/Background handling - Revision history

Apostolos Vagias at 08:07, 7 April 2026

2026-04-07T08:07:52Z

← Older revision		Revision as of 08:07, 7 April 2026
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	** sample system/geometry/the observable physics.		** sample system/geometry/the observable physics.
	* Each system has to be treated in a different way.		* Each system has to be treated in a different way.
	* A survey will help identifying the necessary / common steps among the community for specific classified systems.		* A survey will help identifying the necessary / common steps among the community for specific classified systems. Potentially very helpful input for GISANS from a recent paper (Jung and Papadakis, J. Appl. Cryst. (2023). 56, 1330–1347) regarding strategy to simulate and fit GISAXS patterns.
	* In case of multiple scattering: Include McStas as standard for GISANS analysis?		* In case of multiple scattering: Include McStas as standard for GISANS analysis?

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	* how to judge if the simulation (even if fitting perfectly to the data) is the physical correct one? For the question of which parameters are influencing the cross section mostly using bayesian fitting: see papers from Josh (for reflectometry): https://journals.iucr.org/j/issues/2021/04/00/ge5096/ge5096sup1.pdf		* how to judge if the simulation (even if fitting perfectly to the data) is the physical correct one? For the question of which parameters are influencing the cross section mostly using bayesian fitting: see papers from Josh (for reflectometry): https://journals.iucr.org/j/issues/2021/04/00/ge5096/ge5096sup1.pdf
	* X-ray community:		* X-ray community:
			** Very helpful the recent work (Jung and Papadakis, J. Appl. Cryst. (2023). 56, 1330–1347) regarding strategy to simulate and fit GISAXS patterns, potentially very helpful for GISANS.
	** Grazing incidence background subtraction is very difficult already in the X-ray techniques. State of the art for X-ray techniques is looking for areas around the strong peaks. This solution is not optimal. You can’t put down the sample and so the best situation is to do the same experiment at a liquid-liquid interface with motion. Everything is in the same place, you put only the liquids in the same cell, GISAXS image with everything except the molecule which will be placed at the interface. Then make a new sample with the same position of the interface with an added molecule. The background sample has to be as close to the real sample as possible. = To have more information, not to be taken as the recipe for handling background.		** Grazing incidence background subtraction is very difficult already in the X-ray techniques. State of the art for X-ray techniques is looking for areas around the strong peaks. This solution is not optimal. You can’t put down the sample and so the best situation is to do the same experiment at a liquid-liquid interface with motion. Everything is in the same place, you put only the liquids in the same cell, GISAXS image with everything except the molecule which will be placed at the interface. Then make a new sample with the same position of the interface with an added molecule. The background sample has to be as close to the real sample as possible. = To have more information, not to be taken as the recipe for handling background.
	** Surface scattering needs to be known to disentangle it from reflection.		** Surface scattering needs to be known to disentangle it from reflection.

Annikastellhorn at 07:27, 7 April 2026

2026-04-07T07:27:30Z

← Older revision		Revision as of 07:27, 7 April 2026
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	* measure multiple states / dispersions / other observables to decrease ratio (unkown parameters)/(measured parameters)		* measure multiple states / dispersions / other observables to decrease ratio (unkown parameters)/(measured parameters)
	* how to judge if the simulation (even if fitting perfectly to the data) is the physical correct one? For the question of which parameters are influencing the cross section mostly using bayesian fitting: see papers from Josh (for reflectometry): https://journals.iucr.org/j/issues/2021/04/00/ge5096/ge5096sup1.pdf		* how to judge if the simulation (even if fitting perfectly to the data) is the physical correct one? For the question of which parameters are influencing the cross section mostly using bayesian fitting: see papers from Josh (for reflectometry): https://journals.iucr.org/j/issues/2021/04/00/ge5096/ge5096sup1.pdf
			* X-ray community:
			** Grazing incidence background subtraction is very difficult already in the X-ray techniques. State of the art for X-ray techniques is looking for areas around the strong peaks. This solution is not optimal. You can’t put down the sample and so the best situation is to do the same experiment at a liquid-liquid interface with motion. Everything is in the same place, you put only the liquids in the same cell, GISAXS image with everything except the molecule which will be placed at the interface. Then make a new sample with the same position of the interface with an added molecule. The background sample has to be as close to the real sample as possible. = To have more information, not to be taken as the recipe for handling background.
			** Surface scattering needs to be known to disentangle it from reflection.
			* ToF aspects:
			** Consider also ToF Background!
			* How to acquire the Background:
			** There is no general way to acquire data, many people do empirical background subtraction because there is no way to calculate it.
			** Cut and put a polynomial under a peak without knowing what the polynomial is supposed to represent.

