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Quantum computing is one of the most promising solutions for solving optimization problems in the healthcare world. Quantum computing development aims to light up the execution of a vast and complex set of algorithmic instructions. For its implementation, the machine learning models are continuously evolving. Hence, the new challenge is to improve the existing complex and critical machine learning training models. Therefore, the healthcare sector is shifting from a classical to a quantum domain to sustain patient-oriented attention to healthcare patrons. This paper presents a hybrid classical-quantum approach for training the unsupervised data models. In order to achieve good performance and optimization of the machine learning algorithms, a quantum k-means (QK-means) clustering problem was deployed on the IBM quantum simulators, i.e.,the IBM QASM simulator. In the first place, the approach was theoretically studied and then implemented to analyze the experimental results. The approach was further tested using small synthetics and cardiovascular datasets on a qsam simulator to obtain the clustering solution. The future direction connecting the dots is the incremental k-means algorithm with the quantum platform, which would open hitherto unimaginable technological doors. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel algorithm based on Zidan's quantum computing model for remotely controlling the direction of a quantumcontrolledmobile robot equippedwith n-movements. The proposed algorithm is based on the measurement of concurrence value for the different movements of the robot. Consider a faraway robot that moves in the deep space (e.g., moves toward a galaxy), and it is required to control the direction of this robot from a ground station by some person Alice. She sends an unknown qubit α |0〉+ß |1〉 via the teleportation protocol to the robot. Then, the proposed algorithm decodes the received unknown qubit into an angle θ, that determines the motion direction of the robot, based on the concurrence value. The proposed algorithm has been tested for four and eight movements. Two simulators have been tested; IBM Quantum composer and IBM's system, The two simulators achieved the same result approximately. The motion of any part of the robot is considered, if it has a pre-existing sensor system and a locomotive system. We can use this technique in many places like in space robots (16 directions). The results show that the proposed technique can be easily used for a huge number of movements. However, increasing the number of movements of the robot will increase the number of qubits. [ABSTRACT FROM AUTHOR]

Quantum computers promise to efficiently solve important problems that are intractable on a conventional computer. Quantum computational algorithms have the potential to be an exciting new way of studying quantum cosmology. In quantum cosmology, we learn about the dynamics of the universe without constructing a complete theory of quantum gravity. Since the universal wavefunction exists in an infinite-dimensional superspace over all possible 3D metrics and modes of matter configurations, we take minisuperspaces for our work by constraining the degrees of freedom to particular 3D metrics and uniform scalar field configurations. Here, we consider a wide variety of cosmological models. We begin by analyzing an anisotropic universe with cosmological constant and classical radiation. We then study the results for higher derivatives, Kaluza–Klein theories and string dilaton in quantum cosmology. We use IBM's Quantum Information Science Kit (QISKit) python library and the Variational Quantum Eigensolver (VQE) algorithm for studying these systems. The VQE algorithm is a hybrid algorithm that uses the variational approach and interleaves quantum and classical computations in order to find the minimum eigenvalue of the Hamiltonian for a given system. The minimum eigenvalue of the Hamiltonian obtained will serve as a boundary condition for the given wavefuntion. [ABSTRACT FROM AUTHOR]

Cloning an unknown state is an important task in the field of quantum computation as it is one of the basic operations required in any experiment. The no-cloning theorem states that it is impossible to create an identical copy of an arbitrary unknown quantum state. Hence, techniques are developed to clone unknown states to high fidelities, rather than to exact copies. The usual method of cloning is quantum tomography, which measures a set of observables to reconstruct the unknown state. This method proves to be very expensive when the number of copies of the unknown state is limited. Here, we try to clone an unknown state in IBM's QASM simulator using a quantum reinforcement learning protocol (Albarran-Arriagada et al. in Phys Rev A 98:042315, 2018), where the "right" amount of punishment/reward function and boundary conditions can give much better fidelity than what tomography can offer in limited copies of the state. Using this method, we can attain above 90% fidelity in under 50 copies. This method proves to be very useful for reconstructing quantum states when only limited copies of the state are available. [ABSTRACT FROM AUTHOR]

Quantum teleportation is a secure way to transfer an unknown message using a known channel implementing a simple and efficient protocol. Here, we achieve three-qubit and four-qubit quantum teleportation using a highly entangled Brown et al. state. We simulate the same using the IBM quantum experience platform. Furthermore, we extend this concept to generalize N-qubit teleportation which comprises of two cases, N being odd and even. The results are verified after designing the quantum circuits and simulating using the quantum simulator. [ABSTRACT FROM AUTHOR]

