Our current understanding of the Universe comes, among others, from particle physics and cosmology. In particle physics an almost perfect symmetry between matter and antimatter exists. On cosmological scales, however, a striking matter/antimatter imbalance is observed. This contradiction inspires comparisons of the fundamental properties of particles and antiparticles with high precision. Here we report on a measurement of the g-factor of the antiproton with a fractional precision of 0.8 parts per million at 95% confidence level. Our value /2=2.7928465(23) outperforms the previous best measurement by a factor of 6. The result is consistent with our proton g-factor measurement gp/2=2.792847350(9), and therefore agrees with the fundamental charge, parity, time (CPT) invariance of the Standard Model of particle physics. Additionally, our result improves coefficients of the standard model extension which discusses the sensitivity of experiments with respect to CPT violation by up to a factor of 20.
Precise tests of charge, parity, time (CPT) invariance1 are inspired by the intriguing lack of antimatter in our Universe2. Despite its importance to our understanding of nature, only a few direct precise tests of CPT symmetry are available3,4,5,6,7,8,9. Our experiments contribute such tests by comparing the fundamental properties of protons and antiprotons with high precision. Recently we performed the most precise comparison of the antiproton-to-proton charge-to-mass ratio /(q/m)p with a fractional precision of 69 parts per trillion10. Here, we report an improved measurement of the magnetic moment of the antiproton .
Our comparisons are based on frequency measurements of single particles in cryogenic Penning traps. These traps employ the superposition of a strong magnetic field B0 in the axial direction and an electrostatic quadrupole potential11. Under such conditions, a trapped charged particle follows a stable trajectory consisting of three independent harmonic oscillator motions–the modified cyclotron frequency ν+, the magnetron frequency ν−, and the axial frequency νz. Non-destructive measurements of these frequencies12 enable the determination of the cyclotron frequency (ref. 13). Together with a determination of the spin-precession, or Larmor frequency νL, the magnetic moment can be determined in units of the nuclear magneton μN, where is the g-factor of the particle. The determination of the Larmor frequency relies on the detection of resonantly driven spin transitions by means of the continuous Stern-Gerlach effect14. An axial magnetic field Bz=B2(z2−ρ2/2) is superimposed on the homogeneous magnetic field B0 of the trap. This magnetic bottle couples the spin magnetic moment to the axial oscillation frequency νz of the particle, which is directly accessible by measurement. When a spin-flip takes place, νz is shifted by . This technique has been applied in electron/positron magnetic moment measurements (ref. 3), however, its application to measure the magnetic moments of the proton/antiproton15,16 is much more challenging, since . Therefore, to resolve single antiproton spin transitions an ultra-strong magnetic bottle is needed, we use B2=2.88·105 T m−2.
In this article we report a direct measurement of the g-factor of a single antiproton, with a fractional precision of 0.8 p.p.m. Our result is based on six individual g-factor measurements and is 6 times more precise than the current best value15.
The experiment16 is located at the antiproton decelerator (AD)17 facility of CERN. We operate a cryogenic multi-Penning trap system, see Fig. 1a, which is mounted in the horizontal bore of a superconducting magnet with field strength B0=1.945 T. Each Penning trap consists of a set of five cylindrical gold-plated electrodes in a carefully chosen geometry18. The individual traps are interconnected by transport electrodes. Application of voltage ramps to these electrodes enables adiabatic shuttling of the particles between the traps. Resonant superconducting tuned circuits with high quality factors Q (ref. 19) and effective temperatures of ≈8 K connected to specific electrodes enable resistive particle-cooling, non-destructive detection12 and measurements of the oscillation frequencies of the trapped antiprotons.
The entire trap assembly is mounted in a pinched-off vacuum chamber with a volume of 1.2l. A stainless steel degrader window, with a thickness of 25 μm, is placed on the vacuum flange, which closes the up-stream side of the chamber, being vacuum tight but partly transparent for the 5.3 MeV antiprotons provided by the AD. The chamber is cooled to cryogenic temperatures (6 K), where cryo-pumping produces a vacuum good enough to reach antiproton storage times of more than 1.2 years20.
