlated errors during QEC cycles. The performance of our scheme demonstrates its potential as an indispensable building block for scalable QEC with superconducting qubits.

Fringe photometric stereo

In fringe projection profilometry (FPP), a high spatial frequency of fringe typically indicates powerful error suppression capability; however, it complicates phase unwrapping, necessitating a greater number of patterns and thus compromising the real-time performance of scanning. In this letter, we report a fringe photometric stereo (FPS) to completely bypass phase unwrapping for recovering the continuous 3D surface. We reveal the linear mapping relationship between the phase gradient and depth gradient, thereby facilitating the computation of depth gradients from phase gradients. Thus, we can employ depth gradients to reconstruct high-quality 3D profiles. Experimental results demonstrate that our FPS surpasses traditional phase-shifting profilometry in mitigating Gaussian noise. Our approach enables high-quality and unambiguous 3D reconstruction using single-frequency fringe patterns, relying solely on a camera and a projector without the need for dual, multiple, or light field cameras, thereby paving a path to high-speed and precision 3D imaging.

Optical pump magnetometers parametric correction method based on three-axis coil arrays

Optical pump magnetometers (OPMs), based on the SERF principle, are increasingly prevalent in biomagnetic field detection and localization studies. However, cross-axis crosstalk is an unavoidable consequence of the non-ideal factors introduced during the development of the sensor array, whether during the initial design or manufacturing process. This study introduce a novel method to compensate for cross-axis crosstalk by a set of three-axis coils. The gain matrix of each sensor in an OPM array is calibrated by the magnetic field generated by the activation of the three-axis coils. The results showed that the correlation coefficients between the corrected coil distribution field measurements and the true values improved substantially, exceeding 0.99. Similarly, the similarity between the forward-field simulation and the measured results for the localization of a physical model of a current dipole improved significantly, from 0.78 to 0.96. This work presents the first report of the simultaneous calibration of a large OPM array comprising 64 OPMs. The suppression of cross-axis crosstalk errors improves the sensor measurement accuracy and the consistency of the array. This method is expected to further improve the accuracy of OPM array-based source localization.

Physical coherent cancellation of optical addressing crosstalk in a trapped-ion experiment

Abstract We present an experimental investigation of coherent crosstalk cancellation methods for light delivered to a linear ion chain cryogenic quantum register. The ions are individually addressed using focused laser beams oriented perpendicular to the crystal axis, which are created by imaging each output of a multi-core photonic-crystal fibre waveguide array onto a single ion. The measured nearest-neighbor native crosstalk intensity of this device for ions spaced by 5 µm is found to be ∼ 10 − 2 . We show that we can suppress this intensity crosstalk from waveguide channel coupling and optical diffraction effects by a factor > 10 3 using cancellation light supplied to neighboring channels which destructively interferes with the crosstalk. We measure a rotation error per gate on the order of ϵ x ∼ 10 − 5 on spectator qubits, demonstrating a suppression of crosstalk error by a factor of > 10 2 . We compare the performance to composite pulse methods for crosstalk cancellation, and describe the appropriate calibration methods and procedures to mitigate phase drifts between these different optical paths, including accounting for problems arising due to pulsing of optical modulators.

Quantum Fourier Transform Using Dynamic Circuits.

In dynamic quantum circuits, classical information from midcircuit measurements is fed forward during circuit execution. This emerging capability of quantum computers confers numerous advantages that can enable more efficient and powerful protocols by drastically reducing the resource requirements for certain core algorithmic primitives. In particular, in the case of the n-qubit quantum Fourier transform followed immediately by measurement, the scaling of resource requirements is reduced from O(n^{2}) two-qubit gates in an all-to-all connectivity in the standard unitary formulation to O(n) midcircuit measurements in its dynamic counterpart without any connectivity constraints. Here, we demonstrate the advantage of dynamic quantum circuits for the quantum Fourier transform on IBM's superconducting quantum hardware with certified process fidelities of >50% on up to 16 qubits and >1% on up to 37 qubits, exceeding previous reports across all quantum computing platforms. These results are enabled by our contribution of an efficient method for certifying the process fidelity, as well as of a dynamical decoupling protocol for error suppression during midcircuit measurements and feed forward within a dynamic quantum circuit that we call "feed-forward-compensated dynamical decoupling." Our results demonstrate the advantages of leveraging dynamic circuits in optimizing the compilation of quantum algorithms.

Analysis and suppression of cross-axis modulation coupling errors in optically pumped magnetometers

We propose a method based on sensitive-axis high-frequency modulation (SHFM) method combined with PI closed-loop feedback to suppress the cross-axis modulation coupling error (CMCE) of the optically pumped magnetometer (OPM). Cross-axis modulation is a prevalent approach for three-axis measurement of OPM, but this scheme will introduce CMCE. These errors have the potential to pose undetected hazards in applications of multi-axis magnetic field measurement such as magnetoencephalography (MEG). The SHFM method suppressed the CMCE from 18.50% to 2.10% on average compared to the traditional method. Based on the static situation we also introduce PI closed-loop feedback, which suppressed the CMCE from 22.07% in open-loop mode to 2.10% in closed-loop mode. This approach is both straightforward and efficacious, offering seamless integration into an arrayed OPM-based system. Furthermore, SHFM has the potential to mitigate the challenges associated with MEG localization accuracy and other measurement errors introduced by CMCE, and further unleash the potential of applications of OPM–MEG system.

Solving the Hele–Shaw flow using the Harrow–Hassidim–Lloyd algorithm on superconducting devices: A study of efficiency and challenges

The development of quantum processors for practical fluid flow problems is a promising yet distant goal. Recent advances in quantum linear solvers have highlighted their potential for classical fluid dynamics. In this study, we evaluate the Harrow–Hassidim–Lloyd (HHL) quantum linear systems algorithm (QLSA) for solving the idealized Hele–Shaw flow. Our focus is on the accuracy and computational cost of the HHL solver, which we find to be sensitive to the condition number, scaling exponentially with problem size. This emphasizes the need for preconditioning to enhance the practical use of QLSAs in fluid flow applications. Moreover, we perform shots-based simulations on quantum simulators and test the HHL solver on superconducting quantum devices, where noise, large circuit depths, and gate errors limit performance. Error suppression and mitigation techniques improve accuracy, suggesting that such fluid flow problems can benchmark noise mitigation efforts. Our findings provide a foundation for future, more complex application of QLSAs in fluid flow simulations.

Adaptive hysteresis compensation control of a macro-fiber composite bimorph by improved reinforcement learning

The hysteresis characteristics related to the frequency and amplitude of the control signal seriously affect the precision of the displacement tracking control of the macro-fiber composite (MFC) bimorph. The traditional feedforward compensator tends to exhibit low precision in controlling displacement. Although it enhances the control accuracy to a certain extent by incorporating a feedback controller, the existing feedback controller has a weak adaptive ability. Thus, the Q-learning (QL) algorithm is combined with the Bouc-Wen (BW) feedforward compensator in this study. The output voltage from the BW compensator has a more significant impact on the control accuracy and convergence speed of the QL algorithm. Therefore, this paper proposes an improved QL (IQL) algorithm that leverages the control error. Moreover, a BW-IQL adaptive control method is proposed to realize precise adaptive control of the MFC bimorph. Experimental comparisons are performed with the proposed method and the traditional BW, BW-PID, and BW-fuzzy PID controllers. The BW-IQL controller reduces the average relative errors of the three controllers by 86.9%, 59.9%, and 41.8%, respectively. Meanwhile, the Q̄ table plays a major role in error suppression in the IQL controller. These results verify that the BW-IQL control method has higher adaptability and accuracy.