How to estimate magnetic field strength

Abstract

To provide a method of estimating magnetic field strength, which can improve estimation accuracy.SOLUTION: A method of estimating magnetic field strength includes: a fluorescence detection step of detecting fluorescence emitted from a diamond having nitrogen-vacancy centers in a state where an external magnetic field is applied by irradiating the diamond with excitation light and sweeping microwaves; a noise removal step of removing, as noise, a long-periodic component having a value longer than a preset threshold among the detected fluorescence; a fitting step of fitting the fluorescence remaining after the removing of noise; and a magnetic field strength estimation step of estimating strength of the external magnetic field on the basis of the fluorescence after the fitting.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to a method for estimating magnetic field strength, and more particularly to a method for estimating magnetic field strength using a diamond sensor. [Background technology]

[0002] Diamond sensors, also known as quantum sensors, utilize the properties of nitrogen-vacancy complexes (i.e., NV (Nitrogen-Vacancy) centers) present inside diamonds, which allow them to sensitively detect environmental changes and change their quantum state. Diamond sensors are expected to be used as highly sensitive sensors for magnetic fields, electric fields, temperature, strain, etc.

[0003] Known technologies related to diamond sensors include those described in the following non-patent literature: As an example, Non-patent literature 1 describes a technology that utilizes the property (Zeeman effect) in which the resonance frequency of a quantum state changes depending on the strength of a magnetic field, irradiates the NV center of a diamond with green excitation light while sweeping microwaves in an external magnetic field applied, obtains the spectrum of red fluorescence emitted from the NV center, and estimates the magnetic field strength based on the peak frequency (i.e., resonance frequency) of the obtained spectrum. [Prior art documents] [Non-patent literature]

[0004] [Non-Patent Document 1] Felix M. Sturner et al., “Compact integrated magnetometer based on nitrogen-vacancy centers in diamond”, Diamond & Related Materials 93 (2019) 59-65, http: / / www.elsevier.com / locate / diamond [Non-patent document 2] Akihiro Kuwahata et al., “Magnetometer with nitrogen-vacancy center in a bulk diamond for detecting magnetic nanoparticles in biomedical applications”, Scientific Reports (2020) 10:2483, https: / / doi.org / 10.1038 / s41598-020-59064-6 [Non-patent document 3] Kento Sasaki et al., “Broadband, large-area microwave antenna for optically detected magnetic resonance of nitrogen-vacancy centers in diamond”, Review of Scientific Instruments 87, 053904 (2016), http: / / dx.doi.org / 10.1063 / 1.4952418 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the estimation method described in Non-Patent Document 1 has a problem in that the acquired fluorescence spectrum contains environmental noise such as electric field fluctuations and magnetic field fluctuations, as well as noise such as excitation light fluctuations, which affects the accuracy of estimating the magnetic field strength.

[0006] The present invention has been made to solve such technical problems, and has an object to provide an estimation method that can improve the accuracy of estimating magnetic field strength. [Means for solving the problem]

[0007] The method for estimating magnetic field strength according to the present invention is characterized by comprising a fluorescence detection step of irradiating excitation light onto a diamond having a nitrogen-vacancy complex while applying an external magnetic field, sweeping microwaves, and detecting fluorescence emitted from the diamond; a noise removal step of removing, as noise, long-period components longer than a preset threshold from the detected fluorescence; a fitting step of fitting the fluorescence remaining after noise removal; and a magnetic field strength estimation step of estimating the strength of the external magnetic field based on the fluorescence after fitting.

[0008] In the method for estimating magnetic field strength according to the present invention, by removing components of the detected fluorescence with long periods longer than a preset threshold as noise, it is possible to remove environmental noise such as electric field fluctuations and magnetic field fluctuations, and noise such as excitation light fluctuations, thereby improving the accuracy of estimating magnetic field strength, and as a result, it becomes possible to accurately estimate magnetic field strength even in an environment where electric field fluctuations, magnetic field fluctuations, and excitation light fluctuations are present.

[0009] In the magnetic field strength estimation method according to the present invention, it is preferable that the threshold is a frequency threshold, and that the noise removal step includes performing a fast Fourier transform on the intensity-time signal of the detected fluorescence to obtain the frequency of the fluorescence, removing frequencies of the obtained fluorescence that are lower than the frequency threshold as noise, and performing an inverse fast Fourier transform on the remaining frequencies of the fluorescence. This makes it possible to effectively remove environmental noise such as fluctuations in the electric field and magnetic field, and noise such as fluctuations in the excitation light, thereby improving the accuracy of estimating the magnetic field strength.

[0010] In the method for estimating magnetic field strength according to the present invention, it is preferable that in the noise removal step, values ​​of the fluorescence intensity obtained by the inverse fast Fourier transform that are greater than zero are set to 0. This improves the accuracy of fitting, and therefore the accuracy of estimating the magnetic field strength can be further improved.

[0011] In the method for estimating magnetic field strength according to the present invention, the frequency threshold is preferably equal to or less than 0.4 (1 / MHz), thereby ensuring improved accuracy in estimating magnetic field strength.

[0012] In the method for estimating magnetic field strength according to the present invention, it is preferable that the noise removal step includes squaring the fluorescence intensity obtained by inverse fast Fourier transform and adding a negative value to the squared value, thereby improving the accuracy of fitting and further improving the accuracy of estimating magnetic field strength.

[0013] Furthermore, in the method for estimating magnetic field strength according to the present invention, it is preferable that the fluorescence detection step includes sweeping the microwave to the diamond multiple times and averaging the detected fluorescence multiple times, thereby further improving the accuracy of estimating magnetic field strength. [Effects of the Invention]

[0014] According to the present invention, it is possible to improve the accuracy of estimating magnetic field strength. [Brief explanation of the drawings]

[0015] [Figure 1] FIG. 1 is a schematic diagram showing the configuration of a diamond sensor. [Figure 2] FIG. 2 is a plan view showing a microwave irradiation substrate. [Figure 3] FIG. 1 is a flow chart that reproduces the estimation method described in Non-Patent Document 1. [Figure 4] FIG. 2 is a flow diagram showing a method for estimating magnetic field strength according to an embodiment. [Figure 5] FIG. 1 shows the fluorescence detection results described in Non-Patent Document 1. [Figure 6] FIG. 1 is a diagram showing the intensity of fluorescence obtained by reproducing the estimation method described in Non-Patent Document 1. [Figure 7] FIG. 10 is a diagram showing the intensity of fluorescence obtained by adding a combination of moving average and arithmetic average to the estimation method described in Non-Patent Document 1. [Figure 8] FIG. 10 is a diagram illustrating the relationship between the number of averaging operations and the estimation accuracy of the peak frequency. [Figure 9] FIG. 10 is a diagram for explaining the problem of showing fluorescence intensity after fast Fourier transform. [Figure 10] FIG. 10 shows the results of performing a fitting step after performing a process in which values ​​of the fluorescence intensity greater than zero are set to zero. [Figure 11] FIG. 10 is a diagram for explaining the process of squaring the intensity of fluorescent light and adding a negative value. [Figure 12] FIG. 10 is a diagram for explaining the process of cube- ing the intensity of fluorescent light. DETAILED DESCRIPTION OF THE INVENTION

