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Noise is both ubiquitous and generally deleterious in settings where precision is required. This is especially true in the quantum technology sector where system utility typically decays rapidly under its influence. Understanding the noise in quantum devices is thus a prerequisite for efficient strategies to mitigate or even eliminate its harmful effects. However, this requires resources that are often prohibitive, such that the typically used noise models rely on simplifications that sometimes depart from experimental reality. Here we derive a compact microscopic error model for single-qubit gates that only requires a single experimental input—the noise power spectral density. Our model goes beyond standard depolarizing or Pauli-twirled noise models, explicitly including non-Clifford and non-Markovian contributions to the dynamical error map. We gauge our predictions for experimentally relevant metrics against established characterization techniques run on a trapped-ion quantum computer. In particular, we find that experimental estimates of average gate errors measured through randomized benchmarking and reconstructed via quantum process tomography are tightly lower-bounded by our analytical estimates, while the depolarizing model overestimates the gate error. Our noise modeling including non-Markovian contributions can be readily applied to established frameworks such as dynamical decoupling and dynamically corrected gates, or to provide more realistic thresholds for quantum error correction.

In recent decades, liver tumors have been considered as the leading and most serious causes of death worldwide. One of the most well-known Computer Vision (CV) is medical imaging (MI) which supports healthcare professionals in the early detection and diagnosis of liver tumors. To diagnose patients, professionals read hundreds of images using manual or Computed Tomography (CT). Consequently, a completely automated technique that makes use of CT scans is a common and extensively utilized imaging modality which requires an early diagnosis and identification of tumor. To overcome the above-stated issues, Mayfly Optimization (MFO) and Fully Convolutional Networks (FCN) are proposed for the classification of liver tumors. Image resizing approach is used for preprocessing and Adding Inception Module-UNet (AIM-UNet) is used for image segmentation. The suggested MFO algorithm is used for feature selection which takes the input from the extracted features using ResNet50. FCN is used as a classifier to classify liver tumors. In comparison to the existing techniques like EfficientNetB0 and InceptionV3, the proposed FCN achieves commendable accuracies of 99.5% and 99.98%, respectively, on the LiTS and CHAOS datasets. [ABSTRACT FROM AUTHOR]

We present a novel approach to high bandwidth laser frequency modulation. A lithium niobate chip is used as an intracavity electro-optic modulator in a tunable cateye external cavity diode laser. The modulator is conveniently integrated with the cateye output coupler, providing a unique approach to high bandwidth frequency stabilization and linewidth narrowing. The intracavity modulator feedback was successfully operated below 1 V and achieved superior frequency noise suppression compared to conventional feedback through diode injection current modulation. A closed loop bandwidth of 1.8 MHz was demonstrated, and the laser linewidth reduced to around 1 Hz as measured by the heterodyne measurement.

The information about the algae of Lake Azas, a part of the water area of which belongs to the Azas State Nature Reserve, is reported for the first time. One hundred seventy one species and intraspecific taxa were identified referred to 72 genera, 50 families, and 8 divisions. The basis of the algal flora was found to consist of diatoms and blue-green algae. Fourteen dominants were identified, 9 of which belong to the Bacillariophyta microalgae. Ecological and geographical studies of the algae in the reserved part of the lake were carried out. The algal flora of the water body was found to be represented by benthic species with a prevalence of indifferent forms in relation to halobility and active reaction of the environment. One hundred twenty three species, indicators of water saprobity, were identified in all the biotopes studied. The predominance of betamezosaprobionts and oligosaprobionts was detected. Geographically, cosmopolitan and boreal species dominated. [ABSTRACT FROM AUTHOR]

