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arXiv:quant-ph/9712004

Models to Reduce the Complexity of Simulating a Quantum Computer

Kevin Obenland, Alvin M. Despain

Published Dec 2, 1997• 3 citations
arXivHTMLPDF

Abstract

Recently Quantum Computation has generated a lot of interest due to the discovery of a quantum algorithm which can factor large numbers in polynomial time. The usefulness of a quantum com puter is limited by the effect of errors. Simulation is a useful tool for determining the feasibility of quantum computers in the presence of errors. The size of a quantum computer that can be simulat ed is small because faithfully modeling a quantum computer requires an exponential amount of storage and number of operations. In this paper we define simulation models to study the feasibility of quantum computers. The most detailed of these models is based directly on a proposed imple mentation. We also define less detailed models which are exponentially less complex but still pro duce accurate results. Finally we show that the two different types of errors, decoherence and inaccuracies, are uncorrelated. This decreases the number of simulations which must be per formed.

DOI
10.48550/arxiv.quant-ph/9712004

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Recently Quantum Computation has generated a lot of interest due to the discovery of a quantum algorithm which can factor large numbers in polynomial time. The usefulness of a quantum com puter is limited by the effect of errors. Simulation is a useful tool for determining the feasibility of quantum computers in the presence of errors. The size of a quantum computer that can be simulat ed is small because faithfully modeling a quantum computer requires an exponential amount of storage and number of operations. In this paper we define simulation models to study the feasibility of quantum computers. The most detailed of these models is based directly on a proposed imple mentation. We also define less detailed models which are exponentially less complex but still pro duce accurate results. Finally we show that the two different types of errors, decoherence and inaccuracies, are uncorrelated. This decreases the number of simulations which must be per formed.
Quantum computation is a new technology with the potential for providing exponential parallelism. The feasibility of a quantum computer is limited by two different types of errors, decoherence and inaccuracies. This dissertation uses simulation to investigate the feasibility of implementing one of the proposed realizations of a quantum computer, the trapped ion quantum computer. Because of the exponential complexity of a quantum computer, simulating one requires vast processing and memory resources. For this reason I develop several techniques to reduce the complexity of simulating a quantum computer. A parallel simulator is also used. Using the parallel simulator I am able to simulate circuits with close to 100,000 basic operations. The simulation studies show that the effectiveness of a quantum computer, without a mechanism for controlling errors, is severely limited. However the power of a quantum computer can be increased by using several techniques to mitigate the effects of error. Therefore a realizable quantum computer has three fundamental requirements: First, both hardware and software mechanisms must be used to correct errors as they occur. Second, the architecture of a quantum computer is very important; it must be designed to mitigate errors and it must be able to execute multiple operations in parallel. Last, quantum circuits must be constructed in an efficient manner, to minimize the total number of operations.
The last two decades feature an ever-increasing interest in quantum information processing - generalization of the classical computational models in the view of quantum mechanics (QM). In theory, quantum computational devices are capable of solving in polynomial time problems for which only algorithms with exponential time complexity are known. Such enormous advantage explains the global scale of scientific efforts for creating the quantum computer - physical realization of such computational device. While the results of those efforts are still constrained inside the large experimental laboratories, an adequate tool for studying quantum algorithms will be of great help for educating the next generation of computer scientists - the engineers that will be responsible for operating these devices. The paper describes a quantum computer simulation model that exhibits a certain attractive property - the simulation slowdown does not depend directly on the size of the input data but rather on the complexity of the quantum state, meaning that transformations upon less-entangled data are performed faster. Based on this property the simulation can be spread between the nodes of a grid cluster in a way as to keep the entanglement in each job minimal
A Quantum Computer is a new type of computer which can solve problems such as factoring and database search very efficiently. The usefulness of a quantum computer is limited by the effect of two different types of errors, decoherence and inaccuracies. In this paper we show the results of simulations of a quantum computer which consider both decoherence and inaccuracies. We simulate circuits which factor the numbers 15, 21, 35, and 57 as well as circuits which use database search to solve the circuit satisfaction problem. Our simulations show that the error rate per gate is on the order of 10^-6 for a trapped ion quantum computer whose noise is kept below pi/4096 per gate and with a decoherence rate of 10^-6. This is an important bound because previous studies have shown that a quantum computer can factor more efficiently than a classical computer if the error rate is of order 10^-6.
An ultimate goal of quantum computing is to perform calculations beyond the reach of any classical computer.It is therefore imperative that useful quantum computers be very difficult to simulate classically, otherwise classical computers could be used for the applications envisioned for the quantum ones.Perfect quantum computers are unarguably exponentially difficult to simulate: the classical resources required grow exponentially with the number of qubits N or the depth D of the circuit.This difficulty has triggered recent experiments on deep, random circuits that aim to demonstrate that quantum devices may already perform tasks beyond the reach of classical computing.These real quantum computing devices, however, suffer from many sources of decoherence and imprecision which limit the degree of entanglement that can actually be reached to a fraction of its theoretical maximum.They are characterized by an exponentially decaying fidelity F ∼ ð1 -ϵÞ ND with an error rate ϵ per operation as small as ≈1% for current devices with several dozen qubits or even smaller for smaller devices.In this work, we provide new insight on the computing capabilities of real quantum computers by demonstrating that they can be simulated at a tiny fraction of the cost that would be needed for a perfect quantum computer.Our algorithms compress the representations of quantum wave functions using matrix product states, which are able to capture states with low to moderate entanglement very accurately.This compression introduces a finite error rate ϵ so that the algorithms closely mimic the behavior of real quantum computing devices.The computing time of our algorithm increases only linearly with N and D in sharp contrast with exact simulation algorithms.We illustrate our algorithms with simulations of random circuits for qubits connected in both one-and twodimensional lattices.We find that ϵ can be decreased at a polynomial cost in computing power down to a minimum error ϵ ∞ .Getting below ϵ ∞ requires computing resources that increase exponentially with ϵ ∞ =ϵ.For a two-dimensional array of N ¼ 54 qubits and a circuit with control-Z gates, error rates better than state-of-the-art devices can be obtained on a laptop in a few hours.For more complex gates such as a SWAP gate followed by a controlled rotation, the error rate increases by a factor 3 for similar computing time.Our results suggest that, despite the high fidelity reached by quantum devices, only a tiny fraction ð∼10 -8 Þ of the system Hilbert space is actually being exploited.
A Quantum Computer is a new type of computer which can efficiently solve complex problems such as prime factorization. A quantum computer threatens the security of public key encryption systems because these systems rely on the fact that prime factorization is computationally difficult. Errors limit the effectiveness of quantum computers. Because of the exponential nature of quantum com puters, simulating the effect of errors on them requires a vast amount of processing and memory resources. In this paper we describe a parallel simulator which accesses the feasibility of quantum computers. We also derive and validate an analytical model of execution time for the simulator, which shows that parallel quantum computer simulation is very scalable.
Quantum Computing (QC) research has gained a lot of momentum recently due to several theoretical analyses that indicate that QC is significantly more efficient at solving certain classes of problems than classical computing. While experimental validation will ultimately be required, the primitive nature of current QC hardware leaves practical testing limited to trivial examples. Thus, a robust simulator is needed to study complex QC issues. Most QC simulators model ideal operations, and thus cannot predict the actual time required to execute an algorithm or quantify the effects of errors in the calculation. We have developed a novel QC simulator that models physical hardware implementations. This simulator not only allows the accurate simulation of quantum algorithms on various hardware implementations, but also takes an important step towards providing a framework to determine their true performance and vulnerability to errors.