Wave-packet treatment of neutrino oscillations and its implication on Daya Bay and JUNO experiments

Transcription

1 Wave-packet treatment of neutrino oscillations and its implication on Daya Bay and JUNO experiments Steven C.F.Wong Sun Yat-Sen University 22nd May 2015

2 Overview Part I: My past and current researches The wave-packet impact on current reactor neutrino experiments. Introduction Wave-packet of the neutrino mass eigenstates. Decoherence and Dispersion Effects in the Daya Bay Experiment. Things to do. Part II: Preliminary Future Planning The wave-packet impact on JUNO mass hierarchy measurement. The sensitivity of mass hierarchy measurement with considering wave-packet impact. Part III: Other Research Interests. 2 / 24

3 Part I (Previous and current work) The wave-packet impact on Daya Bay Experiment 3 / 24

4 Introduction Conventionally, plane-wave description for the neutrinos is adopted in most oscillation experiments. However, in reality, as neutrino production and detection are localized events, there must be finite intrinsic energy/momentum uncertainties, and the neutrino should be described by a wave-packet as it propagates freely. Decoherence Effect: the group velocities of the wave-packets depend on the mass (m i ) of different mass eigenstates. The spreading of wave packets: free (unbounded) particles always exhibit dispersion. 4 / 24

5 Decoherence and dispersion effects on flavor oscillations 5 / 24

6 Modification of the neutrino oscillation 6 / 24

7 Neutrino wave-packet of the neutrino mass eigenstates Assume that each neutrino mass state being a Gaussian wave packet: ν i (z, t) = dp 1 (p pν)2 exp( )exp[i(pz E 2π πσν 2σν 2 i (p)t)] ν i, (1) where σ ν is the width of the wave-packet in momentum space. Expand the energy E i (p) around the mean momentum p ν E i (p) = p 2 + mi 2 = E i (p ν) + v i (p ν)(p p ν) + m 2 i 2(E i (p ν)) 3 (p pν)2, (2) where v i (p ν) = de i dp = pν/e i, which is the group velocity of the wave packet. Conventionally, the last term in Eq. (2) is neglected. However, this term leads to the dispersion effect and brings significant modifications to the decoherence effect. 7 / 24

8 The modification of ν e survival probability Pēē =1 1 2 cos4 (θ 13)sin 2 1 (2θ 12)[1 ( ) y exp( λ21)cos(φ 21)] 1 2 sin2 (2θ 13)cos 2 1 (θ 12)[1 ( ) y exp( λ31)cos(φ 31)] 1 2 sin2 (2θ 13)sin 2 1 (θ 12)[1 ( ) y exp( λ32)cos(φ 32)] (3) where σ E σν E, y ij = m2 ijl 2E σ2 E, coming from the dispersion effect, 1 (( mij) 2 2 σe 2 L 2 ) λ ij = 16 E 2, decoherence damping factor, 1 + y 2 φ ij = m2 ijl 2E tan 1 (y ij ) ij 1 (( mij) 2 2 σe 2 L 2 ) 16 E y 2 ij y ij, There are 3 free parameters: σ E, the mixing angles and m 2 in our data analysis. 8 / 24

9 The wave-packet impact on Daya Bay Experiment 9 / 24

10 The decoherence effect depends on the baseline Effective Baseline 561 meters. N obs N exp Σ E 0 Σ E 0.1 Σ E Pēē as a function of L eff /E ν for Daya Bay EH1, compared with data. The black (solid), green (dashed) and brown (dot-dashed) curves correspond to σ E = 0, 10% and 50% neutrino energy respectively. 10 / 24

11 The decoherence effect depends on the baseline Effective Baseline 1579 meters. N obs N exp Σ E 0 Σ E 0.1 Σ E Pēē as a function of L eff /E ν for Daya Bay EH3, compared with data. The black (solid), green (dashed) and brown (dot-dashed) curves correspond to σ E = 0, 10% and 50% neutrino energy respectively. 11 / 24

12 1.0 The contours from Daya Bay data Marginalized over m ΣE sin 2 2Θ 13 The 1 σ (red), 2 σ (green) and 3 σ (blue) constraints on σ E vs sin 2 2θ 13 from the previous Daya Bay data. We have marginalized over m 2 31 in this plot. The vertical black line represents the best-fit sin 2 2θ 13 from the previous Daya Bay announcement. The contours on this page are not the official Daya Bay results. 12 / 24

13 To do list Generating MC samples and do the sensitivity test to explore how well can Daya Bay constrain σ E by collecting more data. Cooperate with other Daya Bay collaborators to finish a global analysis fitter to further study the wave-packet impact on other oscillation experiments, especially reactor experiments. Combine the results from Daya Bay and other experiments, publish a paper 13 / 24

14 Part II (Preliminary plan on the future researches) Potential impact on the determination of Neutrino Mass Hierarchy 14 / 24

15 Determine the mass hierarchy by measuring the fast oscillation of θ 13 at long baseline In Normal Hierarchy, m 2 32 = m 2 31 m In Inverted Hierarchy, m 2 32 = m m Flux arbitrary unit Expected neutrino visible energy spectrum of plane wave neutrino oscillation at 58 km for NH (solid) and IH (dashed). To measure Pēē(NH) and Pēē(IH) in reactor neutrino experiment, Detector has to be located at baseline of about km. 15 / 24 V

16 The potential impact on measuring Mass Hierarchy in long baseline reactor experiments The decoherence effect could be important and affect the future mass-hierarchy measurement. However, since both m 2 32 and L are large in this case, the decoherence effect could be significant and the m 2 32 oscillation term may be averaged out. 16 / 24

