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Questions and answers categorized in: Artificial Intelligence > EITC/AI/TFQML TensorFlow Quantum Machine Learning > Quantum supremacy

What was the exact problem solved in the quantum supremacy achievement?

Wednesday, 11 June 2025 by Mirek Hermut

Quantum supremacy is a milestone that refers to an experimental demonstration where a programmable quantum processor performs a well-defined computational task in a time that is infeasible for any known classical computer. The experiment reported by Google in 2019, carried out on the 53-qubit superconducting processor named “Sycamore”, is the first accepted demonstration of that

  • Published in Artificial Intelligence, EITC/AI/TFQML TensorFlow Quantum Machine Learning, Quantum supremacy, Quantum supremacy explained
Tagged under: Artificial Intelligence, Computational Complexity, Cross-Entropy Benchmarking, Quantum Computing, Random Circuit Sampling, Superconducting Qubits

What are the consequences of the quantum supremacy achievement?

Friday, 28 June 2024 by Mirek Hermut

The achievement of quantum supremacy represents a pivotal milestone in the field of quantum computing, heralding a new era of computational capabilities that surpass those of classical computers for specific tasks. This breakthrough has profound implications across various domains, including artificial intelligence (AI), cryptography, materials science, and more. To fully appreciate the consequences of quantum

  • Published in Artificial Intelligence, EITC/AI/TFQML TensorFlow Quantum Machine Learning, Quantum supremacy, Quantum supremacy explained
Tagged under: Artificial Intelligence, Cryptography, Materials Science, Quantum Algorithms, Quantum Computing, Quantum Machine Learning

How does bootstrapping help verify the statistical uncertainty of the fidelity estimate in the context of the quantum supremacy experiment?

Tuesday, 11 June 2024 by EITCA Academy

In the context of the quantum supremacy experiment, bootstrapping is a powerful statistical technique used to estimate the uncertainty of the fidelity measure, which is important for validating the experiment's results. Quantum supremacy refers to the point at which a quantum computer can perform a calculation that is infeasible for classical computers to execute in

  • Published in Artificial Intelligence, EITC/AI/TFQML TensorFlow Quantum Machine Learning, Quantum supremacy, Estimation of statistical significance of quantum supremacy, Examination review
Tagged under: Artificial Intelligence, Bootstrapping, Confidence Intervals, Fidelity, Quantum Algorithms, Quantum Computing, Statistical Uncertainty

What role does the Kolmogorov-Smirnov (K-S) test play in assessing the accuracy of the fidelity estimation in the quantum supremacy experiment?

Tuesday, 11 June 2024 by EITCA Academy

The Kolmogorov-Smirnov (K-S) test plays a important role in assessing the accuracy of fidelity estimation in quantum supremacy experiments. Quantum supremacy refers to the point at which a quantum computer can perform a computation that is infeasible for any classical computer within a reasonable timeframe. Fidelity estimation is a measure of how closely the output

  • Published in Artificial Intelligence, EITC/AI/TFQML TensorFlow Quantum Machine Learning, Quantum supremacy, Estimation of statistical significance of quantum supremacy, Examination review
Tagged under: Artificial Intelligence, Fidelity Estimation, Kolmogorov-Smirnov Test, Quantum Algorithms, Quantum Computing, Statistical Significance

How does the Porter-Thomas distribution relate to the sampling strategies used in the quantum supremacy experiment?

Tuesday, 11 June 2024 by EITCA Academy

The Porter-Thomas distribution plays a significant role in the context of quantum supremacy experiments, particularly concerning the sampling strategies employed to demonstrate the computational advantage of quantum devices over classical counterparts. Understanding this relationship requires a detailed exploration of the Porter-Thomas distribution itself, the nature of quantum supremacy experiments, and the statistical methodologies used to

  • Published in Artificial Intelligence, EITC/AI/TFQML TensorFlow Quantum Machine Learning, Quantum supremacy, Estimation of statistical significance of quantum supremacy, Examination review
Tagged under: Artificial Intelligence, Cross-Entropy Difference, Porter-Thomas Distribution, Quantum Computing, Random Circuit Sampling, Statistical Significance

What is the significance level ( alpha ) commonly used for major scientific claims, and how does it relate to the concept of sigma in Gaussian distributions?

