SUSY in Silico: numerical D-brane bound state spectroscopy
Abstract
We numerically construct the BPS and non-BPS wavefunctions of an $\mathcal{N}=4$ quiver quantum mechanics with two Abelian nodes and a single arrow. This model captures the dynamics of a pair of wrapped D-branes interacting via a single light string mode. A dimensionless parameter $ν$, which is inversely proportional to the Fayet-Iliopoulos parameter, controls whether the bulk of the wavefunctions are supported on the Higgs branch or the Coulomb branch. We demonstrate how the BPS and excited states morph as $ν$ is tuned. We also numerically compute the energy gap between the ground state and the first excited states as a function of $ν$. An expression for the gap, computed on the Coulomb branch, matches nicely with our numerics at large $ν$ but deviates at small $ν$ where the Higgs branch becomes the relevant description of the physics. In the appendix, we provide the Schrödinger equations fully reduced via symmetries which, in principle, allow for the numerical determination of the entire spectrum at any point in moduli space. For the ground states, this numerical determination of the spectrum can be thought of as the first \emph{in silico} check of various Witten index calculations.
How strong is the evidence?
Evidence Hub reads this as a simulation / modelling, done in computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
Read the paper
Related studies
- Quantum dots: synthesis, bioapplications, and toxicity
- A Guide to In Silico Drug Design
- Quantum Computing for Healthcare: A Review
- Automated in Silico Design of Homogeneous Catalysts
- Identification of Novel 3-Hydroxy-pyran-4-One Derivatives as Potent HIV-1 Integrase Inhibitors Using in silico Structure-Based Combinatorial Library Design Approach
- In silico structural elucidation of RNA-dependent RNA polymerase towards the identification of potential Crimean-Congo Hemorrhagic Fever Virus inhibitors
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.