Quantum Computing Solutions: Solving Real-World Problems Using Quantum Computing and Algorithms

by Bhagvan Kommadi

The key problem related to quantum computing right now is that it still in the development stages. Hence, there is no generalized way of programming for quantum computers. From a developer's point of view, they need to study and create basic quantum computing framework for further development of algorithms. For an interested programmer, even if he knows the basic theories of quantum computing, he needs to create an infrastructure for developing algorithms such as tools and simulators.

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The  main challenges are related to lack of a well documented and clear cut developing platform for quantum programs and the gap between theoretical concepts and practicalities of quantum computing. There are many developers who have no knowledge in developing and applying the concept of quantum computing and the code structuring of a quantum algorithm.

Quantum computing programmers can write algorithms and program them using different technical stacks. They can learn mathematical concepts like matrices, vectors, tensors, and sets. It will be good if they can learn physics topics such as quantum mechanics, quantum operations, and quantum physics. These skills will help them to get on to quantum AI based platforms and cloud services.

Quantum Solutions are related to building quantum algorithms for improving computational tasks within quantum computing, artificial intelligence, data science, and machine learning.  Quantum solutions are picking up in terms of speed compared to quantum computer innovation. Various solutions such as the Traveling Salesman Problem, quantum cryptography, scheduling, and cyber security are implemented based on quantum algorithms. There are other real-life problems which are evolving such as risk assessment and fraud detection in banking. In pharma, we look at drug discovery and protein folding solutions. Supply chain optimization and purchasing solutions are presented in the manufacturing domain. In utility, energy distribution and optimization problems are explained in detail with solutions. Advertising scheduling and revenue optimization solutions are covered by media and technology verticals.

The areas that quantum machine learning is applied is in the areas of nano-particles, material discovery, chemical design, drug design, pattern recognition, and classification. The applicable use cases are creating new materials that can be applied in space tech, wearable tech, renewable energy, nanotech, new drugs, and chemical combinations, genetic science, biometrics, IoT devices, and universe discovery. Rose's Law states that the computational power of quantum computers doubles every 12 months, as opposed to the 18 months doubling of Moore's Law.

Quantum Computers have the potential to solve problems that would take a classical computer longer than the age of the universe. 
- David Deutsch, a professor from Oxford University

Barclays, Goldman Sachs, and other financial firms are investigating the potential use of quantum computing in areas such as portfolio optimization, asset pricing, capital project budgeting, and data security. In aerospace, Airbus is exploring applications in communications and cryptography. Lockheed Martin is investigating applications in the verification and validation of complex systems. The US Navy has plans to develop algorithms for optimization problems such as data storage and energy-efficient data retrieval with underwater autonomous robots. NASA is exploring applications in communications, distributed navigation, and system diagnostics. Technology players such as Alibaba, Google, and IBM are working on applications such as hack-resistant cryptography, software debugging, and machine learning. Life sciences firms are seeking applications of quantum computing in personalized medicine and drug discovery.

About the Author

Bhagvan Kommadi is the founder of Architect Corner, an AI startup, and he has 20 years of industry experience ranging from large-scale enterprise development to helping incubate software product startups. He has a master's degree in industrial systems engineering from the Georgia Institute of Technology and a bachelor's degree in aerospace engineering from the Indian Institute of Technology, Madras. He is a member of the IFX Forum, Oracle JCP, and a participant in the Java Community Process.

Bhagvan founded Quantica Computacao, the first quantum computing startup in India. He has engineered and developed simulators and tools in quantum technology using IBM Q, Microsoft Q#, and Google QScript. The company's focus is on developing quantum cryptographic tools to provide quantum-proof data security, which will help banking institutions protect their transactions. He is now Director of Product Engineering at Value Momentum. Value Momentum has a social network for doctors (White Coats) and provides Telehealth support through the Practice Plus suite of products and services.

This article was contributed by Bhagvan Kommadi, author of Quantum Computing Solutions.