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Computer Applications in Engineering Education

Microcontroller‐Driven Photonic Toolkit for Quantum Computing: A Hardware‐in‐the‐Loop Approach to Engineering Pedagogy

R. R. Sreeja, J. Kamala, S. Akshai, Sahaana Kanagesan

Published May 1, 2026• 0 citations
Publisher

Abstract

ABSTRACT Traditional pedagogical methods for quantum computing often struggle to bridge the gap between abstract mathematical models and physical intuition. This paper presents the development and evaluation of a modular, computer‐aided hardware training kit designed to emulate quantum states and gate operations through an integrated digital‐photonic interface. The system leverages a microcontroller‐driven architecture to control a Photonic Qubit Generator, utilizing 650 nm laser diodes and polarizers to represent polarization‐encoded states (|0〉, |1〉, |+〉, |−〉). By integrating hardware switches and embedded gate logic, the kit enables real‐time interaction with qubits, single‐qubit (Pauli X, Y, Z, Hadamard, Phase S) gates, and multi‐qubit (CNOT, Toffoli) gates operations. Unlike purely theoretical simulations, this hardware‐in‐the‐loop approach provides tactile and visual feedback via light emitting diode/laser indicators, reinforcing the connection between digital control and quantum behavior. A pilot study involving 62 undergraduate and postgraduate engineering students was conducted to assess the kit's impact on computational thinking and conceptual comprehension. Quantitative and qualitative results indicate a significant improvement in student engagement and their ability to map theoretical gate logic to functional hardware outputs. The study concludes that this cost‐effective, scalable platform serves as a vital computer application for engineering classrooms, democratizing access to complex quantum science through interactive, hands‐on experimentation.