Annikastellhorn at 15:27, 25 March 2026

2026-03-25T15:27:08Z

← Older revision		Revision as of 15:27, 25 March 2026
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	~~Ideas for discussion were introduced with the following slides:~~
	~~[[File:Background ideas.pdf\|thumb]]~~

	Short overview from discussions/breakouts:		Short overview from discussions/breakouts:
	* Background subtraction is dependent on:		* Background subtraction is dependent on:

Apostolos Vagias at 16:22, 19 March 2026

2026-03-19T16:22:13Z

← Older revision		Revision as of 16:22, 19 March 2026
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	* measure multiple states / dispersions / other observables to decrease ratio (unkown parameters)/(measured parameters)		* measure multiple states / dispersions / other observables to decrease ratio (unkown parameters)/(measured parameters)
	* how to judge if the simulation (even if fitting perfectly to the data) is the physical correct one? For the question of which parameters are influencing the cross section mostly using bayesian fitting: see papers from Josh (for reflectometry): https://journals.iucr.org/j/issues/2021/04/00/ge5096/ge5096sup1.pdf		* how to judge if the simulation (even if fitting perfectly to the data) is the physical correct one? For the question of which parameters are influencing the cross section mostly using bayesian fitting: see papers from Josh (for reflectometry): https://journals.iucr.org/j/issues/2021/04/00/ge5096/ge5096sup1.pdf


	~~*****~~
	~~group 1~~

	~~Notes:~~
	~~Alexandros: going to a corner and measuring bkg~~

	~~Philipp: this corner you go is below/or above the horizon?~~
	~~Alexandros: below.~~

	~~Philipp: below the horizon, you have negative intensities. the corner will be different below or above the horizon.~~

	~~Alexandros: yes, because you have something that absorbs and scatters at the same time.~~

	~~Philipp: better to take it below the horizon instrument background.~~

	~~Alexandros: problem we had usually with bare substrate, we had no other way to estimate bkg.~~

	~~JF: the incoherent signal you get is not as constant in angle as you expect.~~

	~~SJ: in GISANS, closer to footprint, after 2 cm is all incoherent.~~
	~~JF: and inelastic~~
	~~SJ: instruments masuring reflectometry and GISANS, first you scan through angle (and identify critical edge).~~
	then, use this approach to get average SLD of the sample. problem with this approach would be that no SANS instrument can use this approach. put sample in, first reflectometry (get SLD) and afterwards then GISANS.



	~~intensity and wavelength~~

	~~Henrich: a SANS machine can do everything a reflectometry machine can do.~~
	~~Philipp: can cover some angular range to see total reflection.~~

	~~JF: Yes, but with poor resolution, for subtle variations of SLD this maybe not possible. we try to measure reflectivity curves when we do GISANS measurements.~~

	~~SJ: is always worth it.~~

Annikastellhorn at 07:19, 19 March 2026

2026-03-19T07:19:19Z

← Older revision		Revision as of 07:19, 19 March 2026
Line 1:		Line 1:
	Ideas for discussion were introduced with the following slides:		Ideas for discussion were introduced with the following slides:
	[[File:Background ideas.pdf\|thumb]]		[[File:Background ideas.pdf\|thumb]]

			Short overview from discussions/breakouts:
			* Background subtraction is dependent on:
			** sample system/geometry/the observable physics.
			* Each system has to be treated in a different way.
			* A survey will help identifying the necessary / common steps among the community for specific classified systems.
			* In case of multiple scattering: Include McStas as standard for GISANS analysis?


	Notes:		Notes:

AdrianRennie at 05:21, 19 March 2026

2026-03-19T05:21:58Z

← Older revision		Revision as of 05:21, 19 March 2026
Line 1:		Line 1:
			Ideas for discussion were introduced with the following slides:
			[[File:Background ideas.pdf\|thumb]]

	Notes:		Notes:
	* How do you know which type of (multiple coh/incoh.) scattering exists? And then which model for background to use accordingly? Are there approximations?		* How do you know which type of (multiple coh/incoh.) scattering exists? And then which model for background to use accordingly? Are there approximations?

