Photonics Research, 2022, 10 (4): 04001022, Published Online: Apr. 26, 2022  

Memory-assisted quantum accelerometer with multi-bandwidth

Author Affiliations
1 State Key Laboratory of Precision Spectroscopy, School of Physics and Electronic Science, East China Normal University, Shanghai 200062, China
2 Shanghai Research Center for Quantum Sciences, Shanghai 201315, China
3 School of Physics and Astronomy, Shanghai Jiao Tong University, and Tsung-Dao Lee Institute, Shanghai 200240, China
4 Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan 030006, China
5 e-mail: chyuan@phy.ecnu.edu.cn
6 e-mail: wpzhang@phy.ecnu.edu.cn
Abstract
The accelerometer plays a crucial role in inertial navigation. The performance of conventional accelerometers such as lasers is usually limited by the sensing elements and shot noise limitation (SNL). Here, we propose an advanced development of an accelerometer based on atom–light quantum correlation, which is composed of a cold atomic ensemble, light beams, and an atomic vapor cell. The cold atomic ensemble, prepared in a magneto-optical trap and free-falling in a vacuum chamber, interacts with light beams to generate atom–light quantum correlation. The atomic vapor cell is used as both a memory element storing the correlated photons emitted from cold atoms and a bandwidth controller through the control of free evolution time. Instead of using a conventional sensing element, the proposed accelerometer employs interference between quantum-correlated atoms and light to measure acceleration. Sensitivity below SNL can be achieved due to atom–light quantum correlation, even in the presence of optical loss and atomic decoherence. Sensitivity can be achieved at the ng/Hz level, based on evaluation via practical experimental conditions. The present design has a number of significant advantages over conventional accelerometers such as SNL-broken sensitivity, broad bandwidth from a few hundred Hz to near MHz, and avoidance of the technical restrictions of conventional sensing elements.

1. INTRODUCTION

Accelerometers have extensively been applied as weak force probes, especially in situations that involve inertial navigation, land-based resource exploration, and seismic monitoring [14]. There are many types of accelerometers, including capacitive [5,6], piezoelectric [7], tunnel-current [8], thermal [9], and optical [1016]. Almost all utilize mass-spring-damper systems as displacement sensors [17]. The performance of such accelerometers highly relies on fabrication of the displacement sensors, which directly results in technical limitations to the bandwidth, quality factor Qf, and noise level [18]. Among numerous accelerometers, optical ones have attracted much attention due to their high sensitivity. However, the sensitivity of such accelerometers is fundamentally subject to shot noise limitation (SNL) [19,20]. Developing methods and technologies to break the SNL and remove the technical limitations of conventional displacement sensors is desired for the innovation of accelerometers.

In this paper, we present a memory-assisted quantum accelerometer (MQA), which consists of atomic ensembles, light beams, and optical elements. The MQA has three advantages over conventional accelerometers. First, instead of a mass-spring-damper system, a cold atomic ensemble [21] acts as the displacement sensor, which can avoid the technical restrictions of a mass-spring-damper system. Second, the SNL-broken sensitivity in measurement of acceleration can be achieved by the quantum interference of correlated atoms and light [2224]. The third merit is that the accelerometer allows a tunable bandwidth, which is determined by the controllable memory time tM of the correlated photons stored in a memory element [2527]. We calculate and analyze the sensitivity and bandwidth of the MQA. An inverse relation exists between sensitivity and bandwidth. Sensitivity can reach below the SNL in the range of bandwidth from a few hundred Hz to near MHz due to atom–light quantum correlation, even in the presence of the optical losses and atomic decoherence. An optimal ng/Hz-level sensitivity without loss is anticipated at frequencies 100  Hz for a feasible average atomic number and an available memory time tM=10  ms.

