Photodetector and photodetector

Abstract

The present invention provides a light detection device that can reduce noise components and minimize measurement errors in light intensity. [Solution] The photodetector 1 comprises a photosensor 21 and a circuit. The photosensor 21 is an electron tube and has a housing, a photocathode, and a detection unit. The housing maintains an internal vacuum. The photocathode is located inside the housing and converts photons into photoelectrons. The detection unit is located inside the housing and multiplies the photoelectrons to output a current signal. The circuit generates time-series data Da of a digital signal based on the current signal Ja from the photosensor 21. The circuit includes an I / V conversion circuit 22, an A / D converter 31, and a noise reduction circuit 32. The I / V conversion circuit 22 converts the current signal Ja into an analog voltage signal Va. The A / D converter 31 converts the analog voltage signal Va into time-series data Da. The noise reduction circuit 32 reduces noise components contained in the time-series data Da.

Description

[Technical Field]

[0001] This disclosure relates to an optical detection device and an optical detection method. [Background technology]

[0002] Patent Document 1 discloses a light intensity detection device. This light intensity detection device performs A / D conversion on the detection signal of a photon count type photodetector. If the A / D converted detection signal is above a threshold, the detection signal is sent directly to the subsequent photon count calculation circuit. If the A / D converted detection signal is below the threshold, a preset reference value is sent to the subsequent photon count calculation circuit. The photon count calculation circuit determines the number of photons or light intensity incident on the photon count type photodetector from the area of ​​the detection signal waveform acquired until the light intensity measurement is completed. [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2012-37267 [Overview of the project] [Problems that the invention aims to solve]

[0004] Currently, light detection methods for detecting weak light include avalanche photodiodes (APDs), silicon photomultipliers (SiPMs), and single-photon avalanche diodes (SPADs). Conventionally, in these light detection methods, the amount of detected light is limited depending on the application, so consideration of noise components is not required. In addition, vacuum tube sensors such as photomultiplier tubes (PMTs) and hybrid photodetectors (HPDs) are also used as light detection methods for detecting weak light. Conventionally, in these light detection methods, the gain is set according to the amount of detected light. That is, the gain is increased when the amount of detected light is small, and the gain is decreased when the amount of detected light is large.

[0005] In recent years, there has been a demand, for example in biological research, to simultaneously observe regions with relatively low light intensity and regions with relatively high light intensity. When observing these regions simultaneously, it is necessary to accurately distinguish between signal waveforms caused by a single photon and noise components, especially in regions with relatively low light intensity. Therefore, noise reduction circuits (noise filters) are used to reduce the noise components contained in the detection signal from the photodetector.

[0006] In the noise reduction method described in Patent Document 1, if the peak size of the pulse waveform caused by the photon input is equal to or less than the size of the noise component, the pulse waveform cannot be distinguished from the noise component. Therefore, when reducing the noise component, the pulse waveform caused by the photon input is also reduced along with the noise component, resulting in a large measurement error of the light intensity.

[0007] The purpose of this disclosure is to provide a photodetection device and a photodetection method that can reduce noise components and minimize measurement errors in light intensity. [Means for solving the problem]

[0008] [1] An optical detection device relating to one aspect of the present disclosure comprises an electron tube and a circuit. The electron tube has a housing, a photocathode, and a detection unit. The housing maintains an internal vacuum. The photocathode is located inside the housing and converts photons into photoelectrons. The detection unit is located inside the housing and multiplies the photoelectrons to output a current signal. The circuit receives the current signal from the electron tube and generates time-series data of a digital signal based on the current signal. The circuit includes a current-voltage converter, an analog-to-digital converter, and a noise reduction unit. The current-voltage converter converts the current signal into an analog voltage signal. The analog-to-digital converter converts the analog voltage signal into time-series data. The noise reduction unit is either incorporated into the current-voltage converter or the analog-to-digital converter, or provided separately from the current-voltage converter and the analog-to-digital converter, and reduces noise components contained in the analog voltage signal or time-series data. R is the magnitude of the readout noise caused by the noise superimposed on the analog voltage signal in the current-voltage converter and the noise superimposed on the time-series data in the analog-to-digital converter. M is the gain of the detection unit of the electron tube. Let fc (Hz) be the cutoff frequency of the current-voltage converter. Let Sr (Hz) be the sampling frequency of the analog-to-digital converter. In this case, the photodetector satisfies both of the following equations (1) and (2).

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[0009] Furthermore, an optical detection method relating to one aspect of this disclosure is an optical detection method that generates time-series data of a digital signal based on a current signal output from an electron tube having a housing that maintains an internal vacuum, a photocathode disposed within the housing that converts photons into photoelectrons, and a detection unit disposed within the housing that multiplies the photoelectrons and outputs a current signal. This optical detection method includes a current-voltage conversion step, an analog-to-digital conversion step, and a noise reduction step. In the current-voltage conversion step, the current signal is converted into an analog voltage signal. In the analog-to-digital conversion step, the analog voltage signal is converted into time-series data. The noise reduction step is incorporated into the current-voltage conversion step or the analog-to-digital conversion step, or is provided separately from the current-voltage conversion step and the analog-to-digital conversion step. In the noise reduction step, noise components contained in the analog voltage signal or time-series data are reduced. When R is the magnitude of the readout noise caused by the noise superimposed on the analog voltage signal in the current-voltage conversion step and the noise superimposed on the time-series data in the analog-to-digital conversion step, M is the gain of the electron tube detection unit, fc (Hz) is the cutoff frequency of the current-voltage conversion step, and Sr (Hz) is the sampling frequency of the analog-to-digital conversion step, this optical detection method satisfies both of the above equations (1) and (2).

[0010] To distinguish the pulse waveform resulting from photon input from noise components, it is desirable to make the peak of the pulse waveform larger than that of the noise component. However, if the gain is increased to match the region with relatively low light intensity in order to facilitate distinction from noise components, the detection signal may become too large and saturate in the region with relatively high light intensity, potentially resulting in a narrow dynamic range. Therefore, with the aim of achieving both accurate distinction between signal waveforms and noise components and a high dynamic range, it is conceivable to increase the cutoff frequency of the current-voltage converter to increase only the peak of the pulse waveform without changing the time integral value of the pulse waveform. Increasing the cutoff frequency reduces the pulse width. In such cases, if the sampling frequency of the analog-to-digital converter is small, the reproducibility of the pulse waveform decreases, and the measurement error of the light intensity increases. Therefore, when attempting to increase the peak of the pulse waveform in this way, it is necessary to increase the sampling frequency of the analog-to-digital converter. However, it is not possible to increase the sampling frequency of the analog-to-digital converter indefinitely.

