Synergistic Dynamical Decoupling and Circuit Design for Enhanced Algorithm Performance on Near-Term Quantum Devices.

Dynamical decoupling (DD) is a promising technique for mitigating errors in near-term quantum devices. However, its effectiveness depends on both hardware characteristics and algorithm implementation details. This paper explores the synergistic effects of dynamical decoupling and optimized circuit design in maximizing the performance and robustness of algorithms on near-term quantum devices. By utilizing eight IBM quantum devices, we analyze how hardware features and algorithm design impact the effectiveness of DD for error mitigation. Our analysis takes into account factors such as circuit fidelity, scheduling duration, and hardware-native gate set. We also examine the influence of algorithmic implementation details, including specific gate decompositions, DD sequences, and optimization levels. The results reveal an inverse relationship between the effectiveness of DD and the inherent performance of the algorithm. Furthermore, we emphasize the importance of gate directionality and circuit symmetry in improving performance. This study offers valuable insights for optimizing DD protocols and circuit designs, highlighting the significance of a holistic approach that leverages both hardware features and algorithm design for the high-quality and reliable execution of near-term quantum algorithms.

John Senders, Human Error, and System Safety.

OBJECTIVE: I examine John Senders' work and discuss his influence on the study of error causation,error mitigation, and sociotechnical system safety. BACKGROUND: John Senders' passing calls for an evaluation of the impact of his work. METHOD: I review literature and accident investigation findings to discuss themes in Senders' work and potential associations between that work and error causation and system safety. RESULTS: Senders consistently emphasized empirical rigor and theoretical exploration in his research, with the desire to apply that work to enhance human performance. He has contributed to changing the way error has been viewed, and to developing and implementing programs and techniques to mitigate error. While a causal relationship between Senders' work and safety cannot be established, an association can be drawn between his research and efforts to mitigate error. CONCLUSION: Because of Senders' work, we have a better understanding of error causation and enhanced ways of mitigating system errors. However, new sources of error, involving advanced systems and operators' knowledge and understanding of their functionalities can, if not addressed, degrade system safety. APPLICATION: Modifications to advanced automation and operator training are suggested, and research to improve operator expertise in interacting with automated systems proposed.

Effective Population Size Predicts Local Rates but Not Local Mitigation of Read-through Errors.

In correctly predicting that selection efficiency is positively correlated with the effective population size (Ne), the nearly neutral theory provides a coherent understanding of between-species variation in numerous genomic parameters, including heritable error (germline mutation) rates. Does the same theory also explain variation in phenotypic error rates and in abundance of error mitigation mechanisms? Translational read-through provides a model to investigate both issues as it is common, mostly nonadaptive, and has good proxy for rate (TAA being the least leaky stop codon) and potential error mitigation via "fail-safe" 3' additional stop codons (ASCs). Prior theory of translational read-through has suggested that when population sizes are high, weak selection for local mitigation can be effective thus predicting a positive correlation between ASC enrichment and Ne. Contra to prediction, we find that ASC enrichment is not correlated with Ne. ASC enrichment, although highly phylogenetically patchy, is, however, more common both in unicellular species and in genes expressed in unicellular modes in multicellular species. By contrast, Ne does positively correlate with TAA enrichment. These results imply that local phenotypic error rates, not local mitigation rates, are consistent with a drift barrier/nearly neutral model.

Self-Supervised Sidewalk Perception Using Fast Video Semantic Segmentation for Robotic Wheelchairs in Smart Mobility.

