Fathoming out quantum state space is a challenging endeavor due to its exponentially growing dimensionality. At the expense of being bound in its expressiveness, the discrete and finite subspace of graph states is easier to investigate via a pictorial framework accompanied with a theoretical toolkit from the stabilizer formalism. Analyzing hand-drawn graphs is a tedious and time-consuming task and imposes limitations to the problem sizes that can be addressed. Similarly, algorithmic studies using adjacency matrices alone lack the benefit of a visual representation of the states. We argue that applying visual analytics to investigate graph states can be advantageous. To this end, we introduce GRAPHSTATEVIS, a web-based application for the visual analysis of qubit graph states and their stabilizer groups. Our tool facilitates the interactive construction of a graph through multiple components supported by linking and brushing. The user can explore graph-state-specific properties, including the Pauli-weight distribution of its stabilizer operators and noise thresholds for entanglement criteria. We propose a use case in the context of near-term quantum algorithms to illustrate the capabilities of our prototype. We provide access to GRAPHSTATEVIS as an open-source project and invite the broader quantum computing and engineering communities to take advantage of this tool and further boost its development.
Fathoming out quantum state space is a challenging endeavor due to its exponentially growing dimensionality. At the expense of being bound in its expressiveness, the discrete and finite subspace of graph states is easier to investigate via a pictorial framework accompanied with a theoretical toolkit from the stabilizer formalism. Analyzing hand-drawn graphs is a tedious and time-consuming task and imposes limitations to the problem sizes that can be addressed. Similarly, algorithmic studies using adjacency matrices alone lack the benefit of a visual representation of the states. We argue that applying visual analytics to investigate graph states can be advantageous. To this end, we introduce GRAPHSTATEVIS, a web-based application for the visual analysis of qubit graph states and their stabilizer groups. Our tool facilitates the interactive construction of a graph through multiple components supported by linking and brushing. The user can explore graph-state-specific properties, including the Pauli-weight distribution of its stabilizer operators and noise thresholds for entanglement criteria. We propose a use case in the context of near-term quantum algorithms to illustrate the capabilities of our prototype. We provide access to GRAPHSTATEVIS as an open-source project and invite the broader quantum computing and engineering communities to take advantage of this tool and further boost its development.
Abstract The objective of Quantum State Verification (QSV) is to evaluate whether an unknown quantum state is sufficiently similar to a predetermined target state at a certain confidence level. The required number of identical and independent copies, N, of an unknown state for such a task is inversely proportional to the spectral gap of a verification operator. Stabilizer states form a foundational class of quantum states, extensively utilized in quantum computing. Defined through a group of stabilizer operators constructed from Pauli matrices in qubit systems, their structural properties not only simplify the mathematical representation and simulation of quantum states but also make them particularly suitable for verification protocols that rely on local measurements. Restricting the verification operator to be those that can be achieved by local measurements, previous researches had determined an upper bound for the spectral gap to be 2/3 in the cases of qubit stabilizer states. In this research, we show a similar upper bound of d/(d+1) in the cases of graph states of d-level systems by a technique from [1] but adapted to d-level graph states. In particular, we show that d-level graph states are maximally entangled across any bipartition of the graph, which allows us to reduce the problem to the case of a bipartite maximally entangled d-level systems for which the maximal spectral gap is known.
Advanced quantum computers have the capability to perform practical quantum computing to address specific problems that are intractable for classical computers. Nevertheless, these computers are susceptible to noise, leading to unexpectable errors in outcomes, which makes them less trustworthy. To address this challenge, we propose HammingVis, a visual analytics approach that helps identify and understand errors in quantum outcomes. Given that these errors exhibit latent structural patterns within Hamming space, we introduce two graph visualizations to reveal these patterns from distinct perspectives. One highlights the overall structure of errors, while the other focuses on the impact of errors within important subspaces. We further develop a prototype system for interactively exploring and discerning the correct outcomes within Hamming space. A novel design is presented to distinguish the neighborhood patterns between error and correct outcomes. The effectiveness of our approach is demonstrated through case studies involving two classic quantum algorithms’ outcome data.
