๐คฏ Behold, the "Quadratic Sandwich" ๐๐ฅช๐, where math nerds obsess over bread metaphors while solving optimization problems. Who knew minimizing functions could be this deliciously confusing? ๐ค Just remember, if your "sandwich" isn't tight, you're chewing on chaos! ๐
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If you have ever tried to minimize a function with gradient descent, you probably noticed that some functions are a joy to optimize and others are a nightmare. The difference often boils down to two properties: strong convexity and L-smoothness. These two concepts define a โsandwichโ of quadratic bounds around your function that tells you exactly how well-behaved it is. If the sandwich is tight, life is good. If one slice of bread is missing, things get ugly fast.
Federico Magnaniโs blogAnnealing quantum computers have already shown to be significantly faster than classical computers for certain workloads and will soon be capable of previously unimaginable calculations. Quantum annealing, in particular, has proven to be over three million times faster than classical methods for certain...
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Where quantum computing is already delivering value
While gate model quantum computing holds immense promise for tomorrow, quantum annealing systems are solving complex optimization problems for enterprises today.
InfoWorld
Team demonstrates quantum advantage on optimization problems with a 5,000-qubit programmable spin glass
Over the past decades, researchers and companies worldwide have been trying to develop increasingly advanced quantum computers. The key objective of their efforts is to create systems that will outperform classical computers on specific tasks, which is also known as realizing "quantum advantage."