Quantum Computing System Research Articles

Novel Wafer-Level Ta-Ta Direct Thermocompression Bonding for 3D Integration of Superconducting Interconnects for Scalable Quantum Computing System

Novel Wafer-Level Ta-Ta Direct Thermocompression Bonding for 3D Integration of Superconducting Interconnects for Scalable Quantum Computing System

Impact of AI on cybersecurity and security compliance

Artificial Intelligence (AI) is transforming the field of cybersecurity and reshaping security compliance practices. As cyber threats become increasingly complex, AI offers powerful tools for identifying, mitigating, and preventing attacks in real-time. AI-driven systems excel at processing vast amounts of data, detecting anomalies, and identifying patterns that traditional security systems might miss. Machine learning and deep learning algorithms enhance the ability to predict potential threats, reducing response time and improving the accuracy of threat detection. These capabilities make AI a valuable asset in addressing sophisticated threats such as zero-day vulnerabilities, advanced persistent threats (APTs), and ransomware attacks. In the realm of security compliance, AI plays a pivotal role by automating routine tasks such as monitoring, auditing, and reporting. This reduces the burden on organizations to manually enforce regulatory standards, leading to more efficient compliance with frameworks like GDPR, HIPAA, and PCI-DSS. AI can continuously assess systems to ensure that they meet compliance requirements, enhancing the ability to detect and respond to violations. Furthermore, AI contributes to governance by helping organizations develop robust security policies, track compliance metrics, and streamline incident response. However, the integration of AI in cybersecurity also presents challenges, including adversarial AI, data privacy concerns, and transparency in AI decision-making processes. Additionally, AI-driven attacks are an emerging threat that necessitates further research and regulation. Despite these challenges, the future of AI in cybersecurity and compliance looks promising, with advancements in predictive analytics, quantum computing, and autonomous security systems poised to further revolutionize the field. As AI technologies evolve, they will continue to play a critical role in fortifying cybersecurity defenses and ensuring regulatory compliance across industries.

Growing Semiconductor Industry in India

This paper delves into the growing semiconductor industry in India, and its importance in every aspect of present and future high data processing speed. Semiconductors are crucial electronic components for quantum computing, artificial intelligence (AI), medical devices, aerospace and defence systems, etc. Thus, the use of semiconductors for these most important and future ease concepts, this paper is an understanding approach to the growing importance of semiconductors in India

Quantum Nuclear Dynamics on a Distributed Set of Ion-Trap Quantum Computing Systems.

Quantum nuclear dynamics with wavepacket time evolution is classically intractable and viewed as a promising avenue for quantum information processing. Here, we use IonQ, Inc.'s 11-qubit trapped-ion quantum computer, Harmony, to study the quantum wavepacket dynamics of a shared-proton within a short-strong hydrogen-bonded system. We also provide the first application of distributed quantum computing for chemical dynamics problems, where a distributed set of quantum processes is constructed using a tensor network formalism. For a range of initial states, we experimentally drive the ion-trap system to emulate the quantum nuclear wavepacket as it evolves along the potential surface generated from the electronic structure. Following the experimental creation of the nuclear wavepacket, we extract measurement observables such as its time-dependent spatial projection and its characteristic vibrational frequencies to good agreement with classical results. Vibrational eigenenergies obtained from quantum computation are in agreement with those obtained from classical simulations to within a fraction of a kilocalorie per mole, thus suggesting chemical accuracy. Our approach opens a new paradigm for studying the quantum chemical dynamics and vibrational spectra of molecules and also provides the first demonstration of parallel quantum computation on a distributed set of ion-trap quantum computers.

Chip and Package-Scale Interconnects for General-Purpose, Domain-Specific, and Quantum Computing Systems—Overview, Challenges, and Opportunities

Chip and Package-Scale Interconnects for General-Purpose, Domain-Specific, and Quantum Computing Systems—Overview, Challenges, and Opportunities

Past, present, and future of hybrid plasmonic waveguides for photonics integrated circuits

