Design of a novel hybrid quantum deep neural network in INEQR images classification

We redesign the parameterized quantum circuit in the quantum deep neural network, construct a three-layer structure as the hidden layer, and then use classical optimization algorithms to train the parameterized quantum circuit, thereby propose a novel hybrid quantum deep neural network(HQDNN) used for image classification. After bilinear interpolation reduces the original image to a suitable size, an improved novel enhanced quantum representation(INEQR) is used to encode it into quantum states as the input of the HQDNN. Multi-layer parameterized quantum circuits are used as the main structure to implement feature extraction and classification. The output results of parameterized quantum circuits are converted into classical data through quantum measurements and then optimized on a classical computer. To verify the performance of the HQDNN, we conduct binary classification and three classification experiments on the MNIST(Modified National Institute of Standards and Technology) data set. In the first binary classification, the accuracy of 0 and 4 exceeds98%. Then we compare the performance of three classification with other algorithms, the results on two datasets show that the classification accuracy is higher than that of quantum deep neural network and general quantum convolutional neural network.

A Novel Scheduling Framework for Multi-Programming Quantum Computing in Cloud Environment

As cloud quantum computing gains broader acceptance,a growing quantity of researchers are directing their focus towards this domain.Nevertheless,the rapid surge in demand for cloud-based quantum computing resources has led to a scarcity,which in turn hampers users from achieving optimal satisfaction.Therefore,cloud quantum computing service providers require a unified analysis and scheduling framework for their quantumresources and user jobs to meet the ever-growing usage demands.This paper introduces a new multi-programming scheduling framework for quantum computing in a cloud environment.The framework addresses the issue of limited quantum computing resources in cloud environments and ensures a satisfactory user experience.It introduces three innovative designs:1)Our framework automatically allocates tasks to different quantum backends while ensuring fairness among users by considering both the cloud-based quantum resources and the user-submitted tasks.2)Multi-programming mechanism is employed across different quantum backends to enhance the overall throughput of the quantum cloud.In comparison to conventional task schedulers,our proposed framework achieves a throughput improvement of more than two-fold in the quantum cloud.3)The framework can balance fidelity and user waiting time by adaptively adjusting scheduling parameters.

Quantum circuit-based proxy blind signatures:A novel approach and experimental evaluation on the IBM quantum cloud platform

This paper presents a novel approach to proxy blind signatures in the realm of quantum circuits,aiming to enhance security while safeguarding sensitive information.The main objective of this research is to introduce a quantum proxy blind signature(QPBS)protocol that utilizes quantum logical gates and quantum measurement techniques.The QPBS protocol is constructed by the initial phase,proximal blinding message phase,remote authorization and signature phase,remote validation,and de-blinding phase.This innovative design ensures a secure mechanism for signing documents without revealing the content to the proxy signer,providing practical security authentication in a quantum environment under the assumption that the CNOT gates are securely implemented.Unlike existing approaches,our proposed QPBS protocol eliminates the need for quantum entanglement preparation,thus simplifying the implementation process.To assess the effectiveness and robustness of the QPBS protocol,we conduct comprehensive simulation studies in both ideal and noisy quantum environments on the IBM quantum cloud platform.The results demonstrate the superior performance of the QPBS algorithm,highlighting its resilience against repudiation and forgeability,which are key security concerns in the realm of proxy blind signatures.Furthermore,we have established authentic security thresholds(82.102%)in the presence of real noise,thereby emphasizing the practicality of our proposed solution.

