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Cosmological Evolution of the Fine Structure Constant. a = e 2 /hc. Da = ( a z - a 0 )/ a 0. Chris Churchill (Penn State). In collaboration with: J. Webb, M. Murphy, V.V. Flambaum, V.A. Dzuba, J.D. Barrow, J.X. Prochaska, & A.M. Wolfe. Your “Walk Away” Info. - PowerPoint PPT Presentation
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Cosmological Evolutionof the
Fine Structure Constant
Chris Churchill(Penn State)
= e2/hc = (z-0)/0
In collaboration with: J. Webb, M. Murphy, V.V. Flambaum, V.A. Dzuba,J.D. Barrow, J.X. Prochaska, & A.M. Wolfe
Your “Walk Away” Info
1. 49 absorption cloud systems over redshifts 0.5–3.5 toward 28 QSOs compared to lab wavelengths for many transitions
2. 2 different data sets; low-z (Mg II, Mg I, Fe II) high-z (Si II, Cr II, Zn II, Ni II, Al II, Al III)
3. Find = (–0.72±0.18) × 10-5 (4.1) (statistical)
4. Most important systematic errors are atmospheric dispersion (differential stretching of spectra) and isotopic abundance evolution (Mg & Si; slight shifting in transition wavelengths)
5. Correction for systematic errors yields stronger evolution
Executive Summary
1. History/Motivations2. Terrestrial and CMB/BBN 3. QSO Absorption Line Method4. Doublet Method (DM) & Results5. Many-Multiplet Method (MM) & Results6. Statistical and Systematic Concerns7. Concluding Remarks
Classes of Theories
Attempts to solve some cosmological problems…
• Multi-dimensional and String Theories
• Scalar Theories (varying electron charge)
• Varying Speed of Light Theories
Unification of quantum gravity with other forces…
Couples E+M to cosmological mass density…
Varying Electron Charge Theories
Variation occurs over matter dominated epoch of the universe.
(Barrow etal 2001)
Varying Speed of Light Theories
Motivation is to solve the “flatness” and “horizon” problems of cosmology generated by inflation theory (Barrow 1999, Moffat 2001).
Theory allows variation in to be ~10-5H0 at redshift z=1. Evolution is proportional to ratio of radiation to matter density.
Last scattering vs. z CMB spectrum vs. l
CMB Behavior and ConstraintsSmaller delays epoch of last scattering and results in first peak at larger scales (smaller l) and suppressed second peak due to larger baryon to photon density ratio.
Solid (=0); Dashed (=-0.05); dotted (=+0.05)
Battye etal (2000)
BBN Behavior and Constraints
D, 3He, 4He, 7Li abundances depend upon baryon fraction, b.
Changing a changes b by changing p-n mass difference and Coulomb barrier.
Avelino etal claim no statistical significance for a changed from neither the CMB nor BBN data.
They refute the “cosmic concordance” results of Battye etal, who claim that =-0.05 is favored by CMB data.
Avelino etal (2001)
QSO absorption line methods can sample huge time span
Savedoff (1965) used doublet separations of emission lines from galaxies to search for evolution (first cosmological setting)
Bahcall, Sargent & Schmidt (1967) used alkali-doublet (AD) separations seen in absorption in QSO spectra.
QSO Absorption Lines (history)
Intrinisic QSO Emission/Absorption Lines
H I (Lyman-) 1215.67
C IV 1548, 1550 & Mg II 2796, 2803
We require high resolution spectra…
Interpreting those cloud-cloud separations….
And, of course…
Keck Twins10-meter Mirrors
The Weapon.
The High Resolution Echelle Spectrograph (HIRES)
2-Dimensional Echelle Image
Dark features are absorption lines
Electron Energy and Atomic Configuration
A change in will lead to a change in the electron energy, , according to
where Z is the nuclear charge, |E| is the ionization potential, j and l are the total and orbital angular momentum, and C(l,j) is the contribution to the relativistic correction from the many body effect in many electron elements.
Note proportion to Z2 (heavy elements have larger change)
Note change in sign as j increases and C(l,j) dominates
The “Doublet Method” ex. Mg II 2796, 2803
A change in will lead to a change in the doublet separation according to
where ()z and ()0 are the relative separations at redshift z and in the lab, respectively.
