<p>Color centers play key roles in, e.g., solid state lighting and quantum information technology. Here, we describe an approach for predicting the optical line shapes of such emitters based on direct sampling of the underlying autocorrelation functions through molecular dynamics simulations (MD-ACF). The energy landscapes are represented by a machine-learned potential that describes both the ground and excited state landscapes through a single model, guaranteeing size-consistent predictions. We apply this methodology to the <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41524_2025_1565_Article_IEq1.gif" Format="GIF" Height="23" Rendition="HTML" Resolution="72" Type="Linedraw" Width="72" /> </InlineMediaObject> <EquationSource Format="TEX">\({({{\rm{V}}}_{{\rm{Si}}}{{\rm{V}}}_{{\rm{C}}})}_{kk}^{0}\)</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mrow> <mrow> <mo>(</mo> <mrow> <msub> <mrow> <mi mathvariant="normal">V</mi> </mrow> <mrow> <mi mathvariant="normal">Si</mi> </mrow> </msub> <msub> <mrow> <mi mathvariant="normal">V</mi> </mrow> <mrow> <mi mathvariant="normal">C</mi> </mrow> </msub> </mrow> <mo>)</mo> </mrow> </mrow> <mrow> <mi>k</mi> <mi>k</mi> </mrow> <mrow> <mn>0</mn> </mrow> </msubsup> </math></EquationSource> </InlineEquation> divacancy defect in 4H-SiC and demonstrate that at low temperatures, the present MD-ACF approach reproduces results from the traditional generating function approach. Unlike the latter, it is, however, also applicable at high temperatures as it avoids harmonic and parallel-mode approximations and can be applied to study non-crystalline materials. The MD-ACF methodology thus promises to substantially widen the range of computational predictions of the optical properties of color centers and related defects.</p>

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Optical line shapes of color centers in solids from classical autocorrelation functions

  • Christopher Linderälv,
  • Nicklas Österbacka,
  • Julia Wiktor,
  • Paul Erhart

摘要

Color centers play key roles in, e.g., solid state lighting and quantum information technology. Here, we describe an approach for predicting the optical line shapes of such emitters based on direct sampling of the underlying autocorrelation functions through molecular dynamics simulations (MD-ACF). The energy landscapes are represented by a machine-learned potential that describes both the ground and excited state landscapes through a single model, guaranteeing size-consistent predictions. We apply this methodology to the \({({{\rm{V}}}_{{\rm{Si}}}{{\rm{V}}}_{{\rm{C}}})}_{kk}^{0}\) ( V Si V C ) k k 0 divacancy defect in 4H-SiC and demonstrate that at low temperatures, the present MD-ACF approach reproduces results from the traditional generating function approach. Unlike the latter, it is, however, also applicable at high temperatures as it avoids harmonic and parallel-mode approximations and can be applied to study non-crystalline materials. The MD-ACF methodology thus promises to substantially widen the range of computational predictions of the optical properties of color centers and related defects.