USEQIP: Outcomes and experiences from 17 years of undergraduate summer schools in experimental quantum information science
- URL: http://arxiv.org/abs/2604.25124v1
- Date: Tue, 28 Apr 2026 01:58:42 GMT
- Title: USEQIP: Outcomes and experiences from 17 years of undergraduate summer schools in experimental quantum information science
- Abstract summary: Undergraduate School on Experimental Quantum Information Processing (USEQIP) is a two-week summer school for undergraduate students.<n>We report on the structure, impact, and outlook of the program.<n>We highlight the career trajectories of program alumni, many of whom have made significant contributions to the quantum field.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: To grow the quantum information science and technology workforce, opportunities for students to gain experiential learning and build a sense of belonging in the broader community are essential. The Undergraduate School on Experimental Quantum Information Processing (USEQIP) is a two-week summer school for undergraduate students that has been held since 2009 with the goal of introducing undergraduate students from around the world to the tools of quantum information research, paired with a summer internship program. Here we report on the structure, impact, and outlook of the program, including hands-on laboratory activities refined over many iterations of the program. We highlight the career trajectories of program alumni, many of whom have made significant contributions to the quantum field.
Related papers
- The Design and Implementation of a Quantum Information Science Undergraduate Program [1.4936879993794578]
We present how Universit'e de Sherbrooke, in Quebec, Canada, responded by creating and launching an innovative undergraduate degree in quantum information science.<n>We detail the creative process leading to a coherent curriculum, as well as why the local ecosystem led to these choices.<n>The guiding principles and lessons learned during the development of this interdepartmental and interfaculty degree are shared to inspire other quantum education institutions.
arXiv Detail & Related papers (2024-12-02T17:24:35Z) - The curse of random quantum data [62.24825255497622]
We quantify the performances of quantum machine learning in the landscape of quantum data.
We find that the training efficiency and generalization capabilities in quantum machine learning will be exponentially suppressed with the increase in qubits.
Our findings apply to both the quantum kernel method and the large-width limit of quantum neural networks.
arXiv Detail & Related papers (2024-08-19T12:18:07Z) - Investigating Student Participation in Quantum Workforce Initiatives [0.0]
We interviewed students from two Colorado-based quantum education/workforce development programs.
We highlight the ways in which students' different needs and contexts have informed divergent development of the two programs.
arXiv Detail & Related papers (2024-07-19T23:15:15Z) - Quantum Technology masters: A shortcut to the quantum industry? [0.0]
We investigate a growing trend in the worldwide Quantum Technology (QT) education landscape, that of the development of masters programs.
Through a global survey, we identified 86 masters programs, with substantial growth since 2021.
We identify a range of national efforts to grow the quantum workforce of many countries, quantum program enhancements, which augment the content of existing study programs with quantum content.
arXiv Detail & Related papers (2024-07-10T09:32:12Z) - Measuring Wigner functions of quantum states of light in the
undergraduate laboratory [49.1574468325115]
We present an educational activity aimed at measuring the Wigner distribution functions of quantum states of light.
The project was conceived by students from various courses within the physics undergraduate curriculum at the Universidad de los Andes in Bogot'a, Colombia.
The activity is now part of the course syllabus and its virtual component has proven to be highly valuable for the implementation of distance learning in quantum optics.
arXiv Detail & Related papers (2023-10-26T16:17:54Z) - The QUATRO Application Suite: Quantum Computing for Models of Human
Cognition [49.038807589598285]
We unlock a new class of applications ripe for quantum computing research -- computational cognitive modeling.
We release QUATRO, a collection of quantum computing applications from cognitive models.
arXiv Detail & Related papers (2023-09-01T17:34:53Z) - Quantum data learning for quantum simulations in high-energy physics [55.41644538483948]
We explore the applicability of quantum-data learning to practical problems in high-energy physics.
We make use of ansatz based on quantum convolutional neural networks and numerically show that it is capable of recognizing quantum phases of ground states.
The observation of non-trivial learning properties demonstrated in these benchmarks will motivate further exploration of the quantum-data learning architecture in high-energy physics.
arXiv Detail & Related papers (2023-06-29T18:00:01Z) - Piloting a full-year, optics-based high school course on quantum
computing [0.0]
This article details work at The University of Texas at Austin to develop and pilot the first full-year high school quantum computing class.
We find that the use of classical optics provides a clear and accessible avenue for representing quantum states and gate operators.
Students found that exploring quantum optical phenomena prior to the introduction of mathematical models helped in the understanding and mastery of the material.
arXiv Detail & Related papers (2021-12-30T18:54:08Z) - On exploring the potential of quantum auto-encoder for learning quantum systems [60.909817434753315]
We devise three effective QAE-based learning protocols to address three classically computational hard learning problems.
Our work sheds new light on developing advanced quantum learning algorithms to accomplish hard quantum physics and quantum information processing tasks.
arXiv Detail & Related papers (2021-06-29T14:01:40Z) - Interleaving Computational and Inferential Thinking: Data Science for
Undergraduates at Berkeley [81.01051375191828]
The undergraduate data science curriculum at the University of California, Berkeley is anchored in five new courses.
These courses emphasize computational thinking, inferential thinking, and working on real-world problems.
These courses have become some of the most popular on campus and have led to a surging interest in a new undergraduate major and minor program in data science.
arXiv Detail & Related papers (2021-02-13T22:51:24Z) - Information Scrambling in Computationally Complex Quantum Circuits [56.22772134614514]
We experimentally investigate the dynamics of quantum scrambling on a 53-qubit quantum processor.
We show that while operator spreading is captured by an efficient classical model, operator entanglement requires exponentially scaled computational resources to simulate.
arXiv Detail & Related papers (2021-01-21T22:18:49Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.