Cosmological Evolution of the Fine Structure Constant Chris Churchill (Penn State)  = e 2 /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) × (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/Motivations 2.Terrestrial and CMB/BBN 3.QSO Absorption Line Method 4.Doublet Method (DM) & Results 5.Many-Multiplet Method (MM) & Results 6.Statistical and Systematic Concerns 7.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 -5 H 0 at redshift z=1. Evolution is proportional to ratio of radiation to matter density.

Last scattering vs. zCMB spectrum vs. l CMB Behavior and Constraints Smaller  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, 3 He, 4 He, 7 Li 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-  )

C IV 1548, 1550 & Mg II 2796, 2803

We require high resolution spectra…

Interpreting those cloud-cloud separations….

And, of course… Keck Twins 10-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 Z 2 (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,

Spectrum of multi-cloud Mg II system (z=1.32)

We model the complex profiles as multiple clouds, using Voigt 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:  = –0.5  1.3 ×10 -5 (Murphy et al 2001)

E z = E c + Q 1 Z 2 [R 2 -1] + K 1 (LS)Z 2 R 2 + K 2 (LS) 2 Z 4 R 4 E c = energy of configuration center Q 1, K 1, K 2 = 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 + q 1 x + q 2 y  z = redshifted wave number x = (  z /  0 ) 2 - 1y = (  z /  0 )  0 = rest-frame wave number q 1, q 2 = relativistic correction coefficients for Z and e - configuration Mg II 2803 Mg II 2796 Fe II 2600 Fe II 2586 Fe II 2382 Fe II 2374 Fe II 2344

Typical accuracy is cm -1, a systematic shift in these values would introduce only a  ~ A precision of  ~ 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/N ½ 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 q 1 coefficients, which allows check on and minimization of systematic effects

Possible Systematic Errors 1.Laboratory wavelength errors 2.Heliocentric velocity variation 3.Differential isotopic saturation 4.Isotopic abundance variation (Mg and Si) 5.Hyperfine structure effects (Al II and Al III ) 6.Magnetic fields 7.Kinematic Effects 8.Wavelength mis-calibration 9.Air-vacuum wavelength conversion (high-z sample) 10.Temperature changes during observations 11.Line blending 12.Atmospheric dispersion effects 13.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

CorrectedUncorrected This is because all Fe II are to blue of Mg II anchor and have same q 1 sign (positive) Leads to positive  For high-z data, Zn II and Cr II are To red of Si II and Ni II anchors and have opposite q 1 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 CorrectedUncorrected This is because all Fe II are to blue of Mg II anchor and have same q 1 sign (positive) Leads to positive  For high-z data, Zn II and Cr II are To blue and red of Si II and Ni II anchors and have opposite q 1 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) × (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) × (4.1  ) (statistical)

Soon to the Press Preliminary Findings… Now have a grand total of 138 systems due to adding the HIRES data of Sargent et al. Find  = (–0.65±0.11) × (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 spectra in order to reproduce the HIRES/Keck results