Sequencing Universal Quantum Gates for Arbitrary 2-Qubit Computations

Quantum computers can solve certain problems more efficiently than any possible conventional computer. Small quantum algorithms have been demonstrated on multiple quantum computing platforms, many specifically tailored in hardware to implement a particular algorithm or execute a limited number of computational paths. Here we demonstrate a five-qubit trapped-ion quantum computer that can be programmed in software to implement arbitrary quantum algorithms by executing any sequence of universal quantum logic gates. We compile algorithms into a fully connected set of gate operations that are native to the hardware and have a mean fidelity of 98 per cent. Reconfiguring these gate sequences provides the flexibility to implement a variety of algorithms without altering the hardware. As examples, we implement the Deutsch-Jozsa and Bernstein-Vazirani algorithms with average success rates of 95 and 90 per cent, respectively. We also perform a coherent quantum Fourier transform on five trapped-ion qubits for phase estimation and period finding with average fidelities of 62 and 84 per cent, respectively. This small quantum computer can be scaled to larger numbers of qubits within a single register, and can be further expanded by connecting several such modules through ion shuttling or photonic quantum channels.

We present a comprehensive mathematical framework establishing the foundations of holographic quantum computing, a novel paradigm that leverages holographic phenomena to achieve superior error correction and algorithmic efficiency. We rigorously demonstrate that quantum information can be encoded and processed using holographic principles, establishing fundamental theorems characterizing the error-correcting properties of holographic codes. We develop a complete set of universal quantum gates with explicit constructions and prove exponential speedups for specific classes of computational problems. Our framework demonstrates that holographic quantum codes achieve a code rate scaling as O( 1/ logn ) , superior to traditional quantum LDPC codes, while providing inherent protection against errors via geometric properties of the code structures. We prove a threshold theorem establishing that arbitrary quantum computations can be performed reliably when physical error rates fall below a constant threshold. Notably, our analysis suggests certain algorithms, including those involving high-dimensional state spaces and long-range interactions, achieve exponential speedups over both classical and conventional quantum approaches. This work establishes the theoretical foundations for a new approach to quantum computation that provides natural fault tolerance and scalability, directly addressing longstanding challenges of the field.

One of the current trends in quantum computing is the application of algebraic topological methods in the design of new algorithms and quantum computers, giving rise to topological quantum computing. One of the tools used in it is the Yang-Baxter equation whose solutions are interpreted as universal quantum gates. Lately, more general Yang-Baxter equations have been investigated, making progress as two-spectral equations and Yang-Baxter systems. This paper intends to apply these new findings to the field of topological quantum computation, more specifically, the proposition of the two-spectral Yang-Baxter operators as universal quantum gates for 2 qubits and 2 qutrits systems, obtaining 4x4 and 9x9 matrices respectively, and further elaboration of the corresponding Hamiltonian by the use of computer algebra software Mathematica® and its Qucalc package. In addition, possible physical systems to which the Yang-Baxter operators obtained can be applied are considered. In the present work it is demonstrated the utility of the Yang-Baxter equation to generate universal quantum gates and the power of computer algebra to design them; it is expected that these mathematical studies contribute to the further development of quantum computers

This paper explores the use of quantum computing for solving machine learning problems more efficiently. Today's quantum computers are rather primitive, so only relatively small machine learning problems can be solved at this time. Nevertheless, the machine learning problems described here that have been solved on quantum simulators or actual quantum computers indicates the potential power of quantum computers for solving computationally intensive machine learning problems such as the deep learning multi-layer neural networks.

Artificial Intelligence (AI)’s market is growing very fast all over the world, along with Deep Learning (DL) technologies requiring more and more data and speed to process them, in healthcare, agriculture, automotive, security, and in among several other industries. However, despite this AI rapid and increasing market expansion, there are numerous related challenges need to be tackled. In this paper, the purpose is to show through another structured approach derived from ARIZ algorithm and some principles coined by TrizStartup movement [1], some of the problems deep learning industries are trying to handle. This paper shows how TRIZ can be applied to fix one of those AI problems. In fact, due to DL neural networks (NN) hidden layers, their outputs are not reliable. If an error occurs, how could human reproduce the issue? Human are not able to identify activated neurons to analyse root causes of this malfunction. Therefore, reliability issue from hidden layers versus rapid AI market skyrocket, data and speed processing, generates innovation problems. In order to resolve this, principle 35-parameter changes with Althshuler Matrix, little people, Su-Field analysis, seventy-six standards solutions, have been used to generate quantum functions. The result described in this paper is a new function called QuantumReLU (QReLU), created with Quantum computer in order to extend classical activation function ReLU. It is then possible to fire neuron with activation function QReLU, and to use quantum states to identify activated neurons within hidden layers. Thus, Triz systematic approach led switching neural networks algorithms from classical to quantum computer, and therefore to build deep learning NN on quantum computer, based on the new QReLU activation function.

