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The integration of artificial intelligence (AI) in educational measurement has revolutionized assessment methods, enabling automated scoring, rapid content analysis, and personalized feedback through machine learning and natural language processing. These advancements provide timely, consistent feedback and valuable insights into student performance, thereby enhancing the assessment experience. However, the deployment of AI in education also raises significant ethical concerns regarding validity, reliability, transparency, fairness, and equity. Issues such as algorithmic bias and the opacity of AI decision-making processes pose risks of perpetuating inequalities and affecting assessment outcomes. Responding to these concerns, various stakeholders, including educators, policymakers, and organizations, have developed guidelines to ensure ethical AI use in education. The National Council of Measurement in Education's Special Interest Group on AI in Measurement and Education (AIME) also focuses on establishing ethical standards and advancing research in this area. In this paper, a diverse group of AIME members examines the ethical implications of AI-powered tools in educational measurement, explores significant challenges such as automation bias and environmental impact, and proposes solutions to ensure AI's responsible and effective use in education., Comment: 59 pages, 3 figures, a joint work of the Special Interest Group on Artificial Intelligence in Measurement and Education (AIME) from the National Council of Measurement in Education (NCME)

In this work, we design and implement frequency-robust Molmer-Sorensen gates on a linear chain of trapped ions, using Gaussian amplitude modulation and a constant laser frequency. We select this frequency to balance the entanglement accumulation of all motional modes during the gate to produce a strong robustness to frequency error, even for long ion chains. We demonstrate this technique on a three-ion chain, achieving $<\,1\%$ reduction from peak fidelity over a $20\,$kHz range of frequency offset, and we analyze the performance of this gate design through numerical simulations on chains of two to 33 ions.

This study examined a naturalistic, districtwide implementation of an automated writing evaluation (AWE) software program called "MI Write" in elementary schools. We specifically examined the degree to which aspects of MI Write were implemented, teacher and student attitudes towards MI Write, and whether MI Write usage along with other predictors like demographics and writing self-efficacy explained variability in students' performance on a proximal and distal measure of writing performance. The participants included 1935 students in Grades 3-5 and 135 writing teachers from 14 elementary schools in a mid-Atlantic school district. Findings indicated that though MI Write was somewhat under-utilized, teachers and students held positive attitudes towards the AWE system. Usage of MI Write had a mixed and limited predictive effect on outcomes: The number of essays written had a small predictive effect on state test performance for Grades 3 and 5; gain on revision had a moderate predictive effect on posttest writing quality and a small predictive effect for Grade 5 state test performance. Students' average AWE scores showed consistently moderate to large predictive effects for all outcomes. Interpreted in light of the underlying architecture of MI Write, findings have implications for other school districts considering implementing AWE as well as the design of AWE systems intended to support the teaching and learning of writing. [This paper was published in "International Journal of Artificial Intelligence in Education" v31 p324-276 2021 (EJ1299797).]

Microfabricated surface ion traps are a principle component of many ion-based quantum information science platforms. The operational parameters of these devices are pushed to the edge of their physical capabilities as the experiments strive for increasing performance. When the applied radio-frequency (RF) voltage is increased too much, the devices can experience damaging electric discharge events known as RF breakdown. We introduce two novel techniques for in situ detection of RF breakdown, which we implemented while characterizing the breakdown threshold of surface ion traps produced at Sandia National Laboratories. In these traps, breakdown did not always occur immediately after increasing the RF voltage, but often minutes or even hours later. This result is surprising in the context of the suggested mechanisms for RF breakdown in vacuum. Additionally, the extent of visible damage caused by breakdown events increased with applied voltage. To minimize the probability for damage when RF power is first applied to a device, our results strongly suggest that the voltage should be ramped up over the course of several hours and monitored forbreakdown.

The present study leveraged advances in automated essay scoring (AES) technology to explore a proof of concept for a writing screener using the "Project Essay Grade" (PEG) program. First, the study investigated the extent to which an AES-scored multi-prompt writing screener accurately classified students as at risk of failing a Common Core-aligned English language arts state test. Second, the study explored whether a similar level of classification accuracy could be achieved with a more efficient form of the AES-screener with fewer writing prompts. Third, the classification accuracy of the AES-scored screeners was compared to that of screeners scored for word count. Students in Grades 3-5 (n = 185, 167, and 187, respectively) composed six essays in response to multiple writing-prompt screeners on six different randomly assigned topics, two essays in each of three different genres (narrative, informative, and persuasive). Receiver operating characteristic (ROC) curve analysis was used to assess classification accuracy and to identify multiple cut scores with associated sensitivity and specificity values, and positive and negative posttest probabilities. Results indicated that the AES-scored multi-prompt screener and screeners with fewer prompts yield acceptable classification accuracy, are efficient, and are more accurate than screeners scored for word count. Overall, results illustrate the viability of writing screening using AES. [This paper was published in "Journal of School Psychology" v82 p123-140 2020.]