[0016] Hereinafter, an embodiment of a method for estimating magnetic field strength according to the present invention will be described with reference to the drawings. In the following description, unless otherwise specified, the term "spectrum" refers to the intensity of detected fluorescence, and has the same meaning as "fluorescence intensity."

[0017] Before describing the embodiments, the background to the invention will be described.

[0018] Figure 5 is Figure 3(c) described in Non-Patent Document 1, and is a diagram showing the intensity of red fluorescence detected using the method described in Non-Patent Document 1. In Figure 5, the horizontal axis shows the frequency of the microwave irradiated onto the diamond sensor, and the vertical axis shows the spectrum (arbitrary units) showing the intensity of the detected fluorescence.

[0019] As shown in Figure 5, when a microwave with a frequency of around 2.8 GHz is swept, optically detected magnetic resonance (ODMR) produces points of decline in the fluorescence intensity, and three peaks (the "valleys" in Figure 5) appear, indicating the points of decline in intensity. The magnetic field strength can be estimated based on these peaks. The position of the group of three peaks changes linearly with the magnetic field strength; that is, the relative positions of the individual peaks do not change, but the group of three moves left and right.

[0020] In Figure 5, the dashed line shows the measured data, and the solid line shows the results of fitting the measured data with a Lorentz function. The fitting here is thought to have been performed to reduce environmental noise such as fluctuations in the electric field and magnetic field, and noise such as fluctuations in the excitation light.

[0021] To estimate the strength of the external magnetic field based on the peak frequency of the spectrum (i.e., the resonant frequency), first calculate the shift Δf of the resonant frequency, and then estimate the magnetic field strength B using B = Δf / γ (γ represents the gyromagnetic ratio of the electron spin). The magnetic field strength B is the magnetic flux density, which represents the strength of the magnetic field.

[0022] The accuracy of estimating the magnetic field strength is determined by the resonance frequency of the fluorescence spectrum (in other words, the central position of the peak). That is, the accuracy of estimating the magnetic field strength is determined by the error width of the central position estimate obtained by fitting (for example, fitting using the nonlinear least squares method). There are various definitions of the error width, but in this embodiment, it is defined as the standard deviation (1σ) of the estimate obtained by fitting.

[0023] The resonant frequency shift Δf can be calculated from the results of fitting the three peaks with a Lorentzian function and estimating the center position of the peaks. The center position of the peaks can be calculated in two ways: using the average value of the fitting results of the three peaks (hereinafter referred to as "Method 1"), or using the fitting result of the central peak of the three peaks (hereinafter referred to as "Method 2"). Non-Patent Document 1 does not specify which of the two methods is used, but Method 1 essentially averages the fitting results of three times (n = 3), while Method 2 uses the fitting result of one time (n = 1), so Method 1 is considered to be more accurate.

[0024] The inventors of the present application first reproduced the estimation of magnetic field strength based on the method described in Non-Patent Document 1. The diamond sensor used for the reproduction is shown in FIG. 1 and was fabricated with reference to FIG. 2(a) and FIG. 7 described in Non-Patent Document 2. In the reproduction, the inventors of the present application also estimated the resonant frequency using Method 1 described above.

[0025] [About the structure of diamond sensors] As shown in Figure 1, the diamond sensor 1 is a device for estimating magnetic field strength, and mainly comprises an excitation light irradiation unit 2, a sensor unit 3 in which a diamond 31 is arranged, a microwave source 6, a magnet 7, a detection unit 4, and a control unit 5.

[0026] The excitation light irradiation unit 2 has a laser light source 21 that generates excitation light to be irradiated onto the diamond 31, a first lens 22 that guides the excitation light output from the laser light source 21 to an optical fiber 23, the optical fiber 23 that guides the excitation light toward the diamond 31, an optical fiber 24 that is connected to the optical fiber 23 via a fiber coupler (not shown), and a second lens 25 and a third lens 26 that are optically connected to the optical fiber 24. The laser light source 21 is controlled by the control unit 5 and outputs green excitation light.

[0027] The sensor unit 3 includes a microwave irradiation substrate 32 on which a diamond 31 is disposed. The diamond 31 contains multiple NV centers and emits fluorescence when irradiated with excitation light from a laser light source 21. The microwave irradiation substrate 32 is rectangular in plan view, as shown in FIG. 2, for example. This microwave irradiation substrate 32 has the same structure and dimensions as the microwave antenna shown in FIG. 1 of Non-Patent Document 3. The microwave irradiation substrate 32 has a length L of 60 mm, a width W of 20 mm, and a thickness t of 1.6 mm. The radius R of the outer circle 33 at the center of the microwave irradiation substrate 32 is 7.0 mm, the radius r of the hole 34 is 0.5 mm, and the distance s from the center of the hole 34 to the center of the outer circle 33 is 3.9 mm. The slit width g is 0.1 mm. The outer circle 33 is formed, for example, from copper foil.

[0028] The microwave source 6 is controlled by the control unit 5 and irradiates and sweeps variable frequency microwaves onto the diamond 31. The magnet 7 is made of a permanent magnet and serves to improve responsiveness to the magnetic field by applying a magnetic field of approximately 2 to 3 mT to the position of the diamond 31. The magnetic field source 8 is a source of the magnetic field to be estimated and can apply an external magnetic field to the diamond 31. Examples of the magnetic field source 8 include a magnet, a ferromagnetic material, an electric circuit through which current flows, and copper wire.

[0029] The detection unit 4 includes an optical fiber 41 connected to the optical fiber 23 and the optical fiber 24 via a fiber coupler (not shown), an optical fiber 45 connected to the optical fiber 41 via a first mirror 42, a filter 43 and a second mirror 44, a photodetector 46 that detects light guided by the optical fiber 45, and a voltmeter 47.

