In this workshop, the reader can practice with finding the eigenstate of a Hamiltonian, studying the dynamics of isolated spin states, deriving the density operator and its associated density matrix and calculating the dynamics of an ensemble of spin-1/2 systems.
In many cases, measurements are performed on “mixed” ensembles of realizations of a system, which cannot be associated with a single vector in its Hilbert space. In these cases the state of the system is represented by a proper “density operator.” It is instructive to associate density operators with state vectors in a vector space, termed Liouville’s space, where the Schrödinger equation is reformulated as the Liouville–Von Neumann equation. An important consequence of this equation is that the density operator of a system at equilibrium must commute with its Hamiltonian. Namely, the matrix representation of the density operator in the basis of Hamiltonian eigenstates is diagonal, where the diagonal elements are the relative populations of the system’s Hamiltonian eigenstates. The equilibrium populations are revealed by maximizing the (Von Neumann) entropy, subject to given constraints. We derive the equilibrium density operator explicitly for the cases of canonical and grand canonical ensembles.
In this lecture, I lay down the basics for the study of the dynamics of a large collection of identical spin systems by introducing the concept of a density operator and an equation for its evolution. Ensembles of spin systems represent macroscopic samples; in quantum mechanics, these can only be described in statistical terms through a density operator. This latter can be expressed in terms of spin angular momentum operators. The density operator allows all measurable properties of an ensemble of spin systems to be determined.
Model Hamiltonians represent a convenient way of reducing complex problems of many-electron quantum mechanics to much simpler problems: they can fully reproduce the core behaviors of a system of interest by encoding only the dominant physical interactions and using only a small number of associated parameters. Model Hamiltonians have been successfully applied to describe many chemical and physical phenomena. Density Matrix Downfolding (DMD) [J. Chem. Phys. 2015, 143 (10), 102814] allows the derivation of model Hamiltonians, of any form, in a systematically improvable fashion, by matching the energy spectrum of ab initio Hamiltonians with those of the model Hamiltonians. This method allows not only the improvement of existing models but also the construction of accurate and efficient physical models for various systems. While DMD looks like a promising approach, it has rarely been applied within chemistry, and neither its limits nor practical performance are well understood. In this work we evaluated the performance of DMD, based on non-eigenstates of ab initio Hamiltonians, for several realistic chemical systems: benzene, naphthalene, FeSe, and a prototypical Fe(IV)=O complex found in the active sites of 2-oxoglutarate-dependent oxygenases. Our results show that DMD is a reliable and computationally efficient tool for obtaining optimized model Hamiltonians in quantum chemistry. This not only opens the door to studying complex systems at reduced computational cost but also to isolating and understanding the physical core principles that dominate their behavior — this might offer new insights for tuning, or even designing, chemical systems for applications ranging from biochemistry to catalysis.