Active Learning Configuration Interaction for Excited-State Calculations of Polycyclic Aromatic Hydrocarbons

We present the active learning configuration interaction (ALCI) method for multiconfigurational calculations based on large active spaces. ALCI leverages the use of an active learning procedure to find important electronic configurations among the full configurational space generated within an activ...

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محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	WooSeok Jeong (3206778) (author)
مؤلفون آخرون:	Carlo Alberto Gaggioli (1402807) (author), Laura Gagliardi (1279068) (author)
منشور في:	2021
الموضوعات:	Biophysics Biochemistry Medicine Cell Biology Neuroscience Cancer Science Policy Computational Biology Astronomical and Space Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Physical Sciences not elsewhere classified traditional ci methods polycyclic aromatic hydrocarbons order perturbation theory magnitude fewer determinants experimental excitation energies 2 – 0 space wave functions space configuration interaction traditional complete active active learning procedure larger active spaces multiconfigurational calculations based alci wave functions affordable starting points 26 orbitals ), casci configuration space large active spaces active space active spaces large active 26 electrons 16 orbitals systems presented subsequent second state calculations small fraction alci leverages alci captures 3 ev 16 electrons 10 orders
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Active Learning Configuration Interaction for Excited-State Calculations of Polycyclic Aromatic Hydrocarbons

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