Clusters as calibration tools S. Molendi (IASF-MI)

Motivation Motivation Estimate the quality of the: calibration cross calibration btwn instruments

Motivation Motivation To what level can we trust the calibration of our instruments? How far can we push spectral modelling before we end up fitting instrument systematics rather than astrophysically relevant features?

The final frontier? The final frontier? This is a frontier that is worth exploring, major future X-ray missions are not around the corner, in many respects XMM-Newton and Chandra will be the best experiments for many years to come.

Cross Cal with Clusters Cross Cal with Clusters Has enjoyed some success Lots of photons and no pile-up! No need for simultaneous observations Spectrum is not a simple power-law however at the level of precision we are dealing with are there any pure pl spectra in the X-ray sky? Background can be a limitation

The Sample The Sample only EPIC to be extended to Chandra 16 observations of 13 objects spectra selected to be: Observed in thin or medium filters high SB 1T 2 < kT < < z < 0.09 long exposures WORK IN PROGRESS

The Sample The Sample source ring T SB Z arcmin keV erg cm 2 s -1 amin 2 Solar units A e A e A e A e A e A e A e A e A e A e A e AWM e MKW3s e

Analysis Analysis Bkg should not be a major issue at least below 5 keV Fit spectra with 1T and 2T models In most cases no substantial improvement with 2T, even when improvement is substantial, typically for the brighter objects, 2T modeling is un-physical, possibly associated to systematics Explore residuals in the form of ratio data/model heavily regroup data (beyond resolution limit) to few percent errors

Background Background

Analysis Analysis Fit spectra with 1T and 2T models In most cases no substantial improvement with 2T, even when improvement is substantial, typically for objects with better statystics, 2T modeling is un-physical, possibly associated to systematics

Calibration Calibration Consider data from each camera individualy

X-ray vs radio N H X-ray vs radio N H ● MOS1 ● MOS2 ● pn

X-ray vs radio N H X-ray vs radio N H

Investigating residuals Explore residuals in the form of ratio data/model Heavily regroup data (beyond resolution limit) to achieve few % errors

2A 0335 Ratio data/model 2A 0335 Ratio data/model

Investigating residuals Compute mean residuals averaged over all 16 observations Statistical errors are reduced, systematics should show up

Deviations from a simple thermal model MOS 1

Deviations from a simple thermal model MOS 2

Deviations from a simple thermal model pn

Deviations from a simple thermal model MOS1 & MOS2

Deviations from a simple thermal model MOS1, MOS2 & pn

Stability of residuals Do different objects show similar residuals?

Cold vs Hot MOS2

Cold vs Hot pn

Sample vs Perseus MOS1

Sample vs Perseus MOS2

Sample vs Perseus pn

Investigating residuals Residuals at least in some instances appear to be similar in different objects Spectral model 1T, hot cold, 4T for Perseus -- unlikely Instrument systematics Redistribution -- rmf Effective Area -- arf

pn soft band residua pn soft band residua Centaurus

pn soft band residua pn soft band residua Perseus

pn soft band residua pn soft band residua Mkn 421

mos soft band residua mos soft band residua Centaurus

mos soft band residua mos soft band residua Perseus

Implications Systematics likely related to rmf, particularly true for pn MOS less certain De Grandi+SM 09

Cross-Calibration Cross-Calibration Compare different instruments

MOS1 & pn NH vs MOS2 NH MOS1 & pn NH vs MOS2 NH ● MOS1 ● pn

MOS1 & pn kT vs MOS2 kT MOS1 & pn kT vs MOS2 kT ● MOS1 ● pn

MOS1, MOS2 & pn vs pn model

MOS1 & MOS2 vs pn model

MOS1, MOS2 & pn vs pn model

perseo Mostrare figura residui m1, m2 e pn Per perseo, usando gli spettri con binnaggio originale Commentare soft ok Hard tail, non si capisce

Summary Summary Calibration Redistribution problem on pn MOS, if there is one it’s smaller Cross-calibration Good to 3% in keV band problem with Effective areas at energy

Example of old vs new pn/mos Example of old vs new pn/mos Residuals in the form of ratio data/model for PN data on MOS best fitting model

