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1. Decomposition and embedding in the stochastic GW self-energy

   https://doi.org/10.1063/5.0020430  

   Romanova, Mariya; Vlček, Vojtěch (October 2020, The Journal of Chemical Physics)

   null (Ed.)
2. Full-frequency GW without frequency

   https://doi.org/10.1063/5.0035141  

   Bintrim, Sylvia J.; Berkelbach, Timothy C. (January 2021, The Journal of Chemical Physics)

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3. KHI Tube & Knot Dynamics in a Weakly Unstable Stratospheric Mixing Event

   https://doi.org/10.1029/2024JD041981  

   Mixa, Tyler S; Fritts, David C; Lund, Thomas S (May 2025, Journal of geophysical research Atmospheres)

   Abstract Kelvin‐Helmholtz Instabilities (KHI) are known to be significant drivers of atmospheric turbulence. Recent observations show KHI forming with misaligned or angled billow segments that develop connecting vortex tubes and knots (T&K); these features promote distinctive, event‐defining instability and mixing characteristics that were not accounted for in prior idealized studies. Though T&K have been shown to increase mixing in KHI events with low Richardson numbers (Ri), their influence in weakly KH‐unstable, less‐idealized environments is unknown. Here we present modeling results of KHI in the stratosphere to assess the impact of T&K dynamics in weakly KH‐unstable environments. Radiosonde wind and temperature profiles from 22 February 2006 near Lamont, Oklahoma, measured vertically offset shear and stability peaks near 16.2 km with a minimum Ri = 0.11. Direct numerical simulations (DNS) of this event reveal decreasing shear and increasing stratification, where Ri increases to 0.2 as the shear and stratification peaks move to a common altitude. The resulting KHI exhibit T&K features forming adjacent to, and in superposition with, secondary convective instabilities (CI) rather than superseding them as in prior T&K studies with Ri = 0.05. Newly discovered “crankshaft” instabilities distort the billows and give rise to secondary KHI with delayed, elevated dissipation. KHI that exhibit T&K dynamics are found to accumulate % greater mixing than axially uniform KHI with equal or lower mixing efficiency. The substantial increase in mixing suggests significant contributions of T&K dynamics to KHI events throughout the atmosphere that remain unaddressed in general circulation models' turbulence parameterizations. 

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4. GW/PT Descendent Correspondence via Vertex Operators

   https://doi.org/10.1007/s00220-020-03686-4  

   Oblomkov, A.; Okounkov, A.; Pandharipande, R. (March 2020, Communications in Mathematical Physics)
5. Predicting the excited-state properties of crystalline organic semiconductors using GW+BSE and machine learning

   https://doi.org/10.1039/D4DD00396A  

   Gao, Siyu; Luo, Yiqun; Liu, Xingyu; Marom, Noa (May 2025, Digital Discovery)

   Excited-state properties of crystalline organic semiconductors are key to organic electronic device applications. Machine learning (ML) models capable of predicting these properties could significantly accelerate materials discovery. We use the sure-independence-screening-and-sparsifying-operator (SISSO) ML algorithm to generate models to predict the first singlet excitation energy, which corresponds to the optical gap, the first triplet excitation energy, the singlet–triplet gap, and the singlet exciton binding energy of organic molecular crystals. To train the models we use the “PAH101” dataset of many-body perturbation theory calculations within the GW approximation and Bethe–Salpeter equation (GW+BSE) for 101 crystals of polycyclic aromatic hydrocarbons (PAHs). The best performing SISSO models yield predictions within about 0.2 eV of the GW+BSE reference values. SISSO models are selected based on considerations of accuracy and computational cost to construct materials screening workflows for each property. The screening targets are chosen to demonstrate typical use-cases relevant for organic electronic devices. We show that the workflows based on SISSO models can effectively screen out most of the materials that are not of interest and significantly reduce the number of candidates selected for further evaluation using computationally expensive excited-state theory. 

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