17 The potential impact on measuring Mass Hierarchy in long baseline reactor experiments Predicted neutrino visible energy spectrum at 58km of wave-packet neutrino oscillation for NH (blue) and IH (red), with σ E being 0.01 (top left), 0.02 (top right), 0.05 (bottom left) and 0.1 (bottom right) respectively. 17 / 24

18 The potential impact on measuring Mass Hierarchy in long baseline reactor experiments One way to quantify our conclusion: Assume that the nature is Normal Hierarchy, then we fit both the NH and IH with the least-square methods by scanning over the parameter m 2 ee: Then we calculate χ 2 NH = N bins i (M i T i NH( m 2 ee)) 2 M i, χ 2 IH = N bins i (M i T i IH( m 2 ee)) 2 M i, where M i is the measured event rate in the ith energy bin, T i the expected event rate of NH (or IH) depending on m 2 ee. 18 / 24

19 The potential impact on measuring Mass Hierarchy in long baseline reactor experiments If σ E = 0.0: The plot of χ 2 VS m ee (Yu-Feng Li et.al. PRD 88, ) NH IH Σ 3Σ 5 1Σ simulation from GLoBES The black curve corresponds to Normal Hierarchy, the dashed corresponds Inverted Hierarchy. 19 / 24

20 The potential impact on measuring Mass Hierarchy in long baseline reactor experiments If σ E = 0.02: The plot of χ 2 VS m ee NH IH Σ 3Σ 5 1Σ simulation from GLoBES The black curve corresponds to Normal Hierarchy, the dashed curve corresponds Inverted Hierarchy. 20 / 24

21 Χ 2 MH The potential impact on measuring Mass Hierarchy 4Σ 10 3Σ 5 1Σ simulation from GLoBES χ 2 = χ 2 min(nh) χ 2 min(ih) 21 / 24

22 Preliminary plan Consider the systematics more carefully and experimental setup more carefully and do the simulations again. Try to restore part of the sensitivity under significant decoherence effect, by improving the systematics or design of experimental setup. Investigate the sensitivity of JUNO detector in studying wave-packet impact and other new physics. 22 / 24

23 Researches besides neutrino wave-packet study 23 / 24

24 Sterile neutrino analysis (will perform analyses and simulations to combine the 3+1 oscillation framework and wave-packet impact.) The search of New Physics (such as non-standard interaction oscillation) in Daya Bay and JUNO. The physics potential of future accelerator neutrino oscillation experiment in China, e.g. MOMENT. Different physical mechanisms which could induce neutrinoless double beta decay. 24 / 24

25 Back Up Slides 24 / 24

26 The constraints of wave-packet impact from KamLAND Experiment ΣE sin 2 2Θ 12 The 1 σ (blue), 2 σ (cyan) and 3 σ (pink) allowed regions on σ E vs sin 2 2θ 12 from fitting the KamLAND data. m21 2 has been marginalized in this plot. The vertical black line represents the best-fit sin 2 2θ 12 from our plane-wave analysis. The systematic errors of the KamLAND Experiment were not considered in our analysis. 24 / 24

27 Appendix Decoherence from localization Decoherence Effect from localization: oscillation length being comparable to the spatial uncertainties of production / detection process (but we think this effect can be neglected in most circumstances). Pēē =1 1 2 cos4 (θ 13)sin 2 (2θ 12) 1 [1 ( ) y exp( λ21)exp[ γ 21(1 y21)]cos(φ 2 21)] 1 2 sin2 (2θ 13)cos 2 (θ 12) 1 [1 ( ) y exp( λ31)exp[ γ 31(1 y31)]cos(φ 2 31)] 1 2 sin2 (2θ 13)sin 2 (θ 12) 1 [1 ( ) y exp( λ32)exp[ γ 32(1 y32)]cos(φ 2 32)] (4) where γ ij = ( m 2 ij) E yij 2 1 σ 2 E = π 2 (1 + y 2 ij ) σx 2 L 2 osc, L osc 4πE m 2 ij 24 / 24

28 [σ E ] Log Appendix The upper and lower bounds of σ E 2 Allowed regions for sin (2θ 13 ) and σ E sin (2θ ) The 1 σ (red), 2 σ (green) and 3 σ (blue) constraints on σ E vs sin 2 2θ 13 from the P14A data. We have marginalized over m 2 31 in this plot. The vertical black line represents the best-fit sin 2 2θ 13 from the previous Daya Bay announcement. 24 / 24

29 Appendix Decoherence without considering dispersion If the energy is just expanded to first order, E i (p) = p 2 + mi 2 then = E i (p ν) + v i (p ν)(p p ν) +..., P ee =1 1 2 cos4 (θ 13)sin 2 (2θ 12)[1 exp( σe 2 ( m21) 2 2 L 2 )cos(2 m2 31L 16E 4 4E )] 1 2 sin2 (2θ 13)cos 2 (θ 12)[1 exp( σe 2 ( m31) 2 2 L 2 )cos(2 m2 31L 16E 4 4E )] 1 2 sin2 (2θ 13)sin 2 (θ 12)[1 exp( σ 2 E cos(2 ( m2 31 m21)l 2 )]. 4E ( m 2 31 m 2 21) 2 L 2 16E 4 ) 24 / 24

30 Assuming full cancellation in 76 Ge, the m ββ of 130 Te becomes m ββ of 130 Te under different mechanisms. The black solid lines the destructive interference between light and heavy neutrino; The blue dashed lines only light neutrino contribution ; 24 / 24