ACIS S3 vs EPIC pn ACIS S3 vs EPIC pn We compare Chandra ACIS S3 with EPIC pn We compare Chandra ACIS S3 with EPIC pn About 3×10 6 events for each spectrum extracted from annulus with bounding radii of 1' and 2 ‘ About 3×10 6 events for each spectrum extracted from annulus with bounding radii of 1' and 2 ‘ Used old and new Chandra calibrations (CALDB with hrmaD axeffaN0008.fits) Used old and new Chandra calibrations (CALDB with hrmaD axeffaN0008.fits) Multi T spectral model (Molendi & Gastaldello 09) Multi T spectral model (Molendi & Gastaldello 09)

ACIS S3 vs EPIC pn ACIS S3 vs EPIC pn We start from the EPIC pn spectrum We start from the EPIC pn spectrum

ACIS S3 vs EPIC pn ACIS S3 vs EPIC pn We start from the EPIC pn spectrum We start from the EPIC pn spectrum Perform fit with multi T model Perform fit with multi T model

ACIS S3 vs EPIC pn ACIS S3 vs EPIC pn We start from the EPIC pn spectrum We start from the EPIC pn spectrum Perform fit with multi T model Perform fit with multi T model Fold best fitting model with ACIS response and compare it with ACIS spectrum Fold best fitting model with ACIS response and compare it with ACIS spectrum

ACIS S3 vs EPIC pn ACIS S3 vs EPIC pn Plot residuals in the form of ratio data/model Renorm applied to match spectra at 1.5 keV pn ACIS S3

ACIS S3 vs EPIC pn ACIS S3 vs EPIC pn Plot residuals in the form of ratio data/model Renorm applied to match spectra at 1.5 keV pn ACIS S3

ACIS S3 vs EPIC pn ACIS S3 vs EPIC pn Similar result when using a different region Annulus with bounding radii of 2' and 3 ‘ Showing only plot with new ACIS calibrations pn ACIS S3

Cross Cal Cross Cal pn and ACIS S3 spectral shapes are now in much better agreement! Differences are almost everywhere less than ~5% Major discrepancy in keV range

ACIS S3 vs EPIC pn ACIS S3 vs EPIC pn Residuals in the form of ratio data/model Renorm applied to match spectra at 1.5 keV pn ACIS S3

ACIS S3 vs EPIC MOS ACIS S3 vs EPIC MOS MOS2 appears to be more similar to ACIS in the keV band. MOS1 appears to be somewhere btwn. MOS2 and pn. MOS2 ACIS S3

Flux cross-cal pn vs ACIS Flux cross-cal pn vs ACIS Both figures have renorm factors: 5% for the first; 15% for the second: let’s take them out.Both figures have renorm factors: 5% for the first; 15% for the second: let’s take them out.

Flux cross-cal pn vs ACIS Flux cross-cal pn vs ACIS Both figures have renorm factors: 5% for the first; 15% for the second: let’s take them out.Both figures have renorm factors: 5% for the first; 15% for the second: let’s take them out.

Flux cross-cal Flux cross-cal The new HRMA calibration impacts on the ACIS/EPIC flux cross calibration.The new HRMA calibration impacts on the ACIS/EPIC flux cross calibration. Our analysis indicates that the flux cross calibration below ~ 2 keV will be shifted by about 10%.Our analysis indicates that the flux cross calibration below ~ 2 keV will be shifted by about 10%. Although comparing spectra extracted from a given region of a cluster may not be the best way to go, our data indicates that the flux cross calibration change is not for the better.Although comparing spectra extracted from a given region of a cluster may not be the best way to go, our data indicates that the flux cross calibration change is not for the better.

Summary Summary The new HRMA effective area reduces ACIS S3 vs pn residual calibration errors to less than 5%The new HRMA effective area reduces ACIS S3 vs pn residual calibration errors to less than 5% this is no small achievement! Major remaining discrepancy in keV band Major remaining discrepancy in keV band The new spectral calibration modifies by about 10% Chandra fluxes below 2 keV, ACIS vs EPIC flux cross calibration will be affected The new spectral calibration modifies by about 10% Chandra fluxes below 2 keV, ACIS vs EPIC flux cross calibration will be affected