We are using three traps, a reservoir trap (RT), a co-magnetometer trap (CT) and an analysis trap (AT). The RT with an inner diameter of 9 mm contains a cloud of antiprotons, which has been injected from the AD and supplies single particles to the other traps when needed20. This unique trap enables us to conduct antiproton experiments even during AD machine-shutdowns. The CT has the same geometry as the RT and is located 50 mm away from the AT. Single particle cyclotron frequency measurements at ν+,CT≈29.6 MHz allow for continuous sampling of the trap’s magnetic field, with an absolute resolution of a few nanotesla. The AT has the strong superimposed magnetic bottle B2. The inner diameter is 3.6 mm, and the central ring electrode is made out of ferromagnetic Co/Fe material. This distorts the magnetic field in the centre of the trap such that ν+,AT≈18.727 MHz and νL,AT≈52.337 MHz.
g-factor measurement in the strong magnetic bottle
The strong B2 couples the spin magnetic moment as well as the angular magnetic moment of the radial modes to its axial frequency νz,AT (n+, n−, ms)=νz,0+Δνz(n+, n−, ms)≈674 kHz, where
Here, h is Planck’s constant, and n+ and n− are the principal quantum numbers of the two radial modes, while characterizes the eigenstate of the spin of the antiproton. A cyclotron quantum jump Δn+=±1 changes the axial frequency by Δνz,+=±65 mHz, a transition Δn−=±1 in the magnetron mode leads to Δνz,−=±42 μHz. A single spin transition, however, changes νz,AT by 183 mHz, which can be clearly detected if the changes in the quantum numbers of the radial modes are low enough to achieve a frequency stability of Δνz/νz,AT≈10−7. This is considerably difficult since spurious voltage-noise en on the electrodes with a power spectrum density of causes heating rates21;
in the radial modes, where 1/Λ is a trap specific length. This parasitic heating leads to random walks in the radial modes and continuously changes the axial frequency νz,AT. Voltage-noise densities of order en=50 pV/ to 200 pV/ on the electrodes reproduce the observed axial frequency drifts. Note that dn+,−/dt∝n+,−. Therefore, the preparation of a particle with a sufficient axial frequency stability, which allows efficient detection of spin transitions, needs cooling of the cyclotron mode to sub-thermal energies, E+/kB<1.1 K (ref. 22).
The determination of the g-factor requires precise measurements of ν+,AT and νL,AT. To resolve these frequencies we apply radio-frequency drives to the trap and measure the axial frequency νz,AT of the trapped antiproton as a function of time and for different drive frequencies νrf. Here the axial frequencies are determined as described in ref. 23. Once quantum transitions are resonantly driven, the axial frequency fluctuation Ξz, defined as the s.d. of the difference of subsequent axial frequency measurements σ(νz,k+1−νz,k):=Ξz, increases drastically, as shown in Fig. 1b,c (ref. 23). The shapes of these resonance lines
reflect the Boltzmann distribution of the axial energy due to the continuous interaction of the particle with the detection system. Here νj are the modified cyclotron frequency ν+,AT(Ez=0)=ν+,cut and the Larmor frequency νL,AT(Ez=0)=νL,cut at vanishing axial energy Ez, respectively, Δνj∝νj·B2·Tz is the line-width parameter24 and Θ(νrf−νj) the Heaviside function. The resolution which will eventually be achieved in the determination of the g-factor is consequently limited by the ability to resolve these two frequencies, ν+,cut and νL,cut.
To extract these frequencies, we scan the resonance lines only in a close range around the cut-frequencies. A random walk ξ(t), predominantly in the magnetron mode, continuously changes the magnetron radius ρ−(t), and as a result, the magnetic field experienced by the particle. This softens the slope of the resonance lines close to ν+,cut and νL,cut.