[0011] The inventors have found the minimum magnitude of the pulse waveform peak and the sampling frequency of the analog-to-digital converter that make it possible to distinguish the pulse waveform resulting from the photon input from the noise component. As will be described in later embodiments, by satisfying both equations (1) and (2) above, the photodetector and the photodetector can distinguish the pulse waveform resulting from the photon input from the noise component and reduce the measurement error of the light intensity.

[0012] In this specification, a noise reduction unit or noise reduction step refers to a functional unit or step that determines whether or not an analog voltage signal or time series data contains a signal component by utilizing the difference between the magnitude of a photon-induced signal component and the magnitude of non-signal components contained in the analog voltage signal or time series data, and performs arbitrary arithmetic processing or conversion processing on the analog voltage signal or time series data according to the determination result.

[0013] [2] In the photodetector and photodetector method described in [1] above, the detection unit may be an avalanche diode. A hybrid photodetector (HPD) that combines a photocathode and an avalanche diode has the advantage of having small pulse height distribution (PHD), which is a fluctuation in the peak value of the time waveform of an analog voltage signal caused by fluctuations in the multiplication gain. Therefore, the pulse waveform caused by the input of photons can be distinguished from noise components with greater accuracy, and the measurement error of the light intensity can be further reduced.

[0014] [3] The photodetector described in [1] or [2] above may include a plurality of detection units, each containing the detection unit, and a plurality of current-voltage converters, each corresponding to one of the plurality of detection units. The plurality of current-voltage converters may be integrated into a single IC. By integrating the plurality of current-voltage converters into a single IC, the circuit size can be reduced compared to the case where each current-voltage converter is composed of discrete circuits, contributing to the miniaturization of the photodetector. In addition, the wiring between each current-voltage converter and each detection unit can be shortened, reducing input capacitance and parasitic components. Therefore, noise components can be reduced and the measurement error of light intensity can be reduced.

[0015] [4] Any one of the photodetectors and photodetectors described in [1] to [3] above may further satisfy the following equation (3). In this case, the pulse waveform caused by the photon input can be more clearly distinguished from the noise component, and the measurement error of the light intensity can be further reduced.

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[0016] [5] Any one of the photodetectors and photodetectors described in [1] to [3] above may further satisfy the following equation (4). In this case, the pulse waveform caused by the photon input can be more clearly distinguished from the noise component, and the measurement error of the light intensity can be further reduced.

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[0017] [6] Any one of the photodetectors and photodetectors from [1] to [5] above may further satisfy the following equation (5). In this case, the pulse waveform due to the input of photons can be distinguished more clearly from the noise component, and the measurement error of the light intensity can be further reduced.

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[0018] [7] Any one of the photodetectors and photodetectors from [1] to [5] above may further satisfy the following equation (6). In this case, the pulse waveform due to the input of photons can be distinguished more clearly from the noise component, and the measurement error of the light intensity can be further reduced.

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[0019] This disclosure provides a photodetector and a photodetector method that can reduce noise components and minimize measurement errors in light intensity. [Brief explanation of the drawing]

[0020] [Figure 1] Figure 1 is a schematic diagram showing the configuration of a photodetector according to one embodiment of the present disclosure. [Figure 2] Figure 2 is a graph showing an example of an analog voltage signal and time-series data. [Figure 3] Figure 3 is a block diagram showing the functional configuration of the noise reduction circuit. [Figure 4] Figure 4 is a graph showing the difference in values. [Figure 5] Figure 5 is a graph showing the time-series data after the replacement. [Figure 6] Figure 6 schematically shows a pulsed time waveform originating from a single photon and a steadily superimposed noise component. [Figure 7]Figure 7 schematically shows a pulsed time waveform originating from a single photon and a steadily superimposed noise component. [Figure 8] Figure 8 illustrates the problems that arise when the sampling period in an A / D converter is excessively small compared to the time width of a pulsed time waveform. [Figure 9] Figure 9 shows analog voltage signals and time-series data when the pulsed time waveform has a relatively low peak and a large time width compared to its time width. [Figure 10] Figure 10 shows analog voltage signals and time-series data when the sampling period is relatively large relative to the time width of a pulsed time waveform. [Figure 11] Figure 11 is a graph showing some examples of time-series data. [Figure 12] Figure 12 is a graph showing time-series data after noise reduction when the noise reduction circuit has a determination unit and a replacement unit. [Figure 13] Figure 13 is a graph showing an example of an analog voltage signal that includes a pulsed time waveform. [Figure 14] Figure 14 is a graph showing analog voltage signals and time-series data. [Figure 15] Figure 15 is a graph showing analog voltage signals and time-series data. [Figure 16] Figure 16 is a graph showing the changes in time-series data when the time difference between the sampling timing in the A / D converter and the input timing of the pulsed time waveform is changed. [Figure 17] Figure 17 is a graph showing the changes in time-series data when the time difference between the sampling timing in the A / D converter and the input timing of the pulsed time waveform is changed. [Figure 18] The bar graph shown in Figure 18 illustrates the relationship between the ratio (Sr / fc) and the expected value of the integral exponential variation. [Figure 19] Figure 19 is a graph showing the relationship between the ratio (Sr / fc) and the standard deviation of the integral value exponent of variation. [Figure 20] Figure 20 schematically shows a pulsed time waveform and noise components. [Figure 21] Figure 21 is a graph showing the amount of incident light and its frequency of occurrence as indicated by time-series data. [Figure 22] Figure 22 is a graph showing the amount of incident light and its frequency of occurrence as indicated by time-series data. [Figure 23] Figure 23 is a graph showing the ranges in which R / M and Sr / fc satisfy the specified conditions. [Figure 24] Figure 24 is a graph showing the ranges in which R / M and Sr / fc satisfy the specified conditions. [Figure 25] Figure 25 is a flowchart showing a light detection method according to one embodiment. [Figure 26] Figure 26 is a perspective view showing various configurations of multiple I / V conversion circuits. [Modes for carrying out the invention]

[0021] Specific examples of the present disclosure will be described below with reference to the drawings. However, the present invention is not limited to these examples, and is intended to include all modifications within the meaning and scope of the claims, as defined by the claims. In the following description, identical elements in the drawings are denoted by the same reference numerals, and redundant descriptions are omitted.

