Cloud Quantum Computer Research Articles

Quantum Computing and Cloud Technologies: The Next Frontier in Computing Power

Abstract: This article explores the convergence of quantum computing and cloud technologies, representing a pivotal advancement in computational power with far-reaching implications across various industries and scientific domains. It examines the current state of quantum computing, elucidating its fundamental principles and recent hardware advancements, while comparing its capabilities to classical computing systems. The integration of quantum computing with cloud platforms is analyzed, highlighting the emergence of cloud-based quantum services and their advantages in democratizing access to this cutting-edge technology. The article delves into potential applications of quantum cloud computing, including cryptography, material science, artificial intelligence, and financial modeling, showcasing its transformative potential. Critical challenges facing quantum cloud computing are addressed, such as error correction, scalability issues, and the development of quantumsafe encryption methods. Looking ahead, the article discusses prospects and research directions, including anticipated breakthroughs in quantum hardware, emerging quantum cloud architectures, and the potential impact on various industries. By synthesizing current research and industry developments, this comprehensive overview provides insights into the revolutionary potential of quantum cloud computing and its role in shaping the future of computational capabilities.

Delayed-measurement one-way quantum computing on cloud quantum computer

Abstract One-way quantum computation focuses on initially generating an entangled cluster state followed by a sequence of measurements with classical communication of their individual outcomes. Recently, a delayed-measurement approach has been applied to replace classical communication of individual measurement outcomes. In this work, by considering the delayed-measurement approach, we demonstrate a modified one-way CNOT gate using the on-cloud superconducting quantum computing platform: Quafu. The modified protocol for one-way quantum computing requires only three qubits rather than the four used in the standard protocol. Since this modified cluster state decreases the number of physical qubits required to implement one-way computation, both the scalability and complexity of the computing process are improved. Compared to previous work, this modified one-way CNOT gate is superior to the standard one in both fidelity and resource requirements. We have also numerically compared the behavior of standard and modified methods in large-scale one-way quantum computing. Our results suggest that in a noisy intermediate-scale quantum (NISQ) era, the modified method shows a significant advantage for one-way quantum computation.

Quantum cloud computing: Trends and challenges

Quantum computing is a new paradigm that will revolutionize various areas of computing, especially cloud computing. Quantum computing, still in its infancy, is a costly technology that can operate in highly isolated environments because of its rapid response to environmental factors. This makes quantum computing a challenging technology for researchers to access. These problems can be solved by integrating quantum computing into an isolated remote server, such as a cloud, and making it available to users. Furthermore, experts predict that quantum computing, with its ability to swiftly resolve complex and computationally intensive operations, will offer significant benefits in systems that process large amounts of data, like cloud computing. This article presents the vision and challenges for the quantum cloud computing paradigm that will emerge with the integration of quantum and cloud computing. Next, we present the advantages of quantum computing over classical computing applications. We analyze the effects of quantum computing on cloud systems, such as cost, security, and scalability. Besides all of these advantages, we highlight research gaps in quantum cloud computing, such as qubit stability and efficient resource allocation. This article identifies the advantages and challenges of quantum cloud computing for future research, highlighting research gaps.

AI and pharma: Transforming the paradigm, embracing the new era

This review delves into the dynamic intersection of artificial intelligence (AI) and the pharmaceutical industry, exploring a wide spectrum of clinical and commercial applications, challenges and risks, potential solutions, and future outlooks as these domains converge. With the rapid advancement of AI, this review addresses the profound implications of AI in the life sciences sector, emphasizing its potential to revolutionize drug discovery, clinical trials, personalized medicine, pharmacovigilance, sales, and marketing. While lauding the paradigm-shifting prospects, this paper confronts the ethical, privacy, and bias risks entwined with AI development and deployment. Forward-looking solutions, including fortified data governance frameworks, transparent AI algorithms, and interdisciplinary alliances, stand as bulwarks against these impediments. Furthermore, it considers the possibilities afforded to AI by emergent technologies, such as quantum cloud computing and low-code solutions. In conclusion, this review envisions a future where AI, in collaboration with innovative technologies, reshapes the pharmaceutical landscape. By promoting informed discussions and collaboration, this review seeks to empower the industry to harness the transformative potential of AI in an ethical manner.