To prepare the initial conditions of a g-factor measurement, we extract an antiproton from the reservoir and cool its modified cyclotron mode by resistive cooling in the CT. Subsequently we shuttle the particle to the AT. Using sideband coupling25 we first cool the energy of the magnetron mode to E−/kB<4 mK, then we determine the cyclotron energy by an axial frequency measurement, see equation (1). This sequence is repeated until E+/kB<1.1 K. For particles at such low cyclotron energies and axial frequency averaging times >90 s we achieve axial frequency fluctuations Ξz,back<0.120 Hz. Next, we tune the particle to the centre of the magnetic bottle by adjusting offset voltages on the trap electrodes. This is crucial to suppress systematic shifts in the frequency measurements.
Afterwards, we conduct the actual g-factor measurement as illustrated in Fig. 2a. This starts with (0) cooling of the magnetron motion, followed by (1) a measurement of the modified cyclotron frequency ν+,AT,1. Then (2) we scan the Larmor resonance, which typically takes 9–14 h. This is followed (3) by a second measurement of the modified cyclotron frequency ν+,AT,2. The cycle ends by (4) cooling of the magnetron motion.
To determine the modified cyclotron frequency, we apply a drive which induces on resonance a heating rate of dn+/dt(νrf=ν+,AT(Ez=0))≈4 s−1. We start with a background measurement at νrf,0≈ν+,AT−100 Hz and then scan the drive frequency νrf, typically in steps of 25 Hz over the resonance. For each individual drive frequency νrf,k we record ten axial frequency data-points, each averaged by t=30 s, and evaluate the axial frequency fluctuation Ξz(νrf,k). We repeat this scheme until the resonance line is clearly resolved, which means that for a resonant excitation frequency νrf,e the condition (Ξz(νrf,e)−Ξz,back)/σ(ΔΞz(νrf,e), ΔΞz,back)>3 is fulfilled. Here ΔΞz(νrf,k)=Ξz(νrf,k)/(2N−2)0.5 is the 68% confidence interval of the measurement, N is the number of accumulated data points per drive frequency νrf,k and σ(ΔΞz(νrf,e), ΔΞz,back) the propagated s.e. of Ξz(νrf,e)−Ξz,back. As an example a sequence of 50 axial frequency measurements with applied rf drives at νrf,k is shown in Fig. 2b. The first two data sets at νrf,1 and νrf,2 are consistent with the un-driven background fluctuation. At νrf,3 and νrf,4 the applied rf-drive induces cyclotron quantum transitions which clearly increases the measured axial frequency fluctuation to . Figure 2c displays a projection of measured axial frequencies of an entire measurement sequence to axial frequency fluctuation Ξz(νrf,k) as a function of the applied rf-drive frequency.
The measured distribution of points Ξz(νrf,k) constrains the random walk ξ−(t) in the magnetron mode which has taken place during the frequency scan. Each individual measurement can be associated to a gaussian sub-distribution wk(ν, ν+(0)+ξ−(t))
where is the measurement time, ɛ a scaling factor, and ν+(0)+ξ−(t) the time dependent modified cyclotron frequency while νrf,k was irradiated. We reconstruct the distribution of modified cyclotron frequencies during the entire measurement by minimizing with the strength of the walk ξ− as a free parameter. From the reconstructed distribution we evaluate ν+,AT,1 and derive the 95% confidence interval based on w. We back-up this treatment by Monte-Carlo simulations which model the exact measurement sequence. From the measurement shown in Fig. 2c, we extract ν+,AT,1=18,727,467(33) Hz, the mean value is indicated by the red vertical line, the green lines represent the 95% confidence interval of the measured mean, the blue solid line is the unperturbed line convoluted with the reconstructed w-distribution. The cyclotron frequency νc,AT,1 is obtained by approximating , and using the invariance theorem13.
