# A neural-network-like quantum information processing system

@article{Perus2003ANQ, title={A neural-network-like quantum information processing system}, author={M. Perus and H. Bischof}, journal={arXiv: Quantum Physics}, year={2003} }

The Hopfield neural networks and the holographic neural networks are models which were successfully simulated on conventional computers. Starting with these models, an analogous fundamental quantum information processing system is developed in this article. Neuro-quantum interaction can regulate the "collapse"-readout of quantum computation results. This paper is a comprehensive introduction into associative processing and memory-storage in quantum-physical framework.

#### 5 Citations

Quantum Hopfield Model

- Physics, Mathematics
- 2012

We find the free-energy in the thermodynamic limit of a one dimensional XY model associated to a system of N qubits. The coupling among the sigma_i^z is a long range two bodies random interaction.… Expand

Emerging Consciousness as a Result of Complex-Dynamical Interaction Process

- Mathematics
- 2004

A quite general interaction process within a multi-component system is analysed by the extended effective potential method, liberated from usual limitations of perturbation theory or integrable… Expand

Quantum Associative Memory with Improved Distributed Queries

- Computer Science, Physics
- 2013

An improved quantum associative algorithm with distributed query based on model proposed by Ezhov et al. is proposed that optimized data retrieval of correct multi-patterns simultaneously for any rate of the number of the recognition pattern on the total patterns. Expand

A Bergsonian Conception of Matter as Knowing Substance

- Philosophy
- 2007

This article describes a novel approach to the understanding of the mind-matter relationship in the tradition of Bergson’s conception of matter, falling, in his words, in the middle between… Expand

#### References

SHOWING 1-10 OF 19 REFERENCES

Quantum neural network

- Mathematics
- 2001

It is suggested that a quantum neural network (QNN), a type of artificial neural network, can be built using the principles of quantum information processing. The input and output qubits in the QNN… Expand

Quantum Neural Nets

- Physics
- 1998

The capacity of classical neurocomputers islimited by the number of classical degrees of freedom,which is roughly proportional to the size of thecomputer. By contrast, a hypothetical… Expand

[Physical models of neural networks].

- Computer Science, Medicine
- Biofizika
- 1987

The relaxational dynamics of neurons firing and suppression within the short- term memory layer under the influence of the long-term memory layer is studied and the interaction among the layers has found to create a number of novel stable states which are not the learning patterns. Expand

Modeling brain function: the world of attractor neural networks, 1st Edition

- Computer Science
- 1989

One of a good overview all the output neurons. The fixed point attractors have resulted in order to the attractor furthermore. As well as memory classification and all the basic ideas. Introducing… Expand

Quantum holography.

- Medicine, Physics
- Optics express
- 2001

We propose to make use of quantum entanglement for extracting holographic information about a remote 3-D object in a confined space which light enters, but from which it cannot escape. Light… Expand

An Introduction to Quantum Computers

- Mathematics, Physics
- 1998

This is a short introduction to quantum computers, quantum algorithms and quantum error correcting codes. Familiarity with the principles of quantum theory is assumed. Emphasis is put on a concise… Expand

Synergetic Computers and Cognition

- Computer Science, Psychology
- Springer Series in Synergetics
- 1991

This monograph aims to present a novel approach to neural nets and thus offers a genuine alternative to the hitherto known neuro-computers. This approach is based on the author's discovery of the… Expand

Statistical learning theory

- Computer Science
- 1998

Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more. Expand

Holography in ANNs

- Nature, 343, 325. Psaltis, D., and Mok, F. (1995). Scien. Amer., 273, No. 5 (November), 52. Scarani, V. (1998). Amer. J. Phys., 66, 956. Schempp, W. (1994). In Wavelets and Their Applications, J.S. Byrnes et al., eds., Kluwer, Amsterdam, 1994, p. 213.
- 1990

Modeling Brain Functions (The World of Attractor Neural Nets)

- Physica D
- 1989