[0022] Figure 1 is a schematic diagram showing the configuration of a photodetector 1 according to one embodiment of the present disclosure. As shown in Figure 1, the photodetector 1 of this embodiment comprises a photodetector 2, a signal processing circuit 3, a signal intensity calculation circuit 4, and a computing device 5. Light P is input to the photodetector 2. The photodetector 2 outputs an analog signal (analog voltage signal Va) corresponding to each of the multiple photons constituting the light P. The signal processing circuit 3 converts the analog voltage signal Va into digital time-series data Da, reduces the noise component contained in the time-series data Da, and generates time-series data Db. The signal intensity calculation circuit 4 calculates the signal intensity by integrating the time-series data Db over time and outputs numerical data Dc indicating the signal intensity. The computing device 5 is configured by a computing device such as a personal computer, and reconstructs and displays image or light intensity distribution data based on the numerical data Dc.

[0023] A specific example of the photodetector 2 will be described. The photodetector 2 has a photosensor 21 and an I / V conversion circuit (current-voltage converter) 22. As the photosensor 21, a photosensor capable of single-photon measurement is preferred. The photosensor 21 is an electron tube equipped with a photocathode 211. The electron tube may be, for example, a photomultiplier tube (PMT) equipped with a multi-stage dynode as an electron multiplication unit 212. Alternatively, the electron tube may be an HPD (hybrid photodetector) equipped with an electron multiplication unit 212 that multiplies and detects photoelectrons from the photocathode 211 by electron implantation multiplication and avalanche multiplication, and a semiconductor element as a detection unit 213. That is, the photosensor 21 is an electron tube having a housing that maintains an internal vacuum, a photocathode 211 disposed within the housing that converts photons into photoelectrons, and a detection unit 213 disposed within the housing that multiplies the photoelectrons and outputs a current signal. The detection unit 213 may be a multi-stage dynode and a subsequent anode in a photomultiplier tube, or an avalanche diode (AD) in an HPD. The HPD performs electron multiplication through a two-stage electron multiplication process: electron implantation multiplication caused by electrons incident on the detection unit 213 (avalanche diode), and avalanche multiplication caused by an electron avalanche. Light P is input to the light sensor 21. The light sensor 21 generates photoelectrons corresponding to each of the multiple photons constituting the light P, multiplies these electrons, and outputs a current signal Ja. The I / V conversion circuit 22 is electrically connected to the light sensor 21 and converts the current signal Ja into a voltage signal. The I / V conversion circuit 22 includes, for example, a charge amplifier or a transimpedance amplifier. The photodetector 2 outputs the voltage signal generated in the I / V conversion circuit 22 as an analog voltage signal Va to the signal processing circuit 3. Note that the I / V conversion circuit 22 may be included in the signal processing circuit 3 instead of the photodetector 2. Similarly, a portion of the signal processing circuit 3 may be included in the photodetector 2.

[0024] The signal processing circuit 3 is a circuit that converts an analog voltage signal Va into time-series digital data Db. The signal processing circuit 3 has an input terminal 3a, an output terminal 3b, an analog-to-digital converter (A / D converter) 31, and a noise reduction circuit 32. The input terminal 3a is electrically connected to the signal output terminal of the photodetector 2 and receives the analog voltage signal Va output from the photodetector 2. The A / D converter 31 converts the analog voltage signal Va into time-series data Da, which includes multiple digital signal values ​​with time intervals. Part 2(a) of Figure 2 is a graph showing an example of the analog voltage signal Va. Part 2(b) of Figure 2 is a graph showing the time-series data Da corresponding to the analog voltage signal Va shown in part (a). In Figure 2, the horizontal axis represents time (ns), and the vertical axis represents voltage (V), which indicates the magnitude of the signal. As shown in part 2(a) of Figure 2, in this example, a pulsed time waveform Pa caused by one photon of light P is included in the time variation of the analog voltage signal Va. Furthermore, the time variation of the analog voltage signal Va contains noise components not caused by the light P. These noise components are superimposed on the original signal components, for example, in the wiring from the signal output terminal of the photodetector 2 to the A / D converter 31, and within the A / D converter 31 itself. Part 2(b) of Figure 2 shows the time variation of the analog voltage signal Va containing such noise components, converted directly into time-series data Da of digital signal values. Part 2(b) of Figure 2 shows N digital signal values ​​I(t1) to I(t) that constitute the time-series data Da (N is an integer greater than or equal to 2; in the illustrated example, N=17). N ) is shown (for example, the figure shows the digital signal values ​​I(t1)~I(t 17(This is shown). The sampling frequency of the A / D converter 31 is, for example, 10 MSa / s to 60 MSa / s. Note that 1 MSa / s means that sampling (converting an analog signal to a digital signal value) is performed once per second. When the sampling frequency is 40 MSa / s, the time interval of the digital signal value (i.e., the sampling interval (sampling period)) is 25 ns, which corresponds to the reciprocal of the sampling frequency. Referring to part (b) of Figure 2, it can be seen that the time series data Da also includes a pulsed time waveform Pa, and that the digital signal value is also varied by noise components in other sections other than the time waveform Pa.

[0025] The noise reduction circuit 32 is a digital circuit and is the noise reduction unit in this embodiment. The noise reduction circuit 32 is electrically connected to the A / D converter 31 and receives time-series data Da from the A / D converter 31. The noise reduction circuit 32 generates time-series data Db from the time-series data Da by reducing noise components that are different from the components based on photons of optical P, which are included in the time-series data Da. The noise reduction circuit 32 determines whether or not the components based on photons of optical P are included in the time-series data Da by utilizing the fact that the digital value of the component based on photons of optical P is larger than the digital value of the noise component. The noise reduction circuit 32 does not act on specific frequency components, such as a low-pass filter, high-pass filter, or band-pass filter. Furthermore, the noise reduction circuit 32 does not perform uniform processing on all points, such as a moving average (smoothing). The noise reduction circuit 32 may be composed of, for example, a large-scale logic circuit such as an ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array), or a microcomputer.

[0026] Various noise reduction methods can be used in the noise reduction circuit 32. For example, the noise reduction circuit 32 may use a method like the one described in Patent Document 1, which reduces the digital signal value I(t n If the digital signal value I(t) does not exceed a predetermined threshold,n ) is replaced with a predetermined value (e.g., zero), whereby noise components may be reduced. Alternatively, the noise removal circuit 32 may have a noise reduction method described below.