When Quantum Information Technologies Meet Blockchain in Web 3.0

With the drive to create a decentralized digital economy, Web 3.0 has become a cornerstone of digital transformation, developed on the basis of computing power networks, distributed data storage, and blockchain. With the rapid realization of quantum devices, Web 3.0 is being developed in parallel with the deployment of quantum cloud computing and quantum Internet. In this regard, quantum computing first disrupts the original cryptographic systems that protect data security while reshaping modern cryptography with the advantages of quantum computing and communication. Therefore, in this paper, we introduce a quantum blockchain-driven Web 3.0 framework that provides information-theoretic security for decentralized data transferring and payment transactions. First, we present the framework of quantum blockchain-driven Web 3.0 with futureproof security during the transmission of data and transaction information. Next, we discuss the potential applications and challenges of implementing quantum blockchain in Web 3.0. Finally, we describe a use case for quantum non-fungible tokens (NFTs) and propose a quantum deep learning-based optimal auction for NFT trading to maximize the achievable revenue for sufficient liquidity in Web 3.0. In this way, the proposed framework can achieve proven security and sustainability for the next-generation decentralized digital society.

Quantum Cloud Computing: Transforming Cryptography, Machine Learning, and Drug Discovery

Quantum Cloud Computing is poised to revolutionize various domains by leveraging the principles of quantum mechanics to enhance computational capabilities beyond classical limits. This paper explores the transformative potential of quantum cloud technologies in three critical areas: cryptography, machine learning, and drug discovery. In cryptography, quantum cloud computing enables the development of unbreakable encryption methods through quantum key distribution and post-quantum cryptographic algorithms, ensuring data security in an increasingly interconnected world. In machine learning, quantum algorithms can significantly accelerate data processing and pattern recognition, opening new avenues for complex problem-solving and predictive analytics. Additionally, the application of quantum computing in drug discovery can streamline molecular simulations and optimize drug design processes, leading to faster identification of viable pharmaceutical candidates. By integrating quantum computing with cloud infrastructure, we can democratize access to advanced computational resources, fostering innovation and collaboration across disciplines. This paper discusses the current state of research, potential applications, and the challenges that lie ahead in harnessing quantum cloud computing to drive advancements in these critical fields.

Mapping the metal-insulator phase diagram by algebraically fast-forwarding dynamics on a cloud quantum computer

Mapping the metal-insulator phase diagram by algebraically fast-forwarding dynamics on a cloud quantum computer

Measuring the quadrature coherence scale on a cloud quantum computer

Coherence underlies quantum phenomena, yet it is manifest in classical theories; delineating coherence's role is a fickle business. The quadrature coherence scale (QCS) was invented to remove such ambiguity, quantifying quantum features of any single-mode bosonic system without choosing a preferred orientation of phase space. The QCS is defined for any state, reducing to well-known quantities in appropriate limits, including Gaussian and pure states, and perhaps most importantly for a coherence measure, it is highly sensitive to decoherence. Until recently, it was unknown how to measure the QCS; we here report on an initial measurement of the QCS for squeezed light and thermal states of light. This is performed using Xanadu's machine Borealis, accessed through the cloud, which offers the configurable beam splitters and photon-number-resolving detectors essential for measuring the QCS. The data and theory match well, certifying the usefulness of interferometers and photon-counting devices in certifying quantumness.

Solving the Shortest Path Problem with QAOA

Graph computation is a core technique for solving realistic problems of graph representations. In solving the shortest path problem (SPP), the current classical methods are encountering a huge performance bottleneck. Attempting to solve this dilemma, we try to solve the SPP with a Quantum Approximate Optimal Algorithm (QAOA)-based quantum method. In this paper, we propose a QAOA-based shortest path algorithm (SPA) by constructing a suitable Hamiltonian quantity and using the idea of variational quantum computing, and verify the algorithm using a quantum simulator and an International Business Machines cloud quantum computer. The proposed algorithm is able to achieve a near-optimal solution with a correct rate that significantly exceeds the invalid solutions, reaching a good preliminary result. Furthermore, the proposed algorithm is expected to achieve a huge advantage over the classical algorithm and the SPA based on Grover’s algorithm with a suitable selection of parameters and number of steps. In addition, the proposed algorithm requires fewer quantum bits than other quantum algorithms, thus promising quantum computing superiority on current noisy intermediate-scale quantum (NISQ) quantum computing devices.

