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IEEE Conference on Nanotechnology (IEEE NANO)

Quantum Boolean circuit construction and layout under locality constraint

I.-M. Tsai, Sy‐Yen Kuo

Published Nov 13, 2002• 17 citations
Publisher

Abstract

The discovery of Shor's prime factorization and Grover's fast database search algorithm have made quantum computing the most rapidly expanding research field recently. Nanotechnology, in particular silicon-based nanoscale devices, have been proposed as one of the candidates that can be used to implement a quantum computer. In this paper, we have derived a systematic procedure to realize any general m-to-n bit combinational Boolean logic using elementary quantum gates. The quantum circuit layout under the locality constraint is then formulated, together with the gate count evaluation function, to reduce the total number of quantum gates required to implement the circuit.

DOI
10.1109/nano.2001.966403

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The discovery of Shor's prime factorization and Grover's fast database search algorithm have made quantum computing the most rapidly expanding research field recently. Nanotechnology, in particular silicon-based nanoscale devices, have been proposed as one of the candidates that can be used to implement a quantum computer. In this paper, we have derived a systematic procedure to realize any general m-to-n bit combinational Boolean logic using elementary quantum gates. The quantum circuit layout under the locality constraint is then formulated, together with the gate count evaluation function, to reduce the total number of quantum gates required to implement the circuit.
To build a general-purpose quantum computer, it is crucial for the quantum devices to implement classical boolean logic. A straightforward realization of quantum boolean logic is to use auxiliary qubits as intermediate storage. This inefficient implementation causes a large number of auxiliary qubits to be used. In this paper, we have derived a systematic way of realizing any general m-to-n bit combinational boolean logic using elementary quantum gates. Our approach transforms the m-to-n bit classical mapping into a t-bit unitary quantum operation with minimum number of auxiliary qubits, then a variation of Toffoli gate is used as the basic building block to construct the unitary operation. Finally, each of these building blocks can be decomposed into one-bit rotation and two-bit control-U gates. The efficiency of the network is taken into consideration by formulating it as a constrained set partitioning problem.
Implementing a quantum computer at the circuit level has emerged as an important field of research recently. An important topic of building a general-purpose quantum computer is to implement classical Boolean logic using quantum gates and devices. Since the Toffoli gate is universal in classical Boolean logic, any classical combinational circuit can be implemented by the straightforward replacement algorithm with auxiliary qubits as intermediate storage. However, this inefficient implementation causes a large number of auxiliary qubits to be used. In this paper, a systematic procedure is proposed to derive a minimum space quantum circuit for a given classical combinational logic. We first formulate the problem of transforming an m-to-n bit classical Boolean logic into a t-bit unitary quantum operation. The eligible solution set is then constructed such that a solution can be found simply by selecting any member from this set. Finally, we show that the algorithm is optimal in terms of the space consumption.
The discovery of polynomial time prime factorization, secure key distribution, and fast database search algorithm have recently made quantum computing the most rapidly expanding research field. For a quantum algorithm to be useful, it is essential that the algorithm can be implemented using quantum circuits. Nanotechnology, in particular quantum mechanics based devices, can be used to realize such an algorithm. In this paper, we show how quantum Boolean circuits can be used to implement the oracle circuit and the inversion-about-average function in Grover's search algorithm. We also show that a slight modification of the oracle circuit can be used to search multiple targets.
Abstract Implementing quantum algorithms on realistic devices requires translating high-level global operations into sequences of hardware-native logic gates, a process known as quantum compiling. Physical limitations, such as constraints in connectivity and gate alphabets, often result in unacceptable implementation costs. To enable successful near-term applications, it is crucial to optimize compilation by exploiting the capabilities of existing hardware. Here we implement a resource-efficient construction for a quantum version of AND logic that can reduce the compilation overhead, enabling the execution of key quantum circuits. On a high-scalability superconducting quantum processor, we demonstrate low-depth synthesis of high-fidelity generalized Toffoli gates with up to 8 qubits and Grover’s search algorithm in a search space of up to 64 entries. Our experimental demonstration illustrates a scalable and widely applicable approach to implementing quantum algorithms, bringing more meaningful quantum applications on noisy devices within reach.
Several prominent quantum computing algorithms—including Grover’s search algorithm and Shor’s algorithm for finding the prime factorization of an integer—employ subcircuits termed ‘oracles’ that embed a specific instance of a mathematical function into a corresponding bijective function that is then realized as a quantum circuit representation. Designing oracles, and particularly, designing them to be optimized for a particular use case, can be a non-trivial task. For example, the challenge of implementing quantum circuits in the current era of NISQ-based quantum computers generally dictates that they should be designed with a minimal number of qubits, as larger qubit counts increase the likelihood that computations will fail due to one or more of the qubits decohering. However, some quantum circuits require that function domain values be preserved, which can preclude using the minimal number of qubits in the oracle circuit. Thus, quantum oracles must be designed with a particular application in mind. In this work, we present two methods for automatic quantum oracle synthesis. One of these methods uses a minimal number of qubits, while the other preserves the function domain values while also minimizing the overall required number of qubits. For each method, we describe known quantum circuit use cases, and illustrate implementation using an automated quantum compilation and optimization tool to synthesize oracles for a set of benchmark functions; we can then compare the methods with metrics including required qubit count and quantum circuit complexity.
In recent years, the emergence of the Noisy Intermediate-Scale Quantum (NISQ) era has led to the development of a wide variety of quantum devices, marking a dynamic phase in the field of quantum computing. Despite these advancements, practical applications of quantum computers still face significant challenges, one of the most prominent being the limited connectivity between physical quantum bits (qubits). This limitation requires quantum circuits to be recompiled through layout synthesis before they can be executed on quantum devices. Layout synthesis determines the specific placement of quantum gates within the circuit on the physical hardware. When gates do not align with the connectivity constraints of the device, additional quantum gates must be inserted to remap the qubits, which can negatively affect the circuit’s efficiency and performance. To address this issue, the primary goal of this paper is to enhance the mapping process within layout synthesis, aiming to optimize both the layout and the circuit depth. Experimental results demonstrate that the proposed method effectively reduces the quantum circuit depth, outperforming other existing approaches in terms of efficiency.