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

• URL: http://arxiv.org/abs/2207.13585v1
• Date: Wed, 27 Jul 2022 15:32:30 GMT
• Title: Error-analysis for the Sorkin and Peres tests performed on a quantum computer
• Authors: Simanraj Sadana, Lorenzo Maccone, Urbasi Sinha
• Abstract summary: We use quantum computers to test the foundations of quantum mechanics through quantum algorithms. We show how the algorithms can be used to test the efficacy of a quantum computer in obeying the postulates of quantum mechanics.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

Related papers

• Experimental measurement and a physical interpretation of quantum shadow enumerators [2.2625632663936095]
  We develop a rigorous framework for the direct measurement of quantum weight enumerators. We experimentally demonstrate the possibility of directly measuring weight enumerators on a trapped-ion quantum computer.
  arXiv  Detail & Related papers  (2024-08-29T21:25:56Z)
• The curse of random quantum data [62.24825255497622]
  We quantify the performances of quantum machine learning in the landscape of quantum data. We find that the training efficiency and generalization capabilities in quantum machine learning will be exponentially suppressed with the increase in qubits. Our findings apply to both the quantum kernel method and the large-width limit of quantum neural networks.
  arXiv  Detail & Related papers  (2024-08-19T12:18:07Z)
• Understanding and mitigating noise in molecular quantum linear response for spectroscopic properties on quantum computers [0.0]
  We present a study of quantum linear response theory obtaining spectroscopic properties on simulated fault-tolerant quantum computers. This work introduces novel metrics to analyze and predict the origins of noise in the quantum algorithm. We highlight the significant impact of Pauli saving in reducing measurement costs and noise.
  arXiv  Detail & Related papers  (2024-08-17T23:46:17Z)
• Quantum data learning for quantum simulations in high-energy physics [55.41644538483948]
  We explore the applicability of quantum-data learning to practical problems in high-energy physics. We make use of ansatz based on quantum convolutional neural networks and numerically show that it is capable of recognizing quantum phases of ground states. The observation of non-trivial learning properties demonstrated in these benchmarks will motivate further exploration of the quantum-data learning architecture in high-energy physics.
  arXiv  Detail & Related papers  (2023-06-29T18:00:01Z)
• Quantum Machine Learning: from physics to software engineering [58.720142291102135]
  We show how classical machine learning approach can help improve the facilities of quantum computers. We discuss how quantum algorithms and quantum computers may be useful for solving classical machine learning tasks.
  arXiv  Detail & Related papers  (2023-01-04T23:37:45Z)
• Quantum computers to test fundamental physics or viceversa [0.0]
  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. On the other hand, noisy intermediate-scale quantum (NISQ) devices can be benchmarked using these same tests.
  arXiv  Detail & Related papers  (2021-11-03T11:10:59Z)
• Characterizing quantum instruments: from non-demolition measurements to quantum error correction [48.43720700248091]
  In quantum information processing quantum operations are often processed alongside measurements which result in classical data. Non-unitary dynamical processes can take place on the system, for which common quantum channel descriptions fail to describe the time evolution. Quantum measurements are correctly treated by means of so-called quantum instruments capturing both classical outputs and post-measurement quantum states.
  arXiv  Detail & Related papers  (2021-10-13T18:00:13Z)
• Test of Quantumness with Small-Depth Quantum Circuits [1.90365714903665]
  Recently, we have shown how to construct a test of quantumness based on the learning with errors (LWE) assumption. This test has lead to several cryptographic applications. In this paper, we show that this test of quantumness, and essentially all the above applications, can actually be implemented by a very weak class of quantum circuits.
  arXiv  Detail & Related papers  (2021-05-12T08:16:20Z)
• Towards understanding the power of quantum kernels in the NISQ era [79.8341515283403]
  We show that the advantage of quantum kernels is vanished for large size datasets, few number of measurements, and large system noise. Our work provides theoretical guidance of exploring advanced quantum kernels to attain quantum advantages on NISQ devices.
  arXiv  Detail & Related papers  (2021-03-31T02:41:36Z)
• Post-Hartree-Fock method in Quantum Chemistry for Quantum Computer [0.0]
  Quantum computational chemistry is a potential application of quantum computers. Quantum algorithms, quantum phase estimation, and variational quantum eigensolver have been applied to the post-Hartree-Fock method.
  arXiv  Detail & Related papers  (2020-11-03T07:46:13Z)
• An Application of Quantum Annealing Computing to Seismic Inversion [55.41644538483948]
  We apply a quantum algorithm to a D-Wave quantum annealer to solve a small scale seismic inversions problem. The accuracy achieved by the quantum computer is at least as good as that of the classical computer.
  arXiv  Detail & Related papers  (2020-05-06T14:18:44Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.