[0030] The filter 43 is configured to transmit only the red fluorescence emitted from the diamond 31 and not transmit any other light. The photodetector 46 has, for example, a photodiode, detects the fluorescence guided by the optical fiber 45, and outputs a signal of the detected fluorescence (for example, a fluorescence intensity-time signal) to the control unit 5.

[0031] The control unit 5 is composed of a microcomputer that combines, for example, a CPU (Central processing unit) that performs calculations, a ROM (Read only memory) as a secondary storage device that records the programs for the calculations, and a RAM (Random access memory) as a temporary storage device that saves the calculation progress and temporary control variables, and by executing the stored programs, it controls each component that makes up the diamond sensor 1 and performs calculations related to estimating magnetic field strength.

[0032] For example, the control unit 5 is electrically connected to the laser light source 21, the microwave source 6, and the magnetic field source 8, and controls the operation timing, output, operation time, etc. of each of these. The control unit 5 also estimates the magnetic field intensity based on the fluorescence intensity-time signal output from the photodetector 46. Note that, in this embodiment, an example will be described in which the magnetic field source 8 is electrically connected to the control unit 5, but the magnetic field source 8 does not necessarily have to be electrically connected to the control unit 5.

[0033] [Method for estimating magnetic field strength described in Non-Patent Document 1] Next, the inventors of the present application used the above-mentioned diamond sensor 1 to estimate the magnetic field strength based on the method described in Non-Patent Document 1. FIG. 3 is a flow chart reproducing the estimation method described in Non-Patent Document 1.

[0034] First, in the external magnetic field application step S11, the magnetic field source 8 applies an external magnetic field to the diamond 31 in accordance with the command of the control unit 5, i.e., applies the magnetic field to be estimated. If the magnetic field source 8 is, for example, a copper wire, the external magnetic field is applied by passing a current in accordance with the command of the control unit 5. On the other hand, if the magnetic field source 8 is, for example, a magnet or a ferromagnetic material (i.e., a material that generates its own magnetic field), the external magnetic field is applied by bringing the magnetic field source 8 close to the diamond 31 in accordance with the command of the control unit 5. In the excitation light irradiation step S12 following the external magnetic field application step S11, the laser light source 21 irradiates the diamond 31 with excitation light in accordance with the command of the control unit 5. The excitation light is, for example, a 532 nm green laser light, and its power is 2 mW. The green excitation light is then guided through the first lens 22, the optical fiber 23, and the optical fiber 24, and further passes through the second lens 25 and the third lens 26 before being irradiated onto the diamond 31.

[0035] When irradiated with green excitation light, red fluorescence is emitted from the NV center of the diamond 31. The emitted red fluorescence and a part of the green excitation light are guided to the filter 43 via the optical fiber 24, the optical fiber 41, and the first mirror 42.

[0036] The filter 43 is configured to transmit only the red fluorescence emitted from the diamond 31 and not transmit any other light, so the red fluorescence passes through the filter 43 but the green excitation light and other light are cut off. The red fluorescence that has passed through the filter 43 is then guided to the photodetector 46 by the second mirror 44 and optical fiber 45.

[0037] In a microwave irradiation sweep step S13 following the excitation light irradiation step S12, the microwave source 6 irradiates and sweeps the microwave onto the microwave irradiation substrate 32 in accordance with a command from the control unit 5. The frequency of the microwave can be changed depending on the applied strength of the external magnetic field, but here it is, for example, 2905 MHz to 2925 MHz. Furthermore, the sweep is performed, for example, at 0.25 MHz / step, and the microwave power is 0 (zero) dBm.

[0038] When microwaves of 2905 MHz to 2925 MHz are swept, the electron spins of the NV centers undergo optically detected magnetic resonance, and the red fluorescence emitted from the diamond 31 rapidly weakens. In other words, the intensity of the red fluorescence rapidly decreases at the resonance frequency.

[0039] In the fluorescence detection step S14 following the microwave irradiation sweep step S13, the photodetector 46 detects the red fluorescence and outputs an intensity-time signal of the detected fluorescence to the control unit 5.

[0040] In fitting step S15 following fluorescence detection step S14, controller 5 first acquires the fluorescence intensity-time signal output from photodetector 46, and then acquires a spectrum indicating the fluorescence intensity based on the acquired fluorescence intensity-time signal. The acquired fluorescence spectrum has three peaks (the "valleys" in FIG. 5) indicating a rapid decrease in fluorescence intensity.

[0041] Next, the control unit 5 performs fitting of the three peaks with a Lorentz function and estimates the center positions of the peaks (that is, the resonance frequencies).

[0042] In the magnetic field strength estimation step S16 following the fitting step S15, the control unit 5 first calculates the amount of shift Δf of the resonance frequency due to the external magnetic field by calculating the difference between the resonance frequency estimated by fitting and the resonance frequency when no external magnetic field is applied. Next, the control unit 5 estimates the magnetic field strength B (i.e., the strength of the external magnetic field applied by the magnetic field source 8) using B=Δf / γ based on the calculated amount of shift Δf. Here, γ represents the gyromagnetic ratio of the electron spin, and is, for example, 28 MHz / mT.

[0043] Figure 6 is a diagram showing the intensity of fluorescence obtained by reproducing the estimation method described in Non-Patent Document 1. In Figure 6, similar to Figure 5, the horizontal axis indicates the frequency of the microwave irradiated to the diamond sensor 1, and the vertical axis indicates the spectrum (arbitrary units) showing the intensity of the detected fluorescence.

[0044] As can be seen by comparing Fig. 6 with Fig. 5, Fig. 6, which shows the results of reproducing the estimation method described in Non-Patent Document 1, shows baseline fluctuations or peaks (see arrows in Fig. 6) that are not seen in Non-Patent Document 1. Such baseline fluctuations or peaks are a manifestation of noise, and have a negative effect on the accuracy of fitting, and ultimately on the accuracy of estimating the magnetic field strength.

[0045] The baseline fluctuations or peaks are presumed to be caused by environmental noise, such as electric field fluctuations or magnetic field fluctuations, present in the measurement environment, and noise, such as excitation light fluctuations. Non-Patent Document 1 does not describe the measurement environment, so it is unclear what kind of environment the measurement was performed in. Meanwhile, the measurement environment reproduced by the inventors of this application was a typical laboratory in which no measures were taken against environmental noise.

