Quantum Genetic Algorithms: Optimization- from theory to simulation.

Meetup Organizer- Zen4Quantum, QuantumCurious, quantum connect.Balaji Ramamurthy, working consultant and set up the meet groups for quantum computing and AI/ML discussions and have been active in several areas like Connecticut, Seattle and Bay area.

Zen4Quantum meetup organizer |Balaji Ramamurthy

Speaker: Vinay Phadnis is an instructor in a Udemy course about Genetic Algorithms:Quantum Genetic Algorithms: Optimization- from theory to simulation.Sat, Jul 3, 2021 11:00 AM - 1:00 PM (PDT)Please join my meeting from your computer, tablet or smartphone.https://global.gotomeeting.com/join/964989997You can also dial in using your phone.(For supported devices, tap a one-touch number below to join instantly.)United States: +1 (872) 240-3212- One-touch: tel:+18722403212,,964989997#Access Code: 964-989-997New to GoToMeeting? Get the app now and be ready when your first meeting starts: https://global.gotomeeting.com/install/964989997Genetic Optimization is an algorithm which is inspired by Nature and taking advantage of processes like Natural Selection, Crossovers, genetic mutation and evolution. These algorithms work very well when the population size is high. This results in in the problem having an enormous compute complexity. This is ideal for monovarietal or bivariate problems where causal analysis is important. In case of multivariate problems, the exponential nature of increasing complexity in the case of genetic algorithms make it very difficult to simulate with a decent population size and arrive at a solution in a finite amount of time. Vinay Phadnis is an instructor in a Udemy course about Genetic Algorithms: Optimization from theory to simulation which has helped a lot of students worldwide understand and solve problems using Genetic Algorithms.This is not a boring session about Classical computing and how exponential time complexities slow us down. This session will revolve around how to use Quantum hardware to act as an accelerator for Quantum Computing workloads. The potential here is huge!In this session, we will go through various sections of Genetic Algorithms and analyze how to use Quantum to accelerate the workloads:1) Noise Generation: This phenomenon will be used as a generator for our initial population.2) Quantum Tunnelling: We will understand how Quantum Tunnelling can be used to effectively find the best individual in a particular lot of individuals.3) QUBO: We will write QUBO rules to perform crossover and gene mutationFinally, we will go through some amazing ways in which Genetic Algorithms can be leveraged to help Quantum Computers accelerate their reach on a large scale adoption curve and have fun by analyzing a few fundamentally disruptive problems and their solutionsGoTo Meeting link will be provided one hour before the event:

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Quantum Genetic Algorithms: Optimization- from theory to simulation.

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Quantum Genetic Algorithms: Optimization- from theory to simulation.

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