Tuesday, 11 June 2024 by EITCA Academy

The significance level, denoted as , is a critical concept in statistical hypothesis testing, often employed in the context of validating major scientific claims. In the realm of quantum computing and specifically quantum supremacy, the significance level plays a pivotal role in determining the robustness and credibility of experimental results. The value of commonly used

  • Published in Artificial Intelligence, EITC/AI/TFQML TensorFlow Quantum Machine Learning, Quantum supremacy, Estimation of statistical significance of quantum supremacy, Examination review
Tagged under: Artificial Intelligence, Gaussian Distribution, Hypothesis Testing, P-value, Quantum Computing, Statistical Significance

How is the null hypothesis ( H_0 ) defined in the context of the quantum supremacy experiment conducted with Google's Sycamore processor?

Tuesday, 11 June 2024 by EITCA Academy

The null hypothesis in the context of the quantum supremacy experiment conducted with Google's Sycamore processor is a fundamental concept that serves as a baseline for evaluating the performance and significance of the quantum processor compared to classical computational methods. Quantum supremacy refers to the point at which a quantum computer can perform a calculation

  • Published in Artificial Intelligence, EITC/AI/TFQML TensorFlow Quantum Machine Learning, Quantum supremacy, Estimation of statistical significance of quantum supremacy, Examination review
Tagged under: Artificial Intelligence, CrossEntropyBenchmarking, Google'sSycamore, HypothesisTesting, QuantumComputing, StatisticalSignificance

What are the challenges and advantages of using speckle purity benchmarking compared to traditional quantum state tomography for assessing the coherence of quantum states?

Tuesday, 11 June 2024 by EITCA Academy

The assessment of the coherence of quantum states is a pivotal task in quantum information science, particularly in the context of quantum computing and quantum supremacy experiments. Traditional quantum state tomography (QST) has long been the standard method for this purpose. However, speckle purity benchmarking (SPB) has emerged as a promising alternative. Both techniques have

  • Published in Artificial Intelligence, EITC/AI/TFQML TensorFlow Quantum Machine Learning, Quantum supremacy, Extracting coherence information from random circuits, Examination review
Tagged under: Artificial Intelligence, Quantum Coherence, Quantum Computing, Quantum Information Science, Quantum State Tomography, Speckle Purity Benchmarking

How is the purity of a quantum state mathematically represented and experimentally measured in the context of quantum machine learning?

Tuesday, 11 June 2024 by EITCA Academy

The purity of a quantum state is a important concept in quantum mechanics and quantum information theory, representing how mixed or pure a quantum system is. Mathematically, the purity of a quantum state is defined using the density matrix formalism. For a given quantum state represented by a density matrix , the purity is given

  • Published in Artificial Intelligence, EITC/AI/TFQML TensorFlow Quantum Machine Learning, Quantum supremacy, Extracting coherence information from random circuits, Examination review
Tagged under: Artificial Intelligence, Quantum Coherence, Quantum Information Theory, Quantum Mechanics, Quantum State Tomography, TensorFlow Quantum

What role does the Porter-Thomas distribution play in the analysis of quantum circuits using cross-entropy benchmarking (XEB)?

Tuesday, 11 June 2024 by EITCA Academy

The Porter-Thomas distribution plays a important role in the analysis of quantum circuits using cross-entropy benchmarking (XEB), particularly in the context of quantum supremacy and the extraction of coherence information from random circuits. To understand this role comprehensively, it is essential to consider several foundational concepts, including the nature of random quantum circuits, the principles

  • Published in Artificial Intelligence, EITC/AI/TFQML TensorFlow Quantum Machine Learning, Quantum supremacy, Extracting coherence information from random circuits, Examination review
Tagged under: Artificial Intelligence, Cross-Entropy Benchmarking, Porter-Thomas Distribution, Quantum Circuits, Quantum Coherence, Quantum Computing
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