[0046] If the problem is caused by environmental noise, it can be solved by taking measures such as measuring in a shielded room, but when using the diamond sensor 1 as an on-board sensor, it is difficult to take measures such as using a shielded room. On the other hand, if the problem is caused by fluctuations in the excitation light, the problem can be solved by using an expensive laser light source with an excitation light stabilization mechanism, but this increases the cost of the diamond sensor 1. Furthermore, if the baseline fluctuations or peaks are caused by noise other than the above-mentioned environmental noise and fluctuations in the excitation light, the noise cannot be eliminated even by using an expensive laser light source.

[0047] Therefore, when the diamond sensor 1 is used in a general environment, including as an on-board sensor, it is necessary to eliminate the influence of noise as described above.

[0048] It is also known that using moving averages or arithmetic averages is effective for noise reduction. For this reason, the inventors first performed moving average processing on the detected fluorescence intensity-time signal. However, as shown in Figure 6, it was found that even when using a moving average (see the dashed dotted line in Figure 6), noise components (see the arrow in Figure 6) remained. Note that the moving average here is an auxiliary line for easier visualization. The fitting shown in Figure 6 is the result of fitting the original data as is.

[0049] Next, the inventors of the present application attempted to reduce noise by using a combination of moving average and arithmetic average. Figure 7 shows the fluorescence intensity obtained by adding a combination of moving average and arithmetic average (n = 10) to the estimation method described in Non-Patent Document 1. As shown in Figure 7, it was found that noise components (see arrows in Figure 7) remained even when using a combination of moving average (see dashed line in Figure 7) and arithmetic average (n = 10). Note that the moving average in Figure 7 is an auxiliary line for easier visualization, and the fitting shown in Figure 7 is the result of fitting the original data as is.

[0050] Furthermore, the inventors of the present invention investigated the relationship between the number of averaging operations and the accuracy of estimating the peak frequency, as shown in Fig. 8. As a result, it was found that changing the number of averaging operations did not improve the accuracy of estimating the peak frequency.

[0051] From the above, it has been found that in the case of the estimation method described in Non-Patent Document 1, the estimation accuracy of the magnetic field strength cannot be improved even if an arithmetic average and a moving average are used.

[0052] Therefore, as a result of extensive research, the present inventors discovered that the accuracy of estimating magnetic field strength can be improved by removing, as noise, long-period components of the detected fluorescence that are longer than a preset threshold, and thus completed the present invention. More specifically, the accuracy of estimating magnetic field strength can be improved by obtaining the frequency of the fluorescence by performing a fast Fourier transform on the intensity-time signal of the detected fluorescence, and removing, as noise, frequencies of the obtained fluorescence that are smaller than a preset frequency threshold.

[0053] [Method for estimating magnetic field strength according to the embodiment] To achieve the above, the magnetic field intensity estimation method according to this embodiment includes, as shown in FIG. 4, an external magnetic field application step S21, an excitation light irradiation step S22, a microwave irradiation sweep step S23, a fluorescence detection step S24, a fast Fourier transform step S25, an FFT frequency removal step S26, an inverse fast Fourier transform step S27, a fluorescence intensity post-processing step S28, a fitting step S29, and a magnetic field intensity estimation step S30.

[0054] The external magnetic field application step S21 to the fluorescence detection step S24 are similar to the above-mentioned steps S11 to S14, and therefore a duplicated description thereof will be omitted.

[0055] In the fast Fourier transform step S25 following the fluorescence detection step S24, the control unit 5 first acquires the fluorescence intensity-time signal output from the photodetector 46, and then acquires the fluorescence frequency (FFT frequency) by performing a fast Fourier transform (FFT) on the acquired fluorescence intensity-signal. That is, the control unit 5 converts the fluorescence time domain signal into a frequency domain signal by performing a fast Fourier transform on the fluorescence intensity-signal.

[0056] In the FFT frequency removal step S26 following the fast Fourier transform step S25, the control unit 5 compares the FFT frequency acquired in step S25 with a preset frequency threshold fc, and removes, as noise, any frequency of the fluorescence FFT frequency that is smaller than the frequency threshold fc. The frequency threshold fc is preferably 0.4 (1 / MHz) or less, the reason for which will be described later in Examples 1 to 5. The unit of the frequency threshold fc, 1 / MHz, is a unit determined from the spectrum indicating the intensity of the fluorescence. be .

[0057] In the inverse fast Fourier transform step S27 following the FFT frequency removal step S26, the control unit 5 performs an inverse fast Fourier transform on the FFT frequencies of the remaining fluorescence (in other words, FFT frequencies equal to or greater than the frequency threshold fc) to obtain the intensity (i.e., spectrum) of the fluorescence.

[0058] In the fluorescence intensity post-processing step S28 following the inverse fast Fourier transform step S27, the control unit 5 sets any fluorescence intensity value obtained by the inverse fast Fourier transform that is greater than zero to 0. Here, the reason why any fluorescence intensity value greater than zero is set to 0 will be explained with reference to Figs. 9 and 10.

[0059] FIG. 9 is a diagram for explaining problems shown by fluorescence intensity after fast Fourier transform. In FIG. 9, the graph indicated by the broken line (data before processing) shows the spectrum obtained by performing processing up to the inverse fast Fourier transform step S27 with fc being 0.4 (1 / MHz). As shown in FIG. 9, it can be seen that while the peak becomes sharp due to the “frequency removal of FFT frequency < fc” performed in step S26, the baseline curves. The curvature of the baseline increases the deviation from the Lorentz function, which causes a decrease in the fitting accuracy and thus the estimation accuracy of the magnetic field strength.

[0060] As will be described in detail in Example 11 below, as a result of the present inventor actually performing the fitting process on the data state before processing directly, the effect of improving the estimation accuracy of the magnetic field strength was not obtained. On the other hand, by setting values greater than zero among the fluorescence intensities to zero in step S28, the baseline of the spectrum after the inverse fast Fourier transform can converge to zero mathematically, and the fitting accuracy can be improved. That is, by processing with the same value (zero) regardless of the spectrum in this way, the fitting accuracy can be improved. Note that the graph indicated by the solid line in FIG. 9 (data after processing) shows the result of the process of setting values greater than zero among the fluorescence intensities to zero.

[0061] In the fitting step S29 following the fluorescence intensity post-processing step S28, the control unit 5 performs fitting on the fluorescence intensity obtained in step S28 (in other words, the post-processed fluorescence intensity) using, for example, a Lorentz function, and estimates the resonance frequency as described in step S15 above.

