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Bootstrapping Simple QM Systems

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arxiv 2108.08757 v2 pith:TH7IKYJJ submitted 2021-08-19 hep-th hep-latquant-ph

classification hep-thhep-latquant-ph
keywords approachbootstrapharmoniclevelsspectrumanalyticalatombootstrapping
verification ladder T0 review T1 audit T2 compute T3 formal
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We test the bootstrap approach for determining the spectrum of one dimensional Hamiltonians, following the recent approach of Han, Hartnoll, and Kruthoff. We focus on comparing the bootstrap method data to known analytical predictions for the hydrogen atom and the harmonic oscillator. We resolve many energy levels for each, and more levels are resolved as the size of the matrices used to solve the problem increases. Using the bootstrap approach we find the spectrum of the Coulomb and harmonic potentials converge exponentially fast.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Bootstrapping periodic quantum systems

    hep-th 2025-07 conditional novelty 7.0 of 10

    A bootstrap method that includes the translation operator and uses reality conditions computes accurate Bloch-band dispersion relations for the cosine potential without positivity constraints.

  2. Euclidean-Monte-Carlo-informed ground-state preparation for quantum simulation of scalar field theory

    quant-ph 2025-06 conditional novelty 6.0 of 10

    A classical pipeline turns Euclidean Monte Carlo correlation data into a variational ansatz and an efficient quantum circuit for the (1+1)D phi^4 ground state.

  3. Large N vector models in the Hamiltonian framework

    hep-th 2025-02 conditional novelty 4.0 of 10

    A second-quantized Hamiltonian framework recovers known large N vector model results by interpreting the ground state as a Bose-Einstein condensate of species, with O(N) invariant excitations being bilocal.

  4. Real-time dynamics from convex geometry

    hep-lat 2025-02 conditional novelty 3.0 of 10

    The paper derives model-independent, tight bounds on smeared real-time correlators from Euclidean lattice data by solving a finite-dimensional convex program.

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