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超导动态电感单光子探测器的噪声处理

黄典 戴万霖 王轶文 贺青 韦联福

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超导动态电感单光子探测器的噪声处理

黄典, 戴万霖, 王轶文, 贺青, 韦联福

Noise processing of superconducting kinetic inductance single photon detector

Huang Dian, Dai Wan-Lin, Wang Yi-Wen, He Qing, Wei Lian-Fu
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  • 噪声是影响弱信号检测器件性能指标的主要因素之一, 而最优滤波算法是白噪声背景中自适应提取弱有用信号的一种常见处理方法. 本文针对极低温环境下微波动态电感探测器(microwave kinetic inductance detector, MKID)光子弱信号响应的噪声特性, 在改进噪声模型的基础上利用最优滤波算法改进了探测信号的噪声处理. 结果表明, 经过改进噪声模型的算法处理, MKID的能量分辨(单光子探测器的主要性能指标之一)得到了15%左右的提升, 实现了0.26 eV的红外单光子能量分辨.
    Noise is one of the main factors affecting the performance index of weak signal detection devices, and the optimal filtering algorithm is an effective method to adaptively extract various useful weak signals from the white noise background. In order to improve the performance of single photon detector (especially the photon number resolution ability), one mainly focuses on the optimization of detector hardware such as the optimization of photosensitive materials and the technology of device fabrication. However, in this paper the performance of microwave kinetic Inductance detector (MKID) in the way of data processing is improved. Considering the fact that the template of light pulse signal in the optimal filtering algorithm is obtained by taking the average, we replace the noise model in the original optimal filtering algorithm with the white noise model and the whitening noise model. Then we process the photon response data that are detected by the MKID in an extremely low temperature environment. The results show that the energy resolution (one of the main performance indexes of single photon detector) of MKID is improved by about 15%, and we achieve an infrared single photon energy resolution of 0.26 eV. In this paper, the application and development trends of superconducting single photon detector are briefed. Then, how the MKID responds to weak coherent optical signal in low temperature environment, and the process of signal conversion, acquisition and output are explained in detail. According to the optimal filtering algorithm, we use different noise models to analyze the results of the signals detected by MKID. After that, we count the optimal amplitude multiple, perform the Gaussian fitting analysis on the statistical graph, and compare the energy resolution with the photon number resolution of the optimal filtering algorithm under different noise models. As a result, we find that under the white noise model, the optimal filtering algorithm is used to obtain the best result for MKID processing, and high energy resolution can be achieved.
      通信作者: 韦联福, lfwei@swjtu.edu.cn
    • 基金项目: 国家自然科学基金 (批准号: 11974290, 61871333) 资助的课题
      Corresponding author: Wei Lian-Fu, lfwei@swjtu.edu.cn
    • Funds: Project supported by the National Natural Science Foundation of China (Grant Nos. 11974290, 61871333)
    [1]

    Hiskett P A, Lita A E, Hughes R J, Rosenberg D, Miller A J, Nordholt J E, Peterson C G, Nam S 2006 New J. Phys. 8 193Google Scholar

    [2]

    Knill E, Laflamme R, Milburn G J 2001 Nature 409 46Google Scholar

    [3]

    Zwinkels J C, Ikonen E, Fox N P, Ulm G, Rastello ML 2010 Metrologia 47 R15Google Scholar

    [4]

    周品嘉 2014 博士学位论文 (成都: 西南交通大学)

    Zhou P J 2014 Ph. D. Dissertation (ChengDu: Southwest Jiaotong University) (in Chinese)

    [5]

    Enss C 2005 Cryogenic Particle Detection 1 (Berlin: Springer-Verlag) pp417−452

    [6]

    Zheng F, Xu R, Zhu G, Jin B, Kang L, Xu W, Chen J, Wu P 2016 Sci. Rep. 6 22710Google Scholar

    [7]

    张青雅, 董文慧, 何根芳, 李铁夫, 刘建设, 陈炜 2014 物理学报 63 200303Google Scholar

    Zhang Q Y, Dong W H, He G F, Li T F, Liu J S, Chen W 2014 Acta Phys. Sin. 63 200303Google Scholar

