EPJ Quantum Technology最新文献

Routing design is an important aspect in aiding the completion of the Quantum Processing Unit (QPU) layout design for large-scale superconducting quantum processors. One of the research focuses is how to generate reliable routing schemes within a short time. In this study, we propose a superconducting quantum processor auto-routing method for supporting scalable architecture, which is mainly implemented through the bidirectional A star algorithm, the backtracking algorithm, and the greedy strategy. By using this method, the number of crossovers and corners can be reduced while efficiently completing the processor routing. To verify the effectiveness of our method, we selected 5 types of qubit numbers for processor routing experiments. The experimental results show that compared to the improved A star algorithm of Qiskit Metal, our method reduces the average execution time by at least 43.61% and 41.68% in serial and parallel, respectively. Compared with four other routing algorithms, our method has a minimum average reduction of 10.63% and 1.21% in the number of crossovers and corners, respectively. In addition, our method supports the processor routing design of planar and flip-chip architectures, and can automatically process both airbridge and insulation types of crossovers. Therefore, our method can provide efficient and reliable automated routing design to assist the development of large-scale superconducting quantum processors.

In previous research, it has been argued that many of the student (mis-)conceptions of quantum concepts described in the literature as widespread among learners can be traced back to poorly developed (quantum) model perceptions that hinder the learning of quantum physics. In particular, it has been shown that the degrees of two cognitive dimensions, namely Functional Fidelity and Fidelity of Gestalt, in students’ thinking account for a substantial amount of the variance in students’ model perceptions in quantum physics and may therefore be useful for describing and understanding the (development of) students’ conceptions of quantum physics topics. So far, however, the cognitive dimensions Functional Fidelity and Fidelity of Gestalt have only been investigated in exploratory studies. In this article, we report the results of a confirmatory factor analysis of data collected from N = 179 secondary school students using an instrument adapted from the literature to assess learners’ perceptions of the photon model. The results of our study provide empirical evidence that the two-factor model of learners’ model perceptions in the quantum context is indeed a good fit to the data. Together with literature from science education research on students’ conceptual development, and taking into account earlier findings on Fidelity of Function and Gestalt Fidelity we derive a plausible description of students’ conceptual development in the context of quantum physics – leading to what we call the Fidelities-Model of Conceptual Development. We discuss this framework in the light of previous research and argue for its potential generalisability beyond the teaching and learning of quantum physics topics. The implications of our findings for both science education research and practice are presented.

Quantum cryptography is a central topic in the quantum technology field that is particularly important for secure communication. The training of qualified experts in this field is necessary for continuous development. However, the abstract and complex nature of quantum physics makes the topic difficult to understand. Augmented reality (AR) allows otherwise invisible abstract concepts to be visualized and enables interactive learning, offering significant potential for improving quantum physics education in university lab courses. In addition, personalized feedback on challenging concepts can facilitate learning, and large language models (LLMs) like ChatGPT can effectively deliver such feedback. This study combines these two aspects and explores the impact of an AR-based quantum cryptography experiment with integrated ChatGPT-based feedback on university students’ learning outcomes and cognitive processes. The study involved 21 groups (11 Group A; 10 Group B) of students in a physics laboratory course at a German university and used four open-ended questions to measure learning outcomes and gaze data as a learning process assessment. Statistical analysis was used to compare scores between feedback and non-feedback questions, and the effect of ChatGPT feedback on eye-tracking data was examined. The results show that ChatGPT feedback significantly improved learning outcomes and affected gaze data. While the feedback on conceptual questions tended to direct attention to the visualizations of the underlying model, the feedback on questions about experimental procedures increased visual attention to the real experimental materials. Overall, the results show that AI-based feedback draws visual attention towards task-relevant factors and increases learning performance in general.

A (mathfrak{C^{*}})-circuit, which was proposed in Asiacypt 2022 by Huang and Sun (Advances in cryptology – ASIACRYPT 2022, pp. 614–644, 2022), can directly perform calculations with the existing quantum states, thereby reducing the use of quantum resources in quantum logic synthesis. We theoretically prove how to convert a (mathfrak{C^{0}})-circuit into the corresponding (mathfrak{C^{*}})-circuit through two lemmas and one theorem. The first lemma proves the interchangeability of CNOT gates and NOT gates by using the equivalence of quantum circuits. The second lemma proves that adding CNOT gates to the front of a quantum circuit whose initial states are all (|0rangle )s will not change the output states of the circuit. The theorem is used to describe what kind of (mathfrak{C^{0}})-circuit can be transformed into (mathfrak{C^{*}})-circuit, and the correctness of this transformation is proved. Our work will provide a theoretical basis for converting (mathfrak{C^{0}})-circuit to (mathfrak{C^{*}})-circuit. Then applying the theoretical analysis results to the multiplication over (text{GF}(2^{8})), the constructed quantum circuit needs 27 Toffoli gates and 118 CNOT gates, which is 15 fewer Toffoli gates and 43 CNOT gates than the current best result. This shows that the method of constructing quantum circuits by using the conversion of (mathfrak{C^{0}})-circuit to (mathfrak{C^{*}})-circuit is very efficient.