[0062] FIG. 10 shows the results of performing a fitting step after setting values ​​of fluorescence intensity greater than zero to zero. In FIG. 10, the moving average shown by the dashed-dotted line is an auxiliary line for visual clarity, and the fitting shown by the solid line is the result of directly fitting data after setting values ​​of fluorescence intensity greater than zero to zero. As can be seen from FIG. 10, setting values ​​of fluorescence intensity greater than zero to zero makes the spectral peaks clearer. In other words, setting values ​​of fluorescence intensity greater than zero to zero improves the accuracy of fitting.

[0063] In the magnetic field strength estimation step S30 following the fitting step S29, as described in step S15 above, the control unit 5 estimates the magnetic field strength B (i.e., the strength of the external magnetic field applied by the magnetic field source 8) based on the resonance frequency as B=Δf / γ.

[0064] Of the above steps, the external magnetic field application step S21 to the fluorescence detection step S24 correspond to the "fluorescence detection step" described in the claims, and the fast Fourier transform step S25 to the fluorescence intensity post-processing step S28 correspond to the "noise removal step" described in the claims.

[0065] In the magnetic field intensity estimation method according to this embodiment, the FFT frequency of the detected fluorescence is obtained by fast Fourier transforming the intensity-time signal, and frequencies smaller than a frequency threshold fc are removed as noise from the obtained FFT frequency. The remaining FFT frequency is then subjected to an inverse fast Fourier transform to obtain the fluorescence intensity. This effectively removes environmental noise, such as electric field fluctuations and magnetic field fluctuations, and noise, such as excitation light fluctuations, thereby improving the accuracy of magnetic field intensity estimation. As a result, even in a measurement environment where electric field fluctuations, magnetic field fluctuations, and excitation light fluctuations exist, the diamond sensor 1 can accurately estimate the magnetic field intensity.

[0066] [Comparative Examples and Examples] The inventors of the present application conducted the following comparative examples and examples to verify the effects of the estimation method of this embodiment. In the comparative examples and examples, the effects were verified by evaluating the estimation accuracy of the magnetic field strength. The estimation accuracy of the magnetic field strength is the standard deviation of the estimated value obtained by fitting, and its unit is μT, with a smaller value indicating better estimation accuracy.

[0067] [Comparative Example 1] In Comparative Example 1, the estimation accuracy of magnetic field strength was evaluated under the conditions shown in Table 1 using the above-mentioned diamond sensor 1 and the method described in Non-Patent Document 1 (see FIG. 3). As shown in Table 1, in Comparative Example 1, microwaves were swept once onto diamond 31. The estimation accuracy of Comparative Example 1 is shown in Table 1.

[0068] Comparative Example 2 In Comparative Example 2, using the above-mentioned diamond sensor 1 and the method described in Non-Patent Document 1 (see FIG. 3), microwaves were swept 10 times on diamond 31, as shown in Table 1, and the estimation accuracy of magnetic field strength was evaluated. That is, the microwave irradiation sweep step S13 and the fluorescence detection step S14 were repeated 10 times, and the fluorescence intensity-time signals obtained by the 10 sweeps were averaged. The estimation accuracy of Comparative Example 1 is shown in Table 1.

[0069] Comparative Example 3 In Comparative Example 3, the above-mentioned diamond sensor 1 and the method described in Non-Patent Document 1 (see FIG. 3) were used to sweep microwaves once onto diamond 31, perform a moving average to remove noise, and evaluate the estimation accuracy of the magnetic field strength, as shown in Table 1. The estimation accuracy of Comparative Example 3 is shown in Table 1.

[0070] Comparative Example 4 In Comparative Example 4, the above-mentioned diamond sensor 1 and the method described in Non-Patent Document 1 (see FIG. 3) were used to sweep the microwave 10 times, perform a moving average for each sweep, and evaluate the estimation accuracy of the magnetic field strength, as shown in Table 1. The estimation accuracy of Comparative Example 4 is shown in Table 1.

[0071] As shown in Table 1, the estimation accuracy of the magnetic field strength in both Comparative Example 1 and Comparative Example 2 was 1.9 μT, which shows that with the conventional method (i.e., the method described in Non-Patent Document 1), even performing arithmetic averaging is ineffective in improving estimation accuracy. Furthermore, the results of Comparative Examples 1 and 3 show that performing moving averaging is also ineffective in improving estimation accuracy. Furthermore, the results of Comparative Examples 1 and 4 show that combining arithmetic averaging and moving averaging is also ineffective in improving estimation accuracy.

[0072] [Table 1]

[0073] [Example 1] In Example 1, the estimation accuracy of magnetic field strength was evaluated under the conditions shown in Table 2 using the above-mentioned diamond sensor 1 and the estimation method shown in Figure 4. As shown in Table 2, in the above-mentioned FFT frequency elimination step S26, the frequency threshold fc was set to 0.1 (1 / MHz). That is, in Example 1, frequencies smaller than the frequency threshold fc = 0.1 (1 / MHz) were eliminated as noise. Also, in the microwave irradiation sweep step S23, microwaves were swept once over the diamond 31.

[0074] As shown in Table 2, the estimation accuracy of the magnetic field strength in Example 1 was 1.4 μT, which was improved over the above-mentioned Comparative Example 1 (1.9 μT). This result shows that the estimation method of this embodiment can improve the estimation accuracy of the magnetic field strength.

[0075] [Example 2] In Example 2, the estimation accuracy of magnetic field strength was evaluated under the conditions shown in Table 2 using the diamond sensor 1 described above and the estimation method shown in Figure 4. As shown in Table 2, in the above-mentioned FFT frequency elimination step S26, the frequency threshold fc was set to 0.3 (1 / MHz). That is, in Example 2, frequencies smaller than the frequency threshold fc = 0.3 (1 / MHz) were eliminated as noise. Also, in the microwave irradiation sweep step S23, the microwave was swept once through the diamond 31.

[0076] As shown in Table 2, the estimation accuracy of the magnetic field strength in Example 2 was 1.2 μT, which was improved over the above-mentioned Comparative Example 1 (1.9 μT). This result shows that the estimation method of this embodiment can improve the estimation accuracy of the magnetic field strength.

[0077] [Example 3] In Example 3, the estimation accuracy of magnetic field strength was evaluated under the conditions shown in Table 2 using the above-mentioned diamond sensor 1 and the estimation method shown in Figure 4. As shown in Table 2, in the above-mentioned FFT frequency elimination step S26, the frequency threshold fc was set to 0.4 (1 / MHz). That is, in Example 3, frequencies smaller than the frequency threshold fc = 0.4 (1 / MHz) were eliminated as noise. Also, in the microwave irradiation sweep step S23, microwaves were swept once on the diamond 31.