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    Day P K, Leduc H G, Mazin B A, Vayonakis A, Zmuidzinas J 2003 Nature 425 817Google Scholar

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    李春光, 王佳, 吴云, 王旭, 孙亮, 董慧, 高波, 李浩, 尤立星, 林志荣, 任洁, 李婧, 张文, 贺青, 王轶文, 韦联福, 孙汉聪, 王华兵, 李劲劲, 屈继峰 2021 物理学报 70 018501Google Scholar

    Li C G, Wang J, Wu Y, Wang X, Sun L, Dong H, Gao B, Li H, You L X, Lin Z R, Ren J, Li J, Zhang W, He Q, Wang Y W, Wei L F, Sun H C, Wang H B, Li J J, Qu J F 2021 Acta Phys. Sin. 70 018501Google Scholar

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    周品嘉, 王轶文, 韦联福 2014 物理学报 63 070701Google Scholar

    Zhou P J, Wang Y W, Wei L F 2014 Acta Phys. Sin. 63 070701Google Scholar

    [11]

    Lita A E, Miller A J, Nam S W 2008 Opt. Express 16 3032Google Scholar

    [12]

    Lolli L, Taralli E, Portesi C, Monticone E, Rajteri M 2013 Appl. Phys. Lett. 103 041107Google Scholar

    [13]

    Yang X Y, Li H, Zhang W J, You L X, Zhang L, L iu, X Y, Wang Z, Peng W, Xie X M, Jiang M H 2014 Opt. Express 22 16267Google Scholar

    [14]

    Li X, Tan J R, Zheng K M, Zhang L B, Zhang J L, He W J, Huang P W, Li H C, Zhang B, Chen Q, Ge R, Guo S Y, Huang T, Jia X Q, Zhao Q Y, Tu X C, Kang L, Chen J, Wu P H 2020 Photonics Research 8 637Google Scholar

    [15]

    Geng Y, Zhang W, Li P Z, Zhong J Q, Wang Z, Miao W, Ren Y, Wang J F, Yao Q J, Shi S C 2020 J. Low Temp. Phys. 199 556Google Scholar

    [16]

    Guo W, Liu X, Wang Y, Wei Q, Wei L F, Hubmayr J, Fowler J, Ullom J, Vale L, Vissers M R, Gao J 2017 Appl. Phys. Lett. 110 212601Google Scholar

    [17]

    Liu X, Guo W, Wang Y, Dai M, Wei L F, Dober B, McKenney C M, Hilton G C, Hubmay J, Austermann J E, Ullom J N, Gao J, Ullom J N 2017 Appl. Phys. Lett. 111 252601Google Scholar

    [18]

    Szymkowiak A E, Kelley R L, Moseley S H, Stahle C K 1993 J. Low Temp. Phys. 93 281Google Scholar

    [19]

    Lindeman M A 2000 Ph. D. Dissertation (Davis, California: University of California at Davis)

    [20]

    Anderson B D O, Moore J B 1979 Optimal Filtering (Upper Saddle River: Prentice Hall) pp417−421

    [21]

    Walls D F, Milburn G 2008 Quantum Optics (2nd Ed.) (Berlin: Springer-Verlag) pp46−48

    [22]

    Irwin K D 1995 Ph. D. Dissertation (Palo Alto, California: Stanford University)

    [23]

    Wang L L, Li J, Yang N, Li X 2019 New J. Phys. 21 043005Google Scholar

    [24]

    张贤达 2013 矩阵分析与应用 (第2版) (北京: 清华大学出版社) 第502−508页

    Zhang X D 2013 Matrix analysis and Application (2nd Ed.) (Beijing: Tsinghua University Press) pp502−508 (in Chinese)

    [25]

    Alpert B K, Horansky R D, Bennett D A, Doriese W B, Fowler J W, Hoover A S, Rabin M W, Ullom J N 2013 Rev. Sci. Instrum. 84 056107Google Scholar

  • 图 1  实验测量系统示意图

    Fig. 1.  Schematic diagram of the experimental system for single-photon detection.