DOI
10.1002/cae.70212

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ABSTRACT Traditional pedagogical methods for quantum computing often struggle to bridge the gap between abstract mathematical models and physical intuition. This paper presents the development and evaluation of a modular, computer‐aided hardware training kit designed to emulate quantum states and gate operations through an integrated digital‐photonic interface. The system leverages a microcontroller‐driven architecture to control a Photonic Qubit Generator, utilizing 650 nm laser diodes and polarizers to represent polarization‐encoded states (|0〉, |1〉, |+〉, |−〉). By integrating hardware switches and embedded gate logic, the kit enables real‐time interaction with qubits, single‐qubit (Pauli X, Y, Z, Hadamard, Phase S) gates, and multi‐qubit (CNOT, Toffoli) gates operations. Unlike purely theoretical simulations, this hardware‐in‐the‐loop approach provides tactile and visual feedback via light emitting diode/laser indicators, reinforcing the connection between digital control and quantum behavior. A pilot study involving 62 undergraduate and postgraduate engineering students was conducted to assess the kit's impact on computational thinking and conceptual comprehension. Quantitative and qualitative results indicate a significant improvement in student engagement and their ability to map theoretical gate logic to functional hardware outputs. The study concludes that this cost‐effective, scalable platform serves as a vital computer application for engineering classrooms, democratizing access to complex quantum science through interactive, hands‐on experimentation.
The paper discusses the design and modeling of a simple and illustrative hardware kit for teaching the basics of quantum cryptography to engineering students. The novel solution differs from those already on the market in that it is focused on familiarising trainees with the physical principles of quantum key distribution, as well as with the basics of mathematical formalism in quantum mechanics. This is achieved by using a minimally sufficient set of optical elements with a simple mathematical description in the Jones formalism. This composition of the kit is targeted mostly at engineering students and does not require advanced training in physics as a prerequisite. The configurable architecture of the hardware educational kit contributes to the deeper involvement of students. By independently changing the modular configuration of the system, students can conduct experiments that were not directly provided by the developers. For instance, students can assess the impact of choosing the basic settings of phase retarders on the course of a man-in-the-middle attack. The proposed amount of mathematical and informational support, as well as ready-made formal models, is sufficient to reasonably put forward hypotheses for experimental verification and interpret the obtained empirical data. At this moment, the hardware kit is being replicated, distributed and successfully applied at universities and companies in the communications industry. The accumulated experience of educational use testifies to the high efficiency of the kit as a tool for basic QKD training for people without prior knowledge of quantum mechanics. A discrete event model simulating the operation of the hardware kit is implemented in the non-commercial modeling software CPN Tools and is openly distributed.
Quantum computing is an interdisciplinary field that spans physics, mathematics, computer engineering, and computer science. Teaching quantum computing effectively within a constrained timeframe presents a challenge, particularly for engineering students with diverse academic backgrounds. This paper presents an approach to integrating quantum computing into a broader course on Technologies of Computing Systems (TCS) through a dedicated two-week module. The course structure combines lectures, interactive problem-solving, lab exercises, and a hands-on project to ensure an engaging and practical learning experience. The curriculum covers fundamental quantum computing principles, quantum gates, circuits, algorithms, and quantum technology. Assessment includes project work, exams, and student feedback, demonstrating increased engagement and comprehension. The results indicate that this quantum computing module successfully bridges the gap between classical and quantum paradigms, fostering student interest and understanding within a short period.
This paper presents an engineering design framework for integrating Variational Quantum Circuits (VQCs) into industrial control systems via real-time quantum emulation on embedded hardware. In this work, we present a novel framework for fully embedded real-time quantum machine learning (QML), in which a four-qubit, four-layer VQC is both emulated and trained in situ on an FPGA-based embedded platform (dSPACE MicroLabBox 1202). The system achieves deterministic microsecond-scale response at a closed-loop frequency of 100 kHz, enabling its application in latency-critical control tasks. We demonstrate the feasibility of online VQC training within this architecture by approximating nonlinear functions in real time, thereby validating the potential of embedded QML for advanced signal processing and control applications. This approach provides a scalable and practical path toward real-time Quantum Reinforcement Learning (QRL) and other quantum-enhanced embedded controllers. The results validate the feasibility of real-time quantum emulation and establish a structured engineering design methodology for implementing trainable quantum machine learning (QML) models on embedded platforms, thereby enabling the development of deployable quantum-enhanced controllers.
As quantum computing transitions from theoretical physics to engineering applications, there is a growing need for accessible simulation tools that bridge the gap between abstract linear algebra and practical implementation. While text-based frameworks (like Qiskit or Cirq) are standard, they often present a steep learning curve for students and engineers accustomed to graphical system design. This paper introduces QuVI (Quantum Virtual Instrument), an open-source quantum circuit toolkit developed natively within the NI LabVIEW environment. Moving beyond initial proof-of-concept models, QuVI establishes a robust framework that leverages LabVIEW's "dataflow" paradigm, in which wires represent data and nodes represent operations, to provide an intuitive, visual analog to standard quantum circuit notation while enabling the seamless integration of classical control structures like loops and conditionals. The toolkit's capabilities are demonstrated by constructing and visualizing fundamental quantum algorithms and verifying results against theoretical predictions. By translating "Block Diagrams" directly into quantum state evolutions ("Bloch Spheres"), QuVI offers educators and researchers a powerful platform for prototyping quantum logic without leaving the graphical engineering workspace.
The evolution of quantum computing has created a pressing need to rethink how we introduce fundamental concepts in quantum mechanics and computation in education. Traditional classroom methods, based on classical teaching and theoretical ideas, often fail to effectively convey the unpredictable and strange nature of quantum systems. Simulating quantum environments offers a powerful strategy. It makes quantum principles more accessible, interactive, and engaging for learners at various educational levels. These simulated platforms, which include visual circuit builders and programmable virtual quantum computers, allow students to explore qubits, entanglement, and quantum gates without needing costly or experimental quantum hardware. This chapter examines the role of simulated quantum environments in reshaping STEM education, particularly in secondary and higher education. It starts by discussing the theoretical challenges of teaching quantum concepts, pointing out the limitations of classical analogies and rote calculations in promoting real understanding. Simulation tools help address these issues by providing hands-on, inquiry-based learning.
Quantum computing education requires students to move beyond classical programming intuitions related to state, determinism, and debugging, and to develop reasoning skills grounded in probability, measurement, and interference. This paper reports on the design and delivery of a combined undergraduate and graduate course at Louisiana State University that employed a lab-integrated learning model to support conceptual change and progressive understanding. The course paired lectures with weekly programming labs that served as environments for experimentation and reflection. These labs enabled students to confront misconceptions and refine their mental models through direct observation and evidence-based reasoning. Instruction began with Quantum Without Linear Algebra (QWLA), which introduced core concepts such as superposition and entanglement through intuitive, dictionary representations. The course then transitioned to IBM Qiskit, which provided a professional framework for circuit design, noise simulation, and algorithm implementation. Analysis of student work and feedback indicated that hands-on experimentation improved confidence, conceptual clarity, and fluency across representations. At the same time, it revealed persistent challenges in debugging, reasoning about measurement, and understanding probabilistic outcomes. This paper presents the course structure, instructional strategies, and lessons learned, and argues that lab-integrated learning offers an effective and accessible approach to teaching quantum computing in computer science education.