Threshold-independent method for single-shot readout of spin qubits in semiconductor quantum dots

The single-shot readout data process is essential for the realization of high-fidelity qubits and fault-tolerant quantum algorithms in semiconductor quantum dots. However, the fidelity and visibility of the readout process are sensitive to the choice of the thresholds and limited by the experimental hardware. By demonstrating the linear dependence between the measured spin state probabilities and readout visibilities along with dark counts, we describe an alternative threshold-independent method for the single-shot readout of spin qubits in semiconductor quantum dots. We can obtain the extrapolated spin state probabilities of the prepared probabilities of the excited spin state through the threshold-independent method. We then analyze the corresponding errors of the method, finding that errors of the extrapolated probabilities cannot be neglected with no constraints on the readout time and threshold voltage. Therefore, by limiting the readout time and threshold voltage, we ensure the accuracy of the extrapolated probability. We then prove that the efficiency and robustness of this method are 60 times larger than those of the most commonly used method. Moreover, we discuss the influence of the electron temperature on the effective area with a fixed external magnetic field and provide a preliminary demonstration for a single-shot readout of up to 0.7K/1.5T in the future.

Electric field dependence of spin qubit in a Si-MOS quantum dot

Valley, the intrinsic feature of silicon, is an inescapable subject in silicon-based quantum computing. At the spin–valley hotspot, both Rabi frequency and state relaxation rate are significantly enhanced. With protection against charge noise, the valley degree of freedom is also conceived to encode a qubit to realize noise-resistant quantum computing.Here, based on the spin qubit composed of one or three electrons, we characterize the intrinsic properties of valley in an isotopically enriched silicon quantum dot(QD) device. For one-electron qubit, we measure two electric-dipole spin resonance(EDSR) signals which are attributed to partial occupation of two valley states. The resonance frequencies of two EDSR signals have opposite electric field dependences. Moreover, we characterize the electric field dependence of the upper valley state based on three-electron qubit experiments. The difference of electric field dependences of the two valleys is 52.02 MHz/V, which is beneficial for tuning qubit frequency to meet different experimental requirements. As an extension of electrical control spin qubits, the opposite electric field dependence is crucial for qubit addressability,individual single-qubit control and two-qubit gate approaches in scalable quantum computing.

Enhancing IoT Security:Quantum-Level Resilience against Threats

The rapid growth of the Internet of Things(IoT)operations has necessitated the incorporation of quantum computing technologies tomeet its expanding needs.This integration ismotivated by the need to solve the specific issues provided by the expansion of IoT and the potential benefits that quantum computing can offer in this scenario.The combination of IoT and quantum computing creates new privacy and security problems.This study examines the critical need to prevent potential security concerns from quantum computing in IoT applications.We investigate the incorporation of quantum computing approaches within IoT security frameworks,with a focus on developing effective security mechanisms.Our research,which uses quantum algorithms and cryptographic protocols,provides a unique solution to protecting sensitive information and assuring the integrity of IoT systems.We rigorously analyze critical quantum computing security properties,building a hierarchical framework for systematic examination.We offer concrete solutions flexible to diverse aswell as ambiguous opinions through using a unified computational model with analytical hierarchy process(AHP)multi-criteria decision-making(MCDM)as the technique for ordering preferences by similarity to ideal solutions(TOPSIS)in a fuzzy environment.This study adds practical benefit by supporting practitioners in recognizing,choosing,and prioritizing essential security factors from the standpoint of quantum computing.Our approach is a critical step towards improving quantum-level security in IoT systems,strengthening their resilience against future threats,and preserving the IoT ecosystem’s long-term prosperity.

Tackling the Existential Threats from Quantum Computers and AI

Although AI and quantum computing (QC) are fast emerging as key enablers of the future Internet, experts believe they pose an existential threat to humanity. Responding to the frenzied release of ChatGPT/GPT-4, thousands of alarmed tech leaders recently signed an open letter to pause AI research to prepare for the catastrophic threats to humanity from uncontrolled AGI (Artificial General Intelligence). Perceived as an “epistemological nightmare”, AGI is believed to be on the anvil with GPT-5. Two computing rules appear responsible for these risks. 1) Mandatory third-party permissions that allow computers to run applications at the expense of introducing vulnerabilities. 2) The Halting Problem of Turing-complete AI programming languages potentially renders AGI unstoppable. The double whammy of these inherent weaknesses remains invincible under the legacy systems. A recent cybersecurity breakthrough shows that banning all permissions reduces the computer attack surface to zero, delivering a new zero vulnerability computing (ZVC) paradigm. Deploying ZVC and blockchain, this paper formulates and supports a hypothesis: “Safe, secure, ethical, controllable AGI/QC is possible by conquering the two unassailable rules of computability.” Pursued by a European consortium, testing/proving the proposed hypothesis will have a groundbreaking impact on the future digital infrastructure when AGI/QC starts powering the 75 billion internet devices by 2025.