    图 2  复平面上的脉冲响应图

    Fig. 2.  Pulse response diagram.

    图 3  触发模式记录时间序列信号的示意图

    Fig. 3.  Schematic diagram of the signal triggers and records in time domain.

    图 4  实验测量的探测器噪声 (a)自相关函数; (b)功率谱密度$ J\left(f\right) $

    Fig. 4.  Autocorrelation function (a) and power spectral density(b) of detector noise measured experimentally.

    图 5  光学衰减17 dB (a)和20 dB (b)下脉冲信号幅值统计的高斯拟合结果

    Fig. 5.  Gaussian fitting results of pulse signal amplitudes under optical attenuation of 17 dB (a) and 20 dB (b), respectively, for the experimental noises.

    图 6  信号处理的流程框图

    Fig. 6.  Flow diagram of the signal processing.

    图 7  探测器噪声(点集)及其高斯分布函数拟合(红实线)

    Fig. 7.  Detector noise (point set) and Gaussian distribution function fitting (red solid line).

    图 8  采用白噪声模型后, 光学衰减17 dB (a)和20 dB (b)下的脉冲幅值统计分布以及拟合图像

    Fig. 8.  Gaussian fitting results of pulse signal amplitudes under optical attenuation of 17 dB (a) and 20 dB (b), respectively, for the ideal white noises.

    图 9  白化后的探测器噪声 (a)自相关函数; (b)功率谱密度$ J{'}\left(f\right) $

    Fig. 9.  Autocorrelation function (a) and Power spectral density (b) of the whitened noise.

    图 10  噪声白化后, 光学衰减17 dB (a)和20 dB (b)下探测器的光子数响应拟合

    Fig. 10.  Gaussian fitting results of pulse signal amplitudes under optical attenuation of 17 dB (a) and 20 dB (b), respectively, for the whitened noises.

    表 1  光学衰减17 dB和20 dB下探测器的能量分辨

    Table 1.  Energy resolution of detector under optical attenuation of 17 dB and 20 dB.

    能量分辨$ \Delta E_{{0}}{/{\rm{eV}}} $$ \Delta E_{{1}}{/{\rm{eV}}} $$ \Delta E_{2}{/{\rm{eV}}} $$ \Delta E_{3}{/{\rm{eV}}} $$ \Delta E_{4}{/{\rm{eV}}} $
    衰减17 dB
    的信号
    0.10150.35260.43600.46910.6140
    衰减20 dB
    的信号
    0.09550.32000.41990.4758
    下载: 导出CSV

    表 2  光学衰减17 dB下使用实测噪声和白噪声模型处理后探测器能量分辨对比

    Table 2.  Comparison of detector energy resolutions after processing with measured noise and white noise model under optical attenuation of 17 dB.

    能量分辨$ \Delta E_{{0}}{/{\rm{eV}}} $$ \Delta E_{{1}}{/{\rm{eV}}} $$ \Delta E_{2}{/{\rm{eV}}} $$ \Delta E_{3}{/{\rm{eV}}} $$ \Delta E_{4}{/{\rm{eV}}} $$ \Delta E_{5}{/{\rm{eV}}} $
    实测噪声0.10150.35260.43600.46910.6140
    白噪声模型0.14890.29920.37720.43820.44480.5113
    提高–31.83%+17.85%+15.59%+7.05%+38.04%
    下载: 导出CSV

    表 3  光学衰减20 dB下使用实测噪声和白噪声模型处理后探测器能量分辨对比

    Table 3.  Comparison of detector energy resolutions after processing with measured noise and white noise model under optical attenuation of 20 dB.

    能量分辨$ \Delta E_{{0}}{/{\rm{eV}}} $$ \Delta E_{{1}}{/{\rm{eV}}} $$ \Delta E_{2}{/{\rm{eV}}} $$ \Delta E_{3}{/{\rm{eV}}} $
    实测噪声0.09550.32000.41990.4758
    白噪声模型0.15530.26500.37480.4032
    提高/%–62.61+17.19+10.74+15.26
    下载: 导出CSV

    表 4  光学衰减17 dB下实测噪声和噪声白化后处理得到的探测器能量分辨对比

    Table 4.  Comparison of energy resolutions for the experimental noises and the whitening ones, where the optical pulse is attenuated 17 dB.

