How relevant is quantum computing?
Erik Lucero et al. of the University of California-Santa Barbara built a quantum processor earlier this year to factorize the number 15 using a quantum algorithm (an algorithm that runs on a quantum computer) for integer factorization formulated by Peter Shor in 1994 . The team built a quantum circuit made of four superconducting qubits (bits which are a little bit of both 0 and 1 at the same time) on top of a substrate made of sapphire. These qubits are not exactly easy to implement in reality considering our present technological limitations. Here are some of my thoughts on the relevance of quantum computing.
Moore's Law is dying
Moore's law is the observation that the number of transistors in a dense integrated circuit doubles approximately every two years. Computers have been getting smaller and integrated circuits (ICs) more densely packed with transistors ever since the advent of the first IC-based computer. This is a modest explanation of Moore's Law.
Since 2014, Intel has been shipping 14 nanometer scale devices to consumers and are expected to release 10 nanometer scale devices commercially by 2017. The HIV is a whopping 100 nanometer compared to these tiny transistors! Our technology is approaching subatomic levels and classical mechanics won't make the cut anymore.
Most semiconductor industry forecasters, including Gordon Moore himself expect Moore's law will end by around 2025.
Solving optimization problems
The TSP is a popular example of an optimization problem. The travelling salesman problem (TSP) asks the following question: Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city?
There are several algorithms for solving this problem but they themselves pose problems. A simple TSP test case would take several generations to solve on the best of our computers using these classical algorithms. On the other hand, quantum computing models would be able to solve the same problem in a few seconds!
Stay tuned for more opinions on quantum mechanics and computing in future posts!
Moore's Law is dying
Moore's law is the observation that the number of transistors in a dense integrated circuit doubles approximately every two years. Computers have been getting smaller and integrated circuits (ICs) more densely packed with transistors ever since the advent of the first IC-based computer. This is a modest explanation of Moore's Law.
Since 2014, Intel has been shipping 14 nanometer scale devices to consumers and are expected to release 10 nanometer scale devices commercially by 2017. The HIV is a whopping 100 nanometer compared to these tiny transistors! Our technology is approaching subatomic levels and classical mechanics won't make the cut anymore.
Most semiconductor industry forecasters, including Gordon Moore himself expect Moore's law will end by around 2025.
Solving optimization problems
The TSP is a popular example of an optimization problem. The travelling salesman problem (TSP) asks the following question: Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city?
There are several algorithms for solving this problem but they themselves pose problems. A simple TSP test case would take several generations to solve on the best of our computers using these classical algorithms. On the other hand, quantum computing models would be able to solve the same problem in a few seconds!
Stay tuned for more opinions on quantum mechanics and computing in future posts!
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