SearcharxivSearch

arXiv · 1906.05941

Kinetic energy functionals and the $N$-representability of the electron pair-density given by the classical map hyper-netted-chain (CHNC) method

Abstract

The classical map hypernetted-chain (CHNC) method for interacting electrons uses a kinetic energy functional in the form of a classical-fluid temperature. Here we show that the CHNC generated two-body densities and pair-distribution functions (PDFs) correspond to $N$-representable densities. Comparisons of results from CHNC with quantum Monte Carlo (QMC) and Path Integral Monte Carlo (PIMC) are used to validate the CHNC results. Since the PDFs are sufficient to obtain the equation of state or linear-response properties of electron-ion systems, we apply the CHNC method for fully classical calculations of electron-ion systems in the quantum regime, using hydrogen at 4000K and 350 times the solid density as an example since QMC comparisons are available. We also present neutral pseudo-atom (NPA) calculations which use rigorous density-functional theory (DFT) to reduces the many nuclear problem to an effective one-ion problem. The CHNC PDFs and NPA results agree well with the ion-ion, electron-ion and electron-electron PDFs from QMC, PIMC, or DFT coupled to molecular dynamics simulations where available. The PDFs of a 2D electron-hole system at 5K are given as an example of 2D `warm dense' matter where the electrons and the counter particles (holes) are all in the quantum regime. Basic methods like QMC, PIMC or even DFT become prohibitive while CHNC methods, being independent of the number of particles or the temperature, prove to be easily deployable.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

M. W. C. Dharma-wardana. 2019-11-08. Kinetic energy functionals and the $N$-representability of the electron pair-density given by the classical map hyper-netted-chain (CHNC) method. https://doi.org/10.1103/physrevb.100.155143

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Universal sampling of spin systems across quenched disorder

Statistical physics extracts macroscopic laws by averaging over the many microscopic degrees of freedom of a system. Disordered systems demand a second and far harder average, one over the quenched randomness itself. The classic analytical routes, the replica and cavity methods, become uncontrolled outside mean-field or tree-like limits, and conventional numerical algorithms like parallel tempering require expensive, independent equilibration for every disorder realization. In this work, we introduce a universal neural variational framework that amortizes inference across the disorder ensemble, eliminating both the need for per-instance Markov chain equilibration and the cost of retraining instance-specific variational ansatzes. Built on an encoder-decoder Transformer architecture, after training once, it produces an explicit approximation to the Boltzmann distribution given previously unseen disorder realizations without further optimization. We validate this framework on 2D Edwards-Anderson models, and apply it to the random-bond Ising model, successfully capturing the Binder cumulant crossings near the Nishimori multicritical point. These results shift the object of variational inference from the single instance to the disorder ensemble, opening a route to frustrated many-body systems where instance-by-instance computation is prohibitive.

cond-mat.stat-mech

Information-Theoretic Characterization of Macroscopic Chaos Emerging from the Chemical Master Equation

Open chemical reaction networks exhibit stochastic concentration dynamics at finite system sizes, whereas their macroscopic limit is governed by deterministic rate equations that can display chaos. In this Letter, we show theoretically that a rate of information loss constructed from two-time mutual information recovers the Kolmogorov-Sinai entropy in the deterministic limit. We verify this result through numerical simulations of a Markov jump process for a three-species system involving seven reactions.

cond-mat.stat-mech

Orientational order on non-orientable domains

We study the statistical properties of passive and active many-body systems with orientational degrees of freedom on non-orientable domains. By rephrasing topological constraints as non-local symmetry relations on an orientable double-cover, we show that non-orientability eliminates global rotational soft modes without acting like an external field. In a passive XY model, this results in topological caging, where orientational fluctuations that exhibit conventional diffusive behavior on a torus saturate on a Klein bottle to a finite value that we compute exactly in the thermodynamic limit. In models of active self-propelled particles with orientational degrees of freedom, topological caging persists despite continuously changing interaction neighborhoods. In an active Ising spin model, non-orientability enforces the coexistence of ordered anti-parallel domains with vanishing global polar order, a state that is absent on orientable domains.

cond-mat.stat-mech