The Larmor frequency νL,AT is measured as first reported in ref. 23. First we average the axial detector transients for 90 s and determine the axial frequency νz,1. Subsequently an off-resonant radio-frequency drive at frequency νrf,0<νL(Ez=0) is irradiated and the axial frequency is measured again νz,2. This scheme is repeated twice, with the rf-drive being tuned to values νrf,1 and νrf,2. Both frequencies are chosen to be close to the spin-resonance νrf,1≈νrf,2≈νL(Ez=0). Repetition of this measurement sequence for N times enables us to determine the fluctuations Ξz,back, Ξz(νrf,1) and Ξz(νrf,2) the statistical significance being defined as in the cyclotron measurements. Once spin flips are driven by νrf,k the 183 mHz axial frequency jumps induced by the spin transitions add up to the background frequency fluctuation Ξz,back. In this case the axial frequency fluctuation results in , where pSF(νrf,k) is the spin-flip probability24.
Figure 3a shows results of such a measurement. The blue data-points represent the cumulative axial frequency background fluctuation Ξz,back. The green data points display Ξz(N, νrf,1), measured while an rf-drive at νrf,1=52,336,800 Hz was applied. The red data points show Ξz(N, νrf,2) where the rf-drive was tuned to νrf,2=52,336,900 Hz. The solid lines represent the 68% confidence intervals of Ξz(N, νrf,k). From the measurement shown in Fig. 3a we extract after accumulation of N=93 data points Ξz,back=0.111(8) Hz, Ξz(νrf,1)=0.116(8) Hz and Ξz(νrf,2)=0.168(13)Hz, which corresponds to a detection of spin transitions with >3.5σ statistical significance. Figure 3b shows the statistical significance (Ξz(νrf)−Ξz,back)/(σ(ΔΞz(νrf), ΔΞz,back)) for three different background fluctuations Ξz,back and as a function of the number of accumulated measurements. With the conditions of the experiment Ξz,back<0.120 Hz and spin transitions which are driven at 50% probability we achieve a statistical significance >3.5σ by accumulating at least 80 measurements. In the experiment this is the minimum of data points which has been accumulated per irradiated νrf.
Based on the above measurement we extract the Larmor frequency νL,AT as the arithmetic mean of νrf,1 and νrf,2. To define the 95% confidence interval we run Monte-Carlo simulations with defined parameters and ν+,1−ν+,2. The start frequency ν+,1 and the strength of the magnetron walk ξ−(t) are varied. We accept random walks which reproduce our result that within the 68% confidence bands Ξz(νrf,1)=Ξz,back, and (Ξz(νrf,2)−Ξz,back)/σ(Ξz(νrf,2), Ξz,back)>3.5. We calculate the mean frequency of the simulated walk <νL> and compare to the arithmetic mean frequency νL,exp which would have been extracted from the measurement. By integrating the resulting distribution w(νL,exp−<ν+>) we determine the 95% confidence level of νL,exp. For further details we refer to the Supplementary Discussion. From the measurement shown in Fig. 3a we extract νL,AT=52,336,850(33)Hz.
Using the measured frequencies νc,1, νL,AT and νc,2 the g-factor is evaluated by calculating g/2=νL,AT/<νc>, where <νc>=0.5·(νc,1+νc,2). This accounts for linear drifts in the magnetic field experienced by the particle during the scan of the Larmor frequency.
We performed in total six g-measurements, all of them were carried out during weekend- or night-shifts when magnetic field noise in the accelerator hall is small. The results are shown in Fig. 4. The uncertainties of the measurements are defined by the resolution achieved in the individual frequency measurements convolving the effects of magnetic field drift due to the magnetron random walk. To evaluate the final value of the g-factor we calculate the weighted mean of the entire data-set and extract
The first number in brackets represents the 95% confidence interval of the measured mean, the second number in brackets represents the scatter of the error according to t-test statistics.