Si IV 1393, 1402
2796 2803
Spectrum of multi-cloud Mg II system (z=1.32)
We model the complex profiles as multiple clouds, usingVoigt profile fitting (Lorentzian + Gaussian convolved)
Free parameters are redshift, z, and
Lorentzian is natural line broadening Gaussian is thermal line broadening (line of sight)
Si IV Doublet Results: = –0.51.3 ×10-5
(Murphy et al 2001)
Ez = Ec + Q1Z2[R2-1] + K1(LS)Z2R2 + K2(LS)2Z4R4
Ec = energy of configuration center
Q1, K1, K2 = relativistic coefficients
L = electron total orbital angular momentum
S = electron total spin
Z = nuclear charge R = z/
The energy equation for a transition from the ground state at a redshift z, is written
The “Many-Multiplet Method”
A convenient form is: z = 0 + q1x + q2y
z = redshifted wave number
x = (z/0)2 - 1 y = (z/0)4 - 1
0 = rest-frame wave number
q1, q2 = relativistic correction coefficients for Z and e- configuration
Mg II 2803Mg II 2796Fe II 2600Fe II 2586Fe II 2382Fe II 2374Fe II 2344
Typical accuracy is 0.002 cm-1, a systematic shift in these values would introduce only a ~ 10-6
A precision of ~ 10-5 requires uncertainties in 0 no greater than 0.03 cm-1 (~0.3 km s-1)
Well suited to data quality… we can centroid lines to 0.6 km s-1, with precision going as 0.6/N½ km s-1
Anchors & Data Precision Shifts for ~ 10-5
Advantages/Strengths of the MM Method
1. Inclusion of all relativistic corrections, including ground states, provides an order of magnitude sensitivity gain over AD method
2. In principle, all transitions appearing in QSO absorption systems are fair game, providing a statistical gain for higher precision constraints on compared to AD method
3. Inclusion of transitions with wide range of line strengths provides greater constraints on velocity structure (cloud redshifts)
4. (very important) Allows comparison of transitions with positive and negative q1 coefficients, which allows check on and minimization of systematic effects
Possible Systematic Errors
1. Laboratory wavelength errors2. Heliocentric velocity variation3. Differential isotopic saturation4. Isotopic abundance variation (Mg and Si)5. Hyperfine structure effects (Al II and Al III)6. Magnetic fields7. Kinematic Effects8. Wavelength mis-calibration9. Air-vacuum wavelength conversion (high-z sample)10. Temperature changes during observations11. Line blending12. Atmospheric dispersion effects13. Instrumental profile variations
Isotopic Abundance Variations
There are no observations of high redshift isotopic abundances, so there is no a priori information
Focus on the “anchors”
We re-computed for entire range of isotopic abundances from zero to terrestrial. This provides a secure upper limit on the effect.
Observations of Mg (Gay & Lambert 2000) and theoretical estimates of Si in stars (Timmes & Clayton 1996) show a metallicity dependence
Corrected Uncorrected
This is because all Fe II are to blue of Mg II anchor and have same q1 sign (positive)
Leads to positive
For high-z data, Zn II and Cr II areTo red of Si II and Ni II anchors and have opposite q1 signs
Correction for Isotopic Abundances Effect low-z Data
a = pixel size [Å] , = slit width arcsec/pix,ψ = angular separation of and 2 on slit,θ = angle of slit relative to zenith
Atmospheric Dispersion
Blue feature will have a truncated blue wing!
Red feature will have a truncated red wing!
This is similar to instrumental profile distortion, effectively a stretching of the spectrum
Causes an effective stretching of the spectrum which mimics a non-zero
Correction for Atmospheric Distortions Effect low-z Data
Corrected Uncorrected
This is because all Fe II are to blue of Mg II anchor and have same q1 sign (positive)
Leads to positive
For high-z data, Zn II and Cr II areTo blue and red of Si II and Ni II anchors and have opposite q1 signs
Summary of MM Method
1. 49 absorption clouds systems over redshifts 0.5 to 3.5 toward 28 QSOs compared to lab wavelengths for many transitions
2. 2 different data sets; low-z (Mg II, Mg I, Fe II) high-z (Si II, Cr II, Zn II, Ni II, Al II, Al III)
3. Find = (–0.72±0.18) × 10-5 (4.1) (statistical)
4. Most important systematic errors are atmospheric dispersion (differential stretching of spectra) and isotopic abundance evolution (Mg & Si; slight shifting in transition wavelengths)
5. Correction for systematic errors yields stronger evolution
= (–0.72±0.18) × 10-5 (4.1) (statistical)
Soon to the PressPreliminary Findings…
Now have a grand total of 138 systems due to adding the HIRES data of Sargent et al.
Find = (–0.65±0.11) × 10-5 (6) (statistical)
What We Need: The Future
Same and new systems observed with different instrument and reduced/analyzed by different software and people.
Our plans are to get UVES/VLT and HRS/HET spectrain order to reproduce the HIRES/Keck results