The real-time segmentation of sidewalk environments is critical to achieving autonomous navigation for robotic wheelchairs in urban territories. A robust and real-time video semantic segmentation offers an apt solution for advanced visual perception in such complex domains. The key to this proposition is to have a method with lightweight flow estimations and reliable feature extractions. We address this by selecting an approach based on recent trends in video segmentation. Although these approaches demonstrate efficient and cost-effective segmentation performance in cross-domain implementations, they require additional procedures to put their striking characteristics into practical use. We use our method for developing a visual perception technique to perform in urban sidewalk environments for the robotic wheelchair. We generate a collection of synthetic scenes in a blending target distribution to train and validate our approach. Experimental results show that our method improves prediction accuracy on our benchmark with tolerable loss of speed and without additional overhead. Overall, our technique serves as a reference to transfer and develop perception algorithms for any cross-domain visual perception applications with less downtime.

Distance Measurements in UWB-Radio Localization Systems Corrected with a Feedforward Neural Network Model.

An ultra-wideband (UWB) localization system is an alternative in a GPS-denied environment. However, a distance measurement with UWB modules using a two-way communication protocol induces an orientation-dependent error. Previous research studied this error by looking at parameters such as the received power and the channel response signal. In this paper, the neural network (NN) method for correcting the orientation-induced distance error without the need to calculate the signal strength, obtain the channel response or know any parameters of the antenna and the UWB modules is presented. The NN method utilizes only the measured distance and the tag orientation, and implements an NN model obtained by machine learning, using measurements at different distances and orientations of the two UWB modules. The verification of the experimental setup with 12 anchors and a tag shows that with the proposed NN method, 5 cm better root mean square error values (RMSEs) are obtained for the measured distance between the anchors and the tag compared to the calibration method that did not include orientation information. With the least-square estimator, 14 cm RMSE in 3D is obtained with the NN model corrected distances, with a 9 cm improvement compared to when raw distances are used. The method produces better results without the need to obtain the UWB module's diagnostics parameters that are required to calculate the received signal strength or channel response, and in this way maintain the minimum packet size for the ranging protocol.

A Bayesian Filtering Approach for Error Mitigation in Ultra-Wideband Ranging.

Ultra-wideband (UWB) sensors have been widely used in multi-robot systems for cooperative tracking and positioning purposes due to their advantages such as high ranging accuracy and good real-time performance. In order to reduce the influence of non-line-of-sight (NLOS) UWB communication caused by the presence of obstacles on ranging accuracy in indoor environments, the paper proposes a novel Bayesian filtering approach for UWB ranging error mitigation. Nonparametric UWB sensor models, namely received signal strength (RSS) model and time of arrival (TOA) model, are constructed to capture the probabilistic noise characteristics under the influence of different obstruction conditions and materials within a typical indoor environment. The proposed Bayesian filtering approach can be used either as a standalone error mitigation approach for peer-to-peer (P2P) ranging, or as a part of a higher level Bayesian state estimation framework. Experiments were conducted to validate and evaluate the proposed approach in two configurations, i.e., inter-robot ranging, and mobile robot tracking in a wireless sensor network. The experimental results show that the proposed method can accurately identify the line-of-sight (LOS) and NLOS scenarios with wood and metal obstacles in a probabilistic representation and effectively improve the ranging/tracking accuracy. In addition, the low computational overhead of the approach makes it attractive in real-time systems.

User-Oriented ICT Cloud Architecture for High-Accuracy GNSS-Based Services.

We introduce a new information and communication technology (ICT) cloud-based architecture for Global Navigation Satellite System (GNSS) high-accuracy solutions, offering also a commercial overview of GNSS downstream market to show how the developed innovation is thought to fit in the real context. The designed architecture is featured by dynamic scalability, increased integrity, and greater agility of the ICT system. The novelty of the solution developed is a customized ICT architecture, obtained through unique and privileged access to user communities in the frame of the H2020 project TREASURE, allowing the development of a solution entirely driven by user needs. The economic outlook of GNSS downstream markets evolution highlights how the technology proposed effectively matches the evolving business environment, specifically in regard to the increasing need for flexibility and competitive advantage deriving from services. The simultaneous adoption of the technical and commercial perspective is meant to offer interesting findings to both the scientific community and GNSS industry, creating synergies previously unexplored.