This article introduces QScratch, a novel educational tool designed to introduce fundamental quantum concepts and principles. It is an extension of the high-level block-based visual programming language Scratch, developed by the MIT Media Lab. The quantum concepts taught are presented in a simple and illustrative, yet rigorous way. The selection of topics and their adaptation for this project has been made taking into account the huge complexity of the subject, developing specific intuitive blocks to model the quantum behaviours of superposition, entanglement and measurement. A pilot study carried out with a group of 68 students has demonstrated the validity of the software developed as a tool for introducing complex quantum physics concepts. Thus, the proposed tool complements the original Scratch tool, advancing in the construction of Science, Technology, Engineering and Mathematics (STEM) tools that facilitate the introduction of quantum concepts to everyone.

Precision quantum sensors using cold atom interferometers with long interrogation times are often limited by the ballistic expansion of atomic samples after release from traps, manifesting by means of laser beam wavefront uncertainties. In this study we utilize near-resonant light interacting with an ultracold atomic sample for collective-mode excitation of a ⁸⁷Rb Bose Einstein condensate (BEC) in a magnetic trap. The collective motion is initiated after abruptly modifying the atom-atom interaction energy by reduction of the BEC atom number density via photon scattering using the two-photon transition from (5S_{1/2}) to (5D_{5/2}). We show that the two-photon transition can induce matter-wave lensing of the atomic cloud with minimal center-of-mass perturbation providing an optimal ultra-cold atomic sample for atom-based quantum sensors such as quantum gravimeters and accelerometers.

In my active learning course on quantum mechanics, students build their knowledge by following the scientific process as outlined by the Investigative Science Learning Environment. In this course, open-ended questions on the effect of measurement (collapse) failed to elicit meaningful responses from students. Meaningful responses are crucial for the next steps of testing students’ ideas using hypothetico-deductive reasoning. I wanted to help the students in this process with a pictorial representation. To arrive at a pictorial representation that would have meaning for students, I first asked them to provide their analogies for a superposition state. A common suggestion was the mixture of colours, but other, more inventive analogies were also suggested. I developed a pictorial representation based on the colour analogy. I reformulated the questions on collapse using this representation and a more concretized formulation. The ability of students to meaningfully answer the questions increased to the point where it was possible to complete also the testing part of the process. In the article, I discuss the analogies that students suggested and what underlying ideas known from literature they could represent. I provide the derived representation, the reformulated questions and evidence of how this helped students articulate their answers and helped identify students’ productive ideas that they could not clearly articulate in words. This enabled students to arrive at conclusions about the effect of measurement following the scientific process. This study contributes to the literature by providing student-generated analogies, using a pictorial representation derived from student-generated analogies, and showing an example of an efficiently formulated question on a difficult topic that is able to elicit meaningful responses.

Blind millionaire (BM) problem is an extended version of the initial millionaire problem required to compare the sum of the participants’ secrets between different groups. As a new topic of quantum secure multiparty computing, existing protocols with some special entangled states may not be easily achieved in practice. This study proposes a non-entangled method of solving the quantum blind millionaire (QBM) problem with special d-level single-particle states for the first time. To protect the confidentiality of transmission secrets, this protocol exploits the property of randomly generated d-level single-particle states. Furthermore, simple shift operations are used to encode the respective secrets. Detailed security analysis demonstrates that this protocol is impervious to internal and external threats. The presented methods can not only be used to solve the blind millionaire problem but also be used as a basic module to solve other secure multiparty computing problems.

The present study examined student outcomes from a quantum information science and technology (QIST) summer outreach program for U.S. secondary students. The program focused on foundational principles and skills from classical physics, quantum physics, and quantum computing. Students’ attitudes towards QIST learning and careers were measured through a pretest/posttest research design. Exploratory factor analysis was utilized to identify latent attitudinal themes, followed by comparisons of means to measure changes in these factors and analysis of covariance to assess whether these changes were related to student demographics and prior academic coursework. Two latent themes were identified: (1) QIST career aspiration formation and self-concept, and (2) QIST interest and behavioral intentions. Results indicated that students improved their QIST career aspiration formation and self-concept with a medium to large effect size, yet their QIST interest and behavioral intentions were unchanged. These results were independent of student demographics (gender, ethnicity, grade level) and prior mathematics and computer science course enrollment; however, students who had previously taken chemistry and physics were more likely to improve QIST career aspiration formation and self-concept. Students also increased their intention to take four years of elective mathematics and science with a small effect size. These results suggest that early exposure to QIST principles, skills, and applications may increase students’ consideration of related careers and academic coursetaking plans; however, their interest in QIST may be independent of career aspiration formation. Further research is needed to measure attitudinal sub-domains that may be influenced by early QIST education and specific programmatic elements.