2. RESULTS

2.1 A. Principle of MQA

A schematic diagram of the accelerometer is shown in Fig. 1. The cores are composed of two atomic systems: cold ensemble A1 and atomic vapor cell A2. A1 is prepared in a magneto-optical trap (MOT), free-falling in the vacuum chamber to generate atom (S^a1(1))–light (a^1) quantum correlation and realize atom–light interference via two Raman scattering processes. Atomic vapor cell A2, containing thermal atoms and buffer gas, is a memory element to store the correlated photonic signal a^1 from A1, which acts as a bandwidth modulator. In principle, the memory element can be any quantum memorizer for photons with long coherence times, such as rare-earth-doped crystals [28,29]. All optical devices including the vacuum chamber and memory element are fixed onto a mobile platform. When MOT is turned on, A1 and A2 move together with the platform. The distance L between two atomic systems is fixed as L0 at any velocity or acceleration of the platform. When MOT is turned off, A1 is free-falling in vacuum, acting as the static frame reference, and A2 remains moving with the platform at acceleration a. L=L0+ΔL changes with acceleration, where ΔL is the displacement due to acceleration a. ΔL=12aT2, where T is the free-evolution time duration after the first Raman scattering process and before the second one, that is, the atom–light “wave-splitting” and “wave-recombining” processes, respectively. T is independent of acceleration a and the velocity of the platform. ΔL can be achieved via atom–light quantum interference. Acceleration a can be achieved by the variation of ΔL with time T. The acceleration sensitivity is no longer limited by the performance of the mass-spring-damper system. This is one of the advantages of our scheme.

Fig. 1. Schematic diagram of the MQA. The cold atomic ensemble A1 is free-falling in the vacuum chamber. Atomic vapor A2, the vacuum chamber, and all optical elements are fixed on and move with the platform at acceleration a. The distance between A1 and A2 is changed from L0 to L0+ΔL. ΔL is the acceleration-dependent displacement achieved via atom–light quantum interference, which is realized in three steps. Step 1: a^1 and S^a1(1) are generated by the first stimulated Raman scattering (SRS) in A1 via input seed a^0 and Raman pump P1. The atomic spin wave is S^aj(i), where superscript i (i=1, 2) indicates different atomic ensemble A1 or A2, and subscript j (j=1, 2, 3) represents the evolution state at different times of atomic ensemble Ai. Step 2: a^1 is stored in A2 as S^a1(2) is driven by the strong write pulse W. After memory time tM, S^a2(2), evolved from S^a1(2) due to atomic decay, is retrieved back to a^2 by the read pulse R. Step 3: S^a2(1), evolved from S^a1(1) during the memory time, and a^2 interfere by the second SRS via Raman pump P2.

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The accelerometer is operated in three steps: generation of atom–light quantum correlation via the first Raman scattering in A1, atomic memory in A2, and acceleration acquisition via atom–light interference. Below, we describe the calculation and analysis in detail.

2.2 B. Generation of Quantum Correlation

Atom–light quantum correlation is generated via stimulated Raman scattering (SRS) in A1, which is effectively an atom–light wave-splitting process. A Stokes seed a^0 and a strong Raman beam P1 interact with the atoms in A1 to generate Stokes light a^1 and atomic spin wave S^a1(1) [30]. The input–output relation of SRS can be written as a^1=G1a^0+g1S^a0(1)eiθP1, S^a1(1)=G1S^a0(1)+g1a^0eiθP1. S^a0(1) describes the initial spin wave, which starts from the ground state of the atomic ensemble. G1 and g1 are Raman gains that satisfy G12=g12+1, and θP1 is the phase of beam P1.

After SRS, the generated Stokes signal a^1, transmitting out of A1 and entering A2, quantum-mechanically correlates with the induced atomic spin wave S^a1(1) that remains in A1. The intensity fluctuations of both a^1 and S^a1(1) are amplified to the level above SNL as a result of Raman amplification. But the relative intensity fluctuation S^a1(1)S^a1(1)a^1a^1 is squeezed below SNL by 2G121 times, due to the quantum correlation between a^1 and S^a1(1) (see Appendix A).

2.3 C. Atomic Memory

Stokes signal a^1 propagates into atomic vapor cell A2, and then is stored as atomic spin wave S^a1(2) in the writing process driven by the write beam W. The evolution of the spin wave obeys the Heisenberg propagation equation tS^a1(2)=i(|ΩW|2Δδ+ΔkW·v)S^a1(2)iχa^1,where ΩW is the Rabi frequency of W, Δ is single-photon detuning, δ is two-photon detuning, ΔkW=kWks is the wave vector difference of W and a^1, χ is the Raman coupling coefficient, v is the center of mass velocity of the atoms, and ΔkW·v is the Doppler frequency shift. The solution to Eq. (1) is (see Appendix B) S^a1(2)=(iηWeiθWa^1eiφ+eiθW01ηWS^a0(2))×ei(|ΩW|2Δδ+ΔkW·v)tW/2,where ηW is the writing efficiency determined by the coupling coefficient χ; φ=ksL0, and ks=2π/λs, with λs the Stokes wavelength. θW is the phase of the write field W; tW is the writing time. S^a0(2) is the initial spin wave in A2, which is in the vacuum state. The term |ΩW|2Δ corresponds to the Stark effect. |ΩW|2Δ, δ, and θW0 are acceleration-independent parameters, which can be considered as fixed values.

