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Iranian Conference on Electrical Engineering

GOWQS: Graph-based one-way quantum computation simulator

Eesa Nikahd, Mahboobeh Houshmand, Morteza Saheb Zamani, Mehdi Sedighi

Published May 1, 2016• 1 citation
Publisher

Abstract

In the one-way quantum computation (1WQC) model, computations are done by correlated sequences of entanglement, measurement and local corrections commands. As scalable and reliable quantum computers have not been implemented yet, the only widely available tools for designing and testing quantum algorithms are quantum computation simulators. However, simulating quantum computations on a standard classical computer in most cases requires very large memory and time. Recently, an array-based simulator, called one-way quantum computation simulator (OWQS) has been proposed to directly simulate the 1WQC model. OWQS outperforms the previously proposed quantum computation simulators to simulate the 1WQC model. In this paper, OWQS is modified in a way that it utilizes the graph-based representation of system states using algebraic decision diagram (ADD) in order to benefit from the similarities in the quantum states of 1WQC. This simulator is called graph-based OWQS, GOWQS. Experimental results validate the considerable improvement of the proposed simulator as compared to OWQS.

DOI
10.1109/iraniancee.2016.7585618

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In the one-way quantum computation (1WQC) model, computations are done by correlated sequences of entanglement, measurement and local corrections commands. As scalable and reliable quantum computers have not been implemented yet, the only widely available tools for designing and testing quantum algorithms are quantum computation simulators. However, simulating quantum computations on a standard classical computer in most cases requires very large memory and time. Recently, an array-based simulator, called one-way quantum computation simulator (OWQS) has been proposed to directly simulate the 1WQC model. OWQS outperforms the previously proposed quantum computation simulators to simulate the 1WQC model. In this paper, OWQS is modified in a way that it utilizes the graph-based representation of system states using algebraic decision diagram (ADD) in order to benefit from the similarities in the quantum states of 1WQC. This simulator is called graph-based OWQS, GOWQS. Experimental results validate the considerable improvement of the proposed simulator as compared to OWQS.
In one-way quantum computation (1WQC) model, universal quantum computations are performed using measurements to designated qubits in a highly entangled state. The choices of basis for these measurements as well as the structure of the entanglements specify a quantum algorithm. Although a number of methods have been proposed to simulate quantum circuit model on classical computers, no efficient tool has been developed to simulate the 1WQC model directly. In this paper, some techniques such as qubit elimination, implicit and in-place matrix-vector multiplication and pattern reordering are utilized to considerably reduce the time and memory needed for the simulations. These techniques were implemented in a tool called One-Way Quantum computation Simulator (OWQS). Experimental results validate the efficiency of the proposed approach.
In one-way quantum computation (1WQC) model, universal quantum computations are performed using measurements to designated qubits in a highly entangled state. The choices of bases for these measurements as well as the structure of the entanglements specify a quantum algorithm. As scalable and reliable quantum computers have not been implemented yet, quantum computation simulators are the only widely available tools to design and test quantum algorithms. However, simulating the quantum computations on a standard classical computer in most cases requires exponential memory and time. In this paper, a general direct simulator for 1WQC, called OWQS, is presented. Some techniques such as qubit elimination, pattern reordering and implicit simulation of actions are used to considerably reduce the time and memory needed for the simulations. Moreover, our simulator is adjusted to simulate the measurement patterns with a generalized flow without calculating the measurement probabilities which is called extended one-way quantum computation simulator (EOWQS). Experimental results validate the feasibility of the proposed simulators and that OWQS and EOWQS are faster as compared with the well-known quantum circuit simulators, i.e., QuIDDPro and libquantum for simulating 1WQC model.
In one-way quantum computations (1WQC), quantum correlations in an entangled state, called a cluster or graph state, are exploited to perform universal quantum computations using single-qubit measurements. The choices of bases for these measurements as well as the structure of the entanglements specify a quantum algorithm. The needed computations in this model are organized as patterns. Previously, an approach to extract a 1WQC pattern from a quantum circuit was proposed. The approach takes a quantum circuit consisting of only CZ andj(oc) gates and translates it into a 1WQC pattern after performing some known optimizations. However, most quantum synthesis algorithms decompose circuits using a library containing CNOT and any single-qubit gates. In this paper, we show how this approach can be modified in a way that it can take a circuit consisting of CNOT and any single-qubit gates as well as CZ and J(oc) gates to produce a 1WQC pattern. Experimental results show that adding CNOT gate directly to the pattern decreases the translation run-time.
In one-way quantum computation (1WQC) model, an initial highly entangled state called a graph state is used to perform universal quantum computations by a sequence of adaptive single-qubit measurements and post-measurement Pauli-X and Pauli-Z corrections. The needed computations are organized as measurement patterns or simply patterns in the 1WQC model. The entanglement operations in a pattern can be shown by a graph which together with the set of its input and output qubits is called the geometry of the pattern. Causal flow is a sufficient condition to identify a dependency structure for measurement sequences in order to obtain determinism. Signal shifting is an optimization technique which uses a set of rewrite rules to propagate the Pauli-Z corrections on the measured qubits to the end of patterns. However, automatically applying these rules has difficulties for implementation and is time consuming due to using many ineffective commutation rules. To overcome this problem, in this paper, a new automatic approach is proposed to perform signal shifting on patterns with flows based on their geometries instead of using rewriting rules. It is shown that the time complexity of the proposed approach is improved compared to the previous ones.
We introduce an open-source software library Graphix, which optimizes and simulates measurement-based quantum computation (MBQC). By combining the measurement calculus with an efficient graph state simulator, Graphix allows the classical preprocessing of Pauli measurements in the measurement patterns, significantly reducing the number of operations required to perform the quantum computation while maintaining determinism. For a measurement pattern translated from a quantum circuit, this corresponds to the preprocessing of all Clifford gates, and this improvement in the one-way model is important for efficient operations in quantum hardware with limited qubit numbers. In addition to the direct translation from gate networks, we provide a pattern generation method based on flow-finding algorithms, which automatically generates byproduct correction sequences to ensure determinism. We further implement optimization strategies for measurement patterns beyond the standardization procedure and provide tensor-network backend for classically simulating the MBQC.
In the formalism of measurement based quantum computation we start with a given fixed entangled state of many qubits and perform computation by applying a sequence of measurements to designated qubits in designated bases. The choice of basis for later measurements may depend on earlier measurement outcomes and the final result of the computation is determined from the classical data of all the measurement outcomes. This is in contrast to the more familiar gate array model in which computational steps are unitary operations, developing a large entangled state prior to some final measurements for the output. Two principal schemes of measurement based computation are teleportation quantum computation (TQC) and the so-called cluster model or one-way quantum computer (1WQC). We will describe these schemes and show how they are able to perform universal quantum computation. We will outline various possible relationships between the models which serve to clarify their workings. We will also discuss possible novel computational benefits of the measurement based models compared to the gate array model, especially issues of parallelisability of algorithms.