[0078] As shown in Table 2, the estimation accuracy of the magnetic field strength in Example 3 was 1.0 μT, which was improved over the above-mentioned Comparative Example 1 (1.9 μT). This result shows that the estimation method of this embodiment can improve the estimation accuracy of the magnetic field strength.

[0079] [Example 4] In Example 4, the estimation accuracy of magnetic field strength was evaluated under the conditions shown in Table 2 using the above-mentioned diamond sensor 1 and the estimation method shown in Figure 4. As shown in Table 2, in the above-mentioned FFT frequency elimination step S26, the frequency threshold fc was set to 0.5 (1 / MHz). That is, in Example 4, frequencies smaller than the frequency threshold fc = 0.5 (1 / MHz) were eliminated as noise. Also, in the microwave irradiation sweep step S23, microwaves were swept once on the diamond 31.

[0080] As shown in Table 2, the estimation accuracy of the magnetic field strength in Example 4 was 3.2 μT, which was found to be worse than that in Comparative Example 1 (1.9 μT) described above.

[0081] [Example 5] In Example 5, the estimation accuracy of magnetic field strength was evaluated under the conditions shown in Table 2 using the above-mentioned diamond sensor 1 and the estimation method shown in Figure 4. As shown in Table 2, in the above-mentioned FFT frequency elimination step S26, the frequency threshold fc was set to 0.7 (1 / MHz). That is, in Example 5, frequencies smaller than the frequency threshold fc = 0.7 (1 / MHz) were eliminated as noise. Also, in the microwave irradiation sweep step S23, microwaves were swept once on the diamond 31.

[0082] As shown in Table 2, it was found that the estimation accuracy of the magnetic field strength in Example 5 was so poor that fitting using a Lorentzian function was no longer possible.

[0083] Based on the results of Examples 1 to 5, it was found that in order to improve the estimation accuracy of the magnetic field strength, the frequency threshold fc needs to be 0.4 (1 / MHz) or less.

[0084] [Table 2]

[0085] [Example 6] In Example 6, the estimation accuracy of magnetic field strength was evaluated under the conditions shown in Table 3 using the diamond sensor 1 described above and the estimation method shown in Figure 4. As shown in Table 3, microwaves were swept 10 times on the diamond 31. That is, the microwave irradiation sweep step S23 and the fluorescence detection step S24 were repeated 10 times, and the fluorescence intensity-time signals obtained by the 10 sweeps were averaged. Furthermore, the frequency threshold fc was set to 0.1 (1 / MHz) in the FFT frequency removal step S26.

[0086] As shown in Table 3, the estimation accuracy of the magnetic field strength in Example 6 was 0.69 μT, which was improved compared to the above-mentioned Comparative Example 2 (1.9 μT), in which the microwave was similarly swept 10 times, and it was found that the estimation accuracy could be further improved compared to Example 1 (1.4 μT), which used the same frequency threshold fc.

[0087] [Example 7] In Example 7, the estimation accuracy of magnetic field strength was evaluated under the conditions shown in Table 3 using the diamond sensor 1 described above and the estimation method shown in Figure 4. As shown in Table 3, microwaves were swept 10 times on the diamond 31. That is, the microwave irradiation sweep step S23 and the fluorescence detection step S24 were repeated 10 times, and the fluorescence intensity-time signals obtained by the 10 sweeps were averaged. Furthermore, the frequency threshold fc was set to 0.3 (1 / MHz) in the FFT frequency removal step S26.

[0088] As shown in Table 3, the estimation accuracy of the magnetic field strength in Example 7 was 0.58 μT, which was an improvement over the above-mentioned Comparative Example 2 (1.9 μT), in which the microwave was similarly swept 10 times, and it was found that the estimation accuracy could be further improved compared to Example 2 (1.2 μT), which used the same frequency threshold fc.

[0089] [Example 8] In Example 8, the estimation accuracy of magnetic field strength was evaluated under the conditions shown in Table 3 using the diamond sensor 1 described above and the estimation method shown in Figure 4. As shown in Table 3, microwaves were swept 10 times on the diamond 31. That is, the microwave irradiation sweep step S23 and the fluorescence detection step S24 were repeated 10 times, and the fluorescence intensity-time signals obtained by the 10 sweeps were averaged. Furthermore, the frequency threshold fc was set to 0.4 (1 / MHz) in the FFT frequency removal step S26.

[0090] As shown in Table 3, the estimation accuracy of the magnetic field strength in Example 8 was 0.53 μT, which was an improvement over the above-mentioned Comparative Example 2 (1.9 μT), in which the microwave was similarly swept 10 times, and it was found that the estimation accuracy could be further improved over Example 3 (1.0 μT), which used the same frequency threshold fc.

[0091] [Example 9] In Example 9, the estimation accuracy of magnetic field strength was evaluated under the conditions shown in Table 3 using the diamond sensor 1 described above and the estimation method shown in Figure 4. As shown in Table 3, microwaves were swept 10 times on the diamond 31. That is, the microwave irradiation sweep step S23 and the fluorescence detection step S24 were repeated 10 times, and the fluorescence intensity-time signals obtained by the 10 sweeps were averaged. Furthermore, the frequency threshold fc was set to 0.5 (1 / MHz) in the FFT frequency removal step S26.

[0092] As shown in Table 3, the estimation accuracy of the magnetic field strength in Example 9 was 1.0 μT, which was improved compared to the above-mentioned Comparative Example 2 (1.9 μT) in which the microwave was similarly swept 10 times, and it was found that the estimation accuracy could be improved compared to Example 4 (3.2 μT) which used the same frequency threshold fc. However, the estimation accuracy in Example 9 was lower than in Examples 6 to 8.

[0093] [Example 10] In Example 10, the estimation accuracy of magnetic field strength was evaluated under the conditions shown in Table 3 using the diamond sensor 1 described above and the estimation method shown in Figure 4. As shown in Table 3, microwaves were swept 10 times on the diamond 31. That is, the microwave irradiation sweep step S23 and the fluorescence detection step S24 were repeated 10 times, and the fluorescence intensity-time signals obtained by the 10 sweeps were averaged. Furthermore, the frequency threshold fc was set to 0.7 (1 / MHz) in the FFT frequency removal step S26.

[0094] As shown in Table 3, it was found that the estimation accuracy of the magnetic field strength in Example 10 was deteriorated to the extent that fitting using the Lorentzian function was not possible, similar to Example 5 described above.