This article addresses the past, present, and future status of hybrid plasmonic waveguides (HPWs). It presents a comprehensive review of HPW-based photonic integrated circuits (PICs), covering both passive and active devices, as well as potential application of on-chip HPW-based devices. HPW-based integrated circuits (HPWICs) are compatible with complementary metal oxide semiconductor technology, and their matched refractive indices enables the adaptation of existing fabrication processes for silicon-on-insulator designs. HPWs combine plasmonic and photonic waveguide components to provide strong confinement with longer propagation length Lp of HP modes with nominal losses. These HPWs are able to make a trade-off between low loss and longer Lp, which is not possible with independent plasmonic and photonic waveguide components owing to their inability to simultaneously achieve low propagation loss with rapid and effective all-optical functionality. With HPWs, it is possible to overcome challenges such as high Ohmic losses and enhance the functional performance of PICs through the use of multiple discrete components. HPWs have been employed not only to guide transverse magnetic modes but also for optical beam manipulation, wireless optical communication, filtering, computation, sensing of bending, optical signal emission, and splitting. They also have the potential to play a pivotal role in optical communication systems for quantum computing and within data centers. At present, HPW-based PICs are poised to transform wireless chip-to-chip communication, a number of areas of biomedical science, machine learning, and artificial intelligence, as well as enabling the creation of densely integrated circuits and highly compact photonic devices.

Optimization Applications as Quantum Performance Benchmarks

Combinatorial optimization is anticipated to be one of the primary use cases for quantum computation in the coming years. The Quantum Approximate Optimization Algorithm and Quantum Annealing can potentially demonstrate significant run-time performance benefits over current state-of-the-art solutions. Inspired by existing methods to characterize classical optimization algorithms, we analyze the solution quality obtained by solving Max-cut problems using gate-model quantum devices and a quantum annealing device. This is used to guide the development of an advanced benchmarking framework for quantum computers designed to evaluate the trade-off between run-time execution performance and the solution quality for iterative hybrid quantum-classical applications. The framework generates performance profiles through compelling visualizations that show performance progression as a function of time for various problem sizes and illustrates algorithm limitations uncovered by the benchmarking approach. As an illustration, we explore the factors that influence quantum computing system throughput, using results obtained through execution on various quantum simulators and quantum hardware systems.

A survey analysis of quantum computing adoption and the paradigm of privacy engineering

AbstractThis study investigates the adoption of quantum computing (QC) technology using the diffusion of innovation (DOI) theory and provides an extensive literature review. We deployed structural equation modeling to analyze data from a survey conducted among 96 top managers in various industries from Canada, the US, and Europe, including IT‐based small and medium‐sized enterprises (SMEs) dealing with QC software development. Our survey analysis indicates that the complexity of QC systems and software is the main barrier to the future adoption of quantum computing. This research offers insights into how future quantum computers can impact the security and privacy of information, emphasizing the importance of privacy protection. In this context, the study contributes to the notion of privacy engineering in the complex context of QC. The study established important outlines and tools for shaping future QCs. Our study, backed by empirical evidence, underscores the significant impact of new technology on citizens', organizations', firms', and government‐private data. The results provide a clear message to policymakers, industry leaders, and developers: privacy engineering should be an integral part of technical development, and it's crucial to act before costs escalate. In this context, our study stands out as one of the few that use NLP and structural equation modeling to address privacy challenges in QC research through experimental research, offering practical solutions to real‐world problems.

The Curriculum in NDT Training Have to Include Basics Information Technology to Accomplish Reliability of Automated NDT Result's

Automation in Non-Destructive Testing (NDT) is a reality of modern manufacturing and quality assurance. Information technology applications are simultaneously developed and applied to different fields of NDT methods. The future of doing reliability checks using automated system is inevitable. The results are important to make a variety of decisions regarding the quality of a product and/or service, hence affecting safety and reliability. Depending on artificial intelligence and quantum device development, various NDT training schemes have to adopt a new curriculum to address the issue of the basic knowledge of information technology and automation in NDT. NDT operators are basically dependent on the end results of software, in which the software developer uses a set of algorithms. These are obtained in three categories; 1) Real time database; 2) Synthetic database and 3) Hybrid or combination of them. The developers should know how the NDT systems run and NDT operators in the other hand know the mechanism of the program, so that appropriate action can be taken, in case there is a missed detection, or a detected indication is not very much detrimental to the reliability of the part (Over sizing or wrongly evaluated). For example, a set of algorithms are used to create the focal laws in a phased array ultrasonic test software in space of 1˚ beam steering. Each has a limit of maximum up to 2nd Critical angle. Operators try to copy the same algorithm and set up to 89˚ refraction angle, which will just create creep wave with unreliable results to detect effective size the reflector. Programming knowledge of the operator can effectively eliminate this type of unreliability. In various Schemes of NDT Syllabus which are in common place to employ and train plus certify operators does not have it; actually, the operators do the scope of work which does includes application of Artificial Intelligence (AI) and Software. With the development of Q coupler (Quantum Computing) system, it is obvious to adopt the upcoming technology into the application of NDT industry. Training needs to update the curriculum accordingly. The current topic has intended to focus on the training gap and to address related kind of unreliability.

