Analytic continuation works as a regularization method in physics
the verdict
SUPPORTED
the evidence backs this
confidence 81/100
Analytic continuation is widely used in computational and quantum physics to extract real-frequency dynamical properties from imaginary-time simulations, and because this inverse problem is notoriously ill-posed, regularization methods are required to stabilize the solutions.
Evidence for · 5
PyLIT: Reformulation and implementation of the analytic continuation problem using kernel representation methods
2025 · cited by 9
The paper discusses using regularization techniques such as Bayesian priors and entropic regularizers to solve the ill-conditioned analytic continuation problem in quantum many-body simulations.
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More for · 4
A fractional Landweber iterative regularization method for stable analytic continuation
2021 · cited by 7
The study introduces a fractional Landweber iterative regularization method specifically designed to achieve stable numerical analytic continuation.
A Posteriori Fractional Tikhonov Regularization Method for the Problem of Analytic Continuation
2021 · cited by 4
The paper proposes a fractional Tikhonov regularization method to overcome the ill-posedness of the numerical analytic continuation problem in physics.
Connecting Tikhonov regularization to the maximum entropy method for the analytic continuation of quantum Monte Carlo data
2022 · cited by 3
The paper explores Tikhonov regularization under the discrepancy principle as a reliable method for the analytic continuation of quantum Monte Carlo data.
Parameter-free analytic continuation for quantum many-body calculations
2022 · cited by 3
The research develops a parameter-free analytic continuation method using kernel grids and roughness penalty regularization for quantum calculations.