Apostolos Vagias at 15:54, 18 March 2026

2026-03-18T15:54:26Z

← Older revision		Revision as of 15:54, 18 March 2026
Line 15:		Line 15:
	group 1		group 1

	JF:		Notes:
	Alexandros: going to a corner and measuring bkg		Alexandros: going to a corner and measuring bkg

	Philipp: this corner you go is below/or above the horizon/		Philipp: this corner you go is below/or above the horizon?
	Alexandros: below.		Alexandros: below.

Line 41:		Line 41:

	Henrich: a SANS machine can do everything a reflectometry machine can do.		Henrich: a SANS machine can do everything a reflectometry machine can do.
	Philipp: can cover some angular range to see total reflection~~, but with poor resolution~~.		Philipp: can cover some angular range to see total reflection.

	JF: for subtle variations of SLD maybe not possible. we try to measure reflectivity curves when we do GISANS measurements.		JF: Yes, but with poor resolution, for subtle variations of SLD this maybe not possible. we try to measure reflectivity curves when we do GISANS measurements.

	SJ: is always worth it.		SJ: is always worth it.

Apostolos Vagias at 15:21, 18 March 2026

2026-03-18T15:21:30Z

← Older revision		Revision as of 15:21, 18 March 2026
Line 10:		Line 10:
	* measure multiple states / dispersions / other observables to decrease ratio (unkown parameters)/(measured parameters)		* measure multiple states / dispersions / other observables to decrease ratio (unkown parameters)/(measured parameters)
	* how to judge if the simulation (even if fitting perfectly to the data) is the physical correct one? For the question of which parameters are influencing the cross section mostly using bayesian fitting: see papers from Josh (for reflectometry): https://journals.iucr.org/j/issues/2021/04/00/ge5096/ge5096sup1.pdf		* how to judge if the simulation (even if fitting perfectly to the data) is the physical correct one? For the question of which parameters are influencing the cross section mostly using bayesian fitting: see papers from Josh (for reflectometry): https://journals.iucr.org/j/issues/2021/04/00/ge5096/ge5096sup1.pdf


			*****
			group 1

			JF:
			Alexandros: going to a corner and measuring bkg

			Philipp: this corner you go is below/or above the horizon/
			Alexandros: below.

			Philipp: below the horizon, you have negative intensities. the corner will be different below or above the horizon.

			Alexandros: yes, because you have something that absorbs and scatters at the same time.

			Philipp: better to take it below the horizon instrument background.

			Alexandros: problem we had usually with bare substrate, we had no other way to estimate bkg.

			JF: the incoherent signal you get is not as constant in angle as you expect.

			SJ: in GISANS, closer to footprint, after 2 cm is all incoherent.
			JF: and inelastic
			SJ: instruments masuring reflectometry and GISANS, first you scan through angle (and identify critical edge).
			then, use this approach to get average SLD of the sample. problem with this approach would be that no SANS instrument can use this approach. put sample in, first reflectometry (get SLD) and afterwards then GISANS.



			intensity and wavelength

			Henrich: a SANS machine can do everything a reflectometry machine can do.
			Philipp: can cover some angular range to see total reflection, but with poor resolution.

			JF: for subtle variations of SLD maybe not possible. we try to measure reflectivity curves when we do GISANS measurements.

			SJ: is always worth it.

