Explore a comprehensive lecture on quantum algorithms and their applications from near-term to long-term prospects. Delve into quantum field theory simulations, classical vs. quantum approaches, and key concepts like Hamiltonian simulation and ground-state generation. Examine innovative techniques for state preparation and information extraction from quantum states. Investigate empirical hardness models and their methodology, with a focus on the Hamiltonian Cycle Problem. Gain insights into the future vision for quantum computing and its potential impact on algorithmic problem-solving.
Quantum Algorithms - From Far to Near Future
Overview
Syllabus
Intro
Quantum Field Theory
Why to simulate a QFT?
Classical Simulations
It's all about preparing and measuring quantum states
Kingdome of Q Algorithms: Hamiltonian Simulati
Simulating a QFT on Q computer
Ground-State Generation
State preparation by inequality testing
Beyond ground state and translational symmetries
Extracting information from quantum states
Empirical Hardness Models (EHMs)
Empirical Hardness Methodology
EHM for Hamiltonian Cycle Problem
Vision for Quantum Case
Taught by
Fields Institute
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