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 […]
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, […]
Quantum processors are now able to run quantum circuits that are infeasible to simulate classically, creating a need for benchmarks that assess a quantum processor’s rate of errors when running these circuits. Here, we introduce a general technique for creating efficient benchmarks from any set of quantum computations, specified by unitary circuits. Our benchmarks assess […]
Multiobjective optimization is a ubiquitous problem that arises naturally in many scientific and industrial areas. Network routing optimization with multiobjective performance demands falls into this problem class, and finding good quality solutions at large scales is generally challenging. In this work, we develop a scheme with which near-term quantum computers can be applied to solve […]
We implement a simulation of a quantum field theory in 1+1 space–time dimensions on a gate-based quantum computer using the light-front formulation of the theory. The nonperturbative simulation of the Yukawa model field theory is verified on IBM’s simulator and is also demonstrated on a small-scale IBM circuit-based quantum processor, on the cloud, using IBM […]
This article introduces a process framework for debugging quantum circuits, focusing on three distinct types of circuit blocks: amplitude–permutation, phase-modulation, and amplitude–redistribution circuit blocks. Our research addresses the critical need for specialized debugging approaches tailored to the unique properties of each circuit type. For amplitude–permutation circuits, we propose techniques to correct amplitude–permutations mimicking classical operations. […]
This article introduces a process framework for debugging quantum circuits, focusing on three distinct types of circuit blocks: amplitude–permutation, phase-modulation, and amplitude–redistribution circuit blocks. Our research addresses the critical need for specialized debugging approaches tailored to the unique properties of each circuit type. For amplitude–permutation circuits, we propose techniques to correct amplitude–permutations mimicking classical operations. […]
Recently, quantum computing has been proven as an ideal theory for the design of fuzzy inference engines, thanks to its capability to efficiently solve the rule explosion problem. In this scenario, a quantum fuzzy inference engine (QFIE) was proposed as a quantum algorithm able to generate an exponential computational advantage over conventional fuzzy inference engines. […]
While quantum computers provide exciting opportunities for information processing, they currently suffer from noise during computation that is not fully understood. Incomplete noise models have led to discrepancies between quantum program success rate (SR) estimates and actual machine outcomes. For example, the estimated probability of success (ESP) is the state-of-the-art metric used to gauge quantum […]
While quantum computers provide exciting opportunities for information processing, they currently suffer from noise during computation that is not fully understood. Incomplete noise models have led to discrepancies between quantum program success rate (SR) estimates and actual machine outcomes. For example, the estimated probability of success (ESP) is the state-of-the-art metric used to gauge quantum […]