The USRA Feynman Quantum Academy: If You Give a Student a Quantum Internship
- URL: http://arxiv.org/abs/2505.04641v1
- Date: Mon, 05 May 2025 02:18:48 GMT
- Title: The USRA Feynman Quantum Academy: If You Give a Student a Quantum Internship
- Authors: Zoe Gonzalez Izquierdo, Sophie Block, Besart Mujeci, P. Aaron Lott, Davide Venturelli, David Bell,
- Abstract summary: We review the trajectory of the USRA Feynman Quantum Academy Internship Program over the last 8 years.<n>We place it in the context of the current push to prepare the quantum workforce of the future.
- Score: 1.960466708753349
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In the rapidly expanding field of quantum computing, one key aspect to maintain ongoing progress is ensuring that early career scientists interested in the field get appropriate guidance and opportunity to advance their work, and in return that institutions and enterprises with a stake in quantum computing have access to a qualified pool of talent. Internship programs at the graduate level are the perfect vehicle to achieve this. In this paper, we review the trajectory of the USRA Feynman Quantum Academy Internship Program over the last 8 years, placing it in the context of the current push to prepare the quantum workforce of the future, and highlighting the caliber of the work it produced.
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) - 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) - 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) - Quantum Machine Learning: from physics to software engineering [58.720142291102135]
We show how classical machine learning approach can help improve the facilities of quantum computers.
We discuss how quantum algorithms and quantum computers may be useful for solving classical machine learning tasks.
arXiv Detail & Related papers (2023-01-04T23:37:45Z) - Recent Advances for Quantum Neural Networks in Generative Learning [98.88205308106778]
Quantum generative learning models (QGLMs) may surpass their classical counterparts.
We review the current progress of QGLMs from the perspective of machine learning.
We discuss the potential applications of QGLMs in both conventional machine learning tasks and quantum physics.
arXiv Detail & Related papers (2022-06-07T07:32:57Z) - Evolution of Quantum Computing: A Systematic Survey on the Use of
Quantum Computing Tools [5.557009030881896]
We conduct a systematic survey and categorize papers, tools, frameworks, platforms that facilitate quantum computing.
We discuss the current essence, identify open challenges and provide future research direction.
We conclude that scores of frameworks, tools and platforms are emerged in the past few years, improvement of currently available facilities would exploit the research activities in the quantum research community.
arXiv Detail & Related papers (2022-04-04T21:21:12Z) - 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) - Standard Model Physics and the Digital Quantum Revolution: Thoughts
about the Interface [68.8204255655161]
Advances in isolating, controlling and entangling quantum systems are transforming what was once a curious feature of quantum mechanics into a vehicle for disruptive scientific and technological progress.
From the perspective of three domain science theorists, this article compiles thoughts about the interface on entanglement, complexity, and quantum simulation.
arXiv Detail & Related papers (2021-07-10T06:12:06Z) - 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) - Simulating Quantum Materials with Digital Quantum Computers [55.41644538483948]
Digital quantum computers (DQCs) can efficiently perform quantum simulations that are otherwise intractable on classical computers.
The aim of this review is to provide a summary of progress made towards achieving physical quantum advantage.
arXiv Detail & Related papers (2021-01-21T20:10:38Z) - Preparing for the quantum revolution -- what is the role of higher
education? [3.2531696064515643]
We describe the types of activities being carried out in the quantum industry, profile the types of jobs that exist, and describe the skills valued across the quantum industry.
We present the training and hiring challenges the quantum industry is facing and how higher education may optimize the important role it is currently playing.
arXiv Detail & Related papers (2020-06-30T00:45:32Z)
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.