[0027] FIG. 3 is a block diagram showing a functional configuration of the noise removal circuit 32 as an example. The noise removal circuit 32 includes a determination unit 321 and a replacement unit 322. The determination unit 321 applies a threshold condition indicating the presence of a component based on input of photons of light P to a plurality of digital signal values I(t1) to I(t N ) included in the time-series data Da to determine whether each of the values satisfies the threshold condition. In the present embodiment, a digital signal value at a certain sampling point t n (where n is an integer of 2 or more and N or less) I(t n ) satisfies the threshold condition means that the digital signal value I(t n ) and the digital signal value I(t n ) before (typically immediately before) the digital signal value I(t n-1 ), a difference value S(t n )=I(t n )-I(t n-1 ) exceeds a predetermined threshold. The predetermined threshold is set in advance according to the magnitude of a noise component. In one example, the predetermined threshold is set to be equal to three times a difference standard deviation σ' of output intensity in a state where the light P is not input (dark state). The difference standard deviation σ' of output intensity is based on the standard deviation σ of output intensity, σ'=(σ 2 +σ 2 ) 1 / 2 is calculated as

[0028] The determination unit 321 first calculates difference values S(t2) to S(t N ). Part (a) of FIG. 4 is a graph in which difference values S(t2) to S(t N ) are superimposed on the time-series data Da shown in part (b) of FIG. 2. In the figure, a plurality of black dots indicate difference values S(t n ). Next, the determination unit 321 determines whether the difference value S(t n ) exceeds a predetermined threshold. Part (b) of FIG. 4 shows the difference value S(t nThis is a graph showing the difference between ) and predetermined thresholds TH, -TH. In this case, the difference value S(t n ) exceeds a predetermined threshold if the difference value S(t n This means that the value is either above the threshold TH or below the threshold -TH. In the example shown in part (b) of Figure 4, only the difference value S(t5) is above the threshold TH.

[0029] The substitution unit 322 sets the first period Ta and the second period Tb shown in part (b) of Figure 4. The first period Ta is the period in which the time-series data Da does not include a component based on the input of photons from optical P. The second period Tb is the period in which the time-series data Da includes a component based on the input of photons from optical P. In the illustrated example, the first period Ta and the second period Tb are consecutive, but a gap may be provided between the first period Ta and the second period Tb. The substitution unit 322 determines the first period Ta and the second period Tb based on the determination result by the determination unit 321. That is, the substitution unit 322 defines the second period Tb as the period in which the determination unit 321 determines that a digital signal value among a plurality of digital signal values ​​satisfies the threshold condition, and the digital signal values ​​counting from that digital signal value to at least one before and one after. The substitution unit 322 then sets the period excluding the second period Tb as the first period Ta. In the examples shown in parts (a) and (b) of Figure 4, the second period Tb includes a digital signal value I(t5) where the difference value S(t5) exceeds the threshold TH, and digital signal values ​​I(t4) and S(t6) counting from I(t5) for at least one period before and after. The time width of the second period Tb may be set to be approximately equal to the total width of the pulsed time waveform Pa, or close to the total width of the pulsed time waveform Pa.

[0030] In the examples shown in parts (a) and (b) of Figure 4, the time width of the second period Tb is set to include the digital signal value I(t4) to the digital signal value I(t8). In a system in which the photodetector 1 is used, if the total width of the pulsed time waveform Pa is known, the time width of the second period Tb should be set to be approximately equal to the total width of the pulsed time waveform Pa. The total width of the time waveform Pa can be calculated, for example, from the sampling frequency of the A / D converter 31 and the cutoff frequency of the I / V conversion circuit 22.

[0031] The substitution unit 322 replaces multiple digital signal values ​​included in the first period Ta (in the illustrated example, digital signal values ​​I(t1) to I(t3) and I(t9) to I(t9) 17 Each of the following is replaced with a predetermined value to generate time-series data Db. The predetermined value is, for example, a constant value, and in one embodiment it is zero. Line L in Figure 5 shows the time-series data Db after the replacement.

[0032] Here, we will explain the common challenges faced by noise reduction circuits using various noise reduction methods. Part 6(a) of Figure 6 schematically shows a pulsed time waveform Pa caused by a single photon of light P and a steadily superimposed noise component Pb. As shown in Part 6(a) of Figure 6, if the magnitude of the peak of the time waveform Pa is equal to or less than the magnitude of the noise component Pb, the time waveform Pa does not exceed the reference value R used to determine whether or not it is the noise component Pb, and therefore the time waveform Pa cannot be distinguished from the noise component Pb. In this case, the time waveform Pa is reduced together with the noise component Pb by the noise reduction circuit, and this becomes one of the causes of light intensity measurement errors.

[0033] Furthermore, to solve this problem, it is conceivable to increase the gain of the I / V conversion circuit 22, as shown in part (b) of Figure 6, to make the peak of the time waveform Pa larger than the reference value R. However, in this case, since the time width of the time waveform Pa is maintained, the time integral value of the time waveform Pa becomes larger. Consequently, a new problem arises: the range of measurable light intensity (dynamic range) becomes narrower. Here, the time integral value corresponds to the area of ​​the time waveform Pa.

[0034] Therefore, it is conceivable to increase the cutoff frequency of the I / V conversion circuit 22. In that case, as shown in Figure 7, the time width of the time waveform Pa can be reduced while making the peak of the time waveform Pa larger than the reference value R. At this time, the magnitude of the time integral value of the time waveform Pa depends on the gain of the I / V conversion circuit 22, so if the gain is kept constant, the time integral value of the time waveform Pa will also be constant. Thus, the expansion of the time integral value of the time waveform Pa can be suppressed, and the narrowing of the dynamic range can be suppressed. However, reducing the time width of the time waveform Pa gives rise to new problems, which will be described below.

[0035] Figure 8 illustrates the problems that occur when the sampling period (sampling interval) in the A / D converter 31 is excessively large compared to the time width of the time waveform Pa, in other words, when the sampling frequency is excessively small. Let's assume that an analog voltage signal Va, including the time waveform Pa shown in part (a) of Figure 8, is input to the A / D converter 31. At this time, as shown in part (b) of Figure 8, the A / D converter 31 converts the voltage value of the analog voltage signal Va into digital signal values ​​I(t1) to I(t6) at a sampling period T. Therefore, the waveform of the time waveform Pa included in the time series data Da output from the A / D converter 31 takes the form shown in part (c) of Figure 8. As is clear from comparing parts (a) and (c) of Figure 8, the waveform of the time waveform Pa of the time series data Da is significantly distorted compared to the waveform of the time waveform Pa of the analog voltage signal Va. In other words, the reproducibility of the time waveform Pa of the analog voltage signal Va in the time waveform Pa of the time series data Da is low. Therefore, the integral value of the time waveform Pa of the time-series data Da deviates significantly from the integral value of the time waveform Pa of the analog voltage signal Va, resulting in a large light intensity measurement error.