Calculating the mean exit time (MET) for models of diffusion is a classical problem in statistical physics, with various applications in biophysics, economics and heat and mass transfer. While many exact results for MET are known for diffusion in simple geometries involving homogeneous materials, calculating MET for diffusion in realistic geometries involving heterogeneous materials is typically limited to repeated stochastic simulations or numerical solutions of the associated boundary value problem (BVP). In this work we derive exact solutions for the MET in irregular annular domains, including some applications where diffusion occurs in heterogenous media. These solutions are obtained by taking the exact results for MET in an annulus, and then constructing various perturbation solutions to account for the irregular geometries involved. These solutions, with a range of boundary conditions, are implemented symbolically and compare very well with averaged data from repeated stochastic simulations and with numerical solutions of the associated BVP. Software to implement the exact solutions is available at https://github.com/ProfMJSimpson/Exit_time., Comment: 18 pages, 6 figures, accepted version

The Quantum Scientific Computing Open User Testbed (QSCOUT) at Sandia National Laboratories is a trapped-ion qubit system designed to evaluate the potential of near-term quantum hardware in scientific computing applications for the US Department of Energy (DOE) and its Advanced Scientific Computing Research (ASCR) program. Similar to commercially available platforms, most of which are based on superconducting qubits, it offers quantum hardware that researchers can use to perform quantum algorithms, investigate noise properties unique to quantum systems, and test novel ideas that will be useful for larger and more powerful systems in the future. However, unlike most other quantum computing testbeds, QSCOUT uses trapped $^{171}$Yb$^{+}$ ions as the qubits, provides full connectivity between qubits, and allows both quantum circuit and low-level pulse control access to study new modes of programming and optimization. The purpose of this manuscript is to provide users and the general community with details of the QSCOUT hardware and its interface, enabling them to take maximum advantage of its capabilities., Comment: 39 pages, 35 figures. This work has been submitted to the IEEE for possible publication

Many problems in physics, biology, and economics depend upon the duration of time required for a diffusing particle to cross a boundary. As such, calculations of the distribution of first passage time, and in particular the mean first passage time, is an active area of research relevant to many disciplines. Exact results for the mean first passage time for diffusion on simple geometries, such as lines, discs and spheres, are well--known. In contrast, computational methods are often used to study the first passage time for diffusion on more realistic geometries where closed--form solutions of the governing elliptic boundary value problem are not available. Here, we develop a perturbation solution to calculate the mean first passage time on irregular domains formed by perturbing the boundary of a disc or an ellipse. Classical perturbation expansion solutions are then constructed using the exact solutions available on a disc and an ellipse. We apply the perturbation solutions to compute the mean first exit time on two naturally--occurring irregular domains: a map of Tasmania, an island state of Australia, and a map of Taiwan. Comparing the perturbation solutions with numerical solutions of the elliptic boundary value problem on these irregular domains confirms that we obtain a very accurate solution with a few terms in the series only. Matlab software to implement all calculations is available on GitHub., Comment: 31pages, 12 figures

We observe dynamical fermionization, where the momentum distribution of a Tonks-Girardeau (T-G) gas of strongly interacting bosons in 1D evolves from bosonic to fermionic after its axial confinement is removed. The asymptotic momentum distribution after expansion in 1D is the distribution of rapidities, which are the conserved quantities associated with many-body integrable systems. Rapidities have not previously been measured in any interacting many-body quantum system. Our measurements agree well with T-G gas theory. We also study momentum evolution after the trap depth is suddenly changed to a new non-zero value. We observe the predicted bosonic-fermionic oscillations and see deviations from the theory outside of the T-G gas limit.

SciPy is an open source scientific computing library for the Python programming language. SciPy 1.0 was released in late 2017, about 16 years after the original version 0.1 release. SciPy has become a de facto standard for leveraging scientific algorithms in the Python programming language, with more than 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories, and millions of downloads per year. This includes usage of SciPy in almost half of all machine learning projects on GitHub, and usage by high profile projects including LIGO gravitational wave analysis and creation of the first-ever image of a black hole (M87). The library includes functionality spanning clustering, Fourier transforms, integration, interpolation, file I/O, linear algebra, image processing, orthogonal distance regression, minimization algorithms, signal processing, sparse matrix handling, computational geometry, and statistics. In this work, we provide an overview of the capabilities and development practices of the SciPy library and highlight some recent technical developments., Comment: Article source data is available here: https://github.com/scipy/scipy-articles

We study the loss of atoms in quantum Newton's cradles (QNCs) with a range of average energies and transverse confinements. We find that the three-body collision rate in one-dimension is strongly energy dependent, as predicted by a strictly 1D theory. We adapt the theory to atoms in waveguides, then using detailed momentum measurements to infer all the collisions that occur, we compare the observed loss to the adapted theory and find that they agree well.