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.

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

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.

Quafu-RL:The cloud quantum computers based quantum reinforcement learning

With the rapid advancement of quantum computing,hybrid quantum–classical machine learning has shown numerous potential applications at the current stage,with expectations of being achievable in the noisy intermediate-scale quantum(NISQ)era.Quantum reinforcement learning,as an indispensable study,has recently demonstrated its ability to solve standard benchmark environments with formally provable theoretical advantages over classical counterparts.However,despite the progress of quantum processors and the emergence of quantum computing clouds,implementing quantum reinforcement learning algorithms utilizing parameterized quantum circuits(PQCs)on NISQ devices remains infrequent.In this work,we take the first step towards executing benchmark quantum reinforcement problems on real devices equipped with at most 136 qubits on the BAQIS Quafu quantum computing cloud.The experimental results demonstrate that the policy agents can successfully accomplish objectives under modified conditions in both the training and inference phases.Moreover,we design hardware-efficient PQC architectures in the quantum model using a multi-objective evolutionary algorithm and develop a learning algorithm that is adaptable to quantum devices.We hope that the Quafu-RL can be a guiding example to show how to realize machine learning tasks by taking advantage of quantum computers on the quantum cloud platform.

Quafu-Qcover:Explore combinatorial optimization problems on cloud-based quantum computers

We introduce Quafu-Qcover,an open-source cloud-based software package developed for solving combinatorial optimization problems using quantum simulators and hardware backends.Quafu-Qcover provides a standardized and comprehensive workflow that utilizes the quantum approximate optimization algorithm(QAOA).It facilitates the automatic conversion of the original problem into a quadratic unconstrained binary optimization(QUBO)model and its corresponding Ising model,which can be subsequently transformed into a weight graph.The core of Qcover relies on a graph decomposition-based classical algorithm,which efficiently derives the optimal parameters for the shallow QAOA circuit.Quafu-Qcover incorporates a dedicated compiler capable of translating QAOA circuits into physical quantum circuits that can be executed on Quafu cloud quantum computers.Compared to a general-purpose compiler,our compiler demonstrates the ability to generate shorter circuit depths,while also exhibiting superior speed performance.Additionally,the Qcover compiler has the capability to dynamically create a library of qubits coupling substructures in real-time,utilizing the most recent calibration data from the superconducting quantum devices.This ensures that computational tasks can be assigned to connected physical qubits with the highest fidelity.The Quafu-Qcover allows us to retrieve quantum computing sampling results using a task ID at any time,enabling asynchronous processing.Moreover,it incorporates modules for results preprocessing and visualization,facilitating an intuitive display of solutions for combinatorial optimization problems.We hope that Quafu-Qcover can serve as an instructive illustration for how to explore application problems on the Quafu cloud quantum computers.

The Future of Quantum Computer Advantage

As technological innovations in computers begin to advance past their limit (Moore’s law), a new problem arises: What computational device would emerge after the classical supercomputers reach their physical limitations? At this moment in time, quantum computers are at their starting stage and there are already some strengths and advantages when compared with modern, classical computers. In its testing period, there are a variety of ways to create a quantum computer by processes such as the trapped-ion and the spin-dot methods. Nowadays, there are many drawbacks with quantum computers such as issues with decoherence and scalability, but many of these issues are easily emended. Nevertheless, the benefits of quantum computers at the moment outweigh the potential drawbacks. These benefits include its use of many properties of quantum mechanics such as quantum superposition, entanglement, and parallelism. Using these basic properties of quantum mechanics, quantum computers are capable of achieving faster computational times for certain problems such as finding prime factors of an integer by using Shor’s algorithm. From the advantages such as faster computing times in certain situations and higher computing powers than classical computers, quantum computers have a high probability to be the future of computing after classical computers hit their peak.

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.

Quantum Computer on Nvidia GPU

Geometric Algebra formalism opens the door to developing a theory deeper than conventional quantum mechanics. Generalizations, stemming from implementation of complex numbers as geometrically feasible objects in three dimensions, unambiguous definition of states, observables, measurements, Maxwell equations solution in those terms, bring into reality a kind of physical fields spreading through the whole three-dimensional space and values of the time parameter. The fields can be modified instantly in all points of space and time values, thus eliminating the concept of cause and effect, and perceiving of one-directional time. In the suggested theory all measured observable values get available all together, not through looking one by one. In this way quantum computer appeared to be a kind of analog computer keeping and instantly processing information by and on sets of objects possessing an infinite number of degrees of freedom. As practical implementation, the multithread GPUs bearing the CUDA language functionality allow to simultaneously calculate observable measurement values at a number of space/time discrete points only restricted by the GPU threads capacity.