[0036] For example, consider the case where the time waveform Pa of the analog voltage signal Va has a relatively large time width, as shown in part (a) of Figure 9. In this case, if the sampling period T is relatively small with respect to the time width of the time waveform Pa, the time waveform Pa included in the time series data Da will be close to the time waveform Pa of the analog voltage signal Va. Therefore, the reproducibility of the time waveform Pa of the analog voltage signal Va in the time waveform Pa of the time series data Da will not be so low (see part (b) of Figure 9). In contrast, if the time width of the time waveform Pa is reduced by increasing the cutoff frequency of the I / V conversion circuit 22, the sampling period T becomes relatively large with respect to the time width of the time waveform Pa, as shown in part (a) of Figure 10. In other words, the sampling frequency becomes relatively small with respect to the time width of the time waveform Pa. That is, the number of samples per unit time becomes relatively small, and as a result, the number of data points constituting the time waveform Pa included in the time series data Da decreases. Consequently, the reproducibility of the time waveform Pa of the analog voltage signal Va in the time waveform Pa of the time series data Da becomes low, and the light intensity measurement error increases. To solve this problem, it is desirable to reduce the sampling period T (in other words, increase the sampling frequency) as shown in part (b) of Figure 10, in order to improve the reproducibility of the time waveform Pa of the analog voltage signal Va in the time waveform Pa of the time series data Da.

[0037] The following are specific examples of the above-mentioned problem. Part (a) of Figure 11 is a graph showing several examples of time-series data Da and the threshold THb. In this graph, lines G11 to G14 show the cases where the peak value of the time waveform Pa is 1, 1 / 2, 1 / 3, and 1 / 10 times the peak value of line G11, respectively. In these examples, the digital signal value I(t n If the digital signal value I(t) does not exceed the threshold THb, then nWhen ) is replaced with a predetermined value (for example, zero), the time-series data Db output from the noise reduction circuit 32 becomes as shown in part (b) of Figure 11. The magnitude of the threshold THb is, for example, three times (3σ) the standard deviation σ of the analog voltage signal Va (i.e., noise component Pb) when no light P is input (dark state).

[0038] As shown by line G11, when the peak value of the time waveform Pa is sufficiently larger than the threshold THb, the time waveform Pa remains sufficiently present in the time series data Db. However, as shown by lines G12 and G13, when the peak value of the time waveform Pa is not significantly larger than the threshold THb, the tail portion of the time waveform Pa is truncated in the time series data Db, resulting in a smaller value than the original time waveform Pa. Furthermore, as shown by line G14, when the peak value of the time waveform Pa is smaller than the threshold THb, the time waveform Pa itself disappears in the time series data Db. Therefore, when the peak value of the time waveform Pa is not sufficiently larger than the threshold THb, the light intensity measurement error increases.

[0039] Furthermore, if the noise reduction circuit 32 has the determination unit 321 and replacement unit 322 described above, as shown in Figure 12, the tail portion of the time waveform Pa is not cut off in the time series data Db, so it becomes closer to the original time waveform Pa. However, even in that case, if the peak value of the time waveform Pa is smaller than the threshold THb, as shown by line G14, the time waveform Pa itself disappears in the time series data Db. Therefore, the reduction of light intensity measurement errors is hindered.

[0040] Therefore, in order to consider the above issues, we formulate the signal-to-noise ratio (SNR). Let D be the noise (i.e., dark current) generated at the photocathode 211 of the light sensor 21. Here, we will explain the case where the light sensor 21 is an electron tube (HPD) equipped with an AD as the detection unit 213. Let G be the gain of electron implantation multiplication generated when electrons are incident on the detection unit 213, and the noise (gain variation coefficient) generated due to electron implantation multiplication, respectively. EB and F EBFurthermore, the gain of the detection unit 213, which outputs a current signal Ja by further multiplying electrons multiplied by electron implantation multiplication using avalanche multiplication, and the noise (gain variation coefficient) caused by avalanche multiplication are defined as G, respectively. AD and F AD The gain of the I / V conversion circuit 22 and the noise component generated within the I / V conversion circuit 22 are set to G, respectively. TIA and N TIA The noise component generated in the A / D converter 31 is N. ADC Let N be the error (quantization error) caused by the deformation of the time waveform Pa that occurs in the A / D converter 31. Qerr Let's assume that the total gain from the photon to the time-series data Db is G EB ×G AD ×G TIA It is expressed as follows. Also, the total noise from the photon to the time-series data Db is D × F EB ×F AD ×N TIA ×N ADC ×N Qerr Correlated with ("D×F EB ×F AD ×N TIA ×N ADC ×N Qerr (It increases in proportion to the increase in ). Therefore, the SNR is expressed by the following formula (7). However, PDE is the photon detection efficiency, and P is the number of photons. R is the readout noise, and R = (N TIA 2 +N ADC 2 ) 1 / 2 Therefore, R is the maximum amplitude V of the noise component Pb. noisep-p This is converted to the number of photoelectrons and can also be expressed as shown in the following equation (8). M is the gain (sensor gain) of the electron tube detection unit 213, and M = G EB ×G AD That is. Q err is the error (quantization error) due to the deformation of the time waveform Pa. e is the elementary charge. Note that if the optical sensor 21 is a PMT with N stages of dynodes and anodes as the detection unit 213, the gain and noise of each dynode are set to G Dy1, GDy2, …, G DyN and F Dy1, F Dy2, ..., F DyN In this case, the gain in the electron tube of the light sensor 21 (sensor gain M) is G Dy1 ×G Dy2 ×…×G DyN It is expressed as follows. In addition, the noise generated inside the electron tube is F Dy1 ×F Dy2 ×…×F DyN Correlated with ("F Dy1 ×F Dy2 ×…×F DyN (Increases in proportion to the increase in ").

