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Schrödinger Journal of Physics Education

A Computational Revisit of the Variational Principle: Estimating Ground State Energies of the 1D Harmonic Oscillator via Python

Bikash Kumar Naik

Published Jun 5, 2025• 0 citations
Publisher

Abstract

Purpose of the study:To estimate the ground state energy of the one-dimensional harmonic oscillator using the variational principle and Python-based numerical methods. Methodology:Python 3.11 was used with NumPy, SciPy, and Matplotlib libraries. The variational method was applied using multiple trial wavefunctions. Integrals were computed via Simpson’s rule, and optimization was done through parameter scanning. Main Findings:The Gaussian trial wavefunction produced a ground state energy of 0.5003 ℏω, showing 0.06% error. Other trial functions were less accurate. The results confirm that the choice of trial function critically affects the energy estimate, and Python effectively supports variational computations in quantum systems. Novelty/Originality of this study:This study integrates computational tools with the variational principle, presenting an accessible approach to energy estimation in quantum mechanics. It demonstrates how Python can facilitate variational analysis, making the method replicable and educationally useful for students and researchers.

DOI
10.37251/sjpe.v6i2.1680

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Purpose of the study:To estimate the ground state energy of the one-dimensional harmonic oscillator using the variational principle and Python-based numerical methods. Methodology:Python 3.11 was used with NumPy, SciPy, and Matplotlib libraries. The variational method was applied using multiple trial wavefunctions. Integrals were computed via Simpson’s rule, and optimization was done through parameter scanning. Main Findings:The Gaussian trial wavefunction produced a ground state energy of 0.5003 ℏω, showing 0.06% error. Other trial functions were less accurate. The results confirm that the choice of trial function critically affects the energy estimate, and Python effectively supports variational computations in quantum systems. Novelty/Originality of this study:This study integrates computational tools with the variational principle, presenting an accessible approach to energy estimation in quantum mechanics. It demonstrates how Python can facilitate variational analysis, making the method replicable and educationally useful for students and researchers.
Variational calculations play an important role in quantum mechanics, particularly in determining the ground-state energy of physical systems. Didactic examples in which one can see how the exact energy and wave function are approached by using a family of trial functions are not very numerous. An example was given in a recent book [M. Moshinsky, The Harmonic Oscillator in Modern Physics: From Atoms to Quarks (Gordon and Breach, New York, 1969)] which discusses the ground state of the hydrogen atom using as trial wave function a linear combination of harmonic-oscillator states. In the present paper we carry out a similar analysis for the ground state of a particle of mass m in a three-dimensional square-well potential. We discuss not only the approach to the exact energy when we vary the frequency and the number of oscillator states but also analyze the overlap of the exact and variational wave functions and compare the exact and approximate form factors.
Variational methods in quantum mechanics are customarily presented as invaluable techniques to find approximate estimates of ground state energies. In the present paper a short catalogue of different celebrated potential distributions (both 1D and 3D), for which an exact and complete (energy and wavefunction) ground state determination can be achieved in an elementary way, is illustrated. No previous knowledge of calculus of variations is required. Rather, in all presented cases the exact energy functional minimization is achieved by using only a couple of simple mathematical tricks: 'completion of square' and integration by parts. This makes our approach particularly suitable for undergraduates. Moreover, the key role played by particle localization is emphasized through the entire analysis. This gentle introduction to the variational method could also be potentially attractive for more expert students as a possible elementary route toward a rather advanced topic on quantum mechanics: the factorization method. Such an unexpected connection is outlined in the final part of the paper.
When applying the variational method, it is demonstrated that the systematic improvements in calculating the eigen‐energies of quantum mechanical systems can be achieved by careful study of the general features of the trial wave functions. Two sets of trial wave functions were used for the harmonic oscillator potential. In the first example, it is shown, even with a crude initial guess, that accurate results will be obtained by adjusting the wave function without introducing any additional variational parameters. Even though the second example requires more algebraic manipulation, it is shown that it converges to the exact result much faster. It is suggested that these calculations be incorporated in computer algebra software packages for the teaching of quantum mechanics.
The variational principle is revisited in the context of finding the upper and lower bounds to the ground state energy. It is shown how the variational principle can be employed to find the lower bound by partitioning the Hamiltonian into several parts. We demonstrate how the variational principle can be used to find the exact ground states in some special cases. We consider the harmonic oscillator and the Ising Hamiltonian on a bipartite lattice which are familiar yet instructive examples for students.
We present a systematic study of the Rayleigh--Ritz variational method for quantum oscillators in the Segal--Bargmann space. We rigorously derive the normalizability condition ∣α∣<12|α| < \tfrac{1}{2}∣α∣<21​ for generalized Gaussian trial functions ψ(z)=eαz2+βzψ(z) = e^{αz^2 + βz}ψ(z)=eαz2+βz through convergence analysis of Gaussian integrals in the complex plane. Applications to the harmonic oscillator demonstrate exact recovery of the ground state in Segal--Bargmann space when the trial family contains the true solution. For the quartic anharmonic oscillator (H^=−12∂x2+12x2+λx4\hat{H} = -\tfrac{1}{2}\partial_x^2 + \tfrac{1}{2}x^2 + λx^4H^=−21​∂x2​+21​x2+λx4), adaptive Gaussian ansätze in position space yield a cubic stationarity equation and perturbative energy expansions beyond first order, capturing anharmonic wavefunction narrowing. In contrast, monomial trial functions (ψn(z)=znψ_n(z) = z^nψn​(z)=zn) in the Segal--Bargmann space -- while providing rigorous upper bounds En=n+12+3λ4(2n2+2n+1)E_n = n + \tfrac{1}{2} + \tfrac{3λ}{4}(2n^2 + 2n + 1)En​=n+21​+43λ​(2n2+2n+1) for excited states -- lack width adaptability and are limited to first-order accuracy for ground-state calculations. We further analyze displaced Gaussians and displaced monomials for asymmetric potentials (e.g., x3+x4x^3 + x^4x3+x4), showing that displacement parameters are essential to capture parity breaking and stabilization effects (E0≈12+3μ4−9λ24+⋯E_0 \approx \tfrac{1}{2} + \tfrac{3μ}{4} - \tfrac{9λ^2}{4} + \cdotsE0​≈21​+43μ​−49λ2​+⋯).