[0095] The results of Examples 6 to 10 show that the estimation accuracy can be further improved by performing averaging, assuming that the frequency threshold fc is 0.4 (1 / MHz) or less. Therefore, by performing the microwave irradiation sweep step S23 and the fluorescence detection step S24 multiple times and performing averaging of the detected fluorescence multiple times, the estimation accuracy of the magnetic field strength can be further improved.

[0096] Furthermore, the results of Example 9 show that even when the frequency threshold fc is 0.5 (1 / MHz), the estimation accuracy of the magnetic field strength can be improved by using averaging in combination compared to the conventional method.

[0097] [Table 3]

[0098] Furthermore, assuming that the frequency threshold fc is 0.4 (1 / MHz), the inventors evaluated the accuracy of estimating the magnetic field strength for the following cases: when the fluorescence intensity post-processing step S28 is not performed (indicated by "no post-processing" in Table 4), when the fluorescence intensity post-processing step S28 is replaced by squaring the fluorescence intensity and adding a negative value (indicated by "square and add a negative value" in Table 4), and when the fluorescence intensity post-processing step S28 is replaced by cubeing the fluorescence intensity (indicated by "cube" in Table 4), as shown in Table 4, for the fluorescence intensity (i.e., spectrum) obtained in the inverse fast Fourier transform step S27 described above; and compared the results with those of Example 3 described above (indicated by "values ​​of fluorescence intensity > 0 are set to 0" in Table 4).

[0099] [Example 11] Example 11 is an example corresponding to "no post-processing" shown in Table 4. In Example 11, the estimation accuracy of the magnetic field strength was evaluated under the conditions shown in Table 4 using the above-mentioned diamond sensor 1 and the estimation method shown in Figure 4, but the fluorescence intensity post-processing step S28 was omitted. That is, in Example 11, the frequency threshold fc was set to 0.4 (1 / MHz) in the above-mentioned FFT frequency removal step S26, and after the inverse fast Fourier transform step S27, the fitting step S29 was performed directly without performing the fluorescence intensity post-processing step S28. Note that the microwave was swept once in the microwave irradiation sweep step S23.

[0100] As shown in Table 4, the estimation accuracy of the magnetic field strength in Example 11 was 3.7 μT, which was found to be worse than that in Example 3 (1.0 μT) in which the fluorescence intensity post-processing step S28 was performed. This shows that the fitting accuracy can be improved by setting values ​​of the fluorescence intensity greater than zero to zero, and that the estimation accuracy of the magnetic field strength can be improved.

[0101] [Example 12] Example 12 is an example that corresponds to "squaring and adding a minus sign" shown in Table 4. In Example 12, the estimation accuracy of the magnetic field strength was evaluated under the conditions shown in Table 4 using the diamond sensor 1 described above and the estimation method shown in Figure 4, but instead of the fluorescence intensity post-processing step S28, a process of squaring the fluorescence intensity and adding a minus sign was performed. That is, in Example 12, the frequency threshold fc was set to 0.4 (1 / MHz) in the above-mentioned FFT frequency removal step S26, and after the inverse fast Fourier transform step S27, the obtained fluorescence intensity was squared and added a minus sign, and then the fitting step S29 was performed. Note that the microwave was swept once in the microwave irradiation sweep step S23.

[0102] As shown in Table 4, the estimation accuracy of the magnetic field strength in Example 12 was 1.7 μT, which was found to be worse than that in Example 3 (1.0 μT) in which the fluorescence intensity post-processing step S28 was performed. This shows that the process of setting any fluorescence intensity value greater than zero to zero can improve the estimation accuracy of the magnetic field strength compared to the process of squaring the fluorescence intensity and adding a negative value.

[0103] It is noted from Tables 4 and 1 that the estimation accuracy of the magnetic field strength in Example 12 (1.7 μT) is improved over that of Comparative Example 1 (1.9 μT). The process of squaring the fluorescence intensity and adding a negative value can improve the fitting accuracy, and has been shown to have a certain effect on improving the estimation accuracy.

[0104] FIG. 11 is a diagram illustrating the process of squaring the fluorescence intensity and adding a negative value. In FIG. 11, the dashed line represents the data before processing, i.e., the data obtained in the inverse fast Fourier transform step S27. The solid line represents the data after processing of squaring the fluorescence intensity and adding a negative value. The reason for adding a negative value here is that the upper limit is inverted by squaring the fluorescence intensity and adding a negative value in order to fit to a downwardly convex Lorentzian function.

[0105] [Example 13] Example 13 is an example that corresponds to "cubing" shown in Table 4. In Example 13, the estimation accuracy of the magnetic field strength was evaluated under the conditions shown in Table 4 using the above-mentioned diamond sensor 1 and the estimation method shown in Figure 4, but instead of the fluorescence intensity post-processing step S28, a process of cubed the fluorescence intensity was performed. That is, in Example 13, the frequency threshold fc was set to 0.4 (1 / MHz) in the above-mentioned FFT frequency removal step S26, and after the inverse fast Fourier transform step S27, the obtained fluorescence intensity was cubed, and then the fitting step S29 was performed. Note that the microwave was swept once in the microwave irradiation sweep step S23.

[0106] As shown in Table 4, the estimation accuracy of the magnetic field strength in Example 13 was 2.7 μT, which was found to be worse than that in Example 3 (1.0 μT) in which the fluorescence intensity post-processing step S28 was performed. This shows that the process of setting values ​​of the fluorescence intensity greater than zero to zero can improve the estimation accuracy of the magnetic field strength compared to the process of cubed the fluorescence intensity.

[0107] Fig. 12 is a diagram illustrating the process of cubed fluorescence intensity. In Fig. 12, the dashed line represents the data before processing, i.e., the data obtained in the inverse fast Fourier transform step S27. The solid line represents the data after the process of cubed fluorescence intensity.

[0108] [Table 4]

[0109] Furthermore, assuming that the microwave was swept 10 times and the frequency threshold fc was 0.4 (1 / MHz), the inventors evaluated the estimation accuracy of the magnetic field strength for the fluorescence intensity (i.e., spectrum) obtained in the above-mentioned inverse fast Fourier transform step S27 when the fluorescence intensity post-processing step S28 was not performed (shown as "no post-processing" in Table 5), when the fluorescence intensity post-processing step S28 was replaced by a process of squaring the fluorescence intensity and adding a negative value (shown as "squared and adding a negative value" in Table 5), and when the fluorescence intensity post-processing step S28 was replaced by a process of cubed the fluorescence intensity (shown as "cubed" in Table 5), as shown in Table 5.These results were compared with those of Example 8 described above (shown as "values ​​of fluorescence intensity > 0 set to 0" in Table 5).