Annikastellhorn at 13:58, 18 March 2026

2026-03-18T13:58:55Z

← Older revision		Revision as of 13:58, 18 March 2026
Line 1:		Line 1:
	Notes:		Notes:
	- How do you know which type of (multiple coh/incoh.) scattering exists? And then which model for background to use accordingly? Are there approximations?		* How do you know which type of (multiple coh/incoh.) scattering exists? And then which model for background to use accordingly? Are there approximations?
	- always use multiple terms of the DWBA approximation? Where to draw the boundary?		* always use multiple terms of the DWBA approximation? Where to draw the boundary?
	- should we aim at always including a ray tracing approach (like McStas) to consider multiple scattering effects? (see union components McStas): https://mads-bertelsen.github.io/tutorial/Union_tutorial_1_processes_and_materials.html		* should we aim at always including a ray tracing approach (like McStas) to consider multiple scattering effects? (see union components McStas): https://mads-bertelsen.github.io/tutorial/Union_tutorial_1_processes_and_materials.html
	- this all would strongly affect fitting of GISANS - we guess that this is one reason that no fitting of GISANS exists at the moment?		* this all would strongly affect fitting of GISANS - we guess that this is one reason that no fitting of GISANS exists at the moment?
	- typical approach of subtracting background doesnt work if it comes from "the sample itself, i.e., by multiple scattering in the sample"		* typical approach of subtracting background doesnt work if it comes from "the sample itself, i.e., by multiple scattering in the sample"
	- can this be "tested" how much the sample affects the background, are there test samples for comparison?		* can this be "tested" how much the sample affects the background, are there test samples for comparison?
	- why not the "typical approach": you subtract the instrument background (has to be well known), and all other "background" has to be from the sample and has to be simulated/fitted? this has then to be known for all wavelength bands and incident angles		* why not the "typical approach": you subtract the instrument background (has to be well known), and all other "background" has to be from the sample and has to be simulated/fitted? this has then to be known for all wavelength bands and incident angles
	- comparison to QENS where signals are always weak - how is that handled? Can what is known from there be taken over? QENS: Start with approximations for the model, and this then has to be refined. Also there the precise knowledge of the sample and the estimations of multiple scattering involved have to be taken into account!		* comparison to QENS where signals are always weak - how is that handled? Can what is known from there be taken over? QENS: Start with approximations for the model, and this then has to be refined. Also there the precise knowledge of the sample and the estimations of multiple scattering involved have to be taken into account!
	- measure multiple states / dispersions / other observables to decrease ratio (unkown parameters)/(measured parameters)		* measure multiple states / dispersions / other observables to decrease ratio (unkown parameters)/(measured parameters)
	- how to judge if the simulation (even if fitting perfectly to the data) is the physical correct one? For the question of which parameters are influencing the cross section mostly using bayesian fitting: see papers from Josh (for reflectometry): https://journals.iucr.org/j/issues/2021/04/00/ge5096/ge5096sup1.pdf		* how to judge if the simulation (even if fitting perfectly to the data) is the physical correct one? For the question of which parameters are influencing the cross section mostly using bayesian fitting: see papers from Josh (for reflectometry): https://journals.iucr.org/j/issues/2021/04/00/ge5096/ge5096sup1.pdf

Annikastellhorn at 13:57, 18 March 2026

2026-03-18T13:57:53Z

← Older revision	Revision as of 13:57, 18 March 2026
Line 1:	Line 1:
		Notes:
		- How do you know which type of (multiple coh/incoh.) scattering exists? And then which model for background to use accordingly? Are there approximations?
		- always use multiple terms of the DWBA approximation? Where to draw the boundary?
		- should we aim at always including a ray tracing approach (like McStas) to consider multiple scattering effects? (see union components McStas): https://mads-bertelsen.github.io/tutorial/Union_tutorial_1_processes_and_materials.html
		- this all would strongly affect fitting of GISANS - we guess that this is one reason that no fitting of GISANS exists at the moment?
		- typical approach of subtracting background doesnt work if it comes from "the sample itself, i.e., by multiple scattering in the sample"
		- can this be "tested" how much the sample affects the background, are there test samples for comparison?
		- why not the "typical approach": you subtract the instrument background (has to be well known), and all other "background" has to be from the sample and has to be simulated/fitted? this has then to be known for all wavelength bands and incident angles
		- comparison to QENS where signals are always weak - how is that handled? Can what is known from there be taken over? QENS: Start with approximations for the model, and this then has to be refined. Also there the precise knowledge of the sample and the estimations of multiple scattering involved have to be taken into account!
		- measure multiple states / dispersions / other observables to decrease ratio (unkown parameters)/(measured parameters)
		- how to judge if the simulation (even if fitting perfectly to the data) is the physical correct one? For the question of which parameters are influencing the cross section mostly using bayesian fitting: see papers from Josh (for reflectometry): https://journals.iucr.org/j/issues/2021/04/00/ge5096/ge5096sup1.pdf