{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"The New Quantum Era - innovation in quantum computing, science and technology","title":"Quantum reservoir computing with Susanne Yelin ","html":"","width":"100%","height":180,"duration":1555,"description":"Sebastian is joined by Susanne Yelin, Professor of Physics in Residence at Harvard University and the University of Connecticut.\nSusanne's Background:\nFellow at the American Physical Society and Optica (formerly the American Optics Society)\nBackground in theoretical AMO (Atomic, Molecular, and Optical) physics and quantum optics\nTransition to quantum machine learning and quantum computing applications\nQuantum Machine Learning Challenges\nLimited to simulating small systems (6-10 qubits) due to lack of working quantum computers\nBarren plateau problem: the more quantum and entangled the system, the worse the problem\nMoved towards analog systems and away from universal quantum computers\nQuantum Reservoir Computing\nSubclass of recurrent neural networks where connections between nodes are fixed\nLearning occurs through a filter function on the outputs\nSuitable for analog quantum systems like ensembles of atoms with interactions\nAdvantages: redundancy in learning, quantum effects (interference, non-commuting bases, true randomness)\nPotential for fault tolerance and automatic error correction\nQuantum Chemistry Application\nGoal: leverage classical chemistry knowledge and identify problems hard for classical computers\nCollaboration with quantum chemists Anna Krylov (USC) and Martin Head-Gordon (UC Berkeley)\nFocused on effective input-output between classical and quantum computers\nSimulating a biochemical catalyst molecule with high spin correlation using a combination of analog time evolution and logical gates\nDemonstrating higher fidelity simulation at low energy scales compared to classical methods\nFuture Directions\nExploring fault-tolerant and robust approaches as an alternative to full error correction\nOptimizing pulses tailored for specific quantum chemistry calculations\nInvestigating dynamics of chemical reactions\nCalculating potential energy surfaces for molecules\nImplementing multi-qubit analog ideas on the Rydberg atom array machine at Harvard\nDr. Yelin's work...","thumbnail_url":"https://img.transistorcdn.com/0bJ0_ffy0r0O2l32QT5Tn9-3l9jtqpUcMVwNZnZXwRM/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8yZmZl/YmRlZTAxNDY3MWJk/NmI2MGVkMGMxYmFh/MTM2Mi5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}