Quantum Computing

Quantum computing was first proposed by physicist Paul Benioff in 1980. The idea was motivated primarily to simulate quantum mechanical phenomena. Initial efforts led to the development of first quantum key distribution protocol, Shor’s factoring algorithm, and Grover’s quantum search algorithm. This was followed by a proliferation of interest in quantum computing. We are currently at an inflection point where the quantum ecosystem continues to grow globally with various institutions devoting their resources to the advancement of this field.

For a practitioner, quantum computers can speed up various fundamental algorithms that have applications in financial modeling, machine learning, drug discovery, and many other fields. The enormous potential of quantum computing makes realizing a fully-scalable quantum computer an endeavor of immense academic and industrial interest. Efforts are underway and the current landscape on quantum hardware is focused on developing quantum devices with few reliable qubits and error-mitigation techniques. Such devices, colloquially known as near-term intermediate scale quantum (NISQ) devices, offer good accuracy as long as the time to perform quantum operations is below a threshold.

At Fujitsu, our focus is on enabling research and development on quantum computing. We accomplish this through various academic and industrial collaborations. Specifically, Fujitsu Research of America oversees the power and limits of quantum computing through algorithmic design and applications. We focus on quantum algorithmic applications in data analysis and machine learning that can be potentially implemented on future NISQ devices. Our research also includes designing quantum algorithms that promise provable guarantee over existing classical algorithms with respect to computational resources. Identifying applications of quantum computing in computational models that are realized in real-world scenarios such as sliding window/ streaming model, interaction with clouds, federated computation, etc. is a necessary part of the process to explore future usability of such research. Another research topic of interest is interconnection between quantum information and other research areas.


  1. 1. Sevag Gharibian, Jamie Sikora, and Sarvagya Upadhyay. QMA Variants with Polynomially Many Provers. Quantum Information and Computation, 13(1--2): 0135--0157, 2013.
  2. 2. Rahul Jain, Zhengfeng Ji, Sarvagya Upadhyay, and John Watrous. QIP} = PSPACE. Journal of the ACM, 58(6): Article 30, 2011.
  3. 3. Rahul Jain, Sarvagya Upadhyay, and John Watrous. Two--Message Quantum Interactive Proofs are in PSPACE}. In Proceedings of the 50th Annual IEEE Symposium on Foundations of Computer Science, pages 534--543, 2009.
  4. 4. Richard Cleve, William Slofstra, Falk Unger, and Sarvagya Upadhyay. Perfect Parallel Repetition Theorem for Quantum XOR Proof Systems. Computational Complexity, 17(2): 282--299, 2008.
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