Quantum algorithm for learning secret strings and its experimental demonstration

In this paper, we consider the secret-string-learning problem in the teacher–student setting: the teacher has a secret string s∈{0,1}n, and the student wants to learn the secret s by question–answer interactions with the teacher, where at each time, the student can ask the teacher with a pair (x,q)∈{0,1}n×{0,1,…,n−1} and the teacher returns a bit given by the oracle fs(x,q) that indicates whether the length of the longest common prefix of s and x is greater than q or not. Our contributions are as follows.(i) We prove that any classical deterministic algorithm needs at least n queries to the oracle fs to learn the n-bit secret string s in both the worst case and the average case, and also present an optimal classical deterministic algorithm learning any s using n queries.(ii) We propose a quantum algorithm learning the n-bit secret string s with certainty using n/2 queries to the oracle fs, thus proving a double speedup over classical counterparts.(iii) Experimental demonstrations of our quantum algorithm on the IBM cloud quantum computer are presented, with the average success probabilities of 85.3% and 82.5% for all cases with n=2 and n=3, respectively.

Deterministic one-way logic gates on a cloud quantum computer

One-way quantum computing is a promising candidate for fault-tolerant quantum computing. Here, we propose new protocols to realize a deterministic one-way CNOT gate and one-way $X$-rotations on quantum-computing platforms. By applying a delayed-choice scheme, we overcome a limit of most currently available quantum computers, which are unable to implement further operations on measured qubits or operations conditioned on measurement results from other qubits. Moreover, we decrease the error rate of the one-way logic gates, compared to the original protocol using local operations and classical communication (LOCC). In addition, we apply our deterministic one-way CNOT gate in the Deutsch-Jozsa algorithm to show the feasibility of our proposal. We demonstrate all these one-way gates and algorithms by running experiments on the cloud quantum-computing platform IBM Quantum Experience.

Dual-state purification for practical quantum error mitigation

Quantum error mitigation is essential for many computing tasks on the noisy quantum computer with a limited number of qubits. In this paper, we propose a practical protocol of error mitigation by virtually purifying the quantum state without qubit overhead or requiring only one ancilla qubit. In dual-state purification, we effectively generate a purified state with increased fidelity using the erroneous state and its dual state, respectively, prepared with the noisy quantum circuit and the dual map of its inverse circuit. Combined with tomography purification, we can make sure that the final estimate of an observable is obtained from a pure state. While the absolute error increases, the numerical result, based on a depolarizing model, suggests that our protocol reduces the error compared to the case without the protocol by a rescaling factor decreasing with the qubit number and circuit depth; i.e., the relative performance of purification is better for larger circuits. On a cloud quantum computer, we successfully demonstrate the reduced error with a quantum variational eigensolver circuit.

Design of a quantum repeater using quantum circuits and benchmarking its performance on an IBM quantum computer

Quantum communication relies on the existence of entanglement between two nodes of a network. However, due to its fragile nature, it is nearly impossible to establish entanglement at large distances through the direct transmission of qubits. Quantum repeaters have been proposed to solve this problem, which split-up the network to create small-scale entangled links and then connect them up to create the large-scale link. As researchers race to establish entanglement over larger and larger distances, it becomes essential to gauge the performance and robustness of the different protocols that have been proposed to design a quantum repeater, before deploying them in real life. Currently available noisy quantum computers are ideal for this task, as they can emulate the noisy environment in a quantum communication channel, and provide a measure for how the protocols will perform on real-life hardware. In this paper, we report the circuit-level implementation of the complete architecture of a quantum repeater, and benchmark this protocol on IBM's cloud quantum computer - IBMQ. Our experiments indicate a 26% fidelity of shared bell-pairs for a complete on-chip quantum repeater with a yield of 49%. We also compare these results with simulation data from IBM Qiskit. The results of our experiments provide a quantitative measure for the fidelity of entanglement that currently available repeaters can establish. In addition, the proposed circuit-implementation provides a robust benchmark for state-of-the-art quantum computing hardware.

Evaluating Energy Differences on a Quantum Computer with Robust Phase Estimation.

We adapt the robust phase estimation algorithm to the evaluation of energy differences between two eigenstates using a quantum computer. This approach does not require controlled unitaries between auxiliary and system registers or even a single auxiliary qubit. As a proof of concept, we calculate the energies of the ground state and low-lying electronic excitations of a hydrogen molecule in a minimal basis on a cloud quantum computer. The denominative robustness of our approach is then quantified in terms of a high tolerance to coherent errors in the state preparation and measurement. Conceptually, we note that all quantum phase estimation algorithms ultimately evaluate eigenvalue differences.