Witnessing quantum effects in the gravitational field is found to be exceptionally difficult in practice due to the lack of empirical evidence. Hence, a debate is going on among physicists whether gravity has a quantum domain or not. To date, no convincing experimental proposal was put forward until two recent independent works by Bose et al. (Phys Rev Lett 119:240401, 2017) and Marletto and Vedral (Phys Rev Lett 119:240402, 2017). The authors have proposed schemes to test the quantumness of gravity in two small test masses by entangling two spatially separated objects using gravitational interactions. They have provided a method to witness the entanglement using spin correlation measurements, which could imply evidence for gravity being a quantum coherent mediator. Here we have proposed a simulational model by providing a new quantum circuit for verifying the above schemes. We have simulated the schemes for the first time in IBM's 5-qubit quantum chip 'ibmqx4' by developing a quantum system which shows effects analogous to quantum gravity and calculates the degree of entanglement of the spin correlation. The entanglement witness over a range is obtained for different experimental parameters. [ABSTRACT FROM AUTHOR]

Quantum neural networks have gained significant interest in recent times for the representation of many-body states and classical simulation of quantum computation. Here, we discuss the methods to generate specific initial states in the Restricted Boltzmann Machines analogous to those used as the initial states while performing quantum computation in quantum computers such as IBM Q. We validate our approach by applying the Pauli X gate to the single-qubit and two-qubit initial states using NetKet and compare the results to that obtained by performing the same task in the IBM quantum computer. We find that using this approach, the RBM neural networks can represent desired quantum states with high accuracy. Thus, this method is promising to mimic quantum computation classically in neural networks by using specific initial states. [ABSTRACT FROM AUTHOR]

Medical experts are often skeptical of data-driven models due to the lack of their explainability. Several experimental studies commence with wide-ranging unsupervised learning and precisely with clustering to obtain existing patterns without prior knowledge of newly acquired data. Explainable Artificial Intelligence (XAI) increases the trust between virtual assistance by Machine Learning models and medical experts. Awareness about how data is analyzed and what factors are considered during the decision-making process can be confidently answered with the help of XAI. In this paper, we introduce an improved hybrid classical-quantum clustering (improved qk-means algorithm) approach with the additional explainable method. The proposed model uses learning strategies such as the Local Interpretable Model-agnostic Explanations (LIME) method and improved quantum k-means (q k -means) algorithm to diagnose abnormal activities based on breast cancer images and Knee Magnetic Resonance Imaging (MRI) datasets to generate an explanation of the predictions. Compared with existing algorithms, the clustering accuracy of the generated clusters increases trust in the model-generated explanations. In practice, the experiment uses 600 breast cancer (BC) patient records with seven features and 510 knee MRI records with five features. The result shows that the improved hybrid approach outperforms the classical one in the BC and Knee MRI datasets. [ABSTRACT FROM AUTHOR]

The quantum no-hiding theorem, first proposed by Braunstein and Pati (Phys Rev Lett 98:080502, 2007), was verified experimentally by Samal et al. (Phys Rev Lett 186:080401, 2011) using NMR quantum processor. Till then, this fundamental test has not been explored in any other experimental architectures. Here, we demonstrate the above no-hiding theorem using the IBM 5Q quantum processor. Categorical algebra developed by Coecke and Duncan (New J Phys 13:043016, 2011) has been used for better visualization of the no-hiding theorem by analyzing the quantum circuit using the ZX calculus. The experimental results confirm the recovery of missing information by the application of local unitary operations on the ancillary qubits. [ABSTRACT FROM AUTHOR]

Quantum communication is a secure way to transfer quantum information and to communicate with legitimate parties over distant places in a network. Although communication over a long distance has already been attained, technical problem arises due to unavoidable loss of information through the transmission channel. Quantum repeaters can extend the distance scale using entanglement swapping and purification scheme. Here we demonstrate the working of a quantum repeater by the above two processes. We use IBM's real quantum processor 'ibmqx4' to create two pair of entangled qubits and design an equivalent quantum circuit which consequently swaps the entanglement between the two pairs. We then develop a novel purification protocol which enhances the degree of entanglement in a noisy channel that includes combined errors of bit-flip, phase-flip and phase-change error. We perform quantum state tomography to verify the entanglement swapping between the two pairs of qubits and working of the purification protocol. [ABSTRACT FROM AUTHOR]

Local implementation of non-local quantum gates is necessary in a distributed quantum computer. Here, we demonstrate the non-local implementation of controlled-unitary quantum gates proposed by Eisert et al. (Phys Rev A 62:052317, 2000) using the five-qubit IBM quantum computer. We verify the fidelity and accuracy of the implementation through the techniques of quantum state and process tomographies. [ABSTRACT FROM AUTHOR]