Related papers: Disparities in access to US quantum information ed…
Quantum state discrimination underlies various applications in quantum information processing tasks. It essentially describes the distinguishability of quantum systems in different states, and the general process of extracting classical…
Quantum machine learning is emerging as a promising application of quantum computing due to its distinct way of encoding and processing data. It is believed that large-scale quantum machine learning demonstrates substantial advantages over…
This study examines the Pathways to Quantum Immersion Program at George Mason University, which introduces high school students to quantum concepts and careers. Fifteen group interviews with a total of 45 students were analyzed to examine…
Upper-level, undergraduate quantum mechanics (QM) is widely considered a difficult subject with many varied approaches to teaching it and considerable variation in content coverage. For example, two common approaches to undergraduate QM…
Quantum computing is a technology that promises to offer significant advantages during the coming decades. Though the technology is still in a prototype stage, the last few years have seen many of these prototype devices become accessible…
We describe the development and in-class evaluation of a Quantum Interactive Learning Tutorial (QuILT) on quantum key distribution, a context which involves an exciting application of quantum mechanics. The protocol used in the QuILT…
NISQ (Noisy Intermediate-Scale Quantum) era constraints, high sensitivity to noise and limited qubit count, impose significant barriers on the usability of QPUs (Quantum Process Units) capabilities. To overcome these challenges, researchers…
Studying the behavior of quantum information scrambling in various quantum systems is an active area of research. Recently, Sharma et al. [K.K. Sharma, V.P Gerdt, Quantum Inf. Process 20, 195 (2021)] have shown the mathematical connection…
This position paper examines the substantial divide between academia and industry within quantum software engineering. For example, while academic research related to debugging and testing predominantly focuses on a limited subset of…
The accelerating global development of quantum technologies strengthens the case for introducing quantum computing concepts before university. Yet in Latin America, there is no consolidated, region wide integration of quantum computing into…
Quantum computing is increasingly practiced through programming, yet most educational offerings emphasize algorithmic or framework-level use rather than software engineering concerns such as testing, abstraction, tooling, and lifecycle…
Contribution: In this study, an alternative educational approach for introducing quantum computing to a wider audience is highlighted. The proposed methodology considers quantum computing as a generalized probability theory rather than a…
Quantum computing is a growing field at the intersection of physics and computer science. The goal of this article is to highlight a successfully trialled quantum computing course for high school students between the ages of 15 and 18 years…
Quantum machine learning has proven to be a fruitful area in which to search for potential applications of quantum computers. This is particularly true for those available in the near term, so called noisy intermediate-scale quantum (NISQ)…
Quantum information science and technology (QIST) is a critical and emerging technology with the potential for enormous world impact and is currently invested in by over 40 nations. To bring these large-scale investments to fruition and…
We investigated the intersectional nature of race/racism and gender/sexism in broad scale inequities in physics student learning using a critical quantitative intersectionality. To provide transparency and create a nuanced picture of…
We describe a protocol for quantum information splitting (QIS) of a restricted class of three-qubit states among three parties Alice, Bob and Charlie, using a pair of GHZ states as the quantum channel. There are two different forms of this…
The transition of second-generation quantum technologies from a research topic to a topic of industrial relevance has led to a growing number of quantum companies and companies that are exploring quantum technologies. Examples would include…
Quantum extreme learning machines (QELMs) leverage untrained quantum dynamics to efficiently process information encoded in input quantum states, avoiding the high computational cost of training more complicated nonlinear models. On the…
Quantum computing technology is advancing rapidly. Yet, even accounting for these trends, a quantum leap would be needed for quantum computers to meaningfully impact deep learning over the coming decade or two. We arrive at this conclusion…