Layer VQE: A Variational Approach for Combinatorial Optimization on Noisy Quantum Computers

Combinatorial optimization on near-term quantum devices is a promising path to demonstrating quantum advantage. However, the capabilities of these devices are constrained by high noise or error rates. In this article, inspired by the variational quantum eigensolver (VQE), we propose an iterative layer VQE (L-VQE) approach. We present a large-scale numerical study, simulating circuits with […]

Topological-Graph Dependencies and Scaling Properties of a Heuristic Qubit-Assignment Algorithm

The qubit-mapping problem aims to assign and route qubits of a quantum circuit onto an noisy intermediate-scale quantum (NISQ) device in an optimized fashion, with respect to some cost function. Finding an optimal solution to this problem is known to scale exponentially in computational complexity; as such, it is imperative to investigate scalable qubit-mapping solutions […]

QuantMark: A Benchmarking API for VQE Algorithms

Thanks to the rise of quantum computers, many variations of the variational quantum eigensolver (VQE) have been proposed in recent times. This is a promising development for real quantum algorithms, as the VQE is a promising algorithm that runs on current quantum hardware. However, the popular method of comparing your algorithm versus a classical baseline […]

On the Realistic Worst-Case Analysis of Quantum Arithmetic Circuits

We provide evidence that commonly held intuitions when designing quantum circuits can be misleading. In particular, we show that 1) reducing the T-count can increase the total depth; 2) it may be beneficial to trade controlled NOTs for measurements in noisy intermediate-scale quantum (NISQ) circuits; 2) measurement-based uncomputation of relative phase Toffoli ancillae can make […]

EP-PQM: Efficient Parametric Probabilistic Quantum Memory With Fewer Qubits and Gates

Machine learning (ML) classification tasks can be carried out on a quantum computer (QC) using probabilistic quantum memory (PQM) and its extension, parametric PQM (P-PQM), by calculating the Hamming distance between an input pattern and a database of r patterns containing z features with a distinct attributes. For PQM and P-PQM to correctly compute the Hamming distance, the feature must be […]

Pulse-Engineered Controlled-V Gate and Its Applications on Superconducting Quantum Device

In this article, we demonstrate that, by employing the OpenPulse design kit for IBM superconducting quantum devices, the controlled-V gate ( cv gate) can be implemented in about half the gate time to the controlled-X gate ( cx or cnot gate) and consequently 65.5% reduced gate time compared to the cx -based implementation of cv […]

Neural-Network Decoders for Quantum Error Correction Using Surface Codes: A Space Exploration of the Hardware Cost-Performance Tradeoffs

Quantum error correction (QEC) is required in quantum computers to mitigate the effect of errors on physical qubits. When adopting a QEC scheme based on surface codes, error decoding is the most computationally expensive task in the classical electronic back-end. Decoders employing neural networks (NN) are well-suited for this task but their hardware implementation has […]

A Distributed Learning Scheme for Variational Quantum Algorithms

Variational quantum algorithms (VQAs) are prime contenders to gain computational advantages over classical algorithms using near-term quantum machines. As such, many endeavors have been made to accelerate the optimization of modern VQAs in past years. To further improve the capability of VQAs, here, we propose a quantum distributed optimization scheme (dubbed as QUDIO), whose back […]

The Present and Future of Discrete Logarithm Problems on Noisy Quantum Computers

The discrete logarithm problem (DLP) is the basis for several cryptographic primitives. Since Shor’s work, it has been known that the DLP can be solved by combining a polynomial-size quantum circuit and a polynomial-time classical postprocessing algorithm. The theoretical result corresponds the situation where a quantum device working with a medium number of qubits of […]

Practical Quantum K-Means Clustering: Performance Analysis and Applications in Energy Grid Classification

In this work, we aim to solve a practical use-case of unsupervised clustering that has applications in predictive maintenance in the energy operations sector using quantum computers. Using only cloud access to quantum computers, we complete thorough performance analysis of what some current quantum computing systems are capable of for practical applications involving nontrivial mid-to-high-dimensional […]