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SUMMARY:SR micro-XRF installation on VEPP-3 storage ring. An approach and 
 difficulties in increasing the spatial resolution.
DTSTART;VALUE=DATE-TIME:20160705T090000Z
DTEND;VALUE=DATE-TIME:20160705T100000Z
DTSTAMP;VALUE=DATE-TIME:20260520T035711Z
UID:indico-contribution-1309@indico.inp.nsk.su
DESCRIPTION:Speakers: Dmitry Sorokoletov (Budker Institute of Nuclear Phys
 ics SB RAS)\nX-ray fluorescence microanalysis on synchrotron radiation bea
 ms (SR micro-XRF) is a method to explore the elemental composition of samp
 les and objects of various nature with a typical spatial resolution of 15 
 to 25 μm. Such resolution\, available in qualitative micro-XRF (mapping o
 f fluorescent signal distribution or exploration of area of interest witho
 ut detailed consideration of effects caused by absorption by a sample) is 
 defined by the transverse size of the focal spot of  x-ray optics used. As
  a rule\, up-to-date (monolithic) polycapillary lenses are applied. This q
 ualitative elemental mapping in some cases can provide useful information.
  It can be in demand\, for example\, in reconstruction of paleoclimate (la
 yered samples of bottom sediments\, so called varves) and conditions of ro
 ck formation in deposit occurrences\, as well as in examination  of biolog
 ical objects (hair and large cells)\, particles of earth and meteorite dus
 t and some other objects [1-2].\n\nThe SR XRF experimental station on the 
 VEPP-3 storage ring (the SCSTR) [3] is equipped with the installation "SR 
 micro-XRF"\, which is intensely used by a number of users in most of these
  areas of research. The installation was engaged in an extensive series of
  experiments [3] using qualitative SR micro-XRF\; unique results were obta
 ined in several cases. Two directions of improving the method and installa
 tion were selected so far. The first one is development of certified techn
 iques of (semi-) quantitative XRF\, and the second one is 1.5-2 time impro
 vement of the spatial resolution due to application of complicated algorit
 hms to process experimental data (so called regularization)\, including em
 bedded indirect accuracy control.\n\nRegularization is a method of approxi
 mate solution to unstable inverse problems. It is based on certain control
 led introduction of systematic error into the result. This error is introd
 uced so that its contribution optimally balances [4\, p. 52-55] the influe
 nce of random noise\, because of which the problem cannot be accurately so
 lved by traditional methods. Development of any regularization algorithms 
 implies analysis of feasibility of the above rule (in other words\, the co
 nvergence of the approximate solution) over the entire range of all input 
 parameters. The algorithm user is assumed to know the rules for use of one
  or another regularizing procedure (that may expect\, for example\, normal
  distribution of noise\, absence of systematic errors\, special prior cons
 traints to the solution\, and others) and adhere to them. Unfortunately\, 
 this is not always the case\, and application of regularization of algorit
 hms is often blind and inefficient\, especially when third-party programs 
 are used.\n\nThis work presents an attempt of non-strict but effective pra
 ctical analysis of the influence of various factors "hindering" the regula
 rization (inaccuracy in the determination of the instrumental function\, d
 iscretization errors\, Gibbs boundary effects etc.) on the process of solv
 ing inverse deconvolution problems arising in SR micro-XRF using the Tikho
 nov algorithm [4\, p. 52]. The analysis performed resulted in practical re
 commendations on the optimal regimes of experiment with improved spatial r
 esolution and highlighted the role of numerical simulation in the control 
 of solving real inverse deconvolution problems.\n\nThis work was supported
  by the RFBR Grants № 14-02-00631\, 16-32-00705. The work by D.S. Soroko
 letov was supported by a scholarship of the President of the Russian Feder
 ation (SP-2761.2016.2).\n\nReferences\n\n[1] S. Majumdara\,  J. R. Peralta
 -Videaa\, H. Castillo-Michel et al. Analytica Chimica Acta. 2012. № 755.
  1–16.\n\n[2] B. Menez\, H. Bureau et al. Modern Research and Educationa
 l Topics in Microscopy. 2008. Vol. 2. 976-988.\n\n[3] http://ssrc.inp.nsk.
 su/CKP/stations/passport/3/\n\n[4] S.I. Kabanikhin. Inverse and incorrect 
 problems (in Russian). Novosibirsk\, Siberian scientific publishing house.
  2009. 457 p.\n\nhttps://indico.inp.nsk.su/event/3/contributions/1309/
LOCATION:Budker INP 2nd and 3rd floors
URL:https://indico.inp.nsk.su/event/3/contributions/1309/
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