Miracle-dz/UniFAR-FTUs huggingface dataset:
High-Fidelity State Preparation, Quantum Control, and Readout of an Isotopically Enriched Silicon Spin Qubit

Quantum systems must be prepared, controlled, and measured with high fidelity in order to perform complex quantum algorithms. Control fidelities have greatly improved in silicon spin qubits, but state preparation and readout fidelities have generally been poor. By operating with low electron temperatures and employing high-bandwidth cryogenic amplifiers, we demonstrate single qubit readout visibilities>99%, exceeding the threshold for quantum error correction. In the same device, we achieve average single qubit control fidelities>99.95%. Our results show that silicon spin qubits can be operated with high overall operation fidelity.
Optimizing doping parameters of target to enhance direct-drive implosion

To enhance direct-drive implosion performance while keeping the risk of hydrodynamic instability at a low level, we have designed a procedure to optimize the parameters of the target doped with mid- or high-Z material. In the procedure, a one-dimensional implosion process is simulated, while the effect of high-dimensional instability on its implosion performance is simultaneously evaluated. To find the optimal doping parameters, the procedure is performed in the framework of a global optimization algorithm, where we have used particle swarm optimization in the current work. The opacity of mixture materials quickly obtained by using an interpolation method shows a good agreement with the data of TOPS, a widely-used doping program developed in the Los Alamos National Laboratory. To test the procedure, optimization has been carried out for the CH ablator in the double-cone ignition scheme (Zhang et al 2020 Phil. Trans. R. Soc. A 378 20200015) by doping with Si and Cl. Both one- and two-dimensional simulations show that doping with either Si or Cl can efficiently mitigate the Rayleigh–Taylor instability during the acceleration phase and does not result in significant degradation of the peak areal density. The results from one- and two-dimensional simulations qualitatively match each other, demonstrating the validity of our optimization procedure. This optimization process will be a valuable tool in assisting us in the design of the target and in furthering our understanding of direct-drive implosion physics.
Councils in Action: Automating the Curation of Municipal Governance Data for Research

Large scale comparative research into municipal governance is often prohibitively difficult due to a lack of high‐quality data. Recent advances in speech‐to‐text algorithms and natural language processing techniques has made it possible to more easily collect and analyze this type of data. In this paper, we introduce an open‐source platform, the Council Data Project (CDP), to curate novel datasets for research into municipal governance. The contribution of this work is two‐fold: 1. We demonstrate that CDP, as an infrastructure, can be used to assemble reliable comparative data across municipalities; 2. We provide exploratory analysis to show how CDP data can be used to gain insight into how municipal governments perform over time. We conclude by describing future directions for research on and with CDP such as the development of machine learning models for speaker annotation, outline generation, and named entity recognition to the linking of data for large‐scale comparative research.
A theoretical framework for the Hamiltonian of angular momentum optomechanical system

Photon carries linear momentum and angular momentum simultaneously. Within the light-matter interaction process, exchange of linear momentum results in optical forces, whereas exchange of angular momentum leads to optical torques. Use of optical forces (light pressure or damping) have been long and wide in quantum optomechanics, however, those of optical torque and optical angular momentum are not. Here we propose a theoretical framework based on optical angular momentum and optical torques to derive the Hamiltonians of cavity orbital and spin angular momentum optomechanical systems, respectively. Moreover, based on the method, we successfully obtain the Hamiltonian of the complex angular momentum optomechanical systems consisting of micro-cavity and several torsional oscillators, whose reflection coefficients are non-unit. Our results indicate the general applicability of our theoretical framework for the Hamiltonian of angular momentum optomechanical systems and extend the research scope of quantum optomechanics.
A Maximum Entropy Approach to Defining Cell State