The Goldilocks principle of learning unitaries by interlacing fixed operators with programmable phase shifters on a photonic chip

Programmable photonic integrated circuits represent an emerging technology that amalgamates photonics and electronics, paving the way for light-based information processing at high speeds and low power consumption. Programmable photonics provides a flexible platform that can be reconfigured to perform multiple tasks, thereby holding great promise for revolutionizing future optical networks and quantum computing systems. Over the past decade, there has been constant progress in developing several different architectures for realizing programmable photonic circuits that allow for realizing arbitrary discrete unitary operations with light. Here, we systematically investigate a general family of photonic circuits for realizing arbitrary unitaries based on a simple architecture that interlaces a fixed intervening layer with programmable phase shifter layers. We introduce a criterion for the intervening operator that guarantees the universality of this architecture for representing arbitrary N×N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$N \ imes N$$\\end{document} unitary operators with N+1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$N+1$$\\end{document} phase layers. We explore this criterion for different photonic components, including photonic waveguide lattices and meshes of directional couplers, which allows the identification of several families of photonic components that can serve as the intervening layers in the interlacing architecture. Our findings pave the way for efficiently designing and realizing novel families of programmable photonic integrated circuits for multipurpose analog information processing.

Remote cross-resonance gate between superconducting fixed-frequency qubits

High-fidelity quantum state transfer and remote entanglement between superconducting fixed-frequency qubits have not yet been realized. In this study, we propose an alternative remote cross-resonance gate. Considering multiple modes of a superconducting coaxial cable connecting qubits, we must find conditions under which the cross-resonance gate operates with a certain accuracy even in the presence of qubit frequency shifts due to manufacturing errors. For 0.25- and 0.5 m cables, remote cross-resonance gates with a concurrence of >99.9% in entanglement generation are obtained even with ±10 MHz frequency shifts. For a 1 m cable with a narrow mode spacing, a concurrence of 99.5% is achieved by reducing the coupling between the qubits and cable. The optimized echoed raised-cosine pulse duration is 150–400 ns, which is similar to the operation time of cross-resonance gates between neighboring qubits on a chip. The dissipation through the cable modes does not considerably affect the obtained results. Such high-precision quantum interconnects pave the way not only for scaling up quantum computer systems but also for nonlocal connections on a chip.

A Hybrid Organic‐Crystal‐Based Curved Waveguide Network for Producing, Splitting, and Transducing Multi‐Color Outputs

AbstractHybrid optical components and circuits that deal with multiple signal generation and processing are quintessential for neural networking systems. Herein, the study reports the fabrication of one such component, a hybrid directional coupler (HDC) from blue emissive (4,4′‐bis(2,6‐di(1H‐pyrazol‐1‐yl)pyridin‐4‐yl)biphenyl) (BPP) and green emissive (E)‐1‐(((5‐bromopyridin‐2‐yl)imino)methyl)naphthalen‐2‐ol (BPyIN) pseudo‐plastic molecular crystals. Initially, a BPyIN microcrystal optical waveguide (OW1) is shaped into a strained waveguide with five bends using an atomic force microscopy cantilever‐tip aided mechanophotonics approach. Later, a singly bent BPyIN waveguide (OW2) is integrated into one of the bends at the coupling region on a strained waveguide to produce a 2 × 2 monolithic directional coupler (DC). Later, this 2 × 2 DC is extended to a HDC by integrating a blue emissive BPP waveguide (OW3) at another bend on the deformed waveguide. The fabricated HDC can effectively split the incident light into three parts with different split ratios and deliver multi‐color outputs depending on the port receiving the input signal. The spontaneous generation and processing of various signals produced in the circuit helps in understanding the functioning of complex optical neural networks. The demonstration of such innovative optical components manifests their utility for diverse applications in neural networking and quantum computing systems.