Duality Computing in Quantum Computers

In this letter,we propose a duality computing mode,which resembles particle-wave duality property whena quantum system such as a quantum computer passes through a double-slit.In this mode,computing operations arenot necessarily unitary.The duality mode provides a natural link between classical computing and quantum computing.In addition,the duality mode provides a new tool for quantum algorithm design.

<i>C</i>¹²- <i>C</i>¹³Diamond Quantum Computer with Longitudinal rf-Magnetic Field

In the diamond C12 (nuclear spin zero) structure with a linear chain of C13 (nuclear spin one half) atoms is applied to a transverse static field with respect of this linear chain, having a gradient along the linear chain, and it is also applied to an rf-magnetic field in a plane with a component in the direction of the static field. It is shown that one qubit rotation, the Controlled-Not (CNOT), the Controlled-Controlled-NoT (CCNOT) quantum gates, and teleportation algorithm can be implemented on this structure using integer multiples of electromagnetic π-pulses. Therefore, a quantum computer can be constructed in this form.

Quantum Simulation of 2p-πElectronic Hamiltonian in Molecular Ethylene by Using an NMR Quantum Computer

Classical simulation of a quantum system is a hard problem. It’s known that these problems can be solved efficiently by using quantum computers. This study demonstrates the simulation of the molecular Hamiltonian of 2p-π electrons of ethylene in order to calculate the ground state energy. The ground state energy is estimated by an iterative phase estimation algorithm. The ground state is prepared by the adiabatic state preparation and the implementation of the procedure is carried out by numerical simulation of two-qubit NMR quantum simulator. The readout scheme of the simulator is performed by extracting binary bits via NMR interferometer.

Empirical Analysis of Decision Making of an AI Agent on IBM’s 5Q Quantum Computer

A recent work has shown that using an ion trap quantum processor can speed up the decision making of a reinforcement learning agent. Its quantum advantage is observed when the external environment changes, and then agent needs to relearn again. One character of this quantum hardware system discovered in this study is that it tends to overestimate the values used to determine the actions the agent will take. IBM’s five qubit superconducting quantum processor is a popular quantum platform. The aims of our study are twofold. First we want to identify the hardware characteristic features of IBM’s 5Q quantum computer when running this learning agent, compared with the ion trap processor. Second, through careful analysis, we observe that the quantum circuit employed in the ion trap processor for this agent could be simplified. Furthermore, when tested on IBM’s 5Q quantum processor, our simplified circuit demonstrates its enhanced performance over the original circuit on one of the hard learning tasks investigated in the previous work. We also use IBM’s quantum simulator when a good baseline is needed to compare the performances. As more and more quantum hardware devices are moving out of the laboratory and becoming generally available to public use, our work emphasizes the fact that the features and constraints of the quantum hardware could take a toll on the performance of quantum algorithms.

Optimized quantum singular value thresholding algorithm based on a hybrid quantum computer

Quantum singular value thresholding(QSVT) algorithm,as a core module of many mathematical models,seeks the singular values of a sparse and low rank matrix exceeding a threshold and their associated singular vectors.The existing all-qubit QSVT algorithm demands lots of ancillary qubits,remaining a huge challenge for realization on nearterm intermediate-scale quantum computers.In this paper,we propose a hybrid QSVT(HQSVT) algorithm utilizing both discrete variables(DVs) and continuous variables(CVs).In our algorithm,raw data vectors are encoded into a qubit system and the following data processing is fulfilled by hybrid quantum operations.Our algorithm requires O [log(MN)] qubits with0(1) qumodes and totally performs 0(1) operations,which significantly reduces the space and runtime consumption.

Study of Decoherence of Elementary Gates Implemented in a Chain of Few Nuclear Spins Quantum Computer Model

We study the phenomenon of decoherence during the operation of one qubit transformation, controlled-not (CNOT) and controlled-controlled-not (C2NOT) quantum gates in a quantum computer model formed by a linear chain of three nuclear spins system. We make this study with different type of environments, and we determine the associated decoherence time as a function of the dissipative parameter. We found that the dissipation parameter to get a well defined quantum gates (without significant decoherence) must be within the range of . We also study the behavior of the purity parameter for these gates and different environments and found linear or quadratic decays of this parameter depending on the type of environments.