    能量分辨$ \Delta {{E}}_{{0}}{/{\rm{eV}}} $$ \Delta {{E}}_{{1}}{/{\rm{eV}}} $$ \Delta {{E}}_{2}{/{\rm{eV}}} $$ \Delta {{E}}_{3}{/{\rm{eV}}} $$ \Delta {{E}}_{4}{/{\rm{eV}}} $$ \Delta {{E}}_{5}{/{\rm{eV}}} $
    实测噪声0.10150.35260.43600.46910.6140
    噪声白化0.14690.32740.42630.48970.50090.6216
    提高/%–44.73+7.15+2.22–4.39+18.42
    下载: 导出CSV

    表 5  光学衰减20 dB下实测噪声和噪声白化后处理得到的探测器能量分辨对比

    Table 5.  Comparison of energy resolutions for the experimental noises and the whitening ones, where the optical pulse is attenuated 20 dB.

    能量分辨$ \Delta {{E}}_{{0}}{/{\rm{eV}}} $$ \Delta {{E}}_{{1}}{/{\rm{eV}}} $$ \Delta {{E}}_{2}{/{\rm{eV}}} $$ \Delta {{E}}_{3}{/{\rm{eV}}} $
    实测噪声0.09550.32000.41990.4758
    噪声白化0.19320.28550.396490.4196
    提高/%–100.02+10.78+5.60+11.81
    下载: 导出CSV

    表 6  光学衰减20 dB下原始滤波和改进噪声模型后探测器能量分辨对比(括号中是改进后相对于实测噪声处理所得到的能量分辨的提高百分比)

    Table 6.  Comparison of energy resolutions of the detector for the experimental noise, white noise and withened noise, respectively. The improvemence is relative to the those for the experimental noise. Here, the optical pulse is attenuated 20 dB.

    能量分辨$ \Delta {{E}}_{1}{/{\rm{eV}}} $$ \Delta {{E}}_{{2}}{/{\rm{eV}}} $$ \Delta {{E}}_{3}{/{\rm{eV}}} $
    实测噪声0.32000.41990.4758
    白噪声模型0.2650
    (+17.19%)
    0.3748
    (+10.74%)
    0.4032
    (+15.26%)
    噪声白化0.2855
    (+10.78%)
    0.39649
    (+5.60%)
    0.4196
    (+11.81%)
    下载: 导出CSV
  • [1]

    Hiskett P A, Lita A E, Hughes R J, Rosenberg D, Miller A J, Nordholt J E, Peterson C G, Nam S 2006 New J. Phys. 8 193Google Scholar

    [2]

    Knill E, Laflamme R, Milburn G J 2001 Nature 409 46Google Scholar

    [3]

    Zwinkels J C, Ikonen E, Fox N P, Ulm G, Rastello ML 2010 Metrologia 47 R15Google Scholar

    [4]

    周品嘉 2014 博士学位论文 (成都: 西南交通大学)

    Zhou P J 2014 Ph. D. Dissertation (ChengDu: Southwest Jiaotong University) (in Chinese)

    [5]

    Enss C 2005 Cryogenic Particle Detection 1 (Berlin: Springer-Verlag) pp417−452

    [6]

    Zheng F, Xu R, Zhu G, Jin B, Kang L, Xu W, Chen J, Wu P 2016 Sci. Rep. 6 22710Google Scholar

    [7]

    张青雅, 董文慧, 何根芳, 李铁夫, 刘建设, 陈炜 2014 物理学报 63 200303Google Scholar

    Zhang Q Y, Dong W H, He G F, Li T F, Liu J S, Chen W 2014 Acta Phys. Sin. 63 200303Google Scholar

    [8]