Influence of Quantum Information Technology on International Security

Humanity is currently undergoing the fourth industrial revolution,characterized by advancements in artificial intelligence,clean energy,quantum information technology,virtual reality,and biotechnology.This technological revolution is poised to have a profound impact on the world.Quantum information technology encompasses both quantum computing and the transmission of quantum information.This article aims to integrate quantum information technology with international security concerns,exploring its implications for international security and envisioning its groundbreaking significance.

Defining Quantum Advantage for Building a Sustainable MVP to Deliver Quantum Computing Services

Quantum Computing (QC) is hailed as the future of computers. After Google’s claim of achieving Quantum Supremacy in 2019, several groups challenged the claim. Some QC experts attribute catastrophic risks that unrestrained QC may cause in the future by collapsing the current cryptographic cybersecurity infrastructure. These predictions are relevant only if QC becomes commercially viable and sustainable in the future. No technology can be a one-way ticket to catastrophe, and neither can the definition of superiority of that technology be. If there are catastrophic risks, large-scale QC can never enter the public domain as a minimum viable product (MVP) unless there are safeguards in place. Those safeguards should obviously become an integral part of the definition of its superiority over the legacy systems. NIST (National Institute of Standards & Technology) is pursuing the standardization of Post Quantum Cryptography (PQC) as that safeguard. However, with all the 82 candidate PQCs failing and companies already offering QC as a service, there’s an urgent need for an alternate strategy to mitigate the impending Q-Day threat and render QC sustainable. Our research proposes a novel encryption-agnostic cybersecurity approach to safeguard QC. It articulates a comprehensive definition of an MVP that can potentially set a sustainable gold standard for defining commercially viable quantum advantage over classical computing.

Mechanism of Universal Quantum Computation in the Brain

In this paper, the authors extend [1] and provide more details of how the brain may act like a quantum computer. In particular, positing the difference between voltages on two axons as the environment for ions undergoing spatial superposition, we argue that evolution in the presence of metric perturbations will differ from that in the absence of these waves. This differential state evolution will then encode the information being processed by the tract due to the interaction of the quantum state of the ions at the nodes with the “controlling’ potential. Upon decoherence, which is equal to a measurement, the final spatial state of the ions is decided and it also gets reset by the next impulse initiation time. Under synchronization, several tracts undergo such processes in synchrony and therefore the picture of a quantum computing circuit is complete. Under this model, based on the number of axons in the corpus callosum alone, we estimate that upwards of 50 million quantum states might be prepared and evolved every second in this white matter tract, far greater processing than any present quantum computer can accomplish.

From Standard Policy-Based Zero Trust to Absolute Zero Trust (AZT): A Quantum Leap to Q-Day Security

Cybercrime is projected to cost a whopping $23.8 Trillion by 2027. This is essentially because there’s no computer network that’s not vulnerable. Fool-proof cybersecurity of personal data in a connected computer is considered practically impossible. The advent of quantum computers (QC) will worsen cybersecurity. QC will be a boon for data-intensive industries by drastically reducing the computing time from years to minutes. But QC will render our current cryptography vulnerable to quantum attacks, breaking nearly all modern cryptographic systems. Before QCs with sufficient qubits arrive, we must be ready with quantum-safe strategies to protect our ICT infrastructures. Post-quantum cryptography (PQC) is being aggressively pursued worldwide as a defence from the potential Q-day threat. NIST (National Institute of Standards and Technology), in a rigorous process, tested 82 PQC schemes, 80 of which failed after the final round in 2022. Recently the remaining two PQCs were also cracked by a Swedish and a French team of cryptographers, placing NIST’s PQC standardization process in serious jeopardy. With all the NIST-evaluated PQCs failing, there’s an urgent need to explore alternate strategies. Although cybersecurity heavily relies on cryptography, recent evidence indicates that it can indeed transcend beyond encryption using Zero Vulnerability Computing (ZVC) technology. ZVC is an encryption-agnostic absolute zero trust (AZT) approach that can potentially render computers quantum resistant by banning all third-party permissions, a root cause of most vulnerabilities. Unachievable in legacy systems, AZT is pursued by an experienced consortium of European partners to build compact, solid-state devices that are robust, resilient, energy-efficient, and with zero attack surface, rendering them resistant to malware and future Q-Day threats.

