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arXiv:2207.13585

Error-analysis for the Sorkin and Peres tests performed on a quantum computer

Simanraj Sadana, Lorenzo Maccone, Urbasi Sinha

Published Jul 27, 2022• 0 citations
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Abstract

We use quantum computers to test the foundations of quantum mechanics through quantum algorithms that implement some of the experimental tests as the basis of the theory's postulates. These algorithms can be used as a test of the physical theory under the premise of a perfect hardware or as a test of the hardware under the premise that quantum theory is correct. In this paper, we show how the algorithms can be used to test the efficacy of a quantum computer in obeying the postulates of quantum mechanics. We study the effect of different types of errors on the results of experimental tests of the postulates. A salient feature of this error analysis is that it is deeply rooted in the fundamentals of quantum mechanics as it highlights how systematic errors affect the quantumness of the quantum computer.

DOI
10.48550/arxiv.2207.13585

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We use quantum computers to test the foundations of quantum mechanics through quantum algorithms that implement some of the experimental tests as the basis of the theory's postulates. These algorithms can be used as a test of the physical theory under the premise of a perfect hardware or as a test of the hardware under the premise that quantum theory is correct. In this paper, we show how the algorithms can be used to test the efficacy of a quantum computer in obeying the postulates of quantum mechanics. We study the effect of different types of errors on the results of experimental tests of the postulates. A salient feature of this error analysis is that it is deeply rooted in the fundamentals of quantum mechanics as it highlights how systematic errors affect the quantumness of the quantum computer.
We present two complementary viewpoints for combining quantum computers and the foundations of quantum mechanics. On one hand, ideal devices can be used as testbeds for experimental tests of the foundations of quantum mechanics: we provide algorithms for the Peres test of the superposition principle and the Sorkin test of Born's rule. On the other hand, noisy intermediate-scale quantum (NISQ) devices can be benchmarked using these same tests. These are deep-quantum benchmarks based on the foundations of quantum theory itself. We present test data from Rigetti hardware.
We present two complementary viewpoints for combining quantum computers and the foundations of quantum mechanics.On the one hand, ideal devices can be used as test beds for experimental tests of the foundations of quantum mechanics: We provide algorithms for the Peres test for complex numbers in quantum superpositions and the Sorkin test of Born's rule.On the other hand, noisy intermediate-scale quantum devices can be benchmarked using these same tests.These are deep quantum benchmarks based on the foundations of quantum theory itself.We present test data from Rigetti hardware.
The introduction of quantum computing has presented algorithmic solutions to computationally difficult challenges that are far more efficient than those of classical computers. These algorithms leverage the properties of quantum mechanics to manipulate the quantum properties of subatomic particles, requiring immense precision and stability. Current quantum hardware, however, is too noisy and introduces too many errors for these algorithms to be useful in practice, necessitating the use of error correction algorithms. This field survey seeks to introduce various principles of quantum mechanics relevant to quantum computing and quantum error correction (QEC), detail the implementation and motivations of a basic QEC algorithm, and provide insight into the current research direction.
This research paper provides an in-depth examination of verification and testing approaches for quantum circuits, focusing on methodologies essential for ensuring the correctness, reliability and operational efficiency of quantum computing systems. Since quantum circuits function on the fundamental principles of superposition and entanglement, they present verification challenges that cannot be effectively addressed using conventional classical testing techniques. As a result, the development of specialized quantum-specific verification strategies has become critically important. The study highlights simulation-based verification as a foundational technique, wherein the outcomes of quantum circuit simulations are systematically compared with results obtained from physical quantum hardware. This process enables the identification of functional inconsistencies and supports iterative refinement of circuit designs. In addition, randomized benchmarking is examined as a key evaluation method for estimating circuit fidelity and quantifying error rates through the application of random gate sequences and performance comparisons against established benchmarks. To further improve system robustness, the research investigates fault-tolerant mechanisms, particularly quantum error correction codes, which play a vital role in minimizing the effects of noise, decoherence and hardware imperfections. The integration of advanced quantum metrology and characterization techniques is also explored, enabling precise measurement and detailed analysis of quantum system behavior. These techniques provide deeper insights into circuit performance and contribute significantly to validation processes. By combining simulation-based verification, randomized benchmarking, fault-tolerant protocols and quantum metrology, this study proposes a comprehensive and reliable framework for quantum circuit verification and testing. The findings contribute to the advancement of dependable quantum technologies and support their growing applications in areas such as cryptography, materials science and other emerging domains.
Abstract Quantum computation is conventionally presented, in this book and in most of the relevant literature, as an abstract model of computation derived from the postulates of quantum mechanics as they apply to closed quantum systems. This approach, however, misses one crucial factor: real computational devices are open quantum systems exposed to environmental effects. These environmental effects lead to deviations in the quantum state from that predicted by the postulates of quantum mechanics, which, in turn, means that the ‘correct’ outcome of a quantum computation (when performed on real quantum hardware) may only occur with a certain probability. The remedy for this is quantum error correction, the subject matter of this chapter.
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.