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[0041] Here, the error (quantization error) Q due to the deformation of the time waveform Pa that occurs in the A / D converter 31 is shown. err This will be examined. Figure 13 is a graph showing an example of an analog voltage signal Va including a time waveform Pa. When the analog voltage signal Va shown in this graph is converted to digital time-series data Da, the time-series data Da will be one of parts (a) and (b) of Figure 14, or parts (a) and (b) of Figure 15. Part (a) of Figure 14 shows the case where Sr = 80 (MS / s) and Sr / fc = 16. Part (b) of Figure 14 shows the case where Sr = 40 (MS / s) and Sr / fc = 8. Part (a) of Figure 15 shows the case where Sr = 20 (MS / s) and Sr / fc = 4. Part (b) of Figure 15 shows the case where Sr = 10 (MS / s) and Sr / fc = 2. Here, Sr is the sampling frequency (Hz) of the A / D converter 31, and fc is the cutoff frequency (Hz) of the I / V conversion circuit 22. In this example, fc = 5MHz.

[0042] As is clear from Figures 14 and 15, the smaller the ratio (Sr / fc), the greater the deformation of the time waveform Pa, and the larger the error in the time integral value of the time waveform Pa. Therefore, in this specification, the ratio (Ad / Aa) of the time integral value Aa of the time waveform Pa in the analog voltage signal Va and the time integral value Ad of the time waveform Pa in the time series data Da is used as the integral value variation index A err This is how it is defined.

[0043] Figures 16 and 17 show the change in time-series data Da when the time difference between the timing of each sampling in the A / D converter 31 and the input timing of the time waveform Pa is changed, in the case where Sr / fc = 2. As shown in Figures 16 and 17, the integral value variation exponent A changes depending on the time difference between the timing of each sampling and the input timing of the time waveform Pa. err The integral value of the exponential variation A differs significantly. In the examples shown in parts (a) to (c) of Figure 16, and parts (a) and (b) of Figure 17, the integral value of the exponential variation A err These values ​​are 0.29 (29%), 0.54 (54%), 0.97 (97%), 1.95 (195%), and 2.52 (252%), respectively, and the integral value of the exponential variation A err It can be seen that this integral value variation exponent A err The variation in this is the quantization error N in SNR. Qerr It corresponds to this.

[0044] The bar graph shown in Figure 18 shows the ratio (Sr / fc) and the integral value of the exponential variation A. err This shows the relationship with the expected value. The length of line G21 in the figure is the integral value of the exponential variation A err This corresponds to the standard deviation of . As shown in Figure 18, even if the ratio (Sr / fc) changes, the integral value of the exponential variation A err The expected value of is always 1 (100%). However, the smaller the ratio (Sr / fc), the greater the integral value of the exponential variation A. err The standard deviation of, i.e., the integral value of the exponential variation A err The variability will increase.

[0045] Figure 19 shows the ratio (Sr / fc) and the integral value of the exponential variation A. erris a graph showing the relationship with the standard deviation of . Plot G31 in the figure shows the standard deviation values for each ratio (Sr / fc), and dashed line G32 shows an approximate curve. This approximate curve can be expressed by a mathematical formula as follows.

Math.

[0046] The above formula (7) representing SNR is re-examined. FIG. 20 is a diagram schematically showing a time waveform Pa and a noise component Pb. In FIG. 20, a curve Pa1 represents a time waveform Pa having an average peak value (peak amplitude), a curve Pa2 represents a time waveform Pa having a maximum peak value, and a curve Pa3 represents a time waveform Pa having a minimum peak value. In the following discussion, let the average peak value of the time waveform Pa be V height , and let the difference between the minimum peak value and the maximum peak value, that is, the fluctuation range of the peak value, be V heightp-p . Further, let the average value of the noise component Pb be V noise , and let the maximum amplitude of the noise component Pb be V noisep-p .

[0047] First, a coefficient γ for converting a noise component into the number of electrons is defined as the following formula (10) from the peak value (peak amplitude) of the time waveform Pa corresponding to a single photon. Here, assuming that fluctuation in the peak amplitude of the time waveform Pa is dominant in deformation of the time waveform Pa, using this coefficient γ, Q err is expressed as the following formula (11). However, V height is the expected value of the signal peak amplitude when one photon is detected. G TIA is the I / V conversion coefficient of the I / V conversion circuit 22. e is the elementary charge. V heightp-p is fluctuation in the peak value (peak amplitude) of the time waveform Pa. f c is the cutoff frequency of the I / V conversion circuit 22. S r is the sampling frequency of the A / D converter 31. σ Aerr is the standard deviation of the integrated value fluctuation index A err . Note that V height does not include a noise component. Also, V heightp-pThis represents the fluctuation of the peak value (peak value) of the time waveform Pa, considering only the quantization error.

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[0048] In order for the noise reduction circuit 32 to distinguish the time waveform Pa from the noise component Pb, the average peak value V of the time waveform Pa is height However, the maximum amplitude V of the noise component Pb noisep-p It is sufficient if it is outside the specified range. From this condition, R / M satisfies the following equation (13).

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[0049] Furthermore, the average peak value V of the time waveform Pa height The value (2.5 / 3) times this value represents the maximum amplitude V of the noise component Pb. noisep-p If it is outside the range, the noise reduction circuit 32 can more clearly distinguish the time waveform Pa from the noise component Pb. In that case, R / M satisfies the following equation (14). And PDE=1, P=1, F=1, D=0, Q err When = 0, equation (12) can be deduced that equation (14) must be satisfied in order for the SNR to be 0.86 or greater.

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[0050] Furthermore, the average peak value V of the time waveform Pa height The value that is (2 / 3) times the maximum amplitude V of the noise component Pb. noisep-p If it is outside the range, the noise reduction circuit 32 can distinguish the time waveform Pa from the noise component Pb more clearly. In that case, R / M satisfies the following equation (15). And PDE=1, P=1, F=1, D=0, Q err When = 0, equation (12) can be deduced that equation (15) must be satisfied in order for the SNR to be 0.91 or greater.

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[0051] Here, we will explain the results of a Monte Carlo simulation on the effect of quantization error on the SNR depending on the number of incident photons. Figures 21 and 22 are graphs showing the incident light amount and its frequency of occurrence, as indicated by the time-series data Da obtained from the above simulation. In these figures, the horizontal axis shows the incident light amount (converted to the number of photons) indicated by the time-series data Da, and the vertical axis shows the frequency of occurrence for each incident light amount. Parts (a) and (b) of Figure 21, and parts (a) and (b) of Figure 22, show the cases where the expected number of incident photons to the photodetector 2 is 5, 10, 30, and 50, respectively. In addition, each figure shows the cases where Sr / fc is 1, 2, 2.5, 3, 8, 20, and 40. Note that in this simulation, F=1, D=0, R=0, M=80×10 3 , V height = 1 × 10 -3 (V), G TIA = 80 × 10 3 fc = 5 (MHz).