The past few decades have seen great leaps in technologies to analyze cells and tissues. Omics methods in particular now allow us unprecedented access to their the molecular composition where the base-level resolution of transcripts and their numbers can be determined at a single cell level. Existing methods to analyze the resulting data make use of the count data while discarding the information present in the sequences themselves. In this paper we used a maximum entropy approach to develop a method to analyze RNA-seq data using both the sequence and count information. By mapping sequences to vectors of spins and defining an energy function on them, we were able to identify specific states in a biological process using mean energies and their associated Boltzmann-probabilities. This approach opens up new avenues in the quantitative analysis of -omics data and analysis of biological function.
Spatially resolving amplitude and phase of light with a reconfigurable photonic integrated circuit

Photonic integrated circuits (PICs) play a pivotal role in many applications. Particularly powerful are circuits based on meshes of reconfigurable Mach-Zehnder interferometers as they enable active processing of light. Various possibilities exist to get light into such circuits. Sampling an electromagnetic field distribution with a carefully designed free-space interface is one of them. Here, a reconfigurable PIC is used to optically sample and process free-space beams so as to implement a spatially resolving detector of amplitudes and phases. In order to perform measurements of this kind we develop and experimentally implement a versatile method for the calibration and operation of such integrated photonics based detectors. Our technique works in a wide parameter range, even when running the chip off the design wavelength. Amplitude, phase and polarization sensitive measurements are of enormous importance in modern science and technology, providing a vast range of applications for such detectors.
Design and Development of Rule-based open-domain Question-Answering System on SQuAD v2.0 Dataset

Human mind is the palace of curious questions that seek answers. Computational resolution of this challenge is possible through Natural Language Processing techniques. Statistical techniques like machine learning and deep learning require a lot of data to train and despite that they fail to tap into the nuances of language. Such systems usually perform best on close-domain datasets. We have proposed development of a rule-based open-domain question-answering system which is capable of answering questions of any domain from a corresponding context passage. We have used 1000 questions from SQuAD 2.0 dataset for testing the developed system and it gives satisfactory results. In this paper, we have described the structure of the developed system and have analyzed the performance.
You Are What You Write: Preserving Privacy in the Era of Large Language Models

Large scale adoption of large language models has introduced a new era of convenient knowledge transfer for a slew of natural language processing tasks. However, these models also run the risk of undermining user trust by exposing unwanted information about the data subjects, which may be extracted by a malicious party, e.g. through adversarial attacks. We present an empirical investigation into the extent of the personal information encoded into pre-trained representations by a range of popular models, and we show a positive correlation between the complexity of a model, the amount of data used in pre-training, and data leakage. In this paper, we present the first wide coverage evaluation and comparison of some of the most popular privacy-preserving algorithms, on a large, multi-lingual dataset on sentiment analysis annotated with demographic information (location, age and gender). The results show since larger and more complex models are more prone to leaking private information, use of privacy-preserving methods is highly desirable. We also find that highly privacy-preserving technologies like differential privacy (DP) can have serious model utility effects, which can be ameliorated using hybrid or metric-DP techniques.
Towards Arabic Sentence Simplification via Classification and Generative Approaches

This paper presents an attempt to build a Modern Standard Arabic (MSA) sentence-level simplification system. We experimented with sentence simplification using two approaches: (i) a classification approach leading to lexical simplification pipelines which use Arabic-BERT, a pre-trained contextualised model, as well as a model of fastText word embeddings; and (ii) a generative approach, a Seq2Seq technique by applying a multilingual Text-to-Text Transfer Transformer mT5. We developed our training corpus by aligning the original and simplified sentences from the internationally acclaimed Arabic novel Saaq al-Bambuu. We evaluate effectiveness of these methods by comparing the generated simple sentences to the target simple sentences using the BERTScore evaluation metric. The simple sentences produced by the mT5 model achieve P 0.72, R 0.68 and F-1 0.70 via BERTScore, while, combining Arabic-BERT and fastText achieves P 0.97, R 0.97 and F-1 0.97. In addition, we report a manual error analysis for these experiments.
Multicomponent imaging of the Fermi gamma-ray sky in the spatio-spectral domain