After memory time tM, S^a2(2), evolving from S^a1(2) with decay rate Γ2 due to atomic collisions, can be read out as Stokes a^2 with efficiency ηR by the read beam R. Assuming a reading time tRtW and defining η=ηWηR, Stokes a^2 can be simplified as (see Appendix C) a^2=ηei(Δφa+Δφvφ0)eΓ2tMa^1+1ηe2Γ2tMV^,where V^ is the effective vacuum field. The phase offset φ0 can be safely set to zero since it is independent of the measured acceleration a (see Appendix C). The velocity-dependent phase shift Δφv=ΔkW·vtM is induced by the Doppler effect due to the center of mass motion of atoms. The acceleration-dependent phase shift ΔφaΔkatM(tMtW)/2ks(ΔL), where Δk is the projection of ΔkW along the acceleration. ΔL=12aT2=12a(t1+t2+tM)2, where t1 and t2 are the flying times of the Stokes light between cold ensemble A1 and vapor cell A2 forth and back, respectively. Normally, ks|Δk| and tMtW,Rt1,2, i.e., ΔφaksatM2/2. The phase shift of the Stokes field can be measured through atom–light interference between the readout field a^2 returning to A1 and atomic spin wave S^a1(1) remaining in A1.

2.4 D. Atom–Light Interference

When a2 returns to A1, the atomic spin wave S^a1(1) has experienced free evolution for the duration of memory time tM. As a result, the spin wave has the form S^a2(1)=S^a1(1)eΓ1tM+F^(1), with Doppler dephasing being negligible in the cold ensemble (see Appendix D), where F^(1) is the quantum Langevin operator, reflecting the collision-induced fluctuation and satisfying [F^(1),F^(1)]=1e2Γ1tM [24]. The decay rate Γ1 represents the decoherence effect due to atomic collisions and flying off the laser beam. For a general cold atomic ensemble, the root mean square velocity is ∼ several cm/s, and the diffusion of cold atoms is 1.0mm after a memory time of 10 ms. The whole atomic ensemble will drop 0.5 mm in gravity direction after 10 ms. The mismatch of the spot expansion and dropping of the cold atomic ensemble plays an opposite role in quantum enhancement by destroying atom–light quantum correlation. However, these two effects can be solved using laser beam expansion and light path adjustment in the experiment.

a^2 and S^a2(1) interact with each other in A1, which is driven by P2 with θP2=θP1, and generate Stokes a^out with atomic spin wave S^aout(1) by a second Raman scattering. Setting T1eΓ1tM and T2eΓ2tM, we have the final output a^out=ς1a^0+ς2S^a0(1)+ς3V^+ς4f^ (see Appendix D), where f^ is the normalized noise operator, f^F^(1)/1T1, ς1g1g2T1G1G2ηT2ei(Δφa+Δφv), ς2eiθP2[G1g2T1g1G2ηT2ei(Δφa+Δφv)], ς3G21ηT2, and ς4g2eiθP21T1.

Here, we emphasize that atomic vapor cell A2 moves with the platform. To achieve acceleration, this requires that the vapor atoms and cell wall move as a whole, which implies that a robust thermal equilibrium between the atoms and the cell wall is essential during memory time. This is realized with the assistance of buffer gas in the vapor cell. In a room-temperature cell with buffer gas at several-Torr pressure, the mean free path of atoms is μm, with vrms300  m/s. This allows the vapor atoms to remain in thermal equilibrium with the cell wall under acceleration (see Appendix D). The ground-state coherence can be preserved for up to 108 collisions between the buffer gas and atoms [31]. The buffer gas can separate atoms and decrease the collision between them. Therefore, the value of the decay rate Γ2 is small [32]. Doppler dephasing (Δφv) can be avoided by adopting near-degenerate Zeeman two-photon transitions, as shown in Appendix E. Now the Stokes field a^out, containing only phase Δφa, can be measured through homodyne detection (HD).