Adenine Enrichment at the Fourth CDS Residue in Bacterial Genes Is Consistent with Error Proofing for +1 Frameshifts.

Beyond selection for optimal protein functioning, coding sequences (CDSs) are under selection at the RNA and DNA levels. Here, we identify a possible signature of "dual-coding," namely extensive adenine (A) enrichment at bacterial CDS fourth sites. In 99.07% of studied bacterial genomes, fourth site A use is greater than expected given genomic A-starting codon use. Arguing for nucleotide level selection, A-starting serine and arginine second codons are heavily utilized when compared with their non-A starting synonyms. Several models have the ability to explain some of this trend. In part, A-enrichment likely reduces 5' mRNA stability, promoting translation initiation. However T/U, which may also reduce stability, is avoided. Further, +1 frameshifts on the initiating ATG encode a stop codon (TGA) provided A is the fourth residue, acting either as a frameshift "catch and destroy" or a frameshift stop and adjust mechanism and hence implicated in translation initiation. Consistent with both, genomes lacking TGA stop codons exhibit weaker fourth site A-enrichment. Sequences lacking a Shine-Dalgarno sequence and those without upstream leader genes, that may be more error prone during initiation, have greater utilization of A, again suggesting a role in initiation. The frameshift correction model is consistent with the notion that many genomic features are error-mitigation factors and provides the first evidence for site-specific out of frame stop codon selection. We conjecture that the NTG universal start codon may have evolved as a consequence of TGA being a stop codon and the ability of NTGA to rapidly terminate or adjust a ribosome.

MEMS IMU Error Mitigation Using Rotation Modulation Technique.

Micro-electro-mechanical-systems (MEMS) inertial measurement unit (IMU) outputs are corrupted by significant sensor errors. The navigation errors of a MEMS-based inertial navigation system will therefore accumulate very quickly over time. This requires aiding from other sensors such as Global Navigation Satellite Systems (GNSS). However, it will still remain a significant challenge in the presence of GNSS outages, which are typically in urban canopies. This paper proposed a rotary inertial navigation system (INS) to mitigate navigation errors caused by MEMS inertial sensor errors when external aiding information is not available. A rotary INS is an inertial navigator in which the IMU is installed on a rotation platform. Application of proper rotation schemes can effectively cancel and reduce sensor errors. A rotary INS has the potential to significantly increase the time period that INS can bridge GNSS outages and make MEMS IMU possible to maintain longer autonomous navigation performance when there is no external aiding. In this research, several IMU rotation schemes (rotation about X-, Y- and Z-axes) are analyzed to mitigate the navigation errors caused by MEMS IMU sensor errors. As the IMU rotation induces additional sensor errors, a calibration process is proposed to remove the induced errors. Tests are further conducted with two MEMS IMUs installed on a tri-axial rotation table to verify the error mitigation by IMU rotations.

Entropy-Based TOA Estimation and SVM-Based Ranging Error Mitigation in UWB Ranging Systems.

The major challenges for Ultra-wide Band (UWB) indoor ranging systems are the dense multipath and non-line-of-sight (NLOS) problems of the indoor environment. To precisely estimate the time of arrival (TOA) of the first path (FP) in such a poor environment, a novel approach of entropy-based TOA estimation and support vector machine (SVM) regression-based ranging error mitigation is proposed in this paper. The proposed method can estimate the TOA precisely by measuring the randomness of the received signals and mitigate the ranging error without the recognition of the channel conditions. The entropy is used to measure the randomness of the received signals and the FP can be determined by the decision of the sample which is followed by a great entropy decrease. The SVM regression is employed to perform the ranging-error mitigation by the modeling of the regressor between the characteristics of received signals and the ranging error. The presented numerical simulation results show that the proposed approach achieves significant performance improvements in the CM1 to CM4 channels of the IEEE 802.15.4a standard, as compared to conventional approaches.