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A Streamlit-powered System for Simulating and Visualizing Qubit States

thirupathi

Published Sep 11, 2025• 0 citations
Publisher

Abstract

Abstract Quantum computing utilizes the concepts of quantum mechanics, including superposition and entanglement, to execute calculations that are impractical for traditional computers. Central to this approach is the qubit, a quantum equivalent of the traditional bit, capable of being in a superposition of states. Nonetheless, the conceptual essence of quantum states renders them hard to visualize and comprehend, particularly for students and professionals who are unfamiliar with the domain. To tackle this issue, we created an interactive qubit visualization tool using Streamlit, enabling real-time exploration of qubit behavior under quantum operations.The app enables users to control qubit states directly by modifying the real and imaginary components of probability amplitudes, guaranteeing the normalization of the state vector. It also incorporates a set of essential quantum gates, including Hadamard, Pauli-X, Pauli-Y, and Pauli-Z, as well as continuous rotation gates (Rx, Ry, Rz). In contrast to distinct button-driven functions, the rotation gates are implemented dynamically via angle sliders, enabling users to witness seamless, real-time updates to the qubit state. This provides an intuitive understanding of qubit evolution as it revolves around the Bloch sphere axes.The tool displays the outcomes in both numerical and graphical formats. Users are able to observe the quantum state vector, as well as the probabilities of obtaining |0⟩ and |1⟩, and visual depictions through probability bar charts and Bloch sphere visualizations. By providing a live, interactive setting, this platform connects the divide between mathematical theory and conceptual grasp of quantum mechanics. It functions as both a learning tool for students and a prototyping support for researchers, rendering quantum computation more approachable and captivating.

DOI
10.21203/rs.3.rs-7579530/v1

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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.
Quantum state tomography is a fundamental task in quantum computing, involving the reconstruction of an unknown quantum state from measurement outcomes. Although essential, it is typically introduced at the graduate level due to its reliance on advanced concepts such as the density matrix formalism, tensor product structures, and partial trace operations. This complexity often creates a barrier for students and early learners. In this work, we introduce QubitLens, an interactive visualization tool designed to make quantum state tomography more accessible and intuitive. QubitLens leverages maximum likelihood estimation (MLE), a classical statistical method, to estimate pure quantum states from projective measurement outcomes in theX,YX, YX,Y, andZZZbases. The tool emphasizes conceptual clarity through visual representations, including Bloch sphere plots of true and reconstructed qubit states, bar charts comparing parameter estimates, and fidelity gauges that quantify reconstruction accuracy. QubitLens offers a hands-on approach to learning quantum tomography without requiring deep prior knowledge of density matrices or optimization theory. The tool supports both single- and multi-qubit systems and is intended to bridge the gap between theory and practice in quantum computing education.