2.5 E. Acquisition of Acceleration

All optical devices including the vacuum chamber and memory element are fixed onto a mobile platform. When MOT is turned on, cold ensemble A1 and atomic vapor cell A2 move together with the platform. The distance L between two atomic systems is fixed as L0 at any velocity v0 or acceleration of platform a. When MOT is turned off, the movement of the cold atomic ensemble is independent of the platform. The cold atomic ensemble moves in uniform motion with constant velocity v0. The atomic vapor still moves with the platform under acceleration. Its velocity changes with acceleration, and the distance between two atomic systems also changes from L0 to L0+ΔL, where ΔL=Δv0T+12aT2 is the displacement due to acceleration, with Δv0 the initial relative velocity of A1 and A2, and T is independent of the acceleration a and velocity of the platform. ΔL causes a phase shift. Here, Δv0 is zero because the velocities of two atomic systems are the same before MOT is turned off. Acceleration can be measured in the direction of the seed and pump fields passing the cold ensemble, and it can be expressed in terms of the phase Δφa as follows: a=λsΔφaπtM2.

Using the HD of the quadrature of Stokes field a^out, acceleration is measured, and sensitivity is given by (see Appendix E) Δa=1QeΔaSNL,where Qe is the quantum enhancement factor. Sensitivity breaks the SNL when Qe>1. In general, Qe=2G1G2G12+g12ηeΓ2tMn=14|ςn0|2,where ςn0 are the values of ςn(n=1,,4) at the dark fringe. Defining N0a^0a^0 for the input mean photon number, we work out the SNL for acceleration measurement: ΔaSNL=λsπ(G12N0+g12N0)tM2,where G12N0 and g12N0 are the particle numbers of Stokes signal a^1 and atomic spin wave S^a1(1), respectively. Acceleration sensitivity depends on the phase sensitivity of atom–light interference, whose SNL is determined by the total phase-sensitive particle number (G12+g12)N0 of two interference beams, signal a^1 and atomic spin wave S^a1(1). Here, quantum correlation between S^a1(1) and a^1 is key to breaking the SNL in acceleration sensitivity.

2.6 F. Accelerometer Sensitivity

To obtain the best sensitivity in the acceleration measurement, it is essential to decrease ΔaSNL itself and increase quantum enhancement factor Qe. In general, ΔaSNL can be reduced by increasing the input particle number N0 and prolonging memory time tM. However, this is usually constrained in realistic experiments. In this sense, quantum enhancement provides just an alternative way to further improve sensitivity through SNL breaking.

Factor Qe is complicated, and we numerically analyze the behavior of Qe in Fig. 2(a) as a function of T1 and T2 (T2ηT2) for a different Raman gain G2 under a given G1. The larger T1, T2, and G2, the larger Qe. The red solid curves with Qe=1 in Fig. 2(a) set a critical boundary of the SNL, which reflects a balance of competition between losses and quantum correlation. The region within the curves marks Qe>1, representing quantum enhancement.

Fig. 2. (a) Quantum enhancement factor Qe versus T1 and T2 when G2=2 and 8, respectively. (b) Sensitivity versus s and G2 when T1=0.5 and 1, respectively. s=T2/T1 is the ratio of two beams’ losses. The red curves mark Qe=1 for SNL. Sensitivities within the red curves can beat the SNL. Parameter settings: N0=106, G1=8, λs=795  nm, and tM=1  ms.

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On the other hand, in terms of Eq. (7), the gains G1, g1, and N0 determine the SNL for acceleration sensitivity. To set an SNL as low as possible in the measurement, it is essential to achieve gains as high as possible. Hence, we assume G11 for numeric analysis. Sensitivity Δa is shown as a function of s=T2/T1 and G2 under given G1 and N0 in Fig. 2(b). The quantum enhancing region associated with Qe>1 is marked as the same within the red solid curves. Obviously, high gain G2 and low losses can greatly enhance sensitivity due to the sufficient exploitation of quantum correlation. In addition, quantum enhancement of sensitivity well exhibits a loss tolerance, and highly depends on the balance of losses defined by the ratio s. The best sensitivity appears near s=1 for high gains, where the atomic and optical losses are well balanced. In particular, sensitivity can keep beating the SNL through quantum enhancement until losses approach the limit T1T20.5.