[0052] Referring to Figures 21 and 22, when Sr / fc = 1, the variation in incident light intensity shown in the time-series data Da is large. From this, it can be seen that when Sr / fc is 1 or less, the effect of quantization error is large. On the other hand, when Sr / fc is 2 or greater, the change in the variation of incident light intensity shown in the time-series data Da is small. Therefore, it can be said that Sr / fc ≥ 2 corresponds to the range of acceptable quantization error. To further reduce the quantization error, Sr / fc may be 2.5 or greater, or even 3 or greater.

[0053] Furthermore, based on the simulations described above, the inventors conducted thorough research and found that when applying the general sampling theorem to the time waveform Pa used in this embodiment, Sr / fc must be 100 or greater. In contrast, the inventors found that, for example, in measurement methods such as flow cytometry (FCM) or laser scanning microscope (LSM), sufficiently high-precision measurements are possible even with values ​​of Sr / fc=2, Sr / fc=2.5, or Sr / fc=3, which are extremely small compared to the general sampling theorem. This is due to the following factors. • Use the integral value. When using integral values, the error is averaged out as the number of photons increases, resulting in a reduction of the quantization error to a negligible degree. In the weak light region, where the effects of quantization errors become significant, the influence of other noise factors such as shot noise increases. Therefore, the Sr / fc in this embodiment may be less than 100.

[0054] In the aforementioned formula (12), apply 2 to Sr / fc, and as in the simulation above, F=1, D=0, R=0, M=80×10 3 , V height = 1 × 10 -3 (V), and G TIA = 80 × 10 3 Therefore, we obtain the following equation (16). In other words, this equation (16) represents the lower limit of the acceptable SNR.

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[0055] Applying 2.5 to Sr / fc, the above formula (18) is rewritten as the following formula (19).

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[0056] From the above, in order to make the SNR above the acceptable value and reduce the quantization error, it is preferable that the optical detection device 1 of this embodiment satisfies both equations (13) and (18) above, or both equations (14) and (19), or both equations (15) and (20). Part (a) of Figure 23 is a graph showing the range that satisfies both equations (13) and (18). Part (b) of Figure 23 is a graph showing the range that satisfies both equations (14) and (19). Figure 24 is a graph showing the range that satisfies both equations (15) and (20). In Figures 23 and 24, the horizontal axis represents R / M and the vertical axis represents Sr / fc. For example, when the gain is constant, the larger R / M is, the larger the readout noise, and the smaller Sr / fc is, the larger the quantization error. In Figures 23 and 24, lines G41 to G43 represent the upper limits of equations (13) to (15), respectively, and curves G44 to G46 represent the lower limits of equations (18) to (20), respectively. The range indicated by halftones is the range that satisfies both equations (13) and (18), both equations (14) and (19), or both equations (15) and (20).

[0057] As described above, the inventors have found the minimum magnitude of the pulse waveform peak and the sampling frequency Sr of the A / D converter 31 that makes it possible to distinguish the pulse waveform resulting from the photon input from the noise component. The photodetector 1 can distinguish the pulse waveform resulting from the photon input from the noise component and reduce the measurement error of the light intensity by satisfying both equations (13) and (17), both equations (14) and (18), or both equations (15) and (19).

[0058] Figure 25 is a flowchart illustrating the photodetection method according to this embodiment. This photodetection method can be implemented, for example, using the photodetection device 1 described above. In this photodetection method, first, photons are converted into photoelectrons at the photocathode 211 of the light sensor 21, and the photoelectrons are multiplied at the detection unit 213 to output a current signal Ja from the detection unit 213 (current generation step ST1). Next, the current signal Ja is converted into an analog voltage signal Va at the I / V conversion circuit 22 (current-voltage conversion step ST2). Next, the analog voltage signal Va is converted into time-series data Da at the A / D converter 31 (analog-to-digital conversion step ST3). Next, the noise reduction circuit 32 reduces the noise components contained in the time-series data Da to generate time-series data Db (noise reduction step ST4). This light detection method also satisfies both equations (13) and (18) described above, or both equations (14) and (19), or both equations (15) and (20).

[0059] As mentioned above, the detection unit 213 of the light sensor 21 may be an avalanche diode. In the above explanation, V shown in Figure 20 height The maximum amplitude V of the noise component Pb. noisep-p We calculated the conditions for exceeding V, height As the fluctuations become larger, the maximum amplitude V of the noise component Pb increases. noisep-p This may result in a decrease in SNR. A hybrid photodetector (HPD) combining a photocathode 211 and an avalanche diode has the advantage of small pulse height distribution (PHD), which is a fluctuation in the peak value of the time waveform Pa of the analog voltage signal Va caused by fluctuations in the multiplication gain. Therefore, the pulse waveform caused by the photon input can be distinguished from noise components with greater accuracy, and the measurement error of the light intensity can be further reduced. Note that the detection unit 213 of the light sensor 21 is not limited to an avalanche diode.

[0060] (modified version) In the above embodiment, the photodetector 1 comprises a single detection unit 213, but is not limited to this configuration. The photodetector 1 may be a multi-channel optical sensor comprising multiple detection units 213. In that case, the photodetector 1 comprises multiple I / V conversion circuits 22, each connected to a plurality of detection units 213. Each of the multiple I / V conversion circuits 22 may be composed of discrete circuits, or they may be integrated into a single IC (Integrated Circuit). Part (a) of Figure 26 is a perspective view showing a configuration in which each of the multiple I / V conversion circuits 22 is composed of discrete circuits. Part (b) of Figure 26 is a perspective view showing a configuration in which the multiple I / V conversion circuits 22 are integrated into a single IC 24. In these figures, the plurality of detection units 213 are included in a detection unit array 23. Each of the plurality of detection units 213 is connected to each of the plurality of I / V conversion circuits 22 by each of the plurality of wirings 25. The detection unit array 23, IC 24, and the plurality of wirings 25 are arranged on a single wiring board 26. The electrons E multiplied by the electron multiplication unit 212 (see Figure 1) are incident on one of the multiple detection units 213.