Systematic errors come from non-linear drifts of the field of the superconducting magnet, drifts of the voltage source which is used to define the trapping potential and the random walk ξ+(t) in the modified cyclotron mode. From measurements with the co-magnetometer particle we estimate Δg/g|B0≈0.015 p.p.m. Continuous voltage measurements constrain Δg/g|V<0.001 p.p.m., while we obtain for the random walk in the cyclotron mode Δg/g|+≈0.020 p.p.m. The non-linear contribution of the magnetron walk ξ−(t) to a systematic shift of the g-factor is implicitly considered in the primary data-evaluation of the measured resonance lines. We add these errors by standard error propagation and obtain
This result is consistent with our recently measured value of the magnetic moment of the proton in units of the nuclear magneton gp/2=2.792847350(9)26 and supports CPT invariance.
Our measurement also sets improved limits on parameters of the standard model extension (SME)9,27, which characterizes the sensitivity of a proton/antiproton g-factor comparison with respect to CPT violation. In a very recent comprehensive paper by Ding and Kostelecký28 the SME formalism is applied to Penning traps. There a detailed discussion on comparisons of experiments at different orientation and location is described. By adapting this work to our, data we derive for the leading coefficients described in the SME standard frame GeV and GeV, which corresponds to a 11 and 22-fold improvement compared with the previously published constraints28. A summary of all upper limits on the SME-coefficients which are derived from our experiment are displayed in Table 1.
In our evaluation we have assumed that diurnal variations caused by the Earth’s rotation average out. We neglect a potential bias which might be introduced by the fact that, due to maintenance of the apparatus, only a small amount of data was accumulated between noon and early afternoon. More equally distributed data accumulation will be addressed in our planned future experiments. For further details we refer to the Supplementary Discussion.
In summary, we have measured the magnetic moment of a single trapped antiproton in a single Penning trap with a superimposed magnetic bottle. The achieved fractional precision is at 0.8 p.p.m. (95% confidence level) and outperforms the fractional precision quoted in previous measurements by a factor of 6 (ref. 15). The precision of the result is limited by a background-noise driven random walk in the magnetron mode, which causes line-broadening. The measured antiproton g-factor is in agreement with our recent 3.3 p.p.b. proton g-factor measurement and supports CPT invariance. The much more precise proton measurements are based on the application of the challenging double Penning trap technique26. Implementation of this method to further improve the precision in antiproton magnetic moment measurements to the p.p.b. level will be targeted in our future research.
The data sets for the current study are available from the corresponding authors on reasonable request.
How to cite this article: Nagahama, H. et al. Sixfold improved single particle measurement of the magnetic moment of the antiproton. Nat. Commun. 8, 14084 doi: 10.1038/ncomms14084 (2017).
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Lüders, G. Proof of the TCP theorem. Ann. Phys. 2, 1–15 (1957).
Dine, M. & Kusenko, A. Origin of the matter-antimatter asymmetry. Rev. Mod. Phys. 76, 1–30 (2003).
Van Dyck, R. Jr, Schwinberg, P. & Dehmelt, H. New high-precision comparison of electron and positron g factors. Phys. Rev. Lett. 59, 26–29 (1987).
Schwingenheuer, B. et al. CPT tests in the neutral Kaon system. Phys. Rev. Lett. 74, 4376–4379 (1995).
Miller, J. P., De Rafael, E. & Roberts, B. L. Muon (g-2): experiment and theory. Rep. Prog. Phys. 70, 795–881 (2007).
Gabrielse, G. et al. Precision mass spectroscopy of the antiproton and proton using simultaneously trapped particles. Phys. Rev. Lett. 82, 3198–3201 (1999).
Hori, M. et al. Two photon laser spectroscopy of antiprotonic helium and the antiproton to electron mass ratio. Nature 475, 484–488 (2011).
Ahmadi, M. et al. An improved limit on the charge of antihydrogen from stochastic acceleration. Nature 529, 373–376 (2016).