Leveraging Quantum Computing for the Ising Model to Simulate Two Real Systems: Magnetic Materials and Biological Neural Networks (BNNs)

Quantum computing is a field with increasing relevance as quantum hardware improves and more applications of quantum computing are discovered. In this paper, we demonstrate the feasibility of modeling Ising Model Hamiltonians on the IBM quantum computer. We developed quantum circuits to simulate these systems more efficiently for both closed and open boundary Ising models, with and without perturbations. We tested these various geometries of systems in both 1-D and 2-D space to mimic two real systems: magnetic materials and biological neural networks (BNNs). Our quantum model is more efficient than classical computers, which can struggle to simulate large, complex systems of particles.

The application of quantum coherence as a resource

Quantum coherence is a basic concept in quantum mechanics, representing one of the most fundamental characteristics that distinguishes quantum mechanics from classical physics. Quantum coherence is the basis for multi-particle interference and quantum entanglement. It is also the essential ingredient for various physical phenomena in quantum optics, quantum information, etc. In recent years, with the proposal of a quantum coherence measurement scheme based on a resource theory framework, quantum coherence as a quantum resource has been extensively investigated. This article reviews the resource theories of quantum coherence and introduces the important applications of quantum coherence in quantum computing,quantum information, and interdisciplinary fields, particularly in quantum thermodynamics and quantum biology. Quantum coherence and its applications are still being explored and developed. We hope this review can provide inspiration for relevant research.

High-fidelity universal quantum gates for hybrid systems via the practical photon scattering

High-fidelity quantum logic gates are essential in quantum computation,and both photons and electron spins in quantum dots(QDs)have their own unique advantages in implementing quantum computation.It is of critical significance to achieve high-fidelity quantum gates for photon-QD hybrid systems.Here,we propose two schemes for implementing high-fidelity universal quantum gates including Toffoli gate and Fredkin gate for photon-QD hybrid systems,utilizing the practical scattering of a single photon off a QD-cavity system.The computation errors from the imperfections involved in the practical scattering are detected and prevented from arising in the final results of the two gates.Accordingly,the unity fidelity of each quantum gate is obtained in the nearly realistic condition,and the requirement for experimental realization is relaxed.Furthermore,the quantum circuits for the two gates are compact and no auxiliary qubits are required,which would also be the advantages regarding their experimental feasibility.These features indicate that our schemes may be useful in the practical quantum computation tasks.

Chiral current regulation and detection of Berry phase in triangular triple quantum dots

Based on the hierarchical equations of motion(HEOM)calculation,we theoretically investigate the corresponding control of a triangular triple-quantum-dots(TTQD)ring which is connected to two reservoirs.We initially demonstrate by adding bias voltage and further adjusting the coupling strength between quantum dots,the chiral current induced by bias will go through a transformation of clockwise to counterclockwise direction and an unprecedented effective Hall angle will be triggered.The transformation is very rapid,with a corresponding characteristic time of 80-200 ps.In addition,by adding a magnetic flux to compensate for the chiral current in the original system,we elucidate the relationship between the applied magnetic flux and the Berry phase,which can realize direct measurement of the chiral current and reveal the magnetoelectric coupling relationship.