    Day P K, Leduc H G, Mazin B A, Vayonakis A, Zmuidzinas J 2003 Nature 425 817Google Scholar

    [9]

    李春光, 王佳, 吴云, 王旭, 孙亮, 董慧, 高波, 李浩, 尤立星, 林志荣, 任洁, 李婧, 张文, 贺青, 王轶文, 韦联福, 孙汉聪, 王华兵, 李劲劲, 屈继峰 2021 物理学报 70 018501Google Scholar

    Li C G, Wang J, Wu Y, Wang X, Sun L, Dong H, Gao B, Li H, You L X, Lin Z R, Ren J, Li J, Zhang W, He Q, Wang Y W, Wei L F, Sun H C, Wang H B, Li J J, Qu J F 2021 Acta Phys. Sin. 70 018501Google Scholar

    [10]

    周品嘉, 王轶文, 韦联福 2014 物理学报 63 070701Google Scholar

    Zhou P J, Wang Y W, Wei L F 2014 Acta Phys. Sin. 63 070701Google Scholar

    [11]

    Lita A E, Miller A J, Nam S W 2008 Opt. Express 16 3032Google Scholar

    [12]

    Lolli L, Taralli E, Portesi C, Monticone E, Rajteri M 2013 Appl. Phys. Lett. 103 041107Google Scholar

    [13]

    Yang X Y, Li H, Zhang W J, You L X, Zhang L, L iu, X Y, Wang Z, Peng W, Xie X M, Jiang M H 2014 Opt. Express 22 16267Google Scholar

    [14]

    Li X, Tan J R, Zheng K M, Zhang L B, Zhang J L, He W J, Huang P W, Li H C, Zhang B, Chen Q, Ge R, Guo S Y, Huang T, Jia X Q, Zhao Q Y, Tu X C, Kang L, Chen J, Wu P H 2020 Photonics Research 8 637Google Scholar

    [15]

    Geng Y, Zhang W, Li P Z, Zhong J Q, Wang Z, Miao W, Ren Y, Wang J F, Yao Q J, Shi S C 2020 J. Low Temp. Phys. 199 556Google Scholar

    [16]

    Guo W, Liu X, Wang Y, Wei Q, Wei L F, Hubmayr J, Fowler J, Ullom J, Vale L, Vissers M R, Gao J 2017 Appl. Phys. Lett. 110 212601Google Scholar

    [17]

    Liu X, Guo W, Wang Y, Dai M, Wei L F, Dober B, McKenney C M, Hilton G C, Hubmay J, Austermann J E, Ullom J N, Gao J, Ullom J N 2017 Appl. Phys. Lett. 111 252601Google Scholar

    [18]

    Szymkowiak A E, Kelley R L, Moseley S H, Stahle C K 1993 J. Low Temp. Phys. 93 281Google Scholar

    [19]

    Lindeman M A 2000 Ph. D. Dissertation (Davis, California: University of California at Davis)

    [20]

    Anderson B D O, Moore J B 1979 Optimal Filtering (Upper Saddle River: Prentice Hall) pp417−421

    [21]

    Walls D F, Milburn G 2008 Quantum Optics (2nd Ed.) (Berlin: Springer-Verlag) pp46−48

    [22]

    Irwin K D 1995 Ph. D. Dissertation (Palo Alto, California: Stanford University)

    [23]

    Wang L L, Li J, Yang N, Li X 2019 New J. Phys. 21 043005Google Scholar

    [24]

    张贤达 2013 矩阵分析与应用 (第2版) (北京: 清华大学出版社) 第502−508页

    Zhang X D 2013 Matrix analysis and Application (2nd Ed.) (Beijing: Tsinghua University Press) pp502−508 (in Chinese)

    [25]

    Alpert B K, Horansky R D, Bennett D A, Doriese W B, Fowler J W, Hoover A S, Rabin M W, Ullom J N 2013 Rev. Sci. Instrum. 84 056107Google Scholar

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出版历程
  • 收稿日期:  2020-10-26
  • 修回日期:  2021-02-24
  • 上网日期:  2021-06-07
  • 刊出日期:  2021-07-20

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