2.7 G. Measurement Bandwidth

Sensitivity Δa is the result determined by one single-shot measurement approximately completed in memory time tM, which gives the upper limit of the MQA’s frequency fmax=1/tM. In realistic experiments, if the setup of the system takes time ts, and stable operation for M-times repeating measurements takes time to=MtM, then the overall sensitivity of the accelerometer is given by ΔaoΔa/feff(fmax)3/2, where feff=fmaxto/(ts+to).

There is a trade-off between sensitivity Δao and bandwidth, as shown in Fig. 3. In general, sensitivity Δao has a 3/2 power-law dependence of bandwidth, indicating that sensitivity degrades in the high-frequency region. In Fig. 3, we see that when the losses of the system remain low enough, the accelerometer exhibits well the quantum advantage to achieve an SNL below sensitivity with a broad range of frequencies. Sensitivity rises above the SNL at low frequencies with losses. As a comparison, some available data of sensitivities for previously reported accelerometers are labeled in Fig. 3 as well. Overall, the MQA has great potential in highly-sensitive measurements of acceleration.

Fig. 3. Sensitivity as a function of bandwidth under the conditions G=8, N0=106, λs=795  nm, and η=1. The data of other reported accelerometers are given as comparison. Dark green diamond: microchip optomechanical accelerometer [14]. Orange pentagram: micromechanical capacitive accelerometer [18]. Purple hexagram: MEMS accelerometer [6]. Gray circle: optical accelerometer [15].

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With the available experimental conditions, e.g., N0=106 per pulse, Raman gain G1=8, G2=2, MOT cycle ts=30  ms [33,34], memory time tM10  ms [35,36], we can achieve single-shot sensitivity 23 ng at frequency 100 Hz. Finally, the sensitivity is 4.6  ng/Hz.

For the traditional interferometric accelerometer, the only method to improve sensitivity at a high bandwidth is to increase the quality factor Qf of the damper, which is technically hard to implement. In our scheme, sensitivity at a high bandwidth can be improved by increasing the Raman gain or the number of initial photons and trapping cold atoms, making it much easier to operate.

3. DISCUSSION AND CONCLUSION

We present an innovative principle for a quantum enhanced accelerometer. There are several significant advantages over other interferometer-based accelerometers: broad bandwidth, SNL below sensitivity, and mechanics-free sensing flexibility compared to mass-spring-damper systems. The dynamic range of acceleration depends on that of phase measurement, which is from the phase sensitivity to 2π. With λs of 795 nm, the dynamic range of acceleration of a single shot is from 23 ng to 1.59 mg with tM=10  ms, and from 2.3g to 1.59×105g with tM=1.0μs. It can be seen that the dynamic range is 48  dB with a fixed tM. Furthermore, the measurable range of acceleration is from 23 ng to 1.59×105g, 128  dB, only by adjusting tM to suitable values. In future applications of the MQA, a long atomic coherence time of A1,2 and high memory efficiency η are crucial to achieve high sensitivity. Large optical depths for A1,2 are required to ensure enough atomic numbers to achieve a large input particle number N0 and high gains, so as to lower the level of ΔaSNL and raise the quantum enhancement factor Qe.

We emphasize that this work building the MQA is based on quantum correlation. The physics behind this is universal. Hence, the principle presented in this paper is not limited only to the atom–light coupling system, but can be extended to other systems that can generate and preserve quantum correlation, such as rare-earth-doped crystals [28,29]. Specifically, one crystal can be trapped and released to generate light–crystal correlation. The other crystal, fixed on platform, acts as the quantum memorizer. Acceleration sensitivity also depends on the phase-sensitive particle number and memory time.

References

[1] de Brito AndreP. S.VarumH., Accelerometers: Principles, Structure and Applications (Nova Science, 2013).

[2] BaoM., Micro Mechanical Transducers: Pressure Sensors, Accelerometers and Gyroscopes (Elsevier, 2000).

[3] C.-W. Tan, S. Park. Design of accelerometer-based inertial navigation systems. IEEE Trans. Instrum. Meas., 2005, 54: 2520-2530.