Second generation quantum technologies aim to outperform classical alternatives by utilizing engineered quantum systems. Maintaining the coherence required to enable any quantum advantage requires detailed knowledge and control over the noise that the hosting system is subjected to. Characterizing noise processes via their power spectral density is routinely done throughout science and technology and can be a demanding task. Determining the phase noise power spectrum in leading quantum technology platforms, for example, can be either outside the reach of many phase noise analyzers or prohibitively expensive. In this work, we present and characterize a low-complexity, low-cost optical phase noise analyzer based on the short-delay optical self-heterodyne measurements for quantum technology applications. Using this setup, we compare two ≈1 Hz linewidth ultra-stable oscillators near 729 nm. Their measurements are used as a baseline to determine and discuss the noise floor achieved in this measurement apparatus with a focus on limitations and their tradeoffs. The achieved noise floor in this all-stock-component implementation of an optical phase noise analyzer compares favorably with commercial offerings. This setup can be used particularly without a more stable reference or operational quantum system as a sensor as would be the case for many component manufacturers. [ABSTRACT FROM AUTHOR]

So far, most of the research on classification algorithms in machine learning has been focused only on improving the training speed and further improving the technical performance evaluation measures of the constructed models. There is no focus on improving the runtime efficiency of the classification phase which is much required in some critical applications. In this paper, we are considering the computation complexity of a decision tree’s classification phase as the major criterion. A novel approach has been proposed to predict the class label of an unseen instance using the decision tree in less time than the regular tree traversal method. In the proposed method, the constructed decision tree is represented in the form of arrays. Then, the process of finding the class label is carried out by performing the bitwise operations between the elements of the arrays and test instance. Empirical results on various UCI data sets proved that the proposed method outperforms the standard method and five other benchmark classifiers and its classification is at least four times faster than the regular method.

Introduction. The paper considers the results of surveys taking into account the efficiency increase of passenger traffic in a small town. The need to regulate the work of carriers of various ownership forms, taking into account the characteristics of urban routes, determines the relevance of the research in this area. Therefore, the purpose of the survey is to clarify the total size of the movement of the zones and the city as a whole for the further projects’ development of the road network planning and for the passenger traffic development.Materials and methods. The paper considers alternatives to passenger surveys, i.e. application of the most optimal variants of the transportation plan. The characteristics of the route and load on the routes of Kyzyl are also illustrated. The author uses the methodology of surveying the population transport needs in a small town, in particular, the counting of passengers.Results. As a result, the author conducts the survey of passenger traffic, taking into account the city specific. The characteristics of the route and the load on the routes of Kyzyl are studied. It is important to use the methodology of the transport needs and transport services for population in a small town.Discussion and conclusions. On the basis of the conducted surveys of passenger traffic, the average hourly volume of transportation on routes is revealed and the unevenness of traffic volume is calculated.

"The Great Wave: The Era of Radical Disruption and the Rise of the Outsider" by Michiko Kakutani explores the concept of swift and unpredictable change in the world. The author argues that the current era is characterized by volatility, uncertainty, complexity, and ambiguity, and compares it to historical periods such as the Cold War and the Second World War. However, some readers may find the comparisons oversimplified and lacking in detail. The book also delves into the impact of technology and the role of outsiders in shaping modern culture. While the author's perspective leans towards a chosen political option, readers should approach the book as a post-truth narrative and consider it in the context of understanding political discourse. [Extracted from the article]

Quantum information processing is steadily progressing from a purely academic discipline towards applications throughout science and industry. Transitioning from lab-based, proof-of-concept experiments to robust, integrated realizations of quantum information processing hardware is an important step in this process. However, the nature of traditional laboratory setups does not offer itself readily to scaling up system sizes or allow for applications outside of laboratory-grade environments. This transition requires overcoming challenges in engineering and integration without sacrificing the state-of-the-art performance of laboratory implementations. Here, we present a 19-inch rack quantum computing demonstrator based on ^{40}Ca^{+} optical qubits in a linear Paul trap to address many of these challenges. We outline the mechanical, optical, and electrical subsystems. Furthermore, we describe the automation and remote access components of the quantum computing stack. We conclude by describing characterization measurements relevant to quantum computing including site-resolved single-qubit interactions, and entangling operations mediated by the Mølmer-Sørensen interaction delivered via two distinct addressing approaches. Using this setup, we produce maximally entangled Greenberger-Horne-Zeilinger states with up to 24 ions without the use of postselection or error mitigation techniques; on par with well-established conventional laboratory setups.