How to copy Data into a Quantum Computer?

Can large amounts of data be meaningfully copied into quantum computers? This question is to be assessed using a novel method, with a view to an application in marketing strategy. If this could be affirmed, it would be a major step for the use of quantum computers.

In expert circles, it is often claimed that large amounts of data do not work well with quantum computers: a very large number of computational operations are required to get the data into a quantum state – the computational memory of the quantum computer. Known quantum advantages are thereby lost. Currently, researched methods have not yet reached a holistic view and thus cannot answer the pressing question: will large amounts of data ever become interesting for quantum computations?

In this project, the question of how meaningful it is to copy large amounts of data into quantum memory will now be answered using concrete case examples from machine learning and portfolio optimization. It is possible to accept a loss of quality to significantly reduce the computational operations during the copying process. The project aims to push the boundaries of this method and thereby answer the question whether large amounts of data can be made usefully applicable on quantum computers.

If it could be shown that large amounts of data could be meaningfully combined with quantum computations, this would be important for the entire industry. The area in which quantum computers are useful would expand enormously, creating values in the trillions. On the other hand, it is crucial to know if even the novel approach in the project does not lead to a meaningful utilization. This would also be significant for the development of quantum computers.

The consortium consists of partners with complementary specializations. Under the leadership of data cybernetics, experts in software, research, and consulting, a demonstrator will be developed based on their invention.

DATEV eG, together with DHBW Stuttgart, will explore applications in portfolio optimization and machine learning using a problem from marketing strategy.

The Weierstrass Institute in Berlin, together with data cybernetics, will develop and substantially improve the mathematical foundation of the invention. The University of Hamburg will focus on the physical aspects of the implementation and develop methods to reduce or avoid quantum errors.

Overall, all areas will be orchestrated together to answer the question: can large amounts of data be meaningfully processed with quantum computers?

At the end of the project, all developments will be connected with the application problem of the marketing strategy, and resources will be estimated. The evaluation of this question is the actual result.

Our Goal