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International Conference on Nanotechnology

Test data compression for any quantum Boolean circuits

Yao–Hsin Chou, Sy‐Yen Kuo

Published Jul 26, 2009• 1 citation
OpenAlex

Abstract

In this paper, a novel test data compression method for quantum Boolean circuits is proposed. By using Hadamard transformation as a decompressor for input vectors and as a time compactor for output responses, we can always detect the fault no matter where it occurs at the circuit under test. Following that, a zero-controlled-not gate can be applied as a space compactor. As a result, not only can the stimulus on the input side be significantly compressed to only one test pattern but also the response on the output side can be drastically compacted to one single bit.

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In this paper, a novel test data compression method for quantum Boolean circuits is proposed. By using Hadamard transformation as a decompressor for input vectors and as a time compactor for output responses, we can always detect the fault no matter where it occurs at the circuit under test. Following that, a zero-controlled-not gate can be applied as a space compactor. As a result, not only can the stimulus on the input side be significantly compressed to only one test pattern but also the response on the output side can be drastically compacted to one single bit.
Recently, a systematic procedure was proposed to derive a minimum input quantum circuit for any given classical logic with the generalized quantum Toffoli gate, which is universal in Boolean logic. Since quantum Boolean circuits are reversible, we can apply this property to build quantum iterative logic array (QILA). QILA can be easily tested in constant time (C-testable) if stuck-at fault model is assumed. In this paper, we use Hadamard and general controlled-controlled not gates to make QILA 1-testable. That is, for any quantum Boolean circuit, the number of test patterns is independent of both the size of the array and the length of the inputs.
Recently, a systematic procedure is proposed to derive a minimum space quantum circuit for a given classical logic with the generalized quantum Toffoli gate which is universal in classical boolean logic. Since quantum computation is reversible, we can use this property to build Quantum Iterative Logic Array (QILA). QILA can be easily tested in constant time (C-testable) if stuck-at fault model is assumed. In this paper, we apply Hadamard and general CCN gates on QILA circuits to make them 1-testable. As a result, for quantum boolean circuits, the number of test patterns is independent of both the size of the array and the length of the inputs.
It is shown that the fault testing for quantum circuits does not follow conventional classical techniques. If probabilistic gate like Hadamard gate is included in a circuit then the classical notion of test vector is shown to fail. We have reported several new and distinguishing features of quantum fault and also presented a general methodology for detection of functional faults in a quantum circuit. The technique can generate test vectors for detection of di erent kinds of fault. Speci c examples are given and time complexity of the proposed quantum fault detection algorithm is reported. 1
Test pattern generation is an electronic design automation tool that attempts to find an input (or test) sequence that, when applied to a digital circuit, enables one to distinguish between the correct circuit behavior and the faulty behavior caused by particular faults. The effectiveness of this classical method is measured by the fault coverage achieved for the fault model and the number of generated vectors, which should be directly proportional to test application time. This work address the quantum process validation problem by considering the quantum mechanical adaptation of test pattern generation methods used to test classical circuits. We found that quantum mechanics allows one to execute multiple test vectors concurrently, making each gate realized in the process act on a complete set of characteristic states in space/time complexity that breaks classical testability lower bounds.
As a ubiquitous aspect of modern information technology, data compression has a wide range of applications. Therefore, a quantum autoencoder which can compress quantum information into a low-dimensional space is fundamentally important to achieve automatic data compression in the field of quantum information. Such a quantum autoencoder can be implemented through training the parameters of a quantum device using classical optimization algorithms. In this paper, we demonstrate the condition of achieving a perfect quantum autoencoder and theoretically prove that a quantum autoencoder can losslessly compress high-dimensional quantum information into a low-dimensional space (also called latent space) if the number of maximum linearly independent vectors from input states is no more than the dimension of the latent space. Also, we experimentally realize a universal two-qubit unitary gate and design a quantum autoencoder device by applying a machine learning method. Experimental results demonstrate that our quantum autoencoder is able to compress two two-qubit states into two one-qubit states. Besides compressing quantum information, the quantum autoencoder is used to experimentally discriminate two groups of nonorthogonal states.