Blind quantum computation with a client performing different single-qubit gates

In the field of single-server blind quantum computation(BQC), a major focus is to make the client as classical as possible. To achieve this goal, we propose two single-server BQC protocols to achieve verifiable universal quantum computation. In these two protocols, the client only needs to perform either the gate T(in the first protocol) or the gates H and X(in the second protocol). With assistance from a single server, the client can utilize his quantum capabilities to generate some single-qubit states while keeping the actual state of these qubits confidential from others. By using these single-qubit states, the verifiable universal quantum computation can be achieved.

Energy shift and subharmonics induced by nonlinearity in a quantum dot system

The presence of anticrossings induced by coupling between two states causes curvature in energy levels, yielding a nonlinearity in the quantum system. When the system is driven back and forth along the bending energy levels, subharmonic transitions and energy shifts can be observed, which would cause a significant influence as the system is applied to quantum computing. In this paper, we study a longitudinally driven singlet-triplet(ST) system in a double quantum dot(DQD)system, and illustrate the consequences of nonlinearity by driving the system close to the anticrossings. We provide a straightforward theory to quantitatively describe the energy shift and subharmonics caused by nonlinearity, and find good agreement between our theoretical result and the numerical simulation. Our results reveal the existence of nonlinearity in the vicinity of anticrossings and provide a direct way of analytically assessing its impact, which can be applied to other quantum systems without excessive labor.

Lorentz quantum computer

A theoretical model of computation is proposed based on Lorentz quantum mechanics.Besides the standard qubits,this model has an additional bit,which we call hyperbolic bit(or hybit in short).A set of basic logical gates are constructed and their universality is proved.As an application,a search algorithm is designed for this computer model and is found to be exponentially faster than Grover's search algorithm.

Realization of high-fidelity and robust geometric gates with time-optimal control technique in superconducting quantum circuit

One of the key features required to realize fault-tolerant quantum computation is the robustness of quantum gates against errors.Since geometric quantum gate is naturally insensitivity to noise,it appears to be a promising routine to achieve high-fidelity,robust quantum gates.The implementation of geometric quantum gate however faces some troubles such as its complex interaction among multiple energy levels.Moreover,traditional geometric schemes usually take more time than equivalent dynamical ones.Here,we experimentally demonstrate a geometric gate scheme with the time-optimal control(TOC)technique in a superconducting quantum circuit.With a transmon qubit and operations restricted to two computational levels,we implement a set of geometric gates which exhibit better robustness features against control errors than the dynamical counterparts.The measured fidelities of TOC X gate and X/2 gate are 99.81%and 99.79%respectively.Our work shows a promising routine toward scalable fault-tolerant quantum computation.

Quantum Computing Based Neural Networks for Anomaly Classification in Real-Time Surveillance Videos

For intelligent surveillance videos,anomaly detection is extremely important.Deep learning algorithms have been popular for evaluating realtime surveillance recordings,like traffic accidents,and criminal or unlawful incidents such as suicide attempts.Nevertheless,Deep learning methods for classification,like convolutional neural networks,necessitate a lot of computing power.Quantum computing is a branch of technology that solves abnormal and complex problems using quantum mechanics.As a result,the focus of this research is on developing a hybrid quantum computing model which is based on deep learning.This research develops a Quantum Computing-based Convolutional Neural Network(QC-CNN)to extract features and classify anomalies from surveillance footage.A Quantum-based Circuit,such as the real amplitude circuit,is utilized to improve the performance of the model.As far as my research,this is the first work to employ quantum deep learning techniques to classify anomalous events in video surveillance applications.There are 13 anomalies classified from the UCF-crime dataset.Based on experimental results,the proposed model is capable of efficiently classifying data concerning confusion matrix,Receiver Operating Characteristic(ROC),accuracy,Area Under Curve(AUC),precision,recall as well as F1-score.The proposed QC-CNN has attained the best accuracy of 95.65 percent which is 5.37%greater when compared to other existing models.To measure the efficiency of the proposed work,QC-CNN is also evaluated with classical and quantum models.