[0061] As shown in part (b) of Figure 26, by integrating multiple I / V conversion circuits 22 into a single IC 24, the circuit size can be reduced compared to the case where each I / V conversion circuit 22 is composed of discrete circuits, as shown in part (a) of Figure 26, contributing to the miniaturization of the photodetector 1. In addition, the wiring 25 between each I / V conversion circuit 22 and each detection unit 213 can be shortened, reducing input capacitance and parasitic components. Therefore, noise components can be reduced and the measurement error of light intensity can be reduced. Note that the configuration in which multiple I / V conversion circuits 22 are integrated into a single IC 24 is not limited to this configuration.

[0062] The signal processing circuit and signal processing method according to this disclosure are not limited to the embodiments described above, and various other modifications are possible. For example, in the above embodiment, the noise reduction circuit 32 is provided separately from the A / D converter 31. However, the noise reduction circuit 32 may be incorporated into the A / D converter 31, and is not limited to this configuration. In other words, the A / D converter 31 may have the function of the noise reduction circuit 32. Also, in the above embodiment, the noise reduction circuit 32 reduces the noise components contained in the time-series data Da. However, the noise reduction unit may be provided between the I / V conversion circuit 22 and the A / D converter 31, or incorporated into the I / V conversion circuit 22. Furthermore, the noise reduction unit may reduce the noise components contained in the analog voltage signal Va. [Explanation of Symbols]

[0063] 1...Photodetector, 2...Photodetector, 3...Signal processing circuit, 3a...Input terminal, 3b...Output terminal, 4...Signal quantity calculation circuit, 5...Calculation unit, 21...Optical sensor, 22...I / V conversion circuit, 23...Detection unit array, 24...IC, 25...Wiring, 31...A / D converter, 32...Noise reduction circuit, 211...Photocathode, 212...Electron multiplication unit, 213...Detection unit, 321...Determination unit, 322...Replacement unit, Da, Db...Time series data, Dc...Numerical data, I(t1)~I(t N ), I(t1)~I(t 17 ), I(t n ), I(t n-1 )...Digital signal value, Ja...Current signal, L...Line, P...Light, Pa...Time waveform, Pb...Noise component, R...Reference value, S(t2)~S(t N ), S(t2)~S(t 17 ), S(t n )...Difference value, Sr...Sampling frequency, T...Sampling period, Ta...First period, Tb...Second period, TH,THb...Threshold, V height ...the peak value of the pulsed time waveform, V heightp-p ...V, the range of variation of the peak value of the pulsed time waveform. noise ...the center value of the noise component, V noisep-p ...Maximum amplitude of the noise component, Va...Analog voltage signal.

Claims

1. An electron tube having a housing that maintains an internal vacuum, a photocathode disposed within the housing that converts photons into photoelectrons, and a detection unit disposed within the housing that multiplies the photoelectrons and outputs a current signal, A circuit that receives the current signal from the electron tube and generates time-series data of a digital signal based on the current signal, Equipped with, The aforementioned circuit is A current-voltage converter that converts the aforementioned current signal into an analog voltage signal, An analog-to-digital converter that converts the aforementioned analog voltage signal into the aforementioned time-series data, Noise reduction unit, It has, The noise reduction unit is It is incorporated into the current-voltage converter or the analog-to-digital converter, or provided between the current-voltage converter and the analog-to-digital converter to reduce noise components contained in the analog voltage signal, or It is incorporated into the analog-to-digital converter, or provided downstream of the analog-to-digital converter, to reduce noise components contained in the time-series data. A light detection device that satisfies both of the following equations (1) and (2), where R is the magnitude of the readout noise caused by noise superimposed on the analog voltage signal in the current-voltage converter and noise superimposed on the time-series data in the analog-digital converter, M is the gain of the detection unit of the electron tube, fc (Hz) is the cutoff frequency of the current-voltage converter, and Sr (Hz) is the sampling frequency of the analog-digital converter. [Math 1] [Math 2]

2. The light detection device according to claim 1, wherein the detection unit is an avalanche diode.

3. The system comprises a plurality of detection units including the aforementioned detection unit, and a plurality of current-voltage converters, each corresponding to one of the plurality of detection units and including the aforementioned current-voltage converter. The photodetector according to claim 1 or 2, wherein the plurality of current-voltage converters are integrated into a single IC.

4. The light detection device according to claim 1 or 2, further satisfying the following formula (3). [Math 3]

5. The light detection device according to claim 1 or 2, further satisfying the following formula (4). [Math 4]

6. The light detection device according to claim 1 or 2, further satisfying the following formula (5). [Math 5]

7. The light detection device according to claim 1 or 2, further satisfying the following formula (6). [Math 6]

8. A photodetection method for generating time-series data of a digital signal based on a current signal output from an electron tube having a housing that maintains an internal vacuum, a photocathode disposed within the housing that converts photons into photoelectrons, and a detection unit disposed within the housing that multiplies the photoelectrons and outputs a current signal, wherein the current signal is output from the electron tube, A current-voltage conversion step that converts the current signal into an analog voltage signal, An analog-to-digital conversion step that converts the analog voltage signal into the time-series data, Noise reduction step, It has, The noise reduction step is, The current-voltage conversion step or the analog-to-digital conversion step is incorporated into the current-voltage conversion step or the analog-to-digital conversion step, or the current-voltage conversion step and the analog-to-digital conversion step are performed to reduce noise components contained in the analog voltage signal, or This is incorporated into the analog-to-digital conversion step, or performed after the analog-to-digital conversion step, to reduce noise components contained in the time-series data. A photodetection method that satisfies both of the following equations (7) and (8), where R is the magnitude of the readout noise caused by noise superimposed on the analog voltage signal in the current-voltage conversion step and noise superimposed on the time-series data in the analog-to-digital conversion step, M is the gain of the detection unit of the electron tube, fc (Hz) is the cutoff frequency of the current-voltage conversion step, and Sr (Hz) is the sampling frequency of the analog-to-digital conversion step. [Number 7] [Number 8]

9. The photodetection method according to claim 8, wherein the detection unit is an avalanche diode.

10. The light detection method according to claim 8, further satisfying the following formula (9). [Math. 9]

11. The light detection method according to claim 8, further satisfying the following formula (10). [Number 10]

12. A light detection method according to any one of claims 8 to 11, further satisfying the following formula (11). [Math 11]

13. A light detection method according to any one of claims 8 to 11, further satisfying the following formula (12). [Number 12]

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