New density estimation methods for charged particle beams with applications to microbunching instability

In this paper we discuss representations of charge particle densities in particle-in-cell simulations, analyze the sources and profiles of the intrinsic numerical noise, and present efficient methods for their removal. We devise two alternative estimation methods for charged particle distribution which represent significant improvement over the Monte Carlo cosine expansion used in the 2D code of Bassi et al. [G. Bassi, J. A. Ellison, K. Heinemann, and R. Warnock, Phys. Rev. ST Accel. Beams 12, 080704 (2009); G. Bassi and B. Terzi\ifmmode \acute{c}\else \'{c}\fi{}, in Proceedings of the 23rd Particle Accelerator Conference, Vancouver, Canada, 2009 (IEEE, Piscataway, NJ, 2009), TH5PFP043], designed to simulate coherent synchrotron radiation (CSR) in charged particle beams. The improvement is achieved by employing an alternative beam density estimation to the Monte Carlo cosine expansion. The representation is first binned onto a finite grid, after which two grid-based methods are employed to approximate particle distributions: (i) truncated fast cosine transform; and (ii) thresholded wavelet transform (TWT). We demonstrate that these alternative methods represent a staggering upgrade over the original Monte Carlo cosine expansion in terms of efficiency, while the TWT approximation also provides an appreciable improvement in accuracy. The improvement in accuracy comes from a judicious removal of the numerical noise enabled by the wavelet formulation. The TWT method is then integrated into the CSR code [G. Bassi, J. A. Ellison, K. Heinemann, and R. Warnock, Phys. Rev. ST Accel. Beams 12, 080704 (2009)], and benchmarked against the original version. We show that the new density estimation method provides a superior performance in terms of efficiency and spatial resolution, thus enabling high-fidelity simulations of CSR effects, including microbunching instability.

[1]  Transformation of phase space densities under the coordinate changes of accelerator physics , 2010 .

[2]  M. Victor Wickerhauser,et al.  Adapted wavelet analysis from theory to software , 1994 .

[3]  Courtlandt L. Bohn,et al.  Particle-in-cell beam dynamics simulations with a wavelet-based Poisson solver , 2007 .

[4]  Rui Li SELF-CONSISTENT SIMULATION OF THE CSR EFFECT ON BEAM EMITTANCE , 1999 .

[5]  Ronald R. Coifman,et al.  Entropy-based algorithms for best basis selection , 1992, IEEE Trans. Inf. Theory.

[6]  Alessandro B. Romeo,et al.  N-body simulations with two-orders-of-magnitude higher performance using wavelets , 2003 .

[7]  J. Rosenzweig,et al.  The Physics of High Brightness Beams , 2000 .

[8]  Samuel Krinsky,et al.  Coherent synchrotron radiation instability in a bunch compressor , 2002 .

[9]  Ronald R. Coifman,et al.  In Wavelets and Statistics , 1995 .

[10]  M. Borland Modeling of the microbunching instability , 2008 .

[11]  Michael Borland,et al.  Start-to-end simulation of self-amplified spontaneous emission free electron lasers from the gun through the undulator , 2002 .

[12]  Michael Borland,et al.  Suppression of microbunching instability in the linac coherent light source , 2004 .

[13]  J. Ellison,et al.  Microbunching instability in a chicane: Two-dimensional mean field treatment , 2009 .

[14]  C. Limborg-Deprey,et al.  Measurements and modeling of coherent synchrotron radiation and its impact on the Linac Coherent Light Source electron beam , 2009 .

[15]  Kwang-Je Kim,et al.  Formulas for coherent synchrotron radiation microbunching in a bunch compressor chicane , 2002 .

[16]  Mikhail Yurkov,et al.  On the coherent radiation of an electron bunch moving in an arc of a circle , 1997 .

[17]  F. J. Anscombe,et al.  THE TRANSFORMATION OF POISSON, BINOMIAL AND NEGATIVE-BINOMIAL DATA , 1948 .

[18]  Jean-Michel Poggi,et al.  Wavelets and their applications , 2007 .

[19]  S. Goedecker Wavelets and Their Application: For the Solution of Partial Differential Equations in Physics , 1998 .

[20]  Lianfen Qian,et al.  Nonparametric Curve Estimation: Methods, Theory, and Applications , 1999, Technometrics.

[21]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[22]  S. Mallat A wavelet tour of signal processing , 1998 .

[23]  Praveen Kumar,et al.  Wavelets in Geophysics , 1994 .

[24]  I. Johnstone,et al.  Ideal spatial adaptation by wavelet shrinkage , 1994 .