The discrete logarithm problem (DLP) plays an important role in modern cryptography since it cannot be efficiently solved on a classical computer. Currently, the DLP based on the hyperelliptic curve of genus 2 (HCDLP) is widely used in industry and also a research field of hot interest. At the same time, quantum computing, a new paradigm for computing based on quantum mechanics, provides the ability to solve certain hard problems that cannot be efficiently solved on classical computers. In this paper, we consider the problem of solving the HCDLP in the paradigm of quantum computing. We propose a quantum algorithm for solving the HCDLP by applying the framework of quantum algorithm designed by Shor. The key of the algorithm is the realization of divisor addition. We solve the key problem and get analytical results for divisor addition by geometric meaning of the group addition. Therefore, the procedure can be efficiently realized on a quantum computer using the basic modular arithmetic operations. Finally, we conclude that the HCDLP defined over an n-bit prime field $$\mathbb {F}_{p}$$ can be computed on a quantum computer with at most $$13n+2\lfloor \log _{2}n\rfloor +10$$ qubits using $$2624n^{3} \log _{2}n-2209.2n^{3} + 1792n^{2} \log _{2}n-3012.8n^{2}$$ Toffoli gates. For current parameters at comparable classical security levels, there are fewer qubits and Toffoli gates to solve the HCDLP than the ones to solve the DLP based on elliptic curves.

In this paper, we present the experimental realization of multi-qubit gates $% \Lambda_n(not) $ in macroscopic ensemble of three-qubit and four-qubit molecules. Instead of depending heavily on the two-bit universal gate, which served as the basic quantum operation in quantum computing, we use pulses of well-defined frequency and length that simultaneously apply to all qubits in a quantum register. It appears that this method is experimentally convenient when this procedure is extended to more qubits on some quantum computation, and it can also be used in other physical systems.

Fault-tolerant quantum computers that can solve hard problems rely on quantum error correction1. One of the most promising error correction codes is the surface code2, which requires universal gate fidelities exceeding an error correction threshold of 99 per cent3. Among the many qubit platforms, only superconducting circuits4, trapped ions5 and nitrogen-vacancy centres in diamond6 have delivered this requirement. Electron spin qubits in silicon7-15 are particularly promising for a large-scale quantum computer owing to their nanofabrication capability, but the two-qubit gate fidelity has been limited to 98 per cent owing to the slow operation16. Here we demonstrate a two-qubit gate fidelity of 99.5 per cent, along with single-qubit gate fidelities of 99.8 per cent, in silicon spin qubits by fast electrical control using a micromagnet-induced gradient field and a tunable two-qubit coupling. We identify the qubit rotation speed and coupling strength where we robustly achieve high-fidelity gates. We realize Deutsch-Jozsa and Grover search algorithms with high success rates using our universal gate set. Our results demonstrate universal gate fidelity beyond the fault-tolerance threshold and may enable scalable silicon quantum computers.

Making the right management decisions in the logging industry is a complex multi-factorial task. The multivariance of solutions consists of various options for the application of technological chains of logging operations and timber transportation. Indeed, today the market offers a lot of options for systems of forestry machines, with or without forest storage with timber transportation at different seasons. Previous studies propose mathematical dependencies, an algorithm, and methods to solve all these problems. It makes it possible to search for the maximum flow of minimum cost in the dynamic structure of the technological process of performing work at the enterprise. They determine the conditions for solving the problem by the graph method. However, the proposed calculations for graphs with a large number of vertices and arcs connecting them are very laborious and require a lot of time. To solve this problem, the article presents the development of a computer application that performs basic calculations and calculates the optimal technological sequence of operations. The algorithms of the application, its description and principle of operation have been presented. The developed program enables to automate the process of finding the optimal sequence of technological operations in the logging enterprise operating procedure. Upon receipt of the results, it is possible to compare and analyze various process options for decision making.

Because of the technical difficulty of building large quantum computers, it is important to be able to estimate how faithful a given implementation is to an ideal quantum computer. The common approach of completely characterizing the computation process via quantum process tomography requires an exponential amount of resources, and thus is not practical even for relatively small devices. We solve this problem by demonstrating that twirling experiments previously used to characterize the average fidelity of quantum memories efficiently can be easily adapted to estimate the average fidelity of the experimental implementation of important quantum computation processes, such as unitaries in the Clifford group, in a practical and efficient manner with applicability in current quantum devices. Using this procedure, we demonstrate state-of-the-art coherent control of an ensemble of magnetic moments of nuclear spins in a single crystal solid by implementing the encoding operation for a 3-qubit code with only a 1% degradation in average fidelity discounting preparation and measurement errors. We also highlight one of the advances that was instrumental in achieving such high fidelity control.

