A quantum Hopfield associative memory implemented on an actual quantum processor

In this work, we present a Quantum Hopfield Associative Memory (QHAM) and demonstrate its capabilities in simulation and hardware using IBM Quantum Experience.. The QHAM is based on a quantum neuron design which can be utilized for many different machine learning applications and can be implemented on real quantum hardware without requiring mid-circuit measurement or reset operations. We analyze the accuracy of the neuron and the full QHAM considering hardware errors via simulation with hardware noise models as well as with implementation on the 15-qubit ibmq_16_melbourne device. The quantum neuron and the QHAM are shown to be resilient to noise and require low qubit overhead and gate complexity. We benchmark the QHAM by testing its effective memory capacity and demonstrate its capabilities in the NISQ-era of quantum hardware. This demonstration of the first functional QHAM to be implemented in NISQ-era quantum hardware is a significant step in machine learning at the leading edge of quantum computing.

Efficient Designs of Quantum Adder/Subtractor Using Universal Reversible Gate on IBM Q

Reversible arithmetic and logic unit (ALU) is a necessary part of quantum computing. In this work, we present improved designs of reversible half and full addition and subtraction circuits. The proposed designs are based on a universal one type gate (G gate library). The G gate library can generate all possible permutations of the symmetric group. The presented designs are multi-function circuits that are capable of performing additional logical operations. We achieve a reduction in the quantum cost, gate count, number of constant inputs, and delay with zero garbage, compared to relevant results obtained by others. The experimental results using IBM Quantum Experience (IBM Q) illustrate the success probability of the proposed designs.

An improved novel quantum image representation and its experimental test on IBM quantum experience

Quantum image representation (QIR) is a necessary part of quantum image processing (QIP) and plays an important role in quantum information processing. To address the problems that NCQI cannot handle images with inconsistent horizontal and vertical position sizes and multi-channel image processing, an improved color digital image quantum representation (INCQI) model based on NCQI is proposed in this paper. The INCQI model can process color images and facilitate multi-channel quantum image transformations and transparency information processing of images using auxiliary quantum bits. In addition, the quantum image control circuit was designed based on INCQI. And quantum image preparation experiments were conducted on IBM Quantum Experience (IBMQ) to verify the feasibility and effectiveness of INCQI quantum image preparation. The prepared image information was obtained by quantum measurement in the experiment, and the visualization of quantum information was successfully realized. The research in this paper has some reference value for the research related to QIP.

Computação quântica: uma abordagem para a graduação usando o Qiskit

Neste artigo, apresentamos a ferramenta Quantum Information Software Development Kit – Qiskit para o ensino de computação quântica para estudantes de graduação com conhecimento básico dos postulados da mecânica quântica. Nos concentramos na apresentação da construção dos programas em qualquer laptop ou desktop comum e a sua execução em processadores quânticos reais através do acesso remoto aos hardwares disponibilizados na plataforma IBM Quantum Experience. Os códigos são disponibilizados ao longo do texto para que os leitores, mesmo com pouca experiência em computação científica, possam reproduzi-los e adotar os métodos discutidos neste artigo para abordar seus próprios projetos de computação quântica. Os resultados apresentados estão de acordo com as previsões teóricas, mostrando a eficácia do pacote Qiskit como uma ferramenta de trabalho em sala de aula para a introdução de conceitos aplicados de computação e informação quântica.