arXiv subjects

Parvinder Singh

Publications and source records attributed to Parvinder Singh.

6 recordsLinked to original sources

arXiv2024

Harnessing Quantum Support Vector Machines for Cross-Domain Classification of Quantum States

In the present study, we use cross-domain classification using quantum machine learning for quantum advantages to readdress the entanglement versus separability paradigm. The inherent structure of quantum states and its relation to a particular class of quantum states are used to intuitively classify testing states from domains different from training states, called \textit{cross-domain classification}. Using our quantum machine learning algorithm, we demonstrate efficient classifications of two-qubit mixed states into entangled and separable classes. For analyzing the quantumness of correlations, our model adequately classifies Bell diagonal states as zero and non-zero discord states. In addition, we also extend our analysis to evaluate the robustness of our model using random local unitary transformations. Our results demonstrate the potential of the quantum support vector machine for classifying quantum states across the multi-dimensional Hilbert space in comparison to classical support vector machines and neural networks.

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arXiv2024

A Graph-Theoretical Framework to Analyse Zero Discord Quantum States

This article comprehensively explores matrices and their prerequisites for achieving positive semidefiniteness. The study delves into a series of theorems concerning pure quantum states in the context of weighted graphs. The main objective of this study is to establish a graph-theoretic framework for the study of quantum discord and to identify the necessary and sufficient conditions for zero quantum discord states using unitary operators. This research aims to advance the understanding of quantum discord and its implications for quantum information theory with a graph-theoretic framework.

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arXiv2024

Separability of Graph Laplacian Quantum States: Utilizing Unitary Operators, Neighbourhood Sets and Equivalence Relation

This article delves into an analysis of the intrinsic entanglement and separability feature in quantum states as depicted by graph Laplacian. We show that the presence or absence of edges in the graph plays a pivotal role in defining the entanglement or separability of these states. We propose a set of criteria for ascertaining the separability of quantum states comprising $n$-qubit within a composite Hilbert space, indicated as $H=H_1 \otimes H_2 \otimes \dots \otimes H_n$. This determination is achieved through a combination of unitary operators, neighbourhood sets, and equivalence relations.

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arXiv2023

Quantum-inspired attribute selection algorithm: A Fidelity-based Quantum Decision Tree

A classical decision tree is completely based on splitting measures, which utilize the occurrence of random events in correspondence to its class labels in order to optimally segregate datasets. However, the splitting measures are based on greedy strategy, which leads to construction of an imbalanced tree and hence decreases the prediction accuracy of the classical decision tree algorithm. An intriguing approach is to utilize the foundational aspects of quantum computing for enhancing decision tree algorithm. Therefore, in this work, we propose to use fidelity as a quantum splitting criterion to construct an efficient and balanced quantum decision tree. For this, we construct a quantum state using the occurrence of random events in a feature and its corresponding class. The quantum state is further utilized to compute fidelity for determining the splitting attribute among all features. Using numerical analysis, our results clearly demonstrate that the proposed algorithm cooperatively ensures the construction of a balanced tree. We further compared the efficiency of our proposed quantum splitting criterion to different classical splitting criteria on balanced and imbalanced datasets. Our simulation results show that the proposed splitting criterion exceeds all classical splitting criteria for all possible evaluation metrics.

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arXiv2023

The role of entanglement for enhancing the efficiency of quantum kernels towards classification

Quantum kernels are considered as potential resources to illustrate benefits of quantum computing in machine learning. Considering the impact of hyperparameters on the performance of a classical machine learning model, it is imperative to identify promising hyperparameters using quantum kernel methods in order to achieve quantum advantages. In this work, we analyse and classify sentiments of textual data using a new quantum kernel based on linear and full entangled circuits as hyperparameters for controlling the correlation among words. We also find that the use of linear and full entanglement further controls the expressivity of the Quantum Support Vector Machine (QSVM). In addition, we also compare the efficiency of the proposed circuit with other quantum circuits and classical machine learning algorithms. Our results show that the proposed fully entangled circuit outperforms all other fully or linearly entangled circuits in addition to classical algorithms for most of the features. In fact, as the feature increases the efficiency of our proposed fully entangled model also increases significantly.

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arXiv2016

Usefulness of Multiqubit W-type States in Quantum Information Processing Task

We analyze the efficacy of multiqubit W-type states as resources for quantum information. For this, we identify and generalize four-qubit W-type states. Our results show that the states can be used as resources for deterministic quantum information processing. The utility of results, however, is limited by the availability of experimental setups to perform and distinguish multiqubit measurements. We, therefore, emphasize on another protocol where two users want to establish an optimal bipartite entanglement using the partially entangled W-type states. We found that for such practical purposes, four-qubit W states can be a better resource in comparison to three-qubit W-type states. For dense coding protocol, our states can be used deterministically to send two bits of classical message by locally manipulating a single qubit.

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