[4] D. Jiang, W. Zhang, F. Li. All-metal optical fiber accelerometer with low transverse sensitivity for seismic monitoring. IEEE Sens. J., 2013, 13: 4556-4560.

[5] C. Acar, A. M. Shkel. Experimental evaluation and comparative analysis of commercial variable-capacitance MEMS accelerometers. J. Micromech. Microeng., 2003, 13: 634-645.

[6] DongY.ZwahlenP.NguyenA. M.FrosioR.RudolfF., “Ultra-high precision MEMS accelerometer,” in 16th International Solid-State Sensors, Actuators and Microsystems Conference (2011), pp. 695698.

[7] S. Tadigadapa, K. Mateti. Piezoelectric MEMS sensors: state-of-the-art and perspectives. Meas. Sci. Technol., 2009, 20: 092001.

[8] C. Liu, A. M. Barzilai, J. K. Reynolds, A. Partridge, T. W. Kenny, J. D. Grade, H. K. Rockstad. Characterization of a high-sensitivity micromachined tunneling accelerometer with micro-g resolution. J. Microelectromech. Syst., 1998, 7: 235-244.

[9] R. Mukherjee, J. Basu, P. Mandal, P. K. Guha. A review of micromachined thermal accelerometers. J. Micromech. Microeng., 2017, 27: 123002.

[10] U. Krishnamoorthy, R. H. Olsson, G. R. Bogart, M. S. Baker, D. W. Carr, T. P. Swiler, P. J. Clews. Inplane MEMS-based nano-g accelerometer with sub-wavelength optical resonant sensor. Sens. Actuators A Phys., 2008, 145: 283-290.

[11] ZandiK.WongB.ZouJ.KruzeleckyR. V.JamrozW.PeterY., “In-plane silicon-on-insulator optical MEMS accelerometer using waveguide Fabry-Perot microcavity with silicon/air Bragg mirror,” in IEEE 23rd International Conference on Micro Electro Mechanical Systems (MEMS) (IEEE, 2010), pp. 839842.

[12] W. Noell. Applications of SOI-based optical MEMS. IEEE J. Sel. Top. Quantum Electron., 2002, 8: 148-154.

[13] T. A. Berkoff, A. D. Kersey. Experimental demonstration of a fiber Bragg grating accelerometer. IEEE Photon. Technol. Lett., 1996, 8: 1677-1679.

[14] A. G. Krause, M. Winger, T. D. Blasius, Q. Lin, O. Painter. A microchip optomechanical accelerometer. Nat. Photonics, 2012, 6: 768-772.

[15] Y. Yang, X. Li, K. Kou, L. Zhang. Optical accelerometer design based on laser self-mixing interference. Proc. SPIE, 2015, 9369: 93690R.

[16] Y. L. Li, P. F. Barker. Characterization and testing of a micro-g whispering gallery mode optomechanical accelerometer. J. Lightwave Technol., 2018, 36: 3919-3926.

[17] N. Lagakos, T. Litovitz, P. Macedo, R. Mohr, R. Meister. Multimode optical fiber displacement sensor. Appl. Opt., 1981, 20: 167-168.

[18] S. Chen, H. Xu. Design analysis of a high-Q micromechanical capacitive accelerometer system. IEICE Electron. Express, 2017, 14: 20170410.

[19] M. D. LeHaye, O. Buu, B. Camarota, K. C. Schwab. Approaching the quantum limit of a nanomechanical resonator. Science, 2004, 304: 74-77.

[20] J. P. Dowling. Quantum optical metrology-the lowdown on high-N00N states. Contemp. Phys., 2008, 49: 125-143.

[21] P. Qian, Z. Gu, R. Cao, R. Wen, Z. Y. Ou, J. F. Chen, W. Zhang. Temporal purity and quantum interference of single photons from two independent cold atomic ensembles. Phys. Rev. Lett., 2016, 117: 013602.

[22] B. Chen, C. Qiu, S. Chen, J. Guo, L. Q. Chen, Z. Y. Ou, W. Zhang. Atom-light hybrid interferometer. Phys. Rev. Lett., 2015, 115: 043602.

[23] X. Feng, Z. Yu, B. Chen, S. Chen, Y. Wu, D. Fan, C.-H. Yuan, L. Q. Chen, Z. Y. Ou, W. Zhang. Reducing the mode-mismatch noises in atom-light interactions via optimization of the temporal waveform. Photon. Res., 2020, 8: 1697-1702.