Excitation of exchange spin waves in a magnetic insulator thin film at cryogenic temperatures

Spin waves and their quanta, magnons, are promising candidates for next-generation electronic devices, due to their low-power consumption and compatibility with radio-frequency-based electronic devices. For achieving magnon-based hybrid quantum systems for quantum memory and computation, the investigation of spin-wave propagation at cryogenic temperatures is highly required. In this article, we report the excitation and detection of exchange spin waves with wavelengths of tens of nanometers in an yttrium iron garnet (YIG) thin film at cryogenic temperatures. We find that the exchange spin waves are unidirectional in all temperature ranges, owing to the chiral dynamical dipolar coupling between the spin-wave mode in the YIG and the ferromagnetic resonance mode in the cobalt nanowire. Notably, a high exchange spin-wave group velocity of 2 km s−1 at 10 K is observed. Our results are promising for the development of high-speed and energy-efficient quantum magnonic devices operating at cryogenic temperatures.

Quantum Computing in The Cloud - A Systematic Literature Review

Quantum computing was proposed to simulate processes that surpass the capabilities of its counterpart, classical computing. Utilizing the principles of quantum mechanics, it improves the computing power of quantum computing. Top developers namely IBM, Rigetti, D-Wave, Qutech and Google have invested greatly in the technology. Nowadays, users can access the quantum computing system publicly over the network in a cloud environment, this system architecture is known as cloud-based quantum computing. However, different developers deliver different architecture and functionality of the system on their platforms. This has indirectly spawned a question of which cloud-based quantum computing platform is a better option based on certain specific requirements by an individual or group. The main objective of this study is to provide a proposed framework using the existing cloud-based service of quantum computing based on previous studies for users with their specific demands.

Ultra-compact electro-optic phase modulator based on a lithium niobate topological slow light waveguide.

Electro-optic modulators (EOMs) are essential devices of optical communications and quantum computing systems. In particular, ultra-compact EOMs are necessary for highly integrated photonic chips. Thin film lithium niobate materials are a promising platform for designing highly efficient EOMs. However, EOMs based on conventional waveguide structures are at a millimeter scale and challenging to scale down further, greatly hindering the capability of on-chip integration. Here, we design an EOM based on lithium niobate valley photonic crystal (VPC) structures for the first time. Due to the high effective refractive index introduced by the strong slow light effect, the EOM can achieve an ultra-compact size of 4 μm×14 μm with a half-wave voltage of 1.4 V. The EOM has a high transmittance of 0.87 in the 1068 nm because of the unique spin-valley locking effect in VPC structures. The design is fully compatible with current nanofabrication technology and immune to fabrication defects. Therefore, it opens a new possibility in designing lithium niobate electro-optic modulators and will find broad applications in optical communication and quantum photonic devices.

Testing precision and accuracy of weak value measurements in an IBM quantum system

Historically, weak values have been associated with weak measurements performed on quantum systems. Over the past two decades, a series of works have shown that weak values can be determined via measurements of arbitrary strength. One such proposal by Denkmayr et al. [Phys. Rev. Lett. 118, 010402 (2017)], carried out in neutron interferometry experiments, yielded better outcomes for strong than for weak measurements. We extend this scheme and explain how to implement it in an optical setting as well as in a quantum computational context. Our implementation in a quantum computing system provided by IBM confirms that weak values can be measured, with varying degrees of performance, over a range of measurement strengths. However, at least for this model, strong measurements do not always perform better than weak ones.

Universal quantum computing models: a resource-theoretic study

<sec>Quantum computing has been proven to be powerful, however, there are still great challenges for building real quantum computers due to the requirements of both fault-tolerance and universality. People still lack a systematic way to design fast quantum algorithms and identify the key quantum resources. In this work, we develop a resource-theoretic approach to characterize universal quantum computing models and the universal resources for quantum computing. </sec><sec>Our theory combines the framework of universal quantum computing model (UQCM) and the quantum resource theory (QRT). The former has played major roles in quantum computing, while the later was developed mainly for quantum information theory. Putting them together proves to be ‘win-win’: on one hand, using QRT can provide a resource-theoretic characterization of a UQCM, the relation among models and inspire new ones, and on the other hand, using UQCM offers a framework to apply resources, study relation among resources and classify them. </sec><sec>In quantum theory, we mainly study states, evolution, observable, and probability from measurements, and this motivates the introduction of different families of UQCMs. A family also includes generations depending on a hierarchical structure of resource theories. We introduce a table of UQCMs by first classifying two categories of models: one referring to the format of information, and one referring to the logical evolution of information requiring quantum error-correction codes. Each category contains a few families of models, leading to more than one hundred of them in total. Such a rich spectrum of models include some well-known ones that people use, such as the circuit model, the adiabatic model, but many of them are relatively new and worthy of more study in the future. Among them are the models of quantum von Neumann architectures established recently. This type of architecture or model circumvents the no-go theorems on both the quantum program storage and quantum control unit, enabling the construction of more complete quantum computer systems and high-level programming. </sec><sec>Correspondingly, each model is captured by a unique quantum resource. For instance, in the state family, the universal resource for the circuit model is coherence, for the local quantum Turing machine is bipartite entanglement, and for the cluster-state based, also known as measurement-based model is a specific type of entanglement relevant to symmetry-protected topological order. As program-storage is a central feature of the quantum von Neumann architecture, we find the quantum resources for it are quantum memories, which are dynamical resources closely related to entanglement. In other words, our classification of UQCMs also serves as a computational classification of quantum resources. This can be used to resolve the dispute over the computing power of resources, such as interference, entanglement, or contextuality. In all, we believe our theory lays down a solid framework to study computing models, resources, and design algorithms. </sec>

