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Debating the Reliability and Robustness of the Learned Hamiltonian in the Traversable Wormhole Experiment

Weinstein, Galina (2023) Debating the Reliability and Robustness of the Learned Hamiltonian in the Traversable Wormhole Experiment. [Preprint]

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Abstract

The paper discusses Daniel Jafferis et al.'s "Nature" publication on "Traversable wormhole dynamics on a quantum processor." The experiment utilized Google's Sycamore quantum processor to simulate a sparse SYK model with a learned Hamiltonian. A debate ensued when Bryce Kobrin, Thomas Schuster, and Norman Yao raised concerns about the learned Hamiltonian's reliability, which Jafferis and the team addressed. Recently, there has been an update in the wormhole experiment saga. In an attempt to rescue the commuting Hamiltonian from its inevitable fate of being invalidated, a recent paper by Ping Gao proposed a creative solution to reinvigorate the concept within the context of teleportation through wormholes. This paper delves into the ongoing debate and the recent endeavor to address the comments made by Kobrin et al. I remain skeptical about the efforts to address Kobrin et al.'s challenges. By its nature, a commuting Hamiltonian does not exhibit chaotic behavior like non-commuting Hamiltonians. Moreover, it's always essential to assess the sensitivity of the Hamiltonian to noise to understand its practical feasibility for the real-world Sycamore processor.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Weinstein, Galinagaliweinstein.mc2@gmail.com
Keywords: quantum gravity, AdS/CFT, wormhole, quantum computer, Sycamore processor, machine learning, reliability, quantum chaos, scrambling, teleportation, thermofield double formalism, entanglement,
Subjects: Specific Sciences > Computer Science
General Issues > Computer Simulation
General Issues > Experimentation
General Issues > Models and Idealization
Specific Sciences > Physics > Quantum Gravity
Specific Sciences > Physics > Quantum Mechanics
General Issues > Realism/Anti-realism
Specific Sciences > Physics > Statistical Mechanics/Thermodynamics
General Issues > Technology
Depositing User: Dr. Galina Weinstein
Date Deposited: 03 Aug 2023 14:21
Last Modified: 03 Aug 2023 14:21
Item ID: 22365
Official URL: http://arxiv.org/abs/2308.00697
Subjects: Specific Sciences > Computer Science
General Issues > Computer Simulation
General Issues > Experimentation
General Issues > Models and Idealization
Specific Sciences > Physics > Quantum Gravity
Specific Sciences > Physics > Quantum Mechanics
General Issues > Realism/Anti-realism
Specific Sciences > Physics > Statistical Mechanics/Thermodynamics
General Issues > Technology
Date: 1 August 2023
URI: https://philsci-archive-dev.library.pitt.edu/id/eprint/22365

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