We perform two distinct spatio-spectral reconstructions of the gamma-ray sky in the range of 0.56-316 GeV based on Fermi Large Area Telescope (LAT) data. Both describe the sky brightness to be composed of a diffuse-emission and a point-source component. The first model requires minimal assumptions and provides a template-free reconstruction as a reference. It makes use of spatial and spectral correlations to distinguish between the different components. The second model is physics-informed and further differentiates between diffuse emission of hadronic and leptonic origin. For this, we assume parametric, but spatially varying energy spectra to distinguish between the processes and use thermal Galactic dust observations to indicate the preferred sites of hadronic interactions. To account for instrumental effects we model the point-spread, the energy dispersion, and the exposure of the telescope throughout the observation. The reconstruction problem is formulated as a Bayesian inference task, that is solved by variational inference. We show decompositions of the Gamma-ray flux into diffuse and point-like emissions, and of the diffuse emissions into multiple physically motivated components. The diffuse decomposition provides an unprecedented view of the Galactic leptonic diffuse emission. It shows the Fermi bubbles and their spectral variations in high fidelity and other areas exhibiting strong cosmic ray electron contents, such as a thick disk in the inner Galaxy and outflow regions. Furthermore, we report a hard spectrum gamma ray arc in the northern outer bubble co-spatial with the reported X-ray arc by the eROSITA collaboration. All our spatio-spectral sky reconstructions and their uncertainty quantification are publicly available.
A Detection of H2 in a High-velocity Cloud toward the Large Magellanic Cloud

This work presents a new detection of H2 absorption arising in a high-velocity cloud associated with either the Milky Way or the Large Magellanic Cloud (LMC). The absorber was found in an archival Far Ultraviolet Spectroscopic Explorer spectrum of the LMC star Sk-70°32. This is the fifth well-characterized H2 absorber to be found in the Milky Way’s halo and the second such absorber outside the Magellanic Stream and Bridge. The absorber has a local standard of rest central velocity of +140 km s−1 and a H2 column density of 1017.5 cm−2. It is most likely part of a cool and relatively dense inclusion (T ≈ 75 K, n H ∼ 100 cm−3) in a warmer and more diffuse halo cloud. This halo cloud may be part of a still-rising Milky Way Galactic fountain flow or an outflow from the Large Magellanic Cloud.
LAMNER: Code Comment Generation Using Character Language Model and Named Entity Recognition

Code comment generation is the task of generating a high-level natural language description for a given code method/function. Although researchers have been studying multiple ways to generate code comments automatically, previous work mainly considers representing a code token in its entirety semantics form only (e.g., a language model is used to learn the semantics of a code token), and additional code properties such as the tree structure of a code are included as an auxiliary input to the model. There are two limitations: 1) Learning the code token in its entirety form may not be able to capture information succinctly in source code, and 2) The code token does not contain additional syntactic information, inherently important in programming languages. In this paper, we present LAnguage Model and Named Entity Recognition (LAMNER), a code comment generator capable of en-coding code constructs effectively and capturing the structural property of a code token. A character-level language model is used to learn the semantic representation to encode a code token. For the structural property of a token, a Named Entity Recognition model is trained to learn the different types of code tokens. These representations are then fed into an encoder-decoder architecture to generate code comments. We evaluate the generated comments from LAM-NER and other baselines on a popular Java dataset with four com-monly used metrics. Our results show that LAMNER is effective and improves over the best baseline model in BLEU-1, BLEU-2, BLEU-3, BLEU-4, ROUGE-L, METEOR, and CIDEr by 14.34%, 18.98%,21.55%, 23.00%, 10.52%, 1.44%, and 25.86%, respectively. Additionally, we fused LAMNER's code representation with the baseline models, and the fused models consistently showed improvement over the non-fused models. The human evaluation further shows that LAMNER produces high-quality code comments.
The Population of Compact Radio Sources in M17