We present a general, systematic, and efficient method for decomposing any given exponential operator of bosonic mode operators, describing an arbitrary multimode Hamiltonian evolution, into a set of universal unitary gates. Although our approach is mainly oriented towards continuous-variable quantum computation, it may be used more generally whenever quantum states are to be transformed deterministically, e.g., in quantum control, discrete-variable quantum computation, or Hamiltonian simulation. We illustrate our scheme by presenting decompositions for various nonlinear Hamiltonians including quartic Kerr interactions. Finally, we conclude with two potential experiments utilizing offline-prepared optical cubic states and homodyne detections, in which quantum information is processed optically or in an atomic memory using quadratic light-atom interactions.

As we approach the era of quantum advantage, when quantum computers (QCs) can outperform any classical computer on particular tasks, there remains the difficult challenge of how to validate their performance. While algorithmic success can be easily verified in some instances such as number factoring or oracular algorithms, these approaches only provide pass/fail information of executing specific tasks for a single QC. On the other hand, a comparison between different QCs preparing nominally the same arbitrary circuit provides an insight for generic validation: a quantum computation is only as valid as the agreement between the results produced on different QCs. Such an approach is also at the heart of evaluating metrological standards such as disparate atomic clocks. In this paper, we report a cross-platform QC comparison using randomized and correlated measurements that results in a wealth of information on the QC systems. We execute several quantum circuits on widely different physical QC platforms and analyze the cross-platform state fidelities.

Quantum computation has seen rapid progress in the past years. Due to implementation complexity and cost, cloud-based quantum computing is strongly believed to be the most feasible framework for individual users. Universal blind quantum computing (UBQC) provides the protocol for secure delegation of arbitrary quantum computations and has received significant attention. However, one of the major challenges in UBQC is a secure and reliable transmission of a quantum state over a long distance. Herein, we improve the efficiency of UBQC using alternative photon sources. Our analysis shows that a heralded single-photon source can significantly improve the transmitted distance of UBQC and a modified coherent source can reduce the required transmitted number of pulses. Furthermore, we study the finite-data-size effect, which is a crucial for real-world applications. Our proposed scheme can be a promising alternative for the future development of UBQC.

Quantum error correction is a set of methods to protect quantum information—that is, quantum states—from unwanted environmental interactions (decoherence) and other forms of noise. The information is stored in a quantum error-correcting code, which is a subspace in a larger Hilbert space. This code is designed so that the most common errors move the state into an error space orthogonal to the original code space while preserving the information in the state. It is possible to determine whether an error has occurred by a suitable measurement and to apply a unitary correction that returns the state to the code space without measuring (and hence disturbing) the protected state itself. In general, codewords of a quantum code are entangled states. No code that stores information can protect against all possible errors; instead, codes are designed to correct a specific error set, which should be chosen to match the most likely types of noise. An error set is represented by a set of operators that can multiply the codeword state. Most work on quantum error correction has focused on systems of quantum bits, or qubits, which are two-level quantum systems. These can be physically realized by the states of a spin-1/2 particle, the polarization of a single photon, two distinguished levels of a trapped atom or ion, the current states of a microscopic superconducting loop, or many other physical systems. The most widely used codes are the stabilizer codes, which are closely related to classical linear codes. The code space is the joint +1 eigenspace of a set of commuting Pauli operators on n qubits, called stabilizer generators; the error syndrome is determined by measuring these operators, which allows errors to be diagnosed and corrected. A stabilizer code is characterized by three parameters [[n,k,d]], where n is the number of physical qubits, k is the number of encoded logical qubits, and d is the minimum distance of the code (the smallest number of simultaneous qubit errors that can transform one valid codeword into another). Every useful code has n>k; this physical redundancy is necessary to detect and correct errors without disturbing the logical state. Quantum error correction is used to protect information in quantum communication (where quantum states pass through noisy channels) and quantum computation (where quantum states are transformed through a sequence of imperfect computational steps in the presence of environmental decoherence to solve a computational problem). In quantum computation, error correction is just one component of fault-tolerant design. Other approaches to error mitigation in quantum systems include decoherence-free subspaces, noiseless subsystems, and dynamical decoupling.

We propose a simple scheme for implementing quantum logic gates with a string of two-level trapped cold ions outside the Lamb-Dicke limit. Two internal states of each ion are used as one computational qubit (CQ) and the collective vibration of ions acts as the information bus, i.e., bus qubit (BQ). Using the quantum dynamics for the laser-ion interaction as described by a generalized Jaynes-Cummings model, we show that quantum entanglement between any one CQ and the BQ can be coherently manipulated by applying classical laser beams. As a result, universal quantum gates, i.e. the one-qubit rotation and two-qubit controlled gates, can be implemented exactly. The required experimental parameters for the implementation, including the Lamb-Dicke (LD) parameter and the durations of the applied laser pulses, are derived. Neither the LD approximation for the laser-ion interaction nor the auxiliary atomic level is needed in the present scheme.