Unraveling quantum computing system architectures: An extensive survey of cutting-edge paradigms

Context:The convergence of physics and computer science in the realm of quantum computing systems has sparked a profound revolution within the computer industry. However, despite such promise, the existing focus on quantum software systems primarily centers on the generation of quantum source code, inadvertently overlooking the pivotal role of the overall software architecture. Objectives:In order to provide comprehensive guidance to researchers and practitioners engaged in quantum software development, employing an architecture-centered development model, an extensive literature review was conducted pertaining to existing research on quantum software architecture. The analysis encompasses a detailed examination of the characteristics exhibited by these studies and the identification of prospective challenges that lie ahead in the field of quantum software architecture. Methods:We have closely examined instances of quantum software engineering, quantum modeling languages, quantum design patterns, and quantum communication security to gain insights into the distinctive attributes associated with various software architecture approaches. Results:Our findings underscore the critical significance of prioritizing software architecture in the development of robust and efficient quantum software systems. Through the synthesis of these multifaceted aspects, both researchers and practitioners can devise quantum software solutions that are inherently architecture-centric. Conclusion:The software architecture of quantum computing systems plays a pivotal role in determining their ultimate success and usability. Given the ongoing advancements in quantum computing technology, the migration of traditional software architecture development methods to the domain of quantum software development holds significant importance.

Harmonic balance simulation of the influence of component uniformity and reliability on the performance of a Josephson traveling wave parametric amplifier

A Josephson traveling wave parametric amplifier (JTWPA), which is a quantum-limited amplifier with high gain and large bandwidth, is the core device of large-scale measurement and control systems for quantum computing. A typical JTWPA consists of thousands of Josephson junctions connected in series to form a transmission line and hundreds of shunt LC resonators periodically loaded along the line for phase matching. Because the variation of these capacitors and inductors can be detrimental to their high-frequency characteristics, the fabrication of a JTWPA typically necessitates precise processing equipment. To guide the fabrication process and further improve the design for manufacturability, it is necessary to understand how each electronic component affects the amplifier. In this paper, we use the harmonic balance method to conduct a comprehensive study on the impact of nonuniformity and fabrication yield of the electronic components on the performance of a JTWPA. The results provide insightful and scientific guidance for device design and fabrication processes.

Design Method of Meta Operators Based on Equivalence Class Distribution

Currently, there are many physical systems for quantum computing and to adapt to the physical characteristics of different systems, engineers have designed different basic gate groups for gate circuit calculation models. The quantum algorithm realizes the evolution of the quantum state by applying unitary operators to the quantum states, and the results are obtained by measuring the outputs. These operators will be done in the corresponding physical system by compiling and decomposing into hardware supported basic gates. Universal fundamental gates can construct all quantum algorithms, but their computational efficiency is limited. Drawing on the idea of meta operators in classical machine learning, by constructing a deep learning framework for deep learning models, the common computational logic of operators in different deep learning frameworks is abstracted as ‘meta operators’ [1, 2]. This article aims to study and propose the common computational logic of quantum computing with geometric equivalence class distribution methods, using the volume size of the equivalence class space as a performance indicator for meta operators and identifying the optimal meta operators to optimize the depth of the circuits in the experiments. Which proves the effectiveness of the design method proposed and provides solutions for quantum circuit optimization and dedicated gate design.