# A strategy for quantum algorithm design assisted by machine learning

@article{Bang2014ASF, title={A strategy for quantum algorithm design assisted by machine learning}, author={Jeongho Bang and Junghee Ryu and Seokwon Yoo and M. Pawłowski and Jinhyoung Lee}, journal={New Journal of Physics}, year={2014}, volume={16}, pages={073017} }

We propose a method for quantum algorithm design assisted by machine learning. The method uses a quantum–classical hybrid simulator, where a 'quantum student' is being taught by a 'classical teacher'. In other words, in our method, the learning system is supposed to evolve into a quantum algorithm for a given problem, assisted by a classical main-feedback system. Our method is applicable for designing quantum oracle-based algorithms. We chose, as a case study, an oracle decision problem, called… Expand

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#### References

SHOWING 1-10 OF 46 REFERENCES

The speed of quantum and classical learning for performing the kth root of NOT

- Computer Science, Physics
- 2009

An explicit example of the task for which numerical simulations show that quantum learning is faster than its classical counterpart is found, and the reason for this speed-up is that the classical machine requires memory of size logk = m to accomplish the learning, while the memory of a single qubit is sufficient for the quantum machine for any k. Expand

Quantum algorithm design using dynamic learning

- Computer Science, Mathematics
- Quantum Inf. Comput.
- 2008

A dynamic learning paradigm for "programming" a general quantum computer, used to find the control parameters for a coupled qubitsystem, such that the system at an initial time evolves to a state in which a given measurementresponds to the desired operation. Expand

Quantum Learning Machine

- Mathematics, Physics
- 2008

School of Mathematics and Physics, The Queen’s University of Belfast, BT7 1NN, United Kingdom(Received March 31, 2008)We propose a novel notion of a quantum learning machine for automatically… Expand

Machine learning for precise quantum measurement.

- Computer Science, Physics
- Physical review letters
- 2010

This work adapts machine learning for quantum information and uses its framework to generate autonomous adaptive feedback schemes for quantum measurement that outperform the best known adaptive scheme for interferometric phase estimation. Expand

Optimal quantum learning of a unitary transformation

- Physics
- 2010

We address the problem of learning an unknown unitary transformation from a finite number of examples. The problem consists in finding the learning machine that optimally emulates the examples, thus… Expand

Quantum learning speedup in binary classification

- Computer Science
- 2013

It is shown that quantum superposition enables quantum learning faster than classical learning by expanding the solution regions and is demonstrated by numerical simulations with a standard feedback model, random search, and a practical model, differential evolution. Expand

A genetic-algorithm-based method to find unitary transformations for any desired quantum computation and application to a one-bit oracle decision problem

- Computer Science, Physics
- 2014

A genetic-algorithm-based method to find the unitary transformations for any desired quantum computation and to generalize the corresponding quantum algorithms for a realistic problem, the one-bit oracle decision problem, or the often-called Deutsch problem. Expand

Quantum Mechanics Helps in Searching for a Needle in a Haystack

- Physics
- 1997

Quantum mechanics can speed up a range of search applications over unsorted data. For example, imagine a phone directory containing $N$ names arranged in completely random order. To find someone's… Expand

Deutsch-Jozsa algorithm as a test of quantum computation

- Physics
- 1998

A redundancy in the existing Deutsch-Jozsa quantum algorithm is removed and a refined algorithm, which reduces the size of the register and simplifies the function evaluation, is proposed. The… Expand

Quantum learning by measurement and feedback

- Physics
- 2009

We investigate an approach to quantum computing in which quantum gate strengths are parametrized by quantum degrees of freedom. The capability of the quantum computer to perform desired tasks is… Expand