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Showing 1 to 5 of 5 for “"one-dimensional hydrogen"”.

  1. One-dimensional hydrogen atom

    The photoionization spectrum of highly excited hydrogen atoms in the energy range between E = 0 and E = E$\sb{\rm c}$ ionization thresholds is examined in the presence of a strong dc electric field. Atomic hydrogen is excited from the ground state via a three-photon process to high-lying excited …

    uiuc Repository record for One-dimensional hydrogen atom (opens in a new tab)

  2. One-dimensional hydrogen atom

    The photoionization spectrum of highly excited hydrogen atoms in the energy range between E = 0 and E = Ec ionization thresholds is examined in the presence of a strong de electric field. Atomic hydrogen is excited from the ground state via a three-photon process to high-lying excited states. …

    uiuc Repository record for One-dimensional hydrogen atom (opens in a new tab)

  3. Chaos effects in one-dimensional hydrogen, including the high frequency regime

    The system of highly excited hydrogen in combined strong ac and de electric fields is examined. It is shown that the production and maintainence of effectively one-dimensional states is plausible in this system. The threshold of global classical chaos is calculated using the resonance overlap …

    uiuc Repository record for Chaos effects in one-dimensional hydrogen, including the high frequency regime (opens in a new tab)

  4. Chaos effects in one-dimensional hydrogen, including the high-frequency regime

    The system of highly excited hydrogen in combined strong ac and dc electric fields is examined. It is shown that the production and maintainence of effectively one-dimensional states is plausible in this system. The threshold of global classical chaos is calculated using the resonance overlap …

    uiuc Repository record for Chaos effects in one-dimensional hydrogen, including the high-frequency regime (opens in a new tab)

  5. Acceleration of combustion computation fluid dynamics simulations through machine learning

    … simulations through Deep Operator Networks (DeepONets), achieving up to an 18 times speedup in the chemical source term evaluation. Another numerical experiment showed an overall reduction of approximately 30% in computation time. This was achieved by directly replacing the ODE solver for …

    uiuc Repository record for Acceleration of combustion computation fluid dynamics simulations through machine learning (opens in a new tab)