QNepal QTalk Series 2025 – E8

⚛️ QNepal QTalk Series 2025 – Episode 8

Join the 8th episode of the QNepal QTalk Series 2025 as we explore cutting-edge developments in quantum technologies, celebrating the International Year of Quantum Science and Technology (IYQ 2025). 🌍✨

Fresh from the excitement of the 2025 Nobel Prize in quantum transport, quantum computing is unlocking new possibilities for simulating complex systems in physics. 🌌💡

In this session, Dr. Gaurav Gyawali (PhD, Cornell University), Research Scientist at Hewlett Packard Enterprise Labs, will share his work on using quantum processors to simulate lattice gauge theories, bridging quantum computing and condensed matter physics.

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📅 Event Details

🗓 Date: November 1, 2025
⏰ Time: 8:30 PM – 9:30 PM NPT | 10:45 AM – 11:45 AM EST
💻 Venue: Online (Zoom link shared after registration)

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🎤 Speaker

Dr. Gaurav Gyawali – LinkedIn
🔬 Talk Title: Simulating disorder-free localization using a (2+1)D lattice gauge theory on a quantum processor

Dr. Gaurav Gyawali is a Research Scientist at Hewlett Packard Enterprise Labs, specializing in theoretical condensed matter physics, quantum computing, quantum information, and quantum machine learning. He recently earned his PhD in Physics from Cornell University, building on a BSc in Mathematics and Physics from the University of New Orleans. Prior to his current role, he served as a Student Researcher at Google from 2023 to 2024 and as a Visiting Fellow. With over 150 citations across his publications, Gyawali is advancing scalable quantum technologies at the intersection of theory and computation.

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💡 Why Attend?

• Learn about quantum localization and lattice gauge theories
• Explore the intersection of quantum computing and condensed matter physics
• Gain insights into physics-inspired machine learning and scalable quantum technologies

🔍 Abstract:
Quantum processors available today can be used to simulate complex quantum dynamics, often surpassing the capabilities of classical computers. In this talk, I will present my results on the dynamics of a lattice gauge theory (LGT) on Google’s Willow quantum processors. We observe localization in the dynamics of a disorder-free LGT in the absence of disorder in one and two dimensions, although localization is usually attributed to disordered quantum systems. Leveraging the ability of a quantum processor to create superpositions, we propose an algorithm that achieves a polynomial speedup in sampling disorder configurations —a longstanding challenge in many-body localization studies.

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✨ Don’t miss this opportunity to hear groundbreaking insights from a leading quantum researcher!