This paper describes a practical approach to the quantum theory using the simulation and processing technology available today. The proposed project allows us to create an exploration graph so that for an initial starting configuration of the qubits, all possible states are created given a set of gates selected by the user. For each node in the graph, we can obtain various types of information such as the applied gates from the initial state (the transition route), necessary cost, representation of the quantum circuit, as well as the amplitudes of each state. The project is designed not as an end goal, but rather as a processing platform that allows users to visualize and explore diverse solutions for different quantum problems in a much easier manner. We then describe some potential applications of this project in other research fields, illustrating the way in which the states from the graph can be used as nodes in a new interpretation of a quantum neural network; the steps of a hybrid processing chain are presented for the problem of finding one or more states that verify certain conditions. These concepts can also be used in academia, with their implementation being possible with the help of the Python programming language, the NumPy library, and Qiskit—the open-source quantum framework developed by IBM.
Stabilizer states form an important class of states in quantum information, and are of central importance in quantum error correction. Here, we provide an algorithm for deciding whether one stabilizer (target) state can be obtained from another stabilizer (source) state by single-qubit Clifford operations (LC), single-qubit Pauli measurements (LPM) and classical communication (CC) between sites holding the individual qubits. What is more, we provide a recipe to obtain the sequence of LC+LPM+CC operations which prepare the desired target state from the source state, and show how these operations can be applied in parallel to reach the target state in constant time. Our algorithm has applications in quantum networks, quantum computing, and can also serve as a design tool—for example, to find transformations between quantum error correcting codes. We provide a software implementation of our algorithm that makes this tool easier to apply. A key insight leading to our algorithm is to show that the problem is equivalent to one in graph theory, which is to decide whether some graph G ′ is a vertex-minor of another graph G . The vertex-minor problem is, in general, -Complete, but can be solved efficiently on graphs which are not too complex. A measure of the complexity of a graph is the rank-width which equals the Schmidt-rank width of a subclass of stabilizer states called graph states, and thus intuitively is a measure of entanglement. Here, we show that the vertex-minor problem can be solved in time O (| G | 3 ), where | G | is the size of the graph G , whenever the rank-width of G and the size of G ′ are bounded. Our algorithm is based on techniques by Courcelle for solving fixed parameter tractable problems, where here the relevant fixed parameter is the rank width. The second half of this paper serves as an accessible but far from exhausting introduction to these concepts, that could be useful for many other problems in quantum information. This article is part of a discussion meeting issue ‘Foundations of quantum mechanics and their impact on contemporary society’.
Quantum state visualisation remains a significant challenge in quantum computing education and research due to the abstract mathematical properties of quantum mechanics. This paper presents a new Quantum State Visualiser, an interactive web app that tries to bridge the gap between theoretical quantum mechanics and real-world understanding. The proposed solution operates with multi-qubit quantum circuits, employing partial trace operations to derive single-qubit reduced density matrices, which are then depicted as dynamic 3D Bloch sphere representations. The tool helps you understand abstract ideas like superposition, entanglement, and quantum interference by turning hard math into easy-to-understand pictures. This is useful for students, teachers, researchers, and people who work on quantum computers.The prototype uses Qiskit for quantum Traditional quantum co simulation, Python for computational backends, and modern web technologies for interactive visualisation. The system can accurately show quantum states in real time, which means that circuit changes get instant visual feedback. The new thing is that it combines quantum simulation in real time with 3D visualisation that you can interact with. This creates a fun place to learn that helps people understand quantum phenomena faster. This tool fills a big gap in education and could be used in schools, to fix problems with quantum algorithms, and to make quantum circuits work better. In the future, it will be possible to work with bigger qubit systems, connect it to quantum hardware platforms, and add features for augmented reality visualisation
Stabilizer states, along with Clifford manipulations (unitary transformations and measurements) thereof—despite being efficiently simulable on a classical computer—are an important tool in quantum information processing, with applications to quantum computing, error correction, and networking. Graph states, defined on a graph, are a special class of stabilizer states that are central to measurement-based quantum computing, all-photonic quantum repeaters, distributed quantum computing, and entanglement distribution in a network. All stabilizer states are local-Clifford equivalent to graph states. In this paper, we review the stabilizer framework and extend it by incorporating general stabilizer measurements such as multi-qubit joint projections. We provide an explicit procedure—using Karnaugh maps from Boolean algebra—for converting arbitrary stabilizer gates into tableau operations of the CHP formalism for efficient stabilizer manipulations. We derive graphical rules for arbitrary stabilizer manipulations of graph states, including multi-qubit stabilizer projections and unitaries. We implement the graphical rulebook resulting from above into a MATLAB simulator with a GUI. A user of this tool, e.g., for research in quantum networks, will not require any background in quantum information or the stabilizer framework.