Private Product Computation Using Quantum Entanglement

In this article, we show that a pair of entangled qubits can be used to compute a product privately. More precisely, two participants with a private input from a finite field can perform local operations on a shared, Bell-like quantum state, and when these qubits are later sent to a third participant, the third participant […]

Emulation of Quantum Algorithms Using CMOS Analog Circuits

Quantum computers are regarded as the future of computing, as they are believed to be capable of solving extremely complex problems that are intractable on conventional digital computers. However, near-term quantum computers are prone to a plethora of noise sources that are difficult to mitigate, possibly limiting their scalability and precluding us from running any […]

Hybrid Quantum–Classical Generative Adversarial Network for High-Resolution Image Generation

Quantum machine learning (QML) has received increasing attention due to its potential to outperform classical machine learning methods in problems, such as classification and identification tasks. A subclass of QML methods is quantum generative adversarial networks (QGANs), which have been studied as a quantum counterpart of classical GANs widely used in image manipulation and generation […]

Shor’s Algorithm Using Efficient Approximate Quantum Fourier Transform

Shor’s algorithm solves the integer factoring and discrete logarithm problems in polynomial time. Therefore, the evaluation of Shor’s algorithm is essential for evaluating the security of currently used public-key cryptosystems because the integer factoring and discrete logarithm problems are crucial for the security of these cryptosystems. In this article, a new approximate quantum Fourier transform […]

Approaching Collateral Optimization for NISQ and Quantum-Inspired Computing (May 2023)

Collateral optimization refers to the systematic allocation of financial assets to satisfy obligations or secure transactions while simultaneously minimizing costs and optimizing the usage of available resources. This involves assessing the number of characteristics, such as the cost of funding and quality of the underlying assets to ascertain the optimal collateral quantity to be posted […]

Quantum Algorithm for Position Weight Matrix Matching

In this article, we propose two quantum algorithms for a problem in bioinformatics, position weight matrix (PWM) matching, which aims to find segments (sequence motifs) in a biological sequence, such as DNA and protein that have high scores defined by the PWM and are, thus, of informational importance related to biological function. The two proposed […]

Qubit Reduction and Quantum Speedup for Wireless Channel Assignment Problem

In this article, we propose a novel method of formulating an NP-hard wireless channel assignment problem as a higher-order unconstrained binary optimization (HUBO), where the Grover adaptive search (GAS) is used to provide a quadratic speedup for solving the problem. The conventional method relies on a one-hot encoding of the channel indices, resulting in a […]

Testing Platform-Independent Quantum Error Mitigation on Noisy Quantum Computers

We apply quantum error mitigation (QEM) techniques to a variety of benchmark problems and quantum computers to evaluate the performance of QEM in practice. To do so, we define an empirically motivated, resource-normalized metric of the improvement of error mitigation, which we call the improvement factor, and calculate this metric for each experiment we perform. […]

Analysis of the Vehicle Routing Problem Solved via Hybrid Quantum Algorithms in the Presence of Noisy Channels

The vehicle routing problem (VRP) is an NP-hard optimization problem that has been an interest of research for decades in science and industry. The objective is to plan routes of vehicles to deliver goods to a fixed number of customers with optimal efficiency. Classical tools and methods provide good approximations to reach the optimal global […]

Experimentally Verified, Fast Analytic, and Numerical Design of Superconducting Resonators in Flip-Chip Architectures

In superconducting quantum processors, the predictability of device parameters is of increasing importance as many laboratories scale up their systems to larger sizes in a 3-D-integrated architecture. In particular, the properties of superconducting resonators must be controlled well to ensure high-fidelity multiplexed readout of qubits. Here, we present a method, based on conformal mapping techniques, […]