Quantum Annealing for Robust Principal Component Analysis

Abstract: Principal component analysis is commonly used for dimensionality reduction, feature extraction, denoising, and visualization. The most commonly used principal component analysis method is based upon optimization of the L2-norm; however, the L2-norm is known to exaggerate the contribution of errors and outliers. When optimizing over the L1-norm, the components generated are known to exhibit […]

Improving Decision Diagram-Based Quantum Circuit Simulation Using Static Variable Ordering and Multinode Ring Communication

Abstract: Currently, the development of quantum computers is active; however, large-scale machines remain limited and noisy. Furthermore, such quantum computers do not allow direct access to state vectors, posing challenges for quantum algorithm development. Quantum circuit simulators on classical computers offer a solution, with decision diagram (DD)-based simulators being particularly memory-efficient for representing quantum states. […]

Hardware-Aware and Resource-Efficient Circuit Packing and Scheduling on Trapped-Ion Quantum Computers

Abstract: The rapid expansion of quantum cloud services has led to long job queues due to single-tenant execution models that underutilize hardware resources. Quantum multiprogramming (QMP) mitigates this by executing multiple circuits in parallel on a single device, but existing methods target superconducting systems with limited connectivity, high crosstalk, and lower gate fidelity. Trapped-ion architecture, […]

Hardware-Aware and Resource-Efficient Circuit Packing and Scheduling on Trapped-Ion Quantum Computers

Abstract: The rapid expansion of quantum cloud services has led to long job queues due to single-tenant execution models that underutilize hardware resources. Quantum multiprogramming (QMP) mitigates this by executing multiple circuits in parallel on a single device, but existing methods target superconducting systems with limited connectivity, high crosstalk, and lower gate fidelity. Trapped-ion architecture, […]

Erasure-Tolerance Scheme for the Surface Codes on Neutral Atom Quantum Computers

Abstract: Neutral atom arrays manipulated with optical tweezers are promising candidates for fault-tolerant quantum computers due to their advantageous properties, such as scalability, long coherence times, and optical accessibility for communication. A significant challenge to overcome is the presence of non-Pauli errors, specifically erasure errors and leakage errors. Previous work has shown that leakage errors […]

Simulation of Shor Algorithm for Discrete Logarithm Problems With Comprehensive Pairs of Modulo p and Order q

Abstract: The discrete logarithm problem (DLP) over finite fields, commonly used in classical cryptography, has no known polynomial-time algorithm on classical computers. However, Shor has provided its polynomial-time algorithm on quantum computers. Nevertheless, there are only few examples simulating quantum circuits that operate on general pairs of modulo p and order q. In this article, […]

Engineering Quantum Error Correction Codes Using Evolutionary Algorithms

Quantum error correction and the use of quantum error correction codes are likely to be essential for the realization of practical quantum computing. Because the error models of quantum devices vary widely, quantum codes that are tailored for a particular error model may have much better performance. For more about this article see link below. […]

Variational Quantum Algorithms for Differential Equations on a Noisy Quantum Computer

The role of differential equations (DEs) in science and engineering is of paramount importance, as they provide the mathematical framework for a multitude of natural phenomena. Since quantum computers promise significant advantages over classical computers, quantum algorithms for the solution of DEs have received a lot of attention. Particularly interesting are algorithms that offer advantages […]

Learning a Quantum Computer’s Capability

Accurately predicting a quantum computer’s capability—which circuits it can run and how well it can run them—is a foundational goal of quantum characterization and benchmarking. As modern quantum computers become increasingly hard to simulate, we must develop accurate and scalable predictive capability models to help researchers and stakeholders decide which quantum computers to build and […]

Approximate Solutions of Combinatorial Problems via Quantum Relaxations

Combinatorial problems are formulated to find optimal designs within a fixed set of constraints and are commonly found across diverse engineering and scientific domains. Understanding how to best use quantum computers for combinatorial optimization remains an ongoing area of study. Here, we propose new methods for producing approximate solutions to quadratic unconstrained binary optimization problems, […]