We present a catalog of radio sources of the M17 region based on deep X-band radio observations centered at 10 GHz obtained with the Jansky Very Large Array in the A configuration. We detect a total of 194 radio sources, 12 of them extended and 182 compact. We find that a significant fraction (at least 40% in our catalog) have suspected gyrosynchrotron emission associated with stellar coronal emission. By comparing the radio luminosities of our sources with their X-ray counterparts, when available, we find that they are underluminous in X-rays with respect to the Güdel–Benz relation, but a correlation with a similar slope is obtained provided that only sources with evident nonthermal nature are selected from the sample compiled for the Orion Nebula Cluster (ONC) and M17. The comparison of M17 with the ONC and NGC 6334D-F leads to a similar luminosity function for the three regions, at least for the more luminous sources. However, the radio sources in M17 are three times more numerous compared to the other regions at a given luminosity and their spatial distribution differs from that of Orion. Moreover, an arc-shaped structure of 40″ in extent is observed in our map, identified previously as an ionizing front, with the cometary hypercompact source UC1 at its focus. Archival 1 mm ALMA data reveals compact emission coincident with the radio wavelength peak, possibly associated with a protostellar disk of the massive star exciting UC1.
Auxiliary Loss Reweighting for Image Inpainting

—Image Inpainting is a task that aims to ﬁll in missing regions of corrupted images with plausible contents. Recent inpainting methods have introduced perceptual and style losses as auxiliary losses to guide the learning of inpainting generators. Perceptual and style losses help improve the perceptual quality of inpainted results by supervising deep features of generated regions. However, two challenges have emerged with the usage of perceptual and style losses: (i) the time-consuming grid search is required to decide weights for perceptual and style losses to properly perform, and (ii) loss terms with different auxiliary abilities are equally weighted by perceptual and style losses. To meet these two challenges, we propose a novel framework that independently weights auxiliary loss terms and adaptively adjusts their weights within a single training process, without a time-consuming grid search. Speciﬁcally, to release the auxiliary potential of perceptual and style losses, we propose two auxiliary losses, Tunable Perceptual Loss (TPL) and Tunable Style Loss (TSL) by using different tunable weights to consider the contributions of different loss terms. TPL and TSL are supersets of perceptual and style losses and release the auxiliary potential of standard perceptual and style losses. We further propose the Adaptive Auxiliary Loss (AAL) algorithm, which efﬁciently reweights TPL and TSL in a single training process. AAL is based on the principle that the best auxiliary weights would lead to the most improvement in inpainting performance. We conduct experiments on publically available datasets and ﬁnd that our framework helps current SOTA methods achieve better results.
ns-3 and 5G-LENA Extensions to Support Dual-Polarized MIMO

MIMO spatial multiplexing is an essential feature to increase the communication data rates in current and future cellular systems. Currently, the ns-3 lte module leverages an abstraction model for 2x2 MIMO with spatial multiplexing of two streams; while mmwave and nr modules were lacking the spatial multiplexing option until this work since the ns-3 models were not supporting the usage of multiple antennas for spatial multiplexing. In this paper, we propose, implement, and evaluate models for ns-3 and the nr module to enable Dual-Polarized MIMO (DP-MIMO). The proposed extension for the ns-3 supports multiple antennas for DP-MIMO with spatial multiplexing of two streams and can be used by any ns-3 module that is compatible with the ns-3 antenna array-based models, such as nr and mmwave modules. We leverage this ns-3 extension to model DP-MIMO by exploiting dual-polarized antennas and their orthogonality under line-of-sight conditions, as it happens at high-frequency bands, to send the two data streams. The proposed model does not rely on abstraction, as the MIMO model in the ns-3 lte module, and can thus model more realistically the propagation differences of the two streams, correlation, inter-stream interference, and allows the design and evaluation of the rank adaptation algorithms. Additionally, we propose and evaluate an adaptive rank adaptation scheme and compare it with a fixed scheme. The developed DP-MIMO spatial multiplexing models for the ns-3 simulator and the nr module are openly available.
ANALYSIS OF THE CHARACTERISTICS OF A PILOT IN THE AIRCRAFT FLIGHT

The contribution represents an attempt to analyze the properties of human flight in the aircraft. The approach is shown to create a replacement model the behaviour of humans - pilot in the creation of a replacement model in terms of automatic control. The history has not much information on how to access the analysis features of humans in terms of automatic control. Simulation of "response" to the human impulse input is an essential building block in the design of circuit auto flight aircraft. Particular attention is paid simulations group pilot - aircraft in curbing the fast oscillations aircraft.
Estimating Intraoperative Neurophysiological Monitoring Rates for Anterior Cervical Discectomy and Fusion: Are Diagnostic or Procedural Codes Accurate?

