Role of line search in least-squares optimization of lens design

Abstract

The Levenberg-Marquardt version of least squares, namely the damped least-squares method, is widely used in lens design optimization. Several modifications of the approach have been proposed to accelerate convergence of the optimization procedure. Recent developments in nonlinear optimization theory indicate that the basic Gauss-Newton method of least squares can play a useful role for this purpose in many practical applications. Giving a brief outline of the pertinent developments, the paper reports on the feasibility of using the basic Gauss-Newton method of least squares in practical lens design optimization when, at each iteration, a line search procedure follows the least-squares solution to determine the optimum change vector for that particular iteration stage. It is observed that incorporation of the line search procedure provides good convergence even without any damping of the least-squares procedure. Some illustrative numerical results are presented.