Quantum k-means algorithm based on trusted server in quantum cloud computing

Quantum k-means algorithm is widely used in solving clustering problems. However, the repeated calculation of the core subroutines overloads the quantum computer with mass computing tasks. In addition, due to the decoherence of the quantum state, the computing power of personal quantum computer is limited. Therefore, it is necessary to use high-performance quantum cloud computing to complete data processing. This paper proposes a quantum k-means algorithm in quantum cloud computing, which uploads the data to the server to execute the core subroutines SwapTest (calculating the similarity between ciphertext quantum states) and GroverOptim (quantum minimization algorithm) of quantum k-means algorithm and then sends the ciphertext to the client for further decryption using the decryption key, which reduces the load of the client. An improved quantum homomorphic encryption by t-gate updating in trusted server and data processing in semi-trusted server is introduced as well. In this scheme, the trusted server assists the semi-trusted server to execute the T-gate existing in the quantum circuit, which separates the key from the ciphertext and ensure the security of the ciphertext data processing in the quantum cloud. In our experiment, the two subroutines, SwapTest and GroverOptim, are conducted in ciphertext and plaintext conditions by using IBM Qiskit to evaluate the reliability and feasibility. The result shows that the decrypted ciphertext result is the same as the plaintext. We conclude that the proposed algorithm has a better performance in reducing the cost of load in client and protecting privacy data in cloud by contrast with the original quantum k-means algorithm.

Cloud Quantum Computing Concept and Development: A Systematic Literature Review

Abstract A cloud quantum computer is a quantum computer that can be accessed in a cloud environment through a network. Today, there are numbers of cloud quantum computing services that can be accessed by users. They are used to solve complex problems that require powerful computing. Different cloud quantum computing services deliver different architecture and performances. In our study, we conducted a research on some services to test and evaluate the performances of different cloud quantum computing services and make a comparison out of it. The test will be conducted using two different methods such as visual programming and qiskit. From the result, we can see that the amount of qubit per backend and shots per run pretty much affect the execution time of a cloud quantum computing. This test will give the users some insight and enables them to decide which cloud quantum computing services deliver better performance or faster execution time based on the specification each cloud quantum computer offers.

Quantum cloud computing-a scientometric assessment of global research for the period 1999–2020

The study provides a quantitative and qualitative description of global quantum cloud computing research for the period 2000–2019, using metrics. The data for the study was sourced from Scopus database. During the period, the global research output in the subject totalled 459 publications, registered 39.63% annual average growth rate and 19.85 citations per paper. In addition, the study provides the distribution of global research output by country of publication, lists the top 10 most productive countries in the subject, identifies the leading research organizations as well as leading contributing authors in the subject. The study also provides the distribution of research output by major disciplines in order to bring out the most sought areas of research in quantum cloud computing. The study also identifies the most popular source journals in the subject. IEEE Access (10 papers), Physical Review Letters (6 papers) and Nature (4 papers) were found to be the most productive journals. Information Sciences, Science and Physical Review Letters were found to be the most impactful journals.

Implementation of leakage elimination operators and subspace protection

Decoherence-induced leakage errors can potentially damage physical or logical qubits embedded in a subspace of the entire Hilbert space by coupling them to other system levels. Here we report the first experimental implementation of Leakage Elimination Operators (LEOs) that aims to reduce this undermining. LEOs are a type of dynamical decoupling control that have been previously introduced to counteract leakage from a chosen subspace into the rest of a Hilbert space, and have been widely explored theoretically. Different from other error correction strategies, LEOs are compatible with any gate sequence in a code space, and thus, compatible with universal quantum computation. Using IBM’s cloud quantum computer (QC), we design three potentially applicable examples of subspaces in two- and three-qubit Hilbert spaces and derive the explicit forms of the corresponding LEOs for these subspaces. For the first time, we experimentally demonstrate that these LEOs significantly suppress leakage. The results also show that the LEO time-scale condition can be satisfied with noise in the IBM’s cloud QC and pave a way for quantum setups to get rid of leakage trouble.

Quantum Computing Is Still in Basic Research Phase

Abstract This column assesses the near-term challenges associated with quantum computing, noting that 15 years is an optimistic estimate for commercially viable quantum cloud computing. In the midst of the struggle, however, there is also opportunity, particularly in metrology and component development.

Experimental cryptographic verification for near-term quantum cloud computing

An important task for quantum cloud computing is to make sure that there is a real quantum computer running, instead of classical simulation. Here we explore the applicability of a cryptographic verification scheme for verifying quantum cloud computing. We provided a theoretical extension and implemented the scheme on a 5-qubit NMR quantum processor in the laboratory and a 5-qubit and 16-qubit processors of the IBM quantum cloud. We found that the experimental results of the NMR processor can be verified by the scheme with about 1.4% error, after noise compensation by standard techniques. However, the fidelity of the IBM quantum cloud is currently too low to pass the test (about 42% error). This verification scheme shall become practical when servers claim to offer quantum-computing resources that can achieve quantum supremacy.