Preservation of quantum states via a super-Zeno effect on ensemble quantum computers

Following a recent proposal by Dhar et al （2006 Phys. Rev. Lett. 96 100405）, we demonstrate experimentally the preservation of quantum states in a two-qubit system based on a super-Zeno effect using liquid-state nuclear magnetic resonance techniques. Using inverting radiofrequency pulses and delicately selecting time intervals between two pulses, we suppress the effect of decoherence of quantum states. We observe that preservation of the quantum state ｜11〉 with the super-Zeno effect is three times more efficient than the ordinary one with the standard Zeno effect.

Long-Range Interaction Enhanced Adiabatic Quantum Computers

A quantum computer is not necessarily alone,e.g.,thousands and millions of quantum computers are simultaneously working together for adiabatic quantum computers based on nuclear spins.Long-range interaction is inevitable between these nuclear spin qubits.Here we investigate the effect of long-range dipolar interaction between different adiabatic quantum computers.Our analytical and numerical results show that the dipolar interaction can enhance the final fidelity in adiabatic quantum computation for solving the factorization problem,when the overall interaction is negative.The enhancement will become more prominent if a single quantum computer encounters an extremely small energy gap which occurs more likely for larger-size systems.

Possible schemes of calculation modeling in a quantum computer

In the present work a possibility of computation modeling, which should be realized in a real quantum computer, is discussed. In this connection two models of a device, which work is determined by the structure and dynamics of real molecular systems are reported.

Formulation of the Social Workers’ Problem in Quadratic Unconstrained Binary Optimization Form and Solve It on a Quantum Computer

The problem of social workers visiting their patients at home is a class of combinatorial optimization problems and belongs to the class of problems known as NP-Hard. These problems require heuristic techniques to provide an efficient solution in the best of cases. In this article, in addition to providing a detailed resolution of the social workers’ problem using the Quadratic Unconstrained Binary Optimization Problems (QUBO) formulation, an approach to mapping the inequality constraints in the QUBO form is given. Finally, we map it in the Hamiltonian of the Ising model to solve it with the Quantum Exact Solver and Variational Quantum Eigensolvers (VQE). The quantum feasibility of the algorithm will be tested on IBMQ computers.

Five Experimental Tests on the 5-Qubit IBM Quantum Computer

The 5-qubit quantum computer prototypes that IBM has given open access to on the cloud allow the implementation of real experiments on a quantum processor. We present the results obtained in five experimental tests performed on these computers: dense coding, quantum Fourier transforms, Bell’s inequality, Mermin’s inequalities (up to n=5) and the construction of the prime state . These results serve to assess the functioning of the IBM 5Q chips.

Empirical Analysis of a Quantum Classifier Implemented on IBM’s 5Q Quantum Computer

The development of artificial intelligence today is marked with increased computational power, new algorithms, and big data. One such milestone impressive achievement in this area is Google’s AlphaGo. However, this advancement is beginning to face increasing challenges and the major bottleneck of AI today is the lack of adequate computing power in the processing of big data. Quantum computing offers a new and viable solution to deal with these challenges. A recent work designed a quantum classifier that runs on IBM’s five qubit quantum computer and tested its performance on the Iris data set as well as a circles data set. As quantum machine learning is still an emerging discipline, it may be enlightening to conduct an empirical analysis of this quantum classifier on some artificial datasets to help learn its unique features and potentials. Our work on the quantum classifier can be summarized in three parts. The first is to run its original version as a binary classifier on some artificial datasets using visualization to reveal the quantum nature of this algorithm, and the second is to analyze the swap operation utilized in its original circuit due to the hardware constraint and investigate its impact on the performance of the classifier. The last part is to extend the original circuit for binary classification to a circuit for multiclass classification and test its performance. Our findings shed new light on how this quantum classifier works.

Josephson Fourier Spectrometer Based on HTSP: Construction and Quantum Computer Realization Problem

The possibility of creating a spectrometer of THz range, which is based on non-stationary Josephson effect in HTSP is considered. Simple design of Josephson junction adjustable at cryogenic conditions is proposed. Using of such device for solving the problem of factorization of high value numbers, which in fact is the only motivation for creating a quantum computer, is discussed.