Background The utility of intraoperative neurophysiological monitoring (IONM) is well established for some spine surgeries (eg, intramedullary tumor resection, scoliosis deformity correction), but its benefit for most degenerative spine surgery, including anterior cervical discectomy and fusion (ACDF), remains debated. National datasets provide “big data” approaches to study the impact of IONM on spine surgery outcomes; however, if administrative coding in these datasets misrepresents actual IONM usage, conclusions will be unreliable. The objective of this study was to compare estimated rates (administrative coding) to actual rates (chart review) of IONM for ACDF at our institution and extrapolate findings to estimated rates from 2 national datasets. Methods Patients were included from 3 administrative coding databases: the authors’ single institution database, the Nationwide Inpatient Sample (NIS), and the National Surgical Quality Improvement Program (NSQIP). Estimated and actual institutional rates of IONM during ACDF were determined by administrative codes (International Classification of Diseases [ICD] or Current Procedural Terminology [CPT]) and chart review, respectively. National rates of IONM during ACDF were estimated using the NIS and NSQIP datasets. Results Estimated institutional rates of IONM for ACDF were much higher with CPT than ICD coding (73.2% vs 16.5% in 2019). CPT coding for IONM better approximated actual IONM usage at our institution (74.6% in 2019). Estimated IONM utilization rates for ACDF in national datasets varied widely: 0.76% in CPT-based NSQIP and 18.4% in ICD-based NIS. Conclusions ICD coding underestimated IONM usage during ACDF at our institution, whereas CPT coding was more accurate. Unfortunately, the CPT-based NSQIP is nearly devoid of IONM codes, as it has not been a collection focus of that surgical registry. ICD-based datasets, such as the NIS, likely fail to accurately capture IONM usage. Multicenter and/or national datasets with accurate IONM utilization data are needed to inform surgeons, insurers, and guideline authors on whether IONM has benefit for various spine surgery types. Level of Evidence 4. Clinical Relevance Currently available national databases based on administrative codes do not accurately reflect IONM usage.
Molecular Characteristics and Genetic Diversity of Fasciola Hepatica from Sheep in Xinjiang, China

Abstract Introduction Fasciola hepatica is a trematode infecting ruminants worldwide and occasionally affecting other animal species, including humans. It causes significant economic losses. Geographic distribution and patterns of infection must be considered before control and management measures are developed for this parasite. DNA molecular markers are useful for the identification of flukes and elucidation of their genetic evolution. Therefore, the population structure of F. hepatica was studied using this method in sheep in Xinjiang, China. Material and Methods The molecular characteristics, genetic relationships within the population and dispersal patterns of F. hepatica isolates were analysed based on the cox1 and nad1 genes. The population structure of F. hepatica from three regions of Xinjiang was explored and a neutrality test was conducted. Results The cox1 and nad1 genes have 21 and 42 variable sites, respectively, which can be classified into 34 and 33 haplotypes. Median-joining network and phylogenetic tree analyses showed that there was no significant variation in F. hepatica isolates between the three geographical regions. Analysis of variance revealed that the genetic variation of F. hepatica was mainly present within the populations. The neutrality test indicated that the populations were relatively stable but the Hami population may have undergone short-term expansion. Conclusion This study revealed for the first time the molecular characteristics, genetic diversity and dispersal patterns of F. hepatica isolates from sheep in Xinjiang, thus providing new insights into the genetic variation and haplotype diversity of F. hepatica from indigenous sheep.