Kostelecky, V. A. & Russell, N. Data-tables on Lorentz and CPT Violation. Rev. Mod. Phys. 83, 11–31 (2011).
Ulmer, S. et al. High-precision comparison of the antiproton-to-proton charge-to-mass ratio. Nature 524, 196–199 (2015).
Pierce, J. R. Theory and Design of Electron Beams D. van Nostrand Co. (1949).
Wineland, D. J. & Dehmelt, H. G. Principles of the stored ion calorimeter. J. Appl. Phys. 46, 919–930 (1975).
Brown, L. S. & Gabrielse, G. Precision spectroscopy of a charged particle in an imperfect Penning trap. Phys. Rev. A 25, 2423–2425 (1982).
Dehmelt, H. G. & Ekstroem, P. Continuous Stern-Gerlach effect: principle and idealized apparatus. Proc. Natl Acad. Sci 83, 2291–2294 (1986).
DiSciacca, J. et al. One-particle measurement of the antiproton magnetic moment. Phys. Rev. Lett. 110, 130801 (2013).
Smorra, C. et al. The BASE experiment. Eur. Phys. J. Special Topics 224, 3055–3108 (2015).
Belochitskii, P., Eriksson, T. & Maury, S. The CERN antiproton decelerator (AD) in 2002: status, progress and machine development results. Nucl. Instrum. Meth. Phys. Res. B 214, 176–180 (2004).
Gabrielse, G., Haarsma, L. & Rolston, L. S. Open-endcap Penning traps for high precision experiments. Int. J. Mass Spectrom. 88, 319–332 (1989).
Ulmer, S. et al. A cryogenic detection system at 28.9 MHz for the non-destructive observation of a single proton at low particle energy. Nucl. Instrum. Meth. Phys. Res. A 705, 55–60 (2013).
Smorra, C. et al. A reservoir trap for antiprotons. Int. J. Mass Spectrom. 389, 10–13 (2015).
Savard, T. A., O’Hara, K. M. & Thomas, J. E. Laser-noise-induced heating in far-off resonance optical traps. Phys. Rev. A 56, R1095–R1098 (1997).
Mooser, A. et al. Resolution of single spin flips of a single proton. Phys. Rev. Lett. 110, 140405 (2013).
Ulmer, S. et al. Observation of spin flips with a single trapped proton. Phys. Rev. Lett. 106, 253001 (2011).
Brown, L. S. Geonium lineshape. Ann. Phys. 159, 62–98 (1985).
Cornell, E. A., Weisskoff, R. M., Boyce, K. R. & Pritchard, D. E. Mode coupling in a Penning trap: π pulses and a classical avoided crossing. Phys. Rev. A 41, 312–315 (1990).
Mooser, A. et al. High-precision measurement of the magnetic moment of the proton. Nature 509, 596–599 (2014).
Bluhm, R. et al. CPT and Lorentz tests in Penning traps. Phys. Rev. D 57, 3932–3943 (1998).
Ding, Y. & Kostelecký, V. A. Lorentz-violating spinor electrodynamics and Penning traps. Phys. Rev. D 94, 056008 (2016).
We acknowledge technical support by the Antiproton Decelerator group, CERN’s cryolab team, and all other CERN groups which provide support to Antiproton Decelerator experiments. We acknowledge financial support by RIKEN Initiative Research Unit Program, RIKEN President Funding, RIKEN Pioneering Project Funding, RIKEN FPR Funding, the RIKEN JRA Program, the Grant-in-Aid for Specially Promoted Research (no. 24000008) of MEXT, the Max-Planck Society, the EU (ERC Advanced Grant No. 290870-MEFUCO), the Helmholtz-Gemeinschaft, and the CERN-fellowship programme.
The authors declare no competing financial interests.
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Nagahama, H., Smorra, C., Sellner, S. et al. Sixfold improved single particle measurement of the magnetic moment of the antiproton. Nat Commun 8, 14084 (2017). https://doi.org/10.1038/ncomms14084
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