[0110] [Example 14] Example 14 is an example corresponding to "no post-processing" shown in Table 5. In Example 14, the estimation accuracy of the magnetic field strength was evaluated under the conditions shown in Table 5 using the above-mentioned diamond sensor 1 and the estimation method shown in Figure 4, but the fluorescence intensity post-processing step S28 was omitted. That is, in Example 14, the frequency threshold fc was set to 0.4 (1 / MHz) in the above-mentioned FFT frequency removal step S26, and after the inverse fast Fourier transform step S27, the fitting step S29 was performed directly without performing the fluorescence intensity post-processing step S28. Note that in the microwave irradiation sweep step S23, the microwave was swept 10 times, and an arithmetic average was taken of the fluorescence intensity-time signals obtained by the 10 sweeps.

[0111] As shown in Table 5, the estimation accuracy of the magnetic field strength in Example 14 was 3.0 μT, which was found to be worse than that in Example 8 (0.53 μT) in which the fluorescence intensity post-processing step S28 was performed. This shows that the fitting accuracy can be improved by setting values ​​of the fluorescence intensity greater than zero to zero, and that the estimation accuracy of the magnetic field strength can be improved.

[0112] [Example 15] Example 15 is an example that corresponds to "squaring and adding a minus sign" shown in Table 5. In Example 15, the estimation accuracy of the magnetic field strength was evaluated under the conditions shown in Table 5 using the diamond sensor 1 described above and the estimation method shown in FIG. 4, but instead of the fluorescence intensity post-processing step S28, a process of squaring the fluorescence intensity and adding a minus sign was performed. That is, in Example 15, the frequency threshold fc was set to 0.4 (1 / MHz) in the above-mentioned FFT frequency removal step S26, and after the inverse fast Fourier transform step S27, the obtained fluorescence intensity was squared and added a minus sign, and then the fitting step S29 was performed. Note that in the microwave irradiation sweep step S23, the microwave was swept 10 times, and an arithmetic average was performed on the fluorescence intensity-time signals obtained by the 10 sweeps.

[0113] As shown in Table 5, the estimation accuracy of the magnetic field strength in Example 15 was 1.1 μT, which was found to be worse than that in Example 8 (0.53 μT) in which the fluorescence intensity post-processing step S28 was performed. This shows that the process of setting any fluorescence intensity value greater than zero to zero can improve the estimation accuracy of the magnetic field strength compared to the process of squaring the fluorescence intensity and adding a negative value.

[0114] It is noted from Tables 5 and 1 that the estimation accuracy of the magnetic field strength in Example 15 (1.1 μT) is improved over that of Comparative Example 2 (1.9 μT). The process of squaring the fluorescence intensity and adding a negative value can improve the fitting accuracy, and has been shown to have a certain effect on improving the estimation accuracy.

[0115] [Example 16] Example 16 is an example that corresponds to "cubing" shown in Table 4. In Example 16, the estimation accuracy of the magnetic field strength was evaluated under the conditions shown in Table 5 using the above-mentioned diamond sensor 1 and the estimation method shown in Figure 4, but instead of the fluorescence intensity post-processing step S28, a process of cubing the fluorescence intensity was performed. That is, in Example 16, the frequency threshold fc was set to 0.4 (1 / MHz) in the above-mentioned FFT frequency removal step S26, and after the inverse fast Fourier transform step S27, the obtained fluorescence intensity was cubed, and then the fitting step S29 was performed. Note that in the microwave irradiation sweep step S23, the microwave was swept 10 times, and an arithmetic average was performed on the fluorescence intensity-time signals obtained by the 10 sweeps.

[0116] As shown in Table 5, the magnetic field strength estimation accuracy in Example 16 was 5.9 μT, which was significantly worse than that in Example 8 (0.53 μT) in which the fluorescence intensity post-processing step S28 was performed. This indicates that the process of setting values ​​of fluorescence intensity greater than zero to zero can improve the accuracy of estimating magnetic field strength compared to the process of cubed the fluorescence intensity.

[0117] [Table 5]

[0118] Although the embodiments of the present invention have been described in detail above, the present invention is not limited to the above-described embodiments, and various design modifications can be made without departing from the spirit of the present invention as set forth in the claims. [Explanation of symbols]

[0119] 1: Diamond sensor, 2: Excitation light irradiation unit, 3: Sensor unit, 4: Detection unit, 5: Control unit, 6: Microwave source, 7: Magnet, 8: Magnetic field source, 21: Laser light source, 22: First lens, 2324, 41, 45: Optical fiber, 25: Second lens, 26: Third lens, 31: Diamond, 32: Microwave irradiation substrate, 42: First mirror, 43: Filter, 44: Second mirror, 46: Photodetector, 47: Voltmeter

Claims

1. a fluorescence detection step of irradiating excitation light and sweeping microwaves onto a diamond having nitrogen-vacancy complexes in a state where an external magnetic field is applied, and detecting fluorescence emitted from the diamond with a photodetector; a noise removal step of removing, as noise, components having a long period longer than a predetermined frequency threshold from the electrical signal of the fluorescence detected by the photodetector; a fitting step of performing fitting on the fluorescent electrical signal remaining after noise removal; a magnetic field intensity estimation step of estimating the intensity of the external magnetic field based on the electrical signal of the fluorescence after fitting; A method for estimating magnetic field strength, comprising:

2. A method for estimating magnetic field strength as described in claim 1, wherein in the noise removal step, the frequency of the fluorescence is obtained by performing a fast Fourier transform on the intensity-time signal of the detected fluorescence, and frequencies of the obtained fluorescence that are smaller than the frequency threshold are removed as noise, and the remaining frequencies of the fluorescence are subjected to an inverse fast Fourier transform.

3. 3. The method for estimating magnetic field strength according to claim 2, wherein in the noise removal step, values ​​greater than zero among the intensities of the fluorescence obtained by inverse fast Fourier transform are set to zero.

4. The method for estimating magnetic field strength according to claim 2 , wherein the frequency threshold is equal to or less than 0.4 (1 / MHz).

5. 3. The method for estimating magnetic field strength according to claim 2, wherein in the noise removal step, the intensity of the fluorescence obtained by inverse fast Fourier transform is squared and the negative value is added.

6. 2. The method for estimating magnetic field strength according to claim 1, wherein in the fluorescence detection step, the microwave is swept onto the diamond a plurality of times, and the detected fluorescence is averaged a plurality of times.

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