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IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM)

Modeling a quantum processor using the QRAM model

Mostafa Elhoushi, Mohamed Watheq El-Kharashi, Hatem Elrefaei

Published Aug 1, 2011• 7 citations
Publisher

Abstract

A quantum processor controlled by classical instructions is modeled. The processor follows the quantum random access machine (QRAM) model: a quantum memory and a quantum ALU (qALU) containing a group of quantum gates, which are controlled by classical signals. The processor's instructions are written using a quantum assembly (QASM) language. As test cases, several well-known quantum circuits are described using the QASM language and executed by our model. This model may later be integrated with classical components to form a hybrid quantum computer.

DOI
10.1109/pacrim.2011.6032928

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A quantum processor controlled by classical instructions is modeled. The processor follows the quantum random access machine (QRAM) model: a quantum memory and a quantum ALU (qALU) containing a group of quantum gates, which are controlled by classical signals. The processor's instructions are written using a quantum assembly (QASM) language. As test cases, several well-known quantum circuits are described using the QASM language and executed by our model. This model may later be integrated with classical components to form a hybrid quantum computer.
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Models of quantum computation and quantum programming languages The goal of the presented paper is to provide an introduction to the basic computational models used in quantum information theory. We review various models of quantum Turing machine, quantum circuits and quantum random access machine (QRAM) along with their classical counterparts. We also provide an introduction to quantum programming languages, which are developed using the QRAM model. We review the syntax of several existing quantum programming languages and discuss their features and limitations.
This article presents the definition and implementation of a quantum computer architecture to enable creating a new computational device-a quantum computer as an accelerator. A key question addressed is what such a quantum computer is and how it relates to the classical processor that controls the entire execution process. In this article, we present explicitly the idea of a quantum accelerator that contains the full stack of the layers of an accelerator. Such a stack starts at the highest level describing the target application of the accelerator. The next layer abstracts the quantum logic outlining the algorithm that is to be executed on the quantum accelerator. In our case, the logic is expressed in the universal quantum-classical hybrid computation language developed in the group, called OpenQL, which visualized the quantum processor as a computational accelerator. The OpenQL compiler translates the program to a common assembly language, called cQASM, which can be executed on a quantum simulator. The cQASM represents the instruction set that can be executed by the microarchitecture implemented in the quantum accelerator. In a subsequent step, the compiler can convert the cQASM to generate the eQASM, which is executable on a particular experimental device incorporating the platform-specific parameters. This way, we are able to distinguish clearly the experimental research toward better qubits, and the industrial and societal applications that need to be developed and executed on a quantum device. The first case offers experimental physicists with a full-stack experimental platform using realistic qubits with decoherence and error-rates, whereas the second case offers perfect qubits to the quantum application developer, where there is neither decoherence nor error-rates. We conclude the article by explicitly presenting three examples of full-stack quantum accelerators, for an experimental superconducting processor, for quantum accelerated genome sequencing and for near-term generic optimization problems based on quantum heuristic approaches. The two later full-stack models are currently being actively researched in our group.
This paper presents the definition and implementation of a quantum computer architecture to enable creating a new computational device - a quantum computer as an accelerator. A key question addressed is what such a quantum computer is and how it relates to the classical processor that controls the entire execution process. In this paper, we present explicitly the idea of a quantum accelerator which contains the full stack of the layers of an accelerator. Such a stack starts at the highest level describing the target application of the accelerator. The next layer abstracts the quantum logic outlining the algorithm that is to be executed on the quantum accelerator. In our case, the logic is expressed in the universal quantum-classical hybrid computation language developed in the group, called OpenQL, which visualised the quantum processor as a computational accelerator. The OpenQL compiler translates the program to a common assembly language, called cQASM, which can be executed on a quantum simulator. The cQASM represents the instruction set that can be executed by the micro-architecture implemented in the quantum accelerator. We propose that the industrial and societal application developers use perfect qubits that have no decoherence or error-rates. The perfect qubits offers facilities to the quantum application developer and they are not blocked by issues such as decoherence.
We present the SQRAM architecture for quantum computing, which is based on Knill's QRAM model. We detail a suitable instruction set, which implements a universal set of quantum gates, and demonstrate the operation of the SQRAM with Deutsch's quantum algorithm. The compilation of high-level quantum programs for the SQRAM machine is considered; we present templates for quantum assembly code and a method for decomposing matrices for complex quantum operations. The SQRAM simulator and compiler are discussed, along with directions for future work.
Quantum memory is proposed as an analogue to classical computer memory, like the random-access memory (RAM). RAM is a form of computer memory that can be read and changed in any order, typically used to store working data. In quantum machine learning domain, the usage of quantum random access memory (qRAM) is proposed to avoid input destruction problem. The method of qRAM is related to the entanglement of the index qubits that are in the superposition with the patterns. The method of qRAM is related to the entanglement of the index qubits that are in the superposition with the patterns. As in the method of the entanglement of the index qubits, the qubits of qRAM are entangled during the reading operation and have to be un-computed after computation.