[24] Z.-D. Chen, C.-H. Yuan, H.-M. Ma, D. Li, L. Q. Chen, Z. Y. Ou, W. Zhang. Effects of losses in the atom-light hybrid SU(1,1) interferometer. Opt. Express, 2016, 24: 17766-17778.

[25] C. Liu, Z. Dutton, C. H. Behroozi, L. V. Hau. Observation of coherent optical information storage in an atomic medium using halted light pulses. Nature, 2001, 409: 490-493.

[26] M. Hosseini, B. M. Sparkes, G. Campbell, P. K. Lam, B. C. Buchler. High efficiency coherent optical memory with warm rubidium vapour. Nat. Commun., 2011, 2: 174.

[27] J. Guo, X. Feng, P. Yang, Z. Yu, L. Q. Chen, C.-H. Yuan, W. Zhang. High-performance Raman quantum memory with optimal control in room temperature atoms. Nat. Commun., 2019, 10: 148.

[28] Y. Ma, Y.-Z. Ma, Z.-Q. Zhou, C.-F. Li, G.-C. Guo. One-hour coherent optical storage in an atomic frequency comb memory. Nat. Commun., 2021, 12: 2381.

[29] M. Zhong, M. P. Hedges, R. L. Ahlefeldt, J. G. Bartholomew, S. E. Beavan, S. M. Wittig, J. J. Longdell, M. J. Sellars. Optically addressable nuclear spins in a solid with a six-hour coherence time. Nature, 2015, 517: 177-180.

[30] C. H. van der Wal, M. D. Eisaman, A. André, R. L. Walsworth, D. F. Phillips, A. S. Zibrov, M. D. Lukin. Atomic memory for correlated photon states. Science, 2003, 301: 196-200.

[31] W. Happer. Optical pumping. Rev. Mod. Phys., 1972, 44: 169-249.

[32] S. Manz, T. Fernholz, J. Schmiedmayer, J.-W. Pan. Collisional decoherence during writing and reading quantum states. Phys. Rev. A, 2007, 75: 040101.

[33] S. Zhang, J. F. Chen, C. Liu, S. Zhou, M. M. T. Loy, G. K. L. Wong, S. Du. A dark-line two-dimensional magneto optical trap of 85Rb atoms with high optical depth. Rev. Sci. Instrum., 2012, 83: 073102.

[34] A. G. Radnaev, Y. O. Dudin, R. Zhao, H. H. Jen, S. D. Jenkins, A. Kuzmich, T. A. B. Kennedy. A quantum memory with telecom-wavelength conversion. Nat. Phys., 2010, 6: 894-899.

[35] X.-H. Bao, A. Reingruber, P. Dietrich, J. Rui, A. Duck, T. Strasse, L. Li, N.-L. Liu, B. Zhao, J.-W. Pan. Efficient and long-lived quantum memory with cold atoms inside a ring cavity. Nat. Phys., 2012, 8: 517-521.

[36] O. Katz, O. Firstenberg. Light storage for one second in room-temperature alkali vapor. Nat. Commun., 2018, 9: 2074.

[37] L.-M. Duan, M. D. Lukin, J. I. Cirac, P. Zoller. Long-distance quantum communication with atomic ensembles and linear optics. Nature, 2001, 414: 413-418.

[38] K. Hammerer, A. S. Sorensen, E. S. Polzik. Quantum interface between light and atomic ensembles. Rev. Mod. Phys., 2010, 82: 1041.

[39] Y. Yoshikawa, Y. Torii, T. Kuga. Superradiant light scattering from thermal atomic vapors. Phys. Rev. Lett., 2005, 94: 083602.

[40] B. Zhao, Y. A. Chen, X. H. Bao, T. Strassel, C. S. Chuu, X. M. Jin, J. Schmiedmayer, Z. S. Yuan, S. Chen, J. W. Pan. A millisecond quantum memory for scalable quantum networks. Nat. Phys., 2009, 5: 95-99.

Zhifei Yu, Bo Fang, Liqing Chen, Keye Zhang, Chun-Hua Yuan, Weiping Zhang. Memory-assisted quantum accelerometer with multi-bandwidth[J]. Photonics Research, 2022, 10(4): 04001022.

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