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محتوای ارائه شده توسط Sebastian Hassinger - quantum computing expert and Sebastian Hassinger. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Sebastian Hassinger - quantum computing expert and Sebastian Hassinger یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
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Generative Quantum Eigensolver with Alán Aspuru-Guzik

37:33
 
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Manage episode 462092761 series 3377506
محتوای ارائه شده توسط Sebastian Hassinger - quantum computing expert and Sebastian Hassinger. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Sebastian Hassinger - quantum computing expert and Sebastian Hassinger یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

Welcome back to The New Quantum Era, a podcast by Sebastian Hassinger and Kevin Rowney. After a brief hiatus, we’re excited to bring you a fascinating conversation with a true pioneer in the field of quantum computing, Alán Aspuru-Guzik. Alán is a professor at the University of Toronto and a leading figure in quantum computing, known for his foundational work on the Variational Quantum Eigensolver (VQE). In this episode, we delve into the evolution of VQE and explore Alán’s latest groundbreaking work on the Generative Quantum Eigensolver (GQE). Expect to hear about the intersection of quantum computing and machine learning, and how these advancements could shape the future of the field.

Key Highlights:

  • Origins of VQE: Alan discusses the development of the Variational Quantum Eigensolver, a technique that combines classical and quantum computing to approximate the ground state of chemical systems. This method was a significant step forward in efforts to make practical use of noisy intermediate-scale quantum (NISQ) devices.
  • Challenges and Innovations: The conversation touches on the challenges of variational algorithms, such as the barren plateau problem, and how Alán’s group has been working on innovative solutions to overcome these hurdles.
  • Introduction to GQE: Alán introduces the Generative Quantum Eigensolver, a new approach that leverages generative models like transformers to optimize quantum circuits without relying on quantum gradients. This method aims to make quantum computing more efficient and practical.
  • Future of Quantum Computing: The discussion explores the potential future workflows in quantum computing, where hybrid architectures combining classical and quantum computing will be essential. Alán shares his vision of how GQE could be foundational in this new era.
  • Broader Applications: Beyond chemistry, the GQE technique has potential applications in quantum machine learning and other variational algorithms, making it a versatile tool in the quantum computing toolkit.

Mentioned in this episode:

Stay tuned for more exciting episodes and deep dives into the world of quantum computing. If you enjoyed this episode, please subscribe, review, and share it on your preferred social media platforms. Thank you for listening!

  continue reading

66 قسمت

Artwork
iconاشتراک گذاری
 
Manage episode 462092761 series 3377506
محتوای ارائه شده توسط Sebastian Hassinger - quantum computing expert and Sebastian Hassinger. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Sebastian Hassinger - quantum computing expert and Sebastian Hassinger یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

Welcome back to The New Quantum Era, a podcast by Sebastian Hassinger and Kevin Rowney. After a brief hiatus, we’re excited to bring you a fascinating conversation with a true pioneer in the field of quantum computing, Alán Aspuru-Guzik. Alán is a professor at the University of Toronto and a leading figure in quantum computing, known for his foundational work on the Variational Quantum Eigensolver (VQE). In this episode, we delve into the evolution of VQE and explore Alán’s latest groundbreaking work on the Generative Quantum Eigensolver (GQE). Expect to hear about the intersection of quantum computing and machine learning, and how these advancements could shape the future of the field.

Key Highlights:

  • Origins of VQE: Alan discusses the development of the Variational Quantum Eigensolver, a technique that combines classical and quantum computing to approximate the ground state of chemical systems. This method was a significant step forward in efforts to make practical use of noisy intermediate-scale quantum (NISQ) devices.
  • Challenges and Innovations: The conversation touches on the challenges of variational algorithms, such as the barren plateau problem, and how Alán’s group has been working on innovative solutions to overcome these hurdles.
  • Introduction to GQE: Alán introduces the Generative Quantum Eigensolver, a new approach that leverages generative models like transformers to optimize quantum circuits without relying on quantum gradients. This method aims to make quantum computing more efficient and practical.
  • Future of Quantum Computing: The discussion explores the potential future workflows in quantum computing, where hybrid architectures combining classical and quantum computing will be essential. Alán shares his vision of how GQE could be foundational in this new era.
  • Broader Applications: Beyond chemistry, the GQE technique has potential applications in quantum machine learning and other variational algorithms, making it a versatile tool in the quantum computing toolkit.

Mentioned in this episode:

Stay tuned for more exciting episodes and deep dives into the world of quantum computing. If you enjoyed this episode, please subscribe